hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c5869ccce5e7d168d09e70b5ab2ec61392d5495e
| 169
|
py
|
Python
|
falmer/content/components/base.py
|
sussexstudent/services-api
|
ae735bd9d6177002c3d986e5c19a78102233308f
|
[
"MIT"
] | 2
|
2017-04-27T19:35:59.000Z
|
2017-06-13T16:19:33.000Z
|
falmer/content/components/base.py
|
sussexstudent/falmer
|
ae735bd9d6177002c3d986e5c19a78102233308f
|
[
"MIT"
] | 975
|
2017-04-13T11:31:07.000Z
|
2022-02-10T07:46:18.000Z
|
falmer/content/components/base.py
|
sussexstudent/services-api
|
ae735bd9d6177002c3d986e5c19a78102233308f
|
[
"MIT"
] | 3
|
2018-05-09T06:42:25.000Z
|
2020-12-10T18:29:30.000Z
|
class Component:
def __init__(self, name, block):
self.name = name
self.block = block
def to_pair(self):
return self.name, self.block()
| 21.125
| 38
| 0.597633
| 22
| 169
| 4.363636
| 0.454545
| 0.25
| 0.270833
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.295858
| 169
| 7
| 39
| 24.142857
| 0.806723
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.166667
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
c5c2588ea481ea360aaf182afb4b818168b79d31
| 52,204
|
py
|
Python
|
bpm/dataset/__init__.py
|
TingtingAlice/MPM-LTL
|
b822d1b27493272459d9198dfc438a16f4a18733
|
[
"MIT"
] | null | null | null |
bpm/dataset/__init__.py
|
TingtingAlice/MPM-LTL
|
b822d1b27493272459d9198dfc438a16f4a18733
|
[
"MIT"
] | null | null | null |
bpm/dataset/__init__.py
|
TingtingAlice/MPM-LTL
|
b822d1b27493272459d9198dfc438a16f4a18733
|
[
"MIT"
] | 1
|
2018-11-27T03:10:40.000Z
|
2018-11-27T03:10:40.000Z
|
import numpy as np
import os.path as osp
ospj = osp.join
ospeu = osp.expanduser
from ..utils.utils import load_pickle
from ..utils.dataset_utils import parse_im_name
from .TrainSet import TrainSet
from .TestSet import TestSet
def create_dataset(
name='market1501',
part='trainval',
**kwargs):
assert name in ['market_png_4_1','market_png','market30_retain_pixel3_rand_1','market30_retain_pixel1_4_1','market30_retain_pixel2_4_1','market30_retain_pixel4_4_1','market30_retain_pixel5_4_1',\
'market30_retain_pixel6_4_1','market30_retain_pixel7_4_1','market30_retain_pixel8_4_1','market30_retain_pixel9_4_1',\
'market30_retain_pixel10_4_1','market30_retain_pixel1','market30_retain_pixel2','market30_retain_pixel4','market30_retain_pixel5','market30_retain_pixel6',\
'market30_retain_pixel7','market30_retain_pixel8','market30_retain_pixel9','market30_retain_pixel10',\
'market30_retain_rand_1','market30_retain_pixel3_3_1','market30_retain_pixel3_4_1',\
'market30_retain_pixel3_5_3','market30_retain_pixel3_rand_1','market30_retain_pixel3',\
'cuhk33_retain_3_1','cuhk33_retain_4','cuhk33_retain_4_1','cuhk33_retain_5','cuhk33_retain_5_3','cuhk33_retain_5_6',\
'market30_retain_3_1','market30_retain_4','market30_retain_4_1','market30_retain_5',\
'market30_retain_5_3','market30_retain_5_6','market33_retain_5','market33_retain_5_3',\
'market33_retain_5_6','market33_retain_3','market33_retain_3_1','market33_retain_4','market33_retain_4_1',\
'market30_retain_pixel0_4_1','market30_retain_pixel0_5_6','market30_retain_pixel0_5_3',\
'market30_retain_pixel0_5','market30_retain_pixel0_4_5','market30_retain_pixel0_3_1',\
'cuhk33_retain_3','mars30_retain_pixel7','mars32_retain_pixel7','mars33_retain_pixel7',\
'market30_retain_pixel0','market30_retain_2','market30_retain_3','market30_retain_pixel0_2',\
'market30_retain_pixel0_3','mars_oldmask_retain','mars','mars20','mars22','mars23','mars30',\
'mars32','mars33','market','cuhk20','cuhk22','cuhk23','cuhk20_retain','cuhk22_retain',\
'cuhk23_retain','cuhk30','cuhk32','cuhk33','cuhk30_retain','cuhk32_retain','cuhk33_retain',\
'cuhk40','cuhk42','cuhk43','cuhk40_retain','cuhk42_retain','cuhk43_retain','market1501',\
'market_combined','market23','market22', 'market20','market20_retain','market22_retain',\
'market23_retain', 'market30','market32','market33','market30_retain','market32_retain',\
'market33_retain','market40','market42','market43','market40_retain','market42_retain',\
'market43_retain','market_oldmask','market_oldmask_retain','market_trans','market_png',\
'market1501', 'cuhk03', 'duke', 'combined'], \
"Unsupported Dataset {}".format(name)
assert part in ['trainval', 'train', 'val', 'test'], \
"Unsupported Dataset Part {}".format(part)
########################################
# Specify Directory and Partition File #
########################################
if name == 'market1501':
im_dir = ospeu('~/Dataset/market1501/images')
partition_file = ospeu('~/Dataset/market1501/partitions.pkl')
elif name == 'market_png':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_origin/market-1501-png/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_origin/market-1501-png/partitions.pkl')
elif name == 'market_png_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_origin/market-1501-png/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market30_retain_pixel3_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market30_retain_pixel3_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel3_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market30_retain_pixel3_rand_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market33_retain_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_5_5.pkl')
elif name == 'market33_retain_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market33_retain_5_6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_5_6.pkl')
elif name == 'market33_retain':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/partitions.pkl')
elif name == 'market33_retain_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_3.pkl')
elif name == 'market33_retain_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market33_retain_4':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_4_5.pkl')
elif name == 'market33_retain_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel0_5_6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_5_6.pkl')
elif name == 'market30_retain_pixel0_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market30_retain_pixel0_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_5_5.pkl')
elif name == 'market30_retain_pixel0_4_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_4_5.pkl')
elif name == 'market30_retain_pixel0_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market30_retain_pixel0_2':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_2_2.pkl')
elif name == 'market30_retain_pixel0_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_3.pkl')
elif name == 'market30_retain_pixel0':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/partitions.pkl')
elif name == 'market30_retain_pixel0_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_1/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_1/partitions.pkl')
elif name == 'market30_retain_pixel1_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_1/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel2':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_2/partitions.pkl')
elif name == 'market30_retain_pixel2_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/partitions.pkl')
elif name == 'market30_retain_pixel3_rand_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market30_retain_pixel4':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_4/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_4/partitions.pkl')
elif name == 'market30_retain_pixel4_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_4/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_5/partitions.pkl')
elif name == 'market30_retain_pixel5_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_6/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_6/partitions.pkl')
elif name == 'market30_retain_pixel6_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_6/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel7':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_7/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_7/partitions.pkl')
elif name == 'market30_retain_pixel7_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_7/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel8':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_8/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_8/partitions.pkl')
elif name == 'market30_retain_pixel8_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_8/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel9':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_9/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_9/partitions.pkl')
elif name == 'market30_retain_pixel9_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_9/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel10':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_10/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_10/partitions.pkl')
elif name == 'market30_retain_pixel10_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_10/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_rand_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market30_retain_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market30_retain_4':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_4_5.pkl')
elif name == 'market30_retain_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_5_5.pkl')
elif name == 'market30_retain_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market30_retain_5_6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_5_6.pkl')
elif name == 'market30_retain_2':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_2_2.pkl')
elif name == 'market30_retain_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_3.pkl')
elif name == 'mars_oldmask_retain':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_oldmask_retain/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_oldmask_retain/partitions.pkl')
elif name == 'market30_retain':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/partitions.pkl')
elif name == 'market32_retain':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_2/partitions.pkl')
elif name == 'market33_retain':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/partitions.pkl')
elif name == 'mars20':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_2/mars_2_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_2/mars_2_extend_trans_end_0/partitions.pkl')
elif name == 'mars22':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_2/mars_2_extend_trans_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_2/mars_2_extend_trans_end_2/partitions.pkl')
elif name == 'mars23':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_2/mars_2_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_2/mars_2_extend_trans_end_3/partitions.pkl')
elif name == 'mars30':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3/mars_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3/mars_3_extend_trans_end_0/partitions.pkl')
elif name == 'mars32':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3/mars_3_extend_trans_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3/mars_3_extend_trans_end_2/partitions.pkl')
elif name == 'mars33':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3/mars_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3/mars_3_extend_trans_end_3/partitions.pkl')
elif name == 'mars30_retain_pixel7':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3_retain_7/mars_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3_retain_7/mars_3_extend_trans_end_0/partitions.pkl')
elif name == 'mars32_retain_pixel7':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3_retain_7/mars_3_extend_trans_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3_retain_7/mars_3_extend_trans_end_2/partitions.pkl')
elif name == 'mars33_retain_pixel7':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3_retain_7/mars_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars_3_retain_7/mars_3_extend_trans_end_3/partitions.pkl')
elif name == 'mars':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars/images_RGBA')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/mars/partitions.pkl')
elif name == 'cuhk33_retain':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'partitions.pkl'))
elif name == 'cuhk33_retain_3':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_3.pkl'))
elif name == 'cuhk33_retain_3_1':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_3_1.pkl'))
elif name == 'cuhk33_retain_4':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_4_5.pkl'))
elif name == 'cuhk33_retain_4_1':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_4_1.pkl'))
elif name == 'cuhk33_retain_5':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_5_5.pkl'))
elif name == 'cuhk33_retain_5_3':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_5_3.pkl'))
elif name == 'cuhk33_retain_5_6':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_5_6.pkl'))
elif name == 'duke':
im_dir = ospeu('~/Dataset/duke/images')
partition_file = ospeu('~/Dataset/duke/partitions.pkl')
elif name == 'combined':
assert part in ['trainval'], \
"Only trainval part of the combined dataset is available now."
im_dir = ospeu('~/Dataset/market1501_cuhk03_duke/trainval_images')
partition_file = ospeu('~/Dataset/market1501_cuhk03_duke/partitions.pkl')
##################
# Create Dataset #
##################
# Use standard Market1501 CMC settings for all datasets here.
cmc_kwargs = dict(separate_camera_set=False,
single_gallery_shot=False,
first_match_break=True)
partitions = load_pickle(partition_file)
im_names = partitions['{}_im_names'.format(part)]
if part == 'trainval':
ids2labels = partitions['trainval_ids2labels']
ret_set = TrainSet(
im_dir=im_dir,
im_names=im_names,
ids2labels=ids2labels,
**kwargs)
elif part == 'train':
ids2labels = partitions['train_ids2labels']
ret_set = TrainSet(
im_dir=im_dir,
im_names=im_names,
ids2labels=ids2labels,
**kwargs)
elif part == 'val':
marks = partitions['val_marks']
kwargs.update(cmc_kwargs)
ret_set = TestSet(
im_dir=im_dir,
im_names=im_names,
marks=marks,
**kwargs)
elif part == 'test':
marks = partitions['test_marks']
kwargs.update(cmc_kwargs)
ret_set = TestSet(
im_dir=im_dir,
im_names=im_names,
marks=marks,
**kwargs)
if part in ['trainval', 'train']:
num_ids = len(ids2labels)
elif part in ['val', 'test']:
ids = [parse_im_name(n, 'id') for n in im_names]
num_ids = len(list(set(ids)))
num_query = np.sum(np.array(marks) == 0)
num_gallery = np.sum(np.array(marks) == 1)
num_multi_query = np.sum(np.array(marks) == 2)
# Print dataset information
print('-' * 40)
print('{} {} set'.format(name, part))
print('-' * 40)
print('NO. Images: {}'.format(len(im_names)))
print('NO. IDs: {}'.format(num_ids))
try:
print('NO. Query Images: {}'.format(num_query))
print('NO. Gallery Images: {}'.format(num_gallery))
print('NO. Multi-query Images: {}'.format(num_multi_query))
except:
pass
print('-' * 40)
return ret_set
def create_dataset_tri(
name='market1501',
part='trainval',
flag='anchor',
**kwargs):
assert name in ['market_png_4_1','market_png','market30_retain_pixel3_rand_1','market30_retain_pixel1_4_1','market30_retain_pixel2_4_1','market30_retain_pixel4_4_1','market30_retain_pixel5_4_1',\
'market30_retain_pixel6_4_1','market30_retain_pixel7_4_1','market30_retain_pixel8_4_1','market30_retain_pixel9_4_1',\
'market30_retain_pixel10_4_1','market30_retain_rand_1','market30_retain_pixel3_3_1','market30_retain_pixel3_4_1','market30_retain_pixel3_5_3','market30_retain_pixel3_rand_1',\
'cuhk33_retain_3_1','cuhk33_retain_4','cuhk33_retain_4_1','cuhk33_retain_5','cuhk33_retain_5_3','cuhk33_retain_5_6',\
'market30_retain_3_1','market30_retain_4','market30_retain_4_1','market30_retain_5',\
'market30_retain_5_3','market30_retain_5_6','market33_retain_5','market33_retain_5_3',\
'market33_retain_5_6','market33_retain_3','market33_retain_3_1','market33_retain_4',\
'market33_retain_4_1','market30_retain_pixel0_4_1','market30_retain_pixel0_5_6',\
'market30_retain_pixel0_5_3','market30_retain_pixel0_5','market30_retain_pixel0_4_5',\
'cuhk33_retain_3','market30_retain_pixel0_3_1','market30_retain_2','market30_retain_3',\
'market30_retain_pixel0_2','market30_retain_pixel0_3','mars_oldmask_retain','mars',\
'mars20','mars22','mars23','mars30','mars32','mars33','market','cuhk20','cuhk22',\
'cuhk23','cuhk20_retain','cuhk22_retain','cuhk23_retain','cuhk30','cuhk32','cuhk33',\
'cuhk30_retain','cuhk32_retain','cuhk33_retain','cuhk40','cuhk42','cuhk43',\
'cuhk40_retain','cuhk42_retain','cuhk43_retain','market1501','market_combined',\
'market23','market22', 'market20','market20_retain','market22_retain','market23_retain', \
'market30','market32','market33','market30_retain','market32_retain','market33_retain',
'market40','market42','market43','market40_retain','market42_retain','market43_retain',
'market_oldmask','market_oldmask_retain','market_trans','market_png','market1501',
'cuhk03', 'duke', 'combined'], \
"Unsupported Dataset {}".format(name)
assert part in ['trainval', 'train', 'val', 'test'], \
"Unsupported Dataset Part {}".format(part)
########################################
# Specify Directory and Partition File #
########################################
if name == 'market1501':
im_dir = ospeu('~/Dataset/market1501/images')
partition_file = ospeu('~/Dataset/market1501/partitions.pkl')
elif name == 'market_png':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_origin/market-1501-png/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_origin/market-1501-png/partitions.pkl')
elif name == 'market_png_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_origin/market-1501-png/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market30_retain_pixel3_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market30_retain_pixel3_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel3_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market30_retain_pixel3_rand_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market30_retain_pixel3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/partitions.pkl')
elif name == 'market33_retain_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_5_5.pkl')
elif name == 'market33_retain_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market33_retain_5_6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_5_6.pkl')
elif name == 'market33_retain_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_3.pkl')
elif name == 'market33_retain_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market33_retain_4':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_4_5.pkl')
elif name == 'market33_retain_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel0_5_6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_5_6.pkl')
elif name == 'market30_retain_pixel0_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market30_retain_pixel0_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_5_5.pkl')
elif name == 'market30_retain_pixel0_4_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_4_5.pkl')
elif name == 'market30_retain_pixel0_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market30_retain_pixel0_2':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_2_2.pkl')
elif name == 'market30_retain_pixel0_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/new_shuffle_apn_partitions_3.pkl')
elif name == 'market30_retain_rand_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market30_retain_3_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_3_1.pkl')
elif name == 'market30_retain_4':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_4_5.pkl')
elif name == 'market30_retain_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_5_5.pkl')
elif name == 'market30_retain_5_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_5_3.pkl')
elif name == 'market30_retain_5_6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_5_6.pkl')
elif name == 'market30_retain_2':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/tri/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_2_2.pkl')
elif name == 'market30_retain_3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/tri/Market_3_retain/Market_3_extend_trans_end_0/new_shuffle_apn_partitions_3.pkl')
elif name == 'market30_retain_pixel0':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/partitions.pkl')
elif name == 'market30_retain_pixel0_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_1/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_1/partitions.pkl')
elif name == 'market30_retain_pixel1_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_1/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel2':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_2/partitions.pkl')
elif name == 'market30_retain_pixel2_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_2/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel3':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/partitions.pkl')
elif name == 'market30_retain_pixel3_rand_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_rand_1.pkl')
elif name == 'market30_retain_pixel4':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_4/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_4/partitions.pkl')
elif name == 'market30_retain_pixel4_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_4/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel5':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_5/partitions.pkl')
elif name == 'market30_retain_pixel5_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_retain/Market_3_extend_trans_end_0/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel6':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_6/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_6/partitions.pkl')
elif name == 'market30_retain_pixel6_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_6/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel7':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_7/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_7/partitions.pkl')
elif name == 'market30_retain_pixel7_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_7/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel8':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_8/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_8/partitions.pkl')
elif name == 'market30_retain_pixel8_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_8/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel9':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_9/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_9/partitions.pkl')
elif name == 'market30_retain_pixel9_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_9/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'market30_retain_pixel10':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_10/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_10/partitions.pkl')
elif name == 'market30_retain_pixel10_4_1':
im_dir = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_10/images')
partition_file = ospeu('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/Market_3_pixel/Market_pixel_end_3/new_shuffle_apn_partitions_4_1.pkl')
elif name == 'cuhk03':
im_type = ['detected', 'labeled'][0]
im_dir = ospeu(ospj('~/Dataset/cuhk03', im_type, 'images'))
partition_file = ospeu(ospj('~/Dataset/cuhk03', im_type, 'partitions.pkl'))
elif name == 'cuhk33_retain_3':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'new_shuffle_apn_partitions_3.pkl'))
elif name == 'cuhk33_retain_3_1':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_3_1.pkl'))
elif name == 'cuhk33_retain_4':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_4_5.pkl'))
elif name == 'cuhk33_retain_4_1':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_4_1.pkl'))
elif name == 'cuhk33_retain_5':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_5_5.pkl'))
elif name == 'cuhk33_retain_5_3':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_5_3.pkl'))
elif name == 'cuhk33_retain_5_6':
im_type = ['detected', 'labeled'][1]
im_dir = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, 'images'))
partition_file = ospeu(ospj('/GPUFS/nsccgz_ywang_1/alice/dataset/pcb/trans/cuhk03_3_retain/cuhk03_3_extend_trans_end_3', im_type, im_type+'_new_shuffle_apn_partitions_5_6.pkl'))
elif name == 'duke':
im_dir = ospeu('~/Dataset/duke/images')
partition_file = ospeu('~/Dataset/duke/partitions.pkl')
elif name == 'combined':
assert part in ['trainval'], \
"Only trainval part of the combined dataset is available now."
im_dir = ospeu('~/Dataset/market1501_cuhk03_duke/trainval_images')
partition_file = ospeu('~/Dataset/market1501_cuhk03_duke/partitions.pkl')
##################
# Create Dataset #
##################
# Use standard Market1501 CMC settings for all datasets here.
cmc_kwargs = dict(separate_camera_set=False,
single_gallery_shot=False,
first_match_break=True)
partitions = load_pickle(partition_file)
im_names = partitions['{}_{}_im_names'.format(part,flag)]
if part == 'trainval':
ids2labels = partitions['trainval_ids2labels']
ret_set = TrainSet(
im_dir=im_dir,
im_names=im_names,
ids2labels=ids2labels,
**kwargs)
elif part == 'train':
ids2labels = partitions['train_ids2labels']
ret_set = TrainSet(
im_dir=im_dir,
im_names=im_names,
ids2labels=ids2labels,
**kwargs)
elif part == 'val':
marks = partitions['val_marks']
kwargs.update(cmc_kwargs)
ret_set = TestSet(
im_dir=im_dir,
im_names=im_names,
marks=marks,
**kwargs)
elif part == 'test':
marks = partitions['test_marks']
kwargs.update(cmc_kwargs)
ret_set = TestSet(
im_dir=im_dir,
im_names=im_names,
marks=marks,
**kwargs)
if part in ['trainval', 'train']:
num_ids = len(ids2labels)
elif part in ['val', 'test']:
ids = [parse_im_name(n, 'id') for n in im_names]
num_ids = len(list(set(ids)))
num_query = np.sum(np.array(marks) == 0)
num_gallery = np.sum(np.array(marks) == 1)
num_multi_query = np.sum(np.array(marks) == 2)
# Print dataset information
print('-' * 40)
print('{} {} set'.format(name, part))
print('-' * 40)
print('NO. Images: {}'.format(len(im_names)))
print('NO. IDs: {}'.format(num_ids))
try:
print('NO. Query Images: {}'.format(num_query))
print('NO. Gallery Images: {}'.format(num_gallery))
print('NO. Multi-query Images: {}'.format(num_multi_query))
except:
pass
print('-' * 40)
return ret_set
| 75.113669
| 198
| 0.765497
| 8,137
| 52,204
| 4.453484
| 0.020892
| 0.054473
| 0.117446
| 0.124786
| 0.982781
| 0.981208
| 0.978531
| 0.977206
| 0.976047
| 0.974281
| 0
| 0.05227
| 0.107635
| 52,204
| 694
| 199
| 75.221902
| 0.72562
| 0.005344
| 0
| 0.84466
| 0
| 0.012945
| 0.674224
| 0.593084
| 0
| 0
| 0
| 0
| 0.009709
| 1
| 0.003236
| false
| 0.003236
| 0.009709
| 0
| 0.016181
| 0.029126
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
6810df5330a0e45585e3ad36a65c881bd30519fa
| 4,901
|
py
|
Python
|
tests/psd_tools/psd/test_descriptor.py
|
mrstephenneal/psd-tools2
|
fde1c9768b8d2a232e5afd5f1b58983ec675b960
|
[
"MIT"
] | 19
|
2019-11-21T09:26:52.000Z
|
2022-03-16T13:51:29.000Z
|
tests/psd_tools/psd/test_descriptor.py
|
sfneal/psd-tools3
|
61e780a2b8dd34b4d9be2d2ffea6274ab17d6051
|
[
"MIT"
] | 1
|
2018-10-01T14:14:50.000Z
|
2018-10-01T14:14:50.000Z
|
tests/psd_tools/psd/test_descriptor.py
|
mrstephenneal/psd-tools2
|
fde1c9768b8d2a232e5afd5f1b58983ec675b960
|
[
"MIT"
] | 1
|
2021-12-24T06:42:05.000Z
|
2021-12-24T06:42:05.000Z
|
from __future__ import absolute_import, unicode_literals
import pytest
from psd_tools.constants import UnitFloatType
from psd_tools.psd.descriptor import (TYPES, Descriptor, Reference, Double, String, Bool, LargeInteger, Integer,
UnitFloat)
from ..utils import check_write_read, check_read_write
DESCRIPTOR_DATA = [
(b'\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00null\x00\x00\x00\x01\x00\x00'
b'\x00\x11generatorSettingsObjc\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00'
b'null\x00\x00\x00\x02\x00\x00\x00\x05cremaObjc\x00\x00\x00\x01\x00\x00'
b'\x00\x00\x00\x00null\x00\x00\x00\x01\x00\x00\x00\x04jsonTEXT\x00\x00'
b'\x01\x9f\x00{\x00"\x00a\x00s\x00s\x00e\x00t\x00S\x00e\x00t\x00t\x00i'
b'\x00n\x00g\x00s\x00"\x00:\x00[\x00{\x00"\x00f\x00i\x00l\x00e\x00"\x00:'
b'\x00"\x00l\x00a\x00y\x00e\x00r\x00-\x00e\x00f\x00f\x00e\x00c\x00t\x00s'
b'\x00.\x00s\x00v\x00g\x00"\x00,\x00"\x00n\x00a\x00m\x00e\x00"\x00:\x00"'
b'\x00"\x00,\x00"\x00e\x00x\x00t\x00e\x00n\x00s\x00i\x00o\x00n\x00"\x00:'
b'\x00"\x00s\x00v\x00g\x00"\x00,\x00"\x00i\x00n\x00t\x00e\x00r\x00p\x00o'
b'\x00l\x00a\x00t\x00i\x00o\x00n\x00T\x00y\x00p\x00e\x00"\x00:\x00"\x00b'
b'\x00i\x00c\x00u\x00b\x00i\x00c\x00A\x00u\x00t\x00o\x00m\x00a\x00t\x00i'
b'\x00c\x00"\x00,\x00"\x00m\x00e\x00t\x00a\x00d\x00a\x00t\x00a\x00T\x00y'
b'\x00p\x00e\x00"\x00:\x00"\x00n\x00o\x00n\x00e\x00"\x00,\x00"\x00s\x00c'
b'\x00a\x00l\x00e\x00"\x00:\x001\x00,\x00"\x00u\x00s\x00e\x00I\x00C\x00C'
b'\x00P\x00r\x00o\x00f\x00i\x00l\x00e\x00"\x00:\x00"\x00s\x00R\x00G\x00B'
b'\x00 \x00I\x00E\x00C\x006\x001\x009\x006\x006\x00-\x002\x00.\x001\x00"'
b'\x00,\x00"\x00e\x00m\x00b\x00e\x00d\x00I\x00C\x00C\x00P\x00r\x00o\x00f'
b'\x00i\x00l\x00e\x00"\x00:\x00f\x00a\x00l\x00s\x00e\x00}\x00]\x00,\x00"'
b'\x00d\x00o\x00c\x00S\x00e\x00t\x00t\x00i\x00n\x00g\x00s\x00"\x00:\x00{'
b'\x00"\x00e\x00x\x00t\x00e\x00n\x00s\x00i\x00o\x00n\x00"\x00:\x00"\x00s'
b'\x00v\x00g\x00"\x00,\x00"\x00q\x00u\x00a\x00l\x00i\x00t\x00y\x00"\x00:'
b'\x00"\x001\x000\x000\x00"\x00,\x00"\x00i\x00n\x00t\x00e\x00r\x00p\x00o'
b'\x00l\x00a\x00t\x00i\x00o\x00n\x00T\x00y\x00p\x00e\x00"\x00:\x00"\x00b'
b'\x00i\x00c\x00u\x00b\x00i\x00c\x00A\x00u\x00t\x00o\x00m\x00a\x00t\x00i'
b'\x00c\x00"\x00,\x00"\x00m\x00e\x00t\x00a\x00d\x00a\x00t\x00a\x00T\x00y'
b'\x00p\x00e\x00"\x00:\x00"\x00n\x00o\x00n\x00e\x00"\x00,\x00"\x00u\x00s'
b'\x00e\x00I\x00C\x00C\x00P\x00r\x00o\x00f\x00i\x00l\x00e\x00"\x00:\x00"'
b'\x00s\x00R\x00G\x00B\x00 \x00I\x00E\x00C\x006\x001\x009\x006\x006\x00-'
b'\x002\x00.\x001\x00"\x00}\x00,\x00"\x00a\x00s\x00s\x00e\x00t\x00S\x00i'
b'\x00z\x00e\x00s\x00"\x00:\x00[\x00{\x00"\x00s\x00c\x00a\x00l\x00e\x00"'
b'\x00:\x001\x00,\x00"\x00s\x00u\x00f\x00f\x00i\x00x\x00"\x00:\x00"\x00"'
b'\x00}\x00]\x00,\x00"\x00c\x00r\x00e\x00m\x00a\x00V\x00e\x00r\x00s\x00i'
b'\x00o\x00n\x00"\x00:\x00"\x001\x00.\x001\x00"\x00}\x00\x00\x00\x00\x00'
b'\tlayerTimedoubA\xd6KM\x8a\t\xe0\xdb'),
(b'\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00null\x00\x00'
b'\x00\x01\x00\x00\x00\x00PtrnObjc\x00\x00\x00\x01\x00\x00\x00\x00\x00'
b'\x00Ptrn\x00\x00\x00\x02\x00\x00\x00\x00Nm TEXT\x00\x00\x008\x00$\x00$'
b'\x00$\x00/\x00P\x00a\x00t\x00t\x00e\x00r\x00n\x00s\x00/\x00D\x00e\x00f'
b'\x00a\x00u\x00l\x00t\x00s\x00/\x00H\x00o\x00r\x00i\x00z\x00o\x00n\x00t'
b'\x00a\x00l\x00L\x00i\x00n\x00e\x001\x00=\x00H\x00o\x00r\x00i\x00z\x00o'
b'\x00n\x00t\x00a\x00l\x00 \x00L\x00i\x00n\x00e\x00 \x001\x00\x00\x00\x00'
b'\x00\x00IdntTEXT\x00\x00\x00%\x005\x00e\x00a\x00a\x003\x000\x00c\x007'
b'\x00-\x006\x008\x008\x00d\x00-\x001\x001\x007\x007\x00-\x00b\x002\x00e'
b'\x005\x00-\x00b\x007\x001\x005\x00d\x004\x00e\x002\x00a\x006\x003\x005'
b'\x00\x00'),
]
@pytest.mark.parametrize('cls', [TYPES[key] for key in TYPES])
def test_empty_wr(cls):
check_write_read(cls())
@pytest.mark.parametrize('fixture', DESCRIPTOR_DATA)
def test_descriptor_rw(fixture):
check_read_write(Descriptor, fixture)
@pytest.mark.parametrize('fixture', [(b'\x00\x00\x00\x01name\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00name\x00'
b'\x00\x00\x030j0W\x00\x00')])
def test_reference_rw(fixture):
check_read_write(Reference, fixture)
@pytest.mark.parametrize('kls, value', [
(Double, 1.),
(String, ''),
(Bool, True),
(LargeInteger, 1),
(Integer, 1),
])
def test_value_elements(kls, value):
fixture = kls(value)
assert fixture == value
@pytest.mark.parametrize('unit, value', [
(UnitFloatType.PIXELS, 100.0),
(UnitFloatType.POINTS, 0.0),
])
def test_unit_float(unit, value):
fixture = UnitFloat(unit=unit, value=value)
assert fixture == value
assert fixture + 1.0
assert isinstance(float(fixture), float)
| 50.525773
| 112
| 0.680065
| 847
| 4,901
| 3.899646
| 0.126328
| 0.256131
| 0.19891
| 0.087193
| 0.485316
| 0.423554
| 0.381471
| 0.321829
| 0.284287
| 0.259764
| 0
| 0.306141
| 0.109569
| 4,901
| 96
| 113
| 51.052083
| 0.450733
| 0
| 0
| 0.120482
| 0
| 0.542169
| 0.658437
| 0.647011
| 0
| 0
| 0
| 0
| 0.048193
| 1
| 0.060241
| false
| 0
| 0.060241
| 0
| 0.120482
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
a840b752093b168d505b316937b99ad36edf9979
| 140
|
py
|
Python
|
auxein/mutations/__init__.py
|
auxein/auxein
|
5388cb572b65aecc282f915515c35dc3b987154c
|
[
"Apache-2.0"
] | 1
|
2019-05-08T14:53:27.000Z
|
2019-05-08T14:53:27.000Z
|
auxein/mutations/__init__.py
|
auxein/auxein
|
5388cb572b65aecc282f915515c35dc3b987154c
|
[
"Apache-2.0"
] | 2
|
2020-08-26T09:16:47.000Z
|
2020-10-30T16:47:03.000Z
|
auxein/mutations/__init__.py
|
auxein/auxein
|
5388cb572b65aecc282f915515c35dc3b987154c
|
[
"Apache-2.0"
] | null | null | null |
# flake8: noqa
from .core import Mutation
from .core import Uniform
from .core import FixedVariance
from .core import SelfAdaptiveSingleStep
| 28
| 40
| 0.828571
| 18
| 140
| 6.444444
| 0.5
| 0.275862
| 0.482759
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008197
| 0.128571
| 140
| 5
| 40
| 28
| 0.942623
| 0.085714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
a8513ed46bc15200f1155270d6c475f74c9c1912
| 45,618
|
py
|
Python
|
src/analysis/chunk_feature_dropping_pearson.py
|
Darilbii/Songbird_LFP_Paper
|
20131134353ffc4702eed490fcc3fefec9b08e32
|
[
"MIT"
] | null | null | null |
src/analysis/chunk_feature_dropping_pearson.py
|
Darilbii/Songbird_LFP_Paper
|
20131134353ffc4702eed490fcc3fefec9b08e32
|
[
"MIT"
] | null | null | null |
src/analysis/chunk_feature_dropping_pearson.py
|
Darilbii/Songbird_LFP_Paper
|
20131134353ffc4702eed490fcc3fefec9b08e32
|
[
"MIT"
] | null | null | null |
import BirdSongToolbox.chunk_analysis_tools as cat
import matplotlib.pyplot as plt
import numpy as np
import scipy
import matplotlib.patches as mpatches
import random
from src.analysis.ml_pipeline_utilities import all_bad_channels, all_drop_temps, all_label_instructions
# Functions added for the Report
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
import BirdSongToolbox.free_epoch_tools as fet
from BirdSongToolbox.import_data import ImportData
from BirdSongToolbox.chunk_analysis_tools import random_feature_drop_multi_narrow_chunk
from BirdSongToolbox.file_utility_functions import _save_numpy_data, _load_numpy_data
import src.analysis.ml_pipeline_utilities as mlpu
from src.analysis.chunk_parameter_sweep_bin_offset import get_priors
import src.analysis.hilbert_based_pipeline as hbp
import warnings
channel_drop_path = '/home/debrown/channel_dropping_results'
def get_optimum_channel_dropping_results(bird_id='z007', session='day-2016-09-09', feat_type: str = 'pow',
verbose=True):
""" Import the results of make_parameter_sweep
:param bird_id:
:param session:
:param verbose:
:return:
accuracy : ndarray, (bin_widths, offsets, num_folds, frequencies)
ndarray of the k-fold accuracies
confusions : ndarray, (bin_widths, offsets, num_folds, frequencies)
ndarray of the k-fold confusion matrices
"""
assert feat_type in ['pow', 'phase', 'both'], "invalid feat_type"
mean_curve_list = []
std_curve_list = []
for index in range(5):
mean_curve_name = "mean_curve_" + feat_type + str(index) + "_2"
mean_curve_sel = _load_numpy_data(data_name=mean_curve_name, bird_id=bird_id, session=session,
source=channel_drop_path, verbose=verbose)
mean_curve_list.append(mean_curve_sel)
std_curve_name = "std_curve_" + feat_type + str(index) + "_2"
std_curve_sel = _load_numpy_data(data_name=std_curve_name, bird_id=bird_id, session=session,
source=channel_drop_path, verbose=verbose)
std_curve_list.append(std_curve_sel)
mean_curve = np.concatenate(mean_curve_list, axis=0)
std_curve = np.concatenate(std_curve_list, axis=0)
return mean_curve, std_curve
def get_feature_dropping_results(bird_id='z007', session='day-2016-09-09', feat_type: str = 'pow', verbose=True):
""" Import the results of make_parameter_sweep
:param bird_id:
:param session:
:param verbose:
:return:
accuracy : ndarray, (bin_widths, offsets, num_folds, frequencies)
ndarray of the k-fold accuracies
confusions : ndarray, (bin_widths, offsets, num_folds, frequencies)
ndarray of the k-fold confusion matrices
"""
assert feat_type in ['pow', 'phase', 'both'], "invalid feat_type"
mean_curve_name = "mean_curve_" + feat_type
mean_curve = _load_numpy_data(data_name=mean_curve_name, bird_id=bird_id, session=session, source=channel_drop_path,
verbose=verbose)
std_curve_name = "std_curve_" + feat_type
std_curve = _load_numpy_data(data_name=std_curve_name, bird_id=bird_id, session=session, source=channel_drop_path,
verbose=verbose)
return mean_curve, std_curve
def plot_single_drop_curve(curve, err_bar, ch_range, color, top, bottom, ax=None):
if ax is None:
plt.plot(ch_range[::-1], curve, color=color, label=f" {top} - {bottom} Hz") # Main Drop Curve
plt.fill_between(ch_range[::-1], curve[:, 0] - err_bar[:, 0], curve[:, 0] + err_bar[:, 0],
color=color, alpha=0.2)
else:
ax.plot(ch_range[::-1], curve, color=color, label=f" {top} - {bottom} Hz") # Main Drop Curve
ax.fill_between(ch_range[::-1], curve[:, 0] - err_bar[:, 0], curve[:, 0] + err_bar[:, 0],
color=color, alpha=0.2)
def plot_featdrop_multi(drop_curve_list, std_list, Tops, Bottoms, chance_level, font=20, title_font=30,
title="Place Holder", verbose=False):
""" Plots a single feature dropping cure
:param drop_curve_list:
:param Tops:
:param Bottoms:
:param chance_level:
:param font:
:param title_font:
:param title:
:param verbose:
:return:
"""
# fig= plt.figure(figsize=(15,15))
plt.figure(figsize=(7, 7)) # Create Figure and Set Size
colors = ['aqua', 'darkorange', 'cornflowerblue', 'tab:brown', 'tab:pink',
'tab:gray', 'tab:green', 'xkcd:dark olive green',
'xkcd:ugly yellow', 'xkcd:fire engine red', 'xkcd:radioactive green']
num_channels = drop_curve_list.shape[1] # Make x-axis based off the First Curve
ch_range = np.arange(0, num_channels, 1)
if verbose:
print("Chance Level is: ", chance_level)
# Main Dropping Curve
patch_list = []
for index, (curve, err_bar) in enumerate(zip(drop_curve_list, std_list)):
if verbose:
print('Making plot for curve: ', index)
color = colors[index]
plot_single_drop_curve(curve=curve, err_bar=err_bar, ch_range=ch_range, color=color,
top=Tops[index], bottom=Bottoms[index], ax=None)
patch_list.append(mpatches.Patch(color=color, label=f' {Tops[index]} - {Bottoms[index]} Hz')) # Set Patches
# Plot Chance
plt.plot(ch_range, chance_level * np.ones(ch_range.shape), '--k', linewidth=5)
patch_list.append(mpatches.Patch(color='w', label=f'{round(chance_level,2)} Binomial Chance'))
# Make Legend
plt.legend(handles=patch_list, bbox_to_anchor=(1.05, .61), loc=2, borderaxespad=0.)
# Axis Labels
plt.title(title, fontsize=title_font)
plt.xlabel('No. of Channels', fontsize=font)
plt.ylabel('Accuracy', fontsize=font)
# Format Annotatitng Ticks
plt.tick_params(axis='both', which='major', labelsize=font)
plt.tick_params(axis='both', which='minor', labelsize=font)
plt.ylim(0, 1.0)
plt.xlim(1, num_channels - 1)
def random_feature_drop_multi_narrow_chunk_both(power_data, phase_data, ClassObj, drop_temps, k_folds=5, seed=None,
verbose=False):
""" Runs the Random Channel Feature Dropping algorithm on a set of pre-processed data
Parameters
----------
power_data : ndarray | (classes, instances, frequencies, channels, samples)
Randomly Rebalanced Neural Data (output of balance_classes)
phase_data : ndarray | (classes, instances, frequencies, channels, samples)
Randomly Rebalanced Neural Data (output of balance_classes)
ClassObj : class
classifier object from the scikit-learn package
drop_temps : list
list of the indexes of templates to not use as features
k_folds : int
Number of Folds to Split between Template | Train/Test sets, defaults to 5,
seed : int, RandomState instance or None, optional (default=None)
If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is
the random number generator; If None, the random number generator is the RandomState instance used by np.random.
verbose : bool
If True the funtion will print out useful information for user as it runs, defaults to False.
Returns
-------
"""
# 1.) Make Array for Holding all of the feature dropping curves
nested_dropping_curves = [] # np.zeros([])
# 2.) Create INDEX of all instances of interests : create_discrete_index()
label_identities, label_index = cat.create_discrete_index(event_data=power_data)
identity_index = np.arange(len(label_index))
sss = cat.StratifiedShuffleSplit(n_splits=k_folds, random_state=seed)
sss.get_n_splits(identity_index, label_index)
if verbose:
print(sss)
fold_number = 0
# --------- For Loop over possible Training Sets---------
for train_index, test_index in sss.split(identity_index, label_index):
if verbose:
print("TRAIN:", train_index, "TEST:", test_index)
fold_number += 1
print("On Fold #" + str(fold_number) + ' of ' + str(k_folds))
X_train, X_test = identity_index[train_index], identity_index[test_index]
y_train, y_test = label_index[train_index], label_index[test_index]
# 4.) Use INDEX to Break into corresponding [template/training set| test set] : ml_selector()
# 4.1) Get template set/training : ml_selector(power_data, identity_index, label_index, sel_instances)
sel_train_pow = cat.ml_selector(event_data=power_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_train, )
sel_train_phas = cat.ml_selector(event_data=phase_data, identity_index=label_identities,
label_index=label_index,
sel_instances=X_train, )
# 4.1) Get test set : ml_selector()
sel_test_pow = cat.ml_selector(event_data=power_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_test)
sel_test_phas = cat.ml_selector(event_data=phase_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_test)
# 5.) Use template/training set to make template : make_templates(power_data)
templates_pow = cat.make_templates(event_data=sel_train_pow)
templates_phas = cat.make_templates(event_data=sel_train_phas)
### 5.2) Remove Template that aren't needed from train
templates_pow = np.delete(templates_pow, drop_temps, axis=0)
templates_phas = np.delete(templates_phas, drop_temps, axis=0)
# 6.1) Use template/training INDEX and template to create Training Pearson Features : pearson_extraction()
train_pearson_features_pow = cat.pearson_extraction(event_data=sel_train_pow, templates=templates_pow)
train_pearson_features_phas = cat.pearson_extraction(event_data=sel_train_phas, templates=templates_phas)
# 6.2) Use test INDEX and template to create Test Pearson Features : pearson_extraction()
test_pearson_features_pow = cat.pearson_extraction(event_data=sel_test_pow, templates=templates_pow)
test_pearson_features_phas = cat.pearson_extraction(event_data=sel_test_phas, templates=templates_phas)
# 7.1) Reorganize Test Set into Machine Learning Format : ml_order_pearson()
ml_trials_train_pow, ml_labels_train = cat.ml_order(extracted_features_array=train_pearson_features_pow)
ml_trials_train_phas, _ = cat.ml_order(extracted_features_array=train_pearson_features_phas)
ml_trials_train = np.concatenate([ml_trials_train_pow, ml_trials_train_phas], axis=-1)
# 7.2) Get Ledger of the Features
num_freqs, num_chans, num_temps = np.shape(
train_pearson_features_pow[0][0]) # Get the shape of the Feature data
ordered_index = cat.make_feature_id_ledger(num_freqs=num_freqs, num_chans=num_chans, num_temps=num_temps)
ordered_index = np.concatenate([ordered_index, ordered_index], axis=0)
# 7.3) Reorganize Training Set into Machine Learning Format : ml_order_pearson()
ml_trials_test_pow, ml_labels_test = cat.ml_order(extracted_features_array=test_pearson_features_pow)
ml_trials_test_phas, _ = cat.ml_order(extracted_features_array=test_pearson_features_phas)
ml_trials_test = np.concatenate([ml_trials_test_pow, ml_trials_test_phas], axis=-1)
repeated_freq_curves = []
test_list = list(np.arange(num_chans))
random.seed(0)
for index in range(5000):
drop_order = random.sample(test_list, k=len(test_list))
fold_frequency_curves = []
for freq in range(num_freqs):
# if verbose:
# print("On Frequency Band:", freq, " of:", num_freqs)
ml_trials_train_cp = ml_trials_train.copy() # make a copy of the feature extracted Train data
ml_trials_test_cp = ml_trials_test.copy() # make a copy of the feature extracted Test data
ordered_index_cp = ordered_index.copy() # make a copy of the ordered_index
all_other_freqs = list(np.delete(np.arange(num_freqs), [freq])) # Make a index of the other frequencies
temp_feature_dict = cat.make_feature_dict(ordered_index=ordered_index_cp,
drop_type='frequency') # Feature Dict
# reduce to selected frequency from the COPY of the training data
ml_trials_train_freq, full_drop = cat.drop_features(features=ml_trials_train_cp, keys=temp_feature_dict,
desig_drop_list=all_other_freqs)
# reduce to but the selected frequency from the COPY of test data
ml_trials_test_freq, _ = cat.drop_features(features=ml_trials_test_cp, keys=temp_feature_dict,
desig_drop_list=all_other_freqs)
ordered_index_cp = np.delete(ordered_index_cp, full_drop,
axis=0) # Remove features from other frequencies
# 8.) Perform Nested Feature Dropping with K-Fold Cross Validation
nested_drop_curve = cat.ordered_feature_dropping(train_set=ml_trials_train_freq,
train_labels=ml_labels_train,
test_set=ml_trials_test_freq,
test_labels=ml_labels_test,
ordered_index=ordered_index_cp, drop_type='channel',
Class_Obj=ClassObj, order=drop_order, verbose=False)
fold_frequency_curves.append(nested_drop_curve) # For each Individual Frequency Band
if verbose:
if index % 100 == 0:
print('on loop' + str(index))
repeated_freq_curves.append(fold_frequency_curves) # Exhaustive Feature Dropping
nested_dropping_curves.append(repeated_freq_curves) # All of the Curves
# 9.) Combine all curve arrays to one array
all_drop_curves = np.array(nested_dropping_curves) # (folds, frequencies, num_dropped, 1)
# 10.) Calculate curve metrics
fold_mean_curve = np.mean(all_drop_curves, axis=0)
mean_curve = np.mean(fold_mean_curve, axis=0)
# std_curve = np.std(all_drop_curves, axis=0, ddof=1) # ddof parameter is set to 1 to return the sample std
std_curve = scipy.stats.sem(fold_mean_curve, axis=0)
return mean_curve, std_curve
def make_feature_dropping_report(bird_id='z007', session='day-2016-09-09'):
warnings.filterwarnings("ignore", category=UserWarning) # So that it doesn't print warnings until oblivion
zdata = ImportData(bird_id=bird_id, session=session)
# Get the Bird Specific Machine Learning Meta Data
bad_channels = all_bad_channels[bird_id]
drop_temps = all_drop_temps[bird_id]
# Reshape Handlabels into Useful Format
chunk_labels_list, chunk_onsets_list = fet.get_chunk_handlabels(handlabels_list=zdata.song_handlabels)
# Set the Frequency Bands to Be Used for Feature Extraction
fc_lo = [4, 8, 25, 30, 50]
fc_hi = [8, 12, 35, 50, 70]
# Pre-Process the Data (Power)
pred_data_pow = hbp.feature_extraction_chunk(neural_chunks=zdata.song_neural,
fs=1000,
l_freqs=fc_lo,
h_freqs=fc_hi,
hilbert='amplitude',
bad_channels=bad_channels,
drop_bad=True,
verbose=True)
# Pre-Process the Data (Phase)
pred_data_phase = hbp.feature_extraction_chunk(neural_chunks=zdata.song_neural,
fs=1000,
l_freqs=fc_lo, h_freqs=fc_hi,
hilbert='phase',
bad_channels=bad_channels,
drop_bad=True,
verbose=True)
# Get the Bird Specific label Instructions
label_instructions = all_label_instructions[bird_id] # get this birds default label instructions
times_of_interest = fet.label_extractor(all_labels=chunk_labels_list,
starts=chunk_onsets_list[0],
label_instructions=label_instructions)
# Get Silence Periods
silent_periods = fet.long_silence_finder(silence=8,
all_labels=chunk_labels_list,
all_starts=chunk_onsets_list[0],
all_ends=chunk_onsets_list[1],
window=(-500, 500))
# Append the Selected Silence to the end of the Events array
times_of_interest.append(silent_periods)
# Grab the Neural Activity Centered on Each event
set_window = (-10, 0)
chunk_events_power = fet.event_clipper_nd(data=pred_data_pow, label_events=times_of_interest,
fs=1000, window=set_window)
chunk_events_phase = fet.event_clipper_nd(data=pred_data_phase, label_events=times_of_interest,
fs=1000, window=set_window)
# Balance the sets
chunk_events_balanced_pow = mlpu.balance_classes(chunk_events_power)
chunk_events_balanced_phase = mlpu.balance_classes(chunk_events_phase)
priors = get_priors(num_labels=len(times_of_interest)) # Set the priors to be equal
print(priors)
rand_obj = LinearDiscriminantAnalysis(n_components=None, priors=priors, shrinkage=None,
solver='svd', store_covariance=False, tol=0.0001)
# Run Analysis on Only Power
mean_curve_pow, std_curve_pow = random_feature_drop_multi_narrow_chunk(event_data=chunk_events_balanced_pow,
ClassObj=rand_obj, drop_temps=drop_temps,
k_folds=5, seed=None, verbose=True)
_save_numpy_data(data=mean_curve_pow, data_name="mean_curve_pow", bird_id=bird_id, session=session,
destination=channel_drop_path, make_parents=True, verbose=True)
_save_numpy_data(data=std_curve_pow, data_name="std_curve_pow", bird_id=bird_id, session=session,
destination=channel_drop_path, make_parents=True, verbose=True)
# Run Analysis on Only Phase
mean_curve_phase, std_curve_phase = random_feature_drop_multi_narrow_chunk(event_data=chunk_events_balanced_phase,
ClassObj=rand_obj, drop_temps=drop_temps,
k_folds=5, seed=None, verbose=True)
_save_numpy_data(data=mean_curve_phase, data_name="mean_curve_phase", bird_id=bird_id, session=session,
destination=channel_drop_path, make_parents=True, verbose=True)
_save_numpy_data(data=std_curve_phase, data_name="std_curve_phase", bird_id=bird_id, session=session,
destination=channel_drop_path, make_parents=True, verbose=True)
# Run Analysis on Both Features Independently
mean_curve_both, std_curve_both = random_feature_drop_multi_narrow_chunk_both(power_data=chunk_events_balanced_pow,
phase_data=chunk_events_balanced_phase,
ClassObj=rand_obj,
drop_temps=drop_temps, k_folds=5,
seed=None, verbose=True)
_save_numpy_data(data=mean_curve_both, data_name="mean_curve_both", bird_id=bird_id, session=session,
destination=channel_drop_path, make_parents=True, verbose=True)
_save_numpy_data(data=std_curve_both, data_name="std_curve_both", bird_id=bird_id, session=session,
destination=channel_drop_path, make_parents=True, verbose=True)
##### Re-implementation for the paper
def random_feature_drop_sel_narrow_chunk(event_data, ClassObj, drop_temps, sel_freq, k_folds=5, seed=None,
verbose=False):
""" Runs the Random Channel Feature Dropping algorithm on a set of pre-processed data (defaults to 5K repeats)
Parameters
----------
event_data : ndarray | (classes, instances, frequencies, channels, samples)
Randomly Rebalanced Neural Data (output of balance_classes)
ClassObj : class
classifier object from the scikit-learn package
drop_temps : list
list of the indexes of templates to not use as features
sel_freq : int
the index of the frequency to be used for the narrow channel dropping
k_folds : int
Number of Folds to Split between Template | Train/Test sets, defaults to 5,
seed : int, RandomState instance or None, optional (default=None)
If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is
the random number generator; If None, the random number generator is the RandomState instance used by np.random.
verbose : bool
If True the funtion will print out useful information for user as it runs, defaults to False.
Returns
-------
"""
# 1.) Make Array for Holding all of the feature dropping curves
nested_dropping_curves = [] # np.zeros([])
# 2.) Create INDEX of all instances of interests : create_discrete_index()
label_identities, label_index = cat.create_discrete_index(event_data=event_data)
identity_index = np.arange(len(label_index))
sss = cat.StratifiedShuffleSplit(n_splits=k_folds, random_state=seed)
sss.get_n_splits(identity_index, label_index)
if verbose:
print(sss)
fold_number = 0
# --------- For Loop over possible Training Sets---------
for train_index, test_index in sss.split(identity_index, label_index):
if verbose:
print("TRAIN:", train_index, "TEST:", test_index)
fold_number += 1
print("On Fold #" + str(fold_number) + ' of ' + str(k_folds))
X_train, X_test = identity_index[train_index], identity_index[test_index]
y_train, y_test = label_index[train_index], label_index[test_index]
# 4.) Use INDEX to Break into corresponding [template/training set| test set] : ml_selector()
# 4.1) Get template set/training : ml_selector(event_data, identity_index, label_index, sel_instances)
sel_train = cat.ml_selector(event_data=event_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_train, )
# 4.1) Get test set : ml_selector()
sel_test = cat.ml_selector(event_data=event_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_test)
# 5.) Use template/training set to make template : make_templates(event_data)
templates = cat.make_templates(event_data=sel_train)
# 5.2) Remove Template that aren't needed from train
templates = np.delete(templates, drop_temps, axis=0)
# 6.1) Use template/training INDEX and template to create Training Pearson Features : pearson_extraction()
train_pearson_features = cat.pearson_extraction(event_data=sel_train, templates=templates)
# 6.2) Use test INDEX and template to create Test Pearson Features : pearson_extraction()
test_pearson_features = cat.pearson_extraction(event_data=sel_test, templates=templates)
# 7.1) Reorganize Test Set into Machine Learning Format : ml_order_pearson()
ml_trials_train, ml_labels_train = cat.ml_order(extracted_features_array=train_pearson_features)
# 7.2) Get Ledger of the Features
num_freqs, num_chans, num_temps = np.shape(train_pearson_features[0][0]) # Get the shape of the Feature data
ordered_index = cat.make_feature_id_ledger(num_freqs=num_freqs, num_chans=num_chans, num_temps=num_temps)
# 7.3) Reorganize Training Set into Machine Learning Format : ml_order_pearson()
ml_trials_test, ml_labels_test = cat.ml_order(extracted_features_array=test_pearson_features)
repeated_freq_curves = []
test_list = list(np.arange(num_chans))
random.seed(0)
for index in range(5000):
drop_order = random.sample(test_list, k=len(test_list))
fold_frequency_curves = []
for _, freq in enumerate([sel_freq]):
# if verbose:
# print("On Frequency Band:", freq, " of:", num_freqs)
ml_trials_train_cp = ml_trials_train.copy() # make a copy of the feature extracted Train data
ml_trials_test_cp = ml_trials_test.copy() # make a copy of the feature extracted Test data
ordered_index_cp = ordered_index.copy() # make a copy of the ordered_index
all_other_freqs = list(np.delete(np.arange(num_freqs), [freq])) # Make a index of the other frequencies
temp_feature_dict = cat.make_feature_dict(ordered_index=ordered_index_cp,
drop_type='frequency') # Feature Dict
# reduce to selected frequency from the COPY of the training data
ml_trials_train_freq, full_drop = cat.drop_features(features=ml_trials_train_cp, keys=temp_feature_dict,
desig_drop_list=all_other_freqs)
# reduce to but the selected frequency from the COPY of test data
ml_trials_test_freq, _ = cat.drop_features(features=ml_trials_test_cp, keys=temp_feature_dict,
desig_drop_list=all_other_freqs)
ordered_index_cp = np.delete(ordered_index_cp, full_drop,
axis=0) # Remove features from other frequencies
# 8.) Perform Nested Feature Dropping with K-Fold Cross Validation
nested_drop_curve = cat.ordered_feature_dropping(train_set=ml_trials_train_freq,
train_labels=ml_labels_train,
test_set=ml_trials_test_freq,
test_labels=ml_labels_test,
ordered_index=ordered_index_cp, drop_type='channel',
Class_Obj=ClassObj, order=drop_order, verbose=False)
fold_frequency_curves.append(nested_drop_curve) # For each Individual Frequency Band
if verbose:
if index % 100 == 0:
print('on loop' + str(index))
repeated_freq_curves.append(fold_frequency_curves) # Exhaustive Feature Dropping
nested_dropping_curves.append(repeated_freq_curves) # All of the Curves
# 9.) Combine all curve arrays to one array
all_drop_curves = np.array(nested_dropping_curves) # (folds, 5K Repeats, frequencies, num_dropped, 1)
# 10.) Calculate curve metrics
fold_mean_curve = np.mean(all_drop_curves, axis=0)
mean_curve = np.mean(fold_mean_curve, axis=0)
std_curve = np.std(fold_mean_curve, axis=0, ddof=1) # ddof parameter is set to 1 to return the sample std
# std_curve = scipy.stats.sem(fold_mean_curve, axis=0)
return mean_curve, std_curve
def random_feature_drop_sel_narrow_chunk_both(power_data, phase_data, ClassObj, drop_temps, sel_freq, k_folds=5,
seed=None, verbose=False):
""" Runs the Random Channel Feature Dropping algorithm on a set of pre-processed data
Parameters
----------
power_data : ndarray | (classes, instances, frequencies, channels, samples)
Randomly Rebalanced Neural Data (output of balance_classes)
phase_data : ndarray | (classes, instances, frequencies, channels, samples)
Randomly Rebalanced Neural Data (output of balance_classes)
ClassObj : class
classifier object from the scikit-learn package
drop_temps : list
list of the indexes of templates to not use as features
sel_freq : int
the index of the frequency to be used for the narrow channel dropping
k_folds : int
Number of Folds to Split between Template | Train/Test sets, defaults to 5,
seed : int, RandomState instance or None, optional (default=None)
If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is
the random number generator; If None, the random number generator is the RandomState instance used by np.random.
verbose : bool
If True the funtion will print out useful information for user as it runs, defaults to False.
Returns
-------
"""
# 1.) Make Array for Holding all of the feature dropping curves
nested_dropping_curves = [] # np.zeros([])
# 2.) Create INDEX of all instances of interests : create_discrete_index()
label_identities, label_index = cat.create_discrete_index(event_data=power_data)
identity_index = np.arange(len(label_index))
sss = cat.StratifiedShuffleSplit(n_splits=k_folds, random_state=seed)
sss.get_n_splits(identity_index, label_index)
if verbose:
print(sss)
fold_number = 0
# --------- For Loop over possible Training Sets---------
for train_index, test_index in sss.split(identity_index, label_index):
if verbose:
print("TRAIN:", train_index, "TEST:", test_index)
fold_number += 1
print("On Fold #" + str(fold_number) + ' of ' + str(k_folds))
X_train, X_test = identity_index[train_index], identity_index[test_index]
y_train, y_test = label_index[train_index], label_index[test_index]
# 4.) Use INDEX to Break into corresponding [template/training set| test set] : ml_selector()
# 4.1) Get template set/training : ml_selector(power_data, identity_index, label_index, sel_instances)
sel_train_pow = cat.ml_selector(event_data=power_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_train, )
sel_train_phas = cat.ml_selector(event_data=phase_data, identity_index=label_identities,
label_index=label_index,
sel_instances=X_train, )
# 4.1) Get test set : ml_selector()
sel_test_pow = cat.ml_selector(event_data=power_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_test)
sel_test_phas = cat.ml_selector(event_data=phase_data, identity_index=label_identities, label_index=label_index,
sel_instances=X_test)
# 5.) Use template/training set to make template : make_templates(power_data)
templates_pow = cat.make_templates(event_data=sel_train_pow)
templates_phas = cat.make_templates(event_data=sel_train_phas)
### 5.2) Remove Template that aren't needed from train
templates_pow = np.delete(templates_pow, drop_temps, axis=0)
templates_phas = np.delete(templates_phas, drop_temps, axis=0)
# 6.1) Use template/training INDEX and template to create Training Pearson Features : pearson_extraction()
train_pearson_features_pow = cat.pearson_extraction(event_data=sel_train_pow, templates=templates_pow)
train_pearson_features_phas = cat.pearson_extraction(event_data=sel_train_phas, templates=templates_phas)
# 6.2) Use test INDEX and template to create Test Pearson Features : pearson_extraction()
test_pearson_features_pow = cat.pearson_extraction(event_data=sel_test_pow, templates=templates_pow)
test_pearson_features_phas = cat.pearson_extraction(event_data=sel_test_phas, templates=templates_phas)
# 7.1) Reorganize Test Set into Machine Learning Format : ml_order_pearson()
ml_trials_train_pow, ml_labels_train = cat.ml_order(extracted_features_array=train_pearson_features_pow)
ml_trials_train_phas, _ = cat.ml_order(extracted_features_array=train_pearson_features_phas)
ml_trials_train = np.concatenate([ml_trials_train_pow, ml_trials_train_phas], axis=-1)
# 7.2) Get Ledger of the Features
num_freqs, num_chans, num_temps = np.shape(
train_pearson_features_pow[0][0]) # Get the shape of the Feature data
ordered_index = cat.make_feature_id_ledger(num_freqs=num_freqs, num_chans=num_chans, num_temps=num_temps)
ordered_index = np.concatenate([ordered_index, ordered_index], axis=0)
# 7.3) Reorganize Training Set into Machine Learning Format : ml_order_pearson()
ml_trials_test_pow, ml_labels_test = cat.ml_order(extracted_features_array=test_pearson_features_pow)
ml_trials_test_phas, _ = cat.ml_order(extracted_features_array=test_pearson_features_phas)
ml_trials_test = np.concatenate([ml_trials_test_pow, ml_trials_test_phas], axis=-1)
repeated_freq_curves = []
test_list = list(np.arange(num_chans))
random.seed(0)
for index in range(5000):
drop_order = random.sample(test_list, k=len(test_list))
fold_frequency_curves = []
for _, freq in enumerate([sel_freq]):
# if verbose:
# print("On Frequency Band:", freq, " of:", num_freqs)
ml_trials_train_cp = ml_trials_train.copy() # make a copy of the feature extracted Train data
ml_trials_test_cp = ml_trials_test.copy() # make a copy of the feature extracted Test data
ordered_index_cp = ordered_index.copy() # make a copy of the ordered_index
all_other_freqs = list(np.delete(np.arange(num_freqs), [freq])) # Make a index of the other frequencies
temp_feature_dict = cat.make_feature_dict(ordered_index=ordered_index_cp,
drop_type='frequency') # Feature Dict
# reduce to selected frequency from the COPY of the training data
ml_trials_train_freq, full_drop = cat.drop_features(features=ml_trials_train_cp, keys=temp_feature_dict,
desig_drop_list=all_other_freqs)
# reduce to but the selected frequency from the COPY of test data
ml_trials_test_freq, _ = cat.drop_features(features=ml_trials_test_cp, keys=temp_feature_dict,
desig_drop_list=all_other_freqs)
ordered_index_cp = np.delete(ordered_index_cp, full_drop,
axis=0) # Remove features from other frequencies
# 8.) Perform Nested Feature Dropping with K-Fold Cross Validation
nested_drop_curve = cat.ordered_feature_dropping(train_set=ml_trials_train_freq,
train_labels=ml_labels_train,
test_set=ml_trials_test_freq,
test_labels=ml_labels_test,
ordered_index=ordered_index_cp, drop_type='channel',
Class_Obj=ClassObj, order=drop_order, verbose=False)
fold_frequency_curves.append(nested_drop_curve) # For each Individual Frequency Band
if verbose:
if index % 100 == 0:
print('on loop' + str(index))
repeated_freq_curves.append(fold_frequency_curves) # Exhaustive Feature Dropping
nested_dropping_curves.append(repeated_freq_curves) # All of the Curves
# 9.) Combine all curve arrays to one array
all_drop_curves = np.array(nested_dropping_curves) # (folds, frequencies, num_dropped, 1)
# 10.) Calculate curve metrics
fold_mean_curve = np.mean(all_drop_curves, axis=0)
mean_curve = np.mean(fold_mean_curve, axis=0)
std_curve = np.std(fold_mean_curve, axis=0, ddof=1) # ddof parameter is set to 1 to return the sample std
# std_curve = scipy.stats.sem(fold_mean_curve, axis=0)
return mean_curve, std_curve
# Hard-coded from the results
best_bin_width = {"day-2016-06-03": [90, 185, 90, 85, 90],
"day-2016-06-05": [190, 125, 35, 160, 70],
"day-2016-09-10": [170, 75, 90, 25, 30],
"day-2016-09-11": [195, 170, 70, 20, 70],
"day-2016-06-19": [175, 170, 85, 50, 35],
"day-2016-06-21": [150, 170, 70, 60, 40]}
best_offset = {"day-2016-06-03": [-10, -5, 0, 0, 0],
"day-2016-06-05": [-25, -5, 0, -20, 0],
"day-2016-09-10": [-35, -5, -10, -10, 0],
"day-2016-09-11": [-5, -5, -15, 0, -15],
"day-2016-06-19": [-50, 0, -10, -5, -5],
"day-2016-06-21": [-10, -15, -30, 0, 0]}
Best_Accuracy = {"day-2016-06-03": [0.8545, 0.8945, 0.87272, 0.8436, 0.7782],
"day-2016-06-05": [0.7022, 0.7288, 0.6044, 0.5822, 0.5333],
"day-2016-09-10": [0.9680, 0.9800, 0.9960, 0.9559, 0.9399],
"day-2016-09-11": [0.9565, 0.9710, 0.9420, 0.9014, 0.8753],
"day-2016-06-19": [0.8476, 0.9333, 0.8762, 0.8, 0.6857],
"day-2016-06-21": [0.6060, 0.7030, 0.7454, 0.7030, 0.5636]}
def make_best_feature_dropping_report(bird_id='z007', session='day-2016-09-09'):
warnings.filterwarnings("ignore", category=UserWarning) # So that it doesn't print warnings until oblivion
zdata = ImportData(bird_id=bird_id, session=session)
# Get the Bird Specific Machine Learning Meta Data
bad_channels = all_bad_channels[bird_id]
drop_temps = all_drop_temps[bird_id]
# Get the Best Parameters for Bindwidth and Offset
bin_widths = best_bin_width[session]
offsets = best_offset[session]
# Reshape Handlabels into Useful Format
chunk_labels_list, chunk_onsets_list = fet.get_chunk_handlabels(handlabels_list=zdata.song_handlabels)
# Set the Frequency Bands to Be Used for Feature Extraction
fc_lo = [4, 8, 25, 35, 50]
fc_hi = [8, 12, 35, 50, 70]
# Pre-Process the Data (Power)
pred_data_pow = hbp.feature_extraction_chunk(neural_chunks=zdata.song_neural,
fs=1000,
l_freqs=fc_lo,
h_freqs=fc_hi,
hilbert='amplitude',
bad_channels=bad_channels,
drop_bad=True,
verbose=True)
# Pre-Process the Data (Phase)
pred_data_phase = hbp.feature_extraction_chunk(neural_chunks=zdata.song_neural,
fs=1000,
l_freqs=fc_lo, h_freqs=fc_hi,
hilbert='phase',
bad_channels=bad_channels,
drop_bad=True,
verbose=True)
# Get the Bird Specific label Instructions
label_instructions = all_label_instructions[bird_id] # get this birds default label instructions
times_of_interest = fet.label_extractor(all_labels=chunk_labels_list,
starts=chunk_onsets_list[0],
label_instructions=label_instructions)
# Get Silence Periods
silent_periods = fet.long_silence_finder(silence=8,
all_labels=chunk_labels_list,
all_starts=chunk_onsets_list[0],
all_ends=chunk_onsets_list[1],
window=(-500, 500))
# Append the Selected Silence to the end of the Events array
times_of_interest.append(silent_periods)
for freq_num, (offset, bin_width) in enumerate(zip(offsets, bin_widths)):
# Grab the Neural Activity Centered on Each event
set_window = (offset - bin_width, offset)
chunk_events_power = fet.event_clipper_nd(data=pred_data_pow, label_events=times_of_interest,
fs=1000, window=set_window)
chunk_events_phase = fet.event_clipper_nd(data=pred_data_phase, label_events=times_of_interest,
fs=1000, window=set_window)
# Balance the sets
chunk_events_balanced_pow = mlpu.balance_classes(chunk_events_power)
chunk_events_balanced_phase = mlpu.balance_classes(chunk_events_phase)
priors = get_priors(num_labels=len(times_of_interest)) # Set the priors to be equal
print(priors)
rand_obj = LinearDiscriminantAnalysis(n_components=None, priors=priors, shrinkage=None,
solver='svd', store_covariance=False, tol=0.0001)
# Run Analysis on Only Power
mean_curve_pow, std_curve_pow = random_feature_drop_sel_narrow_chunk(event_data=chunk_events_balanced_pow,
ClassObj=rand_obj, drop_temps=drop_temps,
sel_freq=freq_num,
k_folds=5, seed=None, verbose=True)
_save_numpy_data(data=mean_curve_pow, data_name="mean_curve_pow" + str(freq_num) + "_2", bird_id=bird_id,
session=session, destination=channel_drop_path, make_parents=True, verbose=True)
_save_numpy_data(data=std_curve_pow, data_name="std_curve_pow" + str(freq_num) + "_2", bird_id=bird_id,
session=session, destination=channel_drop_path, make_parents=True, verbose=True)
# Run Analysis on Only Phase
mean_curve_phase, std_curve_phase = random_feature_drop_sel_narrow_chunk(event_data=chunk_events_balanced_phase,
ClassObj=rand_obj,
drop_temps=drop_temps,
sel_freq=freq_num,
k_folds=5, seed=None, verbose=True)
_save_numpy_data(data=mean_curve_phase, data_name="mean_curve_phase" + str(freq_num) + "_2", bird_id=bird_id,
session=session,
destination=channel_drop_path, make_parents=True, verbose=True)
_save_numpy_data(data=std_curve_phase, data_name="std_curve_phase" + str(freq_num) + "_2", bird_id=bird_id,
session=session, destination=channel_drop_path, make_parents=True, verbose=True)
# Run Analysis on Both Features Independently
mean_curve_both, std_curve_both = random_feature_drop_sel_narrow_chunk_both(
power_data=chunk_events_balanced_pow, phase_data=chunk_events_balanced_phase, ClassObj=rand_obj,
drop_temps=drop_temps, sel_freq=freq_num, k_folds=5, seed=None, verbose=True)
_save_numpy_data(data=mean_curve_both, data_name="mean_curve_both" + str(freq_num) + "_2", bird_id=bird_id,
session=session, destination=channel_drop_path, make_parents=True, verbose=True)
_save_numpy_data(data=std_curve_both, data_name="std_curve_both" + str(freq_num) + "_2", bird_id=bird_id,
session=session, destination=channel_drop_path, make_parents=True, verbose=True)
| 54.829327
| 121
| 0.624403
| 5,731
| 45,618
| 4.663235
| 0.084278
| 0.015566
| 0.012647
| 0.008082
| 0.891225
| 0.884453
| 0.876595
| 0.870608
| 0.865706
| 0.862077
| 0
| 0.023793
| 0.297032
| 45,618
| 831
| 122
| 54.895307
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| 0
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| 0.035035
| 0.001784
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| 0.004329
| 1
| 0.019481
| false
| 0
| 0.038961
| 0
| 0.069264
| 0.034632
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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0
| 7
|
76867839e7ab4a668d0d6b6d78ab01544eafe4c5
| 61,790
|
py
|
Python
|
openconfig/ydk/models/openconfig/openconfig_lldp.py
|
Maikor/ydk-py
|
b86c4a7c570ae3b2c5557d098420446df5de4929
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
openconfig/ydk/models/openconfig/openconfig_lldp.py
|
Maikor/ydk-py
|
b86c4a7c570ae3b2c5557d098420446df5de4929
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
openconfig/ydk/models/openconfig/openconfig_lldp.py
|
Maikor/ydk-py
|
b86c4a7c570ae3b2c5557d098420446df5de4929
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
""" openconfig_lldp
This module defines configuration and operational state data
for the LLDP protocol.
"""
from collections import OrderedDict
from ydk.types import Entity, EntityPath, Identity, Enum, YType, YLeaf, YLeafList, YList, LeafDataList, Bits, Empty, Decimal64
from ydk.filters import YFilter
from ydk.errors import YError, YModelError
from ydk.errors.error_handler import handle_type_error as _handle_type_error
class Lldp(Entity):
"""
Top\-level container for LLDP configuration and state data
.. attribute:: config
Configuration data
**type**\: :py:class:`Config <ydk.models.openconfig.openconfig_lldp.Lldp.Config>`
.. attribute:: state
Operational state data
**type**\: :py:class:`State <ydk.models.openconfig.openconfig_lldp.Lldp.State>`
.. attribute:: interfaces
Enclosing container
**type**\: :py:class:`Interfaces <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp, self).__init__()
self._top_entity = None
self.yang_name = "lldp"
self.yang_parent_name = "openconfig-lldp"
self.is_top_level_class = True
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([("config", ("config", Lldp.Config)), ("state", ("state", Lldp.State)), ("interfaces", ("interfaces", Lldp.Interfaces))])
self._leafs = OrderedDict()
self.config = Lldp.Config()
self.config.parent = self
self._children_name_map["config"] = "config"
self.state = Lldp.State()
self.state.parent = self
self._children_name_map["state"] = "state"
self.interfaces = Lldp.Interfaces()
self.interfaces.parent = self
self._children_name_map["interfaces"] = "interfaces"
self._segment_path = lambda: "openconfig-lldp:lldp"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp, [], name, value)
class Config(Entity):
"""
Configuration data
.. attribute:: enabled
System level state of the LLDP protocol
**type**\: bool
**default value**\: true
.. attribute:: hello_timer
System level hello timer for the LLDP protocol
**type**\: int
**range:** 0..18446744073709551615
**units**\: seconds
.. attribute:: suppress_tlv_advertisement
Indicates whether the local system should suppress the advertisement of particular TLVs with the LLDP PDUs that it transmits. Where a TLV type is specified within this list, it should not be included in any LLDP PDU transmitted by the local agent
**type**\: list of :py:class:`LLDPTLV <ydk.models.openconfig.openconfig_lldp_types.LLDPTLV>`
.. attribute:: system_name
The system name field shall contain an alpha\-numeric string that indicates the system's administratively assigned name. The system name should be the system's fully qualified domain name. If implementations support IETF RFC 3418, the sysName object should be used for this field
**type**\: str
**length:** 0..255
.. attribute:: system_description
The system description field shall contain an alpha\-numeric string that is the textual description of the network entity. The system description should include the full name and version identification of the system's hardware type, software operating system, and networking software. If implementations support IETF RFC 3418, the sysDescr object should be used for this field
**type**\: str
**length:** 0..255
.. attribute:: chassis_id
The Chassis ID is a mandatory TLV which identifies the chassis component of the endpoint identifier associated with the transmitting LLDP agent
**type**\: str
.. attribute:: chassis_id_type
This field identifies the format and source of the chassis identifier string. It is an enumerator defined by the LldpChassisIdSubtype object from IEEE 802.1AB MIB
**type**\: :py:class:`ChassisIdType <ydk.models.openconfig.openconfig_lldp_types.ChassisIdType>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Config, self).__init__()
self.yang_name = "config"
self.yang_parent_name = "lldp"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('enabled', (YLeaf(YType.boolean, 'enabled'), ['bool'])),
('hello_timer', (YLeaf(YType.uint64, 'hello-timer'), ['int'])),
('suppress_tlv_advertisement', (YLeafList(YType.identityref, 'suppress-tlv-advertisement'), [('ydk.models.openconfig.openconfig_lldp_types', 'LLDPTLV')])),
('system_name', (YLeaf(YType.str, 'system-name'), ['str'])),
('system_description', (YLeaf(YType.str, 'system-description'), ['str'])),
('chassis_id', (YLeaf(YType.str, 'chassis-id'), ['str'])),
('chassis_id_type', (YLeaf(YType.enumeration, 'chassis-id-type'), [('ydk.models.openconfig.openconfig_lldp_types', 'ChassisIdType', '')])),
])
self.enabled = None
self.hello_timer = None
self.suppress_tlv_advertisement = []
self.system_name = None
self.system_description = None
self.chassis_id = None
self.chassis_id_type = None
self._segment_path = lambda: "config"
self._absolute_path = lambda: "openconfig-lldp:lldp/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Config, ['enabled', 'hello_timer', 'suppress_tlv_advertisement', 'system_name', 'system_description', 'chassis_id', 'chassis_id_type'], name, value)
class State(Entity):
"""
Operational state data
.. attribute:: enabled
System level state of the LLDP protocol
**type**\: bool
**default value**\: true
.. attribute:: hello_timer
System level hello timer for the LLDP protocol
**type**\: int
**range:** 0..18446744073709551615
**units**\: seconds
.. attribute:: suppress_tlv_advertisement
Indicates whether the local system should suppress the advertisement of particular TLVs with the LLDP PDUs that it transmits. Where a TLV type is specified within this list, it should not be included in any LLDP PDU transmitted by the local agent
**type**\: list of :py:class:`LLDPTLV <ydk.models.openconfig.openconfig_lldp_types.LLDPTLV>`
.. attribute:: system_name
The system name field shall contain an alpha\-numeric string that indicates the system's administratively assigned name. The system name should be the system's fully qualified domain name. If implementations support IETF RFC 3418, the sysName object should be used for this field
**type**\: str
**length:** 0..255
.. attribute:: system_description
The system description field shall contain an alpha\-numeric string that is the textual description of the network entity. The system description should include the full name and version identification of the system's hardware type, software operating system, and networking software. If implementations support IETF RFC 3418, the sysDescr object should be used for this field
**type**\: str
**length:** 0..255
.. attribute:: chassis_id
The Chassis ID is a mandatory TLV which identifies the chassis component of the endpoint identifier associated with the transmitting LLDP agent
**type**\: str
.. attribute:: chassis_id_type
This field identifies the format and source of the chassis identifier string. It is an enumerator defined by the LldpChassisIdSubtype object from IEEE 802.1AB MIB
**type**\: :py:class:`ChassisIdType <ydk.models.openconfig.openconfig_lldp_types.ChassisIdType>`
.. attribute:: counters
Global LLDP counters
**type**\: :py:class:`Counters <ydk.models.openconfig.openconfig_lldp.Lldp.State.Counters>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.State, self).__init__()
self.yang_name = "state"
self.yang_parent_name = "lldp"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([("counters", ("counters", Lldp.State.Counters))])
self._leafs = OrderedDict([
('enabled', (YLeaf(YType.boolean, 'enabled'), ['bool'])),
('hello_timer', (YLeaf(YType.uint64, 'hello-timer'), ['int'])),
('suppress_tlv_advertisement', (YLeafList(YType.identityref, 'suppress-tlv-advertisement'), [('ydk.models.openconfig.openconfig_lldp_types', 'LLDPTLV')])),
('system_name', (YLeaf(YType.str, 'system-name'), ['str'])),
('system_description', (YLeaf(YType.str, 'system-description'), ['str'])),
('chassis_id', (YLeaf(YType.str, 'chassis-id'), ['str'])),
('chassis_id_type', (YLeaf(YType.enumeration, 'chassis-id-type'), [('ydk.models.openconfig.openconfig_lldp_types', 'ChassisIdType', '')])),
])
self.enabled = None
self.hello_timer = None
self.suppress_tlv_advertisement = []
self.system_name = None
self.system_description = None
self.chassis_id = None
self.chassis_id_type = None
self.counters = Lldp.State.Counters()
self.counters.parent = self
self._children_name_map["counters"] = "counters"
self._segment_path = lambda: "state"
self._absolute_path = lambda: "openconfig-lldp:lldp/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.State, ['enabled', 'hello_timer', 'suppress_tlv_advertisement', 'system_name', 'system_description', 'chassis_id', 'chassis_id_type'], name, value)
class Counters(Entity):
"""
Global LLDP counters
.. attribute:: frame_in
The number of lldp frames received
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: frame_out
The number of frames transmitted out
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: frame_error_in
The number of LLDP frames received with errors
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: frame_discard
The number of LLDP frames received and discarded
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: tlv_discard
The number of TLV frames received and discarded
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: tlv_unknown
The number of frames received with unknown TLV
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: last_clear
Indicates the last time the counters were cleared
**type**\: str
**pattern:** \\d{4}\-\\d{2}\-\\d{2}T\\d{2}\:\\d{2}\:\\d{2}(\\.\\d+)?(Z\|[\\+\\\-]\\d{2}\:\\d{2})
.. attribute:: tlv_accepted
The number of valid TLVs received
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: entries_aged_out
The number of entries aged out due to timeout
**type**\: int
**range:** 0..18446744073709551615
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.State.Counters, self).__init__()
self.yang_name = "counters"
self.yang_parent_name = "state"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('frame_in', (YLeaf(YType.uint64, 'frame-in'), ['int'])),
('frame_out', (YLeaf(YType.uint64, 'frame-out'), ['int'])),
('frame_error_in', (YLeaf(YType.uint64, 'frame-error-in'), ['int'])),
('frame_discard', (YLeaf(YType.uint64, 'frame-discard'), ['int'])),
('tlv_discard', (YLeaf(YType.uint64, 'tlv-discard'), ['int'])),
('tlv_unknown', (YLeaf(YType.uint64, 'tlv-unknown'), ['int'])),
('last_clear', (YLeaf(YType.str, 'last-clear'), ['str'])),
('tlv_accepted', (YLeaf(YType.uint64, 'tlv-accepted'), ['int'])),
('entries_aged_out', (YLeaf(YType.uint64, 'entries-aged-out'), ['int'])),
])
self.frame_in = None
self.frame_out = None
self.frame_error_in = None
self.frame_discard = None
self.tlv_discard = None
self.tlv_unknown = None
self.last_clear = None
self.tlv_accepted = None
self.entries_aged_out = None
self._segment_path = lambda: "counters"
self._absolute_path = lambda: "openconfig-lldp:lldp/state/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.State.Counters, ['frame_in', 'frame_out', 'frame_error_in', 'frame_discard', 'tlv_discard', 'tlv_unknown', 'last_clear', 'tlv_accepted', 'entries_aged_out'], name, value)
class Interfaces(Entity):
"""
Enclosing container
.. attribute:: interface
List of interfaces on which LLDP is enabled / available
**type**\: list of :py:class:`Interface <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces, self).__init__()
self.yang_name = "interfaces"
self.yang_parent_name = "lldp"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = []
self._child_classes = OrderedDict([("interface", ("interface", Lldp.Interfaces.Interface))])
self._leafs = OrderedDict()
self.interface = YList(self)
self._segment_path = lambda: "interfaces"
self._absolute_path = lambda: "openconfig-lldp:lldp/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces, [], name, value)
class Interface(Entity):
"""
List of interfaces on which LLDP is enabled / available
.. attribute:: name (key)
Reference to the list key
**type**\: str
**refers to**\: :py:class:`name <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Config>`
.. attribute:: config
Configuration data for LLDP on each interface
**type**\: :py:class:`Config <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Config>`
.. attribute:: state
Operational state data
**type**\: :py:class:`State <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.State>`
.. attribute:: neighbors
Enclosing container for list of LLDP neighbors on an interface
**type**\: :py:class:`Neighbors <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface, self).__init__()
self.yang_name = "interface"
self.yang_parent_name = "interfaces"
self.is_top_level_class = False
self.has_list_ancestor = False
self.ylist_key_names = ['name']
self._child_classes = OrderedDict([("config", ("config", Lldp.Interfaces.Interface.Config)), ("state", ("state", Lldp.Interfaces.Interface.State)), ("neighbors", ("neighbors", Lldp.Interfaces.Interface.Neighbors))])
self._leafs = OrderedDict([
('name', (YLeaf(YType.str, 'name'), ['str'])),
])
self.name = None
self.config = Lldp.Interfaces.Interface.Config()
self.config.parent = self
self._children_name_map["config"] = "config"
self.state = Lldp.Interfaces.Interface.State()
self.state.parent = self
self._children_name_map["state"] = "state"
self.neighbors = Lldp.Interfaces.Interface.Neighbors()
self.neighbors.parent = self
self._children_name_map["neighbors"] = "neighbors"
self._segment_path = lambda: "interface" + "[name='" + str(self.name) + "']"
self._absolute_path = lambda: "openconfig-lldp:lldp/interfaces/%s" % self._segment_path()
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface, ['name'], name, value)
class Config(Entity):
"""
Configuration data for LLDP on each interface
.. attribute:: name
Reference to the LLDP Ethernet interface
**type**\: str
**refers to**\: :py:class:`name <ydk.models.openconfig.openconfig_interfaces.Interfaces.Interface>`
.. attribute:: enabled
Enable or disable the LLDP protocol on the interface
**type**\: bool
**default value**\: true
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Config, self).__init__()
self.yang_name = "config"
self.yang_parent_name = "interface"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('name', (YLeaf(YType.str, 'name'), ['str'])),
('enabled', (YLeaf(YType.boolean, 'enabled'), ['bool'])),
])
self.name = None
self.enabled = None
self._segment_path = lambda: "config"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Config, ['name', 'enabled'], name, value)
class State(Entity):
"""
Operational state data
.. attribute:: name
Reference to the LLDP Ethernet interface
**type**\: str
**refers to**\: :py:class:`name <ydk.models.openconfig.openconfig_interfaces.Interfaces.Interface>`
.. attribute:: enabled
Enable or disable the LLDP protocol on the interface
**type**\: bool
**default value**\: true
.. attribute:: counters
LLDP counters on each interface
**type**\: :py:class:`Counters <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.State.Counters>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.State, self).__init__()
self.yang_name = "state"
self.yang_parent_name = "interface"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([("counters", ("counters", Lldp.Interfaces.Interface.State.Counters))])
self._leafs = OrderedDict([
('name', (YLeaf(YType.str, 'name'), ['str'])),
('enabled', (YLeaf(YType.boolean, 'enabled'), ['bool'])),
])
self.name = None
self.enabled = None
self.counters = Lldp.Interfaces.Interface.State.Counters()
self.counters.parent = self
self._children_name_map["counters"] = "counters"
self._segment_path = lambda: "state"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.State, ['name', 'enabled'], name, value)
class Counters(Entity):
"""
LLDP counters on each interface
.. attribute:: frame_in
The number of lldp frames received
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: frame_out
The number of frames transmitted out
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: frame_error_in
The number of LLDP frames received with errors
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: frame_discard
The number of LLDP frames received and discarded
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: tlv_discard
The number of TLV frames received and discarded
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: tlv_unknown
The number of frames received with unknown TLV
**type**\: int
**range:** 0..18446744073709551615
.. attribute:: last_clear
Indicates the last time the counters were cleared
**type**\: str
**pattern:** \\d{4}\-\\d{2}\-\\d{2}T\\d{2}\:\\d{2}\:\\d{2}(\\.\\d+)?(Z\|[\\+\\\-]\\d{2}\:\\d{2})
.. attribute:: frame_error_out
The number of frame transmit errors on the interface
**type**\: int
**range:** 0..18446744073709551615
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.State.Counters, self).__init__()
self.yang_name = "counters"
self.yang_parent_name = "state"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('frame_in', (YLeaf(YType.uint64, 'frame-in'), ['int'])),
('frame_out', (YLeaf(YType.uint64, 'frame-out'), ['int'])),
('frame_error_in', (YLeaf(YType.uint64, 'frame-error-in'), ['int'])),
('frame_discard', (YLeaf(YType.uint64, 'frame-discard'), ['int'])),
('tlv_discard', (YLeaf(YType.uint64, 'tlv-discard'), ['int'])),
('tlv_unknown', (YLeaf(YType.uint64, 'tlv-unknown'), ['int'])),
('last_clear', (YLeaf(YType.str, 'last-clear'), ['str'])),
('frame_error_out', (YLeaf(YType.uint64, 'frame-error-out'), ['int'])),
])
self.frame_in = None
self.frame_out = None
self.frame_error_in = None
self.frame_discard = None
self.tlv_discard = None
self.tlv_unknown = None
self.last_clear = None
self.frame_error_out = None
self._segment_path = lambda: "counters"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.State.Counters, ['frame_in', 'frame_out', 'frame_error_in', 'frame_discard', 'tlv_discard', 'tlv_unknown', 'last_clear', 'frame_error_out'], name, value)
class Neighbors(Entity):
"""
Enclosing container for list of LLDP neighbors on an
interface
.. attribute:: neighbor
List of LLDP neighbors
**type**\: list of :py:class:`Neighbor <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors, self).__init__()
self.yang_name = "neighbors"
self.yang_parent_name = "interface"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([("neighbor", ("neighbor", Lldp.Interfaces.Interface.Neighbors.Neighbor))])
self._leafs = OrderedDict()
self.neighbor = YList(self)
self._segment_path = lambda: "neighbors"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors, [], name, value)
class Neighbor(Entity):
"""
List of LLDP neighbors
.. attribute:: id (key)
**type**\: str
**refers to**\: :py:class:`id <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.State>`
.. attribute:: config
Configuration data
**type**\: :py:class:`Config <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.Config>`
.. attribute:: state
Operational state data
**type**\: :py:class:`State <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.State>`
.. attribute:: custom_tlvs
Enclosing container for list of custom TLVs from a neighbor
**type**\: :py:class:`CustomTlvs <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs>`
.. attribute:: capabilities
Enclosing container for list of LLDP capabilities
**type**\: :py:class:`Capabilities <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor, self).__init__()
self.yang_name = "neighbor"
self.yang_parent_name = "neighbors"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = ['id']
self._child_classes = OrderedDict([("config", ("config", Lldp.Interfaces.Interface.Neighbors.Neighbor.Config)), ("state", ("state", Lldp.Interfaces.Interface.Neighbors.Neighbor.State)), ("custom-tlvs", ("custom_tlvs", Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs)), ("capabilities", ("capabilities", Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities))])
self._leafs = OrderedDict([
('id', (YLeaf(YType.str, 'id'), ['str'])),
])
self.id = None
self.config = Lldp.Interfaces.Interface.Neighbors.Neighbor.Config()
self.config.parent = self
self._children_name_map["config"] = "config"
self.state = Lldp.Interfaces.Interface.Neighbors.Neighbor.State()
self.state.parent = self
self._children_name_map["state"] = "state"
self.custom_tlvs = Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs()
self.custom_tlvs.parent = self
self._children_name_map["custom_tlvs"] = "custom-tlvs"
self.capabilities = Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities()
self.capabilities.parent = self
self._children_name_map["capabilities"] = "capabilities"
self._segment_path = lambda: "neighbor" + "[id='" + str(self.id) + "']"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor, ['id'], name, value)
class Config(Entity):
"""
Configuration data
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.Config, self).__init__()
self.yang_name = "config"
self.yang_parent_name = "neighbor"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict()
self._segment_path = lambda: "config"
self._is_frozen = True
class State(Entity):
"""
Operational state data
.. attribute:: system_name
The system name field shall contain an alpha\-numeric string that indicates the system's administratively assigned name. The system name should be the system's fully qualified domain name. If implementations support IETF RFC 3418, the sysName object should be used for this field
**type**\: str
**length:** 0..255
.. attribute:: system_description
The system description field shall contain an alpha\-numeric string that is the textual description of the network entity. The system description should include the full name and version identification of the system's hardware type, software operating system, and networking software. If implementations support IETF RFC 3418, the sysDescr object should be used for this field
**type**\: str
**length:** 0..255
.. attribute:: chassis_id
The Chassis ID is a mandatory TLV which identifies the chassis component of the endpoint identifier associated with the transmitting LLDP agent
**type**\: str
.. attribute:: chassis_id_type
This field identifies the format and source of the chassis identifier string. It is an enumerator defined by the LldpChassisIdSubtype object from IEEE 802.1AB MIB
**type**\: :py:class:`ChassisIdType <ydk.models.openconfig.openconfig_lldp_types.ChassisIdType>`
.. attribute:: id
System generated identifier for the neighbor on the interface
**type**\: str
.. attribute:: age
Age since discovery
**type**\: int
**range:** 0..18446744073709551615
**units**\: seconds
.. attribute:: last_update
Seconds since last update received
**type**\: int
**range:** \-9223372036854775808..9223372036854775807
.. attribute:: port_id
The Port ID is a mandatory TLV which identifies the port component of the endpoint identifier associated with the transmitting LLDP agent. If the specified port is an IEEE 802.3 Repeater port, then this TLV is optional
**type**\: str
.. attribute:: port_id_type
This field identifies the format and source of the port identifier string. It is an enumerator defined by the PtopoPortIdType object from RFC2922
**type**\: :py:class:`PortIdType <ydk.models.openconfig.openconfig_lldp_types.PortIdType>`
.. attribute:: port_description
The binary string containing the actual port identifier for the port which this LLDP PDU was transmitted. The source and format of this field is defined by PtopoPortId from RFC2922
**type**\: str
.. attribute:: management_address
The Management Address is a mandatory TLV which identifies a network address associated with the local LLDP agent, which can be used to reach the agent on the port identified in the Port ID TLV
**type**\: str
.. attribute:: management_address_type
The enumerated value for the network address type identified in this TLV. This enumeration is defined in the 'Assigned Numbers' RFC [RFC3232] and the ianaAddressFamilyNumbers object
**type**\: str
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.State, self).__init__()
self.yang_name = "state"
self.yang_parent_name = "neighbor"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('system_name', (YLeaf(YType.str, 'system-name'), ['str'])),
('system_description', (YLeaf(YType.str, 'system-description'), ['str'])),
('chassis_id', (YLeaf(YType.str, 'chassis-id'), ['str'])),
('chassis_id_type', (YLeaf(YType.enumeration, 'chassis-id-type'), [('ydk.models.openconfig.openconfig_lldp_types', 'ChassisIdType', '')])),
('id', (YLeaf(YType.str, 'id'), ['str'])),
('age', (YLeaf(YType.uint64, 'age'), ['int'])),
('last_update', (YLeaf(YType.int64, 'last-update'), ['int'])),
('port_id', (YLeaf(YType.str, 'port-id'), ['str'])),
('port_id_type', (YLeaf(YType.enumeration, 'port-id-type'), [('ydk.models.openconfig.openconfig_lldp_types', 'PortIdType', '')])),
('port_description', (YLeaf(YType.str, 'port-description'), ['str'])),
('management_address', (YLeaf(YType.str, 'management-address'), ['str'])),
('management_address_type', (YLeaf(YType.str, 'management-address-type'), ['str'])),
])
self.system_name = None
self.system_description = None
self.chassis_id = None
self.chassis_id_type = None
self.id = None
self.age = None
self.last_update = None
self.port_id = None
self.port_id_type = None
self.port_description = None
self.management_address = None
self.management_address_type = None
self._segment_path = lambda: "state"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor.State, ['system_name', 'system_description', 'chassis_id', 'chassis_id_type', 'id', 'age', 'last_update', 'port_id', 'port_id_type', 'port_description', 'management_address', 'management_address_type'], name, value)
class CustomTlvs(Entity):
"""
Enclosing container for list of custom TLVs from a
neighbor
.. attribute:: tlv
List of custom LLDP TLVs from a neighbor
**type**\: list of :py:class:`Tlv <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs, self).__init__()
self.yang_name = "custom-tlvs"
self.yang_parent_name = "neighbor"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([("tlv", ("tlv", Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv))])
self._leafs = OrderedDict()
self.tlv = YList(self)
self._segment_path = lambda: "custom-tlvs"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs, [], name, value)
class Tlv(Entity):
"""
List of custom LLDP TLVs from a neighbor
.. attribute:: type (key)
Reference to type list key
**type**\: int
**range:** \-2147483648..2147483647
**refers to**\: :py:class:`type <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State>`
.. attribute:: oui (key)
Reference to oui list key
**type**\: str
**refers to**\: :py:class:`oui <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State>`
.. attribute:: oui_subtype (key)
Reference to oui\-subtype list key
**type**\: str
**refers to**\: :py:class:`oui_subtype <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State>`
.. attribute:: config
Configuration data
**type**\: :py:class:`Config <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.Config>`
.. attribute:: state
Operational state data
**type**\: :py:class:`State <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv, self).__init__()
self.yang_name = "tlv"
self.yang_parent_name = "custom-tlvs"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = ['type','oui','oui_subtype']
self._child_classes = OrderedDict([("config", ("config", Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.Config)), ("state", ("state", Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State))])
self._leafs = OrderedDict([
('type', (YLeaf(YType.str, 'type'), ['int'])),
('oui', (YLeaf(YType.str, 'oui'), ['str'])),
('oui_subtype', (YLeaf(YType.str, 'oui-subtype'), ['str'])),
])
self.type = None
self.oui = None
self.oui_subtype = None
self.config = Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.Config()
self.config.parent = self
self._children_name_map["config"] = "config"
self.state = Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State()
self.state.parent = self
self._children_name_map["state"] = "state"
self._segment_path = lambda: "tlv" + "[type='" + str(self.type) + "']" + "[oui='" + str(self.oui) + "']" + "[oui-subtype='" + str(self.oui_subtype) + "']"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv, ['type', 'oui', 'oui_subtype'], name, value)
class Config(Entity):
"""
Configuration data
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.Config, self).__init__()
self.yang_name = "config"
self.yang_parent_name = "tlv"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict()
self._segment_path = lambda: "config"
self._is_frozen = True
class State(Entity):
"""
Operational state data
.. attribute:: type
The integer value identifying the type of information contained in the value field
**type**\: int
**range:** \-2147483648..2147483647
.. attribute:: oui
The organizationally unique identifier field shall contain the organization's OUI as defined in Clause 9 of IEEE Std 802. The high\-order octet is 0 and the low\-order 3 octets are the SMI Network Management Private Enterprise Code of the Vendor in network byte order, as defined in the 'Assigned Numbers' RFC [RFC3232]
**type**\: str
.. attribute:: oui_subtype
The organizationally defined subtype field shall contain a unique subtype value assigned by the defining organization
**type**\: str
.. attribute:: value
A variable\-length octet\-string containing the instance\-specific information for this TLV
**type**\: str
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State, self).__init__()
self.yang_name = "state"
self.yang_parent_name = "tlv"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('type', (YLeaf(YType.int32, 'type'), ['int'])),
('oui', (YLeaf(YType.str, 'oui'), ['str'])),
('oui_subtype', (YLeaf(YType.str, 'oui-subtype'), ['str'])),
('value', (YLeaf(YType.str, 'value'), ['str'])),
])
self.type = None
self.oui = None
self.oui_subtype = None
self.value = None
self._segment_path = lambda: "state"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor.CustomTlvs.Tlv.State, ['type', 'oui', 'oui_subtype', 'value'], name, value)
class Capabilities(Entity):
"""
Enclosing container for list of LLDP capabilities
.. attribute:: capability
List of LLDP system capabilities advertised by the neighbor
**type**\: list of :py:class:`Capability <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities, self).__init__()
self.yang_name = "capabilities"
self.yang_parent_name = "neighbor"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([("capability", ("capability", Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability))])
self._leafs = OrderedDict()
self.capability = YList(self)
self._segment_path = lambda: "capabilities"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities, [], name, value)
class Capability(Entity):
"""
List of LLDP system capabilities advertised by the
neighbor
.. attribute:: name (key)
Reference to capabilities list key
**type**\: :py:class:`LLDPSYSTEMCAPABILITY <ydk.models.openconfig.openconfig_lldp_types.LLDPSYSTEMCAPABILITY>`
.. attribute:: config
Configuration data for LLDP capabilities
**type**\: :py:class:`Config <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.Config>`
.. attribute:: state
Operational state data for LLDP capabilities
**type**\: :py:class:`State <ydk.models.openconfig.openconfig_lldp.Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.State>`
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability, self).__init__()
self.yang_name = "capability"
self.yang_parent_name = "capabilities"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = ['name']
self._child_classes = OrderedDict([("config", ("config", Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.Config)), ("state", ("state", Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.State))])
self._leafs = OrderedDict([
('name', (YLeaf(YType.identityref, 'name'), [('ydk.models.openconfig.openconfig_lldp_types', 'LLDPSYSTEMCAPABILITY')])),
])
self.name = None
self.config = Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.Config()
self.config.parent = self
self._children_name_map["config"] = "config"
self.state = Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.State()
self.state.parent = self
self._children_name_map["state"] = "state"
self._segment_path = lambda: "capability" + "[name='" + str(self.name) + "']"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability, ['name'], name, value)
class Config(Entity):
"""
Configuration data for LLDP capabilities
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.Config, self).__init__()
self.yang_name = "config"
self.yang_parent_name = "capability"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict()
self._segment_path = lambda: "config"
self._is_frozen = True
class State(Entity):
"""
Operational state data for LLDP capabilities
.. attribute:: name
Name of the system capability advertised by the neighbor. Capabilities are represented in a bitmap that defines the primary functions of the system. The capabilities are defined in IEEE 802.1AB
**type**\: :py:class:`LLDPSYSTEMCAPABILITY <ydk.models.openconfig.openconfig_lldp_types.LLDPSYSTEMCAPABILITY>`
.. attribute:: enabled
Indicates whether the corresponding system capability is enabled on the neighbor
**type**\: bool
"""
_prefix = 'oc-lldp'
_revision = '2016-05-16'
def __init__(self):
super(Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.State, self).__init__()
self.yang_name = "state"
self.yang_parent_name = "capability"
self.is_top_level_class = False
self.has_list_ancestor = True
self.ylist_key_names = []
self._child_classes = OrderedDict([])
self._leafs = OrderedDict([
('name', (YLeaf(YType.identityref, 'name'), [('ydk.models.openconfig.openconfig_lldp_types', 'LLDPSYSTEMCAPABILITY')])),
('enabled', (YLeaf(YType.boolean, 'enabled'), ['bool'])),
])
self.name = None
self.enabled = None
self._segment_path = lambda: "state"
self._is_frozen = True
def __setattr__(self, name, value):
self._perform_setattr(Lldp.Interfaces.Interface.Neighbors.Neighbor.Capabilities.Capability.State, ['name', 'enabled'], name, value)
def clone_ptr(self):
self._top_entity = Lldp()
return self._top_entity
| 47.825077
| 401
| 0.474688
| 5,220
| 61,790
| 5.421264
| 0.058238
| 0.041556
| 0.063394
| 0.065585
| 0.840878
| 0.815506
| 0.790876
| 0.766458
| 0.733878
| 0.70794
| 0
| 0.021947
| 0.430733
| 61,790
| 1,291
| 402
| 47.862122
| 0.782573
| 0.28681
| 0
| 0.719165
| 0
| 0
| 0.116113
| 0.020202
| 0.001898
| 0
| 0
| 0
| 0
| 1
| 0.075901
| false
| 0
| 0.009488
| 0
| 0.13093
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
76a46fd744ad57d084380e6e9ffb9c696c6d5cd5
| 12,618
|
py
|
Python
|
geotagged_weibo/download_picture.py
|
placeasmedia/kunming_urban_communities
|
d71e8be686ad3e8271dc13252ac15474e47fa736
|
[
"MIT"
] | null | null | null |
geotagged_weibo/download_picture.py
|
placeasmedia/kunming_urban_communities
|
d71e8be686ad3e8271dc13252ac15474e47fa736
|
[
"MIT"
] | null | null | null |
geotagged_weibo/download_picture.py
|
placeasmedia/kunming_urban_communities
|
d71e8be686ad3e8271dc13252ac15474e47fa736
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
import sqlite3
import urllib
import os
import sys
import datetime
write_dir = '/scratch/users/cchang45/rural'
sqlite_file = 'geotag.sqlite'
def _retrieve_post():
conn = sqlite3.connect(write_dir + sqlite_file, timeout=75)
c = conn.cursor()
select_sql = "select images, post_id, creation_date from posts where imgdate is null limit 20;"
c.execute(select_sql)
records = c.fetchall()
conn.commit()
conn.close()
return records
def _update_post(post_id, imgdate):
conn = sqlite3.connect(write_dir + sqlite_file, timeout=75)
c = conn.cursor()
# print post_id, imgdate
try:
c.execute("""update posts set imgdate = ? WHERE post_id = ?;""", (imgdate, post_id))
except Exception as e:
print e
pass
conn.commit()
conn.close()
def _insert_pic(postid, img, imgpath):
conn = sqlite3.connect(write_dir + sqlite_file, timeout=75)
c = conn.cursor()
table_name = 'pictures'
table_fields = '(post_id, image, imgpath)'
values_string = 'VALUES(?,?,?)'
database_command = 'INSERT INTO ' + table_name + ' ' + values_string
print database_command
database_values = (postid, img, imgpath)
print database_values
try:
c.execute(database_command, database_values)
except Exception as e:
print e
pass
conn.commit()
conn.close()
def _download_img(imglink, post_id, date):
try:
imagelink = IMAGE_BASE_LINK1 + imglink + '.jpg'
## form a date path
imgdirectory = 'Picture/' + date +'/' + post_id
if os.path.exists(write_dir + imgdirectory):
pass
else:
os.mkdir(write_dir + imgdirectory, 0755)
imgpath = write_dir + imgdirectory + '/' + imglink + '.jpg'
urllib.urlretrieve(imagelink, imgpath)
except:
try:
imagelink = IMAGE_BASE_LINK2 + imglink + '.jpg'
urllib.urlretrieve(imagelink, imgpath)
except:
try:
imagelink = IMAGE_BASE_LINK3 + imglink + '.jpg'
urllib.urlretrieve(imagelink, imgpath)
except:
try:
imagelink = IMAGE_BASE_LINK4 + imglink + '.jpg'
urllib.urlretrieve(imagelink, imgpath)
except:
print imagelink
raise
return imgdirectory
if __name__ == "__main__":
## Make DIR
path = './Picture/'
IMAGE_BASE_LINK1 = 'http://wx1.sinaimg.cn/large/'
IMAGE_BASE_LINK2 = 'http://wx2.sinaimg.cn/large/'
IMAGE_BASE_LINK3 = 'http://wx3.sinaimg.cn/large/'
IMAGE_BASE_LINK4 = 'http://wx4.sinaimg.cn/large/'
for n in range(1000000):
records = _retrieve_post()
for record in records:
image = record[0]
post_id = record[1]
post_id = str(post_id)
creation_date = record[2]
creation_date = str(creation_date)
creation_date = creation_date[0:19] + creation_date[25:30]
datet = datetime.datetime.strptime(creation_date, '%a %b %d %H:%M:%S %Y')
datet = datet.strftime("%Y-%m-%d")
if len(image) == 2:
# print post_id, datet
datet = 'NA'
_update_post(post_id, datet)
elif len(image) == 37:
image = str(image[3:35])
# print image, datet
imgdirectory = _download_img(image, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image, imgdirectory)
elif len(image) == 74:
image1 = str(image[3:35])
image2 = str(image[40:72])
# print image1, image2, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
elif len(image) == 111:
# print image
image1 = str(image[3:35])
image2 = str(image[40:72])
image3 = str(image[77:109])
# print image1, image2, image3, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
imgdirectory = _download_img(image3, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
_insert_pic(post_id, image3, imgdirectory)
elif len(image) == 148:
# print image
image1 = str(image[3:35])
image2 = str(image[40:72])
image3 = str(image[77:109])
image4 = str(image[114:146])
# print image1, image2, image3, image4, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
imgdirectory = _download_img(image3, post_id, datet)
imgdirectory = _download_img(image4, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
_insert_pic(post_id, image3, imgdirectory)
_insert_pic(post_id, image4, imgdirectory)
elif len(image) == 185:
# print image
image1 = str(image[3:35])
image2 = str(image[40:72])
image3 = str(image[77:109])
image4 = str(image[114:146])
image5 = str(image[151:183])
# print image1, image2, image3, image4, image5, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
imgdirectory = _download_img(image3, post_id, datet)
imgdirectory = _download_img(image4, post_id, datet)
imgdirectory = _download_img(image5, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
_insert_pic(post_id, image3, imgdirectory)
_insert_pic(post_id, image4, imgdirectory)
_insert_pic(post_id, image5, imgdirectory)
elif len(image) == 222:
# print image
image1 = str(image[3:35])
image2 = str(image[40:72])
image3 = str(image[77:109])
image4 = str(image[114:146])
image5 = str(image[151:183])
image6 = str(image[188:220])
# print image1, image2, image3, image4, image5, image6, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
imgdirectory = _download_img(image3, post_id, datet)
imgdirectory = _download_img(image4, post_id, datet)
imgdirectory = _download_img(image5, post_id, datet)
imgdirectory = _download_img(image6, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
_insert_pic(post_id, image3, imgdirectory)
_insert_pic(post_id, image4, imgdirectory)
_insert_pic(post_id, image5, imgdirectory)
_insert_pic(post_id, image6, imgdirectory)
elif len(image) == 259:
# print image
image1 = str(image[3:35])
image2 = str(image[40:72])
image3 = str(image[77:109])
image4 = str(image[114:146])
image5 = str(image[151:183])
image6 = str(image[188:220])
image7 = str(image[225:257])
# print image1, image2, image3, image4, image5, image6, image7, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
imgdirectory = _download_img(image3, post_id, datet)
imgdirectory = _download_img(image4, post_id, datet)
imgdirectory = _download_img(image5, post_id, datet)
imgdirectory = _download_img(image6, post_id, datet)
imgdirectory = _download_img(image7, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
_insert_pic(post_id, image3, imgdirectory)
_insert_pic(post_id, image4, imgdirectory)
_insert_pic(post_id, image5, imgdirectory)
_insert_pic(post_id, image6, imgdirectory)
_insert_pic(post_id, image7, imgdirectory)
elif len(image) == 296:
# print image
image1 = str(image[3:35])
image2 = str(image[40:72])
image3 = str(image[77:109])
image4 = str(image[114:146])
image5 = str(image[151:183])
image6 = str(image[188:220])
image7 = str(image[225:257])
image8 = str(image[262:294])
# print image1, image2, image3, image4, image5, image6, image7, image8, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
imgdirectory = _download_img(image3, post_id, datet)
imgdirectory = _download_img(image4, post_id, datet)
imgdirectory = _download_img(image5, post_id, datet)
imgdirectory = _download_img(image6, post_id, datet)
imgdirectory = _download_img(image7, post_id, datet)
imgdirectory = _download_img(image8, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
_insert_pic(post_id, image3, imgdirectory)
_insert_pic(post_id, image4, imgdirectory)
_insert_pic(post_id, image5, imgdirectory)
_insert_pic(post_id, image6, imgdirectory)
_insert_pic(post_id, image7, imgdirectory)
_insert_pic(post_id, image8, imgdirectory)
elif len(image) == 333:
# print image
image1 = str(image[3:35])
image2 = str(image[40:72])
image3 = str(image[77:109])
image4 = str(image[114:146])
image5 = str(image[151:183])
image6 = str(image[188:220])
image7 = str(image[225:257])
image8 = str(image[262:294])
image9 = str(image[299:331])
# print image1, image2, image3, image4, image5, image6, image7, image8, image9, datet
imgdirectory = _download_img(image1, post_id, datet)
imgdirectory = _download_img(image2, post_id, datet)
imgdirectory = _download_img(image3, post_id, datet)
imgdirectory = _download_img(image4, post_id, datet)
imgdirectory = _download_img(image5, post_id, datet)
imgdirectory = _download_img(image6, post_id, datet)
imgdirectory = _download_img(image7, post_id, datet)
imgdirectory = _download_img(image8, post_id, datet)
imgdirectory = _download_img(image9, post_id, datet)
_update_post(post_id, datet)
_insert_pic(post_id, image1, imgdirectory)
_insert_pic(post_id, image2, imgdirectory)
_insert_pic(post_id, image3, imgdirectory)
_insert_pic(post_id, image4, imgdirectory)
_insert_pic(post_id, image5, imgdirectory)
_insert_pic(post_id, image6, imgdirectory)
_insert_pic(post_id, image7, imgdirectory)
_insert_pic(post_id, image8, imgdirectory)
_insert_pic(post_id, image9, imgdirectory)
| 44.744681
| 101
| 0.565858
| 1,354
| 12,618
| 4.994092
| 0.120384
| 0.099379
| 0.091097
| 0.186335
| 0.769151
| 0.749335
| 0.740757
| 0.727448
| 0.720497
| 0.704821
| 0
| 0.056511
| 0.340862
| 12,618
| 281
| 102
| 44.903915
| 0.756523
| 0.05088
| 0
| 0.710744
| 0
| 0
| 0.034979
| 0.002427
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.012397
| 0.020661
| null | null | 0.020661
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
76ba333ecdf5f008737570dcda90b20ba132c6a7
| 144
|
py
|
Python
|
aim/sdk/objects/__init__.py
|
osoblanco/aim
|
5ed10e44ddf50da676db662d0de948c60aec5ac9
|
[
"Apache-2.0"
] | null | null | null |
aim/sdk/objects/__init__.py
|
osoblanco/aim
|
5ed10e44ddf50da676db662d0de948c60aec5ac9
|
[
"Apache-2.0"
] | null | null | null |
aim/sdk/objects/__init__.py
|
osoblanco/aim
|
5ed10e44ddf50da676db662d0de948c60aec5ac9
|
[
"Apache-2.0"
] | null | null | null |
from aim.sdk.objects.image import Image
from aim.sdk.objects.distribution import Distribution
from aim.sdk.objects.dictionary import Dictionary
| 36
| 53
| 0.854167
| 21
| 144
| 5.857143
| 0.380952
| 0.170732
| 0.243902
| 0.414634
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 144
| 3
| 54
| 48
| 0.931818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
4f351098c664dc6493db9cbf7ab8aba21212f605
| 68
|
py
|
Python
|
generation/src/offset.py
|
cedric-demongivert/gl-tool-math
|
603d96a6b41247460fe9a386f7320f231f1266d3
|
[
"MIT"
] | null | null | null |
generation/src/offset.py
|
cedric-demongivert/gl-tool-math
|
603d96a6b41247460fe9a386f7320f231f1266d3
|
[
"MIT"
] | null | null | null |
generation/src/offset.py
|
cedric-demongivert/gl-tool-math
|
603d96a6b41247460fe9a386f7320f231f1266d3
|
[
"MIT"
] | null | null | null |
def offset (column, row, columns) :
return column + row * columns
| 22.666667
| 35
| 0.691176
| 9
| 68
| 5.222222
| 0.666667
| 0.382979
| 0.680851
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.205882
| 68
| 2
| 36
| 34
| 0.87037
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
4f3950512c515ecc4a1b64e0a09ff483a155097a
| 6,269
|
py
|
Python
|
tests/test_collection.py
|
kleon1024/ChainMore-API-Flask
|
4fc5f2537ce9b648e37b1679c1af6f95a70d45bf
|
[
"Apache-2.0"
] | 1
|
2019-10-29T06:31:04.000Z
|
2019-10-29T06:31:04.000Z
|
tests/test_collection.py
|
kleon1024/ChainMore-API-Flask
|
4fc5f2537ce9b648e37b1679c1af6f95a70d45bf
|
[
"Apache-2.0"
] | null | null | null |
tests/test_collection.py
|
kleon1024/ChainMore-API-Flask
|
4fc5f2537ce9b648e37b1679c1af6f95a70d45bf
|
[
"Apache-2.0"
] | null | null | null |
from flask import current_app
from tests.base import BaseTestCase
class CollectionTestCase(BaseTestCase):
def test_create_collection(self):
self.login()
response = self.get('/v1/resource/media_type',
query_string=dict(name='text'))
data = self.OK(response)
self.assertEqual(data['items'][0]['name'], 'text')
media_type_id = data['items'][0]['id']
response = self.get('/v1/resource/resource_type',
query_string=dict(name='article'))
data = self.OK(response)
self.assertEqual(data['items'][0]['name'], 'article')
resource_type_id = data['items'][0]['id']
response = self.post('/v1/resource',
json=dict(title='HTML for beginner',
url='https://github.com',
external=True,
free=True,
resource_type_id=resource_type_id,
media_type_id=media_type_id))
data = self.OK(response)
resource_id = data['items'][0]['id']
response = self.post('/v1/collection',
json=dict(
title='HTML Beginner\'s Compilation',
description='Not ready',
domain_id=1,
resources=[resource_id],
))
data = self.OK(response)
self.logout()
def test_collection_duplicate_resource(self):
self.login()
response = self.get('/v1/resource/media_type',
query_string=dict(name='text'))
data = self.OK(response)
self.assertEqual(data['items'][0]['name'], 'text')
media_type_id = data['items'][0]['id']
response = self.get('/v1/resource/resource_type',
query_string=dict(name='article'))
data = self.OK(response)
self.assertEqual(data['items'][0]['name'], 'article')
resource_type_id = data['items'][0]['id']
response = self.post('/v1/resource',
json=dict(title='HTML for beginner',
url='https://github.com',
external=True,
free=True,
resource_type_id=resource_type_id,
media_type_id=media_type_id))
data = self.OK(response)
resource_id = data['items'][0]['id']
response = self.post(
'/v1/collection',
json=dict(
title='HTML Beginner\'s Compilation',
description='Not ready',
domain_id=1,
resources=[resource_id, resource_id, resource_id],
))
data = self.OK(response)
self.logout()
def test_collection_ordered_resource(self):
self.login()
response = self.get('/v1/resource/media_type',
query_string=dict(name='text'))
data = self.OK(response)
self.assertEqual(data['items'][0]['name'], 'text')
media_type_id = data['items'][0]['id']
response = self.get('/v1/resource/resource_type',
query_string=dict(name='article'))
data = self.OK(response)
self.assertEqual(data['items'][0]['name'], 'article')
resource_type_id = data['items'][0]['id']
response = self.post('/v1/resource',
json=dict(title='HTML for beginner',
url='https://github.com',
external=True,
free=True,
resource_type_id=resource_type_id,
media_type_id=media_type_id))
data = self.OK(response)
resource_id = data['items'][0]['id']
response = self.post('/v1/resource/exist',
json=dict(url='https://github.com'))
data = self.OK(response)
self.assertEqual(data['items'][0]['id'], resource_id)
response = self.post('/v1/resource',
json=dict(title='HTML2 for beginner',
url='https://github2.com',
external=True,
free=True,
resource_type_id=resource_type_id,
media_type_id=media_type_id))
data = self.OK(response)
resource2_id = data['items'][0]['id']
response = self.post('/v1/resource',
json=dict(title='HTML3 for beginner',
url='https://github3.com',
external=True,
free=True,
resource_type_id=resource_type_id,
media_type_id=media_type_id))
data = self.OK(response)
resource3_id = data['items'][0]['id']
response = self.post('/v1/collection',
json=dict(
title='HTML Beginner\'s Compilation',
description='Not ready',
domain_id=1,
resources=[resource_id, resource2_id],
))
data = self.OK(response)
collection_id = data['items'][0]['id']
response = self.put('/v1/collection',
json=dict(
id=collection_id,
title='HTML Beginner\'s Compilation',
description='Not ready',
domain_id=1,
resources=[resource3_id, resource2_id],
))
data = self.OK(response)
self.logout()
| 42.646259
| 73
| 0.444409
| 568
| 6,269
| 4.741197
| 0.116197
| 0.115856
| 0.070553
| 0.106944
| 0.882659
| 0.882659
| 0.882659
| 0.847011
| 0.847011
| 0.815819
| 0
| 0.013667
| 0.439783
| 6,269
| 146
| 74
| 42.938356
| 0.753132
| 0
| 0
| 0.809524
| 0
| 0
| 0.124581
| 0.023449
| 0
| 0
| 0
| 0
| 0.055556
| 1
| 0.02381
| false
| 0
| 0.015873
| 0
| 0.047619
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
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| 0
| 0
| 0
| 0
|
0
| 7
|
4f5c9048dd476ea8887e0957e1784c0c1a8ca13f
| 59,174
|
py
|
Python
|
tinkoff/invest/grpc/orders_pb2.py
|
forked-group/invest-python
|
3398391f5bb4a52020c312855de175cfe8cdc021
|
[
"Apache-2.0"
] | null | null | null |
tinkoff/invest/grpc/orders_pb2.py
|
forked-group/invest-python
|
3398391f5bb4a52020c312855de175cfe8cdc021
|
[
"Apache-2.0"
] | null | null | null |
tinkoff/invest/grpc/orders_pb2.py
|
forked-group/invest-python
|
3398391f5bb4a52020c312855de175cfe8cdc021
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: tinkoff/invest/grpc/orders.proto
"""Generated protocol buffer code."""
from google.protobuf.internal import enum_type_wrapper
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from tinkoff.invest.grpc import common_pb2 as tinkoff_dot_invest_dot_grpc_dot_common__pb2
from google.protobuf import timestamp_pb2 as google_dot_protobuf_dot_timestamp__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='tinkoff/invest/grpc/orders.proto',
package='tinkoff.public.invest.api.contract.v1',
syntax='proto3',
serialized_options=b'\n\034ru.tinkoff.piapi.contract.v1P\001Z\014./;investapi\242\002\005TIAPI\252\002\024Tinkoff.InvestApi.V1\312\002\021Tinkoff\\Invest\\V1',
create_key=_descriptor._internal_create_key,
serialized_pb=b'\n tinkoff/invest/grpc/orders.proto\x12%tinkoff.public.invest.api.contract.v1\x1a tinkoff/invest/grpc/common.proto\x1a\x1fgoogle/protobuf/timestamp.proto\"\x15\n\x13TradesStreamRequest\"\xaa\x01\n\x14TradesStreamResponse\x12J\n\x0corder_trades\x18\x01 \x01(\x0b\x32\x32.tinkoff.public.invest.api.contract.v1.OrderTradesH\x00\x12;\n\x04ping\x18\x02 \x01(\x0b\x32+.tinkoff.public.invest.api.contract.v1.PingH\x00\x42\t\n\x07payload\"\xfe\x01\n\x0bOrderTrades\x12\x10\n\x08order_id\x18\x01 \x01(\t\x12.\n\ncreated_at\x18\x02 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12H\n\tdirection\x18\x03 \x01(\x0e\x32\x35.tinkoff.public.invest.api.contract.v1.OrderDirection\x12\x0c\n\x04\x66igi\x18\x04 \x01(\t\x12\x41\n\x06trades\x18\x05 \x03(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.OrderTrade\x12\x12\n\naccount_id\x18\x06 \x01(\t\"\x8e\x01\n\nOrderTrade\x12-\n\tdate_time\x18\x01 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12?\n\x05price\x18\x02 \x01(\x0b\x32\x30.tinkoff.public.invest.api.contract.v1.Quotation\x12\x10\n\x08quantity\x18\x03 \x01(\x03\"\xa9\x02\n\x10PostOrderRequest\x12\x0c\n\x04\x66igi\x18\x01 \x01(\t\x12\x10\n\x08quantity\x18\x02 \x01(\x03\x12?\n\x05price\x18\x03 \x01(\x0b\x32\x30.tinkoff.public.invest.api.contract.v1.Quotation\x12H\n\tdirection\x18\x04 \x01(\x0e\x32\x35.tinkoff.public.invest.api.contract.v1.OrderDirection\x12\x12\n\naccount_id\x18\x05 \x01(\t\x12\x44\n\norder_type\x18\x06 \x01(\x0e\x32\x30.tinkoff.public.invest.api.contract.v1.OrderType\x12\x10\n\x08order_id\x18\x07 \x01(\t\"\xe1\x07\n\x11PostOrderResponse\x12\x10\n\x08order_id\x18\x01 \x01(\t\x12\x62\n\x17\x65xecution_report_status\x18\x02 \x01(\x0e\x32\x41.tinkoff.public.invest.api.contract.v1.OrderExecutionReportStatus\x12\x16\n\x0elots_requested\x18\x03 \x01(\x03\x12\x15\n\rlots_executed\x18\x04 \x01(\x03\x12N\n\x13initial_order_price\x18\x05 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12O\n\x14\x65xecuted_order_price\x18\x06 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12M\n\x12total_order_amount\x18\x07 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12M\n\x12initial_commission\x18\x08 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12N\n\x13\x65xecuted_commission\x18\t \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12\x44\n\taci_value\x18\n \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12\x0c\n\x04\x66igi\x18\x0b \x01(\t\x12H\n\tdirection\x18\x0c \x01(\x0e\x32\x35.tinkoff.public.invest.api.contract.v1.OrderDirection\x12Q\n\x16initial_security_price\x18\r \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12\x44\n\norder_type\x18\x0e \x01(\x0e\x32\x30.tinkoff.public.invest.api.contract.v1.OrderType\x12\x0f\n\x07message\x18\x0f \x01(\t\x12P\n\x16initial_order_price_pt\x18\x10 \x01(\x0b\x32\x30.tinkoff.public.invest.api.contract.v1.Quotation\":\n\x12\x43\x61ncelOrderRequest\x12\x12\n\naccount_id\x18\x01 \x01(\t\x12\x10\n\x08order_id\x18\x02 \x01(\t\"?\n\x13\x43\x61ncelOrderResponse\x12(\n\x04time\x18\x01 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\"<\n\x14GetOrderStateRequest\x12\x12\n\naccount_id\x18\x01 \x01(\t\x12\x10\n\x08order_id\x18\x02 \x01(\t\"&\n\x10GetOrdersRequest\x12\x12\n\naccount_id\x18\x01 \x01(\t\"V\n\x11GetOrdersResponse\x12\x41\n\x06orders\x18\x01 \x03(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.OrderState\"\xd8\x08\n\nOrderState\x12\x10\n\x08order_id\x18\x01 \x01(\t\x12\x62\n\x17\x65xecution_report_status\x18\x02 \x01(\x0e\x32\x41.tinkoff.public.invest.api.contract.v1.OrderExecutionReportStatus\x12\x16\n\x0elots_requested\x18\x03 \x01(\x03\x12\x15\n\rlots_executed\x18\x04 \x01(\x03\x12N\n\x13initial_order_price\x18\x05 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12O\n\x14\x65xecuted_order_price\x18\x06 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12M\n\x12total_order_amount\x18\x07 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12Q\n\x16\x61verage_position_price\x18\x08 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12M\n\x12initial_commission\x18\t \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12N\n\x13\x65xecuted_commission\x18\n \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12\x0c\n\x04\x66igi\x18\x0b \x01(\t\x12H\n\tdirection\x18\x0c \x01(\x0e\x32\x35.tinkoff.public.invest.api.contract.v1.OrderDirection\x12Q\n\x16initial_security_price\x18\r \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12\x41\n\x06stages\x18\x0e \x03(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.OrderStage\x12M\n\x12service_commission\x18\x0f \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12\x10\n\x08\x63urrency\x18\x10 \x01(\t\x12\x44\n\norder_type\x18\x11 \x01(\x0e\x32\x30.tinkoff.public.invest.api.contract.v1.OrderType\x12.\n\norder_date\x18\x12 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\"r\n\nOrderStage\x12@\n\x05price\x18\x01 \x01(\x0b\x32\x31.tinkoff.public.invest.api.contract.v1.MoneyValue\x12\x10\n\x08quantity\x18\x02 \x01(\x03\x12\x10\n\x08trade_id\x18\x03 \x01(\t*d\n\x0eOrderDirection\x12\x1f\n\x1bORDER_DIRECTION_UNSPECIFIED\x10\x00\x12\x17\n\x13ORDER_DIRECTION_BUY\x10\x01\x12\x18\n\x14ORDER_DIRECTION_SELL\x10\x02*T\n\tOrderType\x12\x1a\n\x16ORDER_TYPE_UNSPECIFIED\x10\x00\x12\x14\n\x10ORDER_TYPE_LIMIT\x10\x01\x12\x15\n\x11ORDER_TYPE_MARKET\x10\x02*\x80\x02\n\x1aOrderExecutionReportStatus\x12\'\n#EXECUTION_REPORT_STATUS_UNSPECIFIED\x10\x00\x12 \n\x1c\x45XECUTION_REPORT_STATUS_FILL\x10\x01\x12$\n EXECUTION_REPORT_STATUS_REJECTED\x10\x02\x12%\n!EXECUTION_REPORT_STATUS_CANCELLED\x10\x03\x12\x1f\n\x1b\x45XECUTION_REPORT_STATUS_NEW\x10\x04\x12)\n%EXECUTION_REPORT_STATUS_PARTIALLYFILL\x10\x05\x32\xa1\x01\n\x13OrdersStreamService\x12\x89\x01\n\x0cTradesStream\x12:.tinkoff.public.invest.api.contract.v1.TradesStreamRequest\x1a;.tinkoff.public.invest.api.contract.v1.TradesStreamResponse0\x01\x32\x97\x04\n\rOrdersService\x12~\n\tPostOrder\x12\x37.tinkoff.public.invest.api.contract.v1.PostOrderRequest\x1a\x38.tinkoff.public.invest.api.contract.v1.PostOrderResponse\x12\x84\x01\n\x0b\x43\x61ncelOrder\x12\x39.tinkoff.public.invest.api.contract.v1.CancelOrderRequest\x1a:.tinkoff.public.invest.api.contract.v1.CancelOrderResponse\x12\x7f\n\rGetOrderState\x12;.tinkoff.public.invest.api.contract.v1.GetOrderStateRequest\x1a\x31.tinkoff.public.invest.api.contract.v1.OrderState\x12~\n\tGetOrders\x12\x37.tinkoff.public.invest.api.contract.v1.GetOrdersRequest\x1a\x38.tinkoff.public.invest.api.contract.v1.GetOrdersResponseBa\n\x1cru.tinkoff.piapi.contract.v1P\x01Z\x0c./;investapi\xa2\x02\x05TIAPI\xaa\x02\x14Tinkoff.InvestApi.V1\xca\x02\x11Tinkoff\\Invest\\V1b\x06proto3'
,
dependencies=[tinkoff_dot_invest_dot_grpc_dot_common__pb2.DESCRIPTOR,google_dot_protobuf_dot_timestamp__pb2.DESCRIPTOR,])
_ORDERDIRECTION = _descriptor.EnumDescriptor(
name='OrderDirection',
full_name='tinkoff.public.invest.api.contract.v1.OrderDirection',
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name='ORDER_DIRECTION_UNSPECIFIED', index=0, number=0,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='ORDER_DIRECTION_BUY', index=1, number=1,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='ORDER_DIRECTION_SELL', index=2, number=2,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
],
containing_type=None,
serialized_options=None,
serialized_start=3582,
serialized_end=3682,
)
_sym_db.RegisterEnumDescriptor(_ORDERDIRECTION)
OrderDirection = enum_type_wrapper.EnumTypeWrapper(_ORDERDIRECTION)
_ORDERTYPE = _descriptor.EnumDescriptor(
name='OrderType',
full_name='tinkoff.public.invest.api.contract.v1.OrderType',
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name='ORDER_TYPE_UNSPECIFIED', index=0, number=0,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='ORDER_TYPE_LIMIT', index=1, number=1,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='ORDER_TYPE_MARKET', index=2, number=2,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
],
containing_type=None,
serialized_options=None,
serialized_start=3684,
serialized_end=3768,
)
_sym_db.RegisterEnumDescriptor(_ORDERTYPE)
OrderType = enum_type_wrapper.EnumTypeWrapper(_ORDERTYPE)
_ORDEREXECUTIONREPORTSTATUS = _descriptor.EnumDescriptor(
name='OrderExecutionReportStatus',
full_name='tinkoff.public.invest.api.contract.v1.OrderExecutionReportStatus',
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name='EXECUTION_REPORT_STATUS_UNSPECIFIED', index=0, number=0,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='EXECUTION_REPORT_STATUS_FILL', index=1, number=1,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='EXECUTION_REPORT_STATUS_REJECTED', index=2, number=2,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='EXECUTION_REPORT_STATUS_CANCELLED', index=3, number=3,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='EXECUTION_REPORT_STATUS_NEW', index=4, number=4,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='EXECUTION_REPORT_STATUS_PARTIALLYFILL', index=5, number=5,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
],
containing_type=None,
serialized_options=None,
serialized_start=3771,
serialized_end=4027,
)
_sym_db.RegisterEnumDescriptor(_ORDEREXECUTIONREPORTSTATUS)
OrderExecutionReportStatus = enum_type_wrapper.EnumTypeWrapper(_ORDEREXECUTIONREPORTSTATUS)
ORDER_DIRECTION_UNSPECIFIED = 0
ORDER_DIRECTION_BUY = 1
ORDER_DIRECTION_SELL = 2
ORDER_TYPE_UNSPECIFIED = 0
ORDER_TYPE_LIMIT = 1
ORDER_TYPE_MARKET = 2
EXECUTION_REPORT_STATUS_UNSPECIFIED = 0
EXECUTION_REPORT_STATUS_FILL = 1
EXECUTION_REPORT_STATUS_REJECTED = 2
EXECUTION_REPORT_STATUS_CANCELLED = 3
EXECUTION_REPORT_STATUS_NEW = 4
EXECUTION_REPORT_STATUS_PARTIALLYFILL = 5
_TRADESSTREAMREQUEST = _descriptor.Descriptor(
name='TradesStreamRequest',
full_name='tinkoff.public.invest.api.contract.v1.TradesStreamRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=142,
serialized_end=163,
)
_TRADESSTREAMRESPONSE = _descriptor.Descriptor(
name='TradesStreamResponse',
full_name='tinkoff.public.invest.api.contract.v1.TradesStreamResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='order_trades', full_name='tinkoff.public.invest.api.contract.v1.TradesStreamResponse.order_trades', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='ping', full_name='tinkoff.public.invest.api.contract.v1.TradesStreamResponse.ping', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='payload', full_name='tinkoff.public.invest.api.contract.v1.TradesStreamResponse.payload',
index=0, containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[]),
],
serialized_start=166,
serialized_end=336,
)
_ORDERTRADES = _descriptor.Descriptor(
name='OrderTrades',
full_name='tinkoff.public.invest.api.contract.v1.OrderTrades',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='order_id', full_name='tinkoff.public.invest.api.contract.v1.OrderTrades.order_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='created_at', full_name='tinkoff.public.invest.api.contract.v1.OrderTrades.created_at', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='direction', full_name='tinkoff.public.invest.api.contract.v1.OrderTrades.direction', index=2,
number=3, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='figi', full_name='tinkoff.public.invest.api.contract.v1.OrderTrades.figi', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='trades', full_name='tinkoff.public.invest.api.contract.v1.OrderTrades.trades', index=4,
number=5, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='account_id', full_name='tinkoff.public.invest.api.contract.v1.OrderTrades.account_id', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=339,
serialized_end=593,
)
_ORDERTRADE = _descriptor.Descriptor(
name='OrderTrade',
full_name='tinkoff.public.invest.api.contract.v1.OrderTrade',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='date_time', full_name='tinkoff.public.invest.api.contract.v1.OrderTrade.date_time', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='price', full_name='tinkoff.public.invest.api.contract.v1.OrderTrade.price', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='quantity', full_name='tinkoff.public.invest.api.contract.v1.OrderTrade.quantity', index=2,
number=3, type=3, cpp_type=2, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=596,
serialized_end=738,
)
_POSTORDERREQUEST = _descriptor.Descriptor(
name='PostOrderRequest',
full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='figi', full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest.figi', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='quantity', full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest.quantity', index=1,
number=2, type=3, cpp_type=2, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='price', full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest.price', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='direction', full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest.direction', index=3,
number=4, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='account_id', full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest.account_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='order_type', full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest.order_type', index=5,
number=6, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='order_id', full_name='tinkoff.public.invest.api.contract.v1.PostOrderRequest.order_id', index=6,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=741,
serialized_end=1038,
)
_POSTORDERRESPONSE = _descriptor.Descriptor(
name='PostOrderResponse',
full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='order_id', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.order_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='execution_report_status', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.execution_report_status', index=1,
number=2, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='lots_requested', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.lots_requested', index=2,
number=3, type=3, cpp_type=2, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='lots_executed', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.lots_executed', index=3,
number=4, type=3, cpp_type=2, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='initial_order_price', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.initial_order_price', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='executed_order_price', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.executed_order_price', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='total_order_amount', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.total_order_amount', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='initial_commission', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.initial_commission', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='executed_commission', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.executed_commission', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='aci_value', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.aci_value', index=9,
number=10, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='figi', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.figi', index=10,
number=11, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='direction', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.direction', index=11,
number=12, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='initial_security_price', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.initial_security_price', index=12,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='order_type', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.order_type', index=13,
number=14, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='message', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.message', index=14,
number=15, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='initial_order_price_pt', full_name='tinkoff.public.invest.api.contract.v1.PostOrderResponse.initial_order_price_pt', index=15,
number=16, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1041,
serialized_end=2034,
)
_CANCELORDERREQUEST = _descriptor.Descriptor(
name='CancelOrderRequest',
full_name='tinkoff.public.invest.api.contract.v1.CancelOrderRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='account_id', full_name='tinkoff.public.invest.api.contract.v1.CancelOrderRequest.account_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='order_id', full_name='tinkoff.public.invest.api.contract.v1.CancelOrderRequest.order_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2036,
serialized_end=2094,
)
_CANCELORDERRESPONSE = _descriptor.Descriptor(
name='CancelOrderResponse',
full_name='tinkoff.public.invest.api.contract.v1.CancelOrderResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='time', full_name='tinkoff.public.invest.api.contract.v1.CancelOrderResponse.time', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2096,
serialized_end=2159,
)
_GETORDERSTATEREQUEST = _descriptor.Descriptor(
name='GetOrderStateRequest',
full_name='tinkoff.public.invest.api.contract.v1.GetOrderStateRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='account_id', full_name='tinkoff.public.invest.api.contract.v1.GetOrderStateRequest.account_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='order_id', full_name='tinkoff.public.invest.api.contract.v1.GetOrderStateRequest.order_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2161,
serialized_end=2221,
)
_GETORDERSREQUEST = _descriptor.Descriptor(
name='GetOrdersRequest',
full_name='tinkoff.public.invest.api.contract.v1.GetOrdersRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='account_id', full_name='tinkoff.public.invest.api.contract.v1.GetOrdersRequest.account_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2223,
serialized_end=2261,
)
_GETORDERSRESPONSE = _descriptor.Descriptor(
name='GetOrdersResponse',
full_name='tinkoff.public.invest.api.contract.v1.GetOrdersResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='orders', full_name='tinkoff.public.invest.api.contract.v1.GetOrdersResponse.orders', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2263,
serialized_end=2349,
)
_ORDERSTATE = _descriptor.Descriptor(
name='OrderState',
full_name='tinkoff.public.invest.api.contract.v1.OrderState',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='order_id', full_name='tinkoff.public.invest.api.contract.v1.OrderState.order_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='execution_report_status', full_name='tinkoff.public.invest.api.contract.v1.OrderState.execution_report_status', index=1,
number=2, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='lots_requested', full_name='tinkoff.public.invest.api.contract.v1.OrderState.lots_requested', index=2,
number=3, type=3, cpp_type=2, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='lots_executed', full_name='tinkoff.public.invest.api.contract.v1.OrderState.lots_executed', index=3,
number=4, type=3, cpp_type=2, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='initial_order_price', full_name='tinkoff.public.invest.api.contract.v1.OrderState.initial_order_price', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='executed_order_price', full_name='tinkoff.public.invest.api.contract.v1.OrderState.executed_order_price', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='total_order_amount', full_name='tinkoff.public.invest.api.contract.v1.OrderState.total_order_amount', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='average_position_price', full_name='tinkoff.public.invest.api.contract.v1.OrderState.average_position_price', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='initial_commission', full_name='tinkoff.public.invest.api.contract.v1.OrderState.initial_commission', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='executed_commission', full_name='tinkoff.public.invest.api.contract.v1.OrderState.executed_commission', index=9,
number=10, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='figi', full_name='tinkoff.public.invest.api.contract.v1.OrderState.figi', index=10,
number=11, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='direction', full_name='tinkoff.public.invest.api.contract.v1.OrderState.direction', index=11,
number=12, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='initial_security_price', full_name='tinkoff.public.invest.api.contract.v1.OrderState.initial_security_price', index=12,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='stages', full_name='tinkoff.public.invest.api.contract.v1.OrderState.stages', index=13,
number=14, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='service_commission', full_name='tinkoff.public.invest.api.contract.v1.OrderState.service_commission', index=14,
number=15, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='currency', full_name='tinkoff.public.invest.api.contract.v1.OrderState.currency', index=15,
number=16, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='order_type', full_name='tinkoff.public.invest.api.contract.v1.OrderState.order_type', index=16,
number=17, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='order_date', full_name='tinkoff.public.invest.api.contract.v1.OrderState.order_date', index=17,
number=18, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2352,
serialized_end=3464,
)
_ORDERSTAGE = _descriptor.Descriptor(
name='OrderStage',
full_name='tinkoff.public.invest.api.contract.v1.OrderStage',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='price', full_name='tinkoff.public.invest.api.contract.v1.OrderStage.price', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='quantity', full_name='tinkoff.public.invest.api.contract.v1.OrderStage.quantity', index=1,
number=2, type=3, cpp_type=2, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='trade_id', full_name='tinkoff.public.invest.api.contract.v1.OrderStage.trade_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3466,
serialized_end=3580,
)
_TRADESSTREAMRESPONSE.fields_by_name['order_trades'].message_type = _ORDERTRADES
_TRADESSTREAMRESPONSE.fields_by_name['ping'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._PING
_TRADESSTREAMRESPONSE.oneofs_by_name['payload'].fields.append(
_TRADESSTREAMRESPONSE.fields_by_name['order_trades'])
_TRADESSTREAMRESPONSE.fields_by_name['order_trades'].containing_oneof = _TRADESSTREAMRESPONSE.oneofs_by_name['payload']
_TRADESSTREAMRESPONSE.oneofs_by_name['payload'].fields.append(
_TRADESSTREAMRESPONSE.fields_by_name['ping'])
_TRADESSTREAMRESPONSE.fields_by_name['ping'].containing_oneof = _TRADESSTREAMRESPONSE.oneofs_by_name['payload']
_ORDERTRADES.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_ORDERTRADES.fields_by_name['direction'].enum_type = _ORDERDIRECTION
_ORDERTRADES.fields_by_name['trades'].message_type = _ORDERTRADE
_ORDERTRADE.fields_by_name['date_time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_ORDERTRADE.fields_by_name['price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._QUOTATION
_POSTORDERREQUEST.fields_by_name['price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._QUOTATION
_POSTORDERREQUEST.fields_by_name['direction'].enum_type = _ORDERDIRECTION
_POSTORDERREQUEST.fields_by_name['order_type'].enum_type = _ORDERTYPE
_POSTORDERRESPONSE.fields_by_name['execution_report_status'].enum_type = _ORDEREXECUTIONREPORTSTATUS
_POSTORDERRESPONSE.fields_by_name['initial_order_price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_POSTORDERRESPONSE.fields_by_name['executed_order_price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_POSTORDERRESPONSE.fields_by_name['total_order_amount'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_POSTORDERRESPONSE.fields_by_name['initial_commission'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_POSTORDERRESPONSE.fields_by_name['executed_commission'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_POSTORDERRESPONSE.fields_by_name['aci_value'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_POSTORDERRESPONSE.fields_by_name['direction'].enum_type = _ORDERDIRECTION
_POSTORDERRESPONSE.fields_by_name['initial_security_price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_POSTORDERRESPONSE.fields_by_name['order_type'].enum_type = _ORDERTYPE
_POSTORDERRESPONSE.fields_by_name['initial_order_price_pt'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._QUOTATION
_CANCELORDERRESPONSE.fields_by_name['time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_GETORDERSRESPONSE.fields_by_name['orders'].message_type = _ORDERSTATE
_ORDERSTATE.fields_by_name['execution_report_status'].enum_type = _ORDEREXECUTIONREPORTSTATUS
_ORDERSTATE.fields_by_name['initial_order_price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['executed_order_price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['total_order_amount'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['average_position_price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['initial_commission'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['executed_commission'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['direction'].enum_type = _ORDERDIRECTION
_ORDERSTATE.fields_by_name['initial_security_price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['stages'].message_type = _ORDERSTAGE
_ORDERSTATE.fields_by_name['service_commission'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
_ORDERSTATE.fields_by_name['order_type'].enum_type = _ORDERTYPE
_ORDERSTATE.fields_by_name['order_date'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_ORDERSTAGE.fields_by_name['price'].message_type = tinkoff_dot_invest_dot_grpc_dot_common__pb2._MONEYVALUE
DESCRIPTOR.message_types_by_name['TradesStreamRequest'] = _TRADESSTREAMREQUEST
DESCRIPTOR.message_types_by_name['TradesStreamResponse'] = _TRADESSTREAMRESPONSE
DESCRIPTOR.message_types_by_name['OrderTrades'] = _ORDERTRADES
DESCRIPTOR.message_types_by_name['OrderTrade'] = _ORDERTRADE
DESCRIPTOR.message_types_by_name['PostOrderRequest'] = _POSTORDERREQUEST
DESCRIPTOR.message_types_by_name['PostOrderResponse'] = _POSTORDERRESPONSE
DESCRIPTOR.message_types_by_name['CancelOrderRequest'] = _CANCELORDERREQUEST
DESCRIPTOR.message_types_by_name['CancelOrderResponse'] = _CANCELORDERRESPONSE
DESCRIPTOR.message_types_by_name['GetOrderStateRequest'] = _GETORDERSTATEREQUEST
DESCRIPTOR.message_types_by_name['GetOrdersRequest'] = _GETORDERSREQUEST
DESCRIPTOR.message_types_by_name['GetOrdersResponse'] = _GETORDERSRESPONSE
DESCRIPTOR.message_types_by_name['OrderState'] = _ORDERSTATE
DESCRIPTOR.message_types_by_name['OrderStage'] = _ORDERSTAGE
DESCRIPTOR.enum_types_by_name['OrderDirection'] = _ORDERDIRECTION
DESCRIPTOR.enum_types_by_name['OrderType'] = _ORDERTYPE
DESCRIPTOR.enum_types_by_name['OrderExecutionReportStatus'] = _ORDEREXECUTIONREPORTSTATUS
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
TradesStreamRequest = _reflection.GeneratedProtocolMessageType('TradesStreamRequest', (_message.Message,), {
'DESCRIPTOR' : _TRADESSTREAMREQUEST,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.TradesStreamRequest)
})
_sym_db.RegisterMessage(TradesStreamRequest)
TradesStreamResponse = _reflection.GeneratedProtocolMessageType('TradesStreamResponse', (_message.Message,), {
'DESCRIPTOR' : _TRADESSTREAMRESPONSE,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.TradesStreamResponse)
})
_sym_db.RegisterMessage(TradesStreamResponse)
OrderTrades = _reflection.GeneratedProtocolMessageType('OrderTrades', (_message.Message,), {
'DESCRIPTOR' : _ORDERTRADES,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.OrderTrades)
})
_sym_db.RegisterMessage(OrderTrades)
OrderTrade = _reflection.GeneratedProtocolMessageType('OrderTrade', (_message.Message,), {
'DESCRIPTOR' : _ORDERTRADE,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.OrderTrade)
})
_sym_db.RegisterMessage(OrderTrade)
PostOrderRequest = _reflection.GeneratedProtocolMessageType('PostOrderRequest', (_message.Message,), {
'DESCRIPTOR' : _POSTORDERREQUEST,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.PostOrderRequest)
})
_sym_db.RegisterMessage(PostOrderRequest)
PostOrderResponse = _reflection.GeneratedProtocolMessageType('PostOrderResponse', (_message.Message,), {
'DESCRIPTOR' : _POSTORDERRESPONSE,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.PostOrderResponse)
})
_sym_db.RegisterMessage(PostOrderResponse)
CancelOrderRequest = _reflection.GeneratedProtocolMessageType('CancelOrderRequest', (_message.Message,), {
'DESCRIPTOR' : _CANCELORDERREQUEST,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.CancelOrderRequest)
})
_sym_db.RegisterMessage(CancelOrderRequest)
CancelOrderResponse = _reflection.GeneratedProtocolMessageType('CancelOrderResponse', (_message.Message,), {
'DESCRIPTOR' : _CANCELORDERRESPONSE,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.CancelOrderResponse)
})
_sym_db.RegisterMessage(CancelOrderResponse)
GetOrderStateRequest = _reflection.GeneratedProtocolMessageType('GetOrderStateRequest', (_message.Message,), {
'DESCRIPTOR' : _GETORDERSTATEREQUEST,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.GetOrderStateRequest)
})
_sym_db.RegisterMessage(GetOrderStateRequest)
GetOrdersRequest = _reflection.GeneratedProtocolMessageType('GetOrdersRequest', (_message.Message,), {
'DESCRIPTOR' : _GETORDERSREQUEST,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.GetOrdersRequest)
})
_sym_db.RegisterMessage(GetOrdersRequest)
GetOrdersResponse = _reflection.GeneratedProtocolMessageType('GetOrdersResponse', (_message.Message,), {
'DESCRIPTOR' : _GETORDERSRESPONSE,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.GetOrdersResponse)
})
_sym_db.RegisterMessage(GetOrdersResponse)
OrderState = _reflection.GeneratedProtocolMessageType('OrderState', (_message.Message,), {
'DESCRIPTOR' : _ORDERSTATE,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.OrderState)
})
_sym_db.RegisterMessage(OrderState)
OrderStage = _reflection.GeneratedProtocolMessageType('OrderStage', (_message.Message,), {
'DESCRIPTOR' : _ORDERSTAGE,
'__module__' : 'tinkoff.invest.grpc.orders_pb2'
# @@protoc_insertion_point(class_scope:tinkoff.public.invest.api.contract.v1.OrderStage)
})
_sym_db.RegisterMessage(OrderStage)
DESCRIPTOR._options = None
_ORDERSSTREAMSERVICE = _descriptor.ServiceDescriptor(
name='OrdersStreamService',
full_name='tinkoff.public.invest.api.contract.v1.OrdersStreamService',
file=DESCRIPTOR,
index=0,
serialized_options=None,
create_key=_descriptor._internal_create_key,
serialized_start=4030,
serialized_end=4191,
methods=[
_descriptor.MethodDescriptor(
name='TradesStream',
full_name='tinkoff.public.invest.api.contract.v1.OrdersStreamService.TradesStream',
index=0,
containing_service=None,
input_type=_TRADESSTREAMREQUEST,
output_type=_TRADESSTREAMRESPONSE,
serialized_options=None,
create_key=_descriptor._internal_create_key,
),
])
_sym_db.RegisterServiceDescriptor(_ORDERSSTREAMSERVICE)
DESCRIPTOR.services_by_name['OrdersStreamService'] = _ORDERSSTREAMSERVICE
_ORDERSSERVICE = _descriptor.ServiceDescriptor(
name='OrdersService',
full_name='tinkoff.public.invest.api.contract.v1.OrdersService',
file=DESCRIPTOR,
index=1,
serialized_options=None,
create_key=_descriptor._internal_create_key,
serialized_start=4194,
serialized_end=4729,
methods=[
_descriptor.MethodDescriptor(
name='PostOrder',
full_name='tinkoff.public.invest.api.contract.v1.OrdersService.PostOrder',
index=0,
containing_service=None,
input_type=_POSTORDERREQUEST,
output_type=_POSTORDERRESPONSE,
serialized_options=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='CancelOrder',
full_name='tinkoff.public.invest.api.contract.v1.OrdersService.CancelOrder',
index=1,
containing_service=None,
input_type=_CANCELORDERREQUEST,
output_type=_CANCELORDERRESPONSE,
serialized_options=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='GetOrderState',
full_name='tinkoff.public.invest.api.contract.v1.OrdersService.GetOrderState',
index=2,
containing_service=None,
input_type=_GETORDERSTATEREQUEST,
output_type=_ORDERSTATE,
serialized_options=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='GetOrders',
full_name='tinkoff.public.invest.api.contract.v1.OrdersService.GetOrders',
index=3,
containing_service=None,
input_type=_GETORDERSREQUEST,
output_type=_GETORDERSRESPONSE,
serialized_options=None,
create_key=_descriptor._internal_create_key,
),
])
_sym_db.RegisterServiceDescriptor(_ORDERSSERVICE)
DESCRIPTOR.services_by_name['OrdersService'] = _ORDERSSERVICE
# @@protoc_insertion_point(module_scope)
| 51.366319
| 6,798
| 0.779126
| 7,567
| 59,174
| 5.764372
| 0.049822
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| 1,151
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| 0
| 0
|
0
| 8
|
8c4630fc85fddffad672cbb85d3e3303b631f46f
| 49
|
py
|
Python
|
recipes/recipes_emscripten/future/test_import_future.py
|
emscripten-forge/recipes
|
62cb3e146abc8945ac210f38e4e47c080698eae5
|
[
"MIT"
] | 1
|
2022-03-10T16:50:56.000Z
|
2022-03-10T16:50:56.000Z
|
recipes/recipes_emscripten/future/test_import_future.py
|
emscripten-forge/recipes
|
62cb3e146abc8945ac210f38e4e47c080698eae5
|
[
"MIT"
] | 9
|
2022-03-18T09:26:38.000Z
|
2022-03-29T09:21:51.000Z
|
recipes/recipes_emscripten/future/test_import_future.py
|
emscripten-forge/recipes
|
62cb3e146abc8945ac210f38e4e47c080698eae5
|
[
"MIT"
] | null | null | null |
def test_import_future():
import future
| 12.25
| 25
| 0.673469
| 6
| 49
| 5.166667
| 0.666667
| 0.774194
| 0
| 0
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| 0.265306
| 49
| 4
| 26
| 12.25
| 0.861111
| 0
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| 1
| 0.5
| true
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| 1.5
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| 1
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| null | 1
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| null | 0
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| 1
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| 1
| 0
| 1
| 0
|
0
| 8
|
8c477ee9e508168b7fdfad27e9932756e083549e
| 236
|
py
|
Python
|
Server/Python/src/dbs/dao/MySQL/ProcessedDataset/GetID.py
|
vkuznet/DBS
|
14df8bbe8ee8f874fe423399b18afef911fe78c7
|
[
"Apache-2.0"
] | 8
|
2015-08-14T04:01:32.000Z
|
2021-06-03T00:56:42.000Z
|
Server/Python/src/dbs/dao/MySQL/ProcessedDataset/GetID.py
|
yuyiguo/DBS
|
14df8bbe8ee8f874fe423399b18afef911fe78c7
|
[
"Apache-2.0"
] | 162
|
2015-01-07T21:34:47.000Z
|
2021-10-13T09:42:41.000Z
|
Server/Python/src/dbs/dao/MySQL/ProcessedDataset/GetID.py
|
yuyiguo/DBS
|
14df8bbe8ee8f874fe423399b18afef911fe78c7
|
[
"Apache-2.0"
] | 16
|
2015-01-22T15:27:29.000Z
|
2021-04-28T09:23:28.000Z
|
#!/usr/bin/env python
"""
This module provides ProcessedDataset.GetID data access object.
"""
from dbs.dao.Oracle.ProcessedDataset.GetID import GetID as OraProcessedDatasetGetID
class GetID(OraProcessedDatasetGetID):
pass
| 23.6
| 83
| 0.771186
| 26
| 236
| 7
| 0.807692
| 0.230769
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| 0.144068
| 236
| 9
| 84
| 26.222222
| 0.90099
| 0.355932
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 7
|
4fcc20a7807a2a3dadd3ba701ae5dd8c7d7c9e33
| 47,556
|
py
|
Python
|
hunter_douglas/pm_utils.py
|
thispl/hunter_douglas
|
40ac85e9fba607ec8a9aa6a472b486f8b24f8600
|
[
"MIT"
] | null | null | null |
hunter_douglas/pm_utils.py
|
thispl/hunter_douglas
|
40ac85e9fba607ec8a9aa6a472b486f8b24f8600
|
[
"MIT"
] | null | null | null |
hunter_douglas/pm_utils.py
|
thispl/hunter_douglas
|
40ac85e9fba607ec8a9aa6a472b486f8b24f8600
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Copyright (c) 2017, VHRS and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe,os,base64
import requests
import datetime
import json,calendar
from datetime import datetime,timedelta,date,time
import datetime as dt
from frappe.utils import cint,today,flt,date_diff,add_days,add_months,date_diff,getdate,formatdate,cint,cstr
from frappe.desk.notifications import delete_notification_count_for
from frappe import _
@frappe.whitelist()
def update_pm_manager(doc, method):
if doc.manager:
pmm = frappe.db.get_value("Performance Management Manager", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management Manager", pmm)
else:
epmm = frappe.new_doc("Performance Management Manager")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"manager": c.appraisee_weightage
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"manager": c.self_rating,
"weightage": c.weightage,
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"weightage": c.weightage,
})
epmm.save(ignore_permissions=True)
else:
pmm = frappe.db.get_value("Performance Management HOD", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management HOD", pmm)
else:
epmm = frappe.new_doc("Performance Management HOD")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"potential": "-",
"performance": "-",
"promotion": "-",
"any_other_observations": "-",
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks,
"appraiser_remarks": "-"
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"manager": "-",
"hod": c.appraisee_weightage
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"weightage": c.weightage,
"manager": "-",
"hod": c.self_rating
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weightage": c.weightage,
"self_rating": c.self_rating
})
epmm.set('employee_feedback', [])
# child5 = doc.employee_feedback
for c in range(5):
epmm.append("employee_feedback",{
"appraisee_remarks": "-"
})
epmm.save(ignore_permissions=True)
@frappe.whitelist()
def update_pm_hod(doc, method):
if doc.manager == frappe.session.user:
pmm = frappe.db.get_value("Performance Management HOD", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management HOD", pmm)
else:
epmm = frappe.new_doc("Performance Management HOD")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"potential": doc.potential,
"performance": doc.performance,
"promotion": doc.promotion,
"any_other_observations": doc.any_other_observations,
"potential_hod": doc.potential,
"performance_hod": doc.performance,
"promotion_hod": doc.promotion,
"any_other_observations_hod": doc.any_other_observations,
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks,
"appraiser_remarks": c.appraiser_remarks
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"manager": c.manager,
"hod": c.manager
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"weightage": c.weightage,
"manager": c.manager,
"hod": c.manager
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weightage": c.weightage,
"self_rating": c.self_rating
})
epmm.set('employee_feedback', [])
child5 = doc.employee_feedback
for c in child5:
epmm.append("employee_feedback",{
"appraisee_remarks": c.appraisee_remarks
})
epmm.save(ignore_permissions=True)
@frappe.whitelist()
def update_pm_reviewer(doc, method):
if doc.hod:
pmm = frappe.db.get_value("Performance Management Reviewer", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management Reviewer", pmm)
else:
epmm = frappe.new_doc("Performance Management Reviewer")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"potential": doc.potential,
"performance": doc.performance,
"promotion": doc.promotion,
"any_other_observations": doc.any_other_observations,
"potential_hod": doc.potential_hod,
"performance_hod": doc.performance_hod,
"promotion_hod": doc.promotion_hod,
"any_other_observations_hod": doc.any_other_observations_hod,
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks,
"appraiser_remarks": c.appraiser_remarks
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"appraiser_rating": c.manager,
"hod": c.hod,
"reviewer": c.hod
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weightage": c.weightage,
"self_rating": c.self_rating,
"appraiser_rating_r": c.manager,
"hod": c.hod,
"reviewer": c.hod
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weighted_score": c.weightage,
})
epmm.set('employee_feedback', [])
child5 = doc.employee_feedback
for c in child5:
epmm.append("employee_feedback",{
"appraisee_remarks": c.appraisee_remarks,
"hod": c.hod
})
pm = frappe.db.exists("Performance Management Reviewer",{"employee_code": doc.employee_code,"appraisal_year":(cint(doc.appraisal_year) - 1)})
if pm:
employeedoc = frappe.get_doc("Performance Management Reviewer",pm)
if employeedoc:
epmm.set('management_pm_details', [])
child6 = employeedoc.management_pm_details
for c in child6:
epmm.append("management_pm_details",{
"year": c.year,
"hike": c.hike
})
epmm.save(ignore_permissions=True)
@frappe.whitelist()
def update_self_to_manager():
self_list = ["PMS0177"]
for s in self_list:
doc = frappe.get_doc("Performance Management Self", s)
# if doc.manager:
pmm = frappe.db.get_value("Performance Management Manager", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management Manager", pmm)
else:
epmm = frappe.new_doc("Performance Management Manager")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"manager": c.appraisee_weightage
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"manager": c.self_rating,
"weightage": c.weightage,
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"weightage": c.weightage,
})
epmm.save(ignore_permissions=True)
else:
pmm = frappe.db.get_value("Performance Management HOD", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management HOD", pmm)
else:
epmm = frappe.new_doc("Performance Management HOD")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"potential": "-",
"performance": "-",
"promotion": "-",
"any_other_observations": "-",
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks,
"appraiser_remarks": "-"
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"manager": "-",
"hod": c.appraisee_weightage
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"weightage": c.weightage,
"manager": "-",
"hod": c.self_rating
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weightage": c.weightage,
"self_rating": c.self_rating
})
epmm.set('employee_feedback', [])
# child5 = doc.employee_feedback
for c in range(5):
epmm.append("employee_feedback",{
"appraisee_remarks": "-"
})
epmm.save(ignore_permissions=True)
@frappe.whitelist()
def update_hod():
self_list = ["PMS0210"]
for s in self_list:
doc = frappe.get_doc("Performance Management Self", s)
# if doc.docstatus == 1 and doc.manager:
# print('HI')
pmm = frappe.db.get_value("Performance Management HOD", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management HOD", pmm)
else:
epmm = frappe.new_doc("Performance Management HOD")
epmm.update({
"employee_code": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"potential": "-",
"performance": "-",
"promotion": "-",
"any_other_observations": "-",
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks,
"appraiser_remarks": "-"
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"manager": "-",
"hod": c.appraisee_weightage
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"weightage": c.weightage,
"manager": "-",
"hod": c.self_rating
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weightage": c.weightage,
"self_rating": c.self_rating
})
epmm.set('employee_feedback', [])
# child5 = doc.employee_feedback
for c in range(5):
epmm.append("employee_feedback",{
"appraisee_remarks": "-"
})
epmm.save(ignore_permissions=True)
frappe.db.commit()
@frappe.whitelist()
def update_pm_calibration(doc,method):
if doc.name:
pmc = frappe.db.get_value("Performance Management Calibration", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmc:
epmc = frappe.get_doc("Performance Management Calibration", pmc)
else:
epmc = frappe.new_doc("Performance Management Calibration")
epmc.update({
"competency_assessment": doc.average_score_attained,
"goal_setting_2018": doc.average_score,
"potential": doc.potential_reviewer,
"performance": doc.performance_reviewer,
"promotion": doc.promotion_reviewer,
"any_other_observations": doc.any_other_observations_reviewer,
"increment": doc.increment,
"remarks": doc.remarks,
"salary_correction": doc.salary_correction,
})
epmc.save(ignore_permissions=True)
epmc.db.commit()
# pmm = frappe.db.get_value("Individual Performance", {
# "employee_code": doc.employee_code})
# if pmm:
# epmm = frappe.get_doc("Individual Performance", pmm)
# else:
# epmm = frappe.new_doc("Individual Performance")
# epmm.update({
# "employee_code": doc.employee_code,
# "employee_code1": doc.employee_code,
# "cost_code": doc.cost_code,
# "department": doc.department,
# "year_of_last_promotion": doc.year_of_last_promotion,
# "business_unit": doc.business_unit,
# "grade": doc.grade,
# "employee_name": doc.employee_name,
# "manager": doc.manager,
# "hod": doc.hod,
# "reviewer": doc.reviewer,
# "designation": doc.designation,
# "date_of_joining": doc.date_of_joining,
# "appraisal_year": doc.appraisal_year,
# "location": doc.location,
# "no_of_promotion": doc.no_of_promotion,
# "small_text_12": doc.small_text_12,
# "small_text_14": doc.small_text_14,
# "small_text_16": doc.small_text_16,
# "small_text_18": doc.small_text_18,
# "potential": doc.potential,
# "performance": doc.performance,
# "promotion": doc.promotion,
# "any_other_observations": doc.any_other_observations,
# "potential_hod": doc.potential_hod,
# "performance_hod": doc.performance_hod,
# "promotion_hod": doc.promotion_hod,
# "any_other_observations_hod": doc.any_other_observations_hod,
# "required__job_knowledge": doc.required__job_knowledge,
# "training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
# "required_skills": doc.required_skills,
# "training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
# })
# epmm.set('sales_target', [])
# child = doc.sales_target
# for c in child:
# epmm.append("sales_target",{
# "year": c.year,
# "actual_targets": c.actual_targets,
# "attained_targets": c.attained_targets
# })
# # epmm.set('job_analysis', [])
# # child1 = doc.job_analysis
# # for c in child1:
# # epmm.append("job_analysis",{
# # "appraisee_remarks": c.appraisee_remarks,
# # "appraiser_remarks": c.appraiser_remarks
# # })
# epmm.set('competency_assessment1', [])
# child2 = doc.competency_assessment1
# for c in child2:
# epmm.append("competency_assessment1",{
# "competency": c.competency,
# "weightage": c.weightage,
# "appraisee_weightage": c.appraisee_weightage,
# "reviewer": c.reviewer
# })
# epmm.set('key_result_area', [])
# child3 = doc.key_result_area
# for c in child3:
# epmm.append("key_result_area",{
# "goal_setting_for_current_year": c.goal_setting_for_current_year,
# "performance_measure": c.performance_measure,
# "weightage_w_100": c.weightage_w_100,
# "weightage": c.weightage,
# "self_rating": c.self_rating,
# "reviewer": c.reviewer
# })
# epmm.set('key_results_area', [])
# child4 = doc.key_results_area
# for c in child4:
# epmm.append("key_results_area",{
# "goal_setting_for_last_year": c.goal_setting_for_last_year,
# "performance_measure": c.performance_measure,
# "weightage_w_100": c.weightage_w_100,
# })
# epmm.set('employee_feedback', [])
# child5 = doc.employee_feedback
# for c in child5:
# epmm.append("employee_feedback",{
# "appraisee_remarks": c.appraisee_remarks,
# "hod": c.hod,
# "appraiser_remarks": c.appraiser_remarks
# })
# epmm.save(ignore_permissions=True)
@frappe.whitelist()
def manually_update_pm_calibration_previous_increment():
current_year = '2019'
previous_year = '2018'
docs = frappe.db.get_list("Performance Management Calibration",{"appraisal_year":current_year})
for d in docs:
pmc_cy = frappe.get_doc("Performance Management Calibration",d.name)
if pmc_cy.name:
previous_year_pmc = frappe.db.get_value("Performance Management Calibration", {
"employee_code": pmc_cy.employee_code,"appraisal_year":previous_year})
if previous_year_pmc:
pmc_ly = frappe.get_doc("Performance Management Calibration", previous_year_pmc)
pmc_cy.update({
"basic_ly": pmc_ly.basic,
"hra_ly": pmc_ly.hra,
"special_allowance_ly": pmc_ly.special_allowance,
"transport_ly": pmc_ly.transport,
"education_ly": pmc_ly.education,
"food_allowance_ly": pmc_ly.food_allowance,
"relocation_allowance_ly": pmc_ly.relocation_allowance,
"washing_allowance_ly": pmc_ly.washing_allowance,
"site_allowance_ly": pmc_ly.site_allowance,
"car_allowance_ly": pmc_ly.car_allowance,
"pf_contribution_ly": pmc_ly.pf_contribution,
"esi_ly": pmc_ly.esi,
"monthly_gross_ly": pmc_ly.new_monthly_gross,
"driver_salary_ly": pmc_ly.driver_salary,
"car_emi_ly": pmc_ly.car_emi,
"lta_ly": pmc_ly.lta,
"gratuity_ly": pmc_ly.gratuity,
"exgratia_ly":pmc_ly.exgratia,
"sales_project_support_incentive_ly": pmc_ly.sales_project_support_incentive,
"performance_incentive_ly": pmc_ly.performance_incentive,
"annual_ctc_ly": pmc_ly.new_annual_ctc
})
pmc_cy.save(ignore_permissions=True)
@frappe.whitelist()
def manually_update_pm_calibration():
# if frappe.db.exists("Performance Management Reviewer",{"docstatus": 1}):
docs = frappe.db.get_list("Performance Management Reviewer",{"docstatus": 1,"appraisal_year":"2019"})
for d in docs:
doc = frappe.get_doc("Performance Management Reviewer",d.name)
if doc.name:
pmc = frappe.db.get_value("Performance Management Calibration", {
"employee_code": doc.employee_code1,"appraisal_year":"2019"})
if pmc:
epmc = frappe.get_doc("Performance Management Calibration", pmc)
else:
epmc = frappe.new_doc("Performance Management Calibration")
epmc.update({
"employee_code": doc.employee_code1,
"cost_code": doc.cost_code,
"department": doc.department,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"pm_year": datetime.now().year,
"no_of_promotion": doc.no_of_promotion,
"competency_assessment": doc.average_score_attained,
"goal_setting_2018": doc.average_score,
"potential": doc.potential_reviewer,
"performance": doc.performance_reviewer,
"promotion": doc.promotion_reviewer,
"any_other_observations": doc.any_other_observations_reviewer,
"increment": doc.increment,
"remarks": doc.remarks,
"salary_correction": doc.salary_correction,
"r_designation": doc.designation,
"r_location": doc.location,
"r_grade": doc.grade
})
epmc.set('management_pm_details', [])
child = doc.management_pm_details
for c in child:
epmc.append("management_pm_details",{
"year": c.year,
"hike": c.hike
})
epmc.save(ignore_permissions=True)
# epmc.db.commit()
pmm = frappe.db.get_value("Individual Performance", {
"employee_code": doc.employee_code,"appraisal_year":"2019"})
if pmm:
epmm = frappe.get_doc("Individual Performance", pmm)
else:
epmm = frappe.new_doc("Individual Performance")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"potential": doc.potential,
"performance": doc.performance,
"promotion": doc.promotion,
"any_other_observations": doc.any_other_observations,
"potential_hod": doc.potential_hod,
"performance_hod": doc.performance_hod,
"promotion_hod": doc.promotion_hod,
"any_other_observations_hod": doc.any_other_observations_hod,
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"pm_year": datetime.now().year,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
# epmm.set('job_analysis', [])
# child1 = doc.job_analysis
# for c in child1:
# epmm.append("job_analysis",{
# "appraisee_remarks": c.appraisee_remarks,
# "appraiser_remarks": c.appraiser_remarks
# })
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"reviewer": c.reviewer
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weightage": c.weightage,
"self_rating": c.self_rating,
"reviewer": c.reviewer
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
})
epmm.set('employee_feedback', [])
child5 = doc.employee_feedback
for c in child5:
epmm.append("employee_feedback",{
"appraisee_remarks": c.appraisee_remarks,
"hod": c.hod,
"appraiser_remarks": c.appraiser_remarks
})
epmm.save(ignore_permissions=True)
@frappe.whitelist()
def update_pm_hod_doc():
manager_list = ["PMM0133"]
for m in manager_list:
doc = frappe.get_doc("Performance Management Manager", m)
# doc = frappe.get_doc("Performance Management Manager", {"employee_code": "1204"})
pmm = frappe.db.get_value("Performance Management HOD", {
"employee_code": doc.employee_code,"appraisal_year":doc.appraisal_year})
if pmm:
epmm = frappe.get_doc("Performance Management HOD", pmm)
else:
epmm = frappe.new_doc("Performance Management HOD")
epmm.update({
"employee_code": doc.employee_code,
"employee_code1": doc.employee_code,
"cost_code": doc.cost_code,
"department": doc.department,
"year_of_last_promotion": doc.year_of_last_promotion,
"business_unit": doc.business_unit,
"grade": doc.grade,
"employee_name": doc.employee_name,
"manager": doc.manager,
"hod": doc.hod,
"reviewer": doc.reviewer,
"designation": doc.designation,
"date_of_joining": doc.date_of_joining,
"appraisal_year": doc.appraisal_year,
"location": doc.location,
"no_of_promotion": doc.no_of_promotion,
"small_text_12": doc.small_text_12,
"small_text_14": doc.small_text_14,
"small_text_16": doc.small_text_16,
"small_text_18": doc.small_text_18,
"potential": doc.potential,
"performance": doc.performance,
"promotion": doc.promotion,
"any_other_observations": doc.any_other_observations,
"required__job_knowledge": doc.required__job_knowledge,
"training_required_to_enhance_job_knowledge": doc.training_required_to_enhance_job_knowledge,
"required_skills": doc.required_skills,
"training_required__to_enhance_skills_competencies": doc.training_required__to_enhance_skills_competencies
})
epmm.set('sales_target', [])
child = doc.sales_target
for c in child:
epmm.append("sales_target",{
"year": c.year,
"actual_targets": c.actual_targets,
"attained_targets": c.attained_targets
})
epmm.set('job_analysis', [])
child1 = doc.job_analysis
for c in child1:
epmm.append("job_analysis",{
"appraisee_remarks": c.appraisee_remarks,
"appraiser_remarks": c.appraiser_remarks
})
epmm.set('competency_assessment1', [])
child2 = doc.competency_assessment1
for c in child2:
epmm.append("competency_assessment1",{
"competency": c.competency,
"weightage": c.weightage,
"appraisee_weightage": c.appraisee_weightage,
"manager": c.manager,
"hod": c.manager
})
epmm.set('key_result_area', [])
child3 = doc.key_result_area
for c in child3:
epmm.append("key_result_area",{
"goal_setting_for_current_year": c.goal_setting_for_current_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"self_rating": c.self_rating,
"weightage": c.weightage,
"manager": c.manager,
"hod": c.manager
})
epmm.set('key_results_area', [])
child4 = doc.key_results_area
for c in child4:
epmm.append("key_results_area",{
"goal_setting_for_last_year": c.goal_setting_for_last_year,
"performance_measure": c.performance_measure,
"weightage_w_100": c.weightage_w_100,
"weightage": c.weightage,
"self_rating": c.self_rating
})
epmm.set('employee_feedback', [])
child5 = doc.employee_feedback
for c in child5:
epmm.append("employee_feedback",{
"appraisee_remarks": c.appraisee_remarks
})
epmm.save(ignore_permissions=True)
| 44.403361
| 149
| 0.570927
| 4,883
| 47,556
| 5.197215
| 0.042802
| 0.028371
| 0.014186
| 0.039404
| 0.928639
| 0.920522
| 0.909173
| 0.900071
| 0.895776
| 0.893687
| 0
| 0.014777
| 0.32549
| 47,556
| 1,071
| 150
| 44.403361
| 0.776382
| 0.084868
| 0
| 0.899787
| 0
| 0
| 0.244735
| 0.059859
| 0
| 0
| 0
| 0
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| 1
| 0.009595
| false
| 0
| 0.010661
| 0
| 0.020256
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
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|
0
| 7
|
4fd9e5b2aeb88a8117dc4d087072e1af258cd04c
| 6,504
|
py
|
Python
|
TSA/tests/test_AGNES.py
|
Boyne272/Thin_Section_Analsis
|
91023267f96f709d62fa44d10ff5636d263e346c
|
[
"MIT"
] | 2
|
2020-01-15T09:02:04.000Z
|
2020-01-15T09:02:30.000Z
|
TSA/tests/test_AGNES.py
|
msc-acse/acse-9-independent-research-project-Boyne272
|
b6f52a189dbb1cfb53325793966e32ee39155e9e
|
[
"MIT"
] | null | null | null |
TSA/tests/test_AGNES.py
|
msc-acse/acse-9-independent-research-project-Boyne272
|
b6f52a189dbb1cfb53325793966e32ee39155e9e
|
[
"MIT"
] | 3
|
2019-08-27T12:44:14.000Z
|
2020-01-15T09:02:41.000Z
|
import unittest
import numpy as np
import matplotlib.pyplot as plt
from TSA.merging import AGNES
class Test_AGNES(unittest.TestCase):
def test_2d_dummy(self):
"Generate 2d dummy data and test the whole functionality"
# generate dummy data with 6 regions
np.random.seed(10)
features = np.random.normal(size=[500, 2])
features[50:, :] += 4
features[100:, :] += 4
features[150:, 0] += 4
features[250:300, 1] += 10
features[350:400, 0] += 10
# create object
obj = AGNES(features)
# check obj initalised correctly
assert (obj._dists > 0).all(), "can not be negaive distances"
exp_size = 0.5 * (obj._dists.size - obj._dists.shape[0])
assert np.isfinite(obj._dists).sum() == exp_size, "distances should be lower traingular"
# iterate
obj.iterate()
# check obj post iteration is correct
assert len(obj.merge_log) == len(set(obj.merge_log)), \
'no pair should be joined more than once'
assert np.isinf(obj._dists).all(), \
'every pair should be infinitely far apart once finished'
# check the plot functions run
obj.cluster_distance_plot('all')
# check the grouping is as expected
n_clusters = obj.cluster_by_derivative(n_std=3.).max() + 1
assert n_clusters == 6, 'derivative clustering not as expected'
# check grouping by distance works too
# (using a distance just under what is stated aboive)
n_clusters = obj.cluster_by_distance(cutoff_dist=9.41).max() + 1
assert n_clusters == 6, 'cluster_by_distance clustering not as expected'
# check grouping by distance works too
# (using a distance just under what is stated aboive)
n_clusters = obj.cluster_by_index(500-6).max() + 1
assert n_clusters == 6, 'index clustering not as expected'
# prevent figure build up
plt.close('all')
def test_2d_dummy_plus_outlier(self):
"""
Generate 2d dummy data and test the whole functionality with
an additional outlier
"""
# generate dummy data with 6 regions
np.random.seed(10)
features = np.random.normal(size=[500, 2])
features[50:, :] += 4
features[100:, :] += 4
features[150:, 0] += 4
features[250:300, 1] += 10
features[350:400, 0] += 10
features[-1, -1] += 20
# create object
obj = AGNES(features)
# check obj initalised correctly
assert (obj._dists > 0).all(), "can not be negaive distances"
exp_size = 0.5 * (obj._dists.size - obj._dists.shape[0])
assert np.isfinite(obj._dists).sum() == exp_size, "distances should be lower traingular"
# iterate
obj.iterate()
# check obj post iteration is correct
assert len(obj.merge_log) == len(set(obj.merge_log)), \
'no pair should be joined more than once'
assert np.isinf(obj._dists).all(), \
'every pair should be infinitely far apart once finished'
# check the plot functions run
obj.cluster_distance_plot('all')
# check the grouping is as expected
n_clusters = obj.cluster_by_derivative().max() + 1
assert n_clusters == 7, 'clustering not as expected'
# check grouping by distance works too
# (using a distance just under what is stated aboive)
n_clusters = obj.cluster_by_distance(cutoff_dist=9.41).max() + 1
assert n_clusters == 7, 'cluster_by_distance clustering not as expected'
# check grouping by distance works too
# (using a distance just under what is stated aboive)
n_clusters = obj.cluster_by_index(500-7).max() + 1
assert n_clusters == 7, 'index clustering not as expected'
# prevent figure build up
plt.close('all')
def test_higher_dimensions(self):
"Exact same as test_2d_dummy_plus_outlier but on higer dimensional data"
# generate dummy data with 6 groupings
np.random.seed(10)
features = np.random.normal(size=[500, 5])
features[50:, :] += 4
features[100:, :] += 4
features[150:, 0] += 4
features[250:300, 1] += 10
features[350:400, 0] += 10
features[-1, -1] += 20
# create object
obj = AGNES(features)
# check obj initalised correctly
assert (obj._dists > 0).all(), "can not be negaive distances"
exp_size = 0.5 * (obj._dists.size - obj._dists.shape[0])
actual_size = np.isfinite(obj._dists).sum()
assert actual_size == exp_size, "distances should be lower traingular"
# iterate
obj.iterate()
# check obj post iteration is correct
assert len(obj.merge_log) == len(set(obj.merge_log)), \
'no pair should be joined more than once'
assert np.isinf(obj._dists).all(), \
'every pair should be infinitely far apart'
# check the plot functions run
obj.cluster_distance_plot('all')
# check the grouping is as expected
n_clusters = obj.cluster_by_derivative().max() + 1
assert n_clusters == 7, 'clustering not as expected'
# check grouping by distance works too
# (using a distance just under what is stated aboive)
n_clusters = obj.cluster_by_distance(cutoff_dist=10.4).max() + 1
assert n_clusters == 7, 'cluster_by_distance clustering not as expected'
# check grouping by distance works too
# (using a distance just under what is stated aboive)
n_clusters = obj.cluster_by_index(500-7).max() + 1
assert n_clusters == 7, 'index clustering not as expected'
# prevent figure build up
plt.close('all')
if __name__ == '__main__':
# run all the tests if this is script is run independently
tmp = Test_AGNES()
tmp.test_2d_dummy()
tmp.test_2d_dummy_plus_outlier()
tmp.test_higher_dimensions()
print('all tests passed')
# # unittest.main does not work in google colab, but should work elsewhere
# unittest.main()
| 36.745763
| 97
| 0.59056
| 835
| 6,504
| 4.467066
| 0.185629
| 0.043432
| 0.028954
| 0.045845
| 0.877748
| 0.849598
| 0.838606
| 0.838606
| 0.838606
| 0.838606
| 0
| 0.040027
| 0.316267
| 6,504
| 177
| 98
| 36.745763
| 0.798741
| 0.235547
| 0
| 0.714286
| 1
| 0
| 0.195755
| 0.005358
| 0
| 0
| 0
| 0
| 0.230769
| 1
| 0.032967
| false
| 0.010989
| 0.043956
| 0
| 0.087912
| 0.010989
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
8cb2c5104b81e4cb414ecc7a76afd6c494dabaea
| 1,271
|
py
|
Python
|
tests/test_rotate.py
|
tlambert-forks/pyclesperanto_prototype
|
aea964a75e691f19b7753040daa8b276d57ccf36
|
[
"BSD-3-Clause"
] | 64
|
2020-03-18T12:11:22.000Z
|
2022-03-31T08:19:18.000Z
|
tests/test_rotate.py
|
haesleinhuepf/pyclesperanto_prototype
|
65bc3035d3b2b61a2722c93b95bae310bfbd190e
|
[
"BSD-3-Clause"
] | 148
|
2020-05-14T06:14:11.000Z
|
2022-03-26T15:02:31.000Z
|
tests/test_rotate.py
|
haesleinhuepf/pyclesperanto_prototype
|
65bc3035d3b2b61a2722c93b95bae310bfbd190e
|
[
"BSD-3-Clause"
] | 16
|
2020-05-31T00:53:44.000Z
|
2022-03-23T13:20:57.000Z
|
import pyclesperanto_prototype as cle
import numpy as np
def test_affine_transform_rotate():
source = cle.push(np.asarray([[
[0, 0, 0, 1, 1],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
]]))
reference = cle.push(np.asarray([[
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 1, 1, 0],
[0, 0, 0, 0, 0],
]]))
result = cle.rotate(source, angle_around_z_in_degrees=45.0, rotate_around_center=False)
a = cle.pull(result)
b = cle.pull(reference)
print(a)
print(b)
assert (np.array_equal(a, b))
def test_affine_transform_rotate_around_center():
source = cle.push(np.asarray([[
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 1, 1],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
]]))
reference = cle.push(np.asarray([[
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 1, 0, 0],
[0, 0, 1, 0, 0],
]]))
result = cle.rotate(source, angle_around_z_in_degrees=90.0, rotate_around_center=True)
a = cle.pull(result)
b = cle.pull(reference)
print(a)
print(b)
assert (np.array_equal(a, b))
| 21.913793
| 91
| 0.467349
| 207
| 1,271
| 2.758454
| 0.173913
| 0.283713
| 0.37303
| 0.434326
| 0.805604
| 0.707531
| 0.707531
| 0.707531
| 0.658494
| 0.658494
| 0
| 0.126492
| 0.340677
| 1,271
| 57
| 92
| 22.298246
| 0.554893
| 0
| 0
| 0.840909
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.045455
| 1
| 0.045455
| false
| 0
| 0.045455
| 0
| 0.090909
| 0.090909
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
5066262dbeccf63b8dbf5f5a29e26a421aeb172f
| 5,519
|
py
|
Python
|
face_storage/upload.py
|
Face-Recognition-Learning-Group/face_service
|
c23a8519cbf0f0f6297d7b43a5db8077438c58dd
|
[
"Apache-2.0"
] | 6
|
2021-05-19T06:48:35.000Z
|
2021-11-09T11:52:11.000Z
|
face_storage/upload.py
|
VSOURCE-Platform/VSOURCE_FACE_PLATFORM
|
c23a8519cbf0f0f6297d7b43a5db8077438c58dd
|
[
"Apache-2.0"
] | 1
|
2021-05-09T08:29:39.000Z
|
2021-05-09T08:29:39.000Z
|
face_storage/upload.py
|
VSOURCE-Platform/VSOURCE_FACE_PLATFORM
|
c23a8519cbf0f0f6297d7b43a5db8077438c58dd
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
# @Author : Ecohnoch(xcy)
# @File : upload.py
# @Function : TODO
from werkzeug.utils import secure_filename
from flask import Blueprint
from app import app
import traceback
import flask
import time
import os
upload_api = Blueprint('upload', __name__)
@upload_api.route('/face_upload', methods=['POST'])
def face_upload():
def allowed_file(filename):
# 获取文件扩展名，以'.'为右分割然后取第二个值
return '.' in filename and \
filename.rsplit('.', 1)[1].lower() in ['jpg', 'png']
if 'file' not in flask.request.files:
return flask.jsonify({'status': 500, 'err_msg': '[Face_Storage] No file in files'})
file = flask.request.files['file']
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
uploader_folder = app.config['UPLOAD_FOLDER']
save_dir = os.path.join(uploader_folder, 'face_recognition')
if not os.path.exists(save_dir):
os.makedirs(save_dir)
timestamp = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '-' + str(time.time() - int(time.time()))[2:5]
filepath = os.path.join(timestamp, filename)
if not os.path.exists(os.path.join(save_dir, timestamp)):
os.makedirs(os.path.join(save_dir, timestamp))
file.save(os.path.join(save_dir, filepath))
return flask.jsonify({'status': 200, 'return_path': filepath,
'timestamp': timestamp, 'filename': filename})
return flask.jsonify({'status': 500})
@upload_api.route('/get_image_file/<timestamp>/<filename>')
def face_file(timestamp, filename):
try:
uploader_folder = app.config['UPLOAD_FOLDER']
save_dir = os.path.join(uploader_folder, 'face_recognition')
file_path = os.path.join(save_dir, timestamp, filename)
return flask.send_file(file_path) # flask.Response
except Exception as e:
traceback.print_exc()
return flask.jsonify({'status': 500, 'err_msg': str(e)})
@upload_api.route('/speaker_upload', methods=['POST'])
def speaker_upload():
def allowed_file(filename):
# 获取文件扩展名，以'.'为右分割然后取第二个值
return '.' in filename and \
filename.rsplit('.', 1)[1].lower() in ['wav', 'mp3']
if 'file' not in flask.request.files:
return flask.jsonify({'status': 500, 'err_msg': '[Face_Storage] No file in files'})
file = flask.request.files['file']
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
uploader_folder = app.config['UPLOAD_FOLDER']
save_dir = os.path.join(uploader_folder, 'speaker_recognition')
if not os.path.exists(save_dir):
os.makedirs(save_dir)
timestamp = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '-' + str(time.time() - int(time.time()))[2:5]
filepath = os.path.join(timestamp, filename)
if not os.path.exists(os.path.join(save_dir, timestamp)):
os.makedirs(os.path.join(save_dir, timestamp))
file.save(os.path.join(save_dir, filepath))
return flask.jsonify({'status': 200, 'return_path': filepath,
'timestamp': timestamp, 'filename': filename})
return flask.jsonify({'status': 500})
@upload_api.route('/face_detection_upload', methods=['POST'])
def face_detection_upload():
def allowed_file(filename):
# 获取文件扩展名，以'.'为右分割然后取第二个值
return '.' in filename and \
filename.rsplit('.', 1)[1].lower() in ['jpg', 'png']
if 'file' not in flask.request.files:
return flask.jsonify({'status': 500, 'err_msg': '[Face_Storage] No file in files'})
file = flask.request.files['file']
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
uploader_folder = app.config['UPLOAD_FOLDER']
save_dir = os.path.join(uploader_folder, 'face_detection')
if not os.path.exists(save_dir):
os.makedirs(save_dir)
timestamp = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '-' + str(time.time() - int(time.time()))[2:5]
filepath = os.path.join(timestamp, filename)
if not os.path.exists(os.path.join(save_dir, timestamp)):
os.makedirs(os.path.join(save_dir, timestamp))
file.save(os.path.join(save_dir, filepath))
return flask.jsonify({'status': 200, 'return_path': filepath,
'timestamp': timestamp, 'filename': filename})
return flask.jsonify({'status': 500})
@upload_api.route('/get_face_detection_file/<timestamp>/<filename>')
def face_detection_file(timestamp, filename):
try:
uploader_folder = app.config['UPLOAD_FOLDER']
save_dir = os.path.join(uploader_folder, 'face_detection')
file_path = os.path.join(save_dir, timestamp, filename)
return flask.send_file(file_path) # flask.Response
except Exception as e:
traceback.print_exc()
return flask.jsonify({'status': 500, 'err_msg': str(e)})
@upload_api.route('/get_speaker_file/<timestamp>/<filename>')
def speaker_file(timestamp, filename):
try:
uploader_folder = app.config['UPLOAD_FOLDER']
save_dir = os.path.join(uploader_folder, 'speaker_recognition')
file_path = os.path.join(save_dir, timestamp, filename)
return flask.send_file(file_path) # flask.Response
except Exception as e:
traceback.print_exc()
return flask.jsonify({'status': 500, 'err_msg': str(e)})
| 41.810606
| 121
| 0.641964
| 711
| 5,519
| 4.825598
| 0.129395
| 0.047217
| 0.061207
| 0.083941
| 0.904984
| 0.86826
| 0.86826
| 0.86826
| 0.86826
| 0.86826
| 0
| 0.011436
| 0.207828
| 5,519
| 131
| 122
| 42.129771
| 0.77333
| 0.036782
| 0
| 0.798077
| 0
| 0
| 0.14345
| 0.02771
| 0
| 0
| 0
| 0.007634
| 0
| 1
| 0.086538
| false
| 0
| 0.067308
| 0.028846
| 0.326923
| 0.048077
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
50c66f0bfa8a555c41ba5a7de97a727f1697404c
| 3,911
|
py
|
Python
|
Tests/Elsevier_Test.py
|
PeterMorrison1/JournalPDFScraper
|
ca30112653da9a53c9be5dc742e1409d94f71708
|
[
"MIT"
] | null | null | null |
Tests/Elsevier_Test.py
|
PeterMorrison1/JournalPDFScraper
|
ca30112653da9a53c9be5dc742e1409d94f71708
|
[
"MIT"
] | null | null | null |
Tests/Elsevier_Test.py
|
PeterMorrison1/JournalPDFScraper
|
ca30112653da9a53c9be5dc742e1409d94f71708
|
[
"MIT"
] | null | null | null |
from unittest import TestCase
from pprint import pprint
from Scrapers.ElsevierScraper import ElsevierScraper
from selenium import webdriver
from webdriver_manager.chrome import ChromeDriverManager
class Elsevier_pdf_Test(TestCase):
@classmethod
def setUpClass(cls):
options = webdriver.ChromeOptions()
options.add_argument("--start-maximized")
cls.selenium_driver = webdriver.Chrome(ChromeDriverManager().install(), options=options)
cls.scraper = ElsevierScraper(cls.selenium_driver)
@classmethod
def tearDownClass(cls):
cls.selenium_driver.quit()
def test_pdf_open_access_article_should_pass(self):
scraper = self.scraper
url = "https://www.gastrojournal.org/article/S0016-5085(18)34810-8/fulltext"
expected = "https://www.gastrojournal.org/action/showPdf?pii=S0016-5085%2818%2934810-8"
actual = scraper.find_pdf_url(url)
self.assertTrue(actual == expected, "Article pdf url was not found. Actual: " + str(actual))
def test_pdf_open_access_article_lancet_should_pass(self):
scraper = self.scraper
url = "https://www.thelancet.com/journals/langas/article/PIIS2468-1253(19)30333-4/fulltext"
expected = "https://www.thelancet.com/action/showPdf?pii=S2468-1253%2819%2930333-4"
actual = scraper.find_pdf_url(url)
self.assertTrue(actual == expected, "Article pdf url was not found. Actual: " + str(actual))
def test_pdf_closed_access_article_should_fail(self):
scraper = self.scraper
url = "https://www.gastrojournal.org/article/S0016-5085(18)35206-5/fulltext"
expected = None
actual = scraper.find_pdf_url(url)
self.assertTrue(actual is None, "Article pdf url was found (either now free or wrong url found) actual: " + str(actual))
def test_pdf_wrong_journal_should_fail(self):
scraper = self.scraper
url = "https://www.sciencedirect.com/science/article/pii/S0022460X20300754"
expected = None
actual = scraper.find_pdf_url(url)
self.assertTrue(actual is None, "Article pdf url was found, actual: " + str(actual))
def test_url_open_access_article_should_pass(self):
scraper = self.scraper
url = "https://www.gastrojournal.org/article/S0016-5085(18)34810-8/fulltext"
expected = "https://www.gastrojournal.org/action/showPdf?pii=S0016-5085%2818%2934810-8"
actual = scraper.find_journal_url(url)
self.assertTrue(actual == url, "Article pdf url was not found. Actual: " + str(actual))
def test_url_open_access_article_lancet_should_pass(self):
scraper = self.scraper
url = "https://www.thelancet.com/journals/langas/article/PIIS2468-1253(19)30333-4/fulltext"
expected = "https://www.thelancet.com/action/showPdf?pii=S2468-1253%2819%2930333-4"
actual = scraper.find_journal_url(url)
self.assertTrue(actual == url, "Article pdf url was not found. Actual: " + str(actual))
def test_url_closed_access_article_should_fail(self):
scraper = self.scraper
url = "https://www.gastrojournal.org/article/S0016-5085(18)35206-5/fulltext"
expected = None
actual = scraper.find_journal_url(url)
self.assertTrue(actual is None, "Article pdf url was found (either now free or wrong url found) actual: " + str(actual))
def test_url_wrong_journal_should_fail(self):
scraper = self.scraper
url = "https://www.sciencedirect.com/science/article/pii/S0022460X20300754"
expected = None
actual = scraper.find_journal_url(url)
self.assertTrue(actual is None, "Article pdf url was found, actual: " + str(actual))
| 41.168421
| 128
| 0.666837
| 479
| 3,911
| 5.296451
| 0.185804
| 0.069373
| 0.0473
| 0.069373
| 0.820654
| 0.820654
| 0.816713
| 0.814348
| 0.814348
| 0.814348
| 0
| 0.068439
| 0.230376
| 3,911
| 95
| 129
| 41.168421
| 0.774419
| 0
| 0
| 0.666667
| 0
| 0.15873
| 0.318252
| 0
| 0
| 0
| 0
| 0
| 0.126984
| 1
| 0.15873
| false
| 0.063492
| 0.079365
| 0
| 0.253968
| 0.015873
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
50e5d4ef11b2e91cca3833d0058f4ada2e8bc40a
| 59,781
|
py
|
Python
|
ssp/migrations/0001_initial.py
|
EOP-OMB/opal
|
72db2700cdd7a766093d054372246714cb83d482
|
[
"CC0-1.0"
] | 16
|
2021-04-21T20:12:20.000Z
|
2022-03-28T13:00:15.000Z
|
ssp/migrations/0001_initial.py
|
EOP-OMB/opal
|
72db2700cdd7a766093d054372246714cb83d482
|
[
"CC0-1.0"
] | 16
|
2021-04-26T17:32:07.000Z
|
2022-01-24T15:30:17.000Z
|
ssp/migrations/0001_initial.py
|
EOP-OMB/opal
|
72db2700cdd7a766093d054372246714cb83d482
|
[
"CC0-1.0"
] | 10
|
2021-04-21T20:12:25.000Z
|
2022-03-15T18:09:58.000Z
|
# Generated by Django 3.2.9 on 2021-11-26 20:53
from django.db import migrations, models
import django.db.models.deletion
import model_clone.mixins.clone
import ssp.models.base_classes_and_fields
import uuid
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='address',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('type', models.CharField(max_length=100)),
('postal_address', ssp.models.base_classes_and_fields.customTextField()),
('city', models.CharField(max_length=100)),
('state', models.CharField(max_length=2)),
('postal_code', models.CharField(max_length=25)),
('country', models.CharField(max_length=100)),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='annotation',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('annotationID', models.CharField(max_length=25)),
('ns', models.CharField(max_length=100)),
('value', ssp.models.base_classes_and_fields.customTextField()),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='attachment',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('attachment_type', models.CharField(choices=[('image', 'Image'), ('diagram', 'Diagram'), ('document', 'Document'), ('other', 'Other File Type')], max_length=50)),
('attachment', models.FileField(upload_to='')),
('filename', models.CharField(blank=True, max_length=100)),
('mediaType', models.CharField(blank=True, max_length=100)),
('caption', models.CharField(blank=True, max_length=200)),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='control_baseline',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='control_parameter',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('control_parameter_id', models.CharField(max_length=25)),
('value', ssp.models.base_classes_and_fields.customTextField()),
],
options={
'ordering': ['short_name', 'control_parameter_id'],
},
),
migrations.CreateModel(
name='control_statement',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('control_statement_id', models.CharField(max_length=25)),
('control_statement_text', ssp.models.base_classes_and_fields.customTextField()),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
],
options={
'ordering': ['short_name'],
},
),
migrations.CreateModel(
name='element_property',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('value', models.CharField(blank=True, max_length=100)),
('name', models.CharField(max_length=100)),
('property_id', models.CharField(blank=True, max_length=25)),
('ns', models.CharField(blank=True, max_length=25)),
('prop_class', models.CharField(blank=True, max_length=25)),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='email',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('email', models.EmailField(max_length=254)),
('type', models.CharField(choices=[('work', 'Work'), ('personal', 'Personal'), ('shared', 'Shared'), ('service', 'Service'), ('other', 'Other')], default='work', max_length=50)),
('supports_rich_text', models.BooleanField(default=True)),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='hashed_value',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('value', ssp.models.base_classes_and_fields.customTextField()),
('algorithm', models.CharField(max_length=100)),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='information_type',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('confidentialityImpact', models.CharField(choices=[('High', 'High'), ('Moderate', 'Moderate'), ('Low', 'Low')], max_length=50)),
('integrityImpact', models.CharField(choices=[('High', 'High'), ('Moderate', 'Moderate'), ('Low', 'Low')], max_length=50)),
('availabilityImpact', models.CharField(choices=[('High', 'High'), ('Moderate', 'Moderate'), ('Low', 'Low')], max_length=50)),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='inventory_item_type',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('use', ssp.models.base_classes_and_fields.customTextField()),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='link',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('text', models.CharField(max_length=255)),
('href', models.CharField(max_length=255)),
('requires_authentication', models.BooleanField(default=False)),
('rel', models.CharField(blank=True, max_length=255)),
('mediaType', models.CharField(blank=True, max_length=255)),
('hash', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='link_set', to='ssp.hashed_value')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='location',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('address', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='location_set', to='ssp.address')),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('emailAddresses', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.email')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='nist_control',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('group_id', models.CharField(max_length=50)),
('group_title', models.CharField(max_length=255)),
('control_id', models.CharField(max_length=50)),
('source', models.CharField(max_length=50)),
('control_title', models.CharField(max_length=255)),
('label', models.CharField(max_length=50)),
('sort_id', models.CharField(max_length=50)),
('status', models.CharField(blank=True, max_length=255)),
('catalog', models.CharField(max_length=50, null=True)),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
],
options={
'ordering': ['sort_id', 'catalog', 'control_title'],
},
),
migrations.CreateModel(
name='organization',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('email_addresses', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.email')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('locations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.location')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='person',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('name', models.CharField(max_length=100)),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('email_addresses', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.email')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('locations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.location')),
('organizations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.organization')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
],
options={
'ordering': ('name',),
},
),
migrations.CreateModel(
name='port_range',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('start', models.IntegerField()),
('end', models.IntegerField()),
('transport', models.CharField(max_length=40)),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='protocol',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('portRanges', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.port_range')),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='status',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('state', models.CharField(max_length=30)),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='system_component',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('component_type', models.CharField(max_length=100)),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('component_information_types', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.information_type')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='system_control',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('control_status', models.CharField(choices=[('Implemented', 'Implemented'), ('Parti1ally Implemented ', 'Partially Implemented'), ('Planned ', 'Planned'), ('Alternative Implementation', 'Alternative Implementation'), ('Not Applicable', 'Not Applicable'), ('Other than Implemented', 'Other than Implemented')], max_length=100)),
('control_origination', models.CharField(choices=[('Service Provider Corporate ', 'Service Provider Corporate'), ('Service Provider System Specific ', 'Service Provider System Specific'), ('Service Provider Hybrid (Corporate and System Specific)', 'Service Provider Hybrid'), ('Configured by Customer (Customer System Specific) ', 'Configured by Customer'), ('Provided by Customer (Customer System Specific) ', 'Provided by Customer'), ('Shared (Service Provider and Customer Responsibility) ', 'Shared'), ('Inherited ', 'Inherited'), ('N/A', 'N/A')], max_length=100)),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('control_parameters', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.control_parameter')),
],
options={
'ordering': ['nist_control'],
},
bases=(model_clone.mixins.clone.CloneMixin, models.Model),
),
migrations.CreateModel(
name='system_interconnection',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('external_ip_range', models.CharField(blank=True, max_length=255, null=True)),
('connection_security', models.CharField(choices=[('IPSec', 'Internet Protocal Security (IPSec)'), ('VPN', 'Virtual Private Network (VPN)'), ('SSL', 'Secure Sockets Layer (SSL)'), ('TLS', 'Transport Layer Security (TLS)')], default='TLS', max_length=20)),
('data_direction', models.CharField(choices=[('in', 'Incoming'), ('out', 'Outgoing'), ('both', 'Both')], default='both', max_length=20)),
('desc', ssp.models.base_classes_and_fields.customTextField(verbose_name='Information Being Transmitted')),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('external_organization', models.ForeignKey(null=True, on_delete=django.db.models.deletion.PROTECT, to='ssp.organization')),
('external_poc', models.ForeignKey(null=True, on_delete=django.db.models.deletion.PROTECT, to='ssp.person')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='system_inventory_item',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('item_special_configuration_settings', ssp.models.base_classes_and_fields.customTextField()),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('inventory_item_type', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='system_inventory_item_set', to='ssp.inventory_item_type')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='telephone_number',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('number', models.CharField(max_length=25)),
('type', models.CharField(max_length=25)),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='user_function',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='user_privilege',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('functionsPerformed', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.user_function')),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='user_role',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
('user_privileges', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.user_privilege')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='test_evidence',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('type', models.CharField(choices=[('splunk', 'Splunk Search'), ('shell', 'Shell Command'), ('curl', 'Curl Command')], max_length=255)),
('testing_conditions', models.CharField(max_length=2000)),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('controls', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_control')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
('results', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.attachment')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='system_user',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('roles', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.user_role')),
('user', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='system_user_set', to='ssp.person')),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.CreateModel(
name='system_service',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('service_purpose', ssp.models.base_classes_and_fields.customTextField()),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
('protocols', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.protocol')),
('service_information_types', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.information_type')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='system_security_plan',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('published', models.DateField(blank=True, null=True)),
('lastModified', models.DateTimeField(auto_now=True)),
('date_authorized', models.DateField(blank=True, null=True)),
('authorization_revocation_date', models.DateField(blank=True, null=True)),
('authorization_revocation_reason', models.CharField(blank=True, max_length=200, null=True)),
('version', models.CharField(default='1.0.0', max_length=25)),
('oscalVersion', models.CharField(default='1.0.0', max_length=10)),
('security_sensitivity_level', models.CharField(blank=True, choices=[('high', 'High'), ('moderate', 'Moderate'), ('low', 'Low')], max_length=10)),
('security_objective_confidentiality', models.CharField(blank=True, choices=[('high', 'High'), ('moderate', 'Moderate'), ('low', 'Low')], max_length=10)),
('security_objective_integrity', models.CharField(blank=True, choices=[('high', 'High'), ('moderate', 'Moderate'), ('low', 'Low')], max_length=10)),
('security_objective_availability', models.CharField(blank=True, choices=[('high', 'High'), ('moderate', 'Moderate'), ('low', 'Low')], max_length=10)),
('system_operator_type', models.CharField(blank=True, max_length=20, null=True)),
('public', models.BooleanField(default=True)),
('additional_selected_controls', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.nist_control')),
('annotations', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.annotation')),
('attachments', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.attachment')),
('authorization_boundary_diagram', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='system_authorization_boundary_diagram', to='ssp.attachment')),
('control_baseline', models.ForeignKey(null=True, on_delete=django.db.models.deletion.PROTECT, related_name='ssp_control_baseline_set', to='ssp.control_baseline')),
('controls', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_control')),
('data_flow_diagram', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='system_data_flow_diagram', to='ssp.attachment')),
('information_types', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.information_type')),
('leveraged_authorization', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_security_plan')),
('links', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link')),
('network_architecture_diagram', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='system_network_architecture_diagram', to='ssp.attachment')),
('organizational_unit', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='organizational_unit_set', to='ssp.organization')),
('properties', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property')),
('system_components', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_component')),
('system_interconnections', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_interconnection')),
('system_inventory_items', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_inventory_item')),
('system_services', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_service')),
('system_status', models.ForeignKey(null=True, on_delete=django.db.models.deletion.PROTECT, related_name='ssp_system_status_set', to='ssp.status')),
('system_users', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.system_user')),
],
options={
'abstract': False,
},
),
migrations.AddField(
model_name='system_interconnection',
name='interconnection_responsible_roles',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.user_role'),
),
migrations.AddField(
model_name='system_interconnection',
name='links',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link'),
),
migrations.AddField(
model_name='system_interconnection',
name='permitted_protocols',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.protocol'),
),
migrations.AddField(
model_name='system_interconnection',
name='properties',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property'),
),
migrations.AddField(
model_name='system_control',
name='control_primary_system',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.DO_NOTHING, to='ssp.system_security_plan'),
),
migrations.AddField(
model_name='system_control',
name='control_statements',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.control_statement'),
),
migrations.AddField(
model_name='system_control',
name='links',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link'),
),
migrations.AddField(
model_name='system_control',
name='nist_control',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.DO_NOTHING, related_name='system_control_set', to='ssp.nist_control'),
),
migrations.AddField(
model_name='system_control',
name='properties',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property'),
),
migrations.AddField(
model_name='system_component',
name='component_responsible_roles',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.user_role'),
),
migrations.AddField(
model_name='system_component',
name='component_status',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.PROTECT, related_name='system_component_set', to='ssp.status'),
),
migrations.AddField(
model_name='system_component',
name='links',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link'),
),
migrations.AddField(
model_name='system_component',
name='properties',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property'),
),
migrations.AddField(
model_name='person',
name='telephone_numbers',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.telephone_number'),
),
migrations.AddField(
model_name='organization',
name='telephone_numbers',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.telephone_number'),
),
migrations.CreateModel(
name='nist_control_statement',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('statement_type', models.CharField(max_length=255)),
('statement_text', ssp.models.base_classes_and_fields.customTextField()),
('nist_control', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='ssp.nist_control')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='nist_control_parameter',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('param_id', models.CharField(max_length=255)),
('param_type', models.CharField(choices=[('label', 'Label'), ('description', 'Description'), ('constraint', 'Constraint'), ('guidance', 'Guidance'), ('value', 'Value'), ('select', 'Select')], max_length=255)),
('param_text', models.CharField(blank=True, max_length=1024)),
('param_depends_on', models.CharField(blank=True, max_length=255)),
('param_class', models.CharField(blank=True, max_length=255)),
('nist_control', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='ssp.nist_control')),
],
options={
'abstract': False,
},
),
migrations.AddField(
model_name='location',
name='telephoneNumbers',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.telephone_number'),
),
migrations.AddField(
model_name='inventory_item_type',
name='baseline_configuration',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='baseline_configuration', to='ssp.link'),
),
migrations.AddField(
model_name='inventory_item_type',
name='links',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link'),
),
migrations.AddField(
model_name='inventory_item_type',
name='properties',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property'),
),
migrations.AddField(
model_name='inventory_item_type',
name='responsibleRoles',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.user_role'),
),
migrations.CreateModel(
name='import_catalog',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, max_length=255, null=True)),
('file_url', models.URLField(blank=True, max_length=255, null=True)),
('file', models.FileField(blank=True, null=True, upload_to='catalogs/')),
('added_controls', models.IntegerField(blank=True, null=True)),
('updated_controls', models.IntegerField(blank=True, null=True)),
('user', models.CharField(blank=True, max_length=255, null=True)),
('control_baseline', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.DO_NOTHING, related_name='import_catalog_set', to='ssp.control_baseline')),
],
options={
'abstract': False,
},
),
migrations.AddField(
model_name='control_statement',
name='control_statement_responsible_roles',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.user_role'),
),
migrations.AddField(
model_name='control_statement',
name='links',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link'),
),
migrations.AddField(
model_name='control_statement',
name='properties',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property'),
),
migrations.AddField(
model_name='control_baseline',
name='controls',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.nist_control'),
),
migrations.AddField(
model_name='control_baseline',
name='link',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='control_baseline_set', to='ssp.link'),
),
migrations.CreateModel(
name='continuous_monitoring_action_item',
fields=[
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True, null=True)),
('updated_at', models.DateTimeField(auto_now=True, null=True)),
('title', models.CharField(blank=True, help_text='A title for display and navigation', max_length=255)),
('short_name', models.CharField(blank=True, help_text='A common name, short name, or acronym', max_length=255)),
('desc', ssp.models.base_classes_and_fields.customTextField(help_text='A short textual description', verbose_name='description')),
('remarks', ssp.models.base_classes_and_fields.customTextField(help_text='general notes or comments')),
('automated', models.BooleanField(default=True)),
('frequency', models.CharField(choices=[('daily', 'Daily'), ('weekly', 'weekly'), ('monthly', 'Monthly'), ('quarterly', 'Quarterly'), ('annually', 'Annually'), ('as needed', 'As Needed')], default='as needed', max_length=10)),
('control_statements', ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.control_statement')),
],
options={
'ordering': ['title'],
'abstract': False,
},
),
migrations.AddField(
model_name='attachment',
name='hash',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='attachment_set', to='ssp.hashed_value'),
),
migrations.AddField(
model_name='attachment',
name='links',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.link'),
),
migrations.AddField(
model_name='attachment',
name='properties',
field=ssp.models.base_classes_and_fields.customMany2ManyField(blank=True, to='ssp.element_property'),
),
]
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| 0.864073
| 0.843204
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| 59,781
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| 586
| 69.271147
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
0fa568dfc2aac67c3d6dce1d7ddfeb411e5da3ea
| 3,525
|
py
|
Python
|
src/sage/repl/ipython_tests.py
|
switzel/sage
|
7eb8510dacf61b691664cd8f1d2e75e5d473e5a0
|
[
"BSL-1.0"
] | null | null | null |
src/sage/repl/ipython_tests.py
|
switzel/sage
|
7eb8510dacf61b691664cd8f1d2e75e5d473e5a0
|
[
"BSL-1.0"
] | null | null | null |
src/sage/repl/ipython_tests.py
|
switzel/sage
|
7eb8510dacf61b691664cd8f1d2e75e5d473e5a0
|
[
"BSL-1.0"
] | 1
|
2020-07-24T12:20:37.000Z
|
2020-07-24T12:20:37.000Z
|
'''
Tests for the IPython integration
First, test the pinfo magic for Python code. This is what IPython
calls when you ask for the single-questionmark help, like `foo?` ::
sage: from sage.repl.interpreter import get_test_shell
sage: shell = get_test_shell()
sage: shell.run_cell(u'from sage.repl.ipython_tests import dummy')
sage: shell.run_cell(u'%pinfo dummy')
Signature: dummy(argument, optional=None)
Docstring:
Dummy Docstring Title
<BLANKLINE>
Dummy docstring explanation.
<BLANKLINE>
INPUT:
<BLANKLINE>
* "argument" -- anything. Dummy argument.
<BLANKLINE>
* "optional" -- anything (optional). Dummy optional.
<BLANKLINE>
EXAMPLES:
<BLANKLINE>
...
Init docstring: x.__init__(...) initializes x; see help(type(x)) for signature
File: .../sage/repl/ipython_tests.py
Type: function
Next, test the pinfo magic for Cython code::
sage: from sage.repl.interpreter import get_test_shell
sage: shell = get_test_shell()
sage: shell.run_cell(u'from sage.tests.stl_vector import stl_int_vector')
sage: shell.run_cell(u'%pinfo stl_int_vector')
Docstring:
Example class wrapping an STL vector
<BLANKLINE>
EXAMPLES:
<BLANKLINE>
...
Init docstring: x.__init__(...) initializes x; see help(type(x)) for signature
File: .../sage/tests/stl_vector.pyx
Type: type
Next, test the pinfo2 magic for Python code. This is what IPython
calls when you ask for the double-questionmark help, like `foo??` ::
sage: from sage.repl.interpreter import get_test_shell
sage: shell = get_test_shell()
sage: shell.run_cell(u'from sage.repl.ipython_tests import dummy')
sage: shell.run_cell(u'%pinfo2 dummy')
Signature: dummy(argument, optional=None)
Source:
def dummy(argument, optional=None):
"""
Dummy Docstring Title
<BLANKLINE>
Dummy docstring explanation.
<BLANKLINE>
INPUT:
<BLANKLINE>
- ``argument`` -- anything. Dummy argument.
<BLANKLINE>
- ``optional`` -- anything (optional). Dummy optional.
<BLANKLINE>
EXAMPLES::
<BLANKLINE>
...
"""
return 'Source code would be here'
File: .../sage/repl/ipython_tests.py
Type: function
Next, test the pinfo2 magic for Cython code::
sage: from sage.repl.interpreter import get_test_shell
sage: shell = get_test_shell()
sage: shell.run_cell(u'from sage.tests.stl_vector import stl_int_vector')
sage: shell.run_cell(u'%pinfo2 stl_int_vector')
Source:
cdef class stl_int_vector(SageObject):
"""
Example class wrapping an STL vector
<BLANKLINE>
EXAMPLES::
<BLANKLINE>
...
"""
<BLANKLINE>
cdef vector[int] *data
cdef string *name
<BLANKLINE>
def __cinit__(self):
"""
The Cython constructor.
<BLANKLINE>
EXAMPLES::
<BLANKLINE>
...
File: .../sage/tests/stl_vector.pyx
Type: type
'''
def dummy(argument, optional=None):
"""
Dummy Docstring Title
Dummy docstring explanation.
INPUT:
- ``argument`` -- anything. Dummy argument.
- ``optional`` -- anything (optional). Dummy optional.
EXAMPLES::
sage: from sage.repl.ipython_tests import dummy
sage: dummy(1)
'Source code would be here'
"""
return 'Source code would be here'
| 28.2
| 82
| 0.629787
| 420
| 3,525
| 5.154762
| 0.190476
| 0.049885
| 0.044342
| 0.059122
| 0.854503
| 0.819861
| 0.738106
| 0.738106
| 0.658661
| 0.618014
| 0
| 0.001928
| 0.264113
| 3,525
| 124
| 83
| 28.427419
| 0.832691
| 0.960851
| 0
| 0
| 0
| 0
| 0.301205
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
0fc4f3b72e1d2572a6477269ae98e84ad3ab1b06
| 120
|
py
|
Python
|
dq/qm.py
|
shuaigroup/dummy_qm
|
ddf0a580487e88da584ebb723e9bf920fbc2397e
|
[
"MIT"
] | null | null | null |
dq/qm.py
|
shuaigroup/dummy_qm
|
ddf0a580487e88da584ebb723e9bf920fbc2397e
|
[
"MIT"
] | null | null | null |
dq/qm.py
|
shuaigroup/dummy_qm
|
ddf0a580487e88da584ebb723e9bf920fbc2397e
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
def scf(mol_name):
return len(mol_name)
def dft(mol_name):
return len(mol_name) - 2
| 12
| 28
| 0.608333
| 20
| 120
| 3.45
| 0.55
| 0.405797
| 0.376812
| 0.463768
| 0.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0.021505
| 0.225
| 120
| 9
| 29
| 13.333333
| 0.72043
| 0.175
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 8
|
ba2b2907655e40bf85b18f956a1b4b765f9b3053
| 3,041
|
py
|
Python
|
src/backtracking/tests/test_nqueens.py
|
seahrh/coding-interview
|
517d19e7e88c02acec4aa6336bc20206ce3f1897
|
[
"MIT"
] | null | null | null |
src/backtracking/tests/test_nqueens.py
|
seahrh/coding-interview
|
517d19e7e88c02acec4aa6336bc20206ce3f1897
|
[
"MIT"
] | null | null | null |
src/backtracking/tests/test_nqueens.py
|
seahrh/coding-interview
|
517d19e7e88c02acec4aa6336bc20206ce3f1897
|
[
"MIT"
] | null | null | null |
from backtracking.nqueens import *
class TestNQueens:
def test_queens(self):
assert queens(1) == {(Position(0, 0),)}
assert queens(2) == set()
assert queens(3) == set()
assert queens(4) == {
(
Position(row=0, col=1),
Position(row=1, col=3),
Position(row=2, col=0),
Position(row=3, col=2),
),
(
Position(row=0, col=2),
Position(row=1, col=0),
Position(row=2, col=3),
Position(row=3, col=1),
),
}
assert queens(5) == {
(
Position(row=0, col=0),
Position(row=1, col=2),
Position(row=2, col=4),
Position(row=3, col=1),
Position(row=4, col=3),
),
(
Position(row=0, col=0),
Position(row=1, col=3),
Position(row=2, col=1),
Position(row=3, col=4),
Position(row=4, col=2),
),
(
Position(row=0, col=1),
Position(row=1, col=3),
Position(row=2, col=0),
Position(row=3, col=2),
Position(row=4, col=4),
),
(
Position(row=0, col=1),
Position(row=1, col=4),
Position(row=2, col=2),
Position(row=3, col=0),
Position(row=4, col=3),
),
(
Position(row=0, col=2),
Position(row=1, col=0),
Position(row=2, col=3),
Position(row=3, col=1),
Position(row=4, col=4),
),
(
Position(row=0, col=2),
Position(row=1, col=4),
Position(row=2, col=1),
Position(row=3, col=3),
Position(row=4, col=0),
),
(
Position(row=0, col=3),
Position(row=1, col=0),
Position(row=2, col=2),
Position(row=3, col=4),
Position(row=4, col=1),
),
(
Position(row=0, col=3),
Position(row=1, col=1),
Position(row=2, col=4),
Position(row=3, col=2),
Position(row=4, col=0),
),
(
Position(row=0, col=4),
Position(row=1, col=1),
Position(row=2, col=3),
Position(row=3, col=0),
Position(row=4, col=2),
),
(
Position(row=0, col=4),
Position(row=1, col=2),
Position(row=2, col=0),
Position(row=3, col=3),
Position(row=4, col=1),
),
}
| 32.010526
| 48
| 0.352516
| 320
| 3,041
| 3.346875
| 0.065625
| 0.595705
| 0.134454
| 0.168067
| 0.867414
| 0.865546
| 0.865546
| 0.865546
| 0.865546
| 0.280112
| 0
| 0.082109
| 0.507399
| 3,041
| 94
| 49
| 32.351064
| 0.632844
| 0
| 0
| 0.76087
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.054348
| 1
| 0.01087
| false
| 0
| 0.01087
| 0
| 0.032609
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
e864b30c6597ac2fa1f0d231e0f5b14a0682d533
| 63,079
|
py
|
Python
|
datadotworld/client/_swagger/apis/datasets_api.py
|
DanialBetres/data.world-py
|
0e3acf2be9a07c5ab62ecac9289eb662088d54c7
|
[
"Apache-2.0"
] | 99
|
2017-01-23T16:24:18.000Z
|
2022-03-30T22:51:58.000Z
|
datadotworld/client/_swagger/apis/datasets_api.py
|
DanialBetres/data.world-py
|
0e3acf2be9a07c5ab62ecac9289eb662088d54c7
|
[
"Apache-2.0"
] | 77
|
2017-01-26T04:33:06.000Z
|
2022-03-11T09:39:50.000Z
|
datadotworld/client/_swagger/apis/datasets_api.py
|
DanialBetres/data.world-py
|
0e3acf2be9a07c5ab62ecac9289eb662088d54c7
|
[
"Apache-2.0"
] | 29
|
2017-01-25T16:55:23.000Z
|
2022-01-31T01:44:15.000Z
|
# coding: utf-8
"""
data.world API
# data.world in a nutshell data.world is a productive, secure platform for modern data teamwork. We bring together your data practitioners, subject matter experts, and other stakeholders by removing costly barriers to data discovery, comprehension, integration, and sharing. Everything your team needs to quickly understand and use data stays with it. Social features and integrations encourage collaborators to ask and answer questions, share discoveries, and coordinate closely while still using their preferred tools. Our focus on interoperability helps you enhance your own data with data from any source, including our vast and growing library of free public datasets. Sophisticated permissions, auditing features, and more make it easy to manage who views your data and what they do with it. # Conventions ## Authentication All data.world API calls require an API token. OAuth2 is the preferred and most secure method for authenticating users of your data.world applications. Visit our [oauth documentation](https://apidocs.data.world/toolkit/oauth) for additional information. Alternatively, you can obtain a token for _personal use or testing_ by navigating to your profile settings, under the Advanced tab ([https://data.world/settings/advanced](https://data.world/settings/advanced)). Authentication must be provided in API requests via the `Authorization` header. For example, for a user whose API token is `my_api_token`, the request header should be `Authorization: Bearer my_api_token` (note the `Bearer` prefix). ## Content type By default, `application/json` is the content type used in request and response bodies. Exceptions are noted in respective endpoint documentation. ## HTTPS only Our APIs can only be accessed via HTTPS. # Interested in building data.world apps? Check out our [developer portal](https://apidocs.data.world) for tips on how to get started, tutorials, and to interact with the API endpoints right within your browser.
OpenAPI spec version: 0.21.0
Contact: help@data.world
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import sys
import os
import re
# python 2 and python 3 compatibility library
from six import iteritems
from ..configuration import Configuration
from ..api_client import ApiClient
class DatasetsApi(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
Ref: https://github.com/swagger-api/swagger-codegen
"""
def __init__(self, api_client=None):
config = Configuration()
if api_client:
self.api_client = api_client
else:
if not config.api_client:
config.api_client = ApiClient()
self.api_client = config.api_client
def create_dataset(self, owner, body, **kwargs):
"""
Create a dataset
Create a new dataset.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.create_dataset(owner, body, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param DatasetCreateRequest body: (required)
:return: CreateDatasetResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.create_dataset_with_http_info(owner, body, **kwargs)
else:
(data) = self.create_dataset_with_http_info(owner, body, **kwargs)
return data
def create_dataset_with_http_info(self, owner, body, **kwargs):
"""
Create a dataset
Create a new dataset.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.create_dataset_with_http_info(owner, body, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param DatasetCreateRequest body: (required)
:return: CreateDatasetResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'body']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method create_dataset" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `create_dataset`")
# verify the required parameter 'body' is set
if ('body' not in params) or (params['body'] is None):
raise ValueError("Missing the required parameter `body` when calling `create_dataset`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `create_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/{owner}', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='CreateDatasetResponse',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def delete_dataset(self, owner, id, **kwargs):
"""
Delete a dataset
Delete a dataset and associated data. This operation cannot be undone, but you may recreate the dataset using the same id.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.delete_dataset(owner, id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:return: SuccessMessage
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.delete_dataset_with_http_info(owner, id, **kwargs)
else:
(data) = self.delete_dataset_with_http_info(owner, id, **kwargs)
return data
def delete_dataset_with_http_info(self, owner, id, **kwargs):
"""
Delete a dataset
Delete a dataset and associated data. This operation cannot be undone, but you may recreate the dataset using the same id.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.delete_dataset_with_http_info(owner, id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:return: SuccessMessage
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'id']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method delete_dataset" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `delete_dataset`")
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `delete_dataset`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `delete_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']):
raise ValueError("Invalid value for parameter `id` when calling `delete_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
if 'id' in params:
path_params['id'] = params['id']
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/{owner}/{id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='SuccessMessage',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def download_dataset(self, owner, id, **kwargs):
"""
Download a dataset
Download a .zip file containing all files within a dataset as originally uploaded. Prefer `POST:/sql` or `POST:/sparql` for retrieving clean and structured data.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.download_dataset(owner, id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.download_dataset_with_http_info(owner, id, **kwargs)
else:
(data) = self.download_dataset_with_http_info(owner, id, **kwargs)
return data
def download_dataset_with_http_info(self, owner, id, **kwargs):
"""
Download a dataset
Download a .zip file containing all files within a dataset as originally uploaded. Prefer `POST:/sql` or `POST:/sparql` for retrieving clean and structured data.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.download_dataset_with_http_info(owner, id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'id']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method download_dataset" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `download_dataset`")
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `download_dataset`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `download_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']):
raise ValueError("Invalid value for parameter `id` when calling `download_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
if 'id' in params:
path_params['id'] = params['id']
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/zip'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/download/{owner}/{id}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None,
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def fetch_datasets(self, **kwargs):
"""
List datasets as owner
List datasets that the currently authenticated user has access to because he or she is the owner.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.fetch_datasets(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str limit: Maximum number of items to include in a page of results.
:param str next: Token from previous result page to be used when requesting a subsequent page.
:return: PaginatedDatasetResults
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.fetch_datasets_with_http_info(**kwargs)
else:
(data) = self.fetch_datasets_with_http_info(**kwargs)
return data
def fetch_datasets_with_http_info(self, **kwargs):
"""
List datasets as owner
List datasets that the currently authenticated user has access to because he or she is the owner.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.fetch_datasets_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str limit: Maximum number of items to include in a page of results.
:param str next: Token from previous result page to be used when requesting a subsequent page.
:return: PaginatedDatasetResults
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['limit', 'next']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method fetch_datasets" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
if 'limit' in params:
query_params.append(('limit', params['limit']))
if 'next' in params:
query_params.append(('next', params['next']))
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/user/datasets/own', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PaginatedDatasetResults',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_dataset(self, owner, id, **kwargs):
"""
Retrieve a dataset
Retrieve a dataset. The definition of the dataset will be returned, not its data. Use `GET:/download/{owner}/{id}` or `GET:/file_download/{owner}/{id}/{file}` to retrieve the original files content, or `POST:/sql/{owner}/{id}` or `POST:/sparql/{owner}/{id}` to query the data.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_dataset(owner, id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:return: DatasetSummaryResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_dataset_with_http_info(owner, id, **kwargs)
else:
(data) = self.get_dataset_with_http_info(owner, id, **kwargs)
return data
def get_dataset_with_http_info(self, owner, id, **kwargs):
"""
Retrieve a dataset
Retrieve a dataset. The definition of the dataset will be returned, not its data. Use `GET:/download/{owner}/{id}` or `GET:/file_download/{owner}/{id}/{file}` to retrieve the original files content, or `POST:/sql/{owner}/{id}` or `POST:/sparql/{owner}/{id}` to query the data.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_dataset_with_http_info(owner, id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:return: DatasetSummaryResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'id']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_dataset" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `get_dataset`")
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `get_dataset`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `get_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']):
raise ValueError("Invalid value for parameter `id` when calling `get_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
if 'id' in params:
path_params['id'] = params['id']
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/{owner}/{id}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DatasetSummaryResponse',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_dataset_by_version(self, owner, id, version_id, **kwargs):
"""
Retrieve a dataset version
Retrieve a version of a dataset. The definition of the dataset will be returned, not its data.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_dataset_by_version(owner, id, version_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:param str version_id: Version unique identifier. (required)
:return: DatasetSummaryResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_dataset_by_version_with_http_info(owner, id, version_id, **kwargs)
else:
(data) = self.get_dataset_by_version_with_http_info(owner, id, version_id, **kwargs)
return data
def get_dataset_by_version_with_http_info(self, owner, id, version_id, **kwargs):
"""
Retrieve a dataset version
Retrieve a version of a dataset. The definition of the dataset will be returned, not its data.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_dataset_by_version_with_http_info(owner, id, version_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:param str version_id: Version unique identifier. (required)
:return: DatasetSummaryResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'id', 'version_id']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_dataset_by_version" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `get_dataset_by_version`")
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `get_dataset_by_version`")
# verify the required parameter 'version_id' is set
if ('version_id' not in params) or (params['version_id'] is None):
raise ValueError("Missing the required parameter `version_id` when calling `get_dataset_by_version`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `get_dataset_by_version`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']):
raise ValueError("Invalid value for parameter `id` when calling `get_dataset_by_version`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
if 'id' in params:
path_params['id'] = params['id']
if 'version_id' in params:
path_params['versionId'] = params['version_id']
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/{owner}/{id}/v/{versionId}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DatasetSummaryResponse',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_datasets_by_owner(self, owner, **kwargs):
"""
List datasets for a specified owner
List datasets that the currently authenticated user has access to, for the specified owner; when the dataset is open, private (but discoverable by the authenticated user) or the authenticated user is a contributor with discover visibility
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_datasets_by_owner(owner, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str limit: Maximum number of items to include in a page of results.
:param str next: Token from previous result page to be used when requesting a subsequent page.
:return: PaginatedDatasetResults
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_datasets_by_owner_with_http_info(owner, **kwargs)
else:
(data) = self.get_datasets_by_owner_with_http_info(owner, **kwargs)
return data
def get_datasets_by_owner_with_http_info(self, owner, **kwargs):
"""
List datasets for a specified owner
List datasets that the currently authenticated user has access to, for the specified owner; when the dataset is open, private (but discoverable by the authenticated user) or the authenticated user is a contributor with discover visibility
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_datasets_by_owner_with_http_info(owner, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str limit: Maximum number of items to include in a page of results.
:param str next: Token from previous result page to be used when requesting a subsequent page.
:return: PaginatedDatasetResults
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'limit', 'next']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_datasets_by_owner" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `get_datasets_by_owner`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `get_datasets_by_owner`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
query_params = []
if 'limit' in params:
query_params.append(('limit', params['limit']))
if 'next' in params:
query_params.append(('next', params['next']))
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/{owner}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PaginatedDatasetResults',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def patch_dataset(self, owner, id, body, **kwargs):
"""
Update a dataset
Update an existing dataset. Only elements or files included in the request will be updated. All omitted elements or files will remain untouched.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.patch_dataset(owner, id, body, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:param DatasetPatchRequest body: (required)
:return: SuccessMessage
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.patch_dataset_with_http_info(owner, id, body, **kwargs)
else:
(data) = self.patch_dataset_with_http_info(owner, id, body, **kwargs)
return data
def patch_dataset_with_http_info(self, owner, id, body, **kwargs):
"""
Update a dataset
Update an existing dataset. Only elements or files included in the request will be updated. All omitted elements or files will remain untouched.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.patch_dataset_with_http_info(owner, id, body, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:param DatasetPatchRequest body: (required)
:return: SuccessMessage
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'id', 'body']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method patch_dataset" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `patch_dataset`")
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `patch_dataset`")
# verify the required parameter 'body' is set
if ('body' not in params) or (params['body'] is None):
raise ValueError("Missing the required parameter `body` when calling `patch_dataset`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `patch_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']):
raise ValueError("Invalid value for parameter `id` when calling `patch_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
if 'id' in params:
path_params['id'] = params['id']
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/{owner}/{id}', 'PATCH',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='SuccessMessage',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def replace_dataset(self, owner, id, body, **kwargs):
"""
Create / Replace a dataset
Create or replace a dataset with a given id. If a dataset exists with the same id, this call will reset such dataset and all the data contained in it.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.replace_dataset(owner, id, body, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:param DatasetPutRequest body: (required)
:return: SuccessMessage
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.replace_dataset_with_http_info(owner, id, body, **kwargs)
else:
(data) = self.replace_dataset_with_http_info(owner, id, body, **kwargs)
return data
def replace_dataset_with_http_info(self, owner, id, body, **kwargs):
"""
Create / Replace a dataset
Create or replace a dataset with a given id. If a dataset exists with the same id, this call will reset such dataset and all the data contained in it.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.replace_dataset_with_http_info(owner, id, body, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str owner: User name and unique identifier of the user or organization a resource belongs to. For example, in the URL: [https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), jonloyens is the unique identifier of the owner. (required)
:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:param DatasetPutRequest body: (required)
:return: SuccessMessage
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['owner', 'id', 'body']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method replace_dataset" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'owner' is set
if ('owner' not in params) or (params['owner'] is None):
raise ValueError("Missing the required parameter `owner` when calling `replace_dataset`")
# verify the required parameter 'id' is set
if ('id' not in params) or (params['id'] is None):
raise ValueError("Missing the required parameter `id` when calling `replace_dataset`")
# verify the required parameter 'body' is set
if ('body' not in params) or (params['body'] is None):
raise ValueError("Missing the required parameter `body` when calling `replace_dataset`")
if 'owner' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['owner']):
raise ValueError("Invalid value for parameter `owner` when calling `replace_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
if 'id' in params and not re.search('[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]', params['id']):
raise ValueError("Invalid value for parameter `id` when calling `replace_dataset`, must conform to the pattern `/[a-z0-9](?:-(?!-)|[a-z0-9])+[a-z0-9]/`")
collection_formats = {}
path_params = {}
if 'owner' in params:
path_params['owner'] = params['owner']
if 'id' in params:
path_params['id'] = params['id']
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/{owner}/{id}', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='SuccessMessage',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def search(self, **kwargs):
"""
Search for datasets
Simple Dataset Search. Available for single tenant only.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.search(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str query:
:param str fields:
:param str limit:
:param str next:
:return: PaginatedDatasetResults
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.search_with_http_info(**kwargs)
else:
(data) = self.search_with_http_info(**kwargs)
return data
def search_with_http_info(self, **kwargs):
"""
Search for datasets
Simple Dataset Search. Available for single tenant only.
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.search_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str query:
:param str fields:
:param str limit:
:param str next:
:return: PaginatedDatasetResults
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['query', 'fields', 'limit', 'next']
all_params.append('callback')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method search" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
if 'query' in params:
query_params.append(('query', params['query']))
if 'fields' in params:
query_params.append(('fields', params['fields']))
if 'limit' in params:
query_params.append(('limit', params['limit']))
if 'next' in params:
query_params.append(('next', params['next']))
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
# Authentication setting
auth_settings = ['oauth']
return self.api_client.call_api('/datasets/search', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PaginatedDatasetResults',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
| 53.007563
| 1,984
| 0.601658
| 7,262
| 63,079
| 5.088543
| 0.054117
| 0.043298
| 0.009093
| 0.033123
| 0.936379
| 0.927097
| 0.924228
| 0.914675
| 0.911347
| 0.905853
| 0
| 0.003992
| 0.300988
| 63,079
| 1,189
| 1,985
| 53.052145
| 0.834078
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| 0
| 0.023411
| 0.221989
| 0.066423
| 0
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| 0.035117
| false
| 0
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| 0.098662
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| null | 0
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|
0
| 8
|
e886ce8a094b4f27ee9e8477879351a1dd662e5a
| 28,579
|
py
|
Python
|
docs/source/mmirheo/ParticleVectors/__init__.py
|
cselab/uDeviceX
|
2ad5e9dd9f118e3998b291cbfc35ee91205bbef8
|
[
"MIT"
] | 22
|
2019-07-17T13:06:41.000Z
|
2021-12-15T14:45:24.000Z
|
docs/source/_mirheo/ParticleVectors/__init__.py
|
cselab/Mirheo
|
21e797ae5bd91ad550bb6b39bccb5b861922beef
|
[
"MIT"
] | 63
|
2019-06-26T13:30:47.000Z
|
2021-02-23T10:13:10.000Z
|
docs/source/mmirheo/ParticleVectors/__init__.py
|
dimaleks/uDeviceX
|
2ad5e9dd9f118e3998b291cbfc35ee91205bbef8
|
[
"MIT"
] | 9
|
2019-10-11T07:32:19.000Z
|
2021-05-17T11:25:35.000Z
|
class DataManager:
r"""
A collection of channels in pinned memory.
"""
def __init__():
r"""Initialize self. See help(type(self)) for accurate signature.
"""
pass
class LocalParticleVector:
r"""
Particle local data storage, composed of particle channels.
"""
def __init__():
r"""Initialize self. See help(type(self)) for accurate signature.
"""
pass
@property
def per_particle():
r"""
The :any:`DataManager` that contains the particle channels.
"""
pass
class Mesh:
r"""
Internally used class for describing a simple triangular mesh
"""
def __init__():
r"""__init__(*args, **kwargs)
Overloaded function.
1. __init__(off_filename: str) -> None
Create a mesh by reading the OFF file
Args:
off_filename: path of the OFF file
2. __init__(vertices: List[real3], faces: List[int3]) -> None
Create a mesh by giving coordinates and connectivity
Args:
vertices: vertex coordinates
faces: connectivity: one triangle per entry, each integer corresponding to the vertex indices
"""
pass
def getFaces():
r"""getFaces(self: ParticleVectors.Mesh) -> List[List[int[3]]]
returns the vertex indices for each triangle of the mesh.
"""
pass
def getVertices():
r"""getVertices(self: ParticleVectors.Mesh) -> List[List[float[3]]]
returns the vertex coordinates of the mesh.
"""
pass
class ParticleVector:
r"""
Basic particle vector, consists of identical disconnected particles.
"""
def __init__():
r"""__init__(name: str, mass: float) -> None
Args:
name: name of the created PV
mass: mass of a single particle
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalParticleVector instance, the storage of halo particles.
"""
pass
@property
def local():
r"""
The local LocalParticleVector instance, the storage of local particles.
"""
pass
class LocalObjectVector(LocalParticleVector):
r"""
Object vector local data storage, additionally contains object channels.
"""
def __init__():
r"""Initialize self. See help(type(self)) for accurate signature.
"""
pass
@property
def per_object():
r"""
The :any:`DataManager` that contains the object channels.
"""
pass
@property
def per_particle():
r"""
The :any:`DataManager` that contains the particle channels.
"""
pass
class MembraneMesh(Mesh):
r"""
Internally used class for desctibing a triangular mesh that can be used with the Membrane Interactions.
In contrast with the simple :any:`Mesh`, this class precomputes some required quantities on the mesh,
including connectivity structures and stress-free quantities.
"""
def __init__():
r"""__init__(*args, **kwargs)
Overloaded function.
1. __init__(off_filename: str) -> None
Create a mesh by reading the OFF file.
The stress free shape is the input initial mesh
Args:
off_filename: path of the OFF file
2. __init__(off_initial_mesh: str, off_stress_free_mesh: str) -> None
Create a mesh by reading the OFF file, with a different stress free shape.
Args:
off_initial_mesh: path of the OFF file : initial mesh
off_stress_free_mesh: path of the OFF file : stress-free mesh)
3. __init__(vertices: List[real3], faces: List[int3]) -> None
Create a mesh by giving coordinates and connectivity
Args:
vertices: vertex coordinates
faces: connectivity: one triangle per entry, each integer corresponding to the vertex indices
4. __init__(vertices: List[real3], stress_free_vertices: List[real3], faces: List[int3]) -> None
Create a mesh by giving coordinates and connectivity, with a different stress-free shape.
Args:
vertices: vertex coordinates
stress_free_vertices: vertex coordinates of the stress-free shape
faces: connectivity: one triangle per entry, each integer corresponding to the vertex indices
"""
pass
def getFaces():
r"""getFaces(self: ParticleVectors.Mesh) -> List[List[int[3]]]
returns the vertex indices for each triangle of the mesh.
"""
pass
def getVertices():
r"""getVertices(self: ParticleVectors.Mesh) -> List[List[float[3]]]
returns the vertex coordinates of the mesh.
"""
pass
class ObjectVector(ParticleVector):
r"""
Basic Object Vector.
An Object Vector stores chunks of particles, each chunk belonging to the same object.
.. warning::
In case of interactions with other :any:`ParticleVector`, the extents of the objects must be smaller than a subdomain size. The code only issues a run time warning but it is the responsibility of the user to ensure this condition for correctness.
"""
def __init__():
r"""Initialize self. See help(type(self)) for accurate signature.
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalObjectVector instance, the storage of halo objects.
"""
pass
@property
def local():
r"""
The local LocalObjectVector instance, the storage of local objects.
"""
pass
class MembraneVector(ObjectVector):
r"""
Membrane is an Object Vector representing cell membranes.
It must have a triangular mesh associated with it such that each particle is mapped directly onto single mesh vertex.
"""
def __init__():
r"""__init__(name: str, mass: float, mesh: ParticleVectors.MembraneMesh) -> None
Args:
name: name of the created PV
mass: mass of a single particle
mesh: :any:`MembraneMesh` object
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalObjectVector instance, the storage of halo objects.
"""
pass
@property
def local():
r"""
The local LocalObjectVector instance, the storage of local objects.
"""
pass
class RigidObjectVector(ObjectVector):
r"""
Rigid Object is an Object Vector representing objects that move as rigid bodies, with no relative displacement against each other in an object.
It must have a triangular mesh associated with it that defines the shape of the object.
"""
def __init__():
r"""__init__(name: str, mass: float, inertia: real3, object_size: int, mesh: ParticleVectors.Mesh) -> None
Args:
name: name of the created PV
mass: mass of a single particle
inertia: moment of inertia of the body in its principal axes. The principal axes of the mesh are assumed to be aligned with the default global *OXYZ* axes
object_size: number of frozen particles per object
mesh: :any:`Mesh` object used for bounce back and dump
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalObjectVector instance, the storage of halo objects.
"""
pass
@property
def local():
r"""
The local LocalObjectVector instance, the storage of local objects.
"""
pass
class RodVector(ObjectVector):
r"""
Rod Vector is an :any:`ObjectVector` which reprents rod geometries.
"""
def __init__():
r"""__init__(name: str, mass: float, num_segments: int) -> None
Args:
name: name of the created Rod Vector
mass: mass of a single particle
num_segments: number of elements to discretize the rod
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalObjectVector instance, the storage of halo objects.
"""
pass
@property
def local():
r"""
The local LocalObjectVector instance, the storage of local objects.
"""
pass
class RigidCapsuleVector(RigidObjectVector):
r"""
:any:`RigidObjectVector` specialized for capsule shapes.
The advantage is that it doesn't need mesh and moment of inertia define, as those can be computed analytically.
"""
def __init__():
r"""__init__(*args, **kwargs)
Overloaded function.
1. __init__(name: str, mass: float, object_size: int, radius: float, length: float) -> None
Args:
name: name of the created PV
mass: mass of a single particle
object_size: number of frozen particles per object
radius: radius of the capsule
length: length of the capsule between the half balls. The total height is then "length + 2 * radius"
2. __init__(name: str, mass: float, object_size: int, radius: float, length: float, mesh: ParticleVectors.Mesh) -> None
Args:
name: name of the created PV
mass: mass of a single particle
object_size: number of frozen particles per object
radius: radius of the capsule
length: length of the capsule between the half balls. The total height is then "length + 2 * radius"
mesh: :any:`Mesh` object representing the shape of the object. This is used for dump only.
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalObjectVector instance, the storage of halo objects.
"""
pass
@property
def local():
r"""
The local LocalObjectVector instance, the storage of local objects.
"""
pass
class RigidCylinderVector(RigidObjectVector):
r"""
:any:`RigidObjectVector` specialized for cylindrical shapes.
The advantage is that it doesn't need mesh and moment of inertia define, as those can be computed analytically.
"""
def __init__():
r"""__init__(*args, **kwargs)
Overloaded function.
1. __init__(name: str, mass: float, object_size: int, radius: float, length: float) -> None
Args:
name: name of the created PV
mass: mass of a single particle
object_size: number of frozen particles per object
radius: radius of the cylinder
length: length of the cylinder
2. __init__(name: str, mass: float, object_size: int, radius: float, length: float, mesh: ParticleVectors.Mesh) -> None
Args:
name: name of the created PV
mass: mass of a single particle
object_size: number of frozen particles per object
radius: radius of the cylinder
length: length of the cylinder
mesh: :any:`Mesh` object representing the shape of the object. This is used for dump only.
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalObjectVector instance, the storage of halo objects.
"""
pass
@property
def local():
r"""
The local LocalObjectVector instance, the storage of local objects.
"""
pass
class RigidEllipsoidVector(RigidObjectVector):
r"""
:any:`RigidObjectVector` specialized for ellipsoidal shapes.
The advantage is that it doesn't need mesh and moment of inertia define, as those can be computed analytically.
"""
def __init__():
r"""__init__(*args, **kwargs)
Overloaded function.
1. __init__(name: str, mass: float, object_size: int, semi_axes: real3) -> None
Args:
name: name of the created PV
mass: mass of a single particle
object_size: number of frozen particles per object
semi_axes: ellipsoid principal semi-axes
2. __init__(name: str, mass: float, object_size: int, semi_axes: real3, mesh: ParticleVectors.Mesh) -> None
Args:
name: name of the created PV
mass: mass of a single particle
object_size: number of frozen particles per object
radius: radius of the cylinder
semi_axes: ellipsoid principal semi-axes
mesh: :any:`Mesh` object representing the shape of the object. This is used for dump only.
"""
pass
def getCoordinates():
r"""getCoordinates(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def getForces():
r"""getForces(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def getVelocities():
r"""getVelocities(self: ParticleVectors.ParticleVector) -> List[List[float[3]]]
Returns:
A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
def get_indices():
r"""get_indices(self: ParticleVectors.ParticleVector) -> List[int]
Returns:
A list of unique integer particle identifiers
"""
pass
def setCoordinates():
r"""setCoordinates(coordinates: List[real3]) -> None
Args:
coordinates: A list of :math:`N \times 3` reals: 3 components of coordinate for every of the N particles
"""
pass
def setForces():
r"""setForces(forces: List[real3]) -> None
Args:
forces: A list of :math:`N \times 3` reals: 3 components of force for every of the N particles
"""
pass
def setVelocities():
r"""setVelocities(velocities: List[real3]) -> None
Args:
velocities: A list of :math:`N \times 3` reals: 3 components of velocity for every of the N particles
"""
pass
@property
def halo():
r"""
The halo LocalObjectVector instance, the storage of halo objects.
"""
pass
@property
def local():
r"""
The local LocalObjectVector instance, the storage of local objects.
"""
pass
# Functions
def getReservedBisegmentChannels():
r"""getReservedBisegmentChannels() -> List[str]
Return the list of reserved channel names per bisegment fields
"""
pass
def getReservedObjectChannels():
r"""getReservedObjectChannels() -> List[str]
Return the list of reserved channel names for object fields
"""
pass
def getReservedParticleChannels():
r"""getReservedParticleChannels() -> List[str]
Return the list of reserved channel names for particle fields
"""
pass
| 24.637069
| 258
| 0.561006
| 3,177
| 28,579
| 4.985836
| 0.07932
| 0.026515
| 0.024747
| 0.033333
| 0.868939
| 0.858712
| 0.837058
| 0.82721
| 0.817803
| 0.809912
| 0
| 0.009315
| 0.353931
| 28,579
| 1,159
| 259
| 24.658326
| 0.84857
| 0.671297
| 0
| 0.621212
| 0
| 0
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| 0
| 0
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| 0
| 0
| 0
| 1
| 0.287879
| true
| 0.287879
| 0
| 0
| 0.327273
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
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| null | 0
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| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 9
|
ad171d04bddce02ac07bc4d0d2a074145f6350a1
| 3,019
|
py
|
Python
|
lct/secrets/secrets_provider.py
|
pathbreak/linode-cluster-toolkit
|
280257436105703c9a122e7ed111a72efa79adfc
|
[
"MIT"
] | 11
|
2017-07-19T15:25:39.000Z
|
2021-12-02T20:03:21.000Z
|
lct/secrets/secrets_provider.py
|
pathbreak/linode-cluster-toolkit
|
280257436105703c9a122e7ed111a72efa79adfc
|
[
"MIT"
] | null | null | null |
lct/secrets/secrets_provider.py
|
pathbreak/linode-cluster-toolkit
|
280257436105703c9a122e7ed111a72efa79adfc
|
[
"MIT"
] | 1
|
2021-12-02T20:03:22.000Z
|
2021-12-02T20:03:22.000Z
|
class SecretsProvider(object):
'''
Interface to be implemented by a secrets provider.
'''
def initialize(self, tk):
raise NotImplementedError('subclasses should override this')
def close(self):
raise NotImplementedError('subclasses should override this')
def get_v3_api_key(self, tkctx):
raise NotImplementedError('subclasses should override this')
def get_v4_personal_token(self, tkctx):
raise NotImplementedError('subclasses should override this')
def get_v4_oauth_token(self, tkctx):
raise NotImplementedError('subclasses should override this')
def get_v4_oauth_client_id(self, tkctx):
raise NotImplementedError('subclasses should override this')
def get_v4_oauth_client_secret(self, tkctx):
raise NotImplementedError('subclasses should override this')
def get_default_root_password(self, tkctx):
raise NotImplementedError('subclasses should override this')
def get_default_root_ssh_public_key(self, tkctx):
raise NotImplementedError('subclasses should override this')
def get_node_password(self, tkctx, node, user):
raise NotImplementedError('subclasses should override this')
def get_node_ssh_key(self, tkctx, node, user):
raise NotImplementedError('subclasses should override this')
def store_v3_api_key(self, tkctx, v3_api_key):
raise NotImplementedError('subclasses should override this')
def store_v4_personal_token(self, tkctx, v4_personal_token):
raise NotImplementedError('subclasses should override this')
def store_v4_oauth_token(self, tkctx, v4_oauth_token):
raise NotImplementedError('subclasses should override this')
def store_v4_oauth_client_id(self, tkctx, v4_oauth_client_id):
raise NotImplementedError('subclasses should override this')
def store_v4_oauth_client_secret(self, tkctx, v4_oauth_client_secret):
raise NotImplementedError('subclasses should override this')
def store_default_root_password(self, tkctx, default_root_password):
raise NotImplementedError('subclasses should override this')
def store_default_root_ssh_public_key(self, tkctx, default_root_ssh_public_key):
raise NotImplementedError('subclasses should override this')
def store_node_password(self, tkctx, node, user, password):
raise NotImplementedError('subclasses should override this')
def store_node_ssh_key(self, tkctx, node, user, ssh_key):
raise NotImplementedError('subclasses should override this')
| 29.891089
| 84
| 0.638953
| 306
| 3,019
| 6.045752
| 0.137255
| 0.259459
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| 0.924324
| 0.85027
| 0.814054
| 0.722703
| 0.688649
| 0.568108
| 0
| 0.007092
| 0.299437
| 3,019
| 100
| 85
| 30.19
| 0.867612
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| false
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| null | 1
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| 1
| 1
| 1
| 1
| 1
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 10
|
0f0a8190420d4bda4492f92478a720af128f54ea
| 9,178
|
py
|
Python
|
cotiza/migrations/0011_auto_20201211_0110.py
|
crewxart/gestor-cicloverde
|
3a1289649037f9d3420be8a98af4080ebeb7111e
|
[
"CC0-1.0"
] | null | null | null |
cotiza/migrations/0011_auto_20201211_0110.py
|
crewxart/gestor-cicloverde
|
3a1289649037f9d3420be8a98af4080ebeb7111e
|
[
"CC0-1.0"
] | null | null | null |
cotiza/migrations/0011_auto_20201211_0110.py
|
crewxart/gestor-cicloverde
|
3a1289649037f9d3420be8a98af4080ebeb7111e
|
[
"CC0-1.0"
] | null | null | null |
# Generated by Django 3.1.4 on 2020-12-11 04:10
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('cotiza', '0010_auto_20201210_2225'),
]
operations = [
migrations.CreateModel(
name='todo',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('nombre_cliente', models.CharField(max_length=100)),
('vehiculo', models.CharField(max_length=3)),
('conductor', models.CharField(max_length=100)),
('horas_conductor', models.DecimalField(decimal_places=1, max_digits=8)),
('cant_ayudantes', models.IntegerField()),
('nombre_asistente1', models.CharField(max_length=100)),
('horas_asistente1', models.DecimalField(decimal_places=1, max_digits=8)),
('nombre_asistente2', models.CharField(max_length=100)),
('horas_asistente2', models.DecimalField(decimal_places=1, max_digits=8)),
('valor_colaciones', models.DecimalField(decimal_places=1, max_digits=8)),
('lugar_origen', models.CharField(max_length=150)),
('lugar_destino', models.CharField(max_length=150)),
('lugar_servicio', models.CharField(max_length=150)),
('suma_peajes', models.DecimalField(decimal_places=1, max_digits=9)),
('costo_total', models.DecimalField(decimal_places=1, max_digits=9)),
('utilidad', models.DecimalField(decimal_places=1, max_digits=9)),
('tarifa', models.DecimalField(decimal_places=1, max_digits=8)),
('m3', models.DecimalField(decimal_places=1, max_digits=8)),
],
),
migrations.AlterField(
model_name='gastosadministrativos',
name='TI',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='arriendo',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='encomiendas',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='gastos_comunes',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='generales',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='insumos_aseo',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='insumos_oficina',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='mantencion_banco',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='patentes',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='permisos_circulacion',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosadministrativos',
name='ropa_trabajadores',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosproduccion',
name='cordel',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosproduccion',
name='electricidad',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosproduccion',
name='gas_grua',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosproduccion',
name='insumos_epp',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosproduccion',
name='insumos_planta',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosproduccion',
name='mantencion_maquinaria',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastosproduccion',
name='petroleo',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastostotales',
name='costo_operativo_dia',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastostotales',
name='costo_operativo_hora',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastostotales',
name='costo_operativo_mes',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastostotales',
name='sueldos',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastostotales',
name='total_administrativos',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastostotales',
name='total_asesorias',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='gastostotales',
name='total_produccion',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='petroleo',
name='valor_actual',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='ACHS',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='AFC',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='SIS',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='Total_haberes',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='bonos',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='costo_dia',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='costo_hora',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='gratificaciones',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='horas_trabajadas',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='sueldoBase',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='sueldoImponible',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='sueldo_liquido',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
migrations.AlterField(
model_name='trabajadores',
name='sueldos',
field=models.DecimalField(decimal_places=1, max_digits=9),
),
]
| 39.390558
| 114
| 0.590325
| 842
| 9,178
| 6.212589
| 0.146081
| 0.165169
| 0.229402
| 0.284458
| 0.845154
| 0.834831
| 0.793921
| 0.793921
| 0.721659
| 0.721659
| 0
| 0.023872
| 0.297124
| 9,178
| 232
| 115
| 39.560345
| 0.78701
| 0.004903
| 0
| 0.699115
| 1
| 0
| 0.144453
| 0.032417
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.004425
| 0
| 0.017699
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
7e2a3f6bb37faefd1dddcac23faa8151b77d0a8f
| 590
|
py
|
Python
|
test/test_modify_group.py
|
KlimenkovDM/Python_for_Test
|
29ec28f4d424514a674ce1fccb69494095e2e300
|
[
"Apache-2.0"
] | null | null | null |
test/test_modify_group.py
|
KlimenkovDM/Python_for_Test
|
29ec28f4d424514a674ce1fccb69494095e2e300
|
[
"Apache-2.0"
] | null | null | null |
test/test_modify_group.py
|
KlimenkovDM/Python_for_Test
|
29ec28f4d424514a674ce1fccb69494095e2e300
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
from model.group import Group
def test_modify_first_group(app):
app.session.login(username="admin", password="secret")
app.group.modify_first_group(Group(name='New group'))
app.session.logout()
def test_modify_first_group(app):
app.session.login(username="admin", password="secret")
app.group.modify_first_group(Group(header='New header'))
app.session.logout()
def test_modify_first_group(app):
app.session.login(username="admin", password="secret")
app.group.modify_first_group(Group(footer='New footer'))
app.session.logout()
| 34.705882
| 60
| 0.730508
| 83
| 590
| 5.012048
| 0.277108
| 0.158654
| 0.230769
| 0.129808
| 0.776442
| 0.776442
| 0.776442
| 0.776442
| 0.776442
| 0.776442
| 0
| 0.001916
| 0.115254
| 590
| 17
| 61
| 34.705882
| 0.795019
| 0.035593
| 0
| 0.692308
| 0
| 0
| 0.109155
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.230769
| false
| 0.230769
| 0.076923
| 0
| 0.307692
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
7e696355f7d76b69371a1b09e8fe536efe2d1970
| 12,136
|
py
|
Python
|
src/generator/AutoRest.Python.Azure.Tests/Expected/AcceptanceTests/AzureSpecials/autorestazurespecialparameterstestclient/operations/subscription_in_credentials_operations.py
|
fhoering/autorest
|
b36c77ebb6a5c92aca72eea0894a683506af5817
|
[
"MIT"
] | null | null | null |
src/generator/AutoRest.Python.Azure.Tests/Expected/AcceptanceTests/AzureSpecials/autorestazurespecialparameterstestclient/operations/subscription_in_credentials_operations.py
|
fhoering/autorest
|
b36c77ebb6a5c92aca72eea0894a683506af5817
|
[
"MIT"
] | null | null | null |
src/generator/AutoRest.Python.Azure.Tests/Expected/AcceptanceTests/AzureSpecials/autorestazurespecialparameterstestclient/operations/subscription_in_credentials_operations.py
|
fhoering/autorest
|
b36c77ebb6a5c92aca72eea0894a683506af5817
|
[
"MIT"
] | null | null | null |
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.pipeline import ClientRawResponse
import uuid
from .. import models
class SubscriptionInCredentialsOperations(object):
"""SubscriptionInCredentialsOperations operations.
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An objec model deserializer.
"""
def __init__(self, client, config, serializer, deserializer):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self.config = config
def post_method_global_valid(
self, custom_headers=None, raw=False, **operation_config):
"""POST method with subscriptionId modeled in credentials. Set the
credential subscriptionId to '1234-5678-9012-3456' to succeed.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsAzureSpecials.models.ErrorException>`
"""
# Construct URL
url = '/azurespecials/subscriptionId/method/string/none/path/global/1234-5678-9012-3456/{subscriptionId}'
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
def post_method_global_null(
self, custom_headers=None, raw=False, **operation_config):
"""POST method with subscriptionId modeled in credentials. Set the
credential subscriptionId to null, and client-side validation should
prevent you from making this call.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsAzureSpecials.models.ErrorException>`
"""
# Construct URL
url = '/azurespecials/subscriptionId/method/string/none/path/global/null/{subscriptionId}'
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
def post_method_global_not_provided_valid(
self, custom_headers=None, raw=False, **operation_config):
"""POST method with subscriptionId modeled in credentials. Set the
credential subscriptionId to '1234-5678-9012-3456' to succeed.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsAzureSpecials.models.ErrorException>`
"""
# Construct URL
url = '/azurespecials/subscriptionId/method/string/none/path/globalNotProvided/1234-5678-9012-3456/{subscriptionId}'
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.config.api_version", self.config.api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
def post_path_global_valid(
self, custom_headers=None, raw=False, **operation_config):
"""POST method with subscriptionId modeled in credentials. Set the
credential subscriptionId to '1234-5678-9012-3456' to succeed.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsAzureSpecials.models.ErrorException>`
"""
# Construct URL
url = '/azurespecials/subscriptionId/path/string/none/path/global/1234-5678-9012-3456/{subscriptionId}'
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
def post_swagger_global_valid(
self, custom_headers=None, raw=False, **operation_config):
"""POST method with subscriptionId modeled in credentials. Set the
credential subscriptionId to '1234-5678-9012-3456' to succeed.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:rtype: None
:rtype: :class:`ClientRawResponse<msrest.pipeline.ClientRawResponse>`
if raw=true
:raises:
:class:`ErrorException<Fixtures.AcceptanceTestsAzureSpecials.models.ErrorException>`
"""
# Construct URL
url = '/azurespecials/subscriptionId/swagger/string/none/path/global/1234-5678-9012-3456/{subscriptionId}'
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, **operation_config)
if response.status_code not in [200]:
raise models.ErrorException(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
| 44.782288
| 140
| 0.675758
| 1,286
| 12,136
| 6.203733
| 0.119751
| 0.041364
| 0.030083
| 0.045124
| 0.886939
| 0.886939
| 0.886939
| 0.886939
| 0.886939
| 0.886939
| 0
| 0.016329
| 0.222891
| 12,136
| 270
| 141
| 44.948148
| 0.829605
| 0.327703
| 0
| 0.8
| 0
| 0.032
| 0.169677
| 0.116414
| 0
| 0
| 0
| 0
| 0
| 1
| 0.048
| false
| 0
| 0.024
| 0
| 0.12
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
7e6a04d3063fec61d0e49953695965a7284b18e3
| 5,994
|
py
|
Python
|
GAN-pytorch-book/src/mnist.py
|
threecifanggen/data-science-learning
|
3ca795c60f7abbce5ebd538cb25c1a54cac14d8a
|
[
"MIT"
] | null | null | null |
GAN-pytorch-book/src/mnist.py
|
threecifanggen/data-science-learning
|
3ca795c60f7abbce5ebd538cb25c1a54cac14d8a
|
[
"MIT"
] | null | null | null |
GAN-pytorch-book/src/mnist.py
|
threecifanggen/data-science-learning
|
3ca795c60f7abbce5ebd538cb25c1a54cac14d8a
|
[
"MIT"
] | null | null | null |
from typing import NoReturn
import torch.nn as nn
import torch
import plotly.express as px
import pandas as pd
from .view import View
class MNISTDiscriminator(nn.Module):
"""判别器
"""
def __init__(self):
super().__init__()
self.model = nn.Sequential(
nn.Linear(784, 200),
nn.LeakyReLU(0.02),
nn.LayerNorm(200),
nn.Linear(200, 1),
nn.Sigmoid()
)
self.loss_function = nn.BCELoss()
self.optimiser = torch.optim.Adam(
self.parameters(),
lr=0.0001
)
self.counter = 0
self.progress = []
def forward(self, inputs: torch.FloatTensor):
return self.model(inputs)
def train(
self,
inputs: torch.FloatTensor,
targets: torch.FloatTensor
) -> NoReturn:
outputs = self.forward(inputs)
loss = self.loss_function(outputs, targets)
self.counter += 1
if self.counter % 10 == 0:
self.progress.append(loss.item())
if self.counter % 10000 == 0:
print(f"counter = {self.counter}")
self.optimiser.zero_grad()
loss.backward()
self.optimiser.step()
def plot_progress(self) -> NoReturn:
"""绘制过程图
"""
df = pd.DataFrame({
"step": [i * 10 for i in range(1, len(self.progress) + 1)],
"loss": self.progress
})
fig = px.line(df, x="step", y="loss")
fig.show()
class MNISTGenerator(nn.Module):
"""生成器
"""
def __init__(self):
super().__init__()
self.model = nn.Sequential(
nn.Linear(100, 200),
nn.LeakyReLU(0.02),
nn.LayerNorm(200),
nn.Linear(200, 784),
nn.Sigmoid()
)
self.optimiser = torch.optim.Adam(
self.parameters(),
lr=0.0001
)
self.counter = 0
self.progress = []
def forward(self, inputs: torch.FloatTensor):
return self.model(inputs)
def train(
self,
d: MNISTDiscriminator,
inputs: torch.FloatTensor,
targets: torch.FloatTensor
):
g_output = self.forward(inputs)
d_output = d.forward(g_output)
loss = d.loss_function(d_output, targets)
self.counter += 1
if self.counter % 10 == 0:
self.progress.append(loss.item())
self.optimiser.zero_grad()
loss.backward()
self.optimiser.step()
def plot_progress(self) -> NoReturn:
"""绘制过程图
"""
df = pd.DataFrame({
"step": [i * 10 for i in range(1, len(self.progress) + 1)],
"loss": self.progress
})
fig = px.line(df, x="step", y="loss")
fig.show()
class MNISTConditionalDiscriminator(nn.Module):
"""判别器
"""
def __init__(self):
super().__init__()
self.model = nn.Sequential(
nn.Linear(784+1, 200),
nn.LeakyReLU(0.02),
nn.LayerNorm(200),
nn.Linear(200, 1),
nn.Sigmoid()
)
self.loss_function = nn.BCELoss()
self.optimiser = torch.optim.Adam(
self.parameters(),
lr=0.0001
)
self.counter = 0
self.progress = []
def forward(self, image_tensor: torch.FloatTensor, label_tensor: torch.FloatTensor):
inputs = torch.cat((image_tensor, label_tensor))
return self.model(inputs)
def train(
self,
inputs: torch.FloatTensor,
label_tensor: torch.FloatTensor,
targets: torch.FloatTensor
) -> NoReturn:
outputs = self.forward(inputs, label_tensor)
loss = self.loss_function(outputs, targets)
self.counter += 1
if self.counter % 10 == 0:
self.progress.append(loss.item())
if self.counter % 10000 == 0:
print(f"counter = {self.counter}")
self.optimiser.zero_grad()
loss.backward()
self.optimiser.step()
def plot_progress(self) -> NoReturn:
"""绘制过程图
"""
df = pd.DataFrame({
"step": [i * 10 for i in range(1, len(self.progress) + 1)],
"loss": self.progress
})
fig = px.line(df, x="step", y="loss")
fig.show()
class MNISTConditionalGenerator(nn.Module):
"""生成器
"""
def __init__(self):
super().__init__()
self.model = nn.Sequential(
nn.Linear(100+1, 200),
nn.LeakyReLU(0.02),
nn.LayerNorm(200),
nn.Linear(200, 784),
nn.Sigmoid()
)
self.optimiser = torch.optim.Adam(
self.parameters(),
lr=0.0001
)
self.counter = 0
self.progress = []
def forward(
self,
seed_tensor: torch.FloatTensor,
label_tensor: torch.FloatTensor
):
return self.model(torch.cat((seed_tensor, label_tensor)))
def train(
self,
d: MNISTDiscriminator,
inputs: torch.FloatTensor,
label_tensor: torch.FloatTensor,
targets: torch.FloatTensor
):
g_output = self.forward(inputs, label_tensor)
d_output = d.forward(g_output, label_tensor)
loss = d.loss_function(d_output, targets)
self.counter += 1
if self.counter % 10 == 0:
self.progress.append(loss.item())
self.optimiser.zero_grad()
loss.backward()
self.optimiser.step()
def plot_progress(self) -> NoReturn:
"""绘制过程图
"""
df = pd.DataFrame({
"step": [i * 10 for i in range(1, len(self.progress) + 1)],
"loss": self.progress
})
fig = px.line(df, x="step", y="loss")
fig.show()
| 23.976
| 88
| 0.512679
| 638
| 5,994
| 4.711599
| 0.137931
| 0.05855
| 0.034597
| 0.021291
| 0.90519
| 0.892881
| 0.878244
| 0.845642
| 0.827013
| 0.827013
| 0
| 0.036107
| 0.362362
| 5,994
| 249
| 89
| 24.072289
| 0.750392
| 0.014348
| 0
| 0.805714
| 0
| 0
| 0.019119
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.091429
| false
| 0
| 0.034286
| 0.017143
| 0.171429
| 0.011429
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
7e8367a44dca2914110be84cabd9263c1719002f
| 2,929
|
py
|
Python
|
2016/day/14/solution.py
|
iangregson/advent-of-code
|
e2a2dde30dcaed027a5ba78f9270f8a1976577f1
|
[
"MIT"
] | null | null | null |
2016/day/14/solution.py
|
iangregson/advent-of-code
|
e2a2dde30dcaed027a5ba78f9270f8a1976577f1
|
[
"MIT"
] | null | null | null |
2016/day/14/solution.py
|
iangregson/advent-of-code
|
e2a2dde30dcaed027a5ba78f9270f8a1976577f1
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
import os
import re
import hashlib
dir_path = os.path.dirname(os.path.realpath(__file__))
file = open(dir_path + "/input.txt", "r")
input_txt = 'ahsbgdzn'
# input_txt = 'abc'
print(input_txt)
hashes = {}
def mdee5(i):
if i in hashes:
return hashes[i]
m = hashlib.md5()
m.update(input_txt.encode('utf-8'))
m.update(str(i).encode('utf-8'))
result = m.hexdigest()
hashes[i] = result
return result
def mdee5_pt2(i):
h = mdee5(i)
for i in range(2016):
h = hashlib.md5(h.encode("utf-8")).hexdigest()
return h
def has_tri(s):
matcher = re.compile(r'(.)\1\1')
result = matcher.search(s)
if result is not None:
return result.group(1)
else:
return None
def has_quint(s, t):
match = t*5
if match in s:
return match
else:
return None
def is_key(i, triple):
result = None
j = I + 1
while j < I + 1000:
t = mdee5(j)
# print('\t', j, t)
q = has_quint(t, triple[0])
if q is not None:
result = q
break
j += 1
return result, j
I = 0
keys = []
while True:
T = mdee5(I)
# print(I, T)
tri = has_tri(T)
if tri is not None:
# print('Triple!:', I)
key, key_idx = is_key(I, tri)
if key is not None:
keys.append(I)
# print('KEY:', len(keys), I, tri, key_idx, key)
I += 1
if len(keys) == 64:
break
# print(len(keys))
# print(keys)
print("Part 1 answer:", keys[63])
hashes = {}
def mdee5(i):
if i in hashes:
return hashes[i]
m = hashlib.md5()
m.update(input_txt.encode('utf-8'))
m.update(str(i).encode('utf-8'))
result = m.hexdigest()
hashes[i] = result
return result
def mdee5_pt2(i):
h = mdee5(i)
for i in range(2016):
h = hashlib.md5(h.encode("utf-8")).hexdigest()
return h
def has_tri(s):
matcher = re.compile(r'(.)\1\1')
result = matcher.search(s)
if result is not None:
return result.group(1)
else:
return None
def has_quint(s, t):
match = t*5
if match in s:
return match
else:
return None
def is_key(i, triple):
result = None
j = I + 1
while j < I + 1000:
t = mdee5_pt2(j)
# print('\t', j, t)
q = has_quint(t, triple[0])
if q is not None:
result = q
break
j += 1
return result, j
I = 0
keys = []
while True:
T = mdee5_pt2(I)
# print(I, T)
tri = has_tri(T)
if tri is not None:
# print('Triple!:', I)
key, key_idx = is_key(I, tri)
if key is not None:
keys.append(I)
# print('KEY:', len(keys), I, tri, key_idx, key)
I += 1
if len(keys) == 64:
break
# print(len(keys))
# print(keys)
print("Part 2 answer:", keys[63])
| 17.02907
| 60
| 0.519631
| 449
| 2,929
| 3.320713
| 0.167038
| 0.026828
| 0.04829
| 0.045607
| 0.879946
| 0.879946
| 0.879946
| 0.879946
| 0.879946
| 0.879946
| 0
| 0.035494
| 0.336292
| 2,929
| 171
| 61
| 17.128655
| 0.731481
| 0.100034
| 0
| 0.882883
| 0
| 0
| 0.034706
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.09009
| false
| 0
| 0.027027
| 0
| 0.261261
| 0.027027
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
0e5b49e827e3f73586cb999abf759779cef607be
| 835
|
py
|
Python
|
MDRSREID/utils/data_utils/Similarity/torch_similarity/batch_hard.py
|
nickhuang1996/HJL-re-id
|
107b25f31c961f360f69560cfddd78dfc0da3291
|
[
"MIT"
] | 43
|
2020-09-20T09:40:04.000Z
|
2022-03-29T11:25:22.000Z
|
MDRSREID/utils/data_utils/Similarity/torch_similarity/batch_hard.py
|
nickhuang1996/HJL-re-id
|
107b25f31c961f360f69560cfddd78dfc0da3291
|
[
"MIT"
] | 19
|
2020-10-05T05:35:38.000Z
|
2021-12-10T03:17:31.000Z
|
MDRSREID/utils/data_utils/Similarity/torch_similarity/batch_hard.py
|
nickhuang1996/HJL-re-id
|
107b25f31c961f360f69560cfddd78dfc0da3291
|
[
"MIT"
] | 18
|
2020-10-01T14:41:53.000Z
|
2021-09-02T06:57:57.000Z
|
import torch
def batch_hard(mat_distance, mat_similarity, more_similar):
if more_similar is 'smaller':
sorted_mat_distance, _ = torch.sort(mat_distance + (-9999999.) * (1 - mat_similarity), dim=1,descending=True)
hard_p = sorted_mat_distance[:, 0]
sorted_mat_distance, _ = torch.sort(mat_distance + 9999999. * mat_similarity, dim=1, descending=False)
hard_n = sorted_mat_distance[:, 0]
return hard_p, hard_n
elif more_similar is 'larger':
sorted_mat_distance, _ = torch.sort(mat_distance + 9999999. * (1 - mat_similarity), dim=1, descending=False)
hard_p = sorted_mat_distance[:, 0]
sorted_mat_distance, _ = torch.sort(mat_distance + (-9999999.) * mat_similarity, dim=1, descending=True)
hard_n = sorted_mat_distance[:, 0]
return hard_p, hard_n
| 49.117647
| 117
| 0.686228
| 113
| 835
| 4.699115
| 0.238938
| 0.269303
| 0.256121
| 0.165725
| 0.806026
| 0.806026
| 0.806026
| 0.772128
| 0.772128
| 0.772128
| 0
| 0.057057
| 0.202395
| 835
| 16
| 118
| 52.1875
| 0.74024
| 0
| 0
| 0.428571
| 0
| 0
| 0.015569
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.071429
| false
| 0
| 0.071429
| 0
| 0.285714
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
0ea8e4be6a6c8ada4eadc5cfc0bf1697ebf6fcf2
| 27,128
|
py
|
Python
|
tests/unit/api/jira_server/test_API_Jira_To_Elastic.py
|
pbx-gs/OSBot-jira
|
7677afee1f80398ddcccd6b45423bf6adc20b970
|
[
"Apache-2.0"
] | 1
|
2021-04-02T05:58:23.000Z
|
2021-04-02T05:58:23.000Z
|
tests/unit/api/jira_server/test_API_Jira_To_Elastic.py
|
pbx-gs/OSBot-jira
|
7677afee1f80398ddcccd6b45423bf6adc20b970
|
[
"Apache-2.0"
] | 1
|
2021-09-03T09:55:39.000Z
|
2021-09-03T09:55:39.000Z
|
tests/unit/api/jira_server/test_API_Jira_To_Elastic.py
|
filetrust/OSBot-jira
|
d753fff59cf938cf94a51bf8bc7981691524b686
|
[
"Apache-2.0"
] | 2
|
2021-04-02T05:58:29.000Z
|
2021-09-03T09:43:29.000Z
|
from osbot_aws.helpers.Test_Helper import Test_Helper
from osbot_jira.api.jira_server.API_Jira_To_Elastic import API_Jira_To_Elastic
class test_API_Jira_To_Elastic(Test_Helper):
def setUp(self):
super().setUp()
self.api = API_Jira_To_Elastic()
def test_elastic(self):
self.result = self.api.elastic().exists()
def test_handle_link_event(self):
assert self.api.handle_link_event({},None) == { 'event_key' : 'None None None',
'event_type': None,
'event_user': 'NA',
'raw_data' : {}}
def test_handle__issuelink_created(self):
event_type = 'issuelink_created'
data = {'timestamp': 1580427715757, 'webhookEvent': 'issuelink_created', 'issueLink': {'id': 11822, 'sourceIssueId': 11011, 'destinationIssueId': 11008, 'issueLinkType': {'id': 10000, 'name': 'Blocks', 'outwardName': 'blocks', 'inwardName': 'is blocked by', 'isSubTaskLinkType': False, 'isSystemLinkType': False}, 'systemLink': False}}
self.result = self.api.handle_event(event_type, data)
def test_handle__issuelink_deleted(self):
event_type = 'issuelink_deleted'
data = {'timestamp': 1580428520270, 'webhookEvent': 'issuelink_deleted', 'issueLink': {'id': 11823, 'sourceIssueId': 10378, 'destinationIssueId': 11008, 'issueLinkType': {'id': 10000, 'name': 'Blocks', 'outwardName': 'blocks', 'inwardName': 'is blocked by', 'isSubTaskLinkType': False, 'isSystemLinkType': False}, 'systemLink': False}}
self.result = self.api.handle_event(event_type, data)
def test_handle__issue_created(self):
event_type = 'jira:issue_created'
data = {'timestamp': 1580424169526, 'webhookEvent': 'jira:issue_created', 'issue_event_type_name': 'issue_created', 'user': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'issue': {'id': '11009', 'self': 'https://glasswall.atlassian.net/rest/api/2/11009', 'key': 'TASK-27', 'fields': {'statuscategorychangedate': '2020-01-30T16:42:49.641-0600', 'customfield_10070': None, 'customfield_10071': None, 'customfield_10072': None, 'customfield_10073': None, 'customfield_10074': None, 'fixVersions': [], 'resolution': None, 'lastViewed': '2020-01-30T16:42:49.654-0600', 'customfield_10060': None, 'customfield_10061': None, 'customfield_10062': None, 'customfield_10063': None, 'customfield_10065': None, 'customfield_10066': None, 'priority': {'self': 'https://glasswall.atlassian.net/rest/api/2/priority/3', 'iconUrl': 'https://glasswall.atlassian.net/images/icons/priorities/medium.svg', 'name': 'Medium', 'id': '3'}, 'customfield_10067': None, 'customfield_10068': None, 'customfield_10069': None, 'labels': [], 'timeestimate': None, 'aggregatetimeoriginalestimate': None, 'versions': [], 'issuelinks': [], 'assignee': None, 'status': {'self': 'https://glasswall.atlassian.net/rest/api/2/status/1', 'description': 'The issue is open and ready for the assignee to start work on it.', 'iconUrl': 'https://glasswall.atlassian.net/images/icons/statuses/open.png', 'name': 'Open', 'id': '1', 'statusCategory': {'self': 'https://glasswall.atlassian.net/rest/api/2/statuscategory/2', 'id': 2, 'key': 'new', 'colorName': 'blue-gray', 'name': 'New'}}, 'components': [], 'customfield_10050': None, 'customfield_10051': None, 'customfield_10052': None, 'customfield_10053': None, 'customfield_10054': None, 'customfield_10055': None, 'customfield_10056': None, 'customfield_10057': None, 'customfield_10058': None, 'customfield_10059': None, 'customfield_10049': None, 'aggregatetimeestimate': None, 'creator': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'name': 'dcruz', 'key': 'dcruz', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'subtasks': [], 'customfield_10040': None, 'customfield_10041': None, 'customfield_10042': None, 'reporter': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'name': 'dcruz', 'key': 'dcruz', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'customfield_10043': None, 'customfield_10044': None, 'aggregateprogress': {'progress': 0, 'total': 0}, 'customfield_10045': [], 'customfield_10046': None, 'customfield_10047': None, 'customfield_10048': None, 'customfield_10038': None, 'progress': {'progress': 0, 'total': 0}, 'votes': {'self': 'https://glasswall.atlassian.net/rest/api/2/issue/TASK-27/votes', 'votes': 0, 'hasVoted': False}, 'issuetype': {'self': 'https://glasswall.atlassian.net/rest/api/2/issuetype/10001', 'id': '10001', 'description': 'A small, distinct piece of work.', 'iconUrl': 'https://glasswall.atlassian.net/secure/viewavatar?size=medium&avatarId=10541&avatarType=issuetype', 'name': 'Task', 'subtask': False, 'avatarId': 10541}, 'timespent': None, 'customfield_10030': None, 'project': {'self': 'https://glasswall.atlassian.net/rest/api/2/project/10000', 'id': '10000', 'key': 'TASK', 'name': 'Tasks', 'projectTypeKey': 'business', 'simplified': False, 'avatarUrls': {'48x48': 'https://glasswall.atlassian.net/secure/projectavatar?pid=10000&avatarId=10519', '24x24': 'https://glasswall.atlassian.net/secure/projectavatar?size=small&s=small&pid=10000&avatarId=10519', '16x16': 'https://glasswall.atlassian.net/secure/projectavatar?size=xsmall&s=xsmall&pid=10000&avatarId=10519', '32x32': 'https://glasswall.atlassian.net/secure/projectavatar?size=medium&s=medium&pid=10000&avatarId=10519'}}, 'customfield_10031': None, 'customfield_10032': None, 'customfield_10033': None, 'customfield_10034': None, 'aggregatetimespent': None, 'customfield_10035': None, 'customfield_10036': None, 'customfield_10037': None, 'customfield_10028': None, 'customfield_10029': None, 'resolutiondate': None, 'workratio': -1, 'watches': {'self': 'https://glasswall.atlassian.net/rest/api/2/issue/TASK-27/watchers', 'watchCount': 0, 'isWatching': True}, 'created': '2020-01-30T16:42:49.478-0600', 'customfield_10020': None, 'customfield_10021': None, 'customfield_10022': None, 'customfield_10023': None, 'customfield_10016': None, 'customfield_10017': None, 'customfield_10018': {'hasEpicLinkFieldDependency': False, 'showField': False, 'nonEditableReason': {'reason': 'PLUGIN_LICENSE_ERROR', 'message': 'Portfolio for Jira must be licensed for the Parent Link to be available.'}}, 'customfield_10019': '0|i0061r:', 'updated': '2020-01-30T16:42:49.478-0600', 'timeoriginalestimate': None, 'description': None, 'customfield_10010': None, 'customfield_10014': None, 'customfield_10015': None, 'timetracking': {}, 'customfield_10005': None, 'customfield_10006': None, 'customfield_10007': None, 'security': None, 'customfield_10008': None, 'attachment': [], 'customfield_10009': None, 'summary': 'asd', 'customfield_10000': '{}', 'customfield_10001': None, 'customfield_10002': None, 'customfield_10003': None, 'customfield_10004': None, 'environment': None, 'duedate': None}}, 'changelog': {'id': '17640', 'items': [{'field': 'priority', 'fieldtype': 'jira', 'fieldId': 'priority', 'from': None, 'fromString': None, 'to': '3', 'toString': 'Medium'}, {'field': 'reporter', 'fieldtype': 'jira', 'fieldId': 'reporter', 'from': None, 'fromString': None, 'to': 'dcruz', 'toString': 'Dinis Cruz', 'tmpFromAccountId': None, 'tmpToAccountId': '5dee69782c44a60edee17525'}, {'field': 'Status', 'fieldtype': 'jira', 'fieldId': 'status', 'from': None, 'fromString': None, 'to': '1', 'toString': 'Open'}, {'field': 'summary', 'fieldtype': 'jira', 'fieldId': 'summary', 'from': None, 'fromString': None, 'to': None, 'toString': 'asd'}]}}
self.result = self.api.handle_event(event_type, data)
def test_handle_issue_deleted(self):
event_type = 'jira:issue_deleted'
data = {'timestamp': 1580426442525, 'webhookEvent': 'jira:issue_deleted', 'user': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'issue': {'id': '11009', 'self': 'https://glasswall.atlassian.net/rest/api/2/11009', 'key': 'TASK-27', 'fields': {'statuscategorychangedate': '2020-01-30T16:42:49.641-0600', 'customfield_10070': None, 'customfield_10071': None, 'customfield_10072': None, 'customfield_10073': None, 'customfield_10074': None, 'fixVersions': [], 'resolution': None, 'lastViewed': '2020-01-30T16:42:55.735-0600', 'customfield_10060': None, 'customfield_10061': None, 'customfield_10062': None, 'customfield_10063': None, 'customfield_10065': None, 'customfield_10066': None, 'priority': {'self': 'https://glasswall.atlassian.net/rest/api/2/priority/3', 'iconUrl': 'https://glasswall.atlassian.net/images/icons/priorities/medium.svg', 'name': 'Medium', 'id': '3'}, 'customfield_10067': None, 'customfield_10068': None, 'customfield_10069': None, 'labels': [], 'timeestimate': None, 'aggregatetimeoriginalestimate': None, 'versions': [], 'issuelinks': [], 'assignee': None, 'status': {'self': 'https://glasswall.atlassian.net/rest/api/2/status/1', 'description': 'The issue is open and ready for the assignee to start work on it.', 'iconUrl': 'https://glasswall.atlassian.net/images/icons/statuses/open.png', 'name': 'Open', 'id': '1', 'statusCategory': {'self': 'https://glasswall.atlassian.net/rest/api/2/statuscategory/2', 'id': 2, 'key': 'new', 'colorName': 'blue-gray', 'name': 'To Do'}}, 'components': [], 'customfield_10050': None, 'customfield_10051': None, 'customfield_10052': None, 'customfield_10053': None, 'customfield_10054': None, 'customfield_10055': None, 'customfield_10056': None, 'customfield_10057': None, 'customfield_10058': None, 'customfield_10059': None, 'customfield_10049': None, 'aggregatetimeestimate': None, 'creator': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'name': 'dcruz', 'key': 'dcruz', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'subtasks': [], 'customfield_10040': None, 'customfield_10041': None, 'customfield_10042': None, 'reporter': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'name': 'dcruz', 'key': 'dcruz', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'customfield_10043': None, 'customfield_10044': None, 'aggregateprogress': {'progress': 0, 'total': 0}, 'customfield_10045': [], 'customfield_10046': None, 'customfield_10047': None, 'customfield_10048': None, 'customfield_10038': None, 'progress': {'progress': 0, 'total': 0}, 'votes': {'self': 'https://glasswall.atlassian.net/rest/api/2/issue/TASK-27/votes', 'votes': 0, 'hasVoted': False}, 'worklog': {'startAt': 0, 'maxResults': 20, 'total': 0, 'worklogs': []}, 'issuetype': {'self': 'https://glasswall.atlassian.net/rest/api/2/issuetype/10001', 'id': '10001', 'description': 'A small, distinct piece of work.', 'iconUrl': 'https://glasswall.atlassian.net/secure/viewavatar?size=medium&avatarId=10541&avatarType=issuetype', 'name': 'Task', 'subtask': False, 'avatarId': 10541}, 'timespent': None, 'customfield_10030': 0.0, 'project': {'self': 'https://glasswall.atlassian.net/rest/api/2/project/10000', 'id': '10000', 'key': 'TASK', 'name': 'Tasks', 'projectTypeKey': 'business', 'simplified': False, 'avatarUrls': {'48x48': 'https://glasswall.atlassian.net/secure/projectavatar?pid=10000&avatarId=10519', '24x24': 'https://glasswall.atlassian.net/secure/projectavatar?size=small&s=small&pid=10000&avatarId=10519', '16x16': 'https://glasswall.atlassian.net/secure/projectavatar?size=xsmall&s=xsmall&pid=10000&avatarId=10519', '32x32': 'https://glasswall.atlassian.net/secure/projectavatar?size=medium&s=medium&pid=10000&avatarId=10519'}}, 'customfield_10031': 0.0, 'customfield_10032': 0.0, 'customfield_10033': None, 'aggregatetimespent': None, 'customfield_10034': None, 'customfield_10035': None, 'customfield_10036': None, 'customfield_10037': None, 'customfield_10028': 0.0, 'customfield_10029': 0.0, 'resolutiondate': None, 'workratio': -1, 'watches': {'self': 'https://glasswall.atlassian.net/rest/api/2/issue/TASK-27/watchers', 'watchCount': 1, 'isWatching': True}, 'created': '2020-01-30T16:42:49.478-0600', 'customfield_10020': None, 'customfield_10021': None, 'customfield_10022': None, 'customfield_10023': None, 'customfield_10016': None, 'customfield_10017': None, 'customfield_10018': {'hasEpicLinkFieldDependency': False, 'showField': False, 'nonEditableReason': {'reason': 'PLUGIN_LICENSE_ERROR', 'message': 'Portfolio for Jira must be licensed for the Parent Link to be available.'}}, 'customfield_10019': '0|i0061r:', 'updated': '2020-01-30T16:42:49.478-0600', 'timeoriginalestimate': None, 'description': None, 'customfield_10010': None, 'customfield_10014': None, 'customfield_10015': None, 'timetracking': {}, 'customfield_10005': None, 'customfield_10006': None, 'customfield_10007': None, 'security': None, 'customfield_10008': None, 'customfield_10009': None, 'attachment': [], 'summary': 'asd', 'customfield_10000': '{}', 'customfield_10001': None, 'customfield_10002': None, 'customfield_10003': None, 'customfield_10004': None, 'environment': None, 'duedate': None, 'comment': {'comments': [], 'maxResults': 0, 'total': 0, 'startAt': 0}}}}
self.result = self.api.handle_event(event_type, data)
def test_handle_issue_updated(self):
event_type ='jira:issue_updated'
data = {'timestamp': 1580422845543, 'webhookEvent': 'jira:issue_updated', 'issue_event_type_name': 'issue_updated', 'user': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'issue': {'id': '11007', 'self': 'https://glasswall.atlassian.net/rest/api/2/11007', 'key': 'TASK-25', 'fields': {'statuscategorychangedate': '2020-01-30T16:17:22.169-0600', 'customfield_10070': None, 'customfield_10071': None, 'customfield_10072': None, 'customfield_10073': None, 'customfield_10074': None, 'fixVersions': [], 'resolution': None, 'lastViewed': '2020-01-30T16:19:28.227-0600', 'customfield_10060': None, 'customfield_10061': None, 'customfield_10062': None, 'customfield_10063': None, 'customfield_10065': None, 'customfield_10066': None, 'priority': {'self': 'https://glasswall.atlassian.net/rest/api/2/priority/3', 'iconUrl': 'https://glasswall.atlassian.net/images/icons/priorities/medium.svg', 'name': 'Medium', 'id': '3'}, 'customfield_10067': None, 'customfield_10068': None, 'customfield_10069': None, 'labels': [], 'timeestimate': None, 'aggregatetimeoriginalestimate': None, 'versions': [], 'issuelinks': [], 'assignee': None, 'status': {'self': 'https://glasswall.atlassian.net/rest/api/2/status/1', 'description': 'The issue is open and ready for the assignee to start work on it.', 'iconUrl': 'https://glasswall.atlassian.net/images/icons/statuses/open.png', 'name': 'Open', 'id': '1', 'statusCategory': {'self': 'https://glasswall.atlassian.net/rest/api/2/statuscategory/2', 'id': 2, 'key': 'new', 'colorName': 'blue-gray', 'name': 'New'}}, 'components': [], 'customfield_10050': None, 'customfield_10051': None, 'customfield_10052': None, 'customfield_10053': None, 'customfield_10054': None, 'customfield_10055': None, 'customfield_10056': None, 'customfield_10057': None, 'customfield_10058': None, 'customfield_10059': None, 'customfield_10049': None, 'aggregatetimeestimate': None, 'creator': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'name': 'dcruz', 'key': 'dcruz', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'subtasks': [], 'customfield_10040': None, 'customfield_10041': None, 'customfield_10042': None, 'reporter': {'self': 'https://glasswall.atlassian.net/rest/api/2/user?accountId=5dee69782c44a60edee17525', 'name': 'dcruz', 'key': 'dcruz', 'accountId': '5dee69782c44a60edee17525', 'avatarUrls': {'48x48': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=48&s=48', '24x24': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=24&s=24', '16x16': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=16&s=16', '32x32': 'https://secure.gravatar.com/avatar/cd5c7a867913b97100b706e92add842b?d=https%3A%2F%2Favatar-management--avatars.us-west-2.prod.public.atl-paas.net%2Finitials%2FDC-3.png&size=32&s=32'}, 'displayName': 'Dinis Cruz', 'active': True, 'timeZone': 'America/Chicago', 'accountType': 'atlassian'}, 'customfield_10043': None, 'customfield_10044': None, 'aggregateprogress': {'progress': 0, 'total': 0}, 'customfield_10045': [], 'customfield_10046': None, 'customfield_10047': None, 'customfield_10048': None, 'customfield_10038': None, 'progress': {'progress': 0, 'total': 0}, 'votes': {'self': 'https://glasswall.atlassian.net/rest/api/2/issue/TASK-25/votes', 'votes': 0, 'hasVoted': False}, 'issuetype': {'self': 'https://glasswall.atlassian.net/rest/api/2/issuetype/10001', 'id': '10001', 'description': 'A small, distinct piece of work.', 'iconUrl': 'https://glasswall.atlassian.net/secure/viewavatar?size=medium&avatarId=10541&avatarType=issuetype', 'name': 'Task', 'subtask': False, 'avatarId': 10541}, 'timespent': None, 'customfield_10030': 0.0, 'customfield_10031': 0.0, 'project': {'self': 'https://glasswall.atlassian.net/rest/api/2/project/10000', 'id': '10000', 'key': 'TASK', 'name': 'Tasks', 'projectTypeKey': 'business', 'simplified': False, 'avatarUrls': {'48x48': 'https://glasswall.atlassian.net/secure/projectavatar?pid=10000&avatarId=10519', '24x24': 'https://glasswall.atlassian.net/secure/projectavatar?size=small&s=small&pid=10000&avatarId=10519', '16x16': 'https://glasswall.atlassian.net/secure/projectavatar?size=xsmall&s=xsmall&pid=10000&avatarId=10519', '32x32': 'https://glasswall.atlassian.net/secure/projectavatar?size=medium&s=medium&pid=10000&avatarId=10519'}}, 'customfield_10032': 1.0, 'customfield_10033': None, 'customfield_10034': None, 'aggregatetimespent': None, 'customfield_10035': None, 'customfield_10036': None, 'customfield_10037': None, 'customfield_10028': 0.0, 'customfield_10029': 1.0, 'resolutiondate': None, 'workratio': -1, 'watches': {'self': 'https://glasswall.atlassian.net/rest/api/2/issue/TASK-25/watchers', 'watchCount': 1, 'isWatching': True}, 'created': '2020-01-30T16:17:21.951-0600', 'customfield_10020': None, 'customfield_10021': None, 'customfield_10022': None, 'customfield_10023': None, 'customfield_10016': None, 'customfield_10017': None, 'customfield_10018': {'hasEpicLinkFieldDependency': False, 'showField': False, 'nonEditableReason': {'reason': 'PLUGIN_LICENSE_ERROR', 'message': 'Portfolio for Jira must be licensed for the Parent Link to be available.'}}, 'customfield_10019': '0|i0061j:', 'updated': '2020-01-30T16:20:45.515-0600', 'timeoriginalestimate': None, 'description': 'asd….', 'customfield_10010': None, 'customfield_10014': None, 'timetracking': {}, 'customfield_10015': None, 'customfield_10005': None, 'customfield_10006': None, 'customfield_10007': None, 'security': None, 'customfield_10008': None, 'attachment': [], 'customfield_10009': None, 'summary': 'another test task', 'customfield_10000': '{}', 'customfield_10001': None, 'customfield_10002': None, 'customfield_10003': None, 'customfield_10004': None, 'environment': None, 'duedate': None}}, 'changelog': {'id': '17635', 'items': [{'field': 'description', 'fieldtype': 'jira', 'fieldId': 'description', 'from': None, 'fromString': '….', 'to': None, 'toString': 'asd….'}]}}
self.result = self.api.handle_event(event_type, data)
def test_get_jira_issue(self):
assert self.api.get_jira_issue('Person-1').get('Key') == 'PERSON-1'
self.result = self.api.get_jira_issue('AAAA')
| 542.56
| 8,607
| 0.732011
| 3,392
| 27,128
| 5.771226
| 0.096698
| 0.112638
| 0.063445
| 0.07172
| 0.913414
| 0.896864
| 0.89482
| 0.89482
| 0.892879
| 0.890223
| 0
| 0.133249
| 0.069928
| 27,128
| 49
| 8,608
| 553.632653
| 0.642265
| 0
| 0
| 0.138889
| 0
| 1.5
| 0.727219
| 0.03384
| 0
| 0
| 0
| 0
| 0.055556
| 1
| 0.25
| false
| 0
| 0.055556
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 11
|
7ec606cea9fb5c6879ecbe2dbcb8f2eaf0d71410
| 8,339
|
py
|
Python
|
benchmarks_FEM_active/HM/excavation/BoreholeExcavation/borehole_excav.py
|
GeoStat-Framework/ogs5py_benchmarks
|
0b6db19b87cfad36459757f99ce2458f8e12b20b
|
[
"BSD-4-Clause"
] | 3
|
2019-01-15T17:38:11.000Z
|
2020-01-07T23:44:12.000Z
|
benchmarks/HM/excavation/BoreholeExcavation/borehole_excav.py
|
GeoStat-Framework/ogs5py_benchmarks
|
0b6db19b87cfad36459757f99ce2458f8e12b20b
|
[
"BSD-4-Clause"
] | 1
|
2020-05-12T09:18:09.000Z
|
2020-05-12T10:48:32.000Z
|
benchmarks/HM/excavation/BoreholeExcavation/borehole_excav.py
|
GeoStat-Framework/ogs5py_benchmarks
|
0b6db19b87cfad36459757f99ce2458f8e12b20b
|
[
"BSD-4-Clause"
] | 1
|
2020-01-08T13:28:50.000Z
|
2020-01-08T13:28:50.000Z
|
# -*- coding: utf-8 -*-
from ogs5py import OGS
model = OGS(
task_root='borehole_excav_root',
task_id='borehole_excav',
output_dir='out',
)
model.msh.read_file('borehole_excav.msh')
model.gli.read_file('borehole_excav.gli')
model.pcs.add_block(
main_key='PROCESS',
PCS_TYPE='RICHARDS_FLOW',
BOUNDARY_CONDITION_OUTPUT=[],
TIME_CONTROLLED_EXCAVATION=[1, 1, 0, 1],
NEGLECT_H_INI_EFFECT=1,
UPDATE_INI_STATE=1,
ELEMENT_MATRIX_OUTPUT=0,
)
model.pcs.add_block(
main_key='PROCESS',
PCS_TYPE='DEFORMATION',
NUM_TYPE='NEW',
BOUNDARY_CONDITION_OUTPUT=[],
TIME_CONTROLLED_EXCAVATION=[1, 1, 0, 1],
NEGLECT_H_INI_EFFECT=1,
UPDATE_INI_STATE=1,
ELEMENT_MATRIX_OUTPUT=0,
)
model.rfd.read_file('borehole_excav.rfd')
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
GEO_TYPE=['SURFACE', 'upper'],
DIS_TYPE=['CONSTANT', 5000000.0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
GEO_TYPE=['SURFACE', 'right'],
DIS_TYPE=['CONSTANT', 5000000.0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
GEO_TYPE=['SURFACE', 'back'],
DIS_TYPE=['CONSTANT', 5000000.0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
GEO_TYPE=['SURFACE', 'bottom'],
DIS_TYPE=['CONSTANT', 5000000.0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
GEO_TYPE=['SURFACE', 'left'],
DIS_TYPE=['CONSTANT', 5000000.0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
GEO_TYPE=['SURFACE', 'front'],
DIS_TYPE=['CONSTANT', 5000000.0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
DIS_TYPE=['CONSTANT', 1],
TIM_TYPE=['CURVE', 4],
EXCAVATION=[1, 1],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='DISPLACEMENT_X1',
GEO_TYPE=['SURFACE', 'left'],
DIS_TYPE=['CONSTANT', 0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='DISPLACEMENT_X1',
GEO_TYPE=['SURFACE', 'right'],
DIS_TYPE=['CONSTANT', 0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='DISPLACEMENT_Y1',
GEO_TYPE=['SURFACE', 'back'],
DIS_TYPE=['CONSTANT', 0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='DISPLACEMENT_Y1',
GEO_TYPE=['SURFACE', 'front'],
DIS_TYPE=['CONSTANT', 0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='DISPLACEMENT_Z1',
GEO_TYPE=['SURFACE', 'bottom'],
DIS_TYPE=['CONSTANT', 0],
)
model.bc.add_block(
main_key='BOUNDARY_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='DISPLACEMENT_Z1',
GEO_TYPE=['SURFACE', 'upper'],
DIS_TYPE=['CONSTANT', 0],
)
model.ic.add_block(
main_key='INITIAL_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='STRESS_XX',
GEO_TYPE=[
['SUB_DOMAIN'],
[2],
[0, -9000000.0],
[1, -9000000.0],
],
)
model.ic.add_block(
main_key='INITIAL_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='STRESS_YY',
GEO_TYPE=[
['SUB_DOMAIN'],
[2],
[0, -9000000.0],
[1, -9000000.0],
],
)
model.ic.add_block(
main_key='INITIAL_CONDITION',
PCS_TYPE='DEFORMATION',
PRIMARY_VARIABLE='STRESS_ZZ',
GEO_TYPE=[
['SUB_DOMAIN'],
[2],
[0, -9000000.0],
[1, -9000000.0],
],
)
model.ic.add_block(
main_key='INITIAL_CONDITION',
PCS_TYPE='RICHARDS_FLOW',
PRIMARY_VARIABLE='PRESSURE1',
GEO_TYPE='DOMAIN',
DIS_TYPE=['CONSTANT', 5000000.0],
)
model.mmp.add_block(
main_key='MEDIUM_PROPERTIES',
GEOMETRY_DIMENSION=3,
PERMEABILITY_TENSOR=['A', 1e-19, 0.0, 0.0, 0.0, 1e-19, 0.0, 0.0, 0.0, 1e-20],
POROSITY=[1, 0.156],
PERMEABILITY_SATURATION=[4, 0, 1, 0.5],
CAPILLARY_PRESSURE=[4, 0.00049],
STORAGE=[1, 5e-10],
)
model.mmp.add_block(
main_key='MEDIUM_PROPERTIES',
GEOMETRY_DIMENSION=3,
PERMEABILITY_TENSOR=['A', 1e-19, 0.0, 0.0, 0.0, 1e-19, 0.0, 0.0, 0.0, 1e-20],
POROSITY=[1, 0.156],
PERMEABILITY_SATURATION=[4, 0, 1, 0.5],
CAPILLARY_PRESSURE=[4, 0.00049],
STORAGE=[1, 5e-10],
)
model.msp.add_block(
main_key='SOLID_PROPERTIES',
DENSITY=[1, 0],
ELASTICITY=[
['POISSION', 0.25],
['YOUNGS_MODULUS'],
[1, 5600000000.0],
],
GRAVITY_CONSTANT=0,
BIOT_CONSTANT=0.6,
)
model.msp.add_block(
main_key='SOLID_PROPERTIES',
DENSITY=[1, 0],
ELASTICITY=[
['POISSION', 0.25],
['YOUNGS_MODULUS'],
[1, 5600000000.0],
],
GRAVITY_CONSTANT=0,
BIOT_CONSTANT=0.6,
)
model.mfp.add_block(
main_key='FLUID_PROPERTIES',
FLUID_TYPE='LIQUID',
PCS_TYPE='PRESSURE1',
DENSITY=[1, 1000.0],
VISCOSITY=[1, 0.001],
NON_GRAVITY=[],
)
model.num.add_block(
main_key='NUMERICS',
PCS_TYPE='RICHARDS_FLOW',
ELE_MASS_LUMPING=1,
NON_LINEAR_SOLVER=['PICARD', 1e-05, 100, 1],
LINEAR_SOLVER=[2, 2, 1e-12, 20000, 1, 100, 4],
COUPLING_CONTROL=['LMAX', 100000000.0],
)
model.num.add_block(
main_key='NUMERICS',
PCS_TYPE='DEFORMATION',
ELE_GAUSS_POINTS=3,
LINEAR_SOLVER=[2, 5, 1e-10, 10000, 1.0, 100, 4],
COUPLING_CONTROL=['LMAX', 1.0],
)
model.tim.add_block(
main_key='TIME_STEPPING',
PCS_TYPE='DEFORMATION',
TIME_STEPS=[1, 3600],
TIME_END=43200,
TIME_START=0.0,
)
model.tim.add_block(
main_key='TIME_STEPPING',
PCS_TYPE='RICHARDS_FLOW',
TIME_STEPS=[1, 3600],
TIME_END=43200,
TIME_START=0.0,
)
model.out.add_block(
main_key='OUTPUT',
PCS_TYPE='RICHARDS_FLOW',
NOD_VALUES=[
['PRESSURE1'],
['SATURATION1'],
['VELOCITY_X1'],
['VELOCITY_Y1'],
['VELOCITY_Z1'],
],
GEO_TYPE='DOMAIN',
DAT_TYPE='PVD',
TIM_TYPE=['STEPS', 1],
)
model.out.add_block(
main_key='OUTPUT',
PCS_TYPE='DEFORMATION',
NOD_VALUES=[
['DISPLACEMENT_X1'],
['DISPLACEMENT_Y1'],
['DISPLACEMENT_Z1'],
['STRESS_XX'],
['STRESS_XY'],
['STRESS_YY'],
['STRESS_ZZ'],
['STRESS_XZ'],
['STRESS_YZ'],
['STRAIN_XX'],
['STRAIN_XY'],
['STRAIN_YY'],
['STRAIN_ZZ'],
['STRAIN_XZ'],
['STRAIN_YZ'],
],
GEO_TYPE='DOMAIN',
DAT_TYPE='PVD',
TIM_TYPE=['STEPS', 1],
)
model.out.add_block(
main_key='OUTPUT',
NOD_VALUES=[
['PRESSURE1'],
['SATURATION1'],
['VELOCITY_X1'],
['VELOCITY_Y1'],
['VELOCITY_Z1'],
['DISPLACEMENT_X1'],
['DISPLACEMENT_Y1'],
['DISPLACEMENT_Z1'],
['STRESS_XX'],
['STRESS_XY'],
['STRESS_YY'],
['STRESS_ZZ'],
['STRESS_XZ'],
['STRESS_YZ'],
['STRAIN_XX'],
['STRAIN_XY'],
['STRAIN_YY'],
['STRAIN_ZZ'],
['STRAIN_XZ'],
['STRAIN_YZ'],
['STRAIN_PLS'],
],
GEO_TYPE=['POLYLINE', 'horizon'],
DAT_TYPE='TECPLOT',
TIM_TYPE=['STEPS', 1],
)
model.out.add_block(
main_key='OUTPUT',
NOD_VALUES=[
['HEAD'],
['PRESSURE1'],
['PRESSURE_CAP'],
['SATURATION1'],
['VELOCITY_X1'],
['VELOCITY_Y1'],
['VELOCITY_Z1'],
['DISPLACEMENT_X1'],
['DISPLACEMENT_Y1'],
['DISPLACEMENT_Z1'],
['STRESS_XX'],
['STRESS_XY'],
['STRESS_YY'],
['STRESS_ZZ'],
['STRESS_XZ'],
['STRESS_YZ'],
['STRAIN_XX'],
['STRAIN_XY'],
['STRAIN_YY'],
['STRAIN_ZZ'],
['STRAIN_XZ'],
['STRAIN_YZ'],
['STRAIN_PLS'],
],
GEO_TYPE=['POLYLINE', 'vertikal'],
DAT_TYPE='TECPLOT',
TIM_TYPE=['STEPS', 1],
)
model.write_input()
model.run_model()
| 24.526471
| 81
| 0.601631
| 1,028
| 8,339
| 4.561284
| 0.160506
| 0.054596
| 0.081894
| 0.102367
| 0.865643
| 0.855833
| 0.850928
| 0.835359
| 0.825549
| 0.786522
| 0
| 0.060769
| 0.22053
| 8,339
| 339
| 82
| 24.59882
| 0.660615
| 0.002518
| 0
| 0.79822
| 0
| 0
| 0.258778
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.002967
| 0
| 0.002967
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
7edf123013bf013627c38708f4dac543fcb62feb
| 36
|
py
|
Python
|
src/eval/__init__.py
|
egillanton/ice-atis-nlu-evaluation
|
e80f44e2410c7b43b5a3674648564797c85ea0cd
|
[
"Apache-2.0"
] | null | null | null |
src/eval/__init__.py
|
egillanton/ice-atis-nlu-evaluation
|
e80f44e2410c7b43b5a3674648564797c85ea0cd
|
[
"Apache-2.0"
] | null | null | null |
src/eval/__init__.py
|
egillanton/ice-atis-nlu-evaluation
|
e80f44e2410c7b43b5a3674648564797c85ea0cd
|
[
"Apache-2.0"
] | null | null | null |
def ngram_model():
return True
| 9
| 18
| 0.666667
| 5
| 36
| 4.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 36
| 3
| 19
| 12
| 0.851852
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 0
| 0.5
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
7eee2cc2d184a3f874e258e7885006d43122c6cc
| 44
|
py
|
Python
|
Practice/config_updated.py
|
tanzich/World_Weather_Analysis
|
67d65a736a24c6e3f3a75f1575bcc7260efca0af
|
[
"Apache-2.0"
] | null | null | null |
Practice/config_updated.py
|
tanzich/World_Weather_Analysis
|
67d65a736a24c6e3f3a75f1575bcc7260efca0af
|
[
"Apache-2.0"
] | null | null | null |
Practice/config_updated.py
|
tanzich/World_Weather_Analysis
|
67d65a736a24c6e3f3a75f1575bcc7260efca0af
|
[
"Apache-2.0"
] | null | null | null |
api_key = 'b1746925006c7c4f67cbbd8d6254876a'
| 44
| 44
| 0.886364
| 3
| 44
| 12.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.52381
| 0.045455
| 44
| 1
| 44
| 44
| 0.380952
| 0
| 0
| 0
| 0
| 0
| 0.711111
| 0.711111
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
bc1d9f9d92769b4b6c2a134b3779569689f5c097
| 2,598
|
py
|
Python
|
python-exercise300/281_290.py
|
sharebook-kr/learningspoons-bootcamp-finance
|
0288f3f3b39f54420e4e9987f1de12892dc680ea
|
[
"MIT"
] | 9
|
2020-10-25T15:13:32.000Z
|
2022-03-26T11:27:21.000Z
|
python-exercise300/281_290.py
|
sharebook-kr/learningspoons-bootcamp-finance
|
0288f3f3b39f54420e4e9987f1de12892dc680ea
|
[
"MIT"
] | null | null | null |
python-exercise300/281_290.py
|
sharebook-kr/learningspoons-bootcamp-finance
|
0288f3f3b39f54420e4e9987f1de12892dc680ea
|
[
"MIT"
] | 7
|
2021-03-01T11:06:45.000Z
|
2022-03-14T07:06:04.000Z
|
# 281
# class 차:
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
#
# car = 차(2, 1000)
# print(car.바퀴)
# print(car.가격)
# 282
# class 차:
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
#
# class 자전차(차):
# pass
# 283
# class 차:
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
#
# class 자전차(차):
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
#
# bicycle = 자전차(2, 100)
# print(bicycle.가격)
# 284
# class 차:
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
#
# class 자전차(차):
# def __init__(self, 바퀴, 가격, 구동계):
# super().__init__(바퀴, 가격)
# #차.__init__(self, 바퀴, 가격)
# self.구동계 = 구동계
#
#
# bicycle = 자전차(2, 100, "시마노")
# print(bicycle.구동계)
# print(bicycle.바퀴)
# 285
# class 차:
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
#
# class 자동차(차):
# def __init__(self, 바퀴, 가격):
# super().__init__(바퀴, 가격)
#
# def 정보(self):
# print("바퀴수 ", self.바퀴)
# print("가격 ", self.가격)
#
#
# car = 자동차(4, 1000)
# car.정보()
# 286
# class 차:
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
# def 정보(self):
# print("바퀴수 ", self.바퀴)
# print("가격 ", self.가격)
#
# class 자동차(차):
# def __init__(self, 바퀴, 가격):
# super().__init__(바퀴, 가격)
#
# class 자전차(차):
# def __init__(self, 바퀴, 가격, 구동계):
# super().__init__(바퀴, 가격)
# self.구동계 = 구동계
#
# bicycle = 자전차(2, 100, "시마노")
# bicycle.정보()
# 287
# class 차:
# def __init__(self, 바퀴, 가격):
# self.바퀴 = 바퀴
# self.가격 = 가격
#
# def 정보(self):
# print("바퀴수 ", self.바퀴)
# print("가격 ", self.가격)
#
# class 자동차(차):
# def __init__(self, 바퀴, 가격):
# super().__init__(바퀴, 가격)
#
# class 자전차(차):
# def __init__(self, 바퀴, 가격, 구동계):
# super().__init__(바퀴, 가격)
# self.구동계 = 구동계
#
# def 정보(self):
# super().정보()
# print("구동계 ", self.구동계)
#
# bicycle = 자전차(2, 100, "시마노")
# bicycle.정보()
# 288
# class 부모:
# def 호출(self):
# print("부모호출")
#
# class 자식(부모):
# def 호출(self):
# print("자식호출")
#
#
# 나 = 자식()
# 나.호출()
# 289
# class 부모:
# def __init__(self):
# print("부모생성")
#
# class 자식(부모):
# def __init__(self):
# print("자식생성")
#
# 나 = 자식()
# 290
# class 부모:
# def __init__(self):
# print("부모생성")
#
# class 자식(부모):
# def __init__(self):
# print("자식생성")
# super().__init__()
#
# 나 = 자식()
| 16.339623
| 38
| 0.467667
| 353
| 2,598
| 3.147309
| 0.113314
| 0.140414
| 0.178218
| 0.162016
| 0.814581
| 0.778578
| 0.778578
| 0.778578
| 0.744374
| 0.744374
| 0
| 0.032295
| 0.332564
| 2,598
| 159
| 39
| 16.339623
| 0.60842
| 0.881447
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
70c4e27bf4dfa9d90ac3811ef44d837327de11d3
| 6,491
|
py
|
Python
|
src/preprocessors.py
|
astromid/pandemicdatahack-track3
|
0812dad4ed08c4bb952d80d0610b2fa92d27901a
|
[
"MIT"
] | 3
|
2020-12-20T10:16:30.000Z
|
2022-03-24T04:39:25.000Z
|
src/preprocessors.py
|
astromid/pandemicdatahack-track3
|
0812dad4ed08c4bb952d80d0610b2fa92d27901a
|
[
"MIT"
] | null | null | null |
src/preprocessors.py
|
astromid/pandemicdatahack-track3
|
0812dad4ed08c4bb952d80d0610b2fa92d27901a
|
[
"MIT"
] | 2
|
2020-12-20T10:16:34.000Z
|
2020-12-20T15:18:01.000Z
|
from .base_preprocessor import BasePreprocessor
from category_encoders.cat_boost import CatBoostEncoder
import category_encoders as ce
import random
import numpy as np
import pandas as pd
SEED = 1377
N_FOLDS = 10
random.seed(SEED)
np.random.seed(SEED)
class CatPrep(BasePreprocessor):
def __init__(self, path):
super().__init__(path)
def transform_train(self):
full_train = self.preprocess_train_test(self.raw_train)
# full_train = pd.merge(full_train, self.education, how='left', on='id')
# full_train = pd.merge(full_train, self.employements, how='left', on='id')
# full_train = pd.merge(full_train, self.worldskills, how='left', on='id')
# new_drop_columns = ['status', 'code', 'is_international', 'int_name', 'ru_name']
# full_train = full_train.drop(new_drop_columns, axis=1, errors='ignore')
# full_train[self.cat_columns] = full_train[self.cat_columns].fillna("nan")
# full_train = full_train.dropna()
return full_train
def transform_test(self):
full_test = self.preprocess_train_test(self.raw_test)
# full_test = pd.merge(full_test, self.education, how='left', on='id')
# full_test = pd.merge(full_test, self.employements, how='left', on='id')
# full_test = pd.merge(full_test, self.worldskills, how='left', on='id')
# full_test = full_test.drop(self.drop_columns, axis=1, errors='ignore')
# new_drop_columns = ['status', 'code', 'is_international', 'int_name', 'ru_name']
# full_test = full_test.drop(new_drop_columns, axis=1, errors='ignore')
# full_test[self.cat_columns] = full_test[self.cat_columns].fillna("nan")
return full_test
class LinearPrep(BasePreprocessor):
def __init__(self, path):
super().__init__(path)
def transform_train(self):
full_train = self.preprocess_train_test(self.raw_train)
# full_train = pd.merge(full_train, self.education, how='left', on='id')
# full_train = pd.merge(full_train, self.employements, how='left', on='id')
# full_train = pd.merge(full_train, self.worldskills, how='left', on='id')
# new_drop_columns = ['status', 'code', 'is_international', 'int_name', 'ru_name']
# full_train = full_train.drop(self.drop_columns, axis=1, errors='ignore')
# full_train = full_train.drop(new_drop_columns, axis=1, errors='ignore')
# full_train[self.cat_columns] = full_train[self.cat_columns].fillna("nan")
# full_train = full_train.dropna()
return full_train
def transform_test(self):
full_test = self.preprocess_train_test(self.raw_test)
# full_test = pd.merge(full_test, self.education, how='left', on='id')
# full_test = pd.merge(full_test, self.employements, how='left', on='id')
# full_test = pd.merge(full_test, self.worldskills, how='left', on='id')
# full_test = full_test.drop(self.drop_columns, axis=1, errors='ignore')
# new_drop_columns = ['status', 'code', 'is_international', 'int_name', 'ru_name']
# full_test = full_test.drop(new_drop_columns, axis=1, errors='ignore')
# full_test[self.cat_columns] = full_test[self.cat_columns].fillna("nan")
self.new_cat_columns = full_test.select_dtypes(include=['category', 'boolean']).columns
self.cat_encoder = CatBoostEncoder(
cols=self.new_cat_columns,
)
return full_test
def fit(self, X, y):
self.cat_encoder.fit(X, y)
def transform(self, X):
return self.cat_encoder.transform(X)
class LGBMPrep(BasePreprocessor):
def __init__(self, path):
super().__init__(path)
def transform_train(self):
# full_train = self.preprocess_train_test(self.raw_train)
# full_train = pd.merge(full_train, self.education, how='left', on='id')
# full_train = pd.merge(full_train, self.employements, how='left', on='id')
# full_train = pd.merge(full_train, self.worldskills, how='left', on='id')
# new_drop_columns = ['status', 'code', 'is_international', 'int_name', 'ru_name']
# full_train = full_train.drop(self.drop_columns, axis=1, errors='ignore')
# full_train = full_train.drop(new_drop_columns, axis=1, errors='ignore')
# full_train[self.cat_columns] = full_train[self.cat_columns].fillna("nan")
# full_train = full_train.dropna()
full_train = self.raw_train
# cols = [item for item in (self.train_cat + self.train_binary)
# if item in full_train.columns]
self.cat_features = full_train.select_dtypes(include=['category', 'boolean']).columns.values
# self.cat_encoder = ce.BinaryEncoder(cols=self.cat_features)
# full_train = pd.merge(full_train, self.prep_empls, how='left', on='id')
return full_train
def transform_test(self):
# full_test = self.preprocess_train_test(self.raw_test)
# full_test = pd.merge(full_test, self.education, how='left', on='id')
# full_test = pd.merge(full_test, self.employements, how='left', on='id')
# full_test = pd.merge(full_test, self.worldskills, how='left', on='id')
# full_test = full_test.drop(self.drop_columns, axis=1, errors='ignore')
# new_drop_columns = ['status', 'code', 'is_international', 'int_name', 'ru_name']
# full_test = full_test.drop(new_drop_columns, axis=1, errors='ignore')
# full_test[self.cat_columns] = full_test[self.cat_columns].fillna("nan")
# self.new_cat_columns = full_test.select_dtypes(include=['category', 'boolean']).columns
# full_test = pd.merge(full_test, self.prep_empls, how='left', on='id')
return self.raw_test
def fit(self, X_train, y_train):
# categorical
# self.cat_encoder.fit(X_train, y_train)
#
self.cols_mean = {}
for col in [item for item in (self.train_idk+self.train_dates) if item in X_train.columns
and item not in self.cat_features]:
mean_value = X_train[col].mean()
self.cols_mean[col] = mean_value
def transform(self, X_test):
# X_test = self.cat_encoder.transform(X_test)
X_test = X_test.drop(self.train_text+self.train_idk, axis=1, errors='ignore')
for k, v in self.cols_mean.items():
X_test[k] = X_test[k].fillna(v)
return X_test
| 48.081481
| 109
| 0.650901
| 894
| 6,491
| 4.440716
| 0.105145
| 0.115617
| 0.065491
| 0.055416
| 0.80806
| 0.769521
| 0.748111
| 0.73602
| 0.722418
| 0.722418
| 0
| 0.00352
| 0.21214
| 6,491
| 134
| 110
| 48.440299
| 0.772781
| 0.57418
| 0
| 0.375
| 0
| 0
| 0.013319
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.232143
| false
| 0
| 0.107143
| 0.035714
| 0.535714
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
70cd3a781ecbd3d84802b4ca9e4b6acb93f00234
| 138
|
py
|
Python
|
can_tools/scrapers/official/MD/__init__.py
|
jrybacek/can-scrapers
|
1a32a45be6aa6630de4d100c56c2a8659a1b1025
|
[
"MIT"
] | null | null | null |
can_tools/scrapers/official/MD/__init__.py
|
jrybacek/can-scrapers
|
1a32a45be6aa6630de4d100c56c2a8659a1b1025
|
[
"MIT"
] | null | null | null |
can_tools/scrapers/official/MD/__init__.py
|
jrybacek/can-scrapers
|
1a32a45be6aa6630de4d100c56c2a8659a1b1025
|
[
"MIT"
] | null | null | null |
from can_tools.scrapers.official.MD.md_counties import MarylandCounties
from can_tools.scrapers.official.MD.md_state import MarylandState
| 46
| 71
| 0.884058
| 20
| 138
| 5.9
| 0.55
| 0.118644
| 0.20339
| 0.338983
| 0.542373
| 0.542373
| 0.542373
| 0
| 0
| 0
| 0
| 0
| 0.057971
| 138
| 2
| 72
| 69
| 0.907692
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
cb325d57b49f79432870f56bc837c60633e7740e
| 118,015
|
py
|
Python
|
meta.py
|
weversonvn/mooneyFaceMetaExp
|
88a78a2c0d95cda46eaea25715a2da1507dbc923
|
[
"Apache-2.0"
] | null | null | null |
meta.py
|
weversonvn/mooneyFaceMetaExp
|
88a78a2c0d95cda46eaea25715a2da1507dbc923
|
[
"Apache-2.0"
] | null | null | null |
meta.py
|
weversonvn/mooneyFaceMetaExp
|
88a78a2c0d95cda46eaea25715a2da1507dbc923
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This experiment was created using PsychoPy3 Experiment Builder (v3.2.3),
on ter 18 fev 2020 15:40:44 -03
If you publish work using this script the most relevant publication is:
Peirce J, Gray JR, Simpson S, MacAskill M, Höchenberger R, Sogo H, Kastman E, Lindeløv JK. (2019)
PsychoPy2: Experiments in behavior made easy Behav Res 51: 195.
https://doi.org/10.3758/s13428-018-01193-y
"""
from __future__ import absolute_import, division
from psychopy import locale_setup
from psychopy import prefs
from psychopy import sound, gui, visual, core, data, event, logging, clock
from psychopy.constants import (NOT_STARTED, STARTED, PLAYING, PAUSED,
STOPPED, FINISHED, PRESSED, RELEASED, FOREVER)
import numpy as np # whole numpy lib is available, prepend 'np.'
from numpy import (sin, cos, tan, log, log10, pi, average,
sqrt, std, deg2rad, rad2deg, linspace, asarray)
from numpy.random import random, randint, normal, shuffle
import os # handy system and path functions
import sys # to get file system encoding
from psychopy.hardware import keyboard
# Ensure that relative paths start from the same directory as this script
_thisDir = os.path.dirname(os.path.abspath(__file__))
os.chdir(_thisDir)
# Store info about the experiment session
psychopyVersion = '3.2.3'
expName = 'meta' # from the Builder filename that created this script
expInfo = {'participant': '', 'session': '001'}
dlg = gui.DlgFromDict(dictionary=expInfo, sortKeys=False, title=expName)
if dlg.OK == False:
core.quit() # user pressed cancel
expInfo['date'] = data.getDateStr() # add a simple timestamp
expInfo['expName'] = expName
expInfo['psychopyVersion'] = psychopyVersion
# Data file name stem = absolute path + name; later add .psyexp, .csv, .log, etc
filename = _thisDir + os.sep + u'data/%s_%s_%s' % (expInfo['participant'], expName, expInfo['date'])
# An ExperimentHandler isn't essential but helps with data saving
thisExp = data.ExperimentHandler(name=expName, version='',
extraInfo=expInfo, runtimeInfo=None,
originPath='/home/weverson/Documentos/codes/mooneyFaceMetaExp/meta.py',
savePickle=True, saveWideText=True,
dataFileName=filename)
# save a log file for detail verbose info
logFile = logging.LogFile(filename+'.log', level=logging.EXP)
logging.console.setLevel(logging.WARNING) # this outputs to the screen, not a file
endExpNow = False # flag for 'escape' or other condition => quit the exp
frameTolerance = 0.001 # how close to onset before 'same' frame
# Start Code - component code to be run before the window creation
# Setup the Window
win = visual.Window(
size=(1024, 768), fullscr=True, screen=0,
winType='pyglet', allowGUI=True, allowStencil=False,
monitor='testMonitor', color=[0,0,0], colorSpace='rgb',
blendMode='avg', useFBO=True,
units='height')
# store frame rate of monitor if we can measure it
expInfo['frameRate'] = win.getActualFrameRate()
if expInfo['frameRate'] != None:
frameDur = 1.0 / round(expInfo['frameRate'])
else:
frameDur = 1.0 / 60.0 # could not measure, so guess
# create a default keyboard (e.g. to check for escape)
defaultKeyboard = keyboard.Keyboard()
# Initialize components for Routine "language"
languageClock = core.Clock()
mouse = event.Mouse(win=win)
x, y = [None, None]
mouse.mouseClock = core.Clock()
english = visual.TextStim(win=win, name='english',
text='English',
font='Arial',
pos=(-0.25, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=-1.0);
portugues = visual.TextStim(win=win, name='portugues',
text='Português',
font='Arial',
pos=(0.25, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=-2.0);
# Initialize components for Routine "tela_inicial"
tela_inicialClock = core.Clock()
texto_tela_inicial = visual.TextStim(win=win, name='texto_tela_inicial',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=-1.0);
key_resp_ti = keyboard.Keyboard()
# Initialize components for Routine "instrucao_resposta"
instrucao_respostaClock = core.Clock()
text_ir = visual.TextStim(win=win, name='text_ir',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
key_resp = keyboard.Keyboard()
# Initialize components for Routine "instrucao_inicio"
instrucao_inicioClock = core.Clock()
text_ii = visual.TextStim(win=win, name='text_ii',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
key_resp_ii = keyboard.Keyboard()
f = np.arange(40)
d = np.arange(40)
ff = np.arange(40)
dd = np.arange(40)
ft = np.arange(40)
dt = np.arange(40)
np.random.shuffle(f)
np.random.shuffle(d)
np.random.shuffle(ff)
np.random.shuffle(dd)
np.random.shuffle(ft)
np.random.shuffle(dt)
e = np.random.randint(1,3, size=40)
ee = np.random.randint(1,3, size=40)
et = np.random.randint(1,3, size=40)
caminho = "./mooneyfaces/"
file = ""
bloco = 1
# Initialize components for Routine "reset"
resetClock = core.Clock()
text_3 = visual.TextStim(win=win, name='text_3',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=-1.0);
# Initialize components for Routine "fixate"
fixateClock = core.Clock()
text = visual.TextStim(win=win, name='text',
text='+',
font='Arial',
pos=(0, 0), height=0.1, wrapWidth=None, ori=0,
color='red', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
# Initialize components for Routine "case_test_0"
case_test_0Clock = core.Clock()
image_4 = visual.ImageStim(
win=win,
name='image_4',
image='sin', mask=None,
ori=0, pos=(0, 0), size=(0.5, 0.5),
color=[1,1,1], colorSpace='rgb', opacity=1,
flipHoriz=False, flipVert=False,
texRes=128, interpolate=True, depth=-1.0)
# Initialize components for Routine "inter_time"
inter_timeClock = core.Clock()
text_it = visual.TextStim(win=win, name='text_it',
text=None,
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
# Initialize components for Routine "case_test_1"
case_test_1Clock = core.Clock()
image_5 = visual.ImageStim(
win=win,
name='image_5',
image='sin', mask=None,
ori=0, pos=(0, 0), size=(0.5, 0.5),
color=[1,1,1], colorSpace='rgb', opacity=1,
flipHoriz=False, flipVert=False,
texRes=128, interpolate=True, depth=-1.0)
# Initialize components for Routine "resposta_test"
resposta_testClock = core.Clock()
text_6 = visual.TextStim(win=win, name='text_6',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
key_resp_4 = keyboard.Keyboard()
# Initialize components for Routine "confianca"
confiancaClock = core.Clock()
text_2 = visual.TextStim(win=win, name='text_2',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
rating = visual.RatingScale(win=win, name='rating', marker='triangle', size=1.0, pos=[0.0, -0.6], low=1, high=5, labels=[''], scale='')
# Initialize components for Routine "reset"
resetClock = core.Clock()
text_3 = visual.TextStim(win=win, name='text_3',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=-1.0);
# Initialize components for Routine "fixate"
fixateClock = core.Clock()
text = visual.TextStim(win=win, name='text',
text='+',
font='Arial',
pos=(0, 0), height=0.1, wrapWidth=None, ori=0,
color='red', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
# Initialize components for Routine "case_1"
case_1Clock = core.Clock()
image_1 = visual.ImageStim(
win=win,
name='image_1',
image='sin', mask=None,
ori=0, pos=(0, 0), size=(0.5, 0.5),
color=[1,1,1], colorSpace='rgb', opacity=1,
flipHoriz=False, flipVert=False,
texRes=128, interpolate=True, depth=-1.0)
# Initialize components for Routine "inter_time"
inter_timeClock = core.Clock()
text_it = visual.TextStim(win=win, name='text_it',
text=None,
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
# Initialize components for Routine "case_2"
case_2Clock = core.Clock()
image_2 = visual.ImageStim(
win=win,
name='image_2',
image='sin', mask=None,
ori=0, pos=(0, 0), size=(0.5, 0.5),
color=[1,1,1], colorSpace='rgb', opacity=1,
flipHoriz=False, flipVert=False,
texRes=128, interpolate=True, depth=-1.0)
# Initialize components for Routine "resposta"
respostaClock = core.Clock()
text_4 = visual.TextStim(win=win, name='text_4',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
key_resp_2 = keyboard.Keyboard()
# Initialize components for Routine "confianca"
confiancaClock = core.Clock()
text_2 = visual.TextStim(win=win, name='text_2',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
rating = visual.RatingScale(win=win, name='rating', marker='triangle', size=1.0, pos=[0.0, -0.6], low=1, high=5, labels=[''], scale='')
# Initialize components for Routine "reset"
resetClock = core.Clock()
text_3 = visual.TextStim(win=win, name='text_3',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=-1.0);
# Initialize components for Routine "fixate"
fixateClock = core.Clock()
text = visual.TextStim(win=win, name='text',
text='+',
font='Arial',
pos=(0, 0), height=0.1, wrapWidth=None, ori=0,
color='red', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
# Initialize components for Routine "case_3"
case_3Clock = core.Clock()
image = visual.ImageStim(
win=win,
name='image',
image='sin', mask=None,
ori=0, pos=(0, 0), size=(0.5, 0.5),
color=[1,1,1], colorSpace='rgb', opacity=1,
flipHoriz=False, flipVert=False,
texRes=128, interpolate=True, depth=-1.0)
# Initialize components for Routine "inter_time"
inter_timeClock = core.Clock()
text_it = visual.TextStim(win=win, name='text_it',
text=None,
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
# Initialize components for Routine "case_4"
case_4Clock = core.Clock()
image_3 = visual.ImageStim(
win=win,
name='image_3',
image='sin', mask=None,
ori=0, pos=(0, 0), size=(0.5, 0.5),
color=[1,1,1], colorSpace='rgb', opacity=1,
flipHoriz=False, flipVert=False,
texRes=128, interpolate=True, depth=-1.0)
# Initialize components for Routine "resposta_2"
resposta_2Clock = core.Clock()
text_resposta_2 = visual.TextStim(win=win, name='text_resposta_2',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
key_resp_3 = keyboard.Keyboard()
# Initialize components for Routine "confianca"
confiancaClock = core.Clock()
text_2 = visual.TextStim(win=win, name='text_2',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
rating = visual.RatingScale(win=win, name='rating', marker='triangle', size=1.0, pos=[0.0, -0.6], low=1, high=5, labels=[''], scale='')
# Initialize components for Routine "fim"
fimClock = core.Clock()
text_5 = visual.TextStim(win=win, name='text_5',
text='default text',
font='Arial',
pos=(0, 0), height=0.05, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
languageStyle='LTR',
depth=0.0);
# Create some handy timers
globalClock = core.Clock() # to track the time since experiment started
routineTimer = core.CountdownTimer() # to track time remaining of each (non-slip) routine
# ------Prepare to start Routine "language"-------
# update component parameters for each repeat
# setup some python lists for storing info about the mouse
mouse.clicked_name = []
gotValidClick = False # until a click is received
# keep track of which components have finished
languageComponents = [mouse, english, portugues]
for thisComponent in languageComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
languageClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "language"-------
while continueRoutine:
# get current time
t = languageClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=languageClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *mouse* updates
if mouse.status == NOT_STARTED and t >= 0.0-frameTolerance:
# keep track of start time/frame for later
mouse.frameNStart = frameN # exact frame index
mouse.tStart = t # local t and not account for scr refresh
mouse.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(mouse, 'tStartRefresh') # time at next scr refresh
mouse.status = STARTED
mouse.mouseClock.reset()
prevButtonState = mouse.getPressed() # if button is down already this ISN'T a new click
if mouse.status == STARTED: # only update if started and not finished!
buttons = mouse.getPressed()
if buttons != prevButtonState: # button state changed?
prevButtonState = buttons
if sum(buttons) > 0: # state changed to a new click
# check if the mouse was inside our 'clickable' objects
gotValidClick = False
for obj in [english, portugues]:
if obj.contains(mouse):
gotValidClick = True
mouse.clicked_name.append(obj.name)
if gotValidClick: # abort routine on response
continueRoutine = False
# *english* updates
if english.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
english.frameNStart = frameN # exact frame index
english.tStart = t # local t and not account for scr refresh
english.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(english, 'tStartRefresh') # time at next scr refresh
english.setAutoDraw(True)
# *portugues* updates
if portugues.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
portugues.frameNStart = frameN # exact frame index
portugues.tStart = t # local t and not account for scr refresh
portugues.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(portugues, 'tStartRefresh') # time at next scr refresh
portugues.setAutoDraw(True)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in languageComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "language"-------
for thisComponent in languageComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# store data for thisExp (ExperimentHandler)
x, y = mouse.getPos()
buttons = mouse.getPressed()
if sum(buttons):
# check if the mouse was inside our 'clickable' objects
gotValidClick = False
for obj in [english, portugues]:
if obj.contains(mouse):
gotValidClick = True
mouse.clicked_name.append(obj.name)
thisExp.addData('mouse.x', x)
thisExp.addData('mouse.y', y)
thisExp.addData('mouse.leftButton', buttons[0])
thisExp.addData('mouse.midButton', buttons[1])
thisExp.addData('mouse.rightButton', buttons[2])
if len(mouse.clicked_name):
thisExp.addData('mouse.clicked_name', mouse.clicked_name[0])
thisExp.nextEntry()
# the Routine "language" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
# ------Prepare to start Routine "tela_inicial"-------
# update component parameters for each repeat
screens = ([],[],[],[],[],[],[]) # create a tuple of empty lists
texts = ['','','','','','',''] # create a list of empty strings
if mouse.clicked_name[0] == 'portugues':
language_file = 'languages/pt-br'
elif mouse.clicked_name[0] == 'english':
language_file = 'languages/en'
with open(language_file) as g: # open translation file
for element in screens:
for line in g: # iterates over the lines in language file
if line != '#\n': # checks for the # separator
element.append(line) # insert the line into the list in tuple
else:
break # pass when # is found
cont = 0
for element in screens:
texts[cont] = ''.join(element) # concatenates the list elements into a string
cont += 1
texto_tela_inicial.setText(texts[0])
key_resp_ti.keys = []
key_resp_ti.rt = []
# keep track of which components have finished
tela_inicialComponents = [texto_tela_inicial, key_resp_ti]
for thisComponent in tela_inicialComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
tela_inicialClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "tela_inicial"-------
while continueRoutine:
# get current time
t = tela_inicialClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=tela_inicialClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *texto_tela_inicial* updates
if texto_tela_inicial.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
texto_tela_inicial.frameNStart = frameN # exact frame index
texto_tela_inicial.tStart = t # local t and not account for scr refresh
texto_tela_inicial.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(texto_tela_inicial, 'tStartRefresh') # time at next scr refresh
texto_tela_inicial.setAutoDraw(True)
# *key_resp_ti* updates
waitOnFlip = False
if key_resp_ti.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
key_resp_ti.frameNStart = frameN # exact frame index
key_resp_ti.tStart = t # local t and not account for scr refresh
key_resp_ti.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(key_resp_ti, 'tStartRefresh') # time at next scr refresh
key_resp_ti.status = STARTED
# keyboard checking is just starting
win.callOnFlip(key_resp_ti.clearEvents, eventType='keyboard') # clear events on next screen flip
if key_resp_ti.status == STARTED and not waitOnFlip:
theseKeys = key_resp_ti.getKeys(keyList=['space'], waitRelease=False)
if len(theseKeys):
theseKeys = theseKeys[0] # at least one key was pressed
# check for quit:
if "escape" == theseKeys:
endExpNow = True
# a response ends the routine
continueRoutine = False
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in tela_inicialComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "tela_inicial"-------
for thisComponent in tela_inicialComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# the Routine "tela_inicial" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
# ------Prepare to start Routine "instrucao_resposta"-------
# update component parameters for each repeat
text_ir.setText(texts[1])
key_resp.keys = []
key_resp.rt = []
# keep track of which components have finished
instrucao_respostaComponents = [text_ir, key_resp]
for thisComponent in instrucao_respostaComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
instrucao_respostaClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "instrucao_resposta"-------
while continueRoutine:
# get current time
t = instrucao_respostaClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=instrucao_respostaClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_ir* updates
if text_ir.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_ir.frameNStart = frameN # exact frame index
text_ir.tStart = t # local t and not account for scr refresh
text_ir.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_ir, 'tStartRefresh') # time at next scr refresh
text_ir.setAutoDraw(True)
# *key_resp* updates
waitOnFlip = False
if key_resp.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
key_resp.frameNStart = frameN # exact frame index
key_resp.tStart = t # local t and not account for scr refresh
key_resp.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(key_resp, 'tStartRefresh') # time at next scr refresh
key_resp.status = STARTED
# keyboard checking is just starting
win.callOnFlip(key_resp.clearEvents, eventType='keyboard') # clear events on next screen flip
if key_resp.status == STARTED and not waitOnFlip:
theseKeys = key_resp.getKeys(keyList=['space'], waitRelease=False)
if len(theseKeys):
theseKeys = theseKeys[0] # at least one key was pressed
# check for quit:
if "escape" == theseKeys:
endExpNow = True
# a response ends the routine
continueRoutine = False
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in instrucao_respostaComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "instrucao_resposta"-------
for thisComponent in instrucao_respostaComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# the Routine "instrucao_resposta" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
# ------Prepare to start Routine "instrucao_inicio"-------
# update component parameters for each repeat
text_ii.setText(texts[2])
key_resp_ii.keys = []
key_resp_ii.rt = []
# keep track of which components have finished
instrucao_inicioComponents = [text_ii, key_resp_ii]
for thisComponent in instrucao_inicioComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
instrucao_inicioClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "instrucao_inicio"-------
while continueRoutine:
# get current time
t = instrucao_inicioClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=instrucao_inicioClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_ii* updates
if text_ii.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_ii.frameNStart = frameN # exact frame index
text_ii.tStart = t # local t and not account for scr refresh
text_ii.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_ii, 'tStartRefresh') # time at next scr refresh
text_ii.setAutoDraw(True)
# *key_resp_ii* updates
waitOnFlip = False
if key_resp_ii.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
key_resp_ii.frameNStart = frameN # exact frame index
key_resp_ii.tStart = t # local t and not account for scr refresh
key_resp_ii.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(key_resp_ii, 'tStartRefresh') # time at next scr refresh
key_resp_ii.status = STARTED
# keyboard checking is just starting
win.callOnFlip(key_resp_ii.clearEvents, eventType='keyboard') # clear events on next screen flip
if key_resp_ii.status == STARTED and not waitOnFlip:
theseKeys = key_resp_ii.getKeys(keyList=['space'], waitRelease=False)
if len(theseKeys):
theseKeys = theseKeys[0] # at least one key was pressed
# check for quit:
if "escape" == theseKeys:
endExpNow = True
# a response ends the routine
continueRoutine = False
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in instrucao_inicioComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "instrucao_inicio"-------
for thisComponent in instrucao_inicioComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# the Routine "instrucao_inicio" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
# ------Prepare to start Routine "reset"-------
routineTimer.add(15.000000)
# update component parameters for each repeat
# keep track of which components have finished
resetComponents = [text_3]
for thisComponent in resetComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
resetClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "reset"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = resetClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=resetClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
i = 0
texto = texts[3][:-1] + " %i" %(bloco)
# *text_3* updates
if text_3.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_3.frameNStart = frameN # exact frame index
text_3.tStart = t # local t and not account for scr refresh
text_3.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_3, 'tStartRefresh') # time at next scr refresh
text_3.setAutoDraw(True)
if text_3.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_3.tStartRefresh + 15-frameTolerance:
# keep track of stop time/frame for later
text_3.tStop = t # not accounting for scr refresh
text_3.frameNStop = frameN # exact frame index
win.timeOnFlip(text_3, 'tStopRefresh') # time at next scr refresh
text_3.setAutoDraw(False)
if text_3.status == STARTED: # only update if drawing
text_3.setText(texto, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in resetComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "reset"-------
for thisComponent in resetComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
bloco = bloco + 1
# set up handler to look after randomisation of conditions etc
trials_4 = data.TrialHandler(nReps=40, method='random',
extraInfo=expInfo, originPath=-1,
trialList=[None],
seed=None, name='trials_4')
thisExp.addLoop(trials_4) # add the loop to the experiment
thisTrial_4 = trials_4.trialList[0] # so we can initialise stimuli with some values
# abbreviate parameter names if possible (e.g. rgb = thisTrial_4.rgb)
if thisTrial_4 != None:
for paramName in thisTrial_4:
exec('{} = thisTrial_4[paramName]'.format(paramName))
for thisTrial_4 in trials_4:
currentLoop = trials_4
# abbreviate parameter names if possible (e.g. rgb = thisTrial_4.rgb)
if thisTrial_4 != None:
for paramName in thisTrial_4:
exec('{} = thisTrial_4[paramName]'.format(paramName))
# ------Prepare to start Routine "fixate"-------
routineTimer.add(0.500000)
# update component parameters for each repeat
# keep track of which components have finished
fixateComponents = [text]
for thisComponent in fixateComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
fixateClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "fixate"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = fixateClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=fixateClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text* updates
if text.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text.frameNStart = frameN # exact frame index
text.tStart = t # local t and not account for scr refresh
text.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text, 'tStartRefresh') # time at next scr refresh
text.setAutoDraw(True)
if text.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text.tStartRefresh + 0.5-frameTolerance:
# keep track of stop time/frame for later
text.tStop = t # not accounting for scr refresh
text.frameNStop = frameN # exact frame index
win.timeOnFlip(text, 'tStopRefresh') # time at next scr refresh
text.setAutoDraw(False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in fixateComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "fixate"-------
for thisComponent in fixateComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "case_test_0"-------
routineTimer.add(0.200000)
# update component parameters for each repeat
# keep track of which components have finished
case_test_0Components = [image_4]
for thisComponent in case_test_0Components:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
case_test_0Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "case_test_0"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = case_test_0Clock.getTime()
tThisFlip = win.getFutureFlipTime(clock=case_test_0Clock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
if et[i] == 1:
file = caminho + 'f' + str(ft[i]) + '.jpg'
else:
file = caminho + 'd' +str(dt[i]) + '.jpg'
# *image_4* updates
if image_4.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
image_4.frameNStart = frameN # exact frame index
image_4.tStart = t # local t and not account for scr refresh
image_4.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(image_4, 'tStartRefresh') # time at next scr refresh
image_4.setAutoDraw(True)
if image_4.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > image_4.tStartRefresh + 0.2-frameTolerance:
# keep track of stop time/frame for later
image_4.tStop = t # not accounting for scr refresh
image_4.frameNStop = frameN # exact frame index
win.timeOnFlip(image_4, 'tStopRefresh') # time at next scr refresh
image_4.setAutoDraw(False)
if image_4.status == STARTED: # only update if drawing
image_4.setImage(file, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in case_test_0Components:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "case_test_0"-------
for thisComponent in case_test_0Components:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "inter_time"-------
routineTimer.add(0.300000)
# update component parameters for each repeat
# keep track of which components have finished
inter_timeComponents = [text_it]
for thisComponent in inter_timeComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
inter_timeClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "inter_time"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = inter_timeClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=inter_timeClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_it* updates
if text_it.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_it.frameNStart = frameN # exact frame index
text_it.tStart = t # local t and not account for scr refresh
text_it.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_it, 'tStartRefresh') # time at next scr refresh
text_it.setAutoDraw(True)
if text_it.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_it.tStartRefresh + 0.3-frameTolerance:
# keep track of stop time/frame for later
text_it.tStop = t # not accounting for scr refresh
text_it.frameNStop = frameN # exact frame index
win.timeOnFlip(text_it, 'tStopRefresh') # time at next scr refresh
text_it.setAutoDraw(False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in inter_timeComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "inter_time"-------
for thisComponent in inter_timeComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "case_test_1"-------
routineTimer.add(0.200000)
# update component parameters for each repeat
# keep track of which components have finished
case_test_1Components = [image_5]
for thisComponent in case_test_1Components:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
case_test_1Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "case_test_1"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = case_test_1Clock.getTime()
tThisFlip = win.getFutureFlipTime(clock=case_test_1Clock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
if et[i] == 2:
file = caminho + 'f' + str(ft[i]) + '.jpg'
else:
file = caminho + 'd' + str(dt[i]) + '.jpg'
# *image_5* updates
if image_5.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
image_5.frameNStart = frameN # exact frame index
image_5.tStart = t # local t and not account for scr refresh
image_5.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(image_5, 'tStartRefresh') # time at next scr refresh
image_5.setAutoDraw(True)
if image_5.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > image_5.tStartRefresh + 0.2-frameTolerance:
# keep track of stop time/frame for later
image_5.tStop = t # not accounting for scr refresh
image_5.frameNStop = frameN # exact frame index
win.timeOnFlip(image_5, 'tStopRefresh') # time at next scr refresh
image_5.setAutoDraw(False)
if image_5.status == STARTED: # only update if drawing
image_5.setImage(file, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in case_test_1Components:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "case_test_1"-------
for thisComponent in case_test_1Components:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
i = i + 1
# ------Prepare to start Routine "resposta_test"-------
routineTimer.add(2.000000)
# update component parameters for each repeat
text_6.setText(texts[4])
key_resp_4.keys = []
key_resp_4.rt = []
# keep track of which components have finished
resposta_testComponents = [text_6, key_resp_4]
for thisComponent in resposta_testComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
resposta_testClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "resposta_test"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = resposta_testClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=resposta_testClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_6* updates
if text_6.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_6.frameNStart = frameN # exact frame index
text_6.tStart = t # local t and not account for scr refresh
text_6.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_6, 'tStartRefresh') # time at next scr refresh
text_6.setAutoDraw(True)
if text_6.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_6.tStartRefresh + 2-frameTolerance:
# keep track of stop time/frame for later
text_6.tStop = t # not accounting for scr refresh
text_6.frameNStop = frameN # exact frame index
win.timeOnFlip(text_6, 'tStopRefresh') # time at next scr refresh
text_6.setAutoDraw(False)
# *key_resp_4* updates
waitOnFlip = False
if key_resp_4.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
key_resp_4.frameNStart = frameN # exact frame index
key_resp_4.tStart = t # local t and not account for scr refresh
key_resp_4.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(key_resp_4, 'tStartRefresh') # time at next scr refresh
key_resp_4.status = STARTED
# keyboard checking is just starting
waitOnFlip = True
win.callOnFlip(key_resp_4.clock.reset) # t=0 on next screen flip
win.callOnFlip(key_resp_4.clearEvents, eventType='keyboard') # clear events on next screen flip
if key_resp_4.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > key_resp_4.tStartRefresh + 2-frameTolerance:
# keep track of stop time/frame for later
key_resp_4.tStop = t # not accounting for scr refresh
key_resp_4.frameNStop = frameN # exact frame index
win.timeOnFlip(key_resp_4, 'tStopRefresh') # time at next scr refresh
key_resp_4.status = FINISHED
if key_resp_4.status == STARTED and not waitOnFlip:
theseKeys = key_resp_4.getKeys(keyList=['1', '2'], waitRelease=False)
if len(theseKeys):
theseKeys = theseKeys[0] # at least one key was pressed
# check for quit:
if "escape" == theseKeys:
endExpNow = True
key_resp_4.keys = theseKeys.name # just the last key pressed
key_resp_4.rt = theseKeys.rt
# was this 'correct'?
if (key_resp_4.keys == str(et[i-1])) or (key_resp_4.keys == et[i-1]):
key_resp_4.corr = 1
else:
key_resp_4.corr = 0
# a response ends the routine
continueRoutine = False
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in resposta_testComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "resposta_test"-------
for thisComponent in resposta_testComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# check responses
if key_resp_4.keys in ['', [], None]: # No response was made
key_resp_4.keys = None
# was no response the correct answer?!
if str(et[i-1]).lower() == 'none':
key_resp_4.corr = 1; # correct non-response
else:
key_resp_4.corr = 0; # failed to respond (incorrectly)
# store data for trials_4 (TrialHandler)
trials_4.addData('key_resp_4.keys',key_resp_4.keys)
trials_4.addData('key_resp_4.corr', key_resp_4.corr)
if key_resp_4.keys != None: # we had a response
trials_4.addData('key_resp_4.rt', key_resp_4.rt)
# ------Prepare to start Routine "confianca"-------
# update component parameters for each repeat
text_2.setText(texts[5])
rating.reset()
# keep track of which components have finished
confiancaComponents = [text_2, rating]
for thisComponent in confiancaComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
confiancaClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "confianca"-------
while continueRoutine:
# get current time
t = confiancaClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=confiancaClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_2* updates
if text_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_2.frameNStart = frameN # exact frame index
text_2.tStart = t # local t and not account for scr refresh
text_2.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_2, 'tStartRefresh') # time at next scr refresh
text_2.setAutoDraw(True)
# *rating* updates
if rating.status == NOT_STARTED and t >= 0.0-frameTolerance:
# keep track of start time/frame for later
rating.frameNStart = frameN # exact frame index
rating.tStart = t # local t and not account for scr refresh
rating.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(rating, 'tStartRefresh') # time at next scr refresh
rating.setAutoDraw(True)
continueRoutine &= rating.noResponse # a response ends the trial
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in confiancaComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "confianca"-------
for thisComponent in confiancaComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# store data for trials_4 (TrialHandler)
trials_4.addData('rating.response', rating.getRating())
# the Routine "confianca" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
thisExp.nextEntry()
# completed 40 repeats of 'trials_4'
# set up handler to look after randomisation of conditions etc
trials_3 = data.TrialHandler(nReps=2, method='random',
extraInfo=expInfo, originPath=-1,
trialList=[None],
seed=None, name='trials_3')
thisExp.addLoop(trials_3) # add the loop to the experiment
thisTrial_3 = trials_3.trialList[0] # so we can initialise stimuli with some values
# abbreviate parameter names if possible (e.g. rgb = thisTrial_3.rgb)
if thisTrial_3 != None:
for paramName in thisTrial_3:
exec('{} = thisTrial_3[paramName]'.format(paramName))
for thisTrial_3 in trials_3:
currentLoop = trials_3
# abbreviate parameter names if possible (e.g. rgb = thisTrial_3.rgb)
if thisTrial_3 != None:
for paramName in thisTrial_3:
exec('{} = thisTrial_3[paramName]'.format(paramName))
# ------Prepare to start Routine "reset"-------
routineTimer.add(15.000000)
# update component parameters for each repeat
# keep track of which components have finished
resetComponents = [text_3]
for thisComponent in resetComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
resetClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "reset"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = resetClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=resetClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
i = 0
texto = texts[3][:-1] + " %i" %(bloco)
# *text_3* updates
if text_3.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_3.frameNStart = frameN # exact frame index
text_3.tStart = t # local t and not account for scr refresh
text_3.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_3, 'tStartRefresh') # time at next scr refresh
text_3.setAutoDraw(True)
if text_3.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_3.tStartRefresh + 15-frameTolerance:
# keep track of stop time/frame for later
text_3.tStop = t # not accounting for scr refresh
text_3.frameNStop = frameN # exact frame index
win.timeOnFlip(text_3, 'tStopRefresh') # time at next scr refresh
text_3.setAutoDraw(False)
if text_3.status == STARTED: # only update if drawing
text_3.setText(texto, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in resetComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "reset"-------
for thisComponent in resetComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
bloco = bloco + 1
# set up handler to look after randomisation of conditions etc
trials = data.TrialHandler(nReps=40, method='random',
extraInfo=expInfo, originPath=-1,
trialList=[None],
seed=None, name='trials')
thisExp.addLoop(trials) # add the loop to the experiment
thisTrial = trials.trialList[0] # so we can initialise stimuli with some values
# abbreviate parameter names if possible (e.g. rgb = thisTrial.rgb)
if thisTrial != None:
for paramName in thisTrial:
exec('{} = thisTrial[paramName]'.format(paramName))
for thisTrial in trials:
currentLoop = trials
# abbreviate parameter names if possible (e.g. rgb = thisTrial.rgb)
if thisTrial != None:
for paramName in thisTrial:
exec('{} = thisTrial[paramName]'.format(paramName))
# ------Prepare to start Routine "fixate"-------
routineTimer.add(0.500000)
# update component parameters for each repeat
# keep track of which components have finished
fixateComponents = [text]
for thisComponent in fixateComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
fixateClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "fixate"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = fixateClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=fixateClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text* updates
if text.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text.frameNStart = frameN # exact frame index
text.tStart = t # local t and not account for scr refresh
text.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text, 'tStartRefresh') # time at next scr refresh
text.setAutoDraw(True)
if text.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text.tStartRefresh + 0.5-frameTolerance:
# keep track of stop time/frame for later
text.tStop = t # not accounting for scr refresh
text.frameNStop = frameN # exact frame index
win.timeOnFlip(text, 'tStopRefresh') # time at next scr refresh
text.setAutoDraw(False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in fixateComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "fixate"-------
for thisComponent in fixateComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "case_1"-------
routineTimer.add(0.200000)
# update component parameters for each repeat
# keep track of which components have finished
case_1Components = [image_1]
for thisComponent in case_1Components:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
case_1Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "case_1"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = case_1Clock.getTime()
tThisFlip = win.getFutureFlipTime(clock=case_1Clock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
if e[i] == 1:
file = caminho + 'f' + str(f[i]) + '.jpg'
else:
file = caminho + 'd' +str(d[i]) + '.jpg'
# *image_1* updates
if image_1.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
image_1.frameNStart = frameN # exact frame index
image_1.tStart = t # local t and not account for scr refresh
image_1.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(image_1, 'tStartRefresh') # time at next scr refresh
image_1.setAutoDraw(True)
if image_1.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > image_1.tStartRefresh + 0.2-frameTolerance:
# keep track of stop time/frame for later
image_1.tStop = t # not accounting for scr refresh
image_1.frameNStop = frameN # exact frame index
win.timeOnFlip(image_1, 'tStopRefresh') # time at next scr refresh
image_1.setAutoDraw(False)
if image_1.status == STARTED: # only update if drawing
image_1.setImage(file, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in case_1Components:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "case_1"-------
for thisComponent in case_1Components:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "inter_time"-------
routineTimer.add(0.300000)
# update component parameters for each repeat
# keep track of which components have finished
inter_timeComponents = [text_it]
for thisComponent in inter_timeComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
inter_timeClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "inter_time"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = inter_timeClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=inter_timeClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_it* updates
if text_it.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_it.frameNStart = frameN # exact frame index
text_it.tStart = t # local t and not account for scr refresh
text_it.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_it, 'tStartRefresh') # time at next scr refresh
text_it.setAutoDraw(True)
if text_it.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_it.tStartRefresh + 0.3-frameTolerance:
# keep track of stop time/frame for later
text_it.tStop = t # not accounting for scr refresh
text_it.frameNStop = frameN # exact frame index
win.timeOnFlip(text_it, 'tStopRefresh') # time at next scr refresh
text_it.setAutoDraw(False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in inter_timeComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "inter_time"-------
for thisComponent in inter_timeComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "case_2"-------
routineTimer.add(0.200000)
# update component parameters for each repeat
# keep track of which components have finished
case_2Components = [image_2]
for thisComponent in case_2Components:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
case_2Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "case_2"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = case_2Clock.getTime()
tThisFlip = win.getFutureFlipTime(clock=case_2Clock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
if e[i] == 2:
file = caminho + 'f' + str(f[i]) + '.jpg'
else:
file = caminho + 'd' + str(d[i]) + '.jpg'
# *image_2* updates
if image_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
image_2.frameNStart = frameN # exact frame index
image_2.tStart = t # local t and not account for scr refresh
image_2.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(image_2, 'tStartRefresh') # time at next scr refresh
image_2.setAutoDraw(True)
if image_2.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > image_2.tStartRefresh + 0.2-frameTolerance:
# keep track of stop time/frame for later
image_2.tStop = t # not accounting for scr refresh
image_2.frameNStop = frameN # exact frame index
win.timeOnFlip(image_2, 'tStopRefresh') # time at next scr refresh
image_2.setAutoDraw(False)
if image_2.status == STARTED: # only update if drawing
image_2.setImage(file, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in case_2Components:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "case_2"-------
for thisComponent in case_2Components:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
i = i + 1
# ------Prepare to start Routine "resposta"-------
routineTimer.add(2.000000)
# update component parameters for each repeat
text_4.setText(texts[4])
key_resp_2.keys = []
key_resp_2.rt = []
# keep track of which components have finished
respostaComponents = [text_4, key_resp_2]
for thisComponent in respostaComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
respostaClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "resposta"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = respostaClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=respostaClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_4* updates
if text_4.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_4.frameNStart = frameN # exact frame index
text_4.tStart = t # local t and not account for scr refresh
text_4.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_4, 'tStartRefresh') # time at next scr refresh
text_4.setAutoDraw(True)
if text_4.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_4.tStartRefresh + 2-frameTolerance:
# keep track of stop time/frame for later
text_4.tStop = t # not accounting for scr refresh
text_4.frameNStop = frameN # exact frame index
win.timeOnFlip(text_4, 'tStopRefresh') # time at next scr refresh
text_4.setAutoDraw(False)
# *key_resp_2* updates
waitOnFlip = False
if key_resp_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
key_resp_2.frameNStart = frameN # exact frame index
key_resp_2.tStart = t # local t and not account for scr refresh
key_resp_2.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(key_resp_2, 'tStartRefresh') # time at next scr refresh
key_resp_2.status = STARTED
# keyboard checking is just starting
waitOnFlip = True
win.callOnFlip(key_resp_2.clock.reset) # t=0 on next screen flip
win.callOnFlip(key_resp_2.clearEvents, eventType='keyboard') # clear events on next screen flip
if key_resp_2.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > key_resp_2.tStartRefresh + 2-frameTolerance:
# keep track of stop time/frame for later
key_resp_2.tStop = t # not accounting for scr refresh
key_resp_2.frameNStop = frameN # exact frame index
win.timeOnFlip(key_resp_2, 'tStopRefresh') # time at next scr refresh
key_resp_2.status = FINISHED
if key_resp_2.status == STARTED and not waitOnFlip:
theseKeys = key_resp_2.getKeys(keyList=['1', '2'], waitRelease=False)
if len(theseKeys):
theseKeys = theseKeys[0] # at least one key was pressed
# check for quit:
if "escape" == theseKeys:
endExpNow = True
key_resp_2.keys = theseKeys.name # just the last key pressed
key_resp_2.rt = theseKeys.rt
# was this 'correct'?
if (key_resp_2.keys == str(e[i-1])) or (key_resp_2.keys == e[i-1]):
key_resp_2.corr = 1
else:
key_resp_2.corr = 0
# a response ends the routine
continueRoutine = False
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in respostaComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "resposta"-------
for thisComponent in respostaComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# check responses
if key_resp_2.keys in ['', [], None]: # No response was made
key_resp_2.keys = None
# was no response the correct answer?!
if str(e[i-1]).lower() == 'none':
key_resp_2.corr = 1; # correct non-response
else:
key_resp_2.corr = 0; # failed to respond (incorrectly)
# store data for trials (TrialHandler)
trials.addData('key_resp_2.keys',key_resp_2.keys)
trials.addData('key_resp_2.corr', key_resp_2.corr)
if key_resp_2.keys != None: # we had a response
trials.addData('key_resp_2.rt', key_resp_2.rt)
# ------Prepare to start Routine "confianca"-------
# update component parameters for each repeat
text_2.setText(texts[5])
rating.reset()
# keep track of which components have finished
confiancaComponents = [text_2, rating]
for thisComponent in confiancaComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
confiancaClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "confianca"-------
while continueRoutine:
# get current time
t = confiancaClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=confiancaClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_2* updates
if text_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_2.frameNStart = frameN # exact frame index
text_2.tStart = t # local t and not account for scr refresh
text_2.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_2, 'tStartRefresh') # time at next scr refresh
text_2.setAutoDraw(True)
# *rating* updates
if rating.status == NOT_STARTED and t >= 0.0-frameTolerance:
# keep track of start time/frame for later
rating.frameNStart = frameN # exact frame index
rating.tStart = t # local t and not account for scr refresh
rating.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(rating, 'tStartRefresh') # time at next scr refresh
rating.setAutoDraw(True)
continueRoutine &= rating.noResponse # a response ends the trial
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in confiancaComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "confianca"-------
for thisComponent in confiancaComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# store data for trials (TrialHandler)
trials.addData('rating.response', rating.getRating())
# the Routine "confianca" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
thisExp.nextEntry()
# completed 40 repeats of 'trials'
# ------Prepare to start Routine "reset"-------
routineTimer.add(15.000000)
# update component parameters for each repeat
# keep track of which components have finished
resetComponents = [text_3]
for thisComponent in resetComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
resetClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "reset"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = resetClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=resetClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
i = 0
texto = texts[3][:-1] + " %i" %(bloco)
# *text_3* updates
if text_3.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_3.frameNStart = frameN # exact frame index
text_3.tStart = t # local t and not account for scr refresh
text_3.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_3, 'tStartRefresh') # time at next scr refresh
text_3.setAutoDraw(True)
if text_3.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_3.tStartRefresh + 15-frameTolerance:
# keep track of stop time/frame for later
text_3.tStop = t # not accounting for scr refresh
text_3.frameNStop = frameN # exact frame index
win.timeOnFlip(text_3, 'tStopRefresh') # time at next scr refresh
text_3.setAutoDraw(False)
if text_3.status == STARTED: # only update if drawing
text_3.setText(texto, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in resetComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "reset"-------
for thisComponent in resetComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
bloco = bloco + 1
# set up handler to look after randomisation of conditions etc
trials_2 = data.TrialHandler(nReps=40, method='random',
extraInfo=expInfo, originPath=-1,
trialList=[None],
seed=None, name='trials_2')
thisExp.addLoop(trials_2) # add the loop to the experiment
thisTrial_2 = trials_2.trialList[0] # so we can initialise stimuli with some values
# abbreviate parameter names if possible (e.g. rgb = thisTrial_2.rgb)
if thisTrial_2 != None:
for paramName in thisTrial_2:
exec('{} = thisTrial_2[paramName]'.format(paramName))
for thisTrial_2 in trials_2:
currentLoop = trials_2
# abbreviate parameter names if possible (e.g. rgb = thisTrial_2.rgb)
if thisTrial_2 != None:
for paramName in thisTrial_2:
exec('{} = thisTrial_2[paramName]'.format(paramName))
# ------Prepare to start Routine "fixate"-------
routineTimer.add(0.500000)
# update component parameters for each repeat
# keep track of which components have finished
fixateComponents = [text]
for thisComponent in fixateComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
fixateClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "fixate"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = fixateClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=fixateClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text* updates
if text.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text.frameNStart = frameN # exact frame index
text.tStart = t # local t and not account for scr refresh
text.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text, 'tStartRefresh') # time at next scr refresh
text.setAutoDraw(True)
if text.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text.tStartRefresh + 0.5-frameTolerance:
# keep track of stop time/frame for later
text.tStop = t # not accounting for scr refresh
text.frameNStop = frameN # exact frame index
win.timeOnFlip(text, 'tStopRefresh') # time at next scr refresh
text.setAutoDraw(False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in fixateComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "fixate"-------
for thisComponent in fixateComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "case_3"-------
routineTimer.add(0.200000)
# update component parameters for each repeat
# keep track of which components have finished
case_3Components = [image]
for thisComponent in case_3Components:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
case_3Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "case_3"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = case_3Clock.getTime()
tThisFlip = win.getFutureFlipTime(clock=case_3Clock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
if ee[i] == 1:
file = caminho + 'f' + str(ff[i]) + '.jpg'
else:
file = caminho + 'd' +str(dd[i]) + '.jpg'
# *image* updates
if image.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
image.frameNStart = frameN # exact frame index
image.tStart = t # local t and not account for scr refresh
image.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(image, 'tStartRefresh') # time at next scr refresh
image.setAutoDraw(True)
if image.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > image.tStartRefresh + 0.2-frameTolerance:
# keep track of stop time/frame for later
image.tStop = t # not accounting for scr refresh
image.frameNStop = frameN # exact frame index
win.timeOnFlip(image, 'tStopRefresh') # time at next scr refresh
image.setAutoDraw(False)
if image.status == STARTED: # only update if drawing
image.setImage(file, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in case_3Components:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "case_3"-------
for thisComponent in case_3Components:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "inter_time"-------
routineTimer.add(0.300000)
# update component parameters for each repeat
# keep track of which components have finished
inter_timeComponents = [text_it]
for thisComponent in inter_timeComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
inter_timeClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "inter_time"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = inter_timeClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=inter_timeClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_it* updates
if text_it.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_it.frameNStart = frameN # exact frame index
text_it.tStart = t # local t and not account for scr refresh
text_it.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_it, 'tStartRefresh') # time at next scr refresh
text_it.setAutoDraw(True)
if text_it.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_it.tStartRefresh + 0.3-frameTolerance:
# keep track of stop time/frame for later
text_it.tStop = t # not accounting for scr refresh
text_it.frameNStop = frameN # exact frame index
win.timeOnFlip(text_it, 'tStopRefresh') # time at next scr refresh
text_it.setAutoDraw(False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in inter_timeComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "inter_time"-------
for thisComponent in inter_timeComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# ------Prepare to start Routine "case_4"-------
routineTimer.add(0.200000)
# update component parameters for each repeat
# keep track of which components have finished
case_4Components = [image_3]
for thisComponent in case_4Components:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
case_4Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "case_4"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = case_4Clock.getTime()
tThisFlip = win.getFutureFlipTime(clock=case_4Clock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
if ee[i] == 2:
file = caminho + 'f' + str(ff[i]) + '.jpg'
else:
file = caminho + 'd' + str(dd[i]) + '.jpg'
# *image_3* updates
if image_3.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
image_3.frameNStart = frameN # exact frame index
image_3.tStart = t # local t and not account for scr refresh
image_3.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(image_3, 'tStartRefresh') # time at next scr refresh
image_3.setAutoDraw(True)
if image_3.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > image_3.tStartRefresh + 0.2-frameTolerance:
# keep track of stop time/frame for later
image_3.tStop = t # not accounting for scr refresh
image_3.frameNStop = frameN # exact frame index
win.timeOnFlip(image_3, 'tStopRefresh') # time at next scr refresh
image_3.setAutoDraw(False)
if image_3.status == STARTED: # only update if drawing
image_3.setImage(file, log=False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in case_4Components:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "case_4"-------
for thisComponent in case_4Components:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
i = i + 1
# ------Prepare to start Routine "resposta_2"-------
routineTimer.add(2.000000)
# update component parameters for each repeat
text_resposta_2.setText(texts[4])
key_resp_3.keys = []
key_resp_3.rt = []
# keep track of which components have finished
resposta_2Components = [text_resposta_2, key_resp_3]
for thisComponent in resposta_2Components:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
resposta_2Clock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "resposta_2"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = resposta_2Clock.getTime()
tThisFlip = win.getFutureFlipTime(clock=resposta_2Clock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_resposta_2* updates
if text_resposta_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_resposta_2.frameNStart = frameN # exact frame index
text_resposta_2.tStart = t # local t and not account for scr refresh
text_resposta_2.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_resposta_2, 'tStartRefresh') # time at next scr refresh
text_resposta_2.setAutoDraw(True)
if text_resposta_2.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_resposta_2.tStartRefresh + 2-frameTolerance:
# keep track of stop time/frame for later
text_resposta_2.tStop = t # not accounting for scr refresh
text_resposta_2.frameNStop = frameN # exact frame index
win.timeOnFlip(text_resposta_2, 'tStopRefresh') # time at next scr refresh
text_resposta_2.setAutoDraw(False)
# *key_resp_3* updates
waitOnFlip = False
if key_resp_3.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
key_resp_3.frameNStart = frameN # exact frame index
key_resp_3.tStart = t # local t and not account for scr refresh
key_resp_3.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(key_resp_3, 'tStartRefresh') # time at next scr refresh
key_resp_3.status = STARTED
# keyboard checking is just starting
waitOnFlip = True
win.callOnFlip(key_resp_3.clock.reset) # t=0 on next screen flip
win.callOnFlip(key_resp_3.clearEvents, eventType='keyboard') # clear events on next screen flip
if key_resp_3.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > key_resp_3.tStartRefresh + 2-frameTolerance:
# keep track of stop time/frame for later
key_resp_3.tStop = t # not accounting for scr refresh
key_resp_3.frameNStop = frameN # exact frame index
win.timeOnFlip(key_resp_3, 'tStopRefresh') # time at next scr refresh
key_resp_3.status = FINISHED
if key_resp_3.status == STARTED and not waitOnFlip:
theseKeys = key_resp_3.getKeys(keyList=['1', '2'], waitRelease=False)
if len(theseKeys):
theseKeys = theseKeys[0] # at least one key was pressed
# check for quit:
if "escape" == theseKeys:
endExpNow = True
key_resp_3.keys = theseKeys.name # just the last key pressed
key_resp_3.rt = theseKeys.rt
# was this 'correct'?
if (key_resp_3.keys == str(ee[i-1])) or (key_resp_3.keys == ee[i-1]):
key_resp_3.corr = 1
else:
key_resp_3.corr = 0
# a response ends the routine
continueRoutine = False
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in resposta_2Components:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "resposta_2"-------
for thisComponent in resposta_2Components:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# check responses
if key_resp_3.keys in ['', [], None]: # No response was made
key_resp_3.keys = None
# was no response the correct answer?!
if str(ee[i-1]).lower() == 'none':
key_resp_3.corr = 1; # correct non-response
else:
key_resp_3.corr = 0; # failed to respond (incorrectly)
# store data for trials_2 (TrialHandler)
trials_2.addData('key_resp_3.keys',key_resp_3.keys)
trials_2.addData('key_resp_3.corr', key_resp_3.corr)
if key_resp_3.keys != None: # we had a response
trials_2.addData('key_resp_3.rt', key_resp_3.rt)
# ------Prepare to start Routine "confianca"-------
# update component parameters for each repeat
text_2.setText(texts[5])
rating.reset()
# keep track of which components have finished
confiancaComponents = [text_2, rating]
for thisComponent in confiancaComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
confiancaClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "confianca"-------
while continueRoutine:
# get current time
t = confiancaClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=confiancaClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_2* updates
if text_2.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_2.frameNStart = frameN # exact frame index
text_2.tStart = t # local t and not account for scr refresh
text_2.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_2, 'tStartRefresh') # time at next scr refresh
text_2.setAutoDraw(True)
# *rating* updates
if rating.status == NOT_STARTED and t >= 0.0-frameTolerance:
# keep track of start time/frame for later
rating.frameNStart = frameN # exact frame index
rating.tStart = t # local t and not account for scr refresh
rating.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(rating, 'tStartRefresh') # time at next scr refresh
rating.setAutoDraw(True)
continueRoutine &= rating.noResponse # a response ends the trial
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in confiancaComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "confianca"-------
for thisComponent in confiancaComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# store data for trials_2 (TrialHandler)
trials_2.addData('rating.response', rating.getRating())
# the Routine "confianca" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
thisExp.nextEntry()
# completed 40 repeats of 'trials_2'
thisExp.nextEntry()
# completed 2 repeats of 'trials_3'
# ------Prepare to start Routine "fim"-------
routineTimer.add(5.000000)
# update component parameters for each repeat
text_5.setText(texts[6])
# keep track of which components have finished
fimComponents = [text_5]
for thisComponent in fimComponents:
thisComponent.tStart = None
thisComponent.tStop = None
thisComponent.tStartRefresh = None
thisComponent.tStopRefresh = None
if hasattr(thisComponent, 'status'):
thisComponent.status = NOT_STARTED
# reset timers
t = 0
_timeToFirstFrame = win.getFutureFlipTime(clock="now")
fimClock.reset(-_timeToFirstFrame) # t0 is time of first possible flip
frameN = -1
continueRoutine = True
# -------Run Routine "fim"-------
while continueRoutine and routineTimer.getTime() > 0:
# get current time
t = fimClock.getTime()
tThisFlip = win.getFutureFlipTime(clock=fimClock)
tThisFlipGlobal = win.getFutureFlipTime(clock=None)
frameN = frameN + 1 # number of completed frames (so 0 is the first frame)
# update/draw components on each frame
# *text_5* updates
if text_5.status == NOT_STARTED and tThisFlip >= 0.0-frameTolerance:
# keep track of start time/frame for later
text_5.frameNStart = frameN # exact frame index
text_5.tStart = t # local t and not account for scr refresh
text_5.tStartRefresh = tThisFlipGlobal # on global time
win.timeOnFlip(text_5, 'tStartRefresh') # time at next scr refresh
text_5.setAutoDraw(True)
if text_5.status == STARTED:
# is it time to stop? (based on global clock, using actual start)
if tThisFlipGlobal > text_5.tStartRefresh + 5.0-frameTolerance:
# keep track of stop time/frame for later
text_5.tStop = t # not accounting for scr refresh
text_5.frameNStop = frameN # exact frame index
win.timeOnFlip(text_5, 'tStopRefresh') # time at next scr refresh
text_5.setAutoDraw(False)
# check for quit (typically the Esc key)
if endExpNow or defaultKeyboard.getKeys(keyList=["escape"]):
core.quit()
# check if all components have finished
if not continueRoutine: # a component has requested a forced-end of Routine
break
continueRoutine = False # will revert to True if at least one component still running
for thisComponent in fimComponents:
if hasattr(thisComponent, "status") and thisComponent.status != FINISHED:
continueRoutine = True
break # at least one component has not yet finished
# refresh the screen
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "fim"-------
for thisComponent in fimComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
thisExp.addData('text_5.started', text_5.tStartRefresh)
thisExp.addData('text_5.stopped', text_5.tStopRefresh)
# Flip one final time so any remaining win.callOnFlip()
# and win.timeOnFlip() tasks get executed before quitting
win.flip()
# these shouldn't be strictly necessary (should auto-save)
thisExp.saveAsWideText(filename+'.csv')
thisExp.saveAsPickle(filename)
logging.flush()
# make sure everything is closed down
thisExp.abort() # or data files will save again on exit
win.close()
core.quit()
| 45.530478
| 135
| 0.6232
| 13,729
| 118,015
| 5.28021
| 0.04516
| 0.015064
| 0.012898
| 0.020347
| 0.901879
| 0.887091
| 0.85964
| 0.827871
| 0.783328
| 0.761022
| 0
| 0.016949
| 0.29009
| 118,015
| 2,591
| 136
| 45.548051
| 0.848305
| 0.291302
| 0
| 0.708013
| 0
| 0
| 0.04071
| 0.002297
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.006037
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
cb5a74126e1ebdc965f47d068582699e0002ebd5
| 5,325
|
py
|
Python
|
envi/tests/msp430/ijumps.py
|
rnui2k/vivisect
|
b7b00f2d03defef28b4b8c912e3a8016e956c5f7
|
[
"ECL-2.0",
"Apache-2.0"
] | 716
|
2015-01-01T14:41:11.000Z
|
2022-03-28T06:51:50.000Z
|
envi/tests/msp430/ijumps.py
|
rnui2k/vivisect
|
b7b00f2d03defef28b4b8c912e3a8016e956c5f7
|
[
"ECL-2.0",
"Apache-2.0"
] | 266
|
2015-01-01T15:07:27.000Z
|
2022-03-30T15:19:26.000Z
|
envi/tests/msp430/ijumps.py
|
rnui2k/vivisect
|
b7b00f2d03defef28b4b8c912e3a8016e956c5f7
|
[
"ECL-2.0",
"Apache-2.0"
] | 159
|
2015-01-01T16:19:44.000Z
|
2022-03-21T21:55:34.000Z
|
from envi.archs.msp430.regs import *
checks = [
# JC / JHS
(
'JC #0x4410 (C=0)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "072c", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "072c", 'data': "" }
),
(
'JC #0x4410 (C=1)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 1), (SR_V, 0)], 'code': "072c", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 1), (SR_V, 0)], 'code': "072c", 'data': "" }
),
# JEQ / JZ
(
'JEQ #0x4410 (Z=0)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0724", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0724", 'data': "" }
),
(
'JEQ #0x4410 (Z=1)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 1), (SR_C, 0), (SR_V, 0)], 'code': "0724", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 0), (SR_Z, 1), (SR_C, 0), (SR_V, 0)], 'code': "0724", 'data': "" }
),
# JGE
(
'JGE #0x4410 (N=0 V=0)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0734", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0734", 'data': "" }
),
(
'JGE #0x4410 (N=1 V=1)',
{ 'regs': [], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0734", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0734", 'data': "" }
),
(
'JGE #0x4410 (N=1 V=0)',
{ 'regs': [], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0734", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0734", 'data': "" }
),
(
'JGE #0x4410 (N=0 V=1)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0734", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0734", 'data': "" }
),
# JL
(
'JL #0x4410 (N=0 V=0)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0738", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0738", 'data': "" }
),
(
'JL #0x4410 (N=1 V=1)',
{ 'regs': [], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0738", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0738", 'data': "" }
),
(
'JL #0x4410 (N=1 V=0)',
{ 'regs': [], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0738", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0738", 'data': "" }
),
(
'JL #0x4410 (N=0 V=1)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0738", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 1)], 'code': "0738", 'data': "" }
),
# JMP
(
'JMP #0x4410',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "073c", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "073c", 'data': "" }
),
# JN
(
'JN #0x4410 (N=0)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0730", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0730", 'data': "" }
),
(
'JN #0x4410 (N=1)',
{ 'regs': [], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0730", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 1), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0730", 'data': "" }
),
# JNC / JLO
(
'JNC #0x4410 (C=0)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0728", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0728", 'data': "" }
),
(
'JNC #0x4410 (C=1)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 1), (SR_V, 0)], 'code': "0728", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 1), (SR_V, 0)], 'code': "0728", 'data': "" }
),
# JNE / JNZ
(
'JNC #0x4410 (Z=0)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0720", 'data': "" },
{ 'regs': [(REG_PC, 0x4410)], 'flags': [(SR_N, 0), (SR_Z, 0), (SR_C, 0), (SR_V, 0)], 'code': "0720", 'data': "" }
),
(
'JNC #0x4410 (Z=1)',
{ 'regs': [], 'flags': [(SR_N, 0), (SR_Z, 1), (SR_C, 0), (SR_V, 0)], 'code': "0720", 'data': "" },
{ 'regs': [(REG_PC, 0x4402)], 'flags': [(SR_N, 0), (SR_Z, 1), (SR_C, 0), (SR_V, 0)], 'code': "0720", 'data': "" }
),
]
| 46.304348
| 121
| 0.388357
| 812
| 5,325
| 2.336207
| 0.050493
| 0.151819
| 0.160253
| 0.107538
| 0.938851
| 0.936215
| 0.936215
| 0.936215
| 0.933579
| 0.933579
| 0
| 0.133316
| 0.271737
| 5,325
| 114
| 122
| 46.710526
| 0.355854
| 0.009577
| 0
| 0.193878
| 0
| 0
| 0.216334
| 0
| 0
| 0
| 0.043305
| 0
| 0
| 1
| 0
| false
| 0
| 0.010204
| 0
| 0.010204
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
cbaa4bab6dea599d9bc4ad0353d8a77cc9c194f0
| 119
|
py
|
Python
|
recipe/run_test.py
|
conda-forge/django-debug-toolbar-feedstock
|
8f5d5fde27bf1568da89ef820758625794ff215c
|
[
"BSD-3-Clause"
] | null | null | null |
recipe/run_test.py
|
conda-forge/django-debug-toolbar-feedstock
|
8f5d5fde27bf1568da89ef820758625794ff215c
|
[
"BSD-3-Clause"
] | 28
|
2016-04-02T11:46:43.000Z
|
2021-12-15T23:36:09.000Z
|
recipe/run_test.py
|
conda-forge/django-debug-toolbar-feedstock
|
8f5d5fde27bf1568da89ef820758625794ff215c
|
[
"BSD-3-Clause"
] | 5
|
2016-04-02T11:46:33.000Z
|
2020-09-21T11:42:13.000Z
|
from django.conf import settings; settings.configure(DEBUG=True)
import debug_toolbar
import debug_toolbar.management
| 23.8
| 64
| 0.857143
| 16
| 119
| 6.25
| 0.625
| 0.22
| 0.36
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084034
| 119
| 4
| 65
| 29.75
| 0.917431
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
1db6e681f74db4f17d6f8bae5ab0b63b9cc62368
| 22,319
|
py
|
Python
|
tests/integration/flex_api/v1/test_configuration.py
|
timgates42/twilio-python
|
ef29d03a4857b62b616df4a8f4f2b7c294afbb99
|
[
"MIT"
] | 1
|
2020-10-29T19:28:25.000Z
|
2020-10-29T19:28:25.000Z
|
tests/integration/flex_api/v1/test_configuration.py
|
CostantiniMatteo/twilio-python
|
9eee1ca9e73790b12678e9a5660206ea44948d00
|
[
"MIT"
] | 1
|
2020-08-25T15:27:57.000Z
|
2020-08-25T15:27:57.000Z
|
tests/integration/flex_api/v1/test_configuration.py
|
CostantiniMatteo/twilio-python
|
9eee1ca9e73790b12678e9a5660206ea44948d00
|
[
"MIT"
] | 4
|
2021-03-25T09:00:08.000Z
|
2021-08-05T06:54:23.000Z
|
# coding=utf-8
r"""
This code was generated by
\ / _ _ _| _ _
| (_)\/(_)(_|\/| |(/_ v1.0.0
/ /
"""
from tests import IntegrationTestCase
from tests.holodeck import Request
from twilio.base.exceptions import TwilioException
from twilio.http.response import Response
class ConfigurationTestCase(IntegrationTestCase):
def test_fetch_request(self):
self.holodeck.mock(Response(500, ''))
with self.assertRaises(TwilioException):
self.client.flex_api.v1.configuration().fetch()
self.holodeck.assert_has_request(Request(
'get',
'https://flex-api.twilio.com/v1/Configuration',
))
def test_fetch_response(self):
self.holodeck.mock(Response(
200,
'''
{
"account_sid": "ACaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"date_created": "2016-08-01T22:10:40Z",
"date_updated": "2016-08-01T22:10:40Z",
"attributes": {
"main_attribute": "some_attribute"
},
"status": "ok",
"taskrouter_workspace_sid": "WSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_target_workflow_sid": "WWaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_target_taskqueue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_taskqueues": [
{
"sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"targettable": true
},
{
"sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaac",
"targettable": false
}
],
"taskrouter_skills": [
{
"name": "sales",
"multivalue": false,
"minimum": 0,
"maximum": 0
},
{
"name": "support",
"multivalue": true,
"minimum": 0,
"maximum": 10
}
],
"taskrouter_worker_channels": {
"agent": [
{
"name": "default",
"availability": true,
"capacity": 1
},
{
"name": "voice",
"availability": false,
"capacity": 2
}
],
"supervisor": [
{
"name": "default",
"availability": true,
"capacity": 2
}
]
},
"taskrouter_worker_attributes": {
"agent": {
"region": "us-east"
},
"supervisor": {
"region": "us"
}
},
"taskrouter_offline_activity_sid": "WAaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"runtime_domain": "https://flex.twilio.com",
"messaging_service_instance_sid": "MGaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"chat_service_instance_sid": "ISaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"flex_service_instance_sid": "ISaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"ui_language": "en",
"ui_attributes": {},
"ui_dependencies": {},
"ui_version": "1.0",
"service_version": "1.0",
"call_recording_enabled": true,
"call_recording_webhook_url": "https://www.example.com/call-recording",
"crm_enabled": true,
"crm_type": "custom",
"crm_callback_url": "https://crm.com/a",
"crm_fallback_url": "https://crm.com/b",
"crm_attributes": {
"crm_attribute": "some_crm"
},
"public_attributes": {
"public": "test"
},
"plugin_service_enabled": true,
"plugin_service_attributes": {
"agent-logger": "^3.10.5",
"typewriter": "^7.0.1"
},
"integrations": [
{
"name": "twilio",
"type": "http",
"active": true,
"config": "{\\"callback\\":\\"twilio.com/cb\\",\\"allowed_methods\\":[\\"GET\\",\\"POST\\"]}",
"logo": "logo1",
"author": "somebody1"
},
{
"name": "twilio-stage",
"type": "http",
"active": false,
"config": "{\\"callback\\":\\"twilio.com/cb\\",\\"allowed_methods\\":[\\"GET\\",\\"POST\\"]}"
}
],
"outbound_call_flows": {
"default": {
"caller_id": "+12345",
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"location": "EE",
"workflow_sid": "WWaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
}
},
"queue_stats_configuration": {
"default": {
"service_level_threshold": 20,
"short_abandoned_threshold": 5,
"reset_timezone": "America/New_York",
"reset_time": "00:00"
},
"queue_configurations": [
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"reset_timezone": "Europe/Tallinn",
"reset_time": "01:00"
},
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"reset_timezone": "Europe/Paris",
"reset_time": "02:00"
}
],
"queue_channel_configurations": [
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"channel_sid": "TCaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"service_level_threshold": 10,
"short_abandoned_threshold": 10
},
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"channel_sid": "TCaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"service_level_threshold": 30,
"short_abandoned_threshold": 15
}
]
},
"serverless_service_sids": [
"ZSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"ZSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab"
],
"url": "https://flex-api.twilio.com/v1/Configuration"
}
'''
))
actual = self.client.flex_api.v1.configuration().fetch()
self.assertIsNotNone(actual)
def test_create_request(self):
self.holodeck.mock(Response(500, ''))
with self.assertRaises(TwilioException):
self.client.flex_api.v1.configuration().create()
self.holodeck.assert_has_request(Request(
'post',
'https://flex-api.twilio.com/v1/Configuration',
))
def test_create_response(self):
self.holodeck.mock(Response(
201,
'''
{
"account_sid": "ACaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"date_created": "2016-08-01T22:10:40Z",
"date_updated": "2016-08-01T22:10:40Z",
"attributes": {
"main_attribute": "some_attribute"
},
"status": "ok",
"taskrouter_workspace_sid": "WSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_target_workflow_sid": "WWaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_target_taskqueue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_taskqueues": [
{
"sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"targettable": true
},
{
"sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaac",
"targettable": false
}
],
"taskrouter_skills": [
{
"name": "sales",
"multivalue": false,
"minimum": 0,
"maximum": 0
},
{
"name": "support",
"multivalue": true,
"minimum": 0,
"maximum": 10
}
],
"taskrouter_worker_channels": {
"agent": [
{
"name": "default",
"availability": true,
"capacity": 1
},
{
"name": "voice",
"availability": false,
"capacity": 2
}
],
"supervisor": [
{
"name": "default",
"availability": true,
"capacity": 2
}
]
},
"taskrouter_worker_attributes": {
"agent": {
"region": "us-east"
},
"supervisor": {
"region": "us"
}
},
"taskrouter_offline_activity_sid": "WAaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"runtime_domain": "https://flex.twilio.com",
"messaging_service_instance_sid": "MGaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"chat_service_instance_sid": "ISaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"flex_service_instance_sid": "ISaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"ui_language": "en",
"ui_attributes": {},
"ui_dependencies": {},
"ui_version": "1.0",
"service_version": "1.0",
"call_recording_enabled": true,
"call_recording_webhook_url": "https://www.example.com/call-recording",
"crm_enabled": true,
"crm_type": "custom",
"crm_callback_url": "https://crm.com/a",
"crm_fallback_url": "https://crm.com/b",
"crm_attributes": {
"crm_attribute": "some_crm"
},
"public_attributes": {
"public": "test"
},
"plugin_service_enabled": true,
"plugin_service_attributes": {
"agent-logger": "^3.10.5",
"typewriter": "^7.0.1"
},
"integrations": [
{
"name": "twilio",
"type": "http",
"active": true,
"config": "{\\"callback\\":\\"twilio.com/cb\\",\\"allowed_methods\\":[\\"GET\\",\\"POST\\"]}",
"logo": "logo1",
"author": "somebody1"
},
{
"name": "twilio-stage",
"type": "http",
"active": false,
"config": "{\\"callback\\":\\"twilio.com/cb\\",\\"allowed_methods\\":[\\"GET\\",\\"POST\\"]}"
}
],
"outbound_call_flows": {
"default": {
"caller_id": "+12345",
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"location": "EE",
"workflow_sid": "WWaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
}
},
"queue_stats_configuration": {
"default": {
"service_level_threshold": 20,
"short_abandoned_threshold": 5,
"reset_timezone": "America/New_York",
"reset_time": "00:00"
},
"queue_configurations": [
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"reset_timezone": "Europe/Tallinn",
"reset_time": "01:00"
},
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"reset_timezone": "Europe/Paris",
"reset_time": "02:00"
}
],
"queue_channel_configurations": [
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"channel_sid": "TCaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"service_level_threshold": 10,
"short_abandoned_threshold": 10
},
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"channel_sid": "TCaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"service_level_threshold": 30,
"short_abandoned_threshold": 15
}
]
},
"serverless_service_sids": [
"ZSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"ZSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab"
],
"url": "https://flex-api.twilio.com/v1/Configuration"
}
'''
))
actual = self.client.flex_api.v1.configuration().create()
self.assertIsNotNone(actual)
def test_update_request(self):
self.holodeck.mock(Response(500, ''))
with self.assertRaises(TwilioException):
self.client.flex_api.v1.configuration().update()
self.holodeck.assert_has_request(Request(
'post',
'https://flex-api.twilio.com/v1/Configuration',
))
def test_update_response(self):
self.holodeck.mock(Response(
200,
'''
{
"account_sid": "ACaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"date_created": "2016-08-01T22:10:40Z",
"date_updated": "2016-08-01T22:10:40Z",
"attributes": {
"main_attribute": "some_attribute"
},
"status": "ok",
"taskrouter_workspace_sid": "WSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_target_workflow_sid": "WWaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_target_taskqueue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"taskrouter_taskqueues": [
{
"sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"targettable": true
},
{
"sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaac",
"targettable": false
}
],
"taskrouter_skills": [
{
"name": "sales",
"multivalue": false,
"minimum": 0,
"maximum": 0
},
{
"name": "support",
"multivalue": true,
"minimum": 0,
"maximum": 10
}
],
"taskrouter_worker_channels": {
"agent": [
{
"name": "default",
"availability": true,
"capacity": 1
},
{
"name": "voice",
"availability": false,
"capacity": 2
}
],
"supervisor": [
{
"name": "default",
"availability": true,
"capacity": 2
}
]
},
"taskrouter_worker_attributes": {
"agent": {
"region": "us-east"
},
"supervisor": {
"region": "us"
}
},
"taskrouter_offline_activity_sid": "WAaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"runtime_domain": "https://flex.twilio.com",
"messaging_service_instance_sid": "MGaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"chat_service_instance_sid": "ISaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"flex_service_instance_sid": "ISaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"ui_language": "en",
"ui_attributes": {},
"ui_dependencies": {},
"ui_version": "1.0",
"service_version": "1.0",
"call_recording_enabled": true,
"call_recording_webhook_url": "https://www.example.com/call-recording",
"crm_enabled": true,
"crm_type": "custom",
"crm_callback_url": "https://crm.com/a",
"crm_fallback_url": "https://crm.com/b",
"crm_attributes": {
"crm_attribute": "some_crm"
},
"public_attributes": {
"public": "test"
},
"plugin_service_enabled": false,
"plugin_service_attributes": {
"agent-logger": "^3.10.5",
"typewriter": "^7.0.1"
},
"integrations": [
{
"name": "twilio",
"type": "http",
"active": true,
"config": "{\\"callback\\":\\"twilio.com/cb\\",\\"allowed_methods\\":[\\"GET\\",\\"POST\\"]}",
"logo": "logo1",
"author": "somebody1"
},
{
"name": "twilio-stage",
"type": "http",
"active": false,
"config": "{\\"callback\\":\\"twilio.com/cb\\",\\"allowed_methods\\":[\\"GET\\",\\"POST\\"]}"
}
],
"outbound_call_flows": {
"default": {
"caller_id": "+12345",
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"location": "EE",
"workflow_sid": "WWaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
}
},
"queue_stats_configuration": {
"default": {
"service_level_threshold": 20,
"short_abandoned_threshold": 5,
"reset_timezone": "America/New_York",
"reset_time": "00:00"
},
"queue_configurations": [
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"reset_timezone": "Europe/Tallinn",
"reset_time": "01:00"
},
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"reset_timezone": "Europe/Paris",
"reset_time": "02:00"
}
],
"queue_channel_configurations": [
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"channel_sid": "TCaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"service_level_threshold": 10,
"short_abandoned_threshold": 10
},
{
"queue_sid": "WQaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"channel_sid": "TCaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab",
"service_level_threshold": 30,
"short_abandoned_threshold": 15
}
]
},
"serverless_service_sids": [
"ZSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
"ZSaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab"
],
"url": "https://flex-api.twilio.com/v1/Configuration"
}
'''
))
actual = self.client.flex_api.v1.configuration().update()
self.assertIsNotNone(actual)
| 40.802559
| 118
| 0.391729
| 1,224
| 22,319
| 6.88317
| 0.150327
| 0.016024
| 0.019228
| 0.014243
| 0.964392
| 0.957745
| 0.949792
| 0.949792
| 0.943858
| 0.938754
| 0
| 0.02368
| 0.498589
| 22,319
| 546
| 119
| 40.877289
| 0.729157
| 0.004884
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| 0.583333
| 1
| 0
| 0.075983
| 0
| 0
| 0
| 0
| 0
| 0.1875
| 1
| 0.125
| false
| 0
| 0.083333
| 0
| 0.229167
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
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| 0
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| 0
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| 0
| 1
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| null | 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
1db746a28efcd554e3e7080c4577c8fec173a661
| 107
|
py
|
Python
|
new_deeplab/utils/__init__.py
|
abhineet123/river_ice_segmentation
|
24f0aa60b164fb21c00c269b2309172dbe7d22f4
|
[
"CC-BY-3.0"
] | 10
|
2019-07-24T12:23:05.000Z
|
2022-01-06T04:08:54.000Z
|
new_deeplab/utils/__init__.py
|
abhineet123/river_ice_segmentation
|
24f0aa60b164fb21c00c269b2309172dbe7d22f4
|
[
"CC-BY-3.0"
] | null | null | null |
new_deeplab/utils/__init__.py
|
abhineet123/river_ice_segmentation
|
24f0aa60b164fb21c00c269b2309172dbe7d22f4
|
[
"CC-BY-3.0"
] | 7
|
2019-04-08T17:46:08.000Z
|
2022-02-25T11:06:59.000Z
|
import os
def linux_path(*args, **kwargs):
return os.path.join(*args, **kwargs).replace(os.sep, '/')
| 17.833333
| 61
| 0.64486
| 16
| 107
| 4.25
| 0.6875
| 0.294118
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| 0.140187
| 107
| 5
| 62
| 21.4
| 0.73913
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| 0
| 0.009434
| 0
| 0
| 0
| 0
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| 1
| 0.333333
| true
| 0
| 0.333333
| 0.333333
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| 1
| 1
| 0
| 0
|
0
| 7
|
1df958f169940a78783ec5584c96077769516508
| 9,183
|
py
|
Python
|
pytorch/sje.py
|
tchittesh/zsl-project
|
bfc99ccc0106ca5eebb5b674abf6fce793b26c12
|
[
"MIT"
] | null | null | null |
pytorch/sje.py
|
tchittesh/zsl-project
|
bfc99ccc0106ca5eebb5b674abf6fce793b26c12
|
[
"MIT"
] | null | null | null |
pytorch/sje.py
|
tchittesh/zsl-project
|
bfc99ccc0106ca5eebb5b674abf6fce793b26c12
|
[
"MIT"
] | null | null | null |
import torch
import torch.nn as nn
import torch.nn.functional as F
from utils import normalizeFeaturesL2
class SJE_Original(nn.Module):
def __init__(self, img_feature_size, num_attributes, margin):
super(SJE_Original, self).__init__()
self.margin = margin
# copying initialization technique from original code
W = torch.rand(img_feature_size, num_attributes, requires_grad=True)
W = normalizeFeaturesL2(W.permute(1,0)).permute(1,0)
self.W = nn.Parameter(W, requires_grad=True)
self.avg_pool = nn.AdaptiveAvgPool2d((1, 1))
def forward(self, *args, **kwargs):
if self.training:
return self.forward_train(*args, **kwargs)
else:
return self.forward_test(*args, **kwargs)
def forward_train(self, img_features, all_class_attributes, class_attributes, labels):
'''
img_features: torch.Tensor of shape [B, img_feature_size]
class_attributes: torch.Tensor of shape [B, num_attributes]
labels: torch.Tensor of shape [B]
all_class_attributes: torch.Tensor of shape [num_attributes, num_classes]
returns scalar loss
'''
if len(img_features.shape) == 4:
img_features = self.avg_pool(img_features).squeeze(2).squeeze(2) # remove h, w dimensions
XW = torch.matmul(img_features.unsqueeze(1), self.W).squeeze(1) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
gt_class_scores = scores[torch.arange(len(scores)), labels].unsqueeze(1) # shape [B, 1]
# add margin to scores
losses = self.margin + scores - gt_class_scores # shape [B, num_classes]
losses[torch.arange(len(losses)), labels] = 0.0
losses = losses.max(dim=1)[0] # shape [B]
return losses.clamp(0).mean()
def forward_test(self, img_features, all_class_attributes):
if len(img_features.shape) == 4:
img_features = self.avg_pool(img_features).squeeze(2).squeeze(2) # remove h, w dimensions
XW = torch.matmul(img_features.unsqueeze(1), self.W).squeeze(1) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
return scores.argmax(1) # shape [B]
class SJE_Linear(nn.Module):
def __init__(self, img_feature_size, num_attributes, margin):
super(SJE_Linear, self).__init__()
self.margin = margin
self.projection = nn.Linear(img_feature_size, num_attributes)
self.projection.weight.data = normalizeFeaturesL2(self.projection.weight.data)
def forward(self, *args, **kwargs):
if self.training:
return self.forward_train(*args, **kwargs)
else:
return self.forward_test(*args, **kwargs)
def forward_train(self, img_features, all_class_attributes, class_attributes, labels):
'''
img_features: torch.Tensor of shape [B, img_feature_size]
class_attributes: torch.Tensor of shape [B, num_attributes]
labels: torch.Tensor of shape [B]
all_class_attributes: torch.Tensor of shape [num_attributes, num_classes]
returns scalar loss
'''
XW = self.projection(img_features) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
gt_class_scores = scores[torch.arange(len(scores)), labels].unsqueeze(1) # shape [B, 1]
# add margin to scores
losses = self.margin + scores - gt_class_scores # shape [B, num_classes]
losses[torch.arange(len(losses)), labels] = 0.0
losses = losses.max(dim=1)[0] # shape [B]
return losses.clamp(0).mean()
def forward_test(self, img_features, all_class_attributes):
XW = self.projection(img_features) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
return scores.argmax(1) # shape [B]
class SJE_WeightedCosine(nn.Module):
def __init__(self, img_feature_size, num_attributes, margin):
super(SJE_WeightedCosine, self).__init__()
self.margin = margin
# copying initialization technique from original code
W = torch.rand(img_feature_size, num_attributes, requires_grad=True)
W = normalizeFeaturesL2(W.permute(1,0)).permute(1,0)
self.W = nn.Parameter(W, requires_grad=True)
weights = torch.zeros(num_attributes, requires_grad=True)
self.weights = nn.Parameter(weights, requires_grad=True)
self.avg_pool = nn.AdaptiveAvgPool2d((1, 1))
def get_weights(self):
weights = self.weights + 1.0
return weights / weights.sum() * len(weights) # normalize weights
def forward(self, *args, **kwargs):
if self.training:
return self.forward_train(*args, **kwargs)
else:
return self.forward_test(*args, **kwargs)
def forward_train(self, img_features, all_class_attributes, class_attributes, labels):
'''
img_features: torch.Tensor of shape [B, img_feature_size]
class_attributes: torch.Tensor of shape [B, num_attributes]
labels: torch.Tensor of shape [B]
all_class_attributes: torch.Tensor of shape [num_attributes, num_classes]
returns scalar loss
'''
if len(img_features.shape) == 4:
img_features = self.avg_pool(img_features).squeeze(2).squeeze(2) # remove h, w dimensions
XW = torch.matmul(img_features.unsqueeze(1), self.W).squeeze(1) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
XW = self.get_weights().unsqueeze(0) * XW
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
gt_class_scores = scores[torch.arange(len(scores)), labels].unsqueeze(1) # shape [B, 1]
# add margin to scores
losses = self.margin + scores - gt_class_scores # shape [B, num_classes]
losses[torch.arange(len(losses)), labels] = 0.0
losses = losses.max(dim=1)[0] # shape [B]
return losses.clamp(0).mean()
def forward_test(self, img_features, all_class_attributes):
if len(img_features.shape) == 4:
img_features = self.avg_pool(img_features).squeeze(2).squeeze(2) # remove h, w dimensions
XW = torch.matmul(img_features.unsqueeze(1), self.W).squeeze(1) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
XW = self.get_weights().unsqueeze(0) * XW
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
return scores.argmax(1) # shape [B]
class SJE_MLP(nn.Module):
def __init__(self, img_feature_size, num_attributes, margin):
super(SJE_MLP, self).__init__()
self.margin = margin
self.projection = nn.Sequential(
nn.Linear(img_feature_size, 256, bias=False),
nn.ReLU(),
nn.Dropout(),
nn.Linear(256, num_attributes),
)
def forward(self, *args, **kwargs):
if self.training:
return self.forward_train(*args, **kwargs)
else:
return self.forward_test(*args, **kwargs)
def forward_train(self, img_features, all_class_attributes, class_attributes, labels):
'''
img_features: torch.Tensor of shape [B, img_feature_size]
class_attributes: torch.Tensor of shape [B, num_attributes]
labels: torch.Tensor of shape [B]
all_class_attributes: torch.Tensor of shape [num_attributes, num_classes]
returns scalar loss
'''
XW = self.projection(img_features) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
gt_class_scores = scores[torch.arange(len(scores)), labels].unsqueeze(1) # shape [B, 1]
# add margin to scores
losses = self.margin + scores - gt_class_scores # shape [B, num_classes]
losses[torch.arange(len(losses)), labels] = 0.0
losses = losses.max(dim=1)[0] # shape [B]
return losses.clamp(0).mean()
def forward_test(self, img_features, all_class_attributes):
XW = self.projection(img_features) # shape [B, num_attributes]
XW = normalizeFeaturesL2(XW) # normalize each projected vector to have unit length
scores = torch.matmul(XW.unsqueeze(1), all_class_attributes).squeeze(1) # shape [B, num_classes]
return scores.argmax(1) # shape [B]
| 47.335052
| 104
| 0.665578
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| 9,183
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| 0.929422
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| 0.915136
| 0.901531
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| 0
| 0.014576
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| 9,183
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| 47.580311
| 0.80953
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| 0.80315
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| 0
| 0
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| 0
| 1
| 0.133858
| false
| 0
| 0.031496
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| 0.330709
| 0
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| 0
| null | 0
| 0
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| 1
| 1
| 1
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|
0
| 7
|
697503dd41cef46c1e1587c68964fa1318f1014c
| 39,310
|
py
|
Python
|
billforward/apis/notifications_api.py
|
billforward/bf-python
|
d2b812329ca3ed1fd94364d7f46f69ad74665596
|
[
"Apache-2.0"
] | 2
|
2016-11-23T17:32:37.000Z
|
2022-02-24T05:13:20.000Z
|
billforward/apis/notifications_api.py
|
billforward/bf-python
|
d2b812329ca3ed1fd94364d7f46f69ad74665596
|
[
"Apache-2.0"
] | null | null | null |
billforward/apis/notifications_api.py
|
billforward/bf-python
|
d2b812329ca3ed1fd94364d7f46f69ad74665596
|
[
"Apache-2.0"
] | 1
|
2016-12-30T20:02:48.000Z
|
2016-12-30T20:02:48.000Z
|
# coding: utf-8
"""
BillForward REST API
OpenAPI spec version: 1.0.0
Generated by: https://github.com/swagger-api/swagger-codegen.git
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from __future__ import absolute_import
import sys
import os
import re
# python 2 and python 3 compatibility library
from six import iteritems
from ..configuration import Configuration
from ..api_client import ApiClient
class NotificationsApi(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
Ref: https://github.com/swagger-api/swagger-codegen
"""
def __init__(self, api_client=None):
config = Configuration()
if api_client:
self.api_client = api_client
else:
if not config.api_client:
config.api_client = ApiClient()
self.api_client = config.api_client
def ack_notification(self, notification_id, **kwargs):
"""
Acknowledge a newly recevied notification.
{\"nickname\":\"Acknowledge\",\"response\":\"getNotificationACK.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.ack_notification(notification_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str notification_id: ID of the notification. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.ack_notification_with_http_info(notification_id, **kwargs)
else:
(data) = self.ack_notification_with_http_info(notification_id, **kwargs)
return data
def ack_notification_with_http_info(self, notification_id, **kwargs):
"""
Acknowledge a newly recevied notification.
{\"nickname\":\"Acknowledge\",\"response\":\"getNotificationACK.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.ack_notification_with_http_info(notification_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str notification_id: ID of the notification. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['notification_id', 'organizations']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method ack_notification" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'notification_id' is set
if ('notification_id' not in params) or (params['notification_id'] is None):
raise ValueError("Missing the required parameter `notification_id` when calling `ack_notification`")
resource_path = '/notifications/ack/{notification-ID}'.replace('{format}', 'json')
path_params = {}
if 'notification_id' in params:
path_params['notification-ID'] = params['notification_id']
query_params = {}
if 'organizations' in params:
query_params['organizations'] = params['organizations']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['text/plain'])
# Authentication setting
auth_settings = []
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='NotificationPagedMetadata',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'))
def get_all_notifications(self, **kwargs):
"""
Returns a collection of all notifications. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Get all notifications\",\"response\":\"getNotificationAll.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_all_notifications(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first Subscription to return.
:param int records: The maximum number of Subscriptions to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_all_notifications_with_http_info(**kwargs)
else:
(data) = self.get_all_notifications_with_http_info(**kwargs)
return data
def get_all_notifications_with_http_info(self, **kwargs):
"""
Returns a collection of all notifications. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Get all notifications\",\"response\":\"getNotificationAll.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_all_notifications_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first Subscription to return.
:param int records: The maximum number of Subscriptions to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['organizations', 'offset', 'records', 'order_by', 'order', 'include_retired']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_all_notifications" % key
)
params[key] = val
del params['kwargs']
resource_path = '/notifications'.replace('{format}', 'json')
path_params = {}
query_params = {}
if 'organizations' in params:
query_params['organizations'] = params['organizations']
if 'offset' in params:
query_params['offset'] = params['offset']
if 'records' in params:
query_params['records'] = params['records']
if 'order_by' in params:
query_params['order_by'] = params['order_by']
if 'order' in params:
query_params['order'] = params['order']
if 'include_retired' in params:
query_params['include_retired'] = params['include_retired']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type([])
# Authentication setting
auth_settings = []
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='NotificationPagedMetadata',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'))
def get_notification_by_entity_id(self, entity_id, **kwargs):
"""
Returns a collection of notifications, specified by the entity-ID parameter. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Retrieve by entity\",\"response\":\"getNotificationBySubscriptionID.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notification_by_entity_id(entity_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str entity_id: The string entity-ID of the notification. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first notification to return.
:param int records: The maximum number of notifications to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_notification_by_entity_id_with_http_info(entity_id, **kwargs)
else:
(data) = self.get_notification_by_entity_id_with_http_info(entity_id, **kwargs)
return data
def get_notification_by_entity_id_with_http_info(self, entity_id, **kwargs):
"""
Returns a collection of notifications, specified by the entity-ID parameter. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Retrieve by entity\",\"response\":\"getNotificationBySubscriptionID.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notification_by_entity_id_with_http_info(entity_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str entity_id: The string entity-ID of the notification. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first notification to return.
:param int records: The maximum number of notifications to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_id', 'organizations', 'offset', 'records', 'order_by', 'order', 'include_retired']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_notification_by_entity_id" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_id' is set
if ('entity_id' not in params) or (params['entity_id'] is None):
raise ValueError("Missing the required parameter `entity_id` when calling `get_notification_by_entity_id`")
resource_path = '/notifications/entity-ID/{entity-ID}'.replace('{format}', 'json')
path_params = {}
if 'entity_id' in params:
path_params['entity-ID'] = params['entity_id']
query_params = {}
if 'organizations' in params:
query_params['organizations'] = params['organizations']
if 'offset' in params:
query_params['offset'] = params['offset']
if 'records' in params:
query_params['records'] = params['records']
if 'order_by' in params:
query_params['order_by'] = params['order_by']
if 'order' in params:
query_params['order'] = params['order']
if 'include_retired' in params:
query_params['include_retired'] = params['include_retired']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['text/plain'])
# Authentication setting
auth_settings = []
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='NotificationPagedMetadata',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'))
def get_notification_by_id(self, notification_id, **kwargs):
"""
Returns a single notification, specified by the notification-ID parameter.
{\"nickname\":\"Retrieve an existing notification\",\"response\":\"getNotificationByID.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notification_by_id(notification_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str notification_id: ID of the notification. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_notification_by_id_with_http_info(notification_id, **kwargs)
else:
(data) = self.get_notification_by_id_with_http_info(notification_id, **kwargs)
return data
def get_notification_by_id_with_http_info(self, notification_id, **kwargs):
"""
Returns a single notification, specified by the notification-ID parameter.
{\"nickname\":\"Retrieve an existing notification\",\"response\":\"getNotificationByID.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notification_by_id_with_http_info(notification_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str notification_id: ID of the notification. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['notification_id', 'organizations']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_notification_by_id" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'notification_id' is set
if ('notification_id' not in params) or (params['notification_id'] is None):
raise ValueError("Missing the required parameter `notification_id` when calling `get_notification_by_id`")
resource_path = '/notifications/{notification-ID}'.replace('{format}', 'json')
path_params = {}
if 'notification_id' in params:
path_params['notification-ID'] = params['notification_id']
query_params = {}
if 'organizations' in params:
query_params['organizations'] = params['organizations']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type(['text/plain'])
# Authentication setting
auth_settings = []
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='NotificationPagedMetadata',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'))
def get_notifications_by_webhook_id(self, lower_threshold, upper_threshold, webhook_id, **kwargs):
"""
Returns a collection of notification objects with created times within the period specified by the lower-threshold and upper-threshold parameters for the given webhook id. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Retrieve by creation\",\"response\":\"getNotificationByCreated.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notifications_by_webhook_id(lower_threshold, upper_threshold, webhook_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str lower_threshold: The UTC DateTime specifying the start of the result period. (required)
:param str upper_threshold: The UTC DateTime specifying the end of the result period. (required)
:param str webhook_id: The id of the webhook. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first taxation-link to return.
:param int records: The maximum number of taxation-links to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:param int safety_margin: How many seconds behind server-time upperThreshold may approach.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_notifications_by_webhook_id_with_http_info(lower_threshold, upper_threshold, webhook_id, **kwargs)
else:
(data) = self.get_notifications_by_webhook_id_with_http_info(lower_threshold, upper_threshold, webhook_id, **kwargs)
return data
def get_notifications_by_webhook_id_with_http_info(self, lower_threshold, upper_threshold, webhook_id, **kwargs):
"""
Returns a collection of notification objects with created times within the period specified by the lower-threshold and upper-threshold parameters for the given webhook id. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Retrieve by creation\",\"response\":\"getNotificationByCreated.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notifications_by_webhook_id_with_http_info(lower_threshold, upper_threshold, webhook_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str lower_threshold: The UTC DateTime specifying the start of the result period. (required)
:param str upper_threshold: The UTC DateTime specifying the end of the result period. (required)
:param str webhook_id: The id of the webhook. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first taxation-link to return.
:param int records: The maximum number of taxation-links to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:param int safety_margin: How many seconds behind server-time upperThreshold may approach.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['lower_threshold', 'upper_threshold', 'webhook_id', 'organizations', 'offset', 'records', 'order_by', 'order', 'include_retired', 'safety_margin']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_notifications_by_webhook_id" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'lower_threshold' is set
if ('lower_threshold' not in params) or (params['lower_threshold'] is None):
raise ValueError("Missing the required parameter `lower_threshold` when calling `get_notifications_by_webhook_id`")
# verify the required parameter 'upper_threshold' is set
if ('upper_threshold' not in params) or (params['upper_threshold'] is None):
raise ValueError("Missing the required parameter `upper_threshold` when calling `get_notifications_by_webhook_id`")
# verify the required parameter 'webhook_id' is set
if ('webhook_id' not in params) or (params['webhook_id'] is None):
raise ValueError("Missing the required parameter `webhook_id` when calling `get_notifications_by_webhook_id`")
resource_path = '/notifications/{lower-threshold}/{upper-threshold}/{webhookID}'.replace('{format}', 'json')
path_params = {}
if 'lower_threshold' in params:
path_params['lower-threshold'] = params['lower_threshold']
if 'upper_threshold' in params:
path_params['upper-threshold'] = params['upper_threshold']
if 'webhook_id' in params:
path_params['webhookID'] = params['webhook_id']
query_params = {}
if 'organizations' in params:
query_params['organizations'] = params['organizations']
if 'offset' in params:
query_params['offset'] = params['offset']
if 'records' in params:
query_params['records'] = params['records']
if 'order_by' in params:
query_params['order_by'] = params['order_by']
if 'order' in params:
query_params['order'] = params['order']
if 'include_retired' in params:
query_params['include_retired'] = params['include_retired']
if 'safety_margin' in params:
query_params['safety_margin'] = params['safety_margin']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type([])
# Authentication setting
auth_settings = []
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='NotificationPagedMetadata',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'))
def get_notifications_within_date_range(self, lower_threshold, upper_threshold, **kwargs):
"""
Returns a collection of notification objects with created times within the period specified by the lower-threshold and upper-threshold parameters. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Retrieve by creation\",\"response\":\"getNotificationByCreated.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notifications_within_date_range(lower_threshold, upper_threshold, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str lower_threshold: The UTC DateTime specifying the start of the result period. (required)
:param str upper_threshold: The UTC DateTime specifying the end of the result period. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first taxation-link to return.
:param int records: The maximum number of taxation-links to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:param int safety_margin: How many seconds behind server-time upperThreshold may approach.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.get_notifications_within_date_range_with_http_info(lower_threshold, upper_threshold, **kwargs)
else:
(data) = self.get_notifications_within_date_range_with_http_info(lower_threshold, upper_threshold, **kwargs)
return data
def get_notifications_within_date_range_with_http_info(self, lower_threshold, upper_threshold, **kwargs):
"""
Returns a collection of notification objects with created times within the period specified by the lower-threshold and upper-threshold parameters. By default 10 values are returned. Records are returned in natural order.
{\"nickname\":\"Retrieve by creation\",\"response\":\"getNotificationByCreated.html\"}
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please define a `callback` function
to be invoked when receiving the response.
>>> def callback_function(response):
>>> pprint(response)
>>>
>>> thread = api.get_notifications_within_date_range_with_http_info(lower_threshold, upper_threshold, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str lower_threshold: The UTC DateTime specifying the start of the result period. (required)
:param str upper_threshold: The UTC DateTime specifying the end of the result period. (required)
:param list[str] organizations: A list of organization-IDs used to restrict the scope of API calls.
:param int offset: The offset from the first taxation-link to return.
:param int records: The maximum number of taxation-links to return.
:param str order_by: Specify a field used to order the result set.
:param str order: Ihe direction of any ordering, either ASC or DESC.
:param bool include_retired: Whether retired products should be returned.
:param int safety_margin: How many seconds behind server-time upperThreshold may approach.
:return: NotificationPagedMetadata
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['lower_threshold', 'upper_threshold', 'organizations', 'offset', 'records', 'order_by', 'order', 'include_retired', 'safety_margin']
all_params.append('callback')
all_params.append('_return_http_data_only')
params = locals()
for key, val in iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_notifications_within_date_range" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'lower_threshold' is set
if ('lower_threshold' not in params) or (params['lower_threshold'] is None):
raise ValueError("Missing the required parameter `lower_threshold` when calling `get_notifications_within_date_range`")
# verify the required parameter 'upper_threshold' is set
if ('upper_threshold' not in params) or (params['upper_threshold'] is None):
raise ValueError("Missing the required parameter `upper_threshold` when calling `get_notifications_within_date_range`")
resource_path = '/notifications/{lower-threshold}/{upper-threshold}'.replace('{format}', 'json')
path_params = {}
if 'lower_threshold' in params:
path_params['lower-threshold'] = params['lower_threshold']
if 'upper_threshold' in params:
path_params['upper-threshold'] = params['upper_threshold']
query_params = {}
if 'organizations' in params:
query_params['organizations'] = params['organizations']
if 'offset' in params:
query_params['offset'] = params['offset']
if 'records' in params:
query_params['records'] = params['records']
if 'order_by' in params:
query_params['order_by'] = params['order_by']
if 'order' in params:
query_params['order'] = params['order']
if 'include_retired' in params:
query_params['include_retired'] = params['include_retired']
if 'safety_margin' in params:
query_params['safety_margin'] = params['safety_margin']
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json'])
if not header_params['Accept']:
del header_params['Accept']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.\
select_header_content_type([])
# Authentication setting
auth_settings = []
return self.api_client.call_api(resource_path, 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='NotificationPagedMetadata',
auth_settings=auth_settings,
callback=params.get('callback'),
_return_http_data_only=params.get('_return_http_data_only'))
| 49.014963
| 253
| 0.620173
| 4,309
| 39,310
| 5.470179
| 0.064284
| 0.040728
| 0.025243
| 0.02257
| 0.949642
| 0.940181
| 0.931059
| 0.918035
| 0.90692
| 0.896568
| 0
| 0.000944
| 0.299008
| 39,310
| 801
| 254
| 49.076155
| 0.854442
| 0.422717
| 0
| 0.799465
| 1
| 0
| 0.210821
| 0.055329
| 0
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| 1
| 0.034759
| false
| 0
| 0.018717
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| 1
| 1
| 1
| 1
| 1
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| null | 0
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| 0
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| 0
| 0
| 0
|
0
| 8
|
69976f87d8a0a9f6dfac446f68d5f22ba3b8b9c5
| 6,005
|
py
|
Python
|
mrio_common_metadata/conversion/exiobase_3_hybrid_io/version_config.py
|
brightway-lca/mrio_common_metadata
|
a9a7932b6eabd195f47e7fb0c4e5c071927c2f64
|
[
"BSD-3-Clause"
] | null | null | null |
mrio_common_metadata/conversion/exiobase_3_hybrid_io/version_config.py
|
brightway-lca/mrio_common_metadata
|
a9a7932b6eabd195f47e7fb0c4e5c071927c2f64
|
[
"BSD-3-Clause"
] | 2
|
2020-03-03T12:42:26.000Z
|
2021-09-30T18:00:28.000Z
|
mrio_common_metadata/conversion/exiobase_3_hybrid_io/version_config.py
|
brightway-lca/mrio_common_metadata
|
a9a7932b6eabd195f47e7fb0c4e5c071927c2f64
|
[
"BSD-3-Clause"
] | 1
|
2020-03-03T10:34:46.000Z
|
2020-03-03T10:34:46.000Z
|
VERSIONS = {
"3.3.17 hybrid": {
"nomenclature": {
"extensions": [
{
"filename": "Classifications_v_3_3_17.xlsx",
"worksheet": "Resources",
"mapping": {"Resource name": "name", "Unit": "unit"},
"kind": "resource",
},
{
"filename": "Classifications_v_3_3_17.xlsx",
"worksheet": "Land",
"mapping": {"Land type": "name", "Unit": "unit"},
"kind": "land_use",
},
{
"filename": "Classifications_v_3_3_17.xlsx",
"worksheet": "Emissions",
"mapping": {
"Emission name": "name",
"Unit": "unit",
"Compartment": "compartment",
},
"kind": "emission",
},
],
"locations": [
{
"filename": "Classifications_v_3_3_17.xlsx",
"worksheet": "Country",
"mapping": {"Country code": "code", "Country name": "name"},
}
],
"activities": [
{
"filename": "Classifications_v_3_3_17.xlsx",
"worksheet": "Activities",
"mapping": {
"Contry code": "location",
"Activity name": "name",
"Activity code 1": "code 1",
"Activity code 2": "code 2",
},
}
],
"products": [
{
"filename": "Classifications_v_3_3_17.xlsx",
"worksheet": "Products_HIOT",
"mapping": {
"Country code": "location",
"Product name": "name",
"Product code 1": "code 1",
"Product code 2": "code 2",
"Unit": "unit",
},
}
],
},
"technosphere": {
"filename": "Exiobase_MR_HIOT_2011_v3_3_17_by_prod_tech.xlsb",
"worksheet": "HIOT",
},
"production": {
"filename": "Exiobase_MR_HIOT_2011_v3_3_17_by_prod_tech.xlsb",
"worksheet": "Principal_production_vector",
},
"biosphere": {
"resource": {
"filename": "MR_HIOT_2011_v3_3_17_extensions.xlsb",
"worksheet": "resource_act",
},
"land_use": {
"filename": "MR_HIOT_2011_v3_3_17_extensions.xlsb",
"worksheet": "Land_act",
},
"emission": {
"filename": "MR_HIOT_2011_v3_3_17_extensions.xlsb",
"worksheet": "Emiss_act",
},
},
},
"3.3.18 hybrid": {
"nomenclature": {
"extensions": [
{
"filename": "Classifications_v_3_3_18.xlsx",
"worksheet": "Resources",
"mapping": {"Resource name": "name", "Unit": "unit"},
"kind": "resource",
},
{
"filename": "Classifications_v_3_3_18.xlsx",
"worksheet": "Land",
"mapping": {"Land type": "name", "Unit": "unit"},
"kind": "land_use",
},
{
"filename": "Classifications_v_3_3_18.xlsx",
"worksheet": "Emissions",
"mapping": {
"Emission name": "name",
"Unit": "unit",
"Compartment": "compartment",
},
"kind": "emission",
},
],
"locations": [
{
"filename": "Classifications_v_3_3_18.xlsx",
"worksheet": "Country",
"mapping": {"Country code": "code", "Country name": "name"},
}
],
"activities": [
{
"filename": "Classifications_v_3_3_18.xlsx",
"worksheet": "Activities",
"mapping": {
"Contry code": "location",
"Activity name": "name",
"Activity code 1": "code 1",
"Activity code 2": "code 2",
},
}
],
"products": [
{
"filename": "Classifications_v_3_3_18.xlsx",
"worksheet": "Products_HIOT",
"mapping": {
"Country code": "location",
"Product name": "name",
"Product code 1": "code 1",
"Product code 2": "code 2",
"Unit": "unit",
},
}
],
},
"technosphere": {
"filename": "MR_HIOT_2011_v3_3_18_by_product_technology.csv",
"worksheet": "HIOT",
},
"production": {
"filename": "MR_HIOT_2011_v3_3_18_principal_production.csv",
},
"biosphere": {
"resource": {
"filename": "MR_HIOT_2011_v3_3_18_extensions.xlsb",
"worksheet": "resource_act",
},
"land_use": {
"filename": "MR_HIOT_2011_v3_3_18_extensions.xlsb",
"worksheet": "Land_act",
},
"emission": {
"filename": "MR_HIOT_2011_v3_3_18_extensions.xlsb",
"worksheet": "Emiss_act",
},
},
}
}
| 36.174699
| 80
| 0.368526
| 408
| 6,005
| 5.102941
| 0.129902
| 0.013449
| 0.138329
| 0.144092
| 0.941403
| 0.933718
| 0.933718
| 0.915466
| 0.835735
| 0.835735
| 0
| 0.050819
| 0.501915
| 6,005
| 165
| 81
| 36.393939
| 0.645269
| 0
| 0
| 0.678788
| 0
| 0
| 0.378851
| 0.129226
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
3852753d030c286dd563a008ce30f809b9218873
| 178
|
py
|
Python
|
ttyUSBID/__init__.py
|
quanghuyen1301/ttyusb_id
|
5b82409bd84429944ea25c9eb21f2dc50d5cb005
|
[
"Unlicense"
] | 1
|
2020-03-20T16:44:28.000Z
|
2020-03-20T16:44:28.000Z
|
ttyUSBID/__init__.py
|
quanghuyen1301/ttyusb_id
|
5b82409bd84429944ea25c9eb21f2dc50d5cb005
|
[
"Unlicense"
] | null | null | null |
ttyUSBID/__init__.py
|
quanghuyen1301/ttyusb_id
|
5b82409bd84429944ea25c9eb21f2dc50d5cb005
|
[
"Unlicense"
] | null | null | null |
# __init__.py
from .__main__ import get_ttydata
from .__main__ import get_ttydata_ssh
from .__main__ import list_ttyusb
from .__main__ import tty2id
from .__main__ import id2tty
| 25.428571
| 37
| 0.837079
| 26
| 178
| 4.653846
| 0.461538
| 0.330579
| 0.578512
| 0.280992
| 0.396694
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012821
| 0.123596
| 178
| 6
| 38
| 29.666667
| 0.762821
| 0.061798
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
387895d0b39c944994e1cfc38a9efd06a6400b6b
| 6,177
|
py
|
Python
|
rlschool/metamaze/envs/maze_env.py
|
HaojieSHI98/RLSchool
|
23c21c8028c8398a94dd7ed7aeb2624dc72f1160
|
[
"Apache-2.0"
] | null | null | null |
rlschool/metamaze/envs/maze_env.py
|
HaojieSHI98/RLSchool
|
23c21c8028c8398a94dd7ed7aeb2624dc72f1160
|
[
"Apache-2.0"
] | null | null | null |
rlschool/metamaze/envs/maze_env.py
|
HaojieSHI98/RLSchool
|
23c21c8028c8398a94dd7ed7aeb2624dc72f1160
|
[
"Apache-2.0"
] | null | null | null |
"""
Gym Environment For Maze3D
"""
import numpy
import gym
import pygame
from gym import error, spaces, utils
from gym.utils import seeding
from rlschool.metamaze.envs.maze_gen import Textures, sample_task_config
from rlschool.metamaze.envs.maze_3d import MazeCore3D
from rlschool.metamaze.envs.maze_2d import MazeCore2D
class MetaMaze3D(gym.Env):
def __init__(self,
with_guidepost=True,
enable_render=True,
render_scale=480,
render_godview=True,
resolution=(320, 320),
max_steps = 1000,
):
self.enable_render = enable_render
self.render_viewsize = render_scale
self.render_godview = render_godview
self.maze_core = MazeCore3D(
with_guidepost = with_guidepost,
resolution_horizon = resolution[0],
resolution_vertical = resolution[1],
)
self.max_steps = max_steps
# Turning Left/Right and go backward / forward
self.action_space = spaces.Box(low=numpy.array([-1.0, -1.0]),
high=numpy.array([1.0, 1.0]), dtype=numpy.float32)
# observation is the x, y coordinate of the grid
self.observation_space = spaces.Box(low=numpy.zeros(shape=(resolution[0], resolution[1], 3), dtype=numpy.float32),
high=numpy.full((resolution[0], resolution[1], 3), 256, dtype=numpy.float32),
dtype=numpy.float32)
self.textures = Textures("img")
self.need_reset = True
self.need_set_task = True
def sample_task(self,
cell_scale = 15,
allow_loops = False,
cell_size = 2.0,
wall_height = 3.2,
agent_height = 1.6
):
return sample_task_config(self.textures.n_texts,
max_cells=cell_scale,
allow_loops=allow_loops,
cell_size=cell_size,
wall_height=wall_height,
agent_height=agent_height)
def set_task(self, task_config):
self.maze_core.set_task(task_config, self.textures)
self.need_set_task = False
def reset(self):
if(self.need_set_task):
raise Exception("Must call \"set_task\" before reset")
self.steps = 0
state = self.maze_core.reset()
if(self.enable_render):
self.maze_core.render_init(self.render_viewsize, self.render_godview)
self.keyboard_press = pygame.key.get_pressed()
self.need_reset = False
self.key_done = False
return state
def step(self, action=None):
if(self.need_reset):
raise Exception("Must \"reset\" before doing any actions")
reward = - 0.1
self.steps += 1
if(action is None): # Only when there is no action input can we use keyboard control
pygame.time.delay(20) # 50 FPS
tr, ws = self.maze_core.movement_control(self.keyboard_press)
else:
tr = action[0]
ws = action[1]
done = self.maze_core.do_action(tr, ws)
if(done):
reward += 200
elif(self.steps >= self.max_steps or self.key_done):
done = True
if(done):
self.need_reset=True
info = {"steps": self.steps}
return self.maze_core.get_observation(), reward, done, info
def render(self):
self.key_done, self.keyboard_press = self.maze_core.render_update(self.render_godview)
DISCRETE_ACTIONS=[(-1, 0), (1, 0), (0, -1), (0, 1)]
class MetaMaze2D(gym.Env):
def __init__(self,
enable_render=True,
render_scale=480,
render_godview=True,
max_steps = 1000):
self.enable_render = enable_render
self.maze_core = MazeCore2D()
self.max_steps = max_steps
self.render_viewsize = render_scale
self.render_godview = render_godview
# Turning Left/Right and go backward / forward
self.action_space = spaces.Discrete(4)
# observation is the x, y coordinate of the grid
self.observation_space = spaces.Box(low=-1, high=1, shape=(3,3), dtype=numpy.int32)
self.need_reset = True
self.need_set_task = True
def sample_task(self,
cell_scale = 15,
allow_loops = False,
cell_size = 2.0,
wall_height = 3.2,
agent_height = 1.6
):
return sample_task_config(2,
max_cells=cell_scale,
allow_loops=allow_loops,
cell_size=cell_size,
wall_height=wall_height,
agent_height=agent_height)
def set_task(self, task_config):
self.maze_core.set_task(task_config, None)
self.need_set_task = False
def reset(self):
if(self.need_set_task):
raise Exception("Must call \"set_task\" before reset")
self.steps = 0
state = self.maze_core.reset()
if(self.enable_render):
self.maze_core.render_init(self.render_viewsize, self.render_godview)
self.keyboard_press = pygame.key.get_pressed()
self.need_reset = False
self.key_done = False
return state
def step(self, action=None):
if(self.need_reset):
raise Exception("Must \"reset\" before doing any actions")
reward = - 0.1
self.steps += 1
if(action is None): # Only when there is no action input can we use keyboard control
pygame.time.delay(100) # 10 FPS
action = self.maze_core.movement_control(self.keyboard_press)
else:
action = DISCRETE_ACTIONS[action]
done = self.maze_core.do_action(action)
if(done):
reward += 20
elif(self.steps >= self.max_steps or self.key_done):
done = True
if(done):
self.need_reset=True
info = {"steps": self.steps}
return self.maze_core.get_observation(), reward, done, info
def render(self):
self.key_done, self.keyboard_press = self.maze_core.render_update(self.render_godview)
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0
| 7
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3890cc4211e40f811adcf26f09cacb1ddcb633d1
| 81,903
|
py
|
Python
|
async_v20/interface/order.py
|
gshklover/async_v20
|
965346eafee09ee4ee510b22a064d3cf661b7aa4
|
[
"MIT"
] | 23
|
2017-10-30T18:49:11.000Z
|
2022-02-08T12:22:18.000Z
|
async_v20/interface/order.py
|
gshklover/async_v20
|
965346eafee09ee4ee510b22a064d3cf661b7aa4
|
[
"MIT"
] | 23
|
2017-10-20T12:32:18.000Z
|
2021-03-13T07:43:23.000Z
|
async_v20/interface/order.py
|
gshklover/async_v20
|
965346eafee09ee4ee510b22a064d3cf661b7aa4
|
[
"MIT"
] | 12
|
2017-10-30T18:49:13.000Z
|
2021-02-06T02:26:37.000Z
|
from .decorators import endpoint, shortcut
from ..definitions.types import ClientExtensions
from ..definitions.types import ClientID
from ..definitions.types import DateTime
from ..definitions.types import DecimalNumber
from ..definitions.types import InstrumentName
from ..definitions.types import LimitOrderRequest
from ..definitions.types import MarketIfTouchedOrderRequest
from ..definitions.types import MarketOrderRequest
from ..definitions.types import OrderID
from ..definitions.types import OrderPositionFill
from ..definitions.types import OrderRequest
from ..definitions.types import OrderSpecifier
from ..definitions.types import OrderStateFilter
from ..definitions.types import OrderTriggerCondition
from ..definitions.types import OrderType
from ..definitions.types import PriceValue
from ..definitions.types import StopLossDetails
from ..definitions.types import StopLossOrderRequest
from ..definitions.types import StopOrderRequest
from ..definitions.types import TakeProfitDetails
from ..definitions.types import TakeProfitOrderRequest
from ..definitions.types import TimeInForce
from ..definitions.types import TradeID
from ..definitions.types import TrailingStopLossDetails
from ..definitions.types import TrailingStopLossOrderRequest
from ..endpoints.annotations import Count
from ..endpoints.annotations import Ids
from ..endpoints.annotations import TradeClientExtensions
from ..endpoints.order import *
from ..definitions.helpers import sentinel
__all__ = ['OrderInterface']
class OrderInterface(object):
@endpoint(POSTOrders)
def post_order(self, order_request: OrderRequest = sentinel):
"""
Post an OrderRequest.
Args:
order_request: :class:`~async_v20.OrderRequest`
or a class derived from OrderRequest
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
pass
@shortcut
def create_order(self, instrument: InstrumentName, units: DecimalNumber, type: OrderType = 'MARKET',
trade_id: TradeID = sentinel, price: PriceValue = sentinel, client_trade_id: ClientID = sentinel,
time_in_force: TimeInForce = sentinel, gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = sentinel, client_extensions: ClientExtensions = sentinel,
distance: PriceValue = sentinel, price_bound: PriceValue = sentinel,
position_fill: OrderPositionFill = sentinel, take_profit_on_fill: TakeProfitDetails = sentinel,
stop_loss_on_fill: StopLossDetails = sentinel,
trailing_stop_loss_on_fill: TrailingStopLossDetails = sentinel,
trade_client_extensions: ClientExtensions = sentinel):
"""
create an OrderRequest
Args:
trade_id: :class:`~async_v20.TradeID`
price: :class:`~async_v20.PriceValue`
type: :class:`~async_v20.OrderType`
client_trade_id: :class:`~async_v20.ClientID`
time_in_force: :class:`~async_v20.TimeInForce`
gtd_time: :class:`~async_v20.DateTime`
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
client_extensions: :class:`~async_v20.ClientExtensions`
distance: :class:`~async_v20.PriceValue`
instrument: :class:`~async_v20.InstrumentName`
units: :class:`~async_v20.Unit`
price_bound: :class:`~async_v20.PriceValue`
position_fill: :class:`~async_v20.OrderPositionFill`
take_profit_on_fill: :class:`~async_v20.TakeProfitDetails`
stop_loss_on_fill: :class:`~async_v20.StopLossDetails`
trailing_stop_loss_on_fill: :class:`~async_v20.TrailingStopLossDetails`
trade_client_extensions: :class:`~async_v20.ClientExtensions`
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=OrderRequest(
instrument=instrument, units=units, type=type, trade_id=trade_id, price=price,
client_trade_id=client_trade_id, time_in_force=time_in_force, gtd_time=gtd_time,
trigger_condition=trigger_condition, client_extensions=client_extensions,
distance=distance, price_bound=price_bound, position_fill=position_fill,
take_profit_on_fill=take_profit_on_fill, stop_loss_on_fill=stop_loss_on_fill,
trailing_stop_loss_on_fill=trailing_stop_loss_on_fill,
trade_client_extensions=trade_client_extensions))
@endpoint(GETOrders)
def list_orders(self,
ids: Ids = sentinel,
state: OrderStateFilter = sentinel,
instrument: InstrumentName = sentinel,
count: Count = sentinel,
before_id: OrderID = sentinel):
"""
Get a list of Orders for an Account
Args:
ids: :class:`~async_v20.endpoints.annotations.Ids`
list of Order IDs to retrieve
state: :class:`~async_v20.OrderStateFilter`
The state to filter the requested Orders by
instrument: :class:`~async_v20.InstrumentName`
The instrument to filter the requested orders by
count: :class:`~async_v20.endpoints.annotations.Count`
The maximum number of Orders to return
before_id: :class:`~async_v20.OrderID`
The maximum Order ID to return. If not provided the most recent
Orders in the Account are returned
Returns:
status [200]
:class:`~async_v20.interface.response.Response`
(orders=( :class:`~async_v20.Order`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
"""
pass
@endpoint(GETPendingOrders)
def list_pending_orders(self):
"""
List all pending Orders
Returns:
status [200]
:class:`~async_v20.interface.response.Response`
(orders=( :class:`~async_v20.Order`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
"""
pass
@endpoint(GETOrderSpecifier)
def get_order(self, order_specifier: OrderSpecifier = sentinel):
"""
Get details for a single Order
Args:
order_specifier: :class:`~async_v20.OrderSpecifier`
The Order Specifier
Returns:
status [200]
:class:`~async_v20.interface.response.Response`
(order= :class:`~async_v20.Order`,
lastTransactionID= :class:`~async_v20.TransactionID`)
"""
pass
@endpoint(PUTOrderSpecifier)
def replace_order(self,
order_specifier: OrderSpecifier = sentinel,
order_request: OrderRequest = sentinel):
"""
Replace an Order by simultaneously cancelling it and
creating a replacement Order
Args:
order_specifier: :class:`~async_v20.OrderSpecifier`
The Order Specifier
order_request: :class:`~async_v20.OrderRequest`
Specification of the replacing Order
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
replacingOrderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
pass
@endpoint(PUTOrderSpecifierCancel)
def cancel_order(self, order_specifier: OrderSpecifier = sentinel):
"""
Cancel a pending Order
Args:
order_specifier: :class:`~async_v20.OrderSpecifier`
The Order Specifier
Returns:
status [200]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.OrderCancelRejectTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
pass
@endpoint(PUTClientExtensions)
def set_client_extensions(self,
order_specifier: OrderSpecifier = sentinel,
client_extensions: ClientExtensions = sentinel,
trade_client_extensions: TradeClientExtensions = sentinel):
"""
Update the Client Extensions for an Order . Do not set,
modify, or delete clientExtensions if your account is associated with
MT4.
Args:
order_specifier: :class:`~async_v20.OrderSpecifier`
The Order Specifier
client_extensions: :class:`~async_v20.ClientExtensions`
The Client Extensions to update for the Order. Do not set,
modify, or delete clientExtensions if your account is
associated with MT4.
trade_client_extensions: :class:`~async_v20.endpoints.annotations.TradeClientExtensions`
The Client Extensions to update for the Trade created when the
Order is filled. Do not set, modify, or delete clientExtensions
if your account is associated with MT4.
Returns:
status [200]
:class:`~async_v20.interface.response.Response`
(orderClientExtensionsModifyTransaction=
:class:`~async_v20.OrderClientExtensionsModifyTransaction`,
lastTransactionID= :class:`~async_v20.TransactionID`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),)
status [400]
:class:`~async_v20.interface.response.Response`
(orderClientExtensionsModifyRejectTransaction=
:class:`~async_v20.OrderClientExtensionsModifyRejectTransaction`,
lastTransactionID= :class:`~async_v20.TransactionID`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderClientExtensionsModifyRejectTransaction=
:class:`~async_v20.OrderClientExtensionsModifyRejectTransaction`,
lastTransactionID= :class:`~async_v20.TransactionID`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
pass
@shortcut
def market_order(self, instrument: InstrumentName, units: DecimalNumber,
time_in_force: TimeInForce = 'FOK', price_bound: PriceValue = sentinel,
position_fill: OrderPositionFill = 'DEFAULT', client_extensions: ClientExtensions = sentinel,
take_profit_on_fill: TakeProfitDetails = sentinel, stop_loss_on_fill: StopLossDetails = sentinel,
trailing_stop_loss_on_fill: TrailingStopLossDetails = sentinel,
trade_client_extensions: ClientExtensions = sentinel):
"""
Create a Market Order Request
Args:
instrument: :class:`~async_v20.InstrumentName`
The Market Order's Instrument.
units: :class:`~async_v20.Unit`
The quantity requested to be filled by the Market Order. A posititive number of units
results in a long Order, and a negative number of units results in a short Order.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the Market Order.
Restricted to FOK or IOC for a MarketOrder.
price_bound: :class:`~async_v20.PriceValue`
The worst price that the client is willing to have the Market Order filled at.
position_fill: :class:`~async_v20.OrderPositionFill`
Specification of how Positions in the Account
are modified when the Order is filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
take_profit_on_fill: :class:`~async_v20.TakeProfitDetails`
TakeProfitDetails specifies the details of a Take Profit Order to be created on behalf of
a client. This may happen when an Order
is filled that opens a Trade requiring a Take Profit, or when a Trade's dependent Take Profit Order is
modified directly through the Trade.
stop_loss_on_fill: :class:`~async_v20.StopLossDetails`
StopLossDetails specifies the details of a Stop Loss Order to be created on behalf of a
client. This may happen when an Order
is filled that opens a Trade requiring a Stop Loss, or when a Trade's dependent Stop Loss Order is modified
directly through the Trade.
trailing_stop_loss_on_fill: :class:`~async_v20.TrailingStopLossDetails`
TrailingStopLossDetails specifies the details of a Trailing Stop Loss Order to be
created on behalf of a client. This may happen when an Order is
filled that opens a Trade requiring a Trailing Stop Loss, or when a Trade's dependent Trailing Stop Loss
Order is modified directly through the Trade.
trade_client_extensions: :class:`~async_v20.ClientExtensions`
Client Extensions to add to the Trade created when the Order is filled (if such a
Trade is created). Do not set, modify, or delete tradeClientExtensions if your account is associated with
MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=MarketOrderRequest(
instrument=instrument, units=units, time_in_force=time_in_force,
price_bound=price_bound, position_fill=position_fill,
client_extensions=client_extensions,
take_profit_on_fill=take_profit_on_fill,
stop_loss_on_fill=stop_loss_on_fill,
trailing_stop_loss_on_fill=trailing_stop_loss_on_fill,
trade_client_extensions=trade_client_extensions
))
@shortcut
def limit_order(self, instrument: InstrumentName, units: DecimalNumber, price: PriceValue,
time_in_force: TimeInForce = 'GTC', gtd_time: DateTime = sentinel,
position_fill: OrderPositionFill = 'DEFAULT', trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel, take_profit_on_fill: TakeProfitDetails = sentinel,
stop_loss_on_fill: StopLossDetails = sentinel,
trailing_stop_loss_on_fill: TrailingStopLossDetails = sentinel,
trade_client_extensions: ClientExtensions = sentinel):
"""
Create a Limit Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The Limit Order's Instrument.
units: :class:`~async_v20.Unit`
The quantity requested to be filled by the Limit Order. A posititive number of units
results in a long Order, and a negative number of units results in a short Order.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the Limit Order. The Limit Order will only be
filled by a market price that is equal to or better than this price.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the Limit Order.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the Limit Order will
be cancelled if its timeInForce is "GTD".
position_fill: :class:`~async_v20.OrderPositionFill`
Specification of how Positions in the Account
are modified when the Order is filled.
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
take_profit_on_fill: :class:`~async_v20.TakeProfitDetails`
TakeProfitDetails specifies the details of a Take Profit Order to be created on behalf of
a client. This may happen when an Order
is filled that opens a Trade requiring a Take Profit, or when a Trade's dependent Take Profit Order is
modified directly through the Trade.
stop_loss_on_fill: :class:`~async_v20.StopLossDetails`
StopLossDetails specifies the details of a Stop Loss Order to be created on behalf of a
client. This may happen when an Order
is filled that opens a Trade requiring a Stop Loss, or when a Trade's dependent Stop Loss Order is modified
directly through the Trade.
trailing_stop_loss_on_fill: :class:`~async_v20.TrailingStopLossDetails`
TrailingStopLossDetails specifies the details of a Trailing Stop Loss Order to be
created on behalf of a client. This may happen when an Order is
filled that opens a Trade requiring a Trailing Stop Loss, or when a Trade's dependent Trailing Stop Loss
Order is modified directly through the Trade.
trade_client_extensions: :class:`~async_v20.ClientExtensions`
Client Extensions to add to the Trade created when the Order is filled (if such a
Trade is created). Do not set, modify, or delete tradeClientExtensions if your account is associated with
MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=LimitOrderRequest(
instrument=instrument, units=units, price=price,
time_in_force=time_in_force, gtd_time=gtd_time,
position_fill=position_fill,
trigger_condition=trigger_condition,
client_extensions=client_extensions,
take_profit_on_fill=take_profit_on_fill,
stop_loss_on_fill=stop_loss_on_fill,
trailing_stop_loss_on_fill=trailing_stop_loss_on_fill,
trade_client_extensions=trade_client_extensions
))
@shortcut
def limit_replace_order(self,
instrument: InstrumentName, order_specifier: OrderSpecifier, units: DecimalNumber,
price: PriceValue,
time_in_force: TimeInForce = 'GTC', gtd_time: DateTime = sentinel,
position_fill: OrderPositionFill = 'DEFAULT',
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel, take_profit_on_fill: TakeProfitDetails = sentinel,
stop_loss_on_fill: StopLossDetails = sentinel,
trailing_stop_loss_on_fill: TrailingStopLossDetails = sentinel,
trade_client_extensions: ClientExtensions = sentinel):
"""
Replace a pending Limit Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The Limit Order's Instrument.
order_specifier: :class:`~async_v20.OrderSpecifier`
The ID of the Limit Order to replace
units: :class:`~async_v20.Unit`
The quantity requested to be filled by the Limit Order. A posititive number of units
results in a long Order, and a negative number of units results in a short Order.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the Limit Order. The Limit Order will only be
filled by a market price that is equal to or better than this price.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the Limit Order.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the Limit Order will
be cancelled if its timeInForce is "GTD".
position_fill: :class:`~async_v20.OrderPositionFill`
Specification of how Positions in the Account
are modified when the Order is filled.
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
take_profit_on_fill: :class:`~async_v20.TakeProfitDetails`
TakeProfitDetails specifies the details of a Take Profit Order to be created on behalf of
a client. This may happen when an Order
is filled that opens a Trade requiring a Take Profit, or when a Trade's dependent Take Profit Order is
modified directly through the Trade.
stop_loss_on_fill: :class:`~async_v20.StopLossDetails`
StopLossDetails specifies the details of a Stop Loss Order to be created on behalf of a
client. This may happen when an Order
is filled that opens a Trade requiring a Stop Loss, or when a Trade's dependent Stop Loss Order is modified
directly through the Trade.
trailing_stop_loss_on_fill: :class:`~async_v20.TrailingStopLossDetails`
TrailingStopLossDetails specifies the details of a Trailing Stop Loss Order to be
created on behalf of a client. This may happen when an Order is
filled that opens a Trade requiring a Trailing Stop Loss, or when a Trade's dependent Trailing Stop Loss
Order is modified directly through the Trade.
trade_client_extensions: :class:`~async_v20.ClientExtensions`
Client Extensions to add to the Trade created when the Order is filled (if such a
Trade is created). Do not set, modify, or delete tradeClientExtensions if your account is associated with
MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
replacingOrderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.replace_order(
order_specifier=order_specifier,
order_request=LimitOrderRequest(
instrument=instrument, units=units, price=price,
time_in_force=time_in_force, gtd_time=gtd_time, position_fill=position_fill,
trigger_condition=trigger_condition, client_extensions=client_extensions,
take_profit_on_fill=take_profit_on_fill,
stop_loss_on_fill=stop_loss_on_fill,
trailing_stop_loss_on_fill=trailing_stop_loss_on_fill,
trade_client_extensions=trade_client_extensions
))
@shortcut
def stop_order(self, instrument: InstrumentName, trade_id: TradeID, price: PriceValue,
client_trade_id: ClientID = sentinel, time_in_force: TimeInForce = 'GTC', gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = 'DEFAULT', client_extensions: ClientExtensions = sentinel):
"""
Create a Stop Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The StopOrder's Instrument.
trade_id: :class:`~async_v20.TradeID`
The ID of the Trade to close when the price threshold is breached.
client_trade_id: :class:`~async_v20.TradeID`
The client ID of the Trade to be closed when the price threshold is breached.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the StopLoss Order. The associated Trade will be
closed by a market price that is equal to or worse than this threshold.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the StopLoss Order. Restricted
to "GTC", "GFD" and "GTD" for StopLoss Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the StopLoss Order will
be cancelled if its timeInForce is "GTD".
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=StopLossOrderRequest(
instrument=instrument,
trade_id=trade_id, price=price, client_trade_id=client_trade_id,
time_in_force=time_in_force, gtd_time=gtd_time,
trigger_condition=trigger_condition, client_extensions=client_extensions
))
@shortcut
def stop_replace_order(self,
instrument: InstrumentName,
order_specifier: OrderSpecifier,
units: DecimalNumber, price: PriceValue,
price_bound: PriceValue = sentinel, time_in_force: TimeInForce = 'GTC', gtd_time: DateTime = sentinel,
position_fill: OrderPositionFill = 'DEFAULT',
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel, take_profit_on_fill: TakeProfitDetails = sentinel,
stop_loss_on_fill: StopLossDetails = sentinel,
trailing_stop_loss_on_fill: TrailingStopLossDetails = sentinel,
trade_client_extensions: ClientExtensions = sentinel):
"""
Replace a pending Stop Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The Stop Order's Instrument.
order_specifier: :class:`~async_v20.OrderSpecifier`
The ID of the Stop Order to replace
units: :class:`~async_v20.Unit`
The quantity requested to be filled by the Stop Order. A posititive number of units
results in a long Order, and a negative number of units results in a short Order.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the Stop Order. The Stop Order will only be
filled by a market price that is equal to or worse than this price.
price_bound: :class:`~async_v20.PriceValue`
The worst market price that may be used to fill this Stop Order. If the market gaps and
crosses through both the price and the priceBound, the Stop Order will be cancelled instead of being filled.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the Stop Order.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the Stop Order will
be cancelled if its timeInForce is "GTD".
position_fill: :class:`~async_v20.OrderPositionFill`
Specification of how Positions in the Account
are modified when the Order is filled.
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
take_profit_on_fill: :class:`~async_v20.TakeProfitDetails`
TakeProfitDetails specifies the details of a Take Profit Order to be created on behalf of
a client. This may happen when an Order
is filled that opens a Trade requiring a Take Profit, or when a Trade's dependent Take Profit Order is
modified directly through the Trade.
stop_loss_on_fill: :class:`~async_v20.StopLossDetails`
StopLossDetails specifies the details of a Stop Loss Order to be created on behalf of a
client. This may happen when an Order
is filled that opens a Trade requiring a Stop Loss, or when a Trade's dependent Stop Loss Order is modified
directly through the Trade.
trailing_stop_loss_on_fill: :class:`~async_v20.TrailingStopLossDetails`
TrailingStopLossDetails specifies the details of a Trailing Stop Loss Order to be
created on behalf of a client. This may happen when an Order is
filled that opens a Trade requiring a Trailing Stop Loss, or when a Trade's dependent Trailing Stop Loss
Order is modified directly through the Trade.
trade_client_extensions: :class:`~async_v20.ClientExtensions`
Client Extensions to add to the Trade created when the Order is filled (if such a
Trade is created). Do not set, modify, or delete tradeClientExtensions if your account is associated with
MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
replacingOrderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.replace_order(
order_specifier=order_specifier,
order_request=StopOrderRequest(
instrument=instrument, units=units, price=price,
price_bound=price_bound, time_in_force=time_in_force,
gtd_time=gtd_time, position_fill=position_fill,
trigger_condition=trigger_condition,
client_extensions=client_extensions,
take_profit_on_fill=take_profit_on_fill,
stop_loss_on_fill=stop_loss_on_fill,
trailing_stop_loss_on_fill=trailing_stop_loss_on_fill,
trade_client_extensions=trade_client_extensions
))
@shortcut
def market_if_touched_order(self, instrument: InstrumentName, units: DecimalNumber, price: PriceValue,
price_bound: PriceValue = sentinel,
time_in_force: TimeInForce = 'GTC', gtd_time: DateTime = sentinel,
position_fill: OrderPositionFill = 'DEFAULT',
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel,
take_profit_on_fill: TakeProfitDetails = sentinel,
stop_loss_on_fill: StopLossDetails = sentinel,
trailing_stop_loss_on_fill: TrailingStopLossDetails = sentinel,
trade_client_extensions: ClientExtensions = sentinel):
"""
Create a market if touched order
Args:
instrument: :class:`~async_v20.InstrumentName`
The MarketIfTouched Order's Instrument.
units: :class:`~async_v20.Unit`
The quantity requested to be filled by the MarketIfTouched Order. A posititive number of units
results in a long Order, and a negative number of units results in a short Order.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the MarketIfTouched Order. The MarketIfTouched Order will only be
filled by a market price that crosses this price from the direction of the market price
at the time when the Order was created (the initialMarketPrice). Depending on the value of the Order's
price and initialMarketPrice, the MarketIfTouchedOrder will behave like a Limit or a Stop Order.
price_bound: :class:`~async_v20.PriceValue`
The worst market price that may be used to fill this MarketIfTouched Order.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the MarketIfTouched Order. Restricted
to "GTC", "GFD" and "GTD" for MarketIfTouched Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the MarketIfTouched Order will
be cancelled if its timeInForce is "GTD".
position_fill: :class:`~async_v20.OrderPositionFill`
Specification of how Positions in the Account
are modified when the Order is filled.
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
take_profit_on_fill: :class:`~async_v20.TakeProfitDetails`
TakeProfitDetails specifies the details of a Take Profit Order to be created on behalf of
a client. This may happen when an Order
is filled that opens a Trade requiring a Take Profit, or when a Trade's dependent Take Profit Order is
modified directly through the Trade.
stop_loss_on_fill: :class:`~async_v20.StopLossDetails`
StopLossDetails specifies the details of a Stop Loss Order to be created on behalf of a
client. This may happen when an Order
is filled that opens a Trade requiring a Stop Loss, or when a Trade's dependent Stop Loss Order is modified
directly through the Trade.
trailing_stop_loss_on_fill: :class:`~async_v20.TrailingStopLossDetails`
TrailingStopLossDetails specifies the details of a Trailing Stop Loss Order to be
created on behalf of a client. This may happen when an Order is
filled that opens a Trade requiring a Trailing Stop Loss, or when a Trade's dependent Trailing Stop Loss
Order is modified directly through the Trade.
trade_client_extensions: :class:`~async_v20.ClientExtensions`
Client Extensions to add to the Trade created when the Order is filled (if such a
Trade is created). Do not set, modify, or delete tradeClientExtensions if your account is associated with
MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=MarketIfTouchedOrderRequest(
instrument=instrument, units=units, price=price,
price_bound=price_bound, time_in_force=time_in_force,
gtd_time=gtd_time, position_fill=position_fill,
trigger_condition=trigger_condition,
client_extensions=client_extensions,
take_profit_on_fill=take_profit_on_fill,
stop_loss_on_fill=stop_loss_on_fill,
trailing_stop_loss_on_fill=trailing_stop_loss_on_fill,
trade_client_extensions=trade_client_extensions
))
@shortcut
def market_if_touched_replace_order(self,
instrument: InstrumentName,
order_specifier: OrderSpecifier,
units: DecimalNumber, price: PriceValue,
price_bound: PriceValue = sentinel,
time_in_force: TimeInForce = 'GTC', gtd_time: DateTime = sentinel,
position_fill: OrderPositionFill = 'DEFAULT',
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel,
take_profit_on_fill: TakeProfitDetails = sentinel,
stop_loss_on_fill: StopLossDetails = sentinel,
trailing_stop_loss_on_fill: TrailingStopLossDetails = sentinel,
trade_client_extensions: ClientExtensions = sentinel
):
"""
Replace a pending market if touched order
Args:
instrument: :class:`~async_v20.InstrumentName`
The MarketIfTouched Order's Instrument.
order_specifier: :class:`~async_v20.OrderSpecifier`
The ID of the MarketIfTouched Order to replace
units: :class:`~async_v20.Unit`
The quantity requested to be filled by the MarketIfTouched Order. A posititive number of units
results in a long Order, and a negative number of units results in a short Order.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the MarketIfTouched Order. The MarketIfTouched Order will only be
filled by a market price that crosses this price from the direction of the market price
at the time when the Order was created (the initialMarketPrice). Depending on the value of the Order's
price and initialMarketPrice, the MarketIfTouchedOrder will behave like a Limit or a Stop Order.
price_bound: :class:`~async_v20.PriceValue`
The worst market price that may be used to fill this MarketIfTouched Order.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the MarketIfTouched Order. Restricted
to "GTC", "GFD" and "GTD" for MarketIfTouched Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the MarketIfTouched Order will
be cancelled if its timeInForce is "GTD".
position_fill: :class:`~async_v20.OrderPositionFill`
Specification of how Positions in the Account
are modified when the Order is filled.
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
take_profit_on_fill: :class:`~async_v20.TakeProfitDetails`
TakeProfitDetails specifies the details of a Take Profit Order to be created on behalf of
a client. This may happen when an Order
is filled that opens a Trade requiring a Take Profit, or when a Trade's dependent Take Profit Order is
modified directly through the Trade.
stop_loss_on_fill: :class:`~async_v20.StopLossDetails`
StopLossDetails specifies the details of a Stop Loss Order to be created on behalf of a
client. This may happen when an Order
is filled that opens a Trade requiring a Stop Loss, or when a Trade's dependent Stop Loss Order is modified
directly through the Trade.
trailing_stop_loss_on_fill: :class:`~async_v20.TrailingStopLossDetails`
TrailingStopLossDetails specifies the details of a Trailing Stop Loss Order to be
created on behalf of a client. This may happen when an Order is
filled that opens a Trade requiring a Trailing Stop Loss, or when a Trade's dependent Trailing Stop Loss
Order is modified directly through the Trade.
trade_client_extensions: :class:`~async_v20.ClientExtensions`
Client Extensions to add to the Trade created when the Order is filled (if such a
Trade is created). Do not set, modify, or delete tradeClientExtensions if your account is associated with
MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
replacingOrderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.replace_order(
order_specifier=order_specifier,
order_request=MarketIfTouchedOrderRequest(
instrument=instrument, units=units,
price=price, price_bound=price_bound,
time_in_force=time_in_force,
gtd_time=gtd_time,
position_fill=position_fill,
trigger_condition=trigger_condition,
client_extensions=client_extensions,
take_profit_on_fill=take_profit_on_fill,
stop_loss_on_fill=stop_loss_on_fill,
trailing_stop_loss_on_fill=trailing_stop_loss_on_fill,
trade_client_extensions=trade_client_extensions)
)
@shortcut
def take_profit_order(self, instrument: InstrumentName, trade_id: TradeID, price: PriceValue,
client_trade_id: ClientID = sentinel, time_in_force: TimeInForce = 'GTC',
gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel):
"""
Create a take profit order
Args:
instrument: :class:`~async_v20.InstrumentName`
The TakeProfitOrder's Instrument.
trade_id: :class:`~async_v20.TradeID`
The ID of the Trade to close when the price threshold is breached.
client_trade_id: :class:`~async_v20.TradeID`
The client ID of the Trade to be closed when the price threshold is breached.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the TakeProfit Order. The associated Trade will be
closed by a market price that is equal to or better than this threshold.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the TakeProfit Order. Restricted
to "GTC", "GFD" and "GTD" for TakeProfit Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the TakeProfit Order will
be cancelled if its timeInForce is "GTD".
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=TakeProfitOrderRequest(
instrument=instrument,
trade_id=trade_id, price=price, client_trade_id=client_trade_id,
time_in_force=time_in_force, gtd_time=gtd_time,
trigger_condition=trigger_condition,
client_extensions=client_extensions
))
@shortcut
def take_profit_replace_order(self,
instrument: InstrumentName,
order_specifier: OrderSpecifier,
trade_id: TradeID, price: PriceValue,
client_trade_id: ClientID = sentinel, time_in_force: TimeInForce = 'GTC',
gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel
):
"""
Replace a pending take profit order
Args:
instrument: :class:`~async_v20.InstrumentName`
The TakeProfitOrder's Instrument.
order_specifier: :class:`~async_v20.OrderSpecifier`
The ID of the Take Profit Order to replace
trade_id: :class:`~async_v20.TradeID`
The ID of the Trade to close when the price threshold is breached.
client_trade_id: :class:`~async_v20.TradeID`
The client ID of the Trade to be closed when the price threshold is breached.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the TakeProfit Order. The associated Trade will be
closed by a market price that is equal to or better than this threshold.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the TakeProfit Order. Restricted
to "GTC", "GFD" and "GTD" for TakeProfit Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the TakeProfit Order will
be cancelled if its timeInForce is "GTD".
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
replacingOrderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.replace_order(
order_specifier=order_specifier,
order_request=TakeProfitOrderRequest(
instrument=instrument,
trade_id=trade_id, price=price,
client_trade_id=client_trade_id,
time_in_force=time_in_force, gtd_time=gtd_time,
trigger_condition=trigger_condition,
client_extensions=client_extensions)
)
@shortcut
def stop_loss_order(self, instrument: InstrumentName, trade_id: TradeID, price: PriceValue,
client_trade_id: ClientID = sentinel, time_in_force: TimeInForce = 'GTC', gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel):
"""
Create a Stop Loss Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The StopLossOrder's Instrument.
trade_id: :class:`~async_v20.TradeID`
The ID of the Trade to close when the price threshold is breached.
client_trade_id: :class:`~async_v20.TradeID`
The client ID of the Trade to be closed when the price threshold is breached.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the StopLoss Order. The associated Trade will be
closed by a market price that is equal to or worse than this threshold.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the StopLoss Order. Restricted
to "GTC", "GFD" and "GTD" for StopLoss Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the StopLoss Order will
be cancelled if its timeInForce is "GTD".
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=StopLossOrderRequest(
instrument=instrument,
trade_id=trade_id, price=price, client_trade_id=client_trade_id,
time_in_force=time_in_force, gtd_time=gtd_time,
trigger_condition=trigger_condition, client_extensions=client_extensions
))
@shortcut
def stop_loss_replace_order(self,
instrument: InstrumentName,
order_specifier: OrderSpecifier,
trade_id: TradeID, price: PriceValue,
client_trade_id: ClientID = sentinel, time_in_force: TimeInForce = 'GTC',
gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel):
"""
Replace a pending Stop Loss Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The StopLossOrder's Instrument.
order_specifier: :class:`~async_v20.OrderSpecifier`
The ID of the Stop Loss Order to replace
trade_id: :class:`~async_v20.TradeID`
The ID of the Trade to close when the price threshold is breached.
client_trade_id: :class:`~async_v20.TradeID`
The client ID of the Trade to be closed when the price threshold is breached.
price: :class:`~async_v20.PriceValue`
The price threshold specified for the StopLoss Order. The associated Trade will be
closed by a market price that is equal to or worse than this threshold.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the StopLoss Order. Restricted
to "GTC", "GFD" and "GTD" for StopLoss Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the StopLoss Order will
be cancelled if its timeInForce is "GTD".
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
replacingOrderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.replace_order(
order_specifier=order_specifier,
order_request=StopLossOrderRequest(
instrument=instrument,
trade_id=trade_id, price=price,
client_trade_id=client_trade_id,
time_in_force=time_in_force, gtd_time=gtd_time,
trigger_condition=trigger_condition,
client_extensions=client_extensions
))
@shortcut
def trailing_stop_loss_order(self,
instrument: InstrumentName,
trade_id: TradeID, distance: PriceValue,
client_trade_id: ClientID = sentinel, time_in_force: TimeInForce = 'GTC',
gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel):
"""
Create a Trailing Stop Loss Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The TrailingStopLossOrder's Instrument.
trade_id: :class:`~async_v20.TradeID`
The ID of the Trade to close when the price threshold is breached.
client_trade_id: :class:`~async_v20.TradeID`
The client ID of the Trade to be closed when the price threshold is breached.
distance: :class:`~async_v20.PriceValue`
The price distance specified for the TrailingStopLoss Order.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the TrailingStopLoss Order. Restricted
to "GTC", "GFD" and "GTD" for TrailingStopLoss Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the StopLoss Order will
be cancelled if its timeInForce is "GTD".
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.post_order(
order_request=TrailingStopLossOrderRequest(
instrument=instrument,
trade_id=trade_id, distance=distance,
client_trade_id=client_trade_id,
time_in_force=time_in_force,
gtd_time=gtd_time,
trigger_condition=trigger_condition,
client_extensions=client_extensions
))
@shortcut
def trailing_stop_loss_replace_order(self,
instrument: InstrumentName,
order_specifier: OrderSpecifier,
trade_id: TradeID, distance: PriceValue,
client_trade_id: ClientID = sentinel, time_in_force: TimeInForce = 'GTC',
gtd_time: DateTime = sentinel,
trigger_condition: OrderTriggerCondition = 'DEFAULT',
client_extensions: ClientExtensions = sentinel):
"""
Replace a pending Trailing Stop Loss Order
Args:
instrument: :class:`~async_v20.InstrumentName`
The TrailingStopLossOrder's Instrument.
order_specifier: :class:`~async_v20.OrderSpecifier`
The ID of the Take Profit Order to replace
trade_id: :class:`~async_v20.TradeID`
The ID of the Trade to close when the price threshold is breached.
client_trade_id: :class:`~async_v20.TradeID`
The client ID of the Trade to be closed when the price threshold is breached.
distance: :class:`~async_v20.PriceValue`
The price distance specified for the TrailingStopLoss Order.
time_in_force: :class:`~async_v20.TimeInForce`
The time-in-force requested for the TrailingStopLoss Order. Restricted
to "GTC", "GFD" and "GTD" for TrailingStopLoss Orders.
gtd_time: :class:`~async_v20.DateTime`
The date/time when the StopLoss Order will
be cancelled if its timeInForce is "GTD".
trigger_condition: :class:`~async_v20.OrderTriggerCondition`
Specification of what component of a price should be used
for comparison when determining if the Order should be filled.
client_extensions: :class:`~async_v20.ClientExtensions`
The client extensions to add to the Order. Do not set,
modify, or delete clientExtensions if your account is associated with MT4.
Returns:
status [201]
:class:`~async_v20.interface.response.Response`
(orderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
orderCreateTransaction= :class:`~async_v20.Transaction`,
orderFillTransaction= :class:`~async_v20.OrderFillTransaction`,
orderReissueTransaction= :class:`~async_v20.Transaction`,
orderReissueRejectTransaction= :class:`~async_v20.Transaction`,
replacingOrderCancelTransaction= :class:`~async_v20.OrderCancelTransaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`)
status [400]
:class:`~async_v20.interface.response.Response`
(orderRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
status [401]
:class:`~async_v20.interface.response.Response`
(orderCancelRejectTransaction= :class:`~async_v20.Transaction`,
relatedTransactionIDs=( :class:`~async_v20.TransactionID`, ...),
lastTransactionID= :class:`~async_v20.TransactionID`,
errorCode= :class:`~builtins.str`,
errorMessage= :class:`~builtins.str`)
"""
return self.replace_order(
order_specifier=order_specifier,
order_request=TrailingStopLossOrderRequest(
instrument=instrument,
trade_id=trade_id, distance=distance,
client_trade_id=client_trade_id,
time_in_force=time_in_force,
gtd_time=gtd_time,
trigger_condition=trigger_condition,
client_extensions=client_extensions
))
| 55.565129
| 129
| 0.617828
| 7,980
| 81,903
| 6.174937
| 0.030827
| 0.092743
| 0.120566
| 0.057513
| 0.939281
| 0.932462
| 0.916937
| 0.909997
| 0.903543
| 0.89776
| 0
| 0.019416
| 0.305776
| 81,903
| 1,473
| 130
| 55.602851
| 0.847219
| 0.660684
| 0
| 0.700599
| 0
| 0
| 0.00929
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.062874
| false
| 0.020958
| 0.092814
| 0
| 0.200599
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
2a1140115a553ffe64e515ee78059a2f961b3130
| 172
|
py
|
Python
|
phenom/utils/__init__.py
|
LBJ-Wade/phenom
|
8f0fdc14099dac09cb2eef36d825e577340a8421
|
[
"MIT"
] | 1
|
2020-05-12T00:55:53.000Z
|
2020-05-12T00:55:53.000Z
|
phenom/utils/__init__.py
|
LBJ-Wade/phenom
|
8f0fdc14099dac09cb2eef36d825e577340a8421
|
[
"MIT"
] | null | null | null |
phenom/utils/__init__.py
|
LBJ-Wade/phenom
|
8f0fdc14099dac09cb2eef36d825e577340a8421
|
[
"MIT"
] | 1
|
2021-04-10T22:31:49.000Z
|
2021-04-10T22:31:49.000Z
|
from phenom.utils.utils import *
from phenom.utils.remnant import *
from phenom.utils.swsh import *
from phenom.utils.formats import *
# from phenom.utils.QNMdata import *
| 28.666667
| 36
| 0.784884
| 25
| 172
| 5.4
| 0.32
| 0.37037
| 0.555556
| 0.622222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122093
| 172
| 5
| 37
| 34.4
| 0.89404
| 0.197674
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
aa9a2b1cd87e8e14e6f7346f87f81a214264a4f4
| 3,103
|
py
|
Python
|
hawkeye_autotest/selenium/db.py
|
miaolujing/python_script
|
57ccf89f53ce0ce551804b5693515d8a8db4ce78
|
[
"Apache-2.0"
] | null | null | null |
hawkeye_autotest/selenium/db.py
|
miaolujing/python_script
|
57ccf89f53ce0ce551804b5693515d8a8db4ce78
|
[
"Apache-2.0"
] | null | null | null |
hawkeye_autotest/selenium/db.py
|
miaolujing/python_script
|
57ccf89f53ce0ce551804b5693515d8a8db4ce78
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import config, re, MySQLdb, MySQLdb.cursors
#数据库查询数据--给screen建counter使用
def readtaskid(des):
db = MySQLdb.connect(config.mysqlhost,config.mysqluser,config.mysqlpw,config.mysqlssid)
cursor = db.cursor()
sql = "select taskid from scheduletask where description like '%"+des+"%' and status = '0'"
try:
cursor.execute(sql)
results = cursor.fetchall()
data = []
for i in range(0, len(results)):
data.append(results[i][0])
return data
except Exception, e:
print e
db.close()
def readip(des):
db = MySQLdb.connect(config.mysqlhost,config.mysqluser,config.mysqlpw,config.mysqlssid)
cursor = db.cursor()
sql = "select id from ip where ip_name = '"+des+"'"
try:
cursor.execute(sql)
results = cursor.fetchall()
return len(results)
except Exception, e:
print e
db.close()
#数据库查询监控任务二级菜单id
def readid():
db = MySQLdb.connect(config.mysqlhost,config.mysqluser,config.mysqlpw,config.dashssid)
cursor = db.cursor()
sql = "select id from dashboard_screen where name = '"+config.secondmenu+"'"
try:
cursor.execute(sql)
results = cursor.fetchall()
return results[0][0]
except Exception, e:
print e
db.close()
#判断监控报表新增
def readmonitor(des):
db = MySQLdb.connect(config.mysqlhost,config.mysqluser,config.mysqlpw,config.dashssid)
cusor = db.cursor()
sql = "select title from dashboard_graph where counters = '"+des+"'"
try:
cusor.execute(sql)
results = cusor.fetchall()
return results[0][0]
except Exception, e:
print e
return False
db.close()
#获取报表get地址的id
def readgetid(des):
db = MySQLdb.connect(config.mysqlhost,config.mysqluser,config.mysqlpw,config.dashssid)
cusor = db.cursor()
sql = "select id from tmp_graph where counters = '"+des+"'"
try:
cusor.execute(sql)
results = cusor.fetchall()
return results[0][0]
except Exception, e:
print e
return False
db.close()
def readhttpgetid(des):
db = MySQLdb.connect(config.mysqlhost,config.mysqluser,config.mysqlpw,config.dashssid)
cusor = db.cursor()
sql = "select id from tmp_graph where counters like '%"+des+"'"
try:
cusor.execute(sql)
results = cusor.fetchall()
data = []
for i in range(0, len(results)):
data.append(results[i][0])
return data
except Exception, e:
print e
return False
db.close()
#获取定时任务id
def readcronid(des):
db = MySQLdb.connect(config.mysqlhost,config.mysqluser,config.mysqlpw,config.mysqlssid)
cursor = db.cursor()
sql = "select id from scheduletask where description like '%"+des+"%' and status = '0'"
try:
cursor.execute(sql)
results = cursor.fetchall()
data = []
for i in range(0, len(results)):
data.append(results[i][0])
return data
except Exception, e:
print e
db.close()
| 25.434426
| 95
| 0.619078
| 372
| 3,103
| 5.150538
| 0.201613
| 0.032881
| 0.058455
| 0.080376
| 0.83977
| 0.83977
| 0.83977
| 0.805846
| 0.747912
| 0.738518
| 0
| 0.00651
| 0.257493
| 3,103
| 121
| 96
| 25.644628
| 0.825087
| 0.035772
| 0
| 0.822222
| 0
| 0
| 0.126642
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.011111
| null | null | 0.077778
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
aadd641fa6cd8d036d3a05ffeead0396bccc03e8
| 3,137
|
py
|
Python
|
RecoJets/JetAnalyzers/python/QCD_GenJets_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 852
|
2015-01-11T21:03:51.000Z
|
2022-03-25T21:14:00.000Z
|
RecoJets/JetAnalyzers/python/QCD_GenJets_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 30,371
|
2015-01-02T00:14:40.000Z
|
2022-03-31T23:26:05.000Z
|
RecoJets/JetAnalyzers/python/QCD_GenJets_cfi.py
|
ckamtsikis/cmssw
|
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
|
[
"Apache-2.0"
] | 3,240
|
2015-01-02T05:53:18.000Z
|
2022-03-31T17:24:21.000Z
|
import FWCore.ParameterSet.Config as cms
source = cms.Source("PoolSource",
fileNames = cms.untracked.vstring(
'dcap://cmsgridftp.fnal.gov:24125/pnfs/fnal.gov/usr/cms/WAX/resilient/rharris/MC/QCD_2_1_8/PYTHIA6_QCDpt_0_15_10TeV_GenJets_800Kevts_ptHatFiltered.root',
'dcap://cmsgridftp.fnal.gov:24125/pnfs/fnal.gov/usr/cms/WAX/resilient/rharris/MC/QCD_2_1_8/PYTHIA6_QCDpt_470_600_10TeV_GenJets_800Kevts.root',
'dcap://cmsgridftp.fnal.gov:24125/pnfs/fnal.gov/usr/cms/WAX/resilient/rharris/MC/QCD_2_1_8/PYTHIA6_QCDpt_1400_1800_10TeV_GenJets_800Kevts.root',
'dcap://cmsgridftp.fnal.gov:24125/pnfs/fnal.gov/usr/cms/WAX/resilient/rharris/MC/QCD_2_1_8/PYTHIA6_QCDpt_1000_1400_10TeV_GenJets_800Kevts.root',
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)
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| 153
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| 0.888436
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| 0
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|
0
| 11
|
2ac3c6dd216d10bfa0457e3dd9bdfac2da207db1
| 675
|
py
|
Python
|
accounts/models.py
|
Shefin-CSE16/Course-Registration-Management
|
18130fc474ab9b25363d7ae3a56ebaa97a302217
|
[
"MIT"
] | null | null | null |
accounts/models.py
|
Shefin-CSE16/Course-Registration-Management
|
18130fc474ab9b25363d7ae3a56ebaa97a302217
|
[
"MIT"
] | null | null | null |
accounts/models.py
|
Shefin-CSE16/Course-Registration-Management
|
18130fc474ab9b25363d7ae3a56ebaa97a302217
|
[
"MIT"
] | null | null | null |
from django.db import models
# Create your models here.
class Account(models.Model):
Id = models.IntegerField(default=1)
Name = models.CharField(max_length=255, null="true")
Email = models.CharField(max_length=255, null="true")
Department = models.CharField(max_length=255, null="true")
Verified = models.BooleanField(default=False)
class Teacher(models.Model):
Name = models.CharField(max_length=255, null="true")
Email = models.CharField(max_length=255, null="true")
Department = models.CharField(max_length=255, null="true")
Designation = models.CharField(max_length=255, null="true")
Verified = models.BooleanField(default=False)
| 42.1875
| 63
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| 675
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| 0.735656
| 0.735656
| 0.735656
| 0.735656
| 0.735656
| 0.735656
| 0
| 0.037671
| 0.134815
| 675
| 16
| 64
| 42.1875
| 0.797945
| 0.035556
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| 0
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| 0
| 0
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| 0
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| false
| 0
| 0.076923
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| 0
| null | 1
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| 1
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|
0
| 9
|
2ae3d0963b949be063e2c91a8087566b1e670be2
| 642,560
|
py
|
Python
|
examples/Python/ReconstructionSystem/output.py
|
KayChou/Open3D
|
85fbd5bfab6b27cacfd1637385437f1c8c97a396
|
[
"MIT"
] | null | null | null |
examples/Python/ReconstructionSystem/output.py
|
KayChou/Open3D
|
85fbd5bfab6b27cacfd1637385437f1c8c97a396
|
[
"MIT"
] | null | null | null |
examples/Python/ReconstructionSystem/output.py
|
KayChou/Open3D
|
85fbd5bfab6b27cacfd1637385437f1c8c97a396
|
[
"MIT"
] | null | null | null |
====================================
Configuration
====================================
template_global_mesh : scene/integrated.ply
max_depth : 3.0
depth_map_type : redwood
voxel_size : 0.05
preference_loop_closure_odometry : 0.1
n_frames_per_fragment : 100
debug_mode : False
template_global_posegraph : scene/global_registration.json
global_registration : ransac
name : Captured frames using Realsense
n_keyframes_per_n_frame : 5
folder_fragment : fragments/
template_global_posegraph_optimized : scene/global_registration_optimized.json
max_depth_diff : 0.07
path_dataset : dataset/realsense/
template_fragment_pointcloud : fragments/fragment_%03d.ply
icp_method : color
path_intrinsic : dataset/realsense/camera_intrinsic.json
min_depth : 0.3
template_refined_posegraph_optimized : scene/refined_registration_optimized.json
tsdf_cubic_size : 3.0
python_multi_threading : False
preference_loop_closure_registration : 5.0
template_global_traj : scene/trajectory.log
folder_scene : scene/
template_fragment_posegraph_optimized : fragments/fragment_optimized_%03d.json
template_fragment_posegraph : fragments/fragment_%03d.json
template_refined_posegraph : scene/refined_registration.json
OpenCV is detected. Using ORB + 5pt algorithm
making fragments from RGBD sequence.
Fragment 000 / 009 :: RGBD matching between frame : 0 and 1
Fragment 000 / 009 :: RGBD matching between frame : 0 and 5
Fragment 000 / 009 :: RGBD matching between frame : 0 and 10
Fragment 000 / 009 :: RGBD matching between frame : 0 and 15
Fragment 000 / 009 :: RGBD matching between frame : 0 and 20
Fragment 000 / 009 :: RGBD matching between frame : 0 and 25
Fragment 000 / 009 :: RGBD matching between frame : 0 and 30
Fragment 000 / 009 :: RGBD matching between frame : 0 and 35
Fragment 000 / 009 :: RGBD matching between frame : 0 and 40
Fragment 000 / 009 :: RGBD matching between frame : 0 and 45
Fragment 000 / 009 :: RGBD matching between frame : 0 and 50
Fragment 000 / 009 :: RGBD matching between frame : 0 and 55
Fragment 000 / 009 :: RGBD matching between frame : 0 and 60
Fragment 000 / 009 :: RGBD matching between frame : 0 and 65
Fragment 000 / 009 :: RGBD matching between frame : 0 and 70
Fragment 000 / 009 :: RGBD matching between frame : 0 and 75
Fragment 000 / 009 :: RGBD matching between frame : 0 and 80
Fragment 000 / 009 :: RGBD matching between frame : 0 and 85
Fragment 000 / 009 :: RGBD matching between frame : 0 and 90
Fragment 000 / 009 :: RGBD matching between frame : 0 and 95
Fragment 000 / 009 :: RGBD matching between frame : 1 and 2
Fragment 000 / 009 :: RGBD matching between frame : 2 and 3
Fragment 000 / 009 :: RGBD matching between frame : 3 and 4
Fragment 000 / 009 :: RGBD matching between frame : 4 and 5
Fragment 000 / 009 :: RGBD matching between frame : 5 and 6
Fragment 000 / 009 :: RGBD matching between frame : 5 and 10
Fragment 000 / 009 :: RGBD matching between frame : 5 and 15
Fragment 000 / 009 :: RGBD matching between frame : 5 and 20
Fragment 000 / 009 :: RGBD matching between frame : 5 and 25
Fragment 000 / 009 :: RGBD matching between frame : 5 and 30
Fragment 000 / 009 :: RGBD matching between frame : 5 and 35
Fragment 000 / 009 :: RGBD matching between frame : 5 and 40
Fragment 000 / 009 :: RGBD matching between frame : 5 and 45
Fragment 000 / 009 :: RGBD matching between frame : 5 and 50
Fragment 000 / 009 :: RGBD matching between frame : 5 and 55
Fragment 000 / 009 :: RGBD matching between frame : 5 and 60
Fragment 000 / 009 :: RGBD matching between frame : 5 and 65
Fragment 000 / 009 :: RGBD matching between frame : 5 and 70
Fragment 000 / 009 :: RGBD matching between frame : 5 and 75
Fragment 000 / 009 :: RGBD matching between frame : 5 and 80
Fragment 000 / 009 :: RGBD matching between frame : 5 and 85
Fragment 000 / 009 :: RGBD matching between frame : 5 and 90
Fragment 000 / 009 :: RGBD matching between frame : 5 and 95
Fragment 000 / 009 :: RGBD matching between frame : 6 and 7
Fragment 000 / 009 :: RGBD matching between frame : 7 and 8
Fragment 000 / 009 :: RGBD matching between frame : 8 and 9
Fragment 000 / 009 :: RGBD matching between frame : 9 and 10
Fragment 000 / 009 :: RGBD matching between frame : 10 and 11
Fragment 000 / 009 :: RGBD matching between frame : 10 and 15
Fragment 000 / 009 :: RGBD matching between frame : 10 and 20
Fragment 000 / 009 :: RGBD matching between frame : 10 and 25
Fragment 000 / 009 :: RGBD matching between frame : 10 and 30
Fragment 000 / 009 :: RGBD matching between frame : 10 and 35
Fragment 000 / 009 :: RGBD matching between frame : 10 and 40
Fragment 000 / 009 :: RGBD matching between frame : 10 and 45
Fragment 000 / 009 :: RGBD matching between frame : 10 and 50
Fragment 000 / 009 :: RGBD matching between frame : 10 and 55
Fragment 000 / 009 :: RGBD matching between frame : 10 and 60
Fragment 000 / 009 :: RGBD matching between frame : 10 and 65
Fragment 000 / 009 :: RGBD matching between frame : 10 and 70
Fragment 000 / 009 :: RGBD matching between frame : 10 and 75
Fragment 000 / 009 :: RGBD matching between frame : 10 and 80
Fragment 000 / 009 :: RGBD matching between frame : 10 and 85
Fragment 000 / 009 :: RGBD matching between frame : 10 and 90
Fragment 000 / 009 :: RGBD matching between frame : 10 and 95
Fragment 000 / 009 :: RGBD matching between frame : 11 and 12
Fragment 000 / 009 :: RGBD matching between frame : 12 and 13
Fragment 000 / 009 :: RGBD matching between frame : 13 and 14
Fragment 000 / 009 :: RGBD matching between frame : 14 and 15
Fragment 000 / 009 :: RGBD matching between frame : 15 and 16
Fragment 000 / 009 :: RGBD matching between frame : 15 and 20
Fragment 000 / 009 :: RGBD matching between frame : 15 and 25
Fragment 000 / 009 :: RGBD matching between frame : 15 and 30
Fragment 000 / 009 :: RGBD matching between frame : 15 and 35
Fragment 000 / 009 :: RGBD matching between frame : 15 and 40
Fragment 000 / 009 :: RGBD matching between frame : 15 and 45
Fragment 000 / 009 :: RGBD matching between frame : 15 and 50
Fragment 000 / 009 :: RGBD matching between frame : 15 and 55
Fragment 000 / 009 :: RGBD matching between frame : 15 and 60
Fragment 000 / 009 :: RGBD matching between frame : 15 and 65
Fragment 000 / 009 :: RGBD matching between frame : 15 and 70
Fragment 000 / 009 :: RGBD matching between frame : 15 and 75
Fragment 000 / 009 :: RGBD matching between frame : 15 and 80
Fragment 000 / 009 :: RGBD matching between frame : 15 and 85
Fragment 000 / 009 :: RGBD matching between frame : 15 and 90
Fragment 000 / 009 :: RGBD matching between frame : 15 and 95
Fragment 000 / 009 :: RGBD matching between frame : 16 and 17
Fragment 000 / 009 :: RGBD matching between frame : 17 and 18
Fragment 000 / 009 :: RGBD matching between frame : 18 and 19
Fragment 000 / 009 :: RGBD matching between frame : 19 and 20
Fragment 000 / 009 :: RGBD matching between frame : 20 and 21
Fragment 000 / 009 :: RGBD matching between frame : 20 and 25
Fragment 000 / 009 :: RGBD matching between frame : 20 and 30
Fragment 000 / 009 :: RGBD matching between frame : 20 and 35
Fragment 000 / 009 :: RGBD matching between frame : 20 and 40
Fragment 000 / 009 :: RGBD matching between frame : 20 and 45
Fragment 000 / 009 :: RGBD matching between frame : 20 and 50
Fragment 000 / 009 :: RGBD matching between frame : 20 and 55
Fragment 000 / 009 :: RGBD matching between frame : 20 and 60
Fragment 000 / 009 :: RGBD matching between frame : 20 and 65
Fragment 000 / 009 :: RGBD matching between frame : 20 and 70
Fragment 000 / 009 :: RGBD matching between frame : 20 and 75
Fragment 000 / 009 :: RGBD matching between frame : 20 and 80
Fragment 000 / 009 :: RGBD matching between frame : 20 and 85
Fragment 000 / 009 :: RGBD matching between frame : 20 and 90
Fragment 000 / 009 :: RGBD matching between frame : 20 and 95
Fragment 000 / 009 :: RGBD matching between frame : 21 and 22
Fragment 000 / 009 :: RGBD matching between frame : 22 and 23
Fragment 000 / 009 :: RGBD matching between frame : 23 and 24
Fragment 000 / 009 :: RGBD matching between frame : 24 and 25
Fragment 000 / 009 :: RGBD matching between frame : 25 and 26
Fragment 000 / 009 :: RGBD matching between frame : 25 and 30
Fragment 000 / 009 :: RGBD matching between frame : 25 and 35
Fragment 000 / 009 :: RGBD matching between frame : 25 and 40
Fragment 000 / 009 :: RGBD matching between frame : 25 and 45
Fragment 000 / 009 :: RGBD matching between frame : 25 and 50
Fragment 000 / 009 :: RGBD matching between frame : 25 and 55
Fragment 000 / 009 :: RGBD matching between frame : 25 and 60
Fragment 000 / 009 :: RGBD matching between frame : 25 and 65
Fragment 000 / 009 :: RGBD matching between frame : 25 and 70
Fragment 000 / 009 :: RGBD matching between frame : 25 and 75
Fragment 000 / 009 :: RGBD matching between frame : 25 and 80
Fragment 000 / 009 :: RGBD matching between frame : 25 and 85
Fragment 000 / 009 :: RGBD matching between frame : 25 and 90
Fragment 000 / 009 :: RGBD matching between frame : 25 and 95
Fragment 000 / 009 :: RGBD matching between frame : 26 and 27
Fragment 000 / 009 :: RGBD matching between frame : 27 and 28
Fragment 000 / 009 :: RGBD matching between frame : 28 and 29
Fragment 000 / 009 :: RGBD matching between frame : 29 and 30
Fragment 000 / 009 :: RGBD matching between frame : 30 and 31
Fragment 000 / 009 :: RGBD matching between frame : 30 and 35
Fragment 000 / 009 :: RGBD matching between frame : 30 and 40
Fragment 000 / 009 :: RGBD matching between frame : 30 and 45
Fragment 000 / 009 :: RGBD matching between frame : 30 and 50
Fragment 000 / 009 :: RGBD matching between frame : 30 and 55
Fragment 000 / 009 :: RGBD matching between frame : 30 and 60
Fragment 000 / 009 :: RGBD matching between frame : 30 and 65
Fragment 000 / 009 :: RGBD matching between frame : 30 and 70
Fragment 000 / 009 :: RGBD matching between frame : 30 and 75
Fragment 000 / 009 :: RGBD matching between frame : 30 and 80
Fragment 000 / 009 :: RGBD matching between frame : 30 and 85
Fragment 000 / 009 :: RGBD matching between frame : 30 and 90
Fragment 000 / 009 :: RGBD matching between frame : 30 and 95
Fragment 000 / 009 :: RGBD matching between frame : 31 and 32
Fragment 000 / 009 :: RGBD matching between frame : 32 and 33
Fragment 000 / 009 :: RGBD matching between frame : 33 and 34
Fragment 000 / 009 :: RGBD matching between frame : 34 and 35
Fragment 000 / 009 :: RGBD matching between frame : 35 and 36
Fragment 000 / 009 :: RGBD matching between frame : 35 and 40
Fragment 000 / 009 :: RGBD matching between frame : 35 and 45
Fragment 000 / 009 :: RGBD matching between frame : 35 and 50
Fragment 000 / 009 :: RGBD matching between frame : 35 and 55
Fragment 000 / 009 :: RGBD matching between frame : 35 and 60
Fragment 000 / 009 :: RGBD matching between frame : 35 and 65
Fragment 000 / 009 :: RGBD matching between frame : 35 and 70
Fragment 000 / 009 :: RGBD matching between frame : 35 and 75
Fragment 000 / 009 :: RGBD matching between frame : 35 and 80
Fragment 000 / 009 :: RGBD matching between frame : 35 and 85
Fragment 000 / 009 :: RGBD matching between frame : 35 and 90
Fragment 000 / 009 :: RGBD matching between frame : 35 and 95
Fragment 000 / 009 :: RGBD matching between frame : 36 and 37
Fragment 000 / 009 :: RGBD matching between frame : 37 and 38
Fragment 000 / 009 :: RGBD matching between frame : 38 and 39
Fragment 000 / 009 :: RGBD matching between frame : 39 and 40
Fragment 000 / 009 :: RGBD matching between frame : 40 and 41
Fragment 000 / 009 :: RGBD matching between frame : 40 and 45
Fragment 000 / 009 :: RGBD matching between frame : 40 and 50
Fragment 000 / 009 :: RGBD matching between frame : 40 and 55
Fragment 000 / 009 :: RGBD matching between frame : 40 and 60
Fragment 000 / 009 :: RGBD matching between frame : 40 and 65
Fragment 000 / 009 :: RGBD matching between frame : 40 and 70
Fragment 000 / 009 :: RGBD matching between frame : 40 and 75
Fragment 000 / 009 :: RGBD matching between frame : 40 and 80
Fragment 000 / 009 :: RGBD matching between frame : 40 and 85
Fragment 000 / 009 :: RGBD matching between frame : 40 and 90
Fragment 000 / 009 :: RGBD matching between frame : 40 and 95
Fragment 000 / 009 :: RGBD matching between frame : 41 and 42
Fragment 000 / 009 :: RGBD matching between frame : 42 and 43
Fragment 000 / 009 :: RGBD matching between frame : 43 and 44
Fragment 000 / 009 :: RGBD matching between frame : 44 and 45
Fragment 000 / 009 :: RGBD matching between frame : 45 and 46
Fragment 000 / 009 :: RGBD matching between frame : 45 and 50
Fragment 000 / 009 :: RGBD matching between frame : 45 and 55
Fragment 000 / 009 :: RGBD matching between frame : 45 and 60
Fragment 000 / 009 :: RGBD matching between frame : 45 and 65
Fragment 000 / 009 :: RGBD matching between frame : 45 and 70
Fragment 000 / 009 :: RGBD matching between frame : 45 and 75
Fragment 000 / 009 :: RGBD matching between frame : 45 and 80
Fragment 000 / 009 :: RGBD matching between frame : 45 and 85
Fragment 000 / 009 :: RGBD matching between frame : 45 and 90
Fragment 000 / 009 :: RGBD matching between frame : 45 and 95
Fragment 000 / 009 :: RGBD matching between frame : 46 and 47
Fragment 000 / 009 :: RGBD matching between frame : 47 and 48
Fragment 000 / 009 :: RGBD matching between frame : 48 and 49
Fragment 000 / 009 :: RGBD matching between frame : 49 and 50
Fragment 000 / 009 :: RGBD matching between frame : 50 and 51
Fragment 000 / 009 :: RGBD matching between frame : 50 and 55
Fragment 000 / 009 :: RGBD matching between frame : 50 and 60
Fragment 000 / 009 :: RGBD matching between frame : 50 and 65
Fragment 000 / 009 :: RGBD matching between frame : 50 and 70
Fragment 000 / 009 :: RGBD matching between frame : 50 and 75
Fragment 000 / 009 :: RGBD matching between frame : 50 and 80
Fragment 000 / 009 :: RGBD matching between frame : 50 and 85
Fragment 000 / 009 :: RGBD matching between frame : 50 and 90
Fragment 000 / 009 :: RGBD matching between frame : 50 and 95
Fragment 000 / 009 :: RGBD matching between frame : 51 and 52
Fragment 000 / 009 :: RGBD matching between frame : 52 and 53
Fragment 000 / 009 :: RGBD matching between frame : 53 and 54
Fragment 000 / 009 :: RGBD matching between frame : 54 and 55
Fragment 000 / 009 :: RGBD matching between frame : 55 and 56
Fragment 000 / 009 :: RGBD matching between frame : 55 and 60
Fragment 000 / 009 :: RGBD matching between frame : 55 and 65
Fragment 000 / 009 :: RGBD matching between frame : 55 and 70
Fragment 000 / 009 :: RGBD matching between frame : 55 and 75
Fragment 000 / 009 :: RGBD matching between frame : 55 and 80
Fragment 000 / 009 :: RGBD matching between frame : 55 and 85
Fragment 000 / 009 :: RGBD matching between frame : 55 and 90
Fragment 000 / 009 :: RGBD matching between frame : 55 and 95
Fragment 000 / 009 :: RGBD matching between frame : 56 and 57
Fragment 000 / 009 :: RGBD matching between frame : 57 and 58
Fragment 000 / 009 :: RGBD matching between frame : 58 and 59
Fragment 000 / 009 :: RGBD matching between frame : 59 and 60
Fragment 000 / 009 :: RGBD matching between frame : 60 and 61
Fragment 000 / 009 :: RGBD matching between frame : 60 and 65
Fragment 000 / 009 :: RGBD matching between frame : 60 and 70
Fragment 000 / 009 :: RGBD matching between frame : 60 and 75
Fragment 000 / 009 :: RGBD matching between frame : 60 and 80
Fragment 000 / 009 :: RGBD matching between frame : 60 and 85
Fragment 000 / 009 :: RGBD matching between frame : 60 and 90
Fragment 000 / 009 :: RGBD matching between frame : 60 and 95
Fragment 000 / 009 :: RGBD matching between frame : 61 and 62
Fragment 000 / 009 :: RGBD matching between frame : 62 and 63
Fragment 000 / 009 :: RGBD matching between frame : 63 and 64
Fragment 000 / 009 :: RGBD matching between frame : 64 and 65
Fragment 000 / 009 :: RGBD matching between frame : 65 and 66
Fragment 000 / 009 :: RGBD matching between frame : 65 and 70
Fragment 000 / 009 :: RGBD matching between frame : 65 and 75
Fragment 000 / 009 :: RGBD matching between frame : 65 and 80
Fragment 000 / 009 :: RGBD matching between frame : 65 and 85
Fragment 000 / 009 :: RGBD matching between frame : 65 and 90
Fragment 000 / 009 :: RGBD matching between frame : 65 and 95
Fragment 000 / 009 :: RGBD matching between frame : 66 and 67
Fragment 000 / 009 :: RGBD matching between frame : 67 and 68
Fragment 000 / 009 :: RGBD matching between frame : 68 and 69
Fragment 000 / 009 :: RGBD matching between frame : 69 and 70
Fragment 000 / 009 :: RGBD matching between frame : 70 and 71
Fragment 000 / 009 :: RGBD matching between frame : 70 and 75
Fragment 000 / 009 :: RGBD matching between frame : 70 and 80
Fragment 000 / 009 :: RGBD matching between frame : 70 and 85
Fragment 000 / 009 :: RGBD matching between frame : 70 and 90
Fragment 000 / 009 :: RGBD matching between frame : 70 and 95
Fragment 000 / 009 :: RGBD matching between frame : 71 and 72
Fragment 000 / 009 :: RGBD matching between frame : 72 and 73
Fragment 000 / 009 :: RGBD matching between frame : 73 and 74
Fragment 000 / 009 :: RGBD matching between frame : 74 and 75
Fragment 000 / 009 :: RGBD matching between frame : 75 and 76
Fragment 000 / 009 :: RGBD matching between frame : 75 and 80
Fragment 000 / 009 :: RGBD matching between frame : 75 and 85
Fragment 000 / 009 :: RGBD matching between frame : 75 and 90
Fragment 000 / 009 :: RGBD matching between frame : 75 and 95
Fragment 000 / 009 :: RGBD matching between frame : 76 and 77
Fragment 000 / 009 :: RGBD matching between frame : 77 and 78
Fragment 000 / 009 :: RGBD matching between frame : 78 and 79
Fragment 000 / 009 :: RGBD matching between frame : 79 and 80
Fragment 000 / 009 :: RGBD matching between frame : 80 and 81
Fragment 000 / 009 :: RGBD matching between frame : 80 and 85
Fragment 000 / 009 :: RGBD matching between frame : 80 and 90
Fragment 000 / 009 :: RGBD matching between frame : 80 and 95
Fragment 000 / 009 :: RGBD matching between frame : 81 and 82
Fragment 000 / 009 :: RGBD matching between frame : 82 and 83
Fragment 000 / 009 :: RGBD matching between frame : 83 and 84
Fragment 000 / 009 :: RGBD matching between frame : 84 and 85
Fragment 000 / 009 :: RGBD matching between frame : 85 and 86
Fragment 000 / 009 :: RGBD matching between frame : 85 and 90
Fragment 000 / 009 :: RGBD matching between frame : 85 and 95
Fragment 000 / 009 :: RGBD matching between frame : 86 and 87
Fragment 000 / 009 :: RGBD matching between frame : 87 and 88
Fragment 000 / 009 :: RGBD matching between frame : 88 and 89
Fragment 000 / 009 :: RGBD matching between frame : 89 and 90
Fragment 000 / 009 :: RGBD matching between frame : 90 and 91
Fragment 000 / 009 :: RGBD matching between frame : 90 and 95
Fragment 000 / 009 :: RGBD matching between frame : 91 and 92
Fragment 000 / 009 :: RGBD matching between frame : 92 and 93
Fragment 000 / 009 :: RGBD matching between frame : 93 and 94
Fragment 000 / 009 :: RGBD matching between frame : 94 and 95
Fragment 000 / 009 :: RGBD matching between frame : 95 and 96
Fragment 000 / 009 :: RGBD matching between frame : 96 and 97
Fragment 000 / 009 :: RGBD matching between frame : 97 and 98
Fragment 000 / 009 :: RGBD matching between frame : 98 and 99
Fragment 000 / 009 :: integrate rgbd frame 0 (1 of 100).
Fragment 000 / 009 :: integrate rgbd frame 1 (2 of 100).
Fragment 000 / 009 :: integrate rgbd frame 2 (3 of 100).
Fragment 000 / 009 :: integrate rgbd frame 3 (4 of 100).
Fragment 000 / 009 :: integrate rgbd frame 4 (5 of 100).
Fragment 000 / 009 :: integrate rgbd frame 5 (6 of 100).
Fragment 000 / 009 :: integrate rgbd frame 6 (7 of 100).
Fragment 000 / 009 :: integrate rgbd frame 7 (8 of 100).
Fragment 000 / 009 :: integrate rgbd frame 8 (9 of 100).
Fragment 000 / 009 :: integrate rgbd frame 9 (10 of 100).
Fragment 000 / 009 :: integrate rgbd frame 10 (11 of 100).
Fragment 000 / 009 :: integrate rgbd frame 11 (12 of 100).
Fragment 000 / 009 :: integrate rgbd frame 12 (13 of 100).
Fragment 000 / 009 :: integrate rgbd frame 13 (14 of 100).
Fragment 000 / 009 :: integrate rgbd frame 14 (15 of 100).
Fragment 000 / 009 :: integrate rgbd frame 15 (16 of 100).
Fragment 000 / 009 :: integrate rgbd frame 16 (17 of 100).
Fragment 000 / 009 :: integrate rgbd frame 17 (18 of 100).
Fragment 000 / 009 :: integrate rgbd frame 18 (19 of 100).
Fragment 000 / 009 :: integrate rgbd frame 19 (20 of 100).
Fragment 000 / 009 :: integrate rgbd frame 20 (21 of 100).
Fragment 000 / 009 :: integrate rgbd frame 21 (22 of 100).
Fragment 000 / 009 :: integrate rgbd frame 22 (23 of 100).
Fragment 000 / 009 :: integrate rgbd frame 23 (24 of 100).
Fragment 000 / 009 :: integrate rgbd frame 24 (25 of 100).
Fragment 000 / 009 :: integrate rgbd frame 25 (26 of 100).
Fragment 000 / 009 :: integrate rgbd frame 26 (27 of 100).
Fragment 000 / 009 :: integrate rgbd frame 27 (28 of 100).
Fragment 000 / 009 :: integrate rgbd frame 28 (29 of 100).
Fragment 000 / 009 :: integrate rgbd frame 29 (30 of 100).
Fragment 000 / 009 :: integrate rgbd frame 30 (31 of 100).
Fragment 000 / 009 :: integrate rgbd frame 31 (32 of 100).
Fragment 000 / 009 :: integrate rgbd frame 32 (33 of 100).
Fragment 000 / 009 :: integrate rgbd frame 33 (34 of 100).
Fragment 000 / 009 :: integrate rgbd frame 34 (35 of 100).
Fragment 000 / 009 :: integrate rgbd frame 35 (36 of 100).
Fragment 000 / 009 :: integrate rgbd frame 36 (37 of 100).
Fragment 000 / 009 :: integrate rgbd frame 37 (38 of 100).
Fragment 000 / 009 :: integrate rgbd frame 38 (39 of 100).
Fragment 000 / 009 :: integrate rgbd frame 39 (40 of 100).
Fragment 000 / 009 :: integrate rgbd frame 40 (41 of 100).
Fragment 000 / 009 :: integrate rgbd frame 41 (42 of 100).
Fragment 000 / 009 :: integrate rgbd frame 42 (43 of 100).
Fragment 000 / 009 :: integrate rgbd frame 43 (44 of 100).
Fragment 000 / 009 :: integrate rgbd frame 44 (45 of 100).
Fragment 000 / 009 :: integrate rgbd frame 45 (46 of 100).
Fragment 000 / 009 :: integrate rgbd frame 46 (47 of 100).
Fragment 000 / 009 :: integrate rgbd frame 47 (48 of 100).
Fragment 000 / 009 :: integrate rgbd frame 48 (49 of 100).
Fragment 000 / 009 :: integrate rgbd frame 49 (50 of 100).
Fragment 000 / 009 :: integrate rgbd frame 50 (51 of 100).
Fragment 000 / 009 :: integrate rgbd frame 51 (52 of 100).
Fragment 000 / 009 :: integrate rgbd frame 52 (53 of 100).
Fragment 000 / 009 :: integrate rgbd frame 53 (54 of 100).
Fragment 000 / 009 :: integrate rgbd frame 54 (55 of 100).
Fragment 000 / 009 :: integrate rgbd frame 55 (56 of 100).
Fragment 000 / 009 :: integrate rgbd frame 56 (57 of 100).
Fragment 000 / 009 :: integrate rgbd frame 57 (58 of 100).
Fragment 000 / 009 :: integrate rgbd frame 58 (59 of 100).
Fragment 000 / 009 :: integrate rgbd frame 59 (60 of 100).
Fragment 000 / 009 :: integrate rgbd frame 60 (61 of 100).
Fragment 000 / 009 :: integrate rgbd frame 61 (62 of 100).
Fragment 000 / 009 :: integrate rgbd frame 62 (63 of 100).
Fragment 000 / 009 :: integrate rgbd frame 63 (64 of 100).
Fragment 000 / 009 :: integrate rgbd frame 64 (65 of 100).
Fragment 000 / 009 :: integrate rgbd frame 65 (66 of 100).
Fragment 000 / 009 :: integrate rgbd frame 66 (67 of 100).
Fragment 000 / 009 :: integrate rgbd frame 67 (68 of 100).
Fragment 000 / 009 :: integrate rgbd frame 68 (69 of 100).
Fragment 000 / 009 :: integrate rgbd frame 69 (70 of 100).
Fragment 000 / 009 :: integrate rgbd frame 70 (71 of 100).
Fragment 000 / 009 :: integrate rgbd frame 71 (72 of 100).
Fragment 000 / 009 :: integrate rgbd frame 72 (73 of 100).
Fragment 000 / 009 :: integrate rgbd frame 73 (74 of 100).
Fragment 000 / 009 :: integrate rgbd frame 74 (75 of 100).
Fragment 000 / 009 :: integrate rgbd frame 75 (76 of 100).
Fragment 000 / 009 :: integrate rgbd frame 76 (77 of 100).
Fragment 000 / 009 :: integrate rgbd frame 77 (78 of 100).
Fragment 000 / 009 :: integrate rgbd frame 78 (79 of 100).
Fragment 000 / 009 :: integrate rgbd frame 79 (80 of 100).
Fragment 000 / 009 :: integrate rgbd frame 80 (81 of 100).
Fragment 000 / 009 :: integrate rgbd frame 81 (82 of 100).
Fragment 000 / 009 :: integrate rgbd frame 82 (83 of 100).
Fragment 000 / 009 :: integrate rgbd frame 83 (84 of 100).
Fragment 000 / 009 :: integrate rgbd frame 84 (85 of 100).
Fragment 000 / 009 :: integrate rgbd frame 85 (86 of 100).
Fragment 000 / 009 :: integrate rgbd frame 86 (87 of 100).
Fragment 000 / 009 :: integrate rgbd frame 87 (88 of 100).
Fragment 000 / 009 :: integrate rgbd frame 88 (89 of 100).
Fragment 000 / 009 :: integrate rgbd frame 89 (90 of 100).
Fragment 000 / 009 :: integrate rgbd frame 90 (91 of 100).
Fragment 000 / 009 :: integrate rgbd frame 91 (92 of 100).
Fragment 000 / 009 :: integrate rgbd frame 92 (93 of 100).
Fragment 000 / 009 :: integrate rgbd frame 93 (94 of 100).
Fragment 000 / 009 :: integrate rgbd frame 94 (95 of 100).
Fragment 000 / 009 :: integrate rgbd frame 95 (96 of 100).
Fragment 000 / 009 :: integrate rgbd frame 96 (97 of 100).
Fragment 000 / 009 :: integrate rgbd frame 97 (98 of 100).
Fragment 000 / 009 :: integrate rgbd frame 98 (99 of 100).
Fragment 000 / 009 :: integrate rgbd frame 99 (100 of 100).
Fragment 001 / 009 :: RGBD matching between frame : 100 and 101
Fragment 001 / 009 :: RGBD matching between frame : 100 and 105
Fragment 001 / 009 :: RGBD matching between frame : 100 and 110
Fragment 001 / 009 :: RGBD matching between frame : 100 and 115
Fragment 001 / 009 :: RGBD matching between frame : 100 and 120
Fragment 001 / 009 :: RGBD matching between frame : 100 and 125
Fragment 001 / 009 :: RGBD matching between frame : 100 and 130
Fragment 001 / 009 :: RGBD matching between frame : 100 and 135
Fragment 001 / 009 :: RGBD matching between frame : 100 and 140
Fragment 001 / 009 :: RGBD matching between frame : 100 and 145
Fragment 001 / 009 :: RGBD matching between frame : 100 and 150
Fragment 001 / 009 :: RGBD matching between frame : 100 and 155
Fragment 001 / 009 :: RGBD matching between frame : 100 and 160
Fragment 001 / 009 :: RGBD matching between frame : 100 and 165
Fragment 001 / 009 :: RGBD matching between frame : 100 and 170
Fragment 001 / 009 :: RGBD matching between frame : 100 and 175
Fragment 001 / 009 :: RGBD matching between frame : 100 and 180
Fragment 001 / 009 :: RGBD matching between frame : 100 and 185
Fragment 001 / 009 :: RGBD matching between frame : 100 and 190
Fragment 001 / 009 :: RGBD matching between frame : 100 and 195
Fragment 001 / 009 :: RGBD matching between frame : 101 and 102
Fragment 001 / 009 :: RGBD matching between frame : 102 and 103
Fragment 001 / 009 :: RGBD matching between frame : 103 and 104
Fragment 001 / 009 :: RGBD matching between frame : 104 and 105
Fragment 001 / 009 :: RGBD matching between frame : 105 and 106
Fragment 001 / 009 :: RGBD matching between frame : 105 and 110
Fragment 001 / 009 :: RGBD matching between frame : 105 and 115
Fragment 001 / 009 :: RGBD matching between frame : 105 and 120
Fragment 001 / 009 :: RGBD matching between frame : 105 and 125
Fragment 001 / 009 :: RGBD matching between frame : 105 and 130
Fragment 001 / 009 :: RGBD matching between frame : 105 and 135
Fragment 001 / 009 :: RGBD matching between frame : 105 and 140
Fragment 001 / 009 :: RGBD matching between frame : 105 and 145
Fragment 001 / 009 :: RGBD matching between frame : 105 and 150
Fragment 001 / 009 :: RGBD matching between frame : 105 and 155
Fragment 001 / 009 :: RGBD matching between frame : 105 and 160
Fragment 001 / 009 :: RGBD matching between frame : 105 and 165
Fragment 001 / 009 :: RGBD matching between frame : 105 and 170
Fragment 001 / 009 :: RGBD matching between frame : 105 and 175
Fragment 001 / 009 :: RGBD matching between frame : 105 and 180
Fragment 001 / 009 :: RGBD matching between frame : 105 and 185
Fragment 001 / 009 :: RGBD matching between frame : 105 and 190
Fragment 001 / 009 :: RGBD matching between frame : 105 and 195
Fragment 001 / 009 :: RGBD matching between frame : 106 and 107
Fragment 001 / 009 :: RGBD matching between frame : 107 and 108
Fragment 001 / 009 :: RGBD matching between frame : 108 and 109
Fragment 001 / 009 :: RGBD matching between frame : 109 and 110
Fragment 001 / 009 :: RGBD matching between frame : 110 and 111
Fragment 001 / 009 :: RGBD matching between frame : 110 and 115
Fragment 001 / 009 :: RGBD matching between frame : 110 and 120
Fragment 001 / 009 :: RGBD matching between frame : 110 and 125
Fragment 001 / 009 :: RGBD matching between frame : 110 and 130
Fragment 001 / 009 :: RGBD matching between frame : 110 and 135
Fragment 001 / 009 :: RGBD matching between frame : 110 and 140
Fragment 001 / 009 :: RGBD matching between frame : 110 and 145
Fragment 001 / 009 :: RGBD matching between frame : 110 and 150
Fragment 001 / 009 :: RGBD matching between frame : 110 and 155
Fragment 001 / 009 :: RGBD matching between frame : 110 and 160
Fragment 001 / 009 :: RGBD matching between frame : 110 and 165
Fragment 001 / 009 :: RGBD matching between frame : 110 and 170
Fragment 001 / 009 :: RGBD matching between frame : 110 and 175
Fragment 001 / 009 :: RGBD matching between frame : 110 and 180
Fragment 001 / 009 :: RGBD matching between frame : 110 and 185
Fragment 001 / 009 :: RGBD matching between frame : 110 and 190
Fragment 001 / 009 :: RGBD matching between frame : 110 and 195
Fragment 001 / 009 :: RGBD matching between frame : 111 and 112
Fragment 001 / 009 :: RGBD matching between frame : 112 and 113
Fragment 001 / 009 :: RGBD matching between frame : 113 and 114
Fragment 001 / 009 :: RGBD matching between frame : 114 and 115
Fragment 001 / 009 :: RGBD matching between frame : 115 and 116
Fragment 001 / 009 :: RGBD matching between frame : 115 and 120
Fragment 001 / 009 :: RGBD matching between frame : 115 and 125
Fragment 001 / 009 :: RGBD matching between frame : 115 and 130
Fragment 001 / 009 :: RGBD matching between frame : 115 and 135
Fragment 001 / 009 :: RGBD matching between frame : 115 and 140
Fragment 001 / 009 :: RGBD matching between frame : 115 and 145
Fragment 001 / 009 :: RGBD matching between frame : 115 and 150
Fragment 001 / 009 :: RGBD matching between frame : 115 and 155
Fragment 001 / 009 :: RGBD matching between frame : 115 and 160
Fragment 001 / 009 :: RGBD matching between frame : 115 and 165
Fragment 001 / 009 :: RGBD matching between frame : 115 and 170
Fragment 001 / 009 :: RGBD matching between frame : 115 and 175
Fragment 001 / 009 :: RGBD matching between frame : 115 and 180
Fragment 001 / 009 :: RGBD matching between frame : 115 and 185
Fragment 001 / 009 :: RGBD matching between frame : 115 and 190
Fragment 001 / 009 :: RGBD matching between frame : 115 and 195
Fragment 001 / 009 :: RGBD matching between frame : 116 and 117
Fragment 001 / 009 :: RGBD matching between frame : 117 and 118
Fragment 001 / 009 :: RGBD matching between frame : 118 and 119
Fragment 001 / 009 :: RGBD matching between frame : 119 and 120
Fragment 001 / 009 :: RGBD matching between frame : 120 and 121
Fragment 001 / 009 :: RGBD matching between frame : 120 and 125
Fragment 001 / 009 :: RGBD matching between frame : 120 and 130
Fragment 001 / 009 :: RGBD matching between frame : 120 and 135
Fragment 001 / 009 :: RGBD matching between frame : 120 and 140
Fragment 001 / 009 :: RGBD matching between frame : 120 and 145
Fragment 001 / 009 :: RGBD matching between frame : 120 and 150
Fragment 001 / 009 :: RGBD matching between frame : 120 and 155
Fragment 001 / 009 :: RGBD matching between frame : 120 and 160
Fragment 001 / 009 :: RGBD matching between frame : 120 and 165
Fragment 001 / 009 :: RGBD matching between frame : 120 and 170
Fragment 001 / 009 :: RGBD matching between frame : 120 and 175
Fragment 001 / 009 :: RGBD matching between frame : 120 and 180
Fragment 001 / 009 :: RGBD matching between frame : 120 and 185
Fragment 001 / 009 :: RGBD matching between frame : 120 and 190
Fragment 001 / 009 :: RGBD matching between frame : 120 and 195
Fragment 001 / 009 :: RGBD matching between frame : 121 and 122
Fragment 001 / 009 :: RGBD matching between frame : 122 and 123
Fragment 001 / 009 :: RGBD matching between frame : 123 and 124
Fragment 001 / 009 :: RGBD matching between frame : 124 and 125
Fragment 001 / 009 :: RGBD matching between frame : 125 and 126
Fragment 001 / 009 :: RGBD matching between frame : 125 and 130
Fragment 001 / 009 :: RGBD matching between frame : 125 and 135
Fragment 001 / 009 :: RGBD matching between frame : 125 and 140
Fragment 001 / 009 :: RGBD matching between frame : 125 and 145
Fragment 001 / 009 :: RGBD matching between frame : 125 and 150
Fragment 001 / 009 :: RGBD matching between frame : 125 and 155
Fragment 001 / 009 :: RGBD matching between frame : 125 and 160
Fragment 001 / 009 :: RGBD matching between frame : 125 and 165
Fragment 001 / 009 :: RGBD matching between frame : 125 and 170
Fragment 001 / 009 :: RGBD matching between frame : 125 and 175
Fragment 001 / 009 :: RGBD matching between frame : 125 and 180
Fragment 001 / 009 :: RGBD matching between frame : 125 and 185
Fragment 001 / 009 :: RGBD matching between frame : 125 and 190
Fragment 001 / 009 :: RGBD matching between frame : 125 and 195
Fragment 001 / 009 :: RGBD matching between frame : 126 and 127
Fragment 001 / 009 :: RGBD matching between frame : 127 and 128
Fragment 001 / 009 :: RGBD matching between frame : 128 and 129
Fragment 001 / 009 :: RGBD matching between frame : 129 and 130
Fragment 001 / 009 :: RGBD matching between frame : 130 and 131
Fragment 001 / 009 :: RGBD matching between frame : 130 and 135
Fragment 001 / 009 :: RGBD matching between frame : 130 and 140
Fragment 001 / 009 :: RGBD matching between frame : 130 and 145
Fragment 001 / 009 :: RGBD matching between frame : 130 and 150
Fragment 001 / 009 :: RGBD matching between frame : 130 and 155
Fragment 001 / 009 :: RGBD matching between frame : 130 and 160
Fragment 001 / 009 :: RGBD matching between frame : 130 and 165
Fragment 001 / 009 :: RGBD matching between frame : 130 and 170
Fragment 001 / 009 :: RGBD matching between frame : 130 and 175
Fragment 001 / 009 :: RGBD matching between frame : 130 and 180
Fragment 001 / 009 :: RGBD matching between frame : 130 and 185
Fragment 001 / 009 :: RGBD matching between frame : 130 and 190
Fragment 001 / 009 :: RGBD matching between frame : 130 and 195
Fragment 001 / 009 :: RGBD matching between frame : 131 and 132
Fragment 001 / 009 :: RGBD matching between frame : 132 and 133
Fragment 001 / 009 :: RGBD matching between frame : 133 and 134
Fragment 001 / 009 :: RGBD matching between frame : 134 and 135
Fragment 001 / 009 :: RGBD matching between frame : 135 and 136
Fragment 001 / 009 :: RGBD matching between frame : 135 and 140
Fragment 001 / 009 :: RGBD matching between frame : 135 and 145
Fragment 001 / 009 :: RGBD matching between frame : 135 and 150
Fragment 001 / 009 :: RGBD matching between frame : 135 and 155
Fragment 001 / 009 :: RGBD matching between frame : 135 and 160
Fragment 001 / 009 :: RGBD matching between frame : 135 and 165
Fragment 001 / 009 :: RGBD matching between frame : 135 and 170
Fragment 001 / 009 :: RGBD matching between frame : 135 and 175
Fragment 001 / 009 :: RGBD matching between frame : 135 and 180
Fragment 001 / 009 :: RGBD matching between frame : 135 and 185
Fragment 001 / 009 :: RGBD matching between frame : 135 and 190
Fragment 001 / 009 :: RGBD matching between frame : 135 and 195
Fragment 001 / 009 :: RGBD matching between frame : 136 and 137
Fragment 001 / 009 :: RGBD matching between frame : 137 and 138
Fragment 001 / 009 :: RGBD matching between frame : 138 and 139
Fragment 001 / 009 :: RGBD matching between frame : 139 and 140
Fragment 001 / 009 :: RGBD matching between frame : 140 and 141
Fragment 001 / 009 :: RGBD matching between frame : 140 and 145
Fragment 001 / 009 :: RGBD matching between frame : 140 and 150
Fragment 001 / 009 :: RGBD matching between frame : 140 and 155
Fragment 001 / 009 :: RGBD matching between frame : 140 and 160
Fragment 001 / 009 :: RGBD matching between frame : 140 and 165
Fragment 001 / 009 :: RGBD matching between frame : 140 and 170
Fragment 001 / 009 :: RGBD matching between frame : 140 and 175
Fragment 001 / 009 :: RGBD matching between frame : 140 and 180
Fragment 001 / 009 :: RGBD matching between frame : 140 and 185
Fragment 001 / 009 :: RGBD matching between frame : 140 and 190
Fragment 001 / 009 :: RGBD matching between frame : 140 and 195
Fragment 001 / 009 :: RGBD matching between frame : 141 and 142
Fragment 001 / 009 :: RGBD matching between frame : 142 and 143
Fragment 001 / 009 :: RGBD matching between frame : 143 and 144
Fragment 001 / 009 :: RGBD matching between frame : 144 and 145
Fragment 001 / 009 :: RGBD matching between frame : 145 and 146
Fragment 001 / 009 :: RGBD matching between frame : 145 and 150
Fragment 001 / 009 :: RGBD matching between frame : 145 and 155
Fragment 001 / 009 :: RGBD matching between frame : 145 and 160
Fragment 001 / 009 :: RGBD matching between frame : 145 and 165
Fragment 001 / 009 :: RGBD matching between frame : 145 and 170
Fragment 001 / 009 :: RGBD matching between frame : 145 and 175
Fragment 001 / 009 :: RGBD matching between frame : 145 and 180
Fragment 001 / 009 :: RGBD matching between frame : 145 and 185
Fragment 001 / 009 :: RGBD matching between frame : 145 and 190
Fragment 001 / 009 :: RGBD matching between frame : 145 and 195
Fragment 001 / 009 :: RGBD matching between frame : 146 and 147
Fragment 001 / 009 :: RGBD matching between frame : 147 and 148
Fragment 001 / 009 :: RGBD matching between frame : 148 and 149
Fragment 001 / 009 :: RGBD matching between frame : 149 and 150
Fragment 001 / 009 :: RGBD matching between frame : 150 and 151
Fragment 001 / 009 :: RGBD matching between frame : 150 and 155
Fragment 001 / 009 :: RGBD matching between frame : 150 and 160
Fragment 001 / 009 :: RGBD matching between frame : 150 and 165
Fragment 001 / 009 :: RGBD matching between frame : 150 and 170
Fragment 001 / 009 :: RGBD matching between frame : 150 and 175
Fragment 001 / 009 :: RGBD matching between frame : 150 and 180
Fragment 001 / 009 :: RGBD matching between frame : 150 and 185
Fragment 001 / 009 :: RGBD matching between frame : 150 and 190
Fragment 001 / 009 :: RGBD matching between frame : 150 and 195
Fragment 001 / 009 :: RGBD matching between frame : 151 and 152
Fragment 001 / 009 :: RGBD matching between frame : 152 and 153
Fragment 001 / 009 :: RGBD matching between frame : 153 and 154
Fragment 001 / 009 :: RGBD matching between frame : 154 and 155
Fragment 001 / 009 :: RGBD matching between frame : 155 and 156
Fragment 001 / 009 :: RGBD matching between frame : 155 and 160
Fragment 001 / 009 :: RGBD matching between frame : 155 and 165
Fragment 001 / 009 :: RGBD matching between frame : 155 and 170
Fragment 001 / 009 :: RGBD matching between frame : 155 and 175
Fragment 001 / 009 :: RGBD matching between frame : 155 and 180
Fragment 001 / 009 :: RGBD matching between frame : 155 and 185
Fragment 001 / 009 :: RGBD matching between frame : 155 and 190
Fragment 001 / 009 :: RGBD matching between frame : 155 and 195
Fragment 001 / 009 :: RGBD matching between frame : 156 and 157
Fragment 001 / 009 :: RGBD matching between frame : 157 and 158
Fragment 001 / 009 :: RGBD matching between frame : 158 and 159
Fragment 001 / 009 :: RGBD matching between frame : 159 and 160
Fragment 001 / 009 :: RGBD matching between frame : 160 and 161
Fragment 001 / 009 :: RGBD matching between frame : 160 and 165
Fragment 001 / 009 :: RGBD matching between frame : 160 and 170
Fragment 001 / 009 :: RGBD matching between frame : 160 and 175
Fragment 001 / 009 :: RGBD matching between frame : 160 and 180
Fragment 001 / 009 :: RGBD matching between frame : 160 and 185
Fragment 001 / 009 :: RGBD matching between frame : 160 and 190
Fragment 001 / 009 :: RGBD matching between frame : 160 and 195
Fragment 001 / 009 :: RGBD matching between frame : 161 and 162
Fragment 001 / 009 :: RGBD matching between frame : 162 and 163
Fragment 001 / 009 :: RGBD matching between frame : 163 and 164
Fragment 001 / 009 :: RGBD matching between frame : 164 and 165
Fragment 001 / 009 :: RGBD matching between frame : 165 and 166
Fragment 001 / 009 :: RGBD matching between frame : 165 and 170
Fragment 001 / 009 :: RGBD matching between frame : 165 and 175
Fragment 001 / 009 :: RGBD matching between frame : 165 and 180
Fragment 001 / 009 :: RGBD matching between frame : 165 and 185
Fragment 001 / 009 :: RGBD matching between frame : 165 and 190
Fragment 001 / 009 :: RGBD matching between frame : 165 and 195
Fragment 001 / 009 :: RGBD matching between frame : 166 and 167
Fragment 001 / 009 :: RGBD matching between frame : 167 and 168
Fragment 001 / 009 :: RGBD matching between frame : 168 and 169
Fragment 001 / 009 :: RGBD matching between frame : 169 and 170
Fragment 001 / 009 :: RGBD matching between frame : 170 and 171
Fragment 001 / 009 :: RGBD matching between frame : 170 and 175
Fragment 001 / 009 :: RGBD matching between frame : 170 and 180
Fragment 001 / 009 :: RGBD matching between frame : 170 and 185
Fragment 001 / 009 :: RGBD matching between frame : 170 and 190
Fragment 001 / 009 :: RGBD matching between frame : 170 and 195
Fragment 001 / 009 :: RGBD matching between frame : 171 and 172
Fragment 001 / 009 :: RGBD matching between frame : 172 and 173
Fragment 001 / 009 :: RGBD matching between frame : 173 and 174
Fragment 001 / 009 :: RGBD matching between frame : 174 and 175
Fragment 001 / 009 :: RGBD matching between frame : 175 and 176
Fragment 001 / 009 :: RGBD matching between frame : 175 and 180
Fragment 001 / 009 :: RGBD matching between frame : 175 and 185
Fragment 001 / 009 :: RGBD matching between frame : 175 and 190
Fragment 001 / 009 :: RGBD matching between frame : 175 and 195
Fragment 001 / 009 :: RGBD matching between frame : 176 and 177
Fragment 001 / 009 :: RGBD matching between frame : 177 and 178
Fragment 001 / 009 :: RGBD matching between frame : 178 and 179
Fragment 001 / 009 :: RGBD matching between frame : 179 and 180
Fragment 001 / 009 :: RGBD matching between frame : 180 and 181
Fragment 001 / 009 :: RGBD matching between frame : 180 and 185
Fragment 001 / 009 :: RGBD matching between frame : 180 and 190
Fragment 001 / 009 :: RGBD matching between frame : 180 and 195
Fragment 001 / 009 :: RGBD matching between frame : 181 and 182
Fragment 001 / 009 :: RGBD matching between frame : 182 and 183
Fragment 001 / 009 :: RGBD matching between frame : 183 and 184
Fragment 001 / 009 :: RGBD matching between frame : 184 and 185
Fragment 001 / 009 :: RGBD matching between frame : 185 and 186
Fragment 001 / 009 :: RGBD matching between frame : 185 and 190
Fragment 001 / 009 :: RGBD matching between frame : 185 and 195
Fragment 001 / 009 :: RGBD matching between frame : 186 and 187
Fragment 001 / 009 :: RGBD matching between frame : 187 and 188
Fragment 001 / 009 :: RGBD matching between frame : 188 and 189
Fragment 001 / 009 :: RGBD matching between frame : 189 and 190
Fragment 001 / 009 :: RGBD matching between frame : 190 and 191
Fragment 001 / 009 :: RGBD matching between frame : 190 and 195
Fragment 001 / 009 :: RGBD matching between frame : 191 and 192
Fragment 001 / 009 :: RGBD matching between frame : 192 and 193
Fragment 001 / 009 :: RGBD matching between frame : 193 and 194
Fragment 001 / 009 :: RGBD matching between frame : 194 and 195
Fragment 001 / 009 :: RGBD matching between frame : 195 and 196
Fragment 001 / 009 :: RGBD matching between frame : 196 and 197
Fragment 001 / 009 :: RGBD matching between frame : 197 and 198
Fragment 001 / 009 :: RGBD matching between frame : 198 and 199
Fragment 001 / 009 :: integrate rgbd frame 100 (1 of 100).
Fragment 001 / 009 :: integrate rgbd frame 101 (2 of 100).
Fragment 001 / 009 :: integrate rgbd frame 102 (3 of 100).
Fragment 001 / 009 :: integrate rgbd frame 103 (4 of 100).
Fragment 001 / 009 :: integrate rgbd frame 104 (5 of 100).
Fragment 001 / 009 :: integrate rgbd frame 105 (6 of 100).
Fragment 001 / 009 :: integrate rgbd frame 106 (7 of 100).
Fragment 001 / 009 :: integrate rgbd frame 107 (8 of 100).
Fragment 001 / 009 :: integrate rgbd frame 108 (9 of 100).
Fragment 001 / 009 :: integrate rgbd frame 109 (10 of 100).
Fragment 001 / 009 :: integrate rgbd frame 110 (11 of 100).
Fragment 001 / 009 :: integrate rgbd frame 111 (12 of 100).
Fragment 001 / 009 :: integrate rgbd frame 112 (13 of 100).
Fragment 001 / 009 :: integrate rgbd frame 113 (14 of 100).
Fragment 001 / 009 :: integrate rgbd frame 114 (15 of 100).
Fragment 001 / 009 :: integrate rgbd frame 115 (16 of 100).
Fragment 001 / 009 :: integrate rgbd frame 116 (17 of 100).
Fragment 001 / 009 :: integrate rgbd frame 117 (18 of 100).
Fragment 001 / 009 :: integrate rgbd frame 118 (19 of 100).
Fragment 001 / 009 :: integrate rgbd frame 119 (20 of 100).
Fragment 001 / 009 :: integrate rgbd frame 120 (21 of 100).
Fragment 001 / 009 :: integrate rgbd frame 121 (22 of 100).
Fragment 001 / 009 :: integrate rgbd frame 122 (23 of 100).
Fragment 001 / 009 :: integrate rgbd frame 123 (24 of 100).
Fragment 001 / 009 :: integrate rgbd frame 124 (25 of 100).
Fragment 001 / 009 :: integrate rgbd frame 125 (26 of 100).
Fragment 001 / 009 :: integrate rgbd frame 126 (27 of 100).
Fragment 001 / 009 :: integrate rgbd frame 127 (28 of 100).
Fragment 001 / 009 :: integrate rgbd frame 128 (29 of 100).
Fragment 001 / 009 :: integrate rgbd frame 129 (30 of 100).
Fragment 001 / 009 :: integrate rgbd frame 130 (31 of 100).
Fragment 001 / 009 :: integrate rgbd frame 131 (32 of 100).
Fragment 001 / 009 :: integrate rgbd frame 132 (33 of 100).
Fragment 001 / 009 :: integrate rgbd frame 133 (34 of 100).
Fragment 001 / 009 :: integrate rgbd frame 134 (35 of 100).
Fragment 001 / 009 :: integrate rgbd frame 135 (36 of 100).
Fragment 001 / 009 :: integrate rgbd frame 136 (37 of 100).
Fragment 001 / 009 :: integrate rgbd frame 137 (38 of 100).
Fragment 001 / 009 :: integrate rgbd frame 138 (39 of 100).
Fragment 001 / 009 :: integrate rgbd frame 139 (40 of 100).
Fragment 001 / 009 :: integrate rgbd frame 140 (41 of 100).
Fragment 001 / 009 :: integrate rgbd frame 141 (42 of 100).
Fragment 001 / 009 :: integrate rgbd frame 142 (43 of 100).
Fragment 001 / 009 :: integrate rgbd frame 143 (44 of 100).
Fragment 001 / 009 :: integrate rgbd frame 144 (45 of 100).
Fragment 001 / 009 :: integrate rgbd frame 145 (46 of 100).
Fragment 001 / 009 :: integrate rgbd frame 146 (47 of 100).
Fragment 001 / 009 :: integrate rgbd frame 147 (48 of 100).
Fragment 001 / 009 :: integrate rgbd frame 148 (49 of 100).
Fragment 001 / 009 :: integrate rgbd frame 149 (50 of 100).
Fragment 001 / 009 :: integrate rgbd frame 150 (51 of 100).
Fragment 001 / 009 :: integrate rgbd frame 151 (52 of 100).
Fragment 001 / 009 :: integrate rgbd frame 152 (53 of 100).
Fragment 001 / 009 :: integrate rgbd frame 153 (54 of 100).
Fragment 001 / 009 :: integrate rgbd frame 154 (55 of 100).
Fragment 001 / 009 :: integrate rgbd frame 155 (56 of 100).
Fragment 001 / 009 :: integrate rgbd frame 156 (57 of 100).
Fragment 001 / 009 :: integrate rgbd frame 157 (58 of 100).
Fragment 001 / 009 :: integrate rgbd frame 158 (59 of 100).
Fragment 001 / 009 :: integrate rgbd frame 159 (60 of 100).
Fragment 001 / 009 :: integrate rgbd frame 160 (61 of 100).
Fragment 001 / 009 :: integrate rgbd frame 161 (62 of 100).
Fragment 001 / 009 :: integrate rgbd frame 162 (63 of 100).
Fragment 001 / 009 :: integrate rgbd frame 163 (64 of 100).
Fragment 001 / 009 :: integrate rgbd frame 164 (65 of 100).
Fragment 001 / 009 :: integrate rgbd frame 165 (66 of 100).
Fragment 001 / 009 :: integrate rgbd frame 166 (67 of 100).
Fragment 001 / 009 :: integrate rgbd frame 167 (68 of 100).
Fragment 001 / 009 :: integrate rgbd frame 168 (69 of 100).
Fragment 001 / 009 :: integrate rgbd frame 169 (70 of 100).
Fragment 001 / 009 :: integrate rgbd frame 170 (71 of 100).
Fragment 001 / 009 :: integrate rgbd frame 171 (72 of 100).
Fragment 001 / 009 :: integrate rgbd frame 172 (73 of 100).
Fragment 001 / 009 :: integrate rgbd frame 173 (74 of 100).
Fragment 001 / 009 :: integrate rgbd frame 174 (75 of 100).
Fragment 001 / 009 :: integrate rgbd frame 175 (76 of 100).
Fragment 001 / 009 :: integrate rgbd frame 176 (77 of 100).
Fragment 001 / 009 :: integrate rgbd frame 177 (78 of 100).
Fragment 001 / 009 :: integrate rgbd frame 178 (79 of 100).
Fragment 001 / 009 :: integrate rgbd frame 179 (80 of 100).
Fragment 001 / 009 :: integrate rgbd frame 180 (81 of 100).
Fragment 001 / 009 :: integrate rgbd frame 181 (82 of 100).
Fragment 001 / 009 :: integrate rgbd frame 182 (83 of 100).
Fragment 001 / 009 :: integrate rgbd frame 183 (84 of 100).
Fragment 001 / 009 :: integrate rgbd frame 184 (85 of 100).
Fragment 001 / 009 :: integrate rgbd frame 185 (86 of 100).
Fragment 001 / 009 :: integrate rgbd frame 186 (87 of 100).
Fragment 001 / 009 :: integrate rgbd frame 187 (88 of 100).
Fragment 001 / 009 :: integrate rgbd frame 188 (89 of 100).
Fragment 001 / 009 :: integrate rgbd frame 189 (90 of 100).
Fragment 001 / 009 :: integrate rgbd frame 190 (91 of 100).
Fragment 001 / 009 :: integrate rgbd frame 191 (92 of 100).
Fragment 001 / 009 :: integrate rgbd frame 192 (93 of 100).
Fragment 001 / 009 :: integrate rgbd frame 193 (94 of 100).
Fragment 001 / 009 :: integrate rgbd frame 194 (95 of 100).
Fragment 001 / 009 :: integrate rgbd frame 195 (96 of 100).
Fragment 001 / 009 :: integrate rgbd frame 196 (97 of 100).
Fragment 001 / 009 :: integrate rgbd frame 197 (98 of 100).
Fragment 001 / 009 :: integrate rgbd frame 198 (99 of 100).
Fragment 001 / 009 :: integrate rgbd frame 199 (100 of 100).
Fragment 002 / 009 :: RGBD matching between frame : 200 and 201
Fragment 002 / 009 :: RGBD matching between frame : 200 and 205
Fragment 002 / 009 :: RGBD matching between frame : 200 and 210
Fragment 002 / 009 :: RGBD matching between frame : 200 and 215
Fragment 002 / 009 :: RGBD matching between frame : 200 and 220
Fragment 002 / 009 :: RGBD matching between frame : 200 and 225
Fragment 002 / 009 :: RGBD matching between frame : 200 and 230
Fragment 002 / 009 :: RGBD matching between frame : 200 and 235
Fragment 002 / 009 :: RGBD matching between frame : 200 and 240
Fragment 002 / 009 :: RGBD matching between frame : 200 and 245
Fragment 002 / 009 :: RGBD matching between frame : 200 and 250
Fragment 002 / 009 :: RGBD matching between frame : 200 and 255
Fragment 002 / 009 :: RGBD matching between frame : 200 and 260
Fragment 002 / 009 :: RGBD matching between frame : 200 and 265
Fragment 002 / 009 :: RGBD matching between frame : 200 and 270
Fragment 002 / 009 :: RGBD matching between frame : 200 and 275
Fragment 002 / 009 :: RGBD matching between frame : 200 and 280
Fragment 002 / 009 :: RGBD matching between frame : 200 and 285
Fragment 002 / 009 :: RGBD matching between frame : 200 and 290
Fragment 002 / 009 :: RGBD matching between frame : 200 and 295
Fragment 002 / 009 :: RGBD matching between frame : 201 and 202
Fragment 002 / 009 :: RGBD matching between frame : 202 and 203
Fragment 002 / 009 :: RGBD matching between frame : 203 and 204
Fragment 002 / 009 :: RGBD matching between frame : 204 and 205
Fragment 002 / 009 :: RGBD matching between frame : 205 and 206
Fragment 002 / 009 :: RGBD matching between frame : 205 and 210
Fragment 002 / 009 :: RGBD matching between frame : 205 and 215
Fragment 002 / 009 :: RGBD matching between frame : 205 and 220
Fragment 002 / 009 :: RGBD matching between frame : 205 and 225
Fragment 002 / 009 :: RGBD matching between frame : 205 and 230
Fragment 002 / 009 :: RGBD matching between frame : 205 and 235
Fragment 002 / 009 :: RGBD matching between frame : 205 and 240
Fragment 002 / 009 :: RGBD matching between frame : 205 and 245
Fragment 002 / 009 :: RGBD matching between frame : 205 and 250
Fragment 002 / 009 :: RGBD matching between frame : 205 and 255
Fragment 002 / 009 :: RGBD matching between frame : 205 and 260
Fragment 002 / 009 :: RGBD matching between frame : 205 and 265
Fragment 002 / 009 :: RGBD matching between frame : 205 and 270
Fragment 002 / 009 :: RGBD matching between frame : 205 and 275
Fragment 002 / 009 :: RGBD matching between frame : 205 and 280
Fragment 002 / 009 :: RGBD matching between frame : 205 and 285
Fragment 002 / 009 :: RGBD matching between frame : 205 and 290
Fragment 002 / 009 :: RGBD matching between frame : 205 and 295
Fragment 002 / 009 :: RGBD matching between frame : 206 and 207
Fragment 002 / 009 :: RGBD matching between frame : 207 and 208
Fragment 002 / 009 :: RGBD matching between frame : 208 and 209
Fragment 002 / 009 :: RGBD matching between frame : 209 and 210
Fragment 002 / 009 :: RGBD matching between frame : 210 and 211
Fragment 002 / 009 :: RGBD matching between frame : 210 and 215
Fragment 002 / 009 :: RGBD matching between frame : 210 and 220
Fragment 002 / 009 :: RGBD matching between frame : 210 and 225
Fragment 002 / 009 :: RGBD matching between frame : 210 and 230
Fragment 002 / 009 :: RGBD matching between frame : 210 and 235
Fragment 002 / 009 :: RGBD matching between frame : 210 and 240
Fragment 002 / 009 :: RGBD matching between frame : 210 and 245
Fragment 002 / 009 :: RGBD matching between frame : 210 and 250
Fragment 002 / 009 :: RGBD matching between frame : 210 and 255
Fragment 002 / 009 :: RGBD matching between frame : 210 and 260
Fragment 002 / 009 :: RGBD matching between frame : 210 and 265
Fragment 002 / 009 :: RGBD matching between frame : 210 and 270
Fragment 002 / 009 :: RGBD matching between frame : 210 and 275
Fragment 002 / 009 :: RGBD matching between frame : 210 and 280
Fragment 002 / 009 :: RGBD matching between frame : 210 and 285
Fragment 002 / 009 :: RGBD matching between frame : 210 and 290
Fragment 002 / 009 :: RGBD matching between frame : 210 and 295
Fragment 002 / 009 :: RGBD matching between frame : 211 and 212
Fragment 002 / 009 :: RGBD matching between frame : 212 and 213
Fragment 002 / 009 :: RGBD matching between frame : 213 and 214
Fragment 002 / 009 :: RGBD matching between frame : 214 and 215
Fragment 002 / 009 :: RGBD matching between frame : 215 and 216
Fragment 002 / 009 :: RGBD matching between frame : 215 and 220
Fragment 002 / 009 :: RGBD matching between frame : 215 and 225
Fragment 002 / 009 :: RGBD matching between frame : 215 and 230
Fragment 002 / 009 :: RGBD matching between frame : 215 and 235
Fragment 002 / 009 :: RGBD matching between frame : 215 and 240
Fragment 002 / 009 :: RGBD matching between frame : 215 and 245
Fragment 002 / 009 :: RGBD matching between frame : 215 and 250
Fragment 002 / 009 :: RGBD matching between frame : 215 and 255
Fragment 002 / 009 :: RGBD matching between frame : 215 and 260
Fragment 002 / 009 :: RGBD matching between frame : 215 and 265
Fragment 002 / 009 :: RGBD matching between frame : 215 and 270
Fragment 002 / 009 :: RGBD matching between frame : 215 and 275
Fragment 002 / 009 :: RGBD matching between frame : 215 and 280
Fragment 002 / 009 :: RGBD matching between frame : 215 and 285
Fragment 002 / 009 :: RGBD matching between frame : 215 and 290
Fragment 002 / 009 :: RGBD matching between frame : 215 and 295
Fragment 002 / 009 :: RGBD matching between frame : 216 and 217
Fragment 002 / 009 :: RGBD matching between frame : 217 and 218
Fragment 002 / 009 :: RGBD matching between frame : 218 and 219
Fragment 002 / 009 :: RGBD matching between frame : 219 and 220
Fragment 002 / 009 :: RGBD matching between frame : 220 and 221
Fragment 002 / 009 :: RGBD matching between frame : 220 and 225
Fragment 002 / 009 :: RGBD matching between frame : 220 and 230
Fragment 002 / 009 :: RGBD matching between frame : 220 and 235
Fragment 002 / 009 :: RGBD matching between frame : 220 and 240
Fragment 002 / 009 :: RGBD matching between frame : 220 and 245
Fragment 002 / 009 :: RGBD matching between frame : 220 and 250
Fragment 002 / 009 :: RGBD matching between frame : 220 and 255
Fragment 002 / 009 :: RGBD matching between frame : 220 and 260
Fragment 002 / 009 :: RGBD matching between frame : 220 and 265
Fragment 002 / 009 :: RGBD matching between frame : 220 and 270
Fragment 002 / 009 :: RGBD matching between frame : 220 and 275
Fragment 002 / 009 :: RGBD matching between frame : 220 and 280
Fragment 002 / 009 :: RGBD matching between frame : 220 and 285
Fragment 002 / 009 :: RGBD matching between frame : 220 and 290
Fragment 002 / 009 :: RGBD matching between frame : 220 and 295
Fragment 002 / 009 :: RGBD matching between frame : 221 and 222
Fragment 002 / 009 :: RGBD matching between frame : 222 and 223
Fragment 002 / 009 :: RGBD matching between frame : 223 and 224
Fragment 002 / 009 :: RGBD matching between frame : 224 and 225
Fragment 002 / 009 :: RGBD matching between frame : 225 and 226
Fragment 002 / 009 :: RGBD matching between frame : 225 and 230
Fragment 002 / 009 :: RGBD matching between frame : 225 and 235
Fragment 002 / 009 :: RGBD matching between frame : 225 and 240
Fragment 002 / 009 :: RGBD matching between frame : 225 and 245
Fragment 002 / 009 :: RGBD matching between frame : 225 and 250
Fragment 002 / 009 :: RGBD matching between frame : 225 and 255
Fragment 002 / 009 :: RGBD matching between frame : 225 and 260
Fragment 002 / 009 :: RGBD matching between frame : 225 and 265
Fragment 002 / 009 :: RGBD matching between frame : 225 and 270
Fragment 002 / 009 :: RGBD matching between frame : 225 and 275
Fragment 002 / 009 :: RGBD matching between frame : 225 and 280
Fragment 002 / 009 :: RGBD matching between frame : 225 and 285
Fragment 002 / 009 :: RGBD matching between frame : 225 and 290
Fragment 002 / 009 :: RGBD matching between frame : 225 and 295
Fragment 002 / 009 :: RGBD matching between frame : 226 and 227
Fragment 002 / 009 :: RGBD matching between frame : 227 and 228
Fragment 002 / 009 :: RGBD matching between frame : 228 and 229
Fragment 002 / 009 :: RGBD matching between frame : 229 and 230
Fragment 002 / 009 :: RGBD matching between frame : 230 and 231
Fragment 002 / 009 :: RGBD matching between frame : 230 and 235
Fragment 002 / 009 :: RGBD matching between frame : 230 and 240
Fragment 002 / 009 :: RGBD matching between frame : 230 and 245
Fragment 002 / 009 :: RGBD matching between frame : 230 and 250
Fragment 002 / 009 :: RGBD matching between frame : 230 and 255
Fragment 002 / 009 :: RGBD matching between frame : 230 and 260
Fragment 002 / 009 :: RGBD matching between frame : 230 and 265
Fragment 002 / 009 :: RGBD matching between frame : 230 and 270
Fragment 002 / 009 :: RGBD matching between frame : 230 and 275
Fragment 002 / 009 :: RGBD matching between frame : 230 and 280
Fragment 002 / 009 :: RGBD matching between frame : 230 and 285
Fragment 002 / 009 :: RGBD matching between frame : 230 and 290
Fragment 002 / 009 :: RGBD matching between frame : 230 and 295
Fragment 002 / 009 :: RGBD matching between frame : 231 and 232
Fragment 002 / 009 :: RGBD matching between frame : 232 and 233
Fragment 002 / 009 :: RGBD matching between frame : 233 and 234
Fragment 002 / 009 :: RGBD matching between frame : 234 and 235
Fragment 002 / 009 :: RGBD matching between frame : 235 and 236
Fragment 002 / 009 :: RGBD matching between frame : 235 and 240
Fragment 002 / 009 :: RGBD matching between frame : 235 and 245
Fragment 002 / 009 :: RGBD matching between frame : 235 and 250
Fragment 002 / 009 :: RGBD matching between frame : 235 and 255
Fragment 002 / 009 :: RGBD matching between frame : 235 and 260
Fragment 002 / 009 :: RGBD matching between frame : 235 and 265
Fragment 002 / 009 :: RGBD matching between frame : 235 and 270
Fragment 002 / 009 :: RGBD matching between frame : 235 and 275
Fragment 002 / 009 :: RGBD matching between frame : 235 and 280
Fragment 002 / 009 :: RGBD matching between frame : 235 and 285
Fragment 002 / 009 :: RGBD matching between frame : 235 and 290
Fragment 002 / 009 :: RGBD matching between frame : 235 and 295
Fragment 002 / 009 :: RGBD matching between frame : 236 and 237
Fragment 002 / 009 :: RGBD matching between frame : 237 and 238
Fragment 002 / 009 :: RGBD matching between frame : 238 and 239
Fragment 002 / 009 :: RGBD matching between frame : 239 and 240
Fragment 002 / 009 :: RGBD matching between frame : 240 and 241
Fragment 002 / 009 :: RGBD matching between frame : 240 and 245
Fragment 002 / 009 :: RGBD matching between frame : 240 and 250
Fragment 002 / 009 :: RGBD matching between frame : 240 and 255
Fragment 002 / 009 :: RGBD matching between frame : 240 and 260
Fragment 002 / 009 :: RGBD matching between frame : 240 and 265
Fragment 002 / 009 :: RGBD matching between frame : 240 and 270
Fragment 002 / 009 :: RGBD matching between frame : 240 and 275
Fragment 002 / 009 :: RGBD matching between frame : 240 and 280
Fragment 002 / 009 :: RGBD matching between frame : 240 and 285
Fragment 002 / 009 :: RGBD matching between frame : 240 and 290
Fragment 002 / 009 :: RGBD matching between frame : 240 and 295
Fragment 002 / 009 :: RGBD matching between frame : 241 and 242
Fragment 002 / 009 :: RGBD matching between frame : 242 and 243
Fragment 002 / 009 :: RGBD matching between frame : 243 and 244
Fragment 002 / 009 :: RGBD matching between frame : 244 and 245
Fragment 002 / 009 :: RGBD matching between frame : 245 and 246
Fragment 002 / 009 :: RGBD matching between frame : 245 and 250
Fragment 002 / 009 :: RGBD matching between frame : 245 and 255
Fragment 002 / 009 :: RGBD matching between frame : 245 and 260
Fragment 002 / 009 :: RGBD matching between frame : 245 and 265
Fragment 002 / 009 :: RGBD matching between frame : 245 and 270
Fragment 002 / 009 :: RGBD matching between frame : 245 and 275
Fragment 002 / 009 :: RGBD matching between frame : 245 and 280
Fragment 002 / 009 :: RGBD matching between frame : 245 and 285
Fragment 002 / 009 :: RGBD matching between frame : 245 and 290
Fragment 002 / 009 :: RGBD matching between frame : 245 and 295
Fragment 002 / 009 :: RGBD matching between frame : 246 and 247
Fragment 002 / 009 :: RGBD matching between frame : 247 and 248
Fragment 002 / 009 :: RGBD matching between frame : 248 and 249
Fragment 002 / 009 :: RGBD matching between frame : 249 and 250
Fragment 002 / 009 :: RGBD matching between frame : 250 and 251
Fragment 002 / 009 :: RGBD matching between frame : 250 and 255
Fragment 002 / 009 :: RGBD matching between frame : 250 and 260
Fragment 002 / 009 :: RGBD matching between frame : 250 and 265
Fragment 002 / 009 :: RGBD matching between frame : 250 and 270
Fragment 002 / 009 :: RGBD matching between frame : 250 and 275
Fragment 002 / 009 :: RGBD matching between frame : 250 and 280
Fragment 002 / 009 :: RGBD matching between frame : 250 and 285
Fragment 002 / 009 :: RGBD matching between frame : 250 and 290
Fragment 002 / 009 :: RGBD matching between frame : 250 and 295
Fragment 002 / 009 :: RGBD matching between frame : 251 and 252
Fragment 002 / 009 :: RGBD matching between frame : 252 and 253
Fragment 002 / 009 :: RGBD matching between frame : 253 and 254
Fragment 002 / 009 :: RGBD matching between frame : 254 and 255
Fragment 002 / 009 :: RGBD matching between frame : 255 and 256
Fragment 002 / 009 :: RGBD matching between frame : 255 and 260
Fragment 002 / 009 :: RGBD matching between frame : 255 and 265
Fragment 002 / 009 :: RGBD matching between frame : 255 and 270
Fragment 002 / 009 :: RGBD matching between frame : 255 and 275
Fragment 002 / 009 :: RGBD matching between frame : 255 and 280
Fragment 002 / 009 :: RGBD matching between frame : 255 and 285
Fragment 002 / 009 :: RGBD matching between frame : 255 and 290
Fragment 002 / 009 :: RGBD matching between frame : 255 and 295
Fragment 002 / 009 :: RGBD matching between frame : 256 and 257
Fragment 002 / 009 :: RGBD matching between frame : 257 and 258
Fragment 002 / 009 :: RGBD matching between frame : 258 and 259
Fragment 002 / 009 :: RGBD matching between frame : 259 and 260
Fragment 002 / 009 :: RGBD matching between frame : 260 and 261
Fragment 002 / 009 :: RGBD matching between frame : 260 and 265
Fragment 002 / 009 :: RGBD matching between frame : 260 and 270
Fragment 002 / 009 :: RGBD matching between frame : 260 and 275
Fragment 002 / 009 :: RGBD matching between frame : 260 and 280
Fragment 002 / 009 :: RGBD matching between frame : 260 and 285
Fragment 002 / 009 :: RGBD matching between frame : 260 and 290
Fragment 002 / 009 :: RGBD matching between frame : 260 and 295
Fragment 002 / 009 :: RGBD matching between frame : 261 and 262
Fragment 002 / 009 :: RGBD matching between frame : 262 and 263
Fragment 002 / 009 :: RGBD matching between frame : 263 and 264
Fragment 002 / 009 :: RGBD matching between frame : 264 and 265
Fragment 002 / 009 :: RGBD matching between frame : 265 and 266
Fragment 002 / 009 :: RGBD matching between frame : 265 and 270
Fragment 002 / 009 :: RGBD matching between frame : 265 and 275
Fragment 002 / 009 :: RGBD matching between frame : 265 and 280
Fragment 002 / 009 :: RGBD matching between frame : 265 and 285
Fragment 002 / 009 :: RGBD matching between frame : 265 and 290
Fragment 002 / 009 :: RGBD matching between frame : 265 and 295
Fragment 002 / 009 :: RGBD matching between frame : 266 and 267
Fragment 002 / 009 :: RGBD matching between frame : 267 and 268
Fragment 002 / 009 :: RGBD matching between frame : 268 and 269
Fragment 002 / 009 :: RGBD matching between frame : 269 and 270
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 275 edges.
[Open3D DEBUG] Line process weight : 33.486652
[Open3D DEBUG] [Initial ] residual : 1.916262e+04, lambda : 1.294122e+01
[Open3D DEBUG] [Iteration 00] residual : 1.168100e+03, valid edges : 144, time : 0.002 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.152531e+03, valid edges : 144, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.152432e+03, valid edges : 144, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 1.152430e+03, valid edges : 144, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.008 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 243 edges.
[Open3D DEBUG] Line process weight : 36.401919
[Open3D DEBUG] [Initial ] residual : 1.875269e+02, lambda : 1.415560e+01
[Open3D DEBUG] [Iteration 00] residual : 1.868457e+02, valid edges : 144, time : 0.002 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.868390e+02, valid edges : 144, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.005 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 289 edges.
[Open3D DEBUG] Line process weight : 61.238459
[Open3D DEBUG] [Initial ] residual : 6.342089e+03, lambda : 2.203213e+01
[Open3D DEBUG] [Iteration 00] residual : 1.084951e+03, valid edges : 176, time : 0.002 sec.
[Open3D DEBUG] [Iteration 01] residual : 6.715339e+02, valid edges : 177, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 6.713689e+02, valid edges : 177, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 6.713638e+02, valid edges : 177, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.007 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 276 edges.
[Open3D DEBUG] Line process weight : 62.303346
[Open3D DEBUG] [Initial ] residual : 9.956664e+01, lambda : 2.619504e+01
[Open3D DEBUG] [Iteration 00] residual : 9.320617e+01, valid edges : 177, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 9.292835e+01, valid edges : 177, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 9.292579e+01, valid edges : 177, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.005 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 189 edges.
[Open3D DEBUG] Line process weight : 71.560733
[Open3D DEBUG] [Initial ] residual : 2.865412e+04, lambda : 1.776507e+01
[Open3D DEBUG] [Iteration 00] residual : 1.104708e+03, valid edges : 74, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.064056e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.060195e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 1.059070e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 04] residual : 1.058715e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 05] residual : 1.058600e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 06] residual : 1.058562e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 07] residual : 1.058550e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 08] residual : 1.058545e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 09] residual : 1.058544e+03, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * currentFragment 002 / 009 :: RGBD matching between frame : 270 and 271
Fragment 002 / 009 :: RGBD matching between frame : 270 and 275
Fragment 002 / 009 :: RGBD matching between frame : 270 and 280
Fragment 002 / 009 :: RGBD matching between frame : 270 and 285
Fragment 002 / 009 :: RGBD matching between frame : 270 and 290
Fragment 002 / 009 :: RGBD matching between frame : 270 and 295
Fragment 002 / 009 :: RGBD matching between frame : 271 and 272
Fragment 002 / 009 :: RGBD matching between frame : 272 and 273
Fragment 002 / 009 :: RGBD matching between frame : 273 and 274
Fragment 002 / 009 :: RGBD matching between frame : 274 and 275
Fragment 002 / 009 :: RGBD matching between frame : 275 and 276
Fragment 002 / 009 :: RGBD matching between frame : 275 and 280
Fragment 002 / 009 :: RGBD matching between frame : 275 and 285
Fragment 002 / 009 :: RGBD matching between frame : 275 and 290
Fragment 002 / 009 :: RGBD matching between frame : 275 and 295
Fragment 002 / 009 :: RGBD matching between frame : 276 and 277
Fragment 002 / 009 :: RGBD matching between frame : 277 and 278
Fragment 002 / 009 :: RGBD matching between frame : 278 and 279
Fragment 002 / 009 :: RGBD matching between frame : 279 and 280
Fragment 002 / 009 :: RGBD matching between frame : 280 and 281
Fragment 002 / 009 :: RGBD matching between frame : 280 and 285
Fragment 002 / 009 :: RGBD matching between frame : 280 and 290
Fragment 002 / 009 :: RGBD matching between frame : 280 and 295
Fragment 002 / 009 :: RGBD matching between frame : 281 and 282
Fragment 002 / 009 :: RGBD matching between frame : 282 and 283
Fragment 002 / 009 :: RGBD matching between frame : 283 and 284
Fragment 002 / 009 :: RGBD matching between frame : 284 and 285
Fragment 002 / 009 :: RGBD matching between frame : 285 and 286
Fragment 002 / 009 :: RGBD matching between frame : 285 and 290
Fragment 002 / 009 :: RGBD matching between frame : 285 and 295
Fragment 002 / 009 :: RGBD matching between frame : 286 and 287
Fragment 002 / 009 :: RGBD matching between frame : 287 and 288
Fragment 002 / 009 :: RGBD matching between frame : 288 and 289
Fragment 002 / 009 :: RGBD matching between frame : 289 and 290
Fragment 002 / 009 :: RGBD matching between frame : 290 and 291
Fragment 002 / 009 :: RGBD matching between frame : 290 and 295
Fragment 002 / 009 :: RGBD matching between frame : 291 and 292
Fragment 002 / 009 :: RGBD matching between frame : 292 and 293
Fragment 002 / 009 :: RGBD matching between frame : 293 and 294
Fragment 002 / 009 :: RGBD matching between frame : 294 and 295
Fragment 002 / 009 :: RGBD matching between frame : 295 and 296
Fragment 002 / 009 :: RGBD matching between frame : 296 and 297
Fragment 002 / 009 :: RGBD matching between frame : 297 and 298
Fragment 002 / 009 :: RGBD matching between frame : 298 and 299
Fragment 002 / 009 :: integrate rgbd frame 200 (1 of 100).
Fragment 002 / 009 :: integrate rgbd frame 201 (2 of 100).
Fragment 002 / 009 :: integrate rgbd frame 202 (3 of 100).
Fragment 002 / 009 :: integrate rgbd frame 203 (4 of 100).
Fragment 002 / 009 :: integrate rgbd frame 204 (5 of 100).
Fragment 002 / 009 :: integrate rgbd frame 205 (6 of 100).
Fragment 002 / 009 :: integrate rgbd frame 206 (7 of 100).
Fragment 002 / 009 :: integrate rgbd frame 207 (8 of 100).
Fragment 002 / 009 :: integrate rgbd frame 208 (9 of 100).
Fragment 002 / 009 :: integrate rgbd frame 209 (10 of 100).
Fragment 002 / 009 :: integrate rgbd frame 210 (11 of 100).
Fragment 002 / 009 :: integrate rgbd frame 211 (12 of 100).
Fragment 002 / 009 :: integrate rgbd frame 212 (13 of 100).
Fragment 002 / 009 :: integrate rgbd frame 213 (14 of 100).
Fragment 002 / 009 :: integrate rgbd frame 214 (15 of 100).
Fragment 002 / 009 :: integrate rgbd frame 215 (16 of 100).
Fragment 002 / 009 :: integrate rgbd frame 216 (17 of 100).
Fragment 002 / 009 :: integrate rgbd frame 217 (18 of 100).
Fragment 002 / 009 :: integrate rgbd frame 218 (19 of 100).
Fragment 002 / 009 :: integrate rgbd frame 219 (20 of 100).
Fragment 002 / 009 :: integrate rgbd frame 220 (21 of 100).
Fragment 002 / 009 :: integrate rgbd frame 221 (22 of 100).
Fragment 002 / 009 :: integrate rgbd frame 222 (23 of 100).
Fragment 002 / 009 :: integrate rgbd frame 223 (24 of 100).
Fragment 002 / 009 :: integrate rgbd frame 224 (25 of 100).
Fragment 002 / 009 :: integrate rgbd frame 225 (26 of 100).
Fragment 002 / 009 :: integrate rgbd frame 226 (27 of 100).
Fragment 002 / 009 :: integrate rgbd frame 227 (28 of 100).
Fragment 002 / 009 :: integrate rgbd frame 228 (29 of 100).
Fragment 002 / 009 :: integrate rgbd frame 229 (30 of 100).
Fragment 002 / 009 :: integrate rgbd frame 230 (31 of 100).
Fragment 002 / 009 :: integrate rgbd frame 231 (32 of 100).
Fragment 002 / 009 :: integrate rgbd frame 232 (33 of 100).
Fragment 002 / 009 :: integrate rgbd frame 233 (34 of 100).
Fragment 002 / 009 :: integrate rgbd frame 234 (35 of 100).
Fragment 002 / 009 :: integrate rgbd frame 235 (36 of 100).
Fragment 002 / 009 :: integrate rgbd frame 236 (37 of 100).
Fragment 002 / 009 :: integrate rgbd frame 237 (38 of 100).
Fragment 002 / 009 :: integrate rgbd frame 238 (39 of 100).
Fragment 002 / 009 :: integrate rgbd frame 239 (40 of 100).
Fragment 002 / 009 :: integrate rgbd frame 240 (41 of 100).
Fragment 002 / 009 :: integrate rgbd frame 241 (42 of 100).
Fragment 002 / 009 :: integrate rgbd frame 242 (43 of 100).
Fragment 002 / 009 :: integrate rgbd frame 243 (44 of 100).
Fragment 002 / 009 :: integrate rgbd frame 244 (45 of 100).
Fragment 002 / 009 :: integrate rgbd frame 245 (46 of 100).
Fragment 002 / 009 :: integrate rgbd frame 246 (47 of 100).
Fragment 002 / 009 :: integrate rgbd frame 247 (48 of 100).
Fragment 002 / 009 :: integrate rgbd frame 248 (49 of 100).
Fragment 002 / 009 :: integrate rgbd frame 249 (50 of 100).
Fragment 002 / 009 :: integrate rgbd frame 250 (51 of 100).
Fragment 002 / 009 :: integrate rgbd frame 251 (52 of 100).
Fragment 002 / 009 :: integrate rgbd frame 252 (53 of 100).
Fragment 002 / 009 :: integrate rgbd frame 253 (54 of 100).
Fragment 002 / 009 :: integrate rgbd frame 254 (55 of 100).
Fragment 002 / 009 :: integrate rgbd frame 255 (56 of 100).
Fragment 002 / 009 :: integrate rgbd frame 256 (57 of 100).
Fragment 002 / 009 :: integrate rgbd frame 257 (58 of 100).
Fragment 002 / 009 :: integrate rgbd frame 258 (59 of 100).
Fragment 002 / 009 :: integrate rgbd frame 259 (60 of 100).
Fragment 002 / 009 :: integrate rgbd frame 260 (61 of 100).
Fragment 002 / 009 :: integrate rgbd frame 261 (62 of 100).
Fragment 002 / 009 :: integrate rgbd frame 262 (63 of 100).
Fragment 002 / 009 :: integrate rgbd frame 263 (64 of 100).
Fragment 002 / 009 :: integrate rgbd frame 264 (65 of 100).
Fragment 002 / 009 :: integrate rgbd frame 265 (66 of 100).
Fragment 002 / 009 :: integrate rgbd frame 266 (67 of 100).
Fragment 002 / 009 :: integrate rgbd frame 267 (68 of 100).
Fragment 002 / 009 :: integrate rgbd frame 268 (69 of 100).
Fragment 002 / 009 :: integrate rgbd frame 269 (70 of 100).
Fragment 002 / 009 :: integrate rgbd frame 270 (71 of 100).
Fragment 002 / 009 :: integrate rgbd frame 271 (72 of 100).
Fragment 002 / 009 :: integrate rgbd frame 272 (73 of 100).
Fragment 002 / 009 :: integrate rgbd frame 273 (74 of 100).
Fragment 002 / 009 :: integrate rgbd frame 274 (75 of 100).
Fragment 002 / 009 :: integrate rgbd frame 275 (76 of 100).
Fragment 002 / 009 :: integrate rgbd frame 276 (77 of 100).
Fragment 002 / 009 :: integrate rgbd frame 277 (78 of 100).
Fragment 002 / 009 :: integrate rgbd frame 278 (79 of 100).
Fragment 002 / 009 :: integrate rgbd frame 279 (80 of 100).
Fragment 002 / 009 :: integrate rgbd frame 280 (81 of 100).
Fragment 002 / 009 :: integrate rgbd frame 281 (82 of 100).
Fragment 002 / 009 :: integrate rgbd frame 282 (83 of 100).
Fragment 002 / 009 :: integrate rgbd frame 283 (84 of 100).
Fragment 002 / 009 :: integrate rgbd frame 284 (85 of 100).
Fragment 002 / 009 :: integrate rgbd frame 285 (86 of 100).
Fragment 002 / 009 :: integrate rgbd frame 286 (87 of 100).
Fragment 002 / 009 :: integrate rgbd frame 287 (88 of 100).
Fragment 002 / 009 :: integrate rgbd frame 288 (89 of 100).
Fragment 002 / 009 :: integrate rgbd frame 289 (90 of 100).
Fragment 002 / 009 :: integrate rgbd frame 290 (91 of 100).
Fragment 002 / 009 :: integrate rgbd frame 291 (92 of 100).
Fragment 002 / 009 :: integrate rgbd frame 292 (93 of 100).
Fragment 002 / 009 :: integrate rgbd frame 293 (94 of 100).
Fragment 002 / 009 :: integrate rgbd frame 294 (95 of 100).
Fragment 002 / 009 :: integrate rgbd frame 295 (96 of 100).
Fragment 002 / 009 :: integrate rgbd frame 296 (97 of 100).
Fragment 002 / 009 :: integrate rgbd frame 297 (98 of 100).
Fragment 002 / 009 :: integrate rgbd frame 298 (99 of 100).
Fragment 002 / 009 :: integrate rgbd frame 299 (100 of 100).
Fragment 003 / 009 :: RGBD matching between frame : 300 and 301
Fragment 003 / 009 :: RGBD matching between frame : 300 and 305
Fragment 003 / 009 :: RGBD matching between frame : 300 and 310
Fragment 003 / 009 :: RGBD matching between frame : 300 and 315
Fragment 003 / 009 :: RGBD matching between frame : 300 and 320
Fragment 003 / 009 :: RGBD matching between frame : 300 and 325
Fragment 003 / 009 :: RGBD matching between frame : 300 and 330
Fragment 003 / 009 :: RGBD matching between frame : 300 and 335
Fragment 003 / 009 :: RGBD matching between frame : 300 and 340
Fragment 003 / 009 :: RGBD matching between frame : 300 and 345
Fragment 003 / 009 :: RGBD matching between frame : 300 and 350
Fragment 003 / 009 :: RGBD matching between frame : 300 and 355
Fragment 003 / 009 :: RGBD matching between frame : 300 and 360
Fragment 003 / 009 :: RGBD matching between frame : 300 and 365
Fragment 003 / 009 :: RGBD matching between frame : 300 and 370
Fragment 003 / 009 :: RGBD matching between frame : 300 and 375
Fragment 003 / 009 :: RGBD matching between frame : 300 and 380
Fragment 003 / 009 :: RGBD matching between frame : 300 and 385
Fragment 003 / 009 :: RGBD matching between frame : 300 and 390
Fragment 003 / 009 :: RGBD matching between frame : 300 and 395
Fragment 003 / 009 :: RGBD matching between frame : 301 and 302
Fragment 003 / 009 :: RGBD matching between frame : 302 and 303
Fragment 003 / 009 :: RGBD matching between frame : 303 and 304
Fragment 003 / 009 :: RGBD matching between frame : 304 and 305
Fragment 003 / 009 :: RGBD matching between frame : 305 and 306
Fragment 003 / 009 :: RGBD matching between frame : 305 and 310
Fragment 003 / 009 :: RGBD matching between frame : 305 and 315
Fragment 003 / 009 :: RGBD matching between frame : 305 and 320
Fragment 003 / 009 :: RGBD matching between frame : 305 and 325
Fragment 003 / 009 :: RGBD matching between frame : 305 and 330
Fragment 003 / 009 :: RGBD matching between frame : 305 and 335
Fragment 003 / 009 :: RGBD matching between frame : 305 and 340
Fragment 003 / 009 :: RGBD matching between frame : 305 and 345
Fragment 003 / 009 :: RGBD matching between frame : 305 and 350
Fragment 003 / 009 :: RGBD matching between frame : 305 and 355
Fragment 003 / 009 :: RGBD matching between frame : 305 and 360
Fragment 003 / 009 :: RGBD matching between frame : 305 and 365
Fragment 003 / 009 :: RGBD matching between frame : 305 and 370
Fragment 003 / 009 :: RGBD matching between frame : 305 and 375
Fragment 003 / 009 :: RGBD matching between frame : 305 and 380
Fragment 003 / 009 :: RGBD matching between frame : 305 and 385
Fragment 003 / 009 :: RGBD matching between frame : 305 and 390
Fragment 003 / 009 :: RGBD matching between frame : 305 and 395
Fragment 003 / 009 :: RGBD matching between frame : 306 and 307
Fragment 003 / 009 :: RGBD matching between frame : 307 and 308
Fragment 003 / 009 :: RGBD matching between frame : 308 and 309
Fragment 003 / 009 :: RGBD matching between frame : 309 and 310
Fragment 003 / 009 :: RGBD matching between frame : 310 and 311
Fragment 003 / 009 :: RGBD matching between frame : 310 and 315
Fragment 003 / 009 :: RGBD matching between frame : 310 and 320
Fragment 003 / 009 :: RGBD matching between frame : 310 and 325
Fragment 003 / 009 :: RGBD matching between frame : 310 and 330
Fragment 003 / 009 :: RGBD matching between frame : 310 and 335
Fragment 003 / 009 :: RGBD matching between frame : 310 and 340
Fragment 003 / 009 :: RGBD matching between frame : 310 and 345
Fragment 003 / 009 :: RGBD matching between frame : 310 and 350
Fragment 003 / 009 :: RGBD matching between frame : 310 and 355
Fragment 003 / 009 :: RGBD matching between frame : 310 and 360
Fragment 003 / 009 :: RGBD matching between frame : 310 and 365
Fragment 003 / 009 :: RGBD matching between frame : 310 and 370
Fragment 003 / 009 :: RGBD matching between frame : 310 and 375
Fragment 003 / 009 :: RGBD matching between frame : 310 and 380
Fragment 003 / 009 :: RGBD matching between frame : 310 and 385
Fragment 003 / 009 :: RGBD matching between frame : 310 and 390
Fragment 003 / 009 :: RGBD matching between frame : 310 and 395
Fragment 003 / 009 :: RGBD matching between frame : 311 and 312
Fragment 003 / 009 :: RGBD matching between frame : 312 and 313
Fragment 003 / 009 :: RGBD matching between frame : 313 and 314
Fragment 003 / 009 :: RGBD matching between frame : 314 and 315
Fragment 003 / 009 :: RGBD matching between frame : 315 and 316
Fragment 003 / 009 :: RGBD matching between frame : 315 and 320
Fragment 003 / 009 :: RGBD matching between frame : 315 and 325
Fragment 003 / 009 :: RGBD matching between frame : 315 and 330
Fragment 003 / 009 :: RGBD matching between frame : 315 and 335
Fragment 003 / 009 :: RGBD matching between frame : 315 and 340
Fragment 003 / 009 :: RGBD matching between frame : 315 and 345
Fragment 003 / 009 :: RGBD matching between frame : 315 and 350
Fragment 003 / 009 :: RGBD matching between frame : 315 and 355
Fragment 003 / 009 :: RGBD matching between frame : 315 and 360
Fragment 003 / 009 :: RGBD matching between frame : 315 and 365
Fragment 003 / 009 :: RGBD matching between frame : 315 and 370
Fragment 003 / 009 :: RGBD matching between frame : 315 and 375
Fragment 003 / 009 :: RGBD matching between frame : 315 and 380
Fragment 003 / 009 :: RGBD matching between frame : 315 and 385
Fragment 003 / 009 :: RGBD matching between frame : 315 and 390
Fragment 003 / 009 :: RGBD matching between frame : 315 and 395
Fragment 003 / 009 :: RGBD matching between frame : 316 and 317
Fragment 003 / 009 :: RGBD matching between frame : 317 and 318
Fragment 003 / 009 :: RGBD matching between frame : 318 and 319
Fragment 003 / 009 :: RGBD matching between frame : 319 and 320
Fragment 003 / 009 :: RGBD matching between frame : 320 and 321
Fragment 003 / 009 :: RGBD matching between frame : 320 and 325
Fragment 003 / 009 :: RGBD matching between frame : 320 and 330
Fragment 003 / 009 :: RGBD matching between frame : 320 and 335
Fragment 003 / 009 :: RGBD matching between frame : 320 and 340
Fragment 003 / 009 :: RGBD matching between frame : 320 and 345
Fragment 003 / 009 :: RGBD matching between frame : 320 and 350
Fragment 003 / 009 :: RGBD matching between frame : 320 and 355
Fragment 003 / 009 :: RGBD matching between frame : 320 and 360
Fragment 003 / 009 :: RGBD matching between frame : 320 and 365
Fragment 003 / 009 :: RGBD matching between frame : 320 and 370
Fragment 003 / 009 :: RGBD matching between frame : 320 and 375
Fragment 003 / 009 :: RGBD matching between frame : 320 and 380
Fragment 003 / 009 :: RGBD matching between frame : 320 and 385
Fragment 003 / 009 :: RGBD matching between frame : 320 and 390
Fragment 003 / 009 :: RGBD matching between frame : 320 and 395
Fragment 003 / 009 :: RGBD matching between frame : 321 and 322
Fragment 003 / 009 :: RGBD matching between frame : 322 and 323
Fragment 003 / 009 :: RGBD matching between frame : 323 and 324
Fragment 003 / 009 :: RGBD matching between frame : 324 and 325
Fragment 003 / 009 :: RGBD matching between frame : 325 and 326
Fragment 003 / 009 :: RGBD matching between frame : 325 and 330
Fragment 003 / 009 :: RGBD matching between frame : 325 and 335
Fragment 003 / 009 :: RGBD matching between frame : 325 and 340
Fragment 003 / 009 :: RGBD matching between frame : 325 and 345
Fragment 003 / 009 :: RGBD matching between frame : 325 and 350
Fragment 003 / 009 :: RGBD matching between frame : 325 and 355
Fragment 003 / 009 :: RGBD matching between frame : 325 and 360
Fragment 003 / 009 :: RGBD matching between frame : 325 and 365
Fragment 003 / 009 :: RGBD matching between frame : 325 and 370
Fragment 003 / 009 :: RGBD matching between frame : 325 and 375
Fragment 003 / 009 :: RGBD matching between frame : 325 and 380
Fragment 003 / 009 :: RGBD matching between frame : 325 and 385
Fragment 003 / 009 :: RGBD matching between frame : 325 and 390
Fragment 003 / 009 :: RGBD matching between frame : 325 and 395
Fragment 003 / 009 :: RGBD matching between frame : 326 and 327
Fragment 003 / 009 :: RGBD matching between frame : 327 and 328
Fragment 003 / 009 :: RGBD matching between frame : 328 and 329
Fragment 003 / 009 :: RGBD matching between frame : 329 and 330
Fragment 003 / 009 :: RGBD matching between frame : 330 and 331
Fragment 003 / 009 :: RGBD matching between frame : 330 and 335
Fragment 003 / 009 :: RGBD matching between frame : 330 and 340
Fragment 003 / 009 :: RGBD matching between frame : 330 and 345
Fragment 003 / 009 :: RGBD matching between frame : 330 and 350
Fragment 003 / 009 :: RGBD matching between frame : 330 and 355
Fragment 003 / 009 :: RGBD matching between frame : 330 and 360
Fragment 003 / 009 :: RGBD matching between frame : 330 and 365
Fragment 003 / 009 :: RGBD matching between frame : 330 and 370
Fragment 003 / 009 :: RGBD matching between frame : 330 and 375
Fragment 003 / 009 :: RGBD matching between frame : 330 and 380
Fragment 003 / 009 :: RGBD matching between frame : 330 and 385
Fragment 003 / 009 :: RGBD matching between frame : 330 and 390
Fragment 003 / 009 :: RGBD matching between frame : 330 and 395
Fragment 003 / 009 :: RGBD matching between frame : 331 and 332
Fragment 003 / 009 :: RGBD matching between frame : 332 and 333
Fragment 003 / 009 :: RGBD matching between frame : 333 and 334
Fragment 003 / 009 :: RGBD matching between frame : 334 and 335
Fragment 003 / 009 :: RGBD matching between frame : 335 and 336
Fragment 003 / 009 :: RGBD matching between frame : 335 and 340
Fragment 003 / 009 :: RGBD matching between frame : 335 and 345
Fragment 003 / 009 :: RGBD matching between frame : 335 and 350
Fragment 003 / 009 :: RGBD matching between frame : 335 and 355
Fragment 003 / 009 :: RGBD matching between frame : 335 and 360
Fragment 003 / 009 :: RGBD matching between frame : 335 and 365
Fragment 003 / 009 :: RGBD matching between frame : 335 and 370
Fragment 003 / 009 :: RGBD matching between frame : 335 and 375
Fragment 003 / 009 :: RGBD matching between frame : 335 and 380
Fragment 003 / 009 :: RGBD matching between frame : 335 and 385
Fragment 003 / 009 :: RGBD matching between frame : 335 and 390
Fragment 003 / 009 :: RGBD matching between frame : 335 and 395
Fragment 003 / 009 :: RGBD matching between frame : 336 and 337
Fragment 003 / 009 :: RGBD matching between frame : 337 and 338
Fragment 003 / 009 :: RGBD matching between frame : 338 and 339
Fragment 003 / 009 :: RGBD matching between frame : 339 and 340
Fragment 003 / 009 :: RGBD matching between frame : 340 and 341
Fragment 003 / 009 :: RGBD matching between frame : 340 and 345
Fragment 003 / 009 :: RGBD matching between frame : 340 and 350
Fragment 003 / 009 :: RGBD matching between frame : 340 and 355
Fragment 003 / 009 :: RGBD matching between frame : 340 and 360
Fragment 003 / 009 :: RGBD matching between frame : 340 and 365
Fragment 003 / 009 :: RGBD matching between frame : 340 and 370
Fragment 003 / 009 :: RGBD matching between frame : 340 and 375
Fragment 003 / 009 :: RGBD matching between frame : 340 and 380
Fragment 003 / 009 :: RGBD matching between frame : 340 and 385
Fragment 003 / 009 :: RGBD matching between frame : 340 and 390
Fragment 003 / 009 :: RGBD matching between frame : 340 and 395
Fragment 003 / 009 :: RGBD matching between frame : 341 and 342
Fragment 003 / 009 :: RGBD matching between frame : 342 and 343
Fragment 003 / 009 :: RGBD matching between frame : 343 and 344
Fragment 003 / 009 :: RGBD matching between frame : 344 and 345
Fragment 003 / 009 :: RGBD matching between frame : 345 and 346
Fragment 003 / 009 :: RGBD matching between frame : 345 and 350
Fragment 003 / 009 :: RGBD matching between frame : 345 and 355
Fragment 003 / 009 :: RGBD matching between frame : 345 and 360
Fragment 003 / 009 :: RGBD matching between frame : 345 and 365
Fragment 003 / 009 :: RGBD matching between frame : 345 and 370
Fragment 003 / 009 :: RGBD matching between frame : 345 and 375
Fragment 003 / 009 :: RGBD matching between frame : 345 and 380
Fragment 003 / 009 :: RGBD matching between frame : 345 and 385
Fragment 003 / 009 :: RGBD matching between frame : 345 and 390
Fragment 003 / 009 :: RGBD matching between frame : 345 and 395
Fragment 003 / 009 :: RGBD matching between frame : 346 and 347
Fragment 003 / 009 :: RGBD matching between frame : 347 and 348
Fragment 003 / 009 :: RGBD matching between frame : 348 and 349
Fragment 003 / 009 :: RGBD matching between frame : 349 and 350
Fragment 003 / 009 :: RGBD matching between frame : 350 and 351
Fragment 003 / 009 :: RGBD matching between frame : 350 and 355
Fragment 003 / 009 :: RGBD matching between frame : 350 and 360
Fragment 003 / 009 :: RGBD matching between frame : 350 and 365
Fragment 003 / 009 :: RGBD matching between frame : 350 and 370
Fragment 003 / 009 :: RGBD matching between frame : 350 and 375
Fragment 003 / 009 :: RGBD matching between frame : 350 and 380
Fragment 003 / 009 :: RGBD matching between frame : 350 and 385
Fragment 003 / 009 :: RGBD matching between frame : 350 and 390
Fragment 003 / 009 :: RGBD matching between frame : 350 and 395
Fragment 003 / 009 :: RGBD matching between frame : 351 and 352
Fragment 003 / 009 :: RGBD matching between frame : 352 and 353
Fragment 003 / 009 :: RGBD matching between frame : 353 and 354
Fragment 003 / 009 :: RGBD matching between frame : 354 and 355
Fragment 003 / 009 :: RGBD matching between frame : 355 and 356
Fragment 003 / 009 :: RGBD matching between frame : 355 and 360
Fragment 003 / 009 :: RGBD matching between frame : 355 and 365
Fragment 003 / 009 :: RGBD matching between frame : 355 and 370
Fragment 003 / 009 :: RGBD matching between frame : 355 and 375
Fragment 003 / 009 :: RGBD matching between frame : 355 and 380
Fragment 003 / 009 :: RGBD matching between frame : 355 and 385
Fragment 003 / 009 :: RGBD matching between frame : 355 and 390
Fragment 003 / 009 :: RGBD matching between frame : 355 and 395
Fragment 003 / 009 :: RGBD matching between frame : 356 and 357
Fragment 003 / 009 :: RGBD matching between frame : 357 and 358
Fragment 003 / 009 :: RGBD matching between frame : 358 and 359
Fragment 003 / 009 :: RGBD matching between frame : 359 and 360
Fragment 003 / 009 :: RGBD matching between frame : 360 and 361
Fragment 003 / 009 :: RGBD matching between frame : 360 and 365
Fragment 003 / 009 :: RGBD matching between frame : 360 and 370
Fragment 003 / 009 :: RGBD matching between frame : 360 and 375
Fragment 003 / 009 :: RGBD matching between frame : 360 and 380
Fragment 003 / 009 :: RGBD matching between frame : 360 and 385
Fragment 003 / 009 :: RGBD matching between frame : 360 and 390
Fragment 003 / 009 :: RGBD matching between frame : 360 and 395
Fragment 003 / 009 :: RGBD matching between frame : 361 and 362
Fragment 003 / 009 :: RGBD matching between frame : 362 and 363
Fragment 003 / 009 :: RGBD matching between frame : 363 and 364
Fragment 003 / 009 :: RGBD matching between frame : 364 and 365
Fragment 003 / 009 :: RGBD matching between frame : 365 and 366
Fragment 003 / 009 :: RGBD matching between frame : 365 and 370
Fragment 003 / 009 :: RGBD matching between frame : 365 and 375
Fragment 003 / 009 :: RGBD matching between frame : 365 and 380
Fragment 003 / 009 :: RGBD matching between frame : 365 and 385
Fragment 003 / 009 :: RGBD matching between frame : 365 and 390
Fragment 003 / 009 :: RGBD matching between frame : 365 and 395
Fragment 003 / 009 :: RGBD matching between frame : 366 and 367
Fragment 003 / 009 :: RGBD matching between frame : 367 and 368
Fragment 003 / 009 :: RGBD matching between frame : 368 and 369
Fragment 003 / 009 :: RGBD matching between frame : 369 and 370
Fragment 003 / 009 :: RGBD matching between frame : 370 and 371
Fragment 003 / 009 :: RGBD matching between frame : 370 and 375
Fragment 003 / 009 :: RGBD matching between frame : 370 and 380
Fragment 003 / 009 :: RGBD matching between frame : 370 and 385
Fragment 003 / 009 :: RGBD matching between frame : 370 and 390
Fragment 003 / 009 :: RGBD matching between frame : 370 and 395
Fragment 003 / 009 :: RGBD matching between frame : 371 and 372
Fragment 003 / 009 :: RGBD matching between frame : 372 and 373
Fragment 003 / 009 :: RGBD matching between frame : 373 and 374
Fragment 003 / 009 :: RGBD matching between frame : 374 and 375
Fragment 003 / 009 :: RGBD matching between frame : 375 and 376
Fragment 003 / 009 :: RGBD matching between frame : 375 and 380
Fragment 003 / 009 :: RGBD matching between frame : 375 and 385
Fragment 003 / 009 :: RGBD matching between frame : 375 and 390
Fragment 003 / 009 :: RGBD matching between frame : 375 and 395
Fragment 003 / 009 :: RGBD matching between frame : 376 and 377
Fragment 003 / 009 :: RGBD matching between frame : 377 and 378
Fragment 003 / 009 :: RGBD matching between frame : 378 and 379
Fragment 003 / 009 :: RGBD matching between frame : 379 and 380
Fragment 003 / 009 :: RGBD matching between frame : 380 and 381
Fragment 003 / 009 :: RGBD matching between frame : 380 and 385
Fragment 003 / 009 :: RGBD matching between frame : 380 and 390
Fragment 003 / 009 :: RGBD matching between frame : 380 and 395
Fragment 003 / 009 :: RGBD matching between frame : 381 and 382
Fragment 003 / 009 :: RGBD matching between frame : 382 and 383
Fragment 003 / 009 :: RGBD matching between frame : 383 and 384
Fragment 003 / 009 :: RGBD matching between frame : 384 and 385
Fragment 003 / 009 :: RGBD matching between frame : 385 and 386
Fragment 003 / 009 :: RGBD matching between frame : 385 and 390
Fragment 003 / 009 :: RGBD matching between frame : 385 and 395
Fragment 003 / 009 :: RGBD matching between frame : 386 and 387
Fragment 003 / 009 :: RGBD matching between frame : 387 and 388
Fragment 003 / 009 :: RGBD matching between frame : 388 and 389
Fragment 003 / 009 :: RGBD matching between frame : 389 and 390
Fragment 003 / 009 :: RGBD matching between frame : 390 and 391
Fragment 003 / 009 :: RGBD matching between frame : 390 and 395
Fragment 003 / 009 :: RGBD matching between frame : 391 and 392
Fragment 003 / 009 :: RGBD matching between frame : 392 and 393
Fragment 003 / 009 :: RGBD matching between frame : 393 and 394
Fragment 003 / 009 :: RGBD matching between frame : 394 and 395
Fragment 003 / 009 :: RGBD matching between frame : 395 and 396
Fragment 003 / 009 :: RGBD matching between frame : 396 and 397
Fragment 003 / 009 :: RGBD matching between frame : 397 and 398
Fragment 003 / 009 :: RGBD matching between frame : 398 and 399
Fragment 003 / 009 :: integrate rgbd frame 300 (1 of 100).
Fragment 003 / 009 :: integrate rgbd frame 301 (2 of 100).
Fragment 003 / 009 :: integrate rgbd frame 302 (3 of 100).
Fragment 003 / 009 :: integrate rgbd frame 303 (4 of 100).
Fragment 003 / 009 :: integrate rgbd frame 304 (5 of 100).
Fragment 003 / 009 :: integrate rgbd frame 305 (6 of 100).
Fragment 003 / 009 :: integrate rgbd frame 306 (7 of 100).
Fragment 003 / 009 :: integrate rgbd frame 307 (8 of 100).
Fragment 003 / 009 :: integrate rgbd frame 308 (9 of 100).
Fragment 003 / 009 :: integrate rgbd frame 309 (10 of 100).
Fragment 003 / 009 :: integrate rgbd frame 310 (11 of 100).
Fragment 003 / 009 :: integrate rgbd frame 311 (12 of 100).
Fragment 003 / 009 :: integrate rgbd frame 312 (13 of 100).
Fragment 003 / 009 :: integrate rgbd frame 313 (14 of 100).
Fragment 003 / 009 :: integrate rgbd frame 314 (15 of 100).
Fragment 003 / 009 :: integrate rgbd frame 315 (16 of 100).
Fragment 003 / 009 :: integrate rgbd frame 316 (17 of 100).
Fragment 003 / 009 :: integrate rgbd frame 317 (18 of 100).
Fragment 003 / 009 :: integrate rgbd frame 318 (19 of 100).
Fragment 003 / 009 :: integrate rgbd frame 319 (20 of 100).
Fragment 003 / 009 :: integrate rgbd frame 320 (21 of 100).
Fragment 003 / 009 :: integrate rgbd frame 321 (22 of 100).
Fragment 003 / 009 :: integrate rgbd frame 322 (23 of 100).
Fragment 003 / 009 :: integrate rgbd frame 323 (24 of 100).
Fragment 003 / 009 :: integrate rgbd frame 324 (25 of 100).
Fragment 003 / 009 :: integrate rgbd frame 325 (26 of 100).
Fragment 003 / 009 :: integrate rgbd frame 326 (27 of 100).
Fragment 003 / 009 :: integrate rgbd frame 327 (28 of 100).
Fragment 003 / 009 :: integrate rgbd frame 328 (29 of 100).
Fragment 003 / 009 :: integrate rgbd frame 329 (30 of 100).
Fragment 003 / 009 :: integrate rgbd frame 330 (31 of 100).
Fragment 003 / 009 :: integrate rgbd frame 331 (32 of 100).
Fragment 003 / 009 :: integrate rgbd frame 332 (33 of 100).
Fragment 003 / 009 :: integrate rgbd frame 333 (34 of 100).
Fragment 003 / 009 :: integrate rgbd frame 334 (35 of 100).
Fragment 003 / 009 :: integrate rgbd frame 335 (36 of 100).
Fragment 003 / 009 :: integrate rgbd frame 336 (37 of 100).
Fragment 003 / 009 :: integrate rgbd frame 337 (38 of 100).
Fragment 003 / 009 :: integrate rgbd frame 338 (39 of 100).
Fragment 003 / 009 :: integrate rgbd frame 339 (40 of 100).
Fragment 003 / 009 :: integrate rgbd frame 340 (41 of 100).
Fragment 003 / 009 :: integrate rgbd frame 341 (42 of 100).
Fragment 003 / 009 :: integrate rgbd frame 342 (43 of 100).
Fragment 003 / 009 :: integrate rgbd frame 343 (44 of 100).
Fragment 003 / 009 :: integrate rgbd frame 344 (45 of 100).
Fragment 003 / 009 :: integrate rgbd frame 345 (46 of 100).
Fragment 003 / 009 :: integrate rgbd frame 346 (47 of 100).
Fragment 003 / 009 :: integrate rgbd frame 347 (48 of 100).
Fragment 003 / 009 :: integrate rgbd frame 348 (49 of 100).
Fragment 003 / 009 :: integrate rgbd frame 349 (50 of 100).
Fragment 003 / 009 :: integrate rgbd frame 350 (51 of 100).
Fragment 003 / 009 :: integrate rgbd frame 351 (52 of 100).
Fragment 003 / 009 :: integrate rgbd frame 352 (53 of 100).
Fragment 003 / 009 :: integrate rgbd frame 353 (54 of 100).
Fragment 003 / 009 :: integrate rgbd frame 354 (55 of 100).
Fragment 003 / 009 :: integrate rgbd frame 355 (56 of 100).
Fragment 003 / 009 :: integrate rgbd frame 356 (57 of 100).
Fragment 003 / 009 :: integrate rgbd frame 357 (58 of 100).
Fragment 003 / 009 :: integrate rgbd frame 358 (59 of 100).
Fragment 003 / 009 :: integrate rgbd frame 359 (60 of 100).
Fragment 003 / 009 :: integrate rgbd frame 360 (61 of 100).
Fragment 003 / 009 :: integrate rgbd frame 361 (62 of 100).
Fragment 003 / 009 :: integrate rgbd frame 362 (63 of 100).
Fragment 003 / 009 :: integrate rgbd frame 363 (64 of 100).
Fragment 003 / 009 :: integrate rgbd frame 364 (65 of 100).
Fragment 003 / 009 :: integrate rgbd frame 365 (66 of 100).
Fragment 003 / 009 :: integrate rgbd frame 366 (67 of 100).
Fragment 003 / 009 :: integrate rgbd frame 367 (68 of 100).
Fragment 003 / 009 :: integrate rgbd frame 368 (69 of 100).
Fragment 003 / 009 :: integrate rgbd frame 369 (70 of 100).
Fragment 003 / 009 :: integrate rgbd frame 370 (71 of 100).
Fragment 003 / 009 :: integrate rgbd frame 371 (72 of 100).
Fragment 003 / 009 :: integrate rgbd frame 372 (73 of 100).
Fragment 003 / 009 :: integrate rgbd frame 373 (74 of 100).
Fragment 003 / 009 :: integrate rgbd frame 374 (75 of 100).
Fragment 003 / 009 :: integrate rgbd frame 375 (76 of 100).
Fragment 003 / 009 :: integrate rgbd frame 376 (77 of 100).
Fragment 003 / 009 :: integrate rgbd frame 377 (78 of 100).
Fragment 003 / 009 :: integrate rgbd frame 378 (79 of 100).
Fragment 003 / 009 :: integrate rgbd frame 379 (80 of 100).
Fragment 003 / 009 :: integrate rgbd frame 380 (81 of 100).
Fragment 003 / 009 :: integrate rgbd frame 381 (82 of 100).
Fragment 003 / 009 :: integrate rgbd frame 382 (83 of 100).
Fragment 003 / 009 :: integrate rgbd frame 383 (84 of 100).
Fragment 003 / 009 :: integrate rgbd frame 384 (85 of 100).
Fragment 003 / 009 :: integrate rgbd frame 385 (86 of 100).
Fragment 003 / 009 :: integrate rgbd frame 386 (87 of 100).
Fragment 003 / 009 :: integrate rgbd frame 387 (88 of 100).
Fragment 003 / 009 :: integrate rgbd frame 388 (89 of 100).
Fragment 003 / 009 :: integrate rgbd frame 389 (90 of 100).
Fragment 003 / 009 :: integrate rgbd frame 390 (91 of 100).
Fragment 003 / 009 :: integrate rgbd frame 391 (92 of 100).
Fragment 003 / 009 :: integrate rgbd frame 392 (93 of 100).
Fragment 003 / 009 :: integrate rgbd frame 393 (94 of 100).
Fragment 003 / 009 :: integrate rgbd frame 394 (95 of 100).
Fragment 003 / 009 :: integrate rgbd frame 395 (96 of 100).
Fragment 003 / 009 :: integrate rgbd frame 396 (97 of 100).
Fragment 003 / 009 :: integrate rgbd frame 397 (98 of 100).
Fragment 003 / 009 :: integrate rgbd frame 398 (99 of 100).
Fragment 003 / 009 :: integrate rgbd frame 399 (100 of 100).
Fragment 004 / 009 :: RGBD matching between frame : 400 and 401
Fragment 004 / 009 :: RGBD matching between frame : 400 and 405
Fragment 004 / 009 :: RGBD matching between frame : 400 and 410
Fragment 004 / 009 :: RGBD matching between frame : 400 and 415
Fragment 004 / 009 :: RGBD matching between frame : 400 and 420
Fragment 004 / 009 :: RGBD matching between frame : 400 and 425
Fragment 004 / 009 :: RGBD matching between frame : 400 and 430
Fragment 004 / 009 :: RGBD matching between frame : 400 and 435
Fragment 004 / 009 :: RGBD matching between frame : 400 and 440
Fragment 004 / 009 :: RGBD matching between frame : 400 and 445
Fragment 004 / 009 :: RGBD matching between frame : 400 and 450
Fragment 004 / 009 :: RGBD matching between frame : 400 and 455
Fragment 004 / 009 :: RGBD matching between frame : 400 and 460
Fragment 004 / 009 :: RGBD matching between frame : 400 and 465
Fragment 004 / 009 :: RGBD matching between frame : 400 and 470
Fragment 004 / 009 :: RGBD matching between frame : 400 and 475
Fragment 004 / 009 :: RGBD matching between frame : 400 and 480
Fragment 004 / 009 :: RGBD matching between frame : 400 and 485
Fragment 004 / 009 :: RGBD matching between frame : 400 and 490
Fragment 004 / 009 :: RGBD matching between frame : 400 and 495
Fragment 004 / 009 :: RGBD matching between frame : 401 and 402
Fragment 004 / 009 :: RGBD matching between frame : 402 and 403
Fragment 004 / 009 :: RGBD matching between frame : 403 and 404
Fragment 004 / 009 :: RGBD matching between frame : 404 and 405
Fragment 004 / 009 :: RGBD matching between frame : 405 and 406
Fragment 004 / 009 :: RGBD matching between frame : 405 and 410
Fragment 004 / 009 :: RGBD matching between frame : 405 and 415
Fragment 004 / 009 :: RGBD matching between frame : 405 and 420
Fragment 004 / 009 :: RGBD matching between frame : 405 and 425
Fragment 004 / 009 :: RGBD matching between frame : 405 and 430
Fragment 004 / 009 :: RGBD matching between frame : 405 and 435
Fragment 004 / 009 :: RGBD matching between frame : 405 and 440
Fragment 004 / 009 :: RGBD matching between frame : 405 and 445
Fragment 004 / 009 :: RGBD matching between frame : 405 and 450
Fragment 004 / 009 :: RGBD matching between frame : 405 and 455
Fragment 004 / 009 :: RGBD matching between frame : 405 and 460
Fragment 004 / 009 :: RGBD matching between frame : 405 and 465
Fragment 004 / 009 :: RGBD matching between frame : 405 and 470
Fragment 004 / 009 :: RGBD matching between frame : 405 and 475
Fragment 004 / 009 :: RGBD matching between frame : 405 and 480
Fragment 004 / 009 :: RGBD matching between frame : 405 and 485
Fragment 004 / 009 :: RGBD matching between frame : 405 and 490
Fragment 004 / 009 :: RGBD matching between frame : 405 and 495
Fragment 004 / 009 :: RGBD matching between frame : 406 and 407
Fragment 004 / 009 :: RGBD matching between frame : 407 and 408
Fragment 004 / 009 :: RGBD matching between frame : 408 and 409
Fragment 004 / 009 :: RGBD matching between frame : 409 and 410
Fragment 004 / 009 :: RGBD matching between frame : 410 and 411
Fragment 004 / 009 :: RGBD matching between frame : 410 and 415
Fragment 004 / 009 :: RGBD matching between frame : 410 and 420
Fragment 004 / 009 :: RGBD matching between frame : 410 and 425
Fragment 004 / 009 :: RGBD matching between frame : 410 and 430
Fragment 004 / 009 :: RGBD matching between frame : 410 and 435
Fragment 004 / 009 :: RGBD matching between frame : 410 and 440
Fragment 004 / 009 :: RGBD matching between frame : 410 and 445
Fragment 004 / 009 :: RGBD matching between frame : 410 and 450
Fragment 004 / 009 :: RGBD matching between frame : 410 and 455
Fragment 004 / 009 :: RGBD matching between frame : 410 and 460
Fragment 004 / 009 :: RGBD matching between frame : 410 and 465
Fragment 004 / 009 :: RGBD matching between frame : 410 and 470
Fragment 004 / 009 :: RGBD matching between frame : 410 and 475
Fragment 004 / 009 :: RGBD matching between frame : 410 and 480
Fragment 004 / 009 :: RGBD matching between frame : 410 and 485
Fragment 004 / 009 :: RGBD matching between frame : 410 and 490
Fragment 004 / 009 :: RGBD matching between frame : 410 and 495
Fragment 004 / 009 :: RGBD matching between frame : 411 and 412
Fragment 004 / 009 :: RGBD matching between frame : 412 and 413
Fragment 004 / 009 :: RGBD matching between frame : 413 and 414
Fragment 004 / 009 :: RGBD matching between frame : 414 and 415
Fragment 004 / 009 :: RGBD matching between frame : 415 and 416
Fragment 004 / 009 :: RGBD matching between frame : 415 and 420
Fragment 004 / 009 :: RGBD matching between frame : 415 and 425
Fragment 004 / 009 :: RGBD matching between frame : 415 and 430
Fragment 004 / 009 :: RGBD matching between frame : 415 and 435
Fragment 004 / 009 :: RGBD matching between frame : 415 and 440
Fragment 004 / 009 :: RGBD matching between frame : 415 and 445
Fragment 004 / 009 :: RGBD matching between frame : 415 and 450
Fragment 004 / 009 :: RGBD matching between frame : 415 and 455
Fragment 004 / 009 :: RGBD matching between frame : 415 and 460
Fragment 004 / 009 :: RGBD matching between frame : 415 and 465
Fragment 004 / 009 :: RGBD matching between frame : 415 and 470
Fragment 004 / 009 :: RGBD matching between frame : 415 and 475
Fragment 004 / 009 :: RGBD matching between frame : 415 and 480
Fragment 004 / 009 :: RGBD matching between frame : 415 and 485
Fragment 004 / 009 :: RGBD matching between frame : 415 and 490
Fragment 004 / 009 :: RGBD matching between frame : 415 and 495
Fragment 004 / 009 :: RGBD matching between frame : 416 and 417
Fragment 004 / 009 :: RGBD matching between frame : 417 and 418
Fragment 004 / 009 :: RGBD matching between frame : 418 and 419
Fragment 004 / 009 :: RGBD matching between frame : 419 and 420
Fragment 004 / 009 :: RGBD matching between frame : 420 and 421
Fragment 004 / 009 :: RGBD matching between frame : 420 and 425
Fragment 004 / 009 :: RGBD matching between frame : 420 and 430
Fragment 004 / 009 :: RGBD matching between frame : 420 and 435
Fragment 004 / 009 :: RGBD matching between frame : 420 and 440
Fragment 004 / 009 :: RGBD matching between frame : 420 and 445
Fragment 004 / 009 :: RGBD matching between frame : 420 and 450
Fragment 004 / 009 :: RGBD matching between frame : 420 and 455
Fragment 004 / 009 :: RGBD matching between frame : 420 and 460
Fragment 004 / 009 :: RGBD matching between frame : 420 and 465
Fragment 004 / 009 :: RGBD matching between frame : 420 and 470
Fragment 004 / 009 :: RGBD matching between frame : 420 and 475
Fragment 004 / 009 :: RGBD matching between frame : 420 and 480
Fragment 004 / 009 :: RGBD matching between frame : 420 and 485
Fragment 004 / 009 :: RGBD matching between frame : 420 and 490
Fragment 004 / 009 :: RGBD matching between frame : 420 and 495
Fragment 004 / 009 :: RGBD matching between frame : 421 and 422
Fragment 004 / 009 :: RGBD matching between frame : 422 and 423
Fragment 004 / 009 :: RGBD matching between frame : 423 and 424
Fragment 004 / 009 :: RGBD matching between frame : 424 and 425
Fragment 004 / 009 :: RGBD matching between frame : 425 and 426
Fragment 004 / 009 :: RGBD matching between frame : 425 and 430
Fragment 004 / 009 :: RGBD matching between frame : 425 and 435
Fragment 004 / 009 :: RGBD matching between frame : 425 and 440
Fragment 004 / 009 :: RGBD matching between frame : 425 and 445
Fragment 004 / 009 :: RGBD matching between frame : 425 and 450
Fragment 004 / 009 :: RGBD matching between frame : 425 and 455
Fragment 004 / 009 :: RGBD matching between frame : 425 and 460
Fragment 004 / 009 :: RGBD matching between frame : 425 and 465
Fragment 004 / 009 :: RGBD matching between frame : 425 and 470
Fragment 004 / 009 :: RGBD matching between frame : 425 and 475
Fragment 004 / 009 :: RGBD matching between frame : 425 and 480
Fragment 004 / 009 :: RGBD matching between frame : 425 and 485
Fragment 004 / 009 :: RGBD matching between frame : 425 and 490
Fragment 004 / 009 :: RGBD matching between frame : 425 and 495
Fragment 004 / 009 :: RGBD matching between frame : 426 and 427
Fragment 004 / 009 :: RGBD matching between frame : 427 and 428
Fragment 004 / 009 :: RGBD matching between frame : 428 and 429
Fragment 004 / 009 :: RGBD matching between frame : 429 and 430
Fragment 004 / 009 :: RGBD matching between frame : 430 and 431
Fragment 004 / 009 :: RGBD matching between frame : 430 and 435
Fragment 004 / 009 :: RGBD matching between frame : 430 and 440
Fragment 004 / 009 :: RGBD matching between frame : 430 and 445
Fragment 004 / 009 :: RGBD matching between frame : 430 and 450
Fragment 004 / 009 :: RGBD matching between frame : 430 and 455
Fragment 004 / 009 :: RGBD matching between frame : 430 and 460
Fragment 004 / 009 :: RGBD matching between frame : 430 and 465
Fragment 004 / 009 :: RGBD matching between frame : 430 and 470
Fragment 004 / 009 :: RGBD matching between frame : 430 and 475
Fragment 004 / 009 :: RGBD matching between frame : 430 and 480
Fragment 004 / 009 :: RGBD matching between frame : 430 and 485
Fragment 004 / 009 :: RGBD matching between frame : 430 and 490
Fragment 004 / 009 :: RGBD matching between frame : 430 and 495
Fragment 004 / 009 :: RGBD matching between frame : 431 and 432
Fragment 004 / 009 :: RGBD matching between frame : 432 and 433
Fragment 004 / 009 :: RGBD matching between frame : 433 and 434
Fragment 004 / 009 :: RGBD matching between frame : 434 and 435
Fragment 004 / 009 :: RGBD matching between frame : 435 and 436
Fragment 004 / 009 :: RGBD matching between frame : 435 and 440
Fragment 004 / 009 :: RGBD matching between frame : 435 and 445
Fragment 004 / 009 :: RGBD matching between frame : 435 and 450
Fragment 004 / 009 :: RGBD matching between frame : 435 and 455
Fragment 004 / 009 :: RGBD matching between frame : 435 and 460
Fragment 004 / 009 :: RGBD matching between frame : 435 and 465
Fragment 004 / 009 :: RGBD matching between frame : 435 and 470
Fragment 004 / 009 :: RGBD matching between frame : 435 and 475
Fragment 004 / 009 :: RGBD matching between frame : 435 and 480
Fragment 004 / 009 :: RGBD matching between frame : 435 and 485
Fragment 004 / 009 :: RGBD matching between frame : 435 and 490
Fragment 004 / 009 :: RGBD matching between frame : 435 and 495
Fragment 004 / 009 :: RGBD matching between frame : 436 and 437
Fragment 004 / 009 :: RGBD matching between frame : 437 and 438
Fragment 004 / 009 :: RGBD matching between frame : 438 and 439
Fragment 004 / 009 :: RGBD matching between frame : 439 and 440
Fragment 004 / 009 :: RGBD matching between frame : 440 and 441
Fragment 004 / 009 :: RGBD matching between frame : 440 and 445
Fragment 004 / 009 :: RGBD matching between frame : 440 and 450
Fragment 004 / 009 :: RGBD matching between frame : 440 and 455
Fragment 004 / 009 :: RGBD matching between frame : 440 and 460
Fragment 004 / 009 :: RGBD matching between frame : 440 and 465
Fragment 004 / 009 :: RGBD matching between frame : 440 and 470
Fragment 004 / 009 :: RGBD matching between frame : 440 and 475
Fragment 004 / 009 :: RGBD matching between frame : 440 and 480
Fragment 004 / 009 :: RGBD matching between frame : 440 and 485
Fragment 004 / 009 :: RGBD matching between frame : 440 and 490
Fragment 004 / 009 :: RGBD matching between frame : 440 and 495
Fragment 004 / 009 :: RGBD matching between frame : 441 and 442
Fragment 004 / 009 :: RGBD matching between frame : 442 and 443
Fragment 004 / 009 :: RGBD matching between frame : 443 and 444
Fragment 004 / 009 :: RGBD matching between frame : 444 and 445
Fragment 004 / 009 :: RGBD matching between frame : 445 and 446
Fragment 004 / 009 :: RGBD matching between frame : 445 and 450
Fragment 004 / 009 :: RGBD matching between frame : 445 and 455
Fragment 004 / 009 :: RGBD matching between frame : 445 and 460
Fragment 004 / 009 :: RGBD matching between frame : 445 and 465
Fragment 004 / 009 :: RGBD matching between frame : 445 and 470
Fragment 004 / 009 :: RGBD matching between frame : 445 and 475
Fragment 004 / 009 :: RGBD matching between frame : 445 and 480
Fragment 004 / 009 :: RGBD matching between frame : 445 and 485
Fragment 004 / 009 :: RGBD matching between frame : 445 and 490
Fragment 004 / 009 :: RGBD matching between frame : 445 and 495
Fragment 004 / 009 :: RGBD matching between frame : 446 and 447
Fragment 004 / 009 :: RGBD matching between frame : 447 and 448
Fragment 004 / 009 :: RGBD matching between frame : 448 and 449
Fragment 004 / 009 :: RGBD matching between frame : 449 and 450
Fragment 004 / 009 :: RGBD matching between frame : 450 and 451
Fragment 004 / 009 :: RGBD matching between frame : 450 and 455
Fragment 004 / 009 :: RGBD matching between frame : 450 and 460
Fragment 004 / 009 :: RGBD matching between frame : 450 and 465
Fragment 004 / 009 :: RGBD matching between frame : 450 and 470
Fragment 004 / 009 :: RGBD matching between frame : 450 and 475
Fragment 004 / 009 :: RGBD matching between frame : 450 and 480
Fragment 004 / 009 :: RGBD matching between frame : 450 and 485
Fragment 004 / 009 :: RGBD matching between frame : 450 and 490
Fragment 004 / 009 :: RGBD matching between frame : 450 and 495
Fragment 004 / 009 :: RGBD matching between frame : 451 and 452
Fragment 004 / 009 :: RGBD matching between frame : 452 and 453
Fragment 004 / 009 :: RGBD matching between frame : 453 and 454
Fragment 004 / 009 :: RGBD matching between frame : 454 and 455
Fragment 004 / 009 :: RGBD matching between frame : 455 and 456
Fragment 004 / 009 :: RGBD matching between frame : 455 and 460
Fragment 004 / 009 :: RGBD matching between frame : 455 and 465
Fragment 004 / 009 :: RGBD matching between frame : 455 and 470
Fragment 004 / 009 :: RGBD matching between frame : 455 and 475
Fragment 004 / 009 :: RGBD matching between frame : 455 and 480
Fragment 004 / 009 :: RGBD matching between frame : 455 and 485
Fragment 004 / 009 :: RGBD matching between frame : 455 and 490
Fragment 004 / 009 :: RGBD matching between frame : 455 and 495
Fragment 004 / 009 :: RGBD matching between frame : 456 and 457
Fragment 004 / 009 :: RGBD matching between frame : 457 and 458
Fragment 004 / 009 :: RGBD matching between frame : 458 and 459
Fragment 004 / 009 :: RGBD matching between frame : 459 and 460
Fragment 004 / 009 :: RGBD matching between frame : 460 and 461
Fragment 004 / 009 :: RGBD matching between frame : 460 and 465
Fragment 004 / 009 :: RGBD matching between frame : 460 and 470
Fragment 004 / 009 :: RGBD matching between frame : 460 and 475
Fragment 004 / 009 :: RGBD matching between frame : 460 and 480
Fragment 004 / 009 :: RGBD matching between frame : 460 and 485
Fragment 004 / 009 :: RGBD matching between frame : 460 and 490
Fragment 004 / 009 :: RGBD matching between frame : 460 and 495
Fragment 004 / 009 :: RGBD matching between frame : 461 and 462
Fragment 004 / 009 :: RGBD matching between frame : 462 and 463
Fragment 004 / 009 :: RGBD matching between frame : 463 and 464
Fragment 004 / 009 :: RGBD matching between frame : 464 and 465
Fragment 004 / 009 :: RGBD matching between frame : 465 and 466
Fragment 004 / 009 :: RGBD matching between frame : 465 and 470
Fragment 004 / 009 :: RGBD matching between frame : 465 and 475
Fragment 004 / 009 :: RGBD matching between frame : 465 and 480
Fragment 004 / 009 :: RGBD matching between frame : 465 and 485
Fragment 004 / 009 :: RGBD matching between frame : 465 and 490
Fragment 004 / 009 :: RGBD matching between frame : 465 and 495
Fragment 004 / 009 :: RGBD matching between frame : 466 and 467
Fragment 004 / 009 :: RGBD matching between frame : 467 and 468
Fragment 004 / 009 :: RGBD matching between frame : 468 and 469
Fragment 004 / 009 :: RGBD matching between frame : 469 and 470
Fragment 004 / 009 :: RGBD matching between frame : 470 and 471
Fragment 004 / 009 :: RGBD matching between frame : 470 and 475
Fragment 004 / 009 :: RGBD matching between frame : 470 and 480
Fragment 004 / 009 :: RGBD matching between frame : 470 and 485
_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.012 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 175 edges.
[Open3D DEBUG] Line process weight : 75.253993
[Open3D DEBUG] [Initial ] residual : 1.353551e+02, lambda : 1.917793e+01
[Open3D DEBUG] [Iteration 00] residual : 1.344006e+02, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.343933e+02, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.343920e+02, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 1.343916e+02, valid edges : 76, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.005 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 208 edges.
[Open3D DEBUG] Line process weight : 73.122069
[Open3D DEBUG] [Initial ] residual : 3.316899e+05, lambda : 2.150542e+01
[Open3D DEBUG] [Iteration 00] residual : 2.084534e+03, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 2.057916e+03, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 2.056641e+03, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 2.056521e+03, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] [Iteration 04] residual : 2.056509e+03, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.007 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 180 edges.
[Open3D DEBUG] Line process weight : 79.439668
[Open3D DEBUG] [Initial ] residual : 1.124743e+02, lambda : 2.193154e+01
[Open3D DEBUG] [Iteration 00] residual : 1.071811e+02, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.071456e+02, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.071452e+02, valid edges : 81, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.004 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 203 edges.
[Open3D DEBUG] Line process weight : 29.219827
[Open3D DEBUG] [Initial ] residual : 2.904530e+04, lambda : 1.013153e+01
[Open3D DEBUG] [Iteration 00] residual : 1.008300e+03, valid edges : 71, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.002525e+03, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.000574e+03, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 9.994532e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 04] residual : 9.989084e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 05] residual : 9.986606e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 06] residual : 9.985419e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 07] residual : 9.984811e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 08] residual : 9.984486e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 09] residual : 9.984307e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 10] residual : 9.984206e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 11] residual : 9.984149e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 12] residual : 9.984117e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 13] residual : 9.984098e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 14] residual : 9.984088e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000Fragment 004 / 009 :: RGBD matching between frame : 470 and 490
Fragment 004 / 009 :: RGBD matching between frame : 470 and 495
Fragment 004 / 009 :: RGBD matching between frame : 471 and 472
Fragment 004 / 009 :: RGBD matching between frame : 472 and 473
Fragment 004 / 009 :: RGBD matching between frame : 473 and 474
Fragment 004 / 009 :: RGBD matching between frame : 474 and 475
Fragment 004 / 009 :: RGBD matching between frame : 475 and 476
Fragment 004 / 009 :: RGBD matching between frame : 475 and 480
Fragment 004 / 009 :: RGBD matching between frame : 475 and 485
Fragment 004 / 009 :: RGBD matching between frame : 475 and 490
Fragment 004 / 009 :: RGBD matching between frame : 475 and 495
Fragment 004 / 009 :: RGBD matching between frame : 476 and 477
Fragment 004 / 009 :: RGBD matching between frame : 477 and 478
Fragment 004 / 009 :: RGBD matching between frame : 478 and 479
Fragment 004 / 009 :: RGBD matching between frame : 479 and 480
Fragment 004 / 009 :: RGBD matching between frame : 480 and 481
Fragment 004 / 009 :: RGBD matching between frame : 480 and 485
Fragment 004 / 009 :: RGBD matching between frame : 480 and 490
Fragment 004 / 009 :: RGBD matching between frame : 480 and 495
Fragment 004 / 009 :: RGBD matching between frame : 481 and 482
Fragment 004 / 009 :: RGBD matching between frame : 482 and 483
Fragment 004 / 009 :: RGBD matching between frame : 483 and 484
Fragment 004 / 009 :: RGBD matching between frame : 484 and 485
Fragment 004 / 009 :: RGBD matching between frame : 485 and 486
Fragment 004 / 009 :: RGBD matching between frame : 485 and 490
Fragment 004 / 009 :: RGBD matching between frame : 485 and 495
Fragment 004 / 009 :: RGBD matching between frame : 486 and 487
Fragment 004 / 009 :: RGBD matching between frame : 487 and 488
Fragment 004 / 009 :: RGBD matching between frame : 488 and 489
Fragment 004 / 009 :: RGBD matching between frame : 489 and 490
Fragment 004 / 009 :: RGBD matching between frame : 490 and 491
Fragment 004 / 009 :: RGBD matching between frame : 490 and 495
Fragment 004 / 009 :: RGBD matching between frame : 491 and 492
Fragment 004 / 009 :: RGBD matching between frame : 492 and 493
Fragment 004 / 009 :: RGBD matching between frame : 493 and 494
Fragment 004 / 009 :: RGBD matching between frame : 494 and 495
Fragment 004 / 009 :: RGBD matching between frame : 495 and 496
Fragment 004 / 009 :: RGBD matching between frame : 496 and 497
Fragment 004 / 009 :: RGBD matching between frame : 497 and 498
Fragment 004 / 009 :: RGBD matching between frame : 498 and 499
Fragment 004 / 009 :: integrate rgbd frame 400 (1 of 100).
Fragment 004 / 009 :: integrate rgbd frame 401 (2 of 100).
Fragment 004 / 009 :: integrate rgbd frame 402 (3 of 100).
Fragment 004 / 009 :: integrate rgbd frame 403 (4 of 100).
Fragment 004 / 009 :: integrate rgbd frame 404 (5 of 100).
Fragment 004 / 009 :: integrate rgbd frame 405 (6 of 100).
Fragment 004 / 009 :: integrate rgbd frame 406 (7 of 100).
Fragment 004 / 009 :: integrate rgbd frame 407 (8 of 100).
Fragment 004 / 009 :: integrate rgbd frame 408 (9 of 100).
Fragment 004 / 009 :: integrate rgbd frame 409 (10 of 100).
Fragment 004 / 009 :: integrate rgbd frame 410 (11 of 100).
Fragment 004 / 009 :: integrate rgbd frame 411 (12 of 100).
Fragment 004 / 009 :: integrate rgbd frame 412 (13 of 100).
Fragment 004 / 009 :: integrate rgbd frame 413 (14 of 100).
Fragment 004 / 009 :: integrate rgbd frame 414 (15 of 100).
Fragment 004 / 009 :: integrate rgbd frame 415 (16 of 100).
Fragment 004 / 009 :: integrate rgbd frame 416 (17 of 100).
Fragment 004 / 009 :: integrate rgbd frame 417 (18 of 100).
Fragment 004 / 009 :: integrate rgbd frame 418 (19 of 100).
Fragment 004 / 009 :: integrate rgbd frame 419 (20 of 100).
Fragment 004 / 009 :: integrate rgbd frame 420 (21 of 100).
Fragment 004 / 009 :: integrate rgbd frame 421 (22 of 100).
Fragment 004 / 009 :: integrate rgbd frame 422 (23 of 100).
Fragment 004 / 009 :: integrate rgbd frame 423 (24 of 100).
Fragment 004 / 009 :: integrate rgbd frame 424 (25 of 100).
Fragment 004 / 009 :: integrate rgbd frame 425 (26 of 100).
Fragment 004 / 009 :: integrate rgbd frame 426 (27 of 100).
Fragment 004 / 009 :: integrate rgbd frame 427 (28 of 100).
Fragment 004 / 009 :: integrate rgbd frame 428 (29 of 100).
Fragment 004 / 009 :: integrate rgbd frame 429 (30 of 100).
Fragment 004 / 009 :: integrate rgbd frame 430 (31 of 100).
Fragment 004 / 009 :: integrate rgbd frame 431 (32 of 100).
Fragment 004 / 009 :: integrate rgbd frame 432 (33 of 100).
Fragment 004 / 009 :: integrate rgbd frame 433 (34 of 100).
Fragment 004 / 009 :: integrate rgbd frame 434 (35 of 100).
Fragment 004 / 009 :: integrate rgbd frame 435 (36 of 100).
Fragment 004 / 009 :: integrate rgbd frame 436 (37 of 100).
Fragment 004 / 009 :: integrate rgbd frame 437 (38 of 100).
Fragment 004 / 009 :: integrate rgbd frame 438 (39 of 100).
Fragment 004 / 009 :: integrate rgbd frame 439 (40 of 100).
Fragment 004 / 009 :: integrate rgbd frame 440 (41 of 100).
Fragment 004 / 009 :: integrate rgbd frame 441 (42 of 100).
Fragment 004 / 009 :: integrate rgbd frame 442 (43 of 100).
Fragment 004 / 009 :: integrate rgbd frame 443 (44 of 100).
Fragment 004 / 009 :: integrate rgbd frame 444 (45 of 100).
Fragment 004 / 009 :: integrate rgbd frame 445 (46 of 100).
Fragment 004 / 009 :: integrate rgbd frame 446 (47 of 100).
Fragment 004 / 009 :: integrate rgbd frame 447 (48 of 100).
Fragment 004 / 009 :: integrate rgbd frame 448 (49 of 100).
Fragment 004 / 009 :: integrate rgbd frame 449 (50 of 100).
Fragment 004 / 009 :: integrate rgbd frame 450 (51 of 100).
Fragment 004 / 009 :: integrate rgbd frame 451 (52 of 100).
Fragment 004 / 009 :: integrate rgbd frame 452 (53 of 100).
Fragment 004 / 009 :: integrate rgbd frame 453 (54 of 100).
Fragment 004 / 009 :: integrate rgbd frame 454 (55 of 100).
Fragment 004 / 009 :: integrate rgbd frame 455 (56 of 100).
Fragment 004 / 009 :: integrate rgbd frame 456 (57 of 100).
Fragment 004 / 009 :: integrate rgbd frame 457 (58 of 100).
Fragment 004 / 009 :: integrate rgbd frame 458 (59 of 100).
Fragment 004 / 009 :: integrate rgbd frame 459 (60 of 100).
Fragment 004 / 009 :: integrate rgbd frame 460 (61 of 100).
Fragment 004 / 009 :: integrate rgbd frame 461 (62 of 100).
Fragment 004 / 009 :: integrate rgbd frame 462 (63 of 100).
Fragment 004 / 009 :: integrate rgbd frame 463 (64 of 100).
Fragment 004 / 009 :: integrate rgbd frame 464 (65 of 100).
Fragment 004 / 009 :: integrate rgbd frame 465 (66 of 100).
Fragment 004 / 009 :: integrate rgbd frame 466 (67 of 100).
Fragment 004 / 009 :: integrate rgbd frame 467 (68 of 100).
Fragment 004 / 009 :: integrate rgbd frame 468 (69 of 100).
Fragment 004 / 009 :: integrate rgbd frame 469 (70 of 100).
Fragment 004 / 009 :: integrate rgbd frame 470 (71 of 100).
Fragment 004 / 009 :: integrate rgbd frame 471 (72 of 100).
Fragment 004 / 009 :: integrate rgbd frame 472 (73 of 100).
Fragment 004 / 009 :: integrate rgbd frame 473 (74 of 100).
Fragment 004 / 009 :: integrate rgbd frame 474 (75 of 100).
Fragment 004 / 009 :: integrate rgbd frame 475 (76 of 100).
Fragment 004 / 009 :: integrate rgbd frame 476 (77 of 100).
Fragment 004 / 009 :: integrate rgbd frame 477 (78 of 100).
Fragment 004 / 009 :: integrate rgbd frame 478 (79 of 100).
Fragment 004 / 009 :: integrate rgbd frame 479 (80 of 100).
Fragment 004 / 009 :: integrate rgbd frame 480 (81 of 100).
Fragment 004 / 009 :: integrate rgbd frame 481 (82 of 100).
Fragment 004 / 009 :: integrate rgbd frame 482 (83 of 100).
Fragment 004 / 009 :: integrate rgbd frame 483 (84 of 100).
Fragment 004 / 009 :: integrate rgbd frame 484 (85 of 100).
Fragment 004 / 009 :: integrate rgbd frame 485 (86 of 100).
Fragment 004 / 009 :: integrate rgbd frame 486 (87 of 100).
Fragment 004 / 009 :: integrate rgbd frame 487 (88 of 100).
Fragment 004 / 009 :: integrate rgbd frame 488 (89 of 100).
Fragment 004 / 009 :: integrate rgbd frame 489 (90 of 100).
Fragment 004 / 009 :: integrate rgbd frame 490 (91 of 100).
Fragment 004 / 009 :: integrate rgbd frame 491 (92 of 100).
Fragment 004 / 009 :: integrate rgbd frame 492 (93 of 100).
Fragment 004 / 009 :: integrate rgbd frame 493 (94 of 100).
Fragment 004 / 009 :: integrate rgbd frame 494 (95 of 100).
Fragment 004 / 009 :: integrate rgbd frame 495 (96 of 100).
Fragment 004 / 009 :: integrate rgbd frame 496 (97 of 100).
Fragment 004 / 009 :: integrate rgbd frame 497 (98 of 100).
Fragment 004 / 009 :: integrate rgbd frame 498 (99 of 100).
Fragment 004 / 009 :: integrate rgbd frame 499 (100 of 100).
Fragment 005 / 009 :: RGBD matching between frame : 500 and 501
Fragment 005 / 009 :: RGBD matching between frame : 500 and 505
Fragment 005 / 009 :: RGBD matching between frame : 500 and 510
Fragment 005 / 009 :: RGBD matching between frame : 500 and 515
Fragment 005 / 009 :: RGBD matching between frame : 500 and 520
Fragment 005 / 009 :: RGBD matching between frame : 500 and 525
Fragment 005 / 009 :: RGBD matching between frame : 500 and 530
Fragment 005 / 009 :: RGBD matching between frame : 500 and 535
Fragment 005 / 009 :: RGBD matching between frame : 500 and 540
Fragment 005 / 009 :: RGBD matching between frame : 500 and 545
Fragment 005 / 009 :: RGBD matching between frame : 500 and 550
Fragment 005 / 009 :: RGBD matching between frame : 500 and 555
Fragment 005 / 009 :: RGBD matching between frame : 500 and 560
Fragment 005 / 009 :: RGBD matching between frame : 500 and 565
Fragment 005 / 009 :: RGBD matching between frame : 500 and 570
Fragment 005 / 009 :: RGBD matching between frame : 500 and 575
Fragment 005 / 009 :: RGBD matching between frame : 500 and 580
Fragment 005 / 009 :: RGBD matching between frame : 500 and 585
Fragment 005 / 009 :: RGBD matching between frame : 500 and 590
Fragment 005 / 009 :: RGBD matching between frame : 500 and 595
Fragment 005 / 009 :: RGBD matching between frame : 501 and 502
Fragment 005 / 009 :: RGBD matching between frame : 502 and 503
Fragment 005 / 009 :: RGBD matching between frame : 503 and 504
Fragment 005 / 009 :: RGBD matching between frame : 504 and 505
Fragment 005 / 009 :: RGBD matching between frame : 505 and 506
Fragment 005 / 009 :: RGBD matching between frame : 505 and 510
Fragment 005 / 009 :: RGBD matching between frame : 505 and 515
Fragment 005 / 009 :: RGBD matching between frame : 505 and 520
Fragment 005 / 009 :: RGBD matching between frame : 505 and 525
Fragment 005 / 009 :: RGBD matching between frame : 505 and 530
Fragment 005 / 009 :: RGBD matching between frame : 505 and 535
Fragment 005 / 009 :: RGBD matching between frame : 505 and 540
Fragment 005 / 009 :: RGBD matching between frame : 505 and 545
Fragment 005 / 009 :: RGBD matching between frame : 505 and 550
Fragment 005 / 009 :: RGBD matching between frame : 505 and 555
Fragment 005 / 009 :: RGBD matching between frame : 505 and 560
Fragment 005 / 009 :: RGBD matching between frame : 505 and 565
Fragment 005 / 009 :: RGBD matching between frame : 505 and 570
Fragment 005 / 009 :: RGBD matching between frame : 505 and 575
Fragment 005 / 009 :: RGBD matching between frame : 505 and 580
Fragment 005 / 009 :: RGBD matching between frame : 505 and 585
Fragment 005 / 009 :: RGBD matching between frame : 505 and 590
Fragment 005 / 009 :: RGBD matching between frame : 505 and 595
Fragment 005 / 009 :: RGBD matching between frame : 506 and 507
Fragment 005 / 009 :: RGBD matching between frame : 507 and 508
Fragment 005 / 009 :: RGBD matching between frame : 508 and 509
Fragment 005 / 009 :: RGBD matching between frame : 509 and 510
Fragment 005 / 009 :: RGBD matching between frame : 510 and 511
Fragment 005 / 009 :: RGBD matching between frame : 510 and 515
Fragment 005 / 009 :: RGBD matching between frame : 510 and 520
Fragment 005 / 009 :: RGBD matching between frame : 510 and 525
Fragment 005 / 009 :: RGBD matching between frame : 510 and 530
Fragment 005 / 009 :: RGBD matching between frame : 510 and 535
Fragment 005 / 009 :: RGBD matching between frame : 510 and 540
Fragment 005 / 009 :: RGBD matching between frame : 510 and 545
Fragment 005 / 009 :: RGBD matching between frame : 510 and 550
Fragment 005 / 009 :: RGBD matching between frame : 510 and 555
Fragment 005 / 009 :: RGBD matching between frame : 510 and 560
Fragment 005 / 009 :: RGBD matching between frame : 510 and 565
Fragment 005 / 009 :: RGBD matching between frame : 510 and 570
Fragment 005 / 009 :: RGBD matching between frame : 510 and 575
Fragment 005 / 009 :: RGBD matching between frame : 510 and 580
Fragment 005 / 009 :: RGBD matching between frame : 510 and 585
Fragment 005 / 009 :: RGBD matching between frame : 510 and 590
Fragment 005 / 009 :: RGBD matching between frame : 510 and 595
Fragment 005 / 009 :: RGBD matching between frame : 511 and 512
Fragment 005 / 009 :: RGBD matching between frame : 512 and 513
Fragment 005 / 009 :: RGBD matching between frame : 513 and 514
Fragment 005 / 009 :: RGBD matching between frame : 514 and 515
Fragment 005 / 009 :: RGBD matching between frame : 515 and 516
Fragment 005 / 009 :: RGBD matching between frame : 515 and 520
Fragment 005 / 009 :: RGBD matching between frame : 515 and 525
Fragment 005 / 009 :: RGBD matching between frame : 515 and 530
Fragment 005 / 009 :: RGBD matching between frame : 515 and 535
Fragment 005 / 009 :: RGBD matching between frame : 515 and 540
Fragment 005 / 009 :: RGBD matching between frame : 515 and 545
Fragment 005 / 009 :: RGBD matching between frame : 515 and 550
Fragment 005 / 009 :: RGBD matching between frame : 515 and 555
Fragment 005 / 009 :: RGBD matching between frame : 515 and 560
Fragment 005 / 009 :: RGBD matching between frame : 515 and 565
Fragment 005 / 009 :: RGBD matching between frame : 515 and 570
Fragment 005 / 009 :: RGBD matching between frame : 515 and 575
Fragment 005 / 009 :: RGBD matching between frame : 515 and 580
Fragment 005 / 009 :: RGBD matching between frame : 515 and 585
Fragment 005 / 009 :: RGBD matching between frame : 515 and 590
Fragment 005 / 009 :: RGBD matching between frame : 515 and 595
Fragment 005 / 009 :: RGBD matching between frame : 516 and 517
Fragment 005 / 009 :: RGBD matching between frame : 517 and 518
Fragment 005 / 009 :: RGBD matching between frame : 518 and 519
Fragment 005 / 009 :: RGBD matching between frame : 519 and 520
Fragment 005 / 009 :: RGBD matching between frame : 520 and 521
Fragment 005 / 009 :: RGBD matching between frame : 520 and 525
Fragment 005 / 009 :: RGBD matching between frame : 520 and 530
Fragment 005 / 009 :: RGBD matching between frame : 520 and 535
Fragment 005 / 009 :: RGBD matching between frame : 520 and 540
Fragment 005 / 009 :: RGBD matching between frame : 520 and 545
Fragment 005 / 009 :: RGBD matching between frame : 520 and 550
Fragment 005 / 009 :: RGBD matching between frame : 520 and 555
Fragment 005 / 009 :: RGBD matching between frame : 520 and 560
Fragment 005 / 009 :: RGBD matching between frame : 520 and 565
Fragment 005 / 009 :: RGBD matching between frame : 520 and 570
Fragment 005 / 009 :: RGBD matching between frame : 520 and 575
Fragment 005 / 009 :: RGBD matching between frame : 520 and 580
Fragment 005 / 009 :: RGBD matching between frame : 520 and 585
Fragment 005 / 009 :: RGBD matching between frame : 520 and 590
Fragment 005 / 009 :: RGBD matching between frame : 520 and 595
Fragment 005 / 009 :: RGBD matching between frame : 521 and 522
Fragment 005 / 009 :: RGBD matching between frame : 522 and 523
Fragment 005 / 009 :: RGBD matching between frame : 523 and 524
Fragment 005 / 009 :: RGBD matching between frame : 524 and 525
Fragment 005 / 009 :: RGBD matching between frame : 525 and 526
Fragment 005 / 009 :: RGBD matching between frame : 525 and 530
Fragment 005 / 009 :: RGBD matching between frame : 525 and 535
Fragment 005 / 009 :: RGBD matching between frame : 525 and 540
Fragment 005 / 009 :: RGBD matching between frame : 525 and 545
Fragment 005 / 009 :: RGBD matching between frame : 525 and 550
Fragment 005 / 009 :: RGBD matching between frame : 525 and 555
Fragment 005 / 009 :: RGBD matching between frame : 525 and 560
Fragment 005 / 009 :: RGBD matching between frame : 525 and 565
Fragment 005 / 009 :: RGBD matching between frame : 525 and 570
Fragment 005 / 009 :: RGBD matching between frame : 525 and 575
Fragment 005 / 009 :: RGBD matching between frame : 525 and 580
Fragment 005 / 009 :: RGBD matching between frame : 525 and 585
Fragment 005 / 009 :: RGBD matching between frame : 525 and 590
Fragment 005 / 009 :: RGBD matching between frame : 525 and 595
Fragment 005 / 009 :: RGBD matching between frame : 526 and 527
Fragment 005 / 009 :: RGBD matching between frame : 527 and 528
Fragment 005 / 009 :: RGBD matching between frame : 528 and 529
Fragment 005 / 009 :: RGBD matching between frame : 529 and 530
Fragment 005 / 009 :: RGBD matching between frame : 530 and 531
Fragment 005 / 009 :: RGBD matching between frame : 530 and 535
Fragment 005 / 009 :: RGBD matching between frame : 530 and 540
Fragment 005 / 009 :: RGBD matching between frame : 530 and 545
Fragment 005 / 009 :: RGBD matching between frame : 530 and 550
Fragment 005 / 009 :: RGBD matching between frame : 530 and 555
Fragment 005 / 009 :: RGBD matching between frame : 530 and 560
Fragment 005 / 009 :: RGBD matching between frame : 530 and 565
Fragment 005 / 009 :: RGBD matching between frame : 530 and 570
Fragment 005 / 009 :: RGBD matching between frame : 530 and 575
Fragment 005 / 009 :: RGBD matching between frame : 530 and 580
Fragment 005 / 009 :: RGBD matching between frame : 530 and 585
Fragment 005 / 009 :: RGBD matching between frame : 530 and 590
Fragment 005 / 009 :: RGBD matching between frame : 530 and 595
Fragment 005 / 009 :: RGBD matching between frame : 531 and 532
Fragment 005 / 009 :: RGBD matching between frame : 532 and 533
Fragment 005 / 009 :: RGBD matching between frame : 533 and 534
Fragment 005 / 009 :: RGBD matching between frame : 534 and 535
Fragment 005 / 009 :: RGBD matching between frame : 535 and 536
Fragment 005 / 009 :: RGBD matching between frame : 535 and 540
Fragment 005 / 009 :: RGBD matching between frame : 535 and 545
Fragment 005 / 009 :: RGBD matching between frame : 535 and 550
Fragment 005 / 009 :: RGBD matching between frame : 535 and 555
Fragment 005 / 009 :: RGBD matching between frame : 535 and 560
Fragment 005 / 009 :: RGBD matching between frame : 535 and 565
Fragment 005 / 009 :: RGBD matching between frame : 535 and 570
Fragment 005 / 009 :: RGBD matching between frame : 535 and 575
Fragment 005 / 009 :: RGBD matching between frame : 535 and 580
Fragment 005 / 009 :: RGBD matching between frame : 535 and 585
Fragment 005 / 009 :: RGBD matching between frame : 535 and 590
Fragment 005 / 009 :: RGBD matching between frame : 535 and 595
Fragment 005 / 009 :: RGBD matching between frame : 536 and 537
Fragment 005 / 009 :: RGBD matching between frame : 537 and 538
Fragment 005 / 009 :: RGBD matching between frame : 538 and 539
Fragment 005 / 009 :: RGBD matching between frame : 539 and 540
Fragment 005 / 009 :: RGBD matching between frame : 540 and 541
Fragment 005 / 009 :: RGBD matching between frame : 540 and 545
Fragment 005 / 009 :: RGBD matching between frame : 540 and 550
Fragment 005 / 009 :: RGBD matching between frame : 540 and 555
Fragment 005 / 009 :: RGBD matching between frame : 540 and 560
Fragment 005 / 009 :: RGBD matching between frame : 540 and 565
Fragment 005 / 009 :: RGBD matching between frame : 540 and 570
Fragment 005 / 009 :: RGBD matching between frame : 540 and 575
Fragment 005 / 009 :: RGBD matching between frame : 540 and 580
Fragment 005 / 009 :: RGBD matching between frame : 540 and 585
Fragment 005 / 009 :: RGBD matching between frame : 540 and 590
Fragment 005 / 009 :: RGBD matching between frame : 540 and 595
Fragment 005 / 009 :: RGBD matching between frame : 541 and 542
Fragment 005 / 009 :: RGBD matching between frame : 542 and 543
Fragment 005 / 009 :: RGBD matching between frame : 543 and 544
Fragment 005 / 009 :: RGBD matching between frame : 544 and 545
Fragment 005 / 009 :: RGBD matching between frame : 545 and 546
Fragment 005 / 009 :: RGBD matching between frame : 545 and 550
Fragment 005 / 009 :: RGBD matching between frame : 545 and 555
Fragment 005 / 009 :: RGBD matching between frame : 545 and 560
Fragment 005 / 009 :: RGBD matching between frame : 545 and 565
Fragment 005 / 009 :: RGBD matching between frame : 545 and 570
Fragment 005 / 009 :: RGBD matching between frame : 545 and 575
Fragment 005 / 009 :: RGBD matching between frame : 545 and 580
Fragment 005 / 009 :: RGBD matching between frame : 545 and 585
Fragment 005 / 009 :: RGBD matching between frame : 545 and 590
Fragment 005 / 009 :: RGBD matching between frame : 545 and 595
Fragment 005 / 009 :: RGBD matching between frame : 546 and 547
Fragment 005 / 009 :: RGBD matching between frame : 547 and 548
Fragment 005 / 009 :: RGBD matching between frame : 548 and 549
Fragment 005 / 009 :: RGBD matching between frame : 549 and 550
Fragment 005 / 009 :: RGBD matching between frame : 550 and 551
Fragment 005 / 009 :: RGBD matching between frame : 550 and 555
Fragment 005 / 009 :: RGBD matching between frame : 550 and 560
Fragment 005 / 009 :: RGBD matching between frame : 550 and 565
Fragment 005 / 009 :: RGBD matching between frame : 550 and 570
Fragment 005 / 009 :: RGBD matching between frame : 550 and 575
Fragment 005 / 009 :: RGBD matching between frame : 550 and 580
Fragment 005 / 009 :: RGBD matching between frame : 550 and 585
Fragment 005 / 009 :: RGBD matching between frame : 550 and 590
Fragment 005 / 009 :: RGBD matching between frame : 550 and 595
Fragment 005 / 009 :: RGBD matching between frame : 551 and 552
Fragment 005 / 009 :: RGBD matching between frame : 552 and 553
Fragment 005 / 009 :: RGBD matching between frame : 553 and 554
Fragment 005 / 009 :: RGBD matching between frame : 554 and 555
Fragment 005 / 009 :: RGBD matching between frame : 555 and 556
Fragment 005 / 009 :: RGBD matching between frame : 555 and 560
Fragment 005 / 009 :: RGBD matching between frame : 555 and 565
Fragment 005 / 009 :: RGBD matching between frame : 555 and 570
Fragment 005 / 009 :: RGBD matching between frame : 555 and 575
Fragment 005 / 009 :: RGBD matching between frame : 555 and 580
Fragment 005 / 009 :: RGBD matching between frame : 555 and 585
Fragment 005 / 009 :: RGBD matching between frame : 555 and 590
Fragment 005 / 009 :: RGBD matching between frame : 555 and 595
Fragment 005 / 009 :: RGBD matching between frame : 556 and 557
Fragment 005 / 009 :: RGBD matching between frame : 557 and 558
Fragment 005 / 009 :: RGBD matching between frame : 558 and 559
Fragment 005 / 009 :: RGBD matching between frame : 559 and 560
Fragment 005 / 009 :: RGBD matching between frame : 560 and 561
Fragment 005 / 009 :: RGBD matching between frame : 560 and 565
Fragment 005 / 009 :: RGBD matching between frame : 560 and 570
Fragment 005 / 009 :: RGBD matching between frame : 560 and 575
Fragment 005 / 009 :: RGBD matching between frame : 560 and 580
Fragment 005 / 009 :: RGBD matching between frame : 560 and 585
Fragment 005 / 009 :: RGBD matching between frame : 560 and 590
Fragment 005 / 009 :: RGBD matching between frame : 560 and 595
Fragment 005 / 009 :: RGBD matching between frame : 561 and 562
Fragment 005 / 009 :: RGBD matching between frame : 562 and 563
Fragment 005 / 009 :: RGBD matching between frame : 563 and 564
Fragment 005 / 009 :: RGBD matching between frame : 564 and 565
Fragment 005 / 009 :: RGBD matching between frame : 565 and 566
Fragment 005 / 009 :: RGBD matching between frame : 565 and 570
Fragment 005 / 009 :: RGBD matching between frame : 565 and 575
Fragment 005 / 009 :: RGBD matching between frame : 565 and 580
Fragment 005 / 009 :: RGBD matching between frame : 565 and 585
Fragment 005 / 009 :: RGBD matching between frame : 565 and 590
Fragment 005 / 009 :: RGBD matching between frame : 565 and 595
Fragment 005 / 009 :: RGBD matching between frame : 566 and 567
Fragment 005 / 009 :: RGBD matching between frame : 567 and 568
Fragment 005 / 009 :: RGBD matching between frame : 568 and 569
Fragment 005 / 009 :: RGBD matching between frame : 569 and 570
Fragment 005 / 009 :: RGBD matching between frame : 570 and 571
Fragment 005 / 009 :: RGBD matching between frame : 570 and 575
Fragment 005 / 009 :: RGBD matching between frame : 570 and 580
Fragment 005 / 009 :: RGBD matching between frame : 570 and 585
Fragment 005 / 009 :: RGBD matching between frame : 570 and 590
Fragment 005 / 009 :: RGBD matching between frame : 570 and 595
Fragment 005 / 009 :: RGBD matching between frame : 571 and 572
000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.020 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 171 edges.
[Open3D DEBUG] Line process weight : 32.521690
[Open3D DEBUG] [Initial ] residual : 1.941222e+02, lambda : 1.035821e+01
[Open3D DEBUG] [Iteration 00] residual : 1.885576e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.831088e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.823024e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 1.821679e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 04] residual : 1.821474e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 05] residual : 1.821412e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 06] residual : 1.821389e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 07] residual : 1.821379e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] [Iteration 08] residual : 1.821375e+02, valid edges : 72, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.011 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 179 edges.
[Open3D DEBUG] Line process weight : 22.393214
[Open3D DEBUG] [Initial ] residual : 7.200325e+04, lambda : 7.128003e+00
[Open3D DEBUG] [Iteration 00] residual : 5.212772e+02, valid edges : 64, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 4.446190e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 02] residual : 4.230021e+02, valid edges : 70, time : 0.002 sec.
[Open3D DEBUG] [Iteration 03] residual : 4.187438e+02, valid edges : 70, time : 0.002 sec.
[Open3D DEBUG] [Iteration 04] residual : 4.169354e+02, valid edges : 70, time : 0.002 sec.
[Open3D DEBUG] [Iteration 05] residual : 4.157074e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 06] residual : 4.148299e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 07] residual : 4.142673e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 08] residual : 4.139532e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 09] residual : 4.137974e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 10] residual : 4.137259e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 11] residual : 4.136938e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 12] residual : 4.136786e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 13] residual : 4.136699e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 14] residual : 4.136634e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 15] residual : 4.136573e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 16] residual : 4.136506e+02, valid edges : 67, time : 0.003 sec.
[Open3D DEBUG] [Iteration 17] residual : 4.136428e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 18] residual : 4.136337e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 19] residual : 4.136230e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 20] residual : 4.136102e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 21] residual : 4.135951e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 22] residual : 4.135775e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 23] residual : 4.135569e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 24] residual : 4.135334e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 25] residual : 4.135067e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 26] residual : 4.134778e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 27] residual : 4.134438e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 28] residual : 4.134076e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 29] residual : 4.133742e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 30] residual : 4.133339e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 31] residual : 4.132950e+02, valid edges : 67, time : 0.006 sec.
[Open3D DEBUG] [Iteration 32] residual : 4.132540e+02, valid edges : 67, time : 0.002 sec.
[Open3D DEBUG] [Iteration 33] residual : 4.132015e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 34] residual : 4.131205e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 35] residual : 4.129486e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 36] residual : 4.124169e+02, valid edges : 67, time : 0.005 sec.
[Open3D DEBUG] [Iteration 37] residual : 4.104727e+02, valid edges : 67, time : 0.001 sec.
[Open3D DEBUG] [Iteration 38] residual : 4.055572e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 39] residual : 4.027412e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 40] residual : 4.017551e+02, valid edges : 68, time : 0.004 sec.
[Open3D DEBUG] [Iteration 41] residual : 4.014967e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 42] residual : 4.012795e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 43] residual : 4.011441e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 44] residual : 4.009296e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 45] residual : 4.008753e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 46] residual : 4.007073e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 47] residual : 4.006467e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 48] residual : 4.004369e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 49] residual : 4.002752e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 50] residual : 3.999319e+02, valid edges : 68, time : 0.004 sec.
[Open3D DEBUG] [Iteration 51] residual : 3.997847e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 52] residual : 3.996954e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 53] residual : 3.993479e+02, valid edges : 68, time : 0.003 sec.
[Open3D DEBUG] [Iteration 54] residual : 3.991677e+02, valid edges : 68, time : 0.003 sec.
[Open3D DEBUG] [Iteration 55] residual : 3.990383e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 56] residual : 3.989604e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 57] residual : 3.988493e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 58] residual : 3.987581e+02, valid edges : 68, time : 0.003 sec.
[Open3D DEBUG] [Iteration 59] residual : 3.987193e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 60] residual : 3.986415e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 61] residual : 3.986220e+02, valid edges : 68, time : 0.003 sec.
[Open3D DEBUG] [Iteration 62] residual : 3.986003e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 63] residual : 3.985860e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 64] residual : 3.985787e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 65] residual : 3.985771e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 66] residual : 3.985707e+02, valid edges : 68, time : 0.002 sec.
[Open3D DEBUG] [Iteration 67] residual : 3.985688e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 68] residual : 3.985678e+02, valid edges : 68, time : 0.005 sec.
[Open3D DEBUG] [Iteration 69] residual : 3.985671e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 70] residual : 3.985667e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.129 Fragment 005 / 009 :: RGBD matching between frame : 572 and 573
Fragment 005 / 009 :: RGBD matching between frame : 573 and 574
Fragment 005 / 009 :: RGBD matching between frame : 574 and 575
Fragment 005 / 009 :: RGBD matching between frame : 575 and 576
Fragment 005 / 009 :: RGBD matching between frame : 575 and 580
Fragment 005 / 009 :: RGBD matching between frame : 575 and 585
Fragment 005 / 009 :: RGBD matching between frame : 575 and 590
Fragment 005 / 009 :: RGBD matching between frame : 575 and 595
Fragment 005 / 009 :: RGBD matching between frame : 576 and 577
Fragment 005 / 009 :: RGBD matching between frame : 577 and 578
Fragment 005 / 009 :: RGBD matching between frame : 578 and 579
Fragment 005 / 009 :: RGBD matching between frame : 579 and 580
Fragment 005 / 009 :: RGBD matching between frame : 580 and 581
Fragment 005 / 009 :: RGBD matching between frame : 580 and 585
Fragment 005 / 009 :: RGBD matching between frame : 580 and 590
Fragment 005 / 009 :: RGBD matching between frame : 580 and 595
Fragment 005 / 009 :: RGBD matching between frame : 581 and 582
Fragment 005 / 009 :: RGBD matching between frame : 582 and 583
Fragment 005 / 009 :: RGBD matching between frame : 583 and 584
Fragment 005 / 009 :: RGBD matching between frame : 584 and 585
Fragment 005 / 009 :: RGBD matching between frame : 585 and 586
Fragment 005 / 009 :: RGBD matching between frame : 585 and 590
Fragment 005 / 009 :: RGBD matching between frame : 585 and 595
Fragment 005 / 009 :: RGBD matching between frame : 586 and 587
Fragment 005 / 009 :: RGBD matching between frame : 587 and 588
Fragment 005 / 009 :: RGBD matching between frame : 588 and 589
Fragment 005 / 009 :: RGBD matching between frame : 589 and 590
Fragment 005 / 009 :: RGBD matching between frame : 590 and 591
Fragment 005 / 009 :: RGBD matching between frame : 590 and 595
Fragment 005 / 009 :: RGBD matching between frame : 591 and 592
Fragment 005 / 009 :: RGBD matching between frame : 592 and 593
Fragment 005 / 009 :: RGBD matching between frame : 593 and 594
Fragment 005 / 009 :: RGBD matching between frame : 594 and 595
Fragment 005 / 009 :: RGBD matching between frame : 595 and 596
Fragment 005 / 009 :: RGBD matching between frame : 596 and 597
Fragment 005 / 009 :: RGBD matching between frame : 597 and 598
Fragment 005 / 009 :: RGBD matching between frame : 598 and 599
Fragment 005 / 009 :: integrate rgbd frame 500 (1 of 100).
Fragment 005 / 009 :: integrate rgbd frame 501 (2 of 100).
Fragment 005 / 009 :: integrate rgbd frame 502 (3 of 100).
Fragment 005 / 009 :: integrate rgbd frame 503 (4 of 100).
Fragment 005 / 009 :: integrate rgbd frame 504 (5 of 100).
Fragment 005 / 009 :: integrate rgbd frame 505 (6 of 100).
Fragment 005 / 009 :: integrate rgbd frame 506 (7 of 100).
Fragment 005 / 009 :: integrate rgbd frame 507 (8 of 100).
Fragment 005 / 009 :: integrate rgbd frame 508 (9 of 100).
Fragment 005 / 009 :: integrate rgbd frame 509 (10 of 100).
Fragment 005 / 009 :: integrate rgbd frame 510 (11 of 100).
Fragment 005 / 009 :: integrate rgbd frame 511 (12 of 100).
Fragment 005 / 009 :: integrate rgbd frame 512 (13 of 100).
Fragment 005 / 009 :: integrate rgbd frame 513 (14 of 100).
Fragment 005 / 009 :: integrate rgbd frame 514 (15 of 100).
Fragment 005 / 009 :: integrate rgbd frame 515 (16 of 100).
Fragment 005 / 009 :: integrate rgbd frame 516 (17 of 100).
Fragment 005 / 009 :: integrate rgbd frame 517 (18 of 100).
Fragment 005 / 009 :: integrate rgbd frame 518 (19 of 100).
Fragment 005 / 009 :: integrate rgbd frame 519 (20 of 100).
Fragment 005 / 009 :: integrate rgbd frame 520 (21 of 100).
Fragment 005 / 009 :: integrate rgbd frame 521 (22 of 100).
Fragment 005 / 009 :: integrate rgbd frame 522 (23 of 100).
Fragment 005 / 009 :: integrate rgbd frame 523 (24 of 100).
Fragment 005 / 009 :: integrate rgbd frame 524 (25 of 100).
Fragment 005 / 009 :: integrate rgbd frame 525 (26 of 100).
Fragment 005 / 009 :: integrate rgbd frame 526 (27 of 100).
Fragment 005 / 009 :: integrate rgbd frame 527 (28 of 100).
Fragment 005 / 009 :: integrate rgbd frame 528 (29 of 100).
Fragment 005 / 009 :: integrate rgbd frame 529 (30 of 100).
Fragment 005 / 009 :: integrate rgbd frame 530 (31 of 100).
Fragment 005 / 009 :: integrate rgbd frame 531 (32 of 100).
Fragment 005 / 009 :: integrate rgbd frame 532 (33 of 100).
Fragment 005 / 009 :: integrate rgbd frame 533 (34 of 100).
Fragment 005 / 009 :: integrate rgbd frame 534 (35 of 100).
Fragment 005 / 009 :: integrate rgbd frame 535 (36 of 100).
Fragment 005 / 009 :: integrate rgbd frame 536 (37 of 100).
Fragment 005 / 009 :: integrate rgbd frame 537 (38 of 100).
Fragment 005 / 009 :: integrate rgbd frame 538 (39 of 100).
Fragment 005 / 009 :: integrate rgbd frame 539 (40 of 100).
Fragment 005 / 009 :: integrate rgbd frame 540 (41 of 100).
Fragment 005 / 009 :: integrate rgbd frame 541 (42 of 100).
Fragment 005 / 009 :: integrate rgbd frame 542 (43 of 100).
Fragment 005 / 009 :: integrate rgbd frame 543 (44 of 100).
Fragment 005 / 009 :: integrate rgbd frame 544 (45 of 100).
Fragment 005 / 009 :: integrate rgbd frame 545 (46 of 100).
Fragment 005 / 009 :: integrate rgbd frame 546 (47 of 100).
Fragment 005 / 009 :: integrate rgbd frame 547 (48 of 100).
Fragment 005 / 009 :: integrate rgbd frame 548 (49 of 100).
Fragment 005 / 009 :: integrate rgbd frame 549 (50 of 100).
Fragment 005 / 009 :: integrate rgbd frame 550 (51 of 100).
Fragment 005 / 009 :: integrate rgbd frame 551 (52 of 100).
Fragment 005 / 009 :: integrate rgbd frame 552 (53 of 100).
Fragment 005 / 009 :: integrate rgbd frame 553 (54 of 100).
Fragment 005 / 009 :: integrate rgbd frame 554 (55 of 100).
Fragment 005 / 009 :: integrate rgbd frame 555 (56 of 100).
Fragment 005 / 009 :: integrate rgbd frame 556 (57 of 100).
Fragment 005 / 009 :: integrate rgbd frame 557 (58 of 100).
Fragment 005 / 009 :: integrate rgbd frame 558 (59 of 100).
Fragment 005 / 009 :: integrate rgbd frame 559 (60 of 100).
Fragment 005 / 009 :: integrate rgbd frame 560 (61 of 100).
Fragment 005 / 009 :: integrate rgbd frame 561 (62 of 100).
Fragment 005 / 009 :: integrate rgbd frame 562 (63 of 100).
Fragment 005 / 009 :: integrate rgbd frame 563 (64 of 100).
Fragment 005 / 009 :: integrate rgbd frame 564 (65 of 100).
Fragment 005 / 009 :: integrate rgbd frame 565 (66 of 100).
Fragment 005 / 009 :: integrate rgbd frame 566 (67 of 100).
Fragment 005 / 009 :: integrate rgbd frame 567 (68 of 100).
Fragment 005 / 009 :: integrate rgbd frame 568 (69 of 100).
Fragment 005 / 009 :: integrate rgbd frame 569 (70 of 100).
Fragment 005 / 009 :: integrate rgbd frame 570 (71 of 100).
Fragment 005 / 009 :: integrate rgbd frame 571 (72 of 100).
Fragment 005 / 009 :: integrate rgbd frame 572 (73 of 100).
Fragment 005 / 009 :: integrate rgbd frame 573 (74 of 100).
Fragment 005 / 009 :: integrate rgbd frame 574 (75 of 100).
Fragment 005 / 009 :: integrate rgbd frame 575 (76 of 100).
Fragment 005 / 009 :: integrate rgbd frame 576 (77 of 100).
Fragment 005 / 009 :: integrate rgbd frame 577 (78 of 100).
Fragment 005 / 009 :: integrate rgbd frame 578 (79 of 100).
Fragment 005 / 009 :: integrate rgbd frame 579 (80 of 100).
Fragment 005 / 009 :: integrate rgbd frame 580 (81 of 100).
Fragment 005 / 009 :: integrate rgbd frame 581 (82 of 100).
Fragment 005 / 009 :: integrate rgbd frame 582 (83 of 100).
Fragment 005 / 009 :: integrate rgbd frame 583 (84 of 100).
Fragment 005 / 009 :: integrate rgbd frame 584 (85 of 100).
Fragment 005 / 009 :: integrate rgbd frame 585 (86 of 100).
Fragment 005 / 009 :: integrate rgbd frame 586 (87 of 100).
Fragment 005 / 009 :: integrate rgbd frame 587 (88 of 100).
Fragment 005 / 009 :: integrate rgbd frame 588 (89 of 100).
Fragment 005 / 009 :: integrate rgbd frame 589 (90 of 100).
Fragment 005 / 009 :: integrate rgbd frame 590 (91 of 100).
Fragment 005 / 009 :: integrate rgbd frame 591 (92 of 100).
Fragment 005 / 009 :: integrate rgbd frame 592 (93 of 100).
Fragment 005 / 009 :: integrate rgbd frame 593 (94 of 100).
Fragment 005 / 009 :: integrate rgbd frame 594 (95 of 100).
Fragment 005 / 009 :: integrate rgbd frame 595 (96 of 100).
Fragment 005 / 009 :: integrate rgbd frame 596 (97 of 100).
Fragment 005 / 009 :: integrate rgbd frame 597 (98 of 100).
Fragment 005 / 009 :: integrate rgbd frame 598 (99 of 100).
Fragment 005 / 009 :: integrate rgbd frame 599 (100 of 100).
Fragment 006 / 009 :: RGBD matching between frame : 600 and 601
Fragment 006 / 009 :: RGBD matching between frame : 600 and 605
Fragment 006 / 009 :: RGBD matching between frame : 600 and 610
Fragment 006 / 009 :: RGBD matching between frame : 600 and 615
Fragment 006 / 009 :: RGBD matching between frame : 600 and 620
Fragment 006 / 009 :: RGBD matching between frame : 600 and 625
Fragment 006 / 009 :: RGBD matching between frame : 600 and 630
Fragment 006 / 009 :: RGBD matching between frame : 600 and 635
Fragment 006 / 009 :: RGBD matching between frame : 600 and 640
Fragment 006 / 009 :: RGBD matching between frame : 600 and 645
Fragment 006 / 009 :: RGBD matching between frame : 600 and 650
Fragment 006 / 009 :: RGBD matching between frame : 600 and 655
Fragment 006 / 009 :: RGBD matching between frame : 600 and 660
Fragment 006 / 009 :: RGBD matching between frame : 600 and 665
Fragment 006 / 009 :: RGBD matching between frame : 600 and 670
Fragment 006 / 009 :: RGBD matching between frame : 600 and 675
Fragment 006 / 009 :: RGBD matching between frame : 600 and 680
Fragment 006 / 009 :: RGBD matching between frame : 600 and 685
Fragment 006 / 009 :: RGBD matching between frame : 600 and 690
Fragment 006 / 009 :: RGBD matching between frame : 600 and 695
Fragment 006 / 009 :: RGBD matching between frame : 601 and 602
Fragment 006 / 009 :: RGBD matching between frame : 602 and 603
Fragment 006 / 009 :: RGBD matching between frame : 603 and 604
Fragment 006 / 009 :: RGBD matching between frame : 604 and 605
Fragment 006 / 009 :: RGBD matching between frame : 605 and 606
Fragment 006 / 009 :: RGBD matching between frame : 605 and 610
Fragment 006 / 009 :: RGBD matching between frame : 605 and 615
Fragment 006 / 009 :: RGBD matching between frame : 605 and 620
Fragment 006 / 009 :: RGBD matching between frame : 605 and 625
Fragment 006 / 009 :: RGBD matching between frame : 605 and 630
Fragment 006 / 009 :: RGBD matching between frame : 605 and 635
Fragment 006 / 009 :: RGBD matching between frame : 605 and 640
Fragment 006 / 009 :: RGBD matching between frame : 605 and 645
Fragment 006 / 009 :: RGBD matching between frame : 605 and 650
Fragment 006 / 009 :: RGBD matching between frame : 605 and 655
Fragment 006 / 009 :: RGBD matching between frame : 605 and 660
Fragment 006 / 009 :: RGBD matching between frame : 605 and 665
Fragment 006 / 009 :: RGBD matching between frame : 605 and 670
Fragment 006 / 009 :: RGBD matching between frame : 605 and 675
Fragment 006 / 009 :: RGBD matching between frame : 605 and 680
Fragment 006 / 009 :: RGBD matching between frame : 605 and 685
Fragment 006 / 009 :: RGBD matching between frame : 605 and 690
Fragment 006 / 009 :: RGBD matching between frame : 605 and 695
Fragment 006 / 009 :: RGBD matching between frame : 606 and 607
Fragment 006 / 009 :: RGBD matching between frame : 607 and 608
Fragment 006 / 009 :: RGBD matching between frame : 608 and 609
Fragment 006 / 009 :: RGBD matching between frame : 609 and 610
Fragment 006 / 009 :: RGBD matching between frame : 610 and 611
Fragment 006 / 009 :: RGBD matching between frame : 610 and 615
Fragment 006 / 009 :: RGBD matching between frame : 610 and 620
Fragment 006 / 009 :: RGBD matching between frame : 610 and 625
Fragment 006 / 009 :: RGBD matching between frame : 610 and 630
Fragment 006 / 009 :: RGBD matching between frame : 610 and 635
Fragment 006 / 009 :: RGBD matching between frame : 610 and 640
Fragment 006 / 009 :: RGBD matching between frame : 610 and 645
Fragment 006 / 009 :: RGBD matching between frame : 610 and 650
Fragment 006 / 009 :: RGBD matching between frame : 610 and 655
Fragment 006 / 009 :: RGBD matching between frame : 610 and 660
Fragment 006 / 009 :: RGBD matching between frame : 610 and 665
Fragment 006 / 009 :: RGBD matching between frame : 610 and 670
Fragment 006 / 009 :: RGBD matching between frame : 610 and 675
Fragment 006 / 009 :: RGBD matching between frame : 610 and 680
Fragment 006 / 009 :: RGBD matching between frame : 610 and 685
Fragment 006 / 009 :: RGBD matching between frame : 610 and 690
Fragment 006 / 009 :: RGBD matching between frame : 610 and 695
Fragment 006 / 009 :: RGBD matching between frame : 611 and 612
Fragment 006 / 009 :: RGBD matching between frame : 612 and 613
Fragment 006 / 009 :: RGBD matching between frame : 613 and 614
Fragment 006 / 009 :: RGBD matching between frame : 614 and 615
Fragment 006 / 009 :: RGBD matching between frame : 615 and 616
Fragment 006 / 009 :: RGBD matching between frame : 615 and 620
Fragment 006 / 009 :: RGBD matching between frame : 615 and 625
Fragment 006 / 009 :: RGBD matching between frame : 615 and 630
Fragment 006 / 009 :: RGBD matching between frame : 615 and 635
Fragment 006 / 009 :: RGBD matching between frame : 615 and 640
Fragment 006 / 009 :: RGBD matching between frame : 615 and 645
Fragment 006 / 009 :: RGBD matching between frame : 615 and 650
Fragment 006 / 009 :: RGBD matching between frame : 615 and 655
Fragment 006 / 009 :: RGBD matching between frame : 615 and 660
Fragment 006 / 009 :: RGBD matching between frame : 615 and 665
Fragment 006 / 009 :: RGBD matching between frame : 615 and 670
Fragment 006 / 009 :: RGBD matching between frame : 615 and 675
Fragment 006 / 009 :: RGBD matching between frame : 615 and 680
Fragment 006 / 009 :: RGBD matching between frame : 615 and 685
Fragment 006 / 009 :: RGBD matching between frame : 615 and 690
Fragment 006 / 009 :: RGBD matching between frame : 615 and 695
Fragment 006 / 009 :: RGBD matching between frame : 616 and 617
Fragment 006 / 009 :: RGBD matching between frame : 617 and 618
Fragment 006 / 009 :: RGBD matching between frame : 618 and 619
Fragment 006 / 009 :: RGBD matching between frame : 619 and 620
Fragment 006 / 009 :: RGBD matching between frame : 620 and 621
Fragment 006 / 009 :: RGBD matching between frame : 620 and 625
Fragment 006 / 009 :: RGBD matching between frame : 620 and 630
Fragment 006 / 009 :: RGBD matching between frame : 620 and 635
Fragment 006 / 009 :: RGBD matching between frame : 620 and 640
Fragment 006 / 009 :: RGBD matching between frame : 620 and 645
Fragment 006 / 009 :: RGBD matching between frame : 620 and 650
Fragment 006 / 009 :: RGBD matching between frame : 620 and 655
Fragment 006 / 009 :: RGBD matching between frame : 620 and 660
Fragment 006 / 009 :: RGBD matching between frame : 620 and 665
Fragment 006 / 009 :: RGBD matching between frame : 620 and 670
Fragment 006 / 009 :: RGBD matching between frame : 620 and 675
Fragment 006 / 009 :: RGBD matching between frame : 620 and 680
Fragment 006 / 009 :: RGBD matching between frame : 620 and 685
Fragment 006 / 009 :: RGBD matching between frame : 620 and 690
Fragment 006 / 009 :: RGBD matching between frame : 620 and 695
Fragment 006 / 009 :: RGBD matching between frame : 621 and 622
Fragment 006 / 009 :: RGBD matching between frame : 622 and 623
Fragment 006 / 009 :: RGBD matching between frame : 623 and 624
Fragment 006 / 009 :: RGBD matching between frame : 624 and 625
Fragment 006 / 009 :: RGBD matching between frame : 625 and 626
Fragment 006 / 009 :: RGBD matching between frame : 625 and 630
Fragment 006 / 009 :: RGBD matching between frame : 625 and 635
Fragment 006 / 009 :: RGBD matching between frame : 625 and 640
Fragment 006 / 009 :: RGBD matching between frame : 625 and 645
Fragment 006 / 009 :: RGBD matching between frame : 625 and 650
Fragment 006 / 009 :: RGBD matching between frame : 625 and 655
Fragment 006 / 009 :: RGBD matching between frame : 625 and 660
Fragment 006 / 009 :: RGBD matching between frame : 625 and 665
Fragment 006 / 009 :: RGBD matching between frame : 625 and 670
Fragment 006 / 009 :: RGBD matching between frame : 625 and 675
Fragment 006 / 009 :: RGBD matching between frame : 625 and 680
Fragment 006 / 009 :: RGBD matching between frame : 625 and 685
Fragment 006 / 009 :: RGBD matching between frame : 625 and 690
Fragment 006 / 009 :: RGBD matching between frame : 625 and 695
Fragment 006 / 009 :: RGBD matching between frame : 626 and 627
Fragment 006 / 009 :: RGBD matching between frame : 627 and 628
Fragment 006 / 009 :: RGBD matching between frame : 628 and 629
Fragment 006 / 009 :: RGBD matching between frame : 629 and 630
Fragment 006 / 009 :: RGBD matching between frame : 630 and 631
Fragment 006 / 009 :: RGBD matching between frame : 630 and 635
Fragment 006 / 009 :: RGBD matching between frame : 630 and 640
Fragment 006 / 009 :: RGBD matching between frame : 630 and 645
Fragment 006 / 009 :: RGBD matching between frame : 630 and 650
Fragment 006 / 009 :: RGBD matching between frame : 630 and 655
Fragment 006 / 009 :: RGBD matching between frame : 630 and 660
Fragment 006 / 009 :: RGBD matching between frame : 630 and 665
Fragment 006 / 009 :: RGBD matching between frame : 630 and 670
Fragment 006 / 009 :: RGBD matching between frame : 630 and 675
Fragment 006 / 009 :: RGBD matching between frame : 630 and 680
Fragment 006 / 009 :: RGBD matching between frame : 630 and 685
Fragment 006 / 009 :: RGBD matching between frame : 630 and 690
Fragment 006 / 009 :: RGBD matching between frame : 630 and 695
Fragment 006 / 009 :: RGBD matching between frame : 631 and 632
Fragment 006 / 009 :: RGBD matching between frame : 632 and 633
Fragment 006 / 009 :: RGBD matching between frame : 633 and 634
Fragment 006 / 009 :: RGBD matching between frame : 634 and 635
Fragment 006 / 009 :: RGBD matching between frame : 635 and 636
Fragment 006 / 009 :: RGBD matching between frame : 635 and 640
Fragment 006 / 009 :: RGBD matching between frame : 635 and 645
Fragment 006 / 009 :: RGBD matching between frame : 635 and 650
Fragment 006 / 009 :: RGBD matching between frame : 635 and 655
Fragment 006 / 009 :: RGBD matching between frame : 635 and 660
Fragment 006 / 009 :: RGBD matching between frame : 635 and 665
Fragment 006 / 009 :: RGBD matching between frame : 635 and 670
Fragment 006 / 009 :: RGBD matching between frame : 635 and 675
Fragment 006 / 009 :: RGBD matching between frame : 635 and 680
Fragment 006 / 009 :: RGBD matching between frame : 635 and 685
Fragment 006 / 009 :: RGBD matching between frame : 635 and 690
Fragment 006 / 009 :: RGBD matching between frame : 635 and 695
Fragment 006 / 009 :: RGBD matching between frame : 636 and 637
Fragment 006 / 009 :: RGBD matching between frame : 637 and 638
Fragment 006 / 009 :: RGBD matching between frame : 638 and 639
Fragment 006 / 009 :: RGBD matching between frame : 639 and 640
Fragment 006 / 009 :: RGBD matching between frame : 640 and 641
Fragment 006 / 009 :: RGBD matching between frame : 640 and 645
Fragment 006 / 009 :: RGBD matching between frame : 640 and 650
Fragment 006 / 009 :: RGBD matching between frame : 640 and 655
Fragment 006 / 009 :: RGBD matching between frame : 640 and 660
Fragment 006 / 009 :: RGBD matching between frame : 640 and 665
Fragment 006 / 009 :: RGBD matching between frame : 640 and 670
Fragment 006 / 009 :: RGBD matching between frame : 640 and 675
Fragment 006 / 009 :: RGBD matching between frame : 640 and 680
Fragment 006 / 009 :: RGBD matching between frame : 640 and 685
Fragment 006 / 009 :: RGBD matching between frame : 640 and 690
Fragment 006 / 009 :: RGBD matching between frame : 640 and 695
Fragment 006 / 009 :: RGBD matching between frame : 641 and 642
Fragment 006 / 009 :: RGBD matching between frame : 642 and 643
Fragment 006 / 009 :: RGBD matching between frame : 643 and 644
Fragment 006 / 009 :: RGBD matching between frame : 644 and 645
Fragment 006 / 009 :: RGBD matching between frame : 645 and 646
Fragment 006 / 009 :: RGBD matching between frame : 645 and 650
Fragment 006 / 009 :: RGBD matching between frame : 645 and 655
Fragment 006 / 009 :: RGBD matching between frame : 645 and 660
Fragment 006 / 009 :: RGBD matching between frame : 645 and 665
Fragment 006 / 009 :: RGBD matching between frame : 645 and 670
Fragment 006 / 009 :: RGBD matching between frame : 645 and 675
Fragment 006 / 009 :: RGBD matching between frame : 645 and 680
Fragment 006 / 009 :: RGBD matching between frame : 645 and 685
Fragment 006 / 009 :: RGBD matching between frame : 645 and 690
Fragment 006 / 009 :: RGBD matching between frame : 645 and 695
Fragment 006 / 009 :: RGBD matching between frame : 646 and 647
Fragment 006 / 009 :: RGBD matching between frame : 647 and 648
Fragment 006 / 009 :: RGBD matching between frame : 648 and 649
Fragment 006 / 009 :: RGBD matching between frame : 649 and 650
Fragment 006 / 009 :: RGBD matching between frame : 650 and 651
Fragment 006 / 009 :: RGBD matching between frame : 650 and 655
Fragment 006 / 009 :: RGBD matching between frame : 650 and 660
Fragment 006 / 009 :: RGBD matching between frame : 650 and 665
Fragment 006 / 009 :: RGBD matching between frame : 650 and 670
Fragment 006 / 009 :: RGBD matching between frame : 650 and 675
Fragment 006 / 009 :: RGBD matching between frame : 650 and 680
Fragment 006 / 009 :: RGBD matching between frame : 650 and 685
Fragment 006 / 009 :: RGBD matching between frame : 650 and 690
Fragment 006 / 009 :: RGBD matching between frame : 650 and 695
Fragment 006 / 009 :: RGBD matching between frame : 651 and 652
Fragment 006 / 009 :: RGBD matching between frame : 652 and 653
Fragment 006 / 009 :: RGBD matching between frame : 653 and 654
Fragment 006 / 009 :: RGBD matching between frame : 654 and 655
Fragment 006 / 009 :: RGBD matching between frame : 655 and 656
Fragment 006 / 009 :: RGBD matching between frame : 655 and 660
Fragment 006 / 009 :: RGBD matching between frame : 655 and 665
Fragment 006 / 009 :: RGBD matching between frame : 655 and 670
Fragment 006 / 009 :: RGBD matching between frame : 655 and 675
Fragment 006 / 009 :: RGBD matching between frame : 655 and 680
Fragment 006 / 009 :: RGBD matching between frame : 655 and 685
Fragment 006 / 009 :: RGBD matching between frame : 655 and 690
Fragment 006 / 009 :: RGBD matching between frame : 655 and 695
Fragment 006 / 009 :: RGBD matching between frame : 656 and 657
Fragment 006 / 009 :: RGBD matching between frame : 657 and 658
Fragment 006 / 009 :: RGBD matching between frame : 658 and 659
Fragment 006 / 009 :: RGBD matching between frame : 659 and 660
Fragment 006 / 009 :: RGBD matching between frame : 660 and 661
Fragment 006 / 009 :: RGBD matching between frame : 660 and 665
Fragment 006 / 009 :: RGBD matching between frame : 660 and 670
Fragment 006 / 009 :: RGBD matching between frame : 660 and 675
Fragment 006 / 009 :: RGBD matching between frame : 660 and 680
Fragment 006 / 009 :: RGBD matching between frame : 660 and 685
Fragment 006 / 009 :: RGBD matching between frame : 660 and 690
Fragment 006 / 009 :: RGBD matching between frame : 660 and 695
Fragment 006 / 009 :: RGBD matching between frame : 661 and 662
Fragment 006 / 009 :: RGBD matching between frame : 662 and 663
Fragment 006 / 009 :: RGBD matching between frame : 663 and 664
Fragment 006 / 009 :: RGBD matching between frame : 664 and 665
Fragment 006 / 009 :: RGBD matching between frame : 665 and 666
Fragment 006 / 009 :: RGBD matching between frame : 665 and 670
Fragment 006 / 009 :: RGBD matching between frame : 665 and 675
Fragment 006 / 009 :: RGBD matching between frame : 665 and 680
Fragment 006 / 009 :: RGBD matching between frame : 665 and 685
Fragment 006 / 009 :: RGBD matching between frame : 665 and 690
Fragment 006 / 009 :: RGBD matching between frame : 665 and 695
Fragment 006 / 009 :: RGBD matching between frame : 666 and 667
Fragment 006 / 009 :: RGBD matching between frame : 667 and 668
Fragment 006 / 009 :: RGBD matching between frame : 668 and 669
Fragment 006 / 009 :: RGBD matching between frame : 669 and 670
Fragment 006 / 009 :: RGBD matching between frame : 670 and 671
Fragment 006 / 009 :: RGBD matching between frame : 670 and 675
Fragment 006 / 009 :: RGBD matching between frame : 670 and 680
Fragment 006 / 009 :: RGBD matching between frame : 670 and 685
Fragment 006 / 009 :: RGBD matching between frame : 670 and 690
Fragment 006 / 009 :: RGBD matching between frame : 670 and 695
Fragment 006 / 009 :: RGBD matching between frame : 671 and 672
Fragment 006 / 009 :: RGBD matching between frame : 672 and 673
Fragment 006 / 009 :: RGBD matching between frame : 673 and 674
Fragment 006 / 009 :: RGBD matching between frame : 674 and 675
sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 167 edges.
[Open3D DEBUG] Line process weight : 23.340384
[Open3D DEBUG] [Initial ] residual : 1.897741e+02, lambda : 1.036070e+01
[Open3D DEBUG] [Iteration 00] residual : 1.859363e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.853137e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.852516e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 1.852185e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 04] residual : 1.851866e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 05] residual : 1.851605e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 06] residual : 1.851418e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 07] residual : 1.851290e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 08] residual : 1.851205e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 09] residual : 1.851147e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 10] residual : 1.851109e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 11] residual : 1.851082e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 12] residual : 1.851064e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 13] residual : 1.851051e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 14] residual : 1.851043e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 15] residual : 1.851037e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 16] residual : 1.851033e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 17] residual : 1.851030e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] [Iteration 18] residual : 1.851028e+02, valid edges : 68, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.022 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 269 edges.
[Open3D DEBUG] Line process weight : 69.257657
[Open3D DEBUG] [Initial ] residual : 1.115479e+04, lambda : 2.688187e+01
[Open3D DEBUG] [Iteration 00] residual : 9.429497e+02, valid edges : 158, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 9.031759e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 8.962391e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 8.917369e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 04] residual : 8.882062e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 05] residual : 8.852298e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 06] residual : 8.827301e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 07] residual : 8.807523e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 08] residual : 8.793334e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 09] residual : 8.784281e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 10] residual : 8.779144e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 11] residual : 8.776517e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 12] residual : 8.775280e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 13] residual : 8.774732e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 14] residual : 8.774500e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 15] residual : 8.774404e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 16] residual : 8.774365e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 17] residual : 8.774350e+02, valid edges : 160, time : 0.002 sec.
[Open3D DEBUG] CurrenFragment 006 / 009 :: RGBD matching between frame : 675 and 676
Fragment 006 / 009 :: RGBD matching between frame : 675 and 680
Fragment 006 / 009 :: RGBD matching between frame : 675 and 685
Fragment 006 / 009 :: RGBD matching between frame : 675 and 690
Fragment 006 / 009 :: RGBD matching between frame : 675 and 695
Fragment 006 / 009 :: RGBD matching between frame : 676 and 677
Fragment 006 / 009 :: RGBD matching between frame : 677 and 678
Fragment 006 / 009 :: RGBD matching between frame : 678 and 679
Fragment 006 / 009 :: RGBD matching between frame : 679 and 680
Fragment 006 / 009 :: RGBD matching between frame : 680 and 681
Fragment 006 / 009 :: RGBD matching between frame : 680 and 685
Fragment 006 / 009 :: RGBD matching between frame : 680 and 690
Fragment 006 / 009 :: RGBD matching between frame : 680 and 695
Fragment 006 / 009 :: RGBD matching between frame : 681 and 682
Fragment 006 / 009 :: RGBD matching between frame : 682 and 683
Fragment 006 / 009 :: RGBD matching between frame : 683 and 684
Fragment 006 / 009 :: RGBD matching between frame : 684 and 685
Fragment 006 / 009 :: RGBD matching between frame : 685 and 686
Fragment 006 / 009 :: RGBD matching between frame : 685 and 690
Fragment 006 / 009 :: RGBD matching between frame : 685 and 695
Fragment 006 / 009 :: RGBD matching between frame : 686 and 687
Fragment 006 / 009 :: RGBD matching between frame : 687 and 688
Fragment 006 / 009 :: RGBD matching between frame : 688 and 689
Fragment 006 / 009 :: RGBD matching between frame : 689 and 690
Fragment 006 / 009 :: RGBD matching between frame : 690 and 691
Fragment 006 / 009 :: RGBD matching between frame : 690 and 695
Fragment 006 / 009 :: RGBD matching between frame : 691 and 692
Fragment 006 / 009 :: RGBD matching between frame : 692 and 693
Fragment 006 / 009 :: RGBD matching between frame : 693 and 694
Fragment 006 / 009 :: RGBD matching between frame : 694 and 695
Fragment 006 / 009 :: RGBD matching between frame : 695 and 696
Fragment 006 / 009 :: RGBD matching between frame : 696 and 697
Fragment 006 / 009 :: RGBD matching between frame : 697 and 698
Fragment 006 / 009 :: RGBD matching between frame : 698 and 699
Fragment 006 / 009 :: integrate rgbd frame 600 (1 of 100).
Fragment 006 / 009 :: integrate rgbd frame 601 (2 of 100).
Fragment 006 / 009 :: integrate rgbd frame 602 (3 of 100).
Fragment 006 / 009 :: integrate rgbd frame 603 (4 of 100).
Fragment 006 / 009 :: integrate rgbd frame 604 (5 of 100).
Fragment 006 / 009 :: integrate rgbd frame 605 (6 of 100).
Fragment 006 / 009 :: integrate rgbd frame 606 (7 of 100).
Fragment 006 / 009 :: integrate rgbd frame 607 (8 of 100).
Fragment 006 / 009 :: integrate rgbd frame 608 (9 of 100).
Fragment 006 / 009 :: integrate rgbd frame 609 (10 of 100).
Fragment 006 / 009 :: integrate rgbd frame 610 (11 of 100).
Fragment 006 / 009 :: integrate rgbd frame 611 (12 of 100).
Fragment 006 / 009 :: integrate rgbd frame 612 (13 of 100).
Fragment 006 / 009 :: integrate rgbd frame 613 (14 of 100).
Fragment 006 / 009 :: integrate rgbd frame 614 (15 of 100).
Fragment 006 / 009 :: integrate rgbd frame 615 (16 of 100).
Fragment 006 / 009 :: integrate rgbd frame 616 (17 of 100).
Fragment 006 / 009 :: integrate rgbd frame 617 (18 of 100).
Fragment 006 / 009 :: integrate rgbd frame 618 (19 of 100).
Fragment 006 / 009 :: integrate rgbd frame 619 (20 of 100).
Fragment 006 / 009 :: integrate rgbd frame 620 (21 of 100).
Fragment 006 / 009 :: integrate rgbd frame 621 (22 of 100).
Fragment 006 / 009 :: integrate rgbd frame 622 (23 of 100).
Fragment 006 / 009 :: integrate rgbd frame 623 (24 of 100).
Fragment 006 / 009 :: integrate rgbd frame 624 (25 of 100).
Fragment 006 / 009 :: integrate rgbd frame 625 (26 of 100).
Fragment 006 / 009 :: integrate rgbd frame 626 (27 of 100).
Fragment 006 / 009 :: integrate rgbd frame 627 (28 of 100).
Fragment 006 / 009 :: integrate rgbd frame 628 (29 of 100).
Fragment 006 / 009 :: integrate rgbd frame 629 (30 of 100).
Fragment 006 / 009 :: integrate rgbd frame 630 (31 of 100).
Fragment 006 / 009 :: integrate rgbd frame 631 (32 of 100).
Fragment 006 / 009 :: integrate rgbd frame 632 (33 of 100).
Fragment 006 / 009 :: integrate rgbd frame 633 (34 of 100).
Fragment 006 / 009 :: integrate rgbd frame 634 (35 of 100).
Fragment 006 / 009 :: integrate rgbd frame 635 (36 of 100).
Fragment 006 / 009 :: integrate rgbd frame 636 (37 of 100).
Fragment 006 / 009 :: integrate rgbd frame 637 (38 of 100).
Fragment 006 / 009 :: integrate rgbd frame 638 (39 of 100).
Fragment 006 / 009 :: integrate rgbd frame 639 (40 of 100).
Fragment 006 / 009 :: integrate rgbd frame 640 (41 of 100).
Fragment 006 / 009 :: integrate rgbd frame 641 (42 of 100).
Fragment 006 / 009 :: integrate rgbd frame 642 (43 of 100).
Fragment 006 / 009 :: integrate rgbd frame 643 (44 of 100).
Fragment 006 / 009 :: integrate rgbd frame 644 (45 of 100).
Fragment 006 / 009 :: integrate rgbd frame 645 (46 of 100).
Fragment 006 / 009 :: integrate rgbd frame 646 (47 of 100).
Fragment 006 / 009 :: integrate rgbd frame 647 (48 of 100).
Fragment 006 / 009 :: integrate rgbd frame 648 (49 of 100).
Fragment 006 / 009 :: integrate rgbd frame 649 (50 of 100).
Fragment 006 / 009 :: integrate rgbd frame 650 (51 of 100).
Fragment 006 / 009 :: integrate rgbd frame 651 (52 of 100).
Fragment 006 / 009 :: integrate rgbd frame 652 (53 of 100).
Fragment 006 / 009 :: integrate rgbd frame 653 (54 of 100).
Fragment 006 / 009 :: integrate rgbd frame 654 (55 of 100).
Fragment 006 / 009 :: integrate rgbd frame 655 (56 of 100).
Fragment 006 / 009 :: integrate rgbd frame 656 (57 of 100).
Fragment 006 / 009 :: integrate rgbd frame 657 (58 of 100).
Fragment 006 / 009 :: integrate rgbd frame 658 (59 of 100).
Fragment 006 / 009 :: integrate rgbd frame 659 (60 of 100).
Fragment 006 / 009 :: integrate rgbd frame 660 (61 of 100).
Fragment 006 / 009 :: integrate rgbd frame 661 (62 of 100).
Fragment 006 / 009 :: integrate rgbd frame 662 (63 of 100).
Fragment 006 / 009 :: integrate rgbd frame 663 (64 of 100).
Fragment 006 / 009 :: integrate rgbd frame 664 (65 of 100).
Fragment 006 / 009 :: integrate rgbd frame 665 (66 of 100).
Fragment 006 / 009 :: integrate rgbd frame 666 (67 of 100).
Fragment 006 / 009 :: integrate rgbd frame 667 (68 of 100).
Fragment 006 / 009 :: integrate rgbd frame 668 (69 of 100).
Fragment 006 / 009 :: integrate rgbd frame 669 (70 of 100).
Fragment 006 / 009 :: integrate rgbd frame 670 (71 of 100).
Fragment 006 / 009 :: integrate rgbd frame 671 (72 of 100).
Fragment 006 / 009 :: integrate rgbd frame 672 (73 of 100).
Fragment 006 / 009 :: integrate rgbd frame 673 (74 of 100).
Fragment 006 / 009 :: integrate rgbd frame 674 (75 of 100).
Fragment 006 / 009 :: integrate rgbd frame 675 (76 of 100).
Fragment 006 / 009 :: integrate rgbd frame 676 (77 of 100).
Fragment 006 / 009 :: integrate rgbd frame 677 (78 of 100).
Fragment 006 / 009 :: integrate rgbd frame 678 (79 of 100).
Fragment 006 / 009 :: integrate rgbd frame 679 (80 of 100).
Fragment 006 / 009 :: integrate rgbd frame 680 (81 of 100).
Fragment 006 / 009 :: integrate rgbd frame 681 (82 of 100).
Fragment 006 / 009 :: integrate rgbd frame 682 (83 of 100).
Fragment 006 / 009 :: integrate rgbd frame 683 (84 of 100).
Fragment 006 / 009 :: integrate rgbd frame 684 (85 of 100).
Fragment 006 / 009 :: integrate rgbd frame 685 (86 of 100).
Fragment 006 / 009 :: integrate rgbd frame 686 (87 of 100).
Fragment 006 / 009 :: integrate rgbd frame 687 (88 of 100).
Fragment 006 / 009 :: integrate rgbd frame 688 (89 of 100).
Fragment 006 / 009 :: integrate rgbd frame 689 (90 of 100).
Fragment 006 / 009 :: integrate rgbd frame 690 (91 of 100).
Fragment 006 / 009 :: integrate rgbd frame 691 (92 of 100).
Fragment 006 / 009 :: integrate rgbd frame 692 (93 of 100).
Fragment 006 / 009 :: integrate rgbd frame 693 (94 of 100).
Fragment 006 / 009 :: integrate rgbd frame 694 (95 of 100).
Fragment 006 / 009 :: integrate rgbd frame 695 (96 of 100).
Fragment 006 / 009 :: integrate rgbd frame 696 (97 of 100).
Fragment 006 / 009 :: integrate rgbd frame 697 (98 of 100).
Fragment 006 / 009 :: integrate rgbd frame 698 (99 of 100).
Fragment 006 / 009 :: integrate rgbd frame 699 (100 of 100).
Fragment 007 / 009 :: RGBD matching between frame : 700 and 701
Fragment 007 / 009 :: RGBD matching between frame : 700 and 705
Fragment 007 / 009 :: RGBD matching between frame : 700 and 710
Fragment 007 / 009 :: RGBD matching between frame : 700 and 715
Fragment 007 / 009 :: RGBD matching between frame : 700 and 720
Fragment 007 / 009 :: RGBD matching between frame : 700 and 725
Fragment 007 / 009 :: RGBD matching between frame : 700 and 730
Fragment 007 / 009 :: RGBD matching between frame : 700 and 735
Fragment 007 / 009 :: RGBD matching between frame : 700 and 740
Fragment 007 / 009 :: RGBD matching between frame : 700 and 745
Fragment 007 / 009 :: RGBD matching between frame : 700 and 750
Fragment 007 / 009 :: RGBD matching between frame : 700 and 755
Fragment 007 / 009 :: RGBD matching between frame : 700 and 760
Fragment 007 / 009 :: RGBD matching between frame : 700 and 765
Fragment 007 / 009 :: RGBD matching between frame : 700 and 770
Fragment 007 / 009 :: RGBD matching between frame : 700 and 775
Fragment 007 / 009 :: RGBD matching between frame : 700 and 780
Fragment 007 / 009 :: RGBD matching between frame : 700 and 785
Fragment 007 / 009 :: RGBD matching between frame : 700 and 790
Fragment 007 / 009 :: RGBD matching between frame : 700 and 795
Fragment 007 / 009 :: RGBD matching between frame : 701 and 702
Fragment 007 / 009 :: RGBD matching between frame : 702 and 703
Fragment 007 / 009 :: RGBD matching between frame : 703 and 704
Fragment 007 / 009 :: RGBD matching between frame : 704 and 705
Fragment 007 / 009 :: RGBD matching between frame : 705 and 706
Fragment 007 / 009 :: RGBD matching between frame : 705 and 710
Fragment 007 / 009 :: RGBD matching between frame : 705 and 715
Fragment 007 / 009 :: RGBD matching between frame : 705 and 720
Fragment 007 / 009 :: RGBD matching between frame : 705 and 725
Fragment 007 / 009 :: RGBD matching between frame : 705 and 730
Fragment 007 / 009 :: RGBD matching between frame : 705 and 735
Fragment 007 / 009 :: RGBD matching between frame : 705 and 740
Fragment 007 / 009 :: RGBD matching between frame : 705 and 745
Fragment 007 / 009 :: RGBD matching between frame : 705 and 750
Fragment 007 / 009 :: RGBD matching between frame : 705 and 755
Fragment 007 / 009 :: RGBD matching between frame : 705 and 760
Fragment 007 / 009 :: RGBD matching between frame : 705 and 765
Fragment 007 / 009 :: RGBD matching between frame : 705 and 770
Fragment 007 / 009 :: RGBD matching between frame : 705 and 775
Fragment 007 / 009 :: RGBD matching between frame : 705 and 780
Fragment 007 / 009 :: RGBD matching between frame : 705 and 785
Fragment 007 / 009 :: RGBD matching between frame : 705 and 790
Fragment 007 / 009 :: RGBD matching between frame : 705 and 795
Fragment 007 / 009 :: RGBD matching between frame : 706 and 707
Fragment 007 / 009 :: RGBD matching between frame : 707 and 708
Fragment 007 / 009 :: RGBD matching between frame : 708 and 709
Fragment 007 / 009 :: RGBD matching between frame : 709 and 710
Fragment 007 / 009 :: RGBD matching between frame : 710 and 711
Fragment 007 / 009 :: RGBD matching between frame : 710 and 715
Fragment 007 / 009 :: RGBD matching between frame : 710 and 720
Fragment 007 / 009 :: RGBD matching between frame : 710 and 725
Fragment 007 / 009 :: RGBD matching between frame : 710 and 730
Fragment 007 / 009 :: RGBD matching between frame : 710 and 735
Fragment 007 / 009 :: RGBD matching between frame : 710 and 740
Fragment 007 / 009 :: RGBD matching between frame : 710 and 745
Fragment 007 / 009 :: RGBD matching between frame : 710 and 750
Fragment 007 / 009 :: RGBD matching between frame : 710 and 755
Fragment 007 / 009 :: RGBD matching between frame : 710 and 760
Fragment 007 / 009 :: RGBD matching between frame : 710 and 765
Fragment 007 / 009 :: RGBD matching between frame : 710 and 770
Fragment 007 / 009 :: RGBD matching between frame : 710 and 775
Fragment 007 / 009 :: RGBD matching between frame : 710 and 780
Fragment 007 / 009 :: RGBD matching between frame : 710 and 785
Fragment 007 / 009 :: RGBD matching between frame : 710 and 790
Fragment 007 / 009 :: RGBD matching between frame : 710 and 795
Fragment 007 / 009 :: RGBD matching between frame : 711 and 712
Fragment 007 / 009 :: RGBD matching between frame : 712 and 713
Fragment 007 / 009 :: RGBD matching between frame : 713 and 714
Fragment 007 / 009 :: RGBD matching between frame : 714 and 715
Fragment 007 / 009 :: RGBD matching between frame : 715 and 716
Fragment 007 / 009 :: RGBD matching between frame : 715 and 720
Fragment 007 / 009 :: RGBD matching between frame : 715 and 725
Fragment 007 / 009 :: RGBD matching between frame : 715 and 730
Fragment 007 / 009 :: RGBD matching between frame : 715 and 735
Fragment 007 / 009 :: RGBD matching between frame : 715 and 740
Fragment 007 / 009 :: RGBD matching between frame : 715 and 745
Fragment 007 / 009 :: RGBD matching between frame : 715 and 750
Fragment 007 / 009 :: RGBD matching between frame : 715 and 755
Fragment 007 / 009 :: RGBD matching between frame : 715 and 760
Fragment 007 / 009 :: RGBD matching between frame : 715 and 765
Fragment 007 / 009 :: RGBD matching between frame : 715 and 770
Fragment 007 / 009 :: RGBD matching between frame : 715 and 775
Fragment 007 / 009 :: RGBD matching between frame : 715 and 780
Fragment 007 / 009 :: RGBD matching between frame : 715 and 785
Fragment 007 / 009 :: RGBD matching between frame : 715 and 790
Fragment 007 / 009 :: RGBD matching between frame : 715 and 795
Fragment 007 / 009 :: RGBD matching between frame : 716 and 717
Fragment 007 / 009 :: RGBD matching between frame : 717 and 718
Fragment 007 / 009 :: RGBD matching between frame : 718 and 719
Fragment 007 / 009 :: RGBD matching between frame : 719 and 720
Fragment 007 / 009 :: RGBD matching between frame : 720 and 721
Fragment 007 / 009 :: RGBD matching between frame : 720 and 725
Fragment 007 / 009 :: RGBD matching between frame : 720 and 730
Fragment 007 / 009 :: RGBD matching between frame : 720 and 735
Fragment 007 / 009 :: RGBD matching between frame : 720 and 740
Fragment 007 / 009 :: RGBD matching between frame : 720 and 745
Fragment 007 / 009 :: RGBD matching between frame : 720 and 750
Fragment 007 / 009 :: RGBD matching between frame : 720 and 755
Fragment 007 / 009 :: RGBD matching between frame : 720 and 760
Fragment 007 / 009 :: RGBD matching between frame : 720 and 765
Fragment 007 / 009 :: RGBD matching between frame : 720 and 770
Fragment 007 / 009 :: RGBD matching between frame : 720 and 775
Fragment 007 / 009 :: RGBD matching between frame : 720 and 780
Fragment 007 / 009 :: RGBD matching between frame : 720 and 785
Fragment 007 / 009 :: RGBD matching between frame : 720 and 790
Fragment 007 / 009 :: RGBD matching between frame : 720 and 795
Fragment 007 / 009 :: RGBD matching between frame : 721 and 722
Fragment 007 / 009 :: RGBD matching between frame : 722 and 723
Fragment 007 / 009 :: RGBD matching between frame : 723 and 724
Fragment 007 / 009 :: RGBD matching between frame : 724 and 725
Fragment 007 / 009 :: RGBD matching between frame : 725 and 726
Fragment 007 / 009 :: RGBD matching between frame : 725 and 730
Fragment 007 / 009 :: RGBD matching between frame : 725 and 735
Fragment 007 / 009 :: RGBD matching between frame : 725 and 740
Fragment 007 / 009 :: RGBD matching between frame : 725 and 745
Fragment 007 / 009 :: RGBD matching between frame : 725 and 750
Fragment 007 / 009 :: RGBD matching between frame : 725 and 755
Fragment 007 / 009 :: RGBD matching between frame : 725 and 760
Fragment 007 / 009 :: RGBD matching between frame : 725 and 765
Fragment 007 / 009 :: RGBD matching between frame : 725 and 770
Fragment 007 / 009 :: RGBD matching between frame : 725 and 775
Fragment 007 / 009 :: RGBD matching between frame : 725 and 780
Fragment 007 / 009 :: RGBD matching between frame : 725 and 785
Fragment 007 / 009 :: RGBD matching between frame : 725 and 790
Fragment 007 / 009 :: RGBD matching between frame : 725 and 795
Fragment 007 / 009 :: RGBD matching between frame : 726 and 727
Fragment 007 / 009 :: RGBD matching between frame : 727 and 728
Fragment 007 / 009 :: RGBD matching between frame : 728 and 729
Fragment 007 / 009 :: RGBD matching between frame : 729 and 730
Fragment 007 / 009 :: RGBD matching between frame : 730 and 731
Fragment 007 / 009 :: RGBD matching between frame : 730 and 735
Fragment 007 / 009 :: RGBD matching between frame : 730 and 740
Fragment 007 / 009 :: RGBD matching between frame : 730 and 745
Fragment 007 / 009 :: RGBD matching between frame : 730 and 750
Fragment 007 / 009 :: RGBD matching between frame : 730 and 755
Fragment 007 / 009 :: RGBD matching between frame : 730 and 760
Fragment 007 / 009 :: RGBD matching between frame : 730 and 765
Fragment 007 / 009 :: RGBD matching between frame : 730 and 770
Fragment 007 / 009 :: RGBD matching between frame : 730 and 775
Fragment 007 / 009 :: RGBD matching between frame : 730 and 780
Fragment 007 / 009 :: RGBD matching between frame : 730 and 785
Fragment 007 / 009 :: RGBD matching between frame : 730 and 790
Fragment 007 / 009 :: RGBD matching between frame : 730 and 795
Fragment 007 / 009 :: RGBD matching between frame : 731 and 732
Fragment 007 / 009 :: RGBD matching between frame : 732 and 733
Fragment 007 / 009 :: RGBD matching between frame : 733 and 734
Fragment 007 / 009 :: RGBD matching between frame : 734 and 735
Fragment 007 / 009 :: RGBD matching between frame : 735 and 736
Fragment 007 / 009 :: RGBD matching between frame : 735 and 740
Fragment 007 / 009 :: RGBD matching between frame : 735 and 745
Fragment 007 / 009 :: RGBD matching between frame : 735 and 750
Fragment 007 / 009 :: RGBD matching between frame : 735 and 755
Fragment 007 / 009 :: RGBD matching between frame : 735 and 760
Fragment 007 / 009 :: RGBD matching between frame : 735 and 765
Fragment 007 / 009 :: RGBD matching between frame : 735 and 770
Fragment 007 / 009 :: RGBD matching between frame : 735 and 775
Fragment 007 / 009 :: RGBD matching between frame : 735 and 780
Fragment 007 / 009 :: RGBD matching between frame : 735 and 785
Fragment 007 / 009 :: RGBD matching between frame : 735 and 790
Fragment 007 / 009 :: RGBD matching between frame : 735 and 795
Fragment 007 / 009 :: RGBD matching between frame : 736 and 737
Fragment 007 / 009 :: RGBD matching between frame : 737 and 738
Fragment 007 / 009 :: RGBD matching between frame : 738 and 739
Fragment 007 / 009 :: RGBD matching between frame : 739 and 740
Fragment 007 / 009 :: RGBD matching between frame : 740 and 741
Fragment 007 / 009 :: RGBD matching between frame : 740 and 745
Fragment 007 / 009 :: RGBD matching between frame : 740 and 750
Fragment 007 / 009 :: RGBD matching between frame : 740 and 755
Fragment 007 / 009 :: RGBD matching between frame : 740 and 760
Fragment 007 / 009 :: RGBD matching between frame : 740 and 765
Fragment 007 / 009 :: RGBD matching between frame : 740 and 770
Fragment 007 / 009 :: RGBD matching between frame : 740 and 775
Fragment 007 / 009 :: RGBD matching between frame : 740 and 780
Fragment 007 / 009 :: RGBD matching between frame : 740 and 785
Fragment 007 / 009 :: RGBD matching between frame : 740 and 790
Fragment 007 / 009 :: RGBD matching between frame : 740 and 795
Fragment 007 / 009 :: RGBD matching between frame : 741 and 742
Fragment 007 / 009 :: RGBD matching between frame : 742 and 743
Fragment 007 / 009 :: RGBD matching between frame : 743 and 744
Fragment 007 / 009 :: RGBD matching between frame : 744 and 745
Fragment 007 / 009 :: RGBD matching between frame : 745 and 746
Fragment 007 / 009 :: RGBD matching between frame : 745 and 750
Fragment 007 / 009 :: RGBD matching between frame : 745 and 755
Fragment 007 / 009 :: RGBD matching between frame : 745 and 760
Fragment 007 / 009 :: RGBD matching between frame : 745 and 765
Fragment 007 / 009 :: RGBD matching between frame : 745 and 770
Fragment 007 / 009 :: RGBD matching between frame : 745 and 775
Fragment 007 / 009 :: RGBD matching between frame : 745 and 780
Fragment 007 / 009 :: RGBD matching between frame : 745 and 785
Fragment 007 / 009 :: RGBD matching between frame : 745 and 790
Fragment 007 / 009 :: RGBD matching between frame : 745 and 795
Fragment 007 / 009 :: RGBD matching between frame : 746 and 747
Fragment 007 / 009 :: RGBD matching between frame : 747 and 748
Fragment 007 / 009 :: RGBD matching between frame : 748 and 749
Fragment 007 / 009 :: RGBD matching between frame : 749 and 750
Fragment 007 / 009 :: RGBD matching between frame : 750 and 751
Fragment 007 / 009 :: RGBD matching between frame : 750 and 755
Fragment 007 / 009 :: RGBD matching between frame : 750 and 760
Fragment 007 / 009 :: RGBD matching between frame : 750 and 765
Fragment 007 / 009 :: RGBD matching between frame : 750 and 770
Fragment 007 / 009 :: RGBD matching between frame : 750 and 775
Fragment 007 / 009 :: RGBD matching between frame : 750 and 780
Fragment 007 / 009 :: RGBD matching between frame : 750 and 785
Fragment 007 / 009 :: RGBD matching between frame : 750 and 790
Fragment 007 / 009 :: RGBD matching between frame : 750 and 795
Fragment 007 / 009 :: RGBD matching between frame : 751 and 752
Fragment 007 / 009 :: RGBD matching between frame : 752 and 753
Fragment 007 / 009 :: RGBD matching between frame : 753 and 754
Fragment 007 / 009 :: RGBD matching between frame : 754 and 755
Fragment 007 / 009 :: RGBD matching between frame : 755 and 756
Fragment 007 / 009 :: RGBD matching between frame : 755 and 760
Fragment 007 / 009 :: RGBD matching between frame : 755 and 765
Fragment 007 / 009 :: RGBD matching between frame : 755 and 770
Fragment 007 / 009 :: RGBD matching between frame : 755 and 775
Fragment 007 / 009 :: RGBD matching between frame : 755 and 780
Fragment 007 / 009 :: RGBD matching between frame : 755 and 785
Fragment 007 / 009 :: RGBD matching between frame : 755 and 790
Fragment 007 / 009 :: RGBD matching between frame : 755 and 795
Fragment 007 / 009 :: RGBD matching between frame : 756 and 757
Fragment 007 / 009 :: RGBD matching between frame : 757 and 758
Fragment 007 / 009 :: RGBD matching between frame : 758 and 759
Fragment 007 / 009 :: RGBD matching between frame : 759 and 760
Fragment 007 / 009 :: RGBD matching between frame : 760 and 761
Fragment 007 / 009 :: RGBD matching between frame : 760 and 765
Fragment 007 / 009 :: RGBD matching between frame : 760 and 770
Fragment 007 / 009 :: RGBD matching between frame : 760 and 775
Fragment 007 / 009 :: RGBD matching between frame : 760 and 780
Fragment 007 / 009 :: RGBD matching between frame : 760 and 785
Fragment 007 / 009 :: RGBD matching between frame : 760 and 790
Fragment 007 / 009 :: RGBD matching between frame : 760 and 795
Fragment 007 / 009 :: RGBD matching between frame : 761 and 762
Fragment 007 / 009 :: RGBD matching between frame : 762 and 763
Fragment 007 / 009 :: RGBD matching between frame : 763 and 764
Fragment 007 / 009 :: RGBD matching between frame : 764 and 765
Fragment 007 / 009 :: RGBD matching between frame : 765 and 766
Fragment 007 / 009 :: RGBD matching between frame : 765 and 770
Fragment 007 / 009 :: RGBD matching between frame : 765 and 775
Fragment 007 / 009 :: RGBD matching between frame : 765 and 780
Fragment 007 / 009 :: RGBD matching between frame : 765 and 785
Fragment 007 / 009 :: RGBD matching between frame : 765 and 790
Fragment 007 / 009 :: RGBD matching between frame : 765 and 795
Fragment 007 / 009 :: RGBD matching between frame : 766 and 767
Fragment 007 / 009 :: RGBD matching between frame : 767 and 768
Fragment 007 / 009 :: RGBD matching between frame : 768 and 769
Fragment 007 / 009 :: RGBD matching between frame : 769 and 770
Fragment 007 / 009 :: RGBD matching between frame : 770 and 771
Fragment 007 / 009 :: RGBD matching between frame : 770 and 775
Fragment 007 / 009 :: RGBD matching between frame : 770 and 780
Fragment 007 / 009 :: RGBD matching between frame : 770 and 785
Fragment 007 / 009 :: RGBD matching between frame : 770 and 790
Fragment 007 / 009 :: RGBD matching between frame : 770 and 795
Fragment 007 / 009 :: RGBD matching between frame : 771 and 772
Fragment 007 / 009 :: RGBD matching between frame : 772 and 773
Fragment 007 / 009 :: RGBD matching between frame : 773 and 774
Fragment 007 / 009 :: RGBD matching between frame : 774 and 775
Fragment 007 / 009 :: RGBD matching between frame : 775 and 776
Fragment 007 / 009 :: RGBD matching between frame : 775 and 780
Fragment 007 / 009 :: RGBD matching between frame : 775 and 785
Fragment 007 / 009 :: RGBD matching between frame : 775 and 790
Fragment 007 / 009 :: RGBD matching between frame : 775 and 795
Fragment 007 / 009 :: RGBD matching between frame : 776 and 777
Fragment 007 / 009 :: RGBD matching between frame : 777 and 778
Fragment 007 / 009 :: RGBD matching between frame : 778 and 779
Fragment 007 / 009 :: RGBD matching between frame : 779 and 780
Fragment 007 / 009 :: RGBD matching between frame : 780 and 781
Fragment 007 / 009 :: RGBD matching between frame : 780 and 785
Fragment 007 / 009 :: RGBD matching between frame : 780 and 790
Fragment 007 / 009 :: RGBD matching between frame : 780 and 795
Fragment 007 / 009 :: RGBD matching between frame : 781 and 782
Fragment 007 / 009 :: RGBD matching between frame : 782 and 783
Fragment 007 / 009 :: RGBD matching between frame : 783 and 784
Fragment 007 / 009 :: RGBD matching between frame : 784 and 785
Fragment 007 / 009 :: RGBD matching between frame : 785 and 786
Fragment 007 / 009 :: RGBD matching between frame : 785 and 790
Fragment 007 / 009 :: RGBD matching between frame : 785 and 795
Fragment 007 / 009 :: RGBD matching between frame : 786 and 787
Fragment 007 / 009 :: RGBD matching between frame : 787 and 788
Fragment 007 / 009 :: RGBD matching between frame : 788 and 789
Fragment 007 / 009 :: RGBD matching between frame : 789 and 790
Fragment 007 / 009 :: RGBD matching between frame : 790 and 791
Fragment 007 / 009 :: RGBD matching between frame : 790 and 795
Fragment 007 / 009 :: RGBD matching between frame : 791 and 792
Fragment 007 / 009 :: RGBD matching between frame : 792 and 793
Fragment 007 / 009 :: RGBD matching between frame : 793 and 794
Fragment 007 / 009 :: RGBD matching between frame : 794 and 795
Fragment 007 / 009 :: RGBD matching between frame : 795 and 796
Fragment 007 / 009 :: RGBD matching between frame : 796 and 797
Fragment 007 / 009 :: RGBD matching between frame : 797 and 798
Fragment 007 / 009 :: RGBD matching between frame : 798 and 799
Fragment 007 / 009 :: integrate rgbd frame 700 (1 of 100).
Fragment 007 / 009 :: integrate rgbd frame 701 (2 of 100).
Fragment 007 / 009 :: integrate rgbd frame 702 (3 of 100).
Fragment 007 / 009 :: integrate rgbd frame 703 (4 of 100).
Fragment 007 / 009 :: integrate rgbd frame 704 (5 of 100).
Fragment 007 / 009 :: integrate rgbd frame 705 (6 of 100).
Fragment 007 / 009 :: integrate rgbd frame 706 (7 of 100).
Fragment 007 / 009 :: integrate rgbd frame 707 (8 of 100).
Fragment 007 / 009 :: integrate rgbd frame 708 (9 of 100).
Fragment 007 / 009 :: integrate rgbd frame 709 (10 of 100).
Fragment 007 / 009 :: integrate rgbd frame 710 (11 of 100).
Fragment 007 / 009 :: integrate rgbd frame 711 (12 of 100).
Fragment 007 / 009 :: integrate rgbd frame 712 (13 of 100).
Fragment 007 / 009 :: integrate rgbd frame 713 (14 of 100).
Fragment 007 / 009 :: integrate rgbd frame 714 (15 of 100).
Fragment 007 / 009 :: integrate rgbd frame 715 (16 of 100).
Fragment 007 / 009 :: integrate rgbd frame 716 (17 of 100).
Fragment 007 / 009 :: integrate rgbd frame 717 (18 of 100).
Fragment 007 / 009 :: integrate rgbd frame 718 (19 of 100).
Fragment 007 / 009 :: integrate rgbd frame 719 (20 of 100).
Fragment 007 / 009 :: integrate rgbd frame 720 (21 of 100).
Fragment 007 / 009 :: integrate rgbd frame 721 (22 of 100).
Fragment 007 / 009 :: integrate rgbd frame 722 (23 of 100).
Fragment 007 / 009 :: integrate rgbd frame 723 (24 of 100).
Fragment 007 / 009 :: integrate rgbd frame 724 (25 of 100).
Fragment 007 / 009 :: integrate rgbd frame 725 (26 of 100).
Fragment 007 / 009 :: integrate rgbd frame 726 (27 of 100).
Fragment 007 / 009 :: integrate rgbd frame 727 (28 of 100).
Fragment 007 / 009 :: integrate rgbd frame 728 (29 of 100).
Fragment 007 / 009 :: integrate rgbd frame 729 (30 of 100).
Fragment 007 / 009 :: integrate rgbd frame 730 (31 of 100).
Fragment 007 / 009 :: integrate rgbd frame 731 (32 of 100).
Fragment 007 / 009 :: integrate rgbd frame 732 (33 of 100).
Fragment 007 / 009 :: integrate rgbd frame 733 (34 of 100).
Fragment 007 / 009 :: integrate rgbd frame 734 (35 of 100).
Fragment 007 / 009 :: integrate rgbd frame 735 (36 of 100).
Fragment 007 / 009 :: integrate rgbd frame 736 (37 of 100).
Fragment 007 / 009 :: integrate rgbd frame 737 (38 of 100).
Fragment 007 / 009 :: integrate rgbd frame 738 (39 of 100).
Fragment 007 / 009 :: integrate rgbd frame 739 (40 of 100).
Fragment 007 / 009 :: integrate rgbd frame 740 (41 of 100).
Fragment 007 / 009 :: integrate rgbd frame 741 (42 of 100).
Fragment 007 / 009 :: integrate rgbd frame 742 (43 of 100).
Fragment 007 / 009 :: integrate rgbd frame 743 (44 of 100).
Fragment 007 / 009 :: integrate rgbd frame 744 (45 of 100).
Fragment 007 / 009 :: integrate rgbd frame 745 (46 of 100).
Fragment 007 / 009 :: integrate rgbd frame 746 (47 of 100).
Fragment 007 / 009 :: integrate rgbd frame 747 (48 of 100).
Fragment 007 / 009 :: integrate rgbd frame 748 (49 of 100).
Fragment 007 / 009 :: integrate rgbd frame 749 (50 of 100).
Fragment 007 / 009 :: integrate rgbd frame 750 (51 of 100).
Fragment 007 / 009 :: integrate rgbd frame 751 (52 of 100).
Fragment 007 / 009 :: integrate rgbd frame 752 (53 of 100).
Fragment 007 / 009 :: integrate rgbd frame 753 (54 of 100).
Fragment 007 / 009 :: integrate rgbd frame 754 (55 of 100).
Fragment 007 / 009 :: integrate rgbd frame 755 (56 of 100).
Fragment 007 / 009 :: integrate rgbd frame 756 (57 of 100).
Fragment 007 / 009 :: integrate rgbd frame 757 (58 of 100).
Fragment 007 / 009 :: integrate rgbd frame 758 (59 of 100).
Fragment 007 / 009 :: integrate rgbd frame 759 (60 of 100).
Fragment 007 / 009 :: integrate rgbd frame 760 (61 of 100).
Fragment 007 / 009 :: integrate rgbd frame 761 (62 of 100).
Fragment 007 / 009 :: integrate rgbd frame 762 (63 of 100).
Fragment 007 / 009 :: integrate rgbd frame 763 (64 of 100).
Fragment 007 / 009 :: integrate rgbd frame 764 (65 of 100).
Fragment 007 / 009 :: integrate rgbd frame 765 (66 of 100).
Fragment 007 / 009 :: integrate rgbd frame 766 (67 of 100).
Fragment 007 / 009 :: integrate rgbd frame 767 (68 of 100).
Fragment 007 / 009 :: integrate rgbd frame 768 (69 of 100).
Fragment 007 / 009 :: integrate rgbd frame 769 (70 of 100).
Fragment 007 / 009 :: integrate rgbd frame 770 (71 of 100).
Fragment 007 / 009 :: integrate rgbd frame 771 (72 of 100).
Fragment 007 / 009 :: integrate rgbd frame 772 (73 of 100).
Fragment 007 / 009 :: integrate rgbd frame 773 (74 of 100).
Fragment 007 / 009 :: integrate rgbd frame 774 (75 of 100).
Fragment 007 / 009 :: integrate rgbd frame 775 (76 of 100).
Fragment 007 / 009 :: integrate rgbd frame 776 (77 of 100).
Fragment 007 / 009 :: integrate rgbd frame 777 (78 of 100).
Fragment 007 / 009 :: integrate rgbd frame 778 (79 of 100).
Fragment 007 / 009 :: integrate rgbd frame 779 (80 of 100).
Fragment 007 / 009 :: integrate rgbd frame 780 (81 of 100).
Fragment 007 / 009 :: integrate rgbd frame 781 (82 of 100).
Fragment 007 / 009 :: integrate rgbd frame 782 (83 of 100).
Fragment 007 / 009 :: integrate rgbd frame 783 (84 of 100).
Fragment 007 / 009 :: integrate rgbd frame 784 (85 of 100).
Fragment 007 / 009 :: integrate rgbd frame 785 (86 of 100).
Fragment 007 / 009 :: integrate rgbd frame 786 (87 of 100).
Fragment 007 / 009 :: integrate rgbd frame 787 (88 of 100).
Fragment 007 / 009 :: integrate rgbd frame 788 (89 of 100).
Fragment 007 / 009 :: integrate rgbd frame 789 (90 of 100).
Fragment 007 / 009 :: integrate rgbd frame 790 (91 of 100).
Fragment 007 / 009 :: integrate rgbd frame 791 (92 of 100).
Fragment 007 / 009 :: integrate rgbd frame 792 (93 of 100).
Fragment 007 / 009 :: integrate rgbd frame 793 (94 of 100).
Fragment 007 / 009 :: integrate rgbd frame 794 (95 of 100).
Fragment 007 / 009 :: integrate rgbd frame 795 (96 of 100).
Fragment 007 / 009 :: integrate rgbd frame 796 (97 of 100).
Fragment 007 / 009 :: integrate rgbd frame 797 (98 of 100).
Fragment 007 / 009 :: integrate rgbd frame 798 (99 of 100).
Fragment 007 / 009 :: integrate rgbd frame 799 (100 of 100).
Fragment 008 / 009 :: RGBD matching between frame : 800 and 801
Fragment 008 / 009 :: RGBD matching between frame : 800 and 805
Fragment 008 / 009 :: RGBD matching between frame : 800 and 810
Fragment 008 / 009 :: RGBD matching between frame : 800 and 815
Fragment 008 / 009 :: RGBD matching between frame : 800 and 820
Fragment 008 / 009 :: RGBD matching between frame : 800 and 825
Fragment 008 / 009 :: RGBD matching between frame : 800 and 830
Fragment 008 / 009 :: RGBD matching between frame : 800 and 835
Fragment 008 / 009 :: RGBD matching between frame : 800 and 840
Fragment 008 / 009 :: RGBD matching between frame : 800 and 845
Fragment 008 / 009 :: RGBD matching between frame : 800 and 850
Fragment 008 / 009 :: RGBD matching between frame : 800 and 855
Fragment 008 / 009 :: RGBD matching between frame : 800 and 860
Fragment 008 / 009 :: RGBD matching between frame : 800 and 865
Fragment 008 / 009 :: RGBD matching between frame : 800 and 870
Fragment 008 / 009 :: RGBD matching between frame : 800 and 875
Fragment 008 / 009 :: RGBD matching between frame : 800 and 880
Fragment 008 / 009 :: RGBD matching between frame : 800 and 885
Fragment 008 / 009 :: RGBD matching between frame : 800 and 890
Fragment 008 / 009 :: RGBD matching between frame : 800 and 895
Fragment 008 / 009 :: RGBD matching between frame : 801 and 802
Fragment 008 / 009 :: RGBD matching between frame : 802 and 803
Fragment 008 / 009 :: RGBD matching between frame : 803 and 804
Fragment 008 / 009 :: RGBD matching between frame : 804 and 805
Fragment 008 / 009 :: RGBD matching between frame : 805 and 806
Fragment 008 / 009 :: RGBD matching between frame : 805 and 810
Fragment 008 / 009 :: RGBD matching between frame : 805 and 815
Fragment 008 / 009 :: RGBD matching between frame : 805 and 820
Fragment 008 / 009 :: RGBD matching between frame : 805 and 825
Fragment 008 / 009 :: RGBD matching between frame : 805 and 830
Fragment 008 / 009 :: RGBD matching between frame : 805 and 835
Fragment 008 / 009 :: RGBD matching between frame : 805 and 840
Fragment 008 / 009 :: RGBD matching between frame : 805 and 845
Fragment 008 / 009 :: RGBD matching between frame : 805 and 850
Fragment 008 / 009 :: RGBD matching between frame : 805 and 855
Fragment 008 / 009 :: RGBD matching between frame : 805 and 860
Fragment 008 / 009 :: RGBD matching between frame : 805 and 865
Fragment 008 / 009 :: RGBD matching between frame : 805 and 870
Fragment 008 / 009 :: RGBD matching between frame : 805 and 875
Fragment 008 / 009 :: RGBD matching between frame : 805 and 880
Fragment 008 / 009 :: RGBD matching between frame : 805 and 885
Fragment 008 / 009 :: RGBD matching between frame : 805 and 890
Fragment 008 / 009 :: RGBD matching between frame : 805 and 895
Fragment 008 / 009 :: RGBD matching between frame : 806 and 807
Fragment 008 / 009 :: RGBD matching between frame : 807 and 808
Fragment 008 / 009 :: RGBD matching between frame : 808 and 809
Fragment 008 / 009 :: RGBD matching between frame : 809 and 810
Fragment 008 / 009 :: RGBD matching between frame : 810 and 811
Fragment 008 / 009 :: RGBD matching between frame : 810 and 815
Fragment 008 / 009 :: RGBD matching between frame : 810 and 820
Fragment 008 / 009 :: RGBD matching between frame : 810 and 825
Fragment 008 / 009 :: RGBD matching between frame : 810 and 830
Fragment 008 / 009 :: RGBD matching between frame : 810 and 835
Fragment 008 / 009 :: RGBD matching between frame : 810 and 840
Fragment 008 / 009 :: RGBD matching between frame : 810 and 845
Fragment 008 / 009 :: RGBD matching between frame : 810 and 850
Fragment 008 / 009 :: RGBD matching between frame : 810 and 855
Fragment 008 / 009 :: RGBD matching between frame : 810 and 860
Fragment 008 / 009 :: RGBD matching between frame : 810 and 865
Fragment 008 / 009 :: RGBD matching between frame : 810 and 870
Fragment 008 / 009 :: RGBD matching between frame : 810 and 875
Fragment 008 / 009 :: RGBD matching between frame : 810 and 880
Fragment 008 / 009 :: RGBD matching between frame : 810 and 885
Fragment 008 / 009 :: RGBD matching between frame : 810 and 890
Fragment 008 / 009 :: RGBD matching between frame : 810 and 895
Fragment 008 / 009 :: RGBD matching between frame : 811 and 812
Fragment 008 / 009 :: RGBD matching between frame : 812 and 813
Fragment 008 / 009 :: RGBD matching between frame : 813 and 814
Fragment 008 / 009 :: RGBD matching between frame : 814 and 815
Fragment 008 / 009 :: RGBD matching between frame : 815 and 816
Fragment 008 / 009 :: RGBD matching between frame : 815 and 820
Fragment 008 / 009 :: RGBD matching between frame : 815 and 825
Fragment 008 / 009 :: RGBD matching between frame : 815 and 830
Fragment 008 / 009 :: RGBD matching between frame : 815 and 835
Fragment 008 / 009 :: RGBD matching between frame : 815 and 840
Fragment 008 / 009 :: RGBD matching between frame : 815 and 845
Fragment 008 / 009 :: RGBD matching between frame : 815 and 850
Fragment 008 / 009 :: RGBD matching between frame : 815 and 855
Fragment 008 / 009 :: RGBD matching between frame : 815 and 860
Fragment 008 / 009 :: RGBD matching between frame : 815 and 865
Fragment 008 / 009 :: RGBD matching between frame : 815 and 870
Fragment 008 / 009 :: RGBD matching between frame : 815 and 875
Fragment 008 / 009 :: RGBD matching between frame : 815 and 880
Fragment 008 / 009 :: RGBD matching between frame : 815 and 885
Fragment 008 / 009 :: RGBD matching between frame : 815 and 890
Fragment 008 / 009 :: RGBD matching between frame : 815 and 895
Fragment 008 / 009 :: RGBD matching between frame : 816 and 817
Fragment 008 / 009 :: RGBD matching between frame : 817 and 818
Fragment 008 / 009 :: RGBD matching between frame : 818 and 819
Fragment 008 / 009 :: RGBD matching between frame : 819 and 820
Fragment 008 / 009 :: RGBD matching between frame : 820 and 821
Fragment 008 / 009 :: RGBD matching between frame : 820 and 825
Fragment 008 / 009 :: RGBD matching between frame : 820 and 830
Fragment 008 / 009 :: RGBD matching between frame : 820 and 835
Fragment 008 / 009 :: RGBD matching between frame : 820 and 840
Fragment 008 / 009 :: RGBD matching between frame : 820 and 845
Fragment 008 / 009 :: RGBD matching between frame : 820 and 850
Fragment 008 / 009 :: RGBD matching between frame : 820 and 855
Fragment 008 / 009 :: RGBD matching between frame : 820 and 860
Fragment 008 / 009 :: RGBD matching between frame : 820 and 865
Fragment 008 / 009 :: RGBD matching between frame : 820 and 870
Fragment 008 / 009 :: RGBD matching between frame : 820 and 875
Fragment 008 / 009 :: RGBD matching between frame : 820 and 880
Fragment 008 / 009 :: RGBD matching between frame : 820 and 885
Fragment 008 / 009 :: RGBD matching between frame : 820 and 890
Fragment 008 / 009 :: RGBD matching between frame : 820 and 895
Fragment 008 / 009 :: RGBD matching between frame : 821 and 822
Fragment 008 / 009 :: RGBD matching between frame : 822 and 823
Fragment 008 / 009 :: RGBD matching between frame : 823 and 824
Fragment 008 / 009 :: RGBD matching between frame : 824 and 825
Fragment 008 / 009 :: RGBD matching between frame : 825 and 826
Fragment 008 / 009 :: RGBD matching between frame : 825 and 830
Fragment 008 / 009 :: RGBD matching between frame : 825 and 835
Fragment 008 / 009 :: RGBD matching between frame : 825 and 840
Fragment 008 / 009 :: RGBD matching between frame : 825 and 845
Fragment 008 / 009 :: RGBD matching between frame : 825 and 850
Fragment 008 / 009 :: RGBD matching between frame : 825 and 855
Fragment 008 / 009 :: RGBD matching between frame : 825 and 860
Fragment 008 / 009 :: RGBD matching between frame : 825 and 865
Fragment 008 / 009 :: RGBD matching between frame : 825 and 870
Fragment 008 / 009 :: RGBD matching between frame : 825 and 875
Fragment 008 / 009 :: RGBD matching between frame : 825 and 880
Fragment 008 / 009 :: RGBD matching between frame : 825 and 885
Fragment 008 / 009 :: RGBD matching between frame : 825 and 890
Fragment 008 / 009 :: RGBD matching between frame : 825 and 895
Fragment 008 / 009 :: RGBD matching between frame : 826 and 827
Fragment 008 / 009 :: RGBD matching between frame : 827 and 828
Fragment 008 / 009 :: RGBD matching between frame : 828 and 829
Fragment 008 / 009 :: RGBD matching between frame : 829 and 830
Fragment 008 / 009 :: RGBD matching between frame : 830 and 831
Fragment 008 / 009 :: RGBD matching between frame : 830 and 835
Fragment 008 / 009 :: RGBD matching between frame : 830 and 840
Fragment 008 / 009 :: RGBD matching between frame : 830 and 845
Fragment 008 / 009 :: RGBD matching between frame : 830 and 850
Fragment 008 / 009 :: RGBD matching between frame : 830 and 855
Fragment 008 / 009 :: RGBD matching between frame : 830 and 860
Fragment 008 / 009 :: RGBD matching between frame : 830 and 865
Fragment 008 / 009 :: RGBD matching between frame : 830 and 870
Fragment 008 / 009 :: RGBD matching between frame : 830 and 875
Fragment 008 / 009 :: RGBD matching between frame : 830 and 880
Fragment 008 / 009 :: RGBD matching between frame : 830 and 885
Fragment 008 / 009 :: RGBD matching between frame : 830 and 890
Fragment 008 / 009 :: RGBD matching between frame : 830 and 895
Fragment 008 / 009 :: RGBD matching between frame : 831 and 832
Fragment 008 / 009 :: RGBD matching between frame : 832 and 833
Fragment 008 / 009 :: RGBD matching between frame : 833 and 834
Fragment 008 / 009 :: RGBD matching between frame : 834 and 835
Fragment 008 / 009 :: RGBD matching between frame : 835 and 836
Fragment 008 / 009 :: RGBD matching between frame : 835 and 840
Fragment 008 / 009 :: RGBD matching between frame : 835 and 845
Fragment 008 / 009 :: RGBD matching between frame : 835 and 850
Fragment 008 / 009 :: RGBD matching between frame : 835 and 855
Fragment 008 / 009 :: RGBD matching between frame : 835 and 860
Fragment 008 / 009 :: RGBD matching between frame : 835 and 865
Fragment 008 / 009 :: RGBD matching between frame : 835 and 870
Fragment 008 / 009 :: RGBD matching between frame : 835 and 875
Fragment 008 / 009 :: RGBD matching between frame : 835 and 880
Fragment 008 / 009 :: RGBD matching between frame : 835 and 885
Fragment 008 / 009 :: RGBD matching between frame : 835 and 890
Fragment 008 / 009 :: RGBD matching between frame : 835 and 895
Fragment 008 / 009 :: RGBD matching between frame : 836 and 837
Fragment 008 / 009 :: RGBD matching between frame : 837 and 838
Fragment 008 / 009 :: RGBD matching between frame : 838 and 839
Fragment 008 / 009 :: RGBD matching between frame : 839 and 840
Fragment 008 / 009 :: RGBD matching between frame : 840 and 841
Fragment 008 / 009 :: RGBD matching between frame : 840 and 845
Fragment 008 / 009 :: RGBD matching between frame : 840 and 850
Fragment 008 / 009 :: RGBD matching between frame : 840 and 855
Fragment 008 / 009 :: RGBD matching between frame : 840 and 860
Fragment 008 / 009 :: RGBD matching between frame : 840 and 865
Fragment 008 / 009 :: RGBD matching between frame : 840 and 870
Fragment 008 / 009 :: RGBD matching between frame : 840 and 875
Fragment 008 / 009 :: RGBD matching between frame : 840 and 880
Fragment 008 / 009 :: RGBD matching between frame : 840 and 885
Fragment 008 / 009 :: RGBD matching between frame : 840 and 890
Fragment 008 / 009 :: RGBD matching between frame : 840 and 895
Fragment 008 / 009 :: RGBD matching between frame : 841 and 842
Fragment 008 / 009 :: RGBD matching between frame : 842 and 843
Fragment 008 / 009 :: RGBD matching between frame : 843 and 844
Fragment 008 / 009 :: RGBD matching between frame : 844 and 845
Fragment 008 / 009 :: RGBD matching between frame : 845 and 846
Fragment 008 / 009 :: RGBD matching between frame : 845 and 850
Fragment 008 / 009 :: RGBD matching between frame : 845 and 855
Fragment 008 / 009 :: RGBD matching between frame : 845 and 860
Fragment 008 / 009 :: RGBD matching between frame : 845 and 865
Fragment 008 / 009 :: RGBD matching between frame : 845 and 870
Fragment 008 / 009 :: RGBD matching between frame : 845 and 875
Fragment 008 / 009 :: RGBD matching between frame : 845 and 880
Fragment 008 / 009 :: RGBD matching between frame : 845 and 885
Fragment 008 / 009 :: RGBD matching between frame : 845 and 890
Fragment 008 / 009 :: RGBD matching between frame : 845 and 895
Fragment 008 / 009 :: RGBD matching between frame : 846 and 847
Fragment 008 / 009 :: RGBD matching between frame : 847 and 848
Fragment 008 / 009 :: RGBD matching between frame : 848 and 849
Fragment 008 / 009 :: RGBD matching between frame : 849 and 850
Fragment 008 / 009 :: RGBD matching between frame : 850 and 851
Fragment 008 / 009 :: RGBD matching between frame : 850 and 855
Fragment 008 / 009 :: RGBD matching between frame : 850 and 860
Fragment 008 / 009 :: RGBD matching between frame : 850 and 865
Fragment 008 / 009 :: RGBD matching between frame : 850 and 870
Fragment 008 / 009 :: RGBD matching between frame : 850 and 875
Fragment 008 / 009 :: RGBD matching between frame : 850 and 880
Fragment 008 / 009 :: RGBD matching between frame : 850 and 885
Fragment 008 / 009 :: RGBD matching between frame : 850 and 890
Fragment 008 / 009 :: RGBD matching between frame : 850 and 895
Fragment 008 / 009 :: RGBD matching between frame : 851 and 852
Fragment 008 / 009 :: RGBD matching between frame : 852 and 853
Fragment 008 / 009 :: RGBD matching between frame : 853 and 854
Fragment 008 / 009 :: RGBD matching between frame : 854 and 855
Fragment 008 / 009 :: RGBD matching between frame : 855 and 856
Fragment 008 / 009 :: RGBD matching between frame : 855 and 860
Fragment 008 / 009 :: RGBD matching between frame : 855 and 865
Fragment 008 / 009 :: RGBD matching between frame : 855 and 870
Fragment 008 / 009 :: RGBD matching between frame : 855 and 875
Fragment 008 / 009 :: RGBD matching between frame : 855 and 880
Fragment 008 / 009 :: RGBD matching between frame : 855 and 885
Fragment 008 / 009 :: RGBD matching between frame : 855 and 890
Fragment 008 / 009 :: RGBD matching between frame : 855 and 895
Fragment 008 / 009 :: RGBD matching between frame : 856 and 857
Fragment 008 / 009 :: RGBD matching between frame : 857 and 858
Fragment 008 / 009 :: RGBD matching between frame : 858 and 859
Fragment 008 / 009 :: RGBD matching between frame : 859 and 860
Fragment 008 / 009 :: RGBD matching between frame : 860 and 861
Fragment 008 / 009 :: RGBD matching between frame : 860 and 865
Fragment 008 / 009 :: RGBD matching between frame : 860 and 870
Fragment 008 / 009 :: RGBD matching between frame : 860 and 875
Fragment 008 / 009 :: RGBD matching between frame : 860 and 880
Fragment 008 / 009 :: RGBD matching between frame : 860 and 885
Fragment 008 / 009 :: RGBD matching between frame : 860 and 890
Fragment 008 / 009 :: RGBD matching between frame : 860 and 895
Fragment 008 / 009 :: RGBD matching between frame : 861 and 862
Fragment 008 / 009 :: RGBD matching between frame : 862 and 863
Fragment 008 / 009 :: RGBD matching between frame : 863 and 864
Fragment 008 / 009 :: RGBD matching between frame : 864 and 865
Fragment 008 / 009 :: RGBD matching between frame : 865 and 866
Fragment 008 / 009 :: RGBD matching between frame : 865 and 870
Fragment 008 / 009 :: RGBD matching between frame : 865 and 875
Fragment 008 / 009 :: RGBD matching between frame : 865 and 880
Fragment 008 / 009 :: RGBD matching between frame : 865 and 885
Fragment 008 / 009 :: RGBD matching between frame : 865 and 890
Fragment 008 / 009 :: RGBD matching between frame : 865 and 895
Fragment 008 / 009 :: RGBD matching between frame : 866 and 867
Fragment 008 / 009 :: RGBD matching between frame : 867 and 868
Fragment 008 / 009 :: RGBD matching between frame : 868 and 869
Fragment 008 / 009 :: RGBD matching between frame : 869 and 870
Fragment 008 / 009 :: RGBD matching between frame : 870 and 871
Fragment 008 / 009 :: RGBD matching between frame : 870 and 875
Fragment 008 / 009 :: RGBD matching between frame : 870 and 880
Fragment 008 / 009 :: RGBD matching between frame : 870 and 885
Fragment 008 / 009 :: RGBD matching between frame : 870 and 890
Fragment 008 / 009 :: RGBD matching between frame : 870 and 895
Fragment 008 / 009 :: RGBD matching between frame : 871 and 872
Fragment 008 / 009 :: RGBD matching between frame : 872 and 873
Fragment 008 / 009 :: RGBD matching between frame : 873 and 874
Fragment 008 / 009 :: RGBD matching between frame : 874 and 875
Fragment 008 / 009 :: RGBD matching between frame : 875 and 876
Fragment 008 / 009 :: RGBD matching between frame : 875 and 880
Fragment 008 / 009 :: RGBD matching between frame : 875 and 885
Fragment 008 / 009 :: RGBD matching between frame : 875 and 890
Fragment 008 / 009 :: RGBD matching between frame : 875 and 895
Fragment 008 / 009 :: RGBD matching between frame : 876 and 877t_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.026 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 259 edges.
[Open3D DEBUG] Line process weight : 70.780375
[Open3D DEBUG] [Initial ] residual : 2.865817e+02, lambda : 2.775940e+01
[Open3D DEBUG] [Iteration 00] residual : 2.856153e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 2.855477e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 2.855351e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 03] residual : 2.855311e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 04] residual : 2.855297e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] [Iteration 05] residual : 2.855292e+02, valid edges : 160, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.009 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 289 edges.
[Open3D DEBUG] Line process weight : 65.702588
[Open3D DEBUG] [Initial ] residual : 2.061259e+02, lambda : 2.762859e+01
[Open3D DEBUG] [Iteration 00] residual : 2.351869e+01, valid edges : 190, time : 0.002 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.932616e+01, valid edges : 190, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.932533e+01, valid edges : 190, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.006 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 289 edges.
[Open3D DEBUG] Line process weight : 65.702588
[Open3D DEBUG] [Initial ] residual : 1.932533e+01, lambda : 2.823950e+01
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.001 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 289 edges.
[Open3D DEBUG] Line process weight : 57.225272
[Open3D DEBUG] [Initial ] residual : 7.296191e+02, lambda : 2.435130e+01
[Open3D DEBUG] [Iteration 00] residual : 3.473220e+02, valid edges : 185, time : 0.002 sec.
[Open3D DEBUG] [Iteration 01] residual : 3.456611e+02, valid edges : 185, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 3.456437e+02, valid edges : 185, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.005 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 100 nodes and 284 edges.
[Open3D DEBUG] Line process weight : 57.390139
[Open3D DEBUG] [Initial ] residual : 1.878477e+02, lambda : 2.449058e+01
[Open3D DEBUG] [Iteration 00] residual : 1.848482e+02, valid edges : 185, time : 0.001 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.847259e+02, valid edges : 185, time : 0.001 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.847251e+02, valid edges : 185, time : 0.001 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.005 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 5 nodes and 4 edges.
[Open3D DEBUG] Line process weight : 60.575638
[Open3D DEBUG] [Initial ] residual : 4.442189e-31, lambda : 2.492250e+00
[Open3D DEBUG] Maximum coefficient of right term < 1.000000e-06
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 5 nodes and 4 edges.
[Open3D DEBUG] Line process weight : 60.575638
[Open3D DEBUG] [Initial ] residual : 4.442189e-31, lamb
Fragment 008 / 009 :: RGBD matching between frame : 877 and 878
Fragment 008 / 009 :: RGBD matching between frame : 878 and 879
Fragment 008 / 009 :: RGBD matching between frame : 879 and 880
Fragment 008 / 009 :: RGBD matching between frame : 880 and 881
Fragment 008 / 009 :: RGBD matching between frame : 880 and 885
Fragment 008 / 009 :: RGBD matching between frame : 880 and 890
Fragment 008 / 009 :: RGBD matching between frame : 880 and 895
Fragment 008 / 009 :: RGBD matching between frame : 881 and 882
Fragment 008 / 009 :: RGBD matching between frame : 882 and 883
Fragment 008 / 009 :: RGBD matching between frame : 883 and 884
Fragment 008 / 009 :: RGBD matching between frame : 884 and 885
Fragment 008 / 009 :: RGBD matching between frame : 885 and 886
Fragment 008 / 009 :: RGBD matching between frame : 885 and 890
Fragment 008 / 009 :: RGBD matching between frame : 885 and 895
Fragment 008 / 009 :: RGBD matching between frame : 886 and 887
Fragment 008 / 009 :: RGBD matching between frame : 887 and 888
Fragment 008 / 009 :: RGBD matching between frame : 888 and 889
Fragment 008 / 009 :: RGBD matching between frame : 889 and 890
Fragment 008 / 009 :: RGBD matching between frame : 890 and 891
Fragment 008 / 009 :: RGBD matching between frame : 890 and 895
Fragment 008 / 009 :: RGBD matching between frame : 891 and 892
Fragment 008 / 009 :: RGBD matching between frame : 892 and 893
Fragment 008 / 009 :: RGBD matching between frame : 893 and 894
Fragment 008 / 009 :: RGBD matching between frame : 894 and 895
Fragment 008 / 009 :: RGBD matching between frame : 895 and 896
Fragment 008 / 009 :: RGBD matching between frame : 896 and 897
Fragment 008 / 009 :: RGBD matching between frame : 897 and 898
Fragment 008 / 009 :: RGBD matching between frame : 898 and 899
Fragment 008 / 009 :: integrate rgbd frame 800 (1 of 100).
Fragment 008 / 009 :: integrate rgbd frame 801 (2 of 100).
Fragment 008 / 009 :: integrate rgbd frame 802 (3 of 100).
Fragment 008 / 009 :: integrate rgbd frame 803 (4 of 100).
Fragment 008 / 009 :: integrate rgbd frame 804 (5 of 100).
Fragment 008 / 009 :: integrate rgbd frame 805 (6 of 100).
Fragment 008 / 009 :: integrate rgbd frame 806 (7 of 100).
Fragment 008 / 009 :: integrate rgbd frame 807 (8 of 100).
Fragment 008 / 009 :: integrate rgbd frame 808 (9 of 100).
Fragment 008 / 009 :: integrate rgbd frame 809 (10 of 100).
Fragment 008 / 009 :: integrate rgbd frame 810 (11 of 100).
Fragment 008 / 009 :: integrate rgbd frame 811 (12 of 100).
Fragment 008 / 009 :: integrate rgbd frame 812 (13 of 100).
Fragment 008 / 009 :: integrate rgbd frame 813 (14 of 100).
Fragment 008 / 009 :: integrate rgbd frame 814 (15 of 100).
Fragment 008 / 009 :: integrate rgbd frame 815 (16 of 100).
Fragment 008 / 009 :: integrate rgbd frame 816 (17 of 100).
Fragment 008 / 009 :: integrate rgbd frame 817 (18 of 100).
Fragment 008 / 009 :: integrate rgbd frame 818 (19 of 100).
Fragment 008 / 009 :: integrate rgbd frame 819 (20 of 100).
Fragment 008 / 009 :: integrate rgbd frame 820 (21 of 100).
Fragment 008 / 009 :: integrate rgbd frame 821 (22 of 100).
Fragment 008 / 009 :: integrate rgbd frame 822 (23 of 100).
Fragment 008 / 009 :: integrate rgbd frame 823 (24 of 100).
Fragment 008 / 009 :: integrate rgbd frame 824 (25 of 100).
Fragment 008 / 009 :: integrate rgbd frame 825 (26 of 100).
Fragment 008 / 009 :: integrate rgbd frame 826 (27 of 100).
Fragment 008 / 009 :: integrate rgbd frame 827 (28 of 100).
Fragment 008 / 009 :: integrate rgbd frame 828 (29 of 100).
Fragment 008 / 009 :: integrate rgbd frame 829 (30 of 100).
Fragment 008 / 009 :: integrate rgbd frame 830 (31 of 100).
Fragment 008 / 009 :: integrate rgbd frame 831 (32 of 100).
Fragment 008 / 009 :: integrate rgbd frame 832 (33 of 100).
Fragment 008 / 009 :: integrate rgbd frame 833 (34 of 100).
Fragment 008 / 009 :: integrate rgbd frame 834 (35 of 100).
Fragment 008 / 009 :: integrate rgbd frame 835 (36 of 100).
Fragment 008 / 009 :: integrate rgbd frame 836 (37 of 100).
Fragment 008 / 009 :: integrate rgbd frame 837 (38 of 100).
Fragment 008 / 009 :: integrate rgbd frame 838 (39 of 100).
Fragment 008 / 009 :: integrate rgbd frame 839 (40 of 100).
Fragment 008 / 009 :: integrate rgbd frame 840 (41 of 100).
Fragment 008 / 009 :: integrate rgbd frame 841 (42 of 100).
Fragment 008 / 009 :: integrate rgbd frame 842 (43 of 100).
Fragment 008 / 009 :: integrate rgbd frame 843 (44 of 100).
Fragment 008 / 009 :: integrate rgbd frame 844 (45 of 100).
Fragment 008 / 009 :: integrate rgbd frame 845 (46 of 100).
Fragment 008 / 009 :: integrate rgbd frame 846 (47 of 100).
Fragment 008 / 009 :: integrate rgbd frame 847 (48 of 100).
Fragment 008 / 009 :: integrate rgbd frame 848 (49 of 100).
Fragment 008 / 009 :: integrate rgbd frame 849 (50 of 100).
Fragment 008 / 009 :: integrate rgbd frame 850 (51 of 100).
Fragment 008 / 009 :: integrate rgbd frame 851 (52 of 100).
Fragment 008 / 009 :: integrate rgbd frame 852 (53 of 100).
Fragment 008 / 009 :: integrate rgbd frame 853 (54 of 100).
Fragment 008 / 009 :: integrate rgbd frame 854 (55 of 100).
Fragment 008 / 009 :: integrate rgbd frame 855 (56 of 100).
Fragment 008 / 009 :: integrate rgbd frame 856 (57 of 100).
Fragment 008 / 009 :: integrate rgbd frame 857 (58 of 100).
Fragment 008 / 009 :: integrate rgbd frame 858 (59 of 100).
Fragment 008 / 009 :: integrate rgbd frame 859 (60 of 100).
Fragment 008 / 009 :: integrate rgbd frame 860 (61 of 100).
Fragment 008 / 009 :: integrate rgbd frame 861 (62 of 100).
Fragment 008 / 009 :: integrate rgbd frame 862 (63 of 100).
Fragment 008 / 009 :: integrate rgbd frame 863 (64 of 100).
Fragment 008 / 009 :: integrate rgbd frame 864 (65 of 100).
Fragment 008 / 009 :: integrate rgbd frame 865 (66 of 100).
Fragment 008 / 009 :: integrate rgbd frame 866 (67 of 100).
Fragment 008 / 009 :: integrate rgbd frame 867 (68 of 100).
Fragment 008 / 009 :: integrate rgbd frame 868 (69 of 100).
Fragment 008 / 009 :: integrate rgbd frame 869 (70 of 100).
Fragment 008 / 009 :: integrate rgbd frame 870 (71 of 100).
Fragment 008 / 009 :: integrate rgbd frame 871 (72 of 100).
Fragment 008 / 009 :: integrate rgbd frame 872 (73 of 100).
Fragment 008 / 009 :: integrate rgbd frame 873 (74 of 100).
Fragment 008 / 009 :: integrate rgbd frame 874 (75 of 100).
Fragment 008 / 009 :: integrate rgbd frame 875 (76 of 100).
Fragment 008 / 009 :: integrate rgbd frame 876 (77 of 100).
Fragment 008 / 009 :: integrate rgbd frame 877 (78 of 100).
Fragment 008 / 009 :: integrate rgbd frame 878 (79 of 100).
Fragment 008 / 009 :: integrate rgbd frame 879 (80 of 100).
Fragment 008 / 009 :: integrate rgbd frame 880 (81 of 100).
Fragment 008 / 009 :: integrate rgbd frame 881 (82 of 100).
Fragment 008 / 009 :: integrate rgbd frame 882 (83 of 100).
Fragment 008 / 009 :: integrate rgbd frame 883 (84 of 100).
Fragment 008 / 009 :: integrate rgbd frame 884 (85 of 100).
Fragment 008 / 009 :: integrate rgbd frame 885 (86 of 100).
Fragment 008 / 009 :: integrate rgbd frame 886 (87 of 100).
Fragment 008 / 009 :: integrate rgbd frame 887 (88 of 100).
Fragment 008 / 009 :: integrate rgbd frame 888 (89 of 100).
Fragment 008 / 009 :: integrate rgbd frame 889 (90 of 100).
Fragment 008 / 009 :: integrate rgbd frame 890 (91 of 100).
Fragment 008 / 009 :: integrate rgbd frame 891 (92 of 100).
Fragment 008 / 009 :: integrate rgbd frame 892 (93 of 100).
Fragment 008 / 009 :: integrate rgbd frame 893 (94 of 100).
Fragment 008 / 009 :: integrate rgbd frame 894 (95 of 100).
Fragment 008 / 009 :: integrate rgbd frame 895 (96 of 100).
Fragment 008 / 009 :: integrate rgbd frame 896 (97 of 100).
Fragment 008 / 009 :: integrate rgbd frame 897 (98 of 100).
Fragment 008 / 009 :: integrate rgbd frame 898 (99 of 100).
Fragment 008 / 009 :: integrate rgbd frame 899 (100 of 100).
Fragment 009 / 009 :: RGBD matching between frame : 900 and 901
Fragment 009 / 009 :: RGBD matching between frame : 901 and 902
Fragment 009 / 009 :: RGBD matching between frame : 902 and 903
Fragment 009 / 009 :: RGBD matching between frame : 903 and 904
Fragment 009 / 009 :: integrate rgbd frame 900 (1 of 5).
Fragment 009 / 009 :: integrate rgbd frame 901 (2 of 5).
Fragment 009 / 009 :: integrate rgbd frame 902 (3 of 5).da : 2.492250e+00
[Open3D DEBUG] Maximum coefficient of right term < 1.000000e-06
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 366 points to 240 points.
[Open3D DEBUG] Pointcloud down sampled from 396 points to 312 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7000, RMSE 0.0224
[Open3D DEBUG] Residual : 3.03e-04 (# of elements : 168)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6917, RMSE 0.0220
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 3.02e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.6917, RMSE 0.0226
[Open3D DEBUG] Residual : 3.01e-04 (# of elements : 166)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.6917, RMSE 0.0224
[Open3D DEBUG] Residual : 2.78e-04 (# of elements : 166)
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] total_validation : 500
[Open3D DEBUG] RANSAC: Fitness 1.0000, RMSE 0.0201
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] total_validation : 303
[Open3D DEBUG] RANSAC: Fitness 0.8770, RMSE 0.0322
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] total_validation : 218
[Open3D DEBUG] RANSAC: Fitness 0.6776, RMSE 0.0387
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] total_validation : 304
[Open3D DEBUG] RANSAC: Fitness 0.8197, RMSE 0.0396
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] total_validation : 357
[Open3D DEBUG] RANSAC: Fitness 0.8497, RMSE 0.0274
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] total_validation : 500
[Open3D DEBUG] RANSAC: Fitness 0.8060, RMSE 0.0335
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] total_validation : 505
[Open3D DEBUG] RANSAC: Fitness 0.9727, RMSE 0.0319
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 501
[Open3D DEBUG] RANSAC: Fitness 0.8388, RMSE 0.0346
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 396 points to 312 points.
[Open3D DEBUG] Pointcloud down sampled from 684 points to 521 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.9071, RMSE 0.0221
[Open3D DEBUG] Residual : 3.17e-04 (# of elements : 283)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.9071, RMSE 0.0212
[Open3D DEBUG] Residual : 2.44e-04 (# of elements : 283)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.9071, RMSE 0.0210
[Open3D DEBUG] Residual : 2.37e-04 (# of elements : 283)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.9071, RMSE 0.0210
[Open3D DEBUG] Residual : 2.37e-04 (# of elements : 283)
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] total_validation : 339
[Open3D DEBUG] RANSAC: Fitness 0.6894, RMSE 0.0399
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] total_validation : 117
[Open3D DEBUG] RANSAC: Fitness 0.4747, RMSE 0.0384
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] total_validation : 501
[Open3D DEBUG] RANSAC: Fitness 0.8207, RMSE 0.0294
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] total_validation : 500
[Open3D DEBUG] RANSAC: Fitness 0.7273, RMSE 0.0246
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] total_validation : 374
[Open3D DEBUG] RANSAC: Fitness 0.5859, RMSE 0.0325
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] total_validation : 501
[Open3D DEBUG] RANSAC: Fitness 0.6818, RMSE 0.0324
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 244
[Open3D DEBUG] RANSAC: Fitness 0.4495, RMSE 0.0345
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 684 points to 521 points.
[Open3D DEBUG] Pointcloud down sampled from 811 points to 591 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6814, RMSE 0.0251
[Open3D DEBUG] Residual : 5.74e-04 (# of elements : 355)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6775, RMSE 0.0234
[Open3D DEBUG] Residual : 4.48e-04 (# of elements : 353)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6795, RMSE 0.0234
[Open3D DEBUG] Residual : 4.53e-04 (# of elements : 354)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6833, RMSE 0.0236
[Open3D DEBUG] Residual : 4.64e-04 (# of elements : 356)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6852, RMSE 0.0237
[Open3D DEBUG] Residual : 4.69e-04 (# of elements : 357)
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] total_validation : 53
[Open3D DEBUG] RANSAC: Fitness 0.4254, RMSE 0.0414
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] total_validation : 230
[Open3D DEBUG] RANSAC: Fitness 0.6111, RMSE 0.0328
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] total_validation : 501
[Open3D DEBUG] RANSAC: Fitness 0.6944, RMSE 0.0265
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] total_validation : 363
[Open3D DEBUG] RANSAC: Fitness 0.5702, RMSE 0.0322
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] total_validation : 500
[Open3D DEBUG] RANSAC: Fitness 0.7208, RMSE 0.0287
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 204
[Open3D DEBUG] RANSAC: Fitness 0.5044, RMSE 0.0367
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 811 points to 591 points.
[Open3D DEBUG] Pointcloud down sampled from 446 points to 363 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3587, RMSE 0.0241
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3790, RMSE 0.0262
[Open3D DEBUG] Residual : 1.17e-03 (# of elements : 224)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3773, RMSE 0.0271
[Open3D DEBUG] Residual : 1.21e-03 (# of elements : 223)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3824, RMSE 0.0278
[Open3D DEBUG] Residual : 1.23e-03 (# of elements : 226)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3824, RMSE 0.0281
[Open3D DEBUG] Residual : 1.25e-03 (# of elements : 226)
[Open3D DEBUG] ICP Itera
Fragment 009 / 009 :: integrate rgbd frame 903 (4 of 5).
Fragment 009 / 009 :: integrate rgbd frame 904 (5 of 5).
register fragments.
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_001.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.99599279 0.04162536 -0.07915614 -0.04143244]
[-0.01724005 0.95784417 0.28677051 0.09416674]
[ 0.08775617 -0.2842567 0.95472351 0.01341244]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_002.ply ...
[[ 0.97374733 0.19491709 -0.11757321 -0.07077194]
[-0.12698 0.89379855 0.43011654 0.17814606]
[ 0.18892383 -0.40389539 0.89508452 -0.03137502]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_003.ply ...
[[ 0.85006002 0.49436564 -0.18166062 -0.12809229]
[-0.49757453 0.86687611 0.03074715 0.04819955]
[ 0.17267758 0.06425278 0.98288048 0.1318286 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_004.ply ...
[[ 0.91082347 0.39800362 0.10951585 0.05656879]
[-0.20406206 0.6647416 -0.71866354 0.38328677]
[-0.35883043 0.63222759 0.68667969 0.17800331]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
[[-0.94222687 -0.14738216 -0.30081062 -0.14741001]
[ 0.30305547 -0.75763381 -0.5780557 -0.2428505 ]
[-0.1427092 -0.63582191 0.7585279 -0.61678255]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
[[ 0.89631286 0.42337629 -0.13181721 -0.07985644]
[-0.40246384 0.90153002 0.15895434 0.11192268]
[ 0.18613467 -0.08942116 0.9784466 0.09381462]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
[[ 0.99118139 0.13222389 -0.00873513 -0.08083668]
[-0.13112811 0.98819819 0.07918178 0.0046593 ]
[ 0.01910177 -0.07733808 0.99682192 0.12802125]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
[[ 0.98986896 0.08787386 -0.11152413 -0.05308486]
[-0.08409775 0.99572762 0.03813235 0.03394317]
[ 0.11439849 -0.0283671 0.99302986 0.1334891 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[ 0.99989708 -0.00368839 -0.01386439 0.03667383]
[ 0.00625862 0.9817256 0.19019904 0.02056876]
[ 0.0129095 -0.19026624 0.98164765 0.12381184]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_002.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.98980174 0.13376819 -0.04897545 -0.0612769 ]
[-0.12538882 0.98129085 0.14610243 0.07937003]
[ 0.06760302 -0.13847146 0.98805642 -0.03235261]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_003.ply ...
[[ 0.98006402 -0.19110666 -0.05433937 -0.27668172]
[-0.05574654 -0.00199058 -0.99844297 0.59752462]
[ 0.19070093 0.98156726 -0.01260443 0.64076876]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_004.ply ...
[[-0.97070627 0.24008246 0.00947352 0.28249481]
[-0.01920893 -0.11684774 0.99296406 -0.86369182]
[ 0.23950022 0.96369446 0.11803656 0.22606887]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
[[-0.87809332 -0.2324227 -0.41824849 0.10196977]
[ 0.40781016 -0.82074437 -0.40008693 -0.21595467]
[-0.25028581 -0.52187965 0.81547449 -0.50994019]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
[[ 0.94359501 0.29831486 -0.1436548 -0.09584755]
[-0.32081368 0.93105535 -0.17382321 0.03472424]
[ 0.08189653 0.21010514 0.97424267 0.07600382]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
[[ 0.99638113 0.07777483 -0.03428874 -0.05224443]
[-0.08466707 0.94371829 -0.31973002 -0.02505184]
[ 0.00749197 0.32147608 0.94688806 0.09623336]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
[[ 0.99176673 0.11499072 -0.05635492 -0.03568752]
[-0.12555119 0.95977921 -0.25111901 -0.04728097]
[ 0.02521192 0.25612691 0.96631432 0.09868603]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[ 0.95674088 0.26078828 0.12898204 0.03242388]
[-0.24422854 0.96081795 -0.13107742 -0.04837766]
[-0.15811171 0.09390603 0.98294575 0.10584184]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_003.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.97346079 0.06769904 -0.21861137 -0.06881037]
[-0.1613904 0.88034297 -0.44603743 -0.11603062]
[ 0.16225668 0.46948172 0.86790534 0.0810917 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_004.ply ...
[[ 0.94393462 0.06861989 -0.3229222 0.19919621]
[-0.32279026 0.39698561 -0.85919083 0.1423597 ]
[ 0.06923788 0.91525611 0.39687829 0.03871485]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
[[-0.91623816 -0.10726072 -0.38600878 0.01861288]
[ 0.21236754 -0.94702328 -0.24092933 -0.13053961]
[-0.33971705 -0.30272438 0.89047756 -0.51887752]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
[[ 0.97651961 0.15232877 -0.15233318 -0.03289618]
[-0.19384073 0.92982982 -0.31279751 -0.07738356]
[ 0.09399587 0.33498128 0.93752457 0.09352852]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
[[ 9.98507934e-01 -5.10453993e-02 1.93977695e-02 3.10290309e-02]
[ 5.46038581e-02 9.37042953e-01 -3.44918718e-01 -1.73869002e-01]
[-5.70029543e-04 3.45463270e-01 9.38432099e-01 8.52318986e-02]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 1.00000000e+00]]
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
[[ 0.99967021 -0.02497237 -0.00598808 0.03127721]
[ 0.02046032 0.91543166 -0.40195306 -0.15797285]
[ 0.0155194 0.40169798 0.9156407 0.09344921]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[ 0.96108132 -0.23213234 0.14979075 0.20481148]
[ 0.26593983 0.92421622 -0.27404449 -0.09922822]
[-0.07482445 0.30321437 0.94998018 0.10782698]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_004.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.9871912 -0.07389 0.14139943 0.27261398]
[ 0.15045313 0.72602652 -0.67100622 0.38835793]
[-0.05307909 0.68368542 0.72784397 0.00466068]
[ 0. 0. 0. 1. ]]tion #5: Fitness 0.3841, RMSE 0.0286
[Open3D DEBUG] Residual : 1.28e-03 (# of elements : 227)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3790, RMSE 0.0285
[Open3D DEBUG] Residual : 1.35e-03 (# of elements : 224)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3807, RMSE 0.0291
[Open3D DEBUG] Residual : 1.46e-03 (# of elements : 225)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3739, RMSE 0.0286
[Open3D DEBUG] Residual : 1.44e-03 (# of elements : 221)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3689, RMSE 0.0283
[Open3D DEBUG] Residual : 1.40e-03 (# of elements : 218)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3689, RMSE 0.0285
[Open3D DEBUG] Residual : 1.43e-03 (# of elements : 218)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3672, RMSE 0.0288
[Open3D DEBUG] Residual : 1.47e-03 (# of elements : 217)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3672, RMSE 0.0291
[Open3D DEBUG] Residual : 1.51e-03 (# of elements : 217)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3689, RMSE 0.0295
[Open3D DEBUG] Residual : 1.54e-03 (# of elements : 218)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3638, RMSE 0.0290
[Open3D DEBUG] Residual : 1.52e-03 (# of elements : 215)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3655, RMSE 0.0294
[Open3D DEBUG] Residual : 1.53e-03 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3638, RMSE 0.0292
[Open3D DEBUG] Residual : 1.56e-03 (# of elements : 215)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3621, RMSE 0.0290
[Open3D DEBUG] Residual : 1.54e-03 (# of elements : 214)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3621, RMSE 0.0289
[Open3D DEBUG] Residual : 1.54e-03 (# of elements : 214)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3621, RMSE 0.0289
[Open3D DEBUG] Residual : 1.53e-03 (# of elements : 214)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3621, RMSE 0.0289
[Open3D DEBUG] Residual : 1.53e-03 (# of elements : 214)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3621, RMSE 0.0289
[Open3D DEBUG] Residual : 1.53e-03 (# of elements : 214)
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] total_validation : 96
[Open3D DEBUG] RANSAC: Fitness 0.5302, RMSE 0.0336
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] total_validation : 500
[Open3D DEBUG] RANSAC: Fitness 0.6535, RMSE 0.0338
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] total_validation : 122
[Open3D DEBUG] RANSAC: Fitness 0.5154, RMSE 0.0334
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] total_validation : 320
[Open3D DEBUG] RANSAC: Fitness 0.5919, RMSE 0.0365
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 85
[Open3D DEBUG] RANSAC: Fitness 0.3835, RMSE 0.0331
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] Pointcloud down sampled from 446 points to 363 points.
[Open3D DEBUG] Pointcloud down sampled from 700 points to 531 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2424, RMSE 0.0287
[Open3D DEBUG] Residual : 1.17e-03 (# of elements : 88)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2755, RMSE 0.0287
[Open3D DEBUG] Residual : 1.05e-03 (# of elements : 100)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2893, RMSE 0.0292
[Open3D DEBUG] Residual : 9.06e-04 (# of elements : 105)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3003, RMSE 0.0298
[Open3D DEBUG] Residual : 9.23e-04 (# of elements : 109)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2975, RMSE 0.0302
[Open3D DEBUG] Residual : 8.93e-04 (# of elements : 108)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.2920, RMSE 0.0301
[Open3D DEBUG] Residual : 7.91e-04 (# of elements : 106)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2782, RMSE 0.0296
[Open3D DEBUG] Residual : 7.45e-04 (# of elements : 101)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.2810, RMSE 0.0306
[Open3D DEBUG] Residual : 7.44e-04 (# of elements : 102)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.2810, RMSE 0.0304
[Open3D DEBUG] Residual : 7.37e-04 (# of elements : 102)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.2782, RMSE 0.0303
[Open3D DEBUG] Residual : 7.38e-04 (# of elements : 101)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.2810, RMSE 0.0305
[Open3D DEBUG] Residual : 7.60e-04 (# of elements : 102)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.2810, RMSE 0.0305
[Open3D DEBUG] Residual : 7.53e-04 (# of elements : 102)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.2810, RMSE 0.0303
[Open3D DEBUG] Residual : 7.54e-04 (# of elements : 102)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.2810, RMSE 0.0303
[Open3D DEBUG] Residual : 7.54e-04 (# of elements : 102)
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] total_validation : 125
[Open3D DEBUG] RANSAC: Fitness 0.6547, RMSE 0.0357
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] total_validation : 60
[Open3D DEBUG] RANSAC: Fitness 0.5112, RMSE 0.0433
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] total_validation : 96
[Open3D DEBUG] RANSAC: Fitness 0.6547, RMSE 0.0387
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 41
[Open3D DEBUG] RANSAC: Fitness 0.4552, RMSE 0.0423
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] Pointcloud down sampled from 700 points to 531 points.
[Open3D DEBUG] Pointcloud down sampled from 526 points to 361 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5913, RMSE 0.0272
[Open3D DEBUG] Residual : 6.16e-04 (# of elements : 314)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5989, RMSE 0.0247
[Open3D DEBUG] Residual : 4.59e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5989, RMSE 0.0243
[Open3D DEBUG] Residual : 4.57e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5989, RMSE 0.0243
[Open3D DEBUG] Residual : 4.52e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5989, RMSE 0.0243
[Open3D DEBUG] Residual : 4.52e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5989, RMSE 0.0242
[Open3D DEBUG] Residual : 4.52e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5989, RMSE 0.0242
[Open3D DEBUG] Residual : 4.50e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5989, RMSE 0.0242
[Open3D DEBUG] Residual : 4.47e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5989, RMSE 0.0242
[Open3D DEBUG] Residual : 4.50e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5989, RMSE 0.0242
[Open3D DEBUG] Residual : 4.52e-04 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5989, RMSE 0.0242
[Open3D DEBUG] Residual : 4.52e-04 (# of elements : 318)
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] total_validation : 67
[Open3D DEBUG] RANSAC: Fitness 0.3557, RMSE 0.0430
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] total_validation : 105
[Open3D DEBUG] RANSAC: Fitness 0.4714, RMSE 0.0318
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 24
[Open3D DEBUG] RANSAC: Fitness 0.2900, RMSE 0.0424
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] Pointcloud down sampled from 526 points to 361 points.
[Open3D DEBUG] Pointcloud down sampled from 321 points to 217 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7008, RMSE 0.0255
[Open3D DEBUG] Residual : 4.60e-04 (# of elements : 253)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7230, RMSE 0.0259
[Open3D DEBUG] Residual : 4.73e-04 (# of elements : 261)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7285, RMSE 0.0262
[Open3D DEBUG] Residual : 5.18e-04 (# of elements : 263)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7230, RMSE 0.0260
[Open3D DEBUG] Residual : 5.24e-04 (# of elements : 261)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7230, RMSE 0.0260
[Open3D DEBUG] Residual : 5.18e-04 (# of elements : 261)
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] total_validation : 501
[Open3D DEBUG] RANSAC: Fitness 0.9144, RMSE 0.0334
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 158
[Open3D DEBUG] RANSAC: Fitness 0.5399, RMSE 0.0330
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] Pointcloud down sampled from 321 points to 217 points.
[Open3D DEBUG] Pointcloud down sampled from 437 points to 316 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.9954, RMSE 0.0209
[Open3D DEBUG] Residual : 2.02e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.9954, RMSE 0.0199
[Open3D DEBUG] Residual : 2.03e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.9954, RMSE 0.0198
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.98e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.9954, RMSE 0.0198
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.92e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.9954, RMSE 0.0198
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.9954, RMSE 0.0197
[Open3D DEBUG] Residual : 1.95e-04 (# of elements : 216)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.9954, RMSE 0.0196
[Open3D DEBUG] Residual : 1.94e-04 (# of elements : 216)
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] total_validation : 502
[Open3D DEBUG] RANSAC: Fitness 0.7196, RMSE 0.0337
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] Pointcloud down sampled from 437 points to 316 points.
[Open3D DEBUG] Pointcloud down sampled from 238 points to 168 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6930, RMSE 0.0233
[Open3D DEBUG] Residual : 3.32e-04 (# of elements : 219)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6899, RMSE 0.0230
[Open3D DEBUG] Residual : 3.25e-04 (# of elements : 218)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6930, RMSE 0.0232
[Open3D DEBUG] Residual : 3.25e-04 (# of elements : 219)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6930, RMSE 0.0232
[Open3D DEBUG] Residual : 3.23e-04 (# of elements : 219)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6930, RMSE 0.0232
[Open3D DEBUG] Residual : 3.23e-04 (# of elements : 219)
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 10 nodes and 45 edges.
[Open3D DEBUG] Line process weight : 7.579756
[Open3D DEBUG] [Initial ] residual : 6.281269e+03, lambda : 1.308528e-02
[Open3D DEBUG] [Iteration 00] residual : 2.059893e+02, valid edges : 8, time : 0.000 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.840840e+02, valid edges : 12, time : 0.000 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.460399e+02, valid edges : 22, time : 0.000 sec.
[Open3D DEBUG] [Iteration 03] residual : 1.198095e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 04] residual : 1.118032e+02, valid edges : 25, time : 0.000 sec.
[Open3D DEBUG] [Iteration 05] residual : 1.052973e+02, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 06] residual : 1.020715e+02, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 07] residual : 1.012418e+02, valid edges : 25, time : 0.000 sec.
[Open3D DEBUG] [Iteration 08] residual : 1.005109e+02, valid edges : 24, time : 0.000 sec.
[Open3D DEBUG] [Iteration 09] residual : 9.946242e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 10] residual : 9.783629e+01, valid edges : 27, time : 0.000 sec.
[Open3D DEBUG] [Iteration 11] residual : 9.557321e+01, valid edges : 27, time : 0.000 sec.
[Open3D DEBUG] [Iteration 12] residual : 9.349238e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 13] residual : 9.258257e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 14] residual : 9.239178e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 15] residual : 9.236183e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 16] residual : 9.235591e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 17] residual : 9.235404e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 18] residual : 9.235325e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 19] residual : 9.235288e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 20] residual : 9.235269e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.003 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 10 nodes and 35 edges.
[Open3D DEBUG] Line process weight : 7.878500
[Open3D DEBUG] [Initial ] residual : 3.428556e+01, lambda : 2.996407e-02
[Open3D DEBUG] [Iteration 00] residual : 3.217059e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 01] residual : 3.204515e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 02] residual : 3.204092e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 03] residual : 3.204058e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] [Iteration 04] residual : 3.204054e+01, valid edges : 26, time : 0.000 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.001 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7240, RMSE 0.0220
[Open3D DEBUG] Residual : 3.39e-04 (# of elements : 265)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7240, RMSE 0.0219
[Open3D DEBUG] Residual : 3.37e-04 (# of elements : 265)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7240, RMSE 0.0218
[Open3D DEBUG] Residual : 3.38e-04 (# of elements : 265)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7240, RMSE 0.0218
[Open3D DEBUG] Residual : 3.38e-04 (# of elements : 265)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7240, RMSE 0.0218
[Open3D DEBUG] Residual : 3.38e-04 (# of elements : 265)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 1220 points.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 1295 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6656, RMSE 0.0108
[Open3D DEBUG] Residual : 3.29e-04 (# of elements : 812)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6639, RMSE 0.0111
[Open3D DEBUG] Residual : 3.69e-04 (# of elements : 810)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6664, RMSE 0.0112
[Open3D DEBUG] Residual : 3.92e-04 (# of elements : 813)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6664, RMSE 0.0113
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 813)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6680, RMSE 0.0114
[Open3D DEBUG] Residual : 3.80e-04 (# of elements : 815)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6672, RMSE 0.0114
[Open3D DEBUG] Residual : 3.80e-04 (# of elements : 814)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 3921 points.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 4203 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6123, RMSE 0.0065
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 2401)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6200, RMSE 0.0055
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 2431)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6236, RMSE 0.0056
[Open3D DEBUG] Residual : 2.30e-04 (# of elements : 2445)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6218, RMSE 0.0056
[Open3D DEBUG] Residual : 2.32e-04 (# of elements : 2438)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6215, RMSE 0.0056
[Open3D DEBUG] Residual : 2.34e-04 (# of elements : 2437)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6205, RMSE 0.0056
[Open3D DEBUG] Residual : 2.32e-04 (# of elements : 2433)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6208, RMSE 0.0056
[Open3D DEBUG] Residual : 2.31e-04 (# of elements : 2434)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6208, RMSE 0.0056
[Open3D DEBUG] Residual : 2.32e-04 (# of elements : 2434)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6205, RMSE 0.0056
[Open3D DEBUG] Residual : 2.31e-04 (# of elements : 2433)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6208, RMSE 0.0056
[Open3D DEBUG] Residual : 2.32e-04 (# of elements : 2434)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6205, RMSE 0.0056
[Open3D DEBUG] Residual : 2.31e-04 (# of elements : 2433)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6208, RMSE 0.0056
[Open3D DEBUG] Residual : 2.32e-04 (# of elements : 2434)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6205, RMSE 0.0056
[Open3D DEBUG] Residual : 2.31e-04 (# of elements : 2433)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6208, RMSE 0.0056
[Open3D DEBUG] Residual : 2.32e-04 (# of elements : 2434)
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7300, RMSE 0.0241
[Open3D DEBUG] Residual : 5.44e-04 (# of elements : 384)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7281, RMSE 0.0237
[Open3D DEBUG] Residual : 5.39e-04 (# of elements : 383)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7281, RMSE 0.0237
[Open3D DEBUG] Residual : 5.50e-04 (# of elements : 383)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7281, RMSE 0.0237
[Open3D DEBUG] Residual : 5.57e-04 (# of elements : 383)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7281, RMSE 0.0237
[Open3D DEBUG] Residual : 5.54e-04 (# of elements : 383)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.7281, RMSE 0.0237
[Open3D DEBUG] Residual : 5.54e-04 (# of elements : 383)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.7281, RMSE 0.0237
[Open3D DEBUG] Residual : 5.54e-04 (# of elements : 383)
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 1013 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6194, RMSE 0.0120
[Open3D DEBUG] Residual : 3.81e-04 (# of elements : 1149)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6221, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1154)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6248, RMSE 0.0118
[Open3D DEBUG] Residual : 3.20e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6226, RMSE 0.0119
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1155)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6243, RMSE 0.0118
[Open3D DEBUG] Residual : 3.21e-04 (# of elements : 1158)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6226, RMSE 0.0118
[Open3D DEBUG] Residual : 3.05e-04 (# of elements : 1155)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6243, RMSE 0.0118
[Open3D DEBUG] Residual : 3.06e-04 (# of elements : 1158)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 1157)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6248, RMSE 0.0120
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 1159)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6237, RMSE 0.0118
[Open3D DEBUG] Residual : 2.99e-04 (# of elements : 1157)
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 3196 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5547, RMSE 0.0063
[Open3D DEBUG] Residual : 2.90e-04 (# of elements : 3528)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5542, RMSE 0.0063
[Open3D DEBUG] Residual : 2.74e-04 (# of elements : 3525)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5531, RMSE 0.0063
[Open3D DEBUG] Residual : 2.66e-04 (# of elements : 3518)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5544, RMSE 0.0063
[Open3D DEBUG] Residual : 2.71e-04 (# of elements : 3526)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5544, RMSE 0.0063
[Open3D DEBUG] Residual : 2.69e-04 (# of elements : 3526)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5546, RMSE 0.0063
[Open3D DEBUG] Residual : 2.72e-04 (# of elements : 3527)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5546, RMSE 0.0063
[Open3D DEBUG] Residual : 2.70e-04 (# of elements : 3527)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5544, RMSE 0.0063
[Open3D DEBUG] Residual : 2.72e-04 (# of elements : 3526)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5546, RMSE 0.0063
[Open3D DEBUG] Residual : 2.70e-04 (# of elements : 3527)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5544, RMSE 0.0063
[Open3D DEBUG] Residual : 2.72e-04 (# of elements : 3526)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5546, RMSE 0.0063
[Open3D DEBUG] Residual : 2.70e-04 (# of elements : 3527)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5544, RMSE 0.0063
[Open3D DEBUG] Residual : 2.72e-04 (# of elements : 3526)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5546, RMSE 0.0063
[Open3D DEBUG] Residual : 2.70e-04 (# of elements : 3527)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5544, RMSE 0.0063
[Open3D DEBUG] Residual : 2.72e-04 (# of elements : 3526)
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8080, RMSE 0.0284
[Open3D DEBUG] Residual : 9.97e-04 (# of elements : 425)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8099, RMSE 0.0241
[Open3D DEBUG] Residual : 5.22e-04 (# of elements : 426)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8137, RMSE 0.0231
[Open3D DEBUG] Residual : 4.70e-04 (# of elements : 428)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8023, RMSE 0.0224
[Open3D DEBUG] Residual : 4.30e-04 (# of elements : 422)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8023, RMSE 0.0224
[Open3D DEBUG] Residual : 4.28e-04 (# of elements : 422)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.8023, RMSE 0.0224
[Open3D DEBUG] Residual : 4.28e-04 (# of elements : 422)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.8023, RMSE 0.0224
[Open3D DEBUG] Residual : 4.27e-04 (# of elements : 422)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.8023, RMSE 0.0224
[Open3D DEBUG] Residual : 4.27e-04 (# of elements : 422)
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7062, RMSE 0.0119
[Open3D DEBUG] Residual : 3.54e-04 (# of elements : 1310)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7111, RMSE 0.0116
[Open3D DEBUG] Residual : 3.14e-04 (# of elements : 1319)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7111, RMSE 0.0116
[Open3D DEBUG] Residual : 3.20e-04 (# of elements : 1319)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7111, RMSE 0.0116
[Open3D DEBUG] Residual : 3.20e-04 (# of elements : 1319)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7111, RMSE 0.0116
[Open3D DEBUG] Residual : 3.20e-04 (# of elements : 1319)
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6423, RMSE 0.0062
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 4085)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6399, RMSE 0.0060
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 4070)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6368, RMSE 0.0060
[Open3D DEBUG] Residual : 2.55e-04 (# of elements : 4050)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6363, RMSE 0.0060
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 4047)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6371, RMSE 0.0060
[Open3D DEBUG] Residual : 2.45e-04 (# of elements : 4052)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6358, RMSE 0.0060
[Open3D DEBUG] Residual : 2.55e-04 (# of elements : 4044)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6374, RMSE 0.0060
[Open3D DEBUG] Residual : 2.45e-04 (# of elements : 4054)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6365, RMSE 0.0060
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 4048)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6368, RMSE 0.0060
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 4050)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6365, RMSE 0.0060
[Open3D DEBUG] Residual : 2.46e-04 (# of elements : 4048)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6357, RMSE 0.0060
[Open3D DEBUG] Residual : 2.55e-04 (# of elements : 4043)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6371, RMSE 0.0060
[Open3D DEBUG] Residual : 2.46e-04 (# of elements : 4052)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6368, RMSE 0.0060
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 4050)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6371, RMSE 0.0060
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 4052)
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4620, RMSE 0.0255
[Open3D DEBUG] Residual : 7.68e-04 (# of elements : 243)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4772, RMSE 0.0267
[Open3D DEBUG] Residual : 5.51e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.68e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.4772, RMSE 0.0257
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 251)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.4753, RMSE 0.0265
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 250)
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3817, RMSE 0.0132
[Open3D DEBUG] Residual : 3.02e-04 (# of elements : 708)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3774, RMSE 0.0132
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3774, RMSE 0.0132
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3763, RMSE 0.0131
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3768, RMSE 0.0131
[Open3D DEBUG] Residual : 2.86e-04 (# of elements : 699)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.87e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.3774, RMSE 0.0131
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 700)
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2956, RMSE 0.0068
[Open3D DEBUG] Residual : 4.12e-04 (# of elements : 1880)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3003, RMSE 0.0068
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 1910)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3025, RMSE 0.0068
[Open3D DEBUG] Residual : 3.69e-04 (# of elements : 1924)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3027, RMSE 0.0068
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 1925)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3017, RMSE 0.0068
[Open3D DEBUG] Residual : 3.68e-04 (# of elements : 1919)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3024, RMSE 0.0068
[Open3D DEBUG] Residual : 3.68e-04 (# of elements : 1923)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3027, RMSE 0.0068
[Open3D DEBUG] Residual : 3.71e-04 (# of elements : 1925)
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7978, RMSE 0.0236
[Open3D DEBUG] Residual : 5.72e-04 (# of elements : 292)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8033, RMSE 0.0203
[Open3D DEBUG] Residual : 3.68e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8005, RMSE 0.0202
[Open3D DEBUG] Residual : 3.74e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8005, RMSE 0.0202
[Open3D DEBUG] Residual : 3.69e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.69e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.65e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.69e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 293)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.8005, RMSE 0.0203
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 293)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 1220 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8000, RMSE 0.0111
[Open3D DEBUG] Residual : 3.27e-04 (# of elements : 976)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8016, RMSE 0.0106
[Open3D DEBUG] Residual : 3.42e-04 (# of elements : 978)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8016, RMSE 0.0106
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 978)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8016, RMSE 0.0106
[Open3D DEBUG] Residual : 3.44e-04 (# of elements : 978)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8016, RMSE 0.0106
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 978)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.8016, RMSE 0.0106
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 978)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 3921 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7470, RMSE 0.0062
[Open3D DEBUG] Residual : 2.45e-04 (# of elements : 2929)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7465, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2927)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7473, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2930)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7478, RMSE 0.0065
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 2932)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7478, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2932)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.7470, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2929)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.7475, RMSE 0.0065
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 2931)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.7478, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2932)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.7470, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2929)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.7480, RMSE 0.0065
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 2933)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.7478, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2932)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.7470, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2929)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.7478, RMSE 0.0065
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 2932)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.7478, RMSE 0.0065
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 2932)
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7213, RMSE 0.0291
[Open3D DEBUG] Residual : 8.04e-04 (# of elements : 264)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7213, RMSE 0.0209
[Open3D DEBUG] Residual : 3.19e-04 (# of elements : 264)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7131, RMSE 0.0200
[Open3D DEBUG] Residual : 2.91e-04 (# of elements : 261)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7131, RMSE 0.0200
[Open3D DEBUG] Residual : 2.90e-04 (# of elements : 261)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7131, RMSE 0.0200
[Open3D DEBUG] Residual : 2.90e-04 (# of elements : 261)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 1220 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 1013 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6803, RMSE 0.0114
[Open3D DEBUG] Residual : 2.19e-04 (# of elements : 830)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6852, RMSE 0.0114
[Open3D DEBUG] Residual : 2.03e-04 (# of elements : 836)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6836, RMSE 0.0115
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 834)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6828, RMSE 0.0115
[Open3D DEBUG] Residual : 2.00e-04 (# of elements : 833)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6811, RMSE 0.0114
[Open3D DEBUG] Residual : 2.00e-04 (# of elements : 831)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 3921 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 3196 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6162, RMSE 0.0061
[Open3D DEBUG] Residual : 1.78e-04 (# of elements : 2416)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6169, RMSE 0.0059
[Open3D DEBUG] Residual : 1.62e-04 (# of elements : 2419)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.67e-04 (# of elements : 2422)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.66e-04 (# of elements : 2422)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.66e-04 (# of elements : 2422)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.63e-04 (# of elements : 2422)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6182, RMSE 0.0059
[Open3D DEBUG] Residual : 1.67e-04 (# of elements : 2424)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6172, RMSE 0.0059
[Open3D DEBUG] Residual : 1.63e-04 (# of elements : 2420)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.66e-04 (# of elements : 2422)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.63e-04 (# of elements : 2422)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6182, RMSE 0.0059
[Open3D DEBUG] Residual : 1.67e-04 (# of elements : 2424)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6172, RMSE 0.0059
[Open3D DEBUG] Residual : 1.63e-04 (# of elements : 2420)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.66e-04 (# of elements : 2422)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6177, RMSE 0.0059
[Open3D DEBUG] Residual : 1.63e-04 (# of elements : 2422)
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8825, RMSE 0.0279
[Open3D DEBUG] Residual : 6.86e-04 (# of elements : 323)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8743, RMSE 0.0184
[Open3D DEBUG] Residual : 2.56e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8716, RMSE 0.0178
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8716, RMSE 0.0178
[Open3D DEBUG] Residual : 2.19e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8716, RMSE 0.0178
[Open3D DEBUG] Residual : 2.25e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.24e-04 (# of elements : 319)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.8716, RMSE 0.0179
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 319)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 1220 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8738, RMSE 0.0102
[Open3D DEBUG] Residual : 1.83e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.73e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.83e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.8746, RMSE 0.0100
[Open3D DEBUG] Residual : 1.84e-04 (# of elements : 1067)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.8738, RMSE 0.0100
[Open3D DEBUG] Residual : 1.71e-04 (# of elements : 1066)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 3921 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8261, RMSE 0.0055
[Open3D DEBUG] Residual : 1.46e-04 (# of elements : 3239)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8225, RMSE 0.0055
[Open3D DEBUG] Residual : 1.41e-04 (# of elements : 3225)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8215, RMSE 0.0055
[Open3D DEBUG] Residual : 1.41e-04 (# of elements : 3221)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8220, RMSE 0.0055
[Open3D DEBUG] Residual : 1.41e-04 (# of elements : 3223)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8217, RMSE 0.0055
[Open3D DEBUG] Residual : 1.41e-04 (# of elements : 3222)
[Open3D DEBUG] Read geometry::PointCloud: 19002 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 366 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6967, RMSE 0.0267
[Open3D DEBUG] Residual : 7.09e-04 (# of elements : 255)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7678, RMSE 0.0251
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7705, RMSE 0.0252
[Open3D DEBUG] Residual : 4.88e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7705, RMSE 0.0253
[Open3D DEBUG] Residual : 4.86e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7705, RMSE 0.0253
[Open3D DEBUG] Residual : 4.89e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.7705, RMSE 0.0254
[Open3D DEBUG] Residual : 4.91e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.7678, RMSE 0.0252
[Open3D DEBUG] Residual : 4.86e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.84e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.7678, RMSE 0.0253
[Open3D DEBUG] Residual : 4.85e-04 (# of elements : 281)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 1220 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6705, RMSE 0.0124
[Open3D DEBUG] Residual : 2.94e-04 (# of elements : 818)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6770, RMSE 0.0119
[Open3D DEBUG] Residual : 2.94e-04 (# of elements : 826)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.94e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6762, RMSE 0.0119
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 825)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6754, RMSE 0.0119
[Open3D DEBUG] Residual : 2.95e-04 (# of elements : 824)
[Open3D DEBUG] Pointcloud down sampled from 19002 points to 3921 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5728, RMSE 0.0064
[Open3D DEBUG] Residual : 2.67e-04 (# of elements : 2246)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5815, RMSE 0.0061
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 2280)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5830, RMSE 0.0061
[Open3D DEBUG] Residual : 2.54e-04 (# of elements : 2286)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5817, RMSE 0.0061
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 2281)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5815, RMSE 0.0061
[Open3D DEBUG] Residual : 2.41e-04 (# of elements : 2280)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5810, RMSE 0.0060
[Open3D DEBUG] Residual : 2.49e-04 (# of elements : 2278)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5812, RMSE 0.0061
[Open3D DEBUG] Residual : 2.42e-04 (# of elements : 2279)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5812, RMSE 0.0061
[Open3D DEBUG] Residual : 2.49e-04 (# of elements : 2279)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5817, RMSE 0.0061
[Open3D DEBUG] Residual : 2.52e-04 (# of elements : 2281)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5810, RMSE 0.0060
[Open3D DEBUG] Residual : 2.41e-04 (# of elements : 2278)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5815, RMSE 0.0061
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 2280)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5807, RMSE 0.0061
[Open3D DEBUG] Residual : 2.42e-04 (# of elements : 2277)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5812, RMSE 0.0061
[Open3D DEBUG] Residual : 2.49e-04 (# of elements : 2279)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5810, RMSE 0.0061
[Open3D DEBUG] Residual : 2.42e-04 (# of elements : 2278)
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6324, RMSE 0.0282
[Open3D DEBUG] Residual : 7.92e-04 (# of elements : 203)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6604, RMSE 0.0226
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6542, RMSE 0.0219
[Open3D DEBUG] Residual : 4.14e-04 (# of elements : 210)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6542, RMSE 0.0222
[Open3D DEBUG] Residual : 4.12e-04 (# of elements : 210)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6573, RMSE 0.0222
[Open3D DEBUG] Residual : 4.20e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.6604, RMSE 0.0224
[Open3D DEBUG] Residual : 4.18e-04 (# of elements : 212)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.6573, RMSE 0.0224
[Open3D DEBUG] Residual : 4.16e-04 (# of elements : 211)
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 1013 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6051, RMSE 0.0121
[Open3D DEBUG] Residual : 3.39e-04 (# of elements : 613)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5933, RMSE 0.0116
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 601)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 604)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.98e-04 (# of elements : 604)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 604)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 604)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 604)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 604)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 604)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.96e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.5953, RMSE 0.0117
[Open3D DEBUG] Residual : 2.84e-04 (# of elements : 603)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.5962, RMSE 0.0117
[Open3D DEBUG] Residual : 2.97e-04 (# of elements : 604)
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 3196 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5210, RMSE 0.0063
[Open3D DEBUG] Residual : 2.91e-04 (# of elements : 1665)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5278, RMSE 0.0061
[Open3D DEBUG] Residual : 2.72e-04 (# of elements : 1687)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5269, RMSE 0.0062
[Open3D DEBUG] Residual : 2.71e-04 (# of elements : 1684)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5266, RMSE 0.0062
[Open3D DEBUG] Residual : 2.72e-04 (# of elements : 1683)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5269, RMSE 0.0062
[Open3D DEBUG] Residual : 2.72e-04 (# of
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
[[-0.74939248 0.31193991 -0.58404144 0.1008101 ]
[ 0.20578355 -0.72866192 -0.65322656 -0.12298188]
[-0.62933619 -0.60970919 0.48186166 -0.59327385]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
[[ 0.99921029 -0.01988376 0.034401 0.03460953]
[ 0.01844827 0.99896593 0.04155393 0.09522701]
[-0.03519168 -0.04088647 0.99854386 0.00388203]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
[[ 0.95640976 -0.25711732 0.13845958 0.08096181]
[ 0.25653779 0.96627633 0.02232517 0.01174372]
[-0.1395304 0.01416811 0.99011642 0.00691408]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
[[ 0.96116576 -0.24969195 0.1175343 0.06256369]
[ 0.24505633 0.96808092 0.05259961 -0.04028048]
[-0.12691641 -0.02175442 0.99167483 0.0078566 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[ 0.90332066 -0.39371335 0.17029851 0.18567828]
[ 0.35814195 0.91071071 0.20576771 -0.00126718]
[-0.23610617 -0.12488318 0.96366907 -0.02167187]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.9406858 0.23166201 -0.24787688 -0.16523839]
[-0.16109479 0.94796652 0.27460509 0.16777769]
[ 0.29859454 -0.21838543 0.92905818 -0.0011518 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
[[ 0.95048826 0.30878669 -0.03496926 -0.05851273]
[-0.14474251 0.53947263 0.82946904 -0.26379807]
[ 0.27499396 -0.78333905 0.55745696 0.31502204]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
[[-0.95388496 0.21648882 -0.20793287 0.30207616]
[-0.23754774 -0.96790801 0.08200702 -0.33118533]
[-0.18350628 0.12761925 0.97469932 0.3745237 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
[[ 0.94085781 0.18927849 -0.28099865 0.16179747]
[ 0.06651776 0.71004955 0.70100287 -0.35765887]
[ 0.33220773 -0.67823542 0.65546528 0.31913275]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[ 0.84751581 0.32783998 -0.41741813 0.18199164]
[ 0.17031778 0.57686981 0.79888239 -0.30578951]
[ 0.5027015 -0.74815919 0.43306931 0.29243652]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_005.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
Using RGBD odometry
voxel_size 0.050000
[[-0.84327223 0.16913044 -0.51018314 -0.20118092]
[ 0.1655638 -0.82130991 -0.54592917 -0.44187725]
[-0.51135171 -0.54483477 0.66458596 0.3660831 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_005.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
[[-0.87424425 0.48129918 -0.06362469 0.13534087]
[-0.33145349 -0.6874779 -0.64615225 -0.63315874]
[-0.35473311 -0.54380626 0.76055189 0.39250839]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_005.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
[[-0.87251889 0.31604135 -0.37259717 0.00346088]
[ 0.08059107 -0.65906902 -0.74775203 -0.5445373 ]
[-0.48188782 -0.68245578 0.54958006 0.29038972]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_005.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[-0.73063259 0.61396615 0.29869982 0.13794764]
[-0.56242535 -0.29316244 -0.77313227 -0.53823828]
[-0.38710947 -0.73287198 0.55950417 0.28518714]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_006.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.97635684 -0.20740051 0.06092911 0.05219365]
[ 0.21134242 0.97507686 -0.06752406 -0.06623933]
[-0.04540604 0.07880448 0.99585548 -0.00379162]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_006.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
[[ 0.97013811 -0.24252657 0.00359219 0.04175563]
[ 0.24208449 0.96723716 -0.07646815 -0.07344423]
[ 0.01507106 0.07505428 0.99706555 0.0076169 ]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_006.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[ 0.91943092 -0.35566507 0.16777707 0.16911166]
[ 0.35578443 0.93407391 0.03038709 -0.03313997]
[-0.16752381 0.03175364 0.98535652 -0.00389704]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_007.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.99981197 0.00899813 -0.01717711 -0.00535709]
[-0.00873224 0.99984186 0.01549179 -0.00783696]
[ 0.01731379 -0.01533888 0.99973244 0.00183915]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_007.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
[[ 0.99538208 -0.09083455 -0.03104181 0.15749343]
[ 0.0937338 0.98947321 0.11025763 0.00413429]
[ 0.02069984 -0.11265813 0.99341817 0.00466657]
[ 0. 0. 0. 1. ]]
reading dataset/realsense/fragments/fragment_008.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
Using RGBD odometry
voxel_size 0.050000
[[ 0.97970758 -0.15402418 0.12825603 0.08177017]
[ 0.13789831 0.98235321 0.12635757 0.00324076]
[-0.14545484 -0.10610718 0.98365856 -0.0080231 ]
[ 0. 0. 0. 1. ]]
refine rough registration of fragments.
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_001.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_006.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_006.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_006.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_000.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_007.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_001.ply ... elements : 1684)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5275, RMSE 0.0062
[Open3D DEBUG] Residual : 2.71e-04 (# of elements : 1686)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5272, RMSE 0.0062
[Open3D DEBUG] Residual : 2.71e-04 (# of elements : 1685)
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.23e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.8889, RMSE 0.0194
[Open3D DEBUG] Residual : 2.22e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.8889, RMSE 0.0191
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 352)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 1295 points.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 2366 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8803, RMSE 0.0111
[Open3D DEBUG] Residual : 2.55e-04 (# of elements : 1140)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8795, RMSE 0.0113
[Open3D DEBUG] Residual : 2.52e-04 (# of elements : 1139)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8772, RMSE 0.0114
[Open3D DEBUG] Residual : 2.50e-04 (# of elements : 1136)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8764, RMSE 0.0114
[Open3D DEBUG] Residual : 2.49e-04 (# of elements : 1135)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8764, RMSE 0.0114
[Open3D DEBUG] Residual : 2.49e-04 (# of elements : 1135)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 4203 points.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 8369 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.8432, RMSE 0.0063
[Open3D DEBUG] Residual : 2.46e-04 (# of elements : 3544)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.8306, RMSE 0.0067
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3491)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.8225, RMSE 0.0066
[Open3D DEBUG] Residual : 2.28e-04 (# of elements : 3457)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.8237, RMSE 0.0066
[Open3D DEBUG] Residual : 2.30e-04 (# of elements : 3462)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.8232, RMSE 0.0066
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3460)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.8244, RMSE 0.0066
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3465)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.8230, RMSE 0.0066
[Open3D DEBUG] Residual : 2.30e-04 (# of elements : 3459)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.8227, RMSE 0.0066
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3458)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.8242, RMSE 0.0066
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3464)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.8230, RMSE 0.0066
[Open3D DEBUG] Residual : 2.30e-04 (# of elements : 3459)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.8227, RMSE 0.0066
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3458)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.8242, RMSE 0.0066
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3464)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.8230, RMSE 0.0066
[Open3D DEBUG] Residual : 2.30e-04 (# of elements : 3459)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.8227, RMSE 0.0066
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 3458)
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.9969, RMSE 0.0182
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.9969, RMSE 0.0172
[Open3D DEBUG] Residual : 1.82e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.9969, RMSE 0.0175
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.9969, RMSE 0.0176
[Open3D DEBUG] Residual : 1.88e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.9969, RMSE 0.0177
[Open3D DEBUG] Residual : 1.90e-04 (# of elements : 320)
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 1013 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.9990, RMSE 0.0104
[Open3D DEBUG] Residual : 1.55e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.9990, RMSE 0.0087
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.17e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.9990, RMSE 0.0091
[Open3D DEBUG] Residual : 1.20e-04 (# of elements : 1012)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.9990, RMSE 0.0090
[Open3D DEBUG] Residual : 1.18e-04 (# of elements : 1012)
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 3196 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.9934, RMSE 0.0052
[Open3D DEBUG] Residual : 1.01e-04 (# of elements : 3175)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.9934, RMSE 0.0051
[Open3D DEBUG] Residual : 1.02e-04 (# of elements : 3175)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.9931, RMSE 0.0051
[Open3D DEBUG] Residual : 1.01e-04 (# of elements : 3174)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.9931, RMSE 0.0051
[Open3D DEBUG] Residual : 1.01e-04 (# of elements : 3174)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.9931, RMSE 0.0051
[Open3D DEBUG] Residual : 1.01e-04 (# of elements : 3174)
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7424, RMSE 0.0246
[Open3D DEBUG] Residual : 4.90e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7500, RMSE 0.0225
[Open3D DEBUG] Residual : 3.72e-04 (# of elements : 297)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7449, RMSE 0.0216
[Open3D DEBUG] Residual : 3.45e-04 (# of elements : 295)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7424, RMSE 0.0214
[Open3D DEBUG] Residual : 3.40e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.41e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.44e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.7424, RMSE 0.0215
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 294)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 1295 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 2207 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7073, RMSE 0.0115
[Open3D DEBUG] Residual : 2.81e-04 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7058, RMSE 0.0112
[Open3D DEBUG] Residual : 2.57e-04 (# of elements : 914)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7073, RMSE 0.0112
[Open3D DEBUG] Residual : 2.56e-04 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7058, RMSE 0.0111
[Open3D DEBUG] Residual : 2.57e-04 (# of elements : 914)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7066, RMSE 0.0111
[Open3D DEBUG] Residual : 2.57e-04 (# of elements : 915)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.7066, RMSE 0.0111
[Open3D DEBUG] Residual : 2.57e-04 (# of elements : 915)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.7066, RMSE 0.0111
[Open3D DEBUG] Residual : 2.57e-04 (# of elements : 915)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.7066, RMSE 0.0111
[Open3D DEBUG] Residual : 2.57e-04 (# of elements : 915)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 4203 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 7191 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6602, RMSE 0.0064
[Open3D DEBUG] Residual : 2.37e-04 (# of elements : 2775)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6586, RMSE 0.0062
[Open3D DEBUG] Residual : 2.21e-04 (# of elements : 2768)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6586, RMSE 0.0061
[Open3D DEBUG] Residual : 2.13e-04 (# of elements : 2768)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6579, RMSE 0.0061
[Open3D DEBUG] Residual : 2.13e-04 (# of elements : 2765)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6579, RMSE 0.0061
[Open3D DEBUG] Residual : 2.12e-04 (# of elements : 2765)
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6944, RMSE 0.0217
[Open3D DEBUG] Residual : 3.43e-04 (# of elements : 275)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6869, RMSE 0.0194
[Open3D DEBUG] Residual : 2.91e-04 (# of elements : 272)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6869, RMSE 0.0195
[Open3D DEBUG] Residual : 2.91e-04 (# of elements : 272)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6869, RMSE 0.0194
[Open3D DEBUG] Residual : 2.91e-04 (# of elements : 272)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6869, RMSE 0.0194
[Open3D DEBUG] Residual : 2.91e-04 (# of elements : 272)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 1295 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6656, RMSE 0.0110
[Open3D DEBUG] Residual : 3.28e-04 (# of elements : 862)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6695, RMSE 0.0115
[Open3D DEBUG] Residual : 3.42e-04 (# of elements : 867)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6695, RMSE 0.0116
[Open3D DEBUG] Residual : 3.39e-04 (# of elements : 867)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6695, RMSE 0.0116
[Open3D DEBUG] Residual : 3.46e-04 (# of elements : 867)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6703, RMSE 0.0117
[Open3D DEBUG] Residual : 3.59e-04 (# of elements : 868)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6710, RMSE 0.0117
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 869)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6718, RMSE 0.0118
[Open3D DEBUG] Residual : 3.58e-04 (# of elements : 870)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6726, RMSE 0.0118
[Open3D DEBUG] Residual : 3.57e-04 (# of elements : 871)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6726, RMSE 0.0118
[Open3D DEBUG] Residual : 3.57e-04 (# of elements : 871)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 4203 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6005, RMSE 0.0067
[Open3D DEBUG] Residual : 2.53e-04 (# of elements : 2524)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5924, RMSE 0.0067
[Open3D DEBUG] Residual : 2.45e-04 (# of elements : 2490)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5884, RMSE 0.0066
[Open3D DEBUG] Residual : 2.50e-04 (# of elements : 2473)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5822, RMSE 0.0065
[Open3D DEBUG] Residual : 2.53e-04 (# of elements : 2447)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5798, RMSE 0.0066
[Open3D DEBUG] Residual : 2.54e-04 (# of elements : 2437)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5810, RMSE 0.0066
[Open3D DEBUG] Residual : 2.56e-04 (# of elements : 2442)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5779, RMSE 0.0066
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 2429)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5767, RMSE 0.0066
[Open3D DEBUG] Residual : 2.60e-04 (# of elements : 2424)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5741, RMSE 0.0066
[Open3D DEBUG] Residual : 2.62e-04 (# of elements : 2413)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5715, RMSE 0.0066
[Open3D DEBUG] Residual : 2.59e-04 (# of elements : 2402)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5724, RMSE 0.0066
[Open3D DEBUG] Residual : 2.61e-04 (# of elements : 2406)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5715, RMSE 0.0066
[Open3D DEBUG] Residual : 2.58e-04 (# of elements : 2402)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5732, RMSE 0.0066
[Open3D DEBUG] Residual : 2.62e-04 (# of elements : 2409)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5724, RMSE 0.0066
[Open3D DEBUG] Residual : 2.62e-04 (# of elements : 2406)
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5177, RMSE 0.0271
[Open3D DEBUG] Residual : 6.97e-04 (# of elements : 205)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5177, RMSE 0.0207
[Open3D DEBUG] Residual : 4.70e-04 (# of elements : 205)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5177, RMSE 0.0203
[Open3D DEBUG] Residual : 4.66e-04 (# of elements : 205)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5177, RMSE 0.0204
[Open3D DEBUG] Residual : 4.60e-04 (# of elements : 205)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5177, RMSE 0.0204
[Open3D DEBUG] Residual : 4.47e-04 (# of elements : 205)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5177, RMSE 0.0203
[Open3D DEBUG] Residual : 4.64e-04 (# of elements : 205)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5177, RMSE 0.0204
[Open3D DEBUG] Residual : 4.48e-04 (# of elements : 205)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 1295 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 1013 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4525, RMSE 0.0121
[Open3D DEBUG] Residual : 3.32e-04 (# of elements : 586)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4548, RMSE 0.0112
[Open3D DEBUG] Residual : 4.00e-04 (# of elements : 589)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4548, RMSE 0.0115
[Open3D DEBUG] Residual : 3.64e-04 (# of elements : 589)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4548, RMSE 0.0115
[Open3D DEBUG] Residual : 3.48e-04 (# of elements : 589)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4548, RMSE 0.0114
[Open3D DEBUG] Residual : 3.38e-04 (# of elements : 589)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4556, RMSE 0.0114
[Open3D DEBUG] Residual : 3.42e-04 (# of elements : 590)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4548, RMSE 0.0114
[Open3D DEBUG] Residual : 3.42e-04 (# of elements : 589)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4556, RMSE 0.0114
[Open3D DEBUG] Residual : 3.42e-04 (# of elements : 590)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 4203 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 3196 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4000, RMSE 0.0068
[Open3D DEBUG] Residual : 2.44e-04 (# of elements : 1681)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4064, RMSE 0.0062
[Open3D DEBUG] Residual : 2.16e-04 (# of elements : 1708)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4052, RMSE 0.0062
[Open3D DEBUG] Residual : 2.18e-04 (# of elements : 1703)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4052, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1703)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4047, RMSE 0.0062
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 1701)
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6010, RMSE 0.0272
[Open3D DEBUG] Residual : 6.26e-04 (# of elements : 238)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6237, RMSE 0.0209
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 247)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6237, RMSE 0.0207
[Open3D DEBUG] Residual : 2.77e-04 (# of elements : 247)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6263, RMSE 0.0209
[Open3D DEBUG] Residual : 2.53e-04 (# of elements : 248)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6263, RMSE 0.0201
[Open3D DEBUG] Residual : 2.64e-04 (# of elements : 248)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6263, RMSE 0.0205
[Open3D DEBUG] Residual : 2.62e-04 (# of elements : 248)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6263, RMSE 0.0204
[Open3D DEBUG] Residual : 2.62e-04 (# of elements : 248)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6263, RMSE 0.0204
[Open3D DEBUG] Residual : 2.62e-04 (# of elements : 248)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 1295 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5745, RMSE 0.0113
[Open3D DEBUG] Residual : 2.33e-04 (# of elements : 744)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5699, RMSE 0.0113
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 738)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.41e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.36e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5714, RMSE 0.0114
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 740)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5699, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 738)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.5699, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 738)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.5699, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 738)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.5699, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 738)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 739)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.5699, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 738)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.5722, RMSE 0.0114
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 741)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.5707, RMSE 0.0113
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 739)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 4203 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5356, RMSE 0.0058
[Open3D DEBUG] Residual : 1.92e-04 (# of elements : 2251)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5403, RMSE 0.0057
[Open3D DEBUG] Residual : 2.05e-04 (# of elements : 2271)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5420, RMSE 0.0058
[Open3D DEBUG] Residual : 2.02e-04 (# of elements : 2278)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5410, RMSE 0.0058
[Open3D DEBUG] Residual : 2.04e-04 (# of elements : 2274)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5408, RMSE 0.0058
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 2273)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5415, RMSE 0.0058
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 2276)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5413, RMSE 0.0058
[Open3D DEBUG] Residual : 2.03e-04 (# of elements : 2275)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5403, RMSE 0.0058
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 2271)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5413, RMSE 0.0058
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 2275)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5415, RMSE 0.0058
[Open3D DEBUG] Residual : 2.00e-04 (# of elements : 2276)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5415, RMSE 0.0058
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 2276)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5413, RMSE 0.0058
[Open3D DEBUG] Residual : 2.02e-04 (# of elements : 2275)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5408, RMSE 0.0058
[Open3D DEBUG] Residual : 2.01e-04 (# of elements : 2273)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5410, RMSE 0.0058
[Open3D DEBUG] Residual : 2.02e-04 (# of elements : 2274)
[Open3D DEBUG] Read geometry::PointCloud: 19128 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 396 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3788, RMSE 0.0275
[Open3D DEBUG] Residual : 5.65e-04 (# of elements : 150)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4040, RMSE 0.0251
[Open3D DEBUG] Residual : 4.54e-04 (# of elements : 160)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3914, RMSE 0.0212
[Open3D DEBUG] Residual : 3.50e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3914, RMSE 0.0209
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3914, RMSE 0.0213
[Open3D DEBUG] Residual : 3.55e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3914, RMSE 0.0209
[Open3D DEBUG] Residual : 3.53e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3914, RMSE 0.0214
[Open3D DEBUG] Residual : 3.59e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3914, RMSE 0.0208
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3914, RMSE 0.0214
[Open3D DEBUG] Residual : 3.60e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3939, RMSE 0.0212
[Open3D DEBUG] Residual : 3.62e-04 (# of elements : 156)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3939, RMSE 0.0218
[Open3D DEBUG] Residual : 3.67e-04 (# of elements : 156)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3914, RMSE 0.0209
[Open3D DEBUG] Residual : 3.28e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.3914, RMSE 0.0207
[Open3D DEBUG] Residual : 3.35e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.3914, RMSE 0.0216
[Open3D DEBUG] Residual : 3.56e-04 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.3914, RMSE 0.0215
[Open3D DEBUG] Residual : 3.30e-04 (# of elements : 155)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 1295 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 3.13e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3336, RMSE 0.0115
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 432)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3336, RMSE 0.0114
[Open3D DEBUG] Residual : 2.51e-04 (# of elements : 432)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3344, RMSE 0.0116
[Open3D DEBUG] Residual : 2.50e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3351, RMSE 0.0117
[Open3D DEBUG] Residual : 2.49e-04 (# of elements : 434)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3336, RMSE 0.0116
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 432)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3344, RMSE 0.0114
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.3344, RMSE 0.0117
[Open3D DEBUG] Residual : 2.38e-04 (# of elements : 433)
[Open3D DEBUG] Pointcloud down sampled from 19128 points to 4203 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2976, RMSE 0.0060
[Open3D DEBUG] Residual : 2.04e-04 (# of elements : 1251)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2991, RMSE 0.0060
[Open3D DEBUG] Residual : 1.98e-04 (# of elements : 1257)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2988, RMSE 0.0062
[Open3D DEBUG] Residual : 1.92e-04 (# of elements : 1256)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3000, RMSE 0.0063
[Open3D DEBUG] Residual : 1.93e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2995, RMSE 0.0062
[Open3D DEBUG] Residual : 1.92e-04 (# of elements : 1259)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3000, RMSE 0.0063
[Open3D DEBUG] Residual : 1.93e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2998, RMSE 0.0062
[Open3D DEBUG] Residual : 1.92e-04 (# of elements : 1260)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3000, RMSE 0.0063
[Open3D DEBUG] Residual : 1.93e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3000, RMSE 0.0062
[Open3D DEBUG] Residual : 1.91e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3000, RMSE 0.0063
[Open3D DEBUG] Residual : 1.93e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3000, RMSE 0.0062
[Open3D DEBUG] Residual : 1.91e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3000, RMSE 0.0063
[Open3D DEBUG] Residual : 1.92e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3000, RMSE 0.0063
[Open3D DEBUG] Residual : 1.93e-04 (# of elements : 1261)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3000, RMSE 0.0062
[Open3D DEBUG] Residual : 1.91e-04 (# of elements : 1261)
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.7061, RMSE 0.0217
[Open3D DEBUG] Residual : 5.88e-04 (# of elements : 483)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.7091, RMSE 0.0217
[Open3D DEBUG] Residual : 6.28e-04 (# of elements : 485)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.7105, RMSE 0.0218
[Open3D DEBUG] Residual : 6.27e-04 (# of elements : 486)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.7105, RMSE 0.0218
[Open3D DEBUG] Residual : 6.26e-04 (# of elements : 486)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.7105, RMSE 0.0218
[Open3D DEBUG] Residual : 6.26e-04 (# of elements : 486)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.7105, RMSE 0.0218
[Open3D DEBUG] Residual : 6.26e-04 (# of elements : 486)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 2366 points.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 2886 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6678, RMSE 0.0122
[Open3D DEBUG] Residual : 5.26e-04 (# of elements : 1580)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6665, RMSE 0.0124
[Open3D DEBUG] Residual : 4.95e-04 (# of elements : 1577)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6644, RMSE 0.0124
[Open3D DEBUG] Residual : 4.90e-04 (# of elements : 1572)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6653, RMSE 0.0125
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1574)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.80e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6657, RMSE 0.0126
[Open3D DEBUG] Residual : 4.80e-04 (# of elements : 1575)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 1576)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6661, RMSE 0.0126
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 1576)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 8369 points.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 9882 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5704, RMSE 0.0075
[Open3D DEBUG] Residual : 4.06e-04 (# of elements : 4774)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5690, RMSE 0.0071
[Open3D DEBUG] Residual : 3.72e-04 (# of elements : 4762)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5678, RMSE 0.0071
[Open3D DEBUG] Residual : 3.70e-04 (# of elements : 4752)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5676, RMSE 0.0072
[Open3D DEBUG] Residual : 3.69e-04 (# of elements : 4750)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5677, RMSE 0.0072
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 4751)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5670, RMSE 0.0072
[Open3D DEBUG] Residual : 3.60e-04 (# of elements : 4745)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5664, RMSE 0.0072
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 4740)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5663, RMSE 0.0072
[Open3D DEBUG] Residual : 3.60e-04 (# of elements : 4739)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5667, RMSE 0.0072
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 4743)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5663, RMSE 0.0072
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 4739)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5663, RMSE 0.0072
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 4739)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5666, RMSE 0.0072
[Open3D DEBUG] Residual : 3.59e-04 (# of elements : 4742)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5661, RMSE 0.0072
[Open3D DEBUG] Residual : 3.60e-04 (# of elements : 4738)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5663, RMSE 0.0072
[Open3D DEBUG] Residual : 3.60e-04 (# of elements : 4739)
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5336, RMSE 0.0269
[Open3D DEBUG] Residual : 8.62e-04 (# of elements : 365)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5673, RMSE 0.0234
[Open3D DEBUG] Residual : 6.35e-04 (# of elements : 388)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5658, RMSE 0.0235
[Open3D DEBUG] Residual : 6.41e-04 (# of elements : 387)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5687, RMSE 0.0240
[Open3D DEBUG] Residual : 6.70e-04 (# of elements : 389)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5673, RMSE 0.0239
[Open3D DEBUG] Residual : 6.61e-04 (# of elements : 388)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5687, RMSE 0.0240
[Open3D DEBUG] Residual : 6.59e-04 (# of elements : 389)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5687, RMSE 0.0240
[Open3D DEBUG] Residual : 6.59e-04 (# of elements : 389)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 2366 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 2207 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4962, RMSE 0.0127
[Open3D DEBUG] Residual : 5.32e-04 (# of elements : 1174)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5042, RMSE 0.0119
[Open3D DEBUG] Residual : 5.71e-04 (# of elements : 1193)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5046, RMSE 0.0119
[Open3D DEBUG] Residual : 5.97e-04 (# of elements : 1194)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5063, RMSE 0.0119
[Open3D DEBUG] Residual : 6.09e-04 (# of elements : 1198)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5059, RMSE 0.0119
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 1197)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5101, RMSE 0.0120
[Open3D DEBUG] Residual : 5.73e-04 (# of elements : 1207)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5097, RMSE 0.0120
[Open3D DEBUG] Residual : 5.75e-04 (# of elements : 1206)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5097, RMSE 0.0120
[Open3D DEBUG] Residual : 5.74e-04 (# of elements : 1206)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5097, RMSE 0.0120
[Open3D DEBUG] Residual : 5.74e-04 (# of elements : 1206)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5101, RMSE 0.0120
[Open3D DEBUG] Residual : 5.74e-04 (# of elements : 1207)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 8369 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 7191 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4545, RMSE 0.0066
[Open3D DEBUG] Residual : 5.26e-04 (# of elements : 3804)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4505, RMSE 0.0065
[Open3D DEBUG] Residual : 4.66e-04 (# of elements : 3770)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4478, RMSE 0.0065
[Open3D DEBUG] Residual : 4.56e-04 (# of elements : 3748)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4478, RMSE 0.0065
[Open3D DEBUG] Residual : 4.52e-04 (# of elements : 3748)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4480, RMSE 0.0065
[Open3D DEBUG] Residual : 4.53e-04 (# of elements : 3749)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4478, RMSE 0.0065
[Open3D DEBUG] Residual : 4.53e-04 (# of elements : 3748)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4476, RMSE 0.0065
[Open3D DEBUG] Residual : 4.53e-04 (# of elements : 3746)
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6535, RMSE 0.0228
[Open3D DEBUG] Residual : 4.35e-04 (# of elements : 447)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6491, RMSE 0.0211
[Open3D DEBUG] Residual : 3.29e-04 (# of elements : 444)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6462, RMSE 0.0209
[Open3D DEBUG] Residual : 3.17e-04 (# of elements : 442)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6447, RMSE 0.0207
[Open3D DEBUG] Residual : 3.15e-04 (# of elements : 441)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.6433, RMSE 0.0206
[Open3D DEBUG] Residual : 3.08e-04 (# of elements : 440)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 2366 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6391, RMSE 0.0112
[Open3D DEBUG] Residual : 2.50e-04 (# of elements : 1512)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6386, RMSE 0.0113
[Open3D DEBUG] Residual : 2.49e-04 (# of elements : 1511)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6386, RMSE 0.0113
[Open3D DEBUG] Residual : 2.45e-04 (# of elements : 1511)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6386, RMSE 0.0113
[Open3D DEBUG] Residual : 2.47e-04 (# of elements : 1511)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6382, RMSE 0.0112
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 1510)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6382, RMSE 0.0112
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 1510)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6382, RMSE 0.0112
[Open3D DEBUG] Residual : 2.48e-04 (# of elements : 1510)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 8369 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6017, RMSE 0.0065
[Open3D DEBUG] Residual : 2.34e-04 (# of elements : 5036)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6001, RMSE 0.0064
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 5022)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5992, RMSE 0.0064
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 5015)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5958, RMSE 0.0064
[Open3D DEBUG] Residual : 2.39e-04 (# of elements : 4986)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5960, RMSE 0.0064
[Open3D DEBUG] Residual : 2.42e-04 (# of elements : 4988)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5964, RMSE 0.0064
[Open3D DEBUG] Residual : 2.42e-04 (# of elements : 4991)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5965, RMSE 0.0064
[Open3D DEBUG] Residual : 2.42e-04 (# of elements : 4992)
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5117, RMSE 0.0273
[Open3D DEBUG] Residual : 7.59e-04 (# of elements : 350)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5190, RMSE 0.0251
[Open3D DEBUG] Residual : 5.64e-04 (# of elements : 355)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5205, RMSE 0.0248
[Open3D DEBUG] Residual : 5.68e-04 (# of elements : 356)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5234, RMSE 0.0251
[Open3D DEBUG] Residual : 5.40e-04 (# of elements : 358)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5205, RMSE 0.0248
[Open3D DEBUG] Residual : 5.12e-04 (# of elements : 356)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5161, RMSE 0.0246
[Open3D DEBUG] Residual : 4.88e-04 (# of elements : 353)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5161, RMSE 0.0246
[Open3D DEBUG] Residual : 4.83e-04 (# of elements : 353)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5161, RMSE 0.0246
[Open3D DEBUG] Residual : 4.88e-04 (# of elements : 353)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5146, RMSE 0.0245
[Open3D DEBUG] Residual : 4.79e-04 (# of elements : 352)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5161, RMSE 0.0246
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 353)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5161, RMSE 0.0246
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 353)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5161, RMSE 0.0246
[Open3D DEBUG] Residual : 4.82e-04 (# of elements : 353)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 2366 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 1013 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4467, RMSE 0.0122
[Open3D DEBUG] Residual : 3.60e-04 (# of elements : 1057)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4476, RMSE 0.0114
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 1059)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4472, RMSE 0.0116
[Open3D DEBUG] Residual : 3.20e-04 (# of elements : 1058)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4467, RMSE 0.0116
[Open3D DEBUG] Residual : 3.16e-04 (# of elements : 1057)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4467, RMSE 0.0117
[Open3D DEBUG] Residual : 3.16e-04 (# of elements : 1057)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4472, RMSE 0.0117
[Open3D DEBUG] Residual : 3.16e-04 (# of elements : 1058)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4472, RMSE 0.0117
[Open3D DEBUG] Residual : 3.16e-04 (# of elements : 1058)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4472, RMSE 0.0117
[Open3D DEBUG] Residual : 3.17e-04 (# of elements : 1058)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 8369 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 3196 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3886, RMSE 0.0067
[Open3D DEBUG] Residual : 2.52e-04 (# of elements : 3252)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3947, RMSE 0.0066
[Open3D DEBUG] Residual : 2.41e-04 (# of elements : 3303)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3960, RMSE 0.0065
[Open3D DEBUG] Residual : 2.41e-04 (# of elements : 3314)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3956, RMSE 0.0065
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 3311)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3956, RMSE 0.0065
[Open3D DEBUG] Residual : 2.41e-04 (# of elements : 3311)
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6491, RMSE 0.0226
[Open3D DEBUG] Residual : 4.71e-04 (# of elements : 444)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6564, RMSE 0.0209
[Open3D DEBUG] Residual : 3.59e-04 (# of elements : 449)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6520, RMSE 0.0204
[Open3D DEBUG] Residual : 3.59e-04 (# of elements : 446)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6535, RMSE 0.0205
[Open3D DEBUG] Residual : 3.63e-04 (# of elements : 447)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6535, RMSE 0.0204
[Open3D DEBUG] Residual : 3.62e-04 (# of elements : 447)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6535, RMSE 0.0204
[Open3D DEBUG] Residual : 3.62e-04 (# of elements : 447)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 2366 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5934, RMSE 0.0118
[Open3D DEBUG] Residual : 2.92e-04 (# of elements : 1404)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5938, RMSE 0.0112
[Open3D DEBUG] Residual : 2.86e-04 (# of elements : 1405)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5934, RMSE 0.0113
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 1404)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5934, RMSE 0.0113
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 1404)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5934, RMSE 0.0113
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 1404)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5934, RMSE 0.0113
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 1404)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5934, RMSE 0.0113
[Open3D DEBUG] Residual : 2.86e-04 (# of elements : 1404)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5934, RMSE 0.0113
[Open3D DEBUG] Residual : 2.86e-04 (# of elements : 1404)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5934, RMSE 0.0113
[Open3D DEBUG] Residual : 2.85e-04 (# of elements : 1404)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 8369 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5419, RMSE 0.0061
[Open3D DEBUG] Residual : 2.40e-04 (# of elements : 4535)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5348, RMSE 0.0062
[Open3D DEBUG] Residual : 2.14e-04 (# of elements : 4476)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5346, RMSE 0.0063
[Open3D DEBUG] Residual : 2.20e-04 (# of elements : 4474)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5328, RMSE 0.0063
[Open3D DEBUG] Residual : 2.18e-04 (# of elements : 4459)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5329, RMSE 0.0063
[Open3D DEBUG] Residual : 2.17e-04 (# of elements : 4460)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5330, RMSE 0.0063
[Open3D DEBUG] Residual : 2.18e-04 (# of elements : 4461)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5329, RMSE 0.0063
[Open3D DEBUG] Residual : 2.19e-04 (# of elements : 4460)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5329, RMSE 0.0063
[Open3D DEBUG] Residual : 2.17e-04 (# of elements : 4460)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5330, RMSE 0.0063
[Open3D DEBUG] Residual : 2.18e-04 (# of elements : 4461)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5329, RMSE 0.0063
[Open3D DEBUG] Residual : 2.19e-04 (# of elements : 4460)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5329, RMSE 0.0063
[Open3D DEBUG] Residual : 2.17e-04 (# of elements : 4460)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5330, RMSE 0.0063
[Open3D DEBUG] Residual : 2.18e-04 (# of elements : 4461)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5329, RMSE 0.0063
[Open3D DEBUG] Residual : 2.19e-04 (# of elements : 4460)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5329, RMSE 0.0063
[Open3D DEBUG] Residual : 2.17e-04 (# of elements : 4460)
[Open3D DEBUG] Read geometry::PointCloud: 40052 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 684 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4269, RMSE 0.0311
[Open3D DEBUG] Residual : 1.19e-03 (# of elements : 292)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4474, RMSE 0.0266
[Open3D DEBUG] Residual : 5.83e-04 (# of elements : 306)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4459, RMSE 0.0261
[Open3D DEBUG] Residual : 5.64e-04 (# of elements : 305)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4503, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4547, RMSE 0.0267
[Open3D DEBUG] Residual : 5.90e-04 (# of elements : 311)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4532, RMSE 0.0268
[Open3D DEBUG] Residual : 5.84e-04 (# of elements : 310)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 309)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.4503, RMSE 0.0266
[Open3D DEBUG] Residual : 5.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.4518, RMSE 0.0267
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 309)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 2366 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3508, RMSE 0.0133
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 830)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3576, RMSE 0.0129
[Open3D DEBUG] Residual : 3.85e-04 (# of elements : 846)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3538, RMSE 0.0128
[Open3D DEBUG] Residual : 4.00e-04 (# of elements : 837)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3546, RMSE 0.0128
[Open3D DEBUG] Residual : 3.97e-04 (# of elements : 839)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3533, RMSE 0.0128
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 836)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3542, RMSE 0.0128
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 838)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3546, RMSE 0.0128
[Open3D DEBUG] Residual : 3.97e-04 (# of elements : 839)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3546, RMSE 0.0128
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 839)
[Open3D DEBUG] Pointcloud down sampled from 40052 points to 8369 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2849, RMSE 0.0068
[Open3D DEBUG] Residual : 3.05e-04 (# of elements : 2384)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2859, RMSE 0.0067
[Open3D DEBUG] Residual : 2.76e-04 (# of elements : 2393)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2847, RMSE 0.0066
[Open3D DEBUG] Residual : 2.76e-04 (# of elements : 2383)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2846, RMSE 0.0066
[Open3D DEBUG] Residual : 2.66e-04 (# of elements : 2382)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2847, RMSE 0.0066
[Open3D DEBUG] Residual : 2.64e-04 (# of elements : 2383)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.2846, RMSE 0.0066
[Open3D DEBUG] Residual : 2.64e-04 (# of elements : 2382)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2847, RMSE 0.0066
[Open3D DEBUG] Residual : 2.63e-04 (# of elements : 2383)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.2851, RMSE 0.0066
[Open3D DEBUG] Residual : 2.63e-04 (# of elements : 2386)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.2851, RMSE 0.0066
[Open3D DEBUG] Residual : 2.64e-04 (# of elements : 2386)
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3921, RMSE 0.0286
[Open3D DEBUG] Residual : 1.47e-03 (# of elements : 318)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3970, RMSE 0.0283
[Open3D DEBUG] Residual : 1.42e-03 (# of elements : 322)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4044, RMSE 0.0284
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 328)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4069, RMSE 0.0284
[Open3D DEBUG] Residual : 1.35e-03 (# of elements : 330)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4069, RMSE 0.0282
[Open3D DEBUG] Residual : 1.30e-03 (# of elements : 330)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4106, RMSE 0.0283
[Open3D DEBUG] Residual : 1.30e-03 (# of elements : 333)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4106, RMSE 0.0283
[Open3D DEBUG] Residual : 1.30e-03 (# of elements : 333)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4106, RMSE 0.0282
[Open3D DEBUG] Residual : 1.29e-03 (# of elements : 333)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4143, RMSE 0.0282
[Open3D DEBUG] Residual : 1.26e-03 (# of elements : 336)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4131, RMSE 0.0277
[Open3D DEBUG] Residual : 1.19e-03 (# of elements : 335)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4081, RMSE 0.0269
[Open3D DEBUG] Residual : 1.19e-03 (# of elements : 331)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4069, RMSE 0.0267
[Open3D DEBUG] Residual : 1.18e-03 (# of elements : 330)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4057, RMSE 0.0264
[Open3D DEBUG] Residual : 1.14e-03 (# of elements : 329)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4057, RMSE 0.0261
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 329)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.4044, RMSE 0.0260
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 328)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.4057, RMSE 0.0262
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 329)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.4057, RMSE 0.0262
[Open3D DEBUG] Residual : 1.14e-03 (# of elements : 329)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.4057, RMSE 0.0260
[Open3D DEBUG] Residual : 1.16e-03 (# of elements : 329)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.4044, RMSE 0.0259
[Open3D DEBUG] Residual : 1.16e-03 (# of elements : 328)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.4057, RMSE 0.0262
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 329)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.4057, RMSE 0.0261
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 329)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 2886 points.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 1410 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3039, RMSE 0.0145
[Open3D DEBUG] Residual : 1.17e-03 (# of elements : 877)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3132, RMSE 0.0144
[Open3D DEBUG] Residual : 1.09e-03 (# of elements : 904)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3146, RMSE 0.0141
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 908)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3177, RMSE 0.0140
[Open3D DEBUG] Residual : 1.07e-03 (# of elements : 917)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3181, RMSE 0.0140
[Open3D DEBUG] Residual : 1.07e-03 (# of elements : 918)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3174, RMSE 0.0139
[Open3D DEBUG] Residual : 1.07e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3164, RMSE 0.0139
[Open3D DEBUG] Residual : 1.07e-03 (# of elements : 913)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3164, RMSE 0.0139
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 913)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3167, RMSE 0.0139
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 914)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3167, RMSE 0.0140
[Open3D DEBUG] Residual : 1.07e-03 (# of elements : 914)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.3174, RMSE 0.0140
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 916)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 9882 points.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 4467 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2190, RMSE 0.0075
[Open3D DEBUG] Residual : 1.22e-03 (# of elements : 2164)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2146, RMSE 0.0073
[Open3D DEBUG] Residual : 1.18e-03 (# of elements : 2121)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2111, RMSE 0.0073
[Open3D DEBUG] Residual : 1.14e-03 (# of elements : 2086)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2194, RMSE 0.0073
[Open3D DEBUG] Residual : 1.03e-03 (# of elements : 2168)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2268, RMSE 0.0073
[Open3D DEBUG] Residual : 9.53e-04 (# of elements : 2241)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.2308, RMSE 0.0073
[Open3D DEBUG] Residual : 9.11e-04 (# of elements : 2281)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2303, RMSE 0.0074
[Open3D DEBUG] Residual : 8.45e-04 (# of elements : 2276)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.2280, RMSE 0.0074
[Open3D DEBUG] Residual : 8.15e-04 (# of elements : 2253)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.2269, RMSE 0.0074
[Open3D DEBUG] Residual : 7.86e-04 (# of elements : 2242)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.2239, RMSE 0.0075
[Open3D DEBUG] Residual : 7.45e-04 (# of elements : 2213)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.2216, RMSE 0.0076
[Open3D DEBUG] Residual : 7.16e-04 (# of elements : 2190)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.2156, RMSE 0.0077
[Open3D DEBUG] Residual : 6.55e-04 (# of elements : 2131)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.2119, RMSE 0.0077
[Open3D DEBUG] Residual : 6.49e-04 (# of elements : 2094)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.2081, RMSE 0.0078
[Open3D DEBUG] Residual : 6.23e-04 (# of elements : 2056)
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4686, RMSE 0.0286
[Open3D DEBUG] Residual : 9.01e-04 (# of elements : 380)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4957, RMSE 0.0247
[Open3D DEBUG] Residual : 6.72e-04 (# of elements : 402)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4908, RMSE 0.0238
[Open3D DEBUG] Residual : 5.85e-04 (# of elements : 398)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4957, RMSE 0.0239
[Open3D DEBUG] Residual : 5.81e-04 (# of elements : 402)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4957, RMSE 0.0238
[Open3D DEBUG] Residual : 5.79e-04 (# of elements : 402)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4957, RMSE 0.0237
[Open3D DEBUG] Residual : 5.84e-04 (# of elements : 402)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4957, RMSE 0.0238
[Open3D DEBUG] Residual : 5.80e-04 (# of elements : 402)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4957, RMSE 0.0237
[Open3D DEBUG] Residual : 5.80e-04 (# of elements : 402)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4957, RMSE 0.0238
[Open3D DEBUG] Residual : 5.78e-04 (# of elements : 402)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4957, RMSE 0.0237
[Open3D DEBUG] Residual : 5.78e-04 (# of elements : 402)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 2886 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 2207 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4536, RMSE 0.0129
[Open3D DEBUG] Residual : 6.15e-04 (# of elements : 1309)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4563, RMSE 0.0122
[Open3D DEBUG] Residual : 6.22e-04 (# of elements : 1317)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4532, RMSE 0.0122
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1308)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4532, RMSE 0.0122
[Open3D DEBUG] Residual : 6.17e-04 (# of elements : 1308)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4518, RMSE 0.0122
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1304)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4515, RMSE 0.0122
[Open3D DEBUG] Residual : 6.35e-04 (# of elements : 1303)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4515, RMSE 0.0122
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1303)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.4515, RMSE 0.0122
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1303)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.4515, RMSE 0.0122
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1303)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.4511, RMSE 0.0121
[Open3D DEBUG] Residual : 6.31e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.4511, RMSE 0.0122
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 1302)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.4515, RMSE 0.0122
[Open3D DEBUG] Residual : 6.30e-04 (# of elements : 1303)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 9882 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 7191 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3974, RMSE 0.0070
[Open3D DEBUG] Residual : 5.92e-04 (# of elements : 3927)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3997, RMSE 0.0070
[Open3D DEBUG] Residual : 5.47e-04 (# of elements : 3950)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4044, RMSE 0.0071
[Open3D DEBUG] Residual : 5.33e-04 (# of elements : 3996)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4028, RMSE 0.0071
[Open3D DEBUG] Residual : 5.24e-04 (# of elements : 3980)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4018, RMSE 0.0071
[Open3D DEBUG] Residual : 5.23e-04 (# of elements : 3971)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4024, RMSE 0.0071
[Open3D DEBUG] Residual : 5.29e-04 (# of elements : 3977)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4022, RMSE 0.0071
[Open3D DEBUG] Residual : 5.29e-04 (# of elements : 3975)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4022, RMSE 0.0071
[Open3D DEBUG] Residual : 5.30e-04 (# of elements : 3975)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4015, RMSE 0.0071
[Open3D DEBUG] Residual : 5.29e-04 (# of elements : 3968)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4019, RMSE 0.0071
[Open3D DEBUG] Residual : 5.30e-04 (# of elements : 3972)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4013, RMSE 0.0071
[Open3D DEBUG] Residual : 5.29e-04 (# of elements : 3966)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4021, RMSE 0.0071
[Open3D DEBUG] Residual : 5.29e-04 (# of elements : 3974)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4020, RMSE 0.0071
[Open3D DEBUG] Residual : 5.30e-04 (# of elements : 3973)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4014, RMSE 0.0071
[Open3D DEBUG] Residual : 5.29e-04 (# of elements : 3967)
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5709, RMSE 0.0288
[Open3D DEBUG] Residual : 9.57e-04 (# of elements : 463)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6030, RMSE 0.0228
[Open3D DEBUG] Residual : 5.09e-04 (# of elements : 489)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5968, RMSE 0.0218
[Open3D DEBUG] Residual : 3.89e-04 (# of elements : 484)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5980, RMSE 0.0219
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 485)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6005, RMSE 0.0221
[Open3D DEBUG] Residual : 3.89e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.71e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6005, RMSE 0.0219
[Open3D DEBUG] Residual : 3.84e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.74e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.82e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.87e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.82e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.87e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.82e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.87e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.82e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.87e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.82e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.87e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.82e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.87e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.83e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.82e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 487)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.6005, RMSE 0.0220
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 487)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 2886 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5582, RMSE 0.0121
[Open3D DEBUG] Residual : 3.39e-04 (# of elements : 1611)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5509, RMSE 0.0119
[Open3D DEBUG] Residual : 3.21e-04 (# of elements : 1590)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5492, RMSE 0.0119
[Open3D DEBUG] Residual : 3.18e-04 (# of elements : 1585)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5492, RMSE 0.0119
[Open3D DEBUG] Residual : 3.19e-04 (# of elements : 1585)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5495, RMSE 0.0119
[Open3D DEBUG] Residual : 3.20e-04 (# of elements : 1586)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5492, RMSE 0.0119
[Open3D DEBUG] Residual : 3.17e-04 (# of elements : 1585)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5492, RMSE 0.0119
[Open3D DEBUG] Residual : 3.16e-04 (# of elements : 1585)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5495, RMSE 0.0119
[Open3D DEBUG] Residual : 3.16e-04 (# of elements : 1586)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5495, RMSE 0.0119
[Open3D DEBUG] Residual : 3.16e-04 (# of elements : 1586)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 9882 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4861, RMSE 0.0069
[Open3D DEBUG] Residual : 2.73e-04 (# of elements : 4804)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4862, RMSE 0.0069
[Open3D DEBUG] Residual : 2.61e-04 (# of elements : 4805)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4857, RMSE 0.0068
[Open3D DEBUG] Residual : 2.56e-04 (# of elements : 4800)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4857, RMSE 0.0068
[Open3D DEBUG] Residual : 2.56e-04 (# of elements : 4800)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4861, RMSE 0.0068
[Open3D DEBUG] Residual : 2.56e-04 (# of elements : 4804)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4859, RMSE 0.0068
[Open3D DEBUG] Residual : 2.55e-04 (# of elements : 4802)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4859, RMSE 0.0068
[Open3D DEBUG] Residual : 2.55e-04 (# of elements : 4802)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4859, RMSE 0.0068
[Open3D DEBUG] Residual : 2.55e-04 (# of elements : 4802)
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 15524 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 321 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4476, RMSE 0.0276
[Open3D DEBUG] Residual : 6.25e-04 (# of elements : 363)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4464, RMSE 0.0236
[Open3D DEBUG] Residual : 4.39e-04 (# of elements : 362)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4427, RMSE 0.0233
[Open3D DEBUG] Residual : 4.42e-04 (# of elements : 359)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4414, RMSE 0.0232
[Open3D DEBUG] Residual : 4.36e-04 (# of elements : 358)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4414, RMSE 0.0231
[Open3D DEBUG] Residual : 4.36e-04 (# of elements : 358)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4414, RMSE 0.0231
[Open3D DEBUG] Residual : 4.36e-04 (# of elements : 358)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 2886 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 1013 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3735, RMSE 0.0131
[Open3D DEBUG] Residual : 4.92e-04 (# of elements : 1078)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3704, RMSE 0.0133
[Open3D DEBUG] Residual : 4.86e-04 (# of elements : 1069)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3683, RMSE 0.0134
[Open3D DEBUG] Residual : 4.65e-04 (# of elements : 1063)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3687, RMSE 0.0135
[Open3D DEBUG] Residual : 4.49e-04 (# of elements : 1064)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3694, RMSE 0.0134
[Open3D DEBUG] Residual : 4.49e-04 (# of elements : 1066)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3680, RMSE 0.0133
[Open3D DEBUG] Residual : 4.37e-04 (# of elements : 1062)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3683, RMSE 0.0133
[Open3D DEBUG] Residual : 4.35e-04 (# of elements : 1063)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3680, RMSE 0.0133
[Open3D DEBUG] Residual : 4.35e-04 (# of elements : 1062)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3680, RMSE 0.0133
[Open3D DEBUG] Residual : 4.35e-04 (# of elements : 1062)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 9882 points.
[Open3D DEBUG] Pointcloud down sampled from 15524 points to 3196 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2896, RMSE 0.0074
[Open3D DEBUG] Residual : 4.30e-04 (# of elements : 2862)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3113, RMSE 0.0070
[Open3D DEBUG] Residual : 3.50e-04 (# of elements : 3076)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3155, RMSE 0.0069
[Open3D DEBUG] Residual : 3.34e-04 (# of elements : 3118)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3148, RMSE 0.0068
[Open3D DEBUG] Residual : 3.26e-04 (# of elements : 3111)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3134, RMSE 0.0068
[Open3D DEBUG] Residual : 3.19e-04 (# of elements : 3097)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3124, RMSE 0.0067
[Open3D DEBUG] Residual : 3.10e-04 (# of elements : 3087)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3124, RMSE 0.0067
[Open3D DEBUG] Residual : 3.09e-04 (# of elements : 3087)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3121, RMSE 0.0067
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 3084)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3125, RMSE 0.0067
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 3088)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3125, RMSE 0.0067
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 3088)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3125, RMSE 0.0067
[Open3D DEBUG] Residual : 3.12e-04 (# of elements : 3088)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3125, RMSE 0.0067
[Open3D DEBUG] Residual : 3.11e-04 (# of elements : 3088)
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5031, RMSE 0.0313
[Open3D DEBUG] Residual : 1.20e-03 (# of elements : 408)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5105, RMSE 0.0234
[Open3D DEBUG] Residual : 5.21e-04 (# of elements : 414)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5092, RMSE 0.0242
[Open3D DEBUG] Residual : 4.67e-04 (# of elements : 413)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5129, RMSE 0.0243
[Open3D DEBUG] Residual : 4.67e-04 (# of elements : 416)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5129, RMSE 0.0243
[Open3D DEBUG] Residual : 4.68e-04 (# of elements : 416)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5129, RMSE 0.0243
[Open3D DEBUG] Residual : 4.68e-04 (# of elements : 416)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 2886 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4245, RMSE 0.0124
[Open3D DEBUG] Residual : 4.00e-04 (# of elements : 1225)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4238, RMSE 0.0123
[Open3D DEBUG] Residual : 3.71e-04 (# of elements : 1223)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4241, RMSE 0.0123
[Open3D DEBUG] Residual : 3.72e-04 (# of elements : 1224)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4245, RMSE 0.0123
[Open3D DEBUG] Residual : 3.85e-04 (# of elements : 1225)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.00e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4258, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1229)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4258, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1229)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4258, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1229)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.01e-04 (# of elements : 1228)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.4255, RMSE 0.0123
[Open3D DEBUG] Residual : 4.04e-04 (# of elements : 1228)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 9882 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3658, RMSE 0.0068
[Open3D DEBUG] Residual : 3.61e-04 (# of elements : 3615)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3642, RMSE 0.0070
[Open3D DEBUG] Residual : 3.71e-04 (# of elements : 3599)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3636, RMSE 0.0071
[Open3D DEBUG] Residual : 3.88e-04 (# of elements : 3593)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3637, RMSE 0.0071
[Open3D DEBUG] Residual : 3.89e-04 (# of elements : 3594)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3642, RMSE 0.0071
[Open3D DEBUG] Residual : 3.86e-04 (# of elements : 3599)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3629, RMSE 0.0071
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 3586)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3623, RMSE 0.0071
[Open3D DEBUG] Residual : 3.78e-04 (# of elements : 3580)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3618, RMSE 0.0072
[Open3D DEBUG] Residual : 3.78e-04 (# of elements : 3575)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3619, RMSE 0.0072
[Open3D DEBUG] Residual : 3.76e-04 (# of elements : 3576)
[Open3D DEBUG] Read geometry::PointCloud: 51696 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 811 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3329, RMSE 0.0270
[Open3D DEBUG] Residual : 1.04e-03 (# of elements : 270)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3292, RMSE 0.0260
[Open3D DEBUG] Residual : 8.46e-04 (# of elements : 267)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3354, RMSE 0.0269
[Open3D DEBUG] Residual : 8.58e-04 (# of elements : 272)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3366, RMSE 0.0270
[Open3D DEBUG] Residual : 8.63e-04 (# of elements : 273)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.60e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.61e-04 (# of elements : 274)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.3379, RMSE 0.0271
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 274)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 2886 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2439, RMSE 0.0142
[Open3D DEBUG] Residual : 7.77e-04 (# of elements : 704)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2415, RMSE 0.0140
[Open3D DEBUG] Residual : 7.79e-04 (# of elements : 697)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2401, RMSE 0.0138
[Open3D DEBUG] Residual : 7.42e-04 (# of elements : 693)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2412, RMSE 0.0136
[Open3D DEBUG] Residual : 7.13e-04 (# of elements : 696)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2426, RMSE 0.0137
[Open3D DEBUG] Residual : 6.91e-04 (# of elements : 700)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.90e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2422, RMSE 0.0137
[Open3D DEBUG] Residual : 6.92e-04 (# of elements : 699)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.91e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.2415, RMSE 0.0136
[Open3D DEBUG] Residual : 6.93e-04 (# of elements : 697)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.90e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.2422, RMSE 0.0137
[Open3D DEBUG] Residual : 6.92e-04 (# of elements : 699)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.91e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.2415, RMSE 0.0136
[Open3D DEBUG] Residual : 6.93e-04 (# of elements : 697)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.90e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.2422, RMSE 0.0137
[Open3D DEBUG] Residual : 6.92e-04 (# of elements : 699)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.91e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.2415, RMSE 0.0136
[Open3D DEBUG] Residual : 6.93e-04 (# of elements : 697)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.90e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.2422, RMSE 0.0137
[Open3D DEBUG] Residual : 6.92e-04 (# of elements : 699)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.91e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.2415, RMSE 0.0136
[Open3D DEBUG] Residual : 6.93e-04 (# of elements : 697)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.90e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.2422, RMSE 0.0137
[Open3D DEBUG] Residual : 6.92e-04 (# of elements : 699)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.91e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.2415, RMSE 0.0136
[Open3D DEBUG] Residual : 6.93e-04 (# of elements : 697)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.90e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.2422, RMSE 0.0137
[Open3D DEBUG] Residual : 6.92e-04 (# of elements : 699)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.91e-04 (# of elements : 698)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.2415, RMSE 0.0136
[Open3D DEBUG] Residual : 6.93e-04 (# of elements : 697)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.2419, RMSE 0.0136
[Open3D DEBUG] Residual : 6.90e-04 (# of elements : 698)
[Open3D DEBUG] Pointcloud down sampled from 51696 points to 9882 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.1728, RMSE 0.0074
[Open3D DEBUG] Residual : 7.18e-04 (# of elements : 1708)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.1748, RMSE 0.0074
[Open3D DEBUG] Residual : 6.48e-04 (# of elements : 1727)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.1726, RMSE 0.0075
[Open3D DEBUG] Residual : 6.33e-04 (# of elements : 1706)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.1721, RMSE 0.0075
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 1701)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.1712, RMSE 0.0076
[Open3D DEBUG] Residual : 5.82e-04 (# of elements : 1692)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.1705, RMSE 0.0076
[Open3D DEBUG] Residual : 5.96e-04 (# of elements : 1685)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.1701, RMSE 0.0077
[Open3D DEBUG] Residual : 5.94e-04 (# of elements : 1681)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.1700, RMSE 0.0077
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 1680)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.1715, RMSE 0.0077
[Open3D DEBUG] Residual : 5.98e-04 (# of elements : 1695)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.1708, RMSE 0.0077
[Open3D DEBUG] Residual : 5.87e-04 (# of elements : 1688)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.1703, RMSE 0.0076
[Open3D DEBUG] Residual : 5.62e-04 (# of elements : 1683)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.1684, RMSE 0.0077
[Open3D DEBUG] Residual : 5.70e-04 (# of elements : 1664)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.1690, RMSE 0.0077
[Open3D DEBUG] Residual : 5.99e-04 (# of elements : 1670)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.1708, RMSE 0.0077
[Open3D DEBUG] Residual : 5.66e-04 (# of elements : 1688)
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2646, RMSE 0.0298
[Open3D DEBUG] Residual : 7.73e-04 (# of elements : 118)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2556, RMSE 0.0294
[Open3D DEBUG] Residual : 7.85e-04 (# of elements : 114)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2646, RMSE 0.0298
[Open3D DEBUG] Residual : 7.85e-04 (# of elements : 118)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2668, RMSE 0.0297
[Open3D DEBUG] Residual : 8.06e-04 (# of elements : 119)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2668, RMSE 0.0294
[Open3D DEBUG] Residual : 8.21e-04 (# of elements : 119)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.2780, RMSE 0.0297
[Open3D DEBUG] Residual : 8.05e-04 (# of elements : 124)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2915, RMSE 0.0305
[Open3D DEBUG] Residual : 8.76e-04 (# of elements : 130)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.2937, RMSE 0.0307
[Open3D DEBUG] Residual : 8.94e-04 (# of elements : 131)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.2915, RMSE 0.0305
[Open3D DEBUG] Residual : 8.99e-04 (# of elements : 130)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.2915, RMSE 0.0304
[Open3D DEBUG] Residual : 9.05e-04 (# of elements : 130)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.2937, RMSE 0.0306
[Open3D DEBUG] Residual : 9.10e-04 (# of elements : 131)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.2937, RMSE 0.0306
[Open3D DEBUG] Residual : 9.14e-04 (# of elements : 131)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.2915, RMSE 0.0305
[Open3D DEBUG] Residual : 9.17e-04 (# of elements : 130)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.2892, RMSE 0.0302
[Open3D DEBUG] Residual : 8.95e-04 (# of elements : 129)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.2892, RMSE 0.0301
[Open3D DEBUG] Residual : 8.91e-04 (# of elements : 129)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.2915, RMSE 0.0303
[Open3D DEBUG] Residual : 8.90e-04 (# of elements : 130)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.2915, RMSE 0.0303
[Open3D DEBUG] Residual : 8.98e-04 (# of elements : 130)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.2915, RMSE 0.0303
[Open3D DEBUG] Residual : 8.90e-04 (# of elements : 130)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.2937, RMSE 0.0305
[Open3D DEBUG] Residual : 8.91e-04 (# of elements : 131)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.2937, RMSE 0.0303
[Open3D DEBUG] Residual : 8.90e-04 (# of elements : 131)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.2937, RMSE 0.0303
[Open3D DEBUG] Residual : 8.90e-04 (# of elements : 131)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 1410 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 2207 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2184, RMSE 0.0164
[Open3D DEBUG] Residual : 7.86e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2177, RMSE 0.0154
[Open3D DEBUG] Residual : 6.46e-04 (# of elements : 307)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2184, RMSE 0.0155
[Open3D DEBUG] Residual : 6.05e-04 (# of elements : 308)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2156, RMSE 0.0156
[Open3D DEBUG] Residual : 6.08e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2064, RMSE 0.0153
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 291)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.1979, RMSE 0.0151
[Open3D DEBUG] Residual : 6.03e-04 (# of elements : 279)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.1965, RMSE 0.0154
[Open3D DEBUG] Residual : 5.71e-04 (# of elements : 277)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.1957, RMSE 0.0154
[Open3D DEBUG] Residual : 5.88e-04 (# of elements : 276)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.1936, RMSE 0.0154
[Open3D DEBUG] Residual : 5.96e-04 (# of elements : 273)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.1908, RMSE 0.0151
[Open3D DEBUG] Residual : 5.82e-04 (# of elements : 269)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.1887, RMSE 0.0148
[Open3D DEBUG] Residual : 5.92e-04 (# of elements : 266)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.1929, RMSE 0.0149
[Open3D DEBUG] Residual : 6.05e-04 (# of elements : 272)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.1957, RMSE 0.0150
[Open3D DEBUG] Residual : 6.03e-04 (# of elements : 276)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.1972, RMSE 0.0149
[Open3D DEBUG] Residual : 6.16e-04 (# of elements : 278)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.1972, RMSE 0.0149
[Open3D DEBUG] Residual : 6.04e-04 (# of elements : 278)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.1993, RMSE 0.0149
[Open3D DEBUG] Residual : 6.04e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.1986, RMSE 0.0147
[Open3D DEBUG] Residual : 6.05e-04 (# of elements : 280)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.2007, RMSE 0.0149
[Open3D DEBUG] Residual : 6.22e-04 (# of elements : 283)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.2000, RMSE 0.0149
[Open3D DEBUG] Residual : 6.22e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.2014, RMSE 0.0151
[Open3D DEBUG] Residual : 6.34e-04 (# of elements : 284)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.2014, RMSE 0.0152
[Open3D DEBUG] Residual : 6.41e-04 (# of elements : 284)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.2000, RMSE 0.0152
[Open3D DEBUG] Residual : 6.48e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.1993, RMSE 0.0151
[Open3D DEBUG] Residual : 6.38e-04 (# of elements : 281)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.2000, RMSE 0.0152
[Open3D DEBUG] Residual : 6.35e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.2007, RMSE 0.0152
[Open3D DEBUG] Residual : 6.46e-04 (# of elements : 283)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.1979, RMSE 0.0150
[Open3D DEBUG] Residual : 6.35e-04 (# of elements : 279)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.2000, RMSE 0.0152
[Open3D DEBUG] Residual : 6.38e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.2000, RMSE 0.0151
[Open3D DEBUG] Residual : 6.38e-04 (# of elements : 282)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.2000, RMSE 0.0151
[Open3D DEBUG] Residual : 6.38e-04 (# of elements : 282)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 4467 points.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 7191 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.1466, RMSE 0.0079
[Open3D DEBUG] Residual : 5.21e-04 (# of elements : 655)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.1518, RMSE 0.0076
[Open3D DEBUG] Residual : 5.01e-04 (# of elements : 678)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.1520, RMSE 0.0076
[Open3D DEBUG] Residual : 5.03e-04 (# of elements : 679)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.1509, RMSE 0.0077
[Open3D DEBUG] Residual : 4.92e-04 (# of elements : 674)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.1495, RMSE 0.0077
[Open3D DEBUG] Residual : 5.08e-04 (# of elements : 668)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.1478, RMSE 0.0077
[Open3D DEBUG] Residual : 5.07e-04 (# of elements : 660)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.1460, RMSE 0.0076
[Open3D DEBUG] Residual : 5.14e-04 (# of elements : 652)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.1462, RMSE 0.0077
[Open3D DEBUG] Residual : 5.20e-04 (# of elements : 653)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.1455, RMSE 0.0077
[Open3D DEBUG] Residual : 5.23e-04 (# of elements : 650)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.1435, RMSE 0.0077
[Open3D DEBUG] Residual : 5.13e-04 (# of elements : 641)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.1428, RMSE 0.0077
[Open3D DEBUG] Residual : 5.16e-04 (# of elements : 638)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.1426, RMSE 0.0077
[Open3D DEBUG] Residual : 5.13e-04 (# of elements : 637)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.1424, RMSE 0.0077
[Open3D DEBUG] Residual : 5.06e-04 (# of elements : 636)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.1422, RMSE 0.0077
[Open3D DEBUG] Residual : 5.06e-04 (# of elements : 635)
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5583, RMSE 0.0298
[Open3D DEBUG] Residual : 2.19e-03 (# of elements : 249)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5605, RMSE 0.0287
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 250)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5695, RMSE 0.0289
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 254)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5561, RMSE 0.0281
[Open3D DEBUG] Residual : 1.93e-03 (# of elements : 248)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5561, RMSE 0.0283
[Open3D DEBUG] Residual : 1.89e-03 (# of elements : 248)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5538, RMSE 0.0285
[Open3D DEBUG] Residual : 1.80e-03 (# of elements : 247)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5471, RMSE 0.0280
[Open3D DEBUG] Residual : 1.76e-03 (# of elements : 244)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5448, RMSE 0.0281
[Open3D DEBUG] Residual : 1.80e-03 (# of elements : 243)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5404, RMSE 0.0284
[Open3D DEBUG] Residual : 1.76e-03 (# of elements : 241)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5404, RMSE 0.0288
[Open3D DEBUG] Residual : 1.71e-03 (# of elements : 241)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5404, RMSE 0.0292
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 241)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5426, RMSE 0.0294
[Open3D DEBUG] Residual : 1.71e-03 (# of elements : 242)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5493, RMSE 0.0297
[Open3D DEBUG] Residual : 1.68e-03 (# of elements : 245)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5538, RMSE 0.0298
[Open3D DEBUG] Residual : 1.69e-03 (# of elements : 247)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.5516, RMSE 0.0296
[Open3D DEBUG] Residual : 1.67e-03 (# of elements : 246)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.5471, RMSE 0.0294
[Open3D DEBUG] Residual : 1.67e-03 (# of elements : 244)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.5471, RMSE 0.0294
[Open3D DEBUG] Residual : 1.66e-03 (# of elements : 244)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.5448, RMSE 0.0293
[Open3D DEBUG] Residual : 1.69e-03 (# of elements : 243)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.5448, RMSE 0.0292
[Open3D DEBUG] Residual : 1.68e-03 (# of elements : 243)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.5471, RMSE 0.0293
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 244)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.5471, RMSE 0.0292
[Open3D DEBUG] Residual : 1.71e-03 (# of elements : 244)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.5448, RMSE 0.0291
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 243)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.5448, RMSE 0.0291
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 243)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.5471, RMSE 0.0292
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 244)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.5471, RMSE 0.0292
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 244)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 1410 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4397, RMSE 0.0157
[Open3D DEBUG] Residual : 1.87e-03 (# of elements : 620)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4206, RMSE 0.0152
[Open3D DEBUG] Residual : 1.78e-03 (# of elements : 593)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4000, RMSE 0.0149
[Open3D DEBUG] Residual : 1.68e-03 (# of elements : 564)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3837, RMSE 0.0147
[Open3D DEBUG] Residual : 1.61e-03 (# of elements : 541)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3759, RMSE 0.0148
[Open3D DEBUG] Residual : 1.67e-03 (# of elements : 530)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3681, RMSE 0.0147
[Open3D DEBUG] Residual : 1.63e-03 (# of elements : 519)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3631, RMSE 0.0147
[Open3D DEBUG] Residual : 1.58e-03 (# of elements : 512)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3518, RMSE 0.0144
[Open3D DEBUG] Residual : 1.53e-03 (# of elements : 496)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3511, RMSE 0.0146
[Open3D DEBUG] Residual : 1.54e-03 (# of elements : 495)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3397, RMSE 0.0152
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 479)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3270, RMSE 0.0151
[Open3D DEBUG] Residual : 1.39e-03 (# of elements : 461)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3227, RMSE 0.0149
[Open3D DEBUG] Residual : 1.32e-03 (# of elements : 455)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3121, RMSE 0.0148
[Open3D DEBUG] Residual : 1.21e-03 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.2993, RMSE 0.0146
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 422)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.2943, RMSE 0.0147
[Open3D DEBUG] Residual : 1.20e-03 (# of elements : 415)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.2943, RMSE 0.0148
[Open3D DEBUG] Residual : 1.24e-03 (# of elements : 415)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.2950, RMSE 0.0148
[Open3D DEBUG] Residual : 1.24e-03 (# of elements : 416)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.2957, RMSE 0.0149
[Open3D DEBUG] Residual : 1.24e-03 (# of elements : 417)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.2936, RMSE 0.0148
[Open3D DEBUG] Residual : 1.23e-03 (# of elements : 414)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.2929, RMSE 0.0147
[Open3D DEBUG] Residual : 1.23e-03 (# of elements : 413)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.2844, RMSE 0.0142
[Open3D DEBUG] Residual : 1.22e-03 (# of elements : 401)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.2872, RMSE 0.0142
[Open3D DEBUG] Residual : 1.22e-03 (# of elements : 405)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.2887, RMSE 0.0143
[Open3D DEBUG] Residual : 1.20e-03 (# of elements : 407)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.2901, RMSE 0.0144
[Open3D DEBUG] Residual : 1.19e-03 (# of elements : 409)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.2915, RMSE 0.0145
[Open3D DEBUG] Residual : 1.20e-03 (# of elements : 411)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.2929, RMSE 0.0145
[Open3D DEBUG] Residual : 1.20e-03 (# of elements : 413)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.2922, RMSE 0.0145
[Open3D DEBUG] Residual : 1.21e-03 (# of elements : 412)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.2929, RMSE 0.0145
[Open3D DEBUG] Residual : 1.22e-03 (# of elements : 413)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.2950, RMSE 0.0146
[Open3D DEBUG] Residual : 1.23e-03 (# of elements : 416)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.2965, RMSE 0.0146
[Open3D DEBUG] Residual : 1.24e-03 (# of elements : 418)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 4467 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2180, RMSE 0.0078
[Open3D DEBUG] Residual : 1.21e-03 (# of elements : 974)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2131, RMSE 0.0079
[Open3D DEBUG] Residual : 1.18e-03 (# of elements : 952)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2046, RMSE 0.0079
[Open3D DEBUG] Residual : 1.15e-03 (# of elements : 914)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2039, RMSE 0.0079
[Open3D DEBUG] Residual : 1.13e-03 (# of elements : 911)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2006, RMSE 0.0079
[Open3D DEBUG] Residual : 1.13e-03 (# of elements : 896)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.1963, RMSE 0.0079
[Open3D DEBUG] Residual : 1.14e-03 (# of elements : 877)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.1930, RMSE 0.0080
[Open3D DEBUG] Residual : 1.13e-03 (# of elements : 862)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.1880, RMSE 0.0079
[Open3D DEBUG] Residual : 1.13e-03 (# of elements : 840)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.1860, RMSE 0.0080
[Open3D DEBUG] Residual : 1.18e-03 (# of elements : 831)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.1854, RMSE 0.0080
[Open3D DEBUG] Residual : 1.17e-03 (# of elements : 828)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.1842, RMSE 0.0080
[Open3D DEBUG] Residual : 1.21e-03 (# of elements : 823)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.1863, RMSE 0.0081
[Open3D DEBUG] Residual : 1.25e-03 (# of elements : 832)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.1865, RMSE 0.0082
[Open3D DEBUG] Residual : 1.26e-03 (# of elements : 833)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.1827, RMSE 0.0081
[Open3D DEBUG] Residual : 1.30e-03 (# of elements : 816)
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5045, RMSE 0.0294
[Open3D DEBUG] Residual : 2.29e-03 (# of elements : 225)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5224, RMSE 0.0298
[Open3D DEBUG] Residual : 2.24e-03 (# of elements : 233)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5336, RMSE 0.0296
[Open3D DEBUG] Residual : 2.23e-03 (# of elements : 238)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5426, RMSE 0.0305
[Open3D DEBUG] Residual : 2.18e-03 (# of elements : 242)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5247, RMSE 0.0298
[Open3D DEBUG] Residual : 2.21e-03 (# of elements : 234)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5179, RMSE 0.0293
[Open3D DEBUG] Residual : 2.17e-03 (# of elements : 231)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5090, RMSE 0.0290
[Open3D DEBUG] Residual : 2.13e-03 (# of elements : 227)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5090, RMSE 0.0292
[Open3D DEBUG] Residual : 2.15e-03 (# of elements : 227)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5067, RMSE 0.0293
[Open3D DEBUG] Residual : 2.14e-03 (# of elements : 226)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5045, RMSE 0.0294
[Open3D DEBUG] Residual : 2.05e-03 (# of elements : 225)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4955, RMSE 0.0291
[Open3D DEBUG] Residual : 2.06e-03 (# of elements : 221)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4865, RMSE 0.0293
[Open3D DEBUG] Residual : 1.98e-03 (# of elements : 217)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4798, RMSE 0.0289
[Open3D DEBUG] Residual : 1.96e-03 (# of elements : 214)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4933, RMSE 0.0293
[Open3D DEBUG] Residual : 2.03e-03 (# of elements : 220)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.4955, RMSE 0.0292
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 221)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.4933, RMSE 0.0290
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 220)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.4955, RMSE 0.0287
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 221)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.5022, RMSE 0.0287
[Open3D DEBUG] Residual : 2.02e-03 (# of elements : 224)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.5067, RMSE 0.0287
[Open3D DEBUG] Residual : 2.06e-03 (# of elements : 226)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.5179, RMSE 0.0286
[Open3D DEBUG] Residual : 2.03e-03 (# of elements : 231)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 1.99e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.5179, RMSE 0.0282
[Open3D DEBUG] Residual : 1.99e-03 (# of elements : 231)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.5179, RMSE 0.0281
[Open3D DEBUG] Residual : 2.03e-03 (# of elements : 231)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.5202, RMSE 0.0282
[Open3D DEBUG] Residual : 2.04e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.5179, RMSE 0.0281
[Open3D DEBUG] Residual : 2.04e-03 (# of elements : 231)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.5157, RMSE 0.0280
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 230)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.5179, RMSE 0.0282
[Open3D DEBUG] Residual : 2.03e-03 (# of elements : 231)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.5179, RMSE 0.0282
[Open3D DEBUG] Residual : 1.98e-03 (# of elements : 231)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.5157, RMSE 0.0280
[Open3D DEBUG] Residual : 1.98e-03 (# of elements : 230)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 1.99e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.5247, RMSE 0.0286
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 234)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.5224, RMSE 0.0285
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 233)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.5224, RMSE 0.0285
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 233)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 1.99e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.5202, RMSE 0.0284
[Open3D DEBUG] Residual : 2.01e-03 (# of elements : 232)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.5202, RMSE 0.0283
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 232)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 1410 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3837, RMSE 0.0161
[Open3D DEBUG] Residual : 2.72e-03 (# of elements : 541)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3809, RMSE 0.0162
[Open3D DEBUG] Residual : 2.10e-03 (# of elements : 537)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3681, RMSE 0.0155
[Open3D DEBUG] Residual : 1.91e-03 (# of elements : 519)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3624, RMSE 0.0157
[Open3D DEBUG] Residual : 1.86e-03 (# of elements : 511)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3553, RMSE 0.0158
[Open3D DEBUG] Residual : 1.80e-03 (# of elements : 501)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3461, RMSE 0.0158
[Open3D DEBUG] Residual : 1.81e-03 (# of elements : 488)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3475, RMSE 0.0160
[Open3D DEBUG] Residual : 1.82e-03 (# of elements : 490)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3411, RMSE 0.0160
[Open3D DEBUG] Residual : 1.85e-03 (# of elements : 481)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3270, RMSE 0.0156
[Open3D DEBUG] Residual : 1.81e-03 (# of elements : 461)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3255, RMSE 0.0155
[Open3D DEBUG] Residual : 1.98e-03 (# of elements : 459)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3213, RMSE 0.0154
[Open3D DEBUG] Residual : 2.06e-03 (# of elements : 453)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3142, RMSE 0.0156
[Open3D DEBUG] Residual : 1.99e-03 (# of elements : 443)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3071, RMSE 0.0156
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3043, RMSE 0.0156
[Open3D DEBUG] Residual : 1.99e-03 (# of elements : 429)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3078, RMSE 0.0157
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 434)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3071, RMSE 0.0157
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3085, RMSE 0.0157
[Open3D DEBUG] Residual : 1.95e-03 (# of elements : 435)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3078, RMSE 0.0157
[Open3D DEBUG] Residual : 1.95e-03 (# of elements : 434)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3121, RMSE 0.0158
[Open3D DEBUG] Residual : 1.95e-03 (# of elements : 440)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3113, RMSE 0.0157
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 439)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3092, RMSE 0.0157
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 436)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3113, RMSE 0.0157
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 439)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3092, RMSE 0.0156
[Open3D DEBUG] Residual : 1.96e-03 (# of elements : 436)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3071, RMSE 0.0156
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3071, RMSE 0.0156
[Open3D DEBUG] Residual : 1.99e-03 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3071, RMSE 0.0156
[Open3D DEBUG] Residual : 1.96e-03 (# of elements : 433)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3099, RMSE 0.0157
[Open3D DEBUG] Residual : 1.94e-03 (# of elements : 437)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3092, RMSE 0.0157
[Open3D DEBUG] Residual : 1.96e-03 (# of elements : 436)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3092, RMSE 0.0157
[Open3D DEBUG] Residual : 2.00e-03 (# of elements : 436)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.3085, RMSE 0.0157
[Open3D DEBUG] Residual : 1.98e-03 (# of elements : 435)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 4467 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.1726, RMSE 0.0084
[Open3D DEBUG] Residual : 1.80e-03 (# of elements : 771)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.1739, RMSE 0.0083
[Open3D DEBUG] Residual : 1.81e-03 (# of elements : 777)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.1751, RMSE 0.0082
[Open3D DEBUG] Residual : 1.84e-03 (# of elements : 782)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.1737, RMSE 0.0081
[Open3D DEBUG] Residual : 1.78e-03 (# of elements : 776)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.1773, RMSE 0.0081
[Open3D DEBUG] Residual : 1.71e-03 (# of elements : 792)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.1798, RMSE 0.0082
[Open3D DEBUG] Residual : 1.68e-03 (# of elements : 803)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.1791, RMSE 0.0082
[Open3D DEBUG] Residual : 1.69e-03 (# of elements : 800)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.1780, RMSE 0.0082
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 795)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.1755, RMSE 0.0082
[Open3D DEBUG] Residual : 1.74e-03 (# of elements : 784)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.1708, RMSE 0.0082
[Open3D DEBUG] Residual : 1.73e-03 (# of elements : 763)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.1733, RMSE 0.0083
[Open3D DEBUG] Residual : 1.77e-03 (# of elements : 774)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.1757, RMSE 0.0085
[Open3D DEBUG] Residual : 1.87e-03 (# of elements : 785)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.1748, RMSE 0.0084
[Open3D DEBUG] Residual : 1.90e-03 (# of elements : 781)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.1699, RMSE 0.0085
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 759)
[Open3D DEBUG] Read geometry::PointCloud: 20665 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 446 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.3206, RMSE 0.0321
[Open3D DEBUG] Residual : 2.78e-03 (# of elements : 143)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.3341, RMSE 0.0309
[Open3D DEBUG] Residual : 2.27e-03 (# of elements : 149)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.3498, RMSE 0.0315
[Open3D DEBUG] Residual : 2.10e-03 (# of elements : 156)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.3543, RMSE 0.0308
[Open3D DEBUG] Residual : 1.97e-03 (# of elements : 158)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.3408, RMSE 0.0297
[Open3D DEBUG] Residual : 1.95e-03 (# of elements : 152)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.3318, RMSE 0.0289
[Open3D DEBUG] Residual : 1.89e-03 (# of elements : 148)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.3341, RMSE 0.0291
[Open3D DEBUG] Residual : 1.81e-03 (# of elements : 149)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.3363, RMSE 0.0293
[Open3D DEBUG] Residual : 1.83e-03 (# of elements : 150)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.3274, RMSE 0.0285
[Open3D DEBUG] Residual : 1.78e-03 (# of elements : 146)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.3386, RMSE 0.0294
[Open3D DEBUG] Residual : 1.72e-03 (# of elements : 151)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.3386, RMSE 0.0295
[Open3D DEBUG] Residual : 1.75e-03 (# of elements : 151)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.3430, RMSE 0.0300
[Open3D DEBUG] Residual : 1.69e-03 (# of elements : 153)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3475, RMSE 0.0303
[Open3D DEBUG] Residual : 1.73e-03 (# of elements : 155)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3498, RMSE 0.0299
[Open3D DEBUG] Residual : 1.98e-03 (# of elements : 156)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3767, RMSE 0.0305
[Open3D DEBUG] Residual : 1.62e-03 (# of elements : 168)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3767, RMSE 0.0303
[Open3D DEBUG] Residual : 1.50e-03 (# of elements : 168)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3744, RMSE 0.0301
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 167)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3834, RMSE 0.0307
[Open3D DEBUG] Residual : 1.44e-03 (# of elements : 171)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3834, RMSE 0.0306
[Open3D DEBUG] Residual : 1.46e-03 (# of elements : 171)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3857, RMSE 0.0307
[Open3D DEBUG] Residual : 1.47e-03 (# of elements : 172)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3901, RMSE 0.0310
[Open3D DEBUG] Residual : 1.46e-03 (# of elements : 174)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3879, RMSE 0.0308
[Open3D DEBUG] Residual : 1.41e-03 (# of elements : 173)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3879, RMSE 0.0308
[Open3D DEBUG] Residual : 1.43e-03 (# of elements : 173)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3834, RMSE 0.0305
[Open3D DEBUG] Residual : 1.41e-03 (# of elements : 171)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3789, RMSE 0.0302
[Open3D DEBUG] Residual : 1.40e-03 (# of elements : 169)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3789, RMSE 0.0301
[Open3D DEBUG] Residual : 1.40e-03 (# of elements : 169)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3789, RMSE 0.0302
[Open3D DEBUG] Residual : 1.40e-03 (# of elements : 169)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3789, RMSE 0.0302
[Open3D DEBUG] Residual : 1.40e-03 (# of elements : 169)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3789, RMSE 0.0302
[Open3D DEBUG] Residual : 1.40e-03 (# of elements : 169)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 1410 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.2525, RMSE 0.0160
[Open3D DEBUG] Residual : 1.39e-03 (# of elements : 356)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2567, RMSE 0.0160
[Open3D DEBUG] Residual : 1.30e-03 (# of elements : 362)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2582, RMSE 0.0160
[Open3D DEBUG] Residual : 1.23e-03 (# of elements : 364)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2518, RMSE 0.0160
[Open3D DEBUG] Residual : 1.22e-03 (# of elements : 355)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2539, RMSE 0.0160
[Open3D DEBUG] Residual : 1.26e-03 (# of elements : 358)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.2546, RMSE 0.0159
[Open3D DEBUG] Residual : 1.14e-03 (# of elements : 359)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2546, RMSE 0.0157
[Open3D DEBUG] Residual : 1.10e-03 (# of elements : 359)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.2603, RMSE 0.0159
[Open3D DEBUG] Residual : 1.14e-03 (# of elements : 367)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.2674, RMSE 0.0157
[Open3D DEBUG] Residual : 1.14e-03 (# of elements : 377)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.2624, RMSE 0.0156
[Open3D DEBUG] Residual : 1.05e-03 (# of elements : 370)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.2837, RMSE 0.0160
[Open3D DEBUG] Residual : 1.08e-03 (# of elements : 400)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.2979, RMSE 0.0160
[Open3D DEBUG] Residual : 1.21e-03 (# of elements : 420)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.3014, RMSE 0.0154
[Open3D DEBUG] Residual : 1.17e-03 (# of elements : 425)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.3255, RMSE 0.0155
[Open3D DEBUG] Residual : 1.31e-03 (# of elements : 459)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.3340, RMSE 0.0147
[Open3D DEBUG] Residual : 1.25e-03 (# of elements : 471)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.3333, RMSE 0.0141
[Open3D DEBUG] Residual : 1.30e-03 (# of elements : 470)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.3277, RMSE 0.0140
[Open3D DEBUG] Residual : 1.25e-03 (# of elements : 462)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.3213, RMSE 0.0141
[Open3D DEBUG] Residual : 1.30e-03 (# of elements : 453)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.3199, RMSE 0.0145
[Open3D DEBUG] Residual : 1.42e-03 (# of elements : 451)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.3106, RMSE 0.0149
[Open3D DEBUG] Residual : 1.43e-03 (# of elements : 438)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.3128, RMSE 0.0148
[Open3D DEBUG] Residual : 1.46e-03 (# of elements : 441)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.3064, RMSE 0.0151
[Open3D DEBUG] Residual : 1.46e-03 (# of elements : 432)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.3128, RMSE 0.0150
[Open3D DEBUG] Residual : 1.46e-03 (# of elements : 441)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.3057, RMSE 0.0151
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 431)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.3135, RMSE 0.0149
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 442)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.3057, RMSE 0.0151
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 431)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.3128, RMSE 0.0149
[Open3D DEBUG] Residual : 1.47e-03 (# of elements : 441)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.3057, RMSE 0.0151
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 431)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.3128, RMSE 0.0149
[Open3D DEBUG] Residual : 1.46e-03 (# of elements : 441)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.3057, RMSE 0.0151
[Open3D DEBUG] Residual : 1.45e-03 (# of elements : 431)
[Open3D DEBUG] Pointcloud down sampled from 20665 points to 4467 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.1907, RMSE 0.0081
[Open3D DEBUG] Residual : 1.43e-03 (# of elements : 852)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.2042, RMSE 0.0080
[Open3D DEBUG] Residual : 1.07e-03 (# of elements : 912)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.2109, RMSE 0.0079
[Open3D DEBUG] Residual : 8.64e-04 (# of elements : 942)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.2107, RMSE 0.0079
[Open3D DEBUG] Residual : 8.29e-04 (# of elements : 941)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.2151, RMSE 0.0078
[Open3D DEBUG] Residual : 8.62e-04 (# of elements : 961)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.2210, RMSE 0.0078
[Open3D DEBUG] Residual : 8.79e-04 (# of elements : 987)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.2225, RMSE 0.0077
[Open3D DEBUG] Residual : 9.11e-04 (# of elements : 994)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.2214, RMSE 0.0077
[Open3D DEBUG] Residual : 8.98e-04 (# of elements : 989)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.2218, RMSE 0.0076
[Open3D DEBUG] Residual : 9.18e-04 (# of elements : 991)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.2227, RMSE 0.0077
[Open3D DEBUG] Residual : 8.95e-04 (# of elements : 995)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.2201, RMSE 0.0076
[Open3D DEBUG] Residual : 8.93e-04 (# of elements : 983)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.2227, RMSE 0.0077
[Open3D DEBUG] Residual : 9.03e-04 (# of elements : 995)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.2221, RMSE 0.0077
[Open3D DEBUG] Residual : 8.99e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.2201, RMSE 0.0076
[Open3D DEBUG] Residual : 8.94e-04 (# of elements : 983)
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 9945 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 238 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6957, RMSE 0.0217
[Open3D DEBUG] Residual : 4.05e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6979, RMSE 0.0226
[Open3D DEBUG] Residual : 4.08e-04 (# of elements : 305)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6957, RMSE 0.0224
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #30: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #31: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #32: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #33: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #34: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #35: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #36: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #37: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #38: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #39: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #40: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #41: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #42: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #43: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #44: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #45: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #46: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #47: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #48: Fitness 0.6957, RMSE 0.0223
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 304)
[Open3D DEBUG] ICP Iteration #49: Fitness 0.6957, RMSE 0.0222
[Open3D DEBUG] Residual : 3.98e-04 (# of elements : 304)
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 737 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6296, RMSE 0.0124
[Open3D DEBUG] Residual : 3.17e-04 (# of elements : 877)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.82e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.6324, RMSE 0.0118
[Open3D DEBUG] Residual : 2.83e-04 (# of elements : 881)
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] Pointcloud down sampled from 9945 points to 2213 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5488, RMSE 0.0063
[Open3D DEBUG] Residual : 2.44e-04 (# of elements : 2510)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5531, RMSE 0.0061
[Open3D DEBUG] Residual : 2.30e-04 (# of elements : 2530)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5529, RMSE 0.0061
[Open3D DEBUG] Residual : 2.29e-04 (# of elements : 2529)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5529, RMSE 0.0061
[Open3D DEBUG] Residual : 2.30e-04 (# of elements : 2529)
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 32313 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 526 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5886, RMSE 0.0215
[Open3D DEBUG] Residual : 4.81e-04 (# of elements : 412)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5886, RMSE 0.0216
[Open3D DEBUG] Residual : 4.60e-04 (# of elements : 412)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5886, RMSE 0.0216
[Open3D DEBUG] Residual : 4.55e-04 (# of elements : 412)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5886, RMSE 0.0215
[Open3D DEBUG] Residual : 4.56e-04 (# of elements : 412)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5886, RMSE 0.0215
[Open3D DEBUG] Residual : 4.56e-04 (# of elements : 412)
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 2207 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 1855 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.6026, RMSE 0.0120
[Open3D DEBUG] Residual : 4.28e-04 (# of elements : 1330)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.6008, RMSE 0.0120
[Open3D DEBUG] Residual : 4.19e-04 (# of elements : 1326)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.6013, RMSE 0.0120
[Open3D DEBUG] Residual : 4.13e-04 (# of elements : 1327)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.6013, RMSE 0.0121
[Open3D DEBUG] Residual : 4.11e-04 (# of elements : 1327)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.6017, RMSE 0.0121
[Open3D DEBUG] Residual : 4.09e-04 (# of elements : 1328)
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 7191 points.
[Open3D DEBUG] Pointcloud down sampled from 32313 points to 6360 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.5436, RMSE 0.0068
[Open3D DEBUG] Residual : 3.85e-04 (# of elements : 3909)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.5357, RMSE 0.0069
[Open3D DEBUG] Residual : 3.79e-04 (# of elements : 3852)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.5319, RMSE 0.0070
[Open3D DEBUG] Residual : 3.71e-04 (# of elements : 3825)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.5307, RMSE 0.0070
[Open3D DEBUG] Residual : 3.75e-04 (# of elements : 3816)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.5301, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3812)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.5316, RMSE 0.0070
[Open3D DEBUG] Residual : 3.74e-04 (# of elements : 3823)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.5318, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3824)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.5314, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3821)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.5316, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3823)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.5315, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3822)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.5318, RMSE 0.0070
[Open3D DEBUG] Residual : 3.74e-04 (# of elements : 3824)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.5315, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3822)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.5318, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3824)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.5315, RMSE 0.0070
[Open3D DEBUG] Residual : 3.73e-04 (# of elements : 3822)
[Open3D DEBUG] Read geometry::PointCloud: 35667 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Read geometry::PointCloud: 22195 vertices.
[Open3D DEBUG] [RemoveNoneFinitePoints] 0 nan points have been removed.
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 700 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 437 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4257, RMSE 0.0273
[Open3D DEBUG] Residual : 9.79e-04 (# of elements : 298)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4571, RMSE 0.0245
[Open3D DEBUG] Residual : 6.41e-04 (# of elements : 320)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4614, RMSE 0.0239
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 323)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4643, RMSE 0.0239
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 325)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4657, RMSE 0.0239
[Open3D DEBUG] Residual : 6.20e-04 (# of elements : 326)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4671, RMSE 0.0239
[Open3D DEBUG] Residual : 6.24e-04 (# of elements : 327)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4671, RMSE 0.0239
[Open3D DEBUG] Residual : 6.24e-04 (# of elements : 327)
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 2207 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 1393 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4431, RMSE 0.0123
[Open3D DEBUG] Residual : 6.52e-04 (# of elements : 978)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4463, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 985)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.20e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.15e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.25e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.24e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4499, RMSE 0.0122
[Open3D DEBUG] Residual : 6.23e-04 (# of elements : 993)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.32e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #14: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #15: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #16: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #17: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #18: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #19: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #20: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #21: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #22: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #23: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #24: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #25: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #26: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #27: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] ICP Iteration #28: Fitness 0.4486, RMSE 0.0121
[Open3D DEBUG] Residual : 6.18e-04 (# of elements : 990)
[Open3D DEBUG] ICP Iteration #29: Fitness 0.4495, RMSE 0.0121
[Open3D DEBUG] Residual : 6.12e-04 (# of elements : 992)
[Open3D DEBUG] Pointcloud down sampled from 35667 points to 7191 points.
[Open3D DEBUG] Pointcloud down sampled from 22195 points to 4574 points.
[Open3D DEBUG] InitializePointCloudForColoredICP
[Open3D DEBUG] ICP Iteration #0: Fitness 0.4101, RMSE 0.0065
[Open3D DEBUG] Residual : 5.45e-04 (# of elements : 2949)
[Open3D DEBUG] ICP Iteration #1: Fitness 0.4155, RMSE 0.0066
[Open3D DEBUG] Residual : 5.16e-04 (# of elements : 2988)
[Open3D DEBUG] ICP Iteration #2: Fitness 0.4158, RMSE 0.0066
[Open3D DEBUG] Residual : 5.19e-04 (# of elements : 2990)
[Open3D DEBUG] ICP Iteration #3: Fitness 0.4162, RMSE 0.0066
[Open3D DEBUG] Residual : 5.16e-04 (# of elements : 2993)
[Open3D DEBUG] ICP Iteration #4: Fitness 0.4164, RMSE 0.0066
[Open3D DEBUG] Residual : 5.16e-04 (# of elements : 2994)
[Open3D DEBUG] ICP Iteration #5: Fitness 0.4166, RMSE 0.0066
[Open3D DEBUG] Residual : 5.17e-04 (# of elements : 2996)
[Open3D DEBUG] ICP Iteration #6: Fitness 0.4166, RMSE 0.0066
[Open3D DEBUG] Residual : 5.17e-04 (# of elements : 2996)
[Open3D DEBUG] ICP Iteration #7: Fitness 0.4165, RMSE 0.0066
[Open3D DEBUG] Residual : 5.18e-04 (# of elements : 2995)
[Open3D DEBUG] ICP Iteration #8: Fitness 0.4166, RMSE 0.0066
[Open3D DEBUG] Residual : 5.17e-04 (# of elements : 2996)
[Open3D DEBUG] ICP Iteration #9: Fitness 0.4166, RMSE 0.0066
[Open3D DEBUG] Residual : 5.16e-04 (# of elements : 2996)
[Open3D DEBUG] ICP Iteration #10: Fitness 0.4168, RMSE 0.0066
[Open3D DEBUG] Residual : 5.18e-04 (# of elements : 2997)
[Open3D DEBUG] ICP Iteration #11: Fitness 0.4164, RMSE 0.0066
[Open3D DEBUG] Residual : 5.17e-04 (# of elements : 2994)
[Open3D DEBUG] ICP Iteration #12: Fitness 0.4166, RMSE 0.0066
[Open3D DEBUG] Residual : 5.18e-04 (# of elements : 2996)
[Open3D DEBUG] ICP Iteration #13: Fitness 0.4165, RMSE 0.0066
[Open3D DEBUG] Residual : 5.17e-04 (# of elements : 2995)
[Open3D DEBUG] Validating PoseGraph - finished.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 10 nodes and 35 edges.
[Open3D DEBUG] Line process weight : 74.734800
[Open3D DEBUG] [Initial ] residual : 3.763148e+04, lambda : 9.008583e-02
[Open3D DEBUG] [Iteration 00] residual : 2.633536e+03, valid edges : 5, time : 0.000 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.212536e+03, valid edges : 19, time : 0.000 sec.
[Open3D DEBUG] [Iteration 02] residual : 6.503863e+02, valid edges : 20, time : 0.000 sec.
[Open3D DEBUG] [Iteration 03] residual : 4.958651e+02, valid edges : 24, time : 0.000 sec.
[Open3D DEBUG] [Iteration 04] residual : 3.866140e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 05] residual : 3.698281e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 06] residual : 3.661318e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 07] residual : 3.650482e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 08] residual : 3.647596e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 09] residual : 3.646878e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 10] residual : 3.646694e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 11] residual : 3.646643e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 12] residual : 3.646627e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 13] residual : 3.646621e+02, valid edges :
reading dataset/realsense/fragments/fragment_002.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_007.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_001.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_003.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_002.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_004.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_007.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_003.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_005.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_004.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_008.ply ...
reading dataset/realsense/fragments/fragment_009.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_005.ply ...
reading dataset/realsense/fragments/fragment_006.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
reading dataset/realsense/fragments/fragment_005.ply ...
reading dataset/realsense/fragments/fragment_008.ply ...
voxel_size 0.050000
voxel_size 0.025000
voxel_size 0.012500
registration::PoseGraph with 10 nodes and 35 edges.
integrate the whole RGBD sequence using estimated camera pose.
Fragment 000 / 009 :: integrate rgbd frame 0 (1 of 100).
Fragment 000 / 009 :: integrate rgbd frame 1 (2 of 100).
Fragment 000 / 009 :: integrate rgbd frame 2 (3 of 100).
Fragment 000 / 009 :: integrate rgbd frame 3 (4 of 100).
Fragment 000 / 009 :: integrate rgbd frame 4 (5 of 100).
Fragment 000 / 009 :: integrate rgbd frame 5 (6 of 100).
Fragment 000 / 009 :: integrate rgbd frame 6 (7 of 100).
Fragment 000 / 009 :: integrate rgbd frame 7 (8 of 100).
Fragment 000 / 009 :: integrate rgbd frame 8 (9 of 100).
Fragment 000 / 009 :: integrate rgbd frame 9 (10 of 100).
Fragment 000 / 009 :: integrate rgbd frame 10 (11 of 100).
Fragment 000 / 009 :: integrate rgbd frame 11 (12 of 100).
Fragment 000 / 009 :: integrate rgbd frame 12 (13 of 100).
Fragment 000 / 009 :: integrate rgbd frame 13 (14 of 100).
Fragment 000 / 009 :: integrate rgbd frame 14 (15 of 100).
Fragment 000 / 009 :: integrate rgbd frame 15 (16 of 100).
Fragment 000 / 009 :: integrate rgbd frame 16 (17 of 100).
Fragment 000 / 009 :: integrate rgbd frame 17 (18 of 100).
Fragment 000 / 009 :: integrate rgbd frame 18 (19 of 100).
Fragment 000 / 009 :: integrate rgbd frame 19 (20 of 100).
Fragment 000 / 009 :: integrate rgbd frame 20 (21 of 100).
Fragment 000 / 009 :: integrate rgbd frame 21 (22 of 100).
Fragment 000 / 009 :: integrate rgbd frame 22 (23 of 100).
Fragment 000 / 009 :: integrate rgbd frame 23 (24 of 100).
Fragment 000 / 009 :: integrate rgbd frame 24 (25 of 100).
Fragment 000 / 009 :: integrate rgbd frame 25 (26 of 100).
Fragment 000 / 009 :: integrate rgbd frame 26 (27 of 100).
Fragment 000 / 009 :: integrate rgbd frame 27 (28 of 100).
Fragment 000 / 009 :: integrate rgbd frame 28 (29 of 100).
Fragment 000 / 009 :: integrate rgbd frame 29 (30 of 100).
Fragment 000 / 009 :: integrate rgbd frame 30 (31 of 100).
Fragment 000 / 009 :: integrate rgbd frame 31 (32 of 100).
Fragment 000 / 009 :: integrate rgbd frame 32 (33 of 100).
Fragment 000 / 009 :: integrate rgbd frame 33 (34 of 100).
Fragment 000 / 009 :: integrate rgbd frame 34 (35 of 100).
Fragment 000 / 009 :: integrate rgbd frame 35 (36 of 100).
Fragment 000 / 009 :: integrate rgbd frame 36 (37 of 100).
Fragment 000 / 009 :: integrate rgbd frame 37 (38 of 100).
Fragment 000 / 009 :: integrate rgbd frame 38 (39 of 100).
Fragment 000 / 009 :: integrate rgbd frame 39 (40 of 100).
Fragment 000 / 009 :: integrate rgbd frame 40 (41 of 100).
Fragment 000 / 009 :: integrate rgbd frame 41 (42 of 100).
Fragment 000 / 009 :: integrate rgbd frame 42 (43 of 100).
Fragment 000 / 009 :: integrate rgbd frame 43 (44 of 100).
Fragment 000 / 009 :: integrate rgbd frame 44 (45 of 100).
Fragment 000 / 009 :: integrate rgbd frame 45 (46 of 100).
Fragment 000 / 009 :: integrate rgbd frame 46 (47 of 100).
Fragment 000 / 009 :: integrate rgbd frame 47 (48 of 100).
Fragment 000 / 009 :: integrate rgbd frame 48 (49 of 100).
Fragment 000 / 009 :: integrate rgbd frame 49 (50 of 100).
Fragment 000 / 009 :: integrate rgbd frame 50 (51 of 100).
Fragment 000 / 009 :: integrate rgbd frame 51 (52 of 100).
Fragment 000 / 009 :: integrate rgbd frame 52 (53 of 100).
Fragment 000 / 009 :: integrate rgbd frame 53 (54 of 100).
Fragment 000 / 009 :: integrate rgbd frame 54 (55 of 100).
Fragment 000 / 009 :: integrate rgbd frame 55 (56 of 100).
Fragment 000 / 009 :: integrate rgbd frame 56 (57 of 100).
Fragment 000 / 009 :: integrate rgbd frame 57 (58 of 100).
Fragment 000 / 009 :: integrate rgbd frame 58 (59 of 100).
Fragment 000 / 009 :: integrate rgbd frame 59 (60 of 100).
Fragment 000 / 009 :: integrate rgbd frame 60 (61 of 100).
Fragment 000 / 009 :: integrate rgbd frame 61 (62 of 100).
Fragment 000 / 009 :: integrate rgbd frame 62 (63 of 100).
Fragment 000 / 009 :: integrate rgbd frame 63 (64 of 100).
Fragment 000 / 009 :: integrate rgbd frame 64 (65 of 100).
Fragment 000 / 009 :: integrate rgbd frame 65 (66 of 100).
Fragment 000 / 009 :: integrate rgbd frame 66 (67 of 100).
Fragment 000 / 009 :: integrate rgbd frame 67 (68 of 100).
Fragment 000 / 009 :: integrate rgbd frame 68 (69 of 100).
Fragment 000 / 009 :: integrate rgbd frame 69 (70 of 100).
Fragment 000 / 009 :: integrate rgbd frame 70 (71 of 100).
Fragment 000 / 009 :: integrate rgbd frame 71 (72 of 100).
Fragment 000 / 009 :: integrate rgbd frame 72 (73 of 100).
Fragment 000 / 009 :: integrate rgbd frame 73 (74 of 100).
Fragment 000 / 009 :: integrate rgbd frame 74 (75 of 100).
Fragment 000 / 009 :: integrate rgbd frame 75 (76 of 100).
Fragment 000 / 009 :: integrate rgbd frame 76 (77 of 100).
Fragment 000 / 009 :: integrate rgbd frame 77 (78 of 100).
Fragment 000 / 009 :: integrate rgbd frame 78 (79 of 100).
Fragment 000 / 009 :: integrate rgbd frame 79 (80 of 100).
Fragment 000 / 009 :: integrate rgbd frame 80 (81 of 100).
Fragment 000 / 009 :: integrate rgbd frame 81 (82 of 100).
Fragment 000 / 009 :: integrate rgbd frame 82 (83 of 100).
Fragment 000 / 009 :: integrate rgbd frame 83 (84 of 100).
Fragment 000 / 009 :: integrate rgbd frame 84 (85 of 100).
Fragment 000 / 009 :: integrate rgbd frame 85 (86 of 100).
Fragment 000 / 009 :: integrate rgbd frame 86 (87 of 100).
Fragment 000 / 009 :: integrate rgbd frame 87 (88 of 100).
Fragment 000 / 009 :: integrate rgbd frame 88 (89 of 100).
Fragment 000 / 009 :: integrate rgbd frame 89 (90 of 100).
Fragment 000 / 009 :: integrate rgbd frame 90 (91 of 100).
Fragment 000 / 009 :: integrate rgbd frame 91 (92 of 100).
Fragment 000 / 009 :: integrate rgbd frame 92 (93 of 100).
Fragment 000 / 009 :: integrate rgbd frame 93 (94 of 100).
Fragment 000 / 009 :: integrate rgbd frame 94 (95 of 100).
Fragment 000 / 009 :: integrate rgbd frame 95 (96 of 100).
Fragment 000 / 009 :: integrate rgbd frame 96 (97 of 100).
Fragment 000 / 009 :: integrate rgbd frame 97 (98 of 100).
Fragment 000 / 009 :: integrate rgbd frame 98 (99 of 100).
Fragment 000 / 009 :: integrate rgbd frame 99 (100 of 100).
Fragment 001 / 009 :: integrate rgbd frame 100 (1 of 100).
Fragment 001 / 009 :: integrate rgbd frame 101 (2 of 100).
Fragment 001 / 009 :: integrate rgbd frame 102 (3 of 100).
Fragment 001 / 009 :: integrate rgbd frame 103 (4 of 100).
Fragment 001 / 009 :: integrate rgbd frame 104 (5 of 100).
Fragment 001 / 009 :: integrate rgbd frame 105 (6 of 100).
Fragment 001 / 009 :: integrate rgbd frame 106 (7 of 100).
Fragment 001 / 009 :: integrate rgbd frame 107 (8 of 100).
Fragment 001 / 009 :: integrate rgbd frame 108 (9 of 100).
Fragment 001 / 009 :: integrate rgbd frame 109 (10 of 100).
Fragment 001 / 009 :: integrate rgbd frame 110 (11 of 100).
Fragment 001 / 009 :: integrate rgbd frame 111 (12 of 100).
Fragment 001 / 009 :: integrate rgbd frame 112 (13 of 100).
Fragment 001 / 009 :: integrate rgbd frame 113 (14 of 100).
Fragment 001 / 009 :: integrate rgbd frame 114 (15 of 100).
Fragment 001 / 009 :: integrate rgbd frame 115 (16 of 100).
Fragment 001 / 009 :: integrate rgbd frame 116 (17 of 100).
Fragment 001 / 009 :: integrate rgbd frame 117 (18 of 100).
Fragment 001 / 009 :: integrate rgbd frame 118 (19 of 100).
Fragment 001 / 009 :: integrate rgbd frame 119 (20 of 100).
Fragment 001 / 009 :: integrate rgbd frame 120 (21 of 100).
Fragment 001 / 009 :: integrate rgbd frame 121 (22 of 100).
Fragment 001 / 009 :: integrate rgbd frame 122 (23 of 100).
Fragment 001 / 009 :: integrate rgbd frame 123 (24 of 100).
Fragment 001 / 009 :: integrate rgbd frame 124 (25 of 100).
Fragment 001 / 009 :: integrate rgbd frame 125 (26 of 100).
Fragment 001 / 009 :: integrate rgbd frame 126 (27 of 100).
Fragment 001 / 009 :: integrate rgbd frame 127 (28 of 100).
Fragment 001 / 009 :: integrate rgbd frame 128 (29 of 100).
Fragment 001 / 009 :: integrate rgbd frame 129 (30 of 100).
Fragment 001 / 009 :: integrate rgbd frame 130 (31 of 100).
Fragment 001 / 009 :: integrate rgbd frame 131 (32 of 100).
Fragment 001 / 009 :: integrate rgbd frame 132 (33 of 100).
Fragment 001 / 009 :: integrate rgbd frame 133 (34 of 100).
Fragment 001 / 009 :: integrate rgbd frame 134 (35 of 100).
Fragment 001 / 009 :: integrate rgbd frame 135 (36 of 100).
Fragment 001 / 009 :: integrate rgbd frame 136 (37 of 100).
Fragment 001 / 009 :: integrate rgbd frame 137 (38 of 100).
Fragment 001 / 009 :: integrate rgbd frame 138 (39 of 100).
Fragment 001 / 009 :: integrate rgbd frame 139 (40 of 100).
Fragment 001 / 009 :: integrate rgbd frame 140 (41 of 100).
Fragment 001 / 009 :: integrate rgbd frame 141 (42 of 100).
Fragment 001 / 009 :: integrate rgbd frame 142 (43 of 100).
Fragment 001 / 009 :: integrate rgbd frame 143 (44 of 100).
Fragment 001 / 009 :: integrate rgbd frame 144 (45 of 100).
Fragment 001 / 009 :: integrate rgbd frame 145 (46 of 100).
Fragment 001 / 009 :: integrate rgbd frame 146 (47 of 100).
Fragment 001 / 009 :: integrate rgbd frame 147 (48 of 100).
Fragment 001 / 009 :: integrate rgbd frame 148 (49 of 100).
Fragment 001 / 009 :: integrate rgbd frame 149 (50 of 100).
Fragment 001 / 009 :: integrate rgbd frame 150 (51 of 100).
Fragment 001 / 009 :: integrate rgbd frame 151 (52 of 100).
Fragment 001 / 009 :: integrate rgbd frame 152 (53 of 100).
Fragment 001 / 009 :: integrate rgbd frame 153 (54 of 100).
Fragment 001 / 009 :: integrate rgbd frame 154 (55 of 100).
Fragment 001 / 009 :: integrate rgbd frame 155 (56 of 100).
Fragment 001 / 009 :: integrate rgbd frame 156 (57 of 100).
Fragment 001 / 009 :: integrate rgbd frame 157 (58 of 100).
Fragment 001 / 009 :: integrate rgbd frame 158 (59 of 100).
Fragment 001 / 009 :: integrate rgbd frame 159 (60 of 100).
Fragment 001 / 009 :: integrate rgbd frame 160 (61 of 100).
Fragment 001 / 009 :: integrate rgbd frame 161 (62 of 100).
Fragment 001 / 009 :: integrate rgbd frame 162 (63 of 100).
Fragment 001 / 009 :: integrate rgbd frame 163 (64 of 100).
Fragment 001 / 009 :: integrate rgbd frame 164 (65 of 100).
Fragment 001 / 009 :: integrate rgbd frame 165 (66 of 100).
Fragment 001 / 009 :: integrate rgbd frame 166 (67 of 100).
Fragment 001 / 009 :: integrate rgbd frame 167 (68 of 100).
Fragment 001 / 009 :: integrate rgbd frame 168 (69 of 100).
Fragment 001 / 009 :: integrate rgbd frame 169 (70 of 100).
Fragment 001 / 009 :: integrate rgbd frame 170 (71 of 100).
Fragment 001 / 009 :: integrate rgbd frame 171 (72 of 100).
Fragment 001 / 009 :: integrate rgbd frame 172 (73 of 100).
Fragment 001 / 009 :: integrate rgbd frame 173 (74 of 100).
Fragment 001 / 009 :: integrate rgbd frame 174 (75 of 100).
Fragment 001 / 009 :: integrate rgbd frame 175 (76 of 100).
Fragment 001 / 009 :: integrate rgbd frame 176 (77 of 100).
Fragment 001 / 009 :: integrate rgbd frame 177 (78 of 100).
Fragment 001 / 009 :: integrate rgbd frame 178 (79 of 100).
Fragment 001 / 009 :: integrate rgbd frame 179 (80 of 100).
Fragment 001 / 009 :: integrate rgbd frame 180 (81 of 100).
Fragment 001 / 009 :: integrate rgbd frame 181 (82 of 100).
Fragment 001 / 009 :: integrate rgbd frame 182 (83 of 100).
Fragment 001 / 009 :: integrate rgbd frame 183 (84 of 100).
Fragment 001 / 009 :: integrate rgbd frame 184 (85 of 100).
Fragment 001 / 009 :: integrate rgbd frame 185 (86 of 100).
Fragment 001 / 009 :: integrate rgbd frame 186 (87 of 100).
Fragment 001 / 009 :: integrate rgbd frame 187 (88 of 100).
Fragment 001 / 009 :: integrate rgbd frame 188 (89 of 100).
Fragment 001 / 009 :: integrate rgbd frame 189 (90 of 100).
Fragment 001 / 009 :: integrate rgbd frame 190 (91 of 100).
Fragment 001 / 009 :: integrate rgbd frame 191 (92 of 100).
Fragment 001 / 009 :: integrate rgbd frame 192 (93 of 100).
Fragment 001 / 009 :: integrate rgbd frame 193 (94 of 100).
Fragment 001 / 009 :: integrate rgbd frame 194 (95 of 100).
Fragment 001 / 009 :: integrate rgbd frame 195 (96 of 100).
Fragment 001 / 009 :: integrate rgbd frame 196 (97 of 100).
Fragment 001 / 009 :: integrate rgbd frame 197 (98 of 100).
Fragment 001 / 009 :: integrate rgbd frame 198 (99 of 100).
Fragment 001 / 009 :: integrate rgbd frame 199 (100 of 100).
Fragment 002 / 009 :: integrate rgbd frame 200 (1 of 100).
Fragment 002 / 009 :: integrate rgbd frame 201 (2 of 100).
Fragment 002 / 009 :: integrate rgbd frame 202 (3 of 100).
Fragment 002 / 009 :: integrate rgbd frame 203 (4 of 100).
Fragment 002 / 009 :: integrate rgbd frame 204 (5 of 100).
Fragment 002 / 009 :: integrate rgbd frame 205 (6 of 100).
Fragment 002 / 009 :: integrate rgbd frame 206 (7 of 100).
Fragment 002 / 009 :: integrate rgbd frame 207 (8 of 100).
Fragment 002 / 009 :: integrate rgbd frame 208 (9 of 100).
Fragment 002 / 009 :: integrate rgbd frame 209 (10 of 100).
Fragment 002 / 009 :: integrate rgbd frame 210 (11 of 100).
Fragment 002 / 009 :: integrate rgbd frame 211 (12 of 100).
Fragment 002 / 009 :: integrate rgbd frame 212 (13 of 100).
Fragment 002 / 009 :: integrate rgbd frame 213 (14 of 100).
Fragment 002 / 009 :: integrate rgbd frame 214 (15 of 100).
Fragment 002 / 009 :: integrate rgbd frame 215 (16 of 100).
Fragment 002 / 009 :: integrate rgbd frame 216 (17 of 100).
Fragment 002 / 009 :: integrate rgbd frame 217 (18 of 100).
Fragment 002 / 009 :: integrate rgbd frame 218 (19 of 100).
Fragment 002 / 009 :: integrate rgbd frame 219 (20 of 100).
Fragment 002 / 009 :: integrate rgbd frame 220 (21 of 100).
Fragment 002 / 009 :: integrate rgbd frame 221 (22 of 100).
Fragment 002 / 009 :: integrate rgbd frame 222 (23 of 100).
Fragment 002 / 009 :: integrate rgbd frame 223 (24 of 100).
Fragment 002 / 009 :: integrate rgbd frame 224 (25 of 100).
Fragment 002 / 009 :: integrate rgbd frame 225 (26 of 100).
Fragment 002 / 009 :: integrate rgbd frame 226 (27 of 100).
Fragment 002 / 009 :: integrate rgbd frame 227 (28 of 100).
Fragment 002 / 009 :: integrate rgbd frame 228 (29 of 100).
Fragment 002 / 009 :: integrate rgbd frame 229 (30 of 100).
Fragment 002 / 009 :: integrate rgbd frame 230 (31 of 100).
Fragment 002 / 009 :: integrate rgbd frame 231 (32 of 100).
Fragment 002 / 009 :: integrate rgbd frame 232 (33 of 100).
Fragment 002 / 009 :: integrate rgbd frame 233 (34 of 100).
Fragment 002 / 009 :: integrate rgbd frame 234 (35 of 100).
Fragment 002 / 009 :: integrate rgbd frame 235 (36 of 100).
Fragment 002 / 009 :: integrate rgbd frame 236 (37 of 100).
Fragment 002 / 009 :: integrate rgbd frame 237 (38 of 100).
Fragment 002 / 009 :: integrate rgbd frame 238 (39 of 100).
Fragment 002 / 009 :: integrate rgbd frame 239 (40 of 100).
Fragment 002 / 009 :: integrate rgbd frame 240 (41 of 100).
Fragment 002 / 009 :: integrate rgbd frame 241 (42 of 100).
Fragment 002 / 009 :: integrate rgbd frame 242 (43 of 100).
Fragment 002 / 009 :: integrate rgbd frame 243 (44 of 100).
Fragment 002 / 009 :: integrate rgbd frame 244 (45 of 100).
Fragment 002 / 009 :: integrate rgbd frame 245 (46 of 100).
Fragment 002 / 009 :: integrate rgbd frame 246 (47 of 100).
Fragment 002 / 009 :: integrate rgbd frame 247 (48 of 100).
Fragment 002 / 009 :: integrate rgbd frame 248 (49 of 100).
Fragment 002 / 009 :: integrate rgbd frame 249 (50 of 100).
Fragment 002 / 009 :: integrate rgbd frame 250 (51 of 100).
Fragment 002 / 009 :: integrate rgbd frame 251 (52 of 100).
Fragment 002 / 009 :: integrate rgbd frame 252 (53 of 100).
Fragment 002 / 009 :: integrate rgbd frame 253 (54 of 100).
Fragment 002 / 009 :: integrate rgbd frame 254 (55 of 100).
Fragment 002 / 009 :: integrate rgbd frame 255 (56 of 100).
Fragment 002 / 009 :: integrate rgbd frame 256 (57 of 100).
Fragment 002 / 009 :: integrate rgbd frame 257 (58 of 100).
Fragment 002 / 009 :: integrate rgbd frame 258 (59 of 100).
Fragment 002 / 009 :: integrate rgbd frame 259 (60 of 100).
Fragment 002 / 009 :: integrate rgbd frame 260 (61 of 100).
Fragment 002 / 009 :: integrate rgbd frame 261 (62 of 100).
Fragment 002 / 009 :: integrate rgbd frame 262 (63 of 100).
Fragment 002 / 009 :: integrate rgbd frame 263 (64 of 100).
Fragment 002 / 009 :: integrate rgbd frame 264 (65 of 100).
Fragment 002 / 009 :: integrate rgbd frame 265 (66 of 100).
Fragment 002 / 009 :: integrate rgbd frame 266 (67 of 100).
Fragment 002 / 009 :: integrate rgbd frame 267 (68 of 100).
Fragment 002 / 009 :: integrate rgbd frame 268 (69 of 100).
Fragment 002 / 009 :: integrate rgbd frame 269 (70 of 100).
Fragment 002 / 009 :: integrate rgbd frame 270 (71 of 100).
Fragment 002 / 009 :: integrate rgbd frame 271 (72 of 100).
Fragment 002 / 009 :: integrate rgbd frame 272 (73 of 100).
Fragment 002 / 009 :: integrate rgbd frame 273 (74 of 100).
Fragment 002 / 009 :: integrate rgbd frame 274 (75 of 100).
Fragment 002 / 009 :: integrate rgbd frame 275 (76 of 100).
Fragment 002 / 009 :: integrate rgbd frame 276 (77 of 100).
Fragment 002 / 009 :: integrate rgbd frame 277 (78 of 100).
Fragment 002 / 009 :: integrate rgbd frame 278 (79 of 100).
Fragment 002 / 009 :: integrate rgbd frame 279 (80 of 100).
Fragment 002 / 009 :: integrate rgbd frame 280 (81 of 100).
Fragment 002 / 009 :: integrate rgbd frame 281 (82 of 100).
Fragment 002 / 009 :: integrate rgbd frame 282 (83 of 100).
Fragment 002 / 009 :: integrate rgbd frame 283 (84 of 100).
Fragment 002 / 009 :: integrate rgbd frame 284 (85 of 100).
Fragment 002 / 009 :: integrate rgbd frame 285 (86 of 100).
Fragment 002 / 009 :: integrate rgbd frame 286 (87 of 100).
Fragment 002 / 009 :: integrate rgbd frame 287 (88 of 100).
Fragment 002 / 009 :: integrate rgbd frame 288 (89 of 100).
Fragment 002 / 009 :: integrate rgbd frame 289 (90 of 100).
Fragment 002 / 009 :: integrate rgbd frame 290 (91 of 100).
Fragment 002 / 009 :: integrate rgbd frame 291 (92 of 100).
Fragment 002 / 009 :: integrate rgbd frame 292 (93 of 100).
Fragment 002 / 009 :: integrate rgbd frame 293 (94 of 100).
Fragment 002 / 009 :: integrate rgbd frame 294 (95 of 100).
Fragment 002 / 009 :: integrate rgbd frame 295 (96 of 100).
Fragment 002 / 009 :: integrate rgbd frame 296 (97 of 100).
Fragment 002 / 009 :: integrate rgbd frame 297 (98 of 100).
Fragment 002 / 009 :: integrate rgbd frame 298 (99 of 100).
Fragment 002 / 009 :: integrate rgbd frame 299 (100 of 100).
Fragment 003 / 009 :: integrate rgbd frame 300 (1 of 100).
Fragment 003 / 009 :: integrate rgbd frame 301 (2 of 100).
Fragment 003 / 009 :: integrate rgbd frame 302 (3 of 100).
Fragment 003 / 009 :: integrate rgbd frame 303 (4 of 100).
Fragment 003 / 009 :: integrate rgbd frame 304 (5 of 100).
Fragment 003 / 009 :: integrate rgbd frame 305 (6 of 100).
Fragment 003 / 009 :: integrate rgbd frame 306 (7 of 100).
Fragment 003 / 009 :: integrate rgbd frame 307 (8 of 100).
Fragment 003 / 009 :: integrate rgbd frame 308 (9 of 100).
Fragment 003 / 009 :: integrate rgbd frame 309 (10 of 100).
Fragment 003 / 009 :: integrate rgbd frame 310 (11 of 100).
Fragment 003 / 009 :: integrate rgbd frame 311 (12 of 100).
Fragment 003 / 009 :: integrate rgbd frame 312 (13 of 100).
Fragment 003 / 009 :: integrate rgbd frame 313 (14 of 100).
Fragment 003 / 009 :: integrate rgbd frame 314 (15 of 100).
Fragment 003 / 009 :: integrate rgbd frame 315 (16 of 100).
Fragment 003 / 009 :: integrate rgbd frame 316 (17 of 100).
Fragment 003 / 009 :: integrate rgbd frame 317 (18 of 100).
Fragment 003 / 009 :: integrate rgbd frame 318 (19 of 100).
Fragment 003 / 009 :: integrate rgbd frame 319 (20 of 100).
Fragment 003 / 009 :: integrate rgbd frame 320 (21 of 100).
Fragment 003 / 009 :: integrate rgbd frame 321 (22 of 100).
Fragment 003 / 009 :: integrate rgbd frame 322 (23 of 100).
Fragment 003 / 009 :: integrate rgbd frame 323 (24 of 100).
Fragment 003 / 009 :: integrate rgbd frame 324 (25 of 100).
Fragment 003 / 009 :: integrate rgbd frame 325 (26 of 100).
Fragment 003 / 009 :: integrate rgbd frame 326 (27 of 100).
Fragment 003 / 009 :: integrate rgbd frame 327 (28 of 100).
Fragment 003 / 009 :: integrate rgbd frame 328 (29 of 100).
Fragment 003 / 009 :: integrate rgbd frame 329 (30 of 100).
Fragment 003 / 009 :: integrate rgbd frame 330 (31 of 100).
Fragment 003 / 009 :: integrate rgbd frame 331 (32 of 100).
Fragment 003 / 009 :: integrate rgbd frame 332 (33 of 100).
Fragment 003 / 009 :: integrate rgbd frame 333 (34 of 100).
Fragment 003 / 009 :: integrate rgbd frame 334 (35 of 100).
Fragment 003 / 009 :: integrate rgbd frame 335 (36 of 100).
Fragment 003 / 009 :: integrate rgbd frame 336 (37 of 100).
Fragment 003 / 009 :: integrate rgbd frame 337 (38 of 100).
Fragment 003 / 009 :: integrate rgbd frame 338 (39 of 100).
Fragment 003 / 009 :: integrate rgbd frame 339 (40 of 100).
Fragment 003 / 009 :: integrate rgbd frame 340 (41 of 100).
Fragment 003 / 009 :: integrate rgbd frame 341 (42 of 100).
Fragment 003 / 009 :: integrate rgbd frame 342 (43 of 100).
Fragment 003 / 009 :: integrate rgbd frame 343 (44 of 100).
Fragment 003 / 009 :: integrate rgbd frame 344 (45 of 100).
Fragment 003 / 009 :: integrate rgbd frame 345 (46 of 100).
Fragment 003 / 009 :: integrate rgbd frame 346 (47 of 100).
Fragment 003 / 009 :: integrate rgbd frame 347 (48 of 100).
Fragment 003 / 009 :: integrate rgbd frame 348 (49 of 100).
Fragment 003 / 009 :: integrate rgbd frame 349 (50 of 100).
Fragment 003 / 009 :: integrate rgbd frame 350 (51 of 100).
Fragment 003 / 009 :: integrate rgbd frame 351 (52 of 100).
Fragment 003 / 009 :: integrate rgbd frame 352 (53 of 100).
Fragment 003 / 009 :: integrate rgbd frame 353 (54 of 100).
Fragment 003 / 009 :: integrate rgbd frame 354 (55 of 100).
Fragment 003 / 009 :: integrate rgbd frame 355 (56 of 100).
Fragment 003 / 009 :: integrate rgbd frame 356 (57 of 100).
Fragment 003 / 009 :: integrate rgbd frame 357 (58 of 100).
Fragment 003 / 009 :: integrate rgbd frame 358 (59 of 100).
Fragment 003 / 009 :: integrate rgbd frame 359 (60 of 100).
Fragment 003 / 009 :: integrate rgbd frame 360 (61 of 100).
Fragment 003 / 009 :: integrate rgbd frame 361 (62 of 100).
Fragment 003 / 009 :: integrate rgbd frame 362 (63 of 100).
Fragment 003 / 009 :: integrate rgbd frame 363 (64 of 100).
Fragment 003 / 009 :: integrate rgbd frame 364 (65 of 100).
Fragment 003 / 009 :: integrate rgbd frame 365 (66 of 100).
Fragment 003 / 009 :: integrate rgbd frame 366 (67 of 100).
Fragment 003 / 009 :: integrate rgbd frame 367 (68 of 100).
Fragment 003 / 009 :: integrate rgbd frame 368 (69 of 100).
Fragment 003 / 009 :: integrate rgbd frame 369 (70 of 100).
Fragment 003 / 009 :: integrate rgbd frame 370 (71 of 100).
Fragment 003 / 009 :: integrate rgbd frame 371 (72 of 100).
Fragment 003 / 009 :: integrate rgbd frame 372 (73 of 100).
Fragment 003 / 009 :: integrate rgbd frame 373 (74 of 100).
Fragment 003 / 009 :: integrate rgbd frame 374 (75 of 100).
Fragment 003 / 009 :: integrate rgbd frame 375 (76 of 100).
Fragment 003 / 009 :: integrate rgbd frame 376 (77 of 100).
Fragment 003 / 009 :: integrate rgbd frame 377 (78 of 100).
Fragment 003 / 009 :: integrate rgbd frame 378 (79 of 100).
Fragment 003 / 009 :: integrate rgbd frame 379 (80 of 100).
Fragment 003 / 009 :: integrate rgbd frame 380 (81 of 100).
Fragment 003 / 009 :: integrate rgbd frame 381 (82 of 100).
Fragment 003 / 009 :: integrate rgbd frame 382 (83 of 100).
Fragment 003 / 009 :: integrate rgbd frame 383 (84 of 100).
Fragment 003 / 009 :: integrate rgbd frame 384 (85 of 100).
Fragment 003 / 009 :: integrate rgbd frame 385 (86 of 100).
Fragment 003 / 009 :: integrate rgbd frame 386 (87 of 100).
Fragment 003 / 009 :: integrate rgbd frame 387 (88 of 100).
Fragment 003 / 009 :: integrate rgbd frame 388 (89 of 100).
Fragment 003 / 009 :: integrate rgbd frame 389 (90 of 100).
Fragment 003 / 009 :: integrate rgbd frame 390 (91 of 100).
Fragment 003 / 009 :: integrate rgbd frame 391 (92 of 100).
Fragment 003 / 009 :: integrate rgbd frame 392 (93 of 100).
Fragment 003 / 009 :: integrate rgbd frame 393 (94 of 100).
Fragment 003 / 009 :: integrate rgbd frame 394 (95 of 100).
Fragment 003 / 009 :: integrate rgbd frame 395 (96 of 100).
Fragment 003 / 009 :: integrate rgbd frame 396 (97 of 100).
Fragment 003 / 009 :: integrate rgbd frame 397 (98 of 100).
Fragment 003 / 009 :: integrate rgbd frame 398 (99 of 100).
Fragment 003 / 009 :: integrate rgbd frame 399 (100 of 100).
Fragment 004 / 009 :: integrate rgbd frame 400 (1 of 100).
Fragment 004 / 009 :: integrate rgbd frame 401 (2 of 100).
Fragment 004 / 009 :: integrate rgbd frame 402 (3 of 100).
Fragment 004 / 009 :: integrate rgbd frame 403 (4 of 100).
Fragment 004 / 009 :: integrate rgbd frame 404 (5 of 100).
Fragment 004 / 009 :: integrate rgbd frame 405 (6 of 100).
Fragment 004 / 009 :: integrate rgbd frame 406 (7 of 100).
Fragment 004 / 009 :: integrate rgbd frame 407 (8 of 100).
Fragment 004 / 009 :: integrate rgbd frame 408 (9 of 100).
Fragment 004 / 009 :: integrate rgbd frame 409 (10 of 100).
Fragment 004 / 009 :: integrate rgbd frame 410 (11 of 100).
Fragment 004 / 009 :: integrate rgbd frame 411 (12 of 100).
Fragment 004 / 009 :: integrate rgbd frame 412 (13 of 100).
Fragment 004 / 009 :: integrate rgbd frame 413 (14 of 100).
Fragment 004 / 009 :: integrate rgbd frame 414 (15 of 100).
Fragment 004 / 009 :: integrate rgbd frame 415 (16 of 100).
Fragment 004 / 009 :: integrate rgbd frame 416 (17 of 100).
Fragment 004 / 009 :: integrate rgbd frame 417 (18 of 100).
Fragment 004 / 009 :: integrate rgbd frame 418 (19 of 100).
Fragment 004 / 009 :: integrate rgbd frame 419 (20 of 100).
Fragment 004 / 009 :: integrate rgbd frame 420 (21 of 100).
Fragment 004 / 009 :: integrate rgbd frame 421 (22 of 100).
Fragment 004 / 009 :: integrate rgbd frame 422 (23 of 100).
Fragment 004 / 009 :: integrate rgbd frame 423 (24 of 100).
Fragment 004 / 009 :: integrate rgbd frame 424 (25 of 100).
Fragment 004 / 009 :: integrate rgbd frame 425 (26 of 100).
Fragment 004 / 009 :: integrate rgbd frame 426 (27 of 100).
Fragment 004 / 009 :: integrate rgbd frame 427 (28 of 100).
Fragment 004 / 009 :: integrate rgbd frame 428 (29 of 100).
Fragment 004 / 009 :: integrate rgbd frame 429 (30 of 100).
Fragment 004 / 009 :: integrate rgbd frame 430 (31 of 100).
Fragment 004 / 009 :: integrate rgbd frame 431 (32 of 100).
Fragment 004 / 009 :: integrate rgbd frame 432 (33 of 100).
Fragment 004 / 009 :: integrate rgbd frame 433 (34 of 100).
Fragment 004 / 009 :: integrate rgbd frame 434 (35 of 100).
Fragment 004 / 009 :: integrate rgbd frame 435 (36 of 100).
Fragment 004 / 009 :: integrate rgbd frame 436 (37 of 100).
Fragment 004 / 009 :: integrate rgbd frame 437 (38 of 100).
Fragment 004 / 009 :: integrate rgbd frame 438 (39 of 100).
Fragment 004 / 009 :: integrate rgbd frame 439 (40 of 100).
Fragment 004 / 009 :: integrate rgbd frame 440 (41 of 100).
Fragment 004 / 009 :: integrate rgbd frame 441 (42 of 100).
Fragment 004 / 009 :: integrate rgbd frame 442 (43 of 100).
Fragment 004 / 009 :: integrate rgbd frame 443 (44 of 100).
Fragment 004 / 009 :: integrate rgbd frame 444 (45 of 100).
Fragment 004 / 009 :: integrate rgbd frame 445 (46 of 100).
Fragment 004 / 009 :: integrate rgbd frame 446 (47 of 100).
Fragment 004 / 009 :: integrate rgbd frame 447 (48 of 100).
Fragment 004 / 009 :: integrate rgbd frame 448 (49 of 100).
Fragment 004 / 009 :: integrate rgbd frame 449 (50 of 100).
Fragment 004 / 009 :: integrate rgbd frame 450 (51 of 100).
Fragment 004 / 009 :: integrate rgbd frame 451 (52 of 100).
Fragment 004 / 009 :: integrate rgbd frame 452 (53 of 100).
Fragment 004 / 009 :: integrate rgbd frame 453 (54 of 100).
Fragment 004 / 009 :: integrate rgbd frame 454 (55 of 100).
Fragment 004 / 009 :: integrate rgbd frame 455 (56 of 100).
Fragment 004 / 009 :: integrate rgbd frame 456 (57 of 100).
Fragment 004 / 009 :: integrate rgbd frame 457 (58 of 100).
Fragment 004 / 009 :: integrate rgbd frame 458 (59 of 100).
Fragment 004 / 009 :: integrate rgbd frame 459 (60 of 100).
Fragment 004 / 009 :: integrate rgbd frame 460 (61 of 100).
Fragment 004 / 009 :: integrate rgbd frame 461 (62 of 100).
Fragment 004 / 009 :: integrate rgbd frame 462 (63 of 100).
Fragment 004 / 009 :: integrate rgbd frame 463 (64 of 100).
Fragment 004 / 009 :: integrate rgbd frame 464 (65 of 100).
Fragment 004 / 009 :: integrate rgbd frame 465 (66 of 100).
Fragment 004 / 009 :: integrate rgbd frame 466 (67 of 100).
Fragment 004 / 009 :: integrate rgbd frame 467 (68 of 100).
Fragment 004 / 009 :: integrate rgbd frame 468 (69 of 100).
Fragment 004 / 009 :: integrate rgbd frame 469 (70 of 100).
Fragment 004 / 009 :: integrate rgbd frame 470 (71 of 100).
Fragment 004 / 009 :: integrate rgbd frame 471 (72 of 100).
Fragment 004 / 009 :: integrate rgbd frame 472 (73 of 100).
Fragment 004 / 009 :: integrate rgbd frame 473 (74 of 100).
Fragment 004 / 009 :: integrate rgbd frame 474 (75 of 100).
Fragment 004 / 009 :: integrate rgbd frame 475 (76 of 100).
Fragment 004 / 009 :: integrate rgbd frame 476 (77 of 100).
Fragment 004 / 009 :: integrate rgbd frame 477 (78 of 100).
Fragment 004 / 009 :: integrate rgbd frame 478 (79 of 100).
Fragment 004 / 009 :: integrate rgbd frame 479 (80 of 100).
Fragment 004 / 009 :: integrate rgbd frame 480 (81 of 100).
Fragment 004 / 009 :: integrate rgbd frame 481 (82 of 100).
Fragment 004 / 009 :: integrate rgbd frame 482 (83 of 100).
Fragment 004 / 009 :: integrate rgbd frame 483 (84 of 100).
Fragment 004 / 009 :: integrate rgbd frame 484 (85 of 100).
Fragment 004 / 009 :: integrate rgbd frame 485 (86 of 100).
Fragment 004 / 009 :: integrate rgbd frame 486 (87 of 100).
Fragment 004 / 009 :: integrate rgbd frame 487 (88 of 100).
Fragment 004 / 009 :: integrate rgbd frame 488 (89 of 100).
Fragment 004 / 009 :: integrate rgbd frame 489 (90 of 100).
Fragment 004 / 009 :: integrate rgbd frame 490 (91 of 100).
Fragment 004 / 009 :: integrate rgbd frame 491 (92 of 100).
Fragment 004 / 009 :: integrate rgbd frame 492 (93 of 100).
Fragment 004 / 009 :: integrate rgbd frame 493 (94 of 100).
Fragment 004 / 009 :: integrate rgbd frame 494 (95 of 100).
Fragment 004 / 009 :: integrate rgbd frame 495 (96 of 100).
Fragment 004 / 009 :: integrate rgbd frame 496 (97 of 100).
Fragment 004 / 009 :: integrate rgbd frame 497 (98 of 100).
Fragment 004 / 009 :: integrate rgbd frame 498 (99 of 100).
Fragment 004 / 009 :: integrate rgbd frame 499 (100 of 100).
Fragment 005 / 009 :: integrate rgbd frame 500 (1 of 100).
Fragment 005 / 009 :: integrate rgbd frame 501 (2 of 100).
Fragment 005 / 009 :: integrate rgbd frame 502 (3 of 100).
Fragment 005 / 009 :: integrate rgbd frame 503 (4 of 100).
Fragment 005 / 009 :: integrate rgbd frame 504 (5 of 100).
Fragment 005 / 009 :: integrate rgbd frame 505 (6 of 100).
Fragment 005 / 009 :: integrate rgbd frame 506 (7 of 100).
Fragment 005 / 009 :: integrate rgbd frame 507 (8 of 100).
Fragment 005 / 009 :: integrate rgbd frame 508 (9 of 100).
Fragment 005 / 009 :: integrate rgbd frame 509 (10 of 100).
Fragment 005 / 009 :: integrate rgbd frame 510 (11 of 100).
Fragment 005 / 009 :: integrate rgbd frame 511 (12 of 100).
Fragment 005 / 009 :: integrate rgbd frame 512 (13 of 100).
Fragment 005 / 009 :: integrate rgbd frame 513 (14 of 100).
Fragment 005 / 009 :: integrate rgbd frame 514 (15 of 100).
Fragment 005 / 009 :: integrate rgbd frame 515 (16 of 100).
Fragment 005 / 009 :: integrate rgbd frame 516 (17 of 100).
Fragment 005 / 009 :: integrate rgbd frame 517 (18 of 100).
Fragment 005 / 009 :: integrate rgbd frame 518 (19 of 100).
Fragment 005 / 009 :: integrate rgbd frame 519 (20 of 100).
Fragment 005 / 009 :: integrate rgbd frame 520 (21 of 100).
Fragment 005 / 009 :: integrate rgbd frame 521 (22 of 100).
Fragment 005 / 009 :: integrate rgbd frame 522 (23 of 100).
Fragment 005 / 009 :: integrate rgbd frame 523 (24 of 100).
Fragment 005 / 009 :: integrate rgbd frame 524 (25 of 100).
Fragment 005 / 009 :: integrate rgbd frame 525 (26 of 100).
Fragment 005 / 009 :: integrate rgbd frame 526 (27 of 100).
Fragment 005 / 009 :: integrate rgbd frame 527 (28 of 100).
Fragment 005 / 009 :: integrate rgbd frame 528 (29 of 100).
Fragment 005 / 009 :: integrate rgbd frame 529 (30 of 100).
Fragment 005 / 009 :: integrate rgbd frame 530 (31 of 100).
Fragment 005 / 009 :: integrate rgbd frame 531 (32 of 100).
Fragment 005 / 009 :: integrate rgbd frame 532 (33 of 100).
Fragment 005 / 009 :: integrate rgbd frame 533 (34 of 100).
Fragment 005 / 009 :: integrate rgbd frame 534 (35 of 100).
Fragment 005 / 009 :: integrate rgbd frame 535 (36 of 100).
Fragment 005 / 009 :: integrate rgbd frame 536 (37 of 100).
Fragment 005 / 009 :: integrate rgbd frame 537 (38 of 100).
Fragment 005 / 009 :: integrate rgbd frame 538 (39 of 100).
Fragment 005 / 009 :: integrate rgbd frame 539 (40 of 100).
Fragment 005 / 009 :: integrate rgbd frame 540 (41 of 100).
Fragment 005 / 009 :: integrate rgbd frame 541 (42 of 100).
Fragment 005 / 009 :: integrate rgbd frame 542 (43 of 100).
Fragment 005 / 009 :: integrate rgbd frame 543 (44 of 100).
Fragment 005 / 009 :: integrate rgbd frame 544 (45 of 100).
Fragment 005 / 009 :: integrate rgbd frame 545 (46 of 100).
Fragment 005 / 009 :: integrate rgbd frame 546 (47 of 100).
Fragment 005 / 009 :: integrate rgbd frame 547 (48 of 100).
Fragment 005 / 009 :: integrate rgbd frame 548 (49 of 100).
Fragment 005 / 009 :: integrate rgbd frame 549 (50 of 100).
Fragment 005 / 009 :: integrate rgbd frame 550 (51 of 100).
Fragment 005 / 009 :: integrate rgbd frame 551 (52 of 100).
Fragment 005 / 009 :: integrate rgbd frame 552 (53 of 100).
Fragment 005 / 009 :: integrate rgbd frame 553 (54 of 100).
Fragment 005 / 009 :: integrate rgbd frame 554 (55 of 100).
Fragment 005 / 009 :: integrate rgbd frame 555 (56 of 100).
Fragment 005 / 009 :: integrate rgbd frame 556 (57 of 100).
Fragment 005 / 009 :: integrate rgbd frame 557 (58 of 100).
Fragment 005 / 009 :: integrate rgbd frame 558 (59 of 100).
Fragment 005 / 009 :: integrate rgbd frame 559 (60 of 100).
Fragment 005 / 009 :: integrate rgbd frame 560 (61 of 100).
Fragment 005 / 009 :: integrate rgbd frame 561 (62 of 100).
Fragment 005 / 009 :: integrate rgbd frame 562 (63 of 100).
Fragment 005 / 009 :: integrate rgbd frame 563 (64 of 100).
Fragment 005 / 009 :: integrate rgbd frame 564 (65 of 100).
Fragment 005 / 009 :: integrate rgbd frame 565 (66 of 100).
Fragment 005 / 009 :: integrate rgbd frame 566 (67 of 100).
Fragment 005 / 009 :: integrate rgbd frame 567 (68 of 100).
Fragment 005 / 009 :: integrate rgbd frame 568 (69 of 100).
Fragment 005 / 009 :: integrate rgbd frame 569 (70 of 100).
Fragment 005 / 009 :: integrate rgbd frame 570 (71 of 100).
Fragment 005 / 009 :: integrate rgbd frame 571 (72 of 100).
Fragment 005 / 009 :: integrate rgbd frame 572 (73 of 100).
Fragment 005 / 009 :: integrate rgbd frame 573 (74 of 100).
Fragment 005 / 009 :: integrate rgbd frame 574 (75 of 100).
Fragment 005 / 009 :: integrate rgbd frame 575 (76 of 100).
Fragment 005 / 009 :: integrate rgbd frame 576 (77 of 100).
Fragment 005 / 009 :: integrate rgbd frame 577 (78 of 100).
Fragment 005 / 009 :: integrate rgbd frame 578 (79 of 100).
Fragment 005 / 009 :: integrate rgbd frame 579 (80 of 100).
Fragment 005 / 009 :: integrate rgbd frame 580 (81 of 100).
Fragment 005 / 009 :: integrate rgbd frame 581 (82 of 100).
Fragment 005 / 009 :: integrate rgbd frame 582 (83 of 100).
Fragment 005 / 009 :: integrate rgbd frame 583 (84 of 100).
Fragment 005 / 009 :: integrate rgbd frame 584 (85 of 100).
Fragment 005 / 009 :: integrate rgbd frame 585 (86 of 100).
Fragment 005 / 009 :: integrate rgbd frame 586 (87 of 100).
Fragment 005 / 009 :: integrate rgbd frame 587 (88 of 100).
Fragment 005 / 009 :: integrate rgbd frame 588 (89 of 100).
Fragment 005 / 009 :: integrate rgbd frame 589 (90 of 100).
Fragment 005 / 009 :: integrate rgbd frame 590 (91 of 100).
Fragment 005 / 009 :: integrate rgbd frame 591 (92 of 100).
Fragment 005 / 009 :: integrate rgbd frame 592 (93 of 100).
Fragment 005 / 009 :: integrate rgbd frame 593 (94 of 100).
Fragment 005 / 009 :: integrate rgbd frame 594 (95 of 100).
Fragment 005 / 009 :: integrate rgbd frame 595 (96 of 100).
Fragment 005 / 009 :: integrate rgbd frame 596 (97 of 100).
Fragment 005 / 009 :: integrate rgbd frame 597 (98 of 100).
Fragment 005 / 009 :: integrate rgbd frame 598 (99 of 100).
Fragment 005 / 009 :: integrate rgbd frame 599 (100 of 100).
Fragment 006 / 009 :: integrate rgbd frame 600 (1 of 100).
Fragment 006 / 009 :: integrate rgbd frame 601 (2 of 100).
Fragment 006 / 009 :: integrate rgbd frame 602 (3 of 100).
Fragment 006 / 009 :: integrate rgbd frame 603 (4 of 100).
Fragment 006 / 009 :: integrate rgbd frame 604 (5 of 100).
Fragment 006 / 009 :: integrate rgbd frame 605 (6 of 100).
Fragment 006 / 009 :: integrate rgbd frame 606 (7 of 100).
Fragment 006 / 009 :: integrate rgbd frame 607 (8 of 100).
Fragment 006 / 009 :: integrate rgbd frame 608 (9 of 100).
Fragment 006 / 009 :: integrate rgbd frame 609 (10 of 100).
Fragment 006 / 009 :: integrate rgbd frame 610 (11 of 100).
Fragment 006 / 009 :: integrate rgbd frame 611 (12 of 100).
Fragment 006 / 009 :: integrate rgbd frame 612 (13 of 100).
Fragment 006 / 009 :: integrate rgbd frame 613 (14 of 100).
Fragment 006 / 009 :: integrate rgbd frame 614 (15 of 100).
Fragment 006 / 009 :: integrate rgbd frame 615 (16 of 100).
Fragment 006 / 009 :: integrate rgbd frame 616 (17 of 100).
Fragment 006 / 009 :: integrate rgbd frame 617 (18 of 100).
Fragment 006 / 009 :: integrate rgbd frame 618 (19 of 100).
Fragment 006 / 009 :: integrate rgbd frame 619 (20 of 100).
Fragment 006 / 009 :: integrate rgbd frame 620 (21 of 100).
Fragment 006 / 009 :: integrate rgbd frame 621 (22 of 100).
Fragment 006 / 009 :: integrate rgbd frame 622 (23 of 100).
Fragment 006 / 009 :: integrate rgbd frame 623 (24 of 100).
Fragment 006 / 009 :: integrate rgbd frame 624 (25 of 100).
Fragment 006 / 009 :: integrate rgbd frame 625 (26 of 100).
Fragment 006 / 009 :: integrate rgbd frame 626 (27 of 100).
Fragment 006 / 009 :: integrate rgbd frame 627 (28 of 100).
Fragment 006 / 009 :: integrate rgbd frame 628 (29 of 100).
Fragment 006 / 009 :: integrate rgbd frame 629 (30 of 100).
Fragment 006 / 009 :: integrate rgbd frame 630 (31 of 100).
Fragment 006 / 009 :: integrate rgbd frame 631 (32 of 100).
Fragment 006 / 009 :: integrate rgbd frame 632 (33 of 100).
Fragment 006 / 009 :: integrate rgbd frame 633 (34 of 100).
Fragment 006 / 009 :: integrate rgbd frame 634 (35 of 100).
Fragment 006 / 009 :: integrate rgbd frame 635 (36 of 100).
Fragment 006 / 009 :: integrate rgbd frame 636 (37 of 100).
Fragment 006 / 009 :: integrate rgbd frame 637 (38 of 100).
Fragment 006 / 009 :: integrate rgbd frame 638 (39 of 100).
Fragment 006 / 009 :: integrate rgbd frame 639 (40 of 100).
Fragment 006 / 009 :: integrate rgbd frame 640 (41 of 100).
Fragment 006 / 009 :: integrate rgbd frame 641 (42 of 100).
Fragment 006 / 009 :: integrate rgbd frame 642 (43 of 100).
Fragment 006 / 009 :: integrate rgbd frame 643 (44 of 100).
Fragment 006 / 009 :: integrate rgbd frame 644 (45 of 100).
Fragment 006 / 009 :: integrate rgbd frame 645 (46 of 100).
Fragment 006 / 009 :: integrate rgbd frame 646 (47 of 100).
Fragment 006 / 009 :: integrate rgbd frame 647 (48 of 100).
Fragment 006 / 009 :: integrate rgbd frame 648 (49 of 100).
Fragment 006 / 009 :: integrate rgbd frame 649 (50 of 100).
Fragment 006 / 009 :: integrate rgbd frame 650 (51 of 100).
Fragment 006 / 009 :: integrate rgbd frame 651 (52 of 100).
Fragment 006 / 009 :: integrate rgbd frame 652 (53 of 100).
Fragment 006 / 009 :: integrate rgbd frame 653 (54 of 100).
Fragment 006 / 009 :: integrate rgbd frame 654 (55 of 100).
Fragment 006 / 009 :: integrate rgbd frame 655 (56 of 100).
Fragment 006 / 009 :: integrate rgbd frame 656 (57 of 100).
Fragment 006 / 009 :: integrate rgbd frame 657 (58 of 100).
Fragment 006 / 009 :: integrate rgbd frame 658 (59 of 100).
Fragment 006 / 009 :: integrate rgbd frame 659 (60 of 100).
Fragment 006 / 009 :: integrate rgbd frame 660 (61 of 100).
Fragment 006 / 009 :: integrate rgbd frame 661 (62 of 100).
Fragment 006 / 009 :: integrate rgbd frame 662 (63 of 100).
Fragment 006 / 009 :: integrate rgbd frame 663 (64 of 100).
Fragment 006 / 009 :: integrate rgbd frame 664 (65 of 100).
Fragment 006 / 009 :: integrate rgbd frame 665 (66 of 100).
Fragment 006 / 009 :: integrate rgbd frame 666 (67 of 100).
Fragment 006 / 009 :: integrate rgbd frame 667 (68 of 100).
Fragment 006 / 009 :: integrate rgbd frame 668 (69 of 100).
Fragment 006 / 009 :: integrate rgbd frame 669 (70 of 100).
Fragment 006 / 009 :: integrate rgbd frame 670 (71 of 100).
Fragment 006 / 009 :: integrate rgbd frame 671 (72 of 100).
Fragment 006 / 009 :: integrate rgbd frame 672 (73 of 100).
Fragment 006 / 009 :: integrate rgbd frame 673 (74 of 100).
Fragment 006 / 009 :: integrate rgbd frame 674 (75 of 100).
Fragment 006 / 009 :: integrate rgbd frame 675 (76 of 100).
Fragment 006 / 009 :: integrate rgbd frame 676 (77 of 100).
Fragment 006 / 009 :: integrate rgbd frame 677 (78 of 100).
Fragment 006 / 009 :: integrate rgbd frame 678 (79 of 100).
Fragment 006 / 009 :: integrate rgbd frame 679 (80 of 100).
Fragment 006 / 009 :: integrate rgbd frame 680 (81 of 100).
Fragment 006 / 009 :: integrate rgbd frame 681 (82 of 100).
Fragment 006 / 009 :: integrate rgbd frame 682 (83 of 100).
Fragment 006 / 009 :: integrate rgbd frame 683 (84 of 100).
Fragment 006 / 009 :: integrate rgbd frame 684 (85 of 100).
Fragment 006 / 009 :: integrate rgbd frame 685 (86 of 100).
Fragment 006 / 009 :: integrate rgbd frame 686 (87 of 100).
Fragment 006 / 009 :: integrate rgbd frame 687 (88 of 100).
Fragment 006 / 009 :: integrate rgbd frame 688 (89 of 100).
Fragment 006 / 009 :: integrate rgbd frame 689 (90 of 100).
Fragment 006 / 009 :: integrate rgbd frame 690 (91 of 100).
Fragment 006 / 009 :: integrate rgbd frame 691 (92 of 100).
Fragment 006 / 009 :: integrate rgbd frame 692 (93 of 100).
Fragment 006 / 009 :: integrate rgbd frame 693 (94 of 100).
Fragment 006 / 009 :: integrate rgbd frame 694 (95 of 100).
Fragment 006 / 009 :: integrate rgbd frame 695 (96 of 100).
Fragment 006 / 009 :: integrate rgbd frame 696 (97 of 100).
Fragment 006 / 009 :: integrate rgbd frame 697 (98 of 100).
Fragment 006 / 009 :: integrate rgbd frame 698 (99 of 100).
Fragment 006 / 009 :: integrate rgbd frame 699 (100 of 100).
Fragment 007 / 009 :: integrate rgbd frame 700 (1 of 100).
Fragment 007 / 009 :: integrate rgbd frame 701 (2 of 100).
Fragment 007 / 009 :: integrate rgbd frame 702 (3 of 100).
Fragment 007 / 009 :: integrate rgbd frame 703 (4 of 100).
Fragment 007 / 009 :: integrate rgbd frame 704 (5 of 100).
Fragment 007 / 009 :: integrate rgbd frame 705 (6 of 100).
Fragment 007 / 009 :: integrate rgbd frame 706 (7 of 100).
Fragment 007 / 009 :: integrate rgbd frame 707 (8 of 100).
Fragment 007 / 009 :: integrate rgbd frame 708 (9 of 100).
Fragment 007 / 009 :: integrate rgbd frame 709 (10 of 100).
Fragment 007 / 009 :: integrate rgbd frame 710 (11 of 100).
Fragment 007 / 009 :: integrate rgbd frame 711 (12 of 100).
Fragment 007 / 009 :: integrate rgbd frame 712 (13 of 100).
Fragment 007 / 009 :: integrate rgbd frame 713 (14 of 100).
Fragment 007 / 009 :: integrate rgbd frame 714 (15 of 100).
Fragment 007 / 009 :: integrate rgbd frame 715 (16 of 100).
Fragment 007 / 009 :: integrate rgbd frame 716 (17 of 100).
Fragment 007 / 009 :: integrate rgbd frame 717 (18 of 100).
Fragment 007 / 009 :: integrate rgbd frame 718 (19 of 100).
Fragment 007 / 009 :: integrate rgbd frame 719 (20 of 100).
Fragment 007 / 009 :: integrate rgbd frame 720 (21 of 100).
Fragment 007 / 009 :: integrate rgbd frame 721 (22 of 100).
Fragment 007 / 009 :: integrate rgbd frame 722 (23 of 100).
Fragment 007 / 009 :: integrate rgbd frame 723 (24 of 100).
Fragment 007 / 009 :: integrate rgbd frame 724 (25 of 100).
Fragment 007 / 009 :: integrate rgbd frame 725 (26 of 100).
Fragment 007 / 009 :: integrate rgbd frame 726 (27 of 100).
Fragment 007 / 009 :: integrate rgbd frame 727 (28 of 100).
Fragment 007 / 009 :: integrate rgbd frame 728 (29 of 100).
Fragment 007 / 009 :: integrate rgbd frame 729 (30 of 100).
Fragment 007 / 009 :: integrate rgbd frame 730 (31 of 100).
Fragment 007 / 009 :: integrate rgbd frame 731 (32 of 100).
Fragment 007 / 009 :: integrate rgbd frame 732 (33 of 100).
Fragment 007 / 009 :: integrate rgbd frame 733 (34 of 100).
Fragment 007 / 009 :: integrate rgbd frame 734 (35 of 100).
Fragment 007 / 009 :: integrate rgbd frame 735 (36 of 100).
Fragment 007 / 009 :: integrate rgbd frame 736 (37 of 100).
Fragment 007 / 009 :: integrate rgbd frame 737 (38 of 100).
Fragment 007 / 009 :: integrate rgbd frame 738 (39 of 100).
Fragment 007 / 009 :: integrate rgbd frame 739 (40 of 100).
Fragment 007 / 009 :: integrate rgbd frame 740 (41 of 100).
Fragment 007 / 009 :: integrate rgbd frame 741 (42 of 100).
Fragment 007 / 009 :: integrate rgbd frame 742 (43 of 100).
Fragment 007 / 009 :: integrate rgbd frame 743 (44 of 100).
Fragment 007 / 009 :: integrate rgbd frame 744 (45 of 100).
Fragment 007 / 009 :: integrate rgbd frame 745 (46 of 100).
Fragment 007 / 009 :: integrate rgbd frame 746 (47 of 100).
Fragment 007 / 009 :: integrate rgbd frame 747 (48 of 100).
Fragment 007 / 009 :: integrate rgbd frame 748 (49 of 100).
Fragment 007 / 009 :: integrate rgbd frame 749 (50 of 100).
Fragment 007 / 009 :: integrate rgbd frame 750 (51 of 100).
Fragment 007 / 009 :: integrate rgbd frame 751 (52 of 100).
Fragment 007 / 009 :: integrate rgbd frame 752 (53 of 100).
Fragment 007 / 009 :: integrate rgbd frame 753 (54 of 100).
Fragment 007 / 009 :: integrate rgbd frame 754 (55 of 100).
Fragment 007 / 009 :: integrate rgbd frame 755 (56 of 100).
Fragment 007 / 009 :: integrate rgbd frame 756 (57 of 100).
Fragment 007 / 009 :: integrate rgbd frame 757 (58 of 100).
Fragment 007 / 009 :: integrate rgbd frame 758 (59 of 100).
Fragment 007 / 009 :: integrate rgbd frame 759 (60 of 100).
Fragment 007 / 009 :: integrate rgbd frame 760 (61 of 100).
Fragment 007 / 009 :: integrate rgbd frame 761 (62 of 100).
Fragment 007 / 009 :: integrate rgbd frame 762 (63 of 100).
Fragment 007 / 009 :: integrate rgbd frame 763 (64 of 100).
Fragment 007 / 009 :: integrate rgbd frame 764 (65 of 100).
Fragment 007 / 009 :: integrate rgbd frame 765 (66 of 100).
Fragment 007 / 009 :: integrate rgbd frame 766 (67 of 100).
Fragment 007 / 009 :: integrate rgbd frame 767 (68 of 100).
Fragment 007 / 009 :: integrate rgbd frame 768 (69 of 100).
Fragment 007 / 009 :: integrate rgbd frame 769 (70 of 100).
Fragment 007 / 009 :: integrate rgbd frame 770 (71 of 100).
Fragment 007 / 009 :: integrate rgbd frame 771 (72 of 100).
Fragment 007 / 009 :: integrate rgbd frame 772 (73 of 100).
Fragment 007 / 009 :: integrate rgbd frame 773 (74 of 100).
Fragment 007 / 009 :: integrate rgbd frame 774 (75 of 100).
Fragment 007 / 009 :: integrate rgbd frame 775 (76 of 100).
Fragment 007 / 009 :: integrate rgbd frame 776 (77 of 100).
Fragment 007 / 009 :: integrate rgbd frame 777 (78 of 100).
Fragment 007 / 009 :: integrate rgbd frame 778 (79 of 100).
Fragment 007 / 009 :: integrate rgbd frame 779 (80 of 100).
Fragment 007 / 009 :: integrate rgbd frame 780 (81 of 100).
Fragment 007 / 009 :: integrate rgbd frame 781 (82 of 100).
Fragment 007 / 009 :: integrate rgbd frame 782 (83 of 100).
Fragment 007 / 009 :: integrate rgbd frame 783 (84 of 100).
Fragment 007 / 009 :: integrate rgbd frame 784 (85 of 100).
Fragment 007 / 009 :: integrate rgbd frame 785 (86 of 100).
Fragment 007 / 009 :: integrate rgbd frame 786 (87 of 100).
Fragment 007 / 009 :: integrate rgbd frame 787 (88 of 100).
Fragment 007 / 009 :: integrate rgbd frame 788 (89 of 100).
Fragment 007 / 009 :: integrate rgbd frame 789 (90 of 100).
Fragment 007 / 009 :: integrate rgbd frame 790 (91 of 100).
Fragment 007 / 009 :: integrate rgbd frame 791 (92 of 100).
Fragment 007 / 009 :: integrate rgbd frame 792 (93 of 100).
Fragment 007 / 009 :: integrate rgbd frame 793 (94 of 100).
Fragment 007 / 009 :: integrate rgbd frame 794 (95 of 100).
Fragment 007 / 009 :: integrate rgbd frame 795 (96 of 100).
Fragment 007 / 009 :: integrate rgbd frame 796 (97 of 100).
Fragment 007 / 009 :: integrate rgbd frame 797 (98 of 100).
Fragment 007 / 009 :: integrate rgbd frame 798 (99 of 100).
Fragment 007 / 009 :: integrate rgbd frame 799 (100 of 100).
Fragment 008 / 009 :: integrate rgbd frame 800 (1 of 100).
Fragment 008 / 009 :: integrate rgbd frame 801 (2 of 100).
Fragment 008 / 009 :: integrate rgbd frame 802 (3 of 100).
Fragment 008 / 009 :: integrate rgbd frame 803 (4 of 100).
Fragment 008 / 009 :: integrate rgbd frame 804 (5 of 100).
Fragment 008 / 009 :: integrate rgbd frame 805 (6 of 100).
Fragment 008 / 009 :: integrate rgbd frame 806 (7 of 100).
Fragment 008 / 009 :: integrate rgbd frame 807 (8 of 100).
Fragment 008 / 009 :: integrate rgbd frame 808 (9 of 100).
Fragment 008 / 009 :: integrate rgbd frame 809 (10 of 100).
Fragment 008 / 009 :: integrate rgbd frame 810 (11 of 100).
Fragment 008 / 009 :: integrate rgbd frame 811 (12 of 100).
Fragment 008 / 009 :: integrate rgbd frame 812 (13 of 100).
Fragment 008 / 009 :: integrate rgbd frame 813 (14 of 100).
Fragment 008 / 009 :: integrate rgbd frame 814 (15 of 100).
Fragment 008 / 009 :: integrate rgbd frame 815 (16 of 100).
Fragment 008 / 009 :: integrate rgbd frame 816 (17 of 100).
Fragment 008 / 009 :: integrate rgbd frame 817 (18 of 100).
Fragment 008 / 009 :: integrate rgbd frame 818 (19 of 100).
Fragment 008 / 009 :: integrate rgbd frame 819 (20 of 100).
Fragment 008 / 009 :: integrate rgbd frame 820 (21 of 100).
Fragment 008 / 009 :: integrate rgbd frame 821 (22 of 100).
Fragment 008 / 009 :: integrate rgbd frame 822 (23 of 100).
Fragment 008 / 009 :: integrate rgbd frame 823 (24 of 100).
Fragment 008 / 009 :: integrate rgbd frame 824 (25 of 100).
Fragment 008 / 009 :: integrate rgbd frame 825 (26 of 100).
Fragment 008 / 009 :: integrate rgbd frame 826 (27 of 100).
Fragment 008 / 009 :: integrate rgbd frame 827 (28 of 100).
Fragment 008 / 009 :: integrate rgbd frame 828 (29 of 100).
Fragment 008 / 009 :: integrate rgbd frame 829 (30 of 100).
Fragment 008 / 009 :: integrate rgbd frame 830 (31 of 100).
Fragment 008 / 009 :: integrate rgbd frame 831 (32 of 100).
Fragment 008 / 009 :: integrate rgbd frame 832 (33 of 100).
Fragment 008 / 009 :: integrate rgbd frame 833 (34 of 100).
Fragment 008 / 009 :: integrate rgbd frame 834 (35 of 100).
Fragment 008 / 009 :: integrate rgbd frame 835 (36 of 100).
Fragment 008 / 009 :: integrate rgbd frame 836 (37 of 100).
Fragment 008 / 009 :: integrate rgbd frame 837 (38 of 100).
Fragment 008 / 009 :: integrate rgbd frame 838 (39 of 100).
Fragment 008 / 009 :: integrate rgbd frame 839 (40 of 100).
Fragment 008 / 009 :: integrate rgbd frame 840 (41 of 100).
Fragment 008 / 009 :: integrate rgbd frame 841 (42 of 100).
Fragment 008 / 009 :: integrate rgbd frame 842 (43 of 100).
Fragment 008 / 009 :: integrate rgbd frame 843 (44 of 100).
Fragment 008 / 009 :: integrate rgbd frame 844 (45 of 100).
Fragment 008 / 009 :: integrate rgbd frame 845 (46 of 100).
Fragment 008 / 009 :: integrate rgbd frame 846 (47 of 100).
Fragment 008 / 009 :: integrate rgbd frame 847 (48 of 100).
Fragment 008 / 009 :: integrate rgbd frame 848 (49 of 100).
Fragment 008 / 009 :: integrate rgbd frame 849 (50 of 100).
Fragment 008 / 009 :: integrate rgbd frame 850 (51 of 100).
Fragment 008 / 009 :: integrate rgbd frame 851 (52 of 100).
Fragment 008 / 009 :: integrate rgbd frame 852 (53 of 100).
Fragment 008 / 009 :: integrate rgbd frame 853 (54 of 100).
Fragment 008 / 009 :: integrate rgbd frame 854 (55 of 100).
Fragment 008 / 009 :: integrate rgbd frame 855 (56 of 100).
Fragment 008 / 009 :: integrate rgbd frame 856 (57 of 100).
Fragment 008 / 009 :: integrate rgbd frame 857 (58 of 100).
Fragment 008 / 009 :: integrate rgbd frame 858 (59 of 100).
Fragment 008 / 009 :: integrate rgbd frame 859 (60 of 100).
Fragment 008 / 009 :: integrate rgbd frame 860 (61 of 100).
Fragment 008 / 009 :: integrate rgbd frame 861 (62 of 100).
Fragment 008 / 009 :: integrate rgbd frame 862 (63 of 100).
Fragment 008 / 009 :: integrate rgbd frame 863 (64 of 100).
Fragment 008 / 009 :: integrate rgbd frame 864 (65 of 100).
Fragment 008 / 009 :: integrate rgbd frame 865 (66 of 100).
Fragment 008 / 009 :: integrate rgbd frame 866 (67 of 100).
Fragment 008 / 009 :: integrate rgbd frame 867 (68 of 100).
Fragment 008 / 009 :: integrate rgbd frame 868 (69 of 100).
Fragment 008 / 009 :: integrate rgbd frame 869 (70 of 100).
Fragment 008 / 009 :: integrate rgbd frame 870 (71 of 100).
Fragment 008 / 009 :: integrate rgbd frame 871 (72 of 100).
Fragment 008 / 009 :: integrate rgbd frame 872 (73 of 100).
Fragment 008 / 009 :: integrate rgbd frame 873 (74 of 100).
Fragment 008 / 009 :: integrate rgbd frame 874 (75 of 100).
Fragment 008 / 009 :: integrate rgbd frame 875 (76 of 100).
Fragment 008 / 009 :: integrate rgbd frame 876 (77 of 100).
Fragment 008 / 009 :: integrate rgbd frame 877 (78 of 100).
Fragment 008 / 009 :: integrate rgbd frame 878 (79 of 100).
Fragment 008 / 009 :: integrate rgbd frame 879 (80 of 100).
Fragment 008 / 009 :: integrate rgbd frame 880 (81 of 100).
Fragment 008 / 009 :: integrate rgbd frame 881 (82 of 100).
Fragment 008 / 009 :: integrate rgbd frame 882 (83 of 100).
Fragment 008 / 009 :: integrate rgbd frame 883 (84 of 100).
Fragment 008 / 009 :: integrate rgbd frame 884 (85 of 100).
Fragment 008 / 009 :: integrate rgbd frame 885 (86 of 100).
Fragment 008 / 009 :: integrate rgbd frame 886 (87 of 100).
Fragment 008 / 009 :: integrate rgbd frame 887 (88 of 100).
Fragment 008 / 009 :: integrate rgbd frame 888 (89 of 100).
Fragment 008 / 009 :: integrate rgbd frame 889 (90 of 100).
Fragment 008 / 009 :: integrate rgbd frame 890 (91 of 100).
Fragment 008 / 009 :: integrate rgbd frame 891 (92 of 100).
Fragment 008 / 009 :: integrate rgbd frame 892 (93 of 100).
Fragment 008 / 009 :: integrate rgbd frame 893 (94 of 100).
Fragment 008 / 009 :: integrate rgbd frame 894 (95 of 100).
Fragment 008 / 009 :: integrate rgbd frame 895 (96 of 100).
Fragment 008 / 009 :: integrate rgbd frame 896 (97 of 100).
Fragment 008 / 009 :: integrate rgbd frame 897 (98 of 100).
Fragment 008 / 009 :: integrate rgbd frame 898 (99 of 100).
Fragment 008 / 009 :: integrate rgbd frame 899 (100 of 100).
Fragment 009 / 009 :: integrate rgbd frame 900 (1 of 5).
Fragment 009 / 009 :: integrate rgbd frame 901 (2 of 5).
Fragment 009 / 009 :: integrate rgbd frame 902 (3 of 5).
Fragment 009 / 009 :: integrate rgbd frame 903 (4 of 5).
Fragment 009 / 009 :: integrate rgbd frame 904 (5 of 5).
====================================
Elapsed time (in h:m:s)
====================================
- Making fragments 0:18:39.593087
- Register fragments 0:00:49.357369
- Refine registration 0:00:02.105286
- Integrate frames 0:00:57.097497
- Total 0:20:28.153239
23, time : 0.000 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.002 sec.
[Open3D DEBUG] [GlobalOptimizationLM] Optimizing PoseGraph having 10 nodes and 32 edges.
[Open3D DEBUG] Line process weight : 78.138922
[Open3D DEBUG] [Initial ] residual : 1.897088e+02, lambda : 2.949502e-01
[Open3D DEBUG] [Iteration 00] residual : 1.854947e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 01] residual : 1.851665e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 02] residual : 1.851429e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 03] residual : 1.851405e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] [Iteration 04] residual : 1.851403e+02, valid edges : 23, time : 0.000 sec.
[Open3D DEBUG] Current_residual - new_residual < 1.000000e-06 * current_residual
[Open3D DEBUG] [GlobalOptimizationLM] total time : 0.001 sec.
[Open3D DEBUG] CompensateReferencePoseGraphNode : reference : 0
| 61.027638
| 134
| 0.720275
| 102,939
| 642,560
| 4.491796
| 0.031388
| 0.133342
| 0.084508
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| 0.955742
| 0.950411
| 0.943882
| 0.849767
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0
| 7
|
2d5f08fc20ab9ad9defe3e95a20ca68b93071806
| 97
|
py
|
Python
|
__init__.py
|
vonclites/el_sid
|
c82e4120afd9f3edd105105176f79a14fbf5001c
|
[
"MIT"
] | null | null | null |
__init__.py
|
vonclites/el_sid
|
c82e4120afd9f3edd105105176f79a14fbf5001c
|
[
"MIT"
] | null | null | null |
__init__.py
|
vonclites/el_sid
|
c82e4120afd9f3edd105105176f79a14fbf5001c
|
[
"MIT"
] | 1
|
2021-06-06T06:22:08.000Z
|
2021-06-06T06:22:08.000Z
|
from syd.feature_extraction import random_sample
from syd.feature_extraction import dense_sample
| 32.333333
| 48
| 0.896907
| 14
| 97
| 5.928571
| 0.571429
| 0.168675
| 0.337349
| 0.578313
| 0.722892
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.082474
| 97
| 2
| 49
| 48.5
| 0.932584
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
9304e4355b9aa09da89300128501c54dbd6dbfc5
| 25,643
|
py
|
Python
|
PHASEfilter/tests/test_vcf.py
|
ibigen/PHASEfilter
|
669729f408b9c23d5db2ba72e74195b2228669da
|
[
"MIT"
] | null | null | null |
PHASEfilter/tests/test_vcf.py
|
ibigen/PHASEfilter
|
669729f408b9c23d5db2ba72e74195b2228669da
|
[
"MIT"
] | null | null | null |
PHASEfilter/tests/test_vcf.py
|
ibigen/PHASEfilter
|
669729f408b9c23d5db2ba72e74195b2228669da
|
[
"MIT"
] | null | null | null |
'''
Created on 13/05/2020
@author: mmp
'''
import unittest, os
from PHASEfilter.lib.utils.util import Utils
from PHASEfilter.lib.utils.reference import Reference
from PHASEfilter.lib.utils.vcf_process import VcfProcess
from PHASEfilter.lib.utils.run_extra_software import RunExtraSoftware
from PHASEfilter.lib.utils.lift_over_simple import LiftOverLight
from PHASEfilter.lib.utils.software import Software
### run command line
# export PYTHONPATH='/home/mmp/git/PHASEfilter'
# python3 -m unittest -v tests.test_vcf
# python3 -m unittest discover -s tests -p 'test_*.py'
class Test(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def test_vcf_threshold_ad(self):
run_extra_software = RunExtraSoftware()
utils = Utils("synchronize")
temp_work_dir = utils.get_temp_dir()
seq_file_name_a = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1A.fasta")
seq_file_name_b = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1B.fasta")
self.assertTrue(os.path.exists(seq_file_name_a))
self.assertTrue(os.path.exists(seq_file_name_b))
reference_a = Reference(seq_file_name_a)
reference_b = Reference(seq_file_name_b)
impose_minimap2_only = False
lift_over_ligth = LiftOverLight(reference_a, reference_b, temp_work_dir, impose_minimap2_only, True)
seq_name_a = reference_a.get_first_seq()
self.assertEqual("Ca22chr1A_C_albicans_SC5314", seq_name_a)
seq_name_b = reference_b.get_chr_in_genome(seq_name_a)
self.assertEqual("Ca22chr1B_C_albicans_SC5314", seq_name_b)
lift_over_ligth.synchronize_sequences(seq_name_a, seq_name_b)
self.assertEqual(["35769M1I9181M1I1214M1I23763M"], lift_over_ligth.get_cigar_string(\
Software.SOFTWARE_minimap2_name, seq_name_a, seq_name_b))
self.assertEqual((1, -1), lift_over_ligth.get_pos_in_target(seq_name_a, seq_name_b, 1))
self.assertEqual((487, -1), lift_over_ligth.get_pos_in_target(seq_name_a, seq_name_b, 487))
### read vcf
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_a, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_a, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrB.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_b, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_b, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_out = utils.get_temp_file_with_path(temp_work_dir, "vcf_result", ".vcf")
vcf_out_removed = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_removed", ".vcf")
vcf_out_LOH = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_LOH", ".vcf")
b_print_results = False
threshold_ad = 0.4
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(temp_out_vcf_a, threshold_ad, threshold_remove_variant_ad, b_print_results)
vcf_process.match_vcf_to(seq_name_a, lift_over_ligth, temp_out_vcf_b, seq_name_b, vcf_out, vcf_out_removed, vcf_out_LOH)
self.assertTrue(vcf_process.count_alleles.has_removed_variants())
self.assertTrue(vcf_process.count_alleles.has_saved_variants())
self.assertEqual("Heterozygous (Removed) Keep alleles LOH alleles Other than SNP Don't have hit position Could Not Fetch VCF Record on Hit" +\
" Total alleles Total Alleles new Source VCF", vcf_process.count_alleles.get_header())
self.assertEqual("6 117 2 0 2078 8 2209 2203", str(vcf_process.count_alleles))
## remove everything
utils.remove_dir(temp_work_dir)
utils.remove_file(temp_out_vcf_a)
utils.remove_file(temp_out_vcf_a + ".tbi")
utils.remove_file(temp_out_vcf_b)
utils.remove_file(temp_out_vcf_b + ".tbi")
def test_vcf(self):
run_extra_software = RunExtraSoftware()
utils = Utils("synchronize")
temp_work_dir = utils.get_temp_dir()
seq_file_name_a = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1A.fasta")
seq_file_name_b = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1B.fasta")
self.assertTrue(os.path.exists(seq_file_name_a))
self.assertTrue(os.path.exists(seq_file_name_b))
reference_a = Reference(seq_file_name_a)
reference_b = Reference(seq_file_name_b)
impose_minimap2_only = False
lift_over_ligth = LiftOverLight(reference_a, reference_b, temp_work_dir, impose_minimap2_only, True)
seq_name_a = reference_a.get_first_seq()
self.assertEqual("Ca22chr1A_C_albicans_SC5314", seq_name_a)
seq_name_b = reference_b.get_chr_in_genome(seq_name_a)
self.assertEqual("Ca22chr1B_C_albicans_SC5314", seq_name_b)
lift_over_ligth.synchronize_sequences(seq_name_a, seq_name_b)
self.assertEqual(["35769M1I9181M1I1214M1I23763M"], lift_over_ligth.get_cigar_string(\
Software.SOFTWARE_minimap2_name, seq_name_a, seq_name_b))
self.assertEqual((487, -1), lift_over_ligth.get_pos_in_target(seq_name_a, seq_name_b, 487))
#### read vcf
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_a, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_a, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrB.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_b, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_b, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_out = utils.get_temp_file_with_path(temp_work_dir, "vcf_result", ".vcf")
vcf_out_removed = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_removed", ".vcf")
vcf_out_LOH = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_LOH", ".vcf")
b_print_results = False
threshold_ad = 0.5
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(temp_out_vcf_a, threshold_ad, threshold_remove_variant_ad, b_print_results)
vcf_process.match_vcf_to(seq_name_a, lift_over_ligth, temp_out_vcf_b, seq_name_b, vcf_out, vcf_out_removed, vcf_out_LOH)
self.assertTrue(vcf_process.count_alleles.has_removed_variants())
self.assertTrue(vcf_process.count_alleles.has_saved_variants())
self.assertEqual("Heterozygous (Removed) Keep alleles LOH alleles Other than SNP Don't have hit position Could Not Fetch VCF Record on Hit" +\
" Total alleles Total Alleles new Source VCF", vcf_process.count_alleles.get_header())
self.assertEqual("8 115 0 0 2078 8 2209 2201", str(vcf_process.count_alleles))
### remove everything
utils.remove_dir(temp_work_dir)
utils.remove_file(temp_out_vcf_a)
utils.remove_file(temp_out_vcf_a + ".tbi")
utils.remove_file(temp_out_vcf_b)
utils.remove_file(temp_out_vcf_b + ".tbi")
def test_vcf_remove_AD(self):
run_extra_software = RunExtraSoftware()
utils = Utils("synchronize")
temp_work_dir = utils.get_temp_dir()
seq_file_name_a = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1A.fasta")
seq_file_name_b = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1B.fasta")
self.assertTrue(os.path.exists(seq_file_name_a))
self.assertTrue(os.path.exists(seq_file_name_b))
reference_a = Reference(seq_file_name_a)
reference_b = Reference(seq_file_name_b)
impose_minimap2_only = False
lift_over_ligth = LiftOverLight(reference_a, reference_b, temp_work_dir, impose_minimap2_only, True)
seq_name_a = reference_a.get_first_seq()
self.assertEqual("Ca22chr1A_C_albicans_SC5314", seq_name_a)
seq_name_b = reference_b.get_chr_in_genome(seq_name_a)
self.assertEqual("Ca22chr1B_C_albicans_SC5314", seq_name_b)
lift_over_ligth.synchronize_sequences(seq_name_a, seq_name_b)
self.assertEqual(["35769M1I9181M1I1214M1I23763M"], lift_over_ligth.get_cigar_string(\
Software.SOFTWARE_minimap2_name, seq_name_a, seq_name_b))
self.assertEqual((487, -1), lift_over_ligth.get_pos_in_target(seq_name_a, seq_name_b, 487))
#### read vcf
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_a, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_a, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrB.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_b, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_b, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_out = utils.get_temp_file_with_path(temp_work_dir, "vcf_result", ".vcf")
vcf_out_removed = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_removed", ".vcf")
vcf_out_LOH = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_LOH", ".vcf")
b_print_results = False
threshold_ad = 0.5
threshold_remove_variant_ad = 0.3
vcf_process = VcfProcess(temp_out_vcf_a, threshold_ad, threshold_remove_variant_ad, b_print_results)
vcf_process.match_vcf_to(seq_name_a, lift_over_ligth, temp_out_vcf_b, seq_name_b, vcf_out, vcf_out_removed, vcf_out_LOH)
self.assertTrue(vcf_process.count_alleles.has_removed_variants())
self.assertTrue(vcf_process.count_alleles.has_saved_variants())
self.assertEqual("Heterozygous (Removed) Keep alleles LOH alleles Other than SNP Don't have hit position Could Not Fetch VCF Record on Hit " +\
"Variants removed by AD threshold 0.30 Total alleles Total Alleles new Source VCF", vcf_process.count_alleles.get_header())
self.assertEqual("6 70 0 0 2071 4 58 2151 2145", str(vcf_process.count_alleles))
### remove everything
utils.remove_dir(temp_work_dir)
utils.remove_file(temp_out_vcf_a)
utils.remove_file(temp_out_vcf_a + ".tbi")
utils.remove_file(temp_out_vcf_b)
utils.remove_file(temp_out_vcf_b + ".tbi")
def test_vcf_remove_AD_2(self):
run_extra_software = RunExtraSoftware()
utils = Utils("synchronize")
temp_work_dir = utils.get_temp_dir()
seq_file_name_a = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1A.fasta")
seq_file_name_b = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1B.fasta")
self.assertTrue(os.path.exists(seq_file_name_a))
self.assertTrue(os.path.exists(seq_file_name_b))
reference_a = Reference(seq_file_name_a)
reference_b = Reference(seq_file_name_b)
impose_minimap2_only = False
lift_over_ligth = LiftOverLight(reference_a, reference_b, temp_work_dir, impose_minimap2_only, True)
seq_name_a = reference_a.get_first_seq()
self.assertEqual("Ca22chr1A_C_albicans_SC5314", seq_name_a)
seq_name_b = reference_b.get_chr_in_genome(seq_name_a)
self.assertEqual("Ca22chr1B_C_albicans_SC5314", seq_name_b)
lift_over_ligth.synchronize_sequences(seq_name_a, seq_name_b)
self.assertEqual(["35769M1I9181M1I1214M1I23763M"], lift_over_ligth.get_cigar_string(\
Software.SOFTWARE_minimap2_name, seq_name_a, seq_name_b))
self.assertEqual((487, -1), lift_over_ligth.get_pos_in_target(seq_name_a, seq_name_b, 487))
#### read vcf
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_a, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_a, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrB.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_b, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_b, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_out = utils.get_temp_file_with_path(temp_work_dir, "vcf_result", ".vcf")
vcf_out_removed = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_removed", ".vcf")
vcf_out_LOH = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_LOH", ".vcf")
b_print_results = False
threshold_ad = 0.5
threshold_remove_variant_ad = 0.15
vcf_process = VcfProcess(temp_out_vcf_a, threshold_ad, threshold_remove_variant_ad, b_print_results)
vcf_process.match_vcf_to(seq_name_a, lift_over_ligth, temp_out_vcf_b, seq_name_b, vcf_out, vcf_out_removed, vcf_out_LOH)
self.assertTrue(vcf_process.count_alleles.has_removed_variants())
self.assertTrue(vcf_process.count_alleles.has_saved_variants())
self.assertEqual("Heterozygous (Removed) Keep alleles LOH alleles Other than SNP Don't have hit position Could Not Fetch VCF Record on Hit " +\
"Variants removed by AD threshold 0.15 Total alleles Total Alleles new Source VCF", vcf_process.count_alleles.get_header())
self.assertEqual("8 107 0 0 2077 7 10 2199 2191", str(vcf_process.count_alleles))
### remove everything
utils.remove_dir(temp_work_dir)
utils.remove_file(temp_out_vcf_a)
utils.remove_file(temp_out_vcf_a + ".tbi")
utils.remove_file(temp_out_vcf_b)
utils.remove_file(temp_out_vcf_b + ".tbi")
def test_vcf_remove_AD_3(self):
run_extra_software = RunExtraSoftware()
utils = Utils("synchronize")
temp_work_dir = utils.get_temp_dir()
seq_file_name_a = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1A.fasta")
seq_file_name_b = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1B.fasta")
self.assertTrue(os.path.exists(seq_file_name_a))
self.assertTrue(os.path.exists(seq_file_name_b))
reference_a = Reference(seq_file_name_a)
reference_b = Reference(seq_file_name_b)
impose_minimap2_only = False
lift_over_ligth = LiftOverLight(reference_a, reference_b, temp_work_dir, impose_minimap2_only, True)
seq_name_a = reference_a.get_first_seq()
self.assertEqual("Ca22chr1A_C_albicans_SC5314", seq_name_a)
seq_name_b = reference_b.get_chr_in_genome(seq_name_a)
self.assertEqual("Ca22chr1B_C_albicans_SC5314", seq_name_b)
lift_over_ligth.synchronize_sequences(seq_name_a, seq_name_b)
self.assertEqual(["35769M1I9181M1I1214M1I23763M"], lift_over_ligth.get_cigar_string(\
Software.SOFTWARE_minimap2_name, seq_name_a, seq_name_b))
self.assertEqual((487, -1), lift_over_ligth.get_pos_in_target(seq_name_a, seq_name_b, 487))
#### read vcf
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_a, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_a, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/chrB.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_b, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_b, temp_work_dir)
self.assertEqual(2209, number_of_records)
vcf_out = utils.get_temp_file_with_path(temp_work_dir, "vcf_result", ".vcf")
vcf_out_removed = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_removed", ".vcf")
vcf_out_LOH = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_LOH", ".vcf")
b_print_results = False
threshold_ad = 0.5
threshold_remove_variant_ad = 0.1
vcf_process = VcfProcess(temp_out_vcf_a, threshold_ad, threshold_remove_variant_ad, b_print_results)
vcf_process.match_vcf_to(seq_name_a, lift_over_ligth, temp_out_vcf_b, seq_name_b, vcf_out, vcf_out_removed, vcf_out_LOH)
self.assertTrue(vcf_process.count_alleles.has_removed_variants())
self.assertTrue(vcf_process.count_alleles.has_saved_variants())
self.assertEqual("Heterozygous (Removed) Keep alleles LOH alleles Other than SNP Don't have hit position Could Not Fetch VCF Record on Hit " +\
"Variants removed by AD threshold 0.10 Total alleles Total Alleles new Source VCF", vcf_process.count_alleles.get_header())
self.assertEqual("8 115 0 0 2078 8 0 2209 2201", str(vcf_process.count_alleles))
### remove everything
utils.remove_dir(temp_work_dir)
utils.remove_file(temp_out_vcf_a)
utils.remove_file(temp_out_vcf_a + ".tbi")
utils.remove_file(temp_out_vcf_b)
utils.remove_file(temp_out_vcf_b + ".tbi")
def test_vcf_indel(self):
run_extra_software = RunExtraSoftware()
utils = Utils("synchronize")
temp_work_dir = utils.get_temp_dir()
seq_file_name_a = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1A.fasta")
seq_file_name_b = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/ref/ref_ca22_1B.fasta")
self.assertTrue(os.path.exists(seq_file_name_a))
self.assertTrue(os.path.exists(seq_file_name_b))
reference_a = Reference(seq_file_name_a)
reference_b = Reference(seq_file_name_b)
impose_minimap2_only = False
lift_over_ligth = LiftOverLight(reference_a, reference_b, temp_work_dir, impose_minimap2_only, True)
seq_name_a = reference_a.get_first_seq()
self.assertEqual("Ca22chr1A_C_albicans_SC5314", seq_name_a)
seq_name_b = reference_b.get_chr_in_genome(seq_name_a)
self.assertEqual("Ca22chr1B_C_albicans_SC5314", seq_name_b)
lift_over_ligth.synchronize_sequences(seq_name_a, seq_name_b)
self.assertEqual(["35769M1I9181M1I1214M1I23763M"], lift_over_ligth.get_cigar_string(\
Software.SOFTWARE_minimap2_name, seq_name_a, seq_name_b))
self.assertEqual((487, -1), lift_over_ligth.get_pos_in_target(seq_name_a, seq_name_b, 487))
#### read vcf
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/A-M_S4_chrA_indel.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_a, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_a, temp_work_dir)
self.assertEqual(954, number_of_records)
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/A-M_S4_chrB_indel.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
(temp_out_vcf_b, number_of_records) = run_extra_software.get_vcf_with_only_chr(vcf_file_name, seq_name_b, temp_work_dir)
self.assertEqual(954, number_of_records)
vcf_out = utils.get_temp_file_with_path(temp_work_dir, "vcf_result", ".vcf")
vcf_out_removed = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_removed", ".vcf")
vcf_out_LOH = utils.get_temp_file_with_path(temp_work_dir, "vcf_result_LOH", ".vcf")
b_print_results = False
threshold_ad = 0.5
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(temp_out_vcf_a, threshold_ad, threshold_remove_variant_ad, b_print_results)
vcf_process.match_vcf_to(seq_name_a, lift_over_ligth, temp_out_vcf_b, seq_name_b, vcf_out, vcf_out_removed, vcf_out_LOH)
self.assertTrue(vcf_process.count_alleles.has_removed_variants())
self.assertTrue(vcf_process.count_alleles.has_saved_variants())
self.assertEqual("Heterozygous (Removed) Keep alleles LOH alleles Other than SNP Don't have hit position Could Not Fetch VCF Record on Hit Total alleles Total Alleles new Source VCF", vcf_process.count_alleles.get_header())
self.assertEqual("1 18 0 0 935 0 954 953", str(vcf_process.count_alleles))
### remove everything
utils.remove_dir(temp_work_dir)
utils.remove_file(temp_out_vcf_a)
utils.remove_file(temp_out_vcf_a + ".tbi")
utils.remove_file(temp_out_vcf_b)
utils.remove_file(temp_out_vcf_b + ".tbi")
def test_vcf_ratio(self):
b_print_results = False
threshold_ad = 0.05
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(None, threshold_ad, threshold_remove_variant_ad, b_print_results)
self.assertEqual(0.09, vcf_process.get_ratio([200, 20], 1))
self.assertEqual(0.91, vcf_process.get_ratio([20, 200], 1))
self.assertEqual(0.5, vcf_process.get_ratio([20, 200], 2))
self.assertEqual(1.0, vcf_process.get_ratio([0, 200], 1))
self.assertEqual(0.0, vcf_process.get_ratio([0, 0], 1))
self.assertEqual(0.0, vcf_process.get_ratio([10, 0], 1))
self.assertEqual(0.09, vcf_process.get_ratio([20, 200, 2000], 1))
self.assertEqual(0.9, vcf_process.get_ratio([20, 200, 2000], 2))
self.assertEqual(0.99, vcf_process.get_ratio([20, 200, 2000, 200000], 3))
def test_vcf_match_indels(self):
b_print_results = False
threshold_ad = 0.5
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(None, threshold_ad, threshold_remove_variant_ad, b_print_results)
slice_source = "GAAAAAAAAAAAGTGAAAATC"
slice_hit = "GAAAAAAAAAAAAGTGAAAAT"
ref_source = "G"
alt_base_in_source = "GA"
ref_hit = "GA"
alt_base_in_hit = "G"
(length_bases_after_base_source, length_bases_after_base_hit) = vcf_process.get_length_bases_match(slice_source,\
slice_hit, ref_source, alt_base_in_source, ref_hit, alt_base_in_hit)
self.assertEqual(12, length_bases_after_base_hit)
self.assertEqual(11, length_bases_after_base_source)
slice_source = "GAAAAAAAAAAAGTGAAAATC"
slice_hit = "GAAAAAAAAAAAAGTGAAAAT"
ref_source = "G"
alt_base_in_source = "GAA"
ref_hit = "GAA"
alt_base_in_hit = "G"
(length_bases_after_base_source, length_bases_after_base_hit) = vcf_process.get_length_bases_match(slice_source,\
slice_hit, ref_source, alt_base_in_source, ref_hit, alt_base_in_hit)
self.assertEqual(12, length_bases_after_base_hit)
self.assertEqual(10, length_bases_after_base_source)
slice_source = "GAAAAAAAAAAAAGTGAAAAT"
slice_hit = "GAAAAAAAAAAAGTGAAAATC"
ref_source = "G"
alt_base_in_source = "GAA"
ref_hit = "GAA"
alt_base_in_hit = "G"
(length_bases_after_base_source, length_bases_after_base_hit) = vcf_process.get_length_bases_match(slice_source,\
slice_hit, ref_source, alt_base_in_source, ref_hit, alt_base_in_hit)
self.assertEqual(10, length_bases_after_base_hit)
self.assertEqual(12, length_bases_after_base_source)
slice_source = "GAAAAAAAAAAAAGTGAAAAT"
slice_hit = "GAAAAAAAGTGAAAATC"
ref_source = "G"
alt_base_in_source = "GAA"
ref_hit = "GAA"
alt_base_in_hit = "G"
(length_bases_after_base_source, length_bases_after_base_hit) = vcf_process.get_length_bases_match(slice_source,\
slice_hit, ref_source, alt_base_in_source, ref_hit, alt_base_in_hit)
self.assertEqual(6, length_bases_after_base_hit)
self.assertEqual(12, length_bases_after_base_source)
slice_source = "GAAAAAAAAAAAA"
slice_hit = "GAAAAAAAAAA"
ref_source = "G"
alt_base_in_source = "GAA"
ref_hit = "GAA"
alt_base_in_hit = "G"
(length_bases_after_base_source, length_bases_after_base_hit) = vcf_process.get_length_bases_match(slice_source,\
slice_hit, ref_source, alt_base_in_source, ref_hit, alt_base_in_hit)
self.assertEqual(-1, length_bases_after_base_hit)
self.assertEqual(-1, length_bases_after_base_source)
slice_source = "AGAACTCAGAACTAAAAATAG"
slice_hit = "AAACTCAGAACTAAAAATAGT"
ref_source = "AG"
alt_base_in_source = "A"
ref_hit = "A"
alt_base_in_hit = "AG"
(length_bases_after_base_source, length_bases_after_base_hit) = vcf_process.get_length_bases_match(slice_source,\
slice_hit, ref_source, alt_base_in_source, ref_hit, alt_base_in_hit)
self.assertEqual(0, length_bases_after_base_hit)
self.assertEqual(1, length_bases_after_base_source)
def test_af_in_vcf(self):
"""
Test if vcf has AF tag
"""
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/test_with_AF_chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
b_print_results = False
threshold_ad = 0.05
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(vcf_file_name, threshold_ad, threshold_remove_variant_ad, b_print_results)
self.assertFalse(vcf_process.has_format('AF'))
self.assertTrue(vcf_process.has_format('AD'))
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/test_without_AF_chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
b_print_results = False
threshold_ad = 0.05
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(vcf_file_name, threshold_ad, threshold_remove_variant_ad, b_print_results)
self.assertFalse(vcf_process.has_format('AF'))
self.assertTrue(vcf_process.has_format('DP'))
self.assertFalse(vcf_process.has_format('MF'))
def test_reference_file_name(self):
"""
test reference file name
"""
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/test_with_AF_chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
b_print_results = False
threshold_ad = 0.05
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(vcf_file_name, threshold_ad, threshold_remove_variant_ad, b_print_results)
self.assertFalse(vcf_process.exist_reference_name('AF'))
self.assertTrue(vcf_process.exist_reference_name('C_albicans_SC5314_A22_chromosomes.fasta'))
def test_tag_test(self):
"""
test meta data tag
"""
vcf_file_name = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files/vcf/test_with_AF_chrA.vcf")
self.assertTrue(os.path.exists(vcf_file_name))
b_print_results = False
threshold_ad = 0.05
threshold_remove_variant_ad = -1.0
vcf_process = VcfProcess(vcf_file_name, threshold_ad, threshold_remove_variant_ad, b_print_results)
self.assertFalse(vcf_process.exist_meta_data_tag('AF'))
self.assertTrue(vcf_process.exist_meta_data_tag('reference'))
self.assertTrue(vcf_process.exist_meta_data_tag('FORMAT'))
if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testName']
unittest.main()
| 48.110694
| 225
| 0.792185
| 4,192
| 25,643
| 4.382156
| 0.052481
| 0.036581
| 0.021339
| 0.018291
| 0.93718
| 0.934513
| 0.926619
| 0.921176
| 0.912412
| 0.908492
| 0
| 0.028586
| 0.101002
| 25,643
| 533
| 226
| 48.110694
| 0.768273
| 0.018017
| 0
| 0.807882
| 0
| 0.014778
| 0.128472
| 0.049133
| 0
| 0
| 0
| 0
| 0.295567
| 1
| 0.03202
| false
| 0.004926
| 0.017241
| 0
| 0.051724
| 0.059113
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
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| 1
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| null | 0
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| 0
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| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
935bd4076f369e4943196aa4fe47f5b76d3f22a3
| 5,854
|
py
|
Python
|
daiquiri/auth/tests/test_accounts.py
|
agy-why/daiquiri
|
4d3e2ce51e202d5a8f1df404a0094a4e018dcb4d
|
[
"Apache-2.0"
] | 14
|
2018-12-23T18:35:02.000Z
|
2021-12-15T04:55:12.000Z
|
daiquiri/auth/tests/test_accounts.py
|
agy-why/daiquiri
|
4d3e2ce51e202d5a8f1df404a0094a4e018dcb4d
|
[
"Apache-2.0"
] | 40
|
2018-12-20T12:44:05.000Z
|
2022-03-21T11:35:20.000Z
|
daiquiri/auth/tests/test_accounts.py
|
agy-why/daiquiri
|
4d3e2ce51e202d5a8f1df404a0094a4e018dcb4d
|
[
"Apache-2.0"
] | 5
|
2019-05-16T08:03:35.000Z
|
2021-08-23T20:03:11.000Z
|
from django.urls import reverse
from django.test import TestCase
from ..models import Profile
class AccountsTestCase(TestCase):
fixtures = (
'auth.json',
)
def test_login(self):
url = reverse('account_login')
response = self.client.post(url, {
'login': 'user',
'password': 'user'
})
self.assertRedirects(response, reverse('home'))
def test_invalid(self):
url = reverse('account_login')
response = self.client.post(url, {
'login': 'invalid',
'password': 'invalid'
})
self.assertEqual(response.status_code, 200)
def test_logout(self):
url = reverse('account_logout')
response = self.client.post(url)
self.assertRedirects(response, reverse('home'))
def test_signup_get(self):
url = reverse('account_signup')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
def test_signup_post(self):
url = reverse('account_signup')
response = self.client.post(url, {
'email': 'testing@example.com',
'username': 'testing',
'first_name': 'Tanja',
'last_name': 'Test',
'password1': 'testing',
'password2': 'testing'
})
# check that the signup redirects to the pending page or the confirm email page
self.assertEqual(response.status_code, 302)
# check that a profile was created
profile = Profile.objects.get(user__username='testing')
self.assertEqual(profile.is_pending, True)
def test_signup_post_invalid(self):
url = reverse('account_signup')
response = self.client.post(url, {
'email': 'testing@example.com',
'username': 'testing',
'first_name': 'Tanja',
'last_name': 'Test',
'password1': 'testing',
'password2': 'invalid'
})
# check that the signup returns 200 (with validation error)
self.assertEqual(response.status_code, 200)
self.assertContains(response, '* You must type the same password each time.')
# check that a profile was not created
exists = Profile.objects.filter(user__username='testing').exists()
self.assertEqual(exists, False)
def test_signup_post_exists(self):
url = reverse('account_signup')
response = self.client.post(url, {
'email': 'user@example.com',
'username': 'user',
'first_name': 'Tanja',
'last_name': 'Test',
'password1': 'testing',
'password2': 'testing'
})
# check that the signup returns 200 (with validation error)
self.assertEqual(response.status_code, 200)
self.assertContains(response, '* A user with that username already exists.')
self.assertContains(response, '* A user is already registered with this e-mail address.')
# check that a profile was not created
exists = Profile.objects.filter(user__username='testing').exists()
self.assertEqual(exists, False)
def test_profile_get_for_user(self):
self.client.login(username='user', password='user')
url = reverse('account_profile')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
def test_profile_get_for_anonymous(self):
url = reverse('account_profile')
response = self.client.get(url)
self.assertRedirects(response, reverse('account_login') + '?next=' + url)
def test_profile_post_for_user(self):
self.client.login(username='user', password='user')
url = reverse('account_profile')
response = self.client.post(url, {
'first_name': 'Tanja',
'last_name': 'Test',
})
self.assertRedirects(response, reverse('home'))
def test_profile_cancel_for_user(self):
self.client.login(username='user', password='user')
url = reverse('account_profile')
response = self.client.post(url, {
'cancel': True
})
self.assertRedirects(response, reverse('home'))
def test_profile_post_for_anonymous(self):
url = reverse('account_profile')
response = self.client.post(url, {
'first_name': 'Tanja',
'last_name': 'Test',
})
self.assertRedirects(response, reverse('account_login') + '?next=' + url)
def test_profile_json_get_for_user(self):
self.client.login(username='user', password='user')
url = reverse('account_profile_json')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
def test_profile_json_get_for_anonymous(self):
url = reverse('account_profile_json')
response = self.client.get(url)
self.assertRedirects(response, reverse('account_login') + '?next=' + url)
def test_token_get_for_user(self):
self.client.login(username='user', password='user')
url = reverse('account_token')
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
def test_token_get_for_anonymous(self):
url = reverse('account_token')
response = self.client.get(url)
self.assertRedirects(response, reverse('account_login') + '?next=' + url)
def test_token_post_for_user(self):
self.client.login(username='user', password='user')
url = reverse('account_token')
response = self.client.post(url)
self.assertEqual(response.status_code, 200)
def test_token_post_for_anonymous(self):
url = reverse('account_token')
response = self.client.post(url)
self.assertRedirects(response, reverse('account_login') + '?next=' + url)
| 34.435294
| 97
| 0.617868
| 646
| 5,854
| 5.428793
| 0.134675
| 0.068435
| 0.087254
| 0.071856
| 0.845167
| 0.813801
| 0.81152
| 0.792415
| 0.746222
| 0.715426
| 0
| 0.008986
| 0.258627
| 5,854
| 169
| 98
| 34.639053
| 0.799078
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| 1
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| false
| 0.116279
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| 0
| 0
|
0
| 7
|
fa9343a73576efd2eed18acedcd1a48ad06eef80
| 30,705
|
py
|
Python
|
tests/test_cfg_setup.py
|
KonnexionsGmbH/ocr_bench
|
8f54b386c22b43a2f4e8f98dc6f7ac69edf7e0be
|
[
"CNRI-Python",
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null |
tests/test_cfg_setup.py
|
KonnexionsGmbH/ocr_bench
|
8f54b386c22b43a2f4e8f98dc6f7ac69edf7e0be
|
[
"CNRI-Python",
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null |
tests/test_cfg_setup.py
|
KonnexionsGmbH/ocr_bench
|
8f54b386c22b43a2f4e8f98dc6f7ac69edf7e0be
|
[
"CNRI-Python",
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null |
# pylint: disable=unused-argument
"""Testing Module cfg.setup."""
import os
import cfg.glob
import cfg.setup
import pytest
# -----------------------------------------------------------------------------
# Constants & Globals.
# -----------------------------------------------------------------------------
# pylint: disable=W0212
# @pytest.mark.issue
CONFIG_PARAM_NO: int = 60
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config(fxtr_setup_logger_environment):
"""Test: get_config()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
cfg.glob.setup.is_ignore_duplicates = False
cfg.glob.setup = cfg.setup.Setup()
assert len(cfg.glob.setup._config) == CONFIG_PARAM_NO, "cfg:: complete"
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_IGNORE_DUPLICATES, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_ignore_duplicates, "DCR_CFG_IGNORE_DUPLICATES: false (any not true)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_IGNORE_DUPLICATES, "TruE"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_ignore_duplicates, "DCR_CFG_IGNORE_DUPLICATES: true"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_PDF2IMAGE_TYPE, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
with pytest.raises(SystemExit) as expt:
cfg.glob.setup = cfg.setup.Setup()
assert expt.type == SystemExit, "DCR_CFG_PDF2IMAGE_TYPE: invalid"
assert expt.value.code == 1, "DCR_CFG_PDF2IMAGE_TYPE: invalid"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config() - coverage - false.
# -----------------------------------------------------------------------------
def test_get_config_coverage_false(fxtr_setup_logger_environment):
"""Test: test_get_config_coverage_false()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_DEP_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_ENT_IOB_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_ENT_TYPE_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_I, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_ALPHA, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_CURRENCY, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_DIGIT, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_OOV, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_PUNCT, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_SENT_END, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_SENT_START, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_STOP, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_TITLE, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LANG_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LEFT_EDGE, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LEMMA_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LIKE_EMAIL, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LIKE_NUM, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LIKE_URL, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_NORM_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_POS_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_RIGHT_EDGE, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_SHAPE_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_TAG_, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_TEXT, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_TEXT_WITH_WS, "false"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_WHITESPACE_, "false"),
],
)
cfg.glob.setup = cfg.setup.Setup()
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config() - coverage - true.
# -----------------------------------------------------------------------------
def test_get_config_coverage_true(fxtr_setup_logger_environment):
"""Test: test_get_config_coverage_true()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_DEP_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_ENT_IOB_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_ENT_TYPE_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_I, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_ALPHA, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_CURRENCY, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_DIGIT, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_OOV, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_PUNCT, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_SENT_END, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_SENT_START, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_STOP, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_IS_TITLE, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LANG_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LEFT_EDGE, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LEMMA_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LIKE_EMAIL, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LIKE_NUM, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_LIKE_URL, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_NORM_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_POS_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_RIGHT_EDGE, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_SHAPE_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_TAG_, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_TEXT, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_TEXT_WITH_WS, "true"),
(cfg.glob.setup._DCR_CFG_SPACY_TKN_ATTR_WHITESPACE_, "true"),
],
)
cfg.glob.setup = cfg.setup.Setup()
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_line_footer_preference(fxtr_setup_logger_environment):
"""Test: test_get_config_line_footer_preference()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(
cfg.glob.setup._DCR_CFG_LINE_FOOTER_PREFERENCE,
cfg.glob.INFORMATION_NOT_YET_AVAILABLE,
),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_line_footer_preferred, "DCR_CFG_LINE_FOOTER_PREFERENCE: true (not false)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_LINE_FOOTER_PREFERENCE, "fALSE"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_line_footer_preferred, "DCR_CFG_LINE_FOOTER_PREFERENCE: false"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config() - missing.
# -----------------------------------------------------------------------------
def test_get_config_missing(fxtr_setup_logger_environment):
"""Test: get_config() - missing."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
cfg.glob.setup = cfg.setup.Setup()
assert len(cfg.glob.setup._config) == CONFIG_PARAM_NO, "cfg:: complete"
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_DIRECTORY_INBOX
)
with pytest.raises(SystemExit) as expt:
cfg.glob.setup = cfg.setup.Setup()
assert expt.type == SystemExit, "DCR_CFG_DIRECTORY_INBOX: missing"
assert expt.value.code == 1, "DCR_CFG_DIRECTORY_INBOX: missing"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_DIRECTORY_INBOX_ACCEPTED
)
with pytest.raises(SystemExit) as expt:
cfg.glob.setup = cfg.setup.Setup()
assert expt.type == SystemExit, "DCR_CFG_DIRECTORY_INBOX_ACCEPTED: missing"
assert expt.value.code == 1, "DCR_CFG_DIRECTORY_INBOX_ACCEPTED: missing"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_DIRECTORY_INBOX_REJECTED
)
with pytest.raises(SystemExit) as expt:
cfg.glob.setup = cfg.setup.Setup()
assert expt.type == SystemExit, "DCR_CFG_DIRECTORY_INBOX_REJECTED: missing"
assert expt.value.code == 1, "DCR_CFG_DIRECTORY_INBOX_REJECTED: missing"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_IGNORE_DUPLICATES
)
cfg.glob.setup.is_ignore_duplicates = False
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_ignore_duplicates, "DCR_CFG_IGNORE_DUPLICATES: false (missing)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_PDF2IMAGE_TYPE
)
cfg.glob.setup.pdf2image_type = cfg.glob.setup.PDF2IMAGE_TYPE_JPEG
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.pdf2image_type == cfg.glob.setup.PDF2IMAGE_TYPE_JPEG, (
"DCR_CFG_PDF2IMAGE_TYPE: default should not be '" + cfg.glob.setup.pdf2image_type + "'"
)
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_SIMULATE_PARSER
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_simulate_parser, "DCR_CFG_SIMULATE_PARSER: false (missing)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_VERBOSE
)
cfg.glob.setup.is_verbose = True
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_verbose, "DCR_CFG_VERBOSE: true (missing)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION, cfg.glob.setup._DCR_CFG_VERBOSE_PARSER
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.verbose_parser == "none", "DCR_CFG_VERBOSE_PARSER: none (missing)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_simulate_parser(fxtr_setup_logger_environment):
"""Test: test_get_config_simulate_parser()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_SIMULATE_PARSER, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_simulate_parser, "DCR_CFG_SIMULATE_PARSER: false (not true)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_SIMULATE_PARSER, "tRUE"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_simulate_parser, "DCR_CFG_SIMULATE_PARSER: true"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_tetml_line(fxtr_setup_logger_environment):
"""Test: test_get_config_tetml_line()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_TETML_LINE, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_tetml_line, "DCR_CFG_TETML_LINE: true (not false)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_TETML_LINE, "fALSE"),
(cfg.glob.setup._DCR_CFG_TETML_PAGE, "true"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_tetml_line, "DCR_CFG_TETML_LINE: false"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config() - tetml_line_page.
# -----------------------------------------------------------------------------
def test_get_config_tetml_line_page(fxtr_setup_logger_environment):
"""Test: get_config() - tetml_line & tetml_page."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_TETML_LINE, "false"),
],
)
with pytest.raises(SystemExit) as expt:
cfg.glob.setup = cfg.setup.Setup()
assert expt.type == SystemExit, "DCR_CFG_TETML_LINE and DCR_CFG_TETML_PAGE: both 'false' not allowed"
assert expt.value.code == 1, "DCR_CFG_TETML_LINE and DCR_CFG_TETML_PAGE: both 'false' not allowed"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_tetml_page(fxtr_setup_logger_environment):
"""Test: test_get_config_tetml_page()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_TETML_PAGE, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_tetml_page, "DCR_CFG_TETML_PAGE: false (not true)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_TETML_PAGE, "tRUE"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_tetml_page, "DCR_CFG_TETML_PAGE: true"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_tetml_word(fxtr_setup_logger_environment):
"""Test: test_get_config_tetml_word()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_TETML_WORD, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_tetml_word, "DCR_CFG_TETML_WORD: false (not true)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_TETML_WORD, "tRUE"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_tetml_word, "DCR_CFG_TETML_WORD: true"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config() - unknown.
# -----------------------------------------------------------------------------
def test_get_config_unknown(fxtr_setup_logger_environment):
"""Test: get_config() - unknown."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
cfg.glob.setup = cfg.setup.Setup()
assert len(cfg.glob.setup._config) == CONFIG_PARAM_NO, "cfg:: complete"
# -------------------------------------------------------------------------
pytest.helpers.insert_config_param(
cfg.glob.setup._DCR_CFG_SECTION,
"UNKNOWN",
"n/a",
)
with pytest.raises(SystemExit) as expt:
cfg.glob.setup = cfg.setup.Setup()
assert expt.type == SystemExit, "UNKNOWN: unknown"
assert expt.value.code == 1, "UNKNOWN: unknown"
pytest.helpers.delete_config_param(
cfg.glob.setup._DCR_CFG_SECTION,
"UNKNOWN",
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_verbose(fxtr_setup_logger_environment):
"""Test: get_config_verbose()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_VERBOSE, "FalsE"),
],
)
cfg.glob.setup.is_verbose = True
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_verbose, "DCR_CFG_VERBOSE: false"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_VERBOSE, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup.is_verbose = True
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_verbose, "DCR_CFG_VERBOSE: true (not false)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_verbose_line_type(fxtr_setup_logger_environment):
"""Test: test_get_config_verbose_line_type()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_VERBOSE_LINE_TYPE, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert not cfg.glob.setup.is_verbose_line_type, "DCR_CFG_VERBOSE_LINE_TYPE: false (not true)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_VERBOSE_LINE_TYPE, "tRUE"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.is_verbose_line_type, "DCR_CFG_VERBOSE_LINE_TYPE: true"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_config().
# -----------------------------------------------------------------------------
def test_get_config_verbose_parser(fxtr_setup_logger_environment):
"""Test: get_config_verbose_parser()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_VERBOSE_PARSER, "aLL"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.verbose_parser == "all", "DCR_CFG_VERBOSE_PARSER: all"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_VERBOSE_PARSER, cfg.glob.INFORMATION_NOT_YET_AVAILABLE),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.verbose_parser == "none", "DCR_CFG_VERBOSE_PARSER: none (not all or text)"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
values_original = pytest.helpers.backup_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
[
(cfg.glob.setup._DCR_CFG_VERBOSE_PARSER, "tEXT"),
],
)
cfg.glob.setup = cfg.setup.Setup()
assert cfg.glob.setup.verbose_parser == "text", "DCR_CFG_VERBOSE_PARSER: all"
pytest.helpers.restore_config_params(
cfg.glob.setup._DCR_CFG_SECTION,
values_original,
)
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Test Function - get_environment().
# -----------------------------------------------------------------------------
def test_get_environment(fxtr_setup_logger):
"""Test: get_environment()."""
cfg.glob.logger.debug(cfg.glob.LOGGER_START)
# -------------------------------------------------------------------------
cfg.glob.setup = cfg.setup.Setup()
os.environ[cfg.glob.setup._DCR_ENVIRONMENT_TYPE] = cfg.glob.INFORMATION_NOT_YET_AVAILABLE
with pytest.raises(SystemExit) as expt:
cfg.glob.setup._get_environment_variant()
os.environ[cfg.glob.setup._DCR_ENVIRONMENT_TYPE] = cfg.glob.setup._ENVIRONMENT_TYPE_TEST
assert expt.type == SystemExit, "_DCR_ENVIRONMENT_TYPE: invalid"
assert expt.value.code == 1, "_DCR_ENVIRONMENT_TYPE: invalid"
# -------------------------------------------------------------------------
os.environ.pop(cfg.glob.setup._DCR_ENVIRONMENT_TYPE)
with pytest.raises(SystemExit) as expt:
cfg.glob.setup._get_environment_variant()
os.environ[cfg.glob.setup._DCR_ENVIRONMENT_TYPE] = cfg.glob.setup._ENVIRONMENT_TYPE_TEST
assert expt.type == SystemExit, "_DCR_ENVIRONMENT_TYPE: missing"
assert expt.value.code == 1, "_DCR_ENVIRONMENT_TYPE: missing"
# -------------------------------------------------------------------------
cfg.glob.setup._get_environment_variant()
assert cfg.glob.setup.environment_variant == cfg.glob.setup._ENVIRONMENT_TYPE_TEST, "_DCR_ENVIRONMENT_TYPE: ok"
# -------------------------------------------------------------------------
cfg.glob.logger.debug(cfg.glob.LOGGER_END)
| 37.038601
| 115
| 0.53646
| 3,203
| 30,705
| 4.723072
| 0.040587
| 0.142054
| 0.183236
| 0.150714
| 0.966817
| 0.953001
| 0.937269
| 0.924379
| 0.896021
| 0.841883
| 0
| 0.000934
| 0.163296
| 30,705
| 828
| 116
| 37.083333
| 0.58791
| 0.252369
| 0
| 0.519763
| 0
| 0
| 0.079534
| 0.031401
| 0
| 0
| 0
| 0
| 0.086957
| 1
| 0.029644
| false
| 0
| 0.007905
| 0
| 0.037549
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
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| 0
| 0
| 0
|
0
| 7
|
faa7cf81b7a9c507c520661db87cfd39ad53b1e7
| 2,008
|
py
|
Python
|
tests/test_1338.py
|
sungho-joo/leetcode2github
|
ce7730ef40f6051df23681dd3c0e1e657abba620
|
[
"MIT"
] | null | null | null |
tests/test_1338.py
|
sungho-joo/leetcode2github
|
ce7730ef40f6051df23681dd3c0e1e657abba620
|
[
"MIT"
] | null | null | null |
tests/test_1338.py
|
sungho-joo/leetcode2github
|
ce7730ef40f6051df23681dd3c0e1e657abba620
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
import pytest
"""
Test 1338. Reduce Array Size to The Half
"""
@pytest.fixture(scope="session")
def init_variables_1338():
from src.leetcode_1338_reduce_array_size_to_the_half import Solution
solution = Solution()
def _init_variables_1338():
return solution
yield _init_variables_1338
class TestClass1338:
def test_solution_0(self, init_variables_1338):
assert init_variables_1338().minSetSize([3, 3, 3, 3, 5, 5, 5, 2, 2, 7]) == 2
def test_solution_1(self, init_variables_1338):
assert init_variables_1338().minSetSize([7, 7, 7, 7, 7, 7]) == 1
def test_solution_2(self, init_variables_1338):
assert init_variables_1338().minSetSize([1, 9]) == 1
def test_solution_3(self, init_variables_1338):
assert init_variables_1338().minSetSize([1000, 1000, 3, 7]) == 1
def test_solution_4(self, init_variables_1338):
assert init_variables_1338().minSetSize([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) == 5
#!/usr/bin/env python
import pytest
"""
Test 1338. Reduce Array Size to The Half
"""
@pytest.fixture(scope="session")
def init_variables_1338():
from src.leetcode_1338_reduce_array_size_to_the_half import Solution
solution = Solution()
def _init_variables_1338():
return solution
yield _init_variables_1338
class TestClass1338:
def test_solution_0(self, init_variables_1338):
assert init_variables_1338().minSetSize([3, 3, 3, 3, 5, 5, 5, 2, 2, 7]) == 2
def test_solution_1(self, init_variables_1338):
assert init_variables_1338().minSetSize([7, 7, 7, 7, 7, 7]) == 1
def test_solution_2(self, init_variables_1338):
assert init_variables_1338().minSetSize([1, 9]) == 1
def test_solution_3(self, init_variables_1338):
assert init_variables_1338().minSetSize([1000, 1000, 3, 7]) == 1
def test_solution_4(self, init_variables_1338):
assert init_variables_1338().minSetSize([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) == 5
| 26.773333
| 85
| 0.687251
| 300
| 2,008
| 4.3
| 0.143333
| 0.262016
| 0.342636
| 0.162791
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0.139163
| 0.191235
| 2,008
| 74
| 86
| 27.135135
| 0.655172
| 0.01992
| 0
| 1
| 0
| 0
| 0.007487
| 0
| 0
| 0
| 0
| 0
| 0.263158
| 1
| 0.368421
| false
| 0
| 0.105263
| 0.052632
| 0.578947
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 12
|
faab654c28dc13972f7d8127d5edede1559e747d
| 4,199
|
py
|
Python
|
tests/test_parser/test_variable_declaration.py
|
vbondarevsky/ones_analyzer
|
ab8bff875192db238ed17c20d61c9fa5b55c3fa8
|
[
"MIT"
] | 12
|
2017-11-23T07:04:13.000Z
|
2022-03-01T21:06:56.000Z
|
tests/test_parser/test_variable_declaration.py
|
vbondarevsky/analyzer_test
|
ab8bff875192db238ed17c20d61c9fa5b55c3fa8
|
[
"MIT"
] | 2
|
2017-06-25T21:32:32.000Z
|
2017-11-19T19:05:40.000Z
|
tests/test_parser/test_variable_declaration.py
|
vbondarevsky/analyzer_test
|
ab8bff875192db238ed17c20d61c9fa5b55c3fa8
|
[
"MIT"
] | 5
|
2017-11-21T08:24:56.000Z
|
2021-08-17T23:21:18.000Z
|
from analyzer.syntax_kind import SyntaxKind
from tests.utils import TestCaseParser
class TestParserVariableDeclaration(TestCaseParser):
def test_one_declaration_one_variable(self):
self.parse_source("Перем А")
self.assertNode(self.syntax_tree.declarations, [SyntaxKind.VariableDeclaration])
self.assertNode(self.syntax_tree.declarations[0].var_token, SyntaxKind.VarKeyword)
self.assertNode(self.syntax_tree.declarations[0].variables, [SyntaxKind.IdentifierToken])
self.assertNode(self.syntax_tree.declarations[0].export_token, SyntaxKind.Empty)
self.assertNode(self.syntax_tree.declarations[0].semicolon_token, SyntaxKind.Empty)
def test_one_declaration_two_variables(self):
self.parse_source("Перем А, Б")
self.assertNode(self.syntax_tree.declarations, [SyntaxKind.VariableDeclaration])
self.assertNode(self.syntax_tree.declarations[0].var_token, SyntaxKind.VarKeyword)
self.assertNode(self.syntax_tree.declarations[0].variables, [SyntaxKind.IdentifierToken,
SyntaxKind.CommaToken,
SyntaxKind.IdentifierToken])
self.assertNode(self.syntax_tree.declarations[0].export_token, SyntaxKind.Empty)
self.assertNode(self.syntax_tree.declarations[0].semicolon_token, SyntaxKind.Empty)
def test_one_declaration_one_variable_with_semicolon(self):
self.parse_source("Перем А;")
self.assertNode(self.syntax_tree.declarations, [SyntaxKind.VariableDeclaration])
self.assertNode(self.syntax_tree.declarations[0].var_token, SyntaxKind.VarKeyword)
self.assertNode(self.syntax_tree.declarations[0].variables, [SyntaxKind.IdentifierToken])
self.assertNode(self.syntax_tree.declarations[0].export_token, SyntaxKind.Empty)
self.assertNode(self.syntax_tree.declarations[0].semicolon_token, SyntaxKind.SemicolonToken)
def test_one_declaration_one_variable_with_export(self):
self.parse_source("Перем А Экспорт")
self.assertNode(self.syntax_tree.declarations, [SyntaxKind.VariableDeclaration])
self.assertNode(self.syntax_tree.declarations[0].var_token, SyntaxKind.VarKeyword)
self.assertNode(self.syntax_tree.declarations[0].variables, [SyntaxKind.IdentifierToken])
self.assertNode(self.syntax_tree.declarations[0].export_token, SyntaxKind.ExportKeyword)
self.assertNode(self.syntax_tree.declarations[0].semicolon_token, SyntaxKind.Empty)
def test_one_declaration_one_variable_with_export_and_semicolon(self):
self.parse_source("Перем А Экспорт;")
self.assertNode(self.syntax_tree.declarations, [SyntaxKind.VariableDeclaration])
self.assertNode(self.syntax_tree.declarations[0].var_token, SyntaxKind.VarKeyword)
self.assertNode(self.syntax_tree.declarations[0].variables, [SyntaxKind.IdentifierToken])
self.assertNode(self.syntax_tree.declarations[0].export_token, SyntaxKind.ExportKeyword)
self.assertNode(self.syntax_tree.declarations[0].semicolon_token, SyntaxKind.SemicolonToken)
def test_two_declarations_one_variable(self):
code = \
"""Перем А Экспорт;
Перем Б"""
self.parse_source(code)
self.assertNode(self.syntax_tree.declarations, [SyntaxKind.VariableDeclaration, SyntaxKind.VariableDeclaration])
self.assertNode(self.syntax_tree.declarations[0].var_token, SyntaxKind.VarKeyword)
self.assertNode(self.syntax_tree.declarations[0].variables, [SyntaxKind.IdentifierToken])
self.assertNode(self.syntax_tree.declarations[0].export_token, SyntaxKind.ExportKeyword)
self.assertNode(self.syntax_tree.declarations[0].semicolon_token, SyntaxKind.SemicolonToken)
self.assertNode(self.syntax_tree.declarations[1].var_token, SyntaxKind.VarKeyword)
self.assertNode(self.syntax_tree.declarations[1].variables, [SyntaxKind.IdentifierToken])
self.assertNode(self.syntax_tree.declarations[1].export_token, SyntaxKind.Empty)
self.assertNode(self.syntax_tree.declarations[1].semicolon_token, SyntaxKind.Empty)
| 66.650794
| 120
| 0.748988
| 457
| 4,199
| 6.676149
| 0.09628
| 0.156014
| 0.20059
| 0.267453
| 0.915765
| 0.915765
| 0.897083
| 0.876762
| 0.840708
| 0.816454
| 0
| 0.007861
| 0.151703
| 4,199
| 62
| 121
| 67.725806
| 0.848681
| 0
| 0
| 0.538462
| 0
| 0
| 0.013471
| 0
| 0
| 0
| 0
| 0
| 0.653846
| 1
| 0.115385
| false
| 0
| 0.038462
| 0
| 0.173077
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
fad99017e0c17f991cb42ebcc68bde7c68627bac
| 148
|
py
|
Python
|
isopy/tb.py
|
mattias-ek/isopy
|
96d5530034655c7f9559568ab9b0879b978ef566
|
[
"MIT"
] | null | null | null |
isopy/tb.py
|
mattias-ek/isopy
|
96d5530034655c7f9559568ab9b0879b978ef566
|
[
"MIT"
] | 1
|
2021-08-23T08:48:04.000Z
|
2021-08-23T08:48:04.000Z
|
isopy/tb.py
|
mattias-ek/isopy
|
96d5530034655c7f9559568ab9b0879b978ef566
|
[
"MIT"
] | null | null | null |
from isopy.toolbox.isotope import *
from isopy.toolbox.regress import *
from isopy.toolbox.plotting import *
from isopy.toolbox.doublespike import *
| 37
| 39
| 0.817568
| 20
| 148
| 6.05
| 0.4
| 0.297521
| 0.528926
| 0.545455
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.101351
| 148
| 4
| 39
| 37
| 0.909774
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
fadea4a4be3e185a14c6a66c6f9f07b96fa88eae
| 19,383
|
py
|
Python
|
sdk/python/pulumi_azure/storage/container.py
|
henriktao/pulumi-azure
|
f1cbcf100b42b916da36d8fe28be3a159abaf022
|
[
"ECL-2.0",
"Apache-2.0"
] | 109
|
2018-06-18T00:19:44.000Z
|
2022-02-20T05:32:57.000Z
|
sdk/python/pulumi_azure/storage/container.py
|
henriktao/pulumi-azure
|
f1cbcf100b42b916da36d8fe28be3a159abaf022
|
[
"ECL-2.0",
"Apache-2.0"
] | 663
|
2018-06-18T21:08:46.000Z
|
2022-03-31T20:10:11.000Z
|
sdk/python/pulumi_azure/storage/container.py
|
henriktao/pulumi-azure
|
f1cbcf100b42b916da36d8fe28be3a159abaf022
|
[
"ECL-2.0",
"Apache-2.0"
] | 41
|
2018-07-19T22:37:38.000Z
|
2022-03-14T10:56:26.000Z
|
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
__all__ = ['ContainerArgs', 'Container']
@pulumi.input_type
class ContainerArgs:
def __init__(__self__, *,
storage_account_name: pulumi.Input[str],
container_access_type: Optional[pulumi.Input[str]] = None,
metadata: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a Container resource.
:param pulumi.Input[str] storage_account_name: The name of the Storage Account where the Container should be created.
:param pulumi.Input[str] container_access_type: The Access Level configured for this Container. Possible values are `blob`, `container` or `private`. Defaults to `private`.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] metadata: A mapping of MetaData for this Container. All metadata keys should be lowercase.
:param pulumi.Input[str] name: The name of the Container which should be created within the Storage Account.
"""
pulumi.set(__self__, "storage_account_name", storage_account_name)
if container_access_type is not None:
pulumi.set(__self__, "container_access_type", container_access_type)
if metadata is not None:
pulumi.set(__self__, "metadata", metadata)
if name is not None:
pulumi.set(__self__, "name", name)
@property
@pulumi.getter(name="storageAccountName")
def storage_account_name(self) -> pulumi.Input[str]:
"""
The name of the Storage Account where the Container should be created.
"""
return pulumi.get(self, "storage_account_name")
@storage_account_name.setter
def storage_account_name(self, value: pulumi.Input[str]):
pulumi.set(self, "storage_account_name", value)
@property
@pulumi.getter(name="containerAccessType")
def container_access_type(self) -> Optional[pulumi.Input[str]]:
"""
The Access Level configured for this Container. Possible values are `blob`, `container` or `private`. Defaults to `private`.
"""
return pulumi.get(self, "container_access_type")
@container_access_type.setter
def container_access_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "container_access_type", value)
@property
@pulumi.getter
def metadata(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]:
"""
A mapping of MetaData for this Container. All metadata keys should be lowercase.
"""
return pulumi.get(self, "metadata")
@metadata.setter
def metadata(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]):
pulumi.set(self, "metadata", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the Container which should be created within the Storage Account.
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@pulumi.input_type
class _ContainerState:
def __init__(__self__, *,
container_access_type: Optional[pulumi.Input[str]] = None,
has_immutability_policy: Optional[pulumi.Input[bool]] = None,
has_legal_hold: Optional[pulumi.Input[bool]] = None,
metadata: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None,
resource_manager_id: Optional[pulumi.Input[str]] = None,
storage_account_name: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering Container resources.
:param pulumi.Input[str] container_access_type: The Access Level configured for this Container. Possible values are `blob`, `container` or `private`. Defaults to `private`.
:param pulumi.Input[bool] has_immutability_policy: Is there an Immutability Policy configured on this Storage Container?
:param pulumi.Input[bool] has_legal_hold: Is there a Legal Hold configured on this Storage Container?
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] metadata: A mapping of MetaData for this Container. All metadata keys should be lowercase.
:param pulumi.Input[str] name: The name of the Container which should be created within the Storage Account.
:param pulumi.Input[str] resource_manager_id: The Resource Manager ID of this Storage Container.
:param pulumi.Input[str] storage_account_name: The name of the Storage Account where the Container should be created.
"""
if container_access_type is not None:
pulumi.set(__self__, "container_access_type", container_access_type)
if has_immutability_policy is not None:
pulumi.set(__self__, "has_immutability_policy", has_immutability_policy)
if has_legal_hold is not None:
pulumi.set(__self__, "has_legal_hold", has_legal_hold)
if metadata is not None:
pulumi.set(__self__, "metadata", metadata)
if name is not None:
pulumi.set(__self__, "name", name)
if resource_manager_id is not None:
pulumi.set(__self__, "resource_manager_id", resource_manager_id)
if storage_account_name is not None:
pulumi.set(__self__, "storage_account_name", storage_account_name)
@property
@pulumi.getter(name="containerAccessType")
def container_access_type(self) -> Optional[pulumi.Input[str]]:
"""
The Access Level configured for this Container. Possible values are `blob`, `container` or `private`. Defaults to `private`.
"""
return pulumi.get(self, "container_access_type")
@container_access_type.setter
def container_access_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "container_access_type", value)
@property
@pulumi.getter(name="hasImmutabilityPolicy")
def has_immutability_policy(self) -> Optional[pulumi.Input[bool]]:
"""
Is there an Immutability Policy configured on this Storage Container?
"""
return pulumi.get(self, "has_immutability_policy")
@has_immutability_policy.setter
def has_immutability_policy(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "has_immutability_policy", value)
@property
@pulumi.getter(name="hasLegalHold")
def has_legal_hold(self) -> Optional[pulumi.Input[bool]]:
"""
Is there a Legal Hold configured on this Storage Container?
"""
return pulumi.get(self, "has_legal_hold")
@has_legal_hold.setter
def has_legal_hold(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "has_legal_hold", value)
@property
@pulumi.getter
def metadata(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]:
"""
A mapping of MetaData for this Container. All metadata keys should be lowercase.
"""
return pulumi.get(self, "metadata")
@metadata.setter
def metadata(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]):
pulumi.set(self, "metadata", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the Container which should be created within the Storage Account.
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter(name="resourceManagerId")
def resource_manager_id(self) -> Optional[pulumi.Input[str]]:
"""
The Resource Manager ID of this Storage Container.
"""
return pulumi.get(self, "resource_manager_id")
@resource_manager_id.setter
def resource_manager_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "resource_manager_id", value)
@property
@pulumi.getter(name="storageAccountName")
def storage_account_name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the Storage Account where the Container should be created.
"""
return pulumi.get(self, "storage_account_name")
@storage_account_name.setter
def storage_account_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "storage_account_name", value)
class Container(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
container_access_type: Optional[pulumi.Input[str]] = None,
metadata: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None,
storage_account_name: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
Manages a Container within an Azure Storage Account.
## Example Usage
```python
import pulumi
import pulumi_azure as azure
example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe")
example_account = azure.storage.Account("exampleAccount",
resource_group_name=example_resource_group.name,
location=example_resource_group.location,
account_tier="Standard",
account_replication_type="LRS",
tags={
"environment": "staging",
})
example_container = azure.storage.Container("exampleContainer",
storage_account_name=example_account.name,
container_access_type="private")
```
## Import
Storage Containers can be imported using the `resource id`, e.g.
```sh
$ pulumi import azure:storage/container:Container container1 https://example.blob.core.windows.net/container
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] container_access_type: The Access Level configured for this Container. Possible values are `blob`, `container` or `private`. Defaults to `private`.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] metadata: A mapping of MetaData for this Container. All metadata keys should be lowercase.
:param pulumi.Input[str] name: The name of the Container which should be created within the Storage Account.
:param pulumi.Input[str] storage_account_name: The name of the Storage Account where the Container should be created.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: ContainerArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
Manages a Container within an Azure Storage Account.
## Example Usage
```python
import pulumi
import pulumi_azure as azure
example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe")
example_account = azure.storage.Account("exampleAccount",
resource_group_name=example_resource_group.name,
location=example_resource_group.location,
account_tier="Standard",
account_replication_type="LRS",
tags={
"environment": "staging",
})
example_container = azure.storage.Container("exampleContainer",
storage_account_name=example_account.name,
container_access_type="private")
```
## Import
Storage Containers can be imported using the `resource id`, e.g.
```sh
$ pulumi import azure:storage/container:Container container1 https://example.blob.core.windows.net/container
```
:param str resource_name: The name of the resource.
:param ContainerArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(ContainerArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
container_access_type: Optional[pulumi.Input[str]] = None,
metadata: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None,
storage_account_name: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = ContainerArgs.__new__(ContainerArgs)
__props__.__dict__["container_access_type"] = container_access_type
__props__.__dict__["metadata"] = metadata
__props__.__dict__["name"] = name
if storage_account_name is None and not opts.urn:
raise TypeError("Missing required property 'storage_account_name'")
__props__.__dict__["storage_account_name"] = storage_account_name
__props__.__dict__["has_immutability_policy"] = None
__props__.__dict__["has_legal_hold"] = None
__props__.__dict__["resource_manager_id"] = None
super(Container, __self__).__init__(
'azure:storage/container:Container',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
container_access_type: Optional[pulumi.Input[str]] = None,
has_immutability_policy: Optional[pulumi.Input[bool]] = None,
has_legal_hold: Optional[pulumi.Input[bool]] = None,
metadata: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None,
resource_manager_id: Optional[pulumi.Input[str]] = None,
storage_account_name: Optional[pulumi.Input[str]] = None) -> 'Container':
"""
Get an existing Container resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] container_access_type: The Access Level configured for this Container. Possible values are `blob`, `container` or `private`. Defaults to `private`.
:param pulumi.Input[bool] has_immutability_policy: Is there an Immutability Policy configured on this Storage Container?
:param pulumi.Input[bool] has_legal_hold: Is there a Legal Hold configured on this Storage Container?
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] metadata: A mapping of MetaData for this Container. All metadata keys should be lowercase.
:param pulumi.Input[str] name: The name of the Container which should be created within the Storage Account.
:param pulumi.Input[str] resource_manager_id: The Resource Manager ID of this Storage Container.
:param pulumi.Input[str] storage_account_name: The name of the Storage Account where the Container should be created.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _ContainerState.__new__(_ContainerState)
__props__.__dict__["container_access_type"] = container_access_type
__props__.__dict__["has_immutability_policy"] = has_immutability_policy
__props__.__dict__["has_legal_hold"] = has_legal_hold
__props__.__dict__["metadata"] = metadata
__props__.__dict__["name"] = name
__props__.__dict__["resource_manager_id"] = resource_manager_id
__props__.__dict__["storage_account_name"] = storage_account_name
return Container(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter(name="containerAccessType")
def container_access_type(self) -> pulumi.Output[Optional[str]]:
"""
The Access Level configured for this Container. Possible values are `blob`, `container` or `private`. Defaults to `private`.
"""
return pulumi.get(self, "container_access_type")
@property
@pulumi.getter(name="hasImmutabilityPolicy")
def has_immutability_policy(self) -> pulumi.Output[bool]:
"""
Is there an Immutability Policy configured on this Storage Container?
"""
return pulumi.get(self, "has_immutability_policy")
@property
@pulumi.getter(name="hasLegalHold")
def has_legal_hold(self) -> pulumi.Output[bool]:
"""
Is there a Legal Hold configured on this Storage Container?
"""
return pulumi.get(self, "has_legal_hold")
@property
@pulumi.getter
def metadata(self) -> pulumi.Output[Mapping[str, str]]:
"""
A mapping of MetaData for this Container. All metadata keys should be lowercase.
"""
return pulumi.get(self, "metadata")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
The name of the Container which should be created within the Storage Account.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="resourceManagerId")
def resource_manager_id(self) -> pulumi.Output[str]:
"""
The Resource Manager ID of this Storage Container.
"""
return pulumi.get(self, "resource_manager_id")
@property
@pulumi.getter(name="storageAccountName")
def storage_account_name(self) -> pulumi.Output[str]:
"""
The name of the Storage Account where the Container should be created.
"""
return pulumi.get(self, "storage_account_name")
| 45.076744
| 180
| 0.663778
| 2,261
| 19,383
| 5.439628
| 0.083149
| 0.077811
| 0.068298
| 0.050085
| 0.860151
| 0.829336
| 0.806814
| 0.780145
| 0.762582
| 0.748923
| 0
| 0.000203
| 0.239127
| 19,383
| 429
| 181
| 45.181818
| 0.83374
| 0.356188
| 0
| 0.64
| 1
| 0
| 0.113961
| 0.03737
| 0
| 0
| 0
| 0
| 0
| 1
| 0.16
| false
| 0.004444
| 0.022222
| 0
| 0.28
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
faf344ebe6fc3eeddab236b322b89b50a21d1522
| 124
|
py
|
Python
|
minecraft/networking/types/__init__.py
|
Skelmis/PyMcBot
|
b74b4f344bbcc711974f2551f75da3ddb8874e6f
|
[
"Apache-2.0"
] | 2
|
2020-02-09T08:55:33.000Z
|
2021-03-31T20:53:11.000Z
|
minecraft/networking/types/__init__.py
|
Skelmis/PyMcBot
|
b74b4f344bbcc711974f2551f75da3ddb8874e6f
|
[
"Apache-2.0"
] | 2
|
2020-08-20T14:32:49.000Z
|
2021-02-07T03:28:45.000Z
|
minecraft/networking/types/__init__.py
|
Skelmis/PyMcBot
|
b74b4f344bbcc711974f2551f75da3ddb8874e6f
|
[
"Apache-2.0"
] | 3
|
2020-10-27T14:27:38.000Z
|
2020-12-08T15:11:54.000Z
|
from .basic import * # noqa: F401, F403
from .enum import * # noqa: F401, F403
from .utility import * # noqa: F401, F403
| 31
| 42
| 0.66129
| 18
| 124
| 4.555556
| 0.444444
| 0.365854
| 0.512195
| 0.658537
| 0.536585
| 0
| 0
| 0
| 0
| 0
| 0
| 0.185567
| 0.217742
| 124
| 3
| 43
| 41.333333
| 0.659794
| 0.403226
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
faffd8541eeb0a32bdad3ab61427626de0864c04
| 3,643
|
py
|
Python
|
3.3.1/se34euca/se34euca/testcase/testcase_instance.py
|
eucalyptus/se34euca
|
af5da36754fccca84b7f260ba7605b8fdc30fa55
|
[
"BSD-2-Clause"
] | 8
|
2015-01-08T21:06:08.000Z
|
2019-10-26T13:17:16.000Z
|
3.3.1/se34euca/se34euca/testcase/testcase_instance.py
|
eucalyptus/se34euca
|
af5da36754fccca84b7f260ba7605b8fdc30fa55
|
[
"BSD-2-Clause"
] | null | null | null |
3.3.1/se34euca/se34euca/testcase/testcase_instance.py
|
eucalyptus/se34euca
|
af5da36754fccca84b7f260ba7605b8fdc30fa55
|
[
"BSD-2-Clause"
] | 7
|
2016-08-31T07:02:21.000Z
|
2020-07-18T00:10:36.000Z
|
from se34euca.testcase.testcase_base import *
class testcase_instance(testcase_base):
def launch_instance_basic(self):
print "=== runTest: Launch Instance Basic ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_launch_instance_basic()
self.eucaUITester.base.test_ui_logout()
def terminate_instance_basic(self):
print "=== runTest: Terminate Instance Basic ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_terminate_instance_basic()
self.eucaUITester.base.test_ui_logout()
def terminate_instance_all(self):
print "=== runTest: Terminate Instance All ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_terminate_instance_all()
self.eucaUITester.base.test_ui_logout()
def launch_instance_from_images_lp(self):
print "=== runTest: Launch Instance from Images Landing Page ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_launch_instance_from_images_lp()
self.eucaUITester.base.test_ui_logout()
def launch_instance_from_instances_lp(self):
print "=== runTest: Launch Instance from Instances Landing Page ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_launch_instance_from_instances_lp()
self.eucaUITester.base.test_ui_logout()
def launch_more_like_this(self):
print "=== runTest: Launch More Instances Like This ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_launch_more_like_this()
self.eucaUITester.base.test_ui_logout()
def launch_instance_name_testinstance(self):
print "=== runTest: Launch Instance Named testinstance ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_launch_instance_given_instance_name("testinstance")
self.eucaUITester.base.test_ui_logout()
def launch_and_terminate_instance(self):
print "=== runTest: Launch and Terminate Instance ==="
pause=5 #length of pause in seconds
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_launch_instance_basic()
time.sleep(pause)
self.eucaUITester.instance.test_ui_terminate_instance_basic()
self.eucaUITester.base.test_ui_logout()
time.sleep(pause)
def associate_ip_from_inst_lp(self):
print "=== runTest: Associate IP from Instances Landing Page ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_associate_ip_from_inst_lp()
self.eucaUITester.base.test_ui_logout()
def disassociate_ip_from_inst_lp(self):
print "=== runTest: Disassociate IP from Instances Landing Page ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_disassociate_ip_from_inst_lp()
self.eucaUITester.base.test_ui_logout()
def associate_ip_from_ip_lp(self):
print "=== runTest: Associate IP from IP Landing Page ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_associate_ip_from_ip_lp()
self.eucaUITester.base.test_ui_logout()
def disassociate_ip_from_ip_lp(self):
print "=== runTest: Associate IP from IP Landing Page ==="
self.eucaUITester.base.test_ui_login()
self.eucaUITester.instance.test_ui_disassociate_ip_from_ip_lp()
self.eucaUITester.base.test_ui_logout()
if __name__ == "__main__":
unittest.main()
| 40.477778
| 94
| 0.717815
| 450
| 3,643
| 5.444444
| 0.106667
| 0.241633
| 0.195918
| 0.235102
| 0.872245
| 0.824898
| 0.79551
| 0.737143
| 0.704898
| 0.666531
| 0
| 0.001011
| 0.185287
| 3,643
| 89
| 95
| 40.932584
| 0.824461
| 0.007137
| 0
| 0.470588
| 0
| 0
| 0.170772
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.014706
| null | null | 0.176471
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
87baf84248d99368169df0f25ec2eeabe7e9a264
| 3,599
|
py
|
Python
|
api/metrics/escooter_metric.py
|
scarletstudio/transithealth
|
408e6c1a063e46edb95040c26db93c2ff93c6d33
|
[
"MIT"
] | 2
|
2021-05-18T15:34:19.000Z
|
2021-10-07T01:29:31.000Z
|
api/metrics/escooter_metric.py
|
scarletstudio/transithealth
|
408e6c1a063e46edb95040c26db93c2ff93c6d33
|
[
"MIT"
] | 89
|
2021-05-21T18:31:04.000Z
|
2021-08-16T01:13:02.000Z
|
api/metrics/escooter_metric.py
|
scarletstudio/transithealth
|
408e6c1a063e46edb95040c26db93c2ff93c6d33
|
[
"MIT"
] | 1
|
2021-06-15T10:28:26.000Z
|
2021-06-15T10:28:26.000Z
|
from api.utils.database import rows_to_dicts
class EscooterMetric:
"""
Metrics for escooter travel metric
"""
def __init__(self, con):
self.con = con
def avg_distance_x_to_y(self):
"""
Returns the average distance riders take throughout
the city
"""
query = """
SELECT
start_community_area_number, end_community_area_number, avg_trip_distance
From
Escooter
""".format()
cur = self.con.cursor()
cur.execute(query)
rows = rows_to_dicts(cur, cur.fetchall())
return rows
def avg_distance_based_on_start_can(self):
"""
Returns the avg distance traveled based on starting community area numbers
"""
query = """
SELECT
start_community_area_number AS area_number, avg(avg_trip_distance_miles) AS value
From
Escooter
Group by
start_community_area_number
""".format()
cur = self.con.cursor()
cur.execute(query)
rows = rows_to_dicts(cur, cur.fetchall())
return rows
def avg_distance_based_on_end_can(self):
"""
Returns the avg distance traveled based on end community area numbers
"""
query = """
SELECT
end_community_area_number AS area_number, avg(avg_trip_distance_miles) AS value
From
Escooter
Group by
end_community_area_number
""".format()
cur = self.con.cursor()
cur.execute(query)
rows = rows_to_dicts(cur, cur.fetchall())
return rows
def number_of_trips_x_to_y (self):
"""
Returns the number of trips logged from one specific area
to another
"""
query = """
SELECT
start_community_area_number, end_community_area_number, count_trip_id
From
Escooter
""".format()
cur = self.con.cursor()
cur.execute(query)
rows = rows_to_dicts(cur, cur.fetchall())
return rows
def number_of_trips_based_on_start_cn (self):
"""
Returns the number of trips from all communities that had at least
one ride start there
"""
query = """
SELECT
start_community_area_number AS area_number, sum(count_trip_id) AS value
From
Escooter
Group by
start_community_area_number
""".format()
cur = self.con.cursor()
cur.execute(query)
rows = rows_to_dicts(cur, cur.fetchall())
return rows
def number_of_trips_based_on_end_cn (self):
"""
Returns the number of trips from all communities that had
at least one ride end there
"""
query = """
SELECT
end_community_area_number AS area_number, sum(count_trip_id) AS value
From
Escooter
Group by
end_community_area_number
""".format()
cur = self.con.cursor()
cur.execute(query)
rows = rows_to_dicts(cur, cur.fetchall())
return rows
def total_escooter_rides(self):
"""
Returns the number of trips taken by escooters in 2019
"""
query = """
SELECT
sum(count_trip_id) AS value
From
Escooter
""".format()
cur = self.con.cursor()
cur.execute(query)
rows = rows_to_dicts(cur, cur.fetchall())
return rows
| 28.338583
| 93
| 0.564879
| 414
| 3,599
| 4.647343
| 0.190821
| 0.08316
| 0.118503
| 0.058212
| 0.83264
| 0.81185
| 0.772349
| 0.772349
| 0.761435
| 0.685551
| 0
| 0.001736
| 0.359822
| 3,599
| 127
| 94
| 28.338583
| 0.833333
| 0.149486
| 0
| 0.797753
| 0
| 0
| 0.419558
| 0.130389
| 0
| 0
| 0
| 0
| 0
| 1
| 0.089888
| false
| 0
| 0.011236
| 0
| 0.191011
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
355c8d1ff873466166392d3d8c058a295098bd6f
| 28
|
py
|
Python
|
examples/NIPS/MNIST/noisy_sequence_detection/old_scenarios/scenario001/__init__.py
|
dais-ita/DeepProbCEP
|
22790c1672c1cce49a59d18921c710f61cdde2f2
|
[
"MIT"
] | 6
|
2020-09-10T03:40:53.000Z
|
2021-05-26T07:30:20.000Z
|
examples/NIPS/MNIST/noisy_sequence_detection/old_scenarios/scenario001/__init__.py
|
dais-ita/DeepProbCEP
|
22790c1672c1cce49a59d18921c710f61cdde2f2
|
[
"MIT"
] | null | null | null |
examples/NIPS/MNIST/noisy_sequence_detection/old_scenarios/scenario001/__init__.py
|
dais-ita/DeepProbCEP
|
22790c1672c1cce49a59d18921c710f61cdde2f2
|
[
"MIT"
] | 1
|
2020-11-23T15:55:57.000Z
|
2020-11-23T15:55:57.000Z
|
from .generate_data import *
| 28
| 28
| 0.821429
| 4
| 28
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107143
| 28
| 1
| 28
| 28
| 0.88
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
355e7c69921bf9d89759c9fe52e57fe844bd2a3b
| 24,465
|
py
|
Python
|
src/models.py
|
rinchieeeee/cnn-pipline-for-data-competition
|
d01ba3dcba292b06c23d2e8c7a68a4c15d005ea7
|
[
"MIT"
] | null | null | null |
src/models.py
|
rinchieeeee/cnn-pipline-for-data-competition
|
d01ba3dcba292b06c23d2e8c7a68a4c15d005ea7
|
[
"MIT"
] | null | null | null |
src/models.py
|
rinchieeeee/cnn-pipline-for-data-competition
|
d01ba3dcba292b06c23d2e8c7a68a4c15d005ea7
|
[
"MIT"
] | null | null | null |
import torch
import torch.nn as nn
import torch.nn.functional as F
import timm
import yaml
from arcface import ArcFaceLayer
def adaptive_concat_avgmax_pool2d(x, output_size = 1):
x_avg = F.adaptive_avg_pool2d(x, output_size)
x_max = F.adaptive_max_pool2d(x, output_size)
return torch.cat((x_avg, x_max), dim = 1)
class AdaptiveCatAvgMaxPool2d(nn.Module):
def __init__(self, output_size = 1):
super(AdaptiveCatAvgMaxPool2d, self).__init__()
self.output_size = output_size
def forward(self, x):
return adaptive_concat_avgmax_pool2d(x, self.output_size)
class SelectAdaptivePool2d(nn.Module):
"""
Selectable global pooling layer with dynamic input kernel size
"""
def __init__(self, output_size = 1, pool_type = 'avg', flatten = True):
super(SelectAdaptivePool2d, self).__init__()
self.pool_type = pool_type or '' # convert other falsy values to empty string for consistent TS typing
self.flatten = nn.Flatten(1) if flatten else nn.Identity()
if pool_type == '':
self.pool = nn.Identity() # pass through
elif pool_type == 'avg':
self.pool = nn.AdaptiveAvgPool2d(output_size)
elif pool_type == 'concat_avg_max':
self.pool = AdaptiveCatAvgMaxPool2d(output_size)
elif pool_type == 'max':
self.pool = nn.AdaptiveMaxPool2d(output_size)
else:
assert False, 'Invalid pool type: %s' % pool_type
def is_identity(self):
return not self.pool_type
def forward(self, x):
x = self.pool(x)
x = self.flatten(x)
return x
def feat_mult(self):
return adaptive_pool_feat_mult(self.pool_type)
class CustomNFNet(nn.Module):
def __init__(self, model_name, class_num, in_channels, pretrained = False):
super().__init__()
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.head.fc.in_features
self.model.head.fc = nn.Linear(n_features, class_num)
def forward(self, x):
x = self.model(x)
return x
class CustomRexNet_Base(nn.Module):
def __init__(self, model_name, class_num, in_channels,
dropout_rate = 0.0, global_pool_type = "avg", pretrained = False):
super().__init__()
self.dropout_rate = dropout_rate
self.global_pool_type = global_pool_type
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.head.fc.in_features # get the number of unit size in last fully conection layer
#self.model.fc = nn.Linear(n_features, class_num)
if self.global_pool_type == "concat_avg_max":
n_features = n_features * 2
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
else:
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
self.classifier = nn.Linear(n_features, class_num, bias = True)
def forward(self, x):
x = self.model.forward_features(x)
x = self.global_pool(x)
if self.dropout_rate > 0.0:
x = F.dropout(x, p = self.dropout_rate)
return self.classifier(x)
class CustomDensNet_Base(nn.Module):
def __init__(self, model_name, class_num, in_channels, pretrained = False):
super().__init__()
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.classifier.in_features
self.model.classifier = nn.Linear(n_features, class_num)
def forward(self, x):
x = self.model(x)
return x
class CustomResNet_Base(nn.Module):
def __init__(self, model_name, class_num, in_channels,
dropout_rate = 0.0, global_pool_type = "avg", pretrained = False):
super().__init__()
self.dropout_rate = dropout_rate
self.global_pool_type = global_pool_type
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.fc.in_features # get the number of unit size in last fully conection layer
self.model.fc = nn.Linear(n_features, class_num)
if self.global_pool_type == "concat_avg_max":
n_features = n_features * 2
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
else:
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
self.classifier = nn.Linear(n_features, class_num, bias = True)
def forward(self, x):
x = self.model.forward_features(x)
x = self.global_pool(x)
if self.dropout_rate > 0.0:
x = F.dropout(x, p = self.dropout_rate)
return self.classifier(x)
class CustomECAResNet_Base(nn.Module):
def __init__(self, model_name, class_num, in_channels,
dropout_rate = 0.0, global_pool_type = "avg", pretrained = False):
super().__init__()
self.dropout_rate = dropout_rate
self.global_pool_type = global_pool_type
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.fc.in_features # get the number of unit size in last fully conection layer
#self.model.fc = nn.Linear(n_features, class_num)
if self.global_pool_type == "concat_avg_max":
n_features = n_features * 2
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
else:
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
self.classifier = nn.Linear(n_features, class_num, bias = True)
def forward(self, x):
x = self.model.forward_features(x)
x = self.global_pool(x)
if self.dropout_rate > 0.0:
x = F.dropout(x, p = self.dropout_rate)
return self.classifier(x)
class ResNetArcFace_Base(nn.Module):
def __init__(self, model_name, class_num, in_channels,
dropout_rate = 0.0, global_pool_type = "avg", pretrained = False):
super().__init__()
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.fc.in_features # get the number of unit size in last fully conection layer
self.global_pool_type = global_pool_type
self.dropout_rate = dropout_rate
if self.global_pool_type == "concat_avg_max":
n_features = n_features * 2
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
else:
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
self.arcface_layer = ArcFaceLayer(in_features = n_features, class_num = class_num)
def forward(self, x):
x = self.model.forward_features(x)
x = self.global_pool(x)
if self.dropout_rate > 0.0:
x = F.dropout(x, p = self.dropout_rate)
return self.arcface_layer(x)
class CustomTResNet_Base(nn.Module):
def __init__(self, model_name, class_num, in_channels, pretrained = False,
dropout_rate = 0.0, global_pool_type = "avg"):
super().__init__()
self.dropout_rate = dropout_rate
self.global_pool_type = global_pool_type
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.num_features # get the number of unit size in last fully conection layer
if self.global_pool_type == "concat_avg_max":
n_features = n_features * 2
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
else:
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
self.classifier = nn.Linear(n_features, class_num, bias = True)
def forward(self, x):
x = self.model.forward_features(x) # encoder部分
x = self.global_pool(x)
if self.dropout_rate > 0.0:
x = F.dropout(x, p = self.dropout_rate)
return self.classifier(x)
class CustomEfficientNet_base(nn.Module):
def __init__(self, model_name, class_num, in_channels, pretrained = False,
dropout_rate = 0.0, global_pool_type = "avg"):
super().__init__()
self.dropout_rate = dropout_rate
self.global_pool_type = global_pool_type
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.classifier.in_features # get the number of unit size in last fully conection layer
if self.global_pool_type == "concat_avg_max":
n_features = n_features * 2
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
else:
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
self.classifier = nn.Linear(n_features, class_num, bias = True)
def forward(self, x):
x = self.model.forward_features(x) # encoder部分
x = self.global_pool(x)
if self.dropout_rate > 0.0:
x = F.dropout(x, p = self.dropout_rate)
return self.classifier(x)
class EfficientNetWithArcface_base(nn.Module):
def __init__(self, model_name, class_num, in_channels, pretrained = False,
dropout_rate = 0.0, global_pool_type = "avg"):
super().__init__()
self.dropout_rate = dropout_rate
self.global_pool_type = global_pool_type
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.classifier.in_features # get the number of unit size in last fully conection layer
if self.global_pool_type == "concat_avg_max":
n_features = n_features * 2
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
else:
self.global_pool = SelectAdaptivePool2d(pool_type = self.global_pool_type)
self.arcface_layer = ArcFaceLayer(in_features = n_features, class_num = class_num)
def forward(self, x):
x = self.model.forward_features(x) # encoder部分
x = self.global_pool(x)
if self.dropout_rate > 0.0:
x = F.dropout(x, p = self.dropout_rate)
return self.arcface_layer(x)
class CustomEfficientNetV2_m(nn.Module):
def __init__(self, model_name, class_num, in_channels, pretrained = False):
super().__init__()
self.model = timm.create_model(model_name, in_chans = in_channels, pretrained = pretrained)
n_features = self.model.classifier.in_features # get the number of unit size in last fully conection layer
self.model.classifier = nn.Linear(n_features, class_num)
def forward(self, x):
x = self.model(x)
return x
def get_model(config):
"""
config : original config loading yaml file
"""
config_model = config["model"]
if config_model["name"] == "resnet50":
model = CustomResNet50(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
if config_model["name"] == "resnet34d":
model = CustomResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["pretrained"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "ecaresnet50d":
model = CustomECAResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["pretrained"],
global_pool_type = config_model["global_pool_type"]
)
if config_model["name"] == "resnet50d":
model = CustomResNet50(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "resnetrs50":
model = CustomResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "resnetrs101":
model = CustomResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "resnetrs152":
model = CustomResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "resnet18":
model = CustomResNet18(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "seresnet101":
model = CustomResNet18(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "arcface_resnet":
model = ResNetArcFace_Base(model_name = config_model["name"][8:],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["pretrained"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "resnest":
model = CustomResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "efficientnet_b4":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "efficientnet_b3":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "efficientnet_b5":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "efficientnet_b6":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "efficientnet_b7":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "tf_efficientnet_b3_ns":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "efficientnet_b1":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "efficientnet_b2":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "tf_efficientnet_b2_ns":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif "arcface_efficientnet" in config_model["name"]:
model = EfficientNetWithArcface_base(model_name = config_model["name"][8:],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "efficientnet_b0":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"]
)
elif config_model["name"] == "efficientnetv2_m":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "efficientnetv2_s":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "efficientnetv2_rw_s":
model = CustomEfficientNet_base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"]
)
elif config_model["name"] == "nfnet_f0":
model = CustomNFNet(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"])
elif "densenet" in config_model["name"]:
model = CustomDensNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"])
elif config_model["name"] == "tresnet_m_448":
model = CustomTResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"])
elif "resnest50" in config_model["name"]:
model = CustomResNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"])
elif "rexnet" in config_model["name"]:
model = CustomRexNet_Base(model_name = config_model["name"],
class_num = config_model["class_num"],
in_channels = config_model["in_channels"],
pretrained = config_model["pretrained"],
dropout_rate = config_model["dropout_rate"],
global_pool_type = config_model["global_pool_type"])
return model
| 47.412791
| 114
| 0.565379
| 2,558
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| 0.059421
| 0.151536
| 0.073679
| 0.055723
| 0.883059
| 0.86371
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| 0.858602
| 0.856126
| 0.856126
| 0
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| 0.343593
| 24,465
| 516
| 115
| 47.412791
| 0.797372
| 0.03176
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| 0.08683
| 0.001776
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| 0.002433
| 1
| 0.068127
| false
| 0
| 0.014599
| 0.007299
| 0.150852
| 0
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| null | 0
| 0
| 0
| 1
| 1
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|
0
| 7
|
356d9ef823264b88690c6f360d68f2de9b09b4ed
| 13,100
|
py
|
Python
|
saleor/graphql/attribute/tests/queries/test_attribute_filtering_with_channels.py
|
greentornado/saleor
|
7f58917957a23c4dd90b47214a4500c91c735dee
|
[
"CC-BY-4.0"
] | 1
|
2021-07-22T13:25:11.000Z
|
2021-07-22T13:25:11.000Z
|
saleor/graphql/attribute/tests/queries/test_attribute_filtering_with_channels.py
|
greentornado/saleor
|
7f58917957a23c4dd90b47214a4500c91c735dee
|
[
"CC-BY-4.0"
] | 111
|
2021-06-30T08:51:06.000Z
|
2022-03-28T04:48:49.000Z
|
saleor/graphql/attribute/tests/queries/test_attribute_filtering_with_channels.py
|
IslamDEVO/es-saleor-nginx
|
a56a4aaf23fc308aad7b7489bc090fd4fcdb6315
|
[
"CC-BY-4.0"
] | 6
|
2021-11-08T16:43:05.000Z
|
2022-03-22T17:31:16.000Z
|
from decimal import Decimal
import graphene
import pytest
from .....attribute.models import Attribute, AttributeProduct, AttributeVariant
from .....product.models import (
Product,
ProductChannelListing,
ProductType,
ProductVariant,
ProductVariantChannelListing,
)
from ....tests.utils import assert_graphql_error_with_message, get_graphql_content
@pytest.fixture
def attributes_for_filtering_with_channels(
collection, category, channel_USD, channel_PLN, other_channel_USD
):
attributes = Attribute.objects.bulk_create(
[
Attribute(
name="Attr1",
slug="attr1",
value_required=True,
storefront_search_position=4,
),
Attribute(
name="AttrAttr1",
slug="attr_attr1",
value_required=True,
storefront_search_position=3,
),
Attribute(
name="AttrAttr2",
slug="attr_attr2",
value_required=True,
storefront_search_position=2,
),
Attribute(
name="Attr2",
slug="attr2",
value_required=False,
storefront_search_position=5,
),
Attribute(
name="Attr3",
slug="attr3",
value_required=False,
storefront_search_position=1,
),
]
)
product_type = ProductType.objects.create(name="My Product Type")
product = Product.objects.create(
name="Test product",
product_type=product_type,
category=category,
)
ProductChannelListing.objects.bulk_create(
[
ProductChannelListing(
channel=channel_USD,
product=product,
visible_in_listings=True,
currency=channel_USD.currency_code,
is_published=True,
),
ProductChannelListing(
channel=channel_PLN,
product=product,
visible_in_listings=False,
currency=channel_PLN.currency_code,
is_published=True,
),
ProductChannelListing(
channel=other_channel_USD,
product=product,
visible_in_listings=True,
currency=other_channel_USD.currency_code,
is_published=False,
),
]
)
variant = ProductVariant.objects.create(product=product)
ProductVariantChannelListing.objects.create(
variant=variant,
channel=channel_USD,
cost_price_amount=Decimal(1),
price_amount=Decimal(10),
currency=channel_USD.currency_code,
)
ProductVariantChannelListing.objects.create(
variant=variant,
channel=channel_PLN,
cost_price_amount=Decimal(1),
price_amount=Decimal(10),
currency=channel_PLN.currency_code,
)
ProductVariantChannelListing.objects.create(
variant=variant,
channel=other_channel_USD,
cost_price_amount=Decimal(1),
price_amount=Decimal(10),
currency=other_channel_USD.currency_code,
)
collection.products.add(product)
AttributeVariant.objects.bulk_create(
[
AttributeVariant(
product_type=product_type, attribute=attributes[1], sort_order=1
),
AttributeVariant(
product_type=product_type, attribute=attributes[3], sort_order=2
),
AttributeVariant(
product_type=product_type, attribute=attributes[4], sort_order=3
),
]
)
AttributeProduct.objects.bulk_create(
[
AttributeProduct(
product_type=product_type, attribute=attributes[2], sort_order=1
),
AttributeProduct(
product_type=product_type, attribute=attributes[0], sort_order=2
),
AttributeProduct(
product_type=product_type, attribute=attributes[1], sort_order=3
),
]
)
return attributes
QUERY_ATTRIBUTES_FILTERING = """
query (
$filter: AttributeFilterInput, $channel: String
){
attributes (
first: 10, filter: $filter, channel: $channel
) {
edges {
node {
name
}
}
}
}
"""
@pytest.mark.parametrize(
"tested_field",
["inCategory", "inCollection"],
)
def test_attributes_with_filtering_without_channel(
tested_field,
staff_api_client,
permission_manage_products,
category,
collection,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by}
# when
response = staff_api_client.post_graphql(
QUERY_ATTRIBUTES_FILTERING,
variables,
permissions=[permission_manage_products],
check_no_permissions=False,
)
# then
assert_graphql_error_with_message(response, "A default channel does not exist.")
@pytest.mark.parametrize(
"tested_field, attribute_count",
[("inCategory", 5), ("inCollection", 5)],
)
def test_products_with_filtering_with_as_staff_user(
tested_field,
attribute_count,
staff_api_client,
permission_manage_products,
attributes_for_filtering_with_channels,
category,
collection,
channel_USD,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by, "channel": channel_USD.slug}
# when
response = staff_api_client.post_graphql(
QUERY_ATTRIBUTES_FILTERING,
variables,
permissions=[permission_manage_products],
check_no_permissions=False,
)
# then
content = get_graphql_content(response)
attribute_nodes = content["data"]["attributes"]["edges"]
assert len(attribute_nodes) == attribute_count
@pytest.mark.parametrize(
"tested_field, attribute_count",
[("inCategory", 5), ("inCollection", 5)],
)
def test_products_with_filtering_as_anonymous_client(
tested_field,
attribute_count,
api_client,
attributes_for_filtering_with_channels,
category,
collection,
channel_USD,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by, "channel": channel_USD.slug}
# when
response = api_client.post_graphql(QUERY_ATTRIBUTES_FILTERING, variables)
# then
content = get_graphql_content(response)
attribute_nodes = content["data"]["attributes"]["edges"]
assert len(attribute_nodes) == attribute_count
@pytest.mark.parametrize(
"tested_field, attribute_count",
[("inCategory", 5), ("inCollection", 5)],
)
def test_products_with_filtering_with_not_visible_in_listings_as_staff_user(
tested_field,
attribute_count,
staff_api_client,
permission_manage_products,
attributes_for_filtering_with_channels,
category,
collection,
channel_PLN,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by, "channel": channel_PLN.slug}
# when
response = staff_api_client.post_graphql(
QUERY_ATTRIBUTES_FILTERING,
variables,
permissions=[permission_manage_products],
check_no_permissions=False,
)
# then
content = get_graphql_content(response)
attribute_nodes = content["data"]["attributes"]["edges"]
assert len(attribute_nodes) == attribute_count
@pytest.mark.parametrize(
"tested_field, attribute_count",
[
("inCategory", 0),
# Products not visible in listings should be visible in collections
("inCollection", 5),
],
)
def test_products_with_filtering_with_not_visible_in_listings_as_anonymous_client(
tested_field,
attribute_count,
api_client,
attributes_for_filtering_with_channels,
category,
collection,
channel_PLN,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by, "channel": channel_PLN.slug}
# when
response = api_client.post_graphql(QUERY_ATTRIBUTES_FILTERING, variables)
# then
content = get_graphql_content(response)
attribute_nodes = content["data"]["attributes"]["edges"]
assert len(attribute_nodes) == attribute_count
@pytest.mark.parametrize(
"tested_field, attribute_count",
[("inCategory", 5), ("inCollection", 5)],
)
def test_products_with_filtering_with_not_published_as_staff_user(
tested_field,
attribute_count,
staff_api_client,
permission_manage_products,
attributes_for_filtering_with_channels,
category,
collection,
other_channel_USD,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by, "channel": other_channel_USD.slug}
# when
response = staff_api_client.post_graphql(
QUERY_ATTRIBUTES_FILTERING,
variables,
permissions=[permission_manage_products],
check_no_permissions=False,
)
# then
content = get_graphql_content(response)
attribute_nodes = content["data"]["attributes"]["edges"]
assert len(attribute_nodes) == attribute_count
@pytest.mark.parametrize(
"tested_field, attribute_count",
[("inCategory", 0), ("inCollection", 0)],
)
def test_products_with_filtering_with_not_published_as_anonymous_client(
tested_field,
attribute_count,
api_client,
attributes_for_filtering_with_channels,
category,
collection,
other_channel_USD,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by, "channel": other_channel_USD.slug}
# when
response = api_client.post_graphql(QUERY_ATTRIBUTES_FILTERING, variables)
# then
content = get_graphql_content(response)
attribute_nodes = content["data"]["attributes"]["edges"]
assert len(attribute_nodes) == attribute_count
@pytest.mark.parametrize(
"tested_field",
["inCategory", "inCollection"],
)
def test_products_with_filtering_not_existing_channel(
tested_field,
api_client,
attributes_for_filtering_with_channels,
category,
collection,
):
# given
if "Collection" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Collection", collection.pk)
elif "Category" in tested_field:
filtered_by_node_id = graphene.Node.to_global_id("Category", category.pk)
else:
raise AssertionError(tested_field)
filter_by = {tested_field: filtered_by_node_id}
variables = {"filter": filter_by, "channel": "Not-existing"}
# when
response = api_client.post_graphql(QUERY_ATTRIBUTES_FILTERING, variables)
# then
content = get_graphql_content(response)
attribute_nodes = content["data"]["attributes"]["edges"]
assert len(attribute_nodes) == 0
| 29.772727
| 85
| 0.660534
| 1,368
| 13,100
| 5.962719
| 0.097953
| 0.06473
| 0.055903
| 0.061787
| 0.845531
| 0.824936
| 0.795758
| 0.730661
| 0.712517
| 0.664215
| 0
| 0.005187
| 0.249466
| 13,100
| 439
| 86
| 29.840547
| 0.824451
| 0.014733
| 0
| 0.704918
| 0
| 0
| 0.102088
| 0.00163
| 0
| 0
| 0
| 0
| 0.046448
| 1
| 0.02459
| false
| 0
| 0.016393
| 0
| 0.043716
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
35d59348248e0115522c78d130a17daff3eaff93
| 3,195
|
py
|
Python
|
tests/test_search.py
|
eyllanesc/mkdocs-static-i18n
|
283f9a080603904a581370bdae01d517977c9b51
|
[
"MIT"
] | null | null | null |
tests/test_search.py
|
eyllanesc/mkdocs-static-i18n
|
283f9a080603904a581370bdae01d517977c9b51
|
[
"MIT"
] | null | null | null |
tests/test_search.py
|
eyllanesc/mkdocs-static-i18n
|
283f9a080603904a581370bdae01d517977c9b51
|
[
"MIT"
] | null | null | null |
from mkdocs.commands.build import build
from mkdocs.config.base import load_config
def test_search_add_lang():
mkdocs_config = load_config(
"tests/mkdocs_base.yml",
theme={"name": "mkdocs"},
use_directory_urls=True,
docs_dir="../docs/",
site_url="http://localhost",
extra_javascript=[],
plugins={
"search": {},
"i18n": {
"default_language": "en",
"languages": {"fr": "français", "en": "english"},
},
},
)
build(mkdocs_config)
search_plugin = mkdocs_config["plugins"]["search"]
assert search_plugin.config["lang"] == ["en", "fr"]
def test_search_entries():
mkdocs_config = load_config(
"tests/mkdocs_base.yml",
theme={"name": "mkdocs"},
use_directory_urls=True,
docs_dir="../docs/",
site_url="http://localhost",
extra_javascript=[],
plugins={
"search": {},
"i18n": {
"default_language": "en",
"languages": {
"fr": {"name": "français", "link": "./fr/", "build": True}
},
},
},
)
build(mkdocs_config)
search_plugin = mkdocs_config["plugins"]["search"]
assert len(search_plugin.search_index._entries) == 30
def test_search_entries_no_directory_urls():
mkdocs_config = load_config(
"tests/mkdocs_base.yml",
theme={"name": "mkdocs"},
use_directory_urls=False,
docs_dir="../docs/",
site_url="http://localhost",
extra_javascript=[],
plugins={
"search": {},
"i18n": {
"default_language": "en",
"languages": {"fr": "français"},
},
},
)
build(mkdocs_config)
search_plugin = mkdocs_config["plugins"]["search"]
assert len(search_plugin.search_index._entries) == 30
def test_search_deduplicate_entries():
mkdocs_config = load_config(
"tests/mkdocs_base.yml",
theme={"name": "mkdocs"},
use_directory_urls=True,
docs_dir="../docs/",
site_url="http://localhost",
extra_javascript=[],
plugins={
"search": {},
"i18n": {
"default_language": "en",
"languages": {"fr": "français", "en": "english"},
},
},
)
build(mkdocs_config)
search_plugin = mkdocs_config["plugins"]["search"]
assert len(search_plugin.search_index._entries) == 30
def test_search_deduplicate_entries_no_directory_urls():
mkdocs_config = load_config(
"tests/mkdocs_base.yml",
theme={"name": "mkdocs"},
use_directory_urls=False,
docs_dir="../docs/",
site_url="http://localhost",
extra_javascript=[],
plugins={
"search": {},
"i18n": {
"default_language": "en",
"languages": {"fr": "français", "en": "english"},
},
},
)
build(mkdocs_config)
search_plugin = mkdocs_config["plugins"]["search"]
assert len(search_plugin.search_index._entries) == 30
| 29.045455
| 78
| 0.531768
| 302
| 3,195
| 5.317881
| 0.15894
| 0.119552
| 0.040473
| 0.068493
| 0.902864
| 0.902864
| 0.902864
| 0.902864
| 0.902864
| 0.902864
| 0
| 0.008174
| 0.310798
| 3,195
| 109
| 79
| 29.311927
| 0.721163
| 0
| 0
| 0.727273
| 0
| 0
| 0.196557
| 0.032864
| 0
| 0
| 0
| 0
| 0.050505
| 1
| 0.050505
| false
| 0
| 0.020202
| 0
| 0.070707
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
ea2fd1ed3e21ac0ec6c9bb6f324c39f4465015e9
| 10,326
|
py
|
Python
|
src/tests/withdraw_test.py
|
vitchor/stellar-anchor-server
|
941eb4e2a265b2eacaa07b2eeaf088b6d72c8da7
|
[
"Apache-2.0"
] | null | null | null |
src/tests/withdraw_test.py
|
vitchor/stellar-anchor-server
|
941eb4e2a265b2eacaa07b2eeaf088b6d72c8da7
|
[
"Apache-2.0"
] | null | null | null |
src/tests/withdraw_test.py
|
vitchor/stellar-anchor-server
|
941eb4e2a265b2eacaa07b2eeaf088b6d72c8da7
|
[
"Apache-2.0"
] | null | null | null |
"""This module tests the `/withdraw` endpoint."""
import codecs
import json
from unittest.mock import patch
import pytest
from helpers import format_memo_horizon
from transaction.models import Transaction
from withdraw.tasks import watch_stellar_withdraw
@pytest.mark.django_db
def test_withdraw_success(client, acc1_usd_withdrawal_transaction_factory):
"""`GET /withdraw` succeeds with no optional arguments."""
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=USD", follow=True)
content = json.loads(response.content)
assert response.status_code == 403
assert content["type"] == "interactive_customer_info_needed"
@pytest.mark.django_db
def test_withdraw_invalid_asset(client, acc1_usd_withdrawal_transaction_factory):
"""`GET /withdraw` fails with an invalid asset argument."""
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=ETH", follow=True)
content = json.loads(response.content)
assert response.status_code == 400
assert content == {"error": "invalid operation for asset ETH"}
@pytest.mark.django_db
def test_withdraw_no_asset(client):
"""`GET /withdraw fails with no asset argument."""
response = client.get(f"/withdraw", follow=True)
content = json.loads(response.content)
assert response.status_code == 400
assert content == {"error": "'asset_code' is required"}
@pytest.mark.django_db
def test_withdraw_interactive_no_txid(client, acc1_usd_withdrawal_transaction_factory):
"""
`GET /withdraw/interactive_withdraw` fails with no transaction_id.
"""
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw/interactive_withdraw?", follow=True)
content = json.loads(response.content)
assert response.status_code == 400
assert content == {"error": "no 'transaction_id' provided"}
@pytest.mark.django_db
def test_withdraw_interactive_no_asset(client, acc1_usd_withdrawal_transaction_factory):
"""
`GET /withdraw/interactive_withdraw` fails with no asset_code.
"""
acc1_usd_withdrawal_transaction_factory()
response = client.get(
f"/withdraw/interactive_withdraw?transaction_id=2", follow=True
)
content = json.loads(response.content)
assert response.status_code == 400
assert content == {"error": "invalid 'asset_code'"}
@pytest.mark.django_db
def test_withdraw_interactive_invalid_asset(
client, acc1_usd_withdrawal_transaction_factory
):
"""
`GET /withdraw/interactive_withdraw` fails with invalid asset_code.
"""
acc1_usd_withdrawal_transaction_factory()
response = client.get(
f"/withdraw/interactive_withdraw?transaction_id=2&asset_code=ETH", follow=True
)
content = json.loads(response.content)
assert response.status_code == 400
assert content == {"error": "invalid 'asset_code'"}
# TODO: Decompose the below tests, since they call the same logic. The issue: Pytest complains
# about decomposition when passing fixtures to a helper function.
@pytest.mark.django_db
@patch("withdraw.tasks.get_transactions", return_value=[{}])
@patch(
"withdraw.tasks.watch_stellar_withdraw.delay", side_effect=watch_stellar_withdraw
)
def test_withdraw_interactive_failure_no_memotype(
mock_watch, mock_transactions, client, acc1_usd_withdrawal_transaction_factory
):
"""
`GET /withdraw/interactive_withdraw` fails with no `memo_type` in Horizon response.
"""
del mock_watch, mock_transactions
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=USD", follow=True)
content = json.loads(response.content)
assert response.status_code == 403
assert content["type"] == "interactive_customer_info_needed"
transaction_id = content["id"]
url = content["url"]
response = client.post(
url, {"amount": 20, "bank_account": "123456", "bank": "Bank"}
)
assert response.status_code == 200
assert (
Transaction.objects.get(id=transaction_id).status
== Transaction.STATUS.pending_user_transfer_start
)
@pytest.mark.django_db
@patch("withdraw.tasks.get_transactions", return_value=[{"memo_type": "not_hash"}])
@patch(
"withdraw.tasks.watch_stellar_withdraw.delay", side_effect=watch_stellar_withdraw
)
def test_withdraw_interactive_failure_incorrect_memotype(
mock_watch, mock_transactions, client, acc1_usd_withdrawal_transaction_factory
):
"""
`GET /withdraw/interactive_withdraw` fails with incorrect `memo_type` in Horizon response.
"""
del mock_watch, mock_transactions
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=USD", follow=True)
content = json.loads(response.content)
assert response.status_code == 403
assert content["type"] == "interactive_customer_info_needed"
transaction_id = content["id"]
url = content["url"]
response = client.post(
url, {"amount": 20, "bank_account": "123456", "bank": "Bank"}
)
assert response.status_code == 200
assert (
Transaction.objects.get(id=transaction_id).status
== Transaction.STATUS.pending_user_transfer_start
)
@pytest.mark.django_db
@patch("withdraw.tasks.get_transactions", return_value=[{"memo_type": "hash"}])
@patch(
"withdraw.tasks.watch_stellar_withdraw.delay", side_effect=watch_stellar_withdraw
)
def test_withdraw_interactive_failure_no_memo(
mock_watch, mock_transactions, client, acc1_usd_withdrawal_transaction_factory
):
"""
`GET /withdraw/interactive_withdraw` fails with no `memo` in Horizon response.
"""
del mock_watch, mock_transactions
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=USD", follow=True)
content = json.loads(response.content)
assert response.status_code == 403
assert content["type"] == "interactive_customer_info_needed"
transaction_id = content["id"]
url = content["url"]
response = client.post(
url, {"amount": 20, "bank_account": "123456", "bank": "Bank"}
)
assert response.status_code == 200
assert (
Transaction.objects.get(id=transaction_id).status
== Transaction.STATUS.pending_user_transfer_start
)
@pytest.mark.django_db
@patch(
"withdraw.tasks.get_transactions",
return_value=[{"memo_type": "hash", "memo": "wrong_memo"}],
)
@patch(
"withdraw.tasks.watch_stellar_withdraw.delay", side_effect=watch_stellar_withdraw
)
def test_withdraw_interactive_failure_incorrect_memo(
mock_watch, mock_transactions, client, acc1_usd_withdrawal_transaction_factory
):
"""
`GET /withdraw/interactive_withdraw` fails with incorrect `memo` in Horizon response.
"""
del mock_watch, mock_transactions
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=USD", follow=True)
content = json.loads(response.content)
assert response.status_code == 403
assert content["type"] == "interactive_customer_info_needed"
transaction_id = content["id"]
url = content["url"]
response = client.post(
url, {"amount": 20, "bank_account": "123456", "bank": "Bank"}
)
assert response.status_code == 200
assert (
Transaction.objects.get(id=transaction_id).status
== Transaction.STATUS.pending_user_transfer_start
)
@pytest.mark.django_db
@patch("withdraw.tasks.get_transactions")
@patch("withdraw.tasks.watch_stellar_withdraw.delay", return_value=None)
def test_withdraw_interactive_success_transaction_unsuccessful(
mock_watch, mock_transactions, client, acc1_usd_withdrawal_transaction_factory
):
"""
`GET /withdraw/interactive_withdraw` changes transaction to `pending_stellar`
with unsuccessful transaction.
"""
del mock_watch
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=USD", follow=True)
content = json.loads(response.content)
assert response.status_code == 403
assert content["type"] == "interactive_customer_info_needed"
transaction_id = content["id"]
url = content["url"]
response = client.post(
url, {"amount": 20, "bank_account": "123456", "bank": "Bank"}
)
assert response.status_code == 200
transaction = Transaction.objects.get(id=transaction_id)
assert transaction.status == Transaction.STATUS.pending_user_transfer_start
withdraw_memo = transaction.withdraw_memo
mock_transactions.return_value = [
{
"memo_type": "hash",
"memo": format_memo_horizon(withdraw_memo),
"successful": False,
}
]
watch_stellar_withdraw(withdraw_memo)
assert (
Transaction.objects.get(id=transaction_id).status
== Transaction.STATUS.pending_stellar
)
@pytest.mark.django_db
@patch("withdraw.tasks.get_transactions")
@patch("withdraw.tasks.watch_stellar_withdraw.delay", return_value=None)
def test_withdraw_interactive_success_transaction_successful(
mock_watch, mock_transactions, client, acc1_usd_withdrawal_transaction_factory
):
"""
`GET /withdraw/interactive_withdraw` changes transaction to `completed`
with successful transaction.
"""
del mock_watch
acc1_usd_withdrawal_transaction_factory()
response = client.get(f"/withdraw?asset_code=USD", follow=True)
content = json.loads(response.content)
assert response.status_code == 403
assert content["type"] == "interactive_customer_info_needed"
transaction_id = content["id"]
url = content["url"]
response = client.post(
url, {"amount": 20, "bank_account": "123456", "bank": "Bank"}
)
assert response.status_code == 200
transaction = Transaction.objects.get(id=transaction_id)
assert transaction.status == Transaction.STATUS.pending_user_transfer_start
withdraw_memo = transaction.withdraw_memo
mock_transactions.return_value = [
{
"memo_type": "hash",
"memo": format_memo_horizon(withdraw_memo),
"successful": True,
}
]
watch_stellar_withdraw(withdraw_memo)
transaction = Transaction.objects.get(id=transaction_id)
assert transaction.status == Transaction.STATUS.completed
assert transaction.completed_at
| 35.730104
| 94
| 0.730002
| 1,221
| 10,326
| 5.886159
| 0.101556
| 0.021428
| 0.052038
| 0.08571
| 0.908585
| 0.893836
| 0.893836
| 0.879505
| 0.866147
| 0.853346
| 0
| 0.014546
| 0.161147
| 10,326
| 288
| 95
| 35.854167
| 0.81517
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| 0.110375
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| 0.003472
| 0.178899
| 1
| 0.055046
| false
| 0
| 0.03211
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| null | 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
57b190b7484446c0021f9dbd93e23d148c29284a
| 297
|
py
|
Python
|
machin/utils/__init__.py
|
lethaiq/machin
|
7873cada457328952310394afeedcad4bb6a7c4a
|
[
"MIT"
] | null | null | null |
machin/utils/__init__.py
|
lethaiq/machin
|
7873cada457328952310394afeedcad4bb6a7c4a
|
[
"MIT"
] | null | null | null |
machin/utils/__init__.py
|
lethaiq/machin
|
7873cada457328952310394afeedcad4bb6a7c4a
|
[
"MIT"
] | null | null | null |
from . import \
checker, conf, helper_classes, learning_rate, \
logging, media, prepare, save_env, tensor_board, \
visualize
__all__ = ["checker", "conf", "helper_classes", "learning_rate",
"logging", "media", "prepare", "save_env", "tensor_board",
"visualize"]
| 33
| 69
| 0.636364
| 31
| 297
| 5.709677
| 0.548387
| 0.124294
| 0.19209
| 0.271186
| 0.926554
| 0.926554
| 0.926554
| 0.926554
| 0.926554
| 0.926554
| 0
| 0
| 0.212121
| 297
| 8
| 70
| 37.125
| 0.75641
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| 0.289562
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| 0.142857
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| 0.142857
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| null | 0
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| 1
| 1
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| null | 0
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| 0
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| 0
| 0
| 0
|
0
| 9
|
57bd650f942195400b3de36be2424f272b0a975b
| 60
|
py
|
Python
|
drivers/vna_skrf/keysight_pna/__init__.py
|
pyvisa/pyvisa-drivers
|
a483cef18402e74a5e2521b295b953c14b5f58f0
|
[
"MIT"
] | 10
|
2019-01-26T11:56:34.000Z
|
2021-09-02T11:12:52.000Z
|
drivers/vna_skrf/keysight_pna/__init__.py
|
pyvisa/pyvisa-drivers
|
a483cef18402e74a5e2521b295b953c14b5f58f0
|
[
"MIT"
] | 4
|
2018-03-31T14:13:14.000Z
|
2019-06-26T18:41:23.000Z
|
drivers/vna_skrf/keysight_pna/__init__.py
|
pyvisa/pyvisa-drivers
|
a483cef18402e74a5e2521b295b953c14b5f58f0
|
[
"MIT"
] | 5
|
2018-03-31T14:14:03.000Z
|
2020-03-08T23:37:56.000Z
|
from .keysight_pna import PNA
from .keysight_pna import PNAX
| 30
| 30
| 0.85
| 10
| 60
| 4.9
| 0.5
| 0.489796
| 0.612245
| 0.857143
| 0
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| 0
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| 0
| 0.116667
| 60
| 2
| 30
| 30
| 0.924528
| 0
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| true
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| 1
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| 0
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| null | 0
| 0
| 0
| 0
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| 0
| 1
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| 1
| 0
| 1
| 0
|
0
| 8
|
17b0d3eabca6d4b4c5fbe4c6d7881c32763b4001
| 4,668
|
py
|
Python
|
PyraPose/uncertainty_pnp/un_pnp_utils.py
|
sThalham/RGBDPose
|
d2738aa5b229bd32cad60f4e6da1210945b258bc
|
[
"Apache-2.0"
] | 2
|
2020-12-03T03:02:45.000Z
|
2022-01-13T17:50:41.000Z
|
PyraPose/uncertainty_pnp/un_pnp_utils.py
|
sThalham/RGBDPose
|
d2738aa5b229bd32cad60f4e6da1210945b258bc
|
[
"Apache-2.0"
] | 2
|
2021-02-08T16:14:40.000Z
|
2021-03-25T09:04:09.000Z
|
PyraPose/uncertainty_pnp/un_pnp_utils.py
|
sThalham/RGBDPose
|
d2738aa5b229bd32cad60f4e6da1210945b258bc
|
[
"Apache-2.0"
] | null | null | null |
from ..uncertainty_pnp._ext import lib, ffi
import numpy as np
import cv2
def uncertainty_pnp(points_2d, weights_2d, points_3d, camera_matrix):
'''
:param points_2d: [pn,2]
:param weights_2d: [pn,3] wxx,wxy,wyy
:param points_3d: [pn,3]
:param camera_matrix: [3,3]
:return:
'''
pn = points_2d.shape[0]
assert(points_3d.shape[0] == pn and pn >= 4)
try:
dist_coeffs = uncertainty_pnp.dist_coeffs
except:
dist_coeffs = np.zeros(shape=[8, 1], dtype=np.float64)
points_3d = points_3d.astype(np.float64)
points_2d = points_2d.astype(np.float64)
weights_2d = weights_2d.astype(np.float64)
camera_matrix = camera_matrix.astype(np.float64)
idxs = np.argsort(weights_2d[:, 0]+weights_2d[:, 1])[-4:]
_, R_exp, t = cv2.solvePnP(np.expand_dims(points_3d[idxs,:], 0),
np.expand_dims(points_2d[idxs,:], 0),
camera_matrix, dist_coeffs, None, None, False, flags=cv2.SOLVEPNP_P3P)
if pn == 4:
# no other points
R, _ = cv2.Rodrigues(R_exp)
Rt = np.concatenate([R, t], axis=-1)
return Rt
points_2d = np.ascontiguousarray(points_2d, np.float64)
points_3d = np.ascontiguousarray(points_3d, np.float64)
weights_2d = np.ascontiguousarray(weights_2d, np.float64)
camera_matrix = np.ascontiguousarray(camera_matrix, np.float64)
init_rt = np.ascontiguousarray(np.concatenate([R_exp, t], 0), np.float64)
points_2d_ptr = ffi.cast('double*', points_2d.ctypes.data)
points_3d_ptr = ffi.cast('double*', points_3d.ctypes.data)
weights_3d_ptr = ffi.cast('double*', weights_2d.ctypes.data)
camera_matrix_ptr = ffi.cast('double*', camera_matrix.ctypes.data)
init_rt_ptr = ffi.cast('double*', init_rt.ctypes.data)
result_rt = np.empty([6], np.float64)
result_rt_ptr = ffi.cast('double*', result_rt.ctypes.data)
lib.uncertainty_pnp(points_2d_ptr, points_3d_ptr, weights_3d_ptr, camera_matrix_ptr, init_rt_ptr, result_rt_ptr, pn)
R, _ = cv2.Rodrigues(result_rt[:3])
Rt = np.concatenate([R, result_rt[3:, None]], axis=-1)
return Rt
def uncertainty_pnp_v2(points_2d, covars, points_3d, camera_matrix, type='single'):
'''
:param points_2d: [pn,2]
:param covars: [pn,2,2]
:param points_3d: [pn,3]
:param camera_matrix: [3,3]
:return:
'''
pn = points_2d.shape[0]
assert(points_3d.shape[0] == pn and pn >= 4 and covars.shape[0] == pn)
points_3d = points_3d.astype(np.float64)
points_2d = points_2d.astype(np.float64)
camera_matrix = camera_matrix.astype(np.float64)
weights_2d = []
for pi in range(pn):
weight = 0.0
if covars[pi, 0, 0] < 1e-5:
weights_2d.append(weight)
else:
weight = np.max(np.linalg.eigvals(covars[pi]))
weights_2d.append(1.0/weight)
weights_2d = np.asarray(weights_2d, np.float64)
try:
dist_coeffs = uncertainty_pnp.dist_coeffs
except:
dist_coeffs = np.zeros(shape=[8, 1], dtype=np.float64)
idxs = np.argsort(weights_2d)[-4:]
_, R_exp, t = cv2.solvePnP(np.expand_dims(points_3d[idxs,:], 0),
np.expand_dims(points_2d[idxs,:], 0),
camera_matrix, dist_coeffs, None, None, False, flags=cv2.SOLVEPNP_P3P)
if pn == 4:
# no other points
R, _ = cv2.Rodrigues(R_exp)
Rt = np.concatenate([R, t], axis=-1)
return Rt
points_2d = np.ascontiguousarray(points_2d, np.float64)
points_3d = np.ascontiguousarray(points_3d, np.float64)
weights_2d = weights_2d[:, None]
weights_2d = np.concatenate([weights_2d, np.zeros([pn, 1]), weights_2d], 1)
weights_2d = np.ascontiguousarray(weights_2d, np.float64)
camera_matrix = np.ascontiguousarray(camera_matrix, np.float64)
init_rt = np.ascontiguousarray(np.concatenate([R_exp, t], 0), np.float64)
points_2d_ptr = ffi.cast('double*', points_2d.ctypes.data)
points_3d_ptr = ffi.cast('double*', points_3d.ctypes.data)
weights_3d_ptr = ffi.cast('double*', weights_2d.ctypes.data)
camera_matrix_ptr = ffi.cast('double*', camera_matrix.ctypes.data)
init_rt_ptr = ffi.cast('double*', init_rt.ctypes.data)
result_rt = np.empty([6], np.float64)
result_rt_ptr = ffi.cast('double*', result_rt.ctypes.data)
lib.uncertainty_pnp(points_2d_ptr, points_3d_ptr, weights_3d_ptr, camera_matrix_ptr, init_rt_ptr, result_rt_ptr, pn)
R, _ = cv2.Rodrigues(result_rt[:3])
Rt = np.concatenate([R, result_rt[3:, None]], axis=-1)
return Rt
| 38.262295
| 120
| 0.645458
| 680
| 4,668
| 4.180882
| 0.127941
| 0.07281
| 0.042209
| 0.067534
| 0.844179
| 0.841013
| 0.817446
| 0.80197
| 0.80197
| 0.80197
| 0
| 0.049657
| 0.219152
| 4,668
| 121
| 121
| 38.578512
| 0.730316
| 0.073265
| 0
| 0.746988
| 0
| 0
| 0.021117
| 0
| 0
| 0
| 0
| 0
| 0.024096
| 1
| 0.024096
| false
| 0
| 0.036145
| 0
| 0.108434
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
17d5157cfceccef3137ab29d13641f68c7cb4420
| 8,172
|
py
|
Python
|
tests/libraries/position/test_notional.py
|
overlay-market/v1-core
|
e18fabd242f21c243a555712d3f08ca059941f41
|
[
"MIT"
] | 3
|
2022-02-17T16:11:39.000Z
|
2022-03-10T23:46:19.000Z
|
tests/libraries/position/test_notional.py
|
overlay-market/v1-core
|
e18fabd242f21c243a555712d3f08ca059941f41
|
[
"MIT"
] | 10
|
2022-01-25T21:49:20.000Z
|
2022-03-31T00:32:29.000Z
|
tests/libraries/position/test_notional.py
|
overlay-market/v1-core
|
e18fabd242f21c243a555712d3f08ca059941f41
|
[
"MIT"
] | 2
|
2022-01-21T01:04:54.000Z
|
2022-02-23T08:38:20.000Z
|
def test_notional_initial(position):
mid_price = 100000000000000000000 # 100
notional = 10000000000000000000 # 10
debt = 2000000000000000000 # 2
liquidated = False
# NOTE: mid_ratio tests in test_entry_price.py
oi = int((notional / mid_price) * 1000000000000000000) # 0.1
fraction = 1000000000000000000 # 1
# check initial notional is oi * entry_price = notional
# when long
is_long = True
entry_price = 101000000000000000000 # 101
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = notional
actual = position.notionalInitial(pos, fraction)
assert expect == actual
# check initial notional is oi * entry_price = notional
# when short
is_long = False
entry_price = 99000000000000000000 # 99
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = notional
actual = position.notionalInitial(pos, fraction)
assert expect == actual
def test_notional_initial_when_fraction_less_than_one(position):
mid_price = 100000000000000000000 # 100
entry_price = 101000000000000000000 # 101
notional = 10000000000000000000 # 10
debt = 2000000000000000000 # 2
liquidated = False
# NOTE: mid_ratio tests in test_entry_price.py
oi = int((notional / mid_price) * 1000000000000000000) # 0.1
fraction = 250000000000000000 # 0.25
# check initial notional is oi * entry_price = notional
# when long
is_long = True
entry_price = 101000000000000000000 # 101
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = 2500000000000000000
actual = position.notionalInitial(pos, fraction)
assert expect == actual
# check initial notional is oi * entry_price = notional
# when short
is_long = False
entry_price = 99000000000000000000 # 99
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = 2500000000000000000
actual = position.notionalInitial(pos, fraction)
assert expect == actual
def test_notional_with_pnl(position):
mid_price = 100000000000000000000 # 100
current_price = 150000000000000000000 # 150
notional = 10000000000000000000 # 10
debt = 2000000000000000000 # 2
liquidated = False
# NOTE: mid_ratio tests in test_entry_price.py
oi = int((notional / mid_price) * 1000000000000000000) # 0.1
fraction = 1000000000000000000 # 1
cap_payoff = 5000000000000000000 # 5
# check current notional is oi * current_price
# when long
is_long = True
entry_price = 101000000000000000000 # 101
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = 14900000000000000000
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
# check current notional is 2 * oi * entry_price - oi * current_price
# when short
is_long = False
entry_price = 99000000000000000000 # 99
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = 4900000000000000000
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
def test_notional_with_pnl_when_fraction_less_than_one(position):
mid_price = 100000000000000000000 # 100
current_price = 150000000000000000000 # 150
notional = 10000000000000000000 # 10
debt = 2000000000000000000 # 2
liquidated = False
# NOTE: mid_ratio tests in test_entry_price.py
oi = int((notional / mid_price) * 1000000000000000000) # 0.1
fraction = 250000000000000000 # 0.25
cap_payoff = 5000000000000000000 # 5
# check notional is oi * current_price
# when long
is_long = True
entry_price = 101000000000000000000 # 101
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = 3725000000000000000
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
# check notional is 2 * oi * entry_price - oi * current_price
# when short
is_long = False
entry_price = 99000000000000000000 # 99
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = 1225000000000000000
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
def test_notional_with_pnl_when_payoff_greater_than_cap(position):
mid_price = 100000000000000000000 # 100
entry_price = 101000000000000000000 # 101
current_price = 800000000000000000000 # 800
notional = 10000000000000000000 # 10
debt = 2000000000000000000 # 2
liquidated = False
# NOTE: mid_ratio tests in test_entry_price.py
oi = int((notional / mid_price) * 1000000000000000000) # 0.1
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
fraction = 1000000000000000000 # 1
cap_payoff = 5000000000000000000 # 5
# check notional is oi * entry_price * (1 + cap_payoff)
# when long
is_long = True
expect = 60500000000000000000
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
def test_notional_with_pnl_when_underwater(position):
mid_price = 100000000000000000000 # 100
entry_price = 99000000000000000000 # 99
notional = 10000000000000000000 # 10
debt = 8000000000000000000 # 8
liquidated = False
# NOTE: mid_ratio tests in test_entry_price.py
oi = int((notional / mid_price) * 1000000000000000000) # 0.1
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
fraction = 1000000000000000000 # 1
cap_payoff = 5000000000000000000 # 5
# check notional returns the debt (floors to debt) when short is underwater
is_long = False
current_price = 225000000000000000000 # 225
expect = debt
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
def test_notional_with_pnl_when_oi_zero(position):
current_price = 75000000000000000000 # 75
mid_price = 100000000000000000000 # 100
notional = 0 # 0
debt = 2000000000000000000 # 2
liquidated = False
# NOTE: mid_ratio tests in test_entry_price.py
oi = int((notional / mid_price) * 1000000000000000000) # 0.1
fraction = 1000000000000000000 # 1
cap_payoff = 5000000000000000000 # 5
# check notional returns debt when oi is zero and is long
is_long = True
entry_price = 101000000000000000000 # 101
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = debt
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
# check notional returns the debt when oi is zero and is short
is_long = False
entry_price = 99000000000000000000 # 99
mid_ratio = position.calcEntryToMidRatio(entry_price, mid_price)
pos = (notional, debt, mid_ratio, is_long, liquidated, oi)
expect = debt
actual = position.notionalWithPnl(pos, fraction, oi, oi, current_price,
cap_payoff)
assert expect == actual
| 36.810811
| 79
| 0.691875
| 914
| 8,172
| 5.97046
| 0.088621
| 0.071468
| 0.035184
| 0.076965
| 0.919736
| 0.89683
| 0.89683
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| 0.871724
| 0.851933
| 0
| 0.223278
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| 221
| 80
| 36.977376
| 0.655184
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| 0.888158
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| 0
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| 0.078947
| 1
| 0.046053
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| 0
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| 0
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| 1
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| 1
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| 1
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| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
aa0fc02ef6b3f0244ef891804ca533e5f4a51455
| 137
|
py
|
Python
|
telemetry/third_party/modulegraph/modulegraph/_compat.py
|
tingshao/catapult
|
a8fe19e0c492472a8ed5710be9077e24cc517c5c
|
[
"BSD-3-Clause"
] | 2,151
|
2020-04-18T07:31:17.000Z
|
2022-03-31T08:39:18.000Z
|
telemetry/third_party/modulegraph/modulegraph/_compat.py
|
tingshao/catapult
|
a8fe19e0c492472a8ed5710be9077e24cc517c5c
|
[
"BSD-3-Clause"
] | 395
|
2020-04-18T08:22:18.000Z
|
2021-12-08T13:04:49.000Z
|
telemetry/third_party/modulegraph/modulegraph/_compat.py
|
tingshao/catapult
|
a8fe19e0c492472a8ed5710be9077e24cc517c5c
|
[
"BSD-3-Clause"
] | 338
|
2020-04-18T08:03:10.000Z
|
2022-03-29T12:33:22.000Z
|
import sys
if sys.version_info[0] == 2:
def Bchr(value):
return chr(value)
else:
def Bchr(value):
return value
| 13.7
| 28
| 0.591241
| 20
| 137
| 4
| 0.65
| 0.175
| 0.3
| 0.45
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020833
| 0.29927
| 137
| 9
| 29
| 15.222222
| 0.8125
| 0
| 0
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.142857
| 0.285714
| 0.714286
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
aa24caa620c061c86b362ac7980b4fae8c81aabb
| 3,362
|
py
|
Python
|
graph_embedding/vis_pca.py
|
myracheng/pronear
|
a92e97cd860900f3c535a72a1b867d8f5ad096ab
|
[
"Apache-2.0"
] | null | null | null |
graph_embedding/vis_pca.py
|
myracheng/pronear
|
a92e97cd860900f3c535a72a1b867d8f5ad096ab
|
[
"Apache-2.0"
] | null | null | null |
graph_embedding/vis_pca.py
|
myracheng/pronear
|
a92e97cd860900f3c535a72a1b867d8f5ad096ab
|
[
"Apache-2.0"
] | null | null | null |
import numpy as np
a = np.load('acs.npy')
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
pca = PCA(n_components=3)
pca_result = pca.fit_transform(a)
print(np.shape(pca_result))
# df['pca-one'] = pca_result[:,0]
# df['pca-two'] = pca_result[:,1]
# df['pca-three'] = pca_result[:,2]
print('Explained variation per principal component: {}'.format(pca.explained_variance_ratio_))
# Explained variation per principal component: [0.09746116 0.07155445 0.06149531]
# labels = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
labels = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0]
# [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
# log_file = 'vis.txt'
# ### GET LABEL
# f = open(log_file, "r")
# lines_list = f.readlines()
# # lines = "".join(lines_list)
# scores = []
# for line in lines_list:
# score = [float(s) for s in re.findall("\d+\.\d+",line)]
# # print(score)
# if len(score) != 2:
# print(score)
# else:
# scores.append(score)
# sc = np.array(scores)
# print(np.shape(sc))
# colors = np.array(["cerlean", "pomegranate"])
# plt.scatter(x,y, c=colors[z])
plt.scatter(pca_result[:,0], pca_result[:,1],c=labels,cmap=plt.get_cmap('PiYG'),alpha=0.3)
plt.title("Embeddings of Good and Bad Programs found using NEAR, PCA (Training)")
plt.savefig('hi3.png')
| 90.864865
| 1,163
| 0.44884
| 910
| 3,362
| 1.638462
| 0.105495
| 0.725687
| 0.969819
| 1.156271
| 0.549966
| 0.497653
| 0.497653
| 0.497653
| 0.497653
| 0.497653
| 0
| 0.311535
| 0.267698
| 3,362
| 37
| 1,164
| 90.864865
| 0.29407
| 0.560381
| 0
| 0
| 0
| 0
| 0.091724
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.25
| 0
| 0.25
| 0.166667
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
a4c0487164c34cd090824d10cc7ba4e961dca37b
| 19,922
|
py
|
Python
|
search/views.py
|
Mateusz-Slisz/abme
|
82d0bac56c644a9e3d8e6d5805e9b0b293985809
|
[
"MIT"
] | 1
|
2017-07-15T23:03:00.000Z
|
2017-07-15T23:03:00.000Z
|
search/views.py
|
Mateusz-Slisz/abme
|
82d0bac56c644a9e3d8e6d5805e9b0b293985809
|
[
"MIT"
] | null | null | null |
search/views.py
|
Mateusz-Slisz/abme
|
82d0bac56c644a9e3d8e6d5805e9b0b293985809
|
[
"MIT"
] | null | null | null |
from itertools import chain
from operator import attrgetter
from django.shortcuts import render, redirect, get_object_or_404
from django.db.models.functions import Coalesce
from django.db.models import Avg, Func, Count, Q
from django.contrib.auth.models import User
from api.models import Film, Serial, Person, Article
from serial.models import SerialRating, SerialWatchlist
from film.models import FilmRating, FilmWatchlist
from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger
class Round(Func):
function = 'ROUND'
template = '%(function)s(%(expressions)s, 1)'
def list(request):
films = Film.objects.get_queryset().order_by('id').annotate(
average_score=Coalesce(Round(Avg('filmrating__rate')), 0),
votes=Count('filmrating__user', distinct=True))
serials = Serial.objects.get_queryset().order_by('id').annotate(
average_score=Coalesce(Round(Avg('serialrating__rate')), 0),
votes=Count('serialrating__user', distinct=True))
persons = Person.objects.get_queryset().order_by('id')
articles = Article.objects.get_queryset().order_by('id')
latest_article = articles.order_by('-created_date').first()
keywords = request.GET.get('q')
page = request.GET.get('page')
if keywords:
films = films.filter(
Q(title__icontains=keywords)
)
serials = serials.filter(
Q(title__icontains=keywords)
)
for word in keywords.split():
persons = persons.filter(
Q(first_name__icontains=word)|
Q(last_name__icontains=word)
)
articles = articles.filter(
Q(title__icontains=keywords)
)
films_c = films.count()
serials_c = serials.count()
persons_c = persons.count()
articles_c = articles.count()
result_list = sorted(
chain(films, serials, persons, articles),
key=attrgetter('id'),
reverse=False)
result_list_c = films_c + serials_c + persons_c + articles_c
paginator = Paginator(result_list, per_page=10)
try:
result_list = paginator.page(page)
except PageNotAnInteger:
result_list = paginator.page(1)
except EmptyPage:
result_list = paginator(paginator.num_pages)
if request.user.is_authenticated():
add_film_id = request.GET.get('add_film_id', None)
del_film_id = request.GET.get('del_film_id', None)
add_film_watchlist = request.GET.get('add_film_watchlist', None)
del_film_watchlist = request.GET.get('del_film_watchlist', None)
add_serial_id = request.GET.get('add_serial_id', None)
del_serial_id = request.GET.get('del_serial_id', None)
add_serial_watchlist = request.GET.get('add_serial_watchlist', None)
del_serial_watchlist = request.GET.get('del_serial_watchlist', None)
rate = request.GET.get('rate', None)
activ_user = get_object_or_404(User, username=request.user)
if request.method == 'GET':
if add_film_id is not None and rate is not None:
film = get_object_or_404(Film, id=add_film_id)
if FilmRating.objects.filter(user=activ_user, film=film).exists():
FilmRating.objects.filter(user=activ_user, film=film).update(rate=rate)
else:
FilmRating.objects.create(user=activ_user, film=film, rate=rate)
if del_film_id is not None and rate is not None:
film = get_object_or_404(Film, id=del_film_id)
FilmRating.objects.filter(user=activ_user, film=film, rate=rate).delete()
if add_film_watchlist is not None:
film = get_object_or_404(Film, id=add_film_watchlist)
if FilmWatchlist.objects.filter(user=activ_user, film=film).exists():
FilmWatchlist.objects.filter(user=activ_user, film=film).update()
else:
FilmWatchlist.objects.create(user=activ_user, film=film)
if del_film_watchlist is not None:
film = get_object_or_404(Film, id=del_film_watchlist)
FilmWatchlist.objects.filter(user=activ_user, film=film).delete()
if add_serial_id is not None and rate is not None:
serial = get_object_or_404(Serial, id=add_serial_id)
if SerialRating.objects.filter(user=activ_user, serial=serial).exists():
SerialRating.objects.filter(user=activ_user, serial=serial).update(rate=rate)
else:
SerialRating.objects.create(user=activ_user, serial=serial, rate=rate)
if del_serial_id is not None and rate is not None:
serial = get_object_or_404(Serial, id=del_serial_id)
SerialRating.objects.filter(user=activ_user, serial=serial, rate=rate).delete()
if add_serial_watchlist is not None:
serial = get_object_or_404(Serial, id=add_serial_watchlist)
if SerialWatchlist.objects.filter(user=activ_user, serial=serial).exists():
SerialWatchlist.objects.filter(user=activ_user, serial=serial).update()
else:
SerialWatchlist.objects.create(user=activ_user, serial=serial)
if del_serial_watchlist is not None:
serial = get_object_or_404(Serial, id=del_serial_watchlist)
SerialWatchlist.objects.filter(user=activ_user, serial=serial).delete()
filmrating = FilmRating.objects.filter(user=activ_user)
f_id = filmrating.values_list('film__id', flat=True)
watchlistfilm = FilmWatchlist.objects.filter(user=activ_user)
watchlist_film_id = watchlistfilm.values_list('film__id', flat=True)
serialrating = SerialRating.objects.filter(user=activ_user)
s_id = serialrating.values_list('serial__id', flat=True)
watchlistserial = SerialWatchlist.objects.filter(user=activ_user)
watchlist_serial_id = watchlistserial.values_list('serial__id', flat=True)
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list': result_list,
'result_list_c': result_list_c,
'f_id': f_id,
'watchlist_film_id': watchlist_film_id,
'filmrating': filmrating,
's_id': s_id,
'watchlist_serial_id': watchlist_serial_id,
'serialrating': serialrating,
'latest_article': latest_article,
}
else:
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list': result_list,
'result_list_c': result_list_c,
'latest_article': latest_article,
}
return render(request, 'list.html', context)
def film_list(request):
films = Film.objects.get_queryset().annotate(
average_score=Coalesce(Round(Avg('filmrating__rate')), 0),
votes=Count('filmrating__user', distinct=True))
serials = Serial.objects.get_queryset().order_by('id').annotate(
average_score=Coalesce(Round(Avg('serialrating__rate')), 0),
votes=Count('serialrating__user', distinct=True))
persons = Person.objects.get_queryset().order_by('id')
articles = Article.objects.get_queryset().order_by('id')
latest_article = articles.order_by('-created_date').first()
keywords = request.GET.get('q')
page = request.GET.get('page')
if keywords:
films = films.filter(
Q(title__icontains=keywords)
)
serials = serials.filter(
Q(title__icontains=keywords)
)
for word in keywords.split():
persons = persons.filter(
Q(first_name__icontains=word)|
Q(last_name__icontains=word)
)
articles = articles.filter(
Q(title__icontains=keywords)
)
films_c = films.count()
serials_c = serials.count()
persons_c = persons.count()
articles_c = articles.count()
result_list_c = films_c + serials_c + persons_c + articles_c
paginator = Paginator(films, per_page=10)
try:
films = paginator.page(page)
except PageNotAnInteger:
films = paginator.page(1)
except EmptyPage:
films = paginator(paginator.num_pages)
if request.user.is_authenticated():
add_film_id = request.GET.get('add_film_id', None)
del_film_id = request.GET.get('del_film_id', None)
add_watchlist = request.GET.get('add_watchlist', None)
del_watchlist = request.GET.get('del_watchlist', None)
rate = request.GET.get('rate', None)
activ_user = get_object_or_404(User, username=request.user)
if request.method == 'GET':
if add_film_id is not None and rate is not None:
film = get_object_or_404(Film, id=add_film_id)
if FilmRating.objects.filter(user=activ_user, film=film).exists():
FilmRating.objects.filter(user=activ_user, film=film).update(rate=rate)
else:
FilmRating.objects.create(user=activ_user, film=film, rate=rate)
if del_film_id is not None and rate is not None:
film = get_object_or_404(Film, id=del_film_id)
FilmRating.objects.filter(user=activ_user, film=film, rate=rate).delete()
if add_watchlist is not None:
film = get_object_or_404(Film, id=add_watchlist)
if FilmWatchlist.objects.filter(user=activ_user, film=film).exists():
FilmWatchlist.objects.filter(user=activ_user, film=film).update()
else:
FilmWatchlist.objects.create(user=activ_user, film=film)
if del_watchlist is not None:
film = get_object_or_404(Film, id=del_watchlist)
FilmWatchlist.objects.filter(user=activ_user, film=film).delete()
filmrating = FilmRating.objects.filter(user=activ_user)
f_id = filmrating.values_list('film__id', flat=True)
watchlist = FilmWatchlist.objects.filter(user=activ_user)
watchlist_id = watchlist.values_list('film__id', flat=True)
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list_c': result_list_c,
'f_id': f_id,
'filmrating': filmrating,
'watchlist_id': watchlist_id,
'latest_article': latest_article,
}
else:
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list_c': result_list_c,
'latest_article': latest_article,
}
return render(request, 'film_list.html', context)
def serial_list(request):
films = Film.objects.get_queryset().annotate(
average_score=Coalesce(Round(Avg('filmrating__rate')), 0),
votes=Count('filmrating__user', distinct=True))
serials = Serial.objects.get_queryset().order_by('id').annotate(
average_score=Coalesce(Round(Avg('serialrating__rate')), 0),
votes=Count('serialrating__user', distinct=True))
persons = Person.objects.get_queryset().order_by('id')
articles = Article.objects.get_queryset().order_by('id')
latest_article = articles.order_by('-created_date').first()
keywords = request.GET.get('q')
page = request.GET.get('page')
if keywords:
films = films.filter(
Q(title__icontains=keywords)
)
serials = serials.filter(
Q(title__icontains=keywords)
)
for word in keywords.split():
persons = persons.filter(
Q(first_name__icontains=word)|
Q(last_name__icontains=word)
)
articles = articles.filter(
Q(title__icontains=keywords)
)
films_c = films.count()
serials_c = serials.count()
persons_c = persons.count()
articles_c = articles.count()
result_list_c = films_c + serials_c + persons_c + articles_c
paginator = Paginator(serials, per_page=10)
try:
serials = paginator.page(page)
except PageNotAnInteger:
serials = paginator.page(1)
except EmptyPage:
serials = paginator(paginator.num_pages)
if request.user.is_authenticated():
add_serial_id = request.GET.get('add_serial_id', None)
del_serial_id = request.GET.get('del_serial_id', None)
add_watchlist = request.GET.get('add_watchlist', None)
del_watchlist = request.GET.get('del_watchlist', None)
rate = request.GET.get('rate', None)
activ_user = get_object_or_404(User, username=request.user)
if request.method == 'GET':
if add_serial_id is not None and rate is not None:
serial = get_object_or_404(Serial, id=add_serial_id)
if SerialRating.objects.filter(user=activ_user, serial=serial).exists():
SerialRating.objects.filter(user=activ_user, serial=serial).update(rate=rate)
else:
SerialRating.objects.create(user=activ_user, serial=serial, rate=rate)
if del_serial_id is not None and rate is not None:
serial = get_object_or_404(Serial, id=del_serial_id)
SerialRating.objects.filter(user=activ_user, serial=serial, rate=rate).delete()
if add_watchlist is not None:
serial = get_object_or_404(Serial, id=add_watchlist)
if SerialWatchlist.objects.filter(user=activ_user, serial=serial).exists():
SerialWatchlist.objects.filter(user=activ_user, serial=serial).update()
else:
SerialWatchlist.objects.create(user=activ_user, serial=serial)
if del_watchlist is not None:
serial = get_object_or_404(Serial, id=del_watchlist)
SerialWatchlist.objects.filter(user=activ_user, serial=serial).delete()
serialrating = SerialRating.objects.filter(user=activ_user)
s_id = serialrating.values_list('serial__id', flat=True)
watchlist = SerialWatchlist.objects.filter(user=activ_user)
watchlist_id = watchlist.values_list('serial__id', flat=True)
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list_c': result_list_c,
's_id': s_id,
'serialrating': serialrating,
'watchlist_id': watchlist_id,
'latest_article': latest_article,
}
else:
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list_c': result_list_c,
'latest_article': latest_article,
}
return render(request, 'serial_list.html', context)
def person_list(request):
films = Film.objects.get_queryset().annotate(
average_score=Coalesce(Round(Avg('filmrating__rate')), 0),
votes=Count('filmrating__user', distinct=True))
serials = Serial.objects.get_queryset().order_by('id').annotate(
average_score=Coalesce(Round(Avg('serialrating__rate')), 0),
votes=Count('serialrating__user', distinct=True))
persons = Person.objects.get_queryset().order_by('id')
articles = Article.objects.get_queryset().order_by('id')
latest_article = articles.order_by('-created_date').first()
keywords = request.GET.get('q')
page = request.GET.get('page')
if keywords:
films = films.filter(
Q(title__icontains=keywords)
)
serials = serials.filter(
Q(title__icontains=keywords)
)
for word in keywords.split():
persons = persons.filter(
Q(first_name__icontains=word)|
Q(last_name__icontains=word)
)
articles = articles.filter(
Q(title__icontains=keywords)
)
films_c = films.count()
serials_c = serials.count()
persons_c = persons.count()
articles_c = articles.count()
result_list_c = films_c + serials_c + persons_c + articles_c
paginator = Paginator(persons, per_page=10)
try:
persons = paginator.page(page)
except PageNotAnInteger:
persons = paginator.page(1)
except EmptyPage:
persons = paginator(paginator.num_pages)
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list_c': result_list_c,
'latest_article': latest_article,
}
return render(request, 'person_list.html', context)
def article_list(request):
films = Film.objects.get_queryset().annotate(
average_score=Coalesce(Round(Avg('filmrating__rate')), 0),
votes=Count('filmrating__user', distinct=True))
serials = Serial.objects.get_queryset().order_by('id').annotate(
average_score=Coalesce(Round(Avg('serialrating__rate')), 0),
votes=Count('serialrating__user', distinct=True))
persons = Person.objects.get_queryset().order_by('id')
articles = Article.objects.get_queryset().order_by('id')
latest_article = articles.order_by('-created_date').first()
keywords = request.GET.get('q')
page = request.GET.get('page')
if keywords:
films = films.filter(
Q(title__icontains=keywords)
)
serials = serials.filter(
Q(title__icontains=keywords)
)
for word in keywords.split():
persons = persons.filter(
Q(first_name__icontains=word)|
Q(last_name__icontains=word)
)
articles = articles.filter(
Q(title__icontains=keywords)
)
films_c = films.count()
serials_c = serials.count()
persons_c = persons.count()
articles_c = articles.count()
result_list_c = films_c + serials_c + persons_c + articles_c
paginator = Paginator(articles, per_page=10)
try:
articles = paginator.page(page)
except PageNotAnInteger:
articles = paginator.page(1)
except EmptyPage:
articles = paginator(paginator.num_pages)
context = {
'serials': serials,
'films': films,
'persons': persons,
'articles': articles,
'serials_c': serials_c,
'films_c': films_c,
'persons_c': persons_c,
'articles_c': articles_c,
'result_list_c': result_list_c,
'latest_article': latest_article,
}
return render(request, 'article_list.html', context)
| 38.238004
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| 19,922
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| 0.844087
| 0.844087
| 0
| 0.005916
| 0.270354
| 19,922
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| 98
| 38.238004
| 0.803316
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| 0.001456
| 0
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| 0.011211
| false
| 0
| 0.022422
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| 0.05157
| 0
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| 0
| null | 0
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0
| 7
|
a4c14278831394ab70877398124500b7ced6d1f0
| 57,208
|
py
|
Python
|
contentos_sdk/grpc_pb2/prototype/operation_pb2.py
|
brickgao/cos-python-sdk
|
52d22553e83d0be5c73e8d71a63417e275a32c8e
|
[
"MIT"
] | null | null | null |
contentos_sdk/grpc_pb2/prototype/operation_pb2.py
|
brickgao/cos-python-sdk
|
52d22553e83d0be5c73e8d71a63417e275a32c8e
|
[
"MIT"
] | null | null | null |
contentos_sdk/grpc_pb2/prototype/operation_pb2.py
|
brickgao/cos-python-sdk
|
52d22553e83d0be5c73e8d71a63417e275a32c8e
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: prototype/operation.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from contentos_sdk.grpc_pb2.prototype import type_pb2 as prototype_dot_type__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='prototype/operation.proto',
package='prototype',
syntax='proto3',
serialized_options=_b('\n\"io.contentos.android.sdk.prototypeZ*github.com/coschain/contentos-go/prototype'),
serialized_pb=_b('\n\x19prototype/operation.proto\x12\tprototype\x1a\x14prototype/type.proto\"\xd9\x01\n\x18\x61\x63\x63ount_create_operation\x12\x1c\n\x03\x66\x65\x65\x18\x01 \x01(\x0b\x32\x0f.prototype.coin\x12(\n\x07\x63reator\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x31\n\x10new_account_name\x18\x03 \x01(\x0b\x32\x17.prototype.account_name\x12+\n\x07pub_key\x18\x04 \x01(\x0b\x32\x1a.prototype.public_key_type\x12\x15\n\rjson_metadata\x18\x05 \x01(\t\"o\n\x18\x61\x63\x63ount_update_operation\x12&\n\x05owner\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12+\n\x07pub_key\x18\x02 \x01(\x0b\x32\x1a.prototype.public_key_type\"\x8f\x01\n\x12transfer_operation\x12%\n\x04\x66rom\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12#\n\x02to\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x1f\n\x06\x61mount\x18\x03 \x01(\x0b\x32\x0f.prototype.coin\x12\x0c\n\x04memo\x18\x04 \x01(\t\"\x97\x01\n\x1atransfer_to_vest_operation\x12%\n\x04\x66rom\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12#\n\x02to\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x1f\n\x06\x61mount\x18\x03 \x01(\x0b\x32\x0f.prototype.coin\x12\x0c\n\x04memo\x18\x04 \x01(\t\"I\n\x0evote_operation\x12&\n\x05voter\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\x0f\n\x03idx\x18\x02 \x01(\x04\x42\x02\x30\x01\"\xbd\x01\n\x15\x62p_register_operation\x12&\n\x05owner\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\x0b\n\x03url\x18\x02 \x01(\t\x12\x0c\n\x04\x64\x65sc\x18\x03 \x01(\t\x12\x35\n\x11\x62lock_signing_key\x18\x04 \x01(\x0b\x32\x1a.prototype.public_key_type\x12*\n\x05props\x18\x05 \x01(\x0b\x32\x1b.prototype.chain_properties\"i\n\x13\x62p_update_operation\x12&\n\x05owner\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12*\n\x05props\x18\x02 \x01(\x0b\x32\x1b.prototype.chain_properties\"M\n\x13\x62p_enable_operation\x12&\n\x05owner\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\x0e\n\x06\x63\x61ncel\x18\x02 \x01(\x08\"|\n\x11\x62p_vote_operation\x12&\n\x05voter\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12/\n\x0e\x62lock_producer\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x0e\n\x06\x63\x61ncel\x18\x03 \x01(\x08\"x\n\x10\x66ollow_operation\x12(\n\x07\x61\x63\x63ount\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12*\n\tf_account\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x0e\n\x06\x63\x61ncel\x18\x03 \x01(\x08\"\xa4\x01\n\x19\x63ontract_deploy_operation\x12&\n\x05owner\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\x10\n\x08\x63ontract\x18\x02 \x01(\t\x12\x0b\n\x03\x61\x62i\x18\x03 \x01(\x0c\x12\x0c\n\x04\x63ode\x18\x04 \x01(\x0c\x12\x13\n\x0bupgradeable\x18\x05 \x01(\x08\x12\x0b\n\x03url\x18\x06 \x01(\t\x12\x10\n\x08\x64\x65scribe\x18\x07 \x01(\t\"\xbe\x01\n\x18\x63ontract_apply_operation\x12\'\n\x06\x63\x61ller\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12&\n\x05owner\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x10\n\x08\x63ontract\x18\x03 \x01(\t\x12\x0e\n\x06method\x18\x04 \x01(\t\x12\x0e\n\x06params\x18\x05 \x01(\t\x12\x1f\n\x06\x61mount\x18\x06 \x01(\x0b\x32\x0f.prototype.coin\"\xae\x02\n!internal_contract_apply_operation\x12,\n\x0b\x66rom_caller\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12+\n\nfrom_owner\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x15\n\rfrom_contract\x18\x03 \x01(\t\x12\x13\n\x0b\x66rom_method\x18\x04 \x01(\t\x12)\n\x08to_owner\x18\x05 \x01(\x0b\x32\x17.prototype.account_name\x12\x13\n\x0bto_contract\x18\x06 \x01(\t\x12\x11\n\tto_method\x18\x07 \x01(\t\x12\x0e\n\x06params\x18\x08 \x01(\x0c\x12\x1f\n\x06\x61mount\x18\t \x01(\x0b\x32\x0f.prototype.coin\"\xb2\x01\n\x0epost_operation\x12\x10\n\x04uuid\x18\x01 \x01(\x04\x42\x02\x30\x01\x12&\n\x05owner\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\r\n\x05title\x18\x03 \x01(\t\x12\x0f\n\x07\x63ontent\x18\x04 \x01(\t\x12\x0c\n\x04tags\x18\x05 \x03(\t\x12\x38\n\rbeneficiaries\x18\x06 \x03(\x0b\x32!.prototype.beneficiary_route_type\"\xaf\x01\n\x0freply_operation\x12\x10\n\x04uuid\x18\x01 \x01(\x04\x42\x02\x30\x01\x12&\n\x05owner\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x0f\n\x07\x63ontent\x18\x03 \x01(\t\x12\x17\n\x0bparent_uuid\x18\x04 \x01(\x04\x42\x02\x30\x01\x12\x38\n\rbeneficiaries\x18\x06 \x03(\x0b\x32!.prototype.beneficiary_route_type\"`\n\x16\x63onvert_vest_operation\x12%\n\x04\x66rom\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\x1f\n\x06\x61mount\x18\x02 \x01(\x0b\x32\x0f.prototype.vest\"~\n\x0fstake_operation\x12%\n\x04\x66rom\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12#\n\x02to\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x1f\n\x06\x61mount\x18\x03 \x01(\x0b\x32\x0f.prototype.coin\"\x89\x01\n\x12un_stake_operation\x12)\n\x08\x63reditor\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\'\n\x06\x64\x65\x62tor\x18\x02 \x01(\x0b\x32\x17.prototype.account_name\x12\x1f\n\x06\x61mount\x18\x03 \x01(\x0b\x32\x0f.prototype.coin\"S\n\x18\x61\x63quire_ticket_operation\x12(\n\x07\x61\x63\x63ount\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\r\n\x05\x63ount\x18\x02 \x01(\x04\"d\n\x18vote_by_ticket_operation\x12(\n\x07\x61\x63\x63ount\x18\x01 \x01(\x0b\x32\x17.prototype.account_name\x12\x0f\n\x03idx\x18\x02 \x01(\x04\x42\x02\x30\x01\x12\r\n\x05\x63ount\x18\x03 \x01(\x04\x42P\n\"io.contentos.android.sdk.prototypeZ*github.com/coschain/contentos-go/prototypeb\x06proto3')
,
dependencies=[prototype_dot_type__pb2.DESCRIPTOR,])
_ACCOUNT_CREATE_OPERATION = _descriptor.Descriptor(
name='account_create_operation',
full_name='prototype.account_create_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='fee', full_name='prototype.account_create_operation.fee', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='creator', full_name='prototype.account_create_operation.creator', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='new_account_name', full_name='prototype.account_create_operation.new_account_name', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='pub_key', full_name='prototype.account_create_operation.pub_key', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='json_metadata', full_name='prototype.account_create_operation.json_metadata', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=63,
serialized_end=280,
)
_ACCOUNT_UPDATE_OPERATION = _descriptor.Descriptor(
name='account_update_operation',
full_name='prototype.account_update_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.account_update_operation.owner', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='pub_key', full_name='prototype.account_update_operation.pub_key', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=282,
serialized_end=393,
)
_TRANSFER_OPERATION = _descriptor.Descriptor(
name='transfer_operation',
full_name='prototype.transfer_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='from', full_name='prototype.transfer_operation.from', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to', full_name='prototype.transfer_operation.to', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='amount', full_name='prototype.transfer_operation.amount', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='memo', full_name='prototype.transfer_operation.memo', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=396,
serialized_end=539,
)
_TRANSFER_TO_VEST_OPERATION = _descriptor.Descriptor(
name='transfer_to_vest_operation',
full_name='prototype.transfer_to_vest_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='from', full_name='prototype.transfer_to_vest_operation.from', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to', full_name='prototype.transfer_to_vest_operation.to', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='amount', full_name='prototype.transfer_to_vest_operation.amount', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='memo', full_name='prototype.transfer_to_vest_operation.memo', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=542,
serialized_end=693,
)
_VOTE_OPERATION = _descriptor.Descriptor(
name='vote_operation',
full_name='prototype.vote_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='voter', full_name='prototype.vote_operation.voter', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='idx', full_name='prototype.vote_operation.idx', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=_b('0\001'), file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=695,
serialized_end=768,
)
_BP_REGISTER_OPERATION = _descriptor.Descriptor(
name='bp_register_operation',
full_name='prototype.bp_register_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.bp_register_operation.owner', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='url', full_name='prototype.bp_register_operation.url', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='desc', full_name='prototype.bp_register_operation.desc', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='block_signing_key', full_name='prototype.bp_register_operation.block_signing_key', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='props', full_name='prototype.bp_register_operation.props', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=771,
serialized_end=960,
)
_BP_UPDATE_OPERATION = _descriptor.Descriptor(
name='bp_update_operation',
full_name='prototype.bp_update_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.bp_update_operation.owner', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='props', full_name='prototype.bp_update_operation.props', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=962,
serialized_end=1067,
)
_BP_ENABLE_OPERATION = _descriptor.Descriptor(
name='bp_enable_operation',
full_name='prototype.bp_enable_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.bp_enable_operation.owner', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='cancel', full_name='prototype.bp_enable_operation.cancel', index=1,
number=2, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1069,
serialized_end=1146,
)
_BP_VOTE_OPERATION = _descriptor.Descriptor(
name='bp_vote_operation',
full_name='prototype.bp_vote_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='voter', full_name='prototype.bp_vote_operation.voter', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='block_producer', full_name='prototype.bp_vote_operation.block_producer', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='cancel', full_name='prototype.bp_vote_operation.cancel', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1148,
serialized_end=1272,
)
_FOLLOW_OPERATION = _descriptor.Descriptor(
name='follow_operation',
full_name='prototype.follow_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='account', full_name='prototype.follow_operation.account', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='f_account', full_name='prototype.follow_operation.f_account', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='cancel', full_name='prototype.follow_operation.cancel', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1274,
serialized_end=1394,
)
_CONTRACT_DEPLOY_OPERATION = _descriptor.Descriptor(
name='contract_deploy_operation',
full_name='prototype.contract_deploy_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.contract_deploy_operation.owner', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='contract', full_name='prototype.contract_deploy_operation.contract', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='abi', full_name='prototype.contract_deploy_operation.abi', index=2,
number=3, type=12, cpp_type=9, label=1,
has_default_value=False, default_value=_b(""),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='code', full_name='prototype.contract_deploy_operation.code', index=3,
number=4, type=12, cpp_type=9, label=1,
has_default_value=False, default_value=_b(""),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='upgradeable', full_name='prototype.contract_deploy_operation.upgradeable', index=4,
number=5, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='url', full_name='prototype.contract_deploy_operation.url', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='describe', full_name='prototype.contract_deploy_operation.describe', index=6,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1397,
serialized_end=1561,
)
_CONTRACT_APPLY_OPERATION = _descriptor.Descriptor(
name='contract_apply_operation',
full_name='prototype.contract_apply_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='caller', full_name='prototype.contract_apply_operation.caller', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.contract_apply_operation.owner', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='contract', full_name='prototype.contract_apply_operation.contract', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='method', full_name='prototype.contract_apply_operation.method', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='params', full_name='prototype.contract_apply_operation.params', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='amount', full_name='prototype.contract_apply_operation.amount', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1564,
serialized_end=1754,
)
_INTERNAL_CONTRACT_APPLY_OPERATION = _descriptor.Descriptor(
name='internal_contract_apply_operation',
full_name='prototype.internal_contract_apply_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='from_caller', full_name='prototype.internal_contract_apply_operation.from_caller', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='from_owner', full_name='prototype.internal_contract_apply_operation.from_owner', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='from_contract', full_name='prototype.internal_contract_apply_operation.from_contract', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='from_method', full_name='prototype.internal_contract_apply_operation.from_method', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to_owner', full_name='prototype.internal_contract_apply_operation.to_owner', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to_contract', full_name='prototype.internal_contract_apply_operation.to_contract', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to_method', full_name='prototype.internal_contract_apply_operation.to_method', index=6,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='params', full_name='prototype.internal_contract_apply_operation.params', index=7,
number=8, type=12, cpp_type=9, label=1,
has_default_value=False, default_value=_b(""),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='amount', full_name='prototype.internal_contract_apply_operation.amount', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1757,
serialized_end=2059,
)
_POST_OPERATION = _descriptor.Descriptor(
name='post_operation',
full_name='prototype.post_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='uuid', full_name='prototype.post_operation.uuid', index=0,
number=1, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=_b('0\001'), file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.post_operation.owner', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='title', full_name='prototype.post_operation.title', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='content', full_name='prototype.post_operation.content', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tags', full_name='prototype.post_operation.tags', index=4,
number=5, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='beneficiaries', full_name='prototype.post_operation.beneficiaries', index=5,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2062,
serialized_end=2240,
)
_REPLY_OPERATION = _descriptor.Descriptor(
name='reply_operation',
full_name='prototype.reply_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='uuid', full_name='prototype.reply_operation.uuid', index=0,
number=1, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=_b('0\001'), file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='owner', full_name='prototype.reply_operation.owner', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='content', full_name='prototype.reply_operation.content', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='parent_uuid', full_name='prototype.reply_operation.parent_uuid', index=3,
number=4, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=_b('0\001'), file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='beneficiaries', full_name='prototype.reply_operation.beneficiaries', index=4,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2243,
serialized_end=2418,
)
_CONVERT_VEST_OPERATION = _descriptor.Descriptor(
name='convert_vest_operation',
full_name='prototype.convert_vest_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='from', full_name='prototype.convert_vest_operation.from', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='amount', full_name='prototype.convert_vest_operation.amount', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2420,
serialized_end=2516,
)
_STAKE_OPERATION = _descriptor.Descriptor(
name='stake_operation',
full_name='prototype.stake_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='from', full_name='prototype.stake_operation.from', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to', full_name='prototype.stake_operation.to', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='amount', full_name='prototype.stake_operation.amount', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2518,
serialized_end=2644,
)
_UN_STAKE_OPERATION = _descriptor.Descriptor(
name='un_stake_operation',
full_name='prototype.un_stake_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='creditor', full_name='prototype.un_stake_operation.creditor', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='debtor', full_name='prototype.un_stake_operation.debtor', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='amount', full_name='prototype.un_stake_operation.amount', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2647,
serialized_end=2784,
)
_ACQUIRE_TICKET_OPERATION = _descriptor.Descriptor(
name='acquire_ticket_operation',
full_name='prototype.acquire_ticket_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='account', full_name='prototype.acquire_ticket_operation.account', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='count', full_name='prototype.acquire_ticket_operation.count', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2786,
serialized_end=2869,
)
_VOTE_BY_TICKET_OPERATION = _descriptor.Descriptor(
name='vote_by_ticket_operation',
full_name='prototype.vote_by_ticket_operation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='account', full_name='prototype.vote_by_ticket_operation.account', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='idx', full_name='prototype.vote_by_ticket_operation.idx', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=_b('0\001'), file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='count', full_name='prototype.vote_by_ticket_operation.count', index=2,
number=3, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2871,
serialized_end=2971,
)
_ACCOUNT_CREATE_OPERATION.fields_by_name['fee'].message_type = prototype_dot_type__pb2._COIN
_ACCOUNT_CREATE_OPERATION.fields_by_name['creator'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_ACCOUNT_CREATE_OPERATION.fields_by_name['new_account_name'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_ACCOUNT_CREATE_OPERATION.fields_by_name['pub_key'].message_type = prototype_dot_type__pb2._PUBLIC_KEY_TYPE
_ACCOUNT_UPDATE_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_ACCOUNT_UPDATE_OPERATION.fields_by_name['pub_key'].message_type = prototype_dot_type__pb2._PUBLIC_KEY_TYPE
_TRANSFER_OPERATION.fields_by_name['from'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_TRANSFER_OPERATION.fields_by_name['to'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_TRANSFER_OPERATION.fields_by_name['amount'].message_type = prototype_dot_type__pb2._COIN
_TRANSFER_TO_VEST_OPERATION.fields_by_name['from'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_TRANSFER_TO_VEST_OPERATION.fields_by_name['to'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_TRANSFER_TO_VEST_OPERATION.fields_by_name['amount'].message_type = prototype_dot_type__pb2._COIN
_VOTE_OPERATION.fields_by_name['voter'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_BP_REGISTER_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_BP_REGISTER_OPERATION.fields_by_name['block_signing_key'].message_type = prototype_dot_type__pb2._PUBLIC_KEY_TYPE
_BP_REGISTER_OPERATION.fields_by_name['props'].message_type = prototype_dot_type__pb2._CHAIN_PROPERTIES
_BP_UPDATE_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_BP_UPDATE_OPERATION.fields_by_name['props'].message_type = prototype_dot_type__pb2._CHAIN_PROPERTIES
_BP_ENABLE_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_BP_VOTE_OPERATION.fields_by_name['voter'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_BP_VOTE_OPERATION.fields_by_name['block_producer'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_FOLLOW_OPERATION.fields_by_name['account'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_FOLLOW_OPERATION.fields_by_name['f_account'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_CONTRACT_DEPLOY_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_CONTRACT_APPLY_OPERATION.fields_by_name['caller'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_CONTRACT_APPLY_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_CONTRACT_APPLY_OPERATION.fields_by_name['amount'].message_type = prototype_dot_type__pb2._COIN
_INTERNAL_CONTRACT_APPLY_OPERATION.fields_by_name['from_caller'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_INTERNAL_CONTRACT_APPLY_OPERATION.fields_by_name['from_owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_INTERNAL_CONTRACT_APPLY_OPERATION.fields_by_name['to_owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_INTERNAL_CONTRACT_APPLY_OPERATION.fields_by_name['amount'].message_type = prototype_dot_type__pb2._COIN
_POST_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_POST_OPERATION.fields_by_name['beneficiaries'].message_type = prototype_dot_type__pb2._BENEFICIARY_ROUTE_TYPE
_REPLY_OPERATION.fields_by_name['owner'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_REPLY_OPERATION.fields_by_name['beneficiaries'].message_type = prototype_dot_type__pb2._BENEFICIARY_ROUTE_TYPE
_CONVERT_VEST_OPERATION.fields_by_name['from'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_CONVERT_VEST_OPERATION.fields_by_name['amount'].message_type = prototype_dot_type__pb2._VEST
_STAKE_OPERATION.fields_by_name['from'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_STAKE_OPERATION.fields_by_name['to'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_STAKE_OPERATION.fields_by_name['amount'].message_type = prototype_dot_type__pb2._COIN
_UN_STAKE_OPERATION.fields_by_name['creditor'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_UN_STAKE_OPERATION.fields_by_name['debtor'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_UN_STAKE_OPERATION.fields_by_name['amount'].message_type = prototype_dot_type__pb2._COIN
_ACQUIRE_TICKET_OPERATION.fields_by_name['account'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
_VOTE_BY_TICKET_OPERATION.fields_by_name['account'].message_type = prototype_dot_type__pb2._ACCOUNT_NAME
DESCRIPTOR.message_types_by_name['account_create_operation'] = _ACCOUNT_CREATE_OPERATION
DESCRIPTOR.message_types_by_name['account_update_operation'] = _ACCOUNT_UPDATE_OPERATION
DESCRIPTOR.message_types_by_name['transfer_operation'] = _TRANSFER_OPERATION
DESCRIPTOR.message_types_by_name['transfer_to_vest_operation'] = _TRANSFER_TO_VEST_OPERATION
DESCRIPTOR.message_types_by_name['vote_operation'] = _VOTE_OPERATION
DESCRIPTOR.message_types_by_name['bp_register_operation'] = _BP_REGISTER_OPERATION
DESCRIPTOR.message_types_by_name['bp_update_operation'] = _BP_UPDATE_OPERATION
DESCRIPTOR.message_types_by_name['bp_enable_operation'] = _BP_ENABLE_OPERATION
DESCRIPTOR.message_types_by_name['bp_vote_operation'] = _BP_VOTE_OPERATION
DESCRIPTOR.message_types_by_name['follow_operation'] = _FOLLOW_OPERATION
DESCRIPTOR.message_types_by_name['contract_deploy_operation'] = _CONTRACT_DEPLOY_OPERATION
DESCRIPTOR.message_types_by_name['contract_apply_operation'] = _CONTRACT_APPLY_OPERATION
DESCRIPTOR.message_types_by_name['internal_contract_apply_operation'] = _INTERNAL_CONTRACT_APPLY_OPERATION
DESCRIPTOR.message_types_by_name['post_operation'] = _POST_OPERATION
DESCRIPTOR.message_types_by_name['reply_operation'] = _REPLY_OPERATION
DESCRIPTOR.message_types_by_name['convert_vest_operation'] = _CONVERT_VEST_OPERATION
DESCRIPTOR.message_types_by_name['stake_operation'] = _STAKE_OPERATION
DESCRIPTOR.message_types_by_name['un_stake_operation'] = _UN_STAKE_OPERATION
DESCRIPTOR.message_types_by_name['acquire_ticket_operation'] = _ACQUIRE_TICKET_OPERATION
DESCRIPTOR.message_types_by_name['vote_by_ticket_operation'] = _VOTE_BY_TICKET_OPERATION
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
account_create_operation = _reflection.GeneratedProtocolMessageType('account_create_operation', (_message.Message,), {
'DESCRIPTOR' : _ACCOUNT_CREATE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.account_create_operation)
})
_sym_db.RegisterMessage(account_create_operation)
account_update_operation = _reflection.GeneratedProtocolMessageType('account_update_operation', (_message.Message,), {
'DESCRIPTOR' : _ACCOUNT_UPDATE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.account_update_operation)
})
_sym_db.RegisterMessage(account_update_operation)
transfer_operation = _reflection.GeneratedProtocolMessageType('transfer_operation', (_message.Message,), {
'DESCRIPTOR' : _TRANSFER_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.transfer_operation)
})
_sym_db.RegisterMessage(transfer_operation)
transfer_to_vest_operation = _reflection.GeneratedProtocolMessageType('transfer_to_vest_operation', (_message.Message,), {
'DESCRIPTOR' : _TRANSFER_TO_VEST_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.transfer_to_vest_operation)
})
_sym_db.RegisterMessage(transfer_to_vest_operation)
vote_operation = _reflection.GeneratedProtocolMessageType('vote_operation', (_message.Message,), {
'DESCRIPTOR' : _VOTE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.vote_operation)
})
_sym_db.RegisterMessage(vote_operation)
bp_register_operation = _reflection.GeneratedProtocolMessageType('bp_register_operation', (_message.Message,), {
'DESCRIPTOR' : _BP_REGISTER_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.bp_register_operation)
})
_sym_db.RegisterMessage(bp_register_operation)
bp_update_operation = _reflection.GeneratedProtocolMessageType('bp_update_operation', (_message.Message,), {
'DESCRIPTOR' : _BP_UPDATE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.bp_update_operation)
})
_sym_db.RegisterMessage(bp_update_operation)
bp_enable_operation = _reflection.GeneratedProtocolMessageType('bp_enable_operation', (_message.Message,), {
'DESCRIPTOR' : _BP_ENABLE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.bp_enable_operation)
})
_sym_db.RegisterMessage(bp_enable_operation)
bp_vote_operation = _reflection.GeneratedProtocolMessageType('bp_vote_operation', (_message.Message,), {
'DESCRIPTOR' : _BP_VOTE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.bp_vote_operation)
})
_sym_db.RegisterMessage(bp_vote_operation)
follow_operation = _reflection.GeneratedProtocolMessageType('follow_operation', (_message.Message,), {
'DESCRIPTOR' : _FOLLOW_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.follow_operation)
})
_sym_db.RegisterMessage(follow_operation)
contract_deploy_operation = _reflection.GeneratedProtocolMessageType('contract_deploy_operation', (_message.Message,), {
'DESCRIPTOR' : _CONTRACT_DEPLOY_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.contract_deploy_operation)
})
_sym_db.RegisterMessage(contract_deploy_operation)
contract_apply_operation = _reflection.GeneratedProtocolMessageType('contract_apply_operation', (_message.Message,), {
'DESCRIPTOR' : _CONTRACT_APPLY_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.contract_apply_operation)
})
_sym_db.RegisterMessage(contract_apply_operation)
internal_contract_apply_operation = _reflection.GeneratedProtocolMessageType('internal_contract_apply_operation', (_message.Message,), {
'DESCRIPTOR' : _INTERNAL_CONTRACT_APPLY_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.internal_contract_apply_operation)
})
_sym_db.RegisterMessage(internal_contract_apply_operation)
post_operation = _reflection.GeneratedProtocolMessageType('post_operation', (_message.Message,), {
'DESCRIPTOR' : _POST_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.post_operation)
})
_sym_db.RegisterMessage(post_operation)
reply_operation = _reflection.GeneratedProtocolMessageType('reply_operation', (_message.Message,), {
'DESCRIPTOR' : _REPLY_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.reply_operation)
})
_sym_db.RegisterMessage(reply_operation)
convert_vest_operation = _reflection.GeneratedProtocolMessageType('convert_vest_operation', (_message.Message,), {
'DESCRIPTOR' : _CONVERT_VEST_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.convert_vest_operation)
})
_sym_db.RegisterMessage(convert_vest_operation)
stake_operation = _reflection.GeneratedProtocolMessageType('stake_operation', (_message.Message,), {
'DESCRIPTOR' : _STAKE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.stake_operation)
})
_sym_db.RegisterMessage(stake_operation)
un_stake_operation = _reflection.GeneratedProtocolMessageType('un_stake_operation', (_message.Message,), {
'DESCRIPTOR' : _UN_STAKE_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.un_stake_operation)
})
_sym_db.RegisterMessage(un_stake_operation)
acquire_ticket_operation = _reflection.GeneratedProtocolMessageType('acquire_ticket_operation', (_message.Message,), {
'DESCRIPTOR' : _ACQUIRE_TICKET_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.acquire_ticket_operation)
})
_sym_db.RegisterMessage(acquire_ticket_operation)
vote_by_ticket_operation = _reflection.GeneratedProtocolMessageType('vote_by_ticket_operation', (_message.Message,), {
'DESCRIPTOR' : _VOTE_BY_TICKET_OPERATION,
'__module__' : 'prototype.operation_pb2'
# @@protoc_insertion_point(class_scope:prototype.vote_by_ticket_operation)
})
_sym_db.RegisterMessage(vote_by_ticket_operation)
DESCRIPTOR._options = None
_VOTE_OPERATION.fields_by_name['idx']._options = None
_POST_OPERATION.fields_by_name['uuid']._options = None
_REPLY_OPERATION.fields_by_name['uuid']._options = None
_REPLY_OPERATION.fields_by_name['parent_uuid']._options = None
_VOTE_BY_TICKET_OPERATION.fields_by_name['idx']._options = None
# @@protoc_insertion_point(module_scope)
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|
0
| 8
|
3543351501d53fccf93b6cb0ca7f21ec31839998
| 31,111
|
py
|
Python
|
swagger_client/api/topology_api.py
|
atlanticwave-sdx/sdx-lc-client
|
a442eb3efc327cd39b0d227329cef207ab1505e3
|
[
"Apache-2.0"
] | null | null | null |
swagger_client/api/topology_api.py
|
atlanticwave-sdx/sdx-lc-client
|
a442eb3efc327cd39b0d227329cef207ab1505e3
|
[
"Apache-2.0"
] | null | null | null |
swagger_client/api/topology_api.py
|
atlanticwave-sdx/sdx-lc-client
|
a442eb3efc327cd39b0d227329cef207ab1505e3
|
[
"Apache-2.0"
] | null | null | null |
# coding: utf-8
"""
SDX LC
You can find out more about Swagger at [http://swagger.io](http://swagger.io) or on [irc.freenode.net, #swagger](http://swagger.io/irc/). # noqa: E501
OpenAPI spec version: 1.0.0
Contact: yxin@renci.org
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from swagger_client.api_client import ApiClient
class TopologyApi(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
Ref: https://github.com/swagger-api/swagger-codegen
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def add_topology(self, body, **kwargs): # noqa: E501
"""Send a new topology to SDX-LC # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.add_topology(body, async_req=True)
>>> result = thread.get()
:param async_req bool
:param Topology body: placed for adding a new topology (required)
:return: Topology
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.add_topology_with_http_info(body, **kwargs) # noqa: E501
else:
(data) = self.add_topology_with_http_info(body, **kwargs) # noqa: E501
return data
def add_topology_with_http_info(self, body, **kwargs): # noqa: E501
"""Send a new topology to SDX-LC # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.add_topology_with_http_info(body, async_req=True)
>>> result = thread.get()
:param async_req bool
:param Topology body: placed for adding a new topology (required)
:return: Topology
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['body'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method add_topology" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'body' is set
if ('body' not in params or
params['body'] is None):
raise ValueError("Missing the required parameter `body` when calling `add_topology`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/topology', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Topology', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def delete_topology(self, topology_id, **kwargs): # noqa: E501
"""Deletes a topology # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_topology(topology_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to delete (required)
:param str api_key:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_topology_with_http_info(topology_id, **kwargs) # noqa: E501
else:
(data) = self.delete_topology_with_http_info(topology_id, **kwargs) # noqa: E501
return data
def delete_topology_with_http_info(self, topology_id, **kwargs): # noqa: E501
"""Deletes a topology # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_topology_with_http_info(topology_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to delete (required)
:param str api_key:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['topology_id', 'api_key'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method delete_topology" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'topology_id' is set
if ('topology_id' not in params or
params['topology_id'] is None):
raise ValueError("Missing the required parameter `topology_id` when calling `delete_topology`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
if 'topology_id' in params:
query_params.append(('topologyId', params['topology_id'])) # noqa: E501
header_params = {}
if 'api_key' in params:
header_params['api_key'] = params['api_key'] # noqa: E501
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = ['topology_auth'] # noqa: E501
return self.api_client.call_api(
'/topology', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def delete_topology_version(self, topology_id, version, **kwargs): # noqa: E501
"""Deletes a topology version # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_topology_version(topology_id, version, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to return (required)
:param int version: topology version to delete (required)
:param str api_key:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_topology_version_with_http_info(topology_id, version, **kwargs) # noqa: E501
else:
(data) = self.delete_topology_version_with_http_info(topology_id, version, **kwargs) # noqa: E501
return data
def delete_topology_version_with_http_info(self, topology_id, version, **kwargs): # noqa: E501
"""Deletes a topology version # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_topology_version_with_http_info(topology_id, version, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to return (required)
:param int version: topology version to delete (required)
:param str api_key:
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['topology_id', 'version', 'api_key'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method delete_topology_version" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'topology_id' is set
if ('topology_id' not in params or
params['topology_id'] is None):
raise ValueError("Missing the required parameter `topology_id` when calling `delete_topology_version`") # noqa: E501
# verify the required parameter 'version' is set
if ('version' not in params or
params['version'] is None):
raise ValueError("Missing the required parameter `version` when calling `delete_topology_version`") # noqa: E501
collection_formats = {}
path_params = {}
if 'version' in params:
path_params['version'] = params['version'] # noqa: E501
query_params = []
if 'topology_id' in params:
query_params.append(('topologyId', params['topology_id'])) # noqa: E501
header_params = {}
if 'api_key' in params:
header_params['api_key'] = params['api_key'] # noqa: E501
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = ['topology_auth'] # noqa: E501
return self.api_client.call_api(
'/topology/{version}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_topology(self, **kwargs): # noqa: E501
"""get an existing topology # noqa: E501
ID of the topology # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_topology(async_req=True)
>>> result = thread.get()
:param async_req bool
:return: str
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_topology_with_http_info(**kwargs) # noqa: E501
else:
(data) = self.get_topology_with_http_info(**kwargs) # noqa: E501
return data
def get_topology_with_http_info(self, **kwargs): # noqa: E501
"""get an existing topology # noqa: E501
ID of the topology # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_topology_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool
:return: str
If the method is called asynchronously,
returns the request thread.
"""
all_params = [] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_topology" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['text/plain']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/topology', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='str', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_topologyby_version(self, topology_id, version, **kwargs): # noqa: E501
"""Find topology by version # noqa: E501
Returns a single topology # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_topologyby_version(topology_id, version, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to return (required)
:param int version: version of topology to return (required)
:return: Topology
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_topologyby_version_with_http_info(topology_id, version, **kwargs) # noqa: E501
else:
(data) = self.get_topologyby_version_with_http_info(topology_id, version, **kwargs) # noqa: E501
return data
def get_topologyby_version_with_http_info(self, topology_id, version, **kwargs): # noqa: E501
"""Find topology by version # noqa: E501
Returns a single topology # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_topologyby_version_with_http_info(topology_id, version, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to return (required)
:param int version: version of topology to return (required)
:return: Topology
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['topology_id', 'version'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_topologyby_version" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'topology_id' is set
if ('topology_id' not in params or
params['topology_id'] is None):
raise ValueError("Missing the required parameter `topology_id` when calling `get_topologyby_version`") # noqa: E501
# verify the required parameter 'version' is set
if ('version' not in params or
params['version'] is None):
raise ValueError("Missing the required parameter `version` when calling `get_topologyby_version`") # noqa: E501
collection_formats = {}
path_params = {}
if 'version' in params:
path_params['version'] = params['version'] # noqa: E501
query_params = []
if 'topology_id' in params:
query_params.append(('topologyId', params['topology_id'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/topology/{version}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Topology', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def topology_version(self, topology_id, **kwargs): # noqa: E501
"""Finds topology version # noqa: E501
Topology version # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.topology_version(topology_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str topology_id: topology id (required)
:return: Topology
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.topology_version_with_http_info(topology_id, **kwargs) # noqa: E501
else:
(data) = self.topology_version_with_http_info(topology_id, **kwargs) # noqa: E501
return data
def topology_version_with_http_info(self, topology_id, **kwargs): # noqa: E501
"""Finds topology version # noqa: E501
Topology version # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.topology_version_with_http_info(topology_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str topology_id: topology id (required)
:return: Topology
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['topology_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method topology_version" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'topology_id' is set
if ('topology_id' not in params or
params['topology_id'] is None):
raise ValueError("Missing the required parameter `topology_id` when calling `topology_version`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
if 'topology_id' in params:
query_params.append(('topologyId', params['topology_id'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['topology_auth'] # noqa: E501
return self.api_client.call_api(
'/topology/version', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Topology', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def update_topology(self, body, **kwargs): # noqa: E501
"""Update an existing topology # noqa: E501
ID of topology that needs to be updated. \\\\ The topology update only updates the addition or deletion \\\\ of node, port, link. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_topology(body, async_req=True)
>>> result = thread.get()
:param async_req bool
:param Topology body: topology object that needs to be sent to the SDX LC (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.update_topology_with_http_info(body, **kwargs) # noqa: E501
else:
(data) = self.update_topology_with_http_info(body, **kwargs) # noqa: E501
return data
def update_topology_with_http_info(self, body, **kwargs): # noqa: E501
"""Update an existing topology # noqa: E501
ID of topology that needs to be updated. \\\\ The topology update only updates the addition or deletion \\\\ of node, port, link. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_topology_with_http_info(body, async_req=True)
>>> result = thread.get()
:param async_req bool
:param Topology body: topology object that needs to be sent to the SDX LC (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['body'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method update_topology" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'body' is set
if ('body' not in params or
params['body'] is None):
raise ValueError("Missing the required parameter `body` when calling `update_topology`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = [] # noqa: E501
return self.api_client.call_api(
'/topology', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def upload_file(self, topology_id, **kwargs): # noqa: E501
"""uploads an topology image # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.upload_file(topology_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to update (required)
:param Object body:
:return: ApiResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.upload_file_with_http_info(topology_id, **kwargs) # noqa: E501
else:
(data) = self.upload_file_with_http_info(topology_id, **kwargs) # noqa: E501
return data
def upload_file_with_http_info(self, topology_id, **kwargs): # noqa: E501
"""uploads an topology image # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.upload_file_with_http_info(topology_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param int topology_id: ID of topology to update (required)
:param Object body:
:return: ApiResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['topology_id', 'body'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method upload_file" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'topology_id' is set
if ('topology_id' not in params or
params['topology_id'] is None):
raise ValueError("Missing the required parameter `topology_id` when calling `upload_file`") # noqa: E501
collection_formats = {}
path_params = {}
if 'topology_id' in params:
path_params['topologyId'] = params['topology_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/octet-stream']) # noqa: E501
# Authentication setting
auth_settings = ['topology_auth'] # noqa: E501
return self.api_client.call_api(
'/topology/{topologyId}/uploadImage', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ApiResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
| 38.599256
| 156
| 0.605124
| 3,581
| 31,111
| 5.012008
| 0.054454
| 0.049031
| 0.024961
| 0.032093
| 0.963171
| 0.959494
| 0.955148
| 0.945565
| 0.93899
| 0.930577
| 0
| 0.015676
| 0.304908
| 31,111
| 805
| 157
| 38.647205
| 0.814289
| 0.324483
| 0
| 0.802752
| 0
| 0
| 0.182053
| 0.037682
| 0
| 0
| 0
| 0
| 0
| 1
| 0.038991
| false
| 0
| 0.009174
| 0
| 0.105505
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
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| 0
| 0
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| 1
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| 0
| null | 0
| 0
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| 0
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| 0
| 0
|
0
| 7
|
354893a92c067cbd31ebd43c27f967c89b9c730b
| 194
|
py
|
Python
|
djangotango/djangotango/views.py
|
meghaggarwal/Django-Blog
|
357667c028e0dd05cbf746a51969af35915aa748
|
[
"MIT"
] | null | null | null |
djangotango/djangotango/views.py
|
meghaggarwal/Django-Blog
|
357667c028e0dd05cbf746a51969af35915aa748
|
[
"MIT"
] | null | null | null |
djangotango/djangotango/views.py
|
meghaggarwal/Django-Blog
|
357667c028e0dd05cbf746a51969af35915aa748
|
[
"MIT"
] | null | null | null |
from django.http import HttpResponse
from django.shortcuts import render
def about(request):
return render(request, 'about.html')
def home(request):
return render(request, 'home.html')
| 19.4
| 38
| 0.757732
| 26
| 194
| 5.653846
| 0.5
| 0.136054
| 0.258503
| 0.353742
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.139175
| 194
| 10
| 39
| 19.4
| 0.88024
| 0
| 0
| 0
| 0
| 0
| 0.097436
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 7
|
1021c1899ae3389947d999b2de2180b977a1fd16
| 285
|
py
|
Python
|
great_expectations/render/renderer/content_block/__init__.py
|
RoyalTS/great_expectations
|
5ce4d499da2301d0c0497b243813a349837e95d7
|
[
"Apache-2.0"
] | null | null | null |
great_expectations/render/renderer/content_block/__init__.py
|
RoyalTS/great_expectations
|
5ce4d499da2301d0c0497b243813a349837e95d7
|
[
"Apache-2.0"
] | null | null | null |
great_expectations/render/renderer/content_block/__init__.py
|
RoyalTS/great_expectations
|
5ce4d499da2301d0c0497b243813a349837e95d7
|
[
"Apache-2.0"
] | 1
|
2022-02-10T04:20:37.000Z
|
2022-02-10T04:20:37.000Z
|
from .value_list_content_block import ValueListContentBlockRenderer
from .table_content_block import TableContentBlockRenderer
from .bullet_list_content_block import PrescriptiveBulletListContentBlockRenderer
from .exception_list_content_block import ExceptionListContentBlockRenderer
| 57
| 81
| 0.929825
| 27
| 285
| 9.407407
| 0.481481
| 0.188976
| 0.283465
| 0.259843
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.05614
| 285
| 4
| 82
| 71.25
| 0.944238
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
106458d58bceb4d004cd8b2ae426f11b5e07e240
| 21,836
|
py
|
Python
|
tests/testflows/extended_precision_data_types/tests/array_tuple_map.py
|
chalice19/ClickHouse
|
2f38e7bc5c2113935ab86260439bb543a1737291
|
[
"Apache-2.0"
] | 1
|
2022-02-27T15:21:20.000Z
|
2022-02-27T15:21:20.000Z
|
tests/testflows/extended_precision_data_types/tests/array_tuple_map.py
|
chalice19/ClickHouse
|
2f38e7bc5c2113935ab86260439bb543a1737291
|
[
"Apache-2.0"
] | 16
|
2022-02-14T15:53:29.000Z
|
2022-03-25T18:39:16.000Z
|
tests/testflows/extended_precision_data_types/tests/array_tuple_map.py
|
chalice19/ClickHouse
|
2f38e7bc5c2113935ab86260439bb543a1737291
|
[
"Apache-2.0"
] | null | null | null |
import uuid
from extended_precision_data_types.requirements import *
from extended_precision_data_types.common import *
def get_table_name():
return "table" + "_" + str(uuid.uuid1()).replace("-", "_")
@TestOutline(Suite)
@Requirements(
RQ_SRS_020_ClickHouse_Extended_Precision_Arrays_Int_Supported("1.0"),
RQ_SRS_020_ClickHouse_Extended_Precision_Arrays_Int_NotSupported("1.0"),
RQ_SRS_020_ClickHouse_Extended_Precision_Arrays_Dec_Supported("1.0"),
RQ_SRS_020_ClickHouse_Extended_Precision_Arrays_Dec_NotSupported("1.0"),
)
def array_func(self, data_type, node=None):
"""Check array functions with extended precision data types."""
if node is None:
node = self.context.node
for func in [
"arrayPopBack(",
"arrayPopFront(",
"arraySort(",
"arrayReverseSort(",
"arrayDistinct(",
"arrayEnumerate(",
"arrayEnumerateDense(",
"arrayEnumerateUniq(",
"arrayReverse(",
"reverse(",
"arrayFlatten(",
"arrayCompact(",
"arrayReduceInRanges('sum', [(1, 5)],",
"arrayMap(x -> (x + 2),",
"arrayFill(x -> x=3,",
"arrayReverseFill(x -> x=3,",
f"arrayConcat([{to_data_type(data_type,3)}, {to_data_type(data_type,2)}, {to_data_type(data_type,1)}],",
"arrayFilter(x -> x == 1, ",
]:
with Scenario(f"Inline - {data_type} - {func})"):
execute_query(
f"""
SELECT {func}array({to_data_type(data_type,3)}, {to_data_type(data_type,2)}, {to_data_type(data_type,1)}))
"""
)
with Scenario(f"Table - {data_type} - {func})"):
table_name = get_table_name()
table(name=table_name, data_type=f"Array({data_type})")
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in ["arraySplit((x, y) -> x=y, [0, 0, 0],"]:
with Scenario(f"Inline - {data_type} - {func})"):
execute_query(
f"SELECT {func}array({to_data_type(data_type,3)}, {to_data_type(data_type,2)},"
f"{to_data_type(data_type,1)}))"
)
with Scenario(f"Table - {data_type} - {func})"):
table_name = get_table_name()
table(name=table_name, data_type=f"Array(Array({data_type}))")
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in [f"arrayZip([{to_data_type(data_type,1)}],"]:
with Scenario(f"Inline - {data_type} - {func})"):
execute_query(f"SELECT {func}array({to_data_type(data_type,3)}))")
with Scenario(f"Table - {data_type} - {func})"):
table_name = get_table_name()
table(name=table_name, data_type=f"Array(Tuple({data_type}, {data_type}))")
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}array({to_data_type(data_type,1)}))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in [
"empty(",
"notEmpty(",
"length(",
"arrayCount(x -> x == 1, ",
"arrayUniq(",
"arrayJoin(",
"arrayExists(x -> x==1,",
"arrayAll(x -> x==1,",
"arrayMin(",
"arrayMax(",
"arraySum(",
"arrayAvg(",
"arrayReduce('max', ",
"arrayFirst(x -> x==3,",
"arrayFirstIndex(x -> x==3,",
f"hasAll([{to_data_type(data_type,3)}, {to_data_type(data_type,2)}, {to_data_type(data_type,1)}], ",
f"hasAny([{to_data_type(data_type,2)}, {to_data_type(data_type,1)}], ",
f"hasSubstr([{to_data_type(data_type,2)}, {to_data_type(data_type,1)}], ",
]:
if func in [
"arrayMin(",
"arrayMax(",
"arraySum(",
"arrayAvg(",
] and data_type in ["Decimal256(0)"]:
with Scenario(f"Inline - {data_type} - {func})"):
node.query(
f"SELECT {func}array({to_data_type(data_type,3)}, {to_data_type(data_type,2)}, {to_data_type(data_type,1)}))",
exitcode=44,
message="Exception:",
)
with Scenario(f"Table - {data_type} - {func})"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}))",
exitcode=44,
message="Exception:",
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
else:
with Scenario(f"Inline - {data_type} - {func})"):
execute_query(
f"SELECT {func}array({to_data_type(data_type,3)}, {to_data_type(data_type,2)}, {to_data_type(data_type,1)}))"
)
with Scenario(f"Table - {data_type} - {func})"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in ["arrayDifference(", "arrayCumSum(", "arrayCumSumNonNegative("]:
if data_type in ["Decimal256(0)"]:
exitcode = 44
else:
exitcode = 43
with Scenario(f"Inline - {data_type} - {func})"):
node.query(
f"SELECT {func}array({to_data_type(data_type,3)}, {to_data_type(data_type,2)}, {to_data_type(data_type,1)}))",
exitcode=exitcode,
message="Exception:",
)
with Scenario(f"Table - {data_type} - {func})"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}))",
exitcode=exitcode,
message="Exception:",
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in ["arrayElement"]:
with Scenario(f"Inline - {data_type} - {func}"):
execute_query(
f"""
SELECT {func}(array({to_data_type(data_type,3)}, {to_data_type(data_type,2)}, {to_data_type(data_type,1)}), 1)
"""
)
with Scenario(f"Table - {data_type} - {func}"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}(array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}), 1)"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in ["arrayPushBack", "arrayPushFront"]:
with Scenario(f"Inline - {data_type} - {func}"):
execute_query(
f"SELECT {func}(array({to_data_type(data_type,3)}, {to_data_type(data_type,2)},"
f"{to_data_type(data_type,1)}), {to_data_type(data_type,1)})"
)
with Scenario(f"Table - {data_type} - {func}"):
table_name = get_table_name()
table(name=table_name, data_type=f"Array({data_type})")
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}(array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}), {to_data_type(data_type,1)})"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in ["arrayResize", "arraySlice"]:
with Scenario(f"Inline - {data_type} - {func}"):
execute_query(
f"SELECT {func}(array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}), 1)"
)
with Scenario(f"Table - {data_type} - {func}"):
table_name = get_table_name()
table(name=table_name, data_type=f"Array({data_type})")
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}(array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}), 1)"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
for func in ["has", "indexOf", "countEqual"]:
with Scenario(f"Inline - {data_type} - {func}"):
execute_query(
f"SELECT {func}(array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}), NULL)"
)
with Scenario(f"Table - {data_type} - {func}"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into the table"):
node.query(
f"INSERT INTO {table_name} SELECT {func}(array({to_data_type(data_type,3)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,1)}), NULL)"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
@TestOutline(Suite)
@Requirements(
RQ_SRS_020_ClickHouse_Extended_Precision_Tuple("1.0"),
)
def tuple_func(self, data_type, node=None):
"""Check tuple functions with extended precision data types."""
if node is None:
node = self.context.node
with Scenario(f"Creating a tuple with {data_type}"):
node.query(
f"SELECT tuple({to_data_type(data_type,1)}, {to_data_type(data_type,1)}, {to_data_type(data_type,1)})"
)
with Scenario(f"Creating a tuple with {data_type} on a table"):
table_name = get_table_name()
table(
name=table_name, data_type=f"Tuple({data_type}, {data_type}, {data_type})"
)
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT tuple({to_data_type(data_type,1)},"
f"{to_data_type(data_type,1)}, {to_data_type(data_type,1)})"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
with Scenario(f"tupleElement with {data_type}"):
node.query(
f"SELECT tupleElement(({to_data_type(data_type,1)}, {to_data_type(data_type,1)}), 1)"
)
with Scenario(f"tupleElement with {data_type} on a table"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT tupleElement(({to_data_type(data_type,1)}, {to_data_type(data_type,1)}), 1)"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
with Scenario(f"untuple with {data_type}"):
node.query(f"SELECT untuple(({to_data_type(data_type,1)},))")
with Scenario(f"untuple with {data_type} on a table"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT untuple(({to_data_type(data_type,1)},))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
with Scenario(f"tupleHammingDistance with {data_type}"):
node.query(
f"SELECT tupleHammingDistance(({to_data_type(data_type,1)}, {to_data_type(data_type,1)}),"
f"({to_data_type(data_type,2)}, {to_data_type(data_type,2)}))"
)
with Scenario(f"tupleHammingDistance with {data_type} on a table"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT tupleHammingDistance(({to_data_type(data_type,1)},"
f"{to_data_type(data_type,1)}), ({to_data_type(data_type,2)}, {to_data_type(data_type,2)}))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
@TestOutline(Suite)
@Requirements(
RQ_SRS_020_ClickHouse_Extended_Precision_Map_Supported("1.0"),
RQ_SRS_020_ClickHouse_Extended_Precision_Map_NotSupported("1.0"),
)
def map_func(self, data_type, node=None):
"""Check Map functions with extended precision data types."""
if node is None:
node = self.context.node
with Scenario(f"Creating a map with {data_type}"):
node.query(
f"SELECT map('key1', {to_data_type(data_type,1)}, 'key2', {to_data_type(data_type,2)})"
)
with Scenario(f"Creating a map with {data_type} on a table"):
table_name = get_table_name()
table(name=table_name, data_type=f"Map(String, {data_type})")
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT map('key1', {to_data_type(data_type,1)}, 'key2', {to_data_type(data_type,2)})"
)
execute_query(f"SELECT * FROM {table_name}")
with Scenario(f"mapAdd with {data_type}"):
sql = (
f"SELECT mapAdd(([{to_data_type(data_type,1)}, {to_data_type(data_type,2)}],"
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}]),"
f"([{to_data_type(data_type,1)}, {to_data_type(data_type,2)}],"
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}]))"
)
if data_type.startswith("Decimal"):
node.query(sql, exitcode=43, message="Exception:")
else:
execute_query(sql)
with Scenario(f"mapAdd with {data_type} on a table"):
table_name = get_table_name()
table(
name=table_name, data_type=f"Tuple(Array({data_type}), Array({data_type}))"
)
with When("I insert the output into a table"):
sql = (
f"INSERT INTO {table_name} SELECT mapAdd(("
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}],"
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}]),"
f"([{to_data_type(data_type,1)}, {to_data_type(data_type,2)}],"
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}]))"
)
exitcode, message = 0, None
if data_type.startswith("Decimal"):
exitcode, message = 43, "Exception:"
node.query(sql, exitcode=exitcode, message=message)
execute_query(f"""SELECT * FROM {table_name} ORDER BY a ASC""")
with Scenario(f"mapSubtract with {data_type}"):
sql = (
f"SELECT mapSubtract(("
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}],"
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}]),"
f"([{to_data_type(data_type,1)}, {to_data_type(data_type,2)}],"
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}]))"
)
if data_type.startswith("Decimal"):
node.query(sql, exitcode=43, message="Exception:")
else:
execute_query(sql)
with Scenario(f"mapSubtract with {data_type} on a table"):
table_name = get_table_name()
table(
name=table_name, data_type=f"Tuple(Array({data_type}), Array({data_type}))"
)
with When("I insert the output into a table"):
sql = (
f"INSERT INTO {table_name} SELECT mapSubtract(([{to_data_type(data_type,1)},"
f"{to_data_type(data_type,2)}], [{to_data_type(data_type,1)},"
f"{to_data_type(data_type,2)}]), ([{to_data_type(data_type,1)},"
f"{to_data_type(data_type,2)}], [{to_data_type(data_type,1)}, {to_data_type(data_type,2)}]))"
)
exitcode, message = 0, None
if data_type.startswith("Decimal"):
exitcode, message = 43, "Exception:"
node.query(sql, exitcode=exitcode, message=message)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
with Scenario(f"mapPopulateSeries with {data_type}"):
sql = (
f"SELECT mapPopulateSeries([1,2,3], [{to_data_type(data_type,1)},"
f"{to_data_type(data_type,2)}, {to_data_type(data_type,3)}], 5)"
)
exitcode, message = 0, None
if data_type.startswith("Decimal"):
exitcode, message = 44, "Exception:"
node.query(sql, exitcode=exitcode, message=message)
with Scenario(f"mapPopulateSeries with {data_type} on a table"):
table_name = get_table_name()
table(
name=table_name, data_type=f"Tuple(Array({data_type}), Array({data_type}))"
)
with When("I insert the output into a table"):
sql = (
f"INSERT INTO {table_name} SELECT mapPopulateSeries([1,2,3],"
f"[{to_data_type(data_type,1)}, {to_data_type(data_type,2)}, {to_data_type(data_type,3)}], 5)"
)
exitcode, message = 0, None
if data_type.startswith("Decimal"):
exitcode, message = 44, "Exception:"
node.query(sql, exitcode=exitcode, message=message)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
with Scenario(f"mapContains with {data_type}"):
node.query(
f"SELECT mapContains( map('key1', {to_data_type(data_type,1)},"
f"'key2', {to_data_type(data_type,2)}), 'key1')"
)
with Scenario(f"mapContains with {data_type} on a table"):
table_name = get_table_name()
table(name=table_name, data_type=data_type)
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT mapContains( map('key1', {to_data_type(data_type,1)},"
f"'key2', {to_data_type(data_type,2)}), 'key1')"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
with Scenario(f"mapKeys with {data_type}"):
node.query(
f"SELECT mapKeys( map('key1', {to_data_type(data_type,1)}, 'key2', {to_data_type(data_type,2)}))"
)
with Scenario(f"mapKeys with {data_type} on a table"):
table_name = get_table_name()
table(name=table_name, data_type="Array(String)")
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT mapKeys( map('key1', {to_data_type(data_type,1)},"
f"'key2', {to_data_type(data_type,2)}))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
with Scenario(f"mapValues with {data_type}"):
node.query(
f"SELECT mapValues( map('key1', {to_data_type(data_type,1)}, 'key2', {to_data_type(data_type,2)}))"
)
with Scenario(f"mapValues with {data_type} on a table"):
table_name = get_table_name()
table(name=table_name, data_type=f"Array({data_type})")
with When("I insert the output into a table"):
node.query(
f"INSERT INTO {table_name} SELECT mapValues( map('key1', {to_data_type(data_type,1)},"
f"'key2', {to_data_type(data_type,2)}))"
)
execute_query(f"SELECT * FROM {table_name} ORDER BY a ASC")
@TestFeature
@Name("array, tuple, map")
@Examples(
"data_type",
[
("Int128",),
("Int256",),
("UInt128",),
("UInt256",),
("Decimal256(0)",),
],
)
def feature(self, node="clickhouse1", stress=None, parallel=None):
"""Check that array, tuple, and map functions work with
extended precision data types.
"""
self.context.node = self.context.cluster.node(node)
with allow_experimental_bigint(self.context.node):
for example in self.examples:
(data_type,) = example
with Feature(data_type):
Suite(test=array_func)(data_type=data_type)
Suite(test=tuple_func)(data_type=data_type)
with Given("I allow experimental map type"):
allow_experimental_map_type()
Suite(test=map_func)(data_type=data_type)
| 36.947547
| 130
| 0.571442
| 2,859
| 21,836
| 4.095838
| 0.057363
| 0.269855
| 0.161913
| 0.215884
| 0.890436
| 0.869428
| 0.866781
| 0.822289
| 0.814091
| 0.794449
| 0
| 0.017592
| 0.286728
| 21,836
| 590
| 131
| 37.010169
| 0.734254
| 0.011678
| 0
| 0.548975
| 0
| 0.038724
| 0.466707
| 0.21999
| 0
| 0
| 0
| 0
| 0
| 1
| 0.01139
| false
| 0
| 0.006834
| 0.002278
| 0.020501
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
10a3e57fd9ba2f05578026bfc4e4b2d493b2fea5
| 114
|
py
|
Python
|
tardis/io/atom_data/__init__.py
|
GOLoDovkA-A/tardis
|
847b562022ccda2db2486549f739188ba48f172c
|
[
"BSD-3-Clause"
] | 1
|
2020-02-24T20:58:02.000Z
|
2020-02-24T20:58:02.000Z
|
tardis/io/atom_data/__init__.py
|
GOLoDovkA-A/tardis
|
847b562022ccda2db2486549f739188ba48f172c
|
[
"BSD-3-Clause"
] | null | null | null |
tardis/io/atom_data/__init__.py
|
GOLoDovkA-A/tardis
|
847b562022ccda2db2486549f739188ba48f172c
|
[
"BSD-3-Clause"
] | null | null | null |
from tardis.io.atom_data.base import AtomData
from tardis.io.atom_data.atom_web_download import download_atom_data
| 57
| 68
| 0.885965
| 20
| 114
| 4.75
| 0.5
| 0.252632
| 0.252632
| 0.336842
| 0.421053
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.061404
| 114
| 2
| 68
| 57
| 0.88785
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
52acc8d1530c39cdf478348c494b0f265010373e
| 68
|
py
|
Python
|
python_example/roles.py
|
ZedsArcade/ZBot
|
0c9f059e30ea598556f67dce4cb5698d1b73d1c0
|
[
"MIT"
] | 1
|
2018-11-24T12:50:51.000Z
|
2018-11-24T12:50:51.000Z
|
zbot/roles.py
|
ZedsArcade/ZBot
|
0c9f059e30ea598556f67dce4cb5698d1b73d1c0
|
[
"MIT"
] | null | null | null |
zbot/roles.py
|
ZedsArcade/ZBot
|
0c9f059e30ea598556f67dce4cb5698d1b73d1c0
|
[
"MIT"
] | null | null | null |
car_role = [1,2,3,4,5,6,7,8,9,10]
car_team = [1,1,1,1,1,1,1,1,1,1]
| 17
| 33
| 0.544118
| 24
| 68
| 1.458333
| 0.541667
| 0.514286
| 0.685714
| 0.8
| 0.285714
| 0.285714
| 0.285714
| 0.285714
| 0.285714
| 0
| 0
| 0.344262
| 0.102941
| 68
| 3
| 34
| 22.666667
| 0.229508
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
52b6cb8c8c1b71a608685c70853ffd5765fcd13c
| 9,204
|
py
|
Python
|
tests/src/Diksha_Reports/usage_by_course/check_with_course_collection_records.py
|
JalajaTR/cQube
|
6bf58ab25f0c36709630987ab730bbd5d9192c03
|
[
"MIT"
] | null | null | null |
tests/src/Diksha_Reports/usage_by_course/check_with_course_collection_records.py
|
JalajaTR/cQube
|
6bf58ab25f0c36709630987ab730bbd5d9192c03
|
[
"MIT"
] | 2
|
2022-02-01T00:55:12.000Z
|
2022-03-29T22:29:09.000Z
|
tests/src/Diksha_Reports/usage_by_course/check_with_course_collection_records.py
|
JalajaTR/cQube
|
6bf58ab25f0c36709630987ab730bbd5d9192c03
|
[
"MIT"
] | null | null | null |
import csv
import os
import re
import time
from selenium.webdriver.support.select import Select
from Data.parameters import Data
from filenames import file_extention
from get_dir import pwd
from reuse_func import GetData
class course_records():
def __init__(self,driver):
self.driver = driver
def courserecords_of_last30days(self):
self.data = GetData()
self.msg = file_extention()
self.p = pwd()
count = 0
self.driver.find_element_by_xpath(Data.hyper_link).click()
self.data.page_loading(self.driver)
self.data.page_loading(self.driver)
timeperiod = Select(self.driver.find_element_by_name('timePeriod'))
timeperiod.select_by_visible_text(' Last 30 Days ')
self.data.page_loading(self.driver)
if self.msg.no_data_available() in self.driver.page_source:
print("Last 30 days dont have records")
else:
self.data.page_loading(self.driver)
collnames = Select(self.driver.find_element_by_name('collectionName'))
for i in range(1, len(collnames.options)):
time.sleep(1)
collnames.select_by_index(i)
name = "collectionType_course_data_of" + collnames.options[i].text
fname = name.replace(' ', '_')
time.sleep(2)
self.driver.find_element_by_id(Data.Download).click()
time.sleep(3)
cname = fname.rstrip('_')
self.filename = self.p.get_download_dir() + '/' + cname + '.csv'
file = os.path.isfile(self.filename)
if file == True:
with open(self.filename) as fin:
csv_reader = csv.reader(fin, delimiter=',')
header = next(csv_reader)
content = 0
for row in csv.reader(fin):
content += int(row[4])
usage = self.driver.find_element_by_id("totalCount").text
tsc = re.sub('\D', "", usage)
if int(tsc) != content:
print(collnames.options[i].text, ":", int(content), int(tsc),
"usage content mismatch found")
count = count + 1
os.remove(self.filename)
else:
alname = fname[:-1] + '.csv'
self.filename = self.p.get_download_dir() + '/' + alname
with open(self.filename) as fin:
csv_reader = csv.reader(fin, delimiter=',')
header = next(csv_reader)
content = 0
for row in csv.reader(fin):
content += int(row[4])
usage = self.driver.find_element_by_id("totalCount").text
tsc = re.sub('\D', "", usage)
if int(tsc) != content:
print(collnames.options[i].text, ":", int(content), int(tsc),
"usage content mismatch found")
count = count + 1
os.remove(self.filename)
return count
def courserecords_of_last7days(self):
self.data = GetData()
self.p = pwd()
self.msg = file_extention()
count = 0
self.driver.find_element_by_xpath(Data.hyper_link).click()
self.data.page_loading(self.driver)
timeperiod = Select(self.driver.find_element_by_name('timePeriod'))
timeperiod.select_by_visible_text(' Last 7 Days ')
self.data.page_loading(self.driver)
if self.msg.no_data_available() in self.driver.page_source:
print("Last 7 days dont have records")
else:
self.data.page_loading(self.driver)
collnames = Select(self.driver.find_element_by_name('collectionName'))
for i in range(1,len(collnames.options)):
time.sleep(1)
collnames.select_by_index(i)
name = "collectionType_course_data_of"+collnames.options[i].text
fname = name.replace(' ','_')
time.sleep(2)
self.driver.find_element_by_id(Data.Download).click()
time.sleep(3)
cname = fname.rstrip('_')
self.filename = self.p.get_download_dir()+'/'+cname+'.csv'
file = os.path.isfile(self.filename)
if file == True:
with open(self.filename) as fin:
csv_reader = csv.reader(fin, delimiter=',')
header = next(csv_reader)
content = 0
for row in csv.reader(fin):
content += int(row[4])
usage = self.driver.find_element_by_id("totalCount").text
tsc = re.sub('\D', "", usage)
if int(tsc) != content:
print(collnames.options[i].text, ":", int(content), int(tsc),
"usage content mismatch found")
count = count + 1
os.remove(self.filename)
else:
alname = fname[:-1] +'.csv'
self.filename = self.p.get_download_dir() + '/' +alname
with open(self.filename) as fin:
csv_reader = csv.reader(fin, delimiter=',')
header = next(csv_reader)
content = 0
for row in csv.reader(fin):
content += int(row[4])
usage = self.driver.find_element_by_id("totalCount").text
tsc = re.sub('\D', "", usage)
if int(tsc) != content:
print(collnames.options[i].text, ":", int(content), int(tsc),
"usage content mismatch found")
count = count + 1
os.remove(self.filename)
return count
def courserecords_of_lastday(self):
self.data = GetData()
self.msg = file_extention()
self.p = pwd()
count = 0
self.driver.find_element_by_xpath(Data.hyper_link).click()
self.data.page_loading(self.driver)
timeperiod = Select(self.driver.find_element_by_name('timePeriod'))
timeperiod.select_by_visible_text(' Last Day ')
self.data.page_loading(self.driver)
if self.msg.no_data_available() in self.driver.page_source:
print("Last day dont have records")
else:
self.data.page_loading(self.driver)
collnames = Select(self.driver.find_element_by_name('collectionName'))
for i in range(1, len(collnames.options)):
time.sleep(1)
collnames.select_by_index(i)
name = "collectionType_course_data_of" + collnames.options[i].text
fname = name.replace(' ', '_')
time.sleep(2)
self.driver.find_element_by_id(Data.Download).click()
time.sleep(3)
cname = fname.rstrip('_')
self.filename = self.p.get_download_dir() + '/' + cname + '.csv'
file = os.path.isfile(self.filename)
if file == True:
with open(self.filename) as fin:
csv_reader = csv.reader(fin, delimiter=',')
header = next(csv_reader)
content = 0
for row in csv.reader(fin):
content += int(row[4])
usage = self.driver.find_element_by_id("totalCount").text
tsc = re.sub('\D', "", usage)
if int(tsc) != content:
print(collnames.options[i].text, ":", int(content), int(tsc),
"usage content mismatch found")
count = count + 1
os.remove(self.filename)
else:
alname = fname[:-1] + '.csv'
self.filename = self.p.get_download_dir() + '/' + alname
with open(self.filename) as fin:
csv_reader = csv.reader(fin, delimiter=',')
header = next(csv_reader)
content = 0
for row in csv.reader(fin):
content += int(row[4])
usage = self.driver.find_element_by_id("totalCount").text
tsc = re.sub('\D', "", usage)
if int(tsc) != content:
print(collnames.options[i].text, ":", int(content), int(tsc),
"usage content mismatch found")
count = count + 1
os.remove(self.filename)
return count
| 47.9375
| 89
| 0.489787
| 952
| 9,204
| 4.580882
| 0.114496
| 0.075671
| 0.057785
| 0.086677
| 0.92731
| 0.922036
| 0.922036
| 0.922036
| 0.922036
| 0.922036
| 0
| 0.008198
| 0.403629
| 9,204
| 192
| 90
| 47.9375
| 0.7863
| 0
| 0
| 0.88587
| 0
| 0
| 0.062792
| 0.009451
| 0
| 0
| 0
| 0
| 0
| 1
| 0.021739
| false
| 0
| 0.048913
| 0
| 0.092391
| 0.048913
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
eac05a5006d8f054dab6344562ef7cb06bc38544
| 1,066
|
py
|
Python
|
Script/markov_chain.py
|
JLDevOps/Markov-Morse
|
d670b5987fc421d6c1acd209305e4572b4b4ad16
|
[
"MIT"
] | 1
|
2017-10-17T23:05:24.000Z
|
2017-10-17T23:05:24.000Z
|
Script/markov_chain.py
|
JLDevOps/Markov-Morse
|
d670b5987fc421d6c1acd209305e4572b4b4ad16
|
[
"MIT"
] | null | null | null |
Script/markov_chain.py
|
JLDevOps/Markov-Morse
|
d670b5987fc421d6c1acd209305e4572b4b4ad16
|
[
"MIT"
] | null | null | null |
import os
import markovify
def generate_markov_text(filename, file_format, number_lines):
sentence_list = []
dir = os.path.dirname(__file__)
file_path = 'text_files/' + str(filename) + "." + str(file_format)
filename = os.path.join(dir, file_path)
with open(filename) as f:
text = f.read()
# Build model
text_model = markovify.Text(text)
for i in range(number_lines):
sentence = text_model.make_sentence()
sentence_list.append(sentence)
return sentence_list
def generate_short_markov_text(filename, file_format, number_lines, size_of_sentence):
sentence_list = []
dir = os.path.dirname(__file__)
file_path = 'text_files/' + str(filename) + "." + str(file_format)
filename = os.path.join(dir, file_path)
with open(filename) as f:
text = f.read()
# Build model
text_model = markovify.Text(text)
for i in range(number_lines):
sentence = text_model.make_short_sentence(int(size_of_sentence))
sentence_list.append(sentence)
return sentence_list
| 30.457143
| 86
| 0.684803
| 143
| 1,066
| 4.797203
| 0.265734
| 0.104956
| 0.08309
| 0.06414
| 0.90379
| 0.874636
| 0.874636
| 0.760933
| 0.609329
| 0.609329
| 0
| 0
| 0.209193
| 1,066
| 34
| 87
| 31.352941
| 0.81376
| 0.021576
| 0
| 0.769231
| 1
| 0
| 0.023099
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.076923
| false
| 0
| 0.076923
| 0
| 0.230769
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
f4ab38b6c48423fbdf66e124e6769046ccf28349
| 158
|
py
|
Python
|
sources/viewgui/__init__.py
|
Groomsha/lan-map
|
1c30819470f43f8521e98eb75c70da23939f8f06
|
[
"Apache-2.0"
] | null | null | null |
sources/viewgui/__init__.py
|
Groomsha/lan-map
|
1c30819470f43f8521e98eb75c70da23939f8f06
|
[
"Apache-2.0"
] | null | null | null |
sources/viewgui/__init__.py
|
Groomsha/lan-map
|
1c30819470f43f8521e98eb75c70da23939f8f06
|
[
"Apache-2.0"
] | null | null | null |
from .app_main_window.ui_app_main_window import *
from .form_new_device.ui_table_new_device_ import *
from .form_new_device.ui_interface_new_device import *
| 31.6
| 54
| 0.860759
| 27
| 158
| 4.444444
| 0.407407
| 0.3
| 0.216667
| 0.283333
| 0.416667
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0
| 0.082278
| 158
| 4
| 55
| 39.5
| 0.827586
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
f4bd1d18f717d4923d948d5bee8a69edf3465ce6
| 3,559
|
py
|
Python
|
pgkit/cli/commands/shellx.py
|
SadeghHayeri/pgk
|
258c859f4e6c1ca7d515851552402a2e6bec80dc
|
[
"MIT"
] | 7
|
2021-06-14T07:22:50.000Z
|
2021-12-15T14:25:49.000Z
|
pgkit/cli/commands/shellx.py
|
SadeghHayeri/pgkit
|
258c859f4e6c1ca7d515851552402a2e6bec80dc
|
[
"MIT"
] | null | null | null |
pgkit/cli/commands/shellx.py
|
SadeghHayeri/pgkit
|
258c859f4e6c1ca7d515851552402a2e6bec80dc
|
[
"MIT"
] | null | null | null |
import yaml
import click
from pgkit.application.db import DB
import pgkit.application.pg as PG
@click.command()
@click.argument('name', required=True)
@click.option('--replica', is_flag=True, default=False)
def shell(name, replica):
config = DB.get_config(name)
PG.shell(
config['name'],
config['host'],
config['port'],
config['version'],
config['dbname'],
config['username'],
config['password'],
config['slot'],
config['replica_port'],
shell_to_replica=replica
)
@click.command()
@click.argument('name', required=True)
@click.argument('database_name', required=True)
@click.argument('output_path', required=True)
@click.option('--compress', required=False, is_flag=True)
@click.option('--compression-level', required=False, type=click.Choice(list(map(str, range(1, 10)))))
def dump(name, database_name, output_path, compress, compression_level):
if not compress and compression_level:
return click.echo('--compress flag should be given when compression level is specified')
config = DB.get_config(name)
PG.dump(
config['name'],
config['host'],
config['port'],
config['version'],
config['dbname'],
config['username'],
config['password'],
config['slot'],
config['replica_port'],
database_name=database_name,
output_path=output_path,
compress=compress,
compression_level=compression_level
)
@click.command()
@click.argument('name', required=True)
@click.argument('output_path', required=True)
@click.option('--compress', required=False, is_flag=True)
@click.option('--compression-level', required=False, type=click.Choice(list(map(str, range(1, 10)))))
def dumpall(name, output_path, compress, compression_level):
if not compress and compression_level:
return click.echo('--compress flag should be given when compression level is specified')
config = DB.get_config(name)
PG.dumpall(
config['name'],
config['host'],
config['port'],
config['version'],
config['dbname'],
config['username'],
config['password'],
config['slot'],
config['replica_port'],
output_path=output_path,
compress=compress,
compression_level=compression_level
)
@click.command()
@click.argument('name', required=True)
def stop(name):
config = DB.get_config(name)
PG.stop(
config['name'],
config['host'],
config['port'],
config['version'],
config['dbname'],
config['username'],
config['password'],
config['slot'],
config['replica_port'],
)
@click.command()
@click.argument('name', required=True)
def start(name):
config = DB.get_config(name)
PG.start(
config['name'],
config['host'],
config['port'],
config['version'],
config['dbname'],
config['username'],
config['password'],
config['slot'],
config['replica_port'],
)
@click.command()
@click.argument('name', required=True)
def restart(name):
config = DB.get_config(name)
PG.restart(
config['name'],
config['host'],
config['port'],
config['version'],
config['dbname'],
config['username'],
config['password'],
config['slot'],
config['replica_port'],
)
@click.command()
def list():
return click.echo(yaml.dump(DB.get_configs_list()))
| 26.759398
| 101
| 0.611689
| 396
| 3,559
| 5.39899
| 0.156566
| 0.056127
| 0.052385
| 0.070159
| 0.871375
| 0.858279
| 0.847521
| 0.809635
| 0.786717
| 0.761459
| 0
| 0.002187
| 0.228997
| 3,559
| 132
| 102
| 26.962121
| 0.776968
| 0
| 0
| 0.760684
| 0
| 0
| 0.169149
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.059829
| false
| 0.051282
| 0.034188
| 0.008547
| 0.119658
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 8
|
76076c124b1e46cd8fcdb4bbd80c3e7d9d7a4076
| 6,419
|
py
|
Python
|
model/model.py
|
MotJuMi/AlexNet
|
bab6623c345f2fe6c85db31623609cd5af4d0b5b
|
[
"MIT"
] | 1
|
2019-11-28T08:26:26.000Z
|
2019-11-28T08:26:26.000Z
|
model/model.py
|
MotJuMi/AlexNet
|
bab6623c345f2fe6c85db31623609cd5af4d0b5b
|
[
"MIT"
] | null | null | null |
model/model.py
|
MotJuMi/AlexNet
|
bab6623c345f2fe6c85db31623609cd5af4d0b5b
|
[
"MIT"
] | null | null | null |
from base import BaseModel
import torch.nn as nn
import torch.nn.functional as F
from modules.LRN import LocalResponseNorm
import torch.utils.model_zoo as model_zoo
model_urls = {
'alexnet': 'https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth'
}
class AlexNetModel(nn.Module):
def __init__(self, config, num_classes=1000):
super(AlexNet, self).__init__()
# in_channels, out_channels, kernel_size, stride, padding
# pool_size, pool_stride
self.config = config
self.init_weights = self.config['model']['init_weights']
self.conv_pool_params = {
(3, 96, 11, 4, 2, 3, 2),
(96, 256, 5, 1, 2, 3, 2),
}
self.conv_params = {
(256, 384, 11, 1, 1),
(384, 384, 11, 1, 1),
(384, 256, 11, 1, 1),
}
self.fc_params = {
(256 * 3 * 3, 4096),
(4096, 4096),
(4096, num_classes, 'True')
}
self.features = nn.Sequential(
*nn.ModuleList(
self.conv_pool_layer(params)
for params in self.conv_pool_params
),
*nn.ModuleList(
self.conv_layer(params)
for params in self.conv_params
)
)
self.classifier = nn.Sequential(
*nn.ModuleList(
self.fc_layer(params)
for params in self.fc_params
)
)
if self.init_weights:
self.initialize_weights()
def conv_pool_layer(in_channels, out_channels, kernel_size, stride,
padding, pool_size, pool_stride):
return nn.Sequential(
nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding),
#nn.ReLU(inplace=True),
LocalResponseNorm(n=5, alpha=1e-4, beta=0.75, k=2)
nn.MaxPool2d(kernel_size=pool_size, stride=pool_stride)
)
def conv_layer(in_channels, out_channels, kernel_size, stride, padding):
return nn.Sequential(
nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding),
#nn.ReLU(inplace=True),
)
def fc_layer(in_features, out_features, last=False):
if last:
return nn.Linear(in_features, out_features)
else:
return nn.Sequential(
nn.Dropout()
nn.Linear(in_features, out_features),
nn.ReLU(inplace=True)
)
def initialize_weights(self):
for module in self.modules():
if isinstance(module, nn.Conv2d):
nn.init.kaiming_normal_(module.weight,
mode='fan_out',
nonlinearity='relu')
if module.bias is not None:
nn.init.constant_(module.bias, 0)
elif isinstance(module, nn.Linear):
nn.init.constant_(module.weight, 0, 0.01)
nn.init.constant_(module.bias, 0)
def forward(self, x):
x = self.features(x)
x = x.view(x.size(0), 256 * 6 * 6)
x = self.classifier(x)
return F.log_softmax(x, dim=1)
class AlexNet(nn.Module):
def __init__(self, config, num_classes=1000):
super(AlexNet, self).__init__()
# in_channels, out_channels, kernel_size, stride, padding
# pool_size, pool_stride
self.config = config
self.init_weights = self.config['model']['init_weights']
self.conv_pool_params = {
(3, 96, 11, 4, 2, 3, 2),
(96, 256, 5, 1, 2, 3, 2),
}
self.conv_params = {
(256, 384, 11, 1, 1),
(384, 384, 11, 1, 1),
(384, 256, 11, 1, 1),
}
self.fc_params = {
(256 * 3 * 3, 4096),
(4096, 4096),
(4096, num_classes, 'True')
}
self.features = nn.Sequential(
*nn.ModuleList(
self.conv_pool_layer(params)
for params in self.conv_pool_params
),
*nn.ModuleList(
self.conv_layer(params)
for params in self.conv_params
)
)
self.classifier = nn.Sequential(
*nn.ModuleList(
self.fc_layer(params)
for params in self.fc_params
)
)
if self.init_weights:
self.initialize_weights()
def conv_pool_layer(in_channels, out_channels, kernel_size, stride,
padding, pool_size, pool_stride):
return nn.Sequential(
nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding),
#nn.ReLU(inplace=True),
LocalResponseNorm(n=5, alpha=1e-4, beta=0.75, k=2)
nn.MaxPool2d(kernel_size=pool_size, stride=pool_stride)
)
def conv_layer(in_channels, out_channels, kernel_size, stride, padding):
return nn.Sequential(
nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding),
#nn.ReLU(inplace=True),
)
def fc_layer(in_features, out_features, last=False):
if last:
return nn.Linear(in_features, out_features)
else:
return nn.Sequential(
nn.Dropout()
nn.Linear(in_features, out_features),
nn.ReLU(inplace=True)
)
def initialize_weights(self):
for module in self.modules():
if isinstance(module, nn.Conv2d):
nn.init.kaiming_normal_(module.weight,
mode='fan_out',
nonlinearity='relu')
if module.bias is not None:
nn.init.constant_(module.bias, 0)
elif isinstance(module, nn.Linear):
nn.init.constant_(module.weight, 0, 0.01)
nn.init.constant_(module.bias, 0)
def forward(self, x):
x = self.features(x)
x = x.view(x.size(0), 256 * 6 * 6)
x = self.classifier(x)
return x
def alexnet(pretrained=False, **kwargs):
"""
:param pretrained: use weights from model pre-trained on ImageNet
"""
model = AlexNet(**kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['alexnet']))
return model
| 33.259067
| 79
| 0.536065
| 746
| 6,419
| 4.426273
| 0.156836
| 0.036342
| 0.03937
| 0.063598
| 0.871593
| 0.871593
| 0.871593
| 0.871593
| 0.871593
| 0.871593
| 0
| 0.048254
| 0.357532
| 6,419
| 192
| 80
| 33.432292
| 0.752425
| 0.038168
| 0
| 0.767296
| 0
| 0
| 0.022712
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.031447
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
5223c0b4ea15b40b138c9d353736a1a24f284a0c
| 79,281
|
py
|
Python
|
scripts/klf14_b6ntac_exp_0044_analysis_pipeline_cell_population_profiles.py
|
rcasero/cytometer
|
d76e58fa37f83f6a666d556ba061530d787fcfb2
|
[
"Apache-2.0"
] | 1
|
2021-06-09T10:18:26.000Z
|
2021-06-09T10:18:26.000Z
|
scripts/klf14_b6ntac_exp_0044_analysis_pipeline_cell_population_profiles.py
|
rcasero/cytometer
|
d76e58fa37f83f6a666d556ba061530d787fcfb2
|
[
"Apache-2.0"
] | null | null | null |
scripts/klf14_b6ntac_exp_0044_analysis_pipeline_cell_population_profiles.py
|
rcasero/cytometer
|
d76e58fa37f83f6a666d556ba061530d787fcfb2
|
[
"Apache-2.0"
] | null | null | null |
"""
Areas computed in exp 0043. Reusing code to compute ground truth areas from exp 0038.
"""
"""
This file is part of Cytometer
Copyright 2021 Medical Research Council
SPDX-License-Identifier: Apache-2.0
Author: Ramon Casero <rcasero@gmail.com>
"""
# cross-platform home directory
from pathlib import Path
home = str(Path.home())
import os
import sys
sys.path.extend([os.path.join(home, 'Software/cytometer')])
import cytometer.utils
# limit number of GPUs
os.environ['CUDA_VISIBLE_DEVICES'] = '2,3'
os.environ['KERAS_BACKEND'] = 'tensorflow'
import pickle
import numpy as np
import matplotlib.pyplot as plt
import glob
from cytometer.data import append_paths_to_aida_json_file
import PIL
import tensorflow as tf
from skimage.measure import regionprops
from skimage.morphology import watershed
from sklearn.metrics import confusion_matrix
import inspect
import pandas as pd
# limit GPU memory used
from keras.backend.tensorflow_backend import set_session
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.95
set_session(tf.Session(config=config))
import keras
DEBUG = False
SAVE_FIGS = False
root_data_dir = os.path.join(home, 'Data/cytometer_data/klf14')
data_dir = os.path.join(home, 'scan_srv2_cox/Maz Yon')
training_dir = os.path.join(home, root_data_dir, 'klf14_b6ntac_training')
seg_dir = os.path.join(home, root_data_dir, 'klf14_b6ntac_seg')
figures_dir = os.path.join(root_data_dir, 'figures')
saved_models_dir = os.path.join(root_data_dir, 'saved_models')
results_dir = os.path.join(root_data_dir, 'klf14_b6ntac_results')
annotations_dir = os.path.join(home, 'Data/cytometer_data/aida_data_Klf14_v7/annotations')
metainfo_dir = os.path.join(home, 'Data/cytometer_data/klf14')
saved_contour_model_basename = 'klf14_b6ntac_exp_0034_cnn_contour'
saved_dmap_model_basename = 'klf14_b6ntac_exp_0035_cnn_dmap'
training_augmented_dir = os.path.join(root_data_dir, 'klf14_b6ntac_training_augmented')
# script name to identify this experiment
experiment_id = inspect.getfile(inspect.currentframe())
if experiment_id == '<input>':
experiment_id = 'unknownscript'
else:
experiment_id = os.path.splitext(os.path.basename(experiment_id))[0]
# area (pixel**2) of the smallest object we accept as a cell (pi * (16 pixel)**2 = 804.2 pixel**2)
smallest_cell_area = 804
# training window length
training_window_len = 401
# thresholds for quality network
dice_threshold = 0.9
quality_threshold = 0.5
'''
************************************************************************************************************************
Hand segmented cells (ground truth), no-overlap approximation
************************************************************************************************************************
'''
'''Load data
'''
# CSV file with metainformation of all mice
metainfo_csv_file = os.path.join(metainfo_dir, 'klf14_b6ntac_meta_info.csv')
metainfo = pd.read_csv(metainfo_csv_file)
# list of all non-overlap original files
im_file_list = glob.glob(os.path.join(training_augmented_dir, 'im_seed_nan_*.tif'))
# read pixel size information
orig_file = os.path.basename(im_file_list[0]).replace('im_seed_nan_', '')
im = PIL.Image.open(os.path.join(training_dir, orig_file))
xres = 0.0254 / im.info['dpi'][0] * 1e6 # um
yres = 0.0254 / im.info['dpi'][1] * 1e6 # um
# load data
full_dataset, full_file_list, full_shuffle_idx = \
cytometer.data.load_datasets(im_file_list, prefix_from='im', prefix_to=['im', 'lab'], nblocks=1)
# remove borders between cells in the lab_train data. For this experiment, we want labels touching each other
for i in range(full_dataset['lab'].shape[0]):
full_dataset['lab'][i, :, :, 0] = watershed(image=np.zeros(shape=full_dataset['lab'].shape[1:3],
dtype=full_dataset['lab'].dtype),
markers=full_dataset['lab'][i, :, :, 0],
watershed_line=False)
# relabel background as "0" instead of "1"
full_dataset['lab'][full_dataset['lab'] == 1] = 0
# plot example of data
if DEBUG:
i = 0
plt.clf()
plt.subplot(121)
plt.imshow(full_dataset['im'][i, :, :, :])
plt.subplot(122)
plt.imshow(full_dataset['lab'][i, :, :, 0])
# loop images
df_gtruth = None
for i in range(full_dataset['lab'].shape[0]):
# get area of each cell in um^2
props = regionprops(full_dataset['lab'][i, :, :, 0])
area = np.array([x['area'] for x in props]) * xres * yres
# create dataframe with metainformation from mouse
df_window = cytometer.data.tag_values_with_mouse_info(metainfo, os.path.basename(full_file_list['im'][i]),
area, values_tag='area', tags_to_keep=['id', 'ko_parent', 'sex'])
# add a column with the window filename. This is later used in the linear models
df_window['file'] = os.path.basename(full_file_list['im'][i])
# create new total dataframe, or concat to existing one
if df_gtruth is None:
df_gtruth = df_window
else:
df_gtruth = pd.concat([df_gtruth, df_window], axis=0, ignore_index=True)
# make sure that in the boxplots PAT comes before MAT
df_gtruth['ko_parent'] = df_gtruth['ko_parent'].astype(pd.api.types.CategoricalDtype(categories=['PAT', 'MAT'], ordered=True))
# plot boxplots for f/m, PAT/MAT comparison as in Nature Genetics paper
plt.clf()
ax = plt.subplot(121)
df_gtruth[df_gtruth['sex'] == 'f'].boxplot(column='area', by='ko_parent', ax=ax, notch=True)
#ax.set_ylim(0, 2e4)
ax.set_title('female', fontsize=16)
ax.set_xlabel('')
ax.set_ylabel('area (um^2)', fontsize=14)
plt.tick_params(axis='both', which='major', labelsize=14)
ax = plt.subplot(122)
df_gtruth[df_gtruth['sex'] == 'm'].boxplot(column='area', by='ko_parent', ax=ax, notch=True)
#ax.set_ylim(0, 2e4)
ax.set_title('male', fontsize=16)
ax.set_xlabel('')
plt.tick_params(axis='both', which='major', labelsize=14)
# split data into groups
area_gtruth_f_PAT = df_gtruth['area'][(np.logical_and(df_gtruth['sex'] == 'f', df_gtruth['ko_parent'] == 'PAT'))]
area_gtruth_f_MAT = df_gtruth['area'][(np.logical_and(df_gtruth['sex'] == 'f', df_gtruth['ko_parent'] == 'MAT'))]
area_gtruth_m_PAT = df_gtruth['area'][(np.logical_and(df_gtruth['sex'] == 'm', df_gtruth['ko_parent'] == 'PAT'))]
area_gtruth_m_MAT = df_gtruth['area'][(np.logical_and(df_gtruth['sex'] == 'm', df_gtruth['ko_parent'] == 'MAT'))]
# compute percentile profiles of cell populations
perc = np.linspace(0, 100, num=101)
perc_area_gtruth_f_PAT = np.percentile(area_gtruth_f_PAT, perc)
perc_area_gtruth_f_MAT = np.percentile(area_gtruth_f_MAT, perc)
perc_area_gtruth_m_PAT = np.percentile(area_gtruth_m_PAT, perc)
perc_area_gtruth_m_MAT = np.percentile(area_gtruth_m_MAT, perc)
'''
************************************************************************************************************************
Exp 0042:
Segment all folds of the training data, using the pipeline function.
Here, we take training images as inputs, and pass them to cytometer.utils.segmentation_pipeline().
With this, we replicate the segmentation in exp 0036 + quality control as in 0042 (or in the
2nd experiment in this script).
Quality mask: +1 / -1 band of 75 pixels / 0
************************************************************************************************************************
'''
# quality network
saved_quality_model_basename = 'klf14_b6ntac_exp_0042_cnn_qualitynet_thresholded_sigmoid_pm_1_band_masked_segmentation'
quality_model_name = saved_quality_model_basename + '*.h5'
# CSV file with metainformation of all mice
metainfo_csv_file = os.path.join(metainfo_dir, 'klf14_b6ntac_meta_info.csv')
metainfo = pd.read_csv(metainfo_csv_file)
# list of images, and indices for training vs. testing indices
contour_model_kfold_filename = os.path.join(saved_models_dir, saved_contour_model_basename + '_info.pickle')
with open(contour_model_kfold_filename, 'rb') as f:
aux = pickle.load(f)
im_orig_file_list = aux['file_list']
idx_orig_test_all = aux['idx_test_all']
# read pixel size information
im = PIL.Image.open(im_orig_file_list[0])
xres = 0.0254 / im.info['dpi'][0] * 1e6 # um
yres = 0.0254 / im.info['dpi'][1] * 1e6 # um
# trained models for all folds
contour_model_files = sorted(glob.glob(os.path.join(saved_models_dir, contour_model_name)))
dmap_model_files = sorted(glob.glob(os.path.join(saved_models_dir, dmap_model_name)))
quality_model_files = sorted(glob.glob(os.path.join(saved_models_dir, quality_model_name)))
df_gtruth_pipeline_good = []
df_gtruth_pipeline_bad = []
for i_fold, idx_test in enumerate(idx_orig_test_all):
print('Fold = ' + str(i_fold) + '/' + str(len(idx_orig_test_all) - 1))
'''Load data
'''
# split the data into training and testing datasets
im_test_file_list, im_train_file_list = cytometer.data.split_list(im_orig_file_list, idx_test)
# load training dataset
datasets, _, _ = cytometer.data.load_datasets(im_test_file_list, prefix_from='im',
prefix_to=['im'], nblocks=1)
im = datasets['im']
del datasets
# number of images
n_im = im.shape[0]
# select the models that correspond to current fold
contour_model_file = contour_model_files[i_fold]
dmap_model_file = dmap_model_files[i_fold]
quality_model_file = quality_model_files[i_fold]
# load models
contour_model = keras.models.load_model(contour_model_file)
dmap_model = keras.models.load_model(dmap_model_file)
quality_model = keras.models.load_model(quality_model_file)
'''Cell segmentation with quality control
'''
# segment histology
labels, labels_info = \
cytometer.utils.segmentation_pipeline(im,
contour_model, dmap_model, quality_model,
quality_model_type='-1_1_band',
smallest_cell_area=smallest_cell_area)
for i in range(im.shape[0]):
if DEBUG:
plt.clf()
plt.subplot(221)
plt.imshow(im[i, :, :, :])
plt.subplot(222)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# list of labels that are on the edges
lab_edge = cytometer.utils.edge_labels(labels[i, :, :, 0])
# delete edge cell labels from labels_info
idx_delete = np.where(np.logical_and(labels_info['im'] == i, np.isin(labels_info['label'], lab_edge)))[0]
labels_info = np.delete(labels_info, idx_delete)
# delete edge cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_edge)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(223)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# list of labels that the quality network rejects
idx_bad = np.logical_and(labels_info['im'] == i, labels_info['quality'] < quality_threshold)
lab_bad = labels_info['label'][idx_bad]
# compute cell areas
props = regionprops(labels[i, :, :, 0])
p_label = [p['label'] for p in props]
p_area = np.array([p['area'] for p in props])
areas = p_area * xres * yres # (m^2)
# delete bad labels from labels_info
labels_info = np.delete(labels_info, idx_bad)
# delete bad cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_bad)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(224)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# split areas into good objects and bad objects
idx_bad = np.isin(p_label, lab_bad)
idx_good = np.logical_not(idx_bad)
# create dataframe with mouse metainformation and area values
df_bad = cytometer.data.tag_values_with_mouse_info(metainfo=metainfo, s=os.path.basename(im_test_file_list[i]),
values=areas[idx_bad], values_tag='area',
tags_to_keep=['id', 'ko_parent', 'sex'])
df_good = cytometer.data.tag_values_with_mouse_info(metainfo=metainfo, s=os.path.basename(im_test_file_list[i]),
values=areas[idx_good], values_tag='area',
tags_to_keep=['id', 'ko_parent', 'sex'])
# concatenate results
if len(df_gtruth_pipeline_good) == 0:
df_gtruth_pipeline_good = df_good
else:
df_gtruth_pipeline_good = pd.concat([df_gtruth_pipeline_good, df_good])
if len(df_gtruth_pipeline_bad) == 0:
df_gtruth_pipeline_bad = df_bad
else:
df_gtruth_pipeline_bad = pd.concat([df_gtruth_pipeline_bad, df_bad])
# split data into groups
area_gtruth_pipeline_good_f_PAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'f',
df_gtruth_pipeline_good['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_good_f_MAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'f',
df_gtruth_pipeline_good['ko_parent'] == 'MAT'))]
area_gtruth_pipeline_good_m_PAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'm',
df_gtruth_pipeline_good['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_good_m_MAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'm',
df_gtruth_pipeline_good['ko_parent'] == 'MAT'))]
area_gtruth_pipeline_bad_f_PAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'f',
df_gtruth_pipeline_bad['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_bad_f_MAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'f',
df_gtruth_pipeline_bad['ko_parent'] == 'MAT'))]
area_gtruth_pipeline_bad_m_PAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'm',
df_gtruth_pipeline_bad['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_bad_m_MAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'm',
df_gtruth_pipeline_bad['ko_parent'] == 'MAT'))]
# plot results
if DEBUG:
plt.clf()
plt.boxplot((area_gtruth_f_PAT, area_gtruth_pipeline_good_f_PAT, area_gtruth_pipeline_bad_f_PAT,
area_gtruth_f_MAT, area_gtruth_pipeline_good_f_MAT, area_gtruth_pipeline_bad_f_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Female')
plt.tick_params(axis='both', which='major', labelsize=14)
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0044_area_boxplots_quality_rejection_bias_female.png'))
plt.clf()
plt.boxplot((area_gtruth_m_PAT, area_gtruth_pipeline_good_m_PAT, area_gtruth_pipeline_bad_m_PAT,
area_gtruth_m_MAT, area_gtruth_pipeline_good_m_MAT, area_gtruth_pipeline_bad_m_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Male')
plt.tick_params(axis='both', which='major', labelsize=14)
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0044_area_boxplots_quality_rejection_bias_male.png'))
'''
************************************************************************************************************************
Exp 0045:
Segment all folds of the training data, using the pipeline function.
Here, we take training images as inputs, and pass them to cytometer.utils.segmentation_pipeline().
With this, we replicate the segmentation in exp 0036 + quality control as in 0045.
Quality mask: +1 / -1 band of 20% equivalent radius / 0
Quality trained with binary cross-entropy.
************************************************************************************************************************
'''
# quality network
saved_quality_model_basename = 'klf14_b6ntac_exp_0045_cnn_qualitynet_thresholded_sigmoid_pm_1_prop_band_masked_segmentation'
quality_model_name = saved_quality_model_basename + '*.h5'
# CSV file with metainformation of all mice
metainfo_csv_file = os.path.join(metainfo_dir, 'klf14_b6ntac_meta_info.csv')
metainfo = pd.read_csv(metainfo_csv_file)
# list of images, and indices for training vs. testing indices
contour_model_kfold_filename = os.path.join(saved_models_dir, saved_contour_model_basename + '_info.pickle')
with open(contour_model_kfold_filename, 'rb') as f:
aux = pickle.load(f)
im_orig_file_list = aux['file_list']
idx_orig_test_all = aux['idx_test_all']
# read pixel size information
im = PIL.Image.open(im_orig_file_list[0])
xres = 0.0254 / im.info['dpi'][0] * 1e6 # um
yres = 0.0254 / im.info['dpi'][1] * 1e6 # um
# trained models for all folds
contour_model_files = sorted(glob.glob(os.path.join(saved_models_dir, contour_model_name)))
dmap_model_files = sorted(glob.glob(os.path.join(saved_models_dir, dmap_model_name)))
quality_model_files = sorted(glob.glob(os.path.join(saved_models_dir, quality_model_name)))
df_gtruth_pipeline_good = []
df_gtruth_pipeline_bad = []
for i_fold, idx_test in enumerate(idx_orig_test_all):
print('Fold = ' + str(i_fold) + '/' + str(len(idx_orig_test_all) - 1))
'''Load data
'''
# split the data into training and testing datasets
im_test_file_list, im_train_file_list = cytometer.data.split_list(im_orig_file_list, idx_test)
# load training dataset
datasets, _, _ = cytometer.data.load_datasets(im_test_file_list, prefix_from='im',
prefix_to=['im'], nblocks=1)
im = datasets['im']
del datasets
# number of images
n_im = im.shape[0]
# select the models that correspond to current fold
contour_model_file = contour_model_files[i_fold]
dmap_model_file = dmap_model_files[i_fold]
quality_model_file = quality_model_files[i_fold]
# load models
contour_model = keras.models.load_model(contour_model_file)
dmap_model = keras.models.load_model(dmap_model_file)
quality_model = keras.models.load_model(quality_model_file)
'''Cell segmentation with quality control
'''
# segment histology
labels, labels_info = \
cytometer.utils.segmentation_pipeline(im,
contour_model, dmap_model, quality_model,
quality_model_type='-1_1_prop_band',
smallest_cell_area=smallest_cell_area)
for i in range(im.shape[0]):
if DEBUG:
plt.clf()
plt.subplot(221)
plt.imshow(im[i, :, :, :])
plt.subplot(222)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# list of labels that are on the edges
lab_edge = cytometer.utils.edge_labels(labels[i, :, :, 0])
# delete edge cell labels from labels_info
idx_delete = np.where(np.logical_and(labels_info['im'] == i, np.isin(labels_info['label'], lab_edge)))[0]
labels_info = np.delete(labels_info, idx_delete)
# delete edge cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_edge)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(223)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# list of labels that the quality network rejects
idx_bad = np.logical_and(labels_info['im'] == i, labels_info['quality'] < quality_threshold)
lab_bad = labels_info['label'][idx_bad]
# compute cell areas
props = regionprops(labels[i, :, :, 0])
p_label = [p['label'] for p in props]
p_area = np.array([p['area'] for p in props])
areas = p_area * xres * yres # (m^2)
# delete bad labels from labels_info
labels_info = np.delete(labels_info, idx_bad)
# delete bad cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_bad)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(224)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# split areas into good objects and bad objects
idx_bad = np.isin(p_label, lab_bad)
idx_good = np.logical_not(idx_bad)
# create dataframe with mouse metainformation and area values
df_bad = cytometer.data.tag_values_with_mouse_info(metainfo=metainfo, s=os.path.basename(im_test_file_list[i]),
values=areas[idx_bad], values_tag='area',
tags_to_keep=['id', 'ko_parent', 'sex'])
df_good = cytometer.data.tag_values_with_mouse_info(metainfo=metainfo, s=os.path.basename(im_test_file_list[i]),
values=areas[idx_good], values_tag='area',
tags_to_keep=['id', 'ko_parent', 'sex'])
# concatenate results
if len(df_gtruth_pipeline_good) == 0:
df_gtruth_pipeline_good = df_good
else:
df_gtruth_pipeline_good = pd.concat([df_gtruth_pipeline_good, df_good])
if len(df_gtruth_pipeline_bad) == 0:
df_gtruth_pipeline_bad = df_bad
else:
df_gtruth_pipeline_bad = pd.concat([df_gtruth_pipeline_bad, df_bad])
# split data into groups
area_gtruth_pipeline_good_f_PAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'f',
df_gtruth_pipeline_good['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_good_f_MAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'f',
df_gtruth_pipeline_good['ko_parent'] == 'MAT'))]
area_gtruth_pipeline_good_m_PAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'm',
df_gtruth_pipeline_good['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_good_m_MAT = df_gtruth_pipeline_good['area'][(np.logical_and(df_gtruth_pipeline_good['sex'] == 'm',
df_gtruth_pipeline_good['ko_parent'] == 'MAT'))]
area_gtruth_pipeline_bad_f_PAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'f',
df_gtruth_pipeline_bad['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_bad_f_MAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'f',
df_gtruth_pipeline_bad['ko_parent'] == 'MAT'))]
area_gtruth_pipeline_bad_m_PAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'm',
df_gtruth_pipeline_bad['ko_parent'] == 'PAT'))]
area_gtruth_pipeline_bad_m_MAT = df_gtruth_pipeline_bad['area'][(np.logical_and(df_gtruth_pipeline_bad['sex'] == 'm',
df_gtruth_pipeline_bad['ko_parent'] == 'MAT'))]
# plot results
if DEBUG:
plt.clf()
plt.boxplot((area_gtruth_f_PAT, area_gtruth_pipeline_good_f_PAT, area_gtruth_pipeline_bad_f_PAT,
area_gtruth_f_MAT, area_gtruth_pipeline_good_f_MAT, area_gtruth_pipeline_bad_f_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Female')
plt.tick_params(axis='both', which='major', labelsize=14)
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0044_area_boxplots_quality_rejection_bias_female_quality_prop_band.png'))
plt.clf()
plt.boxplot((area_gtruth_m_PAT, area_gtruth_pipeline_good_m_PAT, area_gtruth_pipeline_bad_m_PAT,
area_gtruth_m_MAT, area_gtruth_pipeline_good_m_MAT, area_gtruth_pipeline_bad_m_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Male')
plt.tick_params(axis='both', which='major', labelsize=14)
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0044_area_boxplots_quality_rejection_bias_male_quality_prop_band.png'))
'''
************************************************************************************************************************
Exp 0046:
Segment all folds of the training data, using the pipeline function.
Here, we take training images as inputs, and pass them to cytometer.utils.segmentation_pipeline().
With this, we replicate the segmentation in exp 0036 + quality control as in 0046.
Quality mask: +1 / -1 band of 20% equivalent radius / 0
Quality trained with focal loss.
************************************************************************************************************************
'''
# quality network
saved_quality_model_basename = 'klf14_b6ntac_exp_0046_cnn_qualitynet_thresholded_sigmoid_pm_1_prop_band_masked_segmentation_focal_loss'
quality_model_name = saved_quality_model_basename + '*.h5'
# CSV file with metainformation of all mice
metainfo_csv_file = os.path.join(metainfo_dir, 'klf14_b6ntac_meta_info.csv')
metainfo = pd.read_csv(metainfo_csv_file)
# list of images, and indices for training vs. testing indices
contour_model_kfold_filename = os.path.join(saved_models_dir, saved_contour_model_basename + '_info.pickle')
with open(contour_model_kfold_filename, 'rb') as f:
aux = pickle.load(f)
im_orig_file_list = aux['file_list']
idx_orig_test_all = aux['idx_test_all']
# change home directory
im_orig_file_list = cytometer.data.change_home_directory(im_orig_file_list, home_path_from='/users/rittscher/rcasero',
home_path_to=home,
check_isfile=False)
# read pixel size information
im = PIL.Image.open(im_orig_file_list[0])
xres = 0.0254 / im.info['dpi'][0] * 1e6 # um
yres = 0.0254 / im.info['dpi'][1] * 1e6 # um
df_gtruth_pipeline = []
for i_fold, idx_test in enumerate(idx_orig_test_all):
print('Fold = ' + str(i_fold) + '/' + str(len(idx_orig_test_all) - 1))
'''Load data
'''
# split the data into training and testing datasets
im_test_file_list, im_train_file_list = cytometer.data.split_list(im_orig_file_list, idx_test)
# load training dataset
datasets, _, _ = cytometer.data.load_datasets(im_test_file_list, prefix_from='im',
prefix_to=['im', 'lab'], nblocks=1)
im = datasets['im']
reflab = datasets['lab']
del datasets
# number of images
n_im = im.shape[0]
# select the models that correspond to current fold
contour_model_file = os.path.join(saved_models_dir, saved_contour_model_basename + '_model_fold_' + str(i_fold) + '.h5')
dmap_model_file = os.path.join(saved_models_dir, saved_dmap_model_basename + '_model_fold_' + str(i_fold) + '.h5')
quality_model_file = os.path.join(saved_models_dir, saved_quality_model_basename + '_model_fold_' + str(i_fold) + '.h5')
# load models
contour_model = keras.models.load_model(contour_model_file)
dmap_model = keras.models.load_model(dmap_model_file)
quality_model = keras.models.load_model(quality_model_file)
'''Cell segmentation with quality control
'''
# segment histology
labels, labels_info = \
cytometer.utils.segmentation_pipeline(im,
contour_model, dmap_model, quality_model,
quality_model_type='-1_1_prop_band',
smallest_cell_area=smallest_cell_area)
for i in range(im.shape[0]):
if DEBUG:
plt.clf()
plt.subplot(221)
plt.imshow(im[i, :, :, :])
plt.subplot(222)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# list of labels that are on the edges
lab_edge = cytometer.utils.edge_labels(labels[i, :, :, 0])
# delete edge cell labels from labels_info
idx_delete = np.where(np.logical_and(labels_info['im'] == i, np.isin(labels_info['label'], lab_edge)))[0]
labels_info = np.delete(labels_info, idx_delete)
# delete edge cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_edge)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(223)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
plt.contour(reflab[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C1')
# compute cell areas from non-edge cells
props = regionprops(labels[i, :, :, 0])
p_label = [p['label'] for p in props]
p_area = np.array([p['area'] for p in props])
areas = p_area * xres * yres # (m^2)
# create dataframe: one cell per row, tagged with mouse metainformation
df = cytometer.data.tag_values_with_mouse_info(metainfo=metainfo, s=os.path.basename(im_test_file_list[i]),
values=areas, values_tag='area',
tags_to_keep=['id', 'ko_parent', 'sex'])
# add to dataframe: image index and cell label
df['im'] = i
df['label'] = p_label
# add to dataframe: Dice coefficients
# get Dice value for each non-edge automatic segmentation. These Dice values are
# computed by comparing the automatic segmentation to the manual segmentation. When there's no manual
# segmentation to compare with, we assume Dice = 0. This is not a perfect choice, as sometimes the pipeline may
# spot a cell that the human operator didn't, but in general we are going to assume that if the human operator
# didn't hand-traced an object it's because it was not a well formed white adipocyte.
#
# We then create a look up table (LUT) so that we can sort the values according to the labels in labels_info
# efficiently.
dice_info = cytometer.utils.match_overlapping_labels(labels_test=labels[i, :, :, 0],
labels_ref=reflab[i, :, :, 0])
dice_lut = np.zeros(shape=(np.max(labels[i, :, :, 0]) + 1, ))
dice_lut[dice_info['lab_test']] = dice_info['dice']
df['dice'] = dice_lut[p_label]
# add to dataframe: quality scores
idx = labels_info['im'] == i
assert(np.all(p_label == labels_info[idx]['label']))
df['quality'] = labels_info[idx]['quality']
## Delete bad segmentations: this is only for display
# list of labels that the quality network rejects
idx_bad = np.logical_and(labels_info['im'] == i, labels_info['quality'] < quality_threshold)
lab_bad = labels_info['label'][idx_bad]
# delete bad labels from labels_info
labels_info = np.delete(labels_info, idx_bad)
# delete bad cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_bad)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(224)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# concatenate results
if len(df_gtruth_pipeline) == 0:
df_gtruth_pipeline = df
else:
df_gtruth_pipeline = pd.concat([df_gtruth_pipeline, df])
#np.savez('/tmp/foo.npz', df_gtruth_pipeline=df_gtruth_pipeline)
# split data into groups
idx_good = np.array(df_gtruth_pipeline['quality'] >= quality_threshold)
idx_f = np.array(df_gtruth_pipeline['sex'] == 'f')
idx_pat = np.array(df_gtruth_pipeline['ko_parent'] == 'PAT')
area_gtruth_pipeline_good_f_PAT = df_gtruth_pipeline['area'][idx_good * idx_f * idx_pat]
area_gtruth_pipeline_good_f_MAT = df_gtruth_pipeline['area'][idx_good * idx_f * ~idx_pat]
area_gtruth_pipeline_good_m_PAT = df_gtruth_pipeline['area'][idx_good * ~idx_f * idx_pat]
area_gtruth_pipeline_good_m_MAT = df_gtruth_pipeline['area'][idx_good * ~idx_f * ~idx_pat]
area_gtruth_pipeline_bad_f_PAT = df_gtruth_pipeline['area'][~idx_good * idx_f * idx_pat]
area_gtruth_pipeline_bad_f_MAT = df_gtruth_pipeline['area'][~idx_good * idx_f * ~idx_pat]
area_gtruth_pipeline_bad_m_PAT = df_gtruth_pipeline['area'][~idx_good * ~idx_f * idx_pat]
area_gtruth_pipeline_bad_m_MAT = df_gtruth_pipeline['area'][~idx_good * ~idx_f * ~idx_pat]
# plot results
if DEBUG:
plt.clf()
plt.boxplot((area_gtruth_f_PAT, area_gtruth_pipeline_good_f_PAT, area_gtruth_pipeline_bad_f_PAT,
area_gtruth_f_MAT, area_gtruth_pipeline_good_f_MAT, area_gtruth_pipeline_bad_f_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Female')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.ylim((0, 15000))
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0044_area_boxplots_quality_rejection_bias_female_quality_prop_band_focal_loss.png'))
plt.clf()
plt.boxplot((area_gtruth_m_PAT, area_gtruth_pipeline_good_m_PAT, area_gtruth_pipeline_bad_m_PAT,
area_gtruth_m_MAT, area_gtruth_pipeline_good_m_MAT, area_gtruth_pipeline_bad_m_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Male')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.ylim((0, 15000))
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0044_area_boxplots_quality_rejection_bias_male_quality_prop_band_focal_loss.png'))
# Compute confusion matrix for all cells together
if DEBUG:
y_true = df_gtruth_pipeline['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='All cells',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# confusion matrix for females
df_gtruth_pipeline_female = df_gtruth_pipeline.loc[df_gtruth_pipeline['sex'] == 'f', :]
y_true = df_gtruth_pipeline_female['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline_female['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='Female',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# confusion matrix for males
df_gtruth_pipeline_male = df_gtruth_pipeline.loc[df_gtruth_pipeline['sex'] == 'm', :]
y_true = df_gtruth_pipeline_male['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline_male['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='Male',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# compute sensitivity and specificity over intervals of cell area
area_intervals = list(range(0, 8000, 250)) + [np.Inf, ]
sensitivity = np.zeros(shape=(len(area_intervals) - 1, ))
specificity = np.zeros(shape=(len(area_intervals) - 1, ))
for i in range(len(area_intervals) - 1):
df = df_gtruth_pipeline.loc[np.logical_and(df_gtruth_pipeline['area'] >= area_intervals[i],
df_gtruth_pipeline['area'] < area_intervals[i + 1]), :]
# sensitivity = TP / P
# TP = Dice >= 0.9 & quality >= 0.5
# P = Dice >= 0.9
TP = np.count_nonzero(np.logical_and(df['dice'] >= dice_threshold, df['quality'] >= quality_threshold))
P = np.count_nonzero(df['dice'] >= dice_threshold)
if P == 0:
sensitivity[i] = np.nan
else:
sensitivity[i] = TP / P
# specificity = TN / N
# TN = Dice < 0.9 & quality < 0.5
# N = Dice < 0.9
TN = np.count_nonzero(np.logical_and(df['dice'] < dice_threshold, df['quality'] < quality_threshold))
N = np.count_nonzero(df['dice'] < dice_threshold)
if N == 0:
specificity[i] = np.nan
else:
specificity[i] = TN / N
if DEBUG:
plt.clf()
area_midpoints = (np.array(area_intervals[0:-1]) + np.array(area_intervals[1:]))/2.0
plt.plot(area_midpoints, sensitivity, label='Sensitivity')
plt.plot(area_midpoints, specificity, label='Specificity')
plt.legend()
plt.xlabel('area ($\mu m^2$)', fontsize=14)
plt.tick_params(axis='both', which='major', labelsize=14)
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0044_pipeline_sensitivity_specificity.png'))
# compute plot of cell area vs. Dice/quality value
if DEBUG:
plt.clf()
plt.subplot(121)
plt.plot(df_gtruth_pipeline['area'][df_gtruth_pipeline['dice'] < dice_threshold],
df_gtruth_pipeline['dice'][df_gtruth_pipeline['dice'] < dice_threshold], '.C0')
plt.plot(df_gtruth_pipeline['area'][df_gtruth_pipeline['dice'] >= dice_threshold],
df_gtruth_pipeline['dice'][df_gtruth_pipeline['dice'] >= dice_threshold], '.C1')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.xlabel('Cell area', fontsize=14)
plt.ylabel('Dice', fontsize=14)
plt.subplot(122)
# quality < 0.5, dice < 0.9
idx = (df_gtruth_pipeline['quality'] < quality_threshold) * (df_gtruth_pipeline['dice'] < dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C0', label="D<0.9, Q<0.5")
# quality >= 0.5, dice < 0.9
idx = (df_gtruth_pipeline['quality'] >= quality_threshold) * (df_gtruth_pipeline['dice'] < dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C1', label="D<0.9, Q$\geq$0.5")
# quality < 0.5, dice >= 0.9
idx = (df_gtruth_pipeline['quality'] < quality_threshold) * (df_gtruth_pipeline['dice'] >= dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C2', label="D$\geq$0.9, Q<0.5")
# quality >= 0.5, dice >= 0.9
idx = (df_gtruth_pipeline['quality'] >= quality_threshold) * (df_gtruth_pipeline['dice'] >= dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C3', label="D$\geq$0.9, Q$\geq$0.5")
plt.tick_params(axis='both', which='major', labelsize=14)
plt.legend()
plt.xlabel('Dice', fontsize=14)
plt.ylabel('Quality', fontsize=14)
# plot Dice vs. quality, and colour according to size
plt.clf()
plt.scatter(df_gtruth_pipeline['dice'], df_gtruth_pipeline['quality'], c=np.log(df_gtruth_pipeline['area']+1), s=5)
plt.colorbar()
plt.tick_params(axis='both', which='major', labelsize=14)
plt.xlabel('Dice', fontsize=14)
plt.ylabel('Quality', fontsize=14)
'''
************************************************************************************************************************
Exp 0048:
Training all folds of DenseNet for quality assessement of individual cells based on classification of
thresholded Dice coefficient (Dice >= 0.9). Here the loss is binary focal loss.
The reason is to center the decision boundary on 0.9, to get finer granularity around that threshold.
Mask one-cell histology windows with 0/-1/+1 mask. The mask has a band with a width of 20% the equivalent radius
of the cell (equivalent radius is the radius of a circle with the same area as the cell).
We then convert the images to polar coordinates before training.
This is part of a series of experiments with different types of masks: 0039, 0040, 0041, 0042 and 0045.
************************************************************************************************************************
'''
# quality network
saved_quality_model_basename = 'klf14_b6ntac_exp_0048_cnn_qualitynet_prop_band_focal_loss_polar'
quality_model_name = saved_quality_model_basename + '*.h5'
# CSV file with metainformation of all mice
metainfo_csv_file = os.path.join(metainfo_dir, 'klf14_b6ntac_meta_info.csv')
metainfo = pd.read_csv(metainfo_csv_file)
# list of images, and indices for training vs. testing indices
contour_model_kfold_filename = os.path.join(saved_models_dir, saved_contour_model_basename + '_info.pickle')
with open(contour_model_kfold_filename, 'rb') as f:
aux = pickle.load(f)
im_orig_file_list = aux['file_list']
idx_orig_test_all = aux['idx_test_all']
# change home directory
im_orig_file_list = cytometer.data.change_home_directory(im_orig_file_list, home_path_from='/users/rittscher/rcasero',
home_path_to=home,
check_isfile=False)
# read pixel size information
im = PIL.Image.open(im_orig_file_list[0])
xres = 0.0254 / im.info['dpi'][0] * 1e6 # um
yres = 0.0254 / im.info['dpi'][1] * 1e6 # um
df_gtruth_pipeline = []
for i_fold, idx_test in enumerate(idx_orig_test_all):
print('Fold = ' + str(i_fold) + '/' + str(len(idx_orig_test_all) - 1))
'''Load data
'''
# split the data into training and testing datasets
im_test_file_list, im_train_file_list = cytometer.data.split_list(im_orig_file_list, idx_test)
# load training dataset
datasets, _, _ = cytometer.data.load_datasets(im_test_file_list, prefix_from='im',
prefix_to=['im', 'lab'], nblocks=1)
im = datasets['im']
reflab = datasets['lab']
del datasets
# number of images
n_im = im.shape[0]
# select the models that correspond to current fold
contour_model_file = os.path.join(saved_models_dir, saved_contour_model_basename + '_model_fold_' + str(i_fold) + '.h5')
dmap_model_file = os.path.join(saved_models_dir, saved_dmap_model_basename + '_model_fold_' + str(i_fold) + '.h5')
quality_model_file = os.path.join(saved_models_dir, saved_quality_model_basename + '_model_fold_' + str(i_fold) + '.h5')
# load models
contour_model = keras.models.load_model(contour_model_file)
dmap_model = keras.models.load_model(dmap_model_file)
quality_model = keras.models.load_model(quality_model_file)
'''Cell segmentation with quality control
'''
# segment histology
labels, labels_info = \
cytometer.utils.segmentation_pipeline(im,
contour_model, dmap_model, quality_model,
quality_model_type='-1_1_prop_band',
quality_model_preprocessing='polar',
smallest_cell_area=smallest_cell_area)
for i in range(im.shape[0]):
if DEBUG:
plt.clf()
plt.subplot(221)
plt.imshow(im[i, :, :, :])
plt.subplot(222)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# list of labels that are on the edges
lab_edge = cytometer.utils.edge_labels(labels[i, :, :, 0])
# delete edge cell labels from labels_info
idx_delete = np.where(np.logical_and(labels_info['im'] == i, np.isin(labels_info['label'], lab_edge)))[0]
labels_info = np.delete(labels_info, idx_delete)
# delete edge cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_edge)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(223)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
plt.contour(reflab[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C1')
# compute cell areas from non-edge cells
props = regionprops(labels[i, :, :, 0])
p_label = [p['label'] for p in props]
p_area = np.array([p['area'] for p in props])
areas = p_area * xres * yres # (m^2)
# create dataframe: one cell per row, tagged with mouse metainformation
df = cytometer.data.tag_values_with_mouse_info(metainfo=metainfo, s=os.path.basename(im_test_file_list[i]),
values=areas, values_tag='area',
tags_to_keep=['id', 'ko_parent', 'sex'])
# add to dataframe: image index and cell label
df['im'] = i
df['label'] = p_label
# add to dataframe: Dice coefficients
# get Dice value for each non-edge automatic segmentation. These Dice values are
# computed by comparing the automatic segmentation to the manual segmentation. When there's no manual
# segmentation to compare with, we assume Dice = 0. This is not a perfect choice, as sometimes the pipeline may
# spot a cell that the human operator didn't, but in general we are going to assume that if the human operator
# didn't hand-traced an object it's because it was not a well formed white adipocyte.
#
# We then create a look up table (LUT) so that we can sort the values according to the labels in labels_info
# efficiently.
dice_info = cytometer.utils.match_overlapping_labels(labels_test=labels[i, :, :, 0],
labels_ref=reflab[i, :, :, 0])
dice_lut = np.zeros(shape=(np.max(labels[i, :, :, 0]) + 1, ))
dice_lut[dice_info['lab_test']] = dice_info['dice']
df['dice'] = dice_lut[p_label]
# add to dataframe: quality scores
idx = labels_info['im'] == i
assert(np.all(p_label == labels_info[idx]['label']))
df['quality'] = labels_info[idx]['quality']
## Delete bad segmentations: this last block of code is only useful to display results
# list of labels that the quality network rejects
idx_bad = np.logical_and(labels_info['im'] == i, labels_info['quality'] < quality_threshold)
lab_bad = labels_info['label'][idx_bad]
# delete bad labels from labels_info
labels_info = np.delete(labels_info, idx_bad)
# delete bad cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_bad)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(224)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# concatenate results
if len(df_gtruth_pipeline) == 0:
df_gtruth_pipeline = df
else:
df_gtruth_pipeline = pd.concat([df_gtruth_pipeline, df])
#np.savez('/tmp/foo.npz', df_gtruth_pipeline=df_gtruth_pipeline)
# delete segmentations with Dice < 0.2, because those don't really have a ground truth. For example,
# the segmentation itself may be a good segmentation of a cell, but that cell had no ground truth.
# So instead, the segmentation is just touching the edge of the ground truth of a neighbour cell
idx = df_gtruth_pipeline['dice'] >= 0.2
df_gtruth_pipeline = df_gtruth_pipeline.loc[idx, :]
# split data into groups
idx_good = np.array(df_gtruth_pipeline['quality'] >= quality_threshold)
idx_f = np.array(df_gtruth_pipeline['sex'] == 'f')
idx_pat = np.array(df_gtruth_pipeline['ko_parent'] == 'PAT')
area_gtruth_pipeline_good_f_PAT = df_gtruth_pipeline['area'][idx_good * idx_f * idx_pat]
area_gtruth_pipeline_good_f_MAT = df_gtruth_pipeline['area'][idx_good * idx_f * ~idx_pat]
area_gtruth_pipeline_good_m_PAT = df_gtruth_pipeline['area'][idx_good * ~idx_f * idx_pat]
area_gtruth_pipeline_good_m_MAT = df_gtruth_pipeline['area'][idx_good * ~idx_f * ~idx_pat]
area_gtruth_pipeline_bad_f_PAT = df_gtruth_pipeline['area'][~idx_good * idx_f * idx_pat]
area_gtruth_pipeline_bad_f_MAT = df_gtruth_pipeline['area'][~idx_good * idx_f * ~idx_pat]
area_gtruth_pipeline_bad_m_PAT = df_gtruth_pipeline['area'][~idx_good * ~idx_f * idx_pat]
area_gtruth_pipeline_bad_m_MAT = df_gtruth_pipeline['area'][~idx_good * ~idx_f * ~idx_pat]
# plot results
if DEBUG:
plt.clf()
plt.boxplot((area_gtruth_f_PAT, area_gtruth_pipeline_good_f_PAT, area_gtruth_pipeline_bad_f_PAT,
area_gtruth_f_MAT, area_gtruth_pipeline_good_f_MAT, area_gtruth_pipeline_bad_f_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Female')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.ylim((0, 9000))
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0048_area_boxplots_quality_rejection_bias_female_quality_prop_band_focal_loss.png'))
plt.clf()
plt.boxplot((area_gtruth_m_PAT, area_gtruth_pipeline_good_m_PAT, area_gtruth_pipeline_bad_m_PAT,
area_gtruth_m_MAT, area_gtruth_pipeline_good_m_MAT, area_gtruth_pipeline_bad_m_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Male')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.ylim((0, 15000))
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0048_area_boxplots_quality_rejection_bias_male_quality_prop_band_focal_loss.png'))
# Compute confusion matrix for all cells together
if DEBUG:
y_true = df_gtruth_pipeline['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='All cells',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# confusion matrix for females
df_gtruth_pipeline_female = df_gtruth_pipeline.loc[df_gtruth_pipeline['sex'] == 'f', :]
y_true = df_gtruth_pipeline_female['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline_female['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='Female',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# confusion matrix for males
df_gtruth_pipeline_male = df_gtruth_pipeline.loc[df_gtruth_pipeline['sex'] == 'm', :]
y_true = df_gtruth_pipeline_male['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline_male['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='Male',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# compute sensitivity and specificity over intervals of cell area
area_intervals = list(range(0, 8000, 250)) + [np.Inf, ]
sensitivity = np.zeros(shape=(len(area_intervals) - 1, ))
specificity = np.zeros(shape=(len(area_intervals) - 1, ))
for i in range(len(area_intervals) - 1):
df = df_gtruth_pipeline.loc[np.logical_and(df_gtruth_pipeline['area'] >= area_intervals[i],
df_gtruth_pipeline['area'] < area_intervals[i + 1]), :]
# sensitivity = TP / P
# TP = Dice >= 0.9 & quality >= 0.5
# P = Dice >= 0.9
TP = np.count_nonzero(np.logical_and(df['dice'] >= dice_threshold, df['quality'] >= quality_threshold))
P = np.count_nonzero(df['dice'] >= dice_threshold)
if P == 0:
sensitivity[i] = np.nan
else:
sensitivity[i] = TP / P
# specificity = TN / N
# TN = Dice < 0.9 & quality < 0.5
# N = Dice < 0.9
TN = np.count_nonzero(np.logical_and(df['dice'] < dice_threshold, df['quality'] < quality_threshold))
N = np.count_nonzero(df['dice'] < dice_threshold)
if N == 0:
specificity[i] = np.nan
else:
specificity[i] = TN / N
if DEBUG:
plt.clf()
area_midpoints = (np.array(area_intervals[0:-1]) + np.array(area_intervals[1:]))/2.0
plt.plot(area_midpoints, sensitivity, label='Sensitivity')
plt.plot(area_midpoints, specificity, label='Specificity')
plt.legend()
plt.xlabel('area ($\mu m^2$)', fontsize=14)
plt.tick_params(axis='both', which='major', labelsize=14)
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0048_pipeline_sensitivity_specificity.png'))
# compute plot of cell area vs. Dice/quality value
if DEBUG:
plt.clf()
plt.subplot(121)
plt.plot(df_gtruth_pipeline['area'][df_gtruth_pipeline['dice'] < dice_threshold],
df_gtruth_pipeline['dice'][df_gtruth_pipeline['dice'] < dice_threshold], '.C0')
plt.plot(df_gtruth_pipeline['area'][df_gtruth_pipeline['dice'] >= dice_threshold],
df_gtruth_pipeline['dice'][df_gtruth_pipeline['dice'] >= dice_threshold], '.C1')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.xlabel('Cell area', fontsize=14)
plt.ylabel('Dice', fontsize=14)
plt.subplot(122)
# quality < 0.5, dice < 0.9
idx = (df_gtruth_pipeline['quality'] < quality_threshold) * (df_gtruth_pipeline['dice'] < dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C0', label="D<0.9, Q<0.5")
# quality >= 0.5, dice < 0.9
idx = (df_gtruth_pipeline['quality'] >= quality_threshold) * (df_gtruth_pipeline['dice'] < dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C1', label="D<0.9, Q$\geq$0.5")
# quality < 0.5, dice >= 0.9
idx = (df_gtruth_pipeline['quality'] < quality_threshold) * (df_gtruth_pipeline['dice'] >= dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C2', label="D$\geq$0.9, Q<0.5")
# quality >= 0.5, dice >= 0.9
idx = (df_gtruth_pipeline['quality'] >= quality_threshold) * (df_gtruth_pipeline['dice'] >= dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C3', label="D$\geq$0.9, Q$\geq$0.5")
plt.tick_params(axis='both', which='major', labelsize=14)
plt.legend()
plt.xlabel('Dice', fontsize=14)
plt.ylabel('Quality', fontsize=14)
# plot Dice vs. quality, and colour according to size
plt.clf()
plt.scatter(df_gtruth_pipeline['dice'], df_gtruth_pipeline['quality'], c=np.log(df_gtruth_pipeline['area']+1), s=5)
plt.colorbar()
plt.tick_params(axis='both', which='major', labelsize=14)
plt.xlabel('Dice', fontsize=14)
plt.ylabel('Quality', fontsize=14)
'''
************************************************************************************************************************
Exp 0049:
Training all folds of DenseNet for quality assessement of individual cells based on classification of
thresholded Dice coefficient (Dice >= 0.9). Here the loss is binary focal loss.
The reason is to center the decision boundary on 0.9, to get finer granularity around that threshold.
Mask one-cell histology windows with 0/-1/+1 mask. The mask has a band with a width of 20% the equivalent radius
of the cell (equivalent radius is the radius of a circle with the same area as the cell).
The difference of this one with 0046 is that here we remove segmentations with Dice < 0.5 (automatic segmentations that
have poor ground truth) from the training dataset.
This is part of a series of experiments with different types of masks: 0039, 0040, 0041, 0042, 0045, 0046, 0048.
************************************************************************************************************************
'''
# quality network
saved_quality_model_basename = 'klf14_b6ntac_exp_0049_cnn_qualitynet_pm_1_prop_band_focal_loss_dice_geq_0_5'
quality_model_name = saved_quality_model_basename + '*.h5'
# CSV file with metainformation of all mice
metainfo_csv_file = os.path.join(metainfo_dir, 'klf14_b6ntac_meta_info.csv')
metainfo = pd.read_csv(metainfo_csv_file)
# list of images, and indices for training vs. testing indices
contour_model_kfold_filename = os.path.join(saved_models_dir, saved_contour_model_basename + '_info.pickle')
with open(contour_model_kfold_filename, 'rb') as f:
aux = pickle.load(f)
im_orig_file_list = aux['file_list']
idx_orig_test_all = aux['idx_test_all']
# change home directory
im_orig_file_list = cytometer.data.change_home_directory(im_orig_file_list, home_path_from='/users/rittscher/rcasero',
home_path_to=home,
check_isfile=False)
# read pixel size information
im = PIL.Image.open(im_orig_file_list[0])
xres = 0.0254 / im.info['dpi'][0] * 1e6 # um
yres = 0.0254 / im.info['dpi'][1] * 1e6 # um
df_gtruth_pipeline = []
for i_fold, idx_test in enumerate(idx_orig_test_all):
print('Fold = ' + str(i_fold) + '/' + str(len(idx_orig_test_all) - 1))
'''Load data
'''
# split the data into training and testing datasets
im_test_file_list, im_train_file_list = cytometer.data.split_list(im_orig_file_list, idx_test)
# load training dataset
datasets, _, _ = cytometer.data.load_datasets(im_test_file_list, prefix_from='im',
prefix_to=['im', 'lab'], nblocks=1)
im = datasets['im']
reflab = datasets['lab']
del datasets
# number of images
n_im = im.shape[0]
# select the models that correspond to current fold
contour_model_file = os.path.join(saved_models_dir, saved_contour_model_basename + '_model_fold_' + str(i_fold) + '.h5')
dmap_model_file = os.path.join(saved_models_dir, saved_dmap_model_basename + '_model_fold_' + str(i_fold) + '.h5')
quality_model_file = os.path.join(saved_models_dir, saved_quality_model_basename + '_model_fold_' + str(i_fold) + '.h5')
# load models
contour_model = keras.models.load_model(contour_model_file)
dmap_model = keras.models.load_model(dmap_model_file)
quality_model = keras.models.load_model(quality_model_file)
'''Cell segmentation with quality control
'''
# segment histology
labels, labels_info = \
cytometer.utils.segmentation_pipeline(im,
contour_model, dmap_model, quality_model,
quality_model_type='-1_1_prop_band',
smallest_cell_area=smallest_cell_area)
for i in range(im.shape[0]):
if DEBUG:
plt.clf()
plt.subplot(221)
plt.imshow(im[i, :, :, :])
plt.subplot(222)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# list of labels that are on the edges
lab_edge = cytometer.utils.edge_labels(labels[i, :, :, 0])
# delete edge cell labels from labels_info
idx_delete = np.where(np.logical_and(labels_info['im'] == i, np.isin(labels_info['label'], lab_edge)))[0]
labels_info = np.delete(labels_info, idx_delete)
# delete edge cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_edge)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(223)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
plt.contour(reflab[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C1')
# compute cell areas from non-edge cells
props = regionprops(labels[i, :, :, 0])
p_label = [p['label'] for p in props]
p_area = np.array([p['area'] for p in props])
areas = p_area * xres * yres # (m^2)
# create dataframe: one cell per row, tagged with mouse metainformation
df = cytometer.data.tag_values_with_mouse_info(metainfo=metainfo, s=os.path.basename(im_test_file_list[i]),
values=areas, values_tag='area',
tags_to_keep=['id', 'ko_parent', 'sex'])
# add to dataframe: image index and cell label
df['im'] = i
df['label'] = p_label
# add to dataframe: Dice coefficients
# get Dice value for each non-edge automatic segmentation. These Dice values are
# computed by comparing the automatic segmentation to the manual segmentation. When there's no manual
# segmentation to compare with, we assume Dice = 0. This is not a perfect choice, as sometimes the pipeline may
# spot a cell that the human operator didn't, but in general we are going to assume that if the human operator
# didn't hand-traced an object it's because it was not a well formed white adipocyte.
#
# We then create a look up table (LUT) so that we can sort the values according to the labels in labels_info
# efficiently.
dice_info = cytometer.utils.match_overlapping_labels(labels_test=labels[i, :, :, 0],
labels_ref=reflab[i, :, :, 0])
dice_lut = np.zeros(shape=(np.max(labels[i, :, :, 0]) + 1, ))
dice_lut[dice_info['lab_test']] = dice_info['dice']
df['dice'] = dice_lut[p_label]
# add to dataframe: quality scores
idx = labels_info['im'] == i
assert(np.all(p_label == labels_info[idx]['label']))
df['quality'] = labels_info[idx]['quality']
## Delete bad segmentations: this last block of code is only useful to display results
# list of labels that the quality network rejects
idx_bad = np.logical_and(labels_info['im'] == i, labels_info['quality'] < quality_threshold)
lab_bad = labels_info['label'][idx_bad]
# delete bad labels from labels_info
labels_info = np.delete(labels_info, idx_bad)
# delete bad cells from the segmentation
labels[i, :, :, 0] = np.logical_not(np.isin(labels[i, :, :, 0], lab_bad)) * labels[i, :, :, 0]
if DEBUG:
plt.subplot(224)
plt.imshow(im[i, :, :, :])
plt.contour(labels[i, :, :, 0], levels=np.unique(labels[i, :, :, 0]), colors='C0')
# concatenate results
if len(df_gtruth_pipeline) == 0:
df_gtruth_pipeline = df
else:
df_gtruth_pipeline = pd.concat([df_gtruth_pipeline, df])
#np.savez('/tmp/foo.npz', df_gtruth_pipeline=df_gtruth_pipeline)
# delete segmentations with Dice < 0.2, because those don't really have a ground truth. For example,
# the segmentation itself may be a good segmentation of a cell, but that cell had no ground truth.
# So instead, the segmentation is just touching the edge of the ground truth of a neighbour cell
idx = df_gtruth_pipeline['dice'] >= 0.2
df_gtruth_pipeline = df_gtruth_pipeline.loc[idx, :]
# split data into groups
idx_good = np.array(df_gtruth_pipeline['quality'] >= quality_threshold)
idx_f = np.array(df_gtruth_pipeline['sex'] == 'f')
idx_pat = np.array(df_gtruth_pipeline['ko_parent'] == 'PAT')
area_gtruth_pipeline_good_f_PAT = df_gtruth_pipeline['area'][idx_good * idx_f * idx_pat]
area_gtruth_pipeline_good_f_MAT = df_gtruth_pipeline['area'][idx_good * idx_f * ~idx_pat]
area_gtruth_pipeline_good_m_PAT = df_gtruth_pipeline['area'][idx_good * ~idx_f * idx_pat]
area_gtruth_pipeline_good_m_MAT = df_gtruth_pipeline['area'][idx_good * ~idx_f * ~idx_pat]
area_gtruth_pipeline_bad_f_PAT = df_gtruth_pipeline['area'][~idx_good * idx_f * idx_pat]
area_gtruth_pipeline_bad_f_MAT = df_gtruth_pipeline['area'][~idx_good * idx_f * ~idx_pat]
area_gtruth_pipeline_bad_m_PAT = df_gtruth_pipeline['area'][~idx_good * ~idx_f * idx_pat]
area_gtruth_pipeline_bad_m_MAT = df_gtruth_pipeline['area'][~idx_good * ~idx_f * ~idx_pat]
# plot results
if DEBUG:
plt.clf()
plt.boxplot((area_gtruth_f_PAT, area_gtruth_pipeline_good_f_PAT, area_gtruth_pipeline_bad_f_PAT,
area_gtruth_f_MAT, area_gtruth_pipeline_good_f_MAT, area_gtruth_pipeline_bad_f_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Female')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.ylim((0, 9000))
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0049_area_boxplots_quality_rejection_bias_female_quality_prop_band_focal_loss.png'))
plt.clf()
plt.boxplot((area_gtruth_m_PAT, area_gtruth_pipeline_good_m_PAT, area_gtruth_pipeline_bad_m_PAT,
area_gtruth_m_MAT, area_gtruth_pipeline_good_m_MAT, area_gtruth_pipeline_bad_m_MAT),
notch=True, labels=('PAT$_{GT}$', 'PAT$_{GT/P,good}$', 'PAT$_{GT/P,bad}$',
'MAT$_{GT}$', 'MAT$_{GT/P,good}$', 'MAT$_{GT/P,bad}$'),
positions=(0, 1, 2, 4, 5, 6))
plt.ylabel('area ($\mu m^2)$', fontsize=14)
plt.title('Male')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.ylim((0, 15000))
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0049_area_boxplots_quality_rejection_bias_male_quality_prop_band_focal_loss.png'))
# Compute confusion matrix for all cells together
if DEBUG:
y_true = df_gtruth_pipeline['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='All cells',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# confusion matrix for females
df_gtruth_pipeline_female = df_gtruth_pipeline.loc[df_gtruth_pipeline['sex'] == 'f', :]
y_true = df_gtruth_pipeline_female['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline_female['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='Female',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# confusion matrix for males
df_gtruth_pipeline_male = df_gtruth_pipeline.loc[df_gtruth_pipeline['sex'] == 'm', :]
y_true = df_gtruth_pipeline_male['dice'] >= dice_threshold
y_pred = df_gtruth_pipeline_male['quality'] >= quality_threshold
cytometer.utils.plot_confusion_matrix(y_true, y_pred,
normalize=True,
title='Male',
xlabel='Predict Quality $\geq$ 0.5',
ylabel='Ground-truth Dice $\geq$ 0.9',
cmap=plt.cm.Blues)
# compute sensitivity and specificity over intervals of cell area
area_intervals = list(range(0, 8000, 250)) + [np.Inf, ]
sensitivity = np.zeros(shape=(len(area_intervals) - 1, ))
specificity = np.zeros(shape=(len(area_intervals) - 1, ))
for i in range(len(area_intervals) - 1):
df = df_gtruth_pipeline.loc[np.logical_and(df_gtruth_pipeline['area'] >= area_intervals[i],
df_gtruth_pipeline['area'] < area_intervals[i + 1]), :]
# sensitivity = TP / P
# TP = Dice >= 0.9 & quality >= 0.5
# P = Dice >= 0.9
TP = np.count_nonzero(np.logical_and(df['dice'] >= dice_threshold, df['quality'] >= quality_threshold))
P = np.count_nonzero(df['dice'] >= dice_threshold)
if P == 0:
sensitivity[i] = np.nan
else:
sensitivity[i] = TP / P
# specificity = TN / N
# TN = Dice < 0.9 & quality < 0.5
# N = Dice < 0.9
TN = np.count_nonzero(np.logical_and(df['dice'] < dice_threshold, df['quality'] < quality_threshold))
N = np.count_nonzero(df['dice'] < dice_threshold)
if N == 0:
specificity[i] = np.nan
else:
specificity[i] = TN / N
if DEBUG:
plt.clf()
area_midpoints = (np.array(area_intervals[0:-1]) + np.array(area_intervals[1:]))/2.0
plt.plot(area_midpoints, sensitivity, label='Sensitivity')
plt.plot(area_midpoints, specificity, label='Specificity')
plt.legend()
plt.xlabel('area ($\mu m^2$)', fontsize=14)
plt.tick_params(axis='both', which='major', labelsize=14)
if SAVE_FIGS:
plt.savefig(
os.path.join(figures_dir, 'klf14_b6ntac_exp_0049_pipeline_sensitivity_specificity.png'))
# compute plot of cell area vs. Dice/quality value
if DEBUG:
plt.clf()
plt.subplot(121)
plt.plot(df_gtruth_pipeline['area'][df_gtruth_pipeline['dice'] < dice_threshold],
df_gtruth_pipeline['dice'][df_gtruth_pipeline['dice'] < dice_threshold], '.C0')
plt.plot(df_gtruth_pipeline['area'][df_gtruth_pipeline['dice'] >= dice_threshold],
df_gtruth_pipeline['dice'][df_gtruth_pipeline['dice'] >= dice_threshold], '.C1')
plt.tick_params(axis='both', which='major', labelsize=14)
plt.xlabel('Cell area', fontsize=14)
plt.ylabel('Dice', fontsize=14)
plt.subplot(122)
# quality < 0.5, dice < 0.9
idx = (df_gtruth_pipeline['quality'] < quality_threshold) * (df_gtruth_pipeline['dice'] < dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C0', label="D<0.9, Q<0.5")
# quality >= 0.5, dice < 0.9
idx = (df_gtruth_pipeline['quality'] >= quality_threshold) * (df_gtruth_pipeline['dice'] < dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C1', label="D<0.9, Q$\geq$0.5")
# quality < 0.5, dice >= 0.9
idx = (df_gtruth_pipeline['quality'] < quality_threshold) * (df_gtruth_pipeline['dice'] >= dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C2', label="D$\geq$0.9, Q<0.5")
# quality >= 0.5, dice >= 0.9
idx = (df_gtruth_pipeline['quality'] >= quality_threshold) * (df_gtruth_pipeline['dice'] >= dice_threshold)
plt.plot(df_gtruth_pipeline['dice'][idx], df_gtruth_pipeline['quality'][idx], '.C3', label="D$\geq$0.9, Q$\geq$0.5")
plt.tick_params(axis='both', which='major', labelsize=14)
plt.legend()
plt.xlabel('Dice', fontsize=14)
plt.ylabel('Quality', fontsize=14)
# plot Dice vs. quality, and colour according to size
plt.clf()
plt.scatter(df_gtruth_pipeline['dice'], df_gtruth_pipeline['quality'], c=np.log(df_gtruth_pipeline['area']+1), s=5)
plt.colorbar()
plt.tick_params(axis='both', which='major', labelsize=14)
plt.xlabel('Dice', fontsize=14)
plt.ylabel('Quality', fontsize=14)
'''
************************************************************************************************************************
Pipeline automatic extraction applied to full slides (both female, one MAT and one PAT).
Areas computed with exp 0043.
************************************************************************************************************************
'''
'''Load area data
'''
# list of histology files
files_list = glob.glob(os.path.join(data_dir, 'KLF14*.ndpi'))
# "KLF14-B6NTAC-MAT-18.2b 58-16 B3 - 2016-02-03 11.01.43.ndpi"
# file_i = 10; file = files_list[file_i]
# "KLF14-B6NTAC-36.1a PAT 96-16 C1 - 2016-02-10 16.12.38.ndpi"
file_i = 331
file = files_list[file_i]
print('File ' + str(file_i) + '/' + str(len(files_list)) + ': ' + file)
# name of file to save annotations
annotations_file = os.path.basename(file)
annotations_file = os.path.splitext(annotations_file)[0]
annotations_file = os.path.join(annotations_dir, annotations_file + '.json')
# name of file to save areas and contours
results_file = os.path.basename(file)
results_file = os.path.splitext(results_file)[0]
results_file = os.path.join(results_dir, results_file + '.npz')
# load areas
results = np.load(results_file)
area_full_pipeline_f_PAT = np.concatenate(tuple(results['areas'])) * 1e12
# "KLF14-B6NTAC-MAT-17.1b 45-16 C1 - 2016-02-01 12.23.50.ndpi"
file_i = 55
file = files_list[file_i]
print('File ' + str(file_i) + '/' + str(len(files_list)) + ': ' + file)
# name of file to save annotations
annotations_file = os.path.basename(file)
annotations_file = os.path.splitext(annotations_file)[0]
annotations_file = os.path.join(annotations_dir, annotations_file + '.json')
# name of file to save areas and contours
results_file = os.path.basename(file)
results_file = os.path.splitext(results_file)[0]
results_file = os.path.join(results_dir, results_file + '.npz')
# load areas
results = np.load(results_file)
area_full_pipeline_f_MAT = np.concatenate(tuple(results['areas'])) * 1e12
'''Compare PAT and MAT populations
'''
# plot boxplots
plt.clf()
plt.boxplot((area_full_pipeline_f_PAT, area_full_pipeline_f_MAT), notch=True, labels=('PAT', 'MAT'))
'''
************************************************************************************************************************
Compare ground truth to pipeline cells
************************************************************************************************************************
'''
plt.clf()
plt.subplot(121)
plt.boxplot((area_gtruth_f_PAT, area_full_pipeline_f_PAT), notch=True, labels=('GT', 'Pipeline'))
plt.title('Female PAT')
plt.ylabel('area (um^2)', fontsize=14)
plt.tick_params(axis='both', which='major', labelsize=14)
plt.subplot(122)
plt.boxplot((area_gtruth_f_MAT, area_full_pipeline_f_MAT), notch=True, labels=('GT', 'Pipeline'))
plt.title('Female MAT')
plt.tick_params(axis='both', which='major', labelsize=14)
'''
************************************************************************************************************************
Distribution of cell areas in the training data set
************************************************************************************************************************
'''
# we assume that we have computed the areas in the training dataset at the beginning of this script, creating the
# dataframe df_gtruth
area_intervals = list(range(0, 8000, 250)) + [np.Inf, ]
area_midpoints = (np.array(area_intervals[0:-1]) + np.array(area_intervals[1:]))/2.0
if DEBUG:
plt.clf()
plt.hist(df_gtruth['area'], bins=area_intervals, density=False)
plt.xlabel('area ($\mu m^2$)', fontsize=14)
plt.ylabel('number of cells', fontsize=14)
plt.tick_params(axis='both', which='major', labelsize=14)
| 46.336061
| 140
| 0.616478
| 10,746
| 79,281
| 4.270519
| 0.05509
| 0.101894
| 0.088558
| 0.023796
| 0.91713
| 0.907106
| 0.899218
| 0.896995
| 0.891155
| 0.877558
| 0
| 0.022288
| 0.231468
| 79,281
| 1,710
| 141
| 46.363158
| 0.730888
| 0.128492
| 0
| 0.881944
| 0
| 0
| 0.10971
| 0.030442
| 0
| 0
| 0
| 0
| 0.002976
| 1
| 0
| false
| 0
| 0.017857
| 0
| 0.017857
| 0.006944
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
523e840b8f6597763df1e62ebc5e24dc41374dbe
| 2,045
|
py
|
Python
|
test.py
|
minhhn2910/QPyTorch
|
bb7e88b9004c18ae3df9a20b934f5a156a6ae557
|
[
"MIT"
] | 4
|
2020-09-15T20:47:38.000Z
|
2021-04-22T06:51:59.000Z
|
test.py
|
minhhn2910/QPyTorch
|
bb7e88b9004c18ae3df9a20b934f5a156a6ae557
|
[
"MIT"
] | 3
|
2021-04-12T06:52:17.000Z
|
2021-05-28T06:00:32.000Z
|
test.py
|
minhhn2910/QPyTorch
|
bb7e88b9004c18ae3df9a20b934f5a156a6ae557
|
[
"MIT"
] | 5
|
2020-07-29T03:43:02.000Z
|
2021-02-15T11:46:37.000Z
|
import torch
import qtorch
from qtorch.quant import posit_quantize, configurable_table_quantize
#full_precision_tensor = torch.rand(5).cuda()
import numpy as np
a = np.random.rand(10) * 20-10
table = np.array(range(-10,10))
table_tensor = torch.tensor(table,dtype=torch.float)
full_precision_tensor = torch.tensor(a,dtype=torch.float)
print("Full Precision: {}".format(full_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor, nsize=4, es=1, rounding="nearest")
print("Low Precision P(4,1): {}".format(low_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor.cuda(), nsize=4, es=1, rounding="nearest")
print("Low Precision P(4,1) CUDA: {}".format(low_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor, nsize=5, es=1, rounding="nearest")
print("Low Precision P(5,1): {}".format(low_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor.cuda(), nsize=5, es=1, rounding="nearest")
print("Low Precision P(5,1) CUDA: {}".format(low_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor, nsize=15, es=2, rounding="nearest")
print("Low Precision P(15,2): {}".format(low_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor.cuda(), nsize=15, es=2, rounding="nearest")
print("Low Precision P(15,2) CUDA: {}".format(low_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor, nsize=7, es=2, rounding="nearest")
print("Low Precision P(7,2): {}".format(low_precision_tensor))
low_precision_tensor = posit_quantize(full_precision_tensor.cuda(), nsize=7, es=2, rounding="nearest")
print("Low Precision P(7,2) CUDA: {}".format(low_precision_tensor))
'''
low_precision_tensor = configurable_table_quantize(full_precision_tensor, table_tensor)
print(": TableLookup sample {}".format(low_precision_tensor))
low_precision_tensor = configurable_table_quantize(full_precision_tensor.cuda(), table_tensor)
print(": TableLookup sample CUDA {}".format(low_precision_tensor))
'''
| 49.878049
| 103
| 0.787775
| 299
| 2,045
| 5.107023
| 0.137124
| 0.324165
| 0.235756
| 0.194499
| 0.841519
| 0.777341
| 0.748527
| 0.748527
| 0.748527
| 0.745907
| 0
| 0.024724
| 0.070416
| 2,045
| 40
| 104
| 51.125
| 0.778538
| 0.021516
| 0
| 0
| 0
| 0
| 0.171327
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.16
| 0
| 0.16
| 0.36
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
525aa41d5ed94b54ade13b392567d87e111f6908
| 12,364
|
py
|
Python
|
tf_quant_finance/models/hull_white/zero_coupon_bond_option_test.py
|
jeorme/tf-quant-finance
|
841d6134a1f594252bf23df214008b7dbadb0873
|
[
"Apache-2.0"
] | 2
|
2021-09-22T18:31:28.000Z
|
2022-03-17T23:32:22.000Z
|
tf_quant_finance/models/hull_white/zero_coupon_bond_option_test.py
|
Aarif1430/tf-quant-finance
|
9372eb1ddf2b48cb1a3d4283bc67a10647ddc7a6
|
[
"Apache-2.0"
] | null | null | null |
tf_quant_finance/models/hull_white/zero_coupon_bond_option_test.py
|
Aarif1430/tf-quant-finance
|
9372eb1ddf2b48cb1a3d4283bc67a10647ddc7a6
|
[
"Apache-2.0"
] | 1
|
2021-02-16T12:08:41.000Z
|
2021-02-16T12:08:41.000Z
|
# Lint as: python3
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for zero_coupon_bond_option.py."""
from absl.testing import parameterized
import numpy as np
import tensorflow.compat.v2 as tf
import tf_quant_finance as tff
from tensorflow.python.framework import test_util # pylint: disable=g-direct-tensorflow-import
# @test_util.run_all_in_graph_and_eager_modes
class HullWhiteBondOptionTest(parameterized.TestCase, tf.test.TestCase):
def setUp(self):
self.mean_reversion_1d = [0.03]
self.volatility_1d = [0.02]
self.volatility_time_dep_1d = [0.01, 0.02]
self.mean_reversion_2d = [0.03, 0.06]
self.volatility_2d = [0.02, 0.01]
super(HullWhiteBondOptionTest, self).setUp()
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_correctness_1d(self, use_analytic_pricing, error_tol):
"""Tests model with constant parameters in 1 dimension."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([1.0])
maturities = np.array([5.0])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries)
price = tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
dim=1,
mean_reversion=self.mean_reversion_1d,
volatility=self.volatility_1d,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
self.assertEqual(price.dtype, dtype)
self.assertAllEqual(price.shape, [1, 1])
price = self.evaluate(price)
self.assertAllClose(price, [[0.02817777]], rtol=error_tol, atol=error_tol)
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_xla(self, use_analytic_pricing, error_tol):
"""Tests model with XLA."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([1.0])
maturities = np.array([5.0])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries)
@tf.function
def xla_fn():
return tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
dim=1,
mean_reversion=self.mean_reversion_1d,
volatility=self.volatility_1d,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
price_xla = tf.xla.experimental.compile(xla_fn)
price = self.evaluate(price_xla)[0]
self.assertAllClose(price, [[0.02817777]], rtol=error_tol, atol=error_tol)
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_correctness_time_dep_1d(self, use_analytic_pricing, error_tol):
"""Tests model with piecewise constant volatility in 1 dimension."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([1.0])
maturities = np.array([5.0])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries)
volatility = tff.math.piecewise.PiecewiseConstantFunc(
jump_locations=[0.5], values=self.volatility_time_dep_1d,
dtype=dtype)
price = tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
dim=1,
mean_reversion=self.mean_reversion_1d,
volatility=volatility,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
self.assertEqual(price.dtype, dtype)
self.assertAllEqual(price.shape, [1, 1])
price = self.evaluate(price)
self.assertAllClose(price, [[0.02237839]], rtol=error_tol, atol=error_tol)
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_1d_batch(self, use_analytic_pricing, error_tol):
"""Tests model with 1d batch of options."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([1.0, 1.0, 1.0])
maturities = np.array([5.0, 5.0, 5.0])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries)
price = tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
dim=1,
mean_reversion=self.mean_reversion_1d,
volatility=self.volatility_1d,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
self.assertEqual(price.dtype, dtype)
self.assertAllEqual(price.shape, [3, 1])
price = self.evaluate(price)
self.assertAllClose(price, [[0.02817777], [0.02817777], [0.02817777]],
rtol=error_tol, atol=error_tol)
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_2d_batch(self, use_analytic_pricing, error_tol):
"""Tests model with 2d batch of options."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([[1.0, 1.0], [2.0, 2.0]])
maturities = np.array([[5.0, 5.0], [4.0, 4.0]])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries)
price = tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
dim=1,
mean_reversion=self.mean_reversion_1d,
volatility=self.volatility_1d,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
self.assertEqual(price.dtype, dtype)
self.assertAllEqual(price.shape, [2, 2, 1])
price = self.evaluate(price)
expected = [[[0.02817777], [0.02817777]], [[0.02042677], [0.02042677]]]
self.assertAllClose(price, expected, rtol=error_tol, atol=error_tol)
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_correctness_2d(self, use_analytic_pricing, error_tol):
"""Tests model with constant parameters in 2 dimension."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([1.0])
maturities = np.array([5.0])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries)
price = tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
dim=2,
mean_reversion=self.mean_reversion_2d,
volatility=self.volatility_2d,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
self.assertEqual(price.dtype, dtype)
self.assertAllEqual(price.shape, [1, 2])
price = self.evaluate(price)
self.assertAllClose(price, [[0.02817777, 0.01309971]],
rtol=error_tol, atol=error_tol)
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_mixed_1d_batch_2d(self, use_analytic_pricing, error_tol):
"""Tests mixed 1d batch with constant parameters in 2 dimension."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([1.0, 1.0, 2.0])
maturities = np.array([5.0, 6.0, 4.0])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries)
price = tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
dim=2,
mean_reversion=self.mean_reversion_2d,
volatility=self.volatility_2d,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
self.assertEqual(price.dtype, dtype)
self.assertAllEqual(price.shape, [3, 2])
price = self.evaluate(price)
expected = [[0.02817777, 0.01309971], [0.03436008, 0.01575343],
[0.02042677, 0.00963248]]
self.assertAllClose(price, expected, rtol=error_tol, atol=error_tol)
@parameterized.named_parameters(
{
'testcase_name': 'analytic',
'use_analytic_pricing': True,
'error_tol': 1e-8,
}, {
'testcase_name': 'simulation',
'use_analytic_pricing': False,
'error_tol': 1e-4,
})
def test_call_put(self, use_analytic_pricing, error_tol):
"""Tests mixed 1d batch with constant parameters in 2 dimension."""
dtype = tf.float64
discount_rate_fn = lambda x: 0.01 * tf.ones_like(x, dtype=dtype)
expiries = np.array([1.0, 1.0, 2.0])
maturities = np.array([5.0, 6.0, 4.0])
strikes = np.exp(-0.01 * maturities) / np.exp(-0.01 * expiries) -0.01
price = tff.models.hull_white.bond_option_price(
strikes=strikes,
expiries=expiries,
maturities=maturities,
is_call_options=[True, False, False],
dim=2,
mean_reversion=self.mean_reversion_2d,
volatility=self.volatility_2d,
discount_rate_fn=discount_rate_fn,
use_analytic_pricing=use_analytic_pricing,
num_samples=500000,
time_step=0.1,
random_type=tff.math.random.RandomType.PSEUDO_ANTITHETIC,
dtype=dtype)
self.assertEqual(price.dtype, dtype)
self.assertAllEqual(price.shape, [3, 2])
price = self.evaluate(price)
expected = [[0.03325893, 0.01857569], [0.02945686, 0.01121538],
[0.01579646, 0.0054692]]
self.assertAllClose(price, expected, rtol=error_tol, atol=error_tol)
if __name__ == '__main__':
tf.test.main()
| 36.152047
| 95
| 0.649062
| 1,590
| 12,364
| 4.82956
| 0.128302
| 0.057299
| 0.093762
| 0.016669
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| 0.818726
| 0.818726
| 0.818596
| 0.805834
| 0.800104
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| 0.059603
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| 12,364
| 341
| 96
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0
| 7
|
871ab81fc0d01cd1852e1b528523696997dbff51
| 129
|
py
|
Python
|
fbExceptionMeansSocketUnknownAddress.py
|
SkyLined/mTCPIPConnection
|
52f6152a83a163c9f5a45c3fd6edc840c8e72a3b
|
[
"CC-BY-4.0"
] | 1
|
2021-01-30T07:26:59.000Z
|
2021-01-30T07:26:59.000Z
|
fbExceptionMeansSocketUnknownAddress.py
|
SkyLined/mTCPIPConnection
|
52f6152a83a163c9f5a45c3fd6edc840c8e72a3b
|
[
"CC-BY-4.0"
] | 1
|
2020-06-21T04:16:25.000Z
|
2020-06-23T09:33:35.000Z
|
fbExceptionMeansSocketUnknownAddress.py
|
SkyLined/mTCPIPConnection
|
52f6152a83a163c9f5a45c3fd6edc840c8e72a3b
|
[
"CC-BY-4.0"
] | null | null | null |
import socket;
def fbExceptionMeansSocketHostnameCannotBeResolved(oException):
return isinstance(oException, socket.gaierror);
| 32.25
| 63
| 0.860465
| 10
| 129
| 11.1
| 0.8
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| 0
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| 0
| 0
| 0.069767
| 129
| 4
| 64
| 32.25
| 0.925
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0
| 7
|
5e6b6875fa78c29e10b6d18a8dfc7e109cd4b56e
| 25,024
|
py
|
Python
|
stochoptim/stochprob/facility_location/facility_location_problem_multistage.py
|
julienkeutchayan/StochOptim
|
925e1b6f2613d982439e4fd1939e0dd34c5ef59d
|
[
"MIT"
] | 9
|
2020-10-27T19:16:24.000Z
|
2022-03-28T11:14:44.000Z
|
stochoptim/stochprob/facility_location/facility_location_problem_multistage.py
|
julienkeutchayan/StochOptim
|
925e1b6f2613d982439e4fd1939e0dd34c5ef59d
|
[
"MIT"
] | null | null | null |
stochoptim/stochprob/facility_location/facility_location_problem_multistage.py
|
julienkeutchayan/StochOptim
|
925e1b6f2613d982439e4fd1939e0dd34c5ef59d
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
import numpy as np
from itertools import product
from .facility_location_solution import FacilityLocationSolution
from ..stochastic_problem_basis import StochasticProblemBasis
class FacilityLocationProblemMultistage(StochasticProblemBasis):
"""Three-Stage Facility Location Problem.
Argument:
---------
param: dict with keys and values:
"pos_client": 2d-array of shape (n_client_locations, 2)
"pos_facility": 2d-array of shape (n_facility_locations, 2)
"opening_cost": 1d-array of shape (n_facility_locations,)
"facility_capacity": 1d-array of shape (n_facility_locations,)
"penalty": 1d-array of shape (n_facility_locations,)
"shipping_cost": (optional) 2d-array of shape (n_client_locations, n_facility_locations)
"resources": (optional) 2d-array of shape (n_client_locations, n_facility_locations)
"max_facilities": int
"min_facilities_in_zone": 1d-array of shape (n_zones,)
"facility_in_zone": 1d-array of shape (n_facility_locations,) (of int values in [0, n_zones-1])
If the keys "shipping_cost" and/or "resources" are not provided, they are computed
from the distances between facilities and clients (see methods: resources() and
shipping_cost()).
"""
def __init__(self, param):
self.param = param
self.n_facility_locations = self.param['pos_facility'].shape[0]
self.n_client_locations = self.param['pos_client'].shape[0]
self.n_zones = self.param['min_facilities_in_zone'].shape[0]
# sets
self.client_locations = range(self.n_client_locations)
self.facility_locations = range(self.n_facility_locations)
self.zones = range(self.n_zones)
# compute the distances between clients and facilities
# this distance is the resource consumed by client c served by facility f
self.dist = 30 * np.linalg.norm(self.pos_client()[:, np.newaxis, :] \
- self.pos_facility()[np.newaxis, :, :], axis=2)
# stochastic problem information
StochasticProblemBasis.__init__(self,
name='Facility Location Problem Multistage',
n_stages=3,
objective_sense='min',
is_obj_random=False,
is_mip=True,
solution_class=FacilityLocationSolution)
# --- Problem definition ---
def decision_variables_definition(self, stage):
"""For each decision variables of type {y_{t,i} \in A : i \in I} where I is an indexing set
(a list of tuples), y_{t,i} is of type A (with A = binary (B), or integer (I), or continuous (C)),
and lb <= y_{t,i} <= ub, this function generates a 5-tuple of the form: ('y', I, lb, ub, A)
under the conditon: stage == t. (lb and ub can be two lists provided they have the same size as I)"""
if stage == 0:
yield 'x', self.facility_locations, 0, 1, 'B'
elif stage == 1:
yield 'y', list(product(self.client_locations, self.facility_locations)), 0, 1, 'B'
elif stage == 2:
yield 'z', self.facility_locations, 0, None, 'C'
def random_variables_definition(self, stage):
"""For each random variable of type {xi_{stage,i} : i \in I} where I is an indexing set (an iterable),
this method generates a 2-tuple of the form ('xi', I)"""
if stage == 1:
yield 'h', self.client_locations
elif stage == 2:
yield 'd', self.client_locations
def objective(self):
"""Returns the problem's objective function"""
return self.dot(self.x(), self.opening_cost()) \
+ self.dot(self.y(), self.shipping_cost().flatten()) \
+ self.dot(self.z(), self.penalty())
def deterministic_linear_constraints(self, stage):
"""Generates all the problem's constraints that do not depend on the random parameters"""
if stage == 0:
yield self.max_facility_constraint()
yield self.min_facility_in_zone_constraint()
if stage == 1:
pass
elif stage == 2:
yield self.resource_consumption_constraint()
def random_linear_constraints(self, stage):
"""Generates all the problem's constraints that depend on the random parameters"""
if stage == 1:
yield self.assignment_client_constraint()
# ---- Decision variables ----
def x(self, f=None):
"""x_{f} = 1 if facility f is open, 0 otherwise"""
return self.get_dvar(0, 'x', f)
def y(self, c=None, f=None):
"""y_{c,f} = 1 if facility f ships to client c, 0 otherwise"""
if c is None and f is None:
return self.get_dvar(1, 'y')
elif c is None and f is not None:
return self.get_dvar(1, 'y').reshape(-1, self.n_facility_locations)[:, f]
elif c is not None and f is None:
return self.get_dvar(1, 'y').reshape(self.n_client_locations, -1)[c, :]
else:
return self.get_dvar(1, 'y', (c, f))
def z(self, f=None):
"""z_{f} = penalty for overloading facility f"""
return self.get_dvar(2, 'z', f)
# ---- Random variables ----
def h(self, c=None):
"""h_{c} = 1 if client c is present in scenario s, 0 otherwise"""
return self.get_rvar(1, 'h', c)
def d(self, c=None):
"""d_{c}: demand form client c"""
return self.get_rvar(2, 'd', c)
# --- Precomputation ---
def precompute_decision_variables(self, stage):
pass
def precompute_parameters(self, stage):
pass
# --- Sanity check ---
def sanity_check(self, stage):
pass
# --- Parameters ---
def pos_client(self, c=None):
"""Position of client c"""
pos = np.array(self.param["pos_client"])
return pos if c is None else pos[c]
def pos_facility(self, f=None):
"""Position of facility f"""
pos = np.array(self.param["pos_facility"])
return pos if f is None else pos[f]
def opening_cost(self, f=None):
"""Cost of locating a facility f"""
cost = np.array(self.param["opening_cost"])
return cost if f is None else cost[f]
def capacity(self, f=None):
"""Facility capacity"""
return self.param['facility_capacity'][f]
def shipping_cost(self, c=None, f=None):
if self.param.get('shipping_cost') is None:
return self.distance(c, f) - 1
else:
if c is None and f is None: return self.param.get('shipping_cost')
elif c is None and f is not None: return self.param.get('shipping_cost')[:, f]
elif c is not None and f is None: return self.param.get('shipping_cost')[c, :]
else: return self.param.get('shipping_cost')[c, f]
def resources(self, c=None, f=None):
"""Resources consumed by facility f shipping to client c"""
if self.param.get('resources') is None:
return self._resources_from_distance(c, f)
else:
return self._resource_from_input_array(c, f)
def _resources_from_distance(self, c=None, f=None):
"""Resources consumed by facility f shipping to client c"""
if c is None and f is None:
return self.distance(c, f) + self.d(c)[:, np.newaxis]
else:
return self.distance(c, f) + self.d(c)
def _resource_from_input_array(self, c=None, f=None):
if c is None and f is None: return self.param.get('resources') + self.d(c)[:, np.newaxis]
elif c is None and f is not None: return self.param.get('resources')[:, f] + self.d(c)
elif c is not None and f is None: return self.param.get('resources')[c, :] + self.d(c)
else: return self.param.get('resources')[c, f] + self.d(c)
def max_facilities(self):
"""Upper bound on the total number of facilities that can be located"""
return self.param["max_facilities"]
def min_facilities(self, z):
"""Minimum number of facilities to be located in zone z"""
return self.param["min_facilities_in_zone"][z]
def penalty(self, f=None):
"""Penality for exceeding facility capacity"""
penalty = np.array(self.param["penalty"])
return penalty if f is None else penalty[f]
def is_in_zone(self, z):
"""Return a 1d-array with True at pos k if facility k is in zone z"""
return np.array(self.param["facility_in_zone"]) == z
def distance(self, c=None, f=None):
"""Distance between client location c and facility location f"""
if c is None and f is None: return self.dist
elif c is None and f is not None: return self.dist[:, f]
elif c is not None and f is None: return self.dist[c, :]
else: return self.dist[c, f]
# --- constraints ---
def max_facility_constraint(self):
yield self.sum(self.x()) <= self.max_facilities(), "max_facilities"
def min_facility_in_zone_constraint(self):
for zone in self.zones:
yield self.sum(self.x()[self.is_in_zone(zone)]) >= self.min_facilities(zone), f"min_facilities_zone_{zone}"
def resource_consumption_constraint(self):
self.big_M = 10**10
for f in self.facility_locations:
yield self.dot(self.y(f=f), self.resources(f=f)) - self.z(f) <= self.capacity(f) * self.x(f), \
f"resource_facility_{f}"
for c in self.client_locations:
yield self.y(c, f) <= self.x(f)
yield self.z(f) <= self.big_M * self.x(f), f"big_M_penalty_facility_{f}_1"
def assignment_client_constraint(self):
for c in self.client_locations:
yield self.sum(self.y(c=c)) == self.h(c), f"assignment_client_{c}"
# --- Load, save ---
@classmethod
def from_file(cls, path, extension='txt'):
if extension == 'txt':
with open(f'{path}.txt', "r") as f:
file_str = f.read()
file_str = file_str.replace('array', 'np.array')
file_str = file_str.replace('nan', 'np.nan')
param = eval(file_str)
elif extension == 'pickle':
import pickle
with open(f'{path}.pickle', "rb") as f:
param = pickle.load(f)
return cls(param)
def to_file(self, path, extension='txt'):
if extension == 'txt':
np.set_printoptions(threshold=np.inf) # no limit on the number of elements printed in an array
with open(f'{path}.txt', "w") as f:
f.write(repr(self.param).replace("),", "),\n"))
elif extension == 'pickle':
import pickle
with open(f'{path}.pickle', "wb") as f:
pickle.dump(self.param, f)
else:
TypeError(f"Extension should be 'pickle' or 'txt', not {extension}.")
# --- Representation ---
def __repr__(self):
string_problem = StochasticProblemBasis.__repr__(self)
string = ("Network: \n"
f" {self.n_facility_locations} facility locations\n"
f" {self.n_client_locations} client locations\n"
f" {self.n_zones} zones")
return string_problem + "\n" + string
class FacilityLocationProblemMultistageCapacity(StochasticProblemBasis):
"""Three-Stage Facility Location Problem with capacity decisions at 2nd stage.
Argument:
---------
param: dict with keys and values:
"pos_client": 2d-array of shape (n_client_locations, 2)
"pos_facility": 2d-array of shape (n_facility_locations, 2)
"opening_cost": 1d-array of shape (n_facility_locations,)
"penalty": 1d-array of shape (n_facility_locations,)
"shipping_cost": (optional) 2d-array of shape (n_client_locations, n_facility_locations)
"resources": (optional) 2d-array of shape (n_client_locations, n_facility_locations)
"max_facilities": int
"min_facilities_in_zone": 1d-array of shape (n_zones,)
"facility_in_zone": 1d-array of shape (n_facility_locations,) (of int values in [0, n_zones-1])
If the keys "shipping_cost" and/or "resources" are not provided, they are computed
from the distances between facilities and clients (see methods: resources() and
shipping_cost()).
"""
def __init__(self, param):
self.param = param
self.n_facility_locations = self.param['pos_facility'].shape[0]
self.n_client_locations = self.param['pos_client'].shape[0]
self.n_zones = self.param['min_facilities_in_zone'].shape[0]
# sets
self.client_locations = range(self.n_client_locations)
self.facility_locations = range(self.n_facility_locations)
self.zones = range(self.n_zones)
# compute the distances between clients and facilities
# this distance is the resource consumed by client c served by facility f
self.dist = 30 * np.linalg.norm(self.pos_client()[:, np.newaxis, :] \
- self.pos_facility()[np.newaxis, :, :], axis=2)
# stochastic problem information
StochasticProblemBasis.__init__(self,
name='Facility Location Problem Multistage',
n_stages=3,
objective_sense='min',
is_obj_random=False,
is_mip=True,
solution_class=FacilityLocationSolution)
# --- Problem definition ---
def decision_variables_definition(self, stage):
"""For each decision variables of type {y_{t,i} \in A : i \in I} where I is an indexing set
(a list of tuples), y_{t,i} is of type A (with A = binary (B), or integer (I), or continuous (C)),
and lb <= y_{t,i} <= ub, this function generates a 5-tuple of the form: ('y', I, lb, ub, A)
under the conditon: stage == t. (lb and ub can be two lists provided they have the same size as I)"""
if stage == 0:
yield 'x', self.facility_locations, 0, 1, 'B'
elif stage == 1:
yield 'u', self.facility_locations, 0, None, 'C'
elif stage == 2:
yield 'y', list(product(self.client_locations, self.facility_locations)), 0, 1, 'B'
yield 'z', self.facility_locations, 0, None, 'C'
yield 'z2', self.facility_locations, 0, None, 'C'
def random_variables_definition(self, stage):
"""For each random variable of type {xi_{stage,i} : i \in I} where I is an indexing set (an iterable),
this method generates a 2-tuple of the form ('xi', I)"""
if stage == 1:
yield 'h', self.client_locations
elif stage == 2:
yield 'd', self.client_locations
def objective(self):
"""Returns the problem's objective function"""
return self.dot(self.x(), self.opening_cost()) \
+ self.dot(self.y(), self.shipping_cost().flatten()) \
+ self.dot(self.z() + self.z2(), self.penalty())
def deterministic_linear_constraints(self, stage):
"""Generates all the problem's constraints that do not depend on the random parameters"""
if stage == 0:
yield self.max_facility_constraint()
yield self.min_facility_in_zone_constraint()
if stage == 1:
pass
elif stage == 2:
pass
def random_linear_constraints(self, stage):
"""Generates all the problem's constraints that depend on the random parameters"""
if stage == 2:
yield self.assignment_client_constraint()
yield self.resource_consumption_constraint()
# ---- Decision variables ----
def x(self, f=None):
"""x_{f} = 1 if facility f is open, 0 otherwise"""
return self.get_dvar(0, 'x', f)
def u(self, f=None):
"""Facility capacity"""
return self.get_dvar(1, 'u', f)
def y(self, c=None, f=None):
"""y_{c,f} = 1 if facility f ships to client c, 0 otherwise"""
if c is None and f is None:
return self.get_dvar(2, 'y')
elif c is None and f is not None:
return self.get_dvar(2, 'y').reshape(-1, self.n_facility_locations)[:, f]
elif c is not None and f is None:
return self.get_dvar(2, 'y').reshape(self.n_client_locations, -1)[c, :]
else:
return self.get_dvar(2, 'y', (c, f))
def z(self, f=None):
"""z_{f} = penalty for overloading facility f"""
return self.get_dvar(2, 'z', f)
def z2(self, f=None):
"""z_{f} = penalty for underloading facility f"""
return self.get_dvar(2, 'z2', f)
# ---- Random variables ----
def h(self, c=None):
"""h_{c} = 1 if client c is present in scenario s, 0 otherwise"""
return self.get_rvar(1, 'h', c)
def d(self, c=None):
"""d_{c}: demand form client c"""
return self.get_rvar(2, 'd', c)
# --- Precomputation ---
def precompute_decision_variables(self, stage):
pass
def precompute_parameters(self, stage):
pass
# --- Sanity check ---
def sanity_check(self, stage):
pass
# --- Parameters ---
def pos_client(self, c=None):
"""Position of client c"""
pos = np.array(self.param["pos_client"])
return pos if c is None else pos[c]
def pos_facility(self, f=None):
"""Position of facility f"""
pos = np.array(self.param["pos_facility"])
return pos if f is None else pos[f]
def opening_cost(self, f=None):
"""Cost of locating a facility f"""
cost = np.array(self.param["opening_cost"])
return cost if f is None else cost[f]
def shipping_cost(self, c=None, f=None):
if self.param.get('shipping_cost') is None:
return self.distance(c, f) - 1
else:
if c is None and f is None: return self.param.get('shipping_cost')
elif c is None and f is not None: return self.param.get('shipping_cost')[:, f]
elif c is not None and f is None: return self.param.get('shipping_cost')[c, :]
else: return self.param.get('shipping_cost')[c, f]
def resources(self, c=None, f=None):
"""Resources consumed by facility f shipping to client c"""
if self.param.get('resources') is None:
return self._resources_from_distance(c, f)
else:
return self._resource_from_input_array(c, f)
def _resources_from_distance(self, c=None, f=None):
"""Resources consumed by facility f shipping to client c"""
if c is None and f is None:
return self.distance(c, f) + self.d(c)[:, np.newaxis]
else:
return self.distance(c, f) + self.d(c)
def _resource_from_input_array(self, c=None, f=None):
if c is None and f is None: return self.param.get('resources') + self.d(c)[:, np.newaxis]
elif c is None and f is not None: return self.param.get('resources')[:, f] + self.d(c)
elif c is not None and f is None: return self.param.get('resources')[c, :] + self.d(c)
else: return self.param.get('resources')[c, f] + self.d(c)
def max_facilities(self):
"""Upper bound on the total number of facilities that can be located"""
return self.param["max_facilities"]
def min_facilities(self, z):
"""Minimum number of facilities to be located in zone z"""
return self.param["min_facilities_in_zone"][z]
def penalty(self, f=None):
"""Penality for exceeding facility capacity"""
penalty = np.array(self.param["penalty"])
return penalty if f is None else penalty[f]
def is_in_zone(self, z):
"""Return a 1d-array with True at pos k if facility k is in zone z"""
return np.array(self.param["facility_in_zone"]) == z
def distance(self, c=None, f=None):
"""Distance between client location c and facility location f"""
if c is None and f is None: return self.dist
elif c is None and f is not None: return self.dist[:, f]
elif c is not None and f is None: return self.dist[c, :]
else: self.dist[c, f]
# --- constraints ---
def max_facility_constraint(self):
yield self.sum(self.x()) <= self.max_facilities(), "max_facilities"
def min_facility_in_zone_constraint(self):
for zone in self.zones:
yield self.sum(self.x()[self.is_in_zone(zone)]) >= self.min_facilities(zone), f"min_facilities_zone_{zone}"
def resource_consumption_constraint(self):
self.big_M = 10**10
for f in self.facility_locations:
yield self.dot(self.y(f=f), self.resources(f=f)) - self.z(f) + self.z2(f) == self.u(f), \
f"resource_facility_{f}"
for c in self.client_locations:
yield self.y(c, f) <= self.x(f)
yield self.z(f) <= self.big_M * self.x(f), f"big_M_penalty_facility_{f}_1"
yield self.z2(f) <= self.big_M * self.x(f), f"big_M_penalty_facility_{f}_2"
yield self.u(f) <= self.big_M * self.x(f), f"big_M_capacity_facility_{f}"
def assignment_client_constraint(self):
for c in self.client_locations:
yield self.sum(self.y(c=c)) == self.h(c), f"assignment_client_{c}"
# --- Load, save ---
@classmethod
def from_file(cls, path, extension='txt'):
if extension == 'txt':
with open(f'{path}.txt', "r") as f:
file_str = f.read()
file_str = file_str.replace('array', 'np.array')
file_str = file_str.replace('nan', 'np.nan')
param = eval(file_str)
elif extension == 'pickle':
import pickle
with open(f'{path}.pickle', "rb") as f:
param = pickle.load(f)
return cls(param)
def to_file(self, path, extension='txt'):
if extension == 'txt':
np.set_printoptions(threshold=np.inf) # no limit on the number of elements printed in an array
with open(f'{path}.txt', "w") as f:
f.write(repr(self.param).replace("),", "),\n"))
elif extension == 'pickle':
import pickle
with open(f'{path}.pickle', "wb") as f:
pickle.dump(self.param, f)
else:
TypeError(f"Extension should be 'pickle' or 'txt', not {extension}.")
# --- Representation ---
def __repr__(self):
string_problem = StochasticProblemBasis.__repr__(self)
string = ("Network: \n"
f" {self.n_facility_locations} facility locations\n"
f" {self.n_client_locations} client locations\n"
f" {self.n_zones} zones")
return string_problem + "\n" + string
from_file = FacilityLocationProblemMultistage.from_file
from_file = FacilityLocationProblemMultistageCapacity.from_file
def generate_random_parameters(n_facility_locations,
n_client_locations,
n_zones,
with_capacity=True,
seed=None):
"""Generate randomly a set of deterministic parameters of the facility location problem"""
if seed is not None:
np.random.seed(seed)
return {"pos_client": np.random.uniform(0, 1, size=(n_client_locations, 2)),
"pos_facility": np.random.uniform(0, 1, size=(n_facility_locations, 2)),
"opening_cost": np.random.randint(40, 81, size=n_facility_locations),
"max_facilities": n_facility_locations,
"facility_capacity": np.random.randint(30, 60, size=n_facility_locations) if with_capacity else None,
"min_facilities_in_zone": np.array([1] * n_zones),
"facility_in_zone": np.random.choice(range(n_zones), size=n_facility_locations),
"penalty": 100 * np.ones(n_facility_locations)}
| 44.926391
| 119
| 0.577006
| 3,341
| 25,024
| 4.17839
| 0.074828
| 0.041547
| 0.030086
| 0.018625
| 0.933238
| 0.916404
| 0.902436
| 0.890831
| 0.887249
| 0.887249
| 0
| 0.008499
| 0.304108
| 25,024
| 557
| 120
| 44.926391
| 0.793155
| 0.240889
| 0
| 0.864407
| 0
| 0
| 0.086051
| 0.024887
| 0
| 0
| 0
| 0
| 0
| 1
| 0.19774
| false
| 0.025424
| 0.022599
| 0
| 0.367232
| 0.00565
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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|
0
| 7
|
5e8ec054a98be93544d62b479dabf577aaff22d6
| 14,489
|
py
|
Python
|
tests/test_backoff.py
|
virtuald/pynsq
|
40a637b02c28edfb7723373b81f7e7b9d5e364ed
|
[
"MIT"
] | null | null | null |
tests/test_backoff.py
|
virtuald/pynsq
|
40a637b02c28edfb7723373b81f7e7b9d5e364ed
|
[
"MIT"
] | null | null | null |
tests/test_backoff.py
|
virtuald/pynsq
|
40a637b02c28edfb7723373b81f7e7b9d5e364ed
|
[
"MIT"
] | null | null | null |
from __future__ import absolute_import
from __future__ import print_function
from __future__ import with_statement
from __future__ import unicode_literals
import os
import sys
import random
import time
from mock import call, patch, create_autospec
from tornado.ioloop import IOLoop
# shunt '..' into sys.path since we are in a 'tests' subdirectory
base_dir = os.path.abspath(os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
if base_dir not in sys.path:
sys.path.insert(0, base_dir)
import nsq
from nsq import event
_conn_port = 4150
def _message_handler(msg):
msg.enable_async()
def _get_reader(io_loop=None, max_in_flight=5):
return nsq.Reader("test", "test",
message_handler=_message_handler,
lookupd_http_addresses=["http://test.local:4161"],
max_in_flight=max_in_flight,
io_loop=io_loop)
def _get_ioloop():
ioloop = create_autospec(IOLoop)
ioloop.time.return_value = 0
return ioloop
def _get_conn(reader):
global _conn_port
with patch('nsq.async.tornado.iostream.IOStream', autospec=True):
conn = reader.connect_to_nsqd('localhost', _conn_port)
_conn_port += 1
conn.trigger(event.READY, conn=conn)
return conn
def _send_message(conn):
msg = _get_message(conn)
conn.trigger(event.MESSAGE, conn=conn, message=msg)
return msg
def _get_message(conn):
msg = nsq.Message("1234", "{}", 1234, 0)
msg.on('finish', conn._on_message_finish)
msg.on('requeue', conn._on_message_requeue)
return msg
def test_backoff_easy():
mock_ioloop = _get_ioloop()
r = _get_reader(mock_ioloop)
conn = _get_conn(r)
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
msg = _send_message(conn)
msg.trigger(event.REQUEUE, message=msg)
assert r.backoff_block is True
assert r.backoff_timer.get_interval() > 0
assert mock_ioloop.add_timeout.called
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
timeout_args[1]()
assert r.backoff_block is False
send_args, send_kwargs = conn.stream.write.call_args
assert send_args[0] == b'RDY 1\n'
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
expected_args = [
b'SUB test test\n',
b'RDY 1\n',
b'RDY 5\n',
b'FIN 1234\n',
b'RDY 0\n',
b'REQ 1234 0\n',
b'RDY 1\n',
b'RDY 5\n',
b'FIN 1234\n'
]
assert conn.stream.write.call_args_list == [call(arg) for arg in expected_args]
def test_backoff_out_of_order():
mock_ioloop = _get_ioloop()
r = _get_reader(mock_ioloop, max_in_flight=4)
conn1 = _get_conn(r)
conn2 = _get_conn(r)
msg = _send_message(conn1)
msg.trigger(event.FINISH, message=msg)
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
msg = _send_message(conn1)
msg.trigger(event.REQUEUE, message=msg)
assert r.backoff_block is True
assert r.backoff_timer.get_interval() > 0
assert mock_ioloop.add_timeout.called
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
msg = _send_message(conn1)
msg.trigger(event.FINISH, message=msg)
assert r.backoff_block is True
assert r.backoff_timer.get_interval() == 0
timeout_args[1]()
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
expected_args = [
b'SUB test test\n',
b'RDY 1\n',
b'RDY 2\n',
b'FIN 1234\n',
b'RDY 0\n',
b'REQ 1234 0\n',
b'FIN 1234\n',
b'RDY 2\n',
]
assert conn1.stream.write.call_args_list == [call(arg) for arg in expected_args]
expected_args = [
b'SUB test test\n',
b'RDY 1\n',
b'RDY 0\n',
b'RDY 2\n'
]
assert conn2.stream.write.call_args_list == [call(arg) for arg in expected_args]
def test_backoff_requeue_recovery():
mock_ioloop = _get_ioloop()
r = _get_reader(mock_ioloop, max_in_flight=2)
conn = _get_conn(r)
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
assert mock_ioloop.add_timeout.call_count == 1
msg = _send_message(conn)
# go into backoff
msg.trigger(event.REQUEUE, message=msg)
assert r.backoff_block is True
assert r.backoff_timer.get_interval() > 0
assert mock_ioloop.add_timeout.call_count == 2
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
# elapse time
timeout_args[1]()
assert r.backoff_block is False
assert r.backoff_timer.get_interval() != 0
msg = _send_message(conn)
# This should not move out of backoff (since backoff=False)
msg.trigger(event.REQUEUE, message=msg, backoff=False)
assert r.backoff_block is True
assert r.backoff_timer.get_interval() != 0
assert mock_ioloop.add_timeout.call_count == 3
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
# elapse time
timeout_args[1]()
assert r.backoff_block is False
assert r.backoff_timer.get_interval() != 0
# this should move out of backoff state
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
print(conn.stream.write.call_args_list)
expected_args = [
b'SUB test test\n',
b'RDY 1\n',
b'RDY 2\n',
b'FIN 1234\n',
b'RDY 0\n',
b'REQ 1234 0\n',
b'RDY 1\n',
b'RDY 0\n',
b'REQ 1234 0\n',
b'RDY 1\n',
b'RDY 2\n',
b'FIN 1234\n'
]
assert conn.stream.write.call_args_list == [call(arg) for arg in expected_args]
def test_backoff_hard():
mock_ioloop = _get_ioloop()
r = _get_reader(io_loop=mock_ioloop)
conn = _get_conn(r)
expected_args = [b'SUB test test\n', b'RDY 1\n', b'RDY 5\n']
num_fails = 0
fail = True
last_timeout_time = 0
for i in range(50):
msg = _send_message(conn)
if fail:
msg.trigger(event.REQUEUE, message=msg)
num_fails += 1
expected_args.append(b'RDY 0\n')
expected_args.append(b'REQ 1234 0\n')
else:
msg.trigger(event.FINISH, message=msg)
num_fails -= 1
expected_args.append(b'RDY 0\n')
expected_args.append(b'FIN 1234\n')
assert r.backoff_block is True
assert r.backoff_timer.get_interval() > 0
assert mock_ioloop.add_timeout.called
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
if timeout_args[0] != last_timeout_time:
timeout_args[1]()
last_timeout_time = timeout_args[0]
assert r.backoff_block is False
expected_args.append(b'RDY 1\n')
fail = True
if random.random() < 0.3 and num_fails > 1:
fail = False
for i in range(num_fails - 1):
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
expected_args.append(b'RDY 0\n')
expected_args.append(b'FIN 1234\n')
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
if timeout_args[0] != last_timeout_time:
timeout_args[1]()
last_timeout_time = timeout_args[0]
expected_args.append(b'RDY 1\n')
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
expected_args.append(b'RDY 5\n')
expected_args.append(b'FIN 1234\n')
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
for i, call in enumerate(conn.stream.write.call_args_list):
print("%d: %s" % (i, call))
assert conn.stream.write.call_args_list == [call(arg) for arg in expected_args]
def test_backoff_many_conns():
mock_ioloop = _get_ioloop()
r = _get_reader(io_loop=mock_ioloop)
num_conns = 5
conns = []
for i in range(num_conns):
conn = _get_conn(r)
conn.expected_args = [b'SUB test test\n', b'RDY 1\n']
conn.fails = 0
conns.append(conn)
fail = True
total_fails = 0
last_timeout_time = 0
conn = random.choice(conns)
for i in range(50):
msg = _send_message(conn)
if r.backoff_timer.get_interval() == 0:
conn.expected_args.append(b'RDY 1\n')
if fail or not conn.fails:
msg.trigger(event.REQUEUE, message=msg)
total_fails += 1
conn.fails += 1
for c in conns:
c.expected_args.append(b'RDY 0\n')
conn.expected_args.append(b'REQ 1234 0\n')
else:
msg.trigger(event.FINISH, message=msg)
total_fails -= 1
conn.fails -= 1
for c in conns:
c.expected_args.append(b'RDY 0\n')
conn.expected_args.append(b'FIN 1234\n')
assert r.backoff_block is True
assert r.backoff_timer.get_interval() > 0
assert mock_ioloop.add_timeout.called
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
if timeout_args[0] != last_timeout_time:
conn = timeout_args[1]()
last_timeout_time = timeout_args[0]
assert r.backoff_block is False
conn.expected_args.append(b'RDY 1\n')
fail = True
if random.random() < 0.3 and total_fails > 1:
fail = False
while total_fails:
print("%r: %d fails (%d total_fails)" % (conn, conn.fails, total_fails))
if not conn.fails:
# force an idle connection
for c in conns:
if c.rdy > 0:
c.last_msg_timestamp = time.time() - 60
c.expected_args.append(b'RDY 0\n')
conn = r._redistribute_rdy_state()
conn.expected_args.append(b'RDY 1\n')
continue
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
total_fails -= 1
conn.fails -= 1
if total_fails > 0:
for c in conns:
c.expected_args.append(b'RDY 0\n')
else:
for c in conns:
c.expected_args.append(b'RDY 1\n')
conn.expected_args.append(b'FIN 1234\n')
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
if timeout_args[0] != last_timeout_time:
conn = timeout_args[1]()
last_timeout_time = timeout_args[0]
if total_fails > 0:
conn.expected_args.append(b'RDY 1\n')
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
for c in conns:
for i, call in enumerate(c.stream.write.call_args_list):
print("%d: %s" % (i, call))
assert c.stream.write.call_args_list == [call(arg) for arg in c.expected_args]
def test_backoff_conns_disconnect():
mock_ioloop = _get_ioloop()
r = _get_reader(io_loop=mock_ioloop)
num_conns = 5
conns = []
for i in range(num_conns):
conn = _get_conn(r)
conn.expected_args = [b'SUB test test\n', b'RDY 1\n']
conn.fails = 0
conns.append(conn)
fail = True
total_fails = 0
last_timeout_time = 0
conn = random.choice(conns)
for i in range(50):
if i % 5 == 0:
if len(r.conns) == num_conns:
conn.trigger(event.CLOSE, conn=conn)
conns.remove(conn)
if conn.rdy and r.backoff_timer.get_interval():
assert r.need_rdy_redistributed
conn = r._redistribute_rdy_state()
if not conn:
conn = random.choice(conns)
else:
conn.expected_args.append(b'RDY 1\n')
continue
else:
c = _get_conn(r)
c.expected_args = [b'SUB test test\n']
c.fails = 0
conns.append(c)
msg = _send_message(conn)
if r.backoff_timer.get_interval() == 0:
conn.expected_args.append(b'RDY 1\n')
if fail or not conn.fails:
msg.trigger(event.REQUEUE, message=msg)
total_fails += 1
conn.fails += 1
for c in conns:
c.expected_args.append(b'RDY 0\n')
conn.expected_args.append(b'REQ 1234 0\n')
else:
msg.trigger(event.FINISH, message=msg)
total_fails -= 1
conn.fails -= 1
for c in conns:
c.expected_args.append(b'RDY 0\n')
conn.expected_args.append(b'FIN 1234\n')
assert r.backoff_block is True
assert r.backoff_timer.get_interval() > 0
assert mock_ioloop.add_timeout.called
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
if timeout_args[0] != last_timeout_time:
conn = timeout_args[1]()
last_timeout_time = timeout_args[0]
assert r.backoff_block is False
conn.expected_args.append(b'RDY 1\n')
fail = True
if random.random() < 0.3 and total_fails > 1:
fail = False
while total_fails:
print("%r: %d fails (%d total_fails)" % (conn, conn.fails, total_fails))
msg = _send_message(conn)
msg.trigger(event.FINISH, message=msg)
total_fails -= 1
conn.fails -= 1
if total_fails > 0:
for c in conns:
c.expected_args.append(b'RDY 0\n')
else:
for c in conns:
c.expected_args.append(b'RDY 1\n')
conn.expected_args.append(b'FIN 1234\n')
timeout_args, timeout_kwargs = mock_ioloop.add_timeout.call_args
if timeout_args[0] != last_timeout_time:
conn = timeout_args[1]()
last_timeout_time = timeout_args[0]
if total_fails > 0:
conn.expected_args.append(b'RDY 1\n')
assert r.backoff_block is False
assert r.backoff_timer.get_interval() == 0
for c in conns:
for i, call in enumerate(c.stream.write.call_args_list):
print("%d: %s" % (i, call))
assert c.stream.write.call_args_list == [call(arg) for arg in c.expected_args]
| 29.211694
| 90
| 0.613293
| 2,100
| 14,489
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| 0.06858
| 0.070008
| 0.074652
| 0.809977
| 0.791285
| 0.776521
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| 0.748184
| 0
| 0.025125
| 0.283042
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| 0.058498
| 0.002455
| 0
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| 0.155673
| 1
| 0.031662
| false
| 0
| 0.031662
| 0.002639
| 0.076517
| 0.01847
| 0
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| 0
| null | 0
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| 0
|
0
| 7
|
5e91c54dba01ef6e5197f33120872bac1121e22f
| 37,641
|
py
|
Python
|
meraki/controllers/clients_controller.py
|
meraki/meraki-python-sdk
|
9894089eb013318243ae48869cc5130eb37f80c0
|
[
"MIT"
] | 37
|
2019-04-24T14:01:33.000Z
|
2022-01-28T01:37:21.000Z
|
meraki/controllers/clients_controller.py
|
ankita66666666/meraki-python-sdk
|
9894089eb013318243ae48869cc5130eb37f80c0
|
[
"MIT"
] | 10
|
2019-07-09T16:35:11.000Z
|
2021-12-07T03:47:53.000Z
|
meraki/controllers/clients_controller.py
|
ankita66666666/meraki-python-sdk
|
9894089eb013318243ae48869cc5130eb37f80c0
|
[
"MIT"
] | 17
|
2019-04-30T23:53:21.000Z
|
2022-02-07T22:57:44.000Z
|
# -*- coding: utf-8 -*-
"""
meraki
This file was automatically generated for meraki by APIMATIC v2.0 ( https://apimatic.io ).
"""
from meraki.api_helper import APIHelper
from meraki.configuration import Configuration
from meraki.controllers.base_controller import BaseController
from meraki.http.auth.custom_header_auth import CustomHeaderAuth
class ClientsController(BaseController):
"""A Controller to access Endpoints in the meraki API."""
def get_device_clients(self,
options=dict()):
"""Does a GET request to /devices/{serial}/clients.
List the clients of a device, up to a maximum of a month ago. The
usage of each client is returned in kilobytes. If the device is a
switch, the switchport is returned; otherwise the switchport field is
null.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
serial -- string -- TODO: type description here. Example:
t_0 -- string -- The beginning of the timespan for the
data. The maximum lookback period is 31 days from
today.
timespan -- float -- The timespan for which the
information will be fetched. If specifying timespan,
do not specify parameter t0. The value must be in
seconds and be less than or equal to 31 days. The
default is 1 day.
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(serial=options.get("serial"))
# Prepare query URL
_url_path = '/devices/{serial}/clients'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'serial': options.get('serial', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_parameters = {
't0': options.get('t_0', None),
'timespan': options.get('timespan', None)
}
_query_builder = APIHelper.append_url_with_query_parameters(_query_builder,
_query_parameters, Configuration.array_serialization)
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_clients(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients.
List the clients that have used this network in the timespan
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
t_0 -- string -- The beginning of the timespan for the
data. The maximum lookback period is 31 days from
today.
timespan -- float -- The timespan for which the
information will be fetched. If specifying timespan,
do not specify parameter t0. The value must be in
seconds and be less than or equal to 31 days. The
default is 1 day.
per_page -- int -- The number of entries per page
returned. Acceptable range is 3 - 1000. Default is
10.
starting_after -- string -- A token used by the server to
indicate the start of the page. Often this is a
timestamp or an ID but it is not limited to those.
This parameter should not be defined by client
applications. The link for the first, last, prev, or
next page in the HTTP Link header should define it.
ending_before -- string -- A token used by the server to
indicate the end of the page. Often this is a
timestamp or an ID but it is not limited to those.
This parameter should not be defined by client
applications. The link for the first, last, prev, or
next page in the HTTP Link header should define it.
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_parameters = {
't0': options.get('t_0', None),
'timespan': options.get('timespan', None),
'perPage': options.get('per_page', None),
'startingAfter': options.get('starting_after', None),
'endingBefore': options.get('ending_before', None)
}
_query_builder = APIHelper.append_url_with_query_parameters(_query_builder,
_query_parameters, Configuration.array_serialization)
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def provision_network_clients(self,
options=dict()):
"""Does a POST request to /networks/{networkId}/clients/provision.
Provisions a client with a name and policy. Clients can be provisioned
before they associate to the network.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
provision_network_clients -- ProvisionNetworkClientsModel
-- TODO: type description here. Example:
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/provision'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json',
'content-type': 'application/json; charset=utf-8'
}
# Prepare and execute request
_request = self.http_client.post(_query_url, headers=_headers, parameters=APIHelper.json_serialize(options.get('provision_network_clients')))
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_client(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients/{clientId}.
Return the client associated with the given identifier. Clients can be
identified by a client key or either the MAC or IP depending on
whether the network uses Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_client_events(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients/{clientId}/events.
Return the events associated with this client. Clients can be
identified by a client key or either the MAC or IP depending on
whether the network uses Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
per_page -- int -- The number of entries per page
returned. Acceptable range is 3 - 100. Default is
100.
starting_after -- string -- A token used by the server to
indicate the start of the page. Often this is a
timestamp or an ID but it is not limited to those.
This parameter should not be defined by client
applications. The link for the first, last, prev, or
next page in the HTTP Link header should define it.
ending_before -- string -- A token used by the server to
indicate the end of the page. Often this is a
timestamp or an ID but it is not limited to those.
This parameter should not be defined by client
applications. The link for the first, last, prev, or
next page in the HTTP Link header should define it.
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/events'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_parameters = {
'perPage': options.get('per_page', None),
'startingAfter': options.get('starting_after', None),
'endingBefore': options.get('ending_before', None)
}
_query_builder = APIHelper.append_url_with_query_parameters(_query_builder,
_query_parameters, Configuration.array_serialization)
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_client_latency_history(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients/{clientId}/latencyHistory.
Return the latency history for a client. Clients can be identified by
a client key or either the MAC or IP depending on whether the network
uses Track-by-IP. The latency data is from a sample of 2% of packets
and is grouped into 4 traffic categories: background, best effort,
video, voice. Within these categories the sampled packet counters are
bucketed by latency in milliseconds.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
t_0 -- string -- The beginning of the timespan for the
data. The maximum lookback period is 791 days from
today.
t_1 -- string -- The end of the timespan for the data. t1
can be a maximum of 791 days after t0.
timespan -- float -- The timespan for which the
information will be fetched. If specifying timespan,
do not specify parameters t0 and t1. The value must be
in seconds and be less than or equal to 791 days. The
default is 1 day.
resolution -- int -- The time resolution in seconds for
returned data. The valid resolutions are: 86400. The
default is 86400.
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/latencyHistory'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_parameters = {
't0': options.get('t_0', None),
't1': options.get('t_1', None),
'timespan': options.get('timespan', None),
'resolution': options.get('resolution', None)
}
_query_builder = APIHelper.append_url_with_query_parameters(_query_builder,
_query_parameters, Configuration.array_serialization)
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_client_policy(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients/{clientId}/policy.
Return the policy assigned to a client on the network. Clients can be
identified by a client key or either the MAC or IP depending on
whether the network uses Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/policy'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def update_network_client_policy(self,
options=dict()):
"""Does a PUT request to /networks/{networkId}/clients/{clientId}/policy.
Update the policy assigned to a client on the network. Clients can be
identified by a client key or either the MAC or IP depending on
whether the network uses Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
update_network_client_policy --
UpdateNetworkClientPolicyModel -- TODO: type
description here. Example:
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/policy'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json',
'content-type': 'application/json; charset=utf-8'
}
# Prepare and execute request
_request = self.http_client.put(_query_url, headers=_headers, parameters=APIHelper.json_serialize(options.get('update_network_client_policy')))
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_client_splash_authorization_status(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients/{clientId}/splashAuthorizationStatus.
Return the splash authorization for a client, for each SSID they've
associated with through splash. Only enabled SSIDs with Click-through
splash enabled will be included. Clients can be identified by a client
key or either the MAC or IP depending on whether the network uses
Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/splashAuthorizationStatus'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def update_network_client_splash_authorization_status(self,
options=dict()):
"""Does a PUT request to /networks/{networkId}/clients/{clientId}/splashAuthorizationStatus.
Update a client's splash authorization. Clients can be identified by a
client key or either the MAC or IP depending on whether the network
uses Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
update_network_client_splash_authorization_status --
UpdateNetworkClientSplashAuthorizationStatusModel --
TODO: type description here. Example:
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/splashAuthorizationStatus'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json',
'content-type': 'application/json; charset=utf-8'
}
# Prepare and execute request
_request = self.http_client.put(_query_url, headers=_headers, parameters=APIHelper.json_serialize(options.get('update_network_client_splash_authorization_status')))
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_client_traffic_history(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients/{clientId}/trafficHistory.
Return the client's network traffic data over time. Usage data is in
kilobytes. This endpoint requires detailed traffic analysis to be
enabled on the Network-wide > General page. Clients can be identified
by a client key or either the MAC or IP depending on whether the
network uses Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
per_page -- int -- The number of entries per page
returned. Acceptable range is 3 - 1000.
starting_after -- string -- A token used by the server to
indicate the start of the page. Often this is a
timestamp or an ID but it is not limited to those.
This parameter should not be defined by client
applications. The link for the first, last, prev, or
next page in the HTTP Link header should define it.
ending_before -- string -- A token used by the server to
indicate the end of the page. Often this is a
timestamp or an ID but it is not limited to those.
This parameter should not be defined by client
applications. The link for the first, last, prev, or
next page in the HTTP Link header should define it.
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/trafficHistory'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_parameters = {
'perPage': options.get('per_page', None),
'startingAfter': options.get('starting_after', None),
'endingBefore': options.get('ending_before', None)
}
_query_builder = APIHelper.append_url_with_query_parameters(_query_builder,
_query_parameters, Configuration.array_serialization)
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
def get_network_client_usage_history(self,
options=dict()):
"""Does a GET request to /networks/{networkId}/clients/{clientId}/usageHistory.
Return the client's daily usage history. Usage data is in kilobytes.
Clients can be identified by a client key or either the MAC or IP
depending on whether the network uses Track-by-IP.
Args:
options (dict, optional): Key-value pairs for any of the
parameters to this API Endpoint. All parameters to the
endpoint are supplied through the dictionary with their names
being the key and their desired values being the value. A list
of parameters that can be used are::
network_id -- string -- TODO: type description here.
Example:
client_id -- string -- TODO: type description here.
Example:
Returns:
mixed: Response from the API. Successful operation
Raises:
APIException: When an error occurs while fetching the data from
the remote API. This exception includes the HTTP Response
code, an error message, and the HTTP body that was received in
the request.
"""
# Validate required parameters
self.validate_parameters(network_id=options.get("network_id"),
client_id=options.get("client_id"))
# Prepare query URL
_url_path = '/networks/{networkId}/clients/{clientId}/usageHistory'
_url_path = APIHelper.append_url_with_template_parameters(_url_path, {
'networkId': options.get('network_id', None),
'clientId': options.get('client_id', None)
})
_query_builder = Configuration.base_uri
_query_builder += _url_path
_query_url = APIHelper.clean_url(_query_builder)
# Prepare headers
_headers = {
'accept': 'application/json'
}
# Prepare and execute request
_request = self.http_client.get(_query_url, headers=_headers)
CustomHeaderAuth.apply(_request)
_context = self.execute_request(_request)
self.validate_response(_context)
# Return appropriate type
return APIHelper.json_deserialize(_context.response.raw_body)
| 44.864124
| 173
| 0.588401
| 4,079
| 37,641
| 5.259868
| 0.072812
| 0.028898
| 0.021254
| 0.025728
| 0.913633
| 0.904731
| 0.898811
| 0.894337
| 0.893778
| 0.891634
| 0
| 0.003067
| 0.350442
| 37,641
| 838
| 174
| 44.917661
| 0.874438
| 0.506124
| 0
| 0.820789
| 1
| 0
| 0.12879
| 0.044916
| 0
| 0
| 0
| 0.02864
| 0
| 1
| 0.043011
| false
| 0
| 0.014337
| 0
| 0.103943
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
5e99798f67eea4ab3a2f5e0bdc3b8049d48e7ac6
| 103
|
py
|
Python
|
__init__.py
|
OpenTMI/opentmi-pyclient
|
034c539d36fe13a2d6538ea421e4c01f00f5687d
|
[
"MIT"
] | null | null | null |
__init__.py
|
OpenTMI/opentmi-pyclient
|
034c539d36fe13a2d6538ea421e4c01f00f5687d
|
[
"MIT"
] | 36
|
2018-06-18T10:03:58.000Z
|
2022-03-30T00:16:31.000Z
|
__init__.py
|
OpenTMI/opentmi-pyclient
|
034c539d36fe13a2d6538ea421e4c01f00f5687d
|
[
"MIT"
] | 1
|
2019-04-17T08:49:24.000Z
|
2019-04-17T08:49:24.000Z
|
#!/usr/bin/env python
from opentmi_client import opentmiclient_main
from opentmi_client import create
| 20.6
| 45
| 0.84466
| 15
| 103
| 5.6
| 0.733333
| 0.261905
| 0.404762
| 0.547619
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106796
| 103
| 4
| 46
| 25.75
| 0.913043
| 0.194175
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
5e99deb5c5ed1f7007a9714063984f4712227776
| 94
|
py
|
Python
|
braise/rebuild_vsm.py
|
alexandercrosson/braise
|
91610a3f7fe47e5e5dd38acf1934ce86c0da113f
|
[
"MIT"
] | null | null | null |
braise/rebuild_vsm.py
|
alexandercrosson/braise
|
91610a3f7fe47e5e5dd38acf1934ce86c0da113f
|
[
"MIT"
] | null | null | null |
braise/rebuild_vsm.py
|
alexandercrosson/braise
|
91610a3f7fe47e5e5dd38acf1934ce86c0da113f
|
[
"MIT"
] | null | null | null |
from doc_collector.doc_collector import get_cleaned_docs_from_db
get_cleaned_docs_from_db()
| 18.8
| 64
| 0.893617
| 16
| 94
| 4.625
| 0.5
| 0.324324
| 0.378378
| 0.486486
| 0.540541
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.074468
| 94
| 4
| 65
| 23.5
| 0.850575
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 7
|
0dba2ed8db6d740931d697898f369d6a971c3bb3
| 2,667
|
py
|
Python
|
tests/test_provider_e_breuninger_netbox.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 507
|
2017-07-26T02:58:38.000Z
|
2022-01-21T12:35:13.000Z
|
tests/test_provider_e_breuninger_netbox.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 135
|
2017-07-20T12:01:59.000Z
|
2021-10-04T22:25:40.000Z
|
tests/test_provider_e_breuninger_netbox.py
|
mjuenema/python-terrascript
|
6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d
|
[
"BSD-2-Clause"
] | 81
|
2018-02-20T17:55:28.000Z
|
2022-01-31T07:08:40.000Z
|
# tests/test_provider_e-breuninger_netbox.py
# Automatically generated by tools/makecode.py (24-Sep-2021 15:22:23 UTC)
def test_provider_import():
import terrascript.provider.e_breuninger.netbox
def test_resource_import():
from terrascript.resource.e_breuninger.netbox import netbox_available_ip_address
from terrascript.resource.e_breuninger.netbox import netbox_cluster
from terrascript.resource.e_breuninger.netbox import netbox_cluster_group
from terrascript.resource.e_breuninger.netbox import netbox_cluster_type
from terrascript.resource.e_breuninger.netbox import netbox_device_role
from terrascript.resource.e_breuninger.netbox import netbox_interface
from terrascript.resource.e_breuninger.netbox import netbox_ip_address
from terrascript.resource.e_breuninger.netbox import netbox_platform
from terrascript.resource.e_breuninger.netbox import netbox_prefix
from terrascript.resource.e_breuninger.netbox import netbox_primary_ip
from terrascript.resource.e_breuninger.netbox import netbox_service
from terrascript.resource.e_breuninger.netbox import netbox_tag
from terrascript.resource.e_breuninger.netbox import netbox_tenant
from terrascript.resource.e_breuninger.netbox import netbox_tenant_group
from terrascript.resource.e_breuninger.netbox import netbox_virtual_machine
from terrascript.resource.e_breuninger.netbox import netbox_vrf
def test_datasource_import():
from terrascript.data.e_breuninger.netbox import netbox_cluster
from terrascript.data.e_breuninger.netbox import netbox_cluster_group
from terrascript.data.e_breuninger.netbox import netbox_device_role
from terrascript.data.e_breuninger.netbox import netbox_interfaces
from terrascript.data.e_breuninger.netbox import netbox_platform
from terrascript.data.e_breuninger.netbox import netbox_prefix
from terrascript.data.e_breuninger.netbox import netbox_tag
from terrascript.data.e_breuninger.netbox import netbox_tenant
from terrascript.data.e_breuninger.netbox import netbox_tenant_group
from terrascript.data.e_breuninger.netbox import netbox_virtual_machines
from terrascript.data.e_breuninger.netbox import netbox_vrf
# TODO: Shortcut imports without namespace for official and supported providers.
# TODO: This has to be moved into a required_providers block.
# def test_version_source():
#
# import terrascript.provider.e_breuninger.netbox
#
# t = terrascript.provider.e_breuninger.netbox.netbox()
# s = str(t)
#
# assert 'https://github.com/e-breuninger/terraform-provider-netbox' in s
# assert '0.2.4' in s
| 33.759494
| 84
| 0.813273
| 352
| 2,667
| 5.928977
| 0.224432
| 0.168663
| 0.252516
| 0.297556
| 0.791088
| 0.773838
| 0.724006
| 0.724006
| 0.396742
| 0.058457
| 0
| 0.006463
| 0.129734
| 2,667
| 78
| 85
| 34.192308
| 0.892719
| 0.191226
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012821
| 0
| 1
| 0.096774
| true
| 0
| 1
| 0
| 1.096774
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 10
|
0deb401ee3b5a1bf1577f83a41337796389dcf79
| 2,643
|
py
|
Python
|
CodingInterview2/25_MergeSortedLists/test_merge_sorted_lists.py
|
hscspring/TheAlgorithms-Python
|
5c2faea1d2d25a9a81a4786e053b0cc58ab46c6f
|
[
"MIT"
] | 10
|
2020-07-06T11:00:58.000Z
|
2022-01-29T09:25:24.000Z
|
CodingInterview2/25_MergeSortedLists/test_merge_sorted_lists.py
|
hscspring/TheAlgorithms-Python
|
5c2faea1d2d25a9a81a4786e053b0cc58ab46c6f
|
[
"MIT"
] | null | null | null |
CodingInterview2/25_MergeSortedLists/test_merge_sorted_lists.py
|
hscspring/TheAlgorithms-Python
|
5c2faea1d2d25a9a81a4786e053b0cc58ab46c6f
|
[
"MIT"
] | 3
|
2020-07-13T06:39:23.000Z
|
2020-08-15T16:29:48.000Z
|
from merge_sorted_lists import merge, merge_recurision, merge2
from merge_sorted_lists import list2link, link2list
def test_no_repeat():
lst1 = [1, 3, 5]
lst2 = [2, 4, 6]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge_recurision(link1, link2)
assert link2list(link) == [1, 2, 3, 4, 5, 6]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge(link1, link2)
assert link2list(link) == [1, 2, 3, 4, 5, 6]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge2(link1, link2)
assert link2list(link) == [1, 2, 3, 4, 5, 6]
def test_repeat():
lst1 = [1, 3, 5]
lst2 = [1, 3, 5]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge_recurision(link1, link2)
assert link2list(link) == [1, 1, 3, 3, 5, 5]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge(link1, link2)
assert link2list(link) == [1, 1, 3, 3, 5, 5]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge2(link1, link2)
assert link2list(link) == [1, 1, 3, 3, 5, 5]
def test_unbanlance():
lst1 = [1, 3, 5, 7, 9]
lst2 = [2, 4]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge_recurision(link1, link2)
assert link2list(link) == [1, 2, 3, 4, 5, 7, 9]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge(link1, link2)
assert link2list(link) == [1, 2, 3, 4, 5, 7, 9]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge2(link1, link2)
assert link2list(link) == [1, 2, 3, 4, 5, 7, 9]
def test_one_none():
lst1 = [1, 3, 5]
lst2 = []
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge_recurision(link1, link2)
assert link2list(link) == [1, 3, 5]
link = merge(link1, link2)
assert link2list(link) == [1, 3, 5]
link = merge2(link1, link2)
assert link2list(link) == [1, 3, 5]
def test_one_element():
lst1 = [1]
lst2 = [2]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge_recurision(link1, link2)
assert link2list(link) == [1, 2]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge(link1, link2)
assert link2list(link) == [1, 2]
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge2(link1, link2)
assert link2list(link) == [1, 2]
def test_none():
lst1 = []
lst2 = []
link1 = list2link(lst1)
link2 = list2link(lst2)
link = merge_recurision(link1, link2)
assert link == None
link = merge(link1, link2)
assert link == None
link = merge2(link1, link2)
assert link == None
| 26.969388
| 62
| 0.600076
| 361
| 2,643
| 4.33795
| 0.085873
| 0.114943
| 0.183908
| 0.239464
| 0.903576
| 0.84355
| 0.796296
| 0.796296
| 0.768838
| 0.740102
| 0
| 0.128114
| 0.25577
| 2,643
| 97
| 63
| 27.247423
| 0.668022
| 0
| 0
| 0.821429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214286
| 1
| 0.071429
| false
| 0
| 0.02381
| 0
| 0.095238
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
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