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string | max_forks_repo_forks_event_max_datetime
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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
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float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
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float64 | qsc_code_num_chars_line_mean_quality_signal
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float64 | qsc_code_frac_chars_comments_quality_signal
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float64 | qsc_code_frac_lines_prompt_comments_quality_signal
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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
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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
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int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d7afd466036552389125ff784e69c476ba724d80
| 153,565
|
py
|
Python
|
atomize/device_modules/PB_ESR_500_pro.py
|
Anatoly1010/Atomize
|
c1d4b508ff00b441ae73805e3e50494e9a6149f8
|
[
"MIT"
] | 5
|
2020-12-31T17:39:51.000Z
|
2022-03-31T13:02:49.000Z
|
atomize/device_modules/PB_ESR_500_pro.py
|
Anatoly1010/Atomize
|
c1d4b508ff00b441ae73805e3e50494e9a6149f8
|
[
"MIT"
] | null | null | null |
atomize/device_modules/PB_ESR_500_pro.py
|
Anatoly1010/Atomize
|
c1d4b508ff00b441ae73805e3e50494e9a6149f8
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import sys
import math
from copy import deepcopy
from operator import iconcat
from functools import reduce
from itertools import groupby, chain
import numpy as np
import atomize.device_modules.config.config_utils as cutil
import atomize.general_modules.general_functions as general
import atomize.general_modules.spinapi as spinapi
# Line 2290
# when min pulse length 12 ns
# there is a problem between phase pulse and previous MW pulse
# in config switch_phase_delay = 32 (for 12 ns min pulse) -> 28
# L2491: element_lna[2] = element_lna[2] + self.overlap_amp_lna_mw + 1
class PB_ESR_500_Pro:
def __init__(self):
# Initialization of the SpinAPI PB library
self.sp = spinapi.SpinAPI()
#### Inizialization
# setting path to *.ini file
self.path_current_directory = os.path.dirname(__file__)
self.path_config_file = os.path.join(self.path_current_directory, 'config','PB_ESR_500_pro_config.ini')
# configuration data
#config = cutil.read_conf_util(self.path_config_file)
self.specific_parameters = cutil.read_specific_parameters(self.path_config_file)
# TO DO
# only awg regime with automatic awg_trigger?
# Channel assignments
self.ch0 = self.specific_parameters['ch0'] # TRIGGER
self.ch1 = self.specific_parameters['ch1'] # AMP_ON
self.ch2 = self.specific_parameters['ch2'] # LNA_PROTCT
self.ch3 = self.specific_parameters['ch3'] # MW
self.ch4 = self.specific_parameters['ch4'] # -X
self.ch5 = self.specific_parameters['ch5'] # +Y
self.ch6 = self.specific_parameters['ch6'] # TRIGGER_AWG
self.ch7 = self.specific_parameters['ch7'] # AWG
# AWG pulse will be substitued by a shifted RECT_AWG pulse and AMP_ON pulse
# TRIGGER_AWG is used to trigger AWG card
self.timebase_dict = {'s': 1000000000, 'ms': 1000000, 'us': 1000, 'ns': 1, }
# -Y for Mikran bridge is simutaneously turned on -X; +Y
# that is why there is no -Y channel instead we add both -X and +Y pulses
self.channel_dict = {self.ch0: 0, self.ch1: 1, self.ch2: 2, self.ch3: 3, self.ch4: 4, self.ch5: 5, \
self.ch6: 6, self.ch7: 7, 'CH8': 8, 'CH9': 9, 'CH10': 10, 'CH11': 11,\
'CH12': 12, 'CH13': 13, 'CH14': 14, 'CH15': 15, 'CH16': 16, 'CH17': 17,\
'CH18': 18, 'CH19': 19, 'CH20': 20, 'CH21': 21, }
# Limits and Ranges (depends on the exact model):
self.clock = float(self.specific_parameters['clock'])
self.timebase = int(float(self.specific_parameters['timebase'])) # in ns/clock; convertion of clock to ns
self.repetition_rate = self.specific_parameters['default_rep_rate']
self.auto_defense = self.specific_parameters['auto_defense']
self.max_pulse_length = int(float(self.specific_parameters['max_pulse_length'])) # in ns
self.min_pulse_length = int(float(self.specific_parameters['min_pulse_length'])) # in ns
# minimal distance between two pulses of MW
# pulse blaster restriction
self.minimal_distance = int(float(self.specific_parameters['minimal_distance'])/self.timebase) # in clock
# a constant that use to overcome short instruction for our diagonal amp_on and mw pulses
# see also add_amp_on_pulses() function; looking for pulses with +-overlap_amp_lna_mw overlap
self.overlap_amp_lna_mw = 5 # in clock ### it was 6; 06.10.2021
# after all manupulations with diagonal amp_on pulses there is a variant
# when we use several mw pulses with app. 40 ns distance and with the phase different from
# +x. In this case two phase pulses start to be at the distance less than current minimal distance
# in 40 ns. That is why a different minimal distance (10 ns) is added for phase pulses
# see also preparing_to_bit_pulse() function
self.minimal_distance_phase = 5 # in clock ### it was 6; 06.10.2021
# minimal distance for joining AMP_ON and LNA_PROTECT pulses
# decided to keep it as 12 ns, while for MW pulses the limit is 40 ns
self.minimal_distance_amp_lna = 6 # in clock
# Delays and restrictions
self.constant_shift = int(250 / self.timebase) # in clock; shift of all sequence for not getting negative start times
self.switch_delay = int(float(self.specific_parameters['switch_delay'])/self.timebase) # in clock; delay for AMP_ON turning on; switch_delay BEFORE MW pulse
self.amp_delay = int(float(self.specific_parameters['amp_delay'])/self.timebase) # in clock; delay for AMP_ON turning off; amp_delay AFTER MW pulse
self.protect_delay = int(float(self.specific_parameters['protect_delay'])/self.timebase) # in clock; delay for LNA_PROTECT turning off; protect_delay AFTER MW pulse
self.switch_phase_delay = int(float(self.specific_parameters['switch_phase_delay'])) # in ns; delay for FAST_PHASE turning on; switch_phase_delay BEFORE MW pulse
self.phase_delay = int(float(self.specific_parameters['phase_delay'])) # in ns; delay for FAST_PHASE turning off; phase_delay AFTER MW pulse
# currently RECT_AWG is coincide with AMP_ON pulse;
self.rect_awg_switch_delay = int(float(self.specific_parameters['rect_awg_switch_delay'])) # in ns; delay for RECT_AWG turning on; rect_awg_switch_delay BEFORE MW pulse
self.rect_awg_delay = int(float(self.specific_parameters['rect_awg_delay'])) # in ns; delay for RECT_AWG turning off; rect_awg_delay AFTER MW pulse
self.protect_awg_delay = int(float(self.specific_parameters['protect_awg_delay'])/self.timebase) # in clock; delay for LNA_PROTECT turning off; because of shift a
# combination of rect_awg_delay and protect_awg_delay is used
# interval that shift the first pulse in the sequence
# start times of other pulses can be calculated from this time.
# I. E. first pulse:
# pb.pulser_pulse(name ='P0', channel = 'MW', start = '100 ns', length = '20 ns')
# second: pb.pulser_pulse(name ='P1', channel = 'MW', start = '330 ns', length = '30 ns', delta_start = '10 ns')
# we will have first pulse at 50 ns (add_shft*2)
# second at (330 - 100) + 50 = 280 ns
# if there is no AMP_ON/LNA_PROTECT pulses
self.add_shift = int(25) # in ns; *self.timebase
# Test run parameters
# These values are returned by the modules in the test run
if len(sys.argv) > 1:
self.test_flag = sys.argv[1]
else:
self.test_flag = 'None'
if self.test_flag != 'test':
#pb_core_clock(self.clock)
self.pulse_array = []
self.phase_array_length = []
self.pulse_name_array = []
self.pulse_array_init = []
self.rep_rate = (self.repetition_rate, )
self.shift_count = 0
self.rep_rate_count = 0
self.increment_count = 0
self.reset_count = 0
self.current_phase_index = 0
self.awg_pulses = 0
self.phase_pulses = 0
self.instr_from_file = 0
self.iterator_of_updates = 0
elif self.test_flag == 'test':
open('instructions.out', 'w').close()
self.test_rep_rate = '2 Hz'
self.pulse_array = []
self.phase_array_length = []
self.pulse_name_array = []
self.pulse_array_init = []
self.rep_rate = (self.repetition_rate, )
self.shift_count = 0
self.rep_rate_count = 0
self.increment_count = 0
self.reset_count = 0
self.current_phase_index = 0
self.awg_pulses = 0
self.phase_pulses = 0
self.instr_from_file = 0
# Module functions
def pulser_name(self):
answer = 'PB ESR 500 Pro'
return answer
def pulser_pulse(self, name = 'P0', channel = 'TRIGGER', start = '0 ns', length = '100 ns', \
delta_start = '0 ns', length_increment = '0 ns', phase_list = []):
"""
A function that added a new pulse at specified channel. The possible arguments:
NAME, CHANNEL, START, LENGTH, DELTA_START, LENGTH_INCREMENT, PHASE_SEQUENCE
"""
if self.test_flag != 'test':
pulse = {'name': name, 'channel': channel, 'start': start, 'length': length, 'delta_start' : delta_start,\
'length_increment': length_increment, 'phase_list': phase_list}
self.pulse_array.append( pulse )
# for saving the initial pulse_array without increments
# deepcopy helps to create a TRULY NEW array and not a link to the object
self.pulse_array_init = deepcopy( self.pulse_array )
# pulse_name array
self.pulse_name_array.append( pulse['name'] )
# for correcting AMP_ON (PB restriction in 10 ns minimal instruction) according to phase pulses
if channel == 'MW':
self.phase_array_length.append(len(list(phase_list)))
elif self.test_flag == 'test':
pulse = {'name': name, 'channel': channel, 'start': start, \
'length': length, 'delta_start' : delta_start, 'length_increment': length_increment, 'phase_list': phase_list}
# phase_list's length
if channel == 'MW':
self.phase_array_length.append(len(list(phase_list)))
# Checks
# two equal names
temp_name = str(name)
set_from_list = set(self.pulse_name_array)
if temp_name in set_from_list:
assert (1 == 2), 'Two pulses have the same name. Please, rename'
self.pulse_name_array.append( pulse['name'] )
temp_length = length.split(" ")
if temp_length[1] in self.timebase_dict:
coef = self.timebase_dict[temp_length[1]]
p_length = coef*float(temp_length[0])
assert(p_length % 2 == 0), 'Pulse length should be divisible by 2'
assert(p_length >= self.min_pulse_length), 'Pulse is shorter than minimum available length (' + str(self.min_pulse_length) +' ns)'
assert(p_length < self.max_pulse_length), 'Pulse is longer than maximum available length (' + str(self.max_pulse_length) +' ns)'
else:
assert( 1 == 2 ), 'Incorrect time dimension (s, ms, us, ns)'
temp_start = start.split(" ")
if temp_start[1] in self.timebase_dict:
coef = self.timebase_dict[temp_start[1]]
p_start = coef*float(temp_start[0])
assert(p_start % 2 == 0), 'Pulse start should be divisible by 2'
assert(p_start >= 0), 'Pulse start is a negative number'
else:
assert( 1 == 2 ), 'Incorrect time dimension (s, ms, us, ns)'
temp_delta_start = delta_start.split(" ")
if temp_delta_start[1] in self.timebase_dict:
coef = self.timebase_dict[temp_delta_start[1]]
p_delta_start = coef*float(temp_delta_start[0])
assert(p_delta_start % 2 == 0), 'Pulse delta start should be divisible by 2'
assert(p_delta_start >= 0), 'Pulse delta start is a negative number'
else:
assert( 1 == 2 ), 'Incorrect time dimension (s, ms, us, ns)'
temp_length_increment = length_increment.split(" ")
if temp_length_increment[1] in self.timebase_dict:
coef = self.timebase_dict[temp_length_increment[1]]
p_length_increment = coef*float(temp_length_increment[0])
assert(p_length_increment % 2 == 0), 'Pulse length increment should be divisible by 2'
assert (p_length_increment >= 0 and p_length_increment < self.max_pulse_length), \
'Pulse length increment is longer than maximum available length or negative'
else:
assert( 1 == 2 ), 'Incorrect time dimension (s, ms, us, ns)'
if channel in self.channel_dict:
if self.auto_defense == 'False':
self.pulse_array.append( pulse )
# for saving the initial pulse_array without increments
# deepcopy helps to create a TRULY NEW array and not a link to the object
self.pulse_array_init = deepcopy(self.pulse_array)
elif self.auto_defense == 'True':
if channel == 'AMP_ON' or channel == 'LNA_PROTECT':
assert( 1 == 2), 'In auto_defense mode AMP_ON and LNA_PROTECT pulses are set automatically'
else:
self.pulse_array.append( pulse )
# for saving the initial pulse_array without increments
# deepcopy helps to create a TRULY NEW array and not a link to the object
self.pulse_array_init = deepcopy(self.pulse_array)
else:
assert(1 == 2), 'Incorrect auto_defense setting'
else:
assert (1 == 2), 'Incorrect channel name'
def pulser_redefine_start(self, *, name, start):
"""
A function for redefining start of the specified pulse.
pulser_redefine_start(name = 'P0', start = '100 ns') changes start of the 'P0' pulse to 100 ns.
The main purpose of the function is non-uniform sampling / 2D experimental scripts
def func(*, name1, name2): defines a function without default values of key arguments
"""
if self.test_flag != 'test':
i = 0
while i < len( self.pulse_array ):
if name == self.pulse_array[i]['name']:
self.pulse_array[i]['start'] = str(start)
self.shift_count = 1
else:
pass
i += 1
elif self.test_flag == 'test':
i = 0
assert( name in self.pulse_name_array ), 'Pulse with the specified name is not defined'
while i < len( self.pulse_array ):
if name == self.pulse_array[i]['name']:
# checks
temp_start = start.split(" ")
if temp_start[1] in self.timebase_dict:
coef = self.timebase_dict[temp_start[1]]
p_start = coef*float(temp_start[0])
assert(p_start % 2 == 0), 'Pulse start should be divisible by 2'
assert(p_start >= 0), 'Pulse start is a negative number'
else:
assert( 1 == 2 ), 'Incorrect time dimension (s, ms, us, ns)'
self.pulse_array[i]['start'] = str(start)
self.shift_count = 1
else:
pass
i += 1
def pulser_redefine_delta_start(self, *, name, delta_start):
"""
A function for redefining delta_start of the specified pulse.
pulser_redefine_delta_start(name = 'P0', delta_start = '10 ns') changes delta_start of the 'P0' pulse to 10 ns.
The main purpose of the function is non-uniform sampling.
def func(*, name1, name2): defines a function without default values of key arguments
"""
if self.test_flag != 'test':
i = 0
while i < len( self.pulse_array ):
if name == self.pulse_array[i]['name']:
self.pulse_array[i]['delta_start'] = str(delta_start)
self.shift_count = 1
else:
pass
i += 1
elif self.test_flag == 'test':
i = 0
assert( name in self.pulse_name_array ), 'Pulse with the specified name is not defined'
while i < len( self.pulse_array ):
if name == self.pulse_array[i]['name']:
# checks
temp_delta_start = delta_start.split(" ")
if temp_delta_start[1] in self.timebase_dict:
coef = self.timebase_dict[temp_delta_start[1]]
p_delta_start = coef*float(temp_delta_start[0])
assert(p_delta_start % 2 == 0), 'Pulse delta start should be divisible by 2'
assert(p_delta_start >= 0), 'Pulse delta start is a negative number'
else:
assert( 1 == 2 ), 'Incorrect time dimension (s, ms, us, ns)'
self.pulse_array[i]['delta_start'] = str(delta_start)
self.shift_count = 1
else:
pass
i += 1
def pulser_redefine_length_increment(self, *, name, length_increment):
"""
A function for redefining length_increment of the specified pulse.
pulser_redefine_length_increment(name = 'P0', length_increment = '10 ns') changes length_increment of the 'P0' pulse to '10 ns'.
The main purpose of the function is non-uniform sampling.
def func(*, name1, name2): defines a function without default values of key arguments
"""
if self.test_flag != 'test':
i = 0
while i < len( self.pulse_array ):
if name == self.pulse_array[i]['name']:
self.pulse_array[i]['length_increment'] = str(length_increment)
self.increment_count = 1
else:
pass
i += 1
elif self.test_flag == 'test':
i = 0
assert( name in self.pulse_name_array ), 'Pulse with the specified name is not defined'
while i < len( self.pulse_array ):
if name == self.pulse_array[i]['name']:
# checks
temp_length_increment = length_increment.split(" ")
if temp_length_increment[1] in self.timebase_dict:
coef = self.timebase_dict[temp_length_increment[1]]
p_length_increment = coef*float(temp_length_increment[0])
assert(p_length_increment % 2 == 0), 'Pulse length increment should be divisible by 2'
assert (p_length_increment >= 0 and p_length_increment < self.max_pulse_length), \
'Pulse length increment is longer than maximum available length or negative'
else:
assert( 1 == 2 ), 'Incorrect time dimension (s, ms, us, ns)'
self.pulse_array[i]['length_increment'] = str(length_increment)
self.increment_count = 1
else:
pass
i += 1
def pulser_next_phase(self):
"""
A function for phase cycling. It works using phase_list decleared in pulser_pulse():
phase_list = ['-y', '+x', '-x', '+x']
self.current_phase_index is an iterator of the current phase
functions pulser_shift() and pulser_increment() reset the iterator
after calling pulser_next_phase() the next phase is taken from phase_list and a
corresponding trigger pulse is added to self.pulse_array
the length of all phase lists specified for different MW pulses has to be the same
the function also immediately sends intructions to pulse blaster as
a function pulser_update() does.
"""
if self.test_flag != 'test':
# deleting old phase switch pulses from self.pulse_array
# before adding new ones
for i in range(self.phase_pulses):
for index, element in enumerate(self.pulse_array):
if element['channel'] == '-X' or element['channel'] == '+Y':
del self.pulse_array[index]
break
self.phase_pulses = 0
# adding phase switch pulses
for index, element in enumerate(self.pulse_array):
if len(list(element['phase_list'])) != 0:
if element['phase_list'][self.current_phase_index] == '+x':
#pass
# 21-08-2021; Correction of non updating case for ['-x', '+x']
self.reset_count = 0
elif element['phase_list'][self.current_phase_index] == '-x':
name = element['name'] + '_ph_seq-x'
# taking into account delays of phase switching
start = self.change_pulse_settings(element['start'], -self.switch_phase_delay)
length = self.change_pulse_settings(element['length'], self.phase_delay + self.switch_phase_delay)
self.pulse_array.append({'name': name, 'channel': '-X', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
self.reset_count = 0
self.phase_pulses += 1
elif element['phase_list'][self.current_phase_index] == '+y':
name = element['name'] + '_ph_seq+y'
# taking into account delays of phase switching
start = self.change_pulse_settings(element['start'], -self.switch_phase_delay)
length = self.change_pulse_settings(element['length'], self.phase_delay + self.switch_phase_delay)
self.pulse_array.append({'name': name, 'channel': '+Y', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
self.reset_count = 0
self.phase_pulses += 1
elif element['phase_list'][self.current_phase_index] == '-y':
name = element['name'] + '_ph_seq-y'
# taking into account delays of phase switching
start = self.change_pulse_settings(element['start'], -self.switch_phase_delay)
length = self.change_pulse_settings(element['length'], self.phase_delay + self.switch_phase_delay)
# -Y for Mikran bridge is simutaneously turned on -X; +Y
# that is why there is no -Y channel
self.pulse_array.append({'name': name, 'channel': '-X', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
self.pulse_array.append({'name': name, 'channel': '+Y', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
self.reset_count = 0
self.phase_pulses += 2
self.current_phase_index += 1
# update pulses
# get repetition rate
rep_rate = self.rep_rate[0]
if rep_rate[-3:] == ' Hz':
rep_time = int(1000000000/float(rep_rate[:-3]))
elif rep_rate[-3:] == 'kHz':
rep_time = int(1000000/float(rep_rate[:-4]))
elif rep_rate[-3:] == 'MHz':
rep_time = int(1000/float(rep_rate[:-4]))
self.pulser_update()
elif self.test_flag == 'test':
# check that the length is equal (compare all elements in self.phase_array_length)
gr = groupby(self.phase_array_length)
if (next(gr, True) and not next(gr, False)) == False:
assert(1 == 2), 'Phase sequence does not have equal length'
for i in range(self.phase_pulses):
for index, element in enumerate(self.pulse_array):
if element['channel'] == '-X' or element['channel'] == '+Y':
del self.pulse_array[index]
break
self.phase_pulses = 0
for index, element in enumerate(self.pulse_array):
if len(list(element['phase_list'])) != 0:
if element['phase_list'][self.current_phase_index] == '+x':
#pass
# 21-08-2021; Correction of non updating case for ['-x', '+x']
self.reset_count = 0
elif element['phase_list'][self.current_phase_index] == '-x':
name = element['name'] + '_ph_seq-x'
# taking into account delays
start = self.change_pulse_settings(element['start'], -self.switch_phase_delay)
length = self.change_pulse_settings(element['length'], self.phase_delay + self.switch_phase_delay)
self.pulse_array.append({'name': name, 'channel': '-X', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
# check that we still have a next phase to switch
self.reset_count = 0
self.phase_pulses += 1
elif element['phase_list'][self.current_phase_index] == '+y':
name = element['name'] + '_ph_seq+y'
# taking into account delays
start = self.change_pulse_settings(element['start'], -self.switch_phase_delay)
length = self.change_pulse_settings(element['length'], self.phase_delay + self.switch_phase_delay)
self.pulse_array.append({'name': name, 'channel': '+Y', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
# check that we still have a next phase to switch
self.reset_count = 0
self.phase_pulses += 1
elif element['phase_list'][self.current_phase_index] == '-y':
name = element['name'] + '_ph_seq-y'
# taking into account delays
start = self.change_pulse_settings(element['start'], -self.switch_phase_delay)
length = self.change_pulse_settings(element['length'], self.phase_delay + self.switch_phase_delay)
# -Y for Mikran bridge is simutaneously turned on -X; +Y
# that is why there is no -Y channel
self.pulse_array.append({'name': name, 'channel': '-X', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
self.pulse_array.append({'name': name, 'channel': '+Y', 'start': start, \
'length': length, 'delta_start' : '0 ns', 'length_increment': '0 ns', 'phase_list': []})
# check that we still have a next phase to switch
self.reset_count = 0
self.phase_pulses += 2
else:
assert( 1 == 2 ), 'Incorrect phase name (+x, -x, +y, -y)'
else:
pass
self.current_phase_index += 1
# update pulses
# get repetition rate
rep_rate = self.rep_rate[0]
if rep_rate[-3:] == ' Hz':
rep_time = int(1000000000/float(rep_rate[:-3]))
elif rep_rate[-3:] == 'kHz':
rep_time = int(1000000/float(rep_rate[:-4]))
elif rep_rate[-3:] == 'MHz':
rep_time = int(1000/float(rep_rate[:-4]))
self.pulser_update()
def pulser_update(self):
"""
A function that write instructions to SpinAPI.
Repetition rate is taking into account by adding
a last pulse with delay.
Currently, all pulses are cycled using BRANCH.
"""
if self.test_flag != 'test':
# get repetition rate
rep_rate = self.rep_rate[0]
if rep_rate[-3:] == ' Hz':
rep_time = int(1000000000/float(rep_rate[:-3]))
elif rep_rate[-3:] == 'kHz':
rep_time = int(1000000/float(rep_rate[:-4]))
elif rep_rate[-3:] == 'MHz':
rep_time = int(1000/float(rep_rate[:-4]))
if self.reset_count == 0 or self.shift_count == 1 or self.increment_count == 1 or self.rep_rate_count == 1:
# using a special functions for convertion to instructions
# we get two return arrays because of pulser_visualizer. It is not the case for test flag.
#temp, visualizer = self.convert_to_bit_pulse( self.pulse_array )
#to_spinapi = self.instruction_pulse( temp, rep_time )
if self.instr_from_file == 0:
to_spinapi = self.split_into_parts( self.pulse_array, rep_time )
elif self.instr_from_file == 1:
raw_data = np.fromstring( self.raw_instructions[self.iterator_of_updates], dtype = int, sep = ',' )
to_spinapi = raw_data.reshape( ( int(len(raw_data)/3), 3 ) ).tolist()
##for element in to_spinapi:
## if element[2] < 10: # it was 12; 06.10.2021
## general.message('Incorrect instruction are found')
## ###general.message('ALARM')
## self.pulser_stop()
#general.message( to_spinapi )
#self.pulser_stop()
# initialization
#pb_init()
#pb.core_clock(self.clock)
self.sp.pb_init()
self.sp.pb_core_clock(self.clock)
#pb_start_programming(PULSE_PROGRAM)
self.sp.pb_start_programming(0)
self.sp.pb_bypass_FF_fix(1)
i = 0
while i < len( to_spinapi ) - 1:
if i == 0:
# to create a link for BRANCH
# start = pb_inst(ON | "0x%X" % to_spinapi[i][0], CONTINUE, 0, "0x%X" % to_spinapi[i][2])
# CONTINUE is 0
# ON is 111 in the first three bits of the Output/Control Word (24 bits)
# it is 14680064 or 0xE00000
start = self.sp.pb_inst(14680064 + to_spinapi[i][0], 0, 0, to_spinapi[i][2])
else:
#pb_inst(ON | "0x%X" % to_spinapi[i, 0], CONTINUE, 0, "0x%X" % to_spinapi[i][2])
self.sp.pb_inst(14680064 + to_spinapi[i][0], 0, 0, to_spinapi[i][2])
###if i == 0:
###pass
#print('ON | ' + "0x%X" % to_spinapi[i][0] + ', CONTINUE, 0, ' + "0x%X" % to_spinapi[i][2] )
###else:
###pass
#print('ON | ' + "0x%X" % to_spinapi[i][0] + ', CONTINUE, 0, ' + "0x%X" % to_spinapi[i][2] )
i += 1
# last instruction for delay
#pb_inst(ON | "0x%X" % to_spinapi[i][0], BRANCH, 0, "0x%X" % to_spinapi[i][2])
#print('ON | ' + "0x%X" % to_spinapi[i][0] + ', BRANCH, start, ' + "0x%X" % to_spinapi[i][2] )
# BRANCH is 6
self.sp.pb_inst(14680064 + to_spinapi[i][0], 6, start, to_spinapi[i][2])
#pb_stop_programming()
#pb_reset()
#pb_start()
self.sp.pb_stop_programming()
self.sp.pb_reset()
self.sp.pb_start()
#pb_close()
self.sp.pb_close()
self.reset_count = 1
self.shift_count = 0
self.increment_count = 0
self.rep_rate_count = 0
self.iterator_of_updates += 1
else:
pass
elif self.test_flag == 'test':
# get repetition rate
rep_rate = self.rep_rate[0]
if rep_rate[-3:] == ' Hz':
rep_time = int(1000000000/float(rep_rate[:-3]))
elif rep_rate[-3:] == 'kHz':
rep_time = int(1000000/float(rep_rate[:-4]))
elif rep_rate[-3:] == 'MHz':
rep_time = int(1000/float(rep_rate[:-4]))
else:
assert(1 == 2), "Incorrect repetition rate dimension (Hz, kHz, MHz)"
if self.reset_count == 0 or self.shift_count == 1 or self.increment_count == 1:
# using a special functions for convertion to instructions
#to_spinapi = self.instruction_pulse( self.convert_to_bit_pulse( self.pulse_array ) )
to_spinapi = self.split_into_parts( self.pulse_array, rep_time )
# instructions from file:
if self.instr_from_file == 1:
with open("instructions.out", "a") as f:
np.savetxt(f, [reduce(iconcat, to_spinapi, [])], delimiter = ',', fmt = '%u')
f.close()
for element in to_spinapi:
if element[2] < 10: # it was 12; 06.10.2021
assert( 1 == 2 ), 'Incorrect instruction are found. Probably Trigger pulses are overlap with other'
self.reset_count = 1
self.shift_count = 0
self.increment_count = 0
self.rep_rate_count = 0
else:
pass
def pulser_repetition_rate(self, *r_rate):
"""
A function to get or set repetition rate.
Repetition rate specifies the delay of the last
SpinAPI instructions
"""
if self.test_flag != 'test':
if len(r_rate) == 1:
self.rep_rate = r_rate
self.rep_rate_count = 1
elif len(r_rate) == 0:
return self.rep_rate[0]
elif self.test_flag == 'test':
if len(r_rate) == 1:
self.rep_rate = r_rate
self.rep_rate_count = 1
elif len(r_rate) == 0:
return self.rep_rate[0]
def pulser_shift(self, *pulses):
"""
A function to shift the start of the pulses.
The function directly affects the pulse_array.
"""
if self.test_flag != 'test':
if len(pulses) == 0:
i = 0
while i < len( self.pulse_array ):
if int( self.pulse_array[i]['delta_start'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[i]['delta_start'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_start = int((temp[0]))*flag
else:
pass
temp2 = self.pulse_array[i]['start'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
st = int((temp2[0]))*flag2
else:
pass
self.pulse_array[i]['start'] = str( st + d_start ) + ' ns'
i += 1
self.shift_count = 1
self.current_phase_index = 0
else:
set_from_list = set(pulses)
for element in set_from_list:
if element in self.pulse_name_array:
pulse_index = self.pulse_name_array.index(element)
if int( self.pulse_array[pulse_index]['delta_start'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[pulse_index]['delta_start'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_start = int((temp[0]))*flag
else:
pass
temp2 = self.pulse_array[pulse_index]['start'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
st = int((temp2[0]))*flag2
else:
pass
self.pulse_array[pulse_index]['start'] = str( st + d_start ) + ' ns'
self.shift_count = 1
self.current_phase_index = 0
elif self.test_flag == 'test':
if len(pulses) == 0:
i = 0
while i < len( self.pulse_array ):
if int( self.pulse_array[i]['delta_start'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[i]['delta_start'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_start = int((temp[0]))*flag
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
temp2 = self.pulse_array[i]['start'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
st = int((temp2[0]))*flag2
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
self.pulse_array[i]['start'] = str( st + d_start ) + ' ns'
i += 1
self.shift_count = 1
self.current_phase_index = 0
else:
set_from_list = set(pulses)
for element in set_from_list:
if element in self.pulse_name_array:
pulse_index = self.pulse_name_array.index(element)
if int( self.pulse_array[pulse_index]['delta_start'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[pulse_index]['delta_start'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_start = int((temp[0]))*flag
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
temp2 = self.pulse_array[pulse_index]['start'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
st = int((temp2[0]))*flag2
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
self.pulse_array[pulse_index]['start'] = str( st + d_start ) + ' ns'
self.shift_count = 1
self.current_phase_index = 0
else:
assert(1 == 2), "There is no pulse with the specified name"
def pulser_increment(self, *pulses):
"""
A function to increment the length of the pulses.
The function directly affects the pulse_array.
"""
if self.test_flag != 'test':
if len(pulses) == 0:
i = 0
while i < len( self.pulse_array ):
if int( self.pulse_array[i]['length_increment'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[i]['length_increment'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_length = int(float(temp[0]))*flag
else:
pass
temp2 = self.pulse_array[i]['length'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
leng = int(float(temp2[0]))*flag2
else:
pass
self.pulse_array[i]['length'] = str( leng + d_length ) + ' ns'
i += 1
self.increment_count = 1
self.current_phase_index = 0
else:
set_from_list = set(pulses)
for element in set_from_list:
if element in self.pulse_name_array:
pulse_index = self.pulse_name_array.index(element)
if int( self.pulse_array[pulse_index]['length_increment'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[pulse_index]['length_increment'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_length = int(float(temp[0]))*flag
else:
pass
temp2 = self.pulse_array[pulse_index]['length'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
leng = int(float(temp2[0]))*flag2
else:
pass
self.pulse_array[pulse_index]['length'] = str( leng + d_length ) + ' ns'
self.increment_count = 1
self.current_phase_index = 0
elif self.test_flag == 'test':
if len(pulses) == 0:
i = 0
while i < len( self.pulse_array ):
if int( self.pulse_array[i]['length_increment'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[i]['length_increment'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_length = int(float(temp[0]))*flag
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
temp2 = self.pulse_array[i]['length'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
leng = int(float(temp2[0]))*flag2
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
if ( leng + d_length ) <= self.max_pulse_length:
self.pulse_array[i]['length'] = str( leng + d_length ) + ' ns'
else:
assert(1 == 2), 'Exceeded maximum pulse length (1900 ns) when increment the pulse'
i += 1
self.increment_count = 1
self.current_phase_index = 0
else:
set_from_list = set(pulses)
for element in set_from_list:
if element in self.pulse_name_array:
pulse_index = self.pulse_name_array.index(element)
if int( self.pulse_array[pulse_index]['length_increment'][:-3] ) == 0:
pass
else:
# convertion to ns
temp = self.pulse_array[pulse_index]['length_increment'].split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
d_length = int(float(temp[0]))*flag
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
temp2 = self.pulse_array[pulse_index]['length'].split(' ')
if temp2[1] in self.timebase_dict:
flag2 = self.timebase_dict[temp2[1]]
leng = int(float(temp2[0]))*flag2
else:
assert(1 == 2), "Incorrect time dimension (ns, us, ms, s)"
if ( leng + d_length ) <= self.max_pulse_length:
self.pulse_array[pulse_index]['length'] = str( leng + d_length ) + ' ns'
else:
assert(1 == 2), 'Exceeded maximum pulse length (1900 ns) when increment the pulse'
self.increment_count = 1
self.current_phase_index = 0
else:
assert(1 == 2), "There is no pulse with the specified name"
def pulser_reset(self):
"""
Reset all pulses to the initial state it was in at the start of the experiment.
It includes the complete functionality of pulser_pulse_reset(), but also immediately
updates the pulser as it is done by calling pulser_update().
"""
if self.test_flag != 'test':
# get repetition rate
rep_rate = self.rep_rate[0]
if rep_rate[-3:] == ' Hz':
rep_time = int(1000000000/float(rep_rate[:-3]))
elif rep_rate[-3:] == 'kHz':
rep_time = int(1000000/float(rep_rate[:-4]))
elif rep_rate[-3:] == 'MHz':
rep_time = int(1000/float(rep_rate[:-4]))
# reset the pulses; deepcopy helps to create a TRULY NEW array
self.pulse_array = deepcopy( self.pulse_array_init )
# using a special functions for convertion to instructions
# we get two return arrays because of pulser_visualizer. It is not the case for test flag.
#temp, visualizer = self.convert_to_bit_pulse( self.pulse_array )
if self.instr_from_file == 0:
to_spinapi = self.split_into_parts( self.pulse_array, rep_time )
elif self.instr_from_file == 1:
self.iterator_of_updates = 0
raw_data = np.fromstring( self.raw_instructions[self.iterator_of_updates], dtype = int, sep = ',' )
to_spinapi = raw_data.reshape( (int(len(raw_data)/3), 3 ) ).tolist()
#general.message( to_spinapi )
# initialization
#pb_init()
#pb.core_clock(self.clock)
self.sp.pb_init()
self.sp.pb_core_clock(self.clock)
#pb_start_programming(0)
self.sp.pb_start_programming(0)
i = 0
while i < len( to_spinapi ) - 1:
if i == 0:
# to create a link for BRANCH
#start = pb_inst(ON | "0x%X" % to_spinapi[i][0], CONTINUE, 0, "0x%X" % to_spinapi[i][2])
start = self.sp.pb_inst(14680064 + to_spinapi[i][0], 0, 0, to_spinapi[i][2])
else:
#pb_inst(ON | "0x%X" % to_spinapi[i][0], CONTINUE, 0, "0x%X" % to_spinapi[i][2])
self.sp.pb_inst(14680064 + to_spinapi[i][0], 0, 0, to_spinapi[i][2])
###if i == 0:
###pass
#print('ON | ' + "0x%X" % to_spinapi[i][0] + ', CONTINUE, 0, ' + "0x%X" % to_spinapi[i][2] )
###else:
###pass
#print('ON | ' + "0x%X" % to_spinapi[i][0] + ', CONTINUE, 0, ' + "0x%X" % to_spinapi[i][2] )
i += 1
# last instruction for delay
#pb_inst(ON | "0x%X" % to_spinapi[i][0], BRANCH, 0, "0x%X" % to_spinapi[i][2])
self.sp.pb_inst(14680064 + to_spinapi[i][0], 6, 0, to_spinapi[i][2])
#print('ON | ' + "0x%X" % to_spinapi[i][0] + ', BRANCH, start, ' + "0x%X" % to_spinapi[i][2] )
#pb_stop_programming()
#pb_reset()
#pb_start()
self.sp.pb_stop_programming()
self.sp.pb_reset()
self.sp.pb_start()
#pb_close()
self.sp.pb_close()
self.reset_count = 1
self.increment_count = 0
self.shift_count = 0
self.current_phase_index = 0
self.iterator_of_updates += 1
elif self.test_flag == 'test':
# get repetition rate
rep_rate = self.rep_rate[0]
if rep_rate[-3:] == ' Hz':
rep_time = int(1000000000/float(rep_rate[:-3]))
elif rep_rate[-3:] == 'kHz':
rep_time = int(1000000/float(rep_rate[:-4]))
elif rep_rate[-3:] == 'MHz':
rep_time = int(1000/float(rep_rate[:-4]))
else:
assert( 1 == 2 ), 'Incorrect dimension of repetition rate (Hz, kHz, MHz)'
# reset the pulses; deepcopy helps to create a TRULY NEW array
self.pulse_array = deepcopy( self.pulse_array_init )
# using a special functions for convertion to instructions
#to_spinapi = self.instruction_pulse( self.convert_to_bit_pulse( self.pulse_array ), rep_time )
to_spinapi = self.split_into_parts( self.pulse_array, rep_time )
self.reset_count = 1
self.increment_count = 0
self.shift_count = 0
self.current_phase_index = 0
def pulser_pulse_reset(self, *pulses):
"""
Reset all pulses to the initial state it was in at the start of the experiment.
It does not update the pulser, if you want to reset all pulses and and also update
the pulser use the function pulser_reset() instead.
"""
if self.test_flag != 'test':
if len(pulses) == 0:
self.pulse_array = deepcopy(self.pulse_array_init)
self.reset_count = 0
self.increment_count = 0
self.shift_count = 0
self.current_phase_index = 0
self.iterator_of_updates = 0
else:
set_from_list = set(pulses)
for element in set_from_list:
if element in self.pulse_name_array:
pulse_index = self.pulse_name_array.index(element)
self.pulse_array[pulse_index]['start'] = self.pulse_array_init[pulse_index]['start']
self.pulse_array[pulse_index]['length'] = self.pulse_array_init[pulse_index]['length']
self.reset_count = 0
self.increment_count = 0
self.shift_count = 0
self.current_phase_index = 0
#self.iterator_of_updates = 0
elif self.test_flag == 'test':
if len(pulses) == 0:
self.pulse_array = deepcopy(self.pulse_array_init)
self.reset_count = 0
self.increment_count = 0
self.shift_count = 0
self.current_phase_index = 0
else:
set_from_list = set(pulses)
for element in set_from_list:
if element in self.pulse_name_array:
pulse_index = self.pulse_name_array.index(element)
self.pulse_array[pulse_index]['start'] = self.pulse_array_init[pulse_index]['start']
self.pulse_array[pulse_index]['length'] = self.pulse_array_init[pulse_index]['length']
self.reset_count = 0
self.increment_count = 0
self.shift_count = 0
self.current_phase_index = 0
def pulser_stop(self):
"""
A function to stop pulse sequence
"""
if self.test_flag != 'test':
# initialization
#pb_init()
#pb.core_clock(self.clock)
self.sp.pb_init()
self.sp.pb_core_clock(self.clock)
#pb_start_programming(PULSE_PROGRAM)
#pb_inst(ON | "0x%X" % 0, CONTINUE, 0, "0x%X" % 16)
self.sp.pb_start_programming(0)
self.sp.pb_inst(14680064, 0, 0, 16)
#general.message('ON | ', "0x%X" % 0, ', CONTINUE, 0, ', "0x%X" % 12)
#pb_inst(ON | "0x%X" % 0, STOP, 0, "0x%X" % 16)
# STOP is 1
self.sp.pb_inst(14680064, 1, 0, 16)
#general.message('ON | ', "0x%X" % 0, ', STOP, 0, ', "0x%X" % 16)
#pb_stop_programming()
#pb_reset()
#pb_start()
#pb_close()
self.sp.pb_stop_programming()
self.sp.pb_reset()
self.sp.pb_start()
###pass
self.sp.pb_close()
#return to_spinapi
elif self.test_flag == 'test':
pass
def pulser_state(self):
if self.test_flag != 'test':
self.sp.pb_init()
answer = self.sp.pb_read_status()
#pass
return answer
elif self.test_flag == 'test':
pass
def pulser_visualize(self):
"""
Function for visualization of pulse sequence.
There are two possibilities:
1) Real final instructions with already summed up channel numbers
2) Individual pulses
"""
if self.test_flag != 'test':
rep_rate = self.rep_rate[0]
if rep_rate[-3:] == ' Hz':
rep_time = int(1000000000/float(rep_rate[:-3]))
elif rep_rate[-3:] == 'kHz':
rep_time = int(1000000/float(rep_rate[:-4]))
elif rep_rate[-3:] == 'MHz':
rep_time = int(1000/float(rep_rate[:-4]))
# Real final instructions with already summed up channel numbers
#preparation = self.split_into_parts( self.pulse_array, rep_time )
#visualizer = self.convert_to_bit_pulse_visualizer_final_instructions( np.asarray(preparation[:-1] ))
# Individual pulses
visualizer = self.convert_to_bit_pulse_visualizer( self.pulse_array )
#general.plot_1d('Plot XY Test', np.arange(len(to_spinapi)), to_spinapi, label='test data1', timeaxis = 'False')
general.plot_2d('Pulses Visualizer', np.transpose( visualizer ), \
start_step = ( (0, 1), (0, 1) ), xname = 'Time',\
xscale = 'ns', yname = 'Pulse Number', yscale = '', zname = '2**(channel)', zscale = '')
elif self.test_flag == 'test':
pass
def pulser_pulse_list(self):
"""
Function for saving a pulse list from
the script into the
header of the experimental data
"""
pulse_list_mod = ''
for element in self.pulse_array_init:
pulse_list_mod = pulse_list_mod + str(element) + '\n'
return pulse_list_mod
def pulser_clear(self):
"""
A special function for Pulse Control module
It clear self.pulse_array and other status flags
"""
self.pulse_array = []
self.phase_array_length = []
self.pulse_name_array = []
self.pulse_array_init = []
self.rep_rate = (self.repetition_rate, )
self.shift_count = 0
self.rep_rate_count = 0
self.increment_count = 0
self.reset_count = 0
self.current_phase_index = 0
self.awg_pulses = 0
self.phase_pulses = 0
def pulser_test_flag(self, flag):
"""
A special function for Pulse Control module
It runs TEST mode
"""
self.test_flag = flag
def pulser_acquisition_cycle(self, data1, data2, acq_cycle = []):
if self.test_flag != 'test':
answer = np.zeros( data1.shape ) + 1j*np.zeros( data2.shape )
for index, element in enumerate(acq_cycle):
if element == '+':
answer = answer + data1[index] + 1j*data2[index]
elif element == '-':
answer = answer - data1[index] - 1j*data2[index]
elif element == '+i':
answer = answer + 1j*data1[index] - data2[index]
elif element == '-i':
answer = answer - 1j*data1[index] + data2[index]
return (answer.real / len(acq_cycle))[0], (answer.imag / len(acq_cycle))[0]
elif self.test_flag == 'test':
assert( len(acq_cycle) == len(data1) ), 'Acquisition cycle and Data 1 have incompatible size'
assert( len(acq_cycle) == len(data2) ), 'Acquisition cycle and Data 2 have incompatible size'
answer = np.zeros( data1.shape ) + 1j*np.zeros( data2.shape )
##for index, element in enumerate(acq_cycle):
## if element == '+':
## answer = answer + data1[index] + 1j*data2[index]
## elif element == '-':
## answer = answer - data1[index] - 1j*data2[index]
## elif element == '+i':
## answer = answer + 1j*data1[index] - data2[index]
## elif element == '-i':
## answer = answer - 1j*data1[index] + data2[index]
## else:
## assert (1 == 2), 'Incorrect operation in the acquisition cycle'
return (answer.real / len(acq_cycle))[0], (answer.imag / len(acq_cycle))[0]
#UNDOCUMENTED
def pulser_instruction_from_file(self, flag):
"""
Special function to read instructions from the .txt file
"""
if self.test_flag != 'test':
if flag == 1:
self.instr_from_file = 1
f = open('instructions.out')
self.raw_instructions = f.read().splitlines()
f.close()
elif flag == 0:
self.instr_from_file = 0
elif self.test_flag == 'test':
if flag == 1:
self.instr_from_file = 1
elif flag == 0:
self.instr_from_file = 0
# Auxilary functions
def convertion_to_numpy(self, p_array):
"""
Convertion of the pulse_array into numpy array in the form of
[channel_number, start, end, delta_start, length_increment]
channel_number is an integer: 2**(ch), where ch from self.channel_dict
start is a pulse start in a pulser self.clock sample rate
end is a pulse end in a pulser self.clock sample rate
delta_start is a pulse delta_start in a pulser self.clock sample rate
length_increment is a pulse length_increment in a pulser self.clock sample rate
The numpy array is shifted (250 ns) and sorted according to channel number
"""
if self.test_flag != 'test':
i = 0
pulse_temp_array = []
num_pulses = len( p_array )
while i < num_pulses:
# get channel number
ch = p_array[i]['channel']
if ch in self.channel_dict:
ch_num = self.channel_dict[ch]
# get start
if ch != 'AWG':
st = p_array[i]['start']
else:
# shift AWG pulse to get RECT_AWG
st = self.change_pulse_settings(p_array[i]['start'], -self.rect_awg_switch_delay)
self.awg_pulses = 1
if st[-2:] == 'ns':
st_time = int(float(st[:-3])/self.timebase)
elif st[-2:] == 'us':
st_time = int(float(st[:-3])*1000/self.timebase)
elif st[-2:] == 'ms':
st_time = int(float(st[:-3])*1000000/self.timebase)
elif st[-2:] == 's':
st_time = int(float(st[:-3])*1000000000/self.timebase)
# get length
if ch != 'AWG':
leng = p_array[i]['length']
else:
# shift AWG pulse to get RECT_AWG
leng = self.change_pulse_settings(p_array[i]['length'], self.rect_awg_switch_delay + self.rect_awg_delay)
self.awg_pulses = 1
if leng[-2:] == 'ns':
leng_time = int(float(leng[:-3])/self.timebase)
elif leng[-2:] == 'us':
leng_time = int(float(leng[:-3])*1000/self.timebase)
elif leng[-2:] == 'ms':
leng_time = int(float(leng[:-3])*1000000/self.timebase)
elif leng[-2:] == 's':
leng_time = int(float(leng[:-3])*1000000000/self.timebase)
# get delta start
del_st = p_array[i]['delta_start']
if del_st[-2:] == 'ns':
delta_start = int(float(del_st[:-3])/self.timebase)
elif del_st[-2:] == 'us':
delta_start = int(float(del_st[:-3])*1000/self.timebase)
elif del_st[-2:] == 'ms':
delta_start = int(float(del_st[:-3])*1000000/self.timebase)
elif del_st[-2:] == 's':
delta_start = int(float(del_st[:-3])*1000000000/self.timebase)
# get length_increment
len_in = p_array[i]['length_increment']
if len_in[-2:] == 'ns':
length_increment = int(float(len_in[:-3])/self.timebase)
elif len_in[-2:] == 'us':
length_increment = int(float(len_in[:-3])*1000/self.timebase)
elif len_in[-2:] == 'ms':
length_increment = int(float(len_in[:-3])*1000000/self.timebase)
elif len_in[-2:] == 's':
length_increment = int(float(len_in[:-3])*1000000000/self.timebase)
# creating converted array
# in terms of bits the number of channel is 2**(ch_num - 1)
#pulse_temp_array.append( (2**(ch_num), st_time, st_time + leng_time, delta_start, length_increment) )
pulse_temp_array.append( (2**(ch_num), st_time + self.constant_shift, self.constant_shift + st_time + leng_time) )
i += 1
# should be sorted according to channel number for corecct splitting into subarrays
return np.asarray(sorted(pulse_temp_array, key = lambda x: int(x[0])), dtype = np.int64)
elif self.test_flag == 'test':
i = 0
pulse_temp_array = []
num_pulses = len( p_array )
while i < num_pulses:
# get channel number
ch = p_array[i]['channel']
if ch in self.channel_dict:
ch_num = self.channel_dict[ch]
# get start
if ch != 'AWG':
st = p_array[i]['start']
else:
st = self.change_pulse_settings(p_array[i]['start'], -self.rect_awg_switch_delay)
self.awg_pulses = 1
if st[-2:] == 'ns':
st_time = int(float(st[:-3])/self.timebase)
elif st[-2:] == 'us':
st_time = int(float(st[:-3])*1000/self.timebase)
elif st[-2:] == 'ms':
st_time = int(float(st[:-3])*1000000/self.timebase)
elif st[-2:] == 's':
st_time = int(float(st[:-3])*1000000000/self.timebase)
# get length
if ch != 'AWG':
leng = p_array[i]['length']
else:
# shift AWG pulse to get RECT_AWG
leng = self.change_pulse_settings(p_array[i]['length'], self.rect_awg_switch_delay + self.rect_awg_delay)
self.awg_pulses = 1
if leng[-2:] == 'ns':
leng_time = int(float(leng[:-3])/self.timebase)
elif leng[-2:] == 'us':
leng_time = int(float(leng[:-3])*1000/self.timebase)
elif leng[-2:] == 'ms':
leng_time = int(float(leng[:-3])*1000000/self.timebase)
elif leng[-2:] == 's':
leng_time = int(float(leng[:-3])*1000000000/self.timebase)
# get delta start
del_st = p_array[i]['delta_start']
if del_st[-2:] == 'ns':
delta_start = int(float(del_st[:-3])/self.timebase)
elif del_st[-2:] == 'us':
delta_start = int(float(del_st[:-3])*1000/self.timebase)
elif del_st[-2:] == 'ms':
delta_start = int(float(del_st[:-3])*1000000/self.timebase)
elif del_st[-2:] == 's':
delta_start = int(float(del_st[:-3])*1000000000/self.timebase)
# get length_increment
len_in = p_array[i]['length_increment']
if len_in[-2:] == 'ns':
length_increment = int(float(len_in[:-3])/self.timebase)
elif len_in[-2:] == 'us':
length_increment = int(float(len_in[:-3])*1000/self.timebase)
elif len_in[-2:] == 'ms':
length_increment = int(float(len_in[:-3])*1000000/self.timebase)
elif len_in[-2:] == 's':
length_increment = int(float(len_in[:-3])*1000000000/self.timebase)
# creating converted array
# in terms of bits the number of channel is 2**(ch_num - 1)
pulse_temp_array.append( (2**(ch_num), self.constant_shift + st_time, self.constant_shift + st_time + leng_time ) )
i += 1
# should be sorted according to channel number for corecct splitting into subarrays
return np.asarray(sorted(pulse_temp_array, key = lambda x: int(x[0])), dtype = np.int64)
def splitting_acc_to_channel(self, np_array):
"""
A function that splits pulse array into
several array that have the same channel
I.E. [[1, 10, 100], [8, 100, 40], [8, 200, 20], [8, 300, 20]
-> [array([[1, 10, 100]]) , array([[8, 100, 40], [8, 200, 20], [8, 300, 20]])]
Input array should be sorted
RECT_AWG pulses are combined with MW pulses in the same array, since for
both of them AMP_ON and LNA_PROTECT pulses are needed
"""
if self.test_flag != 'test':
# according to 0 element (channel number)
answer = np.split(np_array, np.where(np.diff(np_array[:,0]))[0] + 1)
# to save time if there is no AWG pulses
if self.awg_pulses == 0:
pass
elif self.awg_pulses == 1:
# join AWG and MW pulses in order to add AMP_ON and LNA_PROTECT for them together
for index, element in enumerate(answer):
# memorize indexes
if element[0, 0] == 2**self.channel_dict['MW']:
mw_index = index
elif element[0, 0] == 2**self.channel_dict['AWG']:
awg_index = index
# combines arrays of MW and AWG pulses if there is MW and AWG pulses
try:
# Expending RECT_AWG if it is cross some MW pulses in a wrong way;
# the procedure is the same as for AMP_ON or LNA_PROTECT in add_amp_on_pulses() and add_lna_protect_pulses()
for element in answer[awg_index]:
for element_mw in answer[mw_index]:
if (element_mw[1] - element[1] <= self.overlap_amp_lna_mw) and (element_mw[1] - element[1] > 0):
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[1] - element[1] >= -self.overlap_amp_lna_mw) and (element_mw[1] - element[1] < 0):
element[1] = element_mw[1]
elif (element_mw[1] - element[2]) <= self.overlap_amp_lna_mw and (element_mw[1] - element[2] > 0):
element[2] = element_mw[1]
elif (element_mw[1] - element[2]) >= -self.overlap_amp_lna_mw and (element_mw[1] - element[2] < 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[2] = element_mw[2]
else:
element[2] = element[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_mw[2] - element[2] <= self.overlap_amp_lna_mw) and (element_mw[2] - element[2] > 0):
element[2] = element_mw[2]
elif (element_mw[2] - element[2] >= -self.overlap_amp_lna_mw) and (element_mw[2] - element[2] < 0):
element[2] = element[2] + self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) <= self.overlap_amp_lna_mw and (element_mw[2] - element[1] > 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[1] = element_mw[1]
else:
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) >= -self.overlap_amp_lna_mw and (element_mw[2] - element[1] < 0):
element[1] = element_mw[2]
# additional checking for phase and RECT_AWG pulses after
# overlap correction
if len(self.phase_array_length) > 0:
# iterate over all pulses at different channels and taking phase pulses
for index, element in enumerate(answer):
if ( element[0, 0] == 2**self.channel_dict['-X'] ) or ( element[0, 0] == 2**self.channel_dict['+Y'] ):
for element_phase in element:
for element_awg in answer[awg_index]:
if (element_phase[1] - element_awg[2] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[2] > 0):
element_awg[2] = element_phase[1] + self.overlap_amp_lna_mw
elif (element_phase[1] - element_awg[2] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[2] < 0):
element_awg[2] = element_awg[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_phase[1] - element_awg[1] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[1] > 0):
element_awg[1] = element_awg[1] - self.overlap_amp_lna_mw
elif (element_phase[1] - element_awg[1] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[1] < 0):
element_awg[1] = element_phase[1]
else:
pass
# continuation of combining
answer[mw_index] = np.concatenate((answer[mw_index], answer[awg_index]), axis = 0)
# delete duplicated AWG pulses; answer is python list -> pop
answer.pop(awg_index)
except UnboundLocalError:
pass
return answer
elif self.test_flag == 'test':
# according to 0 element (channel number)
answer = np.split(np_array, np.where(np.diff(np_array[:,0]))[0] + 1)
if self.awg_pulses == 0:
pass
elif self.awg_pulses == 1:
# attempt to join AWG and MW pulses in order to add AMP_ON and LNA_PROTECT for them together
for index, element in enumerate(answer):
# memorize indexes
if element[0, 0] == 2**self.channel_dict['MW']:
mw_index = index
elif element[0, 0] == 2**self.channel_dict['AWG']:
awg_index = index
# combines arrays if there is MW and AWG pulses
try:
for element in answer[awg_index]:
for element_mw in answer[mw_index]:
if (element_mw[1] - element[1] <= self.overlap_amp_lna_mw) and (element_mw[1] - element[1] > 0):
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[1] - element[1] >= -self.overlap_amp_lna_mw) and (element_mw[1] - element[1] < 0):
element[1] = element_mw[1]
elif (element_mw[1] - element[2]) <= self.overlap_amp_lna_mw and (element_mw[1] - element[2] > 0):
element[2] = element_mw[1]
elif (element_mw[1] - element[2]) >= -self.overlap_amp_lna_mw and (element_mw[1] - element[2] < 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[2] = element_mw[2]
else:
element[2] = element[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_mw[2] - element[2] <= self.overlap_amp_lna_mw) and (element_mw[2] - element[2] > 0):
element[2] = element_mw[2]
elif (element_mw[2] - element[2] >= -self.overlap_amp_lna_mw) and (element_mw[2] - element[2] < 0):
element[2] = element[2] + self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) <= self.overlap_amp_lna_mw and (element_mw[2] - element[1] > 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[1] = element_mw[1]
else:
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) >= -self.overlap_amp_lna_mw and (element_mw[2] - element[1] < 0):
element[1] = element_mw[2]
# additional checking for phase and RECT_AWG pulses after
# overlap correction
if len(self.phase_array_length) > 0:
# iterate over all pulses at different channels and taking phase pulses
for index, element in enumerate(answer):
if ( element[0, 0] == 2**self.channel_dict['-X'] ) or ( element[0, 0] == 2**self.channel_dict['+Y'] ):
for element_phase in element:
for element_awg in answer[awg_index]:
if (element_phase[1] - element_awg[2] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[2] > 0):
element_awg[2] = element_phase[1] + self.overlap_amp_lna_mw
elif (element_phase[1] - element_awg[2] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[2] < 0):
element_awg[2] = element_awg[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_phase[1] - element_awg[1] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[1] > 0):
element_awg[1] = element_awg[1] - self.overlap_amp_lna_mw
elif (element_phase[1] - element_awg[1] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_awg[1] < 0):
element_awg[1] = element_phase[1]
else:
pass
answer[mw_index] = np.concatenate((answer[mw_index], answer[awg_index]), axis = 0)
# delete duplicated AWG pulses; answer is python list -> pop
answer.pop(awg_index)
except UnboundLocalError:
pass
return answer
def extending_rect_awg(self, np_array):
"""
Replace RECT_AWG pulse with the extending one (in the same way as AMP_ON and LNA_PROTECT)
Instead of directly changing self.pulse_array we change the output of
self.splitting_acc_to_channel() and use this function in the output of preparing_to_bit_pulse()
"""
if self.test_flag != 'test':
answer = self.splitting_acc_to_channel( self.convertion_to_numpy( np_array ) )
# return flatten np.array of pulses that has the same format as self.convertion_to_numpy( np_array )
# but with extended RECT_AWG pulse
return np.asarray(list(chain(*answer)))
elif self.test_flag == 'test':
answer = self.splitting_acc_to_channel( self.convertion_to_numpy( np_array ) )
return np.asarray(list(chain(*answer)))
def check_problem_pulses(self, np_array):
"""
A function for checking whether there is a two
close to each other pulses (less than 40 ns)
In Auto_defense = True we checked everything except
AMN_ON and LNA_PROTECT
"""
if self.test_flag != 'test':
# sorted pulse list in order to be able to have an arbitrary pulse order inside
# the definition in the experimental script
sorted_np_array = np.asarray(sorted(np_array, key = lambda x: int(x[1])), dtype = np.int64)
## 16-09-2021; An attempt to optimize the speed; all pulses should be already checked in the TEST RUN
## Uncomment everything starting with ## if needed
### compare the end time with the start time for each couple of pulses
##for index, element in enumerate(sorted_np_array[:-1]):
## # minimal_distance is 40 ns now
## if sorted_np_array[index + 1][1] - element[2] < self.min_pulse_length:
## assert(1 == 2), 'Overlapping pulses or two pulses with less than ' + str(self.min_pulse_length*2) + ' ns distance'
## else:
## pass
return sorted_np_array
elif self.test_flag == 'test':
sorted_np_array = np.asarray(sorted(np_array, key = lambda x: int(x[1])), dtype = np.int64)
# compare the end time with the start time for each couple of pulses
for index, element in enumerate(sorted_np_array[:-1]):
# minimal_distance is 40 ns now
if sorted_np_array[index + 1][1] - element[2] < self.min_pulse_length:
assert(1 == 2), 'Overlapping pulses or two pulses with less than ' + str(self.min_pulse_length*2) + ' ns distance'
else:
pass
return sorted_np_array
def check_problem_pulses_phase(self, np_array):
"""
A function for checking whether there is a two
close to each other pulses (less than 12 ns)
In Auto_defense = True by this function we checked only
-X +Y -Y pulses since they have different minimal distance
"""
if self.test_flag != 'test':
# sorted pulse list in order to be able to have an arbitrary pulse order inside
# the definition in the experimental script
sorted_np_array = np.asarray(sorted(np_array, key = lambda x: int(x[1])), dtype = np.int64)
## 16-09-2021; An attempt to optimize the speed; all pulses should be already checked in the TEST RUN
## Uncomment everything starting with ## if needed
### compare the end time with the start time for each couple of pulses
##for index, element in enumerate(sorted_np_array[:-1]):
## # minimal_distance is 10 ns now
## if sorted_np_array[index + 1][1] - element[2] < self.minimal_distance_phase:
## assert(1 == 2), 'Overlapping pulses or two pulses with less than ' + str(self.minimal_distance_phase*2) + ' ns distance'
## else:
## pass
return sorted_np_array
elif self.test_flag == 'test':
sorted_np_array = np.asarray(sorted(np_array, key = lambda x: int(x[1])), dtype = np.int64)
# compare the end time with the start time for each couple of pulses
for index, element in enumerate(sorted_np_array[:-1]):
# self.min_pulse_length is 10 ns now
if sorted_np_array[index + 1][1] - element[2] < self.minimal_distance_phase:
assert(1 == 2), 'Overlapping pulses or two pulses with less than ' + str(self.minimal_distance_phase*2) + ' ns distance'
else:
pass
return np_array
def delete_duplicates(self, np_array):
"""
Auxilary function that delete duplicates from numpy array
It is used when we deal with AMP_ON and LNA_PROTECT pulses
with less than 12 ns distance
"""
if self.test_flag != 'test':
no_duplicate_array = np.unique(np_array, axis = 0)
return no_duplicate_array
elif self.test_flag == 'test':
no_duplicate_array = np.unique(np_array, axis = 0)
return no_duplicate_array
def preparing_to_bit_pulse(self, np_array):
"""
For pulses at each channel we check whether there is overlapping pulses using
check_problem_pulses()
This function also automatically adds LNA_PROTECT and AMP_ON pulses
using add_amp_on_pulses() / add_lna_protect_pulses() and check
them on the distance < 12 ns, if so they are combined in one pulse inside
instruction_pulse_short_lna_amp() function
for phase pulses the minimal distance for checking is 10 ns
for mw, awg or cross mw-awg - 40 ns
RECT_AWG pulses are shifted back in order to compare their distance with MW pulses
"""
if self.test_flag != 'test':
if self.auto_defense == 'False':
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( np_array ) )
# iterate over all pulses at different channels
for index, element in enumerate(split_pulse_array):
# for all pulses just check 40 ns distance
self.check_problem_pulses(element)
# get assertion error if the distance < 40 ns
return self.convertion_to_numpy( np_array )
elif self.auto_defense == 'True':
# for delete AWG pulses before overlap check; and for checking only AWG pulses
awg_index = []
mw_index = []
# for checking of overlap MW and non-shifted AWG; in the real pulse sequence AWG is converted to shifter RECT_AWG
shifted_back_awg_pulses = []
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( np_array ) )
# iterate over all pulses at different channels
for index, element in enumerate(split_pulse_array):
if element[0, 0] == 2**self.channel_dict['MW'] or element[0, 0] == 2**self.channel_dict['AWG']:
if self.awg_pulses != 1:
# for MW pulses check 40 ns distance and add AMP_ON, LNA_PROTECT pulses
self.check_problem_pulses(element)
else:
# for AWG we do not check 40 ns distance, since RECT_AWG will be extended in the same way as AMP_ON
for index_awg_mw, element_awg_mw in enumerate(element):
if element_awg_mw[0] == 2**self.channel_dict['AWG']:
# shift back RECT_AWG to AWG
shifted_back_awg_pulses.append([element_awg_mw[0], element_awg_mw[1] + int(self.rect_awg_switch_delay/self.timebase), \
element_awg_mw[2] + int(self.rect_awg_switch_delay/self.timebase) - int(self.rect_awg_switch_delay/self.timebase) - int(self.rect_awg_delay/self.timebase)])
awg_index.append(index_awg_mw)
elif element_awg_mw[0] == 2**self.channel_dict['MW']:
mw_index.append(index_awg_mw)
no_mw_element = np.delete( element, list(dict.fromkeys(mw_index)), axis = 0 ).tolist()
no_awg_element = np.delete( element, list(dict.fromkeys(awg_index)), axis = 0 ).tolist()
# if there is no MW
try:
shifted_back_awg_mw = np.concatenate((no_awg_element, shifted_back_awg_pulses), axis = 0)
except ValueError:
shifted_back_awg_mw = shifted_back_awg_pulses
self.check_problem_pulses(no_awg_element)
self.check_problem_pulses(no_mw_element)
self.check_problem_pulses(shifted_back_awg_mw)
# add AMP_ON and LNA_PROTECT
amp_on_pulses = self.add_amp_on_pulses(element)
lna_pulses = self.add_lna_protect_pulses(element)
# check AMP_ON, LNA_PROTECT pulses on < 12 ns distance
cor_pulses_amp, prob_pulses_amp = self.check_problem_pulses_amp_lna(amp_on_pulses)
cor_pulses_lna, prob_pulses_lna = self.check_problem_pulses_amp_lna(lna_pulses)
# combining short distance AMP_ON pulses; the action depends on
# whether there are "problenatic pulses" (prob_pulses_amp)
# cor_pulses_amp - pulses with > 12 ns distance
# problenatic pulses are joined by convertion to bit array, applying
# check_short_pulses() / joining_pulses() inside convert_to_bit_pulse_amp_lna()
# and back to instruction instruction_pulse_short_lna_amp()
if prob_pulses_amp[0][0] == 0:
cor_pulses_amp_final = cor_pulses_amp
elif cor_pulses_amp[0][0] == 0:
# nothing to concatenate
cor_pulses_amp_final = self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_amp, \
self.channel_dict['AMP_ON']))
else:
cor_pulses_amp_final = np.concatenate((cor_pulses_amp, self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_amp, \
self.channel_dict['AMP_ON']))), axis = 0)
# combining short distance LNA_PROTECT pulses
if prob_pulses_lna[0][0] == 0:
cor_pulses_lna_final = cor_pulses_lna
elif cor_pulses_lna[0][0] == 0:
# nothing to concatenate
cor_pulses_lna_final = self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_lna, \
self.channel_dict['LNA_PROTECT']))
else:
cor_pulses_lna_final = np.concatenate((cor_pulses_lna, self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_lna, \
self.channel_dict['LNA_PROTECT']))), axis = 0)
elif element[0, 0] == 2**self.channel_dict['-X'] or element[0, 0] == 2**self.channel_dict['+Y']:
pass
# for phase pulses just check 10 ns distance
# self.check_problem_pulses(element)
# get assertion error if the distance < 10 ns
else:
pass
# for non-MW pulses just check 40 ns distance
#self.check_problem_pulses(element)
# get assertion error if the distance < 40 ns
# combine all pulses
#np.concatenate( (self.convertion_to_numpy( self.pulse_array ), cor_pulses_amp_final, cor_pulses_lna_final), axis = None)
try:
#return np.row_stack( (self.convertion_to_numpy( self.pulse_array ), cor_pulses_amp_final, cor_pulses_lna_final))
# self.extending_rect_awg( self.pulse_array ) is for extendind RECT_AWG pulses
# see self.extending_rect_awg()
return np.row_stack( (self.extending_rect_awg( self.pulse_array ), cor_pulses_amp_final, cor_pulses_lna_final))
# when we do not MW pulses at all
except UnboundLocalError:
#return self.convertion_to_numpy( self.pulse_array )
return self.extending_rect_awg( self.pulse_array )
elif self.test_flag == 'test':
if self.auto_defense == 'False':
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( np_array ) )
# iterate over all pulses at different channels
for index, element in enumerate(split_pulse_array):
# for all pulses just check 40 ns distance
self.check_problem_pulses(element)
# get assertion error if the distance < 40 ns
return self.convertion_to_numpy( np_array )
elif self.auto_defense == 'True':
awg_index = []
mw_index = []
shifted_back_awg_pulses = []
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( np_array ) )
for index, element in enumerate(split_pulse_array):
if element[0, 0] == 2**self.channel_dict['MW'] or element[0, 0] == 2**self.channel_dict['AWG']:
if self.awg_pulses != 1:
# for MW pulses check 40 ns distance and add AMP_ON, LNA_PROTECT pulses
self.check_problem_pulses(element)
else:
# for AWG we do not check 40 ns distance, since RECT_AWG will be extended in the same way as AMP_ON
for index_awg_mw, element_awg_mw in enumerate(element):
if element_awg_mw[0] == 2**self.channel_dict['AWG']:
# shift back RECT_AWG to AWG
shifted_back_awg_pulses.append([element_awg_mw[0], element_awg_mw[1] + int(self.rect_awg_switch_delay/self.timebase), \
element_awg_mw[2] + int(self.rect_awg_switch_delay/self.timebase) - int(self.rect_awg_switch_delay/self.timebase) - int(self.rect_awg_delay/self.timebase)])
awg_index.append(index_awg_mw)
elif element_awg_mw[0] == 2**self.channel_dict['MW']:
mw_index.append(index_awg_mw)
no_mw_element = np.delete( element, list(dict.fromkeys(mw_index)), axis = 0 ).tolist()
no_awg_element = np.delete( element, list(dict.fromkeys(awg_index)), axis = 0 ).tolist()
# if there is no MW
try:
shifted_back_awg_mw = np.concatenate((no_awg_element, shifted_back_awg_pulses), axis = 0)
except ValueError:
shifted_back_awg_mw = shifted_back_awg_pulses
self.check_problem_pulses(no_awg_element)
# 09-10-2021 Commented next line for full AWG ESEEM
# uncomment in case of problems
self.check_problem_pulses(no_mw_element)
self.check_problem_pulses(shifted_back_awg_mw)
##with open("test.out", "a") as f:
## np.savetxt(f, no_mw_element, delimiter=',', fmt = '%u')
##f.close()
amp_on_pulses = self.add_amp_on_pulses(element)
lna_pulses = self.add_lna_protect_pulses(element)
# check AMP_ON, LNA_PROTECT pulses
cor_pulses_amp, prob_pulses_amp = self.check_problem_pulses_amp_lna(amp_on_pulses)
cor_pulses_lna, prob_pulses_lna = self.check_problem_pulses_amp_lna(lna_pulses)
# combining short distance AMP_ON pulses
if prob_pulses_amp[0][0] == 0:
cor_pulses_amp_final = cor_pulses_amp
elif cor_pulses_amp[0][0] == 0:
cor_pulses_amp_final = self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_amp, \
self.channel_dict['AMP_ON']))
else:
cor_pulses_amp_final = np.concatenate((cor_pulses_amp, self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_amp, \
self.channel_dict['AMP_ON']))), axis = 0)
# combining short distance LNA_PROTECT pulses
if prob_pulses_lna[0][0] == 0:
cor_pulses_lna_final = cor_pulses_lna
elif cor_pulses_lna[0][0] == 0:
cor_pulses_lna_final = self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_lna, \
self.channel_dict['LNA_PROTECT']))
else:
cor_pulses_lna_final = np.concatenate((cor_pulses_lna, self.instruction_pulse_short_lna_amp(self.convert_to_bit_pulse_amp_lna(prob_pulses_lna, \
self.channel_dict['LNA_PROTECT']))), axis = 0)
elif element[0, 0] == 2**self.channel_dict['-X'] or element[0, 0] == 2**self.channel_dict['+Y']:
# for phases pulses just check 10 ns distance
self.check_problem_pulses_phase(element)
else:
# for non-MW pulses just check 40 ns distance
self.check_problem_pulses(element)
# combine all pulses
#np.concatenate( (self.convertion_to_numpy( self.pulse_array ), cor_pulses_amp_final, cor_pulses_lna_final), axis = None)
try:
return np.row_stack( (self.extending_rect_awg( self.pulse_array ), cor_pulses_amp_final, cor_pulses_lna_final))
except UnboundLocalError:
return self.extending_rect_awg( self.pulse_array )
def split_into_parts(self, np_array, rep_time):
"""
When we have situation with a big distance (> 2000 ns) between
two pulses it is time and memory efficient to treat this areas separately.
To do it we:
- Sort pulses using start time
- Find indexes jump
- Apply the obtained mask on initial pulse array
After that each area are treated separately by convert_to_bit_pulse() and
instruction_pulse()
"""
if self.test_flag != 'test':
answer = []
min_list = []
pulses = self.preparing_to_bit_pulse(np_array)
sorted_pulses_start = np.asarray(sorted(pulses, key = lambda x: int(x[1])), dtype = np.int64)
# self.max_pulse_length is 2000 ns now
index_jump = np.where(np.diff(sorted_pulses_start[:,1], axis = 0) > self.max_pulse_length )[0]
sorted_arrays_parts = np.split(sorted_pulses_start, index_jump + 1)
for index, element in enumerate(sorted_arrays_parts):
temp, min_value = self.convert_to_bit_pulse(element)
answer.append(self.instruction_pulse(temp))
# keep them all for further shifting
min_list.append(min_value)
# at this point we have different array for different interval:
# I. E. [[[0, 0, 70], [6, 70, 200], [14, 270, 20], [4, 290, 100],\
# [0, 390, 560], [1, 950, 20]], [[0, 0, 20000050], [6, 20000050, 200], [14, 20000250, 30], [4, 20000280, 100]]]
# We should adjust the beginning of all sub array with index >= 1
for index, element in enumerate(answer):
# the first sub array is ok
if index == 0:
pass
elif index > 0:
# the second and further should be shifted using data from the previous sub array
shift_region = answer[index - 1][-1][1] + answer[index - 1][-1][2]
# sweep through sub array
for index2, element2 in enumerate(element):
# to take into account the jump region between two sub arrays
# - min_list[0]*self.timebase common shifting of the first pulse
if index2 == 0:
element2[1] = shift_region
element2[2] = min_list[index]*self.timebase + element2[2] - shift_region - min_list[0]*self.timebase
elif index2 > 0:
element2[1] = element2[1] + min_list[index]*self.timebase - min_list[0]*self.timebase
#shift_region = element[-1][1] + element[-1][2]
#general.message(shift_region)
#general.message(element)
#element[0][1] = answer[index - 1][-1][1] + answer[index - 1][-1][2]
#element[0][2] = element[0][2] - element[0][1]
# flatten list
one_array = sum(answer, [])
# append delay for repetition rate
#one_array.append( [0, one_array[-1][1] + one_array[-1][2], \
# rep_time - one_array[-1][2] - one_array[-1][1]] )
if rep_time - one_array[-1][2] - one_array[-1][1] > (self.min_pulse_length + 4):
one_array.append( [0, one_array[-1][1] + one_array[-1][2], \
rep_time - one_array[-1][2] - one_array[-1][1]] )
return one_array
else:
general.message('Pulse sequence is longer than one period of the repetition rate')
sys.exit()
elif self.test_flag == 'test':
answer = []
min_list = []
pulses = self.preparing_to_bit_pulse(np_array)
sorted_pulses_start = np.asarray(sorted(pulses, key = lambda x: int(x[1])), dtype = np.int64)
# self.max_pulse_length is 2000 ns now
index_jump = np.where(np.diff(sorted_pulses_start[:,1], axis = 0) > self.max_pulse_length/self.timebase )[0]
sorted_arrays_parts = np.split(sorted_pulses_start, index_jump + 1)
for index, element in enumerate(sorted_arrays_parts):
temp, min_value = self.convert_to_bit_pulse(element)
answer.append(self.instruction_pulse(temp))
# keep them all for further shifting
min_list.append(min_value)
# We should adjust the beginning of all sub array with index >= 1
for index, element in enumerate(answer):
# the first sub array is ok
if index == 0:
pass
elif index > 0:
# the second and further should be shifted using data from the previous sub array
shift_region = answer[index - 1][-1][1] + answer[index - 1][-1][2]
# sweep through sub array
for index2, element2 in enumerate(element):
# to take into account the jump region between two sub arrays
if index2 == 0:
element2[1] = shift_region
element2[2] = min_list[index]*self.timebase + element2[2] - shift_region - min_list[0]*self.timebase
elif index2 > 0:
element2[1] = element2[1] + min_list[index]*self.timebase - min_list[0]*self.timebase
#shift_region = element[-1][1] + element[-1][2]
#general.message(shift_region)
#general.message(element)
#element[0][1] = answer[index - 1][-1][1] + answer[index - 1][-1][2]
#element[0][2] = element[0][2] - element[0][1]
one_array = sum(answer, [])
if rep_time - one_array[-1][2] - one_array[-1][1] > (self.min_pulse_length + 4):
one_array.append( [0, one_array[-1][1] + one_array[-1][2], \
rep_time - one_array[-1][2] - one_array[-1][1]] )
return one_array
else:
assert(1 == 2), 'Pulse sequence is longer than one period of the repetition rate'
def convert_to_bit_pulse(self, np_array):
"""
A function to calculate in which time interval
two or more different channels are on.
All the pulses converted in an bit_array of 0 and 1, where
1 corresponds to the time interval when the channel is on.
The size of the bit_array is determined by the total length
of the full pulse sequence.
Finally, a bit_array is multiplied by a 2**ch in order to
calculate CH instructions for SpinAPI.
It is optimized for using at subarrays inside split_into_parts()
"""
if self.test_flag != 'test':
#pulses = self.preparing_to_bit_pulse(np_array)
pulses = np_array
max_pulse = np.amax(pulses[:,2])
# we get rid of constant shift in the first pulse, since
# it is useless in terms of pulse bluster instructions
# the first pulse in sequence will start at 50 ns all other shifted accordingly
# this value can be adjust by add_shift parameter (multiplited by self.timebase)
min_pulse = np.amin(pulses[:,1]) - self.add_shift
bit_array = np.zeros( max_pulse - min_pulse, dtype = np.int64 )
i = 0
while i < len(pulses):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
translation_array = pulses[i, 0]*np.concatenate( (np.zeros( pulses[i, 1] - min_pulse, dtype = np.int64), \
np.ones(pulses[i, 2] - pulses[i, 1], dtype = np.int64), \
np.zeros(max_pulse - pulses[i, 2], dtype = np.int64)), axis = None)
# summing arrays for each pulse into the finalbit_array
bit_array = bit_array + translation_array
i += 1
return bit_array, min_pulse
elif self.test_flag == 'test':
#pulses = self.preparing_to_bit_pulse(np_array)
pulses = np_array
max_pulse = np.amax(pulses[:,2])
min_pulse = np.amin(pulses[:,1]) - self.add_shift
bit_array = np.zeros( max_pulse - min_pulse, dtype = np.int64 )
i = 0
while i < len(pulses):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
translation_array = pulses[i, 0]*np.concatenate( (np.zeros( pulses[i, 1] - min_pulse, dtype = np.int64), \
np.ones(pulses[i, 2] - pulses[i, 1], dtype = np.int64), \
np.zeros(max_pulse - pulses[i, 2], dtype = np.int64)), axis = None)
# summing arrays for each pulse into the finalbit_array
bit_array = bit_array + translation_array
i += 1
return bit_array, min_pulse
def convert_to_bit_pulse_visualizer(self, np_array):
"""
The same function optimized for using in pulser_visualize()
in which we DO NOT split all area into subarrays if
there are > 2000 ns distance between pulses
A constant shift in the first pulse is omitted
Note that this function provides a different treatment of
pulse sequence. It order to check what EXACTLY we havw after
convert_to_bit_pulse() use convert_to_bit_pulse_visualizer_final_instructions()
"""
if self.test_flag != 'test':
pulses = self.preparing_to_bit_pulse(np_array)
#pulses = np_array
#for index, element in enumerate(pulses):
# element[2] = element[1] + element[2]
max_pulse = np.amax(pulses[:,2])
min_pulse = np.amin(pulses[:,1]) - self.add_shift
bit_array = np.zeros( 2*(max_pulse - min_pulse), dtype = np.int64 )
bit_array_pulses = []
i = 0
while i < len(pulses):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
if pulses[i, 0] != 0:
translation_array = pulses[i, 0]*np.concatenate( (np.zeros( 2*(pulses[i, 1] - min_pulse), dtype = np.int64), \
np.ones(2*(pulses[i, 2] - pulses[i, 1]), dtype = np.int64), \
np.zeros(2*(max_pulse - pulses[i, 2]), dtype = np.int64)), axis = None)
# appending each pulses individually
bit_array_pulses.append(translation_array)
i += 1
return bit_array_pulses
elif self.test_flag == 'test':
pulses = self.preparing_to_bit_pulse(np_array)
#pulses = np_array
#for index, element in enumerate(pulses):
# element[2] = element[1] + element[2]
max_pulse = np.amax(pulses[:,1])
min_pulse = np.amin(pulses[:,1]) - self.add_shift*0
bit_array = np.zeros( max_pulse - 0*min_pulse, dtype = np.int64 )
bit_array_pulses = []
i = 0
while i < len(pulses):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
if pulses[i, 0] != 0:
translation_array = pulses[i, 0]*np.concatenate( (np.zeros( pulses[i, 1] - 0*min_pulse, dtype = np.int64), \
np.ones(pulses[i, 2] - pulses[i, 1], dtype = np.int64), \
np.zeros(max_pulse - pulses[i, 2], dtype = np.int64)), axis = None)
# summing arrays for each pulse into the finalbit_array
bit_array_pulses.append(translation_array)
i += 1
return bit_array_pulses
def convert_to_bit_pulse_visualizer_final_instructions(self, np_array):
"""
The same function optimized for using in pulser_visualize()
in which we DO NOT split all area into subarrays if
there are > 2000 ns distance between pulses
A constant shift in the first pulse is omitted.
It is shown exactly the pulses we will have after convert_to_bit_pulse()
Please note that channel numbers will be already joined if two channels are turned on
simultaneously
"""
if self.test_flag != 'test':
#pulses = self.preparing_to_bit_pulse(np_array)
pulses = np_array
# convert back to channel, start, end
# from channel, start, length
for index, element in enumerate(pulses):
element[2] = element[1] + element[2]
max_pulse = np.amax(pulses[:,2])
min_pulse = np.amin(pulses[:,1]) - self.add_shift*0
bit_array = np.zeros( max_pulse - min_pulse, dtype = np.int64 )
bit_array_pulses = []
i = 0
while i < len(pulses):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
if pulses[i, 0] != 0:
translation_array = pulses[i, 0]*np.concatenate( (np.zeros( pulses[i, 1] - min_pulse, dtype = np.int64), \
np.ones(pulses[i, 2] - pulses[i, 1], dtype = np.int64), \
np.zeros(max_pulse - pulses[i, 2], dtype = np.int64)), axis = None)
# appending each pulses individually
bit_array_pulses.append(translation_array)
i += 1
return bit_array_pulses
elif self.test_flag == 'test':
#pulses = self.preparing_to_bit_pulse(np_array)
pulses = np_array
for index, element in enumerate(pulses):
element[2] = element[1] + element[2]
max_pulse = np.amax(pulses[:,1])
min_pulse = np.amin(pulses[:,1]) - self.add_shift*0
bit_array = np.zeros( max_pulse - min_pulse, dtype = np.int64 )
bit_array_pulses = []
i = 0
while i < len(pulses):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
if pulses[i, 0] != 0:
translation_array = pulses[i, 0]*np.concatenate( (np.zeros( pulses[i, 1] - min_pulse, dtype = np.int64), \
np.ones(pulses[i, 2] - pulses[i, 1], dtype = np.int64), \
np.zeros(max_pulse - pulses[i, 2], dtype = np.int64)), axis = None)
# summing arrays for each pulse into the finalbit_array
bit_array_pulses.append(translation_array)
i += 1
return bit_array_pulses
def instruction_pulse(self, np_array):
"""
Final convertion to the pulse blaster instruction pulses
It splits the bit_array into sequence of bit_arrays for individual pulses
After that convert them into instructions [channel, start, length]
Bit array should not start with nonzero elements
It is used inside convert_to_bit_pulse()
"""
if self.test_flag != 'test':
final_pulse_array = []
# Create an array that is 1 where a is 0, and pad each end with an extra 0.
iszero = np.concatenate(([0], np_array, [0]))
absdiff = np.abs(np.diff(iszero))
# creating a mask to split bit array
ranges = np.where(absdiff != 0)[0]
# using a mask
pulse_array = np.split(np_array, ranges)
pulse_info = np.concatenate(([0], ranges))
# return back self.timebase; convert to instructions
for index, element in enumerate(pulse_info[:-1]):
final_pulse_array.append( [pulse_array[index][0], self.timebase*pulse_info[index], self.timebase*(pulse_info[index + 1] - pulse_info[index])] )
return final_pulse_array
elif self.test_flag == 'test':
final_pulse_array = []
# Create an array that is 1 where a is 0, and pad each end with an extra 0.
iszero = np.concatenate(([0], np_array, [0]))
absdiff = np.abs(np.diff(iszero))
ranges = np.where(absdiff != 0)[0]
pulse_array = np.split(np_array, ranges)
pulse_info = np.concatenate(([0], ranges))
for index, element in enumerate(pulse_info[:-1]):
final_pulse_array.append( [pulse_array[index][0], self.timebase*pulse_info[index], self.timebase*(pulse_info[index + 1] - pulse_info[index])] )
return final_pulse_array
def add_amp_on_pulses(self, p_list):
"""
A function that automatically add AMP_ON pulses with corresponding delays
specified by switch_delay and amp_delay
"""
if self.test_flag != 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
amp_on_list = []
# for dealing with overlap of RECT_AWG pulse with MW; RECT_AWG should behaves the same as AMP_ON
awg_list = []
for index, element in enumerate(p_list):
if element[0] == 2**(self.channel_dict['MW']):
amp_on_list.append( [2**(self.channel_dict['AMP_ON']), element[1] - self.switch_delay, element[2] + self.amp_delay] )
# AMP_ON and RECT_AWG coincide now
elif element[0] == 2**(self.channel_dict['AWG']):
amp_on_list.append( [2**(self.channel_dict['AMP_ON']), element[1] - 0*self.switch_delay, element[2] + 0*self.amp_delay] )
awg_list.append(element)
else:
pass
# additional checking and correcting amp_on pulse in the case
# when amp_on pulses are diagonally shifted to mw pulses
# in this case there can be nasty short overpal of amp_on pulse 2
# and mw pulse 1 and so on
for element in amp_on_list:
for element_mw in p_list:
if (element_mw[1] - element[1] <= self.overlap_amp_lna_mw) and (element_mw[1] - element[1] > 0):
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[1] - element[1] >= -self.overlap_amp_lna_mw) and (element_mw[1] - element[1] < 0):
element[1] = element_mw[1]
elif (element_mw[1] - element[2]) <= self.overlap_amp_lna_mw and (element_mw[1] - element[2] > 0):
element[2] = element_mw[1]
elif (element_mw[1] - element[2]) >= -self.overlap_amp_lna_mw and (element_mw[1] - element[2] < 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[2] = element_mw[2]
else:
element[2] = element[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_mw[2] - element[2] <= self.overlap_amp_lna_mw) and (element_mw[2] - element[2] > 0):
element[2] = element_mw[2]
elif (element_mw[2] - element[2] >= -self.overlap_amp_lna_mw) and (element_mw[2] - element[2] < 0):
element[2] = element[2] + self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) <= self.overlap_amp_lna_mw and (element_mw[2] - element[1] > 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[1] = element_mw[1]
else:
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) >= -self.overlap_amp_lna_mw and (element_mw[2] - element[1] < 0):
element[1] = element_mw[2]
# additional checking for phase and amp_on pulses after
# overlap correction
if len(self.phase_array_length) > 0:
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( self.pulse_array ) )
# iterate over all pulses at different channels and taking phase pulses
for index, element in enumerate(split_pulse_array):
if ( element[0, 0] == 2**self.channel_dict['-X'] ) or ( element[0, 0] == 2**self.channel_dict['+Y'] ):
for element_phase in element:
for element_amp in amp_on_list:
if (element_phase[1] - element_amp[2] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[2] > 0):
element_amp[2] = element_phase[1] + self.overlap_amp_lna_mw
elif (element_phase[1] - element_amp[2] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[2] < 0):
element_amp[2] = element_amp[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_phase[1] - element_amp[1] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[1] > 0):
element_amp[1] = element_amp[1] - self.overlap_amp_lna_mw
elif (element_phase[1] - element_amp[1] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[1] < 0):
element_amp[1] = element_phase[1]
else:
pass
return np.asarray(amp_on_list)
elif self.test_flag == 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
amp_on_list = []
awg_list = []
for index, element in enumerate(p_list):
if element[0] == 2**(self.channel_dict['MW']):
if (element[2] + self.amp_delay) - (element[1] - self.switch_delay) <= self.max_pulse_length/2:
amp_on_list.append( [2**(self.channel_dict['AMP_ON']), element[1] - self.switch_delay, element[2] + self.amp_delay] )
else:
assert(1 == 2), 'Maximum available length (1900 ns) for AMP_ON pulse is reached'
# AMP_ON and RECT_AWG coincide now
elif element[0] == 2**(self.channel_dict['AWG']):
if element[2] - element[1] <= self.max_pulse_length/2:
amp_on_list.append( [2**(self.channel_dict['AMP_ON']), element[1], element[2]] )
awg_list.append(element)
else:
assert(1 == 2), 'Maximum available length (1900 ns) for AMP_ON pulse is reached'
else:
pass
for element in amp_on_list:
for element_mw in p_list:
if (element_mw[1] - element[1] <= self.overlap_amp_lna_mw) and (element_mw[1] - element[1] > 0):
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[1] - element[1] >= -self.overlap_amp_lna_mw) and (element_mw[1] - element[1] < 0):
element[1] = element_mw[1]
elif (element_mw[1] - element[2]) <= self.overlap_amp_lna_mw and (element_mw[1] - element[2] > 0):
element[2] = element_mw[1]
elif (element_mw[1] - element[2]) >= -self.overlap_amp_lna_mw and (element_mw[1] - element[2] < 0):
if element_mw[2] - element_mw[1] <= 30:
element[2] = element_mw[2]
else:
element[2] = element[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_mw[2] - element[2] <= self.overlap_amp_lna_mw) and (element_mw[2] - element[2] > 0):
element[2] = element_mw[2]
elif (element_mw[2] - element[2] >= -self.overlap_amp_lna_mw) and (element_mw[2] - element[2] < 0):
element[2] = element[2] + self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) <= self.overlap_amp_lna_mw and (element_mw[2] - element[1] > 0):
if element_mw[2] - element_mw[1] <= 30:
element[1] = element_mw[1]
else:
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) >= -self.overlap_amp_lna_mw and (element_mw[2] - element[1] < 0):
element[1] = element_mw[2]
if len(self.phase_array_length) > 0:
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( self.pulse_array ) )
# iterate over all pulses at different channels and taking phase pulses
for index, element in enumerate(split_pulse_array):
if ( element[0, 0] == 2**self.channel_dict['-X'] ) or ( element[0, 0] == 2**self.channel_dict['+Y'] ):
for element_phase in element:
for element_amp in amp_on_list:
if (element_phase[1] - element_amp[2] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[2] > 0):
element_amp[2] = element_phase[1] + self.overlap_amp_lna_mw
elif (element_phase[1] - element_amp[2] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[2] < 0):
element_amp[2] = element_amp[2] + self.overlap_amp_lna_mw
if (element_phase[1] - element_amp[1] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[1] > 0):
element_amp[1] = element_amp[1] - self.overlap_amp_lna_mw
elif (element_phase[1] - element_amp[1] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_amp[1] < 0):
element_amp[1] = element_phase[1]
else:
pass
if self.awg_pulses == 1:
for element in awg_list:
for element_mw in p_list:
if (element_mw[1] - element[1] <= self.overlap_amp_lna_mw) and (element_mw[1] - element[1] > 0):
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[1] - element[1] >= -self.overlap_amp_lna_mw) and (element_mw[1] - element[1] < 0):
element[1] = element_mw[1]
elif (element_mw[1] - element[2]) <= self.overlap_amp_lna_mw and (element_mw[1] - element[2] > 0):
element[2] = element_mw[1]
elif (element_mw[1] - element[2]) >= -self.overlap_amp_lna_mw and (element_mw[1] - element[2] < 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[2] = element_mw[2]
else:
element[2] = element[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_mw[2] - element[2] <= self.overlap_amp_lna_mw) and (element_mw[2] - element[2] > 0):
element[2] = element_mw[2]
elif (element_mw[2] - element[2] >= -self.overlap_amp_lna_mw) and (element_mw[2] - element[2] < 0):
element[2] = element[2] + self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) <= self.overlap_amp_lna_mw and (element_mw[2] - element[1] > 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[1] = element_mw[1]
else:
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) >= -self.overlap_amp_lna_mw and (element_mw[2] - element[1] < 0):
element[1] = element_mw[2]
return np.asarray(amp_on_list)
def add_lna_protect_pulses(self, p_list):
"""
A function that automatically add LNA_PROTECT pulses with corresponding delays
specified by switch_delay and protect_delay
"""
if self.test_flag != 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
lna_protect_list = []
for index, element in enumerate(p_list):
if element[0] == 2**(self.channel_dict['MW']):
lna_protect_list.append( [2**(self.channel_dict['LNA_PROTECT']), element[1] - self.switch_delay, element[2] + self.protect_delay] )
# LNA_PROTECT and RECT_AWG coincide in the start position but LNA is longer at protect_delay
elif element[0] == 2**(self.channel_dict['AWG']):
lna_protect_list.append( [2**(self.channel_dict['LNA_PROTECT']), element[1] - 0*self.switch_delay, element[2] - int(self.rect_awg_delay/self.timebase) + self.protect_awg_delay] )
else:
pass
# additional checking and correcting lna_protect pulse in the case
# when lna_protect pulses are diagonally shifted to mw pulses
# in this case there can be nasty short overpal of lna_protect pulse 2
# and mw pulse 1 and so on
for element in lna_protect_list:
for element_mw in p_list:
if (element_mw[1] - element[1] <= self.overlap_amp_lna_mw) and (element_mw[1] - element[1] > 0):
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[1] - element[1] >= -self.overlap_amp_lna_mw) and (element_mw[1] - element[1] < 0):
element[1] = element_mw[1]
elif (element_mw[1] - element[2]) <= self.overlap_amp_lna_mw and (element_mw[1] - element[2] > 0):
element[2] = element_mw[1]
elif (element_mw[1] - element[2]) >= -self.overlap_amp_lna_mw and (element_mw[1] - element[2] < 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[2] = element_mw[2]
else:
element[2] = element[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_mw[2] - element[2] <= self.overlap_amp_lna_mw) and (element_mw[2] - element[2] > 0):
element[2] = element_mw[2]
elif (element_mw[2] - element[2] >= -self.overlap_amp_lna_mw) and (element_mw[2] - element[2] < 0):
element[2] = element[2] + self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) <= self.overlap_amp_lna_mw and (element_mw[2] - element[1] > 0):
# restriction on the pulse length in order to not jump into another restriction....
if element_mw[2] - element_mw[1] <= 30:
element[1] = element_mw[1]
else:
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) >= -self.overlap_amp_lna_mw and (element_mw[2] - element[1] < 0):
element[1] = element_mw[2]
# additional checking for phase and lna_protect pulses after
# overlap correction
if len(self.phase_array_length) > 0:
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( self.pulse_array ) )
# iterate over all pulses at different channels and taking phase pulses
for index, element in enumerate(split_pulse_array):
if ( element[0, 0] == 2**self.channel_dict['-X'] ) or ( element[0, 0] == 2**self.channel_dict['+Y'] ):
for element_phase in element:
for element_lna in lna_protect_list:
if (element_phase[1] - element_lna[2] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[2] > 0):
element_lna[2] = element_phase[1] + self.overlap_amp_lna_mw
elif (element_phase[1] - element_lna[2] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[2] < 0):
element_lna[2] = element_lna[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_phase[1] - element_lna[1] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[1] > 0):
element_lna[1] = element_lna[1] - self.overlap_amp_lna_mw
elif (element_phase[1] - element_lna[1] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[1] < 0):
element_lna[1] = element_phase[1]
else:
pass
return np.asarray(lna_protect_list)
elif self.test_flag == 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
lna_protect_list = []
for index, element in enumerate(p_list):
if element[0] == 2**(self.channel_dict['MW']):
lna_protect_list.append( [2**(self.channel_dict['LNA_PROTECT']), element[1] - self.switch_delay, element[2] + self.protect_delay] )
# LNA_PROTECT and RECT_AWG coincide in the start position but LNA is longer at protect_delay
elif element[0] == 2**(self.channel_dict['AWG']):
lna_protect_list.append( [2**(self.channel_dict['LNA_PROTECT']), element[1] - 0*self.switch_delay, element[2] - int(self.rect_awg_delay/self.timebase) + self.protect_awg_delay] )
else:
pass
for element in lna_protect_list:
for element_mw in p_list:
if (element_mw[1] - element[1] <= self.overlap_amp_lna_mw) and (element_mw[1] - element[1] > 0):
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[1] - element[1] >= -self.overlap_amp_lna_mw) and (element_mw[1] - element[1] < 0):
element[1] = element_mw[1]
elif (element_mw[1] - element[2]) <= self.overlap_amp_lna_mw and (element_mw[1] - element[2] > 0):
element[2] = element_mw[1]
elif (element_mw[1] - element[2]) >= -self.overlap_amp_lna_mw and (element_mw[1] - element[2] < 0):
if element_mw[2] - element_mw[1] <= 30:
element[2] = element_mw[2]
else:
element[2] = element[2] + self.overlap_amp_lna_mw
# checking of start and end should be splitted into two checks
# in case of double start/end restriction
if (element_mw[2] - element[2] <= self.overlap_amp_lna_mw) and (element_mw[2] - element[2] > 0):
element[2] = element_mw[2]
elif (element_mw[2] - element[2] >= -self.overlap_amp_lna_mw) and (element_mw[2] - element[2] < 0):
element[2] = element[2] + self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) <= self.overlap_amp_lna_mw and (element_mw[2] - element[1] > 0):
if element_mw[2] - element_mw[1] <= 30:
element[1] = element_mw[1]
else:
element[1] = element[1] - self.overlap_amp_lna_mw
elif (element_mw[2] - element[1]) >= -self.overlap_amp_lna_mw and (element_mw[2] - element[1] < 0):
element[1] = element_mw[2]
if len(self.phase_array_length) > 0:
split_pulse_array = self.splitting_acc_to_channel( self.convertion_to_numpy( self.pulse_array ) )
# iterate over all pulses at different channels and taking phase pulses
for index, element in enumerate(split_pulse_array):
if ( element[0, 0] == 2**self.channel_dict['-X'] ) or ( element[0, 0] == 2**self.channel_dict['+Y'] ):
for element_phase in element:
for element_lna in lna_protect_list:
if (element_phase[1] - element_lna[2] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[2] > 0):
element_lna[2] = element_phase[1] + self.overlap_amp_lna_mw
elif (element_phase[1] - element_lna[2] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[2] < 0):
element_lna[2] = element_lna[2] + self.overlap_amp_lna_mw
if (element_phase[1] - element_lna[1] <= self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[1] > 0):
element_lna[1] = element_lna[1] - self.overlap_amp_lna_mw
elif (element_phase[1] - element_lna[1] >= -self.overlap_amp_lna_mw) and (element_phase[1] - element_lna[1] < 0):
element_lna[1] = element_phase[1]
else:
pass
return np.asarray(lna_protect_list)
def check_problem_pulses_amp_lna(self, p_list):
"""
A function for checking whether there is a two
close to each other AMP_ON or LNA_PROTECT pulses (less than 12 ns)
If so pulse array is splitted into the problematic part and correct part
Returns both specified parts for further convertion in shich problematic part
are joined using check_short_pulses() and joining_pulses()
"""
if self.test_flag != 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
problem_list = []
# memorize index of problem elements
problem_index = []
# numpy arrays don't support element deletion
no_problem_list = deepcopy(p_list.tolist())
# there STILL can be errors
# now compare two consequnce pulses (end and start + 1)
for index, element in enumerate(p_list[:-1]):
# minimal_distance_amp_lna is 12 ns now
if p_list[index + 1][1] - element[2] < self.minimal_distance_amp_lna:
problem_list.append(element)
problem_list.append(p_list[index + 1])
# memorize indexes of the problem pulses
problem_index.append(index)
problem_index.append(index + 1)
# delete duplicates in the index list: list(dict.fromkeys(problem_index)) )
# delete problem pulses from no_problem_list
# np.delete( no_problem_list, list(dict.fromkeys(problem_index)), axis = 0 ).tolist() )
no_problem_list = np.delete( no_problem_list, list(dict.fromkeys(problem_index)), axis = 0 ).tolist()
# for not returning an empty list
# the same conditions are used in preparing_to_bit_pulse()
if len(problem_list) == 0:
return self.delete_duplicates(np.asarray(no_problem_list)), np.array([[0]])
elif len(no_problem_list) == 0:
return np.array([[0]]), self.delete_duplicates(np.asarray(problem_list))
else:
return self.delete_duplicates(np.asarray(no_problem_list)), self.delete_duplicates(np.asarray(problem_list))
elif self.test_flag == 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
problem_list = []
problem_index = []
# numpy arrays don't support element deletion
no_problem_list = deepcopy(p_list.tolist())
for index, element in enumerate(p_list[:-1]):
# minimal_distance_amp_lna is 12 ns now
if p_list[index + 1][1] - element[2] < (self.minimal_distance_amp_lna):
problem_list.append(element)
problem_list.append(p_list[index + 1])
# memorize indexes of the problem pulses
problem_index.append(index)
problem_index.append(index + 1)
no_problem_list = np.delete( no_problem_list, list(dict.fromkeys(problem_index)), axis = 0 ).tolist()
if len(problem_list) == 0:
return self.delete_duplicates(np.asarray(no_problem_list)), np.array([[0]])
elif len(no_problem_list) == 0:
return np.array([[0]]), self.delete_duplicates(np.asarray(problem_list))
else:
return self.delete_duplicates(np.asarray(no_problem_list)), self.delete_duplicates(np.asarray(problem_list))
def convert_to_bit_pulse_amp_lna(self, p_list, channel):
"""
A function to calculate in which time interval
two or more different channels are on.
All the pulses converted in an bit_array of 0 and 1, where
1 corresponds to the time interval when the channel is on.
The size of the bit_array is determined by the total length
of the full pulse sequence.
Finally, a bit_array is multiplied by a 2**ch in order to
calculate CH instructions for SpinAPI.
It is used to check (check_short_pulses()) whether there are two AMP_ON or LNA_PROTECT pulses
with the distanse less than 12 ns between them
If so they are combined in one pulse by joining_pulses()
Generally, this function is close to convert_to_bit_pulse() and other convertion
functions
"""
if self.test_flag != 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
max_pulse = np.amax(p_list[:,2])
bit_array = np.zeros(max_pulse, dtype = np.int64)
i = 0
while i < len(p_list):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
translation_array = np.concatenate( (np.zeros(p_list[i, 1], dtype = np.int64), \
np.ones(p_list[i, 2] - p_list[i, 1], dtype = np.int64), \
np.zeros(max_pulse - p_list[i, 2], dtype = np.int64)), axis = None)
bit_array = bit_array | translation_array
i += 1
bit_array = 2**(channel)*self.check_short_pulses(bit_array, channel)
return bit_array
elif self.test_flag == 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
max_pulse = np.amax(p_list[:,2])
bit_array = np.zeros(max_pulse, dtype = np.int64)
i = 0
while i < len(p_list):
# convert each pulse in an array of 0 and 1,
# 1 corresponds to the time interval, where the channel is on
translation_array = np.concatenate( (np.zeros(p_list[i, 1], dtype = np.int64), \
np.ones(p_list[i, 2] - p_list[i, 1], dtype = np.int64), \
np.zeros(max_pulse - p_list[i, 2], dtype = np.int64)), axis = None)
bit_array = bit_array | translation_array
i += 1
bit_array = 2**(channel)*self.check_short_pulses(bit_array, channel)
return bit_array
def instruction_pulse_short_lna_amp(self, np_array):
"""
Final convertion to the pulse blaster instruction pulses
It splits the bit_array into sequence of bit_arrays for individual pulses
after that converts them into instructions
We can drop pulses with channel 0 for AMP_ON and LNA_PROTECT case
Generally, this function is close to instruction_pulse()
"""
if self.test_flag != 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
final_pulse_array = []
# Create an array that is 1 where a is 0, and pad each end with an extra 0.
iszero = np.concatenate(([0], np_array, [0]))
absdiff = np.abs(np.diff(iszero))
# creating a mask to split bit array
ranges = np.where(absdiff != 0)[0]
# split using a mask
pulse_array = np.split(np_array, ranges)
pulse_info = np.concatenate(([0], ranges))
for index, element in enumerate(pulse_info[:-1]):
# we can drop pulses with channel 0 for AMP_ON and LNA_PROTECT case
if pulse_array[index][0] != 0:
final_pulse_array.append( [pulse_array[index][0], pulse_info[index], pulse_info[index + 1]] )
else:
pass
return final_pulse_array
elif self.test_flag == 'test':
if self.auto_defense == 'False':
pass
elif self.auto_defense == 'True':
final_pulse_array = []
# Create an array that is 1 where a is 0, and pad each end with an extra 0.
iszero = np.concatenate(([0], np_array, [0]))
absdiff = np.abs(np.diff(iszero))
ranges = np.where(absdiff != 0)[0]
pulse_array = np.split(np_array, ranges)
pulse_info = np.concatenate(([0], ranges))
for index, element in enumerate(pulse_info[:-1]):
if pulse_array[index][0] != 0:
final_pulse_array.append( [pulse_array[index][0], pulse_info[index], pulse_info[index + 1]] )
else:
pass
return final_pulse_array
def check_short_pulses(self, np_array, channel):
"""
A function for checking whether there is two pulses with
the distance between them shorter than 40 ns
If there are such pulses on MW channel an error will be raised
LNA_PROTECT and AMP_ON pulsess will be combined in one pulse
"""
if self.test_flag != 'test':
# checking where the pulses are
one_indexes = np.argwhere(np_array == 1).flatten()
difference = np.diff(one_indexes)
## 16-09-2021; An attempt to optimize the speed; all pulses should be already checked in the TEST RUN
## Uncomment everything starting with ## if needed
if channel == self.channel_dict['LNA_PROTECT'] or channel == self.channel_dict['AMP_ON']:
##if channel != self.channel_dict['LNA_PROTECT'] and channel != self.channel_dict['AMP_ON']:
## # (min_pulse_length + 1) is 13 now
## if any(1 < element < (self.min_pulse_length + 1) for element in difference) == False:
## pass
## else:
## general.message('There are two pulses with shorter than ' + str(self.min_pulse_length*2) + ' ns distance between them')
## sys.exit()
##else:
if any(1 < element < (self.min_pulse_length + 1) for element in difference) == False:
return np_array
else:
final_array = self.joining_pulses(np_array)
return final_array
if self.test_flag == 'test':
# checking where the pulses are
one_indexes = np.argwhere(np_array == 1).flatten()
difference = np.diff(one_indexes)
if channel != self.channel_dict['LNA_PROTECT'] and channel != self.channel_dict['AMP_ON']:
if any(1 < element < (self.min_pulse_length + 1) for element in difference) == False:
pass
else:
assert(1 == 2), 'There are two pulses with shorter than ' + str(self.min_pulse_length*2) + ' ns distance between them'
else:
if any(1 < element < (self.min_pulse_length + 1) for element in difference) == False:
return np_array
else:
final_array = self.joining_pulses(np_array)
return final_array
def joining_pulses(self, np_array):
"""
A function that joing two short pulses in one
It is used for LNA_PROTECT and AMP_ON pulses
"""
i = 0
j = 0
counter = 0
array_len = len(np_array)
# drop several first and last zeros
index_first_one = np.argwhere(np_array == 1)[0]
index_last_one = np.argwhere(np_array == 1)[-1]
short_array = np_array[index_first_one[0]:(index_last_one[0] + 1)]
while i < len(short_array):
if short_array[i] == 0:
# looking for several 0 in a row
if short_array[i + 1] == 0:
counter += 1
elif short_array[i + 1] == 1:
# (minimal_distance + 1) is 13 now
if counter < (self.min_pulse_length + 1):
# replace 0 with 1
while j <= counter:
short_array[i + j - counter] = 1
j += 1
counter = 0
j = 0
else:
counter = 0
i += 1
final_array = np.concatenate( (np.zeros(index_first_one[0], dtype = np.int64), short_array, \
np.zeros( array_len - index_last_one[0] - 1, dtype = np.int64)), axis = None)
return final_array
def change_pulse_settings(self, parameter, delay):
"""
A special function for parsing some parameter (i.e. start, length) value from the pulse
and changing them according to specified delay
It is used in phase cycling
"""
if self.test_flag != 'test':
temp = parameter.split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
par_st = int(int((temp[0]))*flag + delay)
new_parameter = str( par_st ) + ' ns'
return new_parameter
elif self.test_flag == 'test':
temp = parameter.split(' ')
if temp[1] in self.timebase_dict:
flag = self.timebase_dict[temp[1]]
par_st = int(int((temp[0]))*flag + delay)
new_parameter = str( par_st ) + ' ns'
else:
assert(1 == 2), 'Incorrect time dimension (ns, us, ms, s)'
return new_parameter
def main():
pass
if __name__ == "__main__":
main()
| 51.497317
| 202
| 0.520158
| 18,421
| 153,565
| 4.127192
| 0.040823
| 0.022374
| 0.022058
| 0.025451
| 0.840359
| 0.82084
| 0.804425
| 0.790456
| 0.778881
| 0.770082
| 0
| 0.031861
| 0.383173
| 153,565
| 2,981
| 203
| 51.514592
| 0.770763
| 0.211129
| 0
| 0.882419
| 0
| 0
| 0.046344
| 0.000388
| 0
| 0
| 0
| 0
| 0.031091
| 1
| 0.023742
| false
| 0.035613
| 0.006218
| 0
| 0.062182
| 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
|
d7b5347845b5d9532ae91da7e555480d2ed938a0
| 3,457
|
py
|
Python
|
tests/test_write_txt.py
|
hendrikdutoit/TxtWrpr
|
7800254ca76d17b97c77702fcf185fe93ea8bcd6
|
[
"MIT"
] | null | null | null |
tests/test_write_txt.py
|
hendrikdutoit/TxtWrpr
|
7800254ca76d17b97c77702fcf185fe93ea8bcd6
|
[
"MIT"
] | null | null | null |
tests/test_write_txt.py
|
hendrikdutoit/TxtWrpr
|
7800254ca76d17b97c77702fcf185fe93ea8bcd6
|
[
"MIT"
] | null | null | null |
'''Testing write_txt()'''
from pathlib import Path
import tempfile
import beetools
from txtwrpr import TxtWrpr
from conftest import EXP_DATA_01, EXP_DATA_02, EXP_FIELD_DEF_01, EXP_FIELD_DEF_02, PARSED_DATA_01, PARSED_DATA_02, SRC_DATA_01, SRC_DATA_02, SRC_FIELD_DEF_01, SRC_FIELD_DEF_02
_path = Path(__file__)
_name = _path.stem
_VERSION = '0.0.1'
b_tls = beetools.Archiver( _name, _VERSION, __doc__, Path( _path))
def test_write_txt_simple():
'''Testing write_txt_simple()'''
t_wrpr = TxtWrpr(
_name,
0,
SRC_FIELD_DEF_01,
p_src = SRC_DATA_01,
p_has_header = True,
p_verbose = True
)
exp_pth = Path(tempfile.TemporaryDirectory().name) / 'Export.txt'
exp_pth.parent.mkdir()
t_wrpr.write_txt(exp_pth, EXP_FIELD_DEF_01)
assert t_wrpr.exp_data == EXP_DATA_01
assert t_wrpr.exp_pth == exp_pth
assert t_wrpr.exp_field_def == EXP_FIELD_DEF_01
assert t_wrpr.has_header
assert t_wrpr.key_idx == 0
assert t_wrpr.member_cntr == 10
assert t_wrpr.src_data == SRC_DATA_01
assert t_wrpr.src_field_def == SRC_FIELD_DEF_01
assert isinstance(t_wrpr.src_pth, type(list))
assert t_wrpr.parsed_data == PARSED_DATA_01
assert t_wrpr.success
assert t_wrpr.verbose
t_wrpr = TxtWrpr(
_name,
0,
SRC_FIELD_DEF_01,
p_src = exp_pth,
p_has_header = True,
p_verbose = True
)
assert not t_wrpr.exp_data
assert not t_wrpr.exp_pth
assert not t_wrpr.exp_field_def
assert t_wrpr.has_header
assert t_wrpr.key_idx == 0
assert t_wrpr.member_cntr == 10
assert t_wrpr.src_data == SRC_DATA_01
assert t_wrpr.src_field_def == SRC_FIELD_DEF_01
assert isinstance(t_wrpr.src_pth, Path)
assert t_wrpr.parsed_data == PARSED_DATA_01
assert t_wrpr.success
assert t_wrpr.verbose
beetools.rm_tree(exp_pth.parent)
def test_write_txt_add_fixed_field():
'''Testing write_txt_add_fixed_field()'''
t_wrpr = TxtWrpr(
_name,
0,
SRC_FIELD_DEF_01,
p_src = SRC_DATA_01,
p_has_header = True,
p_verbose = True
)
exp_pth = Path(tempfile.TemporaryDirectory().name) / 'Export.txt'
exp_pth.parent.mkdir()
t_wrpr.write_txt(exp_pth, EXP_FIELD_DEF_02)
assert t_wrpr.exp_data == EXP_DATA_02
assert t_wrpr.exp_pth == exp_pth
assert t_wrpr.exp_field_def == EXP_FIELD_DEF_02
assert t_wrpr.has_header
assert t_wrpr.key_idx == 0
assert t_wrpr.member_cntr == 10
assert t_wrpr.src_data == SRC_DATA_01
assert t_wrpr.src_field_def == SRC_FIELD_DEF_01
assert isinstance(t_wrpr.src_pth, type(list))
assert t_wrpr.parsed_data == PARSED_DATA_01
assert t_wrpr.success
assert t_wrpr.verbose
t_wrpr = TxtWrpr(
_name,
0,
SRC_FIELD_DEF_02,
p_src = exp_pth,
p_has_header = True,
p_verbose = True
)
assert not t_wrpr.exp_data
assert not t_wrpr.exp_pth
assert not t_wrpr.exp_field_def
assert t_wrpr.has_header
assert t_wrpr.key_idx == 0
assert t_wrpr.member_cntr == 10
assert t_wrpr.src_data == SRC_DATA_02
assert t_wrpr.src_field_def == SRC_FIELD_DEF_02
assert isinstance(t_wrpr.src_pth, Path)
assert t_wrpr.parsed_data == PARSED_DATA_02
assert t_wrpr.success
assert t_wrpr.verbose
beetools.rm_tree(exp_pth.parent)
test_write_txt_simple()
test_write_txt_add_fixed_field()
del b_tls
| 29.05042
| 175
| 0.701186
| 566
| 3,457
| 3.819788
| 0.10424
| 0.124884
| 0.19334
| 0.054117
| 0.826549
| 0.813136
| 0.790009
| 0.763182
| 0.763182
| 0.747919
| 0
| 0.032318
| 0.22129
| 3,457
| 118
| 176
| 29.29661
| 0.770802
| 0.02372
| 0
| 0.72549
| 0
| 0
| 0.007445
| 0
| 0
| 0
| 0
| 0
| 0.470588
| 1
| 0.019608
| false
| 0
| 0.04902
| 0
| 0.068627
| 0
| 0
| 0
| 0
| null | 0
| 1
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
0bf8307a88992241a4e63ca2004247621e5d9e08
| 109,073
|
py
|
Python
|
tb_rest_client/api/api_ce/telemetry_controller_api.py
|
samson0v/python_tb_rest_client
|
08ff7898740f7cec2170e85d5c3c89e222e967f7
|
[
"Apache-2.0"
] | 30
|
2020-06-19T06:42:50.000Z
|
2021-08-23T21:16:36.000Z
|
tb_rest_client/api/api_ce/telemetry_controller_api.py
|
samson0v/python_tb_rest_client
|
08ff7898740f7cec2170e85d5c3c89e222e967f7
|
[
"Apache-2.0"
] | 25
|
2021-08-30T01:17:27.000Z
|
2022-03-16T14:10:14.000Z
|
tb_rest_client/api/api_ce/telemetry_controller_api.py
|
samson0v/python_tb_rest_client
|
08ff7898740f7cec2170e85d5c3c89e222e967f7
|
[
"Apache-2.0"
] | 23
|
2020-07-06T13:41:54.000Z
|
2021-08-23T21:04:50.000Z
|
# coding: utf-8
"""
ThingsBoard REST API
ThingsBoard open-source IoT platform REST API documentation. # noqa: E501
OpenAPI spec version: 3.3.3-SNAPSHOT
Contact: info@thingsboard.io
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 tb_rest_client.api_client import ApiClient
class TelemetryControllerApi(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 delete_device_attributes_using_delete(self, device_id, scope, keys, **kwargs): # noqa: E501
"""Delete device attributes (deleteDeviceAttributes) # noqa: E501
Delete device attributes using provided Device Id, scope and a list of keys. Referencing a non-existing Device Id will cause an error Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_device_attributes_using_delete(device_id, scope, keys, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str device_id: A string value representing the device id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'. (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_device_attributes_using_delete_with_http_info(device_id, scope, keys, **kwargs) # noqa: E501
else:
(data) = self.delete_device_attributes_using_delete_with_http_info(device_id, scope, keys, **kwargs) # noqa: E501
return data
def delete_device_attributes_using_delete_with_http_info(self, device_id, scope, keys, **kwargs): # noqa: E501
"""Delete device attributes (deleteDeviceAttributes) # noqa: E501
Delete device attributes using provided Device Id, scope and a list of keys. Referencing a non-existing Device Id will cause an error Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_device_attributes_using_delete_with_http_info(device_id, scope, keys, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str device_id: A string value representing the device id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'. (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['device_id', 'scope', 'keys'] # 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_device_attributes_using_delete" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'device_id' is set
if ('device_id' not in params or
params['device_id'] is None):
raise ValueError("Missing the required parameter `device_id` when calling `delete_device_attributes_using_delete`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `delete_device_attributes_using_delete`") # noqa: E501
# verify the required parameter 'keys' is set
if ('keys' not in params or
params['keys'] is None):
raise ValueError("Missing the required parameter `keys` when calling `delete_device_attributes_using_delete`") # noqa: E501
collection_formats = {}
path_params = {}
if 'device_id' in params:
path_params['deviceId'] = params['device_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # noqa: E501
query_params = []
if 'keys' in params:
query_params.append(('keys', params['keys'])) # 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 = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{deviceId}/{scope}{?keys}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_entity_attributes_using_delete(self, entity_type, entity_id, scope, keys, **kwargs): # noqa: E501
"""Delete entity attributes (deleteEntityAttributes) # noqa: E501
Delete entity attributes using provided Entity Id, scope and a list of keys. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_entity_attributes_using_delete(entity_type, entity_id, scope, keys, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'. (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_entity_attributes_using_delete_with_http_info(entity_type, entity_id, scope, keys, **kwargs) # noqa: E501
else:
(data) = self.delete_entity_attributes_using_delete_with_http_info(entity_type, entity_id, scope, keys, **kwargs) # noqa: E501
return data
def delete_entity_attributes_using_delete_with_http_info(self, entity_type, entity_id, scope, keys, **kwargs): # noqa: E501
"""Delete entity attributes (deleteEntityAttributes) # noqa: E501
Delete entity attributes using provided Entity Id, scope and a list of keys. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_entity_attributes_using_delete_with_http_info(entity_type, entity_id, scope, keys, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'. (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'scope', 'keys'] # 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_entity_attributes_using_delete" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `delete_entity_attributes_using_delete`") # noqa: E501
# 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 `delete_entity_attributes_using_delete`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `delete_entity_attributes_using_delete`") # noqa: E501
# verify the required parameter 'keys' is set
if ('keys' not in params or
params['keys'] is None):
raise ValueError("Missing the required parameter `keys` when calling `delete_entity_attributes_using_delete`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # noqa: E501
query_params = []
if 'keys' in params:
query_params.append(('keys', params['keys'])) # 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 = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/{scope}{?keys}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_entity_timeseries_using_delete(self, entity_type, entity_id, keys, **kwargs): # noqa: E501
"""Delete entity time-series data (deleteEntityTimeseries) # noqa: E501
Delete time-series for selected entity based on entity id, entity type and keys. Use 'deleteAllDataForKeys' to delete all time-series data. Use 'startTs' and 'endTs' to specify time-range instead. Use 'rewriteLatestIfDeleted' to rewrite latest value (stored in separate table for performance) after deletion of the time range. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_entity_timeseries_using_delete(entity_type, entity_id, keys, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of telemetry keys. If keys are not selected, the result will return all latest timeseries. For example, 'temperature,humidity'. (required)
:param bool delete_all_data_for_keys: A boolean value to specify if should be deleted all data for selected keys or only data that are in the selected time range.
:param int start_ts: A long value representing the start timestamp of removal time range in milliseconds.
:param int end_ts: A long value representing the end timestamp of removal time range in milliseconds.
:param bool rewrite_latest_if_deleted: If the parameter is set to true, the latest telemetry will be rewritten in case that current latest value was removed, otherwise, in case that parameter is set to false the new latest value will not set.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_entity_timeseries_using_delete_with_http_info(entity_type, entity_id, keys, **kwargs) # noqa: E501
else:
(data) = self.delete_entity_timeseries_using_delete_with_http_info(entity_type, entity_id, keys, **kwargs) # noqa: E501
return data
def delete_entity_timeseries_using_delete_with_http_info(self, entity_type, entity_id, keys, **kwargs): # noqa: E501
"""Delete entity time-series data (deleteEntityTimeseries) # noqa: E501
Delete time-series for selected entity based on entity id, entity type and keys. Use 'deleteAllDataForKeys' to delete all time-series data. Use 'startTs' and 'endTs' to specify time-range instead. Use 'rewriteLatestIfDeleted' to rewrite latest value (stored in separate table for performance) after deletion of the time range. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_entity_timeseries_using_delete_with_http_info(entity_type, entity_id, keys, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of telemetry keys. If keys are not selected, the result will return all latest timeseries. For example, 'temperature,humidity'. (required)
:param bool delete_all_data_for_keys: A boolean value to specify if should be deleted all data for selected keys or only data that are in the selected time range.
:param int start_ts: A long value representing the start timestamp of removal time range in milliseconds.
:param int end_ts: A long value representing the end timestamp of removal time range in milliseconds.
:param bool rewrite_latest_if_deleted: If the parameter is set to true, the latest telemetry will be rewritten in case that current latest value was removed, otherwise, in case that parameter is set to false the new latest value will not set.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'keys', 'delete_all_data_for_keys', 'start_ts', 'end_ts', 'rewrite_latest_if_deleted'] # 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_entity_timeseries_using_delete" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `delete_entity_timeseries_using_delete`") # noqa: E501
# 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 `delete_entity_timeseries_using_delete`") # noqa: E501
# verify the required parameter 'keys' is set
if ('keys' not in params or
params['keys'] is None):
raise ValueError("Missing the required parameter `keys` when calling `delete_entity_timeseries_using_delete`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
query_params = []
if 'keys' in params:
query_params.append(('keys', params['keys'])) # noqa: E501
if 'delete_all_data_for_keys' in params:
query_params.append(('deleteAllDataForKeys', params['delete_all_data_for_keys'])) # noqa: E501
if 'start_ts' in params:
query_params.append(('startTs', params['start_ts'])) # noqa: E501
if 'end_ts' in params:
query_params.append(('endTs', params['end_ts'])) # noqa: E501
if 'rewrite_latest_if_deleted' in params:
query_params.append(('rewriteLatestIfDeleted', params['rewrite_latest_if_deleted'])) # 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 = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/timeseries/delete{?deleteAllDataForKeys,endTs,keys,rewriteLatestIfDeleted,startTs}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_attribute_keys_by_scope_using_get(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Get all attribute keys by scope (getAttributeKeysByScope) # noqa: E501
Returns a set of unique attribute key names for the selected entity and attributes scope: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attribute_keys_by_scope_using_get(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_attribute_keys_by_scope_using_get_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
else:
(data) = self.get_attribute_keys_by_scope_using_get_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
return data
def get_attribute_keys_by_scope_using_get_with_http_info(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Get all attribute keys by scope (getAttributeKeysByScope) # noqa: E501
Returns a set of unique attribute key names for the selected entity and attributes scope: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attribute_keys_by_scope_using_get_with_http_info(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'scope'] # 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_attribute_keys_by_scope_using_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `get_attribute_keys_by_scope_using_get`") # noqa: E501
# 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_attribute_keys_by_scope_using_get`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `get_attribute_keys_by_scope_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/keys/attributes/{scope}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_attribute_keys_using_get(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get all attribute keys (getAttributeKeys) # noqa: E501
Returns a set of unique attribute key names for the selected entity. The response will include merged key names set for all attribute scopes: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attribute_keys_using_get(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_attribute_keys_using_get_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
else:
(data) = self.get_attribute_keys_using_get_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
return data
def get_attribute_keys_using_get_with_http_info(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get all attribute keys (getAttributeKeys) # noqa: E501
Returns a set of unique attribute key names for the selected entity. The response will include merged key names set for all attribute scopes: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attribute_keys_using_get_with_http_info(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_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 get_attribute_keys_using_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `get_attribute_keys_using_get`") # noqa: E501
# 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_attribute_keys_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/keys/attributes', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_attributes_by_scope_using_get(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Get attributes by scope (getAttributesByScope) # noqa: E501
Returns all attributes of a specified scope that belong to specified entity. List of possible attribute scopes depends on the entity type: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. Use optional 'keys' parameter to return specific attributes. Example of the result: ```json [ {\"key\": \"stringAttributeKey\", \"value\": \"value\", \"lastUpdateTs\": 1609459200000}, {\"key\": \"booleanAttributeKey\", \"value\": false, \"lastUpdateTs\": 1609459200001}, {\"key\": \"doubleAttributeKey\", \"value\": 42.2, \"lastUpdateTs\": 1609459200002}, {\"key\": \"longKeyExample\", \"value\": 73, \"lastUpdateTs\": 1609459200003}, {\"key\": \"jsonKeyExample\", \"value\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} }, \"lastUpdateTs\": 1609459200004 } ] ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attributes_by_scope_using_get(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_attributes_by_scope_using_get_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
else:
(data) = self.get_attributes_by_scope_using_get_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
return data
def get_attributes_by_scope_using_get_with_http_info(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Get attributes by scope (getAttributesByScope) # noqa: E501
Returns all attributes of a specified scope that belong to specified entity. List of possible attribute scopes depends on the entity type: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. Use optional 'keys' parameter to return specific attributes. Example of the result: ```json [ {\"key\": \"stringAttributeKey\", \"value\": \"value\", \"lastUpdateTs\": 1609459200000}, {\"key\": \"booleanAttributeKey\", \"value\": false, \"lastUpdateTs\": 1609459200001}, {\"key\": \"doubleAttributeKey\", \"value\": 42.2, \"lastUpdateTs\": 1609459200002}, {\"key\": \"longKeyExample\", \"value\": 73, \"lastUpdateTs\": 1609459200003}, {\"key\": \"jsonKeyExample\", \"value\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} }, \"lastUpdateTs\": 1609459200004 } ] ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attributes_by_scope_using_get_with_http_info(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'scope', 'keys'] # 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_attributes_by_scope_using_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `get_attributes_by_scope_using_get`") # noqa: E501
# 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_attributes_by_scope_using_get`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `get_attributes_by_scope_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # noqa: E501
query_params = []
if 'keys' in params:
query_params.append(('keys', params['keys'])) # 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 = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/values/attributes/{scope}{?keys}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_attributes_using_get(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get attributes (getAttributes) # noqa: E501
Returns all attributes that belong to specified entity. Use optional 'keys' parameter to return specific attributes. Example of the result: ```json [ {\"key\": \"stringAttributeKey\", \"value\": \"value\", \"lastUpdateTs\": 1609459200000}, {\"key\": \"booleanAttributeKey\", \"value\": false, \"lastUpdateTs\": 1609459200001}, {\"key\": \"doubleAttributeKey\", \"value\": 42.2, \"lastUpdateTs\": 1609459200002}, {\"key\": \"longKeyExample\", \"value\": 73, \"lastUpdateTs\": 1609459200003}, {\"key\": \"jsonKeyExample\", \"value\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} }, \"lastUpdateTs\": 1609459200004 } ] ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attributes_using_get(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_attributes_using_get_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
else:
(data) = self.get_attributes_using_get_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
return data
def get_attributes_using_get_with_http_info(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get attributes (getAttributes) # noqa: E501
Returns all attributes that belong to specified entity. Use optional 'keys' parameter to return specific attributes. Example of the result: ```json [ {\"key\": \"stringAttributeKey\", \"value\": \"value\", \"lastUpdateTs\": 1609459200000}, {\"key\": \"booleanAttributeKey\", \"value\": false, \"lastUpdateTs\": 1609459200001}, {\"key\": \"doubleAttributeKey\", \"value\": 42.2, \"lastUpdateTs\": 1609459200002}, {\"key\": \"longKeyExample\", \"value\": 73, \"lastUpdateTs\": 1609459200003}, {\"key\": \"jsonKeyExample\", \"value\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} }, \"lastUpdateTs\": 1609459200004 } ] ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_attributes_using_get_with_http_info(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of attributes keys. For example, 'active,inactivityAlarmTime'.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'keys'] # 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_attributes_using_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `get_attributes_using_get`") # noqa: E501
# 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_attributes_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
query_params = []
if 'keys' in params:
query_params.append(('keys', params['keys'])) # 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 = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/values/attributes{?keys}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_latest_timeseries_using_get(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get latest time-series value (getLatestTimeseries) # noqa: E501
Returns all time-series that belong to specified entity. Use optional 'keys' parameter to return specific time-series. The result is a JSON object. The format of the values depends on the 'useStrictDataTypes' parameter. By default, all time-series values are converted to strings: ```json { \"stringTsKey\": [{ \"value\": \"value\", \"ts\": 1609459200000}], \"booleanTsKey\": [{ \"value\": \"false\", \"ts\": 1609459200000}], \"doubleTsKey\": [{ \"value\": \"42.2\", \"ts\": 1609459200000}], \"longTsKey\": [{ \"value\": \"73\", \"ts\": 1609459200000}], \"jsonTsKey\": [{ \"value\": \"{\\\"someNumber\\\": 42,\\\"someArray\\\": [1,2,3],\\\"someNestedObject\\\": {\\\"key\\\": \\\"value\\\"}}\", \"ts\": 1609459200000}] } ``` However, it is possible to request the values without conversion ('useStrictDataTypes'=true): ```json { \"stringTsKey\": [{ \"value\": \"value\", \"ts\": 1609459200000}], \"booleanTsKey\": [{ \"value\": false, \"ts\": 1609459200000}], \"doubleTsKey\": [{ \"value\": 42.2, \"ts\": 1609459200000}], \"longTsKey\": [{ \"value\": 73, \"ts\": 1609459200000}], \"jsonTsKey\": [{ \"value\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} }, \"ts\": 1609459200000}] } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_latest_timeseries_using_get(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of telemetry keys. If keys are not selected, the result will return all latest timeseries. For example, 'temperature,humidity'.
:param bool use_strict_data_types: Enables/disables conversion of telemetry values to strings. Conversion is enabled by default. Set parameter to 'true' in order to disable the conversion.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_latest_timeseries_using_get_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
else:
(data) = self.get_latest_timeseries_using_get_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
return data
def get_latest_timeseries_using_get_with_http_info(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get latest time-series value (getLatestTimeseries) # noqa: E501
Returns all time-series that belong to specified entity. Use optional 'keys' parameter to return specific time-series. The result is a JSON object. The format of the values depends on the 'useStrictDataTypes' parameter. By default, all time-series values are converted to strings: ```json { \"stringTsKey\": [{ \"value\": \"value\", \"ts\": 1609459200000}], \"booleanTsKey\": [{ \"value\": \"false\", \"ts\": 1609459200000}], \"doubleTsKey\": [{ \"value\": \"42.2\", \"ts\": 1609459200000}], \"longTsKey\": [{ \"value\": \"73\", \"ts\": 1609459200000}], \"jsonTsKey\": [{ \"value\": \"{\\\"someNumber\\\": 42,\\\"someArray\\\": [1,2,3],\\\"someNestedObject\\\": {\\\"key\\\": \\\"value\\\"}}\", \"ts\": 1609459200000}] } ``` However, it is possible to request the values without conversion ('useStrictDataTypes'=true): ```json { \"stringTsKey\": [{ \"value\": \"value\", \"ts\": 1609459200000}], \"booleanTsKey\": [{ \"value\": false, \"ts\": 1609459200000}], \"doubleTsKey\": [{ \"value\": 42.2, \"ts\": 1609459200000}], \"longTsKey\": [{ \"value\": 73, \"ts\": 1609459200000}], \"jsonTsKey\": [{ \"value\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} }, \"ts\": 1609459200000}] } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_latest_timeseries_using_get_with_http_info(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of telemetry keys. If keys are not selected, the result will return all latest timeseries. For example, 'temperature,humidity'.
:param bool use_strict_data_types: Enables/disables conversion of telemetry values to strings. Conversion is enabled by default. Set parameter to 'true' in order to disable the conversion.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'keys', 'use_strict_data_types'] # 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_latest_timeseries_using_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `get_latest_timeseries_using_get`") # noqa: E501
# 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_latest_timeseries_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
query_params = []
if 'keys' in params:
query_params.append(('keys', params['keys'])) # noqa: E501
if 'use_strict_data_types' in params:
query_params.append(('useStrictDataTypes', params['use_strict_data_types'])) # 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 = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/values/timeseries{?keys,useStrictDataTypes}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_timeseries_keys_using_get1(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get time-series keys (getTimeseriesKeys) # noqa: E501
Returns a set of unique time-series key names for the selected entity. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_timeseries_keys_using_get1(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_timeseries_keys_using_get1_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
else:
(data) = self.get_timeseries_keys_using_get1_with_http_info(entity_type, entity_id, **kwargs) # noqa: E501
return data
def get_timeseries_keys_using_get1_with_http_info(self, entity_type, entity_id, **kwargs): # noqa: E501
"""Get time-series keys (getTimeseriesKeys) # noqa: E501
Returns a set of unique time-series key names for the selected entity. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_timeseries_keys_using_get1_with_http_info(entity_type, entity_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_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 get_timeseries_keys_using_get1" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `get_timeseries_keys_using_get1`") # noqa: E501
# 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_timeseries_keys_using_get1`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/keys/timeseries', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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_timeseries_using_get(self, entity_type, entity_id, keys, start_ts, end_ts, **kwargs): # noqa: E501
"""Get time-series data (getTimeseries) # noqa: E501
Returns a range of time-series values for specified entity. Returns not aggregated data by default. Use aggregation function ('agg') and aggregation interval ('interval') to enable aggregation of the results on the database / server side. The aggregation is generally more efficient then fetching all records. ```json { \"temperature\": [ { \"value\": 36.7, \"ts\": 1609459200000 }, { \"value\": 36.6, \"ts\": 1609459201000 } ] } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_timeseries_using_get(entity_type, entity_id, keys, start_ts, end_ts, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of telemetry keys. (required)
:param int start_ts: A long value representing the start timestamp of the time range in milliseconds, UTC. (required)
:param int end_ts: A long value representing the end timestamp of the time range in milliseconds, UTC. (required)
:param int interval: A long value representing the aggregation interval range in milliseconds.
:param int limit: An integer value that represents a max number of timeseries data points to fetch. This parameter is used only in the case if 'agg' parameter is set to 'NONE'.
:param str agg: A string value representing the aggregation function. If the interval is not specified, 'agg' parameter will use 'NONE' value.
:param str order_by: Sort order. ASC (ASCENDING) or DESC (DESCENDING)
:param bool use_strict_data_types: Enables/disables conversion of telemetry values to strings. Conversion is enabled by default. Set parameter to 'true' in order to disable the conversion.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_timeseries_using_get_with_http_info(entity_type, entity_id, keys, start_ts, end_ts, **kwargs) # noqa: E501
else:
(data) = self.get_timeseries_using_get_with_http_info(entity_type, entity_id, keys, start_ts, end_ts, **kwargs) # noqa: E501
return data
def get_timeseries_using_get_with_http_info(self, entity_type, entity_id, keys, start_ts, end_ts, **kwargs): # noqa: E501
"""Get time-series data (getTimeseries) # noqa: E501
Returns a range of time-series values for specified entity. Returns not aggregated data by default. Use aggregation function ('agg') and aggregation interval ('interval') to enable aggregation of the results on the database / server side. The aggregation is generally more efficient then fetching all records. ```json { \"temperature\": [ { \"value\": 36.7, \"ts\": 1609459200000 }, { \"value\": 36.6, \"ts\": 1609459201000 } ] } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # 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_timeseries_using_get_with_http_info(entity_type, entity_id, keys, start_ts, end_ts, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str keys: A string value representing the comma-separated list of telemetry keys. (required)
:param int start_ts: A long value representing the start timestamp of the time range in milliseconds, UTC. (required)
:param int end_ts: A long value representing the end timestamp of the time range in milliseconds, UTC. (required)
:param int interval: A long value representing the aggregation interval range in milliseconds.
:param int limit: An integer value that represents a max number of timeseries data points to fetch. This parameter is used only in the case if 'agg' parameter is set to 'NONE'.
:param str agg: A string value representing the aggregation function. If the interval is not specified, 'agg' parameter will use 'NONE' value.
:param str order_by: Sort order. ASC (ASCENDING) or DESC (DESCENDING)
:param bool use_strict_data_types: Enables/disables conversion of telemetry values to strings. Conversion is enabled by default. Set parameter to 'true' in order to disable the conversion.
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'keys', 'start_ts', 'end_ts', 'interval', 'limit', 'agg', 'order_by', 'use_strict_data_types'] # 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_timeseries_using_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `get_timeseries_using_get`") # noqa: E501
# 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_timeseries_using_get`") # noqa: E501
# verify the required parameter 'keys' is set
if ('keys' not in params or
params['keys'] is None):
raise ValueError("Missing the required parameter `keys` when calling `get_timeseries_using_get`") # noqa: E501
# verify the required parameter 'start_ts' is set
if ('start_ts' not in params or
params['start_ts'] is None):
raise ValueError("Missing the required parameter `start_ts` when calling `get_timeseries_using_get`") # noqa: E501
# verify the required parameter 'end_ts' is set
if ('end_ts' not in params or
params['end_ts'] is None):
raise ValueError("Missing the required parameter `end_ts` when calling `get_timeseries_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
query_params = []
if 'keys' in params:
query_params.append(('keys', params['keys'])) # noqa: E501
if 'start_ts' in params:
query_params.append(('startTs', params['start_ts'])) # noqa: E501
if 'end_ts' in params:
query_params.append(('endTs', params['end_ts'])) # noqa: E501
if 'interval' in params:
query_params.append(('interval', params['interval'])) # noqa: E501
if 'limit' in params:
query_params.append(('limit', params['limit'])) # noqa: E501
if 'agg' in params:
query_params.append(('agg', params['agg'])) # noqa: E501
if 'order_by' in params:
query_params.append(('orderBy', params['order_by'])) # noqa: E501
if 'use_strict_data_types' in params:
query_params.append(('useStrictDataTypes', params['use_strict_data_types'])) # 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 = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/values/timeseries{?agg,endTs,interval,keys,limit,orderBy,startTs,useStrictDataTypes}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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 save_device_attributes_using_post(self, device_id, scope, **kwargs): # noqa: E501
"""Save device attributes (saveDeviceAttributes) # noqa: E501
Creates or updates the device attributes based on device id and specified attribute scope. The request payload is a JSON object with key-value format of attributes to create or update. For example: ```json { \"stringKey\":\"value1\", \"booleanKey\":true, \"doubleKey\":42.0, \"longKey\":73, \"jsonKey\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} } } ``` Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_device_attributes_using_post(device_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str device_id: A string value representing the device id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param JsonNode body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.save_device_attributes_using_post_with_http_info(device_id, scope, **kwargs) # noqa: E501
else:
(data) = self.save_device_attributes_using_post_with_http_info(device_id, scope, **kwargs) # noqa: E501
return data
def save_device_attributes_using_post_with_http_info(self, device_id, scope, **kwargs): # noqa: E501
"""Save device attributes (saveDeviceAttributes) # noqa: E501
Creates or updates the device attributes based on device id and specified attribute scope. The request payload is a JSON object with key-value format of attributes to create or update. For example: ```json { \"stringKey\":\"value1\", \"booleanKey\":true, \"doubleKey\":42.0, \"longKey\":73, \"jsonKey\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} } } ``` Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_device_attributes_using_post_with_http_info(device_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str device_id: A string value representing the device id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param JsonNode body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['device_id', 'scope', '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 save_device_attributes_using_post" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'device_id' is set
if ('device_id' not in params or
params['device_id'] is None):
raise ValueError("Missing the required parameter `device_id` when calling `save_device_attributes_using_post`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `save_device_attributes_using_post`") # noqa: E501
collection_formats = {}
path_params = {}
if 'device_id' in params:
path_params['deviceId'] = params['device_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # 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/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{deviceId}/{scope}', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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 save_entity_attributes_v1_using_post(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Save entity attributes (saveEntityAttributesV1) # noqa: E501
Creates or updates the entity attributes based on Entity Id and the specified attribute scope. List of possible attribute scopes depends on the entity type: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. The request payload is a JSON object with key-value format of attributes to create or update. For example: ```json { \"stringKey\":\"value1\", \"booleanKey\":true, \"doubleKey\":42.0, \"longKey\":73, \"jsonKey\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} } } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_attributes_v1_using_post(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param JsonNode body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.save_entity_attributes_v1_using_post_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
else:
(data) = self.save_entity_attributes_v1_using_post_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
return data
def save_entity_attributes_v1_using_post_with_http_info(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Save entity attributes (saveEntityAttributesV1) # noqa: E501
Creates or updates the entity attributes based on Entity Id and the specified attribute scope. List of possible attribute scopes depends on the entity type: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. The request payload is a JSON object with key-value format of attributes to create or update. For example: ```json { \"stringKey\":\"value1\", \"booleanKey\":true, \"doubleKey\":42.0, \"longKey\":73, \"jsonKey\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} } } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_attributes_v1_using_post_with_http_info(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param JsonNode body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'scope', '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 save_entity_attributes_v1_using_post" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `save_entity_attributes_v1_using_post`") # noqa: E501
# 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 `save_entity_attributes_v1_using_post`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `save_entity_attributes_v1_using_post`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # 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/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/{scope}', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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 save_entity_attributes_v2_using_post(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Save entity attributes (saveEntityAttributesV2) # noqa: E501
Creates or updates the entity attributes based on Entity Id and the specified attribute scope. List of possible attribute scopes depends on the entity type: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. The request payload is a JSON object with key-value format of attributes to create or update. For example: ```json { \"stringKey\":\"value1\", \"booleanKey\":true, \"doubleKey\":42.0, \"longKey\":73, \"jsonKey\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} } } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_attributes_v2_using_post(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param JsonNode body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.save_entity_attributes_v2_using_post_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
else:
(data) = self.save_entity_attributes_v2_using_post_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
return data
def save_entity_attributes_v2_using_post_with_http_info(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Save entity attributes (saveEntityAttributesV2) # noqa: E501
Creates or updates the entity attributes based on Entity Id and the specified attribute scope. List of possible attribute scopes depends on the entity type: * SERVER_SCOPE - supported for all entity types; * CLIENT_SCOPE - supported for devices; * SHARED_SCOPE - supported for devices. The request payload is a JSON object with key-value format of attributes to create or update. For example: ```json { \"stringKey\":\"value1\", \"booleanKey\":true, \"doubleKey\":42.0, \"longKey\":73, \"jsonKey\": { \"someNumber\": 42, \"someArray\": [1,2,3], \"someNestedObject\": {\"key\": \"value\"} } } ``` Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_attributes_v2_using_post_with_http_info(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: A string value representing the attributes scope. For example, 'SERVER_SCOPE'. (required)
:param JsonNode body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'scope', '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 save_entity_attributes_v2_using_post" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `save_entity_attributes_v2_using_post`") # noqa: E501
# 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 `save_entity_attributes_v2_using_post`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `save_entity_attributes_v2_using_post`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # 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/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/attributes/{scope}', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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 save_entity_telemetry_using_post(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Save or update time-series data (saveEntityTelemetry) # noqa: E501
Creates or updates the entity time-series data based on the Entity Id and request payload.The request payload is a JSON document with three possible formats: Simple format without timestamp. In such a case, current server time will be used: ```json {\"temperature\": 26} ``` Single JSON object with timestamp: ```json {\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}} ``` JSON array with timestamps: ```json [{\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}}, {\"ts\":1634712588000,\"values\":{\"temperature\":25, \"humidity\":88}}] ``` The scope parameter is not used in the API call implementation but should be specified whatever value because it is used as a path variable. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_telemetry_using_post(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: Value is deprecated, reserved for backward compatibility and not used in the API call implementation. Specify any scope for compatibility (required)
:param str body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.save_entity_telemetry_using_post_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
else:
(data) = self.save_entity_telemetry_using_post_with_http_info(entity_type, entity_id, scope, **kwargs) # noqa: E501
return data
def save_entity_telemetry_using_post_with_http_info(self, entity_type, entity_id, scope, **kwargs): # noqa: E501
"""Save or update time-series data (saveEntityTelemetry) # noqa: E501
Creates or updates the entity time-series data based on the Entity Id and request payload.The request payload is a JSON document with three possible formats: Simple format without timestamp. In such a case, current server time will be used: ```json {\"temperature\": 26} ``` Single JSON object with timestamp: ```json {\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}} ``` JSON array with timestamps: ```json [{\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}}, {\"ts\":1634712588000,\"values\":{\"temperature\":25, \"humidity\":88}}] ``` The scope parameter is not used in the API call implementation but should be specified whatever value because it is used as a path variable. Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_telemetry_using_post_with_http_info(entity_type, entity_id, scope, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: Value is deprecated, reserved for backward compatibility and not used in the API call implementation. Specify any scope for compatibility (required)
:param str body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'scope', '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 save_entity_telemetry_using_post" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `save_entity_telemetry_using_post`") # noqa: E501
# 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 `save_entity_telemetry_using_post`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `save_entity_telemetry_using_post`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # 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/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/timeseries/{scope}?scope=ANY', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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 save_entity_telemetry_with_ttl_using_post(self, entity_type, entity_id, scope, ttl, **kwargs): # noqa: E501
"""Save or update time-series data with TTL (saveEntityTelemetryWithTTL) # noqa: E501
Creates or updates the entity time-series data based on the Entity Id and request payload.The request payload is a JSON document with three possible formats: Simple format without timestamp. In such a case, current server time will be used: ```json {\"temperature\": 26} ``` Single JSON object with timestamp: ```json {\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}} ``` JSON array with timestamps: ```json [{\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}}, {\"ts\":1634712588000,\"values\":{\"temperature\":25, \"humidity\":88}}] ``` The scope parameter is not used in the API call implementation but should be specified whatever value because it is used as a path variable. The ttl parameter takes affect only in case of Cassandra DB.Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_telemetry_with_ttl_using_post(entity_type, entity_id, scope, ttl, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: Value is deprecated, reserved for backward compatibility and not used in the API call implementation. Specify any scope for compatibility (required)
:param int ttl: A long value representing TTL (Time to Live) parameter. (required)
:param str body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.save_entity_telemetry_with_ttl_using_post_with_http_info(entity_type, entity_id, scope, ttl, **kwargs) # noqa: E501
else:
(data) = self.save_entity_telemetry_with_ttl_using_post_with_http_info(entity_type, entity_id, scope, ttl, **kwargs) # noqa: E501
return data
def save_entity_telemetry_with_ttl_using_post_with_http_info(self, entity_type, entity_id, scope, ttl, **kwargs): # noqa: E501
"""Save or update time-series data with TTL (saveEntityTelemetryWithTTL) # noqa: E501
Creates or updates the entity time-series data based on the Entity Id and request payload.The request payload is a JSON document with three possible formats: Simple format without timestamp. In such a case, current server time will be used: ```json {\"temperature\": 26} ``` Single JSON object with timestamp: ```json {\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}} ``` JSON array with timestamps: ```json [{\"ts\":1634712287000,\"values\":{\"temperature\":26, \"humidity\":87}}, {\"ts\":1634712588000,\"values\":{\"temperature\":25, \"humidity\":88}}] ``` The scope parameter is not used in the API call implementation but should be specified whatever value because it is used as a path variable. The ttl parameter takes affect only in case of Cassandra DB.Referencing a non-existing entity Id or invalid entity type will cause an error. Available for users with 'TENANT_ADMIN' or 'CUSTOMER_USER' authority. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.save_entity_telemetry_with_ttl_using_post_with_http_info(entity_type, entity_id, scope, ttl, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_type: A string value representing the entity type. For example, 'DEVICE' (required)
:param str entity_id: A string value representing the entity id. For example, '784f394c-42b6-435a-983c-b7beff2784f9' (required)
:param str scope: Value is deprecated, reserved for backward compatibility and not used in the API call implementation. Specify any scope for compatibility (required)
:param int ttl: A long value representing TTL (Time to Live) parameter. (required)
:param str body:
:return: DeferredResultResponseEntity
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_type', 'entity_id', 'scope', 'ttl', '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 save_entity_telemetry_with_ttl_using_post" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_type' is set
if ('entity_type' not in params or
params['entity_type'] is None):
raise ValueError("Missing the required parameter `entity_type` when calling `save_entity_telemetry_with_ttl_using_post`") # noqa: E501
# 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 `save_entity_telemetry_with_ttl_using_post`") # noqa: E501
# verify the required parameter 'scope' is set
if ('scope' not in params or
params['scope'] is None):
raise ValueError("Missing the required parameter `scope` when calling `save_entity_telemetry_with_ttl_using_post`") # noqa: E501
# verify the required parameter 'ttl' is set
if ('ttl' not in params or
params['ttl'] is None):
raise ValueError("Missing the required parameter `ttl` when calling `save_entity_telemetry_with_ttl_using_post`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_type' in params:
path_params['entityType'] = params['entity_type'] # noqa: E501
if 'entity_id' in params:
path_params['entityId'] = params['entity_id'] # noqa: E501
if 'scope' in params:
path_params['scope'] = params['scope'] # noqa: E501
if 'ttl' in params:
path_params['ttl'] = params['ttl'] # 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/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/plugins/telemetry/{entityType}/{entityId}/timeseries/{scope}/{ttl}?scope=ANY', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='DeferredResultResponseEntity', # 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)
| 61.173864
| 1,467
| 0.657651
| 13,268
| 109,073
| 5.207039
| 0.029243
| 0.033812
| 0.027791
| 0.023709
| 0.986466
| 0.982428
| 0.979215
| 0.977637
| 0.974149
| 0.969082
| 0
| 0.030223
| 0.244653
| 109,073
| 1,782
| 1,468
| 61.208193
| 0.808334
| 0.492377
| 0
| 0.810204
| 0
| 0.002041
| 0.251487
| 0.096041
| 0
| 0
| 0
| 0
| 0
| 1
| 0.031633
| false
| 0
| 0.004082
| 0
| 0.082653
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
0bff36b28cc339f330667d178b683253356145d2
| 120
|
py
|
Python
|
pgdrive/scene_creator/road/__init__.py
|
gamecraftCZ/pgdrive
|
11fbb5a5ca1dc354d755f00eb282bcffe5720bcc
|
[
"Apache-2.0"
] | null | null | null |
pgdrive/scene_creator/road/__init__.py
|
gamecraftCZ/pgdrive
|
11fbb5a5ca1dc354d755f00eb282bcffe5720bcc
|
[
"Apache-2.0"
] | null | null | null |
pgdrive/scene_creator/road/__init__.py
|
gamecraftCZ/pgdrive
|
11fbb5a5ca1dc354d755f00eb282bcffe5720bcc
|
[
"Apache-2.0"
] | null | null | null |
from pgdrive.scene_creator.road.road import Road, Route
from pgdrive.scene_creator.road.road_network import RoadNetwork
| 40
| 63
| 0.866667
| 18
| 120
| 5.611111
| 0.5
| 0.217822
| 0.316832
| 0.455446
| 0.613861
| 0.613861
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075
| 120
| 2
| 64
| 60
| 0.90991
| 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
|
040246c359c200cbc9810cd8cedda00b0deb2d9e
| 10,705
|
py
|
Python
|
SRC/Python/lib/rseqc.py
|
wenching/CRI-BIO-646-BMB-RKeenan
|
6dfda3f7f1d3f90b45609bcc656a372a87cc795d
|
[
"MIT"
] | null | null | null |
SRC/Python/lib/rseqc.py
|
wenching/CRI-BIO-646-BMB-RKeenan
|
6dfda3f7f1d3f90b45609bcc656a372a87cc795d
|
[
"MIT"
] | null | null | null |
SRC/Python/lib/rseqc.py
|
wenching/CRI-BIO-646-BMB-RKeenan
|
6dfda3f7f1d3f90b45609bcc656a372a87cc795d
|
[
"MIT"
] | null | null | null |
"""RSeQC"""
import os
import sys
import logging
import datetime
import util.ddictfunc
SELF_FILE_PATH = os.path.realpath(__file__)
SELF_DIR_PATH = os.path.dirname(SELF_FILE_PATH)
SELF_FILE = os.path.basename(SELF_FILE_PATH)
def clipping_profile(args, sw_cfg, task_cfg):
"""
RSeQC::clipping_profile
:parm args: an argparse.Namespace object of main argumens {.log_file}
:parm sw_cfg: a dictionary of corresponding software configureation {fastqc}
:parm task_cfg: a dictionary of corresponding task configureation {in_file_path_list, out_dir_path, shell_script_path, log_file_path}
:returns: returns corresponding code snippets, in which will be written to shell_script_path if provided
:raises keyError: NA
"""
# logging
if args.log_file is None:
log_file_path = '{}.{}.log'.format(
SELF_FILE_PATH,
datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S"))
else:
log_file_path = args.log_file
formatter = "%(asctime)-15s %(levelname)-8s %(message)s"
logging.basicConfig(
level=[logging.NOTSET, logging.DEBUG, logging.INFO,
logging.WARNING, logging.ERROR, logging.CRITICAL][1],
format=formatter,
filename=log_file_path)
logging.info("[ {} ] Make Shell Script\n".format(SELF_FILE))
sw_cfg_rseqc = sw_cfg['rseqc']
module = "clipping_profile.py"
task_cfg_module = task_cfg[module]
log_file_path_cmd = '' if 'log_file_path' not in task_cfg_module else '''&>> {}'''.format(task_cfg_module['log_file_path'])
task_cfg_reference = task_cfg['references'][next(iter(task_cfg['references']))]
shell_script_path = '' if 'shell_script_path' not in task_cfg_module else task_cfg_module['shell_script_path']
cmd_list = []
if sw_cfg_rseqc['module'] is not None:
cmd_list.append(sw_cfg_rseqc['module'])
cmd_list.append('''{} \\
--input-file={} \\
--out-prefix={} \\
--mapq={} \\
--sequencing="{}" \\
{}
\n'''.format(
module,
task_cfg_module['in_file_path_list'][0],
task_cfg_module['out_file_base'],
30,
task_cfg_module['sequencing_layout'],
log_file_path_cmd
))
if shell_script_path:
try:
with open(shell_script_path, "w") as outfile:
outfile.write(
'''\n{}\n'''.format(
'\n\n'.join(cmd_list)
)
)
outfile.write("\nexit 0\n")
outfile.close()
except IOError as exc:
print(exc)
logging.debug("[ {} ] Make Shell Script - DONE\n".format(SELF_FILE))
return cmd_list
def geneBody_coverage(args, sw_cfg, task_cfg):
"""
RSeQC::geneBody_coverage
:parm args: an argparse.Namespace object of main argumens {.log_file}
:parm sw_cfg: a dictionary of corresponding software configureation {fastqc}
:parm task_cfg: a dictionary of corresponding task configureation {in_file_path_list, out_dir_path, shell_script_path, log_file_path}
:returns: returns corresponding code snippets, in which will be written to shell_script_path if provided
:raises keyError: NA
"""
# logging
if args.log_file is None:
log_file_path = '{}.{}.log'.format(
SELF_FILE_PATH,
datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S"))
else:
log_file_path = args.log_file
formatter = "%(asctime)-15s %(levelname)-8s %(message)s"
logging.basicConfig(
level=[logging.NOTSET, logging.DEBUG, logging.INFO,
logging.WARNING, logging.ERROR, logging.CRITICAL][1],
format=formatter,
filename=log_file_path)
logging.info("[ {} ] Make Shell Script\n".format(SELF_FILE))
sw_cfg_rseqc = sw_cfg['rseqc']
module = "geneBody_coverage.py"
task_cfg_module = task_cfg[module]
log_file_path_cmd = '' if 'log_file_path' not in task_cfg_module else '''&>> {}'''.format(task_cfg_module['log_file_path'])
task_cfg_reference = task_cfg['references'][next(iter(task_cfg['references']))]
shell_script_path = '' if 'shell_script_path' not in task_cfg_module else task_cfg_module['shell_script_path']
cmd_list = []
if sw_cfg_rseqc['module'] is not None:
cmd_list.append(sw_cfg_rseqc['module'])
cmd_list.append('''{} \\
--input={} \\
--refgene={} \\
--minimum_length={} \\
--format={} \\
--out-prefix={} \\
{}
\n'''.format(
module,
task_cfg_module['in_file_path_list'][0],
task_cfg_reference['anno_bed'],
100,
['pdf', 'png', 'jpeg'][0],
task_cfg_module['out_file_base'],
log_file_path_cmd
))
if shell_script_path:
try:
with open(shell_script_path, "w") as outfile:
outfile.write(
'''\n{}\n'''.format(
'\n\n'.join(cmd_list)
)
)
outfile.write("\nexit 0\n")
outfile.close()
except IOError as exc:
print(exc)
logging.debug("[ {} ] Make Shell Script - DONE\n".format(SELF_FILE))
return cmd_list
def infer_experiment(args, sw_cfg, task_cfg):
"""
RSeQC::infer_experiment
:parm args: an argparse.Namespace object of main argumens {.log_file}
:parm sw_cfg: a dictionary of corresponding software configureation {fastqc}
:parm task_cfg: a dictionary of corresponding task configureation {in_file_path_list, out_dir_path, shell_script_path, log_file_path}
:returns: returns corresponding code snippets, in which will be written to shell_script_path if provided
:raises keyError: NA
"""
# logging
if args.log_file is None:
log_file_path = '{}.{}.log'.format(
SELF_FILE_PATH,
datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S"))
else:
log_file_path = args.log_file
formatter = "%(asctime)-15s %(levelname)-8s %(message)s"
logging.basicConfig(
level=[logging.NOTSET, logging.DEBUG, logging.INFO,
logging.WARNING, logging.ERROR, logging.CRITICAL][1],
format=formatter,
filename=log_file_path)
logging.info("[ {} ] Make Shell Script\n".format(SELF_FILE))
sw_cfg_rseqc = sw_cfg['rseqc']
module = "infer_experiment.py"
task_cfg_module = task_cfg[module]
log_file_path_cmd = '' if 'log_file_path' not in task_cfg_module else '''&>> {}'''.format(task_cfg_module['log_file_path'])
task_cfg_reference = task_cfg['references'][next(iter(task_cfg['references']))]
shell_script_path = '' if 'shell_script_path' not in task_cfg_module else task_cfg_module['shell_script_path']
cmd_list = []
if sw_cfg_rseqc['module'] is not None:
cmd_list.append(sw_cfg_rseqc['module'])
cmd_list.append('''{} \\
--input-file={} \\
--refgene={} \\
--sample-size={} \\
--mapq={} \\
> {}
\n'''.format(
module,
task_cfg_module['in_file_path_list'][0],
task_cfg_reference['anno_bed'],
200000,
30,
task_cfg_module['out_file_path_list'][0]
))
if shell_script_path:
try:
with open(shell_script_path, "w") as outfile:
outfile.write(
'''\n{}\n'''.format(
'\n\n'.join(cmd_list)
)
)
outfile.write("\nexit 0\n")
outfile.close()
except IOError as exc:
print(exc)
logging.debug("[ {} ] Make Shell Script - DONE\n".format(SELF_FILE))
return cmd_list
def RPKM_saturation(args, sw_cfg, task_cfg):
"""
RSeQC::RPKM_saturation
:parm args: an argparse.Namespace object of main argumens {.log_file}
:parm sw_cfg: a dictionary of corresponding software configureation {fastqc}
:parm task_cfg: a dictionary of corresponding task configureation {in_file_path_list, out_dir_path, shell_script_path, log_file_path}
:returns: returns corresponding code snippets, in which will be written to shell_script_path if provided
:raises keyError: NA
"""
# logging
if args.log_file is None:
log_file_path = '{}.{}.log'.format(
SELF_FILE_PATH,
datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S"))
else:
log_file_path = args.log_file
formatter = "%(asctime)-15s %(levelname)-8s %(message)s"
logging.basicConfig(
level=[logging.NOTSET, logging.DEBUG, logging.INFO,
logging.WARNING, logging.ERROR, logging.CRITICAL][1],
format=formatter,
filename=log_file_path)
logging.info("[ {} ] Make Shell Script\n".format(SELF_FILE))
sw_cfg_rseqc = sw_cfg['rseqc']
module = "RPKM_saturation.py"
task_cfg_module = task_cfg[module]
log_file_path_cmd = '' if 'log_file_path' not in task_cfg_module else '''&>> {}'''.format(task_cfg_module['log_file_path'])
strand_rule_cmd = '' if task_cfg_module['strand_specificity'] is None else """--strand='{}'""".format(task_cfg_module['strand_specificity'])
shell_script_path = '' if 'shell_script_path' not in task_cfg_module else task_cfg_module['shell_script_path']
task_cfg_reference = task_cfg['references'][next(iter(task_cfg['references']))]
cmd_list = []
if sw_cfg_rseqc['module'] is not None:
cmd_list.append(sw_cfg_rseqc['module'])
cmd_list.append('''{} \\
--input-file={} \\
--out-prefix={} \\
--refgene={} \\
{} \\
--percentile-floor={} \\
--percentile-ceiling={} \\
--percentile-step={} \\
--rpkm-cutoff={} \\
--mapq={} \\
{}
\n'''.format(
module,
task_cfg_module['in_file_path_list'][0],
task_cfg_module['out_file_base'],
task_cfg_reference['anno_bed'],
strand_rule_cmd,
5,
100,
5,
0.01,
30,
log_file_path_cmd
))
if shell_script_path:
try:
with open(shell_script_path, "w") as outfile:
outfile.write(
'''\n{}\n'''.format(
'\n\n'.join(cmd_list)
)
)
outfile.write("\nexit 0\n")
outfile.close()
except IOError as exc:
print(exc)
logging.debug("[ {} ] Make Shell Script - DONE\n".format(SELF_FILE))
return cmd_list
| 31.860119
| 144
| 0.596917
| 1,323
| 10,705
| 4.538171
| 0.109599
| 0.067622
| 0.075783
| 0.031979
| 0.8999
| 0.882745
| 0.868754
| 0.86459
| 0.86459
| 0.86459
| 0
| 0.006284
| 0.271649
| 10,705
| 335
| 145
| 31.955224
| 0.763755
| 0.16497
| 0
| 0.813333
| 0
| 0
| 0.197479
| 0.005043
| 0
| 0
| 0
| 0
| 0
| 1
| 0.017778
| false
| 0
| 0.022222
| 0
| 0.057778
| 0.017778
| 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
|
0434e55a3a469b36a6c6d26b3716774ed1cc8513
| 117
|
py
|
Python
|
AutoDL_sample_code_submission/Auto_Image/MyDataset.py
|
zhengying-liu/AutoDL-1
|
7bb65572a60b0ffe918dfcdacd93d258632591a8
|
[
"Apache-2.0"
] | 1
|
2021-07-03T08:04:03.000Z
|
2021-07-03T08:04:03.000Z
|
AutoDL_sample_code_submission/Auto_Image/MyDataset.py
|
zichuan-scott-xu/AutoDL-1
|
7bb65572a60b0ffe918dfcdacd93d258632591a8
|
[
"Apache-2.0"
] | null | null | null |
AutoDL_sample_code_submission/Auto_Image/MyDataset.py
|
zichuan-scott-xu/AutoDL-1
|
7bb65572a60b0ffe918dfcdacd93d258632591a8
|
[
"Apache-2.0"
] | 1
|
2021-07-03T08:02:25.000Z
|
2021-07-03T08:02:25.000Z
|
from Auto_Image.skeleton.data.dataset import TFDataset
from Auto_Image.skeleton.data.dataset import TransformDataset
| 39
| 61
| 0.880342
| 16
| 117
| 6.3125
| 0.5625
| 0.158416
| 0.257426
| 0.415842
| 0.752475
| 0.752475
| 0.752475
| 0
| 0
| 0
| 0
| 0
| 0.068376
| 117
| 2
| 62
| 58.5
| 0.926606
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| true
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| null | 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 9
|
0443f66fe6f23ad7c96cc5f5c03d7acf61410a5b
| 40
|
py
|
Python
|
aoc_2020/__init__.py
|
n1ckdm/advent-of-code-2020
|
913ea4cff29fa76df15c0c22616cc1eebb903490
|
[
"MIT"
] | 1
|
2020-12-05T09:25:03.000Z
|
2020-12-05T09:25:03.000Z
|
aoc_2020/__init__.py
|
n1ckdm/advent-of-code-2020
|
913ea4cff29fa76df15c0c22616cc1eebb903490
|
[
"MIT"
] | null | null | null |
aoc_2020/__init__.py
|
n1ckdm/advent-of-code-2020
|
913ea4cff29fa76df15c0c22616cc1eebb903490
|
[
"MIT"
] | null | null | null |
from . import day1
from . import inputs
| 13.333333
| 20
| 0.75
| 6
| 40
| 5
| 0.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.03125
| 0.2
| 40
| 2
| 21
| 20
| 0.90625
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
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| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| null | 1
| 0
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| 0
| 0
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| 1
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| 0
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| null | 0
| 0
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| 0
| 0
| 0
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| 1
| 0
| 1
| 0
|
0
| 7
|
f09b964809ca07a710f4d36661bc673c13c097a1
| 8,653
|
py
|
Python
|
include/algs.py
|
MLI-lab/regularization_based_continual_learning
|
808f2131add659c8c96fb8318e480df74e19f936
|
[
"Apache-1.1"
] | null | null | null |
include/algs.py
|
MLI-lab/regularization_based_continual_learning
|
808f2131add659c8c96fb8318e480df74e19f936
|
[
"Apache-1.1"
] | null | null | null |
include/algs.py
|
MLI-lab/regularization_based_continual_learning
|
808f2131add659c8c96fb8318e480df74e19f936
|
[
"Apache-1.1"
] | null | null | null |
import torch
import torch.nn as nn
import os
import torchvision.transforms as transforms
from torch.autograd import Variable
import numpy as np
import matplotlib.pyplot as plt
import random
from torchvision import datasets
from torch.nn import functional as F
#from torch import nn
from torch import autograd
class EWC():
def __init__(self,lam = 1.0):
self.lam = lam
self.has_data = False
print("EWC", lam)
def update(self,model,data_loader):
self.model = model
self.p0 = torch.cat( [ torch.flatten(p.data.clone()) for p in model.parameters() if p.requires_grad ] )
# update or generate the fisher diagonal matrix
if self.has_data:
print("update data..")
self.task_data += self.compute_task_data(data_loader)
else:
print("generate task data..")
self.task_data = self.compute_task_data(data_loader)
print("..done")
self.has_data = True
#
def loss(self,model):
if self.has_data:
p = torch.cat( [torch.flatten(p) for p in model.parameters() if p.requires_grad ] )
loss = (self.task_data * (p - self.p0)**2).sum()
return self.lam * loss
else:
# ewc loss is 0 if there's no information from previous tasks
return sum( Variable(torch.zeros(1)).cuda() ) # if cuda else Variable(torch.zeros(1))
#
def compute_task_data(self, data_loader):
task_data = None
for i,(xs, ys) in enumerate(data_loader):
# iterate over examples in batch
xs = xs.cuda()
ys = ys.cuda()
for (x,y) in zip(xs,ys):
x = Variable(x).cuda() #if self._is_on_cuda() else Variable(x)
y = Variable(y).cuda() #if self._is_on_cuda() else Variable(y)
x.unsqueeze_(0)
y.unsqueeze_(0)
#loss = F.softmax( self.model(x) , dim=1 )[0,y]
#grad = autograd.grad(loss, [p for p in self.model.parameters() if p.requires_grad] ,retain_graph=False)
num_classes = 10
for i in range(num_classes):
loss = self.model(x)[0][i]
grad = autograd.grad(loss, [p for p in self.model.parameters() if p.requires_grad] ,retain_graph=False)
grad = torch.cat( [torch.flatten(g) for g in grad ] )
if task_data is None:
task_data = grad**2
else:
task_data += grad**2
print( "task data norm and number entries:",torch.norm(task_data), task_data.shape )
return task_data
class L2():
def __init__(self,lam = 1.0,recompute=False):
self.lam = lam
self.recompute = recompute
self.has_data = False
print("L2", lam)
def update(self,model,data_loader):
self.model = model
self.p0 = torch.cat( [ torch.flatten(p.data.clone()) for p in model.parameters() if p.requires_grad ] )
if self.has_data:
if self.recompute:
self.task_data_tmp = self.compute_task_data(data_loader)
self.task_data += self.lam * self.task_data_tmp
else:
self.task_data_tmp = self.compute_task_data(data_loader)
self.task_data = self.lam * self.task_data_tmp
self.has_data = True
#
def loss(self,model):
if self.has_data:
p = torch.cat( [torch.flatten(p) for p in model.parameters() if p.requires_grad ] )
loss = (self.task_data * (p - self.p0)**2).sum()
return loss # lamda comes in in compute task data
else:
# ewc loss is 0 if there's no information from previous tasks
return sum( Variable(torch.zeros(1)).cuda() ) # if cuda else Variable(torch.zeros(1))
#
def compute_task_data(self, data_loader):
# compute once to get statistics
task_data = None
for i,(xs, ys) in enumerate(data_loader):
# iterate over examples in batch
xs = xs.cuda()
ys = ys.cuda()
for (x,y) in zip(xs,ys):
x = Variable(x).cuda() #if self._is_on_cuda() else Variable(x)
y = Variable(y).cuda() #if self._is_on_cuda() else Variable(y)
x.unsqueeze_(0)
y.unsqueeze_(0)
#loss = F.softmax( self.model(x) , dim=1 )[0,y]
#grad = autograd.grad(loss, [p for p in self.model.parameters() if p.requires_grad] ,retain_graph=False)
num_classes = 10
for i in range(num_classes):
loss = self.model(x)[0][i]
grad = autograd.grad(loss, [p for p in self.model.parameters() if p.requires_grad] ,retain_graph=False)
grad = torch.cat( [torch.flatten(g) for g in grad ] )
if task_data is None:
task_data = grad**2
else:
task_data += grad**2
# visualize task data:
sizes = [torch.flatten(p).shape[0] for p in self.model.parameters() if p.requires_grad]
indices = [ sum(sizes[:i]) for i in range(len(sizes)+1)]
for i in range(len(sizes)):
a = task_data[indices[i]:indices[i+1]].cpu().numpy()
plt.hist(a, bins='auto')
plt.show()
for i in range(len(sizes)):
le = len(task_data[indices[i]:indices[i+1]])
mean = torch.mean( task_data[indices[i]:indices[i+1]] )
task_data[indices[i]:indices[i+1]] = torch.ones(le).cuda() * mean
print( "task data norm and number entries:",torch.norm(task_data), task_data.shape )
return task_data
class EWCplusplus():
def __init__(self,lam = 1.0,s=10):
self.lam = lam
self.has_data = False
self.s = s
print("EWC++ ", s, lam)
# update the current estimate of the data
def update(self,model,data_loader):
self.model = model
self.p0 = torch.cat( [torch.flatten(p.data.clone()) for p in model.parameters() if p.requires_grad ] )
if self.has_data:
print("update data..")
self.task_data += [self.compute_task_data(data_loader)]
else:
print("generate task data..")
self.task_data = [self.compute_task_data(data_loader)]
print("..done")
self.has_data = True
#
def loss(self,model):
if self.has_data:
p = torch.cat( [ torch.flatten(p) for p in model.parameters() if p.requires_grad ] )
loss = sum( Variable(torch.zeros(1)).cuda() )
for td in self.task_data:
loss += torch.norm( td.matmul( p - self.p0 ) )**2
return self.lam * loss
else:
# ewc loss is 0 if there's no information from previous tasks
return sum( Variable(torch.zeros(1)).cuda() ) # if cuda else Variable(torch.zeros(1))
#
def compute_task_data(self, data_loader):
task_data = None
for i,(xs, ys) in enumerate(data_loader):
# iterate over examples in batch
xs = xs.cuda()
ys = ys.cuda()
for (x,y) in zip(xs,ys):
x = Variable(x).cuda() #if self._is_on_cuda() else Variable(x)
y = Variable(y).cuda() #if self._is_on_cuda() else Variable(y)
x.unsqueeze_(0)
y.unsqueeze_(0)
num_classes = 10
for i in range(num_classes):
loss = self.model(x)[0][i]
grad = autograd.grad(loss, [p for p in self.model.parameters() if p.requires_grad] ,retain_graph=False)
grad = torch.cat( [torch.flatten(g) for g in grad ] )
S = 1/torch.sqrt(torch.tensor(float(self.s))) * torch.randn(self.s) #*torch.randn(s , list(grad.shape)[0] )
S = S.cuda()
if task_data is None:
task_data = torch.ger( S , grad ) # torch.ger computes outer product
else:
task_data += torch.ger( S , grad ) # torch.ger computes outer product
print( "task data norm and number entries:",torch.norm(task_data), task_data.shape )
return task_data
| 40.624413
| 127
| 0.536346
| 1,146
| 8,653
| 3.922339
| 0.116928
| 0.096107
| 0.034705
| 0.048053
| 0.831146
| 0.825362
| 0.796218
| 0.758843
| 0.758843
| 0.758843
| 0
| 0.010705
| 0.352248
| 8,653
| 213
| 128
| 40.624413
| 0.791258
| 0.141223
| 0
| 0.716981
| 0
| 0
| 0.026358
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.075472
| false
| 0
| 0.069182
| 0
| 0.220126
| 0.075472
| 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
|
f0c5b48504c4070ffb2470f4f126f10a1e7fb8b9
| 10,506
|
py
|
Python
|
birdate/data_process.py
|
sakuranew/KGAttributesExtraction
|
f4d796046ced6ff508442a802962549f4c4a51de
|
[
"MIT"
] | 247
|
2018-12-28T10:56:47.000Z
|
2022-03-09T09:02:23.000Z
|
birdate/data_process.py
|
SunYanCN/BERT-AttributeExtraction
|
f4d796046ced6ff508442a802962549f4c4a51de
|
[
"MIT"
] | 15
|
2018-12-28T06:05:05.000Z
|
2021-02-25T07:53:19.000Z
|
birdate/data_process.py
|
SunYanCN/BERT-AttributeExtraction
|
f4d796046ced6ff508442a802962549f4c4a51de
|
[
"MIT"
] | 61
|
2019-01-03T08:54:38.000Z
|
2022-03-01T16:18:48.000Z
|
import pickle
def data_gen(k):
if k == 1:
f = open('./data/birth_date_train.txt', 'r', encoding='utf-8')
train_x = []
train_y = []
test_x = []
test_y = []
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
train_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
train_x.append(s)
print('reading test data ...')
f = open('./data/birth_date_test.txt', 'r', encoding='utf-8')
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
test_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
test_x.append(s)
print(len(train_x))
# print(sep)
print(len(test_x))
train_x = train_x[:6000]
train_y = train_y[:6000]
return (train_x, test_x), (train_y, test_y)
elif k == 2:
f = open('./data/birth_date_train.txt', 'r', encoding='utf-8')
train_x = []
train_y = []
test_x = []
test_y = []
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
train_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
train_x.append(s)
print('reading test data ...')
f = open('./data/birth_date_test.txt', 'r', encoding='utf-8')
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
test_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
test_x.append(s)
print(len(train_x))
# print(sep)
print(len(test_x))
# train_x=train_x[:6000]
# train_y=train_y[:6000]
return (train_x, test_x), (train_y, test_y)
elif k == 3:
dic = dict()
with open('./data/person_name.txt', 'r', encoding='utf-8') as fin:
content = fin.readlines()
for name in content:
dic[name] = 1
f = open('./data/birth_date_train.txt', 'r', encoding='utf-8')
train_x = []
train_y = []
test_x = []
test_y = []
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
train_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
elif dic.get(en1) is not None:
sentence.replace(en1, "实体")
else:
sentence.replace(en1, "属性")
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
elif dic.get(en2) is not None:
sentence.replace(en2, "实体")
else:
sentence.replace(en2, "属性")
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
train_x.append(s)
print('reading test data ...')
f = open('./data/birth_date_test.txt', 'r', encoding='utf-8')
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
test_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
elif dic.get(en1) is not None:
sentence.replace(en1, "实体")
else:
sentence.replace(en1, "属性")
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
elif dic.get(en2) is not None:
sentence.replace(en2, "实体")
else:
sentence.replace(en2, "属性")
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
test_x.append(s)
print(len(train_x))
# print(sep)
print(len(test_x))
# train_x=train_x[:6000]
# train_y=train_y[:6000]
return (train_x, test_x), (train_y, test_y)
elif k == 4:
dic = dict()
with open('./data/person_name.txt', 'r', encoding='utf-8') as fin:
content = fin.readlines()
for name in content:
dic[name] = 1
f = open('./data/birth_date_train.txt', 'r', encoding='utf-8')
train_x = []
train_y = []
test_x = []
test_y = []
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
train_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
elif dic.get(en1) is not None:
sentence.replace(en1, "<e>")
else:
sentence.replace(en1, "<a>")
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
elif dic.get(en2) is not None:
sentence.replace(en2, "<e>")
else:
sentence.replace(en2, "<a>")
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
train_x.append(s)
print('reading test data ...')
f = open('./data/birth_date_test.txt', 'r', encoding='utf-8')
while True:
content = f.readline()
if content == '':
break
content = content.strip().split('#')
# get entity name
en1 = content[0]
en2 = content[1]
relation = int(content[2])
test_y.append(relation)
# put the same entity pair sentences into a dict
tup = (en1, en2)
label_tag = 0
sentence = content[3]
en1pos = 0
en2pos = 0
# For Chinese
en1pos = sentence.find(en1)
if en1pos == -1:
en1pos = 0
elif dic.get(en1) is not None:
sentence.replace(en1, "<e>")
else:
sentence.replace(en1, "<a>")
en2pos = sentence.find(en2)
if en2pos == -1:
en2pos = 0
elif dic.get(en2) is not None:
sentence.replace(en2, "<e>")
else:
sentence.replace(en2, "<a>")
output = []
s = sentence
# s=[s[i] for i in range(len(s))]
test_x.append(s)
print(len(train_x))
# print(sep)
print(len(test_x))
# train_x=train_x[:6000]
# train_y=train_y[:6000]
return (train_x, test_x), (train_y, test_y)
if __name__ == "__main__":
data_gen(0)
| 26.069479
| 74
| 0.432991
| 1,148
| 10,506
| 3.868467
| 0.073171
| 0.032425
| 0.035127
| 0.033776
| 0.989417
| 0.989417
| 0.989417
| 0.989417
| 0.989417
| 0.989417
| 0
| 0.047421
| 0.452027
| 10,506
| 402
| 75
| 26.134328
| 0.723988
| 0.098706
| 0
| 0.963768
| 0
| 0
| 0.048377
| 0.027159
| 0
| 0
| 0
| 0
| 0
| 1
| 0.003623
| false
| 0
| 0.003623
| 0
| 0.021739
| 0.043478
| 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
|
50559a5b4bb3f7466301839924fe364f37a557e0
| 194
|
py
|
Python
|
brping/__init__.py
|
patrickelectric/ping-python-1
|
99eaf6f87f22920aacd0f4e8b5123d3fa5d5fc9d
|
[
"MIT"
] | 16
|
2019-04-07T00:58:32.000Z
|
2022-02-28T10:09:16.000Z
|
src/brping/__init__.py
|
COHRINT/ping360_sonar
|
637e797d5e633f6175078085d58cdb1a41df17de
|
[
"MIT"
] | 72
|
2018-08-01T23:45:55.000Z
|
2022-03-28T05:29:20.000Z
|
src/brping/__init__.py
|
COHRINT/ping360_sonar
|
637e797d5e633f6175078085d58cdb1a41df17de
|
[
"MIT"
] | 22
|
2018-09-16T21:33:15.000Z
|
2022-01-19T09:21:16.000Z
|
#'Ping python package'
from brping.definitions import *
from brping.pingmessage import *
from brping.device import PingDevice
from brping.ping1d import Ping1D
from brping.ping360 import Ping360
| 27.714286
| 36
| 0.829897
| 26
| 194
| 6.192308
| 0.461538
| 0.310559
| 0.198758
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.046784
| 0.118557
| 194
| 6
| 37
| 32.333333
| 0.894737
| 0.108247
| 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
|
ac9c215fed2a284b025132f7ef883acaf6f31d5c
| 769
|
py
|
Python
|
tests/parser/detcons.5.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/detcons.5.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/detcons.5.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
input = """
% Here the GUS computation is needed.
% Roughly, the following should be done:
% mbt becomes must-be-true because of the constraint.
% f and f2's support counters are decremented.
% The GUS for f and f2's component is computed, deriving their falsity.
% t and t2 become true.
:- not mbt.
mbt | f.
mbt | f2.
f :- f2.
f2 :- f.
t :- not f.
t2 :- not f2.
"""
output = """
% Here the GUS computation is needed.
% Roughly, the following should be done:
% mbt becomes must-be-true because of the constraint.
% f and f2's support counters are decremented.
% The GUS for f and f2's component is computed, deriving their falsity.
% t and t2 become true.
:- not mbt.
mbt | f.
mbt | f2.
f :- f2.
f2 :- f.
t :- not f.
t2 :- not f2.
"""
| 21.971429
| 72
| 0.643693
| 128
| 769
| 3.867188
| 0.296875
| 0.048485
| 0.048485
| 0.056566
| 0.977778
| 0.977778
| 0.977778
| 0.977778
| 0.977778
| 0.977778
| 0
| 0.027444
| 0.241873
| 769
| 34
| 73
| 22.617647
| 0.821612
| 0
| 0
| 0.933333
| 0
| 0
| 0.958051
| 0
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
4a0d083047e8d7d7eb0763a532fbee58f9121a41
| 1,045
|
py
|
Python
|
graph/adj_matrix.py
|
dkryvitskaya/computations
|
52615b486602be43c51b1dc39a6dda696cbf13fd
|
[
"Apache-2.0"
] | null | null | null |
graph/adj_matrix.py
|
dkryvitskaya/computations
|
52615b486602be43c51b1dc39a6dda696cbf13fd
|
[
"Apache-2.0"
] | null | null | null |
graph/adj_matrix.py
|
dkryvitskaya/computations
|
52615b486602be43c51b1dc39a6dda696cbf13fd
|
[
"Apache-2.0"
] | 4
|
2020-12-16T18:12:02.000Z
|
2021-06-05T08:45:26.000Z
|
graph_a = [ [0, 0, 0, 1, 1, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]
graph_b = [ [0, 0, 0, 1, 1, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0]
]
def is_adjacent(graph, vert_a, vert_b):
return False
print("Graph A: ")
for i in range(0, 8):
for j in range(0, 8):
print("Vertice {0} and vertice {1} are adjacent: {2}".format(i, j, is_adjacent(graph_a, i, j)))
print("Graph B: ")
for i in range(0, 8):
for j in range(0, 8):
print("Vertice {0} and vertice {1} are adjacent: {2}".format(i, j, is_adjacent(graph_b, i, j)))
| 26.125
| 112
| 0.354067
| 192
| 1,045
| 1.880208
| 0.119792
| 0.554017
| 0.797784
| 1.019391
| 0.781163
| 0.781163
| 0.781163
| 0.781163
| 0.781163
| 0.781163
| 0
| 0.215753
| 0.441148
| 1,045
| 39
| 113
| 26.794872
| 0.402397
| 0
| 0
| 0.64
| 0
| 0
| 0.10757
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.16
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 12
|
c59d476fa5276be671f540f11a0452393e7b00b6
| 171
|
py
|
Python
|
src/schnetpack/md/simulation_hooks/__init__.py
|
sxie22/schnetpack
|
a421e7c121c7bdb2838fb30f887812110ecfa3c6
|
[
"MIT"
] | null | null | null |
src/schnetpack/md/simulation_hooks/__init__.py
|
sxie22/schnetpack
|
a421e7c121c7bdb2838fb30f887812110ecfa3c6
|
[
"MIT"
] | null | null | null |
src/schnetpack/md/simulation_hooks/__init__.py
|
sxie22/schnetpack
|
a421e7c121c7bdb2838fb30f887812110ecfa3c6
|
[
"MIT"
] | 1
|
2022-02-10T17:39:11.000Z
|
2022-02-10T17:39:11.000Z
|
from .basic_hooks import *
from .barostats import *
from .barostats_rpmd import *
from .thermostats import *
from .thermostats_rpmd import *
from .callback_hooks import *
| 24.428571
| 31
| 0.789474
| 22
| 171
| 5.954545
| 0.363636
| 0.381679
| 0.290076
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.140351
| 171
| 6
| 32
| 28.5
| 0.891156
| 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
|
c5e4fe7034ea8473265650ae3397d298bc43f7a6
| 16,841
|
py
|
Python
|
pieceB26.py
|
Kota-Y/blocks_AI
|
41e041a8053d7a0869cd8123cf5706ddfc946f5a
|
[
"MIT"
] | null | null | null |
pieceB26.py
|
Kota-Y/blocks_AI
|
41e041a8053d7a0869cd8123cf5706ddfc946f5a
|
[
"MIT"
] | null | null | null |
pieceB26.py
|
Kota-Y/blocks_AI
|
41e041a8053d7a0869cd8123cf5706ddfc946f5a
|
[
"MIT"
] | null | null | null |
import numpy as np
a0 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
a1 = a0
a2 = a0
a3 = a0
a4 = a0
a5 = a0
a6 = a0
a7 = a0
pieces=[a0]
#pieces.append(a1)
#pieces.append(a2)
#pieces.append(a3)
#pieces.append(a4)
#pieces.append(a5)
#pieces.append(a6)
#pieces.append(a7)
b0 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
b1 = b0
b2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
b3 = b2
b4 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
b5 = b4
b6 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
b7 = b6
pieces.append(b0)
#pieces.append(b1)
pieces.append(b2)
#pieces.append(b3)
pieces.append(b4)
#pieces.append(b5)
pieces.append(b6)
#pieces.append(b7)
c0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
c1 = c0
c2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
c3 = c2
c4 = c0
c5 = c0
c6 = c2
c7 = c2
pieces.append(c0)
#pieces.append(c1)
pieces.append(c2)
#pieces.append(c3)
#pieces.append(c4)
#pieces.append(c5)
#pieces.append(c6)
#pieces.append(c7)
d0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
d1 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
d2 = d1
d3 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
d4 = d3
d5 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
d6 = d5
d7 = d0
#pieces.append(d0)
pieces.append(d1)
#pieces.append(d2)
pieces.append(d3)
#pieces.append(d4)
pieces.append(d5)
#pieces.append(d6)
pieces.append(d7)
e0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
e1 = e0
e2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,9,8],[0,9,1,1,1,1,9],[0,8,9,9,9,9,8],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
e3 = e2
e4 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
e5 = e4
e6 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[8,9,9,9,9,8,0],[9,1,1,1,1,9,0],[8,9,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
e7 = e6
pieces.append(e0)
#pieces.append(e1)
pieces.append(e2)
#pieces.append(e3)
pieces.append(e4)
#pieces.append(e5)
pieces.append(e6)
#pieces.append(e7)
f0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
f1 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
f2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,1,9,0],[0,0,0,8,9,8,0],[0,0,0,0,0,0,0]])
f3 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[0,8,9,9,1,9,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
f4 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
f5 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
f6 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
f7 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,9,1,9,9,8,0],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
pieces.append(f0)
pieces.append(f1)
pieces.append(f2)
pieces.append(f3)
pieces.append(f4)
pieces.append(f5)
pieces.append(f6)
pieces.append(f7)
g0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
g1 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
g2 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
g3 = g0
g4 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
g5 = g2
g6 = g1
g7 = g4
pieces.append(g0)
pieces.append(g1)
pieces.append(g2)
pieces.append(g3)
#pieces.append(g4)
#pieces.append(g5)
#pieces.append(g6)
#pieces.append(g7)
h0 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
h1 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
h2 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
h3 = h0
h4 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
h5 = h2
h6 = h1
h7 = h4
pieces.append(h0)
#pieces.append(h1)
pieces.append(h2)
#pieces.append(h3)
pieces.append(h4)
#pieces.append(h5)
pieces.append(h6)
#pieces.append(h7)
i0 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,8,0],[0,8,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
i1 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,8,9,1,1,9,0],[0,9,1,1,9,8,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
i2 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[0,0,8,9,1,9,0],[0,0,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
i3 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,8,9,1,9,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
i4 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,8,0],[0,8,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
i5 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,8,9,1,1,9,0],[0,9,1,1,9,8,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
i6 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,9,1,9,8,0,0],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
i7 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,8,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
pieces.append(i0)
pieces.append(i1)
pieces.append(i2)
pieces.append(i3)
pieces.append(i4)
pieces.append(i5)
pieces.append(i6)
pieces.append(i7)
j0 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
j1 = j0
j2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[8,9,9,9,9,9,8],[9,1,1,1,1,1,9],[8,9,9,9,9,9,8],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
j3 = j2
j4 = j0
j5 = j0
j6 = j2
j7 = j2
pieces.append(j0)
#pieces.append(j1)
pieces.append(j2)
#pieces.append(j3)
#pieces.append(j4)
#pieces.append(j5)
#pieces.append(j6)
#pieces.append(j7)
k0 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
k1 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
k2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[8,9,9,9,9,8,0],[9,1,1,1,1,9,0],[8,9,9,9,1,9,0],[0,0,0,8,9,8,0],[0,0,0,0,0,0,0]])
k3 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[8,9,9,9,1,9,0],[9,1,1,1,1,9,0],[8,9,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
k4 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
k5 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
k6 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,9,9,8],[0,9,1,1,1,1,9],[0,8,9,9,9,9,8],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
k7 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,9,8],[0,9,1,1,1,1,9],[0,9,1,9,9,9,8],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
pieces.append(k0)
pieces.append(k1)
pieces.append(k2)
pieces.append(k3)
pieces.append(k4)
pieces.append(k5)
pieces.append(k6)
pieces.append(k7)
l0 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,9,1,9,8,0,0],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
l1 = np.array([[0,0,0,0,0,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,8,9,1,9,0],[0,0,0,8,9,8,0],[0,0,0,0,0,0,0]])
l2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[8,9,9,9,8,0,0],[9,1,1,1,9,8,0],[8,9,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
l3 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[8,9,9,1,1,9,0],[9,1,1,1,9,8,0],[8,9,9,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
l4 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[0,0,8,9,1,9,0],[0,0,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
l5 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,8,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
l6 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,9,8],[0,8,9,1,1,1,9],[0,0,8,9,9,9,8],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
l7 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,9,9,8],[0,8,9,1,1,1,9],[0,9,1,1,9,9,8],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
pieces.append(l0)
pieces.append(l1)
pieces.append(l2)
pieces.append(l3)
pieces.append(l4)
pieces.append(l5)
pieces.append(l6)
pieces.append(l7)
m0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
m1 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
m2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
m3 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,8,9,1,1,9,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
m4 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
m5 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
m6 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
m7 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,9,1,1,9,8,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
pieces.append(m0)
pieces.append(m1)
pieces.append(m2)
pieces.append(m3)
pieces.append(m4)
pieces.append(m5)
pieces.append(m6)
pieces.append(m7)
n0 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
n1 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
n2 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,9,1,9,1,9,0],[0,8,9,8,9,8,0],[0,0,0,0,0,0,0]])
n3 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,9,8,0],[0,9,1,9,1,9,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
n4 = n1
n5 = n0
n6 = n3
n7 = n2
pieces.append(n0)
pieces.append(n1)
pieces.append(n2)
pieces.append(n3)
#pieces.append(n4)
#pieces.append(n5)
#pieces.append(n6)
#pieces.append(n7)
o0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
o1 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
o2 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,9,8],[0,9,1,1,1,1,9],[0,8,9,9,9,9,8],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
o3 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,8,9,9,9,9,8],[0,9,1,1,1,1,9],[0,8,9,1,9,9,8],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
o4 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
o5 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
o6 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[8,9,9,9,9,8,0],[9,1,1,1,1,9,0],[8,9,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
o7 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[8,9,9,1,9,8,0],[9,1,1,1,1,9,0],[8,9,9,9,9,8,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
pieces.append(o0)
pieces.append(o1)
pieces.append(o2)
pieces.append(o3)
pieces.append(o4)
pieces.append(o5)
pieces.append(o6)
pieces.append(o7)
p0 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,8,9,1,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,9,8,0],[0,0,0,0,0,0,0]])
p1 = p0
p2 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[0,8,9,9,1,9,0],[0,9,1,1,1,9,0],[0,8,9,9,1,9,0],[0,0,0,8,9,8,0],[0,0,0,0,0,0,0]])
p3 = p2
p4 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,1,9,8,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
p5 = p4
p6 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,9,8,0],[0,9,1,1,1,9,0],[0,9,1,9,9,8,0],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
p7 = p6
pieces.append(p0)
#pieces.append(p1)
pieces.append(p2)
#pieces.append(p3)
pieces.append(p4)
#pieces.append(p5)
pieces.append(p6)
#pieces.append(p7)
q0 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[0,0,9,1,9,9,8],[0,0,9,1,1,1,9],[0,0,8,9,9,9,8],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
q1 = np.array([[0,0,8,9,8,0,0],[0,0,9,1,9,0,0],[8,9,9,1,9,0,0],[9,1,1,1,9,0,0],[8,9,9,9,8,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]])
q2 = q1
q3 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[8,9,9,9,8,0,0],[9,1,1,1,9,0,0],[8,9,9,1,9,0,0],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
q4 = q3
q5 = np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,8,9,9,9,8],[0,0,9,1,1,1,9],[0,0,9,1,9,9,8],[0,0,9,1,9,0,0],[0,0,8,9,8,0,0]])
q6 = q5
q7 = q0
#pieces.append(q0)
pieces.append(q1)
#pieces.append(q2)
pieces.append(q3)
#pieces.append(q4)
pieces.append(q5)
#pieces.append(q6)
pieces.append(q7)
r0 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,8,0],[0,8,9,1,1,9,0],[0,0,8,9,1,9,0],[0,0,0,8,9,8,0],[0,0,0,0,0,0,0]])
r1 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,8,9,1,1,9,0],[0,9,1,1,9,8,0],[0,9,1,9,8,0,0],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
r2 = r1
r3 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,8,0,0],[0,9,1,1,9,8,0],[0,8,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
r4 = r3
r5 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[0,0,8,9,1,9,0],[0,8,9,1,1,9,0],[0,9,1,1,9,8,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
r6 = r5
r7 = r0
#pieces.append(r0)
pieces.append(r1)
#pieces.append(r2)
pieces.append(r3)
#pieces.append(r4)
pieces.append(r5)
#pieces.append(r6)
pieces.append(r7)
s0 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,1,9,0],[0,0,0,8,9,8,0],[0,0,0,0,0,0,0]])
s1 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[0,8,9,9,1,9,0],[0,9,1,1,1,9,0],[0,9,1,9,9,8,0],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
s2 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,0,9,1,1,9,0],[0,8,9,1,9,8,0],[0,9,1,1,9,9,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
s3 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,0,0],[0,8,9,1,9,8,0],[0,0,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
s4 = s0
s5 = s1
s6 = s2
s7 = s3
pieces.append(s0)
pieces.append(s1)
pieces.append(s2)
pieces.append(s3)
#pieces.append(s4)
#pieces.append(s5)
#pieces.append(s6)
#pieces.append(s7)
t0 = np.array([[0,0,0,0,0,0,0],[0,8,9,8,0,0,0],[0,9,1,9,9,8,0],[0,9,1,1,1,9,0],[0,8,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
t1 = np.array([[0,0,0,0,0,0,0],[0,0,0,8,9,8,0],[0,8,9,9,1,9,0],[0,9,1,1,1,9,0],[0,8,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
t2 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,0,9,1,9,8,0],[0,8,9,1,1,9,0],[0,9,1,1,9,8,0],[0,8,9,9,8,0,0],[0,0,0,0,0,0,0]])
t3 = np.array([[0,0,0,0,0,0,0],[0,8,9,9,8,0,0],[0,9,1,1,9,8,0],[0,8,9,1,1,9,0],[0,0,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
t4 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,8,0],[0,9,1,1,1,9,0],[0,8,9,9,1,9,0],[0,0,0,8,9,8,0],[0,0,0,0,0,0,0]])
t5 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,8,0],[0,9,1,1,1,9,0],[0,9,1,9,9,8,0],[0,8,9,8,0,0,0],[0,0,0,0,0,0,0]])
t6 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,9,8,0],[0,8,9,1,1,9,0],[0,9,1,1,9,8,0],[0,8,9,1,9,0,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
t7 = np.array([[0,0,0,0,0,0,0],[0,0,8,9,8,0,0],[0,8,9,1,9,0,0],[0,9,1,1,9,8,0],[0,8,9,1,1,9,0],[0,0,8,9,9,8,0],[0,0,0,0,0,0,0]])
pieces.append(t0)
pieces.append(t1)
pieces.append(t2)
pieces.append(t3)
pieces.append(t4)
pieces.append(t5)
pieces.append(t6)
pieces.append(t7)
u0 = np.array([[0,0,0,0,0,0,0,],[0,0,8,9,8,0,0],[0,8,9,1,9,8,0],[0,9,1,1,1,9,0],[0,8,9,1,9,8,0],[0,0,8,9,8,0,0],[0,0,0,0,0,0,0]])
u1 = u0
u2 = u0
u3 = u0
u4 = u0
u5 = u0
u6 = u0
u7 = u0
pieces.append(u0)
##pieces.append(u1)
##pieces.append(u2)
##pieces.append(u3)
##pieces.append(u4)
##pieces.append(u5)
##pieces.append(u6)
##pieces.append(u7)
| 44.318421
| 130
| 0.507155
| 5,943
| 16,841
| 1.437153
| 0.030119
| 0.58307
| 0.683878
| 0.713734
| 0.678609
| 0.677789
| 0.677789
| 0.677087
| 0.675682
| 0.674277
| 0
| 0.334967
| 0.042753
| 16,841
| 379
| 131
| 44.435356
| 0.194839
| 0.066623
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.00369
| 0
| 0.00369
| 0
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
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| null | 0
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|
0
| 7
|
a8b22dbc04bbc2e5a07284093102877a37a36fec
| 14,844
|
py
|
Python
|
Model/Preact_Resnet.py
|
CVPR2020/EnAET
|
f490777980d20c68ca63764b7fc25537d7e72660
|
[
"MIT"
] | 3
|
2019-11-22T01:53:41.000Z
|
2020-07-09T08:39:41.000Z
|
Model/Preact_Resnet.py
|
CVPR2020/EnAET
|
f490777980d20c68ca63764b7fc25537d7e72660
|
[
"MIT"
] | 4
|
2021-03-19T08:30:03.000Z
|
2022-01-13T01:51:10.000Z
|
Model/Preact_Resnet.py
|
CVPR2020/EnAET
|
f490777980d20c68ca63764b7fc25537d7e72660
|
[
"MIT"
] | null | null | null |
# /*******************************************************************************
# * Author : CVPR2020_EnAET
# *******************************************************************************/
'''Pre-activation ResNet in PyTorch.
Reference:
[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Identity Mappings in Deep Residual Networks. arXiv:1603.05027
'''
##Pay attention here
#Do not use pre-trained model for weakly supervised learning, that's completely break the law
import torch
import torch.nn as nn
import torch.nn.functional as F
class PreActBlock(nn.Module):
'''Pre-activation version of the BasicBlock.'''
expansion = 1
def __init__(self, in_planes, planes, stride=1):
super(PreActBlock, self).__init__()
self.bn1 = nn.BatchNorm2d(in_planes)
self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn2 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=1, padding=1, bias=False)
if stride != 1 or in_planes != self.expansion*planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, self.expansion*planes, kernel_size=1, stride=stride, bias=False)
)
def forward(self, x):
out = F.relu(self.bn1(x))
shortcut = self.shortcut(out) if hasattr(self, 'shortcut') else x
out = self.conv1(out)
out = self.conv2(F.relu(self.bn2(out)))
out += shortcut
return out
class PreActBottleneck(nn.Module):
'''Pre-activation version of the original Bottleneck module.'''
expansion = 4
def __init__(self, in_planes, planes, stride=1):
super(PreActBottleneck, self).__init__()
self.bn1 = nn.BatchNorm2d(in_planes)
self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=1, bias=False)
self.bn2 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn3 = nn.BatchNorm2d(planes)
self.conv3 = nn.Conv2d(planes, self.expansion*planes, kernel_size=1, bias=False)
if stride != 1 or in_planes != self.expansion*planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, self.expansion*planes, kernel_size=1, stride=stride, bias=False)
)
def forward(self, x):
out = F.relu(self.bn1(x))
shortcut = self.shortcut(out) if hasattr(self, 'shortcut') else x
out = self.conv1(out)
out = self.conv2(F.relu(self.bn2(out)))
out = self.conv3(F.relu(self.bn3(out)))
out += shortcut
return out
class PreActResNet(nn.Module):
def __init__(self, block, num_blocks, num_classes=10):
super(PreActResNet, self).__init__()
self.in_planes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)
self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)
self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)
self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)
self.linear = nn.Linear(512*block.expansion, num_classes)
def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1]*(num_blocks-1)
layers = []
for stride in strides:
layers.append(block(self.in_planes, planes, stride))
self.in_planes = planes * block.expansion
return nn.Sequential(*layers)
def forward(self, x):
out = self.conv1(x)
out = self.layer1(out)
out = self.layer2(out)
out = self.layer3(out)
out = self.layer4(out)
out = F.avg_pool2d(out, 4)
out = out.view(out.size(0), -1)
out = self.linear(out)
return out
from Model.Attention import Self_Attn
#this is for the 32*32 image input, however, for STL10 input, we need to use another resnet
class PreActResNet_WX(nn.Module):
def __init__(self, block, num_blocks, num_classes=10,run_type=0):
self.run_type=run_type
super(PreActResNet_WX, self).__init__()
self.num_stages = len(num_blocks)
if run_type == 0:
blocks = [nn.Sequential() for i in range(self.num_stages)]
else:
blocks = [nn.Sequential() for i in range(self.num_stages + 1)]
self.in_planes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)
self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
count_stage = 0
blocks[count_stage].add_module('Block1_Conv1', self.conv1)
blocks[count_stage].add_module('Layer1',self.layer1)
count_stage+=1
self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)
blocks[count_stage].add_module('Layer2', self.layer2)
count_stage += 1
self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)
blocks[count_stage].add_module('Layer3', self.layer3)
count_stage += 1
if run_type==1:
self.attention = Self_Attn(256, 'relu')
blocks[count_stage].add_module('Attention', self.attention)
count_stage += 1
self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)
blocks[count_stage].add_module('Layer4', self.layer4)
count_stage += 1
self.linear = nn.Linear(512*block.expansion, num_classes)
self._feature_blocks = nn.ModuleList(blocks)
if run_type == 0:
self.all_feat_names =['block' + str(s + 1) for s in
range(self.num_stages)] + ['classifier', ]
elif run_type == 1 or run_type == 2 or run_type == 4 or run_type == 5:
self.all_feat_names = ['block' + str(s + 1) for s in
range(3)] + ['Attention'] + ['block' + str(s + 1) for s in
range(3, self.num_stages)] + [
'classifier', ]
self.num_stages+=1
def _parse_out_keys_arg(self, out_feat_keys):
"""
:param out_feat_keys:
:return:
the lasy layer index from out_feat_keys
"""
# By default return the features of the last layer / module.
out_feat_keys = [self.all_feat_names[-1], ] if out_feat_keys is None else out_feat_keys
if len(out_feat_keys) == 0:
raise ValueError('Empty list of output feature keys.')
for f, key in enumerate(out_feat_keys):
if key not in self.all_feat_names:
raise ValueError(
'Feature with name {0} does not exist. Existing features: {1}.'.format(key, self.all_feat_names))
elif key in out_feat_keys[:f]:
raise ValueError('Duplicate output feature key: {0}.'.format(key))
# Find the highest output feature in `out_feat_keys
max_out_feat = max([self.all_feat_names.index(key) for key in out_feat_keys])
return out_feat_keys, max_out_feat
def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1]*(num_blocks-1)
layers = []
for stride in strides:
layers.append(block(self.in_planes, planes, stride))
self.in_planes = planes * block.expansion
return nn.Sequential(*layers)
def forward(self, x,out_feat_keys=None):
go_direct_flag = False
if out_feat_keys == None:
go_direct_flag = True
out_feat_keys, max_out_feat = self._parse_out_keys_arg(out_feat_keys)
out_feats = [None] * len(out_feat_keys)
go_attention_flag = False
feat = x
for f in range(max_out_feat + 1):
key = self.all_feat_names[f]
if key == 'Attention':
go_attention_flag = True
feat, attention = self._feature_blocks[f](feat)
elif key == 'classifier':
feat = F.avg_pool2d(feat, 4)
feat = feat.view(feat.size(0), -1)
feat = self.linear(feat)
else:
feat = self._feature_blocks[f](feat)
if key in out_feat_keys:
out_feats[out_feat_keys.index(key)] = feat
out_feats = out_feats[0] if len(out_feats) == 1 else out_feats
if go_direct_flag:
return out_feats
# here is an important output link to the classifier
if go_attention_flag:
return out_feats, attention
else:
return out_feats, None
class PreActResNet_STL(nn.Module):
def __init__(self, block, num_blocks, num_classes=10,run_type=0):
self.run_type=run_type
super(PreActResNet_STL, self).__init__()
self.num_stages = len(num_blocks)
if run_type == 0:
blocks = [nn.Sequential() for i in range(self.num_stages)]
else:
blocks = [nn.Sequential() for i in range(self.num_stages + 1)]
self.in_planes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)
self.bn1 = nn.BatchNorm2d(64)
self.relu = nn.ReLU(inplace=True)
self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)#first add this to save gpu memory, if it not work, remove this
self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
count_stage = 0
blocks[count_stage].add_module('Block1_Conv1', self.conv1)
blocks[count_stage].add_module('Block1_BN1', self.bn1)
blocks[count_stage].add_module('Block1_Relu1', self.relu)
blocks[count_stage].add_module('Block1_Maxpool1', self.maxpool)
blocks[count_stage].add_module('Layer1',self.layer1)
count_stage+=1
self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)
blocks[count_stage].add_module('Layer2', self.layer2)
count_stage += 1
self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)
blocks[count_stage].add_module('Layer3', self.layer3)
count_stage += 1
if run_type==1:
self.attention = Self_Attn(256, 'relu')
blocks[count_stage].add_module('Attention', self.attention)
count_stage += 1
self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)
blocks[count_stage].add_module('Layer4', self.layer4)
count_stage += 1
self.linear = nn.Linear(512*block.expansion, num_classes)
self._feature_blocks = nn.ModuleList(blocks)
if run_type == 0:
self.all_feat_names =['block' + str(s + 1) for s in
range(self.num_stages)] + ['classifier', ]
elif run_type == 1 or run_type == 2 or run_type == 4 or run_type == 5:
self.all_feat_names = ['block' + str(s + 1) for s in
range(3)] + ['Attention'] + ['block' + str(s + 1) for s in
range(3, self.num_stages)] + [
'classifier', ]
self.num_stages+=1
def _parse_out_keys_arg(self, out_feat_keys):
"""
:param out_feat_keys:
:return:
the lasy layer index from out_feat_keys
"""
# By default return the features of the last layer / module.
out_feat_keys = [self.all_feat_names[-1], ] if out_feat_keys is None else out_feat_keys
if len(out_feat_keys) == 0:
raise ValueError('Empty list of output feature keys.')
for f, key in enumerate(out_feat_keys):
if key not in self.all_feat_names:
raise ValueError(
'Feature with name {0} does not exist. Existing features: {1}.'.format(key, self.all_feat_names))
elif key in out_feat_keys[:f]:
raise ValueError('Duplicate output feature key: {0}.'.format(key))
# Find the highest output feature in `out_feat_keys
max_out_feat = max([self.all_feat_names.index(key) for key in out_feat_keys])
return out_feat_keys, max_out_feat
def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1]*(num_blocks-1)
layers = []
for stride in strides:
layers.append(block(self.in_planes, planes, stride))
self.in_planes = planes * block.expansion
return nn.Sequential(*layers)
def forward(self, x,out_feat_keys=None):
go_direct_flag = False
if out_feat_keys == None:
go_direct_flag = True
out_feat_keys, max_out_feat = self._parse_out_keys_arg(out_feat_keys)
out_feats = [None] * len(out_feat_keys)
go_attention_flag = False
feat = x
for f in range(max_out_feat + 1):
key = self.all_feat_names[f]
if key == 'Attention':
go_attention_flag = True
feat, attention = self._feature_blocks[f](feat)
elif key == 'classifier':
feat = F.avg_pool2d(feat, feat.size(1))
feat = feat.view(feat.size(0), -1)
feat = self.linear(feat)
else:
feat = self._feature_blocks[f](feat)
if key in out_feat_keys:
out_feats[out_feat_keys.index(key)] = feat
out_feats = out_feats[0] if len(out_feats) == 1 else out_feats
if go_direct_flag:
return out_feats
# here is an important output link to the classifier
if go_attention_flag:
return out_feats, attention
else:
return out_feats, None
def PreActResNet18():
return PreActResNet(PreActBlock, [2,2,2,2])
def PreActResNet34(num_classes,run_type):
return PreActResNet_WX(PreActBlock, [3,4,6,3],num_classes,run_type)
def PreActResNet34STL(num_classes,run_type):
return PreActResNet_STL(PreActBlock, [3,4,6,3],num_classes,run_type)
def PreActResNet50(num_classes):
#Please do not use this
#The paper "Learning to Learn from Noisy Labeled Data" used this backbone to compare with previous paper
#Backbone changed and also used pre-trained model to do this. Which is completely unfair
#Please do not use this to compare with them, they are completely unfair
return PreActResNet_WX(PreActBottleneck, [3,4,6,3],num_classes)
def PreActResNet101():
return PreActResNet(PreActBottleneck, [3,4,23,3])
def PreActResNet152(num_classes,run_type):
#we plan to use this for cifar10 and cifar100 large model
return PreActResNet_WX(PreActBlock, [3,8,36,3],num_classes,run_type)
| 42.778098
| 134
| 0.604823
| 2,006
| 14,844
| 4.262712
| 0.115155
| 0.037656
| 0.048883
| 0.033329
| 0.829611
| 0.819319
| 0.795229
| 0.783417
| 0.783417
| 0.768565
| 0
| 0.032854
| 0.278227
| 14,844
| 347
| 135
| 42.778098
| 0.76526
| 0.102196
| 0
| 0.795455
| 0
| 0
| 0.040484
| 0
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| 0
| 0
| 0
| 0
| 1
| 0.079545
| false
| 0
| 0.015152
| 0.022727
| 0.19697
| 0
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| 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
|
a8d8c0704e0fd75b19d05619de23686aef274856
| 69,427
|
py
|
Python
|
tests/test_cli.py
|
ofir-amir/skipper
|
092e6f86ecd95059367a4760f04cf536a786173b
|
[
"Apache-2.0"
] | null | null | null |
tests/test_cli.py
|
ofir-amir/skipper
|
092e6f86ecd95059367a4760f04cf536a786173b
|
[
"Apache-2.0"
] | null | null | null |
tests/test_cli.py
|
ofir-amir/skipper
|
092e6f86ecd95059367a4760f04cf536a786173b
|
[
"Apache-2.0"
] | null | null | null |
import mock
import os
from six.moves import http_client
import unittest
import click
import six
from click import testing
from skipper import cli
from skipper import config
REGISTRY = 'registry.io:5000'
IMAGE = 'image'
TAG = '1234567'
FQDN_IMAGE = REGISTRY + '/' + IMAGE + ':' + TAG
BUILD_CONTAINER_IMAGE = 'build-container-image'
BUILD_CONTAINER_TAG = 'build-container-tag'
BUILD_CONTAINER_FQDN_IMAGE = REGISTRY + '/' + BUILD_CONTAINER_IMAGE + ':' + BUILD_CONTAINER_TAG
ENV = ["KEY1=VAL1", "KEY2=VAL2"]
SKIPPER_CONF_CONTAINER_CONTEXT = '/some/context'
SKIPPER_CONF_BUILD_CONTAINER_IMAGE = 'skipper-conf-build-container-image'
SKIPPER_CONF_BUILD_CONTAINER_TAG = 'skipper-conf-build-container-tag'
SKIPPER_CONF_BUILD_CONTAINER_FQDN_IMAGE = REGISTRY + '/' + SKIPPER_CONF_BUILD_CONTAINER_IMAGE + ':' + SKIPPER_CONF_BUILD_CONTAINER_TAG
SKIPPER_CONF_MAKEFILE = 'Makefile.skipper'
SKIPPER_CONF = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
}
}
CONFIG_ENV = {
"KEY2": "NOT_VAL2",
"KEY3": "VAL3",
"KEY4": "$VAL4",
"KEY5": "$$VAL5"
}
CONFIG_ENV_EVALUATION = {
"KEY2": "NOT_VAL2",
"KEY3": "VAL3",
"KEY4": "val4-evaluation",
"KEY5": "$VAL5"
}
SKIPPER_CONF_WITH_ENV = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'env': CONFIG_ENV
}
SKIPPER_CONF_WITH_ENV_LIST = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'env': ['key1=value1', 'key2']
}
SKIPPER_CONF_WITH_ENV_WRONG_TYPE = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'env': 'wrong-env-type',
}
SKIPPER_CONF_WITH_CONTAINERS = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'containers': {
'image1': 'app1/Dockerfile',
'image2': 'app2/Dockerfile',
}
}
SKIPPER_CONF_WITH_VOLUMES = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'volumes': [
'volume1',
'volume2',
]
}
SKIPPER_CONF_WITH_WORKDIR = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'workdir': 'test-workdir'
}
SKIPPER_CONF_WITH_GIT_REV = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': 'git:revision',
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
}
SKIPPER_CONF_WITH_CONTEXT = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'build-container-tag': SKIPPER_CONF_BUILD_CONTAINER_TAG,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'container-context': SKIPPER_CONF_CONTAINER_CONTEXT
}
SKIPPER_CONF_WITH_CONTEXT_NO_TAG = {
'registry': REGISTRY,
'build-container-image': SKIPPER_CONF_BUILD_CONTAINER_IMAGE,
'make': {
'makefile': SKIPPER_CONF_MAKEFILE,
},
'container-context': SKIPPER_CONF_CONTAINER_CONTEXT
}
class TestCLI(unittest.TestCase):
def setUp(self):
self._runner = testing.CliRunner()
self.global_params = [
'--registry', REGISTRY,
'--build-container-image', BUILD_CONTAINER_IMAGE,
'--build-container-tag', BUILD_CONTAINER_TAG
]
def test_cli_without_params(self):
result = self._invoke_cli()
self.assertEqual(result.exit_code, 0)
def test_cli_help(self):
result = self._invoke_cli(global_params=['--help'])
self.assertEqual(result.exit_code, 0)
def test_subcommand_help(self):
for subcmd in ('build', 'push', 'make', 'run'):
result = self._invoke_cli(
global_params=None,
subcmd=subcmd,
subcmd_params=['--help']
)
self.assertEqual(result.exit_code, 0)
def test_subcommand_without_global_params(self):
subcmd_params_map = {
'push': [IMAGE],
'run': ['ls' '-l'],
'make': ['-f', 'Makefile', 'all'],
}
for subcmd, subcmd_params in six.iteritems(subcmd_params_map):
result = self._invoke_cli(
global_params=None,
subcmd=subcmd,
subcmd_params=subcmd_params,
)
self.assertIsInstance(result.exception, click.BadParameter)
self.assertEqual(result.exit_code, -1)
@mock.patch('skipper.runner.run', autospec=True)
def test_subcommand_without_subcommand_params(self, skipper_runner_run_mock):
for subcmd in ('build', 'push', 'run', 'make'):
result = self._invoke_cli(self.global_params, subcmd)
self.assertNotEqual(result.exit_code, 0)
self.assertFalse(skipper_runner_run_mock.called)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1',
'image2': '/home/user/work/project/Dockerfile.image2'}))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_build_existing_image(self, skipper_runner_run_mock):
build_params = ['image1']
self._invoke_cli(
global_params=self.global_params,
subcmd='build',
subcmd_params=build_params
)
expected_command = [
'docker',
'build',
'--network=host',
'-f', '/home/user/work/project/Dockerfile.image1',
'-t', 'image1:1234567',
'/home/user/work/project'
]
skipper_runner_run_mock.assert_called_once_with(expected_command)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1'}))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_build_existing_image_with_context(self, skipper_runner_run_mock):
build_params = ['image1',
'--container-context',
'/home/user/work/project']
self._invoke_cli(
global_params=self.global_params,
subcmd='build',
subcmd_params=build_params
)
expected_command = [
'docker',
'build',
'--network=host',
'-f', '/home/user/work/project/Dockerfile.image1',
'-t', 'image1:1234567',
'/home/user/work/project'
]
skipper_runner_run_mock.assert_called_once_with(expected_command)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1',
'image2': '/home/user/work/project/Dockerfile.image2'}))
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_CONTEXT))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_build_with_context_from_config_file(self, skipper_runner_run_mock):
build_params = ['image1']
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='build',
subcmd_params=build_params
)
expected_command = [
'docker',
'build',
'--network=host',
'-f', '/home/user/work/project/Dockerfile.image1',
'-t', 'image1:1234567',
SKIPPER_CONF_CONTAINER_CONTEXT
]
skipper_runner_run_mock.assert_called_once_with(expected_command)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_CONTEXT_NO_TAG))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value=''))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_make_without_build_container_tag_with_context(self, skipper_runner_run_mock):
global_params = self.global_params[:-2]
makefile = 'Makefile'
target = 'all'
make_params = ['-f', makefile, target]
self._invoke_cli(
defaults=config.load_defaults(),
global_params=global_params,
subcmd='make',
subcmd_params=make_params
)
expected_commands = [
mock.call(['docker', 'build', '--network=host', '-t', 'build-container-image', '-f', 'Dockerfile.build-container-image',
SKIPPER_CONF_CONTAINER_CONTEXT]),
mock.call(['make'] + make_params, fqdn_image='build-container-image', environment=[],
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=False))
@mock.patch('skipper.runner.run', autospec=True)
def test_build_non_existing_image(self, skipper_runner_run_mock):
build_params = ['my_image']
self._invoke_cli(
global_params=self.global_params,
subcmd='build',
subcmd_params=build_params
)
self.assertFalse(skipper_runner_run_mock.called)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1',
'image2': '/home/user/work/project/Dockerfile.image2'}))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_build_multiple_images(self, skipper_runner_run_mock):
skipper_runner_run_mock.return_value = 0
build_params = ['image1', 'image2']
self._invoke_cli(
global_params=self.global_params,
subcmd='build',
subcmd_params=build_params
)
expected_commands = [
mock.call(['docker', 'build', '--network=host', '-f', '/home/user/work/project/Dockerfile.image1', '-t', 'image1:1234567',
'/home/user/work/project']),
mock.call(['docker', 'build', '--network=host', '-f', '/home/user/work/project/Dockerfile.image2', '-t', 'image2:1234567',
'/home/user/work/project']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands, any_order=True)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1'}))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('skipper.runner.run', autospec=True, return_value=1)
def test_build_multiple_images_with_invalid_image(self, skipper_runner_run_mock):
build_params = ['image1', 'image2']
self._invoke_cli(
global_params=self.global_params,
subcmd='build',
subcmd_params=build_params
)
expected_command = [
'docker',
'build',
'--network=host',
'-f', '/home/user/work/project/Dockerfile.image1',
'-t', 'image1:1234567',
'/home/user/work/project'
]
skipper_runner_run_mock.assert_called_once_with(expected_command)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1',
'image2': '/home/user/work/project/Dockerfile.image2'}))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('os.path.exists', autospec=True)
@mock.patch('skipper.runner.run', autospec=True, return_value=1)
def test_build_multiple_images_with_non_existing_dockerfile(self, skipper_runner_run_mock, os_path_exists_mock):
os_path_exists_mock.side_effect = lambda dockerfile: 'image1' in dockerfile
build_params = ['image1', 'image2']
self._invoke_cli(
global_params=self.global_params,
subcmd='build',
subcmd_params=build_params
)
expected_command = [
'docker',
'build',
'--network=host',
'-f', '/home/user/work/project/Dockerfile.image1',
'-t', 'image1:1234567',
'/home/user/work/project'
]
skipper_runner_run_mock.assert_called_once_with(expected_command)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1',
'image2': '/home/user/work/project/Dockerfile.image2'}))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_build_all_images(self, skipper_runner_run_mock):
self._invoke_cli(
global_params=self.global_params,
subcmd='build',
)
expected_commands = [
mock.call(['docker', 'build', '--network=host', '-f', '/home/user/work/project/Dockerfile.image1', '-t', 'image1:1234567',
'/home/user/work/project']),
mock.call(['docker', 'build', '--network=host', '-f', '/home/user/work/project/Dockerfile.image2', '-t', 'image2:1234567',
'/home/user/work/project']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands, any_order=True)
@mock.patch('skipper.utils.get_images_from_dockerfiles', mock.MagicMock(autospec=True,
return_value={'image1': '/home/user/work/project/Dockerfile.image1',
'image2': '/home/user/work/project/Dockerfile.image2'}))
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_build_with_defaults_from_config_file(self, skipper_runner_run_mock):
build_params = ['image1']
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='build',
subcmd_params=build_params
)
expected_command = [
'docker',
'build',
'--network=host',
'-f', '/home/user/work/project/Dockerfile.image1',
'-t', 'image1:1234567',
'/home/user/work/project'
]
skipper_runner_run_mock.assert_called_once_with(expected_command)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.abspath', mock.MagicMock(autospec=True, return_value='/home/user/work/project/app1/Dockerfile'))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_CONTAINERS))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_build_with_defaults_from_config_file_including_containers(self, skipper_runner_run_mock):
build_params = ['image1']
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='build',
subcmd_params=build_params
)
expected_command = [
'docker',
'build',
'--network=host',
'-f', '/home/user/work/project/app1/Dockerfile',
'-t', 'image1:1234567',
'/home/user/work/project/app1'
]
skipper_runner_run_mock.assert_called_once_with(expected_command)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_push(self, skipper_runner_run_mock, requests_get_mock):
skipper_runner_run_mock.side_effect = [0, 0]
push_params = ['my_image']
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='push',
subcmd_params=push_params
)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'push', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'rmi', 'registry.io:5000/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_push_already_in_registry(self, skipper_runner_run_mock, requests_get_mock):
skipper_runner_run_mock.side_effect = [0, 0]
push_params = ['my_image']
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb', "1234567"]
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='push',
subcmd_params=push_params
)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'rmi', 'registry.io:5000/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_push_already_in_registry_with_force(self, skipper_runner_run_mock, requests_get_mock):
skipper_runner_run_mock.side_effect = [0, 0]
push_params = ['my_image', "--force"]
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='push',
subcmd_params=push_params
)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'push', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'rmi', 'registry.io:5000/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_push_fail(self, skipper_runner_run_mock, requests_get_mock):
skipper_runner_run_mock.side_effect = [0, 1]
push_params = ['my_image']
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
result = self._invoke_cli(
global_params=self.global_params,
subcmd='push',
subcmd_params=push_params
)
self.assertEqual(result.exit_code, 1)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'push', 'registry.io:5000/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('skipper.runner.run', autospec=True)
def test_push_tag_fail(self, skipper_runner_run_mock):
skipper_runner_run_mock.side_effect = [1]
push_params = ['my_image']
result = self._invoke_cli(
global_params=self.global_params,
subcmd='push',
subcmd_params=push_params
)
self.assertEqual(result.exit_code, 1)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_push_rmi_fail(self, skipper_runner_run_mock, requests_get_mock):
skipper_runner_run_mock.side_effect = [0, 0, 1]
push_params = ['my_image']
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
result = self._invoke_cli(
global_params=self.global_params,
subcmd='push',
subcmd_params=push_params
)
self.assertEqual(result.exit_code, 0)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'push', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'rmi', 'registry.io:5000/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_push_to_namespace(self, skipper_runner_run_mock, requests_get_mock):
skipper_runner_run_mock.side_effect = [0, 0]
push_params = ['--namespace', 'my_namespace', 'my_image']
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='push',
subcmd_params=push_params
)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_namespace/my_image:1234567']),
mock.call(['docker', 'push', 'registry.io:5000/my_namespace/my_image:1234567']),
mock.call(['docker', 'rmi', 'registry.io:5000/my_namespace/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF))
@mock.patch('skipper.git.get_hash', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_push_with_defaults_from_config_file(self, skipper_runner_run_mock, requests_get_mock):
skipper_runner_run_mock.side_effect = [0, 0]
push_params = ['my_image']
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='push',
subcmd_params=push_params
)
expected_commands = [
mock.call(['docker', 'tag', 'my_image:1234567', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'push', 'registry.io:5000/my_image:1234567']),
mock.call(['docker', 'rmi', 'registry.io:5000/my_image:1234567']),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('tabulate.tabulate', autospec=True)
@mock.patch('subprocess.check_output', autospec=True)
def test_images_with_single_local_results(self, subprocess_check_output_mock, tabulate_mock):
subprocess_check_output_mock.return_value = '{"name": "my_image", "tag": "1234567"}'
self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=[]
)
expected_command = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
'my_image'
]
subprocess_check_output_mock.assert_called_once_with(expected_command)
tabulate_mock.assert_called_once_with([['none', 'my_image', '1234567']], headers=['REGISTRY', 'IMAGE', 'TAG'], tablefmt='grid')
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.image1', 'Dockerfile.image2']))
@mock.patch('tabulate.tabulate', autospec=True)
@mock.patch('subprocess.check_output', autospec=True)
def test_images_with_multiple_local_results(self, subprocess_check_output_mock, tabulate_mock):
subprocess_check_output_mock.side_effect = [
'{"name": "image1", "tag": "aaaaaaa"}\n',
'{"name": "image2", "tag": "bbbbbbb"}\n{"name": "image2", "tag": "ccccccc"}\n',
]
self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=[]
)
command_prefix = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
]
expected_check_output_calls = [
mock.call(command_prefix + ['image1']),
mock.call(command_prefix + ['image2']),
]
subprocess_check_output_mock.assert_has_calls(expected_check_output_calls, any_order=True)
expected_table = [
['none', 'image1', 'aaaaaaa'],
['none', 'image2', 'bbbbbbb'],
['none', 'image2', 'ccccccc'],
]
tabulate_mock.assert_called_once_with(expected_table, headers=['REGISTRY', 'IMAGE', 'TAG'], tablefmt='grid')
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('tabulate.tabulate', autospec=True)
@mock.patch('requests.get', autospec=True)
@mock.patch('subprocess.check_output', autospec=True)
def test_images_with_all_results(self, subprocess_check_output_mock, requests_get_mock, tabulate_mock):
subprocess_check_output_mock.return_value = '{"name": "my_image", "tag": "aaaaaaa"}'
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=['-r']
)
expected_command = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
'my_image',
]
subprocess_check_output_mock.assert_called_once_with(expected_command)
expected_url = 'https://%(registry)s/v2/my_image/tags/list' % dict(registry=REGISTRY)
requests_get_mock.assert_called_once_with(
url=expected_url,
verify=False
)
expected_images_results = [
['none', 'my_image', 'aaaaaaa'],
['registry.io:5000', 'my_image', 'latest'],
['registry.io:5000', 'my_image', 'aaaaaaa'],
['registry.io:5000', 'my_image', 'bbbbbbb']
]
tabulate_mock.assert_called_once_with(expected_images_results, headers=['REGISTRY', 'IMAGE', 'TAG'], tablefmt='grid')
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('tabulate.tabulate', autospec=True)
@mock.patch('requests.get', autospec=True)
@mock.patch('subprocess.check_output', autospec=True, return_value='')
def test_images_with_remote_results_only(self, subprocess_check_output_mock, requests_get_mock, tabulate_mock):
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=['-r']
)
expected_command = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
'my_image',
]
subprocess_check_output_mock.assert_called_once_with(expected_command)
expected_url = 'https://%(registry)s/v2/my_image/tags/list' % dict(registry=REGISTRY)
requests_get_mock.assert_called_once_with(
url=expected_url,
verify=False
)
expected_images_results = [
['registry.io:5000', 'my_image', 'latest'],
['registry.io:5000', 'my_image', 'aaaaaaa'],
['registry.io:5000', 'my_image', 'bbbbbbb']
]
tabulate_mock.assert_called_once_with(expected_images_results, headers=['REGISTRY', 'IMAGE', 'TAG'], tablefmt='grid')
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('tabulate.tabulate', autospec=True)
@mock.patch('requests.get', autospec=True)
@mock.patch('subprocess.check_output', autospec=True, return_value='')
def test_images_with_missing_remote_results(self, subprocess_check_output_mock, requests_get_mock, tabulate_mock):
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.ok = False
requests_response_mock.json.return_value = {
u'errors': [{u'message': u'repository name not known to registry', u'code': u'NAME_UNKNOWN', u'detail': {u'name': u'my_image'}}]
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=['-r']
)
expected_command = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
'my_image',
]
subprocess_check_output_mock.assert_called_once_with(expected_command)
expected_url = 'https://%(registry)s/v2/my_image/tags/list' % dict(registry=REGISTRY)
requests_get_mock.assert_called_once_with(
url=expected_url,
verify=False
)
expected_images_results = []
tabulate_mock.assert_called_once_with(expected_images_results, headers=['REGISTRY', 'IMAGE', 'TAG'], tablefmt='grid')
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('tabulate.tabulate', autospec=True)
@mock.patch('requests.get', autospec=True)
@mock.patch('subprocess.check_output', autospec=True)
def test_images_with_local_result_and_missing_remote_results(self, subprocess_check_output_mock, requests_get_mock, tabulate_mock):
subprocess_check_output_mock.return_value = '{"name": "my_image", "tag": "aaaaaaa"}'
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.ok = False
requests_response_mock.json.return_value = {
u'errors': [{u'message': u'repository name not known to registry', u'code': u'NAME_UNKNOWN', u'detail': {u'name': u'my_image'}}]
}
requests_get_mock.return_value = requests_response_mock
self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=['-r']
)
expected_command = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
'my_image',
]
subprocess_check_output_mock.assert_called_once_with(expected_command)
expected_url = 'https://%(registry)s/v2/my_image/tags/list' % dict(registry=REGISTRY)
requests_get_mock.assert_called_once_with(
url=expected_url,
verify=False
)
expected_images_results = [
['none', 'my_image', 'aaaaaaa'],
]
tabulate_mock.assert_called_once_with(expected_images_results, headers=['REGISTRY', 'IMAGE', 'TAG'], tablefmt='grid')
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('tabulate.tabulate', mock.MagicMock(autospec=True))
@mock.patch('requests.get', autospec=True)
@mock.patch('subprocess.check_output', autospec=True, return_value='')
def test_images_with_with_remote_error(self, subprocess_check_output_mock, requests_get_mock):
with mock.patch('requests.Response', autospec=True) as requests_response_class_mock:
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.ok = False
requests_response_mock.json.return_value = {
u'errors': [{u'message': u'repository name not known to registry', u'code': u'UNKNOWN_ERROR', u'detail': {u'name': u'my_image'}}]
}
requests_get_mock.return_value = requests_response_mock
result = self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=['-r']
)
expected_command = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
'my_image',
]
subprocess_check_output_mock.assert_called_once_with(expected_command)
expected_url = 'https://%(registry)s/v2/my_image/tags/list' % dict(registry=REGISTRY)
requests_get_mock.assert_called_once_with(
url=expected_url,
verify=False
)
self.assertIsInstance(result.exception, click.exceptions.ClickException)
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('tabulate.tabulate', autospec=True)
@mock.patch('subprocess.check_output', autospec=True, return_value='')
def test_images_without_local_results(self, subprocess_check_output_mock, tabulate_mock):
self._invoke_cli(
global_params=self.global_params,
subcmd='images',
subcmd_params=[]
)
expected_command = [
'docker',
'images',
'--format', '{"name": "{{.Repository}}", "tag": "{{.Tag}}"}',
'my_image',
]
subprocess_check_output_mock.assert_called_once_with(expected_command)
tabulate_mock.assert_called_once_with([], headers=['REGISTRY', 'IMAGE', 'TAG'], tablefmt='grid')
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.my_image']))
@mock.patch('subprocess.check_call', autospec=True)
def test_rmi_local(self, subprocess_check_call_mock):
self._invoke_cli(
global_params=self.global_params,
subcmd='rmi',
subcmd_params=['my_image', '1234567']
)
expected_command = [
'docker',
'rmi',
'my_image:1234567'
]
subprocess_check_call_mock.assert_called_once_with(expected_command)
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.' + IMAGE]))
@mock.patch('requests.delete', autospec=True)
@mock.patch('requests.get', autospec=True)
def test_rmi_remote(self, requests_get_mock, requests_delete_mock):
requests_get_mock.side_effect = [mock.Mock(headers={'Docker-Content-Digest': 'digest'})]
requests_delete_mock.side_effect = [mock.Mock(ok=True)]
self._invoke_cli(
global_params=self.global_params,
subcmd='rmi',
subcmd_params=['-r', IMAGE, TAG]
)
url = 'https://%(registry)s/v2/%(image)s/manifests/%(reference)s' % dict(registry=REGISTRY, image=IMAGE, reference=TAG)
headers = {"Accept": "application/vnd.docker.distribution.manifest.v2+json"}
requests_get_mock.assert_called_once_with(url=url, headers=headers, verify=False)
url = 'https://%(registry)s/v2/%(image)s/manifests/%(reference)s' % dict(registry=REGISTRY, image=IMAGE, reference='digest')
requests_delete_mock.assert_called_once_with(url=url, verify=False)
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.' + IMAGE]))
@mock.patch('requests.delete', autospec=True)
@mock.patch('requests.get', autospec=True)
def test_rmi_remote_fail(self, requests_get_mock, requests_delete_mock):
requests_get_mock.side_effect = [mock.Mock(headers={'Docker-Content-Digest': 'digest'})]
requests_delete_mock.side_effect = [mock.Mock(ok=False)]
result = self._invoke_cli(
global_params=self.global_params,
subcmd='rmi',
subcmd_params=['-r', IMAGE, TAG]
)
self.assertIsInstance(result.exception, Exception)
url = 'https://%(registry)s/v2/%(image)s/manifests/%(reference)s' % dict(registry=REGISTRY, image=IMAGE, reference=TAG)
headers = {"Accept": "application/vnd.docker.distribution.manifest.v2+json"}
requests_get_mock.assert_called_once_with(url=url, headers=headers, verify=False)
url = 'https://%(registry)s/v2/%(image)s/manifests/%(reference)s' % dict(registry=REGISTRY, image=IMAGE, reference='digest')
requests_delete_mock.assert_called_once_with(url=url, verify=False)
@mock.patch('glob.glob', mock.MagicMock(autospec=True, return_value=['Dockerfile.' + IMAGE]))
def test_validate_project_image(self):
result = self._invoke_cli(
global_params=self.global_params,
subcmd='rmi',
subcmd_params=['-r', 'non-project-image', TAG]
)
self.assertIsInstance(result.exception, click.BadParameter)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_existing_local_build_container(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = command
self._invoke_cli(
global_params=self.global_params,
subcmd='run',
subcmd_params=run_params
)
expected_image_name = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_image_name, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value=''))
@mock.patch('requests.get', autospec=True)
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_existing_remote_build_container(self, skipper_runner_run_mock, requests_get_mock):
requests_response_class_mock = mock.MagicMock(spec='requests.Response')
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb', 'build-container-tag']
}
requests_response_mock.status_code = http_client.OK
requests_get_mock.return_value = requests_response_mock
command = ['ls', '-l']
run_params = command
self._invoke_cli(
global_params=self.global_params,
subcmd='run',
subcmd_params=run_params
)
expected_image_name = 'registry.io:5000/build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_image_name, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value=''))
@mock.patch('skipper.runner.run', mock.MagicMock(autospec=True))
@mock.patch('requests.get', autospec=True)
def test_run_with_non_existing_build_container(self, requests_get_mock):
requests_response_class_mock = mock.MagicMock(spec='requests.Response')
requests_response_mock = requests_response_class_mock.return_value
requests_response_mock.json.return_value = {
'name': 'my_image',
'tags': ['latest', 'aaaaaaa', 'bbbbbbb']
}
requests_get_mock.return_value = requests_response_mock
command = ['ls', '-l']
run_params = command
ret = self._invoke_cli(
global_params=self.global_params,
subcmd='run',
subcmd_params=run_params
)
self.assertIsInstance(ret.exception, click.exceptions.ClickException)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_defaults_from_config_file(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_ENV))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_defaults_and_env_from_config_file(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = command
os.environ['VAL4'] = "val4-evaluation"
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
env = ["%s=%s" % (key, value) for key, value in six.iteritems(CONFIG_ENV_EVALUATION)]
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=env,
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_ENV))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_env_overriding_config_file(self, skipper_runner_run_mock):
os.environ['VAL4'] = "val4-evaluation"
command = ['ls', '-l']
run_params = ['-e', ENV[0], '-e', ENV[1]] + command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
env = ["%s=%s" % (key, value) for key, value in six.iteritems(CONFIG_ENV_EVALUATION)] + ENV
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=env,
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('os.environ', {})
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_ENV_LIST))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_env_list(self, skipper_runner_run_mock):
os.environ['VAL4'] = "val4-evaluation"
command = ['ls', '-l']
run_params = ['-e', ENV[0], '-e', ENV[1]] + command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
env = ['key1=value1'] + ENV
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=env,
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('os.environ', {'key2': 'value2'})
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_ENV_LIST))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_env_list_get_from_env(self, skipper_runner_run_mock):
os.environ['VAL4'] = "val4-evaluation"
command = ['ls', '-l']
run_params = ['-e', ENV[0], '-e', ENV[1]] + command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
env = ['key1=value1', 'key2=value2'] + ENV
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=env,
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_ENV_WRONG_TYPE))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_env_wrong_type(self, skipper_runner_run_mock):
os.environ['VAL4'] = "val4-evaluation"
command = ['ls', '-l']
run_params = ['-e', ENV[0], '-e', ENV[1]] + command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
self.assertEqual(len(skipper_runner_run_mock.mock_calls), 0)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_env(self, skipper_runner_run_mock):
command = ['ls', '-l']
os.environ['VAL4'] = "val4-evaluation"
run_params = ['-e', ENV[0], '-e', ENV[1]] + command
self._invoke_cli(
global_params=self.global_params,
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=ENV,
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_interactive_from_environment(self, skipper_runner_run_mock):
os.environ['SKIPPER_INTERACTIVE'] = 'True'
command = ['ls', '-l']
run_params = command
self._invoke_cli(
global_params=self.global_params,
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=True, name=None, net='host', volumes=None, workdir=None, use_cache=False)
del os.environ['SKIPPER_INTERACTIVE']
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_non_interactive_from_environment(self, skipper_runner_run_mock):
os.environ['SKIPPER_INTERACTIVE'] = 'False'
command = ['ls', '-l']
run_params = command
self._invoke_cli(
global_params=self.global_params,
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
del os.environ['SKIPPER_INTERACTIVE']
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_non_interactive(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = ['--interactive'] + command
self._invoke_cli(
global_params=self.global_params,
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=True, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value=''))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_run_without_build_container_tag(self, skipper_runner_run_mock):
global_params = self.global_params[:-2]
command = ['ls', '-l']
run_params = command
self._invoke_cli(
global_params=global_params,
subcmd='run',
subcmd_params=run_params
)
expected_commands = [
mock.call(['docker', 'build', '--network=host', '-t', 'build-container-image', '-f', 'Dockerfile.build-container-image', '.']),
mock.call(command, fqdn_image='build-container-image', environment=[],
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_non_default_net(self, skipper_runner_run_mock):
global_params = self.global_params
global_params += ['--build-container-net', 'non-default-net']
command = ['ls', '-l']
run_params = command
self._invoke_cli(
global_params=global_params,
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='non-default-net', volumes=None, workdir=None,
use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_VOLUMES))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_defaults_from_config_file_including_volumes(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host',
volumes=['volume1', 'volume2'], workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_WORKDIR))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_defaults_from_config_file_including_workdir(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir='test-workdir', use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_GIT_REV))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.git.uncommitted_changes', mock.MagicMock(return_value=True))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_config_including_git_revision_with_uncommitted_changes(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'skipper-conf-build-container-image:1234567'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF_WITH_GIT_REV))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.git.uncommitted_changes', mock.MagicMock(return_value=False))
@mock.patch('skipper.runner.run', autospec=True)
def test_run_with_config_including_git_revision_without_uncommitted_changes(self, skipper_runner_run_mock):
command = ['ls', '-l']
run_params = command
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='run',
subcmd_params=run_params
)
expected_fqdn_image = 'skipper-conf-build-container-image:1234567'
skipper_runner_run_mock.assert_called_once_with(command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_make(self, skipper_runner_run_mock):
makefile = 'Makefile'
target = 'all'
make_params = ['-f', makefile, target]
self._invoke_cli(
global_params=self.global_params,
subcmd='make',
subcmd_params=make_params
)
expected_command = ['make', '-f', makefile, target]
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(expected_command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_make_with_default_params(self, skipper_runner_run_mock):
self._invoke_cli(
global_params=self.global_params,
subcmd='make',
)
expected_command = ['make', '-f', "Makefile"]
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(expected_command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_make_with_additional_make_params(self, skipper_runner_run_mock):
target = 'all'
make_params = ['-j', '4', target, 'OS=linux']
self._invoke_cli(
global_params=self.global_params,
subcmd='make',
subcmd_params=make_params
)
expected_command = ['make', '-f', 'Makefile', '-j', '4', target, 'OS=linux']
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(expected_command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('__builtin__.open', mock.MagicMock(create=True))
@mock.patch('os.path.exists', mock.MagicMock(autospec=True, return_value=True))
@mock.patch('yaml.load', mock.MagicMock(autospec=True, return_value=SKIPPER_CONF))
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_make_with_defaults_from_config_file(self, skipper_runner_run_mock):
makefile = 'Makefile'
target = 'all'
make_params = ['-f', makefile, target]
self._invoke_cli(
defaults=config.load_defaults(),
subcmd='make',
subcmd_params=make_params
)
expected_command = ['make', '-f', makefile, target]
expected_fqdn_image = 'skipper-conf-build-container-image:skipper-conf-build-container-tag'
skipper_runner_run_mock.assert_called_once_with(expected_command, fqdn_image=expected_fqdn_image, environment=[],
interactive=False, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value=''))
@mock.patch('skipper.runner.run', autospec=True, return_value=0)
def test_make_without_build_container_tag(self, skipper_runner_run_mock):
global_params = self.global_params[:-2]
makefile = 'Makefile'
target = 'all'
make_params = ['-f', makefile, target]
self._invoke_cli(
global_params=global_params,
subcmd='make',
subcmd_params=make_params
)
expected_commands = [
mock.call(['docker', 'build', '--network=host', '-t', 'build-container-image', '-f', 'Dockerfile.build-container-image', '.']),
mock.call(['make'] + make_params, fqdn_image='build-container-image', environment=[],
interactive=False, name=None, net='host', volumes=None, workdir=None, use_cache=False),
]
skipper_runner_run_mock.assert_has_calls(expected_commands)
@mock.patch('subprocess.check_output', mock.MagicMock(autospec=True, return_value='1234567\n'))
@mock.patch('skipper.runner.run', autospec=True)
def test_shell(self, skipper_runner_run_mock):
self._invoke_cli(
global_params=self.global_params,
subcmd='shell',
)
expected_fqdn_image = 'build-container-image:build-container-tag'
skipper_runner_run_mock.assert_called_once_with(['bash'], fqdn_image=expected_fqdn_image, environment=[],
interactive=True, name=None, net='host', volumes=None,
workdir=None, use_cache=False)
@mock.patch('click.echo', autospec=True)
@mock.patch('skipper.cli.get_distribution', autospec=True)
def test_version(self, get_dist_mock, echo_mock):
expected_version = '1.2.3'
get_dist_mock.return_value = mock.MagicMock()
get_dist_mock.return_value.version = expected_version
self._invoke_cli(
subcmd='version',
)
echo_mock.assert_called_once_with(expected_version)
def _invoke_cli(self, defaults=None, global_params=None, subcmd=None, subcmd_params=None):
self.assertFalse(subcmd is None and subcmd_params is not None, 'No sub-command was provided!')
defaults = defaults or {}
cli_params = []
if global_params is not None:
cli_params += global_params
if subcmd is not None:
cli_params += [subcmd]
if subcmd_params is not None:
cli_params += subcmd_params
return self._runner.invoke(cli.cli, cli_params, default_map=defaults, obj={}, standalone_mode=False)
| 48.686536
| 145
| 0.644922
| 7,978
| 69,427
| 5.306593
| 0.031462
| 0.046556
| 0.053666
| 0.065193
| 0.938067
| 0.923517
| 0.907289
| 0.900463
| 0.895479
| 0.886692
| 0
| 0.016964
| 0.224812
| 69,427
| 1,425
| 146
| 48.720702
| 0.769672
| 0
| 0
| 0.705972
| 0
| 0.000766
| 0.196048
| 0.072854
| 0
| 0
| 0
| 0
| 0.064319
| 1
| 0.049005
| false
| 0
| 0.006891
| 0
| 0.057427
| 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
|
7666af7d4b2046a27b53244cac5b4a2e02f09b2b
| 108
|
py
|
Python
|
py/torch_tensorrt/ts/__init__.py
|
narendasan/TRTorch
|
badcc696891596925def4a260a8f58ade24f2296
|
[
"BSD-3-Clause"
] | null | null | null |
py/torch_tensorrt/ts/__init__.py
|
narendasan/TRTorch
|
badcc696891596925def4a260a8f58ade24f2296
|
[
"BSD-3-Clause"
] | null | null | null |
py/torch_tensorrt/ts/__init__.py
|
narendasan/TRTorch
|
badcc696891596925def4a260a8f58ade24f2296
|
[
"BSD-3-Clause"
] | null | null | null |
from torch_tensorrt.ts._compiler import *
from torch_tensorrt.ts._compile_spec import TensorRTCompileSpec
| 21.6
| 63
| 0.861111
| 14
| 108
| 6.285714
| 0.642857
| 0.204545
| 0.386364
| 0.431818
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0.092593
| 108
| 4
| 64
| 27
| 0.897959
| 0
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| true
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| null | 1
| 1
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| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 8
|
4f24aa3c144177018571e70d2e67bc50506b8c99
| 603,589
|
py
|
Python
|
3algo/client6.py
|
allengrr/deadlock_project
|
933878077c45a7df04daa087407bb2620c064617
|
[
"MIT"
] | null | null | null |
3algo/client6.py
|
allengrr/deadlock_project
|
933878077c45a7df04daa087407bb2620c064617
|
[
"MIT"
] | null | null | null |
3algo/client6.py
|
allengrr/deadlock_project
|
933878077c45a7df04daa087407bb2620c064617
|
[
"MIT"
] | 1
|
2021-03-21T17:54:26.000Z
|
2021-03-21T17:54:26.000Z
|
record4 = [[({'t2.103.120.0': {'wcet': 1, 'period': 5, 'deadline': 4}, 't3.103.120.0': {'wcet': 2, 'period': 10, 'deadline': 8}}, {'t2.103.120.0': [0.699, 5.0], 't3.103.120.0': [0.606, 5.0]}), 'newmec-3'], [({'t5.102.120.1': {'wcet': 3, 'period': 15, 'deadline': 12}, 't4.102.120.1': {'wcet': 1, 'period': 10, 'deadline': 9}, 't2.102.120.1': {'wcet': 1, 'period': 5, 'deadline': 4}}, {'t5.102.120.1': [0.467, 5.0], 't4.102.120.1': [0.465, 10.0], 't2.102.120.1': [0.41, 5.0]}), 'newmec-2'], [({'t5.102.120.2': {'wcet': 3, 'period': 15, 'deadline': 12}, 't4.102.120.2': {'wcet': 1, 'period': 10, 'deadline': 9}, 't1.102.120.2': {'wcet': 3, 'period': 20, 'deadline': 15}}, {'t5.102.120.2': [0.613, 5.0], 't4.102.120.2': [0.52, 10.0], 't1.102.120.2': [0.685, 6.667]}), 'newmec-2'], [({'t5.101.120.3': {'wcet': 3, 'period': 15, 'deadline': 12}, 't2.101.120.3': {'wcet': 1, 'period': 5, 'deadline': 4}, 't3.101.120.3': {'wcet': 2, 'period': 10, 'deadline': 8}}, {'t5.101.120.3': [0.423, 5.0], 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[0.619, 5.0], 't4.102.120.588': [0.465, 10.0]}), 'newmec-2'], [({'t3.102.120.589': {'wcet': 2, 'period': 10, 'deadline': 8}, 't5.102.120.589': {'wcet': 3, 'period': 15, 'deadline': 12}, 't4.102.120.589': {'wcet': 1, 'period': 10, 'deadline': 9}}, {'t3.102.120.589': [0.663, 5.0], 't5.102.120.589': [0.655, 5.0], 't4.102.120.589': [0.663, 10.0]}), 'newmec-2'], [({'t3.156.120.590': {'wcet': 2, 'period': 10, 'deadline': 8}, 't5.156.120.590': {'wcet': 3, 'period': 15, 'deadline': 12}, 't4.156.120.590': {'wcet': 1, 'period': 10, 'deadline': 9}}, {'t3.156.120.590': [0.769, 5.0], 't5.156.120.590': [0.408, 5.0], 't4.156.120.590': [0.672, 10.0]}), 'osboxes-0'], [({'t3.156.120.591': {'wcet': 2, 'period': 10, 'deadline': 8}, 't2.156.120.591': {'wcet': 1, 'period': 5, 'deadline': 4}, 't4.156.120.591': {'wcet': 1, 'period': 10, 'deadline': 9}}, {'t3.156.120.591': [0.543, 5.0], 't2.156.120.591': [0.669, 5.0], 't4.156.120.591': [0.444, 10.0]}), 'osboxes-0'], [({'t2.156.120.592': {'wcet': 1, 'period': 5, 'deadline': 4}, 't4.156.120.592': {'wcet': 1, 'period': 10, 'deadline': 9}}, {'t2.156.120.592': [0.466, 5.0], 't4.156.120.592': [0.412, 10.0]}), 'osboxes-0'], [({'t5.105.120.593': {'wcet': 3, 'period': 15, 'deadline': 12}, 't2.105.120.593': {'wcet': 1, 'period': 5, 'deadline': 4}}, {'t5.105.120.593': [0.744, 5.0], 't2.105.120.593': [0.451, 5.0]}), 'newmec-5'], [({'t5.101.120.594': {'wcet': 3, 'period': 15, 'deadline': 12}, 't3.101.120.594': {'wcet': 2, 'period': 10, 'deadline': 8}, 't2.101.120.594': {'wcet': 1, 'period': 5, 'deadline': 4}}, {'t5.101.120.594': [0.532, 5.0], 't3.101.120.594': [0.775, 5.0], 't2.101.120.594': [0.649, 5.0]}), 'newmec-1'], [({'t5.101.120.595': {'wcet': 3, 'period': 15, 'deadline': 12}, 't4.101.120.595': {'wcet': 1, 'period': 10, 'deadline': 9}, 't2.101.120.595': {'wcet': 1, 'period': 5, 'deadline': 4}}, {'t5.101.120.595': [0.596, 5.0], 't4.101.120.595': [0.513, 10.0], 't2.101.120.595': [0.556, 5.0]}), 'newmec-1'], [({'t4.105.120.596': {'wcet': 1, 'period': 10, 'deadline': 9}, 't1.105.120.596': {'wcet': 3, 'period': 20, 'deadline': 15}, 't2.105.120.596': {'wcet': 1, 'period': 5, 'deadline': 4}}, {'t4.105.120.596': [0.437, 10.0], 't1.105.120.596': [0.613, 6.667], 't2.105.120.596': [0.467, 5.0]}), 'newmec-5'], [({'t5.105.120.597': {'wcet': 3, 'period': 15, 'deadline': 12}, 't3.105.120.597': {'wcet': 2, 'period': 10, 'deadline': 8}, 't2.105.120.597': {'wcet': 1, 'period': 5, 'deadline': 4}}, {'t5.105.120.597': [0.691, 5.0], 't3.105.120.597': [0.529, 5.0], 't2.105.120.597': [0.415, 5.0]}), 'newmec-5'], [({'t2.103.120.598': {'wcet': 1, 'period': 5, 'deadline': 4}, 't5.103.120.598': {'wcet': 3, 'period': 15, 'deadline': 12}, 't3.103.120.598': {'wcet': 2, 'period': 10, 'deadline': 8}}, {'t2.103.120.598': [0.487, 5.0], 't5.103.120.598': [0.44, 5.0], 't3.103.120.598': [0.724, 5.0]}), 'newmec-3'], [({'t2.103.120.599': {'wcet': 1, 'period': 5, 'deadline': 4}, 't5.103.120.599': {'wcet': 3, 'period': 15, 'deadline': 12}}, {'t2.103.120.599': [0.627, 5.0], 't5.103.120.599': [0.407, 5.0]}), 'newmec-3']]
| 54,871.727273
| 152,862
| 0.529309
| 113,182
| 603,589
| 2.822755
| 0.007015
| 0.023751
| 0.090277
| 0.050256
| 0.931562
| 0.79446
| 0.776277
| 0.64675
| 0.614426
| 0.134538
| 0
| 0.340547
| 0.103753
| 603,589
| 10
| 152,863
| 60,358.9
| 0.250037
| 0
| 0
| 0
| 0
| 0
| 0.487656
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
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| 1
| 1
| 1
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| 0
| 0
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| 0
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| 1
| 1
| 1
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| null | 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
4f48af053e770f7b810943cc5ab9c6d7674af9b1
| 5,171
|
py
|
Python
|
test/cnnl/op_test/test_unsqueeze.py
|
Cambricon/catch
|
2625da389f25a67066d20fb6b0c38250ef98f8ab
|
[
"BSD-2-Clause"
] | 20
|
2022-03-01T11:40:51.000Z
|
2022-03-30T08:17:47.000Z
|
test/cnnl/op_test/test_unsqueeze.py
|
Cambricon/catch
|
2625da389f25a67066d20fb6b0c38250ef98f8ab
|
[
"BSD-2-Clause"
] | null | null | null |
test/cnnl/op_test/test_unsqueeze.py
|
Cambricon/catch
|
2625da389f25a67066d20fb6b0c38250ef98f8ab
|
[
"BSD-2-Clause"
] | null | null | null |
from __future__ import print_function
import sys
import os
import unittest
import logging
import copy
import torch
import torch_mlu.core.mlu_model as ct # pylint: disable=W0611
cur_dir = os.path.dirname(os.path.abspath(__file__))
sys.path.append(cur_dir + "/../../")
from common_utils import testinfo, TestCase # pylint: disable=C0413, C0411
logging.basicConfig(level=logging.DEBUG)
class TestUnsqueezeOp(TestCase):
#@unittest.skip("not test")
@testinfo()
def test_unsqueeze(self):
shape_list = [(2,3,4,5,6), (2, 5), (5, 4, 6), (12, 3, 22, 22)]
dtype_list = [(torch.float, 0), (torch.half, 3e-3)]
for in_shape in shape_list:
for dim in range(len(in_shape) + 1):
for data_type, err in dtype_list:
input_ = torch.randn(in_shape, dtype=torch.float)
output_cpu = torch.unsqueeze(input_, dim)
output_mlu = torch.unsqueeze(self.to_mlu_dtype(input_, data_type), dim)
self.assertTensorsEqual(output_cpu, output_mlu.cpu().float(), err, use_MSE=True)
#@unittest.skip("not test")
@testinfo()
def test_unsqueeze_channel_last(self):
shape_list = [(12, 3, 22, 22)]
dtype_list = [(torch.float, 0), (torch.half, 3e-3)]
for in_shape in shape_list:
for dim in range(len(in_shape) + 1):
for data_type, err in dtype_list:
input_ = torch.randn(in_shape).to(memory_format=torch.channels_last)
output_cpu = torch.unsqueeze(input_, dim)
output_mlu = torch.unsqueeze(self.to_mlu_dtype(input_, data_type), dim)
self.assertTensorsEqual(output_cpu, output_mlu.cpu().float(), err, use_MSE=True)
#@unittest.skip("not test")
@testinfo()
def test_unsqueeze_not_dense(self):
shape_list = [(2,3,4,5,6), (2, 5), (5, 4, 6), (12, 3, 22, 22)]
dtype_list = [(torch.float, 0), (torch.half, 3e-3)]
for in_shape in shape_list:
for dim in range(len(in_shape) + 1):
for data_type, err in dtype_list:
input_ = torch.randn(in_shape, dtype=torch.float)
output_cpu = torch.unsqueeze(input_[::2], dim)
output_mlu = torch.unsqueeze(self.to_mlu_dtype(input_, data_type)[::2], dim)
self.assertTensorsEqual(output_cpu, output_mlu.cpu().float(), err, use_MSE=True)
# @unittest.skip("not test")
@testinfo()
def test_unsqueeze_inplace(self):
shape_list = [(2,3,4,5,6), (2, 5), (5, 4, 6), (12, 3, 22, 22)]
dtype_list = [(torch.float, 0), (torch.half, 3e-3)]
for in_shape in shape_list:
for dim in range(len(in_shape) + 1):
for data_type, err in dtype_list:
input_ = torch.randn(in_shape, dtype=torch.float)
input_mlu = self.to_mlu_dtype(copy.deepcopy(input_), data_type)
input_mlu_ptr = input_mlu.data_ptr()
input_.unsqueeze_(dim)
input_mlu.unsqueeze_(dim)
input_mlu_ptr_2 = input_mlu.data_ptr()
self.assertEqual(input_mlu_ptr, input_mlu_ptr_2)
self.assertTensorsEqual(input_, input_mlu.cpu().float(), err, use_MSE=True)
# @unittest.skip("not test")
@testinfo()
def test_unsqueeze_inplace_channel_last(self):
shape_list = [(2,3,4,5), (12, 3, 22, 22)]
dtype_list = [(torch.float, 0), (torch.half, 3e-3)]
for in_shape in shape_list:
for dim in range(len(in_shape) + 1):
for data_type, err in dtype_list:
input_ = torch.randn(in_shape).to(memory_format=torch.channels_last)
input_mlu = self.to_mlu_dtype(copy.deepcopy(input_), data_type)
input_mlu_ptr = input_mlu.data_ptr()
input_.unsqueeze_(dim)
input_mlu.unsqueeze_(dim)
input_mlu_ptr_2 = input_mlu.data_ptr()
self.assertEqual(input_mlu_ptr, input_mlu_ptr_2)
self.assertTensorsEqual(input_, input_mlu.cpu().float(), err, use_MSE=True)
# @unittest.skip("not test")
@testinfo()
def test_unsqueeze_inplace_not_dense(self):
shape_list = [(2,3,4,5,6), (2, 5), (5, 4, 6), (12, 3, 22, 22)]
dtype_list = [(torch.float, 0), (torch.half, 3e-3)]
for in_shape in shape_list:
for dim in range(len(in_shape) + 1):
for data_type, err in dtype_list:
input_ = torch.randn(in_shape, dtype=torch.float)
input_mlu = self.to_mlu_dtype(copy.deepcopy(input_), data_type)
input_mlu_ptr = input_mlu.data_ptr()
input_[::2].unsqueeze_(dim)
input_mlu[::2].unsqueeze_(dim)
input_mlu_ptr_2 = input_mlu.data_ptr()
self.assertEqual(input_mlu_ptr, input_mlu_ptr_2)
self.assertTensorsEqual(input_, input_mlu.cpu().float(), err, use_MSE=True)
if __name__ == '__main__':
unittest.main()
| 46.169643
| 100
| 0.585187
| 697
| 5,171
| 4.047346
| 0.126255
| 0.076569
| 0.046792
| 0.040411
| 0.878057
| 0.857852
| 0.857852
| 0.851826
| 0.836583
| 0.836583
| 0
| 0.036036
| 0.291626
| 5,171
| 111
| 101
| 46.585586
| 0.734098
| 0.040418
| 0
| 0.709677
| 0
| 0
| 0.003028
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 1
| 0.064516
| false
| 0
| 0.096774
| 0
| 0.172043
| 0.010753
| 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
|
4f4a0f4d0b948632491d7fd9a41a11802b2ca334
| 224
|
py
|
Python
|
rfcn/symbols/__init__.py
|
necla-ml/Deformable-ConvNets-py3
|
15f14079aacb6e5ef042c5e3a079db1569294529
|
[
"MIT"
] | 1
|
2022-03-20T13:58:58.000Z
|
2022-03-20T13:58:58.000Z
|
rfcn/symbols/__init__.py
|
necla-ml/Deformable-ConvNets-py3
|
15f14079aacb6e5ef042c5e3a079db1569294529
|
[
"MIT"
] | null | null | null |
rfcn/symbols/__init__.py
|
necla-ml/Deformable-ConvNets-py3
|
15f14079aacb6e5ef042c5e3a079db1569294529
|
[
"MIT"
] | 1
|
2022-03-20T13:59:25.000Z
|
2022-03-20T13:59:25.000Z
|
from . import resnet_v1_101_rfcn # py3
from . import resnet_v1_101_rfcn_dcn # py3
from . import resnet_v1_101_rfcn_dcn_rpn # py3
from . import deform_conv_demo # py3
from . import deform_psroi_demo # py3
| 37.333333
| 47
| 0.732143
| 36
| 224
| 4.111111
| 0.361111
| 0.337838
| 0.351351
| 0.364865
| 0.587838
| 0.587838
| 0.418919
| 0.418919
| 0
| 0
| 0
| 0.097701
| 0.223214
| 224
| 5
| 48
| 44.8
| 0.752874
| 0.084821
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 7
|
4fa4ed9d7d85c67506afa605080446d05a855862
| 30,596
|
py
|
Python
|
tests/server/rest/auth_test.py
|
WIPACrepo/iceprod
|
83615da9b0e764bc2498ac588cc2e2b3f5277235
|
[
"MIT"
] | 2
|
2017-01-23T17:12:41.000Z
|
2019-01-14T13:38:17.000Z
|
tests/server/rest/auth_test.py
|
WIPACrepo/iceprod
|
83615da9b0e764bc2498ac588cc2e2b3f5277235
|
[
"MIT"
] | 242
|
2016-05-09T18:46:51.000Z
|
2022-03-31T22:02:29.000Z
|
tests/server/rest/auth_test.py
|
WIPACrepo/iceprod
|
83615da9b0e764bc2498ac588cc2e2b3f5277235
|
[
"MIT"
] | 2
|
2017-03-27T09:13:40.000Z
|
2019-01-27T10:55:30.000Z
|
"""
Test script for REST/auth
"""
import logging
logger = logging.getLogger('rest_auth_test')
import os
import sys
import time
import random
import shutil
import tempfile
import unittest
import subprocess
import json
from functools import partial
from unittest.mock import patch, MagicMock
from tests.util import unittest_reporter, glob_tests
import ldap3
import tornado.web
import tornado.ioloop
from tornado.httpclient import AsyncHTTPClient
from tornado.testing import AsyncTestCase
from rest_tools.server import Auth, RestServer
from iceprod.server.modules.rest_api import setup_rest
from . import RestTestCase
class rest_auth_test(RestTestCase):
def setUp(self):
config = {'rest':{'auth':{}}}
super(rest_auth_test,self).setUp(config=config)
@unittest_reporter(name='REST GET /roles')
def test_100_role(self):
client = AsyncHTTPClient()
r = yield client.fetch('http://localhost:%d/roles'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [])
@unittest_reporter(name='REST PUT /roles/<role_name>')
def test_110_role(self):
client = AsyncHTTPClient()
data = {
'name': 'foo'
}
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:%d/roles'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [{'name': 'foo'}])
@unittest_reporter(name='REST GET /roles/<role_name>')
def test_120_role(self):
client = AsyncHTTPClient()
data = {
'name': 'foo'
}
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'name': 'foo'})
@unittest_reporter(name='REST DELETE /roles/<role_name>')
def test_130_role(self):
client = AsyncHTTPClient()
data = {
'name': 'foo'
}
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'name': 'foo'})
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
method='DELETE',
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
with self.assertRaises(Exception):
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
headers={'Authorization': 'bearer '+self.token})
r = yield client.fetch('http://localhost:%d/roles'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [])
@unittest_reporter(name='REST bad access to PUT /roles/<role_name>')
def test_140_role(self):
client = AsyncHTTPClient()
data = {
'name': 'foo'
}
user_token = Auth('secret').create_token('foo', type='user', payload={'role':'user'})
with self.assertRaises(Exception):
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+user_token})
@unittest_reporter(name='REST GET /groups')
def test_200_group(self):
client = AsyncHTTPClient()
r = yield client.fetch('http://localhost:%d/groups'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [])
@unittest_reporter(name='REST PUT /groups/<group_name>')
def test_210_group(self):
client = AsyncHTTPClient()
data = {
'name': 'foo/bar'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:%d/groups'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [{'name': 'foo/bar'}])
@unittest_reporter(name='REST GET /groups/<group_name>')
def test_220_group(self):
client = AsyncHTTPClient()
data = {
'name': 'foo/bar'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'name': 'foo/bar'})
@unittest_reporter(name='REST DELETE /groups/<group_id>')
def test_230_group(self):
client = AsyncHTTPClient()
data = {
'name': 'foo/bar'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'name': 'foo/bar'})
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
method='DELETE',
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
with self.assertRaises(Exception):
yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
headers={'Authorization': 'bearer '+self.token})
r = yield client.fetch('http://localhost:%d/groups'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [])
@unittest_reporter(name='REST bad access to PUT /groups')
def test_240_group(self):
client = AsyncHTTPClient()
data = {
'name': '/foo/bar'
}
user_token = Auth('secret').create_token('foo', type='user', payload={'role':'user'})
with self.assertRaises(Exception):
yield client.fetch('http://localhost:{}/groups/{}'.format(self.port, data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+user_token})
@unittest_reporter(name='REST GET /users')
def test_300_user(self):
client = AsyncHTTPClient()
r = yield client.fetch('http://localhost:%d/users'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [])
@unittest_reporter(name='REST POST /users')
def test_310_user(self):
client = AsyncHTTPClient()
data = {
'username': 'foo'
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = json.loads(r.body)
self.assertIn('result', data)
self.assertEqual(data['result'], r.headers['Location'])
user_id = data['result'].rsplit('/')[-1]
r = yield client.fetch('http://localhost:%d/users'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertGreater(len(data['results']), 0)
for k,v in {'user_id':user_id, 'username':'foo'}.items():
self.assertIn(k, data['results'][0])
self.assertEqual(data['results'][0][k], v)
@unittest_reporter(name='REST GET /users/<user_id>')
def test_320_user(self):
client = AsyncHTTPClient()
data = {
'username': 'foo'
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = json.loads(r.body)
self.assertIn('result', data)
self.assertEqual(data['result'], r.headers['Location'])
user_id = data['result'].rsplit('/')[-1]
r = yield client.fetch('http://localhost:%d/users/%s'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
for k,v in {'user_id':user_id, 'username':'foo'}.items():
self.assertIn(k, data)
self.assertEqual(data[k], v)
@unittest_reporter(name='REST DELETE /users/<user_id>')
def test_330_user(self):
client = AsyncHTTPClient()
data = {
'username': 'foo'
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = json.loads(r.body)
self.assertIn('result', data)
self.assertEqual(data['result'], r.headers['Location'])
user_id = data['result'].rsplit('/')[-1]
r = yield client.fetch('http://localhost:%d/users/%s'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
for k,v in {'user_id':user_id, 'username':'foo'}.items():
self.assertIn(k, data)
self.assertEqual(data[k], v)
r = yield client.fetch('http://localhost:%d/users/%s'%(self.port, user_id),
method='DELETE',
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
with self.assertRaises(Exception):
yield client.fetch('http://localhost:%d/users/%s'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
r = yield client.fetch('http://localhost:%d/users'%self.port,
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertIn('results', data)
self.assertEqual(data['results'], [])
@unittest_reporter(name='REST bad access to POST /users')
def test_340_user(self):
client = AsyncHTTPClient()
data = {
'username': 'foo'
}
user_token = Auth('secret').create_token('foo', type='user', payload={'role':'user'})
with self.assertRaises(Exception):
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+user_token})
@unittest_reporter(name='REST POST /users/<user_id>/groups')
def test_410_user(self):
client = AsyncHTTPClient()
data = {
'username': 'foo',
'groups': ['bar']
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = json.loads(r.body)
self.assertIn('result', data)
self.assertEqual(data['result'], r.headers['Location'])
user_id = data['result'].rsplit('/')[-1]
r = yield client.fetch('http://localhost:%d/users/%s/groups'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'results': ['bar']})
# now add the new group
data = {
'name': 'baz'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = {'group': data['name']}
r = yield client.fetch('http://localhost:%d/users/%s/groups'%(self.port, user_id),
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:%d/users/%s/groups'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'results': ['bar','baz']})
@unittest_reporter(name='REST PUT /users/<user_id>/groups')
def test_420_user(self):
client = AsyncHTTPClient()
data = {
'username': 'foo',
'groups': ['bar']
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = json.loads(r.body)
self.assertIn('result', data)
self.assertEqual(data['result'], r.headers['Location'])
user_id = data['result'].rsplit('/')[-1]
r = yield client.fetch('http://localhost:%d/users/%s/groups'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'results': ['bar']})
# now add the new group
data = {
'name': 'baz'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = {
'name': 'blah'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = {'groups': ['baz', 'blah']}
r = yield client.fetch('http://localhost:%d/users/%s/groups'%(self.port, user_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:%d/users/%s/groups'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data, {'results': ['baz', 'blah']})
@unittest_reporter(name='REST PUT /users/<user_id>/roles')
def test_500_user(self):
client = AsyncHTTPClient()
data = {
'username': 'foo',
'roles': ['bar']
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = json.loads(r.body)
self.assertIn('result', data)
self.assertEqual(data['result'], r.headers['Location'])
user_id = data['result'].rsplit('/')[-1]
r = yield client.fetch('http://localhost:%d/users/%s'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data['roles'], ['bar'])
# now add the new role
data = {
'name': 'baz'
}
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port, 'baz'),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = {
'name': 'blah'
}
r = yield client.fetch('http://localhost:%d/roles/%s'%(self.port, 'blah'),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = {'roles': ['baz','blah']}
r = yield client.fetch('http://localhost:%d/users/%s/roles'%(self.port, user_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
r = yield client.fetch('http://localhost:%d/users/%s'%(self.port, user_id),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
self.assertEqual(data['roles'], ['baz','blah'])
@patch('ldap3.Connection')
@unittest_reporter(name='REST POST /ldap')
def test_700_ldap(self, ldap_mock):
client = AsyncHTTPClient()
data = {
'username': 'foo',
'password': 'bar',
}
r = yield client.fetch('http://localhost:%d/ldap'%self.port,
method='POST', body=json.dumps(data))
self.assertEqual(r.code, 200)
tok = json.loads(r.body)['token']
data = Auth('secret').validate(tok)
self.assertEqual(data['username'], 'foo')
self.assertIn('role',data)
self.assertIn('groups',data)
@unittest_reporter(name='REST POST /create_token')
def test_800_create_token(self):
client = AsyncHTTPClient()
# test temp token
data = {
'username': 'bar',
'roles': ['foo','user']
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = {
'type': 'temp',
'role': 'foo',
}
token2 = Auth('secret').create_token('bar', type='user',
payload={'username':'bar','role':'user','groups':['baz']})
if isinstance(token2, bytes):
token2 = token2.decode('utf-8')
r = yield client.fetch('http://localhost:%d/create_token'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+token2})
self.assertEqual(r.code, 200)
tok = json.loads(r.body)['result']
data = Auth('secret').validate(tok)
self.assertEqual(data['type'], 'temp')
self.assertEqual(data['username'], 'bar')
self.assertIn('role',data)
self.assertEqual(data['role'], 'user')
self.assertIn('groups',data)
# test switching roles
data = {
'username': 'foo',
'roles': ['admin','user']
}
r = yield client.fetch('http://localhost:%d/users'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 201)
data = {
'type': 'user',
'role': 'admin',
'exp': 10
}
token2 = Auth('secret').create_token('foo', type='user',
payload={'username':'foo','role':'user','groups':['baz']})
if isinstance(token2, bytes):
token2 = token2.decode('utf-8')
r = yield client.fetch('http://localhost:%d/create_token'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+token2})
self.assertEqual(r.code, 200)
tok = json.loads(r.body)['result']
data = Auth('secret').validate(tok)
self.assertEqual(data['type'], 'user')
self.assertEqual(data['username'], 'foo')
self.assertIn('role',data)
self.assertEqual(data['role'], 'admin')
self.assertIn('groups',data)
self.assertLess(data['exp'], time.time()+10)
# test internal token
data = {
'type': 'system',
'role': 'pilot',
}
token2 = Auth('secret').create_token('foo', type='system',
payload={'username':'foo','role':'client','groups':[]})
if isinstance(token2, bytes):
token2 = token2.decode('utf-8')
r = yield client.fetch('http://localhost:%d/create_token'%self.port,
method='POST', body=json.dumps(data),
headers={'Authorization': 'bearer '+token2})
self.assertEqual(r.code, 200)
tok = json.loads(r.body)['result']
data = Auth('secret').validate(tok)
self.assertEqual(data['type'], 'system')
self.assertEqual(data['username'], 'foo')
self.assertIn('role',data)
self.assertEqual(data['role'], 'pilot')
@unittest_reporter(name='REST PUT /auths/<dataset_id>')
def test_900_auths(self):
client = AsyncHTTPClient()
# add group
data = {
'name': 'foo/bar'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
# add dataset auth
data = {
'read_groups': ['foo/bar'],
'write_groups': []
}
dataset_id = '123'
r = yield client.fetch('http://localhost:%d/auths/%s'%(self.port,dataset_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
data = json.loads(r.body)
@unittest_reporter(name='REST GET /auths/<dataset_id>')
def test_901_auths(self):
client = AsyncHTTPClient()
# add group
data = {
'name': 'foo/bar'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
# add dataset auth
data = {
'read_groups': ['foo/bar'],
'write_groups': []
}
dataset_id = '123'
r = yield client.fetch('http://localhost:%d/auths/%s'%(self.port,dataset_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
ret = json.loads(r.body)
# get dataset auth
r = yield client.fetch('http://localhost:%d/auths/%s'%(self.port,dataset_id),
method='GET',
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
ret = json.loads(r.body)
self.assertEqual(data, ret)
@unittest_reporter(name='REST GET /auths/<dataset_id>/actions/read')
def test_902_auths(self):
client = AsyncHTTPClient()
# add group
data = {
'name': 'foo/bar'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
token2 = Auth('secret').create_token('foo', type='user',
payload={'role':'user','groups':['foo/bar']})
if isinstance(token2, bytes):
token2 = token2.decode('utf-8')
# add dataset auth
data = {
'read_groups': ['foo/bar'],
'write_groups': []
}
dataset_id = '123'
r = yield client.fetch('http://localhost:%d/auths/%s'%(self.port,dataset_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
ret = json.loads(r.body)
# get authorization
r = yield client.fetch('http://localhost:%d/auths/%s/actions/read'%(self.port,dataset_id),
method='GET',
headers={'Authorization': 'bearer '+token2})
self.assertEqual(r.code, 200)
# add bad dataset auth
data = {
'read_groups': [],
'write_groups': ['foo/bar']
}
dataset_id = '456'
r = yield client.fetch('http://localhost:%d/auths/%s'%(self.port,dataset_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
ret = json.loads(r.body)
# get authorization
with self.assertRaises(tornado.httpclient.HTTPError) as e:
r = yield client.fetch('http://localhost:%d/auths/%s/actions/read'%(self.port,dataset_id),
method='GET',
headers={'Authorization': 'bearer '+token2})
self.assertEqual(e.exception.code, 403)
@unittest_reporter(name='REST GET /auths/<dataset_id>/actions/write')
def test_903_auths(self):
client = AsyncHTTPClient()
# add group
data = {
'name': 'foo/bar'
}
r = yield client.fetch('http://localhost:{}/groups/{}'.format(self.port,data['name']),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
token2 = Auth('secret').create_token('foo', type='user',
payload={'role':'user','groups':['foo/bar']})
if isinstance(token2, bytes):
token2 = token2.decode('utf-8')
# add dataset auth
data = {
'read_groups': [],
'write_groups': ['foo/bar']
}
dataset_id = '123'
r = yield client.fetch('http://localhost:%d/auths/%s'%(self.port,dataset_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
ret = json.loads(r.body)
# get authorization
r = yield client.fetch('http://localhost:%d/auths/%s/actions/write'%(self.port,dataset_id),
method='GET',
headers={'Authorization': 'bearer '+token2})
self.assertEqual(r.code, 200)
# add bad dataset auth
data = {
'read_groups': ['foo/bar'],
'write_groups': []
}
dataset_id = '456'
r = yield client.fetch('http://localhost:%d/auths/%s'%(self.port,dataset_id),
method='PUT', body=json.dumps(data),
headers={'Authorization': 'bearer '+self.token})
self.assertEqual(r.code, 200)
ret = json.loads(r.body)
# get authorization
with self.assertRaises(tornado.httpclient.HTTPError) as e:
r = yield client.fetch('http://localhost:%d/auths/%s/actions/write'%(self.port,dataset_id),
method='GET',
headers={'Authorization': 'bearer '+token2})
self.assertEqual(e.exception.code, 403)
def load_tests(loader, tests, pattern):
suite = unittest.TestSuite()
alltests = glob_tests(loader.getTestCaseNames(rest_auth_test))
suite.addTests(loader.loadTestsFromNames(alltests,rest_auth_test))
return suite
| 40.794667
| 104
| 0.542424
| 3,325
| 30,596
| 4.937444
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| 0.883109
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| 30,596
| 749
| 105
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| false
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0
| 7
|
96e00e46c6abc0ba54723b911a8e42c9e6678fb1
| 1,320
|
py
|
Python
|
cli/block/interfaces.py
|
Remmeauth/remme-core-cli
|
94cc09fe9d2e718b45273dde68d6c672c4773f6a
|
[
"MIT"
] | null | null | null |
cli/block/interfaces.py
|
Remmeauth/remme-core-cli
|
94cc09fe9d2e718b45273dde68d6c672c4773f6a
|
[
"MIT"
] | 94
|
2019-03-27T09:34:28.000Z
|
2019-08-27T05:32:33.000Z
|
cli/block/interfaces.py
|
Remmeauth/remme-core-cli
|
94cc09fe9d2e718b45273dde68d6c672c4773f6a
|
[
"MIT"
] | 6
|
2019-06-06T15:16:38.000Z
|
2020-02-24T12:55:55.000Z
|
"""
Provide implementation of the block interfaces.
"""
class BlockInterface:
"""
Implements block interface.
"""
def get(self, identifier):
"""
Get a block by its identifier.
"""
pass
def get_list(self, ids, head, limit, reverse):
"""
Get a list of blocks.
A list of blocks could be filtered by blocks identifiers, limit, head, reverse.
Arguments:
ids (list, optional): identifiers to get a list of blocks by.
limit (int, optional): maximum amount of blocks to return.
head (string, optional): block identifier to get a list of transactions to.
reverse (bool, optional): parameter to reverse result.
"""
pass
def get_list_ids(self, ids, head, limit, reverse):
"""
Get a list of blocks identifiers.
A list of blocks identifiers could be filtered by blocks identifiers, limit, head, reverse.
Arguments:
ids (list, optional): identifiers to get a list of blocks by.
limit (int, optional): maximum amount of blocks to return.
head (string, optional): block identifier to get a list of transactions to.
reverse (bool, optional): parameter to reverse result.
"""
pass
| 30
| 99
| 0.60303
| 159
| 1,320
| 4.987421
| 0.251572
| 0.050441
| 0.070618
| 0.075662
| 0.788146
| 0.74401
| 0.74401
| 0.74401
| 0.74401
| 0.74401
| 0
| 0
| 0.318182
| 1,320
| 43
| 100
| 30.697674
| 0.881111
| 0.678788
| 0
| 0.428571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| false
| 0.428571
| 0
| 0
| 0.571429
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
|
0
| 8
|
8c3d9f2549364d992a01b14be3ec3f408beff585
| 130
|
py
|
Python
|
msc/tests/test_ayeright.py
|
ayeright/git-github-travis-lab
|
f370b756355e80ba42716e95f45c3621a807f037
|
[
"Apache-2.0"
] | null | null | null |
msc/tests/test_ayeright.py
|
ayeright/git-github-travis-lab
|
f370b756355e80ba42716e95f45c3621a807f037
|
[
"Apache-2.0"
] | null | null | null |
msc/tests/test_ayeright.py
|
ayeright/git-github-travis-lab
|
f370b756355e80ba42716e95f45c3621a807f037
|
[
"Apache-2.0"
] | null | null | null |
from msc.rot13 import rot13
from msc.rot13 import rot13_char
def test_rot13_char_non_alpha():
assert '#' == rot13_char('#')
| 18.571429
| 33
| 0.730769
| 20
| 130
| 4.45
| 0.5
| 0.303371
| 0.269663
| 0.404494
| 0.516854
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109091
| 0.153846
| 130
| 6
| 34
| 21.666667
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0.015385
| 0
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0.25
| true
| 0
| 0.5
| 0
| 0.75
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 8
|
8c52fcb86062dc2edacf291d5e9b302b02dc9fae
| 134
|
py
|
Python
|
pyxtf/__init__.py
|
actingthegroat/pyxtf
|
b71d38e4435dffc4732748b6c2b9611e20192550
|
[
"MIT"
] | 27
|
2018-04-05T09:07:41.000Z
|
2022-03-03T12:32:08.000Z
|
pyxtf/__init__.py
|
actingthegroat/pyxtf
|
b71d38e4435dffc4732748b6c2b9611e20192550
|
[
"MIT"
] | 12
|
2017-07-24T19:25:31.000Z
|
2021-08-04T12:30:04.000Z
|
pyxtf/__init__.py
|
actingthegroat/pyxtf
|
b71d38e4435dffc4732748b6c2b9611e20192550
|
[
"MIT"
] | 18
|
2017-04-29T16:09:37.000Z
|
2022-03-25T17:09:51.000Z
|
from pyxtf.enumerations import *
from pyxtf.xtf_ctypes import *
from pyxtf.xtf_io import xtf_read, xtf_read_gen, concatenate_channel
| 26.8
| 68
| 0.835821
| 21
| 134
| 5.047619
| 0.52381
| 0.254717
| 0.283019
| 0.339623
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.11194
| 134
| 4
| 69
| 33.5
| 0.890756
| 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
|
8b28f2e01ffdd41f4f46d95e1d90db342bc79ec2
| 4,514
|
py
|
Python
|
solution/raw/test_seg_cur.py
|
renhao0511/SlowFast
|
eff638d730831ec926014c1e2af4ae7233d6c8de
|
[
"Apache-2.0"
] | null | null | null |
solution/raw/test_seg_cur.py
|
renhao0511/SlowFast
|
eff638d730831ec926014c1e2af4ae7233d6c8de
|
[
"Apache-2.0"
] | null | null | null |
solution/raw/test_seg_cur.py
|
renhao0511/SlowFast
|
eff638d730831ec926014c1e2af4ae7233d6c8de
|
[
"Apache-2.0"
] | null | null | null |
import shutil
import os
test_list = [
# 'trainset_split_largebox/冀-廊坊-百世-分拨-市区主线_20210829205340-20210829205410_1_largebox/冀-廊坊-百世-分拨-市区主线_20210829205340-20210829205410_1_largebox',
# 'trainset_split_largebox/琼-海口-圆通-装卸区2_0118009034_20220120224840_0_largebox/琼-海口-圆通-装卸区2_0118009034_20220120224840_0_largebox',
# 'trainset_split_largebox/351W-晋-太原-顺丰转运-全景-F区08_0900000011_20220111171339_0_largebox/351W-晋-太原-顺丰转运-全景-F区08_0900000011_20220111171339_0_largebox',
# 'trainset_split_largebox/贵_贵阳_京东_三线左面发货2_0115181003_20220111162621_0_largebox/贵_贵阳_京东_三线左面发货2_0115181003_20220111162621_0_largebox',
# 'trainset_split_largebox/冀-秦皇岛-中通-秦皇岛33510-出港大件卸货口_0118043631_20220124160105_0_largebox/冀-秦皇岛-中通-秦皇岛33510-出港大件卸货口_0118043631_20220124160105_0_largebox',
# 'trainset_split_largebox/暴力分拣 贵_贵阳_京东_遵义发货_0115181022_20220111152203_0_largebox/暴力分拣 贵_贵阳_京东_遵义发货_0115181022_20220111152203_0_largebox',
# 'trainset_split_largebox/暴力分拣 贵_贵阳_京东_遵义发货1_0115181022_20220111152056_0_largebox/暴力分拣 贵_贵阳_京东_遵义发货1_0115181022_20220111152056_0_largebox',
# 'trainset_split_largebox/山东省-泰安市-邮政-装卸区-12暴力_0901011012_20220111170824_0_largebox/山东省-泰安市-邮政-装卸区-12暴力_0901011012_20220111170824_0_largebox',
# 'trainset_split_largebox/（双人扔抛大件）琼-海口-极兔-建包区3-IDF2-092_0118005871_20220208215957_0_largebox/（双人扔抛大件）琼-海口-极兔-建包区3-IDF2-092_0118005871_20220208215957_0_largebox',
# 'trainset_split_largebox/晋-太原-申通-分拣区-4_0100053011_20220126113634_0_largebox/晋-太原-申通-分拣区-4_0100053011_20220126113634_0_largebox',
# 'trainset_split_largebox/晋-太原-韵达转运-分拣5_0100060016_20220126130658_0_largebox/晋-太原-韵达转运-分拣5_0100060016_20220126130658_0_largebox',
# 'trainset_split_largebox/亳州 Camera 01_0602870997_20220126143001_0_largebox/亳州 Camera 01_0602870997_20220126143001_0_largebox',
# 'trainset_split_largebox/（暴力分拣）川-成都-申通进分拣 青龙场_0100050031_20220222231623_0_largebox/（暴力分拣）川-成都-申通进分拣 青龙场_0100050031_20220222231623_0_largebox',
# 'trainset_split_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222231350_0_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222231350_0_largebox',
# 'trainset_split_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222231447_0_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222231447_0_largebox',
# 'trainset_split_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222231945_0_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222231945_0_largebox',
# 'trainset_split_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222232350_0_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222232350_0_largebox',
# 'trainset_split_largebox/（暴力分拣）晋-大同-中通转运-分拣区-2_62564_largebox/（暴力分拣）晋-大同-中通转运-分拣区-2_62564_largebox',
# 'trainset_split_largebox/（暴力分拣）辽-大连-韵达-海事二七_1646201880943_largebox/（暴力分拣）辽-大连-韵达-海事二七_1646201880943_largebox',
# 'trainset_split_largebox/（暴力分拣）琼-海口-极兔-DWS5号后-IDF2-082_0118005881_20220218201018_0_largebox/（暴力分拣）琼-海口-极兔-DWS5号后-IDF2-082_0118005881_20220218201018_0_largebox',
# 'testset_split_largebox/鄂-武汉-申通-武汉分拣区-6_0100050020_20220112180109_0_largebox/鄂-武汉-申通-武汉分拣区-6_0100050020_20220112180109_0_largebox',
# 'testset_split_largebox/鄂-武汉-申通-武汉转运安检区1-1_0100050003_20220121154821_0_largebox/鄂-武汉-申通-武汉转运安检区1-1_0100050003_20220121154821_0_largebox',
# 'testset_split_largebox/冀-廊坊-百世-分拨-北京短驳_20210829200238-20210829200259_1_largebox/冀-廊坊-百世-分拨-北京短驳_20210829200238-20210829200259_1_largebox',
# 'testset_split_largebox/冀-石家庄-韵达-石家庄-C3-021备装安检_0100060013_20220111205910_0_largebox/冀-石家庄-韵达-石家庄-C3-021备装安检_0100060013_20220111205910_0_largebox',
# 'testset_split_largebox/晋-太原-申通-安检区-1_0100053002_20220120223110_0_largebox/晋-太原-申通-安检区-1_0100053002_20220120223110_0_largebox',
'testset_split_largebox/（暴力分拣）川-成都-申通-土桥_安德0100050030_20220222232259_0_0_largebox/（暴力分拣）川-成都-申通-土桥_安德0100050030_20220222232259_0_0_largebox',
# 'testset_split_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222232427_0_largebox/（暴力分拣）川-成都-申通-土桥_安德_0100050030_20220222232427_0_largebox',
# 'testset_split_largebox/（踩踏-抛扔）琼-海口-极兔-建包区3-IDF2-092_0118005871_20220214210416_0_largebox/（踩踏-抛扔）琼-海口-极兔-建包区3-IDF2-092_0118005871_20220214210416_0_largebox',
# 'testset_split_largebox/（踩踏-抛扔）琼-海口-极兔-建包区3-IDF2-092_0118005871_20220214210709_0_largebox/（踩踏-抛扔）琼-海口-极兔-建包区3-IDF2-092_0118005871_20220214210709_0_largebox',
]
dst_file = '/home/haoren/repo/slowfast/data/raw/anno_seg_test/test.csv'
for test_cur in test_list:
print(test_cur)
src_file = '/home/haoren/repo/slowfast/data/raw/test_acc/' + test_cur + '.txt'
shutil.copy(src_file, dst_file)
os.system('bash test_seg.sh')
| 107.47619
| 166
| 0.846035
| 682
| 4,514
| 5.129032
| 0.22434
| 0.128645
| 0.120069
| 0.157519
| 0.952258
| 0.913665
| 0.90709
| 0.880789
| 0.821612
| 0.714694
| 0
| 0.349977
| 0.05051
| 4,514
| 41
| 167
| 110.097561
| 0.466169
| 0.860656
| 0
| 0
| 0
| 0.090909
| 0.435
| 0.401667
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.181818
| 0
| 0.181818
| 0.090909
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 11
|
8b3612e2ee58aaa0578097145d6de57ac7e99035
| 47
|
py
|
Python
|
tests/test_loop_1.py
|
raffaelfoidl/noworkflow
|
aa4ca189df24fec6c7abd32bcca6a097b21fdf31
|
[
"MIT"
] | 108
|
2015-02-04T14:16:51.000Z
|
2022-03-06T13:52:45.000Z
|
tests/test_loop_1.py
|
raffaelfoidl/noworkflow
|
aa4ca189df24fec6c7abd32bcca6a097b21fdf31
|
[
"MIT"
] | 92
|
2015-01-19T14:58:06.000Z
|
2021-04-19T17:28:50.000Z
|
tests/test_loop_1.py
|
raffaelfoidl/noworkflow
|
aa4ca189df24fec6c7abd32bcca6a097b21fdf31
|
[
"MIT"
] | 31
|
2015-03-03T23:53:59.000Z
|
2021-11-11T04:23:44.000Z
|
def y():
pass
def x():
y()
x()
x()
| 4.272727
| 8
| 0.319149
| 8
| 47
| 1.875
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.425532
| 47
| 10
| 9
| 4.7
| 0.555556
| 0
| 0
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0.166667
| 0
| 0
| 0.333333
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
8c6e469818d139281ee416f7ad63537387b67fc4
| 125,032
|
py
|
Python
|
models/dialog.py
|
kaniblu/vhda
|
35941097ef552568c29f66cc55d8ce1927f34978
|
[
"MIT"
] | 3
|
2021-01-12T05:43:20.000Z
|
2021-03-05T17:03:06.000Z
|
models/dialog.py
|
kaniblu/vhda
|
35941097ef552568c29f66cc55d8ce1927f34978
|
[
"MIT"
] | null | null | null |
models/dialog.py
|
kaniblu/vhda
|
35941097ef552568c29f66cc55d8ce1927f34978
|
[
"MIT"
] | null | null | null |
__all__ = ["AbstractTDA", "VHCR", "VHDA", "HDA", "VHDAWithoutGoal",
"VHDAWithoutGoalAct", "VHRED", "VHUS"]
import math
import torch
import torch.nn as nn
import torch.distributions as dist
import torchmodels
import utils
from utils import Stacked1DTensor
from utils import DoublyStacked1DTensor
from datasets import VocabSet
from datasets import BatchData
from datasets import ActSlotValue
from .state_decoder import AbstractStateDecoder
from .gaussian import MultiGaussian
from .gaussian import MultiGaussianLayer
from .seq_encoder import AbstractSequenceEncoder
from .sent_decoder import AbstractSentDecoder
from .context import AbstractContextEncoder
from .word import AbstractWordEncoder
class AbstractTDA(torchmodels.Module):
"""Abstract class for task-oriented dialog autoencoder
Initialization Arguments:
vocab (Vocabulary): word vocabulary object
word_dim (int): word dimensions
num_labels (list of int): a list of labels and their class sizes
mode (str): forward behavior (default: inference)
inference: teacher force all utterances in the decoding step and
return relevant output logits.
"""
def __init__(self, vocabs: VocabSet):
super(AbstractTDA, self).__init__()
self.vocabs = vocabs
self.mode = "inference"
def inference(self):
self.mode = "inference"
def genconv_post(self):
self.mode = "genconv-post"
def genconv_prior(self):
self.mode = "genconv-prior"
def encode(self):
self.mode = "encode"
def decode_optimal(self):
self.mode = "decode-optimal"
def _encode_impl(self, data, *args, **kwargs):
"""Encodes the dialog data into latent variables.
Arguments:
data (dict): Data to be used for posterior calculation.
The data is specified using a dictionary with at
least the following keys.
conv_lens (LongTensor): [batch_size]
sent (LongTensor): [batch_size x max_conv_len x max_sent_len]
sent_lens (LongTensor): [batch_size x max_conv_len]
speaker (LongTensor): [batch_size x max_conv_len]
goal (LongTensor): [batch_size x max_conv_len x max_goal_lens]
goal_lens (LongTensor): [batch_size x max_conv_len]
state (LongTensor): [batch_size x max_conv_len x max_state_lens]
state_lens (LongTensor): [batch_size x max_conv_len]
asv (LongTensor): [num_asv x max_asv_len]
asv_lens (LongTensor): [num_asv]
Returns:
post (dict): posterior distributions containing following keys.
zconv (MultiGaussian): gaussian distribution object for
conversation latent variables.
"""
raise NotImplementedError
def _decode_optimal_impl(self, data, *args, **kwargs):
"""Decodes and generates a dialog from the given conversation
latent variable vector. Must use optimal decoding method (in contrast
to greedy method).
Arguments:
data (dict): Data to be used for decoding.
The data is specified using a dictionary with at
least the following keys.
zconv (FloatTensor): [batch_size x conv_dim]
asv (LongTensor): [num_asv x max_asv_len]
asv_lens (LongTensor): [num_asv]
"""
raise NotImplementedError
@staticmethod
def tuplize_data(data: dict):
return tuple(data[k] for k in
["conv_lens", "sent", "sent_lens", "speaker", "goal",
"goal_lens", "state", "state_lens", "asv", "asv_lens"])
def _genconv_prior_impl(self, data, *args, **kwargs):
"""Generates entire conversations from the prior distribution
Arguments:
data (dict): Data to be used for posterior calculation.
The data is specified using a dictionary with at
least the following keys.
n (LongTensor): a zero-dimensional Tensor that
contains the number of samples to generate.
asv (LongTensor): [num_asv x max_asv_len]
asv_lens (LongTensor): [num_asv]
"""
raise NotImplementedError
def _genconv_post_impl(self, data, *args, **kwargs):
"""Generates entire conversations from the posterior
distribution depending on the input type.
Arguments:
data (dict): Data to be used for posterior calculation.
The data is specified using a dictionary with at
least the following keys.
conv_lens (LongTensor): [batch_size]
sent (LongTensor): [batch_size x max_conv_len x max_sent_len]
sent_lens (LongTensor): [batch_size x max_conv_len]
speaker (LongTensor): [batch_size x max_conv_len]
goal (LongTensor): [batch_size x max_conv_len x max_goal_lens]
goal_lens (LongTensor): [batch_size x max_conv_len]
state (LongTensor): [batch_size x max_conv_len x max_state_lens]
state_lens (LongTensor): [batch_size x max_conv_len]
asv (LongTensor): [num_asv x max_asv_len]
asv_lens (LongTensor): [num_asv]
"""
raise NotImplementedError
def _genturn_impl(self, data, *args, **kwargs):
"""Generates turns with given contexts from conditional priors.
Arguments:
data (dict): Data to be used for posterior calculation.
The data is specified using a dictionary with at
least the following keys.
conv_lens (LongTensor): [batch_size]
sent (LongTensor): [batch_size x max_conv_len x max_sent_len]
sent_lens (LongTensor): [batch_size x max_conv_len]
speaker (LongTensor): [batch_size x max_conv_len]
goal (LongTensor): [batch_size x max_conv_len x max_goal_lens]
goal_lens (LongTensor): [batch_size x max_conv_len]
state (LongTensor): [batch_size x max_conv_len x max_state_lens]
state_lens (LongTensor): [batch_size x max_conv_len]
asv (LongTensor): [num_asv x max_asv_len]
asv_lens (LongTensor): [num_asv]
"""
raise NotImplementedError
def _inference_impl(self, data, *args, **kwargs):
"""
Arguments:
data (dict): Data to be used for posterior calculation.
The data is specified using a dictionary with at
least the following keys.
conv_lens (LongTensor): [batch_size]
sent (LongTensor): [batch_size x max_conv_len x max_sent_len]
sent_lens (LongTensor): [batch_size x max_conv_len]
speaker (LongTensor): [batch_size x max_conv_len]
goal (LongTensor): [batch_size x max_conv_len x max_goal_lens]
goal_lens (LongTensor): [batch_size x max_conv_len]
state (LongTensor): [batch_size x max_conv_len x max_state_lens]
state_lens (LongTensor): [batch_size x max_conv_len]
asv (LongTensor): [num_asv x max_asv_len]
asv_lens (LongTensor): [num_asv]
"""
raise NotImplementedError
def forward(self, *args, **kwargs):
"""Computes forward computation, depending on the mode currently set on.
Supported modes are as follows.
- Inference Mode: `self.inference_mode()`
- Conversation Generation Mode: `self.gen_conv_mode()`
- Utterance Generation Mode: `self.utt_conv_mode()`
Returns:
# TODO: update return signature
logit_dict (Mapping):
sent (FloatTensor):
[batch_size x max_conv_len x max_sent_len x vocab_size]
speaker_logits (FloatTensor):
[batch_size x max_conv_len x num_speakers]
goal (FloatTensor):
[batch_size x max_conv_len x num_labels x max_num_classes]
turn (FloatTensor):
[batch_size x max_conv_len x num_labels x max_num_classes]
post_dict (Mapping[str, MultiGaussian]):
sent (MultiGaussian): sent posterior distribution
speaker (MultiGaussian): speaker posterior distribution
goal (MultiGaussian): goal posterior distribution
turn (MultiGaussian): turn posterior distribution
conv (MultiGaussian): conv posterior distribution
prior_dict (Mapping[str, MultiGaussian]):
sent (MultiGaussian): sent prior distribution
speaker (MultiGaussian): speaker prior distribution
goal (MultiGaussian): goal prior distribution
turn (MultiGaussian): turn prior distribution
conv (MultiGaussian): conv prior distribution
"""
if self.mode == "inference":
return self._inference_impl(*args, **kwargs)
elif self.mode == "genconv-post":
return self._genconv_post_impl(*args, **kwargs)
elif self.mode == "genconv-prior":
return self._genconv_prior_impl(*args, **kwargs)
elif self.mode == "genturn":
return self._genturn_impl(*args, **kwargs)
elif self.mode == "encode":
return self._encode_impl(*args, **kwargs)
elif self.mode == "decode-optimal":
return self._decode_optimal_impl(*args, **kwargs)
else:
raise ValueError(f"unsupported mode: {self.mode}")
class VHCR(AbstractTDA):
name = "vhcr"
def __init__(self, *args,
conv_dim=256, word_dim=100, sent_dim=128, ctx_dim=256,
zsent_dim=16, zconv_dim=16,
sent_dropout=0.0, word_dropout=0.0,
word_encoder=AbstractWordEncoder,
seq_encoder=AbstractSequenceEncoder,
sent_decoder=AbstractSentDecoder,
ctx_encoder=AbstractContextEncoder, **kwargs):
super().__init__(*args, **kwargs)
self.word_dim = word_dim
self.sent_dim = sent_dim
self.conv_dim = conv_dim
self.ctx_dim = ctx_dim
self.zconv_dim = zconv_dim
self.zsent_dim = zsent_dim
self.word_encoder_cls = word_encoder
self.seq_encoder_cls = seq_encoder
self.sent_decoder_cls = sent_decoder
self.ctx_encoder_cls = ctx_encoder
self.sent_dropout = sent_dropout
self.word_dropout = word_dropout
self.word_encoder = self.word_encoder_cls(
vocab=self.vocabs.word,
word_dim=self.word_dim
)
self.sent_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=0,
hidden_dim=self.sent_dim
)
self.conv_encoder = self.seq_encoder_cls(
input_dim=self.sent_dim,
query_dim=0,
hidden_dim=self.conv_dim
)
self.ctx_encoder = self.ctx_encoder_cls(
input_dim=(self.zconv_dim + self.sent_dim),
ctx_dim=self.ctx_dim
)
self.sent_decoder = self.sent_decoder_cls(
vocab=self.vocabs.word,
word_encoder=self.word_encoder,
hidden_dim=(self.ctx_dim + self.zconv_dim + self.zsent_dim)
)
self.zconv_post = MultiGaussianLayer(
input_dim=self.conv_dim,
hidden_dim=self.zconv_dim
)
self.zsent_prior = MultiGaussianLayer(
input_dim=(self.ctx_dim + self.zconv_dim),
hidden_dim=self.zsent_dim
)
self.zsent_post = MultiGaussianLayer(
input_dim=(self.ctx_dim + self.zconv_dim + self.sent_dim),
hidden_dim=self.zsent_dim
)
self.sent_unk = nn.Parameter(torch.zeros(self.sent_dim))
self.word_unk = nn.Parameter(torch.zeros(self.word_dim))
@property
def num_speakers(self):
return self.vocabs.num_speakers
def reset_parameters(self):
super().reset_parameters()
nn.init.normal_(self.sent_unk, 0, 1 / math.sqrt(self.sent_dim))
nn.init.normal_(self.word_unk, 0, 1 / math.sqrt(self.word_dim))
def dropout(self, x, dropout_rate, unk):
if not self.training:
return x
x_size = x.size()
x = x.view(-1, x.size(-1))
idx = dist.Bernoulli(dropout_rate).sample((x.size(0),)).bool()
if idx.any():
x[idx] = unk
return x.view(*x_size)
def _inference_impl(self, data, sample_scale=1.0,
dropout_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
max_goal_len, max_state_len = g.size(-1), s.size(-1)
num_asv, max_asv_len = asv.size()
num_speakers = len(self.vocabs.speaker)
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
)
zconv_post: MultiGaussian = self.zconv_post(c)
zconv = zconv_post.sample(sample_scale)
zconv_exp = zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
zconv_exp_flat = zconv_exp.reshape(-1, self.zconv_dim)
w_emb = self.dropout(w_emb,
dropout_rate=self.word_dropout * dropout_scale,
unk=self.word_unk)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = self.dropout(u, self.sent_dropout * dropout_scale, self.sent_unk)
context, _, _ = self.ctx_encoder(
torch.cat([
utils.shift(u, dim=1),
zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
], 2),
conv_lens
)
zsent_post: MultiGaussian = self.zsent_post(
torch.cat([
u.view(-1, self.sent_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent_prior: MultiGaussian = self.zsent_prior(
torch.cat([
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent = (zsent_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
w_logit = self.sent_decoder(
(torch.cat([zsent, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1)),
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
).view(batch_size, max_conv_len, max_sent_len, -1)
# gibberish
p_logit = w_logit.new(batch_size, max_conv_len, num_speakers).normal_()
g_logit = w_logit.new(batch_size, max_conv_len, num_asv).normal_()
s_logit = w_logit.new(batch_size, max_conv_len, num_asv).normal_()
return (
{ # logits
"sent": w_logit,
"speaker": p_logit,
"goal": g_logit,
"state": s_logit
}, { # posterior
"conv": zconv_post,
"sent": zsent_post,
"speaker": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
}, { # prior
"conv": (MultiGaussian.unit(*zconv_post.size())
.to(w_logit.device)),
"sent": zsent_prior,
"speaker": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
}
)
def _encode_impl(self, data, **kwargs):
conv_lens = data["conv_lens"]
w, w_lens = data["sent"], data["sent_lens"]
batch_size, max_conv_len, max_sent_len = w.size()
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(u, conv_lens)
return self.zconv_post(c)
def _decode_optimal_impl(self, data,
conv_state=None,
init_u=None,
max_conv_len=20, max_sent_len=30, sent_scale=1.0,
beam_size=8, **kwargs):
zconv = data["zconv"]
batch_size = zconv.size(0)
eoc_idx = self.vocabs.word["<eoc>"]
asv_pad = ActSlotValue("<pad>", "<pad>", "<pad>")
asv_pad_idx = self.vocabs.goal_state.asv[asv_pad]
sents, spkrs, goals, states = list(), list(), list(), list()
conv_lens = zconv.new(batch_size).long().zero_()
conv_done = zconv.new(batch_size).bool().zero_()
sent_logprob = zconv.new(batch_size).zero_()
if init_u is None:
u = zconv.new(batch_size, self.sent_dim).zero_()
else:
u = init_u
if conv_state is None:
conv_state = self.ctx_encoder.init_state(batch_size)
for i in range(max_conv_len):
context, _, conv_state = self.ctx_encoder(
torch.cat([u, zconv], 1).unsqueeze(1),
lens=u.new(batch_size).long().fill_(1),
h=conv_state
)
context = context.view(-1, self.ctx_dim)
zutt = self.zsent_prior(
torch.cat([context, zconv], 1)
).sample(sent_scale)
w, w_lens, w_prob = self.sent_decoder.generate(
h=torch.cat([
zutt,
context.view(batch_size, self.ctx_dim),
zconv
], 1),
beam_size=beam_size,
max_len=max_sent_len
)
w_logprob = w_prob.log()
sents.append(Stacked1DTensor(w, w_lens))
_, u = self.sent_encoder(self.word_encoder(w, w_lens), w_lens)
spkrs.append(w.new(batch_size).zero_().long())
goals.append(Stacked1DTensor(
value=w.new(batch_size, 0).zero_().long(),
lens=w.new(batch_size).zero_().long()
))
states.append(Stacked1DTensor(
value=w.new(batch_size, 0).zero_().long(),
lens=w.new(batch_size).zero_().long()
))
conv_lens += 1 - conv_done.long()
done = ((w == eoc_idx) & utils.mask(w_lens, w.size(1))).any(1)
conv_done |= done
sent_logprob = w_logprob.masked_fill(conv_done, 0)
if conv_done.all().item():
break
sents = utils.stack_stacked1dtensors(sents)
goals = utils.stack_stacked1dtensors(goals)
states = utils.stack_stacked1dtensors(states)
return BatchData(
sent=DoublyStacked1DTensor(
value=sents.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=sents.lens1.t().contiguous()
),
speaker=Stacked1DTensor(
value=torch.stack(spkrs).transpose(1, 0).contiguous(),
lens=conv_lens
),
goal=DoublyStacked1DTensor(
value=goals.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=goals.lens1.t().contiguous()
),
state=DoublyStacked1DTensor(
value=states.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=states.lens1.t().contiguous()
),
), dict(
logprob=sent_logprob,
sent_logprob=sent_logprob,
goal_logprob=sent_logprob.clone().fill_(float("nan")),
state_logprob=sent_logprob.clone().fill_(float("nan")),
spkr_logprob=sent_logprob.clone().fill_(float("nan")),
)
def _genconv_prior_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
n = data["n"]
zconv = MultiGaussian.unit(n.item(), self.ctx_dim).to(n.device)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample, "asv": data["asv"],
"asv_lens": data["asv_lens"]},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
goal_scale=goal_scale,
state_scale=state_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
def _genconv_post_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
zconv = self._encode_impl(data)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample, "asv": data["asv"],
"asv_lens": data["asv_lens"]},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
goal_scale=goal_scale,
state_scale=state_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
class VHUS(AbstractTDA):
name = "vhus"
def __init__(self, *args,
word_dim=150, asv_dim=200, conv_dim=200,
goal_dim=200, state_dim=200, zstate_dim=200,
asv_dropout=0.0,
word_encoder=AbstractWordEncoder,
seq_encoder=AbstractSequenceEncoder,
ctx_encoder=AbstractContextEncoder,
state_decoder=AbstractStateDecoder, **kwargs):
super().__init__(*args, **kwargs)
self.asv_dim = asv_dim
self.conv_dim = conv_dim
self.word_dim = word_dim
self.goal_dim = goal_dim
self.state_dim = state_dim
self.zstate_dim = zstate_dim
self.asv_dropout = asv_dropout
self.word_encoder_cls = word_encoder
self.seq_encoder_cls = seq_encoder
self.ctx_encoder_cls = ctx_encoder
self.state_decoder_cls = state_decoder
self.asv_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=0,
hidden_dim=self.asv_dim
)
self.word_encoder = self.word_encoder_cls(
vocab=self.vocabs.word,
word_dim=self.word_dim
)
self.goal_encoder = self.seq_encoder_cls(
input_dim=self.asv_dim,
query_dim=0,
hidden_dim=self.goal_dim
)
self.state_encoder = self.seq_encoder_cls(
input_dim=self.asv_dim,
query_dim=0,
hidden_dim=self.state_dim
)
self.ctx_encoder = self.ctx_encoder_cls(
input_dim=self.goal_dim + self.state_dim,
ctx_dim=self.conv_dim
)
self.state_decoder = self.state_decoder_cls(
vocabs=self.vocabs, state_type="state",
# conv_rnn + z_conv + z_speaker + z_goal + z_turn
input_dim=self.zstate_dim,
asv_dim=self.asv_dim
)
self.zstate_post = MultiGaussianLayer(
input_dim=self.conv_dim,
hidden_dim=self.zstate_dim
)
self.zstate_prior = MultiGaussianLayer(
input_dim=self.conv_dim,
hidden_dim=self.zstate_dim
)
self.asv_unk = nn.Parameter(torch.zeros(self.asv_dim))
self.spkr_eye = nn.Parameter(torch.eye(self.num_speakers),
requires_grad=False)
@property
def num_speakers(self):
return self.vocabs.num_speakers
def reset_parameters(self):
super().reset_parameters()
nn.init.normal_(self.asv_unk, 0, 1 / math.sqrt(self.word_dim))
def dropout(self, x, dropout_rate, unk):
if not self.training:
return x
x_size = x.size()
x = x.view(-1, x.size(-1))
idx = dist.Bernoulli(dropout_rate).sample((x.size(0),)).bool()
if idx.any():
x[idx] = unk
return x.view(*x_size)
def _inference_impl(self, data, sample_scale=1.0,
dropout_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
max_goal_len, max_state_len = g.size(-1), s.size(-1)
num_asv, max_asv_len = asv.size()
conv_mask = utils.mask(conv_lens)
g_mask = utils.mask(g_lens) & conv_mask.unsqueeze(-1)
s_mask = utils.mask(s_lens) & conv_mask.unsqueeze(-1)
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
g_asv = self.dropout(
asv_h[g.masked_fill(~g_mask, 0)],
dropout_rate=self.asv_dropout * dropout_scale,
unk=self.asv_unk
)
v = self.goal_encoder(
g_asv.view(-1, max_goal_len, self.asv_dim),
g_lens.view(-1)
)[1].view(batch_size, max_conv_len, self.goal_dim)
s_asv = self.dropout(
asv_h[s.masked_fill(~s_mask, 0)],
dropout_rate=self.asv_dropout * dropout_scale,
unk=self.asv_unk
)
t = self.state_encoder(
s_asv.view(-1, max_state_len, self.asv_dim),
s_lens.view(-1)
)[1].view(batch_size, max_conv_len, self.state_dim)
ctx, _, _ = self.ctx_encoder(torch.cat([v, t], -1), conv_lens)
zstate_post: MultiGaussian = self.zstate_post(ctx)
zstate_prior: MultiGaussian = self.zstate_prior(
utils.shift(ctx, n=1, dim=1)
)
if self.training:
zstate = zstate_post.sample()
else:
zstate = zstate_prior.sample()
s_logit = self.state_decoder(
zstate.view(batch_size * max_conv_len, -1),
p.view(batch_size * max_conv_len),
asv_h
).view(batch_size, max_conv_len, -1)
# gibberish
w_logit = s_logit.new(batch_size, max_conv_len,
max_sent_len, len(self.vocabs.word)).normal_()
p_logit = s_logit.new(batch_size, max_conv_len,
self.num_speakers).normal_()
g_logit = s_logit.new(batch_size, max_conv_len, num_asv).normal_()
return (
{ # logits
"sent": w_logit,
"speaker": p_logit,
"goal": g_logit,
"state": s_logit
}, { # posterior
"conv": (MultiGaussian.unit(batch_size, 1)
.to(w_logit.device)),
"sent": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(s_logit.device)),
"speaker": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": zstate_post,
}, { # prior
"conv": (MultiGaussian.unit(batch_size, 1)
.to(w_logit.device)),
"sent": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"speaker": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": zstate_prior,
}
)
def _genconv_prior_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
raise NotImplementedError
def _encode_impl(self, data, *args, **kwargs):
raise NotImplementedError
def _decode_optimal_impl(self, data, *args, **kwargs):
raise NotImplementedError
def _genconv_post_impl(self, data, beam_size=4, max_sent_len=30,
sent_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
max_goal_len, max_state_len = g.size(-1), s.size(-1)
num_asv, max_asv_len = asv.size()
conv_mask = utils.mask(conv_lens)
g_mask = utils.mask(g_lens) & conv_mask.unsqueeze(-1)
s_mask = utils.mask(s_lens) & conv_mask.unsqueeze(-1)
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
g_asv = asv_h[g.masked_fill(~g_mask, 0)]
v = self.goal_encoder(
g_asv.view(-1, max_goal_len, self.asv_dim),
g_lens.view(-1)
)[1].view(batch_size, max_conv_len, self.goal_dim)
s_asv = asv_h[s.masked_fill(~s_mask, 0)]
t = self.state_encoder(
s_asv.view(-1, max_state_len, self.asv_dim),
s_lens.view(-1)
)[1].view(batch_size, max_conv_len, self.state_dim)
ctx, _, _ = self.ctx_encoder(torch.cat([v, t], -1), conv_lens)
zstate_prior: MultiGaussian = self.zstate_prior(
utils.shift(ctx, n=1, dim=1)
)
zstate = zstate_prior.sample()
s_logit = self.state_decoder(
zstate.view(batch_size * max_conv_len, -1),
p.view(batch_size * max_conv_len),
asv_h
)
s_prob = torch.sigmoid(s_logit)
s_prime = utils.to_sparse(s_prob > 0.5)
logprob = s_prob.masked_fill(s_prob == 0, 1.0).log().sum(-1)
return BatchData(
sent=DoublyStacked1DTensor(
value=w.view(batch_size, max_conv_len, -1),
lens=conv_lens,
lens1=w_lens.view(batch_size, max_conv_len)
),
speaker=Stacked1DTensor(
value=w.new(batch_size, max_conv_len).zero_().long(),
lens=conv_lens
),
goal=DoublyStacked1DTensor(
value=w.new(batch_size, max_conv_len, 0).zero_().long(),
lens=conv_lens,
lens1=w.new(batch_size, max_conv_len).zero_().long()
),
state=DoublyStacked1DTensor(
value=s_prime.value.view(batch_size, max_conv_len, -1),
lens=conv_lens,
lens1=s_prime.lens.view(batch_size, max_conv_len)
),
), dict(
logprob=logprob,
sent_logprob=logprob.clone().fill_(float("nan")),
goal_logprob=logprob.clone().fill_(float("nan")),
state_logprob=logprob,
spkr_logprob=logprob.clone().fill_(float("nan")),
)
class VHRED(AbstractTDA):
name = "vhred"
def __init__(self, *args,
conv_dim=256, word_dim=100, sent_dim=128, zsent_dim=16,
word_dropout=0.0, sent_dropout=0.0,
word_encoder=AbstractWordEncoder,
seq_encoder=AbstractSequenceEncoder,
sent_decoder=AbstractSentDecoder, **kwargs):
super().__init__(*args, **kwargs)
self.word_dim = word_dim
self.sent_dim = sent_dim
self.conv_dim = conv_dim
self.zsent_dim = zsent_dim
self.word_encoder_cls = word_encoder
self.seq_encoder_cls = seq_encoder
self.sent_decoder_cls = sent_decoder
self.word_dropout = word_dropout
self.sent_dropout = sent_dropout
self.word_encoder = self.word_encoder_cls(
vocab=self.vocabs.word,
word_dim=self.word_dim
)
self.sent_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=0,
hidden_dim=self.sent_dim
)
self.conv_encoder = self.seq_encoder_cls(
input_dim=self.sent_dim,
query_dim=0,
hidden_dim=self.conv_dim
)
self.sent_decoder = self.sent_decoder_cls(
vocab=self.vocabs.word,
word_encoder=self.word_encoder,
hidden_dim=(self.conv_dim + self.zsent_dim)
)
self.zsent_post = MultiGaussianLayer(
input_dim=(self.conv_dim + self.conv_dim),
hidden_dim=self.zsent_dim
)
self.zsent_prior = MultiGaussianLayer(
input_dim=self.conv_dim,
hidden_dim=self.zsent_dim
)
self.word_unk = nn.Parameter(torch.zeros(self.word_dim))
self.sent_unk = nn.Parameter(torch.zeros(self.sent_dim))
@property
def num_speakers(self):
return self.vocabs.num_speakers
def reset_parameters(self):
super().reset_parameters()
nn.init.normal_(self.word_unk, 0, 1 / math.sqrt(self.word_dim))
def dropout(self, x, dropout_rate, unk):
if not self.training:
return x
x_size = x.size()
x = x.view(-1, x.size(-1))
idx = dist.Bernoulli(dropout_rate).sample((x.size(0),)).bool()
if idx.any():
x[idx] = unk
return x.view(*x_size)
def _inference_impl(self, data, sample_scale=1.0,
dropout_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
num_asv, max_asv_len = asv.size()
num_speakers = len(self.vocabs.speaker)
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
u = self.dropout(u, self.sent_dropout, self.sent_unk)
ctx, _ = self.conv_encoder(u, conv_lens)
zsent_post: MultiGaussian = self.zsent_post(
torch.cat([utils.shift(ctx, n=1, dim=1), ctx], -1)
)
zsent_prior: MultiGaussian = self.zsent_prior(ctx)
zsent = zsent_post.sample()
w_emb = self.dropout(w_emb,
dropout_rate=self.word_dropout * dropout_scale,
unk=self.word_unk)
w_logit = self.sent_decoder(
(torch.cat([zsent, ctx], 2)
.view(batch_size * max_conv_len, -1)),
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
).view(batch_size, max_conv_len, max_sent_len, -1)
# gibberish
p_logit = w_logit.new(batch_size, max_conv_len, num_speakers).normal_()
g_logit = w_logit.new(batch_size, max_conv_len, num_asv).normal_()
s_logit = w_logit.new(batch_size, max_conv_len, num_asv).normal_()
return (
{ # logits
"sent": w_logit,
"speaker": p_logit,
"goal": g_logit,
"state": s_logit
}, { # posterior
"conv": (MultiGaussian.unit(batch_size, 1)
.to(w_logit.device)),
"sent": zsent_post,
"speaker": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
}, { # prior
"conv": (MultiGaussian.unit(batch_size, 1)
.to(w_logit.device)),
"sent": zsent_prior,
"speaker": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
}
)
def _genconv_prior_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
raise NotImplementedError
def _encode_impl(self, data, *args, **kwargs):
raise NotImplementedError
def _decode_optimal_impl(self, data, *args, **kwargs):
raise NotImplementedError
def _genconv_post_impl(self, data, beam_size=4, max_sent_len=30,
sent_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
ctx, _ = self.conv_encoder(u, conv_lens)
zsent_post: MultiGaussian = self.zsent_post(
torch.cat([utils.shift(ctx, n=1, dim=1), ctx], -1)
)
zsent = zsent_post.sample()
w, w_lens, w_prob = self.sent_decoder.generate(
h=torch.cat([zsent.view(-1, self.zsent_dim),
ctx.view(-1, self.conv_dim), ], 1),
beam_size=beam_size,
max_len=max_sent_len
)
sent_logprob = w_prob.log().view(batch_size, max_conv_len).sum(-1)
return BatchData(
sent=DoublyStacked1DTensor(
value=w.view(batch_size, max_conv_len, -1),
lens=conv_lens,
lens1=w_lens.view(batch_size, max_conv_len)
),
speaker=Stacked1DTensor(
value=w.new(batch_size, max_conv_len).zero_().long(),
lens=conv_lens
),
goal=DoublyStacked1DTensor(
value=w.new(batch_size, max_conv_len, 0).zero_().long(),
lens=conv_lens,
lens1=w.new(batch_size, max_conv_len).zero_().long()
),
state=DoublyStacked1DTensor(
value=w.new(batch_size, max_conv_len, 0).zero_().long(),
lens=conv_lens,
lens1=w.new(batch_size, max_conv_len).zero_().long()
),
), dict(
logprob=sent_logprob,
sent_logprob=sent_logprob,
goal_logprob=sent_logprob.clone().fill_(float("nan")),
state_logprob=sent_logprob.clone().fill_(float("nan")),
spkr_logprob=sent_logprob.clone().fill_(float("nan")),
)
class VHDA(AbstractTDA):
name = "vhda"
def __init__(self, *args,
conv_dim=256, word_dim=100, sent_dim=128, asv_dim=64,
state_dim=32, goal_dim=32, spkr_dim=8, ctx_dim=256,
zsent_dim=16, zstate_dim=8, zgoal_dim=8,
zspkr_dim=2, zconv_dim=16,
spkr_dropout=0.0, asv_dropout=0.0, goal_dropout=0.0,
state_dropout=0.0, sent_dropout=0.0, word_dropout=0.0,
word_encoder=AbstractWordEncoder,
seq_encoder=AbstractSequenceEncoder,
sent_decoder=AbstractSentDecoder,
state_decoder=AbstractStateDecoder,
ctx_encoder=AbstractContextEncoder, **kwargs):
super().__init__(*args, **kwargs)
self.word_dim = word_dim
self.sent_dim = sent_dim
self.asv_dim = asv_dim
self.state_dim = state_dim
self.goal_dim = goal_dim
self.spkr_dim = spkr_dim
self.conv_dim = conv_dim
self.ctx_dim = ctx_dim
self.zconv_dim = zconv_dim
self.zspkr_dim = zspkr_dim
self.zgoal_dim = zgoal_dim
self.zstate_dim = zstate_dim
self.zsent_dim = zsent_dim
self.word_encoder_cls = word_encoder
self.seq_encoder_cls = seq_encoder
self.state_decoder_cls = state_decoder
self.sent_decoder_cls = sent_decoder
self.ctx_encoder_cls = ctx_encoder
self.asv_dropout = asv_dropout
self.spkr_dropout = spkr_dropout
self.goal_dropout = goal_dropout
self.state_dropout = state_dropout
self.sent_dropout = sent_dropout
self.word_dropout = word_dropout
self.word_encoder = self.word_encoder_cls(
vocab=self.vocabs.word,
word_dim=self.word_dim
)
self.asv_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=0,
hidden_dim=self.asv_dim
)
self.post_query = nn.Parameter(torch.randn(self.sent_dim))
self.sent_post_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.sent_dim,
hidden_dim=self.sent_dim
)
self.conv_encoder = self.seq_encoder_cls(
input_dim=self.sent_dim,
query_dim=self.sent_dim,
hidden_dim=self.conv_dim
)
self.ctx_encoder = self.ctx_encoder_cls(
input_dim=(self.zconv_dim + self.spkr_dim +
self.goal_dim + self.state_dim + self.sent_dim),
ctx_dim=self.ctx_dim
)
self.spkr_encoder = torchmodels.Linear(
in_features=len(self.vocabs.speaker),
out_features=self.spkr_dim
)
self.spkr_decoder = torchmodels.Linear(
# conv_rnn + z_conv + z_speaker
in_features=self.ctx_dim + self.zconv_dim + self.zspkr_dim,
out_features=len(self.vocabs.speaker)
)
self.goal_encoder = self.seq_encoder_cls(
input_dim=self.asv_dim,
query_dim=self.zconv_dim,
hidden_dim=self.goal_dim
)
self.goal_decoder = self.state_decoder_cls(
vocabs=self.vocabs, state_type="goal",
# conv_rnn + z_conv + z_speaker + z_goal
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim + self.zgoal_dim),
asv_dim=self.asv_dim
)
self.state_encoder = self.seq_encoder_cls(
input_dim=self.asv_dim,
query_dim=self.zconv_dim,
hidden_dim=self.state_dim
)
self.state_decoder = self.state_decoder_cls(
vocabs=self.vocabs, state_type="state",
# conv_rnn + z_conv + z_speaker + z_goal + z_turn
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim + self.zgoal_dim + self.zstate_dim),
asv_dim=self.asv_dim
)
self.sent_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.zconv_dim,
hidden_dim=self.sent_dim
)
self.sent_decoder = self.sent_decoder_cls(
vocab=self.vocabs.word,
word_encoder=self.word_encoder,
# conv_rnn + z_conv + z_sp + z_goal + z_turn + z_utt
hidden_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.zgoal_dim + self.zstate_dim + self.zsent_dim)
)
self.zconv_post = MultiGaussianLayer(
input_dim=self.conv_dim,
hidden_dim=self.zconv_dim
)
self.zspkr_prior = MultiGaussianLayer(
# conv_rnn + z_conv
input_dim=self.ctx_dim + self.zconv_dim,
hidden_dim=self.zspkr_dim
)
self.zspkr_post = MultiGaussianLayer(
# conv_rnn + z_conv + h_speaker
input_dim=self.ctx_dim + self.zconv_dim + self.spkr_dim,
hidden_dim=self.zspkr_dim
)
self.zgoal_prior = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker
input_dim=self.ctx_dim + self.zconv_dim + self.zspkr_dim,
hidden_dim=self.zgoal_dim
)
self.zgoal_post = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker + h_goal
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim + self.goal_dim),
hidden_dim=self.zgoal_dim
)
self.zstate_prior = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker + z_goal
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim + self.zgoal_dim),
hidden_dim=self.zstate_dim
)
self.zstate_post = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker + z_goal + h_turn
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim + self.zgoal_dim + self.state_dim),
hidden_dim=self.zstate_dim
)
self.zsent_prior = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker + z_goal + z_turn
input_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.zgoal_dim + self.zstate_dim),
hidden_dim=self.zsent_dim
)
self.zsent_post = MultiGaussianLayer(
# conv_rnn + z_conv + z_sp + z_goal + z_turn + h_utt
input_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.zgoal_dim + self.zstate_dim + self.sent_dim),
hidden_dim=self.zsent_dim
)
self.spkr_unk = nn.Parameter(torch.zeros(self.spkr_dim))
self.goal_unk = nn.Parameter(torch.zeros(self.goal_dim))
self.state_unk = nn.Parameter(torch.zeros(self.state_dim))
self.sent_unk = nn.Parameter(torch.zeros(self.sent_dim))
self.word_unk = nn.Parameter(torch.zeros(self.word_dim))
self.asv_unk = nn.Parameter(torch.zeros(self.asv_dim))
self.spkr_eye = nn.Parameter(torch.eye(self.num_speakers),
requires_grad=False)
@property
def num_speakers(self):
return self.vocabs.num_speakers
def reset_parameters(self):
super().reset_parameters()
nn.init.normal_(self.spkr_unk, 0, 1 / math.sqrt(self.spkr_dim))
nn.init.normal_(self.goal_unk, 0, 1 / math.sqrt(self.goal_dim))
nn.init.normal_(self.state_unk, 0, 1 / math.sqrt(self.state_dim))
nn.init.normal_(self.sent_unk, 0, 1 / math.sqrt(self.sent_dim))
nn.init.normal_(self.word_unk, 0, 1 / math.sqrt(self.word_dim))
nn.init.normal_(self.asv_unk, 0, 1 / math.sqrt(self.asv_dim))
nn.init.normal_(self.post_query, 0, 1 / math.sqrt(len(self.post_query)))
def dropout(self, x, dropout_rate, unk):
if not self.training:
return x
x_size = x.size()
x = x.view(-1, x.size(-1))
idx = dist.Bernoulli(dropout_rate).sample((x.size(0),)).bool()
if idx.any():
x[idx] = unk
return x.view(*x_size)
def _inference_impl(self, data, sample_scale=1.0,
dropout_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
max_goal_len, max_state_len = g.size(-1), s.size(-1)
num_asv, max_asv_len = asv.size()
conv_mask = utils.mask(conv_lens)
w_mask = utils.mask(w_lens) & conv_mask.unsqueeze(-1)
g_mask = utils.mask(g_lens) & conv_mask.unsqueeze(-1)
s_mask = utils.mask(s_lens) & conv_mask.unsqueeze(-1)
w_emb = self.word_encoder(w, w_lens)
p_emb = self.spkr_eye[p]
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
zconv_post: MultiGaussian = self.zconv_post(c)
zconv = zconv_post.sample(sample_scale)
zconv_exp = zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
zconv_exp_flat = zconv_exp.reshape(-1, self.zconv_dim)
w_emb = self.dropout(w_emb,
dropout_rate=self.word_dropout * dropout_scale,
unk=self.word_unk)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
zconv_exp_flat
)[1].view(batch_size, max_conv_len, self.sent_dim)
g_asv = self.dropout(
asv_h[g.masked_fill(~g_mask, 0)],
dropout_rate=self.asv_dropout * dropout_scale,
unk=self.asv_unk
)
v = self.goal_encoder(
g_asv.view(-1, max_goal_len, self.asv_dim),
g_lens.view(-1),
zconv_exp_flat,
)[1].view(batch_size, max_conv_len, self.goal_dim)
s_asv = self.dropout(
asv_h[s.masked_fill(~s_mask, 0)],
dropout_rate=self.asv_dropout * dropout_scale,
unk=self.asv_unk
)
t = self.state_encoder(
s_asv.view(-1, max_state_len, self.asv_dim),
s_lens.view(-1),
zconv_exp_flat
)[1].view(batch_size, max_conv_len, self.state_dim)
u = self.dropout(u, self.sent_dropout * dropout_scale, self.sent_unk)
v = self.dropout(v, self.goal_dropout * dropout_scale, self.goal_unk)
t = self.dropout(t, self.state_dropout * dropout_scale, self.state_unk)
r = self.dropout(self.spkr_encoder(p_emb),
dropout_rate=self.spkr_dropout * dropout_scale,
unk=self.spkr_unk)
context, _, _ = self.ctx_encoder(
torch.cat([
utils.shift(u, dim=1),
utils.shift(v, dim=1),
utils.shift(t, dim=1),
utils.shift(r, dim=1),
zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
], 2),
conv_lens
)
zspkr_post: MultiGaussian = self.zspkr_post(
torch.cat([
r.view(-1, self.spkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zspkr_dim)
zspkr_prior: MultiGaussian = self.zspkr_prior(
torch.cat([
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zspkr_dim)
zspkr = (zspkr_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
zgoal_post: MultiGaussian = self.zgoal_post(
torch.cat([
v.view(-1, self.goal_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zgoal_dim)
zgoal_prior: MultiGaussian = self.zgoal_prior(
torch.cat([
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zgoal_dim)
zgoal = (zgoal_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
zstate_post: MultiGaussian = self.zstate_post(
torch.cat([
t.view(-1, self.state_dim),
zgoal.view(-1, self.zgoal_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zstate_dim)
zstate_prior: MultiGaussian = self.zstate_prior(
torch.cat([
zgoal.view(-1, self.zgoal_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zstate_dim)
zstate = (zstate_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
zsent_post: MultiGaussian = self.zsent_post(
torch.cat([
u.view(-1, self.sent_dim),
zstate.view(-1, self.zstate_dim),
zgoal.view(-1, self.zgoal_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent_prior: MultiGaussian = self.zsent_prior(
torch.cat([
zstate.view(-1, self.zstate_dim),
zgoal.view(-1, self.zgoal_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent = (zsent_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
p_logit = self.spkr_decoder(
(torch.cat([zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1))
).view(batch_size, max_conv_len, -1)
g_logit = self.goal_decoder(
(torch.cat([zgoal, zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1)),
p.view(batch_size * max_conv_len),
asv_h
).view(batch_size, max_conv_len, -1)
s_logit = self.state_decoder(
(torch.cat([zstate, zgoal, zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1)),
p.view(batch_size * max_conv_len),
asv_h
).view(batch_size, max_conv_len, -1)
w_logit = self.sent_decoder(
(torch.cat([zsent, zstate, zgoal, zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1)),
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
).view(batch_size, max_conv_len, max_sent_len, -1)
return (
{ # logits
"sent": w_logit,
"speaker": p_logit,
"goal": g_logit,
"state": s_logit
}, { # posterior
"conv": zconv_post,
"sent": zsent_post,
"speaker": zspkr_post,
"goal": zgoal_post,
"state": zstate_post,
}, { # prior
"conv": (MultiGaussian.unit(*zconv_post.size())
.to(w_logit.device)),
"sent": zsent_prior,
"speaker": zspkr_prior,
"goal": zgoal_prior,
"state": zstate_prior
}
)
def _encode_impl(self, data, *args, **kwargs):
conv_lens = data["conv_lens"]
w, w_lens = data["sent"], data["sent_lens"]
batch_size, max_conv_len, max_sent_len = w.size()
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
return self.zconv_post(c)
def _decode_optimal_impl(self, data, asv_h=None,
conv_state=None,
init_u=None, init_v=None, init_t=None, init_r=None,
max_conv_len=20, max_sent_len=30,
spkr_scale=1.0, goal_scale=1.0,
state_scale=1.0, sent_scale=1.0,
beam_size=8, **kwargs):
def pred_prob(prob, threshold=0.5):
"""Computes the prediction prob, given the threshold."""
prob = prob.clone()
mask = prob > 0.5
prob[mask] = 1 - prob[mask]
return prob
def state_sparse(mask):
# pad empty state with asv_pad at the last of the sequence
mask = mask.clone()
mask[:, asv_pad_idx] = 0 # turn off asv_pad first
state = utils.to_sparse(mask)
value, lens = state.value, state.lens
value = torch.cat([value, value.new(batch_size, 1).zero_()], 1)
value[torch.arange(batch_size), lens] = asv_pad_idx
return Stacked1DTensor(
value=value,
lens=lens + 1
)
zconv, asv, asv_lens = data["zconv"], data["asv"], data["asv_lens"]
if asv_h is None:
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
batch_size = zconv.size(0)
eoc_idx = self.vocabs.word["<eoc>"]
asv_pad = ActSlotValue("<pad>", "<pad>", "<pad>")
asv_pad_idx = self.vocabs.goal_state.asv[asv_pad]
sents, spkrs, goals, states = list(), list(), list(), list()
conv_lens = zconv.new(batch_size).long().zero_()
conv_done = zconv.new(batch_size).bool().zero_()
spkr_logprob = zconv.new(batch_size).zero_()
sent_logprob = zconv.new(batch_size).zero_()
goal_logprob = zconv.new(batch_size).zero_()
state_logprob = zconv.new(batch_size).zero_()
if init_u is None:
u = zconv.new(batch_size, self.sent_dim).zero_()
else:
u = init_u
if init_v is None:
v = zconv.new(batch_size, self.goal_dim).zero_()
else:
v = init_v
if init_t is None:
t = zconv.new(batch_size, self.state_dim).zero_()
else:
t = init_t
if init_r is None:
r = zconv.new(batch_size, self.spkr_dim).zero_()
else:
r = init_r
if conv_state is None:
conv_state = self.ctx_encoder.init_state(batch_size)
for i in range(max_conv_len):
context, _, conv_state = self.ctx_encoder(
torch.cat([u, v, t, r, zconv], 1).unsqueeze(1),
lens=u.new(batch_size).long().fill_(1),
h=conv_state
)
context = context.view(-1, self.ctx_dim)
zspkr = self.zspkr_prior(
torch.cat([context, zconv], 1)
).sample(spkr_scale)
zgoal = self.zgoal_prior(
torch.cat([zspkr, context, zconv], 1)
).sample(goal_scale)
zstate = self.zstate_prior(
torch.cat([zgoal, zspkr, context, zconv], 1)
).sample(state_scale)
zutt = self.zsent_prior(
torch.cat([zstate, zgoal, zspkr, context, zconv], 1)
).sample(sent_scale)
p_logit = self.spkr_decoder(
torch.cat([zspkr, context, zconv], 1)
)
p_prob, p = torch.softmax(p_logit, -1).max(-1)
p_logprob = p_prob.log().sum(-1)
r = self.spkr_encoder(self.spkr_eye[p])
g_logit = self.goal_decoder(
torch.cat([zgoal, zspkr, context, zconv], 1),
p, asv_h
)
g_prob = utils.sigmoid_inf(g_logit)
g = state_sparse(g_prob > 0.5)
g_logprob = pred_prob(g_prob).log().sum(-1)
v = self.goal_encoder(asv_h[g.value], g.lens, zconv)[1]
s_logit = self.state_decoder(
torch.cat([zstate, zgoal, zspkr, context, zconv], 1),
p, asv_h
)
s_prob = utils.sigmoid_inf(s_logit)
s = state_sparse(s_prob > 0.5)
s_logprob = pred_prob(s_prob).log().sum(-1)
t = self.state_encoder(asv_h[s.value], s.lens, zconv)[1]
w, w_lens, w_prob = self.sent_decoder.generate(
h=torch.cat([
zutt,
zstate,
zgoal,
zspkr,
context.view(batch_size, self.ctx_dim),
zconv
], 1),
beam_size=beam_size,
max_len=max_sent_len
)
w_logprob = w_prob.log()
sents.append(Stacked1DTensor(w, w_lens))
_, u = self.sent_encoder(self.word_encoder(w, w_lens),
w_lens, zconv)
spkrs.append(p), goals.append(g), states.append(s)
conv_lens += 1 - conv_done.long()
done = ((w == eoc_idx) & utils.mask(w_lens, w.size(1))).any(1)
conv_done |= done
sent_logprob = w_logprob.masked_fill(conv_done, 0)
goal_logprob = g_logprob.masked_fill(conv_done, 0)
state_logprob = s_logprob.masked_fill(conv_done, 0)
spkr_logprob = p_logprob.masked_fill(conv_done, 0)
if conv_done.all().item():
break
sents = utils.stack_stacked1dtensors(sents)
goals = utils.stack_stacked1dtensors(goals)
states = utils.stack_stacked1dtensors(states)
return BatchData(
sent=DoublyStacked1DTensor(
value=sents.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=sents.lens1.t().contiguous()
),
speaker=Stacked1DTensor(
value=torch.stack(spkrs).transpose(1, 0).contiguous(),
lens=conv_lens
),
goal=DoublyStacked1DTensor(
value=goals.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=goals.lens1.t().contiguous()
),
state=DoublyStacked1DTensor(
value=states.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=states.lens1.t().contiguous()
),
), dict(
logprob=sum((sent_logprob, goal_logprob,
state_logprob, spkr_logprob)),
sent_logprob=sent_logprob,
goal_logprob=goal_logprob,
state_logprob=state_logprob,
spkr_logprob=spkr_logprob,
)
def _genconv_prior_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
n = data["n"]
zconv = MultiGaussian.unit(n.item(), self.ctx_dim).to(n.device)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample, "asv": data["asv"],
"asv_lens": data["asv_lens"]},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
goal_scale=goal_scale,
state_scale=state_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
def _genconv_post_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
zconv = self._encode_impl(data)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample, "asv": data["asv"],
"asv_lens": data["asv_lens"]},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
goal_scale=goal_scale,
state_scale=state_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
class HDA(AbstractTDA):
name = "hda"
def __init__(self, *args,
conv_dim=256, word_dim=100, sent_dim=128, asv_dim=64,
state_dim=32, goal_dim=32, spkr_dim=8, ctx_dim=256,
spkr_dropout=0.0, asv_dropout=0.0, goal_dropout=0.0,
state_dropout=0.0, sent_dropout=0.0, word_dropout=0.0,
word_encoder=AbstractWordEncoder,
seq_encoder=AbstractSequenceEncoder,
sent_decoder=AbstractSentDecoder,
state_decoder=AbstractStateDecoder,
ctx_encoder=AbstractContextEncoder, **kwargs):
super().__init__(*args, **kwargs)
self.word_dim = word_dim
self.sent_dim = sent_dim
self.asv_dim = asv_dim
self.state_dim = state_dim
self.goal_dim = goal_dim
self.spkr_dim = spkr_dim
self.conv_dim = conv_dim
self.ctx_dim = ctx_dim
self.word_encoder_cls = word_encoder
self.seq_encoder_cls = seq_encoder
self.state_decoder_cls = state_decoder
self.sent_decoder_cls = sent_decoder
self.ctx_encoder_cls = ctx_encoder
self.asv_dropout = asv_dropout
self.spkr_dropout = spkr_dropout
self.goal_dropout = goal_dropout
self.state_dropout = state_dropout
self.sent_dropout = sent_dropout
self.word_dropout = word_dropout
self.word_encoder = self.word_encoder_cls(
vocab=self.vocabs.word,
word_dim=self.word_dim
)
self.asv_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=0,
hidden_dim=self.asv_dim
)
self.post_query = nn.Parameter(torch.randn(self.sent_dim))
self.sent_post_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.sent_dim,
hidden_dim=self.sent_dim
)
self.conv_encoder = self.seq_encoder_cls(
input_dim=self.sent_dim,
query_dim=self.sent_dim,
hidden_dim=self.conv_dim
)
self.ctx_encoder = self.ctx_encoder_cls(
input_dim=(self.conv_dim + self.spkr_dim +
self.goal_dim + self.state_dim + self.sent_dim),
ctx_dim=self.ctx_dim
)
self.spkr_encoder = torchmodels.Linear(
in_features=len(self.vocabs.speaker),
out_features=self.spkr_dim
)
self.spkr_decoder = torchmodels.Linear(
# conv_rnn + z_conv + z_speaker
in_features=self.ctx_dim + self.conv_dim + self.spkr_dim,
out_features=len(self.vocabs.speaker)
)
self.goal_encoder = self.seq_encoder_cls(
input_dim=self.asv_dim,
query_dim=self.conv_dim,
hidden_dim=self.goal_dim
)
self.goal_decoder = self.state_decoder_cls(
vocabs=self.vocabs, state_type="goal",
# conv_rnn + z_conv + z_speaker + z_goal
input_dim=(self.ctx_dim + self.conv_dim +
self.spkr_dim + self.goal_dim),
asv_dim=self.asv_dim
)
self.state_encoder = self.seq_encoder_cls(
input_dim=self.asv_dim,
query_dim=self.conv_dim,
hidden_dim=self.state_dim
)
self.state_decoder = self.state_decoder_cls(
vocabs=self.vocabs, state_type="state",
# conv_rnn + z_conv + z_speaker + z_goal + z_turn
input_dim=(self.ctx_dim + self.conv_dim +
self.spkr_dim + self.goal_dim + self.state_dim),
asv_dim=self.asv_dim
)
self.sent_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.conv_dim,
hidden_dim=self.sent_dim
)
self.sent_decoder = self.sent_decoder_cls(
vocab=self.vocabs.word,
word_encoder=self.word_encoder,
# conv_rnn + z_conv + z_sp + z_goal + z_turn + z_utt
hidden_dim=(self.ctx_dim + self.conv_dim + self.spkr_dim +
self.goal_dim + self.state_dim + self.sent_dim)
)
self.spkr_unk = nn.Parameter(torch.zeros(self.spkr_dim))
self.goal_unk = nn.Parameter(torch.zeros(self.goal_dim))
self.state_unk = nn.Parameter(torch.zeros(self.state_dim))
self.sent_unk = nn.Parameter(torch.zeros(self.sent_dim))
self.word_unk = nn.Parameter(torch.zeros(self.word_dim))
self.asv_unk = nn.Parameter(torch.zeros(self.asv_dim))
self.spkr_eye = nn.Parameter(torch.eye(self.num_speakers),
requires_grad=False)
@property
def num_speakers(self):
return self.vocabs.num_speakers
def reset_parameters(self):
super().reset_parameters()
nn.init.normal_(self.spkr_unk, 0, 1 / math.sqrt(self.spkr_dim))
nn.init.normal_(self.goal_unk, 0, 1 / math.sqrt(self.goal_dim))
nn.init.normal_(self.state_unk, 0, 1 / math.sqrt(self.state_dim))
nn.init.normal_(self.sent_unk, 0, 1 / math.sqrt(self.sent_dim))
nn.init.normal_(self.word_unk, 0, 1 / math.sqrt(self.word_dim))
nn.init.normal_(self.asv_unk, 0, 1 / math.sqrt(self.asv_dim))
nn.init.normal_(self.post_query, 0, 1 / math.sqrt(len(self.post_query)))
def dropout(self, x, dropout_rate, unk):
if not self.training:
return x
x_size = x.size()
x = x.view(-1, x.size(-1))
idx = dist.Bernoulli(dropout_rate).sample((x.size(0),)).bool()
if idx.any():
x[idx] = unk
return x.view(*x_size)
def _inference_impl(self, data, sample_scale=1.0,
dropout_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
max_goal_len, max_state_len = g.size(-1), s.size(-1)
num_asv, max_asv_len = asv.size()
conv_mask = utils.mask(conv_lens)
w_mask = utils.mask(w_lens) & conv_mask.unsqueeze(-1)
g_mask = utils.mask(g_lens) & conv_mask.unsqueeze(-1)
s_mask = utils.mask(s_lens) & conv_mask.unsqueeze(-1)
w_emb = self.word_encoder(w, w_lens)
p_emb = self.spkr_eye[p]
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
c_exp = c.unsqueeze(1).expand(-1, max_conv_len, -1)
c_exp_flat = c_exp.reshape(-1, self.conv_dim)
w_emb = self.dropout(w_emb,
dropout_rate=self.word_dropout * dropout_scale,
unk=self.word_unk)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
c_exp_flat
)[1].view(batch_size, max_conv_len, self.sent_dim)
g_asv = self.dropout(
asv_h[g.masked_fill(~g_mask, 0)],
dropout_rate=self.asv_dropout * dropout_scale,
unk=self.asv_unk
)
v = self.goal_encoder(
g_asv.view(-1, max_goal_len, self.asv_dim),
g_lens.view(-1),
c_exp_flat,
)[1].view(batch_size, max_conv_len, self.goal_dim)
s_asv = self.dropout(
asv_h[s.masked_fill(~s_mask, 0)],
dropout_rate=self.asv_dropout * dropout_scale,
unk=self.asv_unk
)
t = self.state_encoder(
s_asv.view(-1, max_state_len, self.asv_dim),
s_lens.view(-1),
c_exp_flat
)[1].view(batch_size, max_conv_len, self.state_dim)
u = self.dropout(u, self.sent_dropout * dropout_scale, self.sent_unk)
v = self.dropout(v, self.goal_dropout * dropout_scale, self.goal_unk)
t = self.dropout(t, self.state_dropout * dropout_scale, self.state_unk)
r = self.dropout(self.spkr_encoder(p_emb),
dropout_rate=self.spkr_dropout * dropout_scale,
unk=self.spkr_unk)
context, _, _ = self.ctx_encoder(
torch.cat([
utils.shift(u, dim=1),
utils.shift(v, dim=1),
utils.shift(t, dim=1),
utils.shift(r, dim=1),
c.unsqueeze(1).expand(-1, max_conv_len, -1)
], 2),
conv_lens
)
p_logit = self.spkr_decoder(
(torch.cat([r, context, c_exp], 2)
.view(batch_size * max_conv_len, -1))
).view(batch_size, max_conv_len, -1)
g_logit = self.goal_decoder(
(torch.cat([v, r, context, c_exp], 2)
.view(batch_size * max_conv_len, -1)),
p.view(batch_size * max_conv_len),
asv_h
).view(batch_size, max_conv_len, -1)
s_logit = self.state_decoder(
(torch.cat([t, v, r, context, c_exp], 2)
.view(batch_size * max_conv_len, -1)),
p.view(batch_size * max_conv_len),
asv_h
).view(batch_size, max_conv_len, -1)
w_logit = self.sent_decoder(
(torch.cat([u, t, v, r, context, c_exp], 2)
.view(batch_size * max_conv_len, -1)),
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
).view(batch_size, max_conv_len, max_sent_len, -1)
conv_dist = MultiGaussian.unit(*c.size()).to(w.device)
conv_dist.mu = c
return (
{ # logits
"sent": w_logit,
"speaker": p_logit,
"goal": g_logit,
"state": s_logit
}, { # posterior
"conv": conv_dist,
"sent": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device),
"speaker": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device),
"goal": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device),
"state": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device),
}, { # prior
"conv": MultiGaussian.unit(*conv_dist.size()).to(c.device),
"sent": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device),
"speaker": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device),
"goal": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device),
"state": MultiGaussian.unit(batch_size, max_conv_len, 1).to(
w.device)
}
)
def _encode_impl(self, data, *args, **kwargs):
conv_lens = data["conv_lens"]
w, w_lens = data["sent"], data["sent_lens"]
batch_size, max_conv_len, max_sent_len = w.size()
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
return MultiGaussian(c, c.clone().detach().fill_(float("-inf")))
def _decode_optimal_impl(self, data, asv_h=None,
conv_state=None,
init_u=None, init_v=None, init_t=None, init_r=None,
max_conv_len=20, max_sent_len=30,
spkr_scale=1.0, goal_scale=1.0,
state_scale=1.0, sent_scale=1.0,
beam_size=8, **kwargs):
def pred_prob(prob, threshold=0.5):
"""Computes the prediction prob, given the threshold."""
prob = prob.clone()
mask = prob > 0.5
prob[mask] = 1 - prob[mask]
return prob
def state_sparse(mask):
# pad empty state with asv_pad at the last of the sequence
mask = mask.clone()
mask[:, asv_pad_idx] = 0 # turn off asv_pad first
state = utils.to_sparse(mask)
value, lens = state.value, state.lens
value = torch.cat([value, value.new(batch_size, 1).zero_()], 1)
value[torch.arange(batch_size), lens] = asv_pad_idx
return Stacked1DTensor(
value=value,
lens=lens + 1
)
c, asv, asv_lens = data["zconv"], data["asv"], data["asv_lens"]
if asv_h is None:
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
batch_size = c.size(0)
eoc_idx = self.vocabs.word["<eoc>"]
asv_pad = ActSlotValue("<pad>", "<pad>", "<pad>")
asv_pad_idx = self.vocabs.goal_state.asv[asv_pad]
sents, spkrs, goals, states = list(), list(), list(), list()
conv_lens = c.new(batch_size).long().zero_()
conv_done = c.new(batch_size).bool().zero_()
spkr_logprob = c.new(batch_size).zero_()
sent_logprob = c.new(batch_size).zero_()
goal_logprob = c.new(batch_size).zero_()
state_logprob = c.new(batch_size).zero_()
if init_u is None:
u = c.new(batch_size, self.sent_dim).zero_()
else:
u = init_u
if init_v is None:
v = c.new(batch_size, self.goal_dim).zero_()
else:
v = init_v
if init_t is None:
t = c.new(batch_size, self.state_dim).zero_()
else:
t = init_t
if init_r is None:
r = c.new(batch_size, self.spkr_dim).zero_()
else:
r = init_r
if conv_state is None:
conv_state = self.ctx_encoder.init_state(batch_size)
for i in range(max_conv_len):
context, _, conv_state = self.ctx_encoder(
torch.cat([u, v, t, r, c], 1).unsqueeze(1),
lens=u.new(batch_size).long().fill_(1),
h=conv_state
)
context = context.view(-1, self.ctx_dim)
r = self._perturb(r, max(spkr_scale - 1.0, 0.0))
v = self._perturb(v, max(goal_scale - 1.0, 0.0))
t = self._perturb(t, max(state_scale - 1.0, 0.0))
u = self._perturb(u, max(sent_scale - 1.0, 0.0))
p_logit = self.spkr_decoder(
torch.cat([r, context, c], 1)
)
p_prob, p = torch.softmax(p_logit, -1).max(-1)
p_logprob = p_prob.log().sum(-1)
r = self.spkr_encoder(self.spkr_eye[p])
g_logit = self.goal_decoder(
torch.cat([v, r, context, c], 1),
p, asv_h
)
g_prob = utils.sigmoid_inf(g_logit)
g = state_sparse(g_prob > 0.5)
g_logprob = pred_prob(g_prob).log().sum(-1)
v = self.goal_encoder(asv_h[g.value], g.lens, c)[1]
s_logit = self.state_decoder(
torch.cat([t, v, r, context, c], 1),
p, asv_h
)
s_prob = utils.sigmoid_inf(s_logit)
s = state_sparse(s_prob > 0.5)
s_logprob = pred_prob(s_prob).log().sum(-1)
t = self.state_encoder(asv_h[s.value], s.lens, c)[1]
w, w_lens, w_prob = self.sent_decoder.generate(
h=torch.cat([
u,
t,
v,
r,
context.view(batch_size, self.ctx_dim),
c
], 1),
beam_size=beam_size,
max_len=max_sent_len
)
w_logprob = w_prob.log()
sents.append(Stacked1DTensor(w, w_lens))
_, u = self.sent_encoder(self.word_encoder(w, w_lens),
w_lens, c)
spkrs.append(p), goals.append(g), states.append(s)
conv_lens += 1 - conv_done.long()
done = ((w == eoc_idx) & utils.mask(w_lens, w.size(1))).any(1)
conv_done |= done
sent_logprob = w_logprob.masked_fill(conv_done, 0)
goal_logprob = g_logprob.masked_fill(conv_done, 0)
state_logprob = s_logprob.masked_fill(conv_done, 0)
spkr_logprob = p_logprob.masked_fill(conv_done, 0)
if conv_done.all().item():
break
sents = utils.stack_stacked1dtensors(sents)
goals = utils.stack_stacked1dtensors(goals)
states = utils.stack_stacked1dtensors(states)
return BatchData(
sent=DoublyStacked1DTensor(
value=sents.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=sents.lens1.t().contiguous()
),
speaker=Stacked1DTensor(
value=torch.stack(spkrs).transpose(1, 0).contiguous(),
lens=conv_lens
),
goal=DoublyStacked1DTensor(
value=goals.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=goals.lens1.t().contiguous()
),
state=DoublyStacked1DTensor(
value=states.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=states.lens1.t().contiguous()
),
), dict(
logprob=sum((sent_logprob, goal_logprob,
state_logprob, spkr_logprob)),
sent_logprob=sent_logprob,
goal_logprob=goal_logprob,
state_logprob=state_logprob,
spkr_logprob=spkr_logprob,
)
def _genconv_prior_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
raise NotImplementedError
@staticmethod
def _perturb(x, eps):
return x + x.clone().uniform_(-eps, eps)
def _genconv_post_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
c = self._encode_impl(data).mu
c_sample = self._perturb(c, max(conv_scale - 1.0, 0.0))
batch, info = self._decode_optimal_impl(
data={"zconv": c, "asv": data["asv"],
"asv_lens": data["asv_lens"]},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
goal_scale=goal_scale,
state_scale=state_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
conv_dist = MultiGaussian.unit(*c.size()).to(c.device)
conv_dist.mu = c
info["zconv"] = conv_dist
info["zconv-sample"] = c_sample
return batch, info
class VHDAWithoutGoal(AbstractTDA):
name = "vhda-nogoal"
def __init__(self, *args,
conv_dim=256, word_dim=100, sent_dim=128, asv_dim=64,
state_dim=32, spkr_dim=8, ctx_dim=256,
zsent_dim=16, zstate_dim=8,
zspkr_dim=2, zconv_dim=16,
spkr_dropout=0.0, asv_dropout=0.0,
state_dropout=0.0, sent_dropout=0.0, word_dropout=0.0,
word_encoder=AbstractWordEncoder,
seq_encoder=AbstractSequenceEncoder,
sent_decoder=AbstractSentDecoder,
state_decoder=AbstractStateDecoder,
ctx_encoder=AbstractContextEncoder, **kwargs):
super().__init__(*args, **kwargs)
self.word_dim = word_dim
self.sent_dim = sent_dim
self.asv_dim = asv_dim
self.state_dim = state_dim
self.spkr_dim = spkr_dim
self.conv_dim = conv_dim
self.ctx_dim = ctx_dim
self.zconv_dim = zconv_dim
self.zspkr_dim = zspkr_dim
self.zstate_dim = zstate_dim
self.zsent_dim = zsent_dim
self.word_encoder_cls = word_encoder
self.seq_encoder_cls = seq_encoder
self.state_decoder_cls = state_decoder
self.sent_decoder_cls = sent_decoder
self.ctx_encoder_cls = ctx_encoder
self.asv_dropout = asv_dropout
self.spkr_dropout = spkr_dropout
self.state_dropout = state_dropout
self.sent_dropout = sent_dropout
self.word_dropout = word_dropout
self.word_encoder = self.word_encoder_cls(
vocab=self.vocabs.word,
word_dim=self.word_dim
)
self.asv_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=0,
hidden_dim=self.asv_dim
)
self.post_query = nn.Parameter(torch.randn(self.sent_dim))
self.sent_post_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.sent_dim,
hidden_dim=self.sent_dim
)
self.conv_encoder = self.seq_encoder_cls(
input_dim=self.sent_dim,
query_dim=self.sent_dim,
hidden_dim=self.conv_dim
)
self.ctx_encoder = self.ctx_encoder_cls(
input_dim=(self.zconv_dim + self.spkr_dim +
self.state_dim + self.sent_dim),
ctx_dim=self.ctx_dim
)
self.spkr_encoder = torchmodels.Linear(
in_features=len(self.vocabs.speaker),
out_features=self.spkr_dim
)
self.spkr_decoder = torchmodels.Linear(
# conv_rnn + z_conv + z_speaker
in_features=self.ctx_dim + self.zconv_dim + self.zspkr_dim,
out_features=len(self.vocabs.speaker)
)
self.state_encoder = self.seq_encoder_cls(
input_dim=self.asv_dim,
query_dim=self.zconv_dim,
hidden_dim=self.state_dim
)
self.state_decoder = self.state_decoder_cls(
vocabs=self.vocabs, state_type="state",
# conv_rnn + z_conv + z_speaker + z_turn
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim + self.zstate_dim),
asv_dim=self.asv_dim
)
self.sent_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.zconv_dim,
hidden_dim=self.sent_dim
)
self.sent_decoder = self.sent_decoder_cls(
vocab=self.vocabs.word,
word_encoder=self.word_encoder,
# conv_rnn + z_conv + z_sp + z_turn + z_utt
hidden_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.zstate_dim + self.zsent_dim)
)
self.zconv_post = MultiGaussianLayer(
input_dim=self.conv_dim,
hidden_dim=self.zconv_dim
)
self.zspkr_prior = MultiGaussianLayer(
# conv_rnn + z_conv
input_dim=self.ctx_dim + self.zconv_dim,
hidden_dim=self.zspkr_dim
)
self.zspkr_post = MultiGaussianLayer(
# conv_rnn + z_conv + h_speaker
input_dim=self.ctx_dim + self.zconv_dim + self.spkr_dim,
hidden_dim=self.zspkr_dim
)
self.zstate_prior = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim),
hidden_dim=self.zstate_dim
)
self.zstate_post = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker + h_turn
input_dim=(self.ctx_dim + self.zconv_dim +
self.zspkr_dim + self.state_dim),
hidden_dim=self.zstate_dim
)
self.zsent_prior = MultiGaussianLayer(
# conv_rnn + z_conv + z_speaker + z_turn
input_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.zstate_dim),
hidden_dim=self.zsent_dim
)
self.zsent_post = MultiGaussianLayer(
# conv_rnn + z_conv + z_sp + z_turn + h_utt
input_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.zstate_dim + self.sent_dim),
hidden_dim=self.zsent_dim
)
self.spkr_unk = nn.Parameter(torch.zeros(self.spkr_dim))
self.state_unk = nn.Parameter(torch.zeros(self.state_dim))
self.sent_unk = nn.Parameter(torch.zeros(self.sent_dim))
self.word_unk = nn.Parameter(torch.zeros(self.word_dim))
self.asv_unk = nn.Parameter(torch.zeros(self.asv_dim))
self.spkr_eye = nn.Parameter(torch.eye(self.num_speakers),
requires_grad=False)
@property
def num_speakers(self):
return self.vocabs.num_speakers
def reset_parameters(self):
super().reset_parameters()
nn.init.normal_(self.spkr_unk, 0, 1 / math.sqrt(self.spkr_dim))
nn.init.normal_(self.state_unk, 0, 1 / math.sqrt(self.state_dim))
nn.init.normal_(self.sent_unk, 0, 1 / math.sqrt(self.sent_dim))
nn.init.normal_(self.word_unk, 0, 1 / math.sqrt(self.word_dim))
nn.init.normal_(self.asv_unk, 0, 1 / math.sqrt(self.asv_dim))
nn.init.normal_(self.post_query, 0, 1 / math.sqrt(len(self.post_query)))
def dropout(self, x, dropout_rate, unk):
if not self.training:
return x
x_size = x.size()
x = x.view(-1, x.size(-1))
idx = dist.Bernoulli(dropout_rate).sample((x.size(0),)).bool()
if idx.any():
x[idx] = unk
return x.view(*x_size)
def _inference_impl(self, data, sample_scale=1.0,
dropout_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
max_state_len = s.size(-1)
num_asv, max_asv_len = asv.size()
conv_mask = utils.mask(conv_lens)
w_mask = utils.mask(w_lens) & conv_mask.unsqueeze(-1)
g_mask = utils.mask(g_lens) & conv_mask.unsqueeze(-1)
s_mask = utils.mask(s_lens) & conv_mask.unsqueeze(-1)
w_emb = self.word_encoder(w, w_lens)
p_emb = self.spkr_eye[p]
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
zconv_post: MultiGaussian = self.zconv_post(c)
zconv = zconv_post.sample(sample_scale)
zconv_exp = zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
zconv_exp_flat = zconv_exp.reshape(-1, self.zconv_dim)
w_emb = self.dropout(w_emb,
dropout_rate=self.word_dropout * dropout_scale,
unk=self.word_unk)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
zconv_exp_flat
)[1].view(batch_size, max_conv_len, self.sent_dim)
s_asv = self.dropout(
asv_h[s.masked_fill(~s_mask, 0)],
dropout_rate=self.asv_dropout * dropout_scale,
unk=self.asv_unk
)
t = self.state_encoder(
s_asv.view(-1, max_state_len, self.asv_dim),
s_lens.view(-1),
zconv_exp_flat
)[1].view(batch_size, max_conv_len, self.state_dim)
u = self.dropout(u, self.sent_dropout * dropout_scale, self.sent_unk)
t = self.dropout(t, self.state_dropout * dropout_scale, self.state_unk)
r = self.dropout(self.spkr_encoder(p_emb),
dropout_rate=self.spkr_dropout * dropout_scale,
unk=self.spkr_unk)
context, _, _ = self.ctx_encoder(
torch.cat([
utils.shift(u, dim=1),
utils.shift(t, dim=1),
utils.shift(r, dim=1),
zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
], 2),
conv_lens
)
zspkr_post: MultiGaussian = self.zspkr_post(
torch.cat([
r.view(-1, self.spkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zspkr_dim)
zspkr_prior: MultiGaussian = self.zspkr_prior(
torch.cat([
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zspkr_dim)
zspkr = (zspkr_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
zstate_post: MultiGaussian = self.zstate_post(
torch.cat([
t.view(-1, self.state_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zstate_dim)
zstate_prior: MultiGaussian = self.zstate_prior(
torch.cat([
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zstate_dim)
zstate = (zstate_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
zsent_post: MultiGaussian = self.zsent_post(
torch.cat([
u.view(-1, self.sent_dim),
zstate.view(-1, self.zstate_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent_prior: MultiGaussian = self.zsent_prior(
torch.cat([
zstate.view(-1, self.zstate_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent = (zsent_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
p_logit = self.spkr_decoder(
(torch.cat([zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1))
).view(batch_size, max_conv_len, -1)
s_logit = self.state_decoder(
(torch.cat([zstate, zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1)),
p.view(batch_size * max_conv_len),
asv_h
).view(batch_size, max_conv_len, -1)
w_logit = self.sent_decoder(
(torch.cat([zsent, zstate, zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1)),
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
).view(batch_size, max_conv_len, max_sent_len, -1)
return (
{ # logits
"sent": w_logit,
"speaker": p_logit,
"goal": s_logit.detach().clone(),
"state": s_logit
}, { # posterior
"conv": zconv_post,
"sent": zsent_post,
"speaker": zspkr_post,
"goal": MultiGaussian.unit(*zstate_post.size()).to(w.device),
"state": zstate_post,
}, { # prior
"conv": (MultiGaussian.unit(*zconv_post.size())
.to(w_logit.device)),
"sent": zsent_prior,
"speaker": zspkr_prior,
"goal": MultiGaussian.unit(*zstate_prior.size()).to(w.device),
"state": zstate_prior
}
)
def _encode_impl(self, data, *args, **kwargs):
conv_lens = data["conv_lens"]
w, w_lens = data["sent"], data["sent_lens"]
batch_size, max_conv_len, max_sent_len = w.size()
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
return self.zconv_post(c)
def _decode_optimal_impl(self, data, asv_h=None,
conv_state=None,
init_u=None, init_v=None, init_t=None, init_r=None,
max_conv_len=20, max_sent_len=30,
spkr_scale=1.0, goal_scale=1.0,
state_scale=1.0, sent_scale=1.0,
beam_size=8, **kwargs):
def pred_prob(prob, threshold=0.5):
"""Computes the prediction prob, given the threshold."""
prob = prob.clone()
mask = prob > 0.5
prob[mask] = 1 - prob[mask]
return prob
def state_sparse(mask):
# pad empty state with asv_pad at the last of the sequence
mask = mask.clone()
mask[:, asv_pad_idx] = 0 # turn off asv_pad first
state = utils.to_sparse(mask)
value, lens = state.value, state.lens
value = torch.cat([value, value.new(batch_size, 1).zero_()], 1)
value[torch.arange(batch_size), lens] = asv_pad_idx
return Stacked1DTensor(
value=value,
lens=lens + 1
)
zconv, asv, asv_lens = data["zconv"], data["asv"], data["asv_lens"]
if asv_h is None:
asv_emb = self.word_encoder(asv, asv_lens)
_, asv_h = self.asv_encoder(asv_emb, asv_lens)
batch_size = zconv.size(0)
eoc_idx = self.vocabs.word["<eoc>"]
asv_pad = ActSlotValue("<pad>", "<pad>", "<pad>")
asv_pad_idx = self.vocabs.goal_state.asv[asv_pad]
sents, spkrs, states = list(), list(), list()
conv_lens = zconv.new(batch_size).long().zero_()
conv_done = zconv.new(batch_size).bool().zero_()
spkr_logprob = zconv.new(batch_size).zero_()
sent_logprob = zconv.new(batch_size).zero_()
state_logprob = zconv.new(batch_size).zero_()
if init_u is None:
u = zconv.new(batch_size, self.sent_dim).zero_()
else:
u = init_u
if init_t is None:
t = zconv.new(batch_size, self.state_dim).zero_()
else:
t = init_t
if init_r is None:
r = zconv.new(batch_size, self.spkr_dim).zero_()
else:
r = init_r
if conv_state is None:
conv_state = self.ctx_encoder.init_state(batch_size)
for i in range(max_conv_len):
context, _, conv_state = self.ctx_encoder(
torch.cat([u, t, r, zconv], 1).unsqueeze(1),
lens=u.new(batch_size).long().fill_(1),
h=conv_state
)
context = context.view(-1, self.ctx_dim)
zspkr = self.zspkr_prior(
torch.cat([context, zconv], 1)
).sample(spkr_scale)
zstate = self.zstate_prior(
torch.cat([zspkr, context, zconv], 1)
).sample(state_scale)
zutt = self.zsent_prior(
torch.cat([zstate, zspkr, context, zconv], 1)
).sample(sent_scale)
p_logit = self.spkr_decoder(
torch.cat([zspkr, context, zconv], 1)
)
p_prob, p = torch.softmax(p_logit, -1).max(-1)
p_logprob = p_prob.log().sum(-1)
r = self.spkr_encoder(self.spkr_eye[p])
s_logit = self.state_decoder(
torch.cat([zstate, zspkr, context, zconv], 1),
p, asv_h
)
s_prob = utils.sigmoid_inf(s_logit)
s = state_sparse(s_prob > 0.5)
s_logprob = pred_prob(s_prob).log().sum(-1)
t = self.state_encoder(asv_h[s.value], s.lens, zconv)[1]
w, w_lens, w_prob = self.sent_decoder.generate(
h=torch.cat([
zutt,
zstate,
zspkr,
context.view(batch_size, self.ctx_dim),
zconv
], 1),
beam_size=beam_size,
max_len=max_sent_len
)
w_logprob = w_prob.log()
sents.append(Stacked1DTensor(w, w_lens))
_, u = self.sent_encoder(self.word_encoder(w, w_lens),
w_lens, zconv)
spkrs.append(p), states.append(s)
conv_lens += 1 - conv_done.long()
done = ((w == eoc_idx) & utils.mask(w_lens, w.size(1))).any(1)
conv_done |= done
sent_logprob = w_logprob.masked_fill(conv_done, 0)
state_logprob = s_logprob.masked_fill(conv_done, 0)
spkr_logprob = p_logprob.masked_fill(conv_done, 0)
if conv_done.all().item():
break
sents = utils.stack_stacked1dtensors(sents)
states = utils.stack_stacked1dtensors(states)
return BatchData(
sent=DoublyStacked1DTensor(
value=sents.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=sents.lens1.t().contiguous()
),
speaker=Stacked1DTensor(
value=torch.stack(spkrs).transpose(1, 0).contiguous(),
lens=conv_lens
),
goal=DoublyStacked1DTensor(
value=zconv.new(batch_size, max_conv_len, 0).zero_().long(),
lens=conv_lens,
lens1=zconv.new(batch_size, max_conv_len).zero_().long()
),
state=DoublyStacked1DTensor(
value=states.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=states.lens1.t().contiguous()
),
), dict(
logprob=sum((sent_logprob, state_logprob, spkr_logprob)),
sent_logprob=sent_logprob,
goal_logprob=sent_logprob.clone().fill_(float("nan")),
state_logprob=state_logprob,
spkr_logprob=spkr_logprob,
)
def _genconv_prior_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
n = data["n"]
zconv = MultiGaussian.unit(n.item(), self.ctx_dim).to(n.device)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample, "asv": data["asv"],
"asv_lens": data["asv_lens"]},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
goal_scale=goal_scale,
state_scale=state_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
def _genconv_post_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
zconv = self._encode_impl(data)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample, "asv": data["asv"],
"asv_lens": data["asv_lens"]},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
goal_scale=goal_scale,
state_scale=state_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
class VHDAWithoutGoalAct(AbstractTDA):
name = "vhda-nogoalact"
def __init__(self, *args,
conv_dim=256, word_dim=100, sent_dim=128,
spkr_dim=8, ctx_dim=256,
zsent_dim=16,
zspkr_dim=2, zconv_dim=16,
spkr_dropout=0.0, sent_dropout=0.0, word_dropout=0.0,
word_encoder=AbstractWordEncoder,
seq_encoder=AbstractSequenceEncoder,
sent_decoder=AbstractSentDecoder,
ctx_encoder=AbstractContextEncoder, **kwargs):
super().__init__(*args, **kwargs)
self.word_dim = word_dim
self.sent_dim = sent_dim
self.spkr_dim = spkr_dim
self.conv_dim = conv_dim
self.ctx_dim = ctx_dim
self.zconv_dim = zconv_dim
self.zspkr_dim = zspkr_dim
self.zsent_dim = zsent_dim
self.word_encoder_cls = word_encoder
self.seq_encoder_cls = seq_encoder
self.sent_decoder_cls = sent_decoder
self.ctx_encoder_cls = ctx_encoder
self.spkr_dropout = spkr_dropout
self.sent_dropout = sent_dropout
self.word_dropout = word_dropout
self.word_encoder = self.word_encoder_cls(
vocab=self.vocabs.word,
word_dim=self.word_dim
)
self.post_query = nn.Parameter(torch.randn(self.sent_dim))
self.sent_post_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.sent_dim,
hidden_dim=self.sent_dim
)
self.conv_encoder = self.seq_encoder_cls(
input_dim=self.sent_dim,
query_dim=self.sent_dim,
hidden_dim=self.conv_dim
)
self.ctx_encoder = self.ctx_encoder_cls(
input_dim=(self.zconv_dim + self.spkr_dim +
self.goal_dim + self.state_dim + self.sent_dim),
ctx_dim=self.ctx_dim
)
self.spkr_encoder = torchmodels.Linear(
in_features=len(self.vocabs.speaker),
out_features=self.spkr_dim
)
self.spkr_decoder = torchmodels.Linear(
# conv_rnn + z_conv + z_speaker
in_features=self.ctx_dim + self.zconv_dim + self.zspkr_dim,
out_features=len(self.vocabs.speaker)
)
self.sent_encoder = self.seq_encoder_cls(
input_dim=self.word_dim,
query_dim=self.zconv_dim,
hidden_dim=self.sent_dim
)
self.sent_decoder = self.sent_decoder_cls(
vocab=self.vocabs.word,
word_encoder=self.word_encoder,
hidden_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.zsent_dim)
)
self.zconv_post = MultiGaussianLayer(
input_dim=self.conv_dim,
hidden_dim=self.zconv_dim
)
self.zspkr_prior = MultiGaussianLayer(
# conv_rnn + z_conv
input_dim=self.ctx_dim + self.zconv_dim,
hidden_dim=self.zspkr_dim
)
self.zspkr_post = MultiGaussianLayer(
# conv_rnn + z_conv + h_speaker
input_dim=self.ctx_dim + self.zconv_dim + self.spkr_dim,
hidden_dim=self.zspkr_dim
)
self.zsent_prior = MultiGaussianLayer(
input_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim),
hidden_dim=self.zsent_dim
)
self.zsent_post = MultiGaussianLayer(
input_dim=(self.ctx_dim + self.zconv_dim + self.zspkr_dim +
self.sent_dim),
hidden_dim=self.zsent_dim
)
self.spkr_unk = nn.Parameter(torch.zeros(self.spkr_dim))
self.sent_unk = nn.Parameter(torch.zeros(self.sent_dim))
self.word_unk = nn.Parameter(torch.zeros(self.word_dim))
self.spkr_eye = nn.Parameter(torch.eye(self.num_speakers),
requires_grad=False)
@property
def num_speakers(self):
return self.vocabs.num_speakers
def reset_parameters(self):
super().reset_parameters()
nn.init.normal_(self.spkr_unk, 0, 1 / math.sqrt(self.spkr_dim))
nn.init.normal_(self.sent_unk, 0, 1 / math.sqrt(self.sent_dim))
nn.init.normal_(self.word_unk, 0, 1 / math.sqrt(self.word_dim))
nn.init.normal_(self.post_query, 0, 1 / math.sqrt(len(self.post_query)))
def dropout(self, x, dropout_rate, unk):
if not self.training:
return x
x_size = x.size()
x = x.view(-1, x.size(-1))
idx = dist.Bernoulli(dropout_rate).sample((x.size(0),)).bool()
if idx.any():
x[idx] = unk
return x.view(*x_size)
def _inference_impl(self, data, sample_scale=1.0,
dropout_scale=1.0, **kwargs):
conv_lens, w, w_lens, p, g, g_lens, s, s_lens, asv, asv_lens = \
self.tuplize_data(data)
batch_size, max_conv_len, max_sent_len = w.size()
num_asv, max_asv_len = asv.size()
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
p_emb = self.spkr_eye[p]
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
zconv_post: MultiGaussian = self.zconv_post(c)
zconv = zconv_post.sample(sample_scale)
zconv_exp = zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
zconv_exp_flat = zconv_exp.reshape(-1, self.zconv_dim)
w_emb = self.dropout(w_emb,
dropout_rate=self.word_dropout * dropout_scale,
unk=self.word_unk)
u = self.sent_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
zconv_exp_flat
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = self.dropout(u, self.sent_dropout * dropout_scale, self.sent_unk)
r = self.dropout(self.spkr_encoder(p_emb),
dropout_rate=self.spkr_dropout * dropout_scale,
unk=self.spkr_unk)
context, _, _ = self.ctx_encoder(
torch.cat([
utils.shift(u, dim=1),
utils.shift(r, dim=1),
zconv.unsqueeze(1).expand(-1, max_conv_len, -1)
], 2),
conv_lens
)
zspkr_post: MultiGaussian = self.zspkr_post(
torch.cat([
r.view(-1, self.spkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zspkr_dim)
zspkr_prior: MultiGaussian = self.zspkr_prior(
torch.cat([
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zspkr_dim)
zspkr = (zspkr_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
zsent_post: MultiGaussian = self.zsent_post(
torch.cat([
u.view(-1, self.sent_dim),
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent_prior: MultiGaussian = self.zsent_prior(
torch.cat([
zspkr.view(-1, self.zspkr_dim),
context.view(-1, self.ctx_dim),
zconv_exp_flat
], 1)
).view_(batch_size, max_conv_len, self.zsent_dim)
zsent = (zsent_post.sample(sample_scale)
.view(batch_size, max_conv_len, -1)
.masked_fill(~conv_mask.unsqueeze(-1), 0))
p_logit = self.spkr_decoder(
(torch.cat([zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1))
).view(batch_size, max_conv_len, -1)
w_logit = self.sent_decoder(
(torch.cat([zsent, zspkr, context, zconv_exp], 2)
.view(batch_size * max_conv_len, -1)),
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1)
).view(batch_size, max_conv_len, max_sent_len, -1)
# gibberish
g_logit = w_logit.new(batch_size, max_conv_len, num_asv).normal_()
s_logit = w_logit.new(batch_size, max_conv_len, num_asv).normal_()
return (
{ # logits
"sent": w_logit,
"speaker": p_logit,
"goal": g_logit,
"state": s_logit
}, { # posterior
"conv": zconv_post,
"sent": zsent_post,
"speaker": zspkr_post,
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
}, { # prior
"conv": (MultiGaussian.unit(*zconv_post.size())
.to(w_logit.device)),
"sent": zsent_prior,
"speaker": zspkr_prior,
"goal": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device)),
"state": (MultiGaussian.unit(batch_size, max_conv_len, 1)
.to(w_logit.device))
}
)
def _encode_impl(self, data, *args, **kwargs):
conv_lens = data["conv_lens"]
w, w_lens = data["sent"], data["sent_lens"]
batch_size, max_conv_len, max_sent_len = w.size()
conv_mask = utils.mask(conv_lens)
w_emb = self.word_encoder(w, w_lens)
u = self.sent_post_encoder(
w_emb.view(-1, max_sent_len, self.word_dim),
w_lens.view(-1),
self.post_query.unsqueeze(0).expand(batch_size * max_conv_len, -1)
)[1].view(batch_size, max_conv_len, self.sent_dim)
u = u.masked_fill(~conv_mask.unsqueeze(-1), 0)
_, c = self.conv_encoder(
u,
conv_lens,
self.post_query.unsqueeze(0).expand(batch_size, -1),
)
return self.zconv_post(c)
def _decode_optimal_impl(self, data, conv_state=None,
init_u=None, init_r=None,
max_conv_len=20, max_sent_len=30,
spkr_scale=1.0, sent_scale=1.0,
beam_size=8, **kwargs):
zconv = data["zconv"]
batch_size = zconv.size(0)
eoc_idx = self.vocabs.word["<eoc>"]
sents, spkrs, goals, states = list(), list(), list(), list()
conv_lens = zconv.new(batch_size).long().zero_()
conv_done = zconv.new(batch_size).bool().zero_()
spkr_logprob = zconv.new(batch_size).zero_()
sent_logprob = zconv.new(batch_size).zero_()
goal_logprob = zconv.new(batch_size).zero_()
state_logprob = zconv.new(batch_size).zero_()
if init_u is None:
u = zconv.new(batch_size, self.sent_dim).zero_()
else:
u = init_u
if init_r is None:
r = zconv.new(batch_size, self.spkr_dim).zero_()
else:
r = init_r
if conv_state is None:
conv_state = self.ctx_encoder.init_state(batch_size)
for i in range(max_conv_len):
context, _, conv_state = self.ctx_encoder(
torch.cat([u, r, zconv], 1).unsqueeze(1),
lens=u.new(batch_size).long().fill_(1),
h=conv_state
)
context = context.view(-1, self.ctx_dim)
zspkr = self.zspkr_prior(
torch.cat([context, zconv], 1)
).sample(spkr_scale)
zutt = self.zsent_prior(
torch.cat([zspkr, context, zconv], 1)
).sample(sent_scale)
p_logit = self.spkr_decoder(
torch.cat([zspkr, context, zconv], 1)
)
p_prob, p = torch.softmax(p_logit, -1).max(-1)
p_logprob = p_prob.log().sum(-1)
r = self.spkr_encoder(self.spkr_eye[p])
w, w_lens, w_prob = self.sent_decoder.generate(
h=torch.cat([
zutt,
zspkr,
context.view(batch_size, self.ctx_dim),
zconv
], 1),
beam_size=beam_size,
max_len=max_sent_len
)
w_logprob = w_prob.log()
sents.append(Stacked1DTensor(w, w_lens))
_, u = self.sent_encoder(self.word_encoder(w, w_lens),
w_lens, zconv)
spkrs.append(p)
goals.append(Stacked1DTensor(
value=w.new(batch_size, 0).zero_().long(),
lens=w.new(batch_size).zero_().long()
))
states.append(Stacked1DTensor(
value=w.new(batch_size, 0).zero_().long(),
lens=w.new(batch_size).zero_().long()
))
conv_lens += 1 - conv_done.long()
done = ((w == eoc_idx) & utils.mask(w_lens, w.size(1))).any(1)
conv_done |= done
sent_logprob = w_logprob.masked_fill(conv_done, 0)
spkr_logprob = p_logprob.masked_fill(conv_done, 0)
if conv_done.all().item():
break
sents = utils.stack_stacked1dtensors(sents)
goals = utils.stack_stacked1dtensors(goals)
states = utils.stack_stacked1dtensors(states)
return BatchData(
sent=DoublyStacked1DTensor(
value=sents.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=sents.lens1.t().contiguous()
),
speaker=Stacked1DTensor(
value=torch.stack(spkrs).transpose(1, 0).contiguous(),
lens=conv_lens
),
goal=DoublyStacked1DTensor(
value=goals.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=goals.lens1.t().contiguous()
),
state=DoublyStacked1DTensor(
value=states.value.permute(1, 0, 2).contiguous(),
lens=conv_lens,
lens1=states.lens1.t().contiguous()
),
), dict(
logprob=(sent_logprob + spkr_logprob),
sent_logprob=sent_logprob,
goal_logprob=goal_logprob,
state_logprob=state_logprob,
spkr_logprob=spkr_logprob,
)
def _genconv_prior_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
n = data["n"]
zconv = MultiGaussian.unit(n.item(), self.ctx_dim).to(n.device)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
def _genconv_post_impl(self, data, max_conv_len=20,
beam_size=4, max_sent_len=30,
conv_scale=1.0, spkr_scale=1.0,
goal_scale=1.0, state_scale=1.0, sent_scale=1.0):
zconv = self._encode_impl(data)
zconv_sample = zconv.sample(conv_scale)
batch, info = self._decode_optimal_impl(
data={"zconv": zconv_sample},
eoc="<eoc>",
max_conv_len=max_conv_len,
spkr_scale=spkr_scale,
sent_scale=sent_scale,
beam_size=beam_size,
max_sent_len=max_sent_len
)
info["zconv"] = zconv
info["zconv-sample"] = zconv_sample
return batch, info
| 41.607987
| 80
| 0.556122
| 15,790
| 125,032
| 4.09601
| 0.020709
| 0.048055
| 0.039891
| 0.04354
| 0.940024
| 0.936004
| 0.926572
| 0.915502
| 0.909565
| 0.904509
| 0
| 0.015502
| 0.33497
| 125,032
| 3,004
| 81
| 41.621838
| 0.762321
| 0.061744
| 0
| 0.842301
| 0
| 0
| 0.013091
| 0
| 0
| 0
| 0
| 0.000333
| 0
| 1
| 0.031169
| false
| 0
| 0.006679
| 0.00334
| 0.06679
| 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
|
8c7cae92481aac2e1c3807558bd565ce483b8d95
| 152
|
py
|
Python
|
src/system_of_equations/__init__.py
|
jestra52/supor-numerical-analysis-api
|
3cebc86cf2bba95789de1cb45232aaad182f332f
|
[
"MIT"
] | 1
|
2020-06-09T17:18:01.000Z
|
2020-06-09T17:18:01.000Z
|
src/system_of_equations/__init__.py
|
jestra52/supor-numerical-analysis-api
|
3cebc86cf2bba95789de1cb45232aaad182f332f
|
[
"MIT"
] | null | null | null |
src/system_of_equations/__init__.py
|
jestra52/supor-numerical-analysis-api
|
3cebc86cf2bba95789de1cb45232aaad182f332f
|
[
"MIT"
] | null | null | null |
from system_of_equations.gauss_elimination import *
from system_of_equations.factorization import *
from system_of_equations.iterative_methods import *
| 38
| 51
| 0.881579
| 20
| 152
| 6.3
| 0.5
| 0.238095
| 0.285714
| 0.5
| 0.428571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.078947
| 152
| 3
| 52
| 50.666667
| 0.9
| 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
|
8ceea2da2bd242952f8d307dc6962e8fe363bcc6
| 52
|
py
|
Python
|
class9/ex7/mytest/__init__.py
|
patrebert/pynet_cert
|
b82cce3ddb20d9e4abc89d74579ddeb3513bdf55
|
[
"Apache-2.0"
] | null | null | null |
class9/ex7/mytest/__init__.py
|
patrebert/pynet_cert
|
b82cce3ddb20d9e4abc89d74579ddeb3513bdf55
|
[
"Apache-2.0"
] | null | null | null |
class9/ex7/mytest/__init__.py
|
patrebert/pynet_cert
|
b82cce3ddb20d9e4abc89d74579ddeb3513bdf55
|
[
"Apache-2.0"
] | null | null | null |
from world import func3
from world import testclass
| 17.333333
| 27
| 0.846154
| 8
| 52
| 5.5
| 0.625
| 0.409091
| 0.681818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.022727
| 0.153846
| 52
| 2
| 28
| 26
| 0.977273
| 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
|
8cf4cfdf4fec8582ddbb5784c247874fbad65c23
| 271
|
py
|
Python
|
vega/algorithms/__init__.py
|
This-50m/vega
|
43602d062331336d854d908ac3066f42b2ea3a92
|
[
"MIT"
] | 724
|
2020-06-22T12:05:30.000Z
|
2022-03-31T07:10:54.000Z
|
vega/algorithms/__init__.py
|
NiuRc/vega
|
52b53582fe7df95d7aacc8425013fd18645d079f
|
[
"MIT"
] | 147
|
2020-06-30T13:34:46.000Z
|
2022-03-29T11:30:17.000Z
|
vega/algorithms/__init__.py
|
NiuRc/vega
|
52b53582fe7df95d7aacc8425013fd18645d079f
|
[
"MIT"
] | 160
|
2020-06-29T18:27:58.000Z
|
2022-03-23T08:42:21.000Z
|
from .nas import * # noqa: F401, F403
from .hpo import * # noqa: F401, F403
from .data_augmentation import * # noqa: F401, F403
from .compression import * # noqa: F401, F403
from .auto_loss import * # noqa: F401, F403
from .fully_train import *
from .nlp import *
| 33.875
| 52
| 0.690037
| 39
| 271
| 4.717949
| 0.384615
| 0.271739
| 0.380435
| 0.48913
| 0.597826
| 0
| 0
| 0
| 0
| 0
| 0
| 0.138889
| 0.202952
| 271
| 7
| 53
| 38.714286
| 0.712963
| 0.309963
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 7
|
50c8893817fbd49ae7b515183787c6840238ff39
| 291
|
py
|
Python
|
sknetwork/data/__init__.py
|
mynameisvinn/scikit-network
|
255e99b2f7d5ad8914a8fad3a89d7817764666e0
|
[
"BSD-3-Clause"
] | null | null | null |
sknetwork/data/__init__.py
|
mynameisvinn/scikit-network
|
255e99b2f7d5ad8914a8fad3a89d7817764666e0
|
[
"BSD-3-Clause"
] | null | null | null |
sknetwork/data/__init__.py
|
mynameisvinn/scikit-network
|
255e99b2f7d5ad8914a8fad3a89d7817764666e0
|
[
"BSD-3-Clause"
] | null | null | null |
"""data module"""
from sknetwork.data.toy_graphs import *
from sknetwork.data.models import *
from sknetwork.data.load import load_netset, load_konect, clear_data_home, get_data_home, save, load
from sknetwork.data.parse import load_edge_list, load_labels, load_graphml, load_adjacency_list
| 48.5
| 100
| 0.828179
| 45
| 291
| 5.066667
| 0.466667
| 0.22807
| 0.298246
| 0.201754
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.089347
| 291
| 5
| 101
| 58.2
| 0.860377
| 0.037801
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 7
|
50eb22da1d1feeebb0578e9468c73d2f5cdde516
| 116
|
py
|
Python
|
ps/routes/api/v1/__init__.py
|
Vizzuality/python-skeleton
|
0303ab8b851f35bc4d3e72e33c5e0413a1dc6b57
|
[
"MIT"
] | null | null | null |
ps/routes/api/v1/__init__.py
|
Vizzuality/python-skeleton
|
0303ab8b851f35bc4d3e72e33c5e0413a1dc6b57
|
[
"MIT"
] | null | null | null |
ps/routes/api/v1/__init__.py
|
Vizzuality/python-skeleton
|
0303ab8b851f35bc4d3e72e33c5e0413a1dc6b57
|
[
"MIT"
] | 3
|
2018-01-25T03:52:23.000Z
|
2021-03-10T20:11:26.000Z
|
from ps.routes.api.v1.psone_router import psone_endpoints
from ps.routes.api.v1.pstwo_router import pstwo_endpoints
| 38.666667
| 57
| 0.862069
| 20
| 116
| 4.8
| 0.5
| 0.125
| 0.25
| 0.3125
| 0.354167
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018519
| 0.068966
| 116
| 2
| 58
| 58
| 0.87037
| 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
|
0fa2ef82fe960c5150ee9fb857854a62f374d260
| 2,206
|
py
|
Python
|
Apartment_Renting_App/backend/models/message.py
|
sushilkplassar/csc848_LiveGator
|
e95d861679f1dfb8f547d5b9f7d9b7a4fa530c8d
|
[
"MIT"
] | null | null | null |
Apartment_Renting_App/backend/models/message.py
|
sushilkplassar/csc848_LiveGator
|
e95d861679f1dfb8f547d5b9f7d9b7a4fa530c8d
|
[
"MIT"
] | 1
|
2021-03-20T05:01:15.000Z
|
2021-03-20T05:01:15.000Z
|
Apartment_Renting_App/backend/models/message.py
|
pancreaspinch/LiveGator
|
680592aaf7a6c1603c0ae798a8094ca5f3ff250f
|
[
"MIT"
] | null | null | null |
####################################
# File name: message.py #
# Description:
# Author: Team-13 #
# Submission: Spring-2019 #
# Instructor: Dragutin Petkovic #
####################################
from ..db import DButils
def get_msg_by_customerid(customer_id):
all_msg = DButils.get_all_msg_by_id("customer_id", customer_id)
# renter_id_set = set()
# for msg in all_msg:
# renter_id_set.add(msg[0])
# renter_username = []
# for renter_id in renter_id_set:
# renter = DButils.get_user("user_id", renter_id)
# renter_username.append(renter[1])
return all_msg
def get_msg_by_renterid(landlord_id):
all_msg = DButils.get_all_msg_by_id("landlord_id", landlord_id)
# customer_id_set = set()
# for msg in all_msg:
# customer_id_set.add(msg[1])
# customer_username = []
# for landlord_id in customer_id_set:
# renter = DButils.get_user("user_id", landlord_id)
# customer_username.append(renter[1])
return all_msg
''' Below are the old messaging system. Discarded on April 30 by Kim
# def get_msg_by_customerid(customer_id):
# all_msg = DButils.get_all_msg_by_id("customer_id", customer_id)
# renter_id_set = set()
# for msg in all_msg:
# renter_id_set.add(msg[0])
# renter_username = []
# for renter_id in renter_id_set:
# renter = DButils.get_user("user_id", renter_id)
# renter_username.append(renter[1])
# return renter_username
#
#
# def get_msg_by_renterid(landlord_id):
# all_msg = DButils.get_all_msg_by_id("landlord_id", landlord_id)
# customer_id_set = set()
# for msg in all_msg:
# customer_id_set.add(msg[1])
# customer_username = []
# for landlord_id in customer_id_set:
# renter = DButils.get_user("user_id", landlord_id)
# customer_username.append(renter[1])
# return customer_username
'''
def get_msg_detail(renter_id, customer_id):
return DButils.get_msg_detail(renter_id, customer_id)
def send_msg(renter_id, customer_id, house_id, sender, msg):
DButils.send_msg(renter_id, customer_id, house_id, sender, msg)
#
#
# def send_msg_from_dashboard()
| 32.441176
| 69
| 0.655032
| 310
| 2,206
| 4.277419
| 0.177419
| 0.120664
| 0.090498
| 0.033183
| 0.822021
| 0.822021
| 0.822021
| 0.767722
| 0.767722
| 0.767722
| 0
| 0.009164
| 0.208522
| 2,206
| 68
| 70
| 32.441176
| 0.750286
| 0.281958
| 0
| 0.181818
| 0
| 0
| 0.036789
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.363636
| false
| 0
| 0.090909
| 0.090909
| 0.727273
| 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
|
0fe56b12c30a9d0156f52b5941ecd2349354583b
| 29,382
|
py
|
Python
|
deep_lynx/api/data_export_api.py
|
idaholab/Deep-Lynx-Python-Package
|
99927cc877eba8e2ee396feec807da1c48c64893
|
[
"MIT"
] | 3
|
2021-06-16T20:34:41.000Z
|
2021-06-16T23:54:36.000Z
|
deep_lynx/api/data_export_api.py
|
idaholab/Deep-Lynx-Python-Package
|
99927cc877eba8e2ee396feec807da1c48c64893
|
[
"MIT"
] | null | null | null |
deep_lynx/api/data_export_api.py
|
idaholab/Deep-Lynx-Python-Package
|
99927cc877eba8e2ee396feec807da1c48c64893
|
[
"MIT"
] | null | null | null |
# coding: utf-8
"""
Deep Lynx
The construction of megaprojects has consistently demonstrated challenges for project managers in regard to meeting cost, schedule, and performance requirements. Megaproject construction challenges are common place within megaprojects with many active projects in the United States failing to meet cost and schedule efforts by significant margins. Currently, engineering teams operate in siloed tools and disparate teams where connections across design, procurement, and construction systems are translated manually or over brittle point-to-point integrations. The manual nature of data exchange increases the risk of silent errors in the reactor design, with each silent error cascading across the design. These cascading errors lead to uncontrollable risk during construction, resulting in significant delays and cost overruns. Deep Lynx allows for an integrated platform during design and operations of mega projects. The Deep Lynx Core API delivers a few main features. 1. Provides a set of methods and endpoints for manipulating data in an object oriented database. This allows us to store complex datatypes as records and then to compile them into actual, modifiable objects at run-time. Users can store taxonomies or ontologies in a readable format. 2. Provides methods for storing and retrieving data in a graph database. This data is structured and validated against the aformentioned object oriented database before storage. # noqa: E501
OpenAPI spec version: 1.0
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 deep_lynx.api_client import ApiClient
class DataExportApi(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 create_data_export(self, body, container_id, **kwargs): # noqa: E501
"""Create Data Export # noqa: E501
Create a new data export with the included configuration. Configuration values may be encrypted depending on the adapter you've choosen. See the readme for the exporters for more information. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_data_export(body, container_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateDataExportRequest body: (required)
:param str container_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.create_data_export_with_http_info(body, container_id, **kwargs) # noqa: E501
else:
(data) = self.create_data_export_with_http_info(body, container_id, **kwargs) # noqa: E501
return data
def create_data_export_with_http_info(self, body, container_id, **kwargs): # noqa: E501
"""Create Data Export # noqa: E501
Create a new data export with the included configuration. Configuration values may be encrypted depending on the adapter you've choosen. See the readme for the exporters for more information. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_data_export_with_http_info(body, container_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateDataExportRequest body: (required)
:param str container_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['body', 'container_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 create_data_export" % 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 `create_data_export`") # noqa: E501
# verify the required parameter 'container_id' is set
if ('container_id' not in params or
params['container_id'] is None):
raise ValueError("Missing the required parameter `container_id` when calling `create_data_export`") # noqa: E501
collection_formats = {}
path_params = {}
if 'container_id' in params:
path_params['container_id'] = params['container_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/json']) # noqa: E501
# Authentication setting
auth_settings = ['BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/containers/{container_id}/data/export', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Generic200Response', # 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_data_export(self, container_id, export_id, **kwargs): # noqa: E501
"""Delete Data Export # noqa: E501
Deletes a data export record. This does not guarantee the export will stop immediately. # 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_data_export(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
else:
(data) = self.delete_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
return data
def delete_data_export_with_http_info(self, container_id, export_id, **kwargs): # noqa: E501
"""Delete Data Export # noqa: E501
Deletes a data export record. This does not guarantee the export will stop immediately. # 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_data_export_with_http_info(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['container_id', 'export_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 delete_data_export" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'container_id' is set
if ('container_id' not in params or
params['container_id'] is None):
raise ValueError("Missing the required parameter `container_id` when calling `delete_data_export`") # noqa: E501
# verify the required parameter 'export_id' is set
if ('export_id' not in params or
params['export_id'] is None):
raise ValueError("Missing the required parameter `export_id` when calling `delete_data_export`") # noqa: E501
collection_formats = {}
path_params = {}
if 'container_id' in params:
path_params['container_id'] = params['container_id'] # noqa: E501
if 'export_id' in params:
path_params['export_id'] = params['export_id'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/containers/{container_id}/data/export/{export_id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Generic200Response', # 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 list_data_exports(self, container_id, **kwargs): # noqa: E501
"""List Data Exports # noqa: E501
List data exports for the container. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.list_data_exports(container_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param bool count: boolean indicating if the return value should be a count only
:param int limit:
:param int offset:
:param str sort_by: column to sort results by
:param bool sort_desc: boolean indicating if results should be in descending order
:return: ListDataExportsResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.list_data_exports_with_http_info(container_id, **kwargs) # noqa: E501
else:
(data) = self.list_data_exports_with_http_info(container_id, **kwargs) # noqa: E501
return data
def list_data_exports_with_http_info(self, container_id, **kwargs): # noqa: E501
"""List Data Exports # noqa: E501
List data exports for the container. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.list_data_exports_with_http_info(container_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param bool count: boolean indicating if the return value should be a count only
:param int limit:
:param int offset:
:param str sort_by: column to sort results by
:param bool sort_desc: boolean indicating if results should be in descending order
:return: ListDataExportsResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['container_id', 'count', 'limit', 'offset', 'sort_by', 'sort_desc'] # 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 list_data_exports" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'container_id' is set
if ('container_id' not in params or
params['container_id'] is None):
raise ValueError("Missing the required parameter `container_id` when calling `list_data_exports`") # noqa: E501
collection_formats = {}
path_params = {}
if 'container_id' in params:
path_params['container_id'] = params['container_id'] # noqa: E501
query_params = []
if 'count' in params:
query_params.append(('count', params['count'])) # noqa: E501
if 'limit' in params:
query_params.append(('limit', params['limit'])) # noqa: E501
if 'offset' in params:
query_params.append(('offset', params['offset'])) # noqa: E501
if 'sort_by' in params:
query_params.append(('sortBy', params['sort_by'])) # noqa: E501
if 'sort_desc' in params:
query_params.append(('sortDesc', params['sort_desc'])) # 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 = ['BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/containers/{container_id}/data/export', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ListDataExportsResponse', # 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 retrieve_data_export(self, container_id, export_id, **kwargs): # noqa: E501
"""Retrieve Data Export # noqa: E501
Fetch a data export record by ID # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.retrieve_data_export(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: GetDataExportResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.retrieve_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
else:
(data) = self.retrieve_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
return data
def retrieve_data_export_with_http_info(self, container_id, export_id, **kwargs): # noqa: E501
"""Retrieve Data Export # noqa: E501
Fetch a data export record by ID # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.retrieve_data_export_with_http_info(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: GetDataExportResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['container_id', 'export_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 retrieve_data_export" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'container_id' is set
if ('container_id' not in params or
params['container_id'] is None):
raise ValueError("Missing the required parameter `container_id` when calling `retrieve_data_export`") # noqa: E501
# verify the required parameter 'export_id' is set
if ('export_id' not in params or
params['export_id'] is None):
raise ValueError("Missing the required parameter `export_id` when calling `retrieve_data_export`") # noqa: E501
collection_formats = {}
path_params = {}
if 'container_id' in params:
path_params['container_id'] = params['container_id'] # noqa: E501
if 'export_id' in params:
path_params['export_id'] = params['export_id'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/containers/{container_id}/data/export/{export_id}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='GetDataExportResponse', # 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 start_data_export(self, container_id, export_id, **kwargs): # noqa: E501
"""Start Data Export # noqa: E501
Start or restart a data export by id. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.start_data_export(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.start_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
else:
(data) = self.start_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
return data
def start_data_export_with_http_info(self, container_id, export_id, **kwargs): # noqa: E501
"""Start Data Export # noqa: E501
Start or restart a data export by id. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.start_data_export_with_http_info(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['container_id', 'export_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 start_data_export" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'container_id' is set
if ('container_id' not in params or
params['container_id'] is None):
raise ValueError("Missing the required parameter `container_id` when calling `start_data_export`") # noqa: E501
# verify the required parameter 'export_id' is set
if ('export_id' not in params or
params['export_id'] is None):
raise ValueError("Missing the required parameter `export_id` when calling `start_data_export`") # noqa: E501
collection_formats = {}
path_params = {}
if 'container_id' in params:
path_params['container_id'] = params['container_id'] # noqa: E501
if 'export_id' in params:
path_params['export_id'] = params['export_id'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/containers/{container_id}/data/export/{export_id}', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Generic200Response', # 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 stop_data_export(self, container_id, export_id, **kwargs): # noqa: E501
"""Stop Data Export # noqa: E501
Stops a data export. Please note that this just sends a **stop** signal. The application's export adapter determines how to handle the said signal. In some cases the export stopping might not be immediate. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.stop_data_export(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.stop_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
else:
(data) = self.stop_data_export_with_http_info(container_id, export_id, **kwargs) # noqa: E501
return data
def stop_data_export_with_http_info(self, container_id, export_id, **kwargs): # noqa: E501
"""Stop Data Export # noqa: E501
Stops a data export. Please note that this just sends a **stop** signal. The application's export adapter determines how to handle the said signal. In some cases the export stopping might not be immediate. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.stop_data_export_with_http_info(container_id, export_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str container_id: (required)
:param str export_id: (required)
:return: Generic200Response
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['container_id', 'export_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 stop_data_export" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'container_id' is set
if ('container_id' not in params or
params['container_id'] is None):
raise ValueError("Missing the required parameter `container_id` when calling `stop_data_export`") # noqa: E501
# verify the required parameter 'export_id' is set
if ('export_id' not in params or
params['export_id'] is None):
raise ValueError("Missing the required parameter `export_id` when calling `stop_data_export`") # noqa: E501
collection_formats = {}
path_params = {}
if 'container_id' in params:
path_params['container_id'] = params['container_id'] # noqa: E501
if 'export_id' in params:
path_params['export_id'] = params['export_id'] # noqa: E501
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']) # noqa: E501
# Authentication setting
auth_settings = ['BearerAuth'] # noqa: E501
return self.api_client.call_api(
'/containers/{container_id}/data/export/{export_id}', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Generic200Response', # 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)
| 43.98503
| 1,455
| 0.63253
| 3,502
| 29,382
| 5.070817
| 0.09309
| 0.063183
| 0.026805
| 0.029958
| 0.883433
| 0.873071
| 0.868679
| 0.863104
| 0.853756
| 0.85308
| 0
| 0.016557
| 0.282588
| 29,382
| 667
| 1,456
| 44.050975
| 0.825893
| 0.371758
| 0
| 0.773743
| 0
| 0
| 0.217059
| 0.044645
| 0
| 0
| 0
| 0
| 0
| 1
| 0.036313
| false
| 0
| 0.011173
| 0
| 0.100559
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
ba1d9be87b0a1174d4ce4e249ef077a2826cacca
| 3,203
|
py
|
Python
|
tests/unit/api/test_docker_blacklist.py
|
mateuspontes/fastlane
|
a77505a344da990ad67cffd0ee0eb830489f7324
|
[
"MIT"
] | 32
|
2019-02-19T01:37:57.000Z
|
2022-03-19T22:12:23.000Z
|
tests/unit/api/test_docker_blacklist.py
|
mateuspontes/fastlane
|
a77505a344da990ad67cffd0ee0eb830489f7324
|
[
"MIT"
] | 15
|
2019-02-18T17:51:57.000Z
|
2020-03-20T16:27:38.000Z
|
tests/unit/api/test_docker_blacklist.py
|
mateuspontes/fastlane
|
a77505a344da990ad67cffd0ee0eb830489f7324
|
[
"MIT"
] | 26
|
2019-02-14T20:00:11.000Z
|
2020-01-24T18:12:57.000Z
|
# Standard Library
from json import dumps
from random import randrange
from uuid import uuid4
# 3rd Party
from preggy import expect
# Fastlane
from fastlane.worker.docker import BLACKLIST_KEY
def test_docker_blacklist1(client):
"""Test blacklisting a docker server"""
def ensure_blacklist(method):
docker_host = "{domain}:{port}".format(
domain=str(uuid4()).replace("-", "."),
port=int(randrange(10, 99999)) # nosec
)
data = {"host": docker_host}
response = getattr(client, method)(
"/docker-executor/blacklist", data=dumps(data), follow_redirects=True
)
expect(response.status_code).to_equal(200)
expect(response.data).to_be_empty()
app = client.application
res = app.redis.exists(BLACKLIST_KEY)
expect(res).to_be_true()
res = app.redis.sismember(BLACKLIST_KEY, docker_host)
expect(res).to_be_true()
for method in ["post", "put"]:
ensure_blacklist(method)
def test_docker_blacklist2(client):
"""
Test blacklisting a docker server with invalid body or
without a host property in the JSON body
"""
def ensure_blacklist(method):
response = getattr(client, method)(
"/docker-executor/blacklist", data=dumps({}), follow_redirects=True
)
expect(response.status_code).to_equal(400)
expect(response.data).to_be_like(
"Failed to add host to blacklist because 'host' attribute was not found in JSON body."
)
app = client.application
res = app.redis.exists(BLACKLIST_KEY)
expect(res).to_be_false()
for method in ["post", "put"]:
ensure_blacklist(method)
def test_docker_blacklist3(client):
"""Test removing from blacklist a docker server"""
docker_host = "{domain}:{port}".format(
domain=str(uuid4()).replace("-", "."),
port=int(randrange(10, 99999)) # nosec
)
data = {"host": docker_host}
response = client.post(
"/docker-executor/blacklist", data=dumps(data), follow_redirects=True
)
expect(response.status_code).to_equal(200)
expect(response.data).to_be_empty()
app = client.application
res = app.redis.exists(BLACKLIST_KEY)
expect(res).to_be_true()
res = app.redis.sismember(BLACKLIST_KEY, docker_host)
expect(res).to_be_true()
data = {"host": docker_host}
response = client.delete(
"/docker-executor/blacklist", data=dumps(data), follow_redirects=True
)
expect(response.status_code).to_equal(200)
expect(response.data).to_be_empty()
app = client.application
res = app.redis.exists(BLACKLIST_KEY)
expect(res).to_be_false()
def test_docker_blacklist4(client):
"""
Test removing a server from blacklist with invalid body or
without a host property in the JSON body
"""
response = client.delete(
"/docker-executor/blacklist", data=dumps({}), follow_redirects=True
)
expect(response.status_code).to_equal(400)
expect(response.data).to_be_like(
"Failed to remove host from blacklist because 'host' attribute was not found in JSON body."
)
| 27.144068
| 99
| 0.655635
| 398
| 3,203
| 5.11809
| 0.213568
| 0.0216
| 0.032401
| 0.038292
| 0.81296
| 0.81296
| 0.766814
| 0.766814
| 0.747177
| 0.724595
| 0
| 0.014943
| 0.226975
| 3,203
| 117
| 100
| 27.376068
| 0.807754
| 0.100843
| 0
| 0.704225
| 0
| 0
| 0.128405
| 0.045985
| 0
| 0
| 0
| 0
| 0
| 1
| 0.084507
| false
| 0
| 0.070423
| 0
| 0.15493
| 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
|
ba20dca917bcdd00712d6f1975c8144fbf5df43c
| 44,501
|
py
|
Python
|
Contents/Libraries/Shared/PicartoClientAPI/apis/public_api.py
|
Sythelux/Picarto.bundle
|
f2e9e9e75421b15c562c961c8c31090c508166ff
|
[
"BSD-3-Clause"
] | null | null | null |
Contents/Libraries/Shared/PicartoClientAPI/apis/public_api.py
|
Sythelux/Picarto.bundle
|
f2e9e9e75421b15c562c961c8c31090c508166ff
|
[
"BSD-3-Clause"
] | 5
|
2018-01-29T23:18:20.000Z
|
2018-01-29T23:57:15.000Z
|
Contents/Libraries/Shared/PicartoClientAPI/apis/public_api.py
|
Sythelux/Picarto.bundle
|
f2e9e9e75421b15c562c961c8c31090c508166ff
|
[
"BSD-3-Clause"
] | null | null | null |
# coding: utf-8
"""
Picarto.TV API Documentation
The Picarto.TV API documentation Note, for fixed access tokens, the header that needs to be sent is of the format: `Authorization: Bearer yourTokenHere` This can be generated at https://oauth.picarto.tv/ For chat API, see https://docs.picarto.tv/chat/chat.proto - contact via the email below for implementation details
OpenAPI spec version: 1.2.5
Contact: api@picarto.tv
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 PublicApi(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 categories_get(self, **kwargs):
"""
Get information about all categories
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.categories_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:return: Categories
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.categories_get_with_http_info(**kwargs)
else:
(data) = self.categories_get_with_http_info(**kwargs)
return data
def categories_get_with_http_info(self, **kwargs):
"""
Get information about all categories
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.categories_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:return: Categories
If the method is called asynchronously,
returns the request thread.
"""
all_params = []
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 categories_get" % 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(['application/json; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/categories', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Categories',
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 channel_id_channel_id_get(self, channel_id, **kwargs):
"""
Gets information about a channel by 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.channel_id_channel_id_get(channel_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param int channel_id: Channel ID of user you wish to read (required)
:return: ChannelDetails
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.channel_id_channel_id_get_with_http_info(channel_id, **kwargs)
else:
(data) = self.channel_id_channel_id_get_with_http_info(channel_id, **kwargs)
return data
def channel_id_channel_id_get_with_http_info(self, channel_id, **kwargs):
"""
Gets information about a channel by 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.channel_id_channel_id_get_with_http_info(channel_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param int channel_id: Channel ID of user you wish to read (required)
:return: ChannelDetails
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['channel_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 channel_id_channel_id_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'channel_id' is set
if ('channel_id' not in params) or (params['channel_id'] is None):
raise ValueError("Missing the required parameter `channel_id` when calling `channel_id_channel_id_get`")
collection_formats = {}
path_params = {}
if 'channel_id' in params:
path_params['channel_id'] = params['channel_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; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/channel/id/{channel_id}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ChannelDetails',
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 channel_id_channel_id_videos_get(self, channel_id, **kwargs):
"""
Get all videos for a channel by 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.channel_id_channel_id_videos_get(channel_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param int channel_id: Channel ID of the user you want to get videos for (required)
:return: ChannelVideos
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.channel_id_channel_id_videos_get_with_http_info(channel_id, **kwargs)
else:
(data) = self.channel_id_channel_id_videos_get_with_http_info(channel_id, **kwargs)
return data
def channel_id_channel_id_videos_get_with_http_info(self, channel_id, **kwargs):
"""
Get all videos for a channel by 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.channel_id_channel_id_videos_get_with_http_info(channel_id, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param int channel_id: Channel ID of the user you want to get videos for (required)
:return: ChannelVideos
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['channel_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 channel_id_channel_id_videos_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'channel_id' is set
if ('channel_id' not in params) or (params['channel_id'] is None):
raise ValueError("Missing the required parameter `channel_id` when calling `channel_id_channel_id_videos_get`")
collection_formats = {}
path_params = {}
if 'channel_id' in params:
path_params['channel_id'] = params['channel_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; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/channel/id/{channel_id}/videos', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ChannelVideos',
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 channel_name_channel_name_get(self, channel_name, **kwargs):
"""
Gets information about a channel by name
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.channel_name_channel_name_get(channel_name, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str channel_name: Channel name of user you wish to read (required)
:return: ChannelDetails
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.channel_name_channel_name_get_with_http_info(channel_name, **kwargs)
else:
(data) = self.channel_name_channel_name_get_with_http_info(channel_name, **kwargs)
return data
def channel_name_channel_name_get_with_http_info(self, channel_name, **kwargs):
"""
Gets information about a channel by name
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.channel_name_channel_name_get_with_http_info(channel_name, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str channel_name: Channel name of user you wish to read (required)
:return: ChannelDetails
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['channel_name']
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 channel_name_channel_name_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'channel_name' is set
if ('channel_name' not in params) or (params['channel_name'] is None):
raise ValueError("Missing the required parameter `channel_name` when calling `channel_name_channel_name_get`")
collection_formats = {}
path_params = {}
if 'channel_name' in params:
path_params['channel_name'] = params['channel_name']
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; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/channel/name/{channel_name}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ChannelDetails',
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 channel_name_channel_name_videos_get(self, channel_name, **kwargs):
"""
Get all videos for a channel by name
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.channel_name_channel_name_videos_get(channel_name, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str channel_name: Channel name of the user you want to get videos for (required)
:return: ChannelVideos
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.channel_name_channel_name_videos_get_with_http_info(channel_name, **kwargs)
else:
(data) = self.channel_name_channel_name_videos_get_with_http_info(channel_name, **kwargs)
return data
def channel_name_channel_name_videos_get_with_http_info(self, channel_name, **kwargs):
"""
Get all videos for a channel by name
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.channel_name_channel_name_videos_get_with_http_info(channel_name, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str channel_name: Channel name of the user you want to get videos for (required)
:return: ChannelVideos
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['channel_name']
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 channel_name_channel_name_videos_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'channel_name' is set
if ('channel_name' not in params) or (params['channel_name'] is None):
raise ValueError("Missing the required parameter `channel_name` when calling `channel_name_channel_name_videos_get`")
collection_formats = {}
path_params = {}
if 'channel_name' in params:
path_params['channel_name'] = params['channel_name']
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; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/channel/name/{channel_name}/videos', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ChannelVideos',
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 events_get(self, **kwargs):
"""
Get all events that are about to run or are running
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.events_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:return: Events
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.events_get_with_http_info(**kwargs)
else:
(data) = self.events_get_with_http_info(**kwargs)
return data
def events_get_with_http_info(self, **kwargs):
"""
Get all events that are about to run or are running
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.events_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:return: Events
If the method is called asynchronously,
returns the request thread.
"""
all_params = []
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 events_get" % 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(['application/json; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/events', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Events',
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 notifications_get(self, **kwargs):
"""
Get all global notifications/announcements
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.notifications_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:return: list[Notification]
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.notifications_get_with_http_info(**kwargs)
else:
(data) = self.notifications_get_with_http_info(**kwargs)
return data
def notifications_get_with_http_info(self, **kwargs):
"""
Get all global notifications/announcements
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.notifications_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:return: list[Notification]
If the method is called asynchronously,
returns the request thread.
"""
all_params = []
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 notifications_get" % 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(['application/json; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/notifications', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='list[Notification]',
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 online_get(self, **kwargs):
"""
Gets all currently online channels
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.online_get(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param bool adult: Whether or not to include adult channels (defaults to `false`)
:param bool gaming: Whether or not to include gaming channels (defaults to `false`)
:param str categories: What categories to limit this to (blank/not included doesn't filter) - seperate multiple categories by a `,` character
:return: OnlineChannels
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.online_get_with_http_info(**kwargs)
else:
(data) = self.online_get_with_http_info(**kwargs)
return data
def online_get_with_http_info(self, **kwargs):
"""
Gets all currently online channels
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.online_get_with_http_info(callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param bool adult: Whether or not to include adult channels (defaults to `false`)
:param bool gaming: Whether or not to include gaming channels (defaults to `false`)
:param str categories: What categories to limit this to (blank/not included doesn't filter) - seperate multiple categories by a `,` character
:return: OnlineChannels
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['adult', 'gaming', 'categories']
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 online_get" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
if 'adult' in params:
query_params.append(('adult', params['adult']))
if 'gaming' in params:
query_params.append(('gaming', params['gaming']))
if 'categories' in params:
query_params.append(('categories', params['categories']))
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/online', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='OnlineChannels',
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_channels_get(self, q, **kwargs):
"""
Get all channels matching the given search criteria (by name and tags)
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_channels_get(q, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str q: The search query to use (does not currently support special qualifiers) (required)
:param bool adult: Whether or not to include adult channels (defaults to `false`)
:param int page: The page to display (defaults to `1`)
:param bool commissions: Whether or not to filter by streams offering commissions
:return: ChannelSearchResults
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.search_channels_get_with_http_info(q, **kwargs)
else:
(data) = self.search_channels_get_with_http_info(q, **kwargs)
return data
def search_channels_get_with_http_info(self, q, **kwargs):
"""
Get all channels matching the given search criteria (by name and tags)
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_channels_get_with_http_info(q, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str q: The search query to use (does not currently support special qualifiers) (required)
:param bool adult: Whether or not to include adult channels (defaults to `false`)
:param int page: The page to display (defaults to `1`)
:param bool commissions: Whether or not to filter by streams offering commissions
:return: ChannelSearchResults
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['q', 'adult', 'page', 'commissions']
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_channels_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'q' is set
if ('q' not in params) or (params['q'] is None):
raise ValueError("Missing the required parameter `q` when calling `search_channels_get`")
collection_formats = {}
path_params = {}
query_params = []
if 'q' in params:
query_params.append(('q', params['q']))
if 'adult' in params:
query_params.append(('adult', params['adult']))
if 'page' in params:
query_params.append(('page', params['page']))
if 'commissions' in params:
query_params.append(('commissions', params['commissions']))
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/search/channels', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ChannelSearchResults',
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_videos_get(self, q, **kwargs):
"""
Get all videos matching the given search criteria
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_videos_get(q, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str q: The search query to use (does not currently support special qualifiers) (required)
:param bool adult: Whether or not to include adult channels (defaults to `false`)
:param int page: The page to display (defaults to `1`)
:return: VideoSearchResults
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('callback'):
return self.search_videos_get_with_http_info(q, **kwargs)
else:
(data) = self.search_videos_get_with_http_info(q, **kwargs)
return data
def search_videos_get_with_http_info(self, q, **kwargs):
"""
Get all videos matching the given search criteria
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_videos_get_with_http_info(q, callback=callback_function)
:param callback function: The callback function
for asynchronous request. (optional)
:param str q: The search query to use (does not currently support special qualifiers) (required)
:param bool adult: Whether or not to include adult channels (defaults to `false`)
:param int page: The page to display (defaults to `1`)
:return: VideoSearchResults
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['q', 'adult', 'page']
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_videos_get" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'q' is set
if ('q' not in params) or (params['q'] is None):
raise ValueError("Missing the required parameter `q` when calling `search_videos_get`")
collection_formats = {}
path_params = {}
query_params = []
if 'q' in params:
query_params.append(('q', params['q']))
if 'adult' in params:
query_params.append(('adult', params['adult']))
if 'page' in params:
query_params.append(('page', params['page']))
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.\
select_header_accept(['application/json; charset=utf-8', 'text/plain; charset=utf-8'])
# Authentication setting
auth_settings = []
return self.api_client.call_api('/search/videos', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='VideoSearchResults',
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)
| 42.666347
| 326
| 0.567987
| 4,576
| 44,501
| 5.286713
| 0.051573
| 0.066138
| 0.023148
| 0.029762
| 0.954406
| 0.947627
| 0.945685
| 0.938285
| 0.924231
| 0.920098
| 0
| 0.001043
| 0.35379
| 44,501
| 1,042
| 327
| 42.707294
| 0.840213
| 0.338082
| 0
| 0.794574
| 0
| 0
| 0.161351
| 0.039255
| 0
| 0
| 0
| 0
| 0
| 1
| 0.040698
| false
| 0
| 0.013566
| 0
| 0.114341
| 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
|
e88e7eb13a03ace63c2f0ab895dc6960118d7adc
| 10,461
|
py
|
Python
|
tests/dhcpv4/relay/test_v4_release_relay.py
|
shawnmullaney/forge
|
aaaef0a0645f73d24666aab6a400f3604e753aac
|
[
"0BSD"
] | null | null | null |
tests/dhcpv4/relay/test_v4_release_relay.py
|
shawnmullaney/forge
|
aaaef0a0645f73d24666aab6a400f3604e753aac
|
[
"0BSD"
] | null | null | null |
tests/dhcpv4/relay/test_v4_release_relay.py
|
shawnmullaney/forge
|
aaaef0a0645f73d24666aab6a400f3604e753aac
|
[
"0BSD"
] | null | null | null |
"""DHCPv4 address release process"""
# pylint: disable=invalid-name,line-too-long
import pytest
import srv_control
import srv_msg
import misc
@pytest.mark.v4
@pytest.mark.dhcp4
@pytest.mark.relay
@pytest.mark.release
def test_v4_relay_release_success():
misc.test_setup()
srv_control.config_srv_subnet('192.168.50.0/24', '192.168.50.1-192.168.50.1')
srv_control.build_and_send_config_files('SSH', 'config-file')
srv_control.start_srv('DHCP', 'started')
misc.test_procedure()
# this is setting for every message in this test
srv_msg.network_variable('source_port', '67')
srv_msg.network_variable('source_address', '$(GIADDR4)')
srv_msg.network_variable('destination_address', '$(SRV4_ADDR)')
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('DISCOVER')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'OFFER')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
# Response MUST contain giaddr $(GIADDR4).
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
misc.test_procedure()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_copy_option('server_id')
srv_msg.client_does_include_with_value('requested_addr', '192.168.50.1')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('REQUEST')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'ACK')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
misc.test_procedure()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_copy_option('server_id')
srv_msg.client_sets_value('Client', 'ciaddr', '192.168.50.1')
srv_msg.client_send_msg('RELEASE')
misc.pass_criteria()
srv_msg.send_dont_wait_for_message()
misc.test_procedure()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_sets_value('Client', 'chaddr', '00:00:00:00:00:11')
srv_msg.client_does_include_with_value('client_id', '00010203040111')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('DISCOVER')
misc.pass_criteria()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.send_wait_for_message('MUST', None, 'OFFER')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
# Response MUST contain giaddr $(GIADDR4).
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
@pytest.mark.v4
@pytest.mark.dhcp4
@pytest.mark.relay
@pytest.mark.release
def test_v4_relay_release_success_with_additional_offer():
misc.test_setup()
srv_control.config_srv_subnet('192.168.50.0/24', '192.168.50.1-192.168.50.1')
srv_control.build_and_send_config_files('SSH', 'config-file')
srv_control.start_srv('DHCP', 'started')
misc.test_procedure()
srv_msg.network_variable('source_port', '67')
srv_msg.network_variable('source_address', '$(GIADDR4)')
srv_msg.network_variable('destination_address', '$(SRV4_ADDR)')
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('DISCOVER')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'OFFER')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_include_option('Response', None, '54')
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
srv_msg.response_check_option_content('Response', '54', None, 'value', '$(SRV4_ADDR)')
misc.test_procedure()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_copy_option('server_id')
srv_msg.client_does_include_with_value('requested_addr', '192.168.50.1')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('REQUEST')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'ACK')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_include_option('Response', None, '54')
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
srv_msg.response_check_option_content('Response', '54', None, 'value', '$(SRV4_ADDR)')
misc.test_procedure()
srv_msg.client_save_option('server_id')
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_sets_value('Client', 'chaddr', '00:00:00:00:00:00')
srv_msg.client_does_include_with_value('client_id', '00010203040506')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('DISCOVER')
misc.pass_criteria()
srv_msg.send_dont_wait_for_message()
misc.test_procedure()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_sets_value('Client', 'chaddr', 'default')
srv_msg.client_add_saved_option(None)
srv_msg.client_sets_value('Client', 'ciaddr', '192.168.50.1')
srv_msg.client_send_msg('RELEASE')
misc.pass_criteria()
srv_msg.send_dont_wait_for_message()
misc.test_procedure()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_sets_value('Client', 'chaddr', '00:00:00:00:00:11')
srv_msg.client_does_include_with_value('client_id', '00010203040111')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('DISCOVER')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'OFFER')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_include_option('Response', None, '54')
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
srv_msg.response_check_option_content('Response', '54', None, 'value', '$(SRV4_ADDR)')
@pytest.mark.v4
@pytest.mark.dhcp4
@pytest.mark.relay
@pytest.mark.release
def test_v4_relay_release_only_chaddr_same_chaddr():
misc.test_setup()
srv_control.config_srv_subnet('192.168.50.0/24', '192.168.50.1-192.168.50.1')
srv_control.build_and_send_config_files('SSH', 'config-file')
srv_control.start_srv('DHCP', 'started')
misc.test_procedure()
srv_msg.network_variable('source_port', '67')
srv_msg.network_variable('source_address', '$(GIADDR4)')
srv_msg.network_variable('destination_address', '$(SRV4_ADDR)')
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_sets_value('Client', 'chaddr', '00:1F:D0:00:00:11')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('DISCOVER')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'OFFER')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_include_option('Response', None, '54')
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
srv_msg.response_check_option_content('Response', '54', None, 'value', '$(SRV4_ADDR)')
misc.test_procedure()
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_sets_value('Client', 'chaddr', '00:1f:d0:00:00:11')
srv_msg.client_copy_option('server_id')
srv_msg.client_does_include_with_value('requested_addr', '192.168.50.1')
srv_msg.client_requests_option('1')
srv_msg.client_send_msg('REQUEST')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'ACK')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_include_option('Response', None, '54')
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
srv_msg.response_check_option_content('Response', '54', None, 'value', '$(SRV4_ADDR)')
misc.test_procedure()
# client id changed!
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_sets_value('Client', 'chaddr', '00:1f:d0:00:00:11')
srv_msg.client_copy_option('server_id')
srv_msg.client_sets_value('Client', 'ciaddr', '192.168.50.1')
srv_msg.client_send_msg('RELEASE')
# address not released
misc.pass_criteria()
srv_msg.send_dont_wait_for_message()
misc.test_procedure()
srv_msg.client_sets_value('Client', 'chaddr', '00:00:00:00:00:00')
srv_msg.client_requests_option('1')
srv_msg.client_sets_value('Client', 'giaddr', '$(GIADDR4)')
srv_msg.client_sets_value('Client', 'hops', '1')
srv_msg.client_send_msg('DISCOVER')
misc.pass_criteria()
srv_msg.send_wait_for_message('MUST', None, 'OFFER')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_content('Response', None, 'yiaddr', '192.168.50.1')
srv_msg.response_check_include_option('Response', None, '1')
srv_msg.response_check_include_option('Response', None, '54')
srv_msg.response_check_option_content('Response', '1', None, 'value', '255.255.255.0')
srv_msg.response_check_option_content('Response', '54', None, 'value', '$(SRV4_ADDR)')
| 43.049383
| 90
| 0.717331
| 1,532
| 10,461
| 4.524804
| 0.070496
| 0.119446
| 0.129833
| 0.109636
| 0.96004
| 0.96004
| 0.96004
| 0.96004
| 0.96004
| 0.951818
| 0
| 0.058875
| 0.118344
| 10,461
| 242
| 91
| 43.227273
| 0.692725
| 0.023229
| 0
| 0.938144
| 0
| 0
| 0.228079
| 0.007348
| 0
| 0
| 0
| 0
| 0
| 1
| 0.015464
| true
| 0.06701
| 0.020619
| 0
| 0.036082
| 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
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 9
|
e8b6683b3bf1be172ca74c9677acaf3cb6796b26
| 104,368
|
py
|
Python
|
2-3-OT-to-1-2-OT-1.sagews.py
|
anpc/perfect-reductions
|
7b0de1185d6b3ebf4c16650daea7c13d398fc3bb
|
[
"MIT"
] | null | null | null |
2-3-OT-to-1-2-OT-1.sagews.py
|
anpc/perfect-reductions
|
7b0de1185d6b3ebf4c16650daea7c13d398fc3bb
|
[
"MIT"
] | null | null | null |
2-3-OT-to-1-2-OT-1.sagews.py
|
anpc/perfect-reductions
|
7b0de1185d6b3ebf4c16650daea7c13d398fc3bb
|
[
"MIT"
] | null | null | null |
︠d7d05283-2842-485a-9a03-7f0ef91252c0︠
%md
# This project explores the construction of 2-out-of-3-OT from 1-of-2-OT
Here we make $T$ parallel calls to the OT oracles.
We start with $T = 3$
## Problem representation:
$C_1,C_2,C_3$ are the client's valid inputs.
From client's correctness, each 6-tuple of bits is assigned to some $(x1,x2,x3)$ triple.
The assignments should create an independent set in a graph with $2^{2T+3}$ veritces.
There is an edge between $v_g$ and ${v'}_{g'}$ iff. $g$ and $g'$ differ of a pair $(i,j)=[3]\setminus \{k\}$ of bits, but $v[c_k] \ne v'[c_k]$.
︡4dfc1cbd-2917-4c36-8301-9f53e8f37c45︡{"done":true,"md":"# This project explores the construction of 2-out-of-3-OT from 1-of-2-OT\n\nHere we make $T$ parallel calls to the OT oracles.\n\nWe start with $T = 3$\n\n## Problem representation:\n\n$C_1,C_2,C_3$ are the client's valid inputs.\n\nFrom client's correctness, each 6-tuple of bits is assigned to some $(x1,x2,x3)$ triple.\n\nThe assignments should create an independent set in a graph with $2^{2T+3}$ veritces.\n\nThere is an edge between $v_g$ and ${v'}_{g'}$ iff. $g$ and $g'$ differ of a pair $(i,j)=[3]\\setminus \\{k\\}$ of bits, but $v[c_k] \\ne v'[c_k]$."}
︠71951939-ef54-4de0-b65f-e2a9a1bfda7fs︠
import itertools
import pprint
import random
from __future__ import division
def verify_vector(result):
epsilon = 0.00001
for i in range(64):
s = sum([1 if result[j*64+i] > epsilon else 0 for j in range(8)])
if s > 1:
return 0
return 1
def get_rand_dir():
l = [random.randint(0,9) for i in range(512)]
s = sum(l)
# print 'returning ',[float(x)/s for x in l]
return [float(x)/s for x in l]
def tup_to_num(g):
(ind, v_arr) = g
return 256*ind[0] + 128*ind[1] + 64*ind[2] + v_arr[2][1] + 2*v_arr[2][0] + 4*v_arr[1][1] + 8*v_arr[1][0] + 16*v_arr[0][1] + 32*v_arr[0][0]
def change_one(pair, index, new_value):
"""Return new tuple with one element modified."""
new_pair = list(pair)
new_pair[index] = new_value
return tuple(new_pair)
def product(*args, **kwargs):
return list(itertools.product(*args, **kwargs))
# v_arr has the right value at c projection fixed
def add_constraints1(p, lv, client_index, v_ind1, v_ind2, v_arr):
L = []
weights = {}
v_ind_list = [v_ind1, v_ind2]
w = [1, -1]
for i in range(2):
v_ind = v_ind_list[i]
weight = w[i]
for rest in itertools.product(range(2), repeat = 3):
v_arr_new = tuple([change_one(pair, 1-c, r)
for (pair, c, r) in zip(v_arr, client_index, rest)])
# print 'v_arr_new = ',v_arr_new
L.append(str((v_ind, v_arr_new)))
weights[str((v_ind, v_arr_new))] = weight
# print 'added constraint ',L
p.add_constraint(sum(weights[o] * lv[o] for o in L) <= 0)
p.add_constraint(sum(-weights[o] * lv[o] for o in L) <= 0)
# print 'added according to L = ',L
# is this necessary or does lv actually pass by reference ?
def add_constraints2(p, lv, v_ind):
L = []
for v_arr in product(list(product(range(2), repeat = 2)), repeat = 3):
L.append(str((v_ind, v_arr)))
# print 'added according to L = ',L
p.add_constraint(sum(lv[o] for o in L) <= 1)
p.add_constraint(sum(-lv[o] for o in L) <= -1)
# each of the list elements is a non-empty list of triples
def generate_LP(client_index_list):
p = MixedIntegerLinearProgram()
lv = p.new_variable()
lv.set_min(0)
# type 1 constraints
for k in range(3):
for (x,y) in itertools.product(range(2), repeat = 2):
for client_index in c_lists[k]:
#print 'client_index,k',client_index,',',k
for v_arr_c in itertools.product(range(2), repeat = 3):
# print 'k,(x,y),client_index,v_arr_c =',k,',',x,y,',',client_index,',',v_arr_c
v_arr = [change_one((0, 0), c, r) for (c, r) in zip(client_index, v_arr_c)]
v1_ind = [0,0,0]
v2_ind = [0,0,0]
v1_ind[k] = 0
v2_ind[k] = 1
v1_ind[(k+1) % 3] = v2_ind[(k+1) % 3] = x
v1_ind[(k+2) % 3] = v2_ind[(k+2) % 3] = y
# print 'v_arr = ',v_arr
add_constraints1(p, lv, client_index, tuple(v1_ind), tuple(v2_ind), v_arr)
# type 2 constraints
print 'ADDING T2 CONSTRAINTS'
for v_ind in itertools.product(range(2), repeat = 3):
add_constraints2(p, lv, v_ind)
# objective
for i in range(400):
L = []
rand_dir = get_rand_dir()
for v_ind in itertools.product(range(2), repeat = 3):
for v_arr in product(list(product(range(2), repeat = 2)), repeat = 3):
L.append(str((v_ind, v_arr)))
p.set_objective(sum(lv[d]*rand_dir[i] for (i,d) in enumerate(L)))
# p.set_objective(5)
p.solve()
pairs = [t for t in p.get_values(lv).iteritems()]
pairs = sorted(pairs)
vlist = [int(y*10000)/10000.0 for (x,y) in pairs]
vec_is_ok = verify_vector(vlist)
if vec_is_ok:
print 'vec_is_really_ok!',vec_is_ok
print 'solution = \n',vlist
#for (x,y) in pairs:
# if y != 0:
# print '(x,y)=',x,y,' ; ',
print 'now as a matrix\n'
m = matrix(QQ, 8, 64, vlist)
sage.plot.matrix_plot.matrix_plot(m).show()
elif i % 30 == 0:
print 'vec_is_ok',vec_is_ok,',',i
print 'starting up'
vectors = list(itertools.product(range(2), repeat = 3))
print 'vectors = ', vectors
spread_indices = list(itertools.product(range(3), repeat = 5))
# print 'spread_indices = ', spread_indices
nsteps = 0
for i in spread_indices:
flag1 = (1 in i)
flag2 = (2 in i)
endings = []
print 'flags =',
if flag1 and flag2:
endings = list(itertools.product(range(3), repeat = 2))
elif flag1 and not flag2:
endings = [(2,0),(2,1),(2,2),(0,2),(1,2)]
elif flag2 and not flag1:
endings = [(1,0),(1,1),(1,2),(0,1),(2,1)]
else:
endings = [(1,2),(2,1)]
print 'went over endings in ',i,' = ',endings
for j in endings:
c_distr = i + j
c_lists = [[(0,0,0)],[],[]]
for (t,d) in enumerate(c_distr):
c_lists[d].append(vectors[t+1])
print 'c distribution = ',c_distr
p = generate_LP(c_lists)
nsteps = nsteps + 1
if nsteps > 10:
break
︡28c8f53b-fdf8-414f-997b-9c5a241b90b8︡{"stdout":"starting up\n"}︡{"stdout":"vectors = [(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1), (1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1)]\n"}︡{"stdout":"flags = went over endings in (0, 0, 0, 0, 0) = [(1, 2), (2, 1)]\nc distribution = (0, 0, 0, 0, 0, 1, 2)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_really_ok!"}︡{"stdout":" 1\nsolution = \n[0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.500000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.500000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 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0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.499900000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.499900000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.499900000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.499900000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 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0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.499900000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.499900000000000, 0.000000000000000]"}︡{"stdout":"\nnow as a matrix\n\n"}︡{"file":{"filename":"/home/user/.sage/temp/project-9005d034-5886-4217-bd5e-49c40dc11971/1139/tmp_tzNa24.svg","show":true,"text":null,"uuid":"46b25b6d-c3dc-4ae7-b7c7-f1813c3a66f8"},"once":false}︡{"stdout":"vec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nc distribution = "}︡{"stdout":" (0, 0, 0, 0, 0, 2, 1)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_ok"}︡{"stdout":" 0 , 120\nvec_is_ok"}︡{"stdout":" 0 , 150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nflags ="}︡{"stdout":" went over endings in (0, 0, 0, 0, 1) = [(2, 0), (2, 1), (2, 2), (0, 2), (1, 2)]\nc distribution = (0, 0, 0, 0, 1, 2, 0)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_ok"}︡{"stdout":" 0 , 120\nvec_is_ok"}︡{"stdout":" 0 , 150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nc distribution = "}︡{"stdout":" (0, 0, 0, 0, 1, 2, 1)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_ok"}︡{"stdout":" 0 , 120\nvec_is_ok"}︡{"stdout":" 0 , 150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nvec_is_really_ok!"}︡{"stdout":" 1\nsolution = \n[0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 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150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_really_ok!"}︡{"stdout":" 1\nsolution = \n[0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.500000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.500000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 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2) = [(1, 0), (1, 1), (1, 2), (0, 1), (2, 1)]\nc distribution = (0, 0, 0, 0, 2, 1, 0)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_ok"}︡{"stdout":" 0 , 120\nvec_is_ok"}︡{"stdout":" 0 , 150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nc distribution = "}︡{"stdout":" (0, 0, 0, 0, 2, 1, 1)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_really_ok!"}︡{"stdout":" 1\nsolution = \n[0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 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180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nc distribution = "}︡{"stdout":" (0, 0, 0, 0, 2, 1, 2)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_ok"}︡{"stdout":" 0 , 120\nvec_is_ok"}︡{"stdout":" 0 , 150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nc distribution = "}︡{"stdout":" (0, 0, 0, 0, 2, 0, 1)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_ok"}︡{"stdout":" 0 , 120\nvec_is_really_ok!"}︡{"stdout":" 1\nsolution = \n[0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.500000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 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0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000]"}︡{"stdout":"\nnow as a matrix\n\n"}︡{"file":{"filename":"/home/user/.sage/temp/project-9005d034-5886-4217-bd5e-49c40dc11971/1139/tmp_GYtQG1.svg","show":true,"text":null,"uuid":"ad5d7494-647e-49d1-a744-4c9393d554ba"},"once":false}︡{"stdout":"vec_is_ok"}︡{"stdout":" 0 , 150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\nc distribution = "}︡{"stdout":" (0, 0, 0, 0, 2, 2, 1)\nADDING T2 CONSTRAINTS"}︡{"stdout":"\nvec_is_ok 0 , 0\nvec_is_ok"}︡{"stdout":" 0 , 30\nvec_is_ok"}︡{"stdout":" 0 , 60\nvec_is_ok"}︡{"stdout":" 0 , 90\nvec_is_ok"}︡{"stdout":" 0 , 120\nvec_is_ok"}︡{"stdout":" 0 , 150\nvec_is_ok"}︡{"stdout":" 0 , 180\nvec_is_ok"}︡{"stdout":" 0 , 210\nvec_is_ok"}︡{"stdout":" 0 , 240\nvec_is_ok"}︡{"stdout":" 0 , 270\nvec_is_ok"}︡{"stdout":" 0 , 300\nvec_is_ok"}︡{"stdout":" 0 , 330\nvec_is_really_ok!"}︡{"stdout":" 1\nsolution = \n[0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.500000000000000, 0.500000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.000000000000000, 0.500000000000000, 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matrix\n\n"}︡{"file":{"filename":"/home/user/.sage/temp/project-9005d034-5886-4217-bd5e-49c40dc11971/1139/tmp_xw_d9W.svg","show":true,"text":null,"uuid":"18f02674-e32f-404c-8b1a-7475ecdc5d45"},"once":false}︡{"stdout":"vec_is_ok"}︡{"stdout":" 0 , 360\nvec_is_ok"}︡{"stdout":" 0 , 390\n"}︡{"done":true}︡
︠81c75631-c8b5-42e4-aa08-f4d68c56274c︠
p = MixedIntegerLinearProgram()
v = p.new_variable(real=True, nonnegative=True)
p.solve()
x, y, z = v['x'], v['y'], v['z']
type(2*x <= 0)
v = p.get_values(v)
print v.values()
print v.keys()
x=1
s=55
print x/s
︡f62d3342-0386-45b6-be86-7e2b8f37daa1︡{"stdout":"0.0\n"}︡{"stdout":"<type 'sage.numerical.linear_functions.LinearConstraint'>\n"}︡{"stdout":"[0.0, 0.0, 0.0]\n"}︡{"stdout":"['y', 'x', 'z']\n"}︡{"stdout":"1/55\n"}︡{"done":true}︡
︠b61934bf-c082-4fe2-9588-4d09688e101bw︠
type(1), type(1r)
︡8afba460-faec-4f95-b239-5b6d6480a2b6︡
︠8a557a48-4e83-4a9c-90d6-5d573a2a49b4︠
︠7dcf55ec-c018-4009-8544-a64ce0b7afd1︠
| 514.128079
| 97,037
| 0.803589
| 12,329
| 104,368
| 6.779625
| 0.030741
| 0.854497
| 0.906073
| 1.651951
| 0.964468
| 0.962996
| 0.956871
| 0.954789
| 0.953629
| 0.952516
| 0
| 0.777044
| 0.070242
| 104,368
| 202
| 97,038
| 516.673267
| 0.081814
| 0.007368
| 0
| 0.091549
| 0
| 0.169014
| 0.925954
| 0.014944
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.028169
| null | null | 0.098592
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 15
|
fa0645331a197208b6c4764490654193a27a6119
| 9,883
|
py
|
Python
|
Augmenters/augmenters.py
|
123prashanth123/Fault-Detection-System
|
fa59ca81ce4627a42648e654b55cdc505cde2103
|
[
"MIT"
] | null | null | null |
Augmenters/augmenters.py
|
123prashanth123/Fault-Detection-System
|
fa59ca81ce4627a42648e654b55cdc505cde2103
|
[
"MIT"
] | null | null | null |
Augmenters/augmenters.py
|
123prashanth123/Fault-Detection-System
|
fa59ca81ce4627a42648e654b55cdc505cde2103
|
[
"MIT"
] | 1
|
2021-07-26T08:58:43.000Z
|
2021-07-26T08:58:43.000Z
|
"""
1. Information regarding various Augmentation Pipelines used.
2. Add all augmentation pipelines used for reference.
"""
import imgaug
from imgaug import augmenters
# ******************************************************************************************************************** #
def get_augments_1(augment_seed=None):
imgaug.seed(entropy=augment_seed)
dataset_augment = augmenters.Sequential([
augmenters.HorizontalFlip(p=0.25),
augmenters.VerticalFlip(p=0.25),
augmenters.SomeOf(5, [
augmenters.blur.GaussianBlur(sigma=(0, 5), seed=augment_seed),
augmenters.blur.MedianBlur(k=(1, 7), seed=augment_seed),
augmenters.size.Crop(percent=(0, 0.15), seed=augment_seed),
augmenters.geometric.Affine(rotate=(-45, 45), scale=(0.75, 1.25), translate_percent=(-0.15, 0.15), seed=augment_seed),
augmenters.geometric.Rot90(k=(1, 3), seed=augment_seed),
augmenters.arithmetic.Dropout(p=(0, 0.075), seed=augment_seed),
augmenters.arithmetic.SaltAndPepper(p=(0, 0.075), seed=augment_seed),
augmenters.color.MultiplyBrightness(mul=(0.5, 1.5)),
augmenters.color.MultiplySaturation(mul=(0, 5), seed=augment_seed),
augmenters.iaa_convolutional.Sharpen(alpha=(0.75, 1), lightness=(0.75, 1.25), seed=augment_seed),
augmenters.iaa_convolutional.Emboss(alpha=(0.75, 1), strength=(0.75, 1.25), seed=augment_seed),
augmenters.contrast.CLAHE(seed=augment_seed),
augmenters.contrast.GammaContrast(gamma=(0.2, 5), seed=augment_seed),
])
])
imgaug.seed(entropy=augment_seed)
roi_augment = augmenters.Sequential([augmenters.imgcorruptlike.GlassBlur(severity=(3, 5), seed=augment_seed)] * 3)
return dataset_augment, roi_augment
# ******************************************************************************************************************** #
def get_augments_2(augment_seed=None):
imgaug.seed(entropy=augment_seed)
dataset_augment = augmenters.Sequential([
augmenters.HorizontalFlip(p=0.25),
augmenters.VerticalFlip(p=0.25),
augmenters.SomeOf(5, [
augmenters.blur.GaussianBlur(sigma=(0, 5), seed=augment_seed),
augmenters.blur.MedianBlur(k=(1, 7), seed=augment_seed),
augmenters.size.Crop(percent=(0, 0.15), seed=augment_seed),
augmenters.geometric.Affine(rotate=(-45, 45), scale=(0.9, 1.1), translate_percent=(-0.1, 0.1), seed=augment_seed),
augmenters.geometric.Rot90(k=(1, 3), seed=augment_seed),
augmenters.arithmetic.Dropout(p=(0, 0.05), seed=augment_seed),
augmenters.arithmetic.SaltAndPepper(p=(0, 0.05), seed=augment_seed),
augmenters.color.MultiplyBrightness(mul=(0.5, 1.5)),
augmenters.color.MultiplySaturation(mul=(0, 5), seed=augment_seed),
augmenters.iaa_convolutional.Sharpen(alpha=(0.75, 1), lightness=(0.75, 1.25), seed=augment_seed),
augmenters.iaa_convolutional.Emboss(alpha=(0.75, 1), strength=(0.75, 1.25), seed=augment_seed),
augmenters.contrast.CLAHE(seed=augment_seed),
augmenters.contrast.GammaContrast(gamma=(0.2, 5), seed=augment_seed),
])
])
imgaug.seed(entropy=augment_seed)
roi_augment = augmenters.Sequential([augmenters.imgcorruptlike.GlassBlur(severity=(3, 5), seed=augment_seed)] * 3)
return dataset_augment, roi_augment
# ******************************************************************************************************************** #
def get_augments_3(augment_seed=None):
imgaug.seed(entropy=augment_seed)
dataset_augment = augmenters.Sequential([
augmenters.HorizontalFlip(p=0.25),
augmenters.VerticalFlip(p=0.25),
augmenters.SomeOf(5, [
augmenters.blur.GaussianBlur(sigma=(0, 5), seed=augment_seed),
augmenters.blur.MedianBlur(k=(1, 7), seed=augment_seed),
augmenters.size.Crop(percent=(0, 0.25), seed=augment_seed),
augmenters.geometric.Affine(rotate=(-45, 45), scale=(0.5, 1.5), translate_percent=(-0.25, 0.25), seed=augment_seed),
augmenters.geometric.Rot90(k=(1, 3), seed=augment_seed),
augmenters.arithmetic.Dropout(p=(0, 0.05), seed=augment_seed),
augmenters.arithmetic.SaltAndPepper(p=(0, 0.05), seed=augment_seed),
augmenters.color.MultiplyBrightness(mul=(0.5, 1.5)),
augmenters.color.MultiplySaturation(mul=(0, 5), seed=augment_seed),
augmenters.iaa_convolutional.Sharpen(alpha=(0.75, 1), lightness=(0.5, 1.5), seed=augment_seed),
augmenters.iaa_convolutional.Emboss(alpha=(0.75, 1), strength=(0.5, 1.5), seed=augment_seed),
augmenters.contrast.CLAHE(seed=augment_seed),
augmenters.contrast.GammaContrast(gamma=(0.2, 5), seed=augment_seed),
])
])
imgaug.seed(entropy=augment_seed)
roi_augment = augmenters.Sequential([augmenters.imgcorruptlike.GlassBlur(severity=(3, 5), seed=augment_seed)] * 5)
return dataset_augment, roi_augment
# ******************************************************************************************************************** #
def get_augments_4(augment_seed=None):
imgaug.seed(entropy=augment_seed)
dataset_augment = augmenters.Sequential([
augmenters.HorizontalFlip(p=0.25),
augmenters.VerticalFlip(p=0.25),
augmenters.SomeOf(5, [
augmenters.blur.GaussianBlur(sigma=(0, 5), seed=augment_seed),
augmenters.blur.MedianBlur(k=(1, 7), seed=augment_seed),
augmenters.size.Crop(percent=(0, 0.15), seed=augment_seed),
augmenters.geometric.Affine(rotate=(-45, 45), scale=(0.75, 1.25), translate_percent=(-0.15, 0.15), seed=augment_seed, cval=(0, 255), mode="symmetric"),
augmenters.geometric.Rot90(k=(1, 3), seed=augment_seed),
augmenters.arithmetic.Dropout(p=(0, 0.075), seed=augment_seed),
augmenters.arithmetic.SaltAndPepper(p=(0, 0.075), seed=augment_seed),
augmenters.color.MultiplyBrightness(mul=(0.5, 1.5)),
augmenters.color.MultiplySaturation(mul=(0, 5), seed=augment_seed),
augmenters.iaa_convolutional.Sharpen(alpha=(0.75, 1), lightness=(0.75, 1.25), seed=augment_seed),
augmenters.iaa_convolutional.Emboss(alpha=(0.75, 1), strength=(0.75, 1.25), seed=augment_seed),
augmenters.contrast.CLAHE(seed=augment_seed),
augmenters.contrast.GammaContrast(gamma=(0.2, 5), seed=augment_seed),
])
])
imgaug.seed(entropy=augment_seed)
# roi_augment = augmenters.Sequential([augmenters.imgcorruptlike.GlassBlur(severity=(3, 5), seed=augment_seed)] * 3)
roi_augment = augmenters.Sequential([augmenters.imgcorruptlike.Pixelate(severity=5, seed=augment_seed)])
return dataset_augment, roi_augment
# ******************************************************************************************************************** #
def get_augments_5(augment_seed=None):
imgaug.seed(entropy=augment_seed)
dataset_augment = augmenters.Sequential([
augmenters.HorizontalFlip(p=0.25),
augmenters.VerticalFlip(p=0.25),
augmenters.SomeOf(5, [
augmenters.blur.GaussianBlur(sigma=(0, 5), seed=augment_seed),
augmenters.blur.MedianBlur(k=(1, 7), seed=augment_seed),
augmenters.size.Crop(percent=(0, 0.15), seed=augment_seed),
augmenters.geometric.Affine(rotate=(-45, 45), scale=(0.75, 1.25), translate_percent=(-0.15, 0.15), seed=augment_seed, cval=(0, 255), mode="symmetric"),
augmenters.geometric.Rot90(k=(1, 3), seed=augment_seed),
augmenters.arithmetic.Dropout(p=(0, 0.075), seed=augment_seed),
augmenters.arithmetic.SaltAndPepper(p=(0, 0.075), seed=augment_seed),
augmenters.contrast.CLAHE(seed=augment_seed),
augmenters.contrast.GammaContrast(gamma=(0.2, 5), seed=augment_seed),
])
])
return dataset_augment
# ******************************************************************************************************************** #
def get_augments_6(augment_seed=None):
imgaug.seed(entropy=augment_seed)
dataset_augment = augmenters.Sequential([
augmenters.HorizontalFlip(p=0.25),
augmenters.VerticalFlip(p=0.25),
augmenters.SomeOf(5, [
augmenters.blur.GaussianBlur(sigma=(0, 2), seed=augment_seed),
augmenters.blur.MedianBlur(k=(1, 3), seed=augment_seed),
augmenters.size.Crop(percent=(0, 0.10), seed=augment_seed),
augmenters.geometric.Affine(rotate=(-45, 45), scale=(0.9, 1.1), translate_percent=(-0.05, 0.05), seed=augment_seed, cval=100, mode="symmetric"),
augmenters.geometric.Rot90(k=(1, 3), seed=augment_seed),
augmenters.arithmetic.Dropout(p=(0, 0.075), seed=augment_seed),
augmenters.arithmetic.SaltAndPepper(p=(0, 0.075), seed=augment_seed),
augmenters.color.MultiplyBrightness(mul=(0.5, 1.5)),
augmenters.color.MultiplySaturation(mul=(0, 5), seed=augment_seed),
augmenters.iaa_convolutional.Sharpen(alpha=(0.75, 1), lightness=(0.75, 1.25), seed=augment_seed),
augmenters.iaa_convolutional.Emboss(alpha=(0.75, 1), strength=(0.75, 1.25), seed=augment_seed),
augmenters.contrast.CLAHE(seed=augment_seed),
augmenters.contrast.GammaContrast(gamma=(0.2, 5), seed=augment_seed),
])
])
imgaug.seed(entropy=augment_seed)
roi_augment = augmenters.Sequential([augmenters.imgcorruptlike.GlassBlur(severity=5, seed=augment_seed),])
return dataset_augment, roi_augment
# ******************************************************************************************************************** #
| 55.212291
| 163
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0
| 9
|
fa6126fa86d0e2928ba4afd382c16cab62b8058c
| 12,302
|
py
|
Python
|
tests/test_hunminjeongeum.py
|
Pusnow/Sortable-Hangul
|
8dab1effa1e589530fa50c58bf2f455610e12e25
|
[
"MIT"
] | 1
|
2018-12-28T07:00:31.000Z
|
2018-12-28T07:00:31.000Z
|
tests/test_hunminjeongeum.py
|
Pusnow/Sortable-Hangul
|
8dab1effa1e589530fa50c58bf2f455610e12e25
|
[
"MIT"
] | null | null | null |
tests/test_hunminjeongeum.py
|
Pusnow/Sortable-Hangul
|
8dab1effa1e589530fa50c58bf2f455610e12e25
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
import unittest
from sortable_hangul import encoder
TEXT = """
솅〮宗조ᇰ御ᅌᅥᆼ〮製졩〮訓훈〮民민正져ᇰ〮音ᅙᅳᆷ
製졩〮ᄂᆞᆫ〮글〮지ᅀᅳᆯ〮씨〮니〮御ᅌᅥᆼ〮製졩〮ᄂᆞᆫ〮님〯금〮지〯ᅀᅳ샨〮그〮리라〮訓훈〮은〮ᄀᆞᄅᆞ칠〮씨〮오〮民민ᄋᆞᆫ〮百ᄇᆡᆨ〮姓셔ᇰ〮이〮오〮音ᅙᅳᆷ은〮소리〮니〮訓훈〮民민正져ᇰ〮音ᅙᅳᆷ은〮百ᄇᆡᆨ〮姓셔ᇰ〮ᄀᆞᄅᆞ치〮시논〮正져ᇰ〮ᄒᆞᆫ소리〮라〮
國귁〮之징語ᅌᅥᆼ〯音ᅙᅳᆷ이〮
國귁〮ᄋᆞᆫ〮나라〮히라〮之징ᄂᆞᆫ〮입〮겨〮지라〮語ᅌᅥᆼ〯는말〯ᄊᆞ미라〮
나랏〮말〯ᄊᆞ미〮
異잉〮乎ᅘᅩᆼ中듀ᇰ國귁〮ᄒᆞ〮야〮
異잉〮ᄂᆞᆫ〮다ᄅᆞᆯ씨라乎ᅘᅩᆼᄂᆞᆫ〮아〯모〮그ᅌᅦᄒᆞ〮논겨〮체ᄡᅳ〮는字ᄍᆞᆼ〮ㅣ라〮中듀ᇰ國귁〮ᄋᆞᆫ〮
皇ᅘᅪᇰ帝뎽〮겨〯신나라〮히니〮우〮리〮나랏〮常쌰ᇰ談땀애〮江가ᇰ南남이〮라〮ᄒᆞ〮ᄂᆞ〮니라〮
中듀ᇰ國귁〮에〮달아〮
與영〯文문字ᄍᆞᆼ〮로〮不부ᇙ〮相샤ᇰ流류ᇢ通토ᇰᄒᆞᆯᄊᆡ〮
與영〯는〮이〮와〮뎌〮와〮ᄒᆞ〮ᄂᆞᆫ겨〮체ᄡᅳ〮ᄂᆞᆫ字ᄍᆞᆼ〮ㅣ라〮文문은〮글〮와〮리라〮不부ᇙ〮은〮아니〮ᄒᆞ〮논ᄠᅳ〮디라〮相샤ᇰᄋᆞᆫ〮서르ᄒᆞ〮논ᄠᅳ〮디라〮流류ᇢ通토ᇰᄋᆞᆫ〮흘러〮ᄉᆞᄆᆞᄎᆞᆯ〮씨〮라〮
文문字ᄍᆞᆼ〮와〮로〮서르ᄉᆞᄆᆞᆺ디〮아니〮ᄒᆞᆯᄊᆡ〮
故공〮로〮愚ᅌᅮᆼ民민이〮有ᅌᅮᇢ〯所송〯欲욕〮言ᅌᅥᆫᄒᆞ〮야도〮
故공〮ᄂᆞᆫ〮젼ᄎᆡ〮라〮愚ᅌᅮᆼ는〮어릴〮씨〮라〮有ᅌᅮᇢ〯는이실씨〮라〮所송〯ᄂᆞᆫ〮배〮라〮欲욕〮ᄋᆞᆫ〮ᄒᆞ고〮져〮ᄒᆞᆯ씨〮라〮言ᅌᅥᆫ은〮니를씨〮라〮
이〮런젼ᄎᆞ〮로〮어린〮百ᄇᆡᆨ姓셔ᇰ〮이〮니르고〮져〮호ᇙ〮배〮이셔〮도〮
而ᅀᅵᆼ終쥬ᇰ不부ᇙ〮得득〮伸신其끵情쪄ᇰ者:쟝ㅣ多당矣ᅌᅴᆼ〯라〮
而ᅀᅵᆼᄂᆞᆫ〮입〮겨〮지라〮終쥬ᇰ은ᄆᆞᄎᆞ〮미라〮得득〮은〮시를〮씨〮라〮伸신ᄋᆞᆫ〮펼씨〮라〮其끵ᄂᆞᆫ〮제〯라〮情쪄ᇰ은〮ᄠᅳ〮디라〮者쟝〯ᄂᆞᆫ〮노〮미라〮多당ᄂᆞᆫ〮할씨〮라〮矣ᅌᅴᆼ〯ᄂᆞᆫ〮말〯ᄆᆞᆺᄂᆞᆫ입〮겨〮지라〮
ᄆᆞᄎᆞᆷ〮내〯제ᄠᅳ〮들〮시러〮펴디〮몯〯ᄒᆞᇙ노〮미〮하니〮라〮
予영ㅣ爲윙〮此ᄎᆞᆼ〯憫민〯然ᅀᅧᆫᄒᆞ〮야〮
予영는〮내〮ᄒᆞ〮ᅀᆞᆸ시〮논ᄠᅳ〮디〮시니〮라〮此ᄎᆞᆼ〯ᄂᆞᆫ〮이〮라〮憫민〯然ᅀᅧᆫ은〮어〯엿비〮너기〮실씨〮라〮
내〮이〮ᄅᆞᆯ〮爲윙〮ᄒᆞ〮야〮어〯엿비〮너겨〮
新신制졩〮二ᅀᅵᆼ〮十씹〮八바ᇙ〮字ᄍᆞᆼ〮ᄒᆞ〮노니〮
新신ᄋᆞᆫ〮새〮라〮制졩〮ᄂᆞᆫ〮ᄆᆡᇰᄀᆞ〮ᄅᆞ〮실씨〮라〮二ᅀᅵᆼ〮十씹〮八바ᇙ〮ᄋᆞᆫ〮스〮믈〮여들〮비라〮
새〮로〮스〮믈〮여듧〮字ᄍᆞᆼ〮ᄅᆞᆯ〮ᄆᆡᇰᄀᆞ〮노니〮
欲욕〮使ᄉᆞᆼ〯人ᅀᅵᆫ人ᅀᅵᆫᄋᆞ〮로〮易잉〮習씹〮ᄒᆞ〮야〮便뼌於ᅙᅥᆼ日ᅀᅵᇙ〮用요ᇰ〮耳ᅀᅵᆼ〯니라〮
使ᄉᆞᆼ〯ᄂᆞᆫ〮ᄒᆡ〯ᅇᅧ〮ᄒᆞ〮논마〮리라〮人ᅀᅵᆫᄋᆞᆫ〮사〯ᄅᆞ〮미라〮易잉〮ᄂᆞᆫ〮쉬〯ᄫᅳᆯ씨〮라〮習씹〮ᄋᆞᆫ〮니길〮씨〮라〮便뼌은〮便뼌安ᅙᅡᆫᄒᆞᆯ씨〮라〮於ᅙᅥᆼ는〮아〯모〮그ᅌᅦᄒᆞ〮논겨〮체ᄡᅳ〮는字ᄍᆞᆼ〮ㅣ라〮日ᅀᅵᇙ〮ᄋᆞᆫ〮나〮리라〮用요ᇰ〮ᄋᆞᆫ〮ᄡᅳᆯ〮씨〮라〮耳ᅀᅵᆼ〯ᄂᆞᆫ〮ᄯᆞᄅᆞ미〮라〮ᄒᆞ〮논ᄠᅳ〮디라〮
사〯ᄅᆞᆷ마〯다〮ᄒᆡ〯ᅇᅧ〮수〯ᄫᅵ〮니겨〮날〮로〮ᄡᅮ〮메〮便뼌安ᅙᅡᆫ킈〮ᄒᆞ고〮져〮ᄒᆞᇙᄯᆞᄅᆞ미〮니라〮
ㄱᄂᆞᆫ〮牙ᅌᅡᆼ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ君군ㄷ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ虯뀨ᇢㅸ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
牙ᅌᅡᆼᄂᆞᆫ〮어〯미라〮如ᅀᅧᆼ는〮ᄀᆞ〮ᄐᆞᆯ씨〮라〮初총發버ᇙ〮聲셔ᇰ은〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮라〮並버ᇙ〮書셩는〮ᄀᆞᆯᄫᅡ〮쓸〮씨〮라〮
ㄱᄂᆞᆫ〮엄〯쏘리〮니〮君군ㄷ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯᄫᅡ〮쓰〮면〮虯뀨ᇢㅸ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅋᄂᆞᆫ〮牙ᅌᅡᆼ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ快쾡〮ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰ니〮라〮
ㅋᄂᆞᆫ〮엄〯쏘리〮니〮快쾡〮ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㆁᄂᆞᆫ〮牙ᅌᅡᆼ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ業ᅌᅥᆸ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰ니〮라〮
ㆁᄂᆞᆫ〮엄〯쏘리〮니〮業ᅌᅥᆸ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㄷᄂᆞᆫ〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ斗두ᇢㅸ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ覃땀ㅂ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
舌쎠ᇙ〮은〮혜〮라〮
ㄷᄂᆞᆫ〮혀〮쏘리〮니〮斗두ᇢㅸ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯᄫᅡ〮쓰〮면〮覃땀ㅂ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅌᄂᆞᆫ〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅌᄂᆞᆫ〮혀〮쏘리〮니〮呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㄴᄂᆞᆫ〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ那낭ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㄴᄂᆞᆫ〮혀〮쏘리〮니〮那낭ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅂᄂᆞᆫ〮脣쓘音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ彆벼ᇙ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ歩뽕ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
脣쓘은〮입시우〮리라〮
ㅂᄂᆞᆫ〮입시울〮쏘리〮니〮彆벼ᇙ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮歩뽕ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅍᄂᆞᆫ〮脣쓘音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ漂표ᇢㅸ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅍᄂᆞᆫ〮입시울〮쏘리〮니〮漂표ᇢㅸ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅁᄂᆞᆫ〮脣쓘音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ彌밍ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅁᄂᆞᆫ〮입시울〮쏘리〮니〮彌밍ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅈᄂᆞᆫ〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ卽즉〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ慈ᄍᆞᆼㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
齒ᄂᆞᆫ〮니〮라〮
ㅈᄂᆞᆫ〮니〮쏘리〮니〮卽즉〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮慈ᄍᆞᆼㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅊᄂᆞᆫ〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ侵침ㅂ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅊᄂᆞᆫ〮니〮쏘리〮니〮侵침ㅂ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅅᄂᆞᆫ〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ戌슈ᇙ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ邪썅ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅅᄂᆞᆫ〮니〮쏘리〮니〮戌슈ᇙ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮邪썅ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㆆᄂᆞᆫ〮喉ᅘᅮᇢ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ挹ᅙᅳᆸ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
喉ᅘᅮᇢ는〮모기〮라〮
ㆆᄂᆞᆫ〮목소리〮니〮挹ᅙᅳᆸ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅎᄂᆞᆫ〮喉ᅘᅮᇢ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ虛헝ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅎᄂᆞᆫ〮목소리〮니〮虛헝ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅇᄂᆞᆫ〮喉ᅘᅮᇢ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ欲욕〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅇᄂᆞᆫ〮목소리〮니〮欲욕〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㄹᄂᆞᆫ〮半반〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ閭령ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㄹᄂᆞᆫ〮半반〮혀〮쏘리〮니〮閭령ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅿᄂᆞᆫ〮半반〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅿᄂᆞᆫ〮半반〮니〮쏘리〮니〮穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㆍᄂᆞᆫ〮如ᅀᅧᆼ呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
中듀ᇰ은〮가온〮ᄃᆡ〮라〮
ㆍᄂᆞᆫ〮呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅡᄂᆞᆫ〮卽즉〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅡᄂᆞᆫ〮卽즉〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅣᄂᆞᆫ〮侵침ㅂ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅣᄂᆞᆫ〮侵침ㅂ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅗᄂᆞᆫ〮洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅗᄂᆞᆫ〮洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅏᄂᆞᆫ〮覃땀ㅂ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅏᄂᆞᆫ〮覃땀ㅂ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅜᄂᆞᆫ〮君군ㄷ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅜᄂᆞᆫ〮君군ㄷ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅓᄂᆞᆫ〮業ᅌᅥᆸ〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅓᄂᆞᆫ〮業ᅌᅥᆸ〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅛᄂᆞᆫ〮欲욕〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅛᄂᆞᆫ〮欲욕〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅑᄂᆞᆫ〮穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅑᄂᆞᆫ〮穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅠᄂᆞᆫ〮戌슈ᇙ〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅠᄂᆞᆫ〮戌슈ᇙ〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅕᄂᆞᆫ〮彆벼ᇙ〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅕᄂᆞᆫ〮彆벼ᇙ〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
終쥬ᇰ聲셔ᇰ은〮復뿌ᇢ〮用요ᇰ〮初총聲셔ᇰᄒᆞ〮ᄂᆞ〮니라〮
復뿌ᇢ〮는〮다시〮ᄒᆞ〮논ᄠᅳ〮디라〮
乃냉〯終쥬ᇰᄀᅠ소리〮ᄂᆞᆫ〮다시〮처〮소리〮ᄅᆞᆯ〮ᄡᅳ〮ᄂᆞ〮니라〮
ㅇᄅᆞᆯ連련書셩脣쓘音ᅙᅳᆷ之징下ᅘᅡᆼ〯ᄒᆞ면則즉〮爲ᅌᅱᆼ脣쓘輕켜ᇰ音ᅙᅳᆷᄒᆞ〮ᄂᆞ〮니라〮
連련은〮니ᅀᅳᆯ〮씨〮라〮下ᅘᅡᆼ〮ᄂᆞᆫ〮아래〮라〮則즉〮은〮아〯ᄆᆞ〮리ᄒᆞ면〮ᄒᆞ〮ᄂᆞᆫ겨〮체〮ᄡᅳ〮ᄂᆞᆫ字ᄍᆞᆼ〮ㅣ라爲ᅌᅱᆼᄂᆞᆫ〮ᄃᆞ욀씨〮라〮輕켜ᇰ은〮가ᄇᆡ〮야ᄫᆞᆯ〮씨〮라〮
ㅇᄅᆞᆯ〮입시울〮쏘리〮아래〮니ᅀᅥ〮쓰〮면〮입시울〮가ᄇᆡ〮야ᄫᆞᆫ〮소리〮ᄃᆞ외ᄂᆞ니〮라〮
初총聲셔ᇰ을〮合ᅘᅡᆸ〮用요ᇰ〮호ᇙ〮디면〮則즉〮並버ᇙ〮書셩ᄒᆞ라〮終쥬ᇰ聲셔ᇰ도〮同또ᇰᄒᆞ니〮라〮
合ᅘᅡᆸ〮ᄋᆞᆫ〮어울〮씨〮라〮同또ᇰᄋᆞᆫ〮ᄒᆞᆫ가지〮라〮ᄒᆞ〮논ᄠᅳ〮디라〮
처〮소리〮ᄅᆞᆯ〮어울〮워〮ᄡᅮᇙ〮디〮면〮ᄀᆞᆯᄫᅡ〮쓰〮라〮乃냉〯終쥬ᇰㄱ소리〮도〮ᄒᆞᆫ가지〮라〮
ㆍㅡㅗㅜㅛㅠ라〮附뿡〮書셩初총聲셔ᇰ之징下ᅘᅡᆼ〯ᄒᆞ고〮
附뿡〮는〮브틀〮씨〮라〮
ㆍ와〮ㅗ와〮ㅜ와〮ㅛ와〮ㅠ와〮라〮처〮소리〮아래〮브텨〮쓰〮고〮
ㅣㅏㅓㅑㅕ라〮附뿡〮書셩於ᅙᅥᆼ右ᅌᅮᇢ〯ᄒᆞ라〮.
右ᅌᅮᇢ〯는〮올〮ᄒᆞᆫ녀기〮라〮
ㅣ와〮ㅏ와〮ㅓ와〮ㅑ와〮ㅕ와〮라〮와〮ᄒᆞᆫ녀긔〮브텨〮쓰〮라〮
凡뻠字ᄍᆞᆼ〮ㅣ必비ᇙ〮合ᅘᅡᆸ〮而ᅀᅵᆼ成쎠ᇰ音ᅙᅳᆷᄒᆞ〮ᄂᆞ니〮
凡뻠은〮믈읫ᄒᆞ〮논ᄠᅳ〮디라〮必비ᇙ〮ᄋᆞᆫ〮모로〮매〮ᄒᆞ〮논ᄠᅳ〮디라〮成쎠ᇰ은〮일〯씨〮라〮
믈읫字ᄍᆞᆼ〮ㅣ모로〮매〮어우〮러ᅀᅡ〮소리〮이〯ᄂᆞ니〮
左장〯加강一ᅙᅵᇙ〮點뎜〯ᄒᆞ면〮則즉〮去컹〮聲셔ᇰ이〮오〮
左장〯ᄂᆞᆫ〮왼〯녀기〮라〮加강ᄂᆞᆫ〮더을씨〮라〮一ᅙᅵᇙ〮ᄋᆞᆫ〮ᆞᆫᄒᆞ나히〮라〮去컹聲셔ᇰ은〮ᄆᆞᆺ〮노ᄑᆞᆫ〮소리〮라〮
왼〯녀긔〮ᄒᆞᆫ點뎜〯을〮더으면〮ᄆᆞᆺ〮노ᄑᆞᆫ〮소리〮오〮
二ᅀᅵᆼ〮則즉〮上쌰ᇰ〯聲셔ᇰ이〮오〮
二ᅀᅵᆼ〮ᄂᆞᆫ〮둘〯히라〮上쌰ᇰ〯聲셔ᇰ은〮처〮ᅀᅥ미〮ᄂᆞᆺ갑〯고乃냉〯終쥬ᇰ이〮노ᄑᆞᆫ〮소리〮라〮
點뎜〯이〮둘〯히면〮上쌰ᇰ〯聲셔ᇰ이〮오〮
無뭉則즉〮平버ᇙ聲셔ᇰ이〮오〮
無뭉는〮업〯슬씨〮라〮平버ᇙ聲셔ᇰ은〮ᄆᆞᆺ〮ᄂᆞᆺ가ᄫᆞᆫ〮소리〮라〮
點뎜〯이〮업〯스면〮平펴ᇰ聲셔ᇰ이〮오〮
入ᅀᅵᆸ〮聲셔ᇰ은〮加강點뎜〯이〮同또ᇰ而ᅀᅵᆼ促쵹〮急그〮ᄒᆞ니라
入ᅀᅵᆸ〮聲셔ᇰ은〮ᄲᆞᆯ리〮긋ᄃᆞᆮᄂᆞᆫ소리〮라〮促쵹〮急그〮은〮ᄲᆞᄅᆞᆯ씨〮라〮
入ᅀᅵᆸ〮聲셔ᇰ은〮點뎜〯더우〮믄〮ᄒᆞᆫ가지〮로ᄃᆡ〮ᄲᆞᄅᆞ니〮라〮
漢한〮音ᅙᅳᆷ齒칭〯聲셔ᇰ은〮有ᅌᅮᇢ〯齒칭〯頭뚜ᇢ正져ᇰ〮齒칭〯之징别벼ᇙ〮ᄒᆞ니〮
漢한〮音ᅙᅳᆷ은〮中듀ᇰ國귁〮소리〮라〮頭뚜ᇢ는〮머리〮라〮别벼ᇙ〮은〮ᄀᆞᆯᄒᆡᆯ〮씨〮라〮
中듀ᇰ國귁〮소리〮예〮니〮쏘리〮ᄂᆞᆫ〮齒칭〯頭뚜ᇢ와〮正져ᇰ〮齒칭〯왜〮ᄀᆞᆯᄒᆡ〮요미〮잇ᄂᆞ니〮
ᅎᅠᅔᅠᅏᅠᄼᅠᄽᅠ字ᄍᆞᆼ〮ᄂᆞᆫ〮用요ᇰ〮於ᅙᅥᆼ齒칭〯頭뚜ᇢᄒᆞ고〮
이〮소리〮ᄂᆞᆫ〮우〮리〮나라〮소리〮예셔〮열ᄫᅳ〮니〮혓〮그〮티〮웃니〮머리〮예〮다ᄔᆞ니〮라〮
ᅎᅠᅔᅠᅏᅠᄼᅠᄽᅠ字ᄍᆞᆼ〮ᄂᆞᆫ〮齒칭〯頭뚜ᇢㅅ소리〮예〮ᄡᅳ〮고〮
ᅐᅠᅕᅠᅑᅠᄾᅠᄿᅠ字ᄍᆞᆼ〮ᄂᆞᆫ〮用요ᇰ〮於ᅙᅥᆼ正져ᇰ〮齒칭〯ᄒᆞ〮ᄂᆞ니〮
이〮소리〮ᄂᆞᆫ〮우〮리〮나라〮소리〮예셔〮두터ᄫᅳ니〮혓〮그〮티〮아랫〮니〮므유메〮다ᄔᆞ니〮라〮
ᅐᅠᅕᅠᅑᅠᄾᅠᄿᅠ字ᄍᆞᆼ〮ᄂᆞᆫ正져ᇰ〮齒칭〯ㅅ소리〮예〮ᄡᅳ〮ᄂᆞ니〮
牙ᅌᅡᆼ舌쎠ᇙ〮脣쓘喉ᅘᅮᇢ之징字ᄍᆞᆼ〮ᄂᆞᆫ〮通토ᇰ用요ᇰ〮於ᅙᅥᆼ漢한〮音ᅙᅳᆷᄒᆞ〮ᄂᆞ〮니라〮
엄〯과〮혀〮와〮입시울〮와〮목소리〮옛〮字ᄍᆞᆼ〮ᄂᆞᆫ〮中듀ᇰ國귁〮소리〮예〮通토ᇰ히〮ᄡᅳ〮ᄂᆞ〮니라〮
訓훈〮民민正져ᇰ〮音ᅙᅳᆷ
"""
TEXT_SORTED = """
中듀ᇰ國귁〮소리〮예〮니〮쏘리〮ᄂᆞᆫ〮齒칭〯頭뚜ᇢ와〮正져ᇰ〮齒칭〯왜〮ᄀᆞᆯᄒᆡ〮요미〮잇ᄂᆞ니〮
中듀ᇰ國귁〮에〮달아〮
中듀ᇰ은〮가온〮ᄃᆡ〮라〮
乃냉〯終쥬ᇰᄀᅠ소리〮ᄂᆞᆫ〮다시〮처〮소리〮ᄅᆞᆯ〮ᄡᅳ〮ᄂᆞ〮니라〮
予영ㅣ爲윙〮此ᄎᆞᆼ〯憫민〯然ᅀᅧᆫᄒᆞ〮야〮
予영는〮내〮ᄒᆞ〮ᅀᆞᆸ시〮논ᄠᅳ〮디〮시니〮라〮此ᄎᆞᆼ〯ᄂᆞᆫ〮이〮라〮憫민〯然ᅀᅧᆫ은〮어〯엿비〮너기〮실씨〮라〮
二ᅀᅵᆼ〮則즉〮上쌰ᇰ〯聲셔ᇰ이〮오〮
二ᅀᅵᆼ〮ᄂᆞᆫ〮둘〯히라〮上쌰ᇰ〯聲셔ᇰ은〮처〮ᅀᅥ미〮ᄂᆞᆺ갑〯고乃냉〯終쥬ᇰ이〮노ᄑᆞᆫ〮소리〮라〮
使ᄉᆞᆼ〯ᄂᆞᆫ〮ᄒᆡ〯ᅇᅧ〮ᄒᆞ〮논마〮리라〮人ᅀᅵᆫᄋᆞᆫ〮사〯ᄅᆞ〮미라〮易잉〮ᄂᆞᆫ〮쉬〯ᄫᅳᆯ씨〮라〮習씹〮ᄋᆞᆫ〮니길〮씨〮라〮便뼌은〮便뼌安ᅙᅡᆫᄒᆞᆯ씨〮라〮於ᅙᅥᆼ는〮아〯모〮그ᅌᅦᄒᆞ〮논겨〮체ᄡᅳ〮는字ᄍᆞᆼ〮ㅣ라〮日ᅀᅵᇙ〮ᄋᆞᆫ〮나〮리라〮用요ᇰ〮ᄋᆞᆫ〮ᄡᅳᆯ〮씨〮라〮耳ᅀᅵᆼ〯ᄂᆞᆫ〮ᄯᆞᄅᆞ미〮라〮ᄒᆞ〮논ᄠᅳ〮디라〮
入ᅀᅵᆸ〮聲셔ᇰ은〮加강點뎜〯이〮同또ᇰ而ᅀᅵᆼ促쵹〮急그〮ᄒᆞ니라
入ᅀᅵᆸ〮聲셔ᇰ은〮點뎜〯더우〮믄〮ᄒᆞᆫ가지〮로ᄃᆡ〮ᄲᆞᄅᆞ니〮라〮
入ᅀᅵᆸ〮聲셔ᇰ은〮ᄲᆞᆯ리〮긋ᄃᆞᆮᄂᆞᆫ소리〮라〮促쵹〮急그〮은〮ᄲᆞᄅᆞᆯ씨〮라〮
凡뻠字ᄍᆞᆼ〮ㅣ必비ᇙ〮合ᅘᅡᆸ〮而ᅀᅵᆼ成쎠ᇰ音ᅙᅳᆷᄒᆞ〮ᄂᆞ니〮
凡뻠은〮믈읫ᄒᆞ〮논ᄠᅳ〮디라〮必비ᇙ〮ᄋᆞᆫ〮모로〮매〮ᄒᆞ〮논ᄠᅳ〮디라〮成쎠ᇰ은〮일〯씨〮라〮
初총聲셔ᇰ을〮合ᅘᅡᆸ〮用요ᇰ〮호ᇙ〮디면〮則즉〮並버ᇙ〮書셩ᄒᆞ라〮終쥬ᇰ聲셔ᇰ도〮同또ᇰᄒᆞ니〮라〮
右ᅌᅮᇢ〯는〮올〮ᄒᆞᆫ녀기〮라〮
合ᅘᅡᆸ〮ᄋᆞᆫ〮어울〮씨〮라〮同또ᇰᄋᆞᆫ〮ᄒᆞᆫ가지〮라〮ᄒᆞ〮논ᄠᅳ〮디라〮
喉ᅘᅮᇢ는〮모기〮라〮
國귁〮之징語ᅌᅥᆼ〯音ᅙᅳᆷ이〮
國귁〮ᄋᆞᆫ〮나라〮히라〮之징ᄂᆞᆫ〮입〮겨〮지라〮語ᅌᅥᆼ〯는말〯ᄊᆞ미라〮
左장〯加강一ᅙᅵᇙ〮點뎜〯ᄒᆞ면〮則즉〮去컹〮聲셔ᇰ이〮오〮
左장〯ᄂᆞᆫ〮왼〯녀기〮라〮加강ᄂᆞᆫ〮더을씨〮라〮一ᅙᅵᇙ〮ᄋᆞᆫ〮ᆞᆫᄒᆞ나히〮라〮去컹聲셔ᇰ은〮ᄆᆞᆺ〮노ᄑᆞᆫ〮소리〮라〮
復뿌ᇢ〮는〮다시〮ᄒᆞ〮논ᄠᅳ〮디라〮
故공〮ᄂᆞᆫ〮젼ᄎᆡ〮라〮愚ᅌᅮᆼ는〮어릴〮씨〮라〮有ᅌᅮᇢ〯는이실씨〮라〮所송〯ᄂᆞᆫ〮배〮라〮欲욕〮ᄋᆞᆫ〮ᄒᆞ고〮져〮ᄒᆞᆯ씨〮라〮言ᅌᅥᆫ은〮니를씨〮라〮
故공〮로〮愚ᅌᅮᆼ民민이〮有ᅌᅮᇢ〯所송〯欲욕〮言ᅌᅥᆫᄒᆞ〮야도〮
文문字ᄍᆞᆼ〮와〮로〮서르ᄉᆞᄆᆞᆺ디〮아니〮ᄒᆞᆯᄊᆡ〮
新신制졩〮二ᅀᅵᆼ〮十씹〮八바ᇙ〮字ᄍᆞᆼ〮ᄒᆞ〮노니〮
新신ᄋᆞᆫ〮새〮라〮制졩〮ᄂᆞᆫ〮ᄆᆡᇰᄀᆞ〮ᄅᆞ〮실씨〮라〮二ᅀᅵᆼ〮十씹〮八바ᇙ〮ᄋᆞᆫ〮스〮믈〮여들〮비라〮
欲욕〮使ᄉᆞᆼ〯人ᅀᅵᆫ人ᅀᅵᆫᄋᆞ〮로〮易잉〮習씹〮ᄒᆞ〮야〮便뼌於ᅙᅥᆼ日ᅀᅵᇙ〮用요ᇰ〮耳ᅀᅵᆼ〯니라〮
漢한〮音ᅙᅳᆷ齒칭〯聲셔ᇰ은〮有ᅌᅮᇢ〯齒칭〯頭뚜ᇢ正져ᇰ〮齒칭〯之징别벼ᇙ〮ᄒᆞ니〮
漢한〮音ᅙᅳᆷ은〮中듀ᇰ國귁〮소리〮라〮頭뚜ᇢ는〮머리〮라〮别벼ᇙ〮은〮ᄀᆞᆯᄒᆡᆯ〮씨〮라〮
無뭉則즉〮平버ᇙ聲셔ᇰ이〮오〮
無뭉는〮업〯슬씨〮라〮平버ᇙ聲셔ᇰ은〮ᄆᆞᆺ〮ᄂᆞᆺ가ᄫᆞᆫ〮소리〮라〮
牙ᅌᅡᆼ舌쎠ᇙ〮脣쓘喉ᅘᅮᇢ之징字ᄍᆞᆼ〮ᄂᆞᆫ〮通토ᇰ用요ᇰ〮於ᅙᅥᆼ漢한〮音ᅙᅳᆷᄒᆞ〮ᄂᆞ〮니라〮
牙ᅌᅡᆼᄂᆞᆫ〮어〯미라〮如ᅀᅧᆼ는〮ᄀᆞ〮ᄐᆞᆯ씨〮라〮初총發버ᇙ〮聲셔ᇰ은〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮라〮並버ᇙ〮書셩는〮ᄀᆞᆯᄫᅡ〮쓸〮씨〮라〮
異잉〮乎ᅘᅩᆼ中듀ᇰ國귁〮ᄒᆞ〮야〮
異잉〮ᄂᆞᆫ〮다ᄅᆞᆯ씨라乎ᅘᅩᆼᄂᆞᆫ〮아〯모〮그ᅌᅦᄒᆞ〮논겨〮체ᄡᅳ〮는字ᄍᆞᆼ〮ㅣ라〮中듀ᇰ國귁〮ᄋᆞᆫ〮
皇ᅘᅪᇰ帝뎽〮겨〯신나라〮히니〮우〮리〮나랏〮常쌰ᇰ談땀애〮江가ᇰ南남이〮라〮ᄒᆞ〮ᄂᆞ〮니라〮
終쥬ᇰ聲셔ᇰ은〮復뿌ᇢ〮用요ᇰ〮初총聲셔ᇰᄒᆞ〮ᄂᆞ〮니라〮
而ᅀᅵᆼ終쥬ᇰ不부ᇙ〮得득〮伸신其끵情쪄ᇰ者:쟝ㅣ多당矣ᅌᅴᆼ〯라〮
而ᅀᅵᆼᄂᆞᆫ〮입〮겨〮지라〮終쥬ᇰ은ᄆᆞᄎᆞ〮미라〮得득〮은〮시를〮씨〮라〮伸신ᄋᆞᆫ〮펼씨〮라〮其끵ᄂᆞᆫ〮제〯라〮情쪄ᇰ은〮ᄠᅳ〮디라〮者쟝〯ᄂᆞᆫ〮노〮미라〮多당ᄂᆞᆫ〮할씨〮라〮矣ᅌᅴᆼ〯ᄂᆞᆫ〮말〯ᄆᆞᆺᄂᆞᆫ입〮겨〮지라〮
脣쓘은〮입시우〮리라〮
與영〯文문字ᄍᆞᆼ〮로〮不부ᇙ〮相샤ᇰ流류ᇢ通토ᇰᄒᆞᆯᄊᆡ〮
與영〯는〮이〮와〮뎌〮와〮ᄒᆞ〮ᄂᆞᆫ겨〮체ᄡᅳ〮ᄂᆞᆫ字ᄍᆞᆼ〮ㅣ라〮文문은〮글〮와〮리라〮不부ᇙ〮은〮아니〮ᄒᆞ〮논ᄠᅳ〮디라〮相샤ᇰᄋᆞᆫ〮서르ᄒᆞ〮논ᄠᅳ〮디라〮流류ᇢ通토ᇰᄋᆞᆫ〮흘러〮ᄉᆞᄆᆞᄎᆞᆯ〮씨〮라〮
舌쎠ᇙ〮은〮혜〮라〮
製졩〮ᄂᆞᆫ〮글〮지ᅀᅳᆯ〮씨〮니〮御ᅌᅥᆼ〮製졩〮ᄂᆞᆫ〮님〯금〮지〯ᅀᅳ샨〮그〮리라〮訓훈〮은〮ᄀᆞᄅᆞ칠〮씨〮오〮民민ᄋᆞᆫ〮百ᄇᆡᆨ〮姓셔ᇰ〮이〮오〮音ᅙᅳᆷ은〮소리〮니〮訓훈〮民민正져ᇰ〮音ᅙᅳᆷ은〮百ᄇᆡᆨ〮姓셔ᇰ〮ᄀᆞᄅᆞ치〮시논〮正져ᇰ〮ᄒᆞᆫ소리〮라〮
訓훈〮民민正져ᇰ〮音ᅙᅳᆷ
連련은〮니ᅀᅳᆯ〮씨〮라〮下ᅘᅡᆼ〮ᄂᆞᆫ〮아래〮라〮則즉〮은〮아〯ᄆᆞ〮리ᄒᆞ면〮ᄒᆞ〮ᄂᆞᆫ겨〮체〮ᄡᅳ〮ᄂᆞᆫ字ᄍᆞᆼ〮ㅣ라爲ᅌᅱᆼᄂᆞᆫ〮ᄃᆞ욀씨〮라〮輕켜ᇰ은〮가ᄇᆡ〮야ᄫᆞᆯ〮씨〮라〮
附뿡〮는〮브틀〮씨〮라〮
點뎜〯이〮둘〯히면〮上쌰ᇰ〯聲셔ᇰ이〮오〮
點뎜〯이〮업〯스면〮平펴ᇰ聲셔ᇰ이〮오〮
齒ᄂᆞᆫ〮니〮라〮
ㅏᄂᆞᆫ〮覃땀ㅂ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅏᄂᆞᆫ〮覃땀ㅂ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅑᄂᆞᆫ〮穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅑᄂᆞᆫ〮穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅓᄂᆞᆫ〮業ᅌᅥᆸ〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅓᄂᆞᆫ〮業ᅌᅥᆸ〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅕᄂᆞᆫ〮彆벼ᇙ〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅕᄂᆞᆫ〮彆벼ᇙ〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅗᄂᆞᆫ〮洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅗᄂᆞᆫ〮洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅛᄂᆞᆫ〮欲욕〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅛᄂᆞᆫ〮欲욕〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅜᄂᆞᆫ〮君군ㄷ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅜᄂᆞᆫ〮君군ㄷ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅠᄂᆞᆫ〮戌슈ᇙ〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅠᄂᆞᆫ〮戌슈ᇙ〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅡᄂᆞᆫ〮卽즉〮字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅡᄂᆞᆫ〮卽즉〮字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅣㅏㅓㅑㅕ라〮附뿡〮書셩於ᅙᅥᆼ右ᅌᅮᇢ〯ᄒᆞ라〮.
ㅣᄂᆞᆫ〮侵침ㅂ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㅣᄂᆞᆫ〮侵침ㅂ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅣ와〮ㅏ와〮ㅓ와〮ㅑ와〮ㅕ와〮라〮와〮ᄒᆞᆫ녀긔〮브텨〮쓰〮라〮
ㆍㅡㅗㅜㅛㅠ라〮附뿡〮書셩初총聲셔ᇰ之징下ᅘᅡᆼ〯ᄒᆞ고〮
ㆍᄂᆞᆫ〮呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮가온〮ᄃᆡᆺ〮소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㆍᄂᆞᆫ〮如ᅀᅧᆼ呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮中듀ᇰ聲셔ᇰᄒᆞ니〮라〮
ㆍ와〮ㅗ와〮ㅜ와〮ㅛ와〮ㅠ와〮라〮처〮소리〮아래〮브텨〮쓰〮고〮
ㄱᄂᆞᆫ〮牙ᅌᅡᆼ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ君군ㄷ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ虯뀨ᇢㅸ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㄱᄂᆞᆫ〮엄〯쏘리〮니〮君군ㄷ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯᄫᅡ〮쓰〮면〮虯뀨ᇢㅸ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㄴᄂᆞᆫ〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ那낭ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㄴᄂᆞᆫ〮혀〮쏘리〮니〮那낭ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
나랏〮말〯ᄊᆞ미〮
내〮이〮ᄅᆞᆯ〮爲윙〮ᄒᆞ〮야〮어〯엿비〮너겨〮
ㄷᄂᆞᆫ〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ斗두ᇢㅸ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ覃땀ㅂ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㄷᄂᆞᆫ〮혀〮쏘리〮니〮斗두ᇢㅸ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯᄫᅡ〮쓰〮면〮覃땀ㅂ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㄹᄂᆞᆫ〮半반〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ閭령ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㄹᄂᆞᆫ〮半반〮혀〮쏘리〮니〮閭령ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅁᄂᆞᆫ〮脣쓘音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ彌밍ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅁᄂᆞᆫ〮입시울〮쏘리〮니〮彌밍ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
믈읫字ᄍᆞᆼ〮ㅣ모로〮매〮어우〮러ᅀᅡ〮소리〮이〯ᄂᆞ니〮
ᄆᆞᄎᆞᆷ〮내〯제ᄠᅳ〮들〮시러〮펴디〮몯〯ᄒᆞᇙ노〮미〮하니〮라〮
ㅂᄂᆞᆫ〮脣쓘音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ彆벼ᇙ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ歩뽕ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅂᄂᆞᆫ〮입시울〮쏘리〮니〮彆벼ᇙ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮歩뽕ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅅᄂᆞᆫ〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ戌슈ᇙ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ邪썅ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅅᄂᆞᆫ〮니〮쏘리〮니〮戌슈ᇙ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮邪썅ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
사〯ᄅᆞᆷ마〯다〮ᄒᆡ〯ᅇᅧ〮수〯ᄫᅵ〮니겨〮날〮로〮ᄡᅮ〮메〮便뼌安ᅙᅡᆫ킈〮ᄒᆞ고〮져〮ᄒᆞᇙᄯᆞᄅᆞ미〮니라〮
새〮로〮스〮믈〮여듧〮字ᄍᆞᆼ〮ᄅᆞᆯ〮ᄆᆡᇰᄀᆞ〮노니〮
솅〮宗조ᇰ御ᅌᅥᆼ〮製졩〮訓훈〮民민正져ᇰ〮音ᅙᅳᆷ
ㅿᄂᆞᆫ〮半반〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅿᄂᆞᆫ〮半반〮니〮쏘리〮니〮穰ᅀᅣᇰㄱ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅇᄂᆞᆫ〮喉ᅘᅮᇢ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ欲욕〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅇᄂᆞᆫ〮목소리〮니〮欲욕〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅇᄅᆞᆯ連련書셩脣쓘音ᅙᅳᆷ之징下ᅘᅡᆼ〯ᄒᆞ면則즉〮爲ᅌᅱᆼ脣쓘輕켜ᇰ音ᅙᅳᆷᄒᆞ〮ᄂᆞ〮니라〮
ㅇᄅᆞᆯ〮입시울〮쏘리〮아래〮니ᅀᅥ〮쓰〮면〮입시울〮가ᄇᆡ〮야ᄫᆞᆫ〮소리〮ᄃᆞ외ᄂᆞ니〮라〮
엄〯과〮혀〮와〮입시울〮와〮목소리〮옛〮字ᄍᆞᆼ〮ᄂᆞᆫ〮中듀ᇰ國귁〮소리〮예〮通토ᇰ히〮ᄡᅳ〮ᄂᆞ〮니라〮
왼〯녀긔〮ᄒᆞᆫ點뎜〯을〮더으면〮ᄆᆞᆺ〮노ᄑᆞᆫ〮소리〮오〮
이〮런젼ᄎᆞ〮로〮어린〮百ᄇᆡᆨ姓셔ᇰ〮이〮니르고〮져〮호ᇙ〮배〮이셔〮도〮
이〮소리〮ᄂᆞᆫ〮우〮리〮나라〮소리〮예셔〮두터ᄫᅳ니〮혓〮그〮티〮아랫〮니〮므유메〮다ᄔᆞ니〮라〮
이〮소리〮ᄂᆞᆫ〮우〮리〮나라〮소리〮예셔〮열ᄫᅳ〮니〮혓〮그〮티〮웃니〮머리〮예〮다ᄔᆞ니〮라〮
ㆁᄂᆞᆫ〮牙ᅌᅡᆼ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ業ᅌᅥᆸ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰ니〮라〮
ㆁᄂᆞᆫ〮엄〯쏘리〮니〮業ᅌᅥᆸ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅈᄂᆞᆫ〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ卽즉〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ慈ᄍᆞᆼㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅈᄂᆞᆫ〮니〮쏘리〮니〮卽즉〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮慈ᄍᆞᆼㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ᅎᅠᅔᅠᅏᅠᄼᅠᄽᅠ字ᄍᆞᆼ〮ᄂᆞᆫ〮用요ᇰ〮於ᅙᅥᆼ齒칭〯頭뚜ᇢᄒᆞ고〮
ᅎᅠᅔᅠᅏᅠᄼᅠᄽᅠ字ᄍᆞᆼ〮ᄂᆞᆫ〮齒칭〯頭뚜ᇢㅅ소리〮예〮ᄡᅳ〮고〮
ᅐᅠᅕᅠᅑᅠᄾᅠᄿᅠ字ᄍᆞᆼ〮ᄂᆞᆫ正져ᇰ〮齒칭〯ㅅ소리〮예〮ᄡᅳ〮ᄂᆞ니〮
ᅐᅠᅕᅠᅑᅠᄾᅠᄿᅠ字ᄍᆞᆼ〮ᄂᆞᆫ〮用요ᇰ〮於ᅙᅥᆼ正져ᇰ〮齒칭〯ᄒᆞ〮ᄂᆞ니〮
ㅊᄂᆞᆫ〮齒칭〯音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ侵침ㅂ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅊᄂᆞᆫ〮니〮쏘리〮니〮侵침ㅂ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
처〮소리〮ᄅᆞᆯ〮어울〮워〮ᄡᅮᇙ〮디〮면〮ᄀᆞᆯᄫᅡ〮쓰〮라〮乃냉〯終쥬ᇰㄱ소리〮도〮ᄒᆞᆫ가지〮라〮
ㅋᄂᆞᆫ〮牙ᅌᅡᆼ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ快쾡〮ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰ니〮라〮
ㅋᄂᆞᆫ〮엄〯쏘리〮니〮快쾡〮ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅌᄂᆞᆫ〮舌쎠ᇙ〮音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅌᄂᆞᆫ〮혀〮쏘리〮니〮呑ᄐᆞᆫㄷ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅍᄂᆞᆫ〮脣쓘音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ漂표ᇢㅸ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅍᄂᆞᆫ〮입시울〮쏘리〮니〮漂표ᇢㅸ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㅎᄂᆞᆫ〮喉ᅘᅮᇢ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ虛헝ㆆ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮並버ᇙ〮書셩ᄒᆞ면〮如ᅀᅧᆼ洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㅎᄂᆞᆫ〮목소리〮니〮虛헝ㆆ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ니〮ᄀᆞᆯ〮ᄫᅡ〮쓰〮면〮洪ᅘᅩᇰㄱ字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
ㆆᄂᆞᆫ〮喉ᅘᅮᇢ音ᅙᅳᆷ이〮니〮如ᅀᅧᆼ挹ᅙᅳᆸ〮字ᄍᆞᆼ〮初총發버ᇙ〮聲셔ᇰᄒᆞ니〮라〮
ㆆᄂᆞᆫ〮목소리〮니〮挹ᅙᅳᆸ〮字ᄍᆞᆼ〮처〮ᅀᅥᆷ펴〮아〮나〮ᄂᆞᆫ소리〮ᄀᆞ〮ᄐᆞ〮니라〮
"""
class HunminjeongumTest(unittest.TestCase):
def test_humminjeongeum(self):
sort_list = []
for line in TEXT.splitlines():
sort_list.append((encoder.encode(line), line))
sort_text = "\n".join((line for _, line in sorted(sort_list))) + "\n"
self.assertTrue(sort_text == TEXT_SORTED)
| 43.624113
| 176
| 0.735571
| 5,705
| 12,302
| 2.079053
| 0.092025
| 0.030689
| 0.045022
| 0.028328
| 0.977152
| 0.977152
| 0.97496
| 0.967709
| 0.967709
| 0.961555
| 0
| 0.000084
| 0.029264
| 12,302
| 281
| 177
| 43.779359
| 0.756825
| 0.001707
| 0
| 0.96
| 0
| 0.385455
| 0.96604
| 0.907892
| 0
| 0
| 0
| 0
| 0.003636
| 1
| 0.003636
| false
| 0
| 0.007273
| 0
| 0.014545
| 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
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
fa71ff14158ea0a926d4b833646d30a1ed335bf2
| 7,791
|
py
|
Python
|
migration/migrator/migrations/course/20210929172618_remove_gradeable_data_overall_comment.py
|
tlasich/Submitty
|
cf9b6ceda15ec0a661e2ca81ea7864790094c64a
|
[
"BSD-3-Clause"
] | 1
|
2019-05-07T03:27:08.000Z
|
2019-05-07T03:27:08.000Z
|
migration/migrator/migrations/course/20210929172618_remove_gradeable_data_overall_comment.py
|
KaelanWillauer/Submitty
|
cf9b6ceda15ec0a661e2ca81ea7864790094c64a
|
[
"BSD-3-Clause"
] | 391
|
2019-09-29T21:10:15.000Z
|
2022-03-31T10:27:29.000Z
|
migration/migrator/migrations/course/20210929172618_remove_gradeable_data_overall_comment.py
|
KaelanWillauer/Submitty
|
cf9b6ceda15ec0a661e2ca81ea7864790094c64a
|
[
"BSD-3-Clause"
] | 17
|
2019-09-23T16:14:16.000Z
|
2022-02-22T19:01:38.000Z
|
"""Migration for a given Submitty course database."""
def up(config, database, semester, course):
"""
Run up migration.
:param config: Object holding configuration details about Submitty
:type config: migrator.config.Config
:param database: Object for interacting with given database for environment
:type database: migrator.db.Database
:param semester: Semester of the course being migrated
:type semester: str
:param course: Code of course being migrated
:type course: str
"""
result = database.execute("SELECT 1 FROM gradeable_data WHERE gd_overall_comment <> '' LIMIT 1").first()
if result is not None:
result = database.execute("SELECT 1 FROM users WHERE user_group=1 LIMIT 1").first()
if result is None:
raise Exception("ERROR: semester \'{}\' course \'{}\' has no instructors, but needs at least one to move overall comment data.".format(semester, course))
database.execute("INSERT INTO gradeable_data_overall_comment (g_id, goc_team_id, goc_grader_id, goc_overall_comment) SELECT g_id, gd_team_id, (SELECT user_id FROM users WHERE user_group=1 LIMIT 1), gd_overall_comment FROM gradeable_data WHERE gd_overall_comment <> '' AND gd_team_id IS NOT NULL ON CONFLICT ON CONSTRAINT gradeable_data_overall_comment_team_unique DO UPDATE SET goc_overall_comment = gradeable_data_overall_comment.goc_overall_comment || E'\nPrevious Overall Comment: ' || excluded.goc_overall_comment")
database.execute("INSERT INTO gradeable_data_overall_comment (g_id, goc_user_id, goc_grader_id, goc_overall_comment) SELECT g_id, gd_user_id, (SELECT user_id FROM users WHERE user_group=1 LIMIT 1), gd_overall_comment FROM gradeable_data WHERE gd_overall_comment <> '' AND gd_user_id IS NOT NULL ON CONFLICT ON CONSTRAINT gradeable_data_overall_comment_user_unique DO UPDATE SET goc_overall_comment = gradeable_data_overall_comment.goc_overall_comment || E'\nPrevious Overall Comment: ' || excluded.goc_overall_comment")
database.execute("ALTER TABLE gradeable_data DROP COLUMN IF EXISTS gd_overall_comment")
database.execute("""CREATE OR REPLACE FUNCTION public.csv_to_numeric_gradeable(vcode text[], gradeable_id text, grader_id text) RETURNS boolean
LANGUAGE plpgsql
AS $$
DECLARE
-- Size of first array after splitting
size INTEGER;
-- Array of individual line after splitting
line TEXT[];
-- Variable to store each line in the array
i TEXT;
-- Array of gc_ids for this gradeable
gcids INTEGER[];
-- gradeable_data id for this gradeable for this student
gdid INTEGER;
-- Array counter
j INTEGER;
-- Is this gradeable component text?
istext BOOLEAN[];
--Score to be inserted
score NUMERIC;
BEGIN
gcids := ARRAY(SELECT gc_id FROM gradeable_component WHERE g_id = gradeable_id);
istext := ARRAY(SELECT gc_is_text FROM gradeable_component WHERE g_id = gradeable_id);
-- Get the number of gradeable components for this gradeable. Will be used to test
-- for uniform sized arrays
size := array_length(gcids, 1);
FOREACH i IN ARRAY vcode
LOOP
-- Split the current line
line := string_to_array(i, ',');
-- Check for uniform size
IF array_length(line, 1) <> size + 1 THEN
RAISE EXCEPTION 'INVALID SIZE: Arrays are jagged.';
END IF;
-- Remove any existing record for this student for this gradeable
DELETE FROM gradeable_data WHERE gd_user_id = line[1] AND g_id = gradeable_id;
INSERT INTO gradeable_data(g_id, gd_user_id) VALUES (gradeable_id, line[1]);
SELECT gd_id INTO gdid FROM gradeable_data WHERE g_id = gradeable_id AND gd_user_id = line[1];
FOR j IN 1..size
LOOP
IF istext[j] THEN
--COME BACK AND FIX: need to put in gcd_grade_time...double check to see that CSV upload still works for numeric/text
INSERT INTO gradeable_component_data(gc_id, gd_id, gcd_component_comment, gcd_grader_id, gcd_graded_version, gcd_grade_time) VALUES (gcids[j], gdid, line[j+1], grader_id, NULL);
ELSE
score := CAST(line[j+1] AS NUMERIC);
INSERT INTO gradeable_component_data(gc_id, gd_id, gcd_score, gcd_grader_id, gcd_graded_version, gcd_grade_time) VALUES (gcids[j], gdid, score, grader_id, NULL);
END IF;
END LOOP;
END LOOP;
RETURN TRUE ;
END;
$$;""")
def down(config, database, semester, course):
"""
Run down migration (rollback).
:param config: Object holding configuration details about Submitty
:type config: migrator.config.Config
:param database: Object for interacting with given database for environment
:type database: migrator.db.Database
:param semester: Semester of the course being migrated
:type semester: str
:param course: Code of course being migrated
:type course: str
"""
database.execute("ALTER TABLE gradeable_data ADD COLUMN IF NOT EXISTS gd_overall_comment character varying NOT NULL DEFAULT ''")
database.execute("""CREATE OR REPLACE FUNCTION public.csv_to_numeric_gradeable(vcode text[], gradeable_id text, grader_id text) RETURNS boolean
LANGUAGE plpgsql
AS $$
DECLARE
-- Size of first array after splitting
size INTEGER;
-- Array of individual line after splitting
line TEXT[];
-- Variable to store each line in the array
i TEXT;
-- Array of gc_ids for this gradeable
gcids INTEGER[];
-- gradeable_data id for this gradeable for this student
gdid INTEGER;
-- Array counter
j INTEGER;
-- Is this gradeable component text?
istext BOOLEAN[];
--Score to be inserted
score NUMERIC;
BEGIN
gcids := ARRAY(SELECT gc_id FROM gradeable_component WHERE g_id = gradeable_id);
istext := ARRAY(SELECT gc_is_text FROM gradeable_component WHERE g_id = gradeable_id);
-- Get the number of gradeable components for this gradeable. Will be used to test
-- for uniform sized arrays
size := array_length(gcids, 1);
FOREACH i IN ARRAY vcode
LOOP
-- Split the current line
line := string_to_array(i, ',');
-- Check for uniform size
IF array_length(line, 1) <> size + 1 THEN
RAISE EXCEPTION 'INVALID SIZE: Arrays are jagged.';
END IF;
-- Remove any existing record for this student for this gradeable
DELETE FROM gradeable_data WHERE gd_user_id = line[1] AND g_id = gradeable_id;
INSERT INTO gradeable_data(g_id, gd_user_id, gd_overall_comment) VALUES (gradeable_id, line[1], '');
SELECT gd_id INTO gdid FROM gradeable_data WHERE g_id = gradeable_id AND gd_user_id = line[1];
FOR j IN 1..size
LOOP
IF istext[j] THEN
--COME BACK AND FIX: need to put in gcd_grade_time...double check to see that CSV upload still works for numeric/text
INSERT INTO gradeable_component_data(gc_id, gd_id, gcd_component_comment, gcd_grader_id, gcd_graded_version, gcd_grade_time) VALUES (gcids[j], gdid, line[j+1], grader_id, NULL);
ELSE
score := CAST(line[j+1] AS NUMERIC);
INSERT INTO gradeable_component_data(gc_id, gd_id, gcd_score, gcd_grader_id, gcd_graded_version, gcd_grade_time) VALUES (gcids[j], gdid, score, grader_id, NULL);
END IF;
END LOOP;
END LOOP;
RETURN TRUE ;
END;
$$;""")
| 49.624204
| 527
| 0.671287
| 1,070
| 7,791
| 4.691589
| 0.170093
| 0.069721
| 0.025498
| 0.022311
| 0.930279
| 0.917131
| 0.886653
| 0.879084
| 0.873108
| 0.873108
| 0
| 0.004662
| 0.256706
| 7,791
| 156
| 528
| 49.942308
| 0.8622
| 0.103709
| 0
| 0.886957
| 0
| 0.078261
| 0.930844
| 0.085428
| 0
| 0
| 0
| 0
| 0
| 1
| 0.017391
| false
| 0
| 0
| 0
| 0.017391
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
d75e7689fa40e66350bb57c0fd7dd4718428afb9
| 123
|
py
|
Python
|
test_workspaces/generated_proto/main.py
|
jesseschalken/rules_proto_grpc
|
2e8be8e27cc82203794f14dbdcf37189b02ab722
|
[
"Apache-2.0"
] | null | null | null |
test_workspaces/generated_proto/main.py
|
jesseschalken/rules_proto_grpc
|
2e8be8e27cc82203794f14dbdcf37189b02ab722
|
[
"Apache-2.0"
] | null | null | null |
test_workspaces/generated_proto/main.py
|
jesseschalken/rules_proto_grpc
|
2e8be8e27cc82203794f14dbdcf37189b02ab722
|
[
"Apache-2.0"
] | null | null | null |
# Attempt to import proto files, this should succeed
import generated_pb2
import generated_elsewhere_pb2
import static_pb2
| 24.6
| 52
| 0.861789
| 18
| 123
| 5.666667
| 0.666667
| 0.294118
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027778
| 0.121951
| 123
| 4
| 53
| 30.75
| 0.916667
| 0.406504
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 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
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
d76f1b76d1bc2c44b30ee94207b3a31ef842e63a
| 2,597
|
py
|
Python
|
holoviews/tests/plotting/plotly/testareaplot.py
|
narutsoo/holoviews
|
a93281b3b346e5827b740d85886decd22706e7c7
|
[
"BSD-3-Clause"
] | null | null | null |
holoviews/tests/plotting/plotly/testareaplot.py
|
narutsoo/holoviews
|
a93281b3b346e5827b740d85886decd22706e7c7
|
[
"BSD-3-Clause"
] | null | null | null |
holoviews/tests/plotting/plotly/testareaplot.py
|
narutsoo/holoviews
|
a93281b3b346e5827b740d85886decd22706e7c7
|
[
"BSD-3-Clause"
] | null | null | null |
import numpy as np
from holoviews.element import Area
from .testplot import TestPlotlyPlot
class TestAreaPlot(TestPlotlyPlot):
def test_area_to_zero_y(self):
curve = Area([1, 2, 3])
state = self._get_plot_state(curve)
self.assertEqual(state['data'][0]['x'], np.array([0, 1, 2]))
self.assertEqual(state['data'][0]['y'], np.array([1, 2, 3]))
self.assertEqual(state['data'][0]['mode'], 'lines')
self.assertEqual(state['data'][0]['fill'], 'tozeroy')
self.assertEqual(state['layout']['yaxis']['range'], [0, 3])
def test_area_to_zero_x(self):
curve = Area([1, 2, 3]).options(invert_axes=True)
state = self._get_plot_state(curve)
self.assertEqual(state['data'][0]['x'], np.array([1, 2, 3]))
self.assertEqual(state['data'][0]['y'], np.array([0, 1, 2]))
self.assertEqual(state['data'][0]['mode'], 'lines')
self.assertEqual(state['data'][0]['fill'], 'tozerox')
self.assertEqual(state['layout']['xaxis']['range'], [0, 3])
self.assertEqual(state['layout']['yaxis']['range'], [0, 2])
self.assertEqual(state['layout']['xaxis']['title']['text'], 'y')
self.assertEqual(state['layout']['yaxis']['title']['text'], 'x')
def test_area_fill_between_ys(self):
area = Area([(0, 1, 0.5), (1, 2, 1), (2, 3, 2.25)], vdims=['y', 'y2'])
state = self._get_plot_state(area)
self.assertEqual(state['data'][0]['y'], np.array([0.5, 1, 2.25]))
self.assertEqual(state['data'][0]['mode'], 'lines')
self.assertEqual(state['data'][0].get('fill', None), None)
self.assertEqual(state['data'][1]['y'], np.array([1, 2, 3]))
self.assertEqual(state['data'][1]['mode'], 'lines')
self.assertEqual(state['data'][1]['fill'], 'tonexty')
self.assertEqual(state['layout']['yaxis']['range'], [0.5, 3])
def test_area_fill_between_xs(self):
area = Area([(0, 1, 0.5), (1, 2, 1), (2, 3, 2.25)], vdims=['y', 'y2']).options(invert_axes=True)
state = self._get_plot_state(area)
self.assertEqual(state['data'][0]['x'], np.array([0.5, 1, 2.25]))
self.assertEqual(state['data'][0]['mode'], 'lines')
self.assertEqual(state['data'][0].get('fill', None), None)
self.assertEqual(state['data'][1]['x'], np.array([1, 2, 3]))
self.assertEqual(state['data'][1]['mode'], 'lines')
self.assertEqual(state['data'][1]['fill'], 'tonextx')
self.assertEqual(state['layout']['xaxis']['range'], [0.5, 3])
self.assertEqual(state['layout']['yaxis']['range'], [0, 2])
| 49
| 104
| 0.576049
| 364
| 2,597
| 4.027473
| 0.151099
| 0.286494
| 0.381992
| 0.327422
| 0.886767
| 0.791269
| 0.769441
| 0.668486
| 0.668486
| 0.584584
| 0
| 0.044965
| 0.177898
| 2,597
| 52
| 105
| 49.942308
| 0.641686
| 0
| 0
| 0.318182
| 0
| 0
| 0.13015
| 0
| 0
| 0
| 0
| 0
| 0.636364
| 1
| 0.090909
| false
| 0
| 0.068182
| 0
| 0.181818
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 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
| 7
|
ad5de3268f89154a45b4351ca9cbfa52d4206d32
| 1,897
|
py
|
Python
|
scripts/python/preprocessing/serialization/routines/download.py
|
AaronBlare/dnam
|
4d97c879cb24447eee0852eaf48fc5b3ef8e159b
|
[
"MIT"
] | null | null | null |
scripts/python/preprocessing/serialization/routines/download.py
|
AaronBlare/dnam
|
4d97c879cb24447eee0852eaf48fc5b3ef8e159b
|
[
"MIT"
] | null | null | null |
scripts/python/preprocessing/serialization/routines/download.py
|
AaronBlare/dnam
|
4d97c879cb24447eee0852eaf48fc5b3ef8e159b
|
[
"MIT"
] | null | null | null |
import pandas as pd
import GEOparse
from tqdm import tqdm
def download_betas_and_pvals_from_gsms(gsms, path):
for gsm_id, gsm in tqdm(enumerate(gsms)):
while True:
try:
gsm_data = GEOparse.get_GEO(geo=gsm, destdir= f"{path}/gsms", include_data=True, how="full", silent=True)
except ValueError:
continue
except ConnectionError:
continue
except IOError:
continue
break
gsm_data.table.set_index('ID_REF', inplace=True)
if gsm_id == 0:
betas = pd.DataFrame(0, index=gsm_data.table.index, columns=gsms)
pvals = pd.DataFrame(0, index=gsm_data.table.index, columns=gsms)
betas[gsm] = gsm_data.table.iloc[:, 0]
pvals[gsm] = gsm_data.table.iloc[:, 1]
betas = betas.T
betas.index.name = "subject_id"
pvals = pvals.T
pvals.index.name = "subject_id"
print(f"Number of NaNs in betas: {betas.isna().values.sum()}")
print(f"Number of NaNs in pvals: {pvals.isna().values.sum()}")
return betas, pvals
def download_betas_from_gsms(gsms, path):
for gsm_id, gsm in tqdm(enumerate(gsms)):
while True:
try:
gsm_data = GEOparse.get_GEO(geo=gsm, destdir= f"{path}/gsms", include_data=True, how="full", silent=True)
except ValueError:
continue
except ConnectionError:
continue
except IOError:
continue
break
gsm_data.table.set_index('ID_REF', inplace=True)
if gsm_id == 0:
betas = pd.DataFrame(0, index=gsm_data.table.index, columns=gsms)
betas[gsm] = gsm_data.table.iloc[:, 0]
betas = betas.T
betas.index.name = "subject_id"
print(f"Number of NaNs in betas: {betas.isna().values.sum()}")
return betas
| 31.098361
| 121
| 0.588297
| 246
| 1,897
| 4.402439
| 0.239837
| 0.064635
| 0.088643
| 0.047091
| 0.879963
| 0.830102
| 0.811634
| 0.811634
| 0.765466
| 0.765466
| 0
| 0.00602
| 0.29942
| 1,897
| 61
| 122
| 31.098361
| 0.808879
| 0
| 0
| 0.75
| 0
| 0
| 0.120126
| 0.042677
| 0
| 0
| 0
| 0
| 0
| 1
| 0.041667
| false
| 0
| 0.0625
| 0
| 0.145833
| 0.0625
| 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
|
d10b05aef47ab507e5becda350aa531800ee05e2
| 140
|
py
|
Python
|
MAC_changer.py
|
mandres2/MAC_Changer
|
a2a418ce377ca8815b4eb4d3adcfb452822a0e40
|
[
"Apache-2.0"
] | null | null | null |
MAC_changer.py
|
mandres2/MAC_Changer
|
a2a418ce377ca8815b4eb4d3adcfb452822a0e40
|
[
"Apache-2.0"
] | null | null | null |
MAC_changer.py
|
mandres2/MAC_Changer
|
a2a418ce377ca8815b4eb4d3adcfb452822a0e40
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
import subprocess
# For Windows OS:
# subprocess.run("ifconfig", shell=True)
subprocess.run("ifconfig", shell=True)
| 17.5
| 40
| 0.735714
| 19
| 140
| 5.421053
| 0.684211
| 0.252427
| 0.407767
| 0.504854
| 0.582524
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107143
| 140
| 8
| 41
| 17.5
| 0.824
| 0.535714
| 0
| 0
| 0
| 0
| 0.126984
| 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
|
d149f2d145daa262096d2a3826cf787441fa276b
| 1,407
|
py
|
Python
|
euler8.py
|
nixin72/Euler-Project
|
16ef62cb95deeb94c0289e67a6a9c90da2fa38fe
|
[
"MIT"
] | 1
|
2022-03-10T15:08:32.000Z
|
2022-03-10T15:08:32.000Z
|
euler8.py
|
nixin72/Euler-Project
|
16ef62cb95deeb94c0289e67a6a9c90da2fa38fe
|
[
"MIT"
] | null | null | null |
euler8.py
|
nixin72/Euler-Project
|
16ef62cb95deeb94c0289e67a6a9c90da2fa38fe
|
[
"MIT"
] | null | null | null |
#!/usr/bin/python3.4
number = "7316717653133062491922511967442657474235534919493496983520312774506326239578318016984801869478851843858615607891129494954595017379583319528532088055111254069874715852386305071569329096329522744304355766896648950445244523161731856403098711121722383113622298934233803081353362766142828064444866452387493035890729629049156044077239071381051585930796086670172427121883998797908792274921901699720888093776657273330010533678812202354218097512545405947522435258490771167055601360483958644670632441572215539753697817977846174064955149290862569321978468622482839722413756570560574902614079729686524145351004748216637048440319989000889524345065854122758866688116427171479924442928230863465674813919123162824586178664583591245665294765456828489128831426076900422421902267105562632111110937054421750694165896040807198403850962455444362981230987879927244284909188845801561660979191338754992005240636899125607176060588611646710940507754100225698315520005593572972571636269561882670428252483600823257530420752963450"
lProd = 0
finalNums = []
sIndex = 0
for x, q in enumerate(number):
if x < len(number)-13:
prod = 1
for k in range(0,13):
prod = prod * int(number[x:][k])
#print("index: " + str(x) + " current: " + str(q) + " product: " + str(prod))
if prod > lProd:
lProd = prod
finalNums = number[x:x+13]
sIndex = x
print(lProd)
print(finalNums)
print(sIndex)
| 52.111111
| 1,011
| 0.878465
| 64
| 1,407
| 19.3125
| 0.4375
| 0.009709
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.77193
| 0.06823
| 1,407
| 26
| 1,012
| 54.115385
| 0.170862
| 0.06823
| 0
| 0
| 0
| 0
| 0.766284
| 0.766284
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.1875
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
d1585eadf5c13eb0d048a19f7994efc51a43bd78
| 118
|
py
|
Python
|
config.py
|
c0dejump/notForbidden
|
4b2924a7254826d02eec2f56a23c02e1c23a10d6
|
[
"MIT"
] | 2
|
2021-11-03T12:57:50.000Z
|
2022-03-23T19:56:02.000Z
|
config.py
|
c0dejump/notForbidden
|
4b2924a7254826d02eec2f56a23c02e1c23a10d6
|
[
"MIT"
] | null | null | null |
config.py
|
c0dejump/notForbidden
|
4b2924a7254826d02eec2f56a23c02e1c23a10d6
|
[
"MIT"
] | null | null | null |
# coding: utf-8
INFO = "\033[34m[i] \033[0m"
LESS = "\033[33m[-] \033[0m"
BYP = "\033[32m\u251c BYPASSED \033[0m"
| 23.6
| 39
| 0.576271
| 21
| 118
| 3.238095
| 0.666667
| 0.220588
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.316327
| 0.169492
| 118
| 5
| 39
| 23.6
| 0.377551
| 0.110169
| 0
| 0
| 0
| 0
| 0.69
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.333333
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
66f84743ac5c090f112f8522dd4bb77aa0baf930
| 14,642
|
py
|
Python
|
tests/test_services/test_set_488.py
|
ucloud/ucloud-sdk-python2
|
90fb43198df73a78d64bbd98675dc7b302856057
|
[
"Apache-2.0"
] | 19
|
2019-05-15T13:41:58.000Z
|
2019-11-13T09:09:37.000Z
|
tests/test_services/test_set_488.py
|
ucloud/ucloud-sdk-python2
|
90fb43198df73a78d64bbd98675dc7b302856057
|
[
"Apache-2.0"
] | 9
|
2019-07-24T08:31:33.000Z
|
2020-09-22T04:01:46.000Z
|
tests/test_services/test_set_488.py
|
ucloud/ucloud-sdk-python2
|
90fb43198df73a78d64bbd98675dc7b302856057
|
[
"Apache-2.0"
] | 3
|
2019-06-18T00:22:07.000Z
|
2020-04-24T02:28:06.000Z
|
# -*- coding: utf-8 -*-
""" Code is generated by ucloud-model, DO NOT EDIT IT. """
import pytest
import logging
from ucloud.core import exc
from ucloud.testing import env, funcs, op, utest
logger = logging.getLogger(__name__)
scenario = utest.Scenario(488)
@pytest.mark.skipif(env.is_ut(), reason=env.get_skip_reason())
def test_set_488(client, variables):
scenario.initial(variables)
scenario.variables["Region"] = "cn-bj2"
scenario.variables["Zone"] = "cn-bj2-02"
scenario.variables["DBTypeId"] = "percona-5.6"
scenario.variables["InstanceMode"] = "HA"
scenario.variables["InstanceType"] = "Normal"
scenario.variables["Port"] = 3306
scenario.variables["MemoryLimit"] = 1000
scenario.variables["DiskSpace"] = 20
scenario.variables["DBName"] = "auto_habz_"
scenario.variables["UseSSD"] = False
scenario.run(client)
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="DescribeUDBInstance",
)
def describe_udb_instance_00(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
"ClassType": "sql",
}
try:
resp = client.udb().describe_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=1,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="DescribeUDBType",
)
def describe_udb_type_01(client, variables):
d = {"Zone": variables.get("Zone"), "Region": variables.get("Region")}
try:
resp = client.udb().describe_udb_type(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=2,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="DescribeUDBParamGroup",
)
def describe_udb_param_group_02(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
}
try:
resp = client.udb().describe_udb_param_group(d)
except exc.RetCodeException as e:
resp = e.json()
variables["DataSet_paramGroup"] = utest.value_at_path(resp, "DataSet")
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=1,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="DescribeUDBInstancePrice",
)
def describe_udb_instance_price_03(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"MemoryLimit": variables.get("MemoryLimit"),
"DiskSpace": variables.get("DiskSpace"),
"DBTypeId": variables.get("DBTypeId"),
"Count": 1,
}
try:
resp = client.udb().describe_udb_instance_price(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=1,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="CheckUDBInstanceAllowance",
)
def check_udb_instance_allowance_04(client, variables):
d = {
"Zone": variables.get("Zone"),
"UseSSD": variables.get("UseSSD"),
"Region": variables.get("Region"),
"MemoryLimit": variables.get("MemoryLimit"),
"DiskSpace": variables.get("DiskSpace"),
"Count": 1,
"ClassType": "SQL",
}
try:
resp = client.invoke("CheckUDBInstanceAllowance", d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=3,
retry_interval=1,
startup_delay=1,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="CreateUDBInstance",
)
def create_udb_instance_05(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Quantity": 0,
"Port": variables.get("Port"),
"ParamGroupId": funcs.search_value(
variables.get("DataSet_paramGroup"),
"DBTypeId",
variables.get("DBTypeId"),
"GroupId",
),
"Name": funcs.concat(
variables.get("DBName"), variables.get("DBTypeId")
),
"MemoryLimit": variables.get("MemoryLimit"),
"InstanceType": variables.get("InstanceType"),
"InstanceMode": variables.get("InstanceMode"),
"DiskSpace": variables.get("DiskSpace"),
"DBTypeId": variables.get("DBTypeId"),
"ChargeType": "Month",
"AdminPassword": "guanliyuanmima",
}
try:
resp = client.udb().create_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
variables["DBId"] = utest.value_at_path(resp, "DBId")
return resp
@scenario.step(
max_retries=60,
retry_interval=3,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
(
"str_eq",
"DataSet.0.Name",
funcs.concat(variables.get("DBName"), variables.get("DBTypeId")),
),
("str_eq", "DataSet.0.DBTypeId", variables.get("DBTypeId")),
],
action="DescribeUDBInstance",
)
def describe_udb_instance_06(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
"DBId": variables.get("DBId"),
"ClassType": "sql",
}
try:
resp = client.udb().describe_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=50,
retry_interval=10,
startup_delay=30,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
("str_eq", "State", "Running"),
],
action="DescribeUDBInstanceState",
)
def describe_udb_instance_state_07(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().describe_udb_instance_state(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
("str_eq", "Action", "DescribeUDBInstancePhpMyAdminURLResponse"),
("ne", "PMAPath", ""),
],
action="DescribeUDBInstancePhpMyAdminURL",
)
def describe_udb_instance_php_my_admin_url_08(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"DBId": variables.get("DBId"),
}
try:
resp = client.invoke("DescribeUDBInstancePhpMyAdminURL", d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=10,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="ModifyUDBInstanceName",
)
def modify_udb_instance_name_09(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Name": funcs.concat("rename_", variables.get("DBTypeId")),
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().modify_udb_instance_name(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=20,
retry_interval=3,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
(
"str_eq",
"DataSet.0.Name",
funcs.concat("rename_", variables.get("DBTypeId")),
),
("str_eq", "DataSet.0.DBTypeId", variables.get("DBTypeId")),
],
action="DescribeUDBInstance",
)
def describe_udb_instance_10(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
"DBId": variables.get("DBId"),
"ClassType": "sql",
}
try:
resp = client.udb().describe_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=1,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="ModifyUDBInstancePassword",
)
def modify_udb_instance_password_11(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Password": "Guanliyuanmima",
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().modify_udb_instance_password(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=3,
retry_interval=1,
startup_delay=2,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="RestartUDBInstance",
)
def restart_udb_instance_12(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().restart_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=100,
retry_interval=3,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
("str_eq", "DataSet.0.DBTypeId", variables.get("DBTypeId")),
("str_eq", "DataSet.0.State", "Running"),
],
action="DescribeUDBInstance",
)
def describe_udb_instance_13(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
"DBId": variables.get("DBId"),
"ClassType": "sql",
}
try:
resp = client.udb().describe_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=3,
retry_interval=1,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="StopUDBInstance",
)
def stop_udb_instance_14(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().stop_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=100,
retry_interval=3,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
("str_eq", "DataSet.0.DBTypeId", variables.get("DBTypeId")),
("str_eq", "DataSet.0.State", "Shutoff"),
],
action="DescribeUDBInstance",
)
def describe_udb_instance_15(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
"DBId": variables.get("DBId"),
"ClassType": "sql",
}
try:
resp = client.udb().describe_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=3,
retry_interval=1,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="StartUDBInstance",
)
def start_udb_instance_16(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().start_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=100,
retry_interval=3,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
("str_eq", "DataSet.0.DBTypeId", variables.get("DBTypeId")),
("str_eq", "DataSet.0.State", "Running"),
],
action="DescribeUDBInstance",
)
def describe_udb_instance_17(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
"DBId": variables.get("DBId"),
"ClassType": "sql",
}
try:
resp = client.udb().describe_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=3,
retry_interval=1,
startup_delay=10,
fast_fail=False,
validators=lambda variables: [("str_eq", "RetCode", 0)],
action="StopUDBInstance",
)
def stop_udb_instance_18(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().stop_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=100,
retry_interval=3,
startup_delay=0,
fast_fail=False,
validators=lambda variables: [
("str_eq", "RetCode", 0),
("str_eq", "DataSet.0.DBTypeId", variables.get("DBTypeId")),
("str_eq", "DataSet.0.State", "Shutoff"),
],
action="DescribeUDBInstance",
)
def describe_udb_instance_19(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"Offset": 0,
"Limit": 100,
"DBId": variables.get("DBId"),
"ClassType": "sql",
}
try:
resp = client.udb().describe_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
@scenario.step(
max_retries=0,
retry_interval=0,
startup_delay=10,
fast_fail=False,
action="DeleteUDBInstance",
)
def delete_udb_instance_20(client, variables):
d = {
"Zone": variables.get("Zone"),
"Region": variables.get("Region"),
"DBId": variables.get("DBId"),
}
try:
resp = client.udb().delete_udb_instance(d)
except exc.RetCodeException as e:
resp = e.json()
return resp
| 26.573503
| 77
| 0.603128
| 1,628
| 14,642
| 5.268428
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| 0.740469
| 0.732191
| 0
| 0.019045
| 0.243341
| 14,642
| 550
| 78
| 26.621818
| 0.755122
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| 0.168807
| 0.018474
| 0
| 0
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| 0
| 1
| 0.043825
| false
| 0.00996
| 0.007968
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| 0.093626
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| null | 0
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|
0
| 7
|
0f1242f93aa159d519b7bb9c8ab3e4dc2c010b52
| 19,073
|
py
|
Python
|
LUPI_oneclass_methods.py
|
Chandan-IITI/AEKOCPlus_or_AAKELMPlus_or_AALSSVMPlus
|
4b7aae7e85cbcc5913f5372a98b6835e0d086b3c
|
[
"MIT"
] | null | null | null |
LUPI_oneclass_methods.py
|
Chandan-IITI/AEKOCPlus_or_AAKELMPlus_or_AALSSVMPlus
|
4b7aae7e85cbcc5913f5372a98b6835e0d086b3c
|
[
"MIT"
] | null | null | null |
LUPI_oneclass_methods.py
|
Chandan-IITI/AEKOCPlus_or_AAKELMPlus_or_AALSSVMPlus
|
4b7aae7e85cbcc5913f5372a98b6835e0d086b3c
|
[
"MIT"
] | null | null | null |
# Author: Chandan Gautam
# Institute: IIT Indore, India
# Email: chandangautam31@gmail.com , phd1501101001@iiti.ac.in
# Following papers are implemented in the following codes:
# Paper1 (KOC+): Gautam, Chandan, Aruna Tiwari, and M. Tanveer. "KOC+: Kernel ridge regression based one-class classification using privileged information."
# Information Sciences 504 (2019): 324-333.
# Paper2 (OCKELM/KOC): Leng, Qian, et al. "One-class classification with extreme learning machine."
# Mathematical problems in engineering 2015 (2015).
# Paper3 (AEKOC+): Gautam, Chandan, Aruna Tiwari, and M. Tanveer. "AEKOC+: Kernel ridge regression based Auto-Encoder for one-class classification using privileged information."
# (Submitted after first revision in Cognitive computation, Springer.)
# Paper4 (AEKOC/AAKELM): Gautam, Chandan, Aruna Tiwari, and Qian Leng. "On the construction of extreme learning machine for online and offline one-class classification-An expanded toolbox."
# Neurocomputing 261 (2017): 126-143.
# Paper5 (SVDD+): Zhang, Wenbo. "Support vector data description using privileged information."
# Electronics Letters 51.14 (2015): 1075-1076.
# Paper6 (OCSVM+): Zhu, Wenxin, and Ping Zhong. "A new one-class SVM based on hidden information."
# Knowledge-Based Systems 60 (2014): 35-43.
# AND
# Burnaev, Evgeny, and Dmitry Smolyakov. "One-class SVM with privileged information and its application to malware detection."
# 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). IEEE, 2016.
import numpy as np
from cvxopt import matrix
from cvxopt import sparse
from cvxopt.solvers import qp
import math
def linear_kernel(X, Y=None):
return np.dot(X, X.T) if Y is None else np.dot(X, Y.T)
class IKOC(object):
'''
This class implements KOC+ algorithm,
Paper: Gautam, Chandan, Aruna Tiwari, and M. Tanveer. "KOC+: Kernel ridge regression based one-class classification using privileged information."
Information Sciences 504 (2019): 324-333.
'''
def __init__(self, nu, features_kernel=linear_kernel,
privileged_kernel=linear_kernel,
privileged_regularization=0.1,
regularization=0, tol=0.001):
self.nu = nu
self.tol = tol
self.features_kernel = features_kernel
self.privileged_kernel = privileged_kernel
self.regularization = regularization
self.privileged_regularization = privileged_regularization
self.dual_solution = None
self.support_indices = None
self.support_vectors = None
self.dual_alpha = None
def fit(self, X, Z):
'''
Method takes matrix with feature values (X)
and information from privilaged feature
space (Z), compute output weight beta
'''
kernel_x = self.features_kernel(X)
kernel_z = self.privileged_kernel(Z)
if self.regularization==0:
C = 1.0 / len(X) / self.nu # Like SVDD or ISVDD
else:
C = self.regularization # Fix the nu at 0.05 or 0.10 and vary C
Cpriv = self.privileged_regularization
size = X.shape[0]
T = np.ones((size, 1))
self.dual_alpha = np.dot(np.dot(np.linalg.inv(Cpriv * kernel_x + C * (np.dot(kernel_x, kernel_z)) + kernel_z),(np.eye(size)*Cpriv + C * kernel_z)), T)
self.support_vectors = X
score1 = abs(T - np.dot(kernel_x,self.dual_alpha))
#score1_sort = score1.sort()
score1_sort = sorted(score1)
fracrej = self.nu
self.threshold = score1_sort[int(math.ceil(size*(1-fracrej)))-1]
self.score_train = self.threshold - score1
return self
def decision_function(self, X):
"""
Return anomaly score for points in X
"""
T_one = np.ones((X.shape[0], 1))
score_test = self.threshold - abs(T_one - np.dot(self.features_kernel(X, self.support_vectors),self.dual_alpha))
return score_test
class KOC(object):
'''
This class implements KOC algorithm,
Paper: Leng, Qian, et al. "One-class classification with extreme learning machine."
Mathematical problems in engineering 2015 (2015).
'''
def __init__(self, nu, features_kernel=linear_kernel,
regularization=0, tol=0.001):
self.nu = nu
self.tol = tol
self.features_kernel = features_kernel
self.regularization = regularization
self.dual_solution = None
self.support_indices = None
self.support_vectors = None
self.dual_alpha = None
def fit(self, X):
'''
Method takes matrix with feature values (X)
and information from privilaged feature
space (Z), compute output weight beta
'''
kernel_x = self.features_kernel(X)
if self.regularization==0:
C = 1.0 / len(X) / self.nu # Like SVDD or ISVDD
else:
C = self.regularization # Fix the nu at 0.05 or 0.10 and vary C
size = X.shape[0]
T = np.ones((size, 1))
self.dual_alpha = np.dot(np.linalg.inv(np.eye(size)*C + kernel_x), T)
self.support_vectors = X
score1 = abs(T - np.dot(kernel_x,self.dual_alpha))
#score1_sort = score1.sort()
score1_sort = sorted(score1)
fracrej = self.nu
self.threshold = score1_sort[int(math.ceil(size*(1-fracrej)))-1]
self.score_train = self.threshold - score1
return self
def decision_function(self, X):
"""
Return anomaly score for points in X
"""
T_one = np.ones((X.shape[0], 1))
score_test = self.threshold - abs(T_one - np.dot(self.features_kernel(X, self.support_vectors),self.dual_alpha))
return score_test
### For another threshold criteria
def fit1(self, X):
'''
Method takes matrix with feature values (X)
and information from privilaged feature
space (Z), compute output weight beta
'''
kernel_x = self.features_kernel(X)
if self.regularization==0:
C = 1.0 / len(X) / self.nu # Like SVDD or ISVDD
else:
C = self.regularization # Fix the nu at 0.05 or 0.10 and vary C
size = X.shape[0]
T = np.ones((size, 1))
self.dual_alpha = np.dot(np.linalg.inv(np.eye(size)*C + kernel_x), T)
self.support_vectors = X
outY = np.dot(kernel_x,self.dual_alpha)
self.meanY = np.mean(outY)
fracrej = self.nu
self.threshold = self.meanY * fracrej
self.score_train = abs(outY - self.meanY)
return self
def decision_function1(self, X):
"""
Return anomaly score for points in X
"""
score_test = self.threshold - abs(self.meanY - np.dot(self.features_kernel(X, self.support_vectors),self.dual_alpha))
return score_test
class IAEKOC(object):
'''
This class implements AEKOC+ algorithm,
Paper: Gautam, Chandan, Aruna Tiwari, and M. Tanveer. "AEKOC+: Kernel ridge regression based Auto-Encoder for one-class classification using privileged information."
(Submitted after first revision in Cognitive computation, Springer.)
'''
def __init__(self, nu, features_kernel=linear_kernel,
privileged_kernel=linear_kernel,
privileged_regularization=0.1,
regularization=0, tol=0.001):
self.nu = nu
self.tol = tol
self.features_kernel = features_kernel
self.privileged_kernel = privileged_kernel
self.regularization = regularization
self.privileged_regularization = privileged_regularization
self.dual_solution = None
self.support_indices = None
self.support_vectors = None
self.dual_alpha = None
def fit(self, X, Z):
'''
Method takes matrix with feature values (X)
and information from privilaged feature
space (Z), compute output weight beta
'''
kernel_x = self.features_kernel(X)
kernel_z = self.privileged_kernel(Z)
if self.regularization==0:
C = 1.0 / len(X) / self.nu # Like SVDD or ISVDD
else:
C = self.regularization # Fix the nu at 0.05 or 0.10 and vary C
Cpriv = self.privileged_regularization
size = X.shape[0]
T = X
self.dual_alpha = np.dot(np.dot(np.linalg.inv(Cpriv * kernel_x + C * (np.dot(kernel_x, kernel_z)) + kernel_z),(np.eye(size)*Cpriv + C * kernel_z)), T)
# self.dual_alpha = np.dot(np.dot(np.linalg.inv(Cpriv * kernel_x + C * (np.dot(kernel_x, kernel_z)) + kernel_z+ np.eye(size)*C),(np.eye(size)*Cpriv + C * kernel_z)), T)
self.support_vectors = X
score1 = np.sum((T-np.dot(kernel_x,self.dual_alpha))**2,1)
#score1_sort = score1.sort()
score1_sort = sorted(score1)
fracrej = self.nu
self.threshold = score1_sort[int(math.ceil(size*(1-fracrej)))-1]
self.score_train = self.threshold - score1
return self
def decision_function(self, X):
"""
Return anomaly score for points in X
"""
score_test = self.threshold - np.sum((X-np.dot(self.features_kernel(X, self.support_vectors),self.dual_alpha))**2,1)
return score_test
class AEKOC(object):
'''
This class implements AEKOC/AAKELM algorithm,
Paper: Gautam, Chandan, Aruna Tiwari, and Qian Leng. "On the construction of extreme learning machine for online and offline one-class classification-An expanded toolbox."
Neurocomputing 261 (2017): 126-143.
'''
def __init__(self, nu, features_kernel=linear_kernel,
regularization=0, tol=0.001):
self.nu = nu
self.tol = tol
self.features_kernel = features_kernel
self.regularization = regularization
self.dual_solution = None
self.support_indices = None
self.support_vectors = None
self.dual_alpha = None
def fit(self, X):
'''
Method takes matrix with feature values (X)
and information from privilaged feature
space (Z), compute output weight beta
'''
kernel_x = self.features_kernel(X)
if self.regularization==0:
C = 1.0 / len(X) / self.nu # Like SVDD or ISVDD
else:
C = self.regularization # Fix the nu at 0.05 or 0.10 and vary C
size = X.shape[0]
T = X
self.dual_alpha = np.dot(np.linalg.inv(np.eye(size)*C + kernel_x), T)
self.support_vectors = X
score1 = np.sum((T-np.dot(kernel_x,self.dual_alpha))**2,1)
# score1 = ((T-np.dot(kernel_x,self.dual_alpha))**2).sum(1)
#score1_sort = score1.sort()
score1_sort = sorted(score1)
fracrej = self.nu
self.threshold = score1_sort[int(math.ceil(size*(1-fracrej)))-1]
self.score_train = self.threshold - score1
return self
def decision_function(self, X):
"""
Return anomaly score for points in X
"""
score_test = self.threshold - np.sum((X-np.dot(self.features_kernel(X, self.support_vectors),self.dual_alpha))**2,1)
return score_test
class ISVDD(object):
'''
This class implements SVDD+ algorithm,
Paper: Zhang, Wenbo. "Support vector data description using privileged information."
Electronics Letters 51.14 (2015): 1075-1076.
'''
def __init__(self, nu, features_kernel=linear_kernel,
privileged_kernel=linear_kernel,
privileged_regularization=0.1,
tol=0.001, max_iter=100, silent=True):
# Setting initial parameters
self.nu = nu
self.tol = tol
self.max_iter = max_iter
self.features_kernel = features_kernel
self.privileged_kernel = privileged_kernel
self.privileged_regularization = privileged_regularization
self.tol = tol
self.silent = silent
# Initializing with None some futer parameters
self.dual_solution = None
self.support_indices = None
self.support_vectors = None
self.dual_alpha = None
def _prepare_problem(self, X, Z):
"""
Initializes optimization
problem in form of several matrices
for cvxopt framework
"""
gamma = self.privileged_regularization
C = 1.0 / len(X) / self.nu
size = X.shape[0]
kernel_x = self.features_kernel(X)
kernel_z = self.privileged_kernel(Z)
zeros_matrix = np.zeros_like(kernel_x)
P = 2 * np.bmat([[kernel_x, zeros_matrix],
[zeros_matrix, 0.5*gamma*kernel_z]])
P = matrix(P)
q = matrix(list(np.diag(kernel_x)) + [0] * size)
A = matrix([[1.]*size + [0.]*size, [1.] * size*2]).T
b = matrix([1., 1.])
G = np.bmat([[-np.eye(size), zeros_matrix],
[-np.eye(size), np.eye(size)],
[np.eye(size), -np.eye(size)]])
G = matrix(G)
G = sparse(G)
h = matrix([0]*size*2 + [C]*size)
optimization_problem = {'P': P, 'q': q, 'G': G,
'h': h, 'A': A, 'b': b}
return optimization_problem
# Helper function for prediction
def _scalar_product_with_center(self, X):
return np.dot(self.features_kernel(X, self.support_vectors),
self.dual_alpha)
def _calculate_threshold(self):
"""
Calculates critical value of the decision function
"""
kernel_support = self.features_kernel(self.support_vectors)
self.centre_norm = np.dot(self.dual_alpha,
np.dot(kernel_support,
self.dual_alpha))
# Select the first support vector since distance
# between it center equal to R
single_support_vector = self.support_vectors[0, :]
first_support_vector = single_support_vector.reshape(1, -1)
support_vector_norm = self.features_kernel(first_support_vector)
dot_product_with_centre = 2 * self._scalar_product_with_center(
single_support_vector[np.newaxis, :])
self.radius = (support_vector_norm +
self.centre_norm -
dot_product_with_centre)
self.threshold = self.centre_norm - self.radius
def fit(self, X, Z):
'''
Method takes matrix with feature values
and information from privilaged feature
space, solves optimization probem and
calculate center and radius of sphere
'''
problem = self._prepare_problem(X, Z)
options = {}
options['show_progress'] = False #self.silent
options['maxiters'] = self.max_iter
options['abstol'] = self.tol
problem['options'] = options
solver = qp(**problem)
if solver['status'] != 'optimal':
raise ValueError("Failed Optimization")
self.dual_solution = np.array(solver['x']).reshape(2*len(X),)
self.support_indices = np.where(self.dual_solution[:len(X)] > 0)[0]
self.support_vectors = X[self.support_indices, :]
self.dual_alpha = self.dual_solution[self.support_indices]
self._calculate_threshold()
return self
def decision_function(self, X):
"""
Return anomaly score for points in X
"""
test_norm = np.diag(self.features_kernel(X))
scalar_product = self._scalar_product_with_center(X)
return test_norm.ravel() + self.threshold - 2*scalar_product
class IOneClassSVM(object):
'''
This class implements OCSVM+ algorithm,
Paper1: Zhu, Wenxin, and Ping Zhong. "A new one-class SVM based on hidden information."
Knowledge-Based Systems 60 (2014): 35-43.
Paper2: Burnaev, Evgeny, and Dmitry Smolyakov. "One-class SVM with privileged information and its application to malware detection."
2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). IEEE, 2016.
'''
def __init__(self, nu, features_kernel=linear_kernel,
privileged_kernel=linear_kernel,
privileged_regularization=0.1,
max_iter=100, tol=0.001):
self.nu = nu
self.max_iter = max_iter
self.tol = tol
self.features_kernel = features_kernel
self.privileged_kernel = privileged_kernel
self.privileged_regularization = privileged_regularization
self.dual_solution = None
self.support_indices = None
self.support_vectors = None
self.dual_alpha = None
def _prepare_problem(self, X, Z):
"""
Initializes optimization
problem in form of several matrices
for cvxopt framework
"""
gamma = self.privileged_regularization
C = 1.0 / len(X) / self.nu
size = X.shape[0]
kernel_x = self.features_kernel(X)
kernel_z = self.privileged_kernel(Z)
q = np.zeros(len(X) * 2, dtype='float')
q = matrix(q)
zeros_matrix = np.zeros_like(kernel_x)
P = 2 * np.bmat([[kernel_x, zeros_matrix],
[zeros_matrix, 0.5*gamma*kernel_z]])
P = matrix(P)
A = matrix([[1.]*size + [0.]*size, [1.] * size*2]).T
b = matrix([1., 1.])
G = np.bmat([[-np.eye(size), zeros_matrix],
[-np.eye(size), np.eye(size)],
[np.eye(size), -np.eye(size)]])
G = matrix(G)
G = sparse(G)
h = matrix([0]*size*2 + [C]*size)
optimization_problem = {'P': P, 'q': q, 'G': G,
'h': h, 'A': A, 'b': b}
return optimization_problem
def fit(self, X, Z):
'''
Method takes matrix with feature values
and information from privilaged feature
space, solves optimization probem and
calculate center and radius of sphere
'''
problem = self._prepare_problem(X, Z)
options = {}
options['show_progress'] = False
problem['options'] = options
options['maxiters'] = self.max_iter
options['abstol'] = self.tol
solver = qp(**problem)
if solver['status'] != 'optimal':
raise ValueError("Failed Optimization")
self.dual_solution = np.array(solver['x']).reshape(2*len(X),)
self.support_indices = np.where(self.dual_solution[:len(X)] > 0)[0]
self.support_vectors = X[self.support_indices, :]
self.dual_alpha = self.dual_solution[self.support_indices]
return self
def decision_function(self, X):
"""
Return anomaly score for points in X
"""
return -np.dot(self.features_kernel(X, self.support_vectors),
self.dual_alpha)
| 39.407025
| 191
| 0.609395
| 2,422
| 19,073
| 4.661024
| 0.123865
| 0.026663
| 0.033395
| 0.025246
| 0.860749
| 0.846488
| 0.844007
| 0.83072
| 0.83072
| 0.817699
| 0
| 0.025637
| 0.286269
| 19,073
| 484
| 192
| 39.407025
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| 0.011555
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| 1
| 0.085616
| false
| 0
| 0.017123
| 0.006849
| 0.184932
| 0
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| 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
|
0f5d42256648afe3d23ee4b7c56282e359c12022
| 7,391
|
py
|
Python
|
parl/remote/grpc_heartbeat/tests/heartbeat_server_arguments_test.py
|
ShuaibinLi/PARL
|
0e6e28269d61525404672eae2b1cd95cea0b1748
|
[
"ECL-2.0",
"Apache-2.0"
] | 2
|
2022-03-29T08:44:27.000Z
|
2022-03-29T08:47:09.000Z
|
parl/remote/grpc_heartbeat/tests/heartbeat_server_arguments_test.py
|
Nicer0815/PARL
|
6da27aae70cb8577a40f3eb2086b5b598e74ad7c
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
parl/remote/grpc_heartbeat/tests/heartbeat_server_arguments_test.py
|
Nicer0815/PARL
|
6da27aae70cb8577a40f3eb2086b5b598e74ad7c
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
import time
import unittest
from parl.remote.grpc_heartbeat import HeartbeatServerThread
from parl.remote.grpc_heartbeat import HeartbeatClientThread
from parl.remote import remote_constants
class TestHeartbeatServerArguments(unittest.TestCase):
def setUp(self):
self.server_exited = False
self.client_exited = False
def test_heartbeat_server_exit_with_args(self):
arg1_value = 10
def server_exit_func(arg1):
print("exit heartbeat server")
assert arg1 == arg1_value
self.server_exited = True
heartbeat_server_thread = HeartbeatServerThread(
server_exit_func, exit_func_args=(arg1_value, ))
heartbeat_server_thread.start()
server_address = heartbeat_server_thread.get_address()
def client_exit_func():
print("exit heartbeat client")
self.client_exited = True
heartbeat_client_thread = HeartbeatClientThread(
server_address, client_exit_func)
heartbeat_client_thread.start()
time.sleep(remote_constants.HEARTBEAT_RCVTIMEO_S * 2)
# check server and client are still alive after HEARTBEAT_RCVTIMEO_S * 2
assert heartbeat_server_thread.is_alive()
assert heartbeat_client_thread.is_alive()
heartbeat_server_thread.exit() # manually exit the server
# wait for threads exiting
for _ in range(6):
if not heartbeat_server_thread.is_alive(
) and not heartbeat_client_thread.is_alive():
break
time.sleep(remote_constants.HEARTBEAT_INTERVAL_S)
# check heartbeat server and client are exited
assert not heartbeat_server_thread.is_alive()
assert not heartbeat_client_thread.is_alive()
assert self.server_exited == True
assert self.client_exited == True
def test_heartbeat_server_exit_with_wrong_args(self):
arg1_value = 10
def server_exit_func(arg1):
print("exit heartbeat server")
assert arg1 == arg1_value
self.server_exited = True
heartbeat_server_thread = HeartbeatServerThread(
server_exit_func, exit_func_args=(arg1_value, "wrong_args"))
heartbeat_server_thread.start()
server_address = heartbeat_server_thread.get_address()
def client_exit_func():
print("exit heartbeat client")
self.client_exited = True
heartbeat_client_thread = HeartbeatClientThread(
server_address, client_exit_func)
heartbeat_client_thread.start()
time.sleep(remote_constants.HEARTBEAT_RCVTIMEO_S * 2)
# check server and client are still alive after HEARTBEAT_RCVTIMEO_S * 2
assert heartbeat_server_thread.is_alive()
assert heartbeat_client_thread.is_alive()
heartbeat_server_thread.exit() # manually exit the server
# will raise an exception in the backend thread
# wait for threads exiting
for _ in range(6):
if not heartbeat_server_thread.is_alive(
) and not heartbeat_client_thread.is_alive():
break
time.sleep(remote_constants.HEARTBEAT_INTERVAL_S)
# check heartbeat server and client are exited
assert not heartbeat_server_thread.is_alive()
assert not heartbeat_client_thread.is_alive()
assert self.server_exited == False # the heartbeat server cannot exit normally
assert self.client_exited == True
def test_heartbeat_server_exit_with_kwargs(self):
arg1_value = 10
def server_exit_func(arg1):
print("exit heartbeat server")
assert arg1 == arg1_value
self.server_exited = True
heartbeat_server_thread = HeartbeatServerThread(
server_exit_func, exit_func_kwargs={"arg1": arg1_value})
heartbeat_server_thread.start()
server_address = heartbeat_server_thread.get_address()
def client_exit_func():
print("exit heartbeat client")
self.client_exited = True
heartbeat_client_thread = HeartbeatClientThread(
server_address, client_exit_func)
heartbeat_client_thread.start()
time.sleep(remote_constants.HEARTBEAT_RCVTIMEO_S * 2)
# check server and client are still alive after HEARTBEAT_RCVTIMEO_S * 2
assert heartbeat_server_thread.is_alive()
assert heartbeat_client_thread.is_alive()
heartbeat_server_thread.exit() # manually exit the server
# wait for threads exiting
for _ in range(6):
if not heartbeat_server_thread.is_alive(
) and not heartbeat_client_thread.is_alive():
break
time.sleep(remote_constants.HEARTBEAT_INTERVAL_S)
# check heartbeat server and client are exited
assert not heartbeat_server_thread.is_alive()
assert not heartbeat_client_thread.is_alive()
assert self.server_exited == True
assert self.client_exited == True
def test_heartbeat_server_exit_with_wrong_kwargs(self):
arg1_value = 10
def server_exit_func(arg1):
print("exit heartbeat server")
assert arg1 == arg1_value
self.server_exited = True
heartbeat_server_thread = HeartbeatServerThread(
server_exit_func, exit_func_kwargs={"wrong_args": arg1_value})
heartbeat_server_thread.start()
server_address = heartbeat_server_thread.get_address()
def client_exit_func():
print("exit heartbeat client")
self.client_exited = True
heartbeat_client_thread = HeartbeatClientThread(
server_address, client_exit_func)
heartbeat_client_thread.start()
time.sleep(remote_constants.HEARTBEAT_RCVTIMEO_S * 2)
# check server and client are still alive after HEARTBEAT_RCVTIMEO_S * 2
assert heartbeat_server_thread.is_alive()
assert heartbeat_client_thread.is_alive()
heartbeat_server_thread.exit() # manually exit the server
# will raise an exception in the backend thread
# wait for threads exiting
for _ in range(6):
if not heartbeat_server_thread.is_alive(
) and not heartbeat_client_thread.is_alive():
break
time.sleep(remote_constants.HEARTBEAT_INTERVAL_S)
# check heartbeat server and client are exited
assert not heartbeat_server_thread.is_alive()
assert not heartbeat_client_thread.is_alive()
assert self.server_exited == False # the heartbeat server cannot exit normally
assert self.client_exited == True
if __name__ == '__main__':
unittest.main()
| 35.533654
| 87
| 0.684752
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| 0.131579
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| 1
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| false
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| 0.062992
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0
| 7
|
7e7eaeb0235597a06f39924575d0f8d5c153c35c
| 158,143
|
py
|
Python
|
venv/lib/python3.8/site-packages/azureml/_restclient/operations/dataset_operations.py
|
amcclead7336/Enterprise_Data_Science_Final
|
ccdc0aa08d4726bf82d71c11a1cc0c63eb301a28
|
[
"Unlicense",
"MIT"
] | null | null | null |
venv/lib/python3.8/site-packages/azureml/_restclient/operations/dataset_operations.py
|
amcclead7336/Enterprise_Data_Science_Final
|
ccdc0aa08d4726bf82d71c11a1cc0c63eb301a28
|
[
"Unlicense",
"MIT"
] | null | null | null |
venv/lib/python3.8/site-packages/azureml/_restclient/operations/dataset_operations.py
|
amcclead7336/Enterprise_Data_Science_Final
|
ccdc0aa08d4726bf82d71c11a1cc0c63eb301a28
|
[
"Unlicense",
"MIT"
] | 2
|
2021-05-23T16:46:31.000Z
|
2021-05-26T23:51:09.000Z
|
# 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 2.3.33.0
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.pipeline import ClientRawResponse
from msrest.exceptions import HttpOperationError
from .. import models
class DatasetOperations(object):
"""DatasetOperations operations.
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
"""
models = models
def __init__(self, client, config, serializer, deserializer):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self.config = config
def list_actions(
self, subscription_id, resource_group_name, workspace_name, dataset_id, continuation_token=None, count=30, action_type=None, custom_headers=None, raw=False, **operation_config):
"""List.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param continuation_token:
:type continuation_token: str
:param count:
:type count: int
:param action_type:
:type action_type: str
: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>`.
:return: PaginatedResultActionDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.PaginatedResultActionDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.list_actions.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if continuation_token is not None:
query_parameters['continuationToken'] = self._serialize.query("continuation_token", continuation_token, 'str')
if count is not None:
query_parameters['count'] = self._serialize.query("count", count, 'int')
if action_type is not None:
query_parameters['actionType'] = self._serialize.query("action_type", action_type, 'str')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('PaginatedResultActionDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
list_actions.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions'}
def submit_action(
self, subscription_id, resource_group_name, workspace_name, dataset_id, request=None, custom_headers=None, raw=False, **operation_config):
"""Submit.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param request:
:type request: ~_restclient.models.ActionRequestDto
: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>`.
:return: ActionDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.ActionDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.submit_action.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_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-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request is not None:
body_content = self._serialize.body(request, 'ActionRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ActionDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
submit_action.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions'}
def delete_actions(
self, subscription_id, resource_group_name, workspace_name, dataset_id, custom_headers=None, raw=False, **operation_config):
"""DeleteActions.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.delete_actions.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.delete(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
delete_actions.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions'}
def get_action_result(
self, subscription_id, resource_group_name, workspace_name, dataset_id, request=None, custom_headers=None, raw=False, **operation_config):
"""GetResult.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param request:
:type request: ~_restclient.models.ActionRequestDto
: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>`.
:return: ActionResultDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.ActionResultDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_action_result.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_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-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request is not None:
body_content = self._serialize.body(request, 'ActionRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ActionResultDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_action_result.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions/result'}
def list_actions_from_request(
self, subscription_id, resource_group_name, workspace_name, dataset_id, request, count=50, continuation_token=None, custom_headers=None, raw=False, **operation_config):
"""ListActionsFromRequest.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param request:
:type request: ~_restclient.models.ActionRequestDto
:param count:
:type count: int
:param continuation_token:
:type continuation_token: str
: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>`.
:return: PaginatedResultActionDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.PaginatedResultActionDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.list_actions_from_request.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if count is not None:
query_parameters['count'] = self._serialize.query("count", count, 'int')
if continuation_token is not None:
query_parameters['continuationToken'] = self._serialize.query("continuation_token", continuation_token, 'str')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(request, 'ActionRequestDto')
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('PaginatedResultActionDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
list_actions_from_request.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions/listactionsfromrequest'}
def get_action_by_id(
self, subscription_id, resource_group_name, workspace_name, dataset_id, action_id, check_staleness=False, custom_headers=None, raw=False, **operation_config):
"""Get.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param action_id:
:type action_id: str
:param check_staleness:
:type check_staleness: bool
: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>`.
:return: ActionDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.ActionDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_action_by_id.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'actionId': self._serialize.url("action_id", action_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if check_staleness is not None:
query_parameters['checkStaleness'] = self._serialize.query("check_staleness", check_staleness, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ActionDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_action_by_id.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions/{actionId}'}
def cancel_action_by_id(
self, subscription_id, resource_group_name, workspace_name, dataset_id, action_id, custom_headers=None, raw=False, **operation_config):
"""Cancel.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param action_id:
:type action_id: str
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.cancel_action_by_id.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'actionId': self._serialize.url("action_id", action_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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
cancel_action_by_id.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions/{actionId}/cancel'}
def update_action_result(
self, subscription_id, resource_group_name, workspace_name, dataset_id, action_id, result_update_dto=None, custom_headers=None, raw=False, **operation_config):
"""UpdateResult.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param action_id:
:type action_id: str
:param result_update_dto:
:type result_update_dto: ~_restclient.models.ActionResultUpdateDto
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.update_action_result.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'actionId': self._serialize.url("action_id", action_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-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if result_update_dto is not None:
body_content = self._serialize.body(result_update_dto, 'ActionResultUpdateDto')
else:
body_content = None
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
update_action_result.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/actions/{actionId}/result'}
def get_associations(
self, subscription_id, resource_group_name, workspace_name, dataset_id, dataset_associate_dto=None, custom_headers=None, raw=False, **operation_config):
"""Get associations.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param dataset_associate_dto:
:type dataset_associate_dto: ~_restclient.models.AssociationRequestDto
: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>`.
:return: PaginatedResultAssociationDto or ClientRawResponse if
raw=true
:rtype: ~_restclient.models.PaginatedResultAssociationDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_associations.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_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-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataset_associate_dto is not None:
body_content = self._serialize.body(dataset_associate_dto, 'AssociationRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('PaginatedResultAssociationDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_associations.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/associations'}
def associate_datasets(
self, subscription_id, resource_group_name, workspace_name, dataset_id, dataset_associate_dto=None, custom_headers=None, raw=False, **operation_config):
"""Associate two datasets.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param dataset_associate_dto:
:type dataset_associate_dto: ~_restclient.models.AssociationRequestDto
: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>`.
:return: AssociationDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.AssociationDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.associate_datasets.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_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-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataset_associate_dto is not None:
body_content = self._serialize.body(dataset_associate_dto, 'AssociationRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('AssociationDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
associate_datasets.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/associations'}
def dissociate_datasets(
self, subscription_id, resource_group_name, workspace_name, dataset_id, dataset_associate_dto=None, custom_headers=None, raw=False, **operation_config):
"""Dissociate two datasets.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param dataset_associate_dto:
:type dataset_associate_dto: ~_restclient.models.AssociationRequestDto
: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>`.
:return: int or ClientRawResponse if raw=true
:rtype: int or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.dissociate_datasets.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_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-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataset_associate_dto is not None:
body_content = self._serialize.body(dataset_associate_dto, 'AssociationRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('int', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
dissociate_datasets.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/associations/remove'}
def get_dataset_definition(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version:
:type version: str
: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>`.
:return: DatasetDefinitionDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDefinitionDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_dataset_definition.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'version': self._serialize.url("version", version, '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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDefinitionDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_dataset_definition.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions/{version}'}
def get_data_path(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version:
:type version: str
: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>`.
:return: DataPathDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DataPathDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_data_path.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'version': self._serialize.url("version", version, '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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DataPathDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_data_path.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions/{version}/path'}
def get_dataset_preview_by_dataset_request(
self, subscription_id, resource_group_name, workspace_name, request_dto=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param request_dto:
:type request_dto: ~_restclient.models.DatasetRequestDto
: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>`.
:return: DataViewSetResult or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DataViewSetResult or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_dataset_preview_by_dataset_request.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request_dto is not None:
body_content = self._serialize.body(request_dto, 'DatasetRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DataViewSetResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_dataset_preview_by_dataset_request.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/preview'}
def get_dataset_preview_by_dataflow_json(
self, subscription_id, resource_group_name, workspace_name, dataflow_json=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataflow_json:
:type dataflow_json: str
: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>`.
:return: DataViewSetResult or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DataViewSetResult or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_dataset_preview_by_dataflow_json.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataflow_json is not None:
body_content = self._serialize.body(dataflow_json, 'str')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DataViewSetResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_dataset_preview_by_dataflow_json.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/dataflow/preview'}
def get_dataset_preview_by_dataset_id(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version_id=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version_id:
:type version_id: str
: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>`.
:return: DataViewSetResult or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DataViewSetResult or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_dataset_preview_by_dataset_id.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if version_id is not None:
query_parameters['versionId'] = self._serialize.query("version_id", version_id, 'str')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DataViewSetResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_dataset_preview_by_dataset_id.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/preview'}
def get_quick_profile_by_dataset_id(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version_id=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version_id:
:type version_id: str
: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>`.
:return: list or ClientRawResponse if raw=true
:rtype: list[~_restclient.models.ProfileResult] or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_quick_profile_by_dataset_id.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if version_id is not None:
query_parameters['versionId'] = self._serialize.query("version_id", version_id, 'str')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('[ProfileResult]', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_quick_profile_by_dataset_id.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/quickprofile'}
def get_quick_profile_by_dataset_request(
self, subscription_id, resource_group_name, workspace_name, request_dto=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param request_dto:
:type request_dto: ~_restclient.models.DatasetRequestDto
: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>`.
:return: list or ClientRawResponse if raw=true
:rtype: list[~_restclient.models.ProfileResult] or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_quick_profile_by_dataset_request.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request_dto is not None:
body_content = self._serialize.body(request_dto, 'DatasetRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('[ProfileResult]', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_quick_profile_by_dataset_request.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/quickprofile'}
def get_quick_profile_by_dataflow_json(
self, subscription_id, resource_group_name, workspace_name, dataflow_json=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataflow_json:
:type dataflow_json: str
: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>`.
:return: list or ClientRawResponse if raw=true
:rtype: list[~_restclient.models.ProfileResult] or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_quick_profile_by_dataflow_json.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataflow_json is not None:
body_content = self._serialize.body(dataflow_json, 'str')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('[ProfileResult]', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_quick_profile_by_dataflow_json.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/quickprofile/dataflow'}
def get_all_dataset_definitions(
self, subscription_id, resource_group_name, workspace_name, dataset_id, continuation_token=None, page_size=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param continuation_token:
:type continuation_token: str
:param page_size:
:type page_size: int
: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>`.
:return: PaginatedResultDatasetDefinitionDto or ClientRawResponse if
raw=true
:rtype: ~_restclient.models.PaginatedResultDatasetDefinitionDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_all_dataset_definitions.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if continuation_token is not None:
query_parameters['continuationToken'] = self._serialize.query("continuation_token", continuation_token, 'str')
if page_size is not None:
query_parameters['pageSize'] = self._serialize.query("page_size", page_size, 'int')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('PaginatedResultDatasetDefinitionDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_all_dataset_definitions.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions'}
def update_definition(
self, subscription_id, resource_group_name, workspace_name, dataset_id, new_definition=None, register_as_pending=False, force_update=False, custom_headers=None, raw=False, **operation_config):
"""UpdateDefinition.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param new_definition:
:type new_definition: ~_restclient.models.DatasetDefinitionDto
:param register_as_pending:
:type register_as_pending: bool
:param force_update:
:type force_update: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.update_definition.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if register_as_pending is not None:
query_parameters['registerAsPending'] = self._serialize.query("register_as_pending", register_as_pending, 'bool')
if force_update is not None:
query_parameters['forceUpdate'] = self._serialize.query("force_update", force_update, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if new_definition is not None:
body_content = self._serialize.body(new_definition, 'DatasetDefinitionDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
update_definition.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions'}
def get_dataset_by_id(
self, subscription_id, resource_group_name, workspace_name, dataset_id, include_latest_definition=True, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param include_latest_definition:
:type include_latest_definition: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_dataset_by_id.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if include_latest_definition is not None:
query_parameters['includeLatestDefinition'] = self._serialize.query("include_latest_definition", include_latest_definition, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_dataset_by_id.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}'}
def update_dataset(
self, subscription_id, resource_group_name, workspace_name, dataset_id, new_dataset_dto=None, force_update=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param new_dataset_dto:
:type new_dataset_dto: ~_restclient.models.DatasetDto
:param force_update:
:type force_update: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.update_dataset.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if force_update is not None:
query_parameters['forceUpdate'] = self._serialize.query("force_update", force_update, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if new_dataset_dto is not None:
body_content = self._serialize.body(new_dataset_dto, 'DatasetDto')
else:
body_content = None
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
update_dataset.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}'}
def get_dataset_by_name(
self, subscription_id, resource_group_name, workspace_name, dataset_name, version_id=None, include_latest_definition=True, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_name:
:type dataset_name: str
:param version_id:
:type version_id: str
:param include_latest_definition:
:type include_latest_definition: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_dataset_by_name.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetName': self._serialize.url("dataset_name", dataset_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if version_id is not None:
query_parameters['versionId'] = self._serialize.query("version_id", version_id, 'str')
if include_latest_definition is not None:
query_parameters['includeLatestDefinition'] = self._serialize.query("include_latest_definition", include_latest_definition, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_dataset_by_name.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/query/name={datasetName}'}
def get_datasets_by_saved_dataset_id(
self, subscription_id, resource_group_name, workspace_name, saved_dataset_id, page_size=10, continuation_token=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param saved_dataset_id:
:type saved_dataset_id: str
:param page_size:
:type page_size: int
:param continuation_token:
:type continuation_token: str
: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>`.
:return: PaginatedResultDatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.PaginatedResultDatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_datasets_by_saved_dataset_id.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'savedDatasetId': self._serialize.url("saved_dataset_id", saved_dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if page_size is not None:
query_parameters['pageSize'] = self._serialize.query("page_size", page_size, 'int')
if continuation_token is not None:
query_parameters['continuationToken'] = self._serialize.query("continuation_token", continuation_token, 'str')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('PaginatedResultDatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_datasets_by_saved_dataset_id.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/query/savedDatasetId={savedDatasetId}'}
def list(
self, subscription_id, resource_group_name, workspace_name, dataset_names=None, search_text=None, include_invisible=False, status=None, continuation_token=None, page_size=None, include_latest_definition=False, custom_headers=None, raw=False, **operation_config):
"""List.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_names:
:type dataset_names: list[str]
:param search_text:
:type search_text: str
:param include_invisible:
:type include_invisible: bool
:param status:
:type status: str
:param continuation_token:
:type continuation_token: str
:param page_size:
:type page_size: int
:param include_latest_definition:
:type include_latest_definition: bool
: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>`.
:return: PaginatedResultDatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.PaginatedResultDatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.list.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if dataset_names is not None:
query_parameters['datasetNames'] = self._serialize.query("dataset_names", dataset_names, '[str]', div=',')
if search_text is not None:
query_parameters['searchText'] = self._serialize.query("search_text", search_text, 'str')
if include_invisible is not None:
query_parameters['includeInvisible'] = self._serialize.query("include_invisible", include_invisible, 'bool')
if status is not None:
query_parameters['status'] = self._serialize.query("status", status, 'str')
if continuation_token is not None:
query_parameters['continuationToken'] = self._serialize.query("continuation_token", continuation_token, 'str')
if page_size is not None:
query_parameters['pageSize'] = self._serialize.query("page_size", page_size, 'int')
if include_latest_definition is not None:
query_parameters['includeLatestDefinition'] = self._serialize.query("include_latest_definition", include_latest_definition, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('PaginatedResultDatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
list.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets'}
def register(
self, subscription_id, resource_group_name, workspace_name, dataset_dto=None, register_as_pending=False, if_exists_ok=True, update_definition_if_exists=False, with_data_hash=False, custom_headers=None, raw=False, **operation_config):
"""Register.
Register new Dataset.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_dto:
:type dataset_dto: ~_restclient.models.DatasetDto
:param register_as_pending:
:type register_as_pending: bool
:param if_exists_ok:
:type if_exists_ok: bool
:param update_definition_if_exists:
:type update_definition_if_exists: bool
:param with_data_hash:
:type with_data_hash: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.register.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if register_as_pending is not None:
query_parameters['registerAsPending'] = self._serialize.query("register_as_pending", register_as_pending, 'bool')
if if_exists_ok is not None:
query_parameters['ifExistsOk'] = self._serialize.query("if_exists_ok", if_exists_ok, 'bool')
if update_definition_if_exists is not None:
query_parameters['updateDefinitionIfExists'] = self._serialize.query("update_definition_if_exists", update_definition_if_exists, 'bool')
if with_data_hash is not None:
query_parameters['withDataHash'] = self._serialize.query("with_data_hash", with_data_hash, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataset_dto is not None:
body_content = self._serialize.body(dataset_dto, 'DatasetDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
register.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets'}
def delete_all_datasets(
self, subscription_id, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.delete_all_datasets.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, '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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.delete(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
delete_all_datasets.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets'}
def register_from_data_path(
self, subscription_id, resource_group_name, workspace_name, request=None, register_as_pending=False, if_exists_ok=True, update_definition_if_exists=False, skip_validation=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param request:
:type request: ~_restclient.models.DatasetRequestDto
:param register_as_pending:
:type register_as_pending: bool
:param if_exists_ok:
:type if_exists_ok: bool
:param update_definition_if_exists:
:type update_definition_if_exists: bool
:param skip_validation:
:type skip_validation: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.register_from_data_path.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if register_as_pending is not None:
query_parameters['registerAsPending'] = self._serialize.query("register_as_pending", register_as_pending, 'bool')
if if_exists_ok is not None:
query_parameters['ifExistsOK'] = self._serialize.query("if_exists_ok", if_exists_ok, 'bool')
if update_definition_if_exists is not None:
query_parameters['updateDefinitionIfExists'] = self._serialize.query("update_definition_if_exists", update_definition_if_exists, 'bool')
if skip_validation is not None:
query_parameters['skipValidation'] = self._serialize.query("skip_validation", skip_validation, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request is not None:
body_content = self._serialize.body(request, 'DatasetRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
register_from_data_path.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/register'}
def parse_data_path(
self, subscription_id, resource_group_name, workspace_name, request=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param request:
:type request: ~_restclient.models.DatasetRequestDto
: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>`.
:return: DatasetRequestDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetRequestDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.parse_data_path.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request is not None:
body_content = self._serialize.body(request, 'DatasetRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetRequestDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
parse_data_path.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/parse'}
def update_pending_definition(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version_id, new_definition=None, force_update=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version_id:
:type version_id: str
:param new_definition:
:type new_definition: ~_restclient.models.DatasetDefinitionDto
:param force_update:
:type force_update: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.update_pending_definition.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'versionId': self._serialize.url("version_id", version_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if force_update is not None:
query_parameters['forceUpdate'] = self._serialize.query("force_update", force_update, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if new_definition is not None:
body_content = self._serialize.body(new_definition, 'DatasetDefinitionDto')
else:
body_content = None
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
update_pending_definition.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions/{versionId}'}
def update_definition_state(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version, new_state=None, force_update=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version:
:type version: str
:param new_state:
:type new_state: ~_restclient.models.DatasetStateDto
:param force_update:
:type force_update: bool
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.update_definition_state.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'version': self._serialize.url("version", version, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if force_update is not None:
query_parameters['forceUpdate'] = self._serialize.query("force_update", force_update, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if new_state is not None:
body_content = self._serialize.body(new_state, 'DatasetStateDto')
else:
body_content = None
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
update_definition_state.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions/{version}/state'}
def update_dataset_state(
self, subscription_id, resource_group_name, workspace_name, dataset_id, new_state=None, force_update=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param new_state:
:type new_state: ~_restclient.models.DatasetStateDto
:param force_update:
:type force_update: bool
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.update_dataset_state.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if force_update is not None:
query_parameters['forceUpdate'] = self._serialize.query("force_update", force_update, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if new_state is not None:
body_content = self._serialize.body(new_state, 'DatasetStateDto')
else:
body_content = None
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
update_dataset_state.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/state'}
def sample(
self, subscription_id, resource_group_name, workspace_name, dataset_id, sample_request=None, register_as_pending=False, if_exists_ok=True, update_definition_if_exists=False, custom_headers=None, raw=False, **operation_config):
"""Creates new sample dataset.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param sample_request:
:type sample_request: ~_restclient.models.DatasetSampleDto
:param register_as_pending:
:type register_as_pending: bool
:param if_exists_ok:
:type if_exists_ok: bool
:param update_definition_if_exists:
:type update_definition_if_exists: bool
: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>`.
:return: DatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.sample.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if register_as_pending is not None:
query_parameters['registerAsPending'] = self._serialize.query("register_as_pending", register_as_pending, 'bool')
if if_exists_ok is not None:
query_parameters['ifExistsOk'] = self._serialize.query("if_exists_ok", if_exists_ok, 'bool')
if update_definition_if_exists is not None:
query_parameters['updateDefinitionIfExists'] = self._serialize.query("update_definition_if_exists", update_definition_if_exists, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if sample_request is not None:
body_content = self._serialize.body(sample_request, 'DatasetSampleDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
sample.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/sample'}
def unregister_dataset(
self, subscription_id, resource_group_name, workspace_name, name, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param name:
:type name: str
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.unregister_dataset.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'name': self._serialize.url("name", name, '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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.delete(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
unregister_dataset.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{name}'}
def upload_dataset_artifact(
self, subscription_id, resource_group_name, workspace_name, dataset_id, dataset_artifact_dto=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param dataset_artifact_dto:
:type dataset_artifact_dto: ~_restclient.models.DatasetArtifactDto
: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>`.
:return: str or ClientRawResponse if raw=true
:rtype: str or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.upload_dataset_artifact.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_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-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataset_artifact_dto is not None:
body_content = self._serialize.body(dataset_artifact_dto, 'DatasetArtifactDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('str', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
upload_dataset_artifact.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/artifacts'}
def get_profile(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version_id, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version_id:
:type version_id: str
: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>`.
:return: ProfileActionResultDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.ProfileActionResultDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_profile.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'versionId': self._serialize.url("version_id", version_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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ProfileActionResultDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_profile.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions/{versionId}/profile'}
def generate_profile(
self, subscription_id, resource_group_name, workspace_name, dataset_id, version_id, compute_target=None, generate_preview=False, row_count=1000, pip_arguments=None, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param version_id:
:type version_id: str
:param compute_target:
:type compute_target: str
:param generate_preview:
:type generate_preview: bool
:param row_count:
:type row_count: int
:param pip_arguments:
:type pip_arguments: list[str]
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.generate_profile.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'versionId': self._serialize.url("version_id", version_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if compute_target is not None:
query_parameters['computeTarget'] = self._serialize.query("compute_target", compute_target, 'str')
if generate_preview is not None:
query_parameters['generatePreview'] = self._serialize.query("generate_preview", generate_preview, 'bool')
if row_count is not None:
query_parameters['rowCount'] = self._serialize.query("row_count", row_count, 'int')
if pip_arguments is not None:
query_parameters['pipArguments'] = self._serialize.query("pip_arguments", pip_arguments, '[str]', div=',')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
generate_profile.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/definitions/{versionId}/profile'}
def get_all_dataset_snapshots(
self, subscription_id, resource_group_name, workspace_name, dataset_id, continuation_token=None, page_size=None, custom_headers=None, raw=False, **operation_config):
"""GetAllDatasetSnapshots.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param continuation_token:
:type continuation_token: str
:param page_size:
:type page_size: int
: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>`.
:return: PaginatedResultDatasetSnapshotDto or ClientRawResponse if
raw=true
:rtype: ~_restclient.models.PaginatedResultDatasetSnapshotDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_all_dataset_snapshots.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if continuation_token is not None:
query_parameters['continuationToken'] = self._serialize.query("continuation_token", continuation_token, 'str')
if page_size is not None:
query_parameters['pageSize'] = self._serialize.query("page_size", page_size, 'int')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('PaginatedResultDatasetSnapshotDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_all_dataset_snapshots.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/datasetSnapshots'}
def create_dataset_snapshot(
self, subscription_id, resource_group_name, workspace_name, dataset_id, request=None, if_exists_ok=True, custom_headers=None, raw=False, **operation_config):
"""CreateDatasetSnapshot.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param request:
:type request: ~_restclient.models.DatasetSnapshotRequestDto
:param if_exists_ok:
:type if_exists_ok: bool
: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>`.
:return: DatasetSnapshotDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetSnapshotDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.create_dataset_snapshot.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if if_exists_ok is not None:
query_parameters['ifExistsOk'] = self._serialize.query("if_exists_ok", if_exists_ok, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request is not None:
body_content = self._serialize.body(request, 'DatasetSnapshotRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetSnapshotDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
create_dataset_snapshot.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/datasetSnapshots'}
def get_dataset_snapshot(
self, subscription_id, resource_group_name, workspace_name, dataset_id, dataset_snapshot_name, custom_headers=None, raw=False, **operation_config):
"""GetDatasetSnapshot.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param dataset_snapshot_name:
:type dataset_snapshot_name: str
: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>`.
:return: DatasetSnapshotDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.DatasetSnapshotDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_dataset_snapshot.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'datasetSnapshotName': self._serialize.url("dataset_snapshot_name", dataset_snapshot_name, '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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('DatasetSnapshotDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_dataset_snapshot.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/datasetSnapshots/{datasetSnapshotName}'}
def delete_dataset_snapshot(
self, subscription_id, resource_group_name, workspace_name, dataset_id, dataset_snapshot_name, custom_headers=None, raw=False, **operation_config):
"""DeleteDatasetSnapshot.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset_id:
:type dataset_id: str
:param dataset_snapshot_name:
:type dataset_snapshot_name: str
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.delete_dataset_snapshot.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'datasetId': self._serialize.url("dataset_id", dataset_id, 'str'),
'datasetSnapshotName': self._serialize.url("dataset_snapshot_name", dataset_snapshot_name, '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 custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.delete(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
delete_dataset_snapshot.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetId}/datasetSnapshots/{datasetSnapshotName}'}
def list_open_datasets(
self, subscription_id, resource_group_name, workspace_name, page_size=None, custom_headers=None, raw=False, **operation_config):
"""List.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param page_size:
:type page_size: int
: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>`.
:return: list or ClientRawResponse if raw=true
:rtype: list[~_restclient.models.DatasetRegistryDto] or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.list_open_datasets.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if page_size is not None:
query_parameters['pageSize'] = self._serialize.query("page_size", page_size, 'int')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('[DatasetRegistryDto]', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
list_open_datasets.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/openDatasets'}
def ensure_saved(
self, subscription_id, resource_group_name, workspace_name, dataset=None, with_data_hash=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param dataset:
:type dataset: ~_restclient.models.SavedDatasetDto
:param with_data_hash:
:type with_data_hash: bool
: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>`.
:return: SavedDatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.SavedDatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.ensure_saved.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if with_data_hash is not None:
query_parameters['withDataHash'] = self._serialize.query("with_data_hash", with_data_hash, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if dataset is not None:
body_content = self._serialize.body(dataset, 'SavedDatasetDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('SavedDatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
ensure_saved.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/saveddatasets'}
def ensure_saved_from_request(
self, subscription_id, resource_group_name, workspace_name, request=None, with_data_hash=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param request:
:type request: ~_restclient.models.DatasetRequestDto
:param with_data_hash:
:type with_data_hash: bool
: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>`.
:return: SavedDatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.SavedDatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.ensure_saved_from_request.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if with_data_hash is not None:
query_parameters['withDataHash'] = self._serialize.query("with_data_hash", with_data_hash, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if request is not None:
body_content = self._serialize.body(request, 'DatasetRequestDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('SavedDatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
ensure_saved_from_request.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/saveddatasets/from-request'}
def ensure_saved_from_data_path(
self, subscription_id, resource_group_name, workspace_name, data_path_dto=None, with_data_hash=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param data_path_dto:
:type data_path_dto: ~_restclient.models.DataPathDto
:param with_data_hash:
:type with_data_hash: bool
: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>`.
:return: SavedDatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.SavedDatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.ensure_saved_from_data_path.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if with_data_hash is not None:
query_parameters['withDataHash'] = self._serialize.query("with_data_hash", with_data_hash, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json-patch+json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
if data_path_dto is not None:
body_content = self._serialize.body(data_path_dto, 'DataPathDto')
else:
body_content = None
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('SavedDatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
ensure_saved_from_data_path.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/saveddatasets/from-data-path'}
def get_by_id(
self, subscription_id, resource_group_name, workspace_name, id, check_data_hash=False, resolve_legacy_id=False, custom_headers=None, raw=False, **operation_config):
"""
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param id:
:type id: str
:param check_data_hash:
:type check_data_hash: bool
:param resolve_legacy_id:
:type resolve_legacy_id: bool
: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>`.
:return: SavedDatasetDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.SavedDatasetDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_by_id.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'id': self._serialize.url("id", id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if check_data_hash is not None:
query_parameters['checkDataHash'] = self._serialize.query("check_data_hash", check_data_hash, 'bool')
if resolve_legacy_id is not None:
query_parameters['resolveLegacyId'] = self._serialize.query("resolve_legacy_id", resolve_legacy_id, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('SavedDatasetDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_by_id.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/saveddatasets/{id}'}
def ping(
self, custom_headers=None, raw=False, **operation_config):
"""alive.
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.ping.metadata['url']
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
ping.metadata = {'url': '/dataset/v1.0/meta/ping'}
def ping1(
self, custom_headers=None, raw=False, **operation_config):
"""alive.
: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>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.ping1.metadata['url']
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
ping1.metadata = {'url': '/dataset/v1.0/meta/alive'}
def get_service_version_metadata(
self, custom_headers=None, raw=False, **operation_config):
"""version.
: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>`.
:return: MetaApiVersionResponse or ClientRawResponse if raw=true
:rtype: ~_restclient.models.MetaApiVersionResponse or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.get_service_version_metadata.metadata['url']
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('MetaApiVersionResponse', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
get_service_version_metadata.metadata = {'url': '/dataset/v1.0/meta/version'}
def generate_profile_with_preview(
self, subscription_id, resource_group_name, workspace_name, id, compute_target, experiment_name=None, run_id=None, pip_arguments=None, custom_headers=None, raw=False, **operation_config):
"""GenerateProfileWithPreview.
:param subscription_id:
:type subscription_id: str
:param resource_group_name:
:type resource_group_name: str
:param workspace_name:
:type workspace_name: str
:param id:
:type id: str
:param compute_target:
:type compute_target: str
:param experiment_name:
:type experiment_name: str
:param run_id:
:type run_id: str
:param pip_arguments:
:type pip_arguments: list[str]
: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>`.
:return: ActionDto or ClientRawResponse if raw=true
:rtype: ~_restclient.models.ActionDto or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.generate_profile_with_preview.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("subscription_id", subscription_id, 'str'),
'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'),
'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'),
'id': self._serialize.url("id", id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['computeTarget'] = self._serialize.query("compute_target", compute_target, 'str')
if experiment_name is not None:
query_parameters['experimentName'] = self._serialize.query("experiment_name", experiment_name, 'str')
if run_id is not None:
query_parameters['runId'] = self._serialize.query("run_id", run_id, 'str')
if pip_arguments is not None:
query_parameters['pipArguments'] = self._serialize.query("pip_arguments", pip_arguments, '[str]', div=',')
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.post(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('ActionDto', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
generate_profile_with_preview.metadata = {'url': '/dataset/v1.0/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/saveddatasets/{id}/profilewithpreview'}
| 45.75897
| 275
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0
| 7
|
0e465250d5b6be7700ea37063d7cc04c9d530aeb
| 18,338
|
py
|
Python
|
sdk/python/pulumi_azure/bot/channel_teams.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/bot/channel_teams.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/bot/channel_teams.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__ = ['ChannelTeamsArgs', 'ChannelTeams']
@pulumi.input_type
class ChannelTeamsArgs:
def __init__(__self__, *,
bot_name: pulumi.Input[str],
resource_group_name: pulumi.Input[str],
calling_web_hook: Optional[pulumi.Input[str]] = None,
enable_calling: Optional[pulumi.Input[bool]] = None,
location: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a ChannelTeams resource.
:param pulumi.Input[str] bot_name: The name of the Bot Resource this channel will be associated with. Changing this forces a new resource to be created.
:param pulumi.Input[str] resource_group_name: The name of the resource group in which to create the Bot Channel. Changing this forces a new resource to be created.
:param pulumi.Input[str] calling_web_hook: Specifies the webhook for Microsoft Teams channel calls.
:param pulumi.Input[bool] enable_calling: Specifies whether to enable Microsoft Teams channel calls. This defaults to `false`.
:param pulumi.Input[str] location: The supported Azure location where the resource exists. Changing this forces a new resource to be created.
"""
pulumi.set(__self__, "bot_name", bot_name)
pulumi.set(__self__, "resource_group_name", resource_group_name)
if calling_web_hook is not None:
pulumi.set(__self__, "calling_web_hook", calling_web_hook)
if enable_calling is not None:
pulumi.set(__self__, "enable_calling", enable_calling)
if location is not None:
pulumi.set(__self__, "location", location)
@property
@pulumi.getter(name="botName")
def bot_name(self) -> pulumi.Input[str]:
"""
The name of the Bot Resource this channel will be associated with. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "bot_name")
@bot_name.setter
def bot_name(self, value: pulumi.Input[str]):
pulumi.set(self, "bot_name", value)
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> pulumi.Input[str]:
"""
The name of the resource group in which to create the Bot Channel. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "resource_group_name")
@resource_group_name.setter
def resource_group_name(self, value: pulumi.Input[str]):
pulumi.set(self, "resource_group_name", value)
@property
@pulumi.getter(name="callingWebHook")
def calling_web_hook(self) -> Optional[pulumi.Input[str]]:
"""
Specifies the webhook for Microsoft Teams channel calls.
"""
return pulumi.get(self, "calling_web_hook")
@calling_web_hook.setter
def calling_web_hook(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "calling_web_hook", value)
@property
@pulumi.getter(name="enableCalling")
def enable_calling(self) -> Optional[pulumi.Input[bool]]:
"""
Specifies whether to enable Microsoft Teams channel calls. This defaults to `false`.
"""
return pulumi.get(self, "enable_calling")
@enable_calling.setter
def enable_calling(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "enable_calling", value)
@property
@pulumi.getter
def location(self) -> Optional[pulumi.Input[str]]:
"""
The supported Azure location where the resource exists. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "location")
@location.setter
def location(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "location", value)
@pulumi.input_type
class _ChannelTeamsState:
def __init__(__self__, *,
bot_name: Optional[pulumi.Input[str]] = None,
calling_web_hook: Optional[pulumi.Input[str]] = None,
enable_calling: Optional[pulumi.Input[bool]] = None,
location: Optional[pulumi.Input[str]] = None,
resource_group_name: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering ChannelTeams resources.
:param pulumi.Input[str] bot_name: The name of the Bot Resource this channel will be associated with. Changing this forces a new resource to be created.
:param pulumi.Input[str] calling_web_hook: Specifies the webhook for Microsoft Teams channel calls.
:param pulumi.Input[bool] enable_calling: Specifies whether to enable Microsoft Teams channel calls. This defaults to `false`.
:param pulumi.Input[str] location: The supported Azure location where the resource exists. Changing this forces a new resource to be created.
:param pulumi.Input[str] resource_group_name: The name of the resource group in which to create the Bot Channel. Changing this forces a new resource to be created.
"""
if bot_name is not None:
pulumi.set(__self__, "bot_name", bot_name)
if calling_web_hook is not None:
pulumi.set(__self__, "calling_web_hook", calling_web_hook)
if enable_calling is not None:
pulumi.set(__self__, "enable_calling", enable_calling)
if location is not None:
pulumi.set(__self__, "location", location)
if resource_group_name is not None:
pulumi.set(__self__, "resource_group_name", resource_group_name)
@property
@pulumi.getter(name="botName")
def bot_name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the Bot Resource this channel will be associated with. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "bot_name")
@bot_name.setter
def bot_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "bot_name", value)
@property
@pulumi.getter(name="callingWebHook")
def calling_web_hook(self) -> Optional[pulumi.Input[str]]:
"""
Specifies the webhook for Microsoft Teams channel calls.
"""
return pulumi.get(self, "calling_web_hook")
@calling_web_hook.setter
def calling_web_hook(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "calling_web_hook", value)
@property
@pulumi.getter(name="enableCalling")
def enable_calling(self) -> Optional[pulumi.Input[bool]]:
"""
Specifies whether to enable Microsoft Teams channel calls. This defaults to `false`.
"""
return pulumi.get(self, "enable_calling")
@enable_calling.setter
def enable_calling(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "enable_calling", value)
@property
@pulumi.getter
def location(self) -> Optional[pulumi.Input[str]]:
"""
The supported Azure location where the resource exists. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "location")
@location.setter
def location(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "location", value)
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the resource group in which to create the Bot Channel. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "resource_group_name")
@resource_group_name.setter
def resource_group_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "resource_group_name", value)
class ChannelTeams(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
bot_name: Optional[pulumi.Input[str]] = None,
calling_web_hook: Optional[pulumi.Input[str]] = None,
enable_calling: Optional[pulumi.Input[bool]] = None,
location: Optional[pulumi.Input[str]] = None,
resource_group_name: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
Manages a MS Teams integration for a Bot Channel
> **Note** A bot can only have a single MS Teams Channel associated with it.
## Example Usage
```python
import pulumi
import pulumi_azure as azure
current = azure.core.get_client_config()
example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe")
example_channels_registration = azure.bot.ChannelsRegistration("exampleChannelsRegistration",
location="global",
resource_group_name=example_resource_group.name,
sku="F0",
microsoft_app_id=current.client_id)
example_channel_teams = azure.bot.ChannelTeams("exampleChannelTeams",
bot_name=example_channels_registration.name,
location=example_channels_registration.location,
resource_group_name=example_resource_group.name)
```
## Import
The Microsoft Teams Integration for a Bot Channel can be imported using the `resource id`, e.g.
```sh
$ pulumi import azure:bot/channelTeams:ChannelTeams example /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/example/providers/Microsoft.BotService/botServices/example/channels/MsTeamsChannel
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] bot_name: The name of the Bot Resource this channel will be associated with. Changing this forces a new resource to be created.
:param pulumi.Input[str] calling_web_hook: Specifies the webhook for Microsoft Teams channel calls.
:param pulumi.Input[bool] enable_calling: Specifies whether to enable Microsoft Teams channel calls. This defaults to `false`.
:param pulumi.Input[str] location: The supported Azure location where the resource exists. Changing this forces a new resource to be created.
:param pulumi.Input[str] resource_group_name: The name of the resource group in which to create the Bot Channel. Changing this forces a new resource to be created.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: ChannelTeamsArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
Manages a MS Teams integration for a Bot Channel
> **Note** A bot can only have a single MS Teams Channel associated with it.
## Example Usage
```python
import pulumi
import pulumi_azure as azure
current = azure.core.get_client_config()
example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe")
example_channels_registration = azure.bot.ChannelsRegistration("exampleChannelsRegistration",
location="global",
resource_group_name=example_resource_group.name,
sku="F0",
microsoft_app_id=current.client_id)
example_channel_teams = azure.bot.ChannelTeams("exampleChannelTeams",
bot_name=example_channels_registration.name,
location=example_channels_registration.location,
resource_group_name=example_resource_group.name)
```
## Import
The Microsoft Teams Integration for a Bot Channel can be imported using the `resource id`, e.g.
```sh
$ pulumi import azure:bot/channelTeams:ChannelTeams example /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/example/providers/Microsoft.BotService/botServices/example/channels/MsTeamsChannel
```
:param str resource_name: The name of the resource.
:param ChannelTeamsArgs 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(ChannelTeamsArgs, 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,
bot_name: Optional[pulumi.Input[str]] = None,
calling_web_hook: Optional[pulumi.Input[str]] = None,
enable_calling: Optional[pulumi.Input[bool]] = None,
location: Optional[pulumi.Input[str]] = None,
resource_group_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__ = ChannelTeamsArgs.__new__(ChannelTeamsArgs)
if bot_name is None and not opts.urn:
raise TypeError("Missing required property 'bot_name'")
__props__.__dict__["bot_name"] = bot_name
__props__.__dict__["calling_web_hook"] = calling_web_hook
__props__.__dict__["enable_calling"] = enable_calling
__props__.__dict__["location"] = location
if resource_group_name is None and not opts.urn:
raise TypeError("Missing required property 'resource_group_name'")
__props__.__dict__["resource_group_name"] = resource_group_name
super(ChannelTeams, __self__).__init__(
'azure:bot/channelTeams:ChannelTeams',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
bot_name: Optional[pulumi.Input[str]] = None,
calling_web_hook: Optional[pulumi.Input[str]] = None,
enable_calling: Optional[pulumi.Input[bool]] = None,
location: Optional[pulumi.Input[str]] = None,
resource_group_name: Optional[pulumi.Input[str]] = None) -> 'ChannelTeams':
"""
Get an existing ChannelTeams 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] bot_name: The name of the Bot Resource this channel will be associated with. Changing this forces a new resource to be created.
:param pulumi.Input[str] calling_web_hook: Specifies the webhook for Microsoft Teams channel calls.
:param pulumi.Input[bool] enable_calling: Specifies whether to enable Microsoft Teams channel calls. This defaults to `false`.
:param pulumi.Input[str] location: The supported Azure location where the resource exists. Changing this forces a new resource to be created.
:param pulumi.Input[str] resource_group_name: The name of the resource group in which to create the Bot Channel. Changing this forces a new resource to be created.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _ChannelTeamsState.__new__(_ChannelTeamsState)
__props__.__dict__["bot_name"] = bot_name
__props__.__dict__["calling_web_hook"] = calling_web_hook
__props__.__dict__["enable_calling"] = enable_calling
__props__.__dict__["location"] = location
__props__.__dict__["resource_group_name"] = resource_group_name
return ChannelTeams(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter(name="botName")
def bot_name(self) -> pulumi.Output[str]:
"""
The name of the Bot Resource this channel will be associated with. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "bot_name")
@property
@pulumi.getter(name="callingWebHook")
def calling_web_hook(self) -> pulumi.Output[str]:
"""
Specifies the webhook for Microsoft Teams channel calls.
"""
return pulumi.get(self, "calling_web_hook")
@property
@pulumi.getter(name="enableCalling")
def enable_calling(self) -> pulumi.Output[Optional[bool]]:
"""
Specifies whether to enable Microsoft Teams channel calls. This defaults to `false`.
"""
return pulumi.get(self, "enable_calling")
@property
@pulumi.getter
def location(self) -> pulumi.Output[str]:
"""
The supported Azure location where the resource exists. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "location")
@property
@pulumi.getter(name="resourceGroupName")
def resource_group_name(self) -> pulumi.Output[str]:
"""
The name of the resource group in which to create the Bot Channel. Changing this forces a new resource to be created.
"""
return pulumi.get(self, "resource_group_name")
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| 218
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| 0.847042
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| 0.824548
| 0.812919
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| 0
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| 0
| 0
| 1
| 0.156863
| false
| 0.004902
| 0.02451
| 0
| 0.27451
| 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
|
0e6af7edf806e9b9af758413097e67c353d31fd0
| 182
|
py
|
Python
|
invisible_hand/__init__.py
|
Naetw/invisible-hand
|
a77d88a40ed8afb30be2247f0827230c7c3d48f2
|
[
"MIT"
] | null | null | null |
invisible_hand/__init__.py
|
Naetw/invisible-hand
|
a77d88a40ed8afb30be2247f0827230c7c3d48f2
|
[
"MIT"
] | null | null | null |
invisible_hand/__init__.py
|
Naetw/invisible-hand
|
a77d88a40ed8afb30be2247f0827230c7c3d48f2
|
[
"MIT"
] | 1
|
2020-10-07T21:37:43.000Z
|
2020-10-07T21:37:43.000Z
|
from .config.github import init_constants as github_init_constants
from .config.gsheet import init_constants as gsheet_init_constants
github_init_constants()
gsheet_init_constants()
| 36.4
| 66
| 0.879121
| 26
| 182
| 5.769231
| 0.307692
| 0.52
| 0.253333
| 0.28
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.076923
| 182
| 5
| 67
| 36.4
| 0.892857
| 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
|
0e6b621f04eebf94f66049c73f8281c46bd83b28
| 5,002
|
py
|
Python
|
Word-Puzzle-Solver(v2.0).py
|
Gordon24771402/WordMint-Puzzles-Solver
|
4695765549823bfe59ac445dcbd8b6f901d73de3
|
[
"MIT"
] | null | null | null |
Word-Puzzle-Solver(v2.0).py
|
Gordon24771402/WordMint-Puzzles-Solver
|
4695765549823bfe59ac445dcbd8b6f901d73de3
|
[
"MIT"
] | null | null | null |
Word-Puzzle-Solver(v2.0).py
|
Gordon24771402/WordMint-Puzzles-Solver
|
4695765549823bfe59ac445dcbd8b6f901d73de3
|
[
"MIT"
] | null | null | null |
import numpy as np
# 01: Capture Data
data = []
print('Copy and Paste: ')
while True:
row = input()
if row == '':
break
data.append(row.upper().split(' '))
data = np.array(data)
# 02: Return Word
while True:
wordExpect = input("Enter a Word: ").upper()
if wordExpect == '':
break
startIndex = np.where(data == wordExpect[0])
# Left
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x][y - i]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x][y - i] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
# Right
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x][y + i]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x][y + i] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
# Up
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x - i][y]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x - i][y] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
# Down
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x + i][y]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x + i][y] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
# Up-Left
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x - i][y - i]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x - i][y - i] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
# Up-Right
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x - i][y + i]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x - i][y + i] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
# Down-Left
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x + i][y - i]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x + i][y - i] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
# Down-Right
for mainCoordinate in range(len(startIndex[0])):
x = startIndex[0][mainCoordinate]
y = startIndex[1][mainCoordinate]
wordSearch = ''
try:
for i in range(len(wordExpect)):
wordSearch += data[x + i][y + i]
if wordSearch == wordExpect:
answer = data.copy()
for i in range(len(wordExpect)):
answer[x + i][y + i] = '*'
for x in answer:
print(" ".join(map(str, x)))
except:
wordSearch = ''
| 30.315152
| 52
| 0.464414
| 508
| 5,002
| 4.572835
| 0.098425
| 0.07232
| 0.103315
| 0.075764
| 0.907878
| 0.907878
| 0.907878
| 0.907878
| 0.907878
| 0.907878
| 0
| 0.009817
| 0.409436
| 5,002
| 164
| 53
| 30.5
| 0.776574
| 0.017793
| 0
| 0.80597
| 0
| 0
| 0.00959
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.007463
| 0
| 0.007463
| 0.067164
| 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
|
7eec785d83b3c690a18e615075412f04085c6305
| 262
|
py
|
Python
|
textattack/goal_functions/__init__.py
|
srujanjoshi/TextAttack
|
b86d0f840b6f13b1eb8d0f17b3fceeeca62b08ed
|
[
"MIT"
] | null | null | null |
textattack/goal_functions/__init__.py
|
srujanjoshi/TextAttack
|
b86d0f840b6f13b1eb8d0f17b3fceeeca62b08ed
|
[
"MIT"
] | null | null | null |
textattack/goal_functions/__init__.py
|
srujanjoshi/TextAttack
|
b86d0f840b6f13b1eb8d0f17b3fceeeca62b08ed
|
[
"MIT"
] | 1
|
2022-03-06T22:41:03.000Z
|
2022-03-06T22:41:03.000Z
|
""".. _goal_functions:
Goal Functions
==================================================================
Goal Functions determine if an attack has been successful.
"""
from .goal_function import GoalFunction
from .classification import *
from .text import *
| 20.153846
| 66
| 0.572519
| 24
| 262
| 6.125
| 0.625
| 0.265306
| 0.231293
| 0.353742
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.118321
| 262
| 12
| 67
| 21.833333
| 0.636364
| 0.618321
| 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
| 0
| 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
|
7efe4b45cc3fa0a47cc72f148337bc852ca4e2fd
| 2,257
|
py
|
Python
|
tools/fileinfo/bugs/huge-memory-consumption/test.py
|
xbabka01/retdec-regression-tests
|
1ac40cca5165740364e6f7fb72b20820eac9bc7c
|
[
"MIT"
] | 8
|
2017-12-14T14:25:17.000Z
|
2019-03-09T03:29:12.000Z
|
tools/fileinfo/bugs/huge-memory-consumption/test.py
|
xbabka01/retdec-regression-tests
|
1ac40cca5165740364e6f7fb72b20820eac9bc7c
|
[
"MIT"
] | 10
|
2019-06-14T09:12:55.000Z
|
2021-10-01T12:15:43.000Z
|
tools/fileinfo/bugs/huge-memory-consumption/test.py
|
xbabka01/retdec-regression-tests
|
1ac40cca5165740364e6f7fb72b20820eac9bc7c
|
[
"MIT"
] | 8
|
2019-05-10T14:59:48.000Z
|
2022-03-07T16:34:23.000Z
|
from regression_tests import *
class InvalidCoffStringTableTest1(Test):
settings=TestSettings(
tool='fileinfo',
args='--json --verbose',
input='rc7.ex'
)
def test(self):
assert self.fileinfo.succeeded
self.assertEqual(self.fileinfo.output['sectionTable']['numberOfSections'], '20')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][3]['name'], '/4')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][9]['name'], '/14')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][10]['name'], '/29')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][11]['name'], '/41')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][12]['name'], '/55')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][13]['name'], '/67')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][14]['name'], '/80')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][15]['name'], '/91')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][16]['name'], '/102')
class InvalidCoffStringTableTest2(Test):
settings=TestSettings(
tool='fileinfo',
args='--json --verbose',
input='NitroTyper_ver_1.3_64_bit.ex'
)
def test(self):
assert self.fileinfo.succeeded
self.assertEqual(self.fileinfo.output['sectionTable']['numberOfSections'], '18')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][9]['name'], '/4')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][10]['name'], '/19')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][11]['name'], '/31')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][12]['name'], '/45')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][13]['name'], '/57')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][14]['name'], '/70')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][15]['name'], '/81')
self.assertEqual(self.fileinfo.output['sectionTable']['sections'][16]['name'], '/92')
| 55.04878
| 94
| 0.650421
| 235
| 2,257
| 6.225532
| 0.251064
| 0.172249
| 0.246753
| 0.350649
| 0.898838
| 0.898838
| 0.898838
| 0.862611
| 0.862611
| 0.138072
| 0
| 0.038521
| 0.13735
| 2,257
| 40
| 95
| 56.425
| 0.712892
| 0
| 0
| 0.277778
| 0
| 0
| 0.26584
| 0.012406
| 0
| 0
| 0
| 0
| 0.583333
| 1
| 0.055556
| false
| 0
| 0.027778
| 0
| 0.194444
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 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
| 8
|
7d160d25b4f85f437606caa563293f50903135bf
| 234
|
py
|
Python
|
pidal/connection_delegate.py
|
pi-plan/pidal
|
bfd1b9c4de87bc92565acbcff108270265757e39
|
[
"BSD-3-Clause"
] | 6
|
2021-02-05T04:21:00.000Z
|
2021-11-29T06:46:21.000Z
|
pidal/connection_delegate.py
|
pi-plan/pidal
|
bfd1b9c4de87bc92565acbcff108270265757e39
|
[
"BSD-3-Clause"
] | 1
|
2021-11-30T06:08:53.000Z
|
2021-11-30T06:08:53.000Z
|
pidal/connection_delegate.py
|
pi-plan/pidal
|
bfd1b9c4de87bc92565acbcff108270265757e39
|
[
"BSD-3-Clause"
] | null | null | null |
import abc
class ConnectionDelegate(metaclass=abc.ABCMeta):
@abc.abstractmethod
def on_close():
pass
@abc.abstractmethod
def on_send():
pass
@abc.abstractmethod
def on_recv():
pass
| 13.764706
| 48
| 0.619658
| 25
| 234
| 5.68
| 0.52
| 0.359155
| 0.422535
| 0.464789
| 0.366197
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.294872
| 234
| 16
| 49
| 14.625
| 0.860606
| 0
| 0
| 0.545455
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.272727
| true
| 0.272727
| 0.090909
| 0
| 0.454545
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
7d301a9e613a14afa8f623b90e9fb2ae7e9c5128
| 480
|
py
|
Python
|
palindrome/palindrome_test.py
|
mamaz/learn-stuffs-with-python
|
2677203717bb5ddc30b0a907b8e38a9c9c7f8015
|
[
"MIT"
] | null | null | null |
palindrome/palindrome_test.py
|
mamaz/learn-stuffs-with-python
|
2677203717bb5ddc30b0a907b8e38a9c9c7f8015
|
[
"MIT"
] | null | null | null |
palindrome/palindrome_test.py
|
mamaz/learn-stuffs-with-python
|
2677203717bb5ddc30b0a907b8e38a9c9c7f8015
|
[
"MIT"
] | null | null | null |
from palindrome import is_palindrome
def test_palindrome_true():
assert is_palindrome("kasurusak") == True
def test_palindrome_madam():
assert is_palindrome("madam") == True
def test_palindrome_racecar():
assert is_palindrome("racecar") == True
def test_palindrome_empty():
assert is_palindrome("") == True
def test_palindrome_single_letter():
assert is_palindrome("a") == True
def test_palindrome_false():
assert is_palindrome("anatabaka") == False
| 24
| 46
| 0.741667
| 59
| 480
| 5.694915
| 0.288136
| 0.25
| 0.303571
| 0.3125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.145833
| 480
| 19
| 47
| 25.263158
| 0.819512
| 0
| 0
| 0
| 0
| 0
| 0.064583
| 0
| 0
| 0
| 0
| 0
| 0.461538
| 1
| 0.461538
| true
| 0
| 0.076923
| 0
| 0.538462
| 0
| 0
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 7
|
ada67fc41da3fbf8b6249909e55330f2319908ea
| 1,487
|
py
|
Python
|
venv/lib/python2.7/site-packages/pychart/afm/Palatino_Roman.py
|
Christian-Castro/castro_odoo8
|
8247fdb20aa39e043b6fa0c4d0af509462ab3e00
|
[
"Unlicense"
] | 1
|
2019-12-19T01:53:13.000Z
|
2019-12-19T01:53:13.000Z
|
venv/lib/python2.7/site-packages/pychart/afm/Palatino_Roman.py
|
Christian-Castro/castro_odoo8
|
8247fdb20aa39e043b6fa0c4d0af509462ab3e00
|
[
"Unlicense"
] | null | null | null |
venv/lib/python2.7/site-packages/pychart/afm/Palatino_Roman.py
|
Christian-Castro/castro_odoo8
|
8247fdb20aa39e043b6fa0c4d0af509462ab3e00
|
[
"Unlicense"
] | null | null | null |
# AFM font Palatino-Roman (path: /usr/share/fonts/afms/adobe/pplr8a.afm).
# Derived from Ghostscript distribution.
# Go to www.cs.wisc.edu/~ghost to get the Ghostcript source code.
import dir
dir.afm["Palatino-Roman"] = (500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 250, 278, 371, 500, 500, 840, 778, 278, 333, 333, 389, 606, 250, 333, 250, 606, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 250, 250, 606, 606, 606, 444, 747, 778, 611, 709, 774, 611, 556, 763, 832, 337, 333, 726, 611, 946, 831, 786, 604, 786, 668, 525, 613, 778, 722, 1000, 667, 667, 667, 333, 606, 333, 606, 500, 278, 500, 553, 444, 611, 479, 333, 556, 582, 291, 234, 556, 291, 883, 582, 546, 601, 560, 395, 424, 326, 603, 565, 834, 516, 556, 500, 333, 606, 333, 606, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 278, 500, 500, 167, 500, 500, 500, 500, 208, 500, 500, 331, 331, 605, 608, 500, 500, 500, 500, 250, 500, 628, 606, 278, 500, 500, 500, 1000, 1144, 500, 444, 500, 333, 333, 333, 333, 333, 333, 250, 333, 500, 333, 333, 500, 380, 313, 333, 1000, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 944, 500, 333, 500, 500, 500, 500, 611, 833, 998, 333, 500, 500, 500, 500, 500, 758, 500, 500, 500, 287, 500, 500, 291, 556, 827, 556, )
| 247.833333
| 1,294
| 0.62273
| 287
| 1,487
| 3.226481
| 0.310105
| 0.706264
| 0.923326
| 1.101512
| 0.408207
| 0.311015
| 0.311015
| 0.311015
| 0.311015
| 0.311015
| 0
| 0.629446
| 0.186954
| 1,487
| 5
| 1,295
| 297.4
| 0.136476
| 0.117014
| 0
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0
| 10
|
70b46e66cce1ecf40d8183998c5e963f3a5a7dc5
| 18,895
|
py
|
Python
|
sdk/python/pulumi_alicloud/vpc/route_entry.py
|
pulumi/pulumi-alicloud
|
9c34d84b4588a7c885c6bec1f03b5016e5a41683
|
[
"ECL-2.0",
"Apache-2.0"
] | 42
|
2019-03-18T06:34:37.000Z
|
2022-03-24T07:08:57.000Z
|
sdk/python/pulumi_alicloud/vpc/route_entry.py
|
pulumi/pulumi-alicloud
|
9c34d84b4588a7c885c6bec1f03b5016e5a41683
|
[
"ECL-2.0",
"Apache-2.0"
] | 152
|
2019-04-15T21:03:44.000Z
|
2022-03-29T18:00:57.000Z
|
sdk/python/pulumi_alicloud/vpc/route_entry.py
|
pulumi/pulumi-alicloud
|
9c34d84b4588a7c885c6bec1f03b5016e5a41683
|
[
"ECL-2.0",
"Apache-2.0"
] | 3
|
2020-08-26T17:30:07.000Z
|
2021-07-05T01:37:45.000Z
|
# 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__ = ['RouteEntryArgs', 'RouteEntry']
@pulumi.input_type
class RouteEntryArgs:
def __init__(__self__, *,
route_table_id: pulumi.Input[str],
destination_cidrblock: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
nexthop_id: Optional[pulumi.Input[str]] = None,
nexthop_type: Optional[pulumi.Input[str]] = None,
router_id: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a RouteEntry resource.
:param pulumi.Input[str] route_table_id: The ID of the route table.
:param pulumi.Input[str] destination_cidrblock: The RouteEntry's target network segment.
:param pulumi.Input[str] name: The name of the route entry. This name can have a string of 2 to 128 characters, must contain only alphanumeric characters or hyphens, such as "-",".","_", and must not begin or end with a hyphen, and must not begin with http:// or https://.
:param pulumi.Input[str] nexthop_id: The route entry's next hop. ECS instance ID or VPC router interface ID.
:param pulumi.Input[str] nexthop_type: The next hop type. Available values:
:param pulumi.Input[str] router_id: This argument has beeb deprecated. Please use other arguments to launch a custom route entry.
"""
pulumi.set(__self__, "route_table_id", route_table_id)
if destination_cidrblock is not None:
pulumi.set(__self__, "destination_cidrblock", destination_cidrblock)
if name is not None:
pulumi.set(__self__, "name", name)
if nexthop_id is not None:
pulumi.set(__self__, "nexthop_id", nexthop_id)
if nexthop_type is not None:
pulumi.set(__self__, "nexthop_type", nexthop_type)
if router_id is not None:
warnings.warn("""Attribute router_id has been deprecated and suggest removing it from your template.""", DeprecationWarning)
pulumi.log.warn("""router_id is deprecated: Attribute router_id has been deprecated and suggest removing it from your template.""")
if router_id is not None:
pulumi.set(__self__, "router_id", router_id)
@property
@pulumi.getter(name="routeTableId")
def route_table_id(self) -> pulumi.Input[str]:
"""
The ID of the route table.
"""
return pulumi.get(self, "route_table_id")
@route_table_id.setter
def route_table_id(self, value: pulumi.Input[str]):
pulumi.set(self, "route_table_id", value)
@property
@pulumi.getter(name="destinationCidrblock")
def destination_cidrblock(self) -> Optional[pulumi.Input[str]]:
"""
The RouteEntry's target network segment.
"""
return pulumi.get(self, "destination_cidrblock")
@destination_cidrblock.setter
def destination_cidrblock(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "destination_cidrblock", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the route entry. This name can have a string of 2 to 128 characters, must contain only alphanumeric characters or hyphens, such as "-",".","_", and must not begin or end with a hyphen, and must not begin with http:// or https://.
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter(name="nexthopId")
def nexthop_id(self) -> Optional[pulumi.Input[str]]:
"""
The route entry's next hop. ECS instance ID or VPC router interface ID.
"""
return pulumi.get(self, "nexthop_id")
@nexthop_id.setter
def nexthop_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "nexthop_id", value)
@property
@pulumi.getter(name="nexthopType")
def nexthop_type(self) -> Optional[pulumi.Input[str]]:
"""
The next hop type. Available values:
"""
return pulumi.get(self, "nexthop_type")
@nexthop_type.setter
def nexthop_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "nexthop_type", value)
@property
@pulumi.getter(name="routerId")
def router_id(self) -> Optional[pulumi.Input[str]]:
"""
This argument has beeb deprecated. Please use other arguments to launch a custom route entry.
"""
return pulumi.get(self, "router_id")
@router_id.setter
def router_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "router_id", value)
@pulumi.input_type
class _RouteEntryState:
def __init__(__self__, *,
destination_cidrblock: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
nexthop_id: Optional[pulumi.Input[str]] = None,
nexthop_type: Optional[pulumi.Input[str]] = None,
route_table_id: Optional[pulumi.Input[str]] = None,
router_id: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering RouteEntry resources.
:param pulumi.Input[str] destination_cidrblock: The RouteEntry's target network segment.
:param pulumi.Input[str] name: The name of the route entry. This name can have a string of 2 to 128 characters, must contain only alphanumeric characters or hyphens, such as "-",".","_", and must not begin or end with a hyphen, and must not begin with http:// or https://.
:param pulumi.Input[str] nexthop_id: The route entry's next hop. ECS instance ID or VPC router interface ID.
:param pulumi.Input[str] nexthop_type: The next hop type. Available values:
:param pulumi.Input[str] route_table_id: The ID of the route table.
:param pulumi.Input[str] router_id: This argument has beeb deprecated. Please use other arguments to launch a custom route entry.
"""
if destination_cidrblock is not None:
pulumi.set(__self__, "destination_cidrblock", destination_cidrblock)
if name is not None:
pulumi.set(__self__, "name", name)
if nexthop_id is not None:
pulumi.set(__self__, "nexthop_id", nexthop_id)
if nexthop_type is not None:
pulumi.set(__self__, "nexthop_type", nexthop_type)
if route_table_id is not None:
pulumi.set(__self__, "route_table_id", route_table_id)
if router_id is not None:
warnings.warn("""Attribute router_id has been deprecated and suggest removing it from your template.""", DeprecationWarning)
pulumi.log.warn("""router_id is deprecated: Attribute router_id has been deprecated and suggest removing it from your template.""")
if router_id is not None:
pulumi.set(__self__, "router_id", router_id)
@property
@pulumi.getter(name="destinationCidrblock")
def destination_cidrblock(self) -> Optional[pulumi.Input[str]]:
"""
The RouteEntry's target network segment.
"""
return pulumi.get(self, "destination_cidrblock")
@destination_cidrblock.setter
def destination_cidrblock(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "destination_cidrblock", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
The name of the route entry. This name can have a string of 2 to 128 characters, must contain only alphanumeric characters or hyphens, such as "-",".","_", and must not begin or end with a hyphen, and must not begin with http:// or https://.
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter(name="nexthopId")
def nexthop_id(self) -> Optional[pulumi.Input[str]]:
"""
The route entry's next hop. ECS instance ID or VPC router interface ID.
"""
return pulumi.get(self, "nexthop_id")
@nexthop_id.setter
def nexthop_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "nexthop_id", value)
@property
@pulumi.getter(name="nexthopType")
def nexthop_type(self) -> Optional[pulumi.Input[str]]:
"""
The next hop type. Available values:
"""
return pulumi.get(self, "nexthop_type")
@nexthop_type.setter
def nexthop_type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "nexthop_type", value)
@property
@pulumi.getter(name="routeTableId")
def route_table_id(self) -> Optional[pulumi.Input[str]]:
"""
The ID of the route table.
"""
return pulumi.get(self, "route_table_id")
@route_table_id.setter
def route_table_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "route_table_id", value)
@property
@pulumi.getter(name="routerId")
def router_id(self) -> Optional[pulumi.Input[str]]:
"""
This argument has beeb deprecated. Please use other arguments to launch a custom route entry.
"""
return pulumi.get(self, "router_id")
@router_id.setter
def router_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "router_id", value)
class RouteEntry(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
destination_cidrblock: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
nexthop_id: Optional[pulumi.Input[str]] = None,
nexthop_type: Optional[pulumi.Input[str]] = None,
route_table_id: Optional[pulumi.Input[str]] = None,
router_id: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
## Import
Router entry can be imported using the id, e.g (formatted as<route_table_id:router_id:destination_cidrblock:nexthop_type:nexthop_id>).
```sh
$ pulumi import alicloud:vpc/routeEntry:RouteEntry example vtb-123456:vrt-123456:0.0.0.0/0:NatGateway:ngw-123456
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] destination_cidrblock: The RouteEntry's target network segment.
:param pulumi.Input[str] name: The name of the route entry. This name can have a string of 2 to 128 characters, must contain only alphanumeric characters or hyphens, such as "-",".","_", and must not begin or end with a hyphen, and must not begin with http:// or https://.
:param pulumi.Input[str] nexthop_id: The route entry's next hop. ECS instance ID or VPC router interface ID.
:param pulumi.Input[str] nexthop_type: The next hop type. Available values:
:param pulumi.Input[str] route_table_id: The ID of the route table.
:param pulumi.Input[str] router_id: This argument has beeb deprecated. Please use other arguments to launch a custom route entry.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: RouteEntryArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
## Import
Router entry can be imported using the id, e.g (formatted as<route_table_id:router_id:destination_cidrblock:nexthop_type:nexthop_id>).
```sh
$ pulumi import alicloud:vpc/routeEntry:RouteEntry example vtb-123456:vrt-123456:0.0.0.0/0:NatGateway:ngw-123456
```
:param str resource_name: The name of the resource.
:param RouteEntryArgs 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(RouteEntryArgs, 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,
destination_cidrblock: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
nexthop_id: Optional[pulumi.Input[str]] = None,
nexthop_type: Optional[pulumi.Input[str]] = None,
route_table_id: Optional[pulumi.Input[str]] = None,
router_id: 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__ = RouteEntryArgs.__new__(RouteEntryArgs)
__props__.__dict__["destination_cidrblock"] = destination_cidrblock
__props__.__dict__["name"] = name
__props__.__dict__["nexthop_id"] = nexthop_id
__props__.__dict__["nexthop_type"] = nexthop_type
if route_table_id is None and not opts.urn:
raise TypeError("Missing required property 'route_table_id'")
__props__.__dict__["route_table_id"] = route_table_id
if router_id is not None and not opts.urn:
warnings.warn("""Attribute router_id has been deprecated and suggest removing it from your template.""", DeprecationWarning)
pulumi.log.warn("""router_id is deprecated: Attribute router_id has been deprecated and suggest removing it from your template.""")
__props__.__dict__["router_id"] = router_id
super(RouteEntry, __self__).__init__(
'alicloud:vpc/routeEntry:RouteEntry',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
destination_cidrblock: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
nexthop_id: Optional[pulumi.Input[str]] = None,
nexthop_type: Optional[pulumi.Input[str]] = None,
route_table_id: Optional[pulumi.Input[str]] = None,
router_id: Optional[pulumi.Input[str]] = None) -> 'RouteEntry':
"""
Get an existing RouteEntry 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] destination_cidrblock: The RouteEntry's target network segment.
:param pulumi.Input[str] name: The name of the route entry. This name can have a string of 2 to 128 characters, must contain only alphanumeric characters or hyphens, such as "-",".","_", and must not begin or end with a hyphen, and must not begin with http:// or https://.
:param pulumi.Input[str] nexthop_id: The route entry's next hop. ECS instance ID or VPC router interface ID.
:param pulumi.Input[str] nexthop_type: The next hop type. Available values:
:param pulumi.Input[str] route_table_id: The ID of the route table.
:param pulumi.Input[str] router_id: This argument has beeb deprecated. Please use other arguments to launch a custom route entry.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _RouteEntryState.__new__(_RouteEntryState)
__props__.__dict__["destination_cidrblock"] = destination_cidrblock
__props__.__dict__["name"] = name
__props__.__dict__["nexthop_id"] = nexthop_id
__props__.__dict__["nexthop_type"] = nexthop_type
__props__.__dict__["route_table_id"] = route_table_id
__props__.__dict__["router_id"] = router_id
return RouteEntry(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter(name="destinationCidrblock")
def destination_cidrblock(self) -> pulumi.Output[Optional[str]]:
"""
The RouteEntry's target network segment.
"""
return pulumi.get(self, "destination_cidrblock")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
The name of the route entry. This name can have a string of 2 to 128 characters, must contain only alphanumeric characters or hyphens, such as "-",".","_", and must not begin or end with a hyphen, and must not begin with http:// or https://.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="nexthopId")
def nexthop_id(self) -> pulumi.Output[Optional[str]]:
"""
The route entry's next hop. ECS instance ID or VPC router interface ID.
"""
return pulumi.get(self, "nexthop_id")
@property
@pulumi.getter(name="nexthopType")
def nexthop_type(self) -> pulumi.Output[Optional[str]]:
"""
The next hop type. Available values:
"""
return pulumi.get(self, "nexthop_type")
@property
@pulumi.getter(name="routeTableId")
def route_table_id(self) -> pulumi.Output[str]:
"""
The ID of the route table.
"""
return pulumi.get(self, "route_table_id")
@property
@pulumi.getter(name="routerId")
def router_id(self) -> pulumi.Output[str]:
"""
This argument has beeb deprecated. Please use other arguments to launch a custom route entry.
"""
return pulumi.get(self, "router_id")
| 46.654321
| 280
| 0.651707
| 2,380
| 18,895
| 4.960504
| 0.081513
| 0.076402
| 0.094867
| 0.095036
| 0.865323
| 0.845587
| 0.833644
| 0.825682
| 0.817805
| 0.796629
| 0
| 0.005262
| 0.245621
| 18,895
| 404
| 281
| 46.769802
| 0.822997
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| 0
| 0.771784
| 1
| 0
| 0.137454
| 0.018577
| 0
| 0
| 0
| 0
| 0
| 1
| 0.153527
| false
| 0.004149
| 0.020747
| 0
| 0.26556
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
70c964f4d7d2e3baafd3157790682d3ed855d3e8
| 4,477
|
py
|
Python
|
yalr/tests/test_associativity_2.py
|
jan-g/python-yalr
|
9491d7bd99c64a34e7722919c137466e71bf781b
|
[
"Apache-2.0"
] | null | null | null |
yalr/tests/test_associativity_2.py
|
jan-g/python-yalr
|
9491d7bd99c64a34e7722919c137466e71bf781b
|
[
"Apache-2.0"
] | null | null | null |
yalr/tests/test_associativity_2.py
|
jan-g/python-yalr
|
9491d7bd99c64a34e7722919c137466e71bf781b
|
[
"Apache-2.0"
] | null | null | null |
""" More complex tests of associativity
A grammar with + and * (left and right assoc resp)
cannot be simply resolved: reduce/reduce error.
A grammar with + and * (both left assoc)
should give rise to a reduce/reduce error also.
A grammar with a higher-precedence *
(left or right assoc) should resolve correctly.
"""
import pytest
from .. import LR1, GrammarError
from .test_associativity import make_l
def make_g(Grammar=LR1, compile=True, assoc=None):
g = Grammar()
if assoc is not None:
assoc(g)
n = g.nt
@n.E(str)
def _(id):
return id
@n.E(n.E, '+', n.E)
def plus(e1, _, e2):
return "({} + {})".format(e1, e2)
@n.E(n.E, '*', n.E)
def splat(e1, _, e2):
return "({} * {})".format(e1, e2)
if compile:
g.compile(start=n.E)
return g
def test_non_assoc_equal():
l = make_l() # noqa
def assoc(g):
g.nonassoc('+', '*')
g = make_g(assoc=assoc)
with pytest.raises(GrammarError):
assert g.parse(l.lex("a + b + c")) == '(a + (b + c))'
with pytest.raises(GrammarError):
assert g.parse(l.lex("a * b + c")) == '(a * (b + c))'
with pytest.raises(GrammarError):
assert g.parse(l.lex("a + b * c")) == '(a + (b * c))'
with pytest.raises(GrammarError):
assert g.parse(l.lex("a * b * c")) == '(a * (b * c))'
def test_non_assoc_higher():
l = make_l() # noqa
def assoc(g):
g.nonassoc('+')
g.nonassoc('*')
g = make_g(assoc=assoc)
with pytest.raises(GrammarError):
assert g.parse(l.lex("a + b + c")) == '(a + b + c)'
assert g.parse(l.lex("a * b + c")) == '((a * b) + c)'
assert g.parse(l.lex("a + b * c")) == '(a + (b * c))'
with pytest.raises(GrammarError):
assert g.parse(l.lex("a * b * c")) == '(a * b * c)'
def test_non_assoc_lower():
l = make_l() # noqa
def assoc(g):
g.nonassoc('*')
g.nonassoc('+')
g = make_g(assoc=assoc)
with pytest.raises(GrammarError):
assert g.parse(l.lex("a + b + c")) == '(a + b + c)'
assert g.parse(l.lex("a * b + c")) == '(a * (b + c))'
assert g.parse(l.lex("a + b * c")) == '((a + b) * c)'
with pytest.raises(GrammarError):
assert g.parse(l.lex("a * b * c")) == '(a * b * c)'
def test_right_equal():
l = make_l()
def assoc(g):
g.right('+', '*')
g = make_g(assoc=assoc)
assert g.parse(l.lex("a + b + c")) == '(a + (b + c))'
assert g.parse(l.lex("a * b + c")) == '(a * (b + c))'
assert g.parse(l.lex("a + b * c")) == '(a + (b * c))'
assert g.parse(l.lex("a * b * c")) == '(a * (b * c))'
def test_left_equal():
l = make_l()
def assoc(g):
g.left('+', '*')
g = make_g(assoc=assoc)
assert g.parse(l.lex("a + b + c")) == '((a + b) + c)'
assert g.parse(l.lex("a * b + c")) == '((a * b) + c)'
assert g.parse(l.lex("a + b * c")) == '((a + b) * c)'
assert g.parse(l.lex("a * b * c")) == '((a * b) * c)'
def test_right_higher():
l = make_l()
def assoc(g):
g.left('+')
g.right('*')
g = make_g(assoc=assoc)
assert g.parse(l.lex("a + b + c")) == '((a + b) + c)'
assert g.parse(l.lex("a * b + c")) == '((a * b) + c)'
assert g.parse(l.lex("a + b * c")) == '(a + (b * c))'
assert g.parse(l.lex("a * b * c")) == '(a * (b * c))'
def test_left_higher():
l = make_l()
def assoc(g):
g.left('+')
g.left('*')
g = make_g(assoc=assoc)
assert g.parse(l.lex("a + b + c")) == '((a + b) + c)'
assert g.parse(l.lex("a * b + c")) == '((a * b) + c)'
assert g.parse(l.lex("a + b * c")) == '(a + (b * c))'
assert g.parse(l.lex("a * b * c")) == '((a * b) * c)'
def test_right_lower():
l = make_l()
def assoc(g):
g.right('*')
g.left('+')
g = make_g(assoc=assoc)
assert g.parse(l.lex("a + b + c")) == '((a + b) + c)'
assert g.parse(l.lex("a * b + c")) == '(a * (b + c))'
assert g.parse(l.lex("a + b * c")) == '((a + b) * c)'
assert g.parse(l.lex("a * b * c")) == '(a * (b * c))'
def test_left_lower():
l = make_l()
def assoc(g):
g.left('*')
g.left('+')
g = make_g(assoc=assoc)
assert g.parse(l.lex("a + b + c")) == '((a + b) + c)'
assert g.parse(l.lex("a * b + c")) == '(a * (b + c))'
assert g.parse(l.lex("a + b * c")) == '((a + b) * c)'
assert g.parse(l.lex("a * b * c")) == '((a * b) * c)'
| 23.81383
| 61
| 0.470851
| 726
| 4,477
| 2.841598
| 0.095041
| 0.069801
| 0.104702
| 0.226854
| 0.772661
| 0.772661
| 0.753272
| 0.744547
| 0.734852
| 0.710131
| 0
| 0.003136
| 0.287693
| 4,477
| 187
| 62
| 23.941176
| 0.643775
| 0.07304
| 0
| 0.721739
| 0
| 0
| 0.199708
| 0
| 0
| 0
| 0
| 0
| 0.313043
| 1
| 0.191304
| false
| 0
| 0.026087
| 0.026087
| 0.252174
| 0
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
cb0e6147fbfdb8c9e0ab1d58227ef1ba214e11a2
| 966
|
py
|
Python
|
tools/conan/conans/test/model/scope_test.py
|
aversiveplusplus/aversiveplusplus
|
5f5fe9faca50197fd6207e2c816efa7e9af6c804
|
[
"BSD-3-Clause"
] | 29
|
2016-01-27T09:43:44.000Z
|
2020-03-12T04:16:02.000Z
|
tools/conan/conans/test/model/scope_test.py
|
aversiveplusplus/aversiveplusplus
|
5f5fe9faca50197fd6207e2c816efa7e9af6c804
|
[
"BSD-3-Clause"
] | 20
|
2016-01-22T15:59:33.000Z
|
2016-10-28T10:22:45.000Z
|
tools/conan/conans/test/model/scope_test.py
|
aversiveplusplus/aversiveplusplus
|
5f5fe9faca50197fd6207e2c816efa7e9af6c804
|
[
"BSD-3-Clause"
] | 6
|
2016-02-11T14:09:04.000Z
|
2018-03-17T00:18:35.000Z
|
import unittest
from conans.model.scope import Scopes
class ScopeTest(unittest.TestCase):
def from_list_test(self):
scope = Scopes.from_list(["theroot:thescope=http://conan.io"])
self.assertEquals(scope["theroot"]["thescope"], "http://conan.io")
self.assertEquals(scope.package_scope("theroot")["thescope"], "http://conan.io")
scope = Scopes.from_list(["thescope=http://conan.io"])
self.assertEquals(scope["0CONAN_ROOT*"]["thescope"], "http://conan.io")
scope = Scopes.from_list(["theroot:thescope=TRUE"])
self.assertTrue(scope["theroot"]["thescope"])
scope = Scopes.from_list(["theroot:thescope=true"])
self.assertTrue(scope["theroot"]["thescope"])
scope = Scopes.from_list(["theroot:thescope=FALSE"])
self.assertFalse(scope["theroot"]["thescope"])
scope = Scopes.from_list(["theroot:thescope=false"])
self.assertFalse(scope["theroot"]["thescope"])
| 37.153846
| 88
| 0.658385
| 109
| 966
| 5.743119
| 0.247706
| 0.263578
| 0.14377
| 0.182109
| 0.821086
| 0.821086
| 0.771566
| 0.707668
| 0.466454
| 0.466454
| 0
| 0.001232
| 0.15942
| 966
| 25
| 89
| 38.64
| 0.769704
| 0
| 0
| 0.235294
| 0
| 0
| 0.307453
| 0.089027
| 0
| 0
| 0
| 0
| 0.411765
| 1
| 0.058824
| false
| 0
| 0.117647
| 0
| 0.235294
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 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
| 7
|
cb292176baea3242d0e9625d942dba6db5400d7c
| 6,193
|
py
|
Python
|
zfit/core/tensorlike.py
|
nsahoo/zfit
|
fcad2578f31138f5383f7fa5de6c0f8c6b1dbaa4
|
[
"BSD-3-Clause"
] | 129
|
2018-03-24T22:27:55.000Z
|
2022-03-19T21:04:07.000Z
|
zfit/core/tensorlike.py
|
nsahoo/zfit
|
fcad2578f31138f5383f7fa5de6c0f8c6b1dbaa4
|
[
"BSD-3-Clause"
] | 195
|
2018-03-22T11:31:47.000Z
|
2022-03-29T17:01:45.000Z
|
zfit/core/tensorlike.py
|
nsahoo/zfit
|
fcad2578f31138f5383f7fa5de6c0f8c6b1dbaa4
|
[
"BSD-3-Clause"
] | 45
|
2018-03-22T10:12:31.000Z
|
2022-02-01T10:45:27.000Z
|
# Copyright (c) 2021 zfit
import functools
import tensorflow as tf
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from zfit.core import interfaces as zinterfaces
def register_tensor_conversion(convertable, name=None, overload_operators=True,
priority=10): # higher than any tf conversion
def _dense_var_to_tensor(var, dtype=None, name=None, as_ref=False):
return var._dense_var_to_tensor(dtype=dtype, name=name, as_ref=as_ref)
ops.register_tensor_conversion_function(convertable, _dense_var_to_tensor, priority=priority)
if name:
pass
# _pywrap_utils.RegisterType(name, convertable)
if overload_operators:
convertable._OverloadAllOperators(cls=convertable)
class OverloadableMixin:
# Conversion to tensor.
@staticmethod
def _TensorConversionFunction(v, dtype=None, name=None, as_ref=False): # pylint: disable=invalid-name
"""Utility function for converting a Variable to a Tensor."""
_ = name
if dtype and not dtype.is_compatible_with(v.dtype):
raise ValueError(
"Incompatible type conversion requested to type '%s' for variable "
"of type '%s'" % (dtype.name, v.dtype.name))
if as_ref:
return v._ref() # pylint: disable=protected-access
else:
return v.value()
def _dense_var_to_tensor(self, dtype=None, name=None, as_ref=False):
del name
if dtype and not dtype.is_compatible_with(self.dtype):
raise ValueError(
"Incompatible type conversion requested to type '%s' for variable "
"of type '%s'" % (dtype.name, self.dtype.name))
if as_ref:
if hasattr(self, '_ref'):
return self._ref()
else:
raise RuntimeError("Why is this needed?")
else:
return self.value()
def _AsTensor(self):
return self.value()
@staticmethod
def _OverloadAllOperators(cls): # pylint: disable=invalid-name
"""Register overloads for all operators."""
for operator in tf.Tensor.OVERLOADABLE_OPERATORS:
cls._OverloadOperator(cls, operator)
# For slicing, bind getitem differently than a tensor (use SliceHelperVar
# instead)
# pylint: disable=protected-access
setattr(cls, "__getitem__", array_ops._SliceHelperVar)
@staticmethod
def _OverloadOperator(cls, operator): # pylint: disable=invalid-name
"""Defer an operator overload to `ops.Tensor`.
We pull the operator out of ops.Tensor dynamically to avoid ordering issues.
Args:
operator: string. The operator name.
"""
# We can't use the overload mechanism on __eq__ & __ne__ since __eq__ is
# called when adding a variable to sets. As a result we call a.value() which
# causes infinite recursion when operating within a GradientTape
# TODO(gjn): Consider removing this
if operator == "__eq__" or operator == "__ne__":
return
tensor_oper = getattr(tf.Tensor, operator)
def _run_op(a, *args, **kwargs):
# pylint: disable=protected-access
return tensor_oper(a.value(), *args, **kwargs)
functools.update_wrapper(_run_op, tensor_oper)
setattr(cls, operator, _run_op)
class OverloadableMixinValues:
# Conversion to tensor.
@staticmethod
def _TensorConversionFunction(v, dtype=None, name=None, as_ref=False): # pylint: disable=invalid-name
"""Utility function for converting a Variable to a Tensor."""
_ = name
if dtype and not dtype.is_compatible_with(v.dtype):
raise ValueError(
"Incompatible type conversion requested to type '%s' for variable "
"of type '%s'" % (dtype.name, v.dtype.name))
if as_ref:
return v._ref() # pylint: disable=protected-access
else:
return v.values()
def _dense_var_to_tensor(self, dtype=None, name=None, as_ref=False):
del name
if dtype and not dtype.is_compatible_with(self.dtype):
raise ValueError(
"Incompatible type conversion requested to type '%s' for variable "
"of type '%s'" % (dtype.name, self.dtype.name))
if as_ref:
if hasattr(self, '_ref'):
return self._ref()
else:
raise RuntimeError("Why is this needed?")
else:
return self.values()
def _AsTensor(self):
return self.values()
@staticmethod
def _OverloadAllOperators(cls): # pylint: disable=invalid-name
"""Register overloads for all operators."""
for operator in tf.Tensor.OVERLOADABLE_OPERATORS:
cls._OverloadOperator(cls, operator)
# For slicing, bind getitem differently than a tensor (use SliceHelperVar
# instead)
# pylint: disable=protected-access
setattr(cls, "__getitem__", array_ops._SliceHelperVar)
@staticmethod
def _OverloadOperator(cls, operator): # pylint: disable=invalid-name
"""Defer an operator overload to `ops.Tensor`.
We pull the operator out of ops.Tensor dynamically to avoid ordering issues.
Args:
operator: string. The operator name.
"""
# We can't use the overload mechanism on __eq__ & __ne__ since __eq__ is
# called when adding a variable to sets. As a result we call a.value() which
# causes infinite recursion when operating within a GradientTape
# TODO(gjn): Consider removing this
if operator == "__eq__" or operator == "__ne__":
return
tensor_oper = getattr(tf.Tensor, operator)
def _run_op(a, *args, **kwargs):
# pylint: disable=protected-access
return tensor_oper(a.values(), *args, **kwargs)
functools.update_wrapper(_run_op, tensor_oper)
setattr(cls, operator, _run_op)
class MetaBaseParameter(type(tf.Variable), type(zinterfaces.ZfitParameter)): # resolve metaclasses
pass
| 38.228395
| 106
| 0.637978
| 726
| 6,193
| 5.246556
| 0.203857
| 0.040956
| 0.031504
| 0.037805
| 0.819638
| 0.801523
| 0.801523
| 0.794434
| 0.794434
| 0.794434
| 0
| 0.001335
| 0.274342
| 6,193
| 161
| 107
| 38.465839
| 0.846239
| 0.275634
| 0
| 0.795918
| 0
| 0
| 0.091743
| 0
| 0
| 0
| 0
| 0.012422
| 0
| 1
| 0.142857
| false
| 0.020408
| 0.05102
| 0.05102
| 0.377551
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
cb2c53d7f80df1c4ccf42bbeabec5f35f41ccad6
| 46,196
|
py
|
Python
|
Netconf/bindings/bindingConfiguration.py
|
lrodrin/transceivers
|
62b8e44c0a459615a0464a9567e28e195c4dabf1
|
[
"MIT"
] | null | null | null |
Netconf/bindings/bindingConfiguration.py
|
lrodrin/transceivers
|
62b8e44c0a459615a0464a9567e28e195c4dabf1
|
[
"MIT"
] | null | null | null |
Netconf/bindings/bindingConfiguration.py
|
lrodrin/transceivers
|
62b8e44c0a459615a0464a9567e28e195c4dabf1
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from operator import attrgetter
from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType
from pyangbind.lib.yangtypes import RestrictedClassType
from pyangbind.lib.yangtypes import TypedListType
from pyangbind.lib.yangtypes import YANGBool
from pyangbind.lib.yangtypes import YANGListType
from pyangbind.lib.yangtypes import YANGDynClass
from pyangbind.lib.yangtypes import ReferenceType
from pyangbind.lib.base import PybindBase
from collections import OrderedDict
from decimal import Decimal
from bitarray import bitarray
import six
# PY3 support of some PY2 keywords (needs improved)
if six.PY3:
import builtins as __builtin__
long = int
elif six.PY2:
import __builtin__
class yc_constellation_blueSPACE_DRoF_configuration__DRoF_configuration_constellation(PybindBase):
"""
This class was auto-generated by the PythonClass plugin for PYANG
from YANG module blueSPACE-DRoF-configuration - based on the path /DRoF-configuration/constellation. Each member element of
the container is represented as a class variable - with a specific
YANG type.
"""
__slots__ = ('_path_helper', '_extmethods', '__subcarrier_id','__bitsxsymbol','__powerxsymbol',)
_yang_name = 'constellation'
_yang_namespace = 'urn:blueSPACE-DRoF-configuration'
_pybind_generated_by = 'container'
def __init__(self, *args, **kwargs):
self._path_helper = False
self._extmethods = False
self.__powerxsymbol = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="powerxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
self.__subcarrier_id = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
self.__bitsxsymbol = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="bitsxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
load = kwargs.pop("load", None)
if args:
if len(args) > 1:
raise TypeError("cannot create a YANG container with >1 argument")
all_attr = True
for e in self._pyangbind_elements:
if not hasattr(args[0], e):
all_attr = False
break
if not all_attr:
raise ValueError("Supplied object did not have the correct attributes")
for e in self._pyangbind_elements:
nobj = getattr(args[0], e)
if nobj._changed() is False:
continue
setmethod = getattr(self, "_set_%s" % e)
if load is None:
setmethod(getattr(args[0], e))
else:
setmethod(getattr(args[0], e), load=load)
def _path(self):
if hasattr(self, "_parent"):
return self._parent._path()+[self._yang_name]
else:
return ['DRoF-configuration', 'constellation']
def _get_subcarrier_id(self):
"""
Getter method for subcarrier_id, mapped from YANG variable /DRoF_configuration/constellation/subcarrier_id (string)
"""
return self.__subcarrier_id
def _set_subcarrier_id(self, v, load=False):
"""
Setter method for subcarrier_id, mapped from YANG variable /DRoF_configuration/constellation/subcarrier_id (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_subcarrier_id is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_subcarrier_id() directly.
"""
parent = getattr(self, "_parent", None)
if parent is not None and load is False:
raise AttributeError("Cannot set keys directly when" +
" within an instantiated list")
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """subcarrier_id must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)""",
})
self.__subcarrier_id = t
if hasattr(self, '_set'):
self._set()
def _unset_subcarrier_id(self):
self.__subcarrier_id = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
def _get_bitsxsymbol(self):
"""
Getter method for bitsxsymbol, mapped from YANG variable /DRoF_configuration/constellation/bitsxsymbol (string)
"""
return self.__bitsxsymbol
def _set_bitsxsymbol(self, v, load=False):
"""
Setter method for bitsxsymbol, mapped from YANG variable /DRoF_configuration/constellation/bitsxsymbol (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_bitsxsymbol is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_bitsxsymbol() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="bitsxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """bitsxsymbol must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="bitsxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)""",
})
self.__bitsxsymbol = t
if hasattr(self, '_set'):
self._set()
def _unset_bitsxsymbol(self):
self.__bitsxsymbol = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="bitsxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
def _get_powerxsymbol(self):
"""
Getter method for powerxsymbol, mapped from YANG variable /DRoF_configuration/constellation/powerxsymbol (string)
"""
return self.__powerxsymbol
def _set_powerxsymbol(self, v, load=False):
"""
Setter method for powerxsymbol, mapped from YANG variable /DRoF_configuration/constellation/powerxsymbol (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_powerxsymbol is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_powerxsymbol() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="powerxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """powerxsymbol must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="powerxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)""",
})
self.__powerxsymbol = t
if hasattr(self, '_set'):
self._set()
def _unset_powerxsymbol(self):
self.__powerxsymbol = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="powerxsymbol", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
subcarrier_id = __builtin__.property(_get_subcarrier_id, _set_subcarrier_id)
bitsxsymbol = __builtin__.property(_get_bitsxsymbol, _set_bitsxsymbol)
powerxsymbol = __builtin__.property(_get_powerxsymbol, _set_powerxsymbol)
_pyangbind_elements = OrderedDict([('subcarrier_id', subcarrier_id), ('bitsxsymbol', bitsxsymbol), ('powerxsymbol', powerxsymbol), ])
class yc_monitor_blueSPACE_DRoF_configuration__DRoF_configuration_monitor(PybindBase):
"""
This class was auto-generated by the PythonClass plugin for PYANG
from YANG module blueSPACE-DRoF-configuration - based on the path /DRoF-configuration/monitor. Each member element of
the container is represented as a class variable - with a specific
YANG type.
"""
__slots__ = ('_path_helper', '_extmethods', '__subcarrier_id','__SNR',)
_yang_name = 'monitor'
_yang_namespace = 'urn:blueSPACE-DRoF-configuration'
_pybind_generated_by = 'container'
def __init__(self, *args, **kwargs):
self._path_helper = False
self._extmethods = False
self.__SNR = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="SNR", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
self.__subcarrier_id = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
load = kwargs.pop("load", None)
if args:
if len(args) > 1:
raise TypeError("cannot create a YANG container with >1 argument")
all_attr = True
for e in self._pyangbind_elements:
if not hasattr(args[0], e):
all_attr = False
break
if not all_attr:
raise ValueError("Supplied object did not have the correct attributes")
for e in self._pyangbind_elements:
nobj = getattr(args[0], e)
if nobj._changed() is False:
continue
setmethod = getattr(self, "_set_%s" % e)
if load is None:
setmethod(getattr(args[0], e))
else:
setmethod(getattr(args[0], e), load=load)
def _path(self):
if hasattr(self, "_parent"):
return self._parent._path()+[self._yang_name]
else:
return ['DRoF-configuration', 'monitor']
def _get_subcarrier_id(self):
"""
Getter method for subcarrier_id, mapped from YANG variable /DRoF_configuration/monitor/subcarrier_id (string)
"""
return self.__subcarrier_id
def _set_subcarrier_id(self, v, load=False):
"""
Setter method for subcarrier_id, mapped from YANG variable /DRoF_configuration/monitor/subcarrier_id (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_subcarrier_id is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_subcarrier_id() directly.
"""
parent = getattr(self, "_parent", None)
if parent is not None and load is False:
raise AttributeError("Cannot set keys directly when" +
" within an instantiated list")
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """subcarrier_id must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)""",
})
self.__subcarrier_id = t
if hasattr(self, '_set'):
self._set()
def _unset_subcarrier_id(self):
self.__subcarrier_id = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="subcarrier-id", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, is_keyval=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
def _get_SNR(self):
"""
Getter method for SNR, mapped from YANG variable /DRoF_configuration/monitor/SNR (string)
"""
return self.__SNR
def _set_SNR(self, v, load=False):
"""
Setter method for SNR, mapped from YANG variable /DRoF_configuration/monitor/SNR (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_SNR is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_SNR() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="SNR", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """SNR must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="SNR", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)""",
})
self.__SNR = t
if hasattr(self, '_set'):
self._set()
def _unset_SNR(self):
self.__SNR = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="SNR", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
subcarrier_id = __builtin__.property(_get_subcarrier_id)
SNR = __builtin__.property(_get_SNR)
_pyangbind_elements = OrderedDict([('subcarrier_id', subcarrier_id), ('SNR', SNR), ])
class yc_DRoF_configuration_blueSPACE_DRoF_configuration__DRoF_configuration(PybindBase):
"""
This class was auto-generated by the PythonClass plugin for PYANG
from YANG module blueSPACE-DRoF-configuration - based on the path /DRoF-configuration. Each member element of
the container is represented as a class variable - with a specific
YANG type.
"""
__slots__ = ('_path_helper', '_extmethods', '__status','__nominal_central_frequency','__constellation','__FEC','__equalization','__monitor','__BER',)
_yang_name = 'DRoF-configuration'
_yang_namespace = 'urn:blueSPACE-DRoF-configuration'
_pybind_generated_by = 'container'
def __init__(self, *args, **kwargs):
self._path_helper = False
self._extmethods = False
self.__monitor = YANGDynClass(base=YANGListType("subcarrier_id",yc_monitor_blueSPACE_DRoF_configuration__DRoF_configuration_monitor, yang_name="monitor", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="monitor", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)
self.__nominal_central_frequency = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="nominal-central-frequency", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
self.__equalization = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="equalization", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
self.__FEC = YANGDynClass(base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="FEC", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)
self.__constellation = YANGDynClass(base=YANGListType("subcarrier_id",yc_constellation_blueSPACE_DRoF_configuration__DRoF_configuration_constellation, yang_name="constellation", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="constellation", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)
self.__BER = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="BER", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
self.__status = YANGDynClass(base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'blueSPACE-DRoF-configuration:active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)
load = kwargs.pop("load", None)
if args:
if len(args) > 1:
raise TypeError("cannot create a YANG container with >1 argument")
all_attr = True
for e in self._pyangbind_elements:
if not hasattr(args[0], e):
all_attr = False
break
if not all_attr:
raise ValueError("Supplied object did not have the correct attributes")
for e in self._pyangbind_elements:
nobj = getattr(args[0], e)
if nobj._changed() is False:
continue
setmethod = getattr(self, "_set_%s" % e)
if load is None:
setmethod(getattr(args[0], e))
else:
setmethod(getattr(args[0], e), load=load)
def _path(self):
if hasattr(self, "_parent"):
return self._parent._path()+[self._yang_name]
else:
return ['DRoF-configuration']
def _get_status(self):
"""
Getter method for status, mapped from YANG variable /DRoF_configuration/status (identityref)
"""
return self.__status
def _set_status(self, v, load=False):
"""
Setter method for status, mapped from YANG variable /DRoF_configuration/status (identityref)
If this variable is read-only (config: false) in the
source YANG file, then _set_status is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_status() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'blueSPACE-DRoF-configuration:active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """status must be of a type compatible with identityref""",
'defined-type': "blueSPACE-DRoF-configuration:identityref",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'blueSPACE-DRoF-configuration:active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)""",
})
self.__status = t
if hasattr(self, '_set'):
self._set()
def _unset_status(self):
self.__status = YANGDynClass(base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'blueSPACE-DRoF-configuration:active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'active': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'standby': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'off': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="status", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)
def _get_nominal_central_frequency(self):
"""
Getter method for nominal_central_frequency, mapped from YANG variable /DRoF_configuration/nominal_central_frequency (string)
"""
return self.__nominal_central_frequency
def _set_nominal_central_frequency(self, v, load=False):
"""
Setter method for nominal_central_frequency, mapped from YANG variable /DRoF_configuration/nominal_central_frequency (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_nominal_central_frequency is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_nominal_central_frequency() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="nominal-central-frequency", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """nominal_central_frequency must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="nominal-central-frequency", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)""",
})
self.__nominal_central_frequency = t
if hasattr(self, '_set'):
self._set()
def _unset_nominal_central_frequency(self):
self.__nominal_central_frequency = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="nominal-central-frequency", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
def _get_constellation(self):
"""
Getter method for constellation, mapped from YANG variable /DRoF_configuration/constellation (list)
"""
return self.__constellation
def _set_constellation(self, v, load=False):
"""
Setter method for constellation, mapped from YANG variable /DRoF_configuration/constellation (list)
If this variable is read-only (config: false) in the
source YANG file, then _set_constellation is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_constellation() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=YANGListType("subcarrier_id",yc_constellation_blueSPACE_DRoF_configuration__DRoF_configuration_constellation, yang_name="constellation", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="constellation", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """constellation must be of a type compatible with list""",
'defined-type': "list",
'generated-type': """YANGDynClass(base=YANGListType("subcarrier_id",yc_constellation_blueSPACE_DRoF_configuration__DRoF_configuration_constellation, yang_name="constellation", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="constellation", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)""",
})
self.__constellation = t
if hasattr(self, '_set'):
self._set()
def _unset_constellation(self):
self.__constellation = YANGDynClass(base=YANGListType("subcarrier_id",yc_constellation_blueSPACE_DRoF_configuration__DRoF_configuration_constellation, yang_name="constellation", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="constellation", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)
def _get_FEC(self):
"""
Getter method for FEC, mapped from YANG variable /DRoF_configuration/FEC (identityref)
"""
return self.__FEC
def _set_FEC(self, v, load=False):
"""
Setter method for FEC, mapped from YANG variable /DRoF_configuration/FEC (identityref)
If this variable is read-only (config: false) in the
source YANG file, then _set_FEC is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_FEC() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="FEC", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """FEC must be of a type compatible with identityref""",
'defined-type': "blueSPACE-DRoF-configuration:identityref",
'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="FEC", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)""",
})
self.__FEC = t
if hasattr(self, '_set'):
self._set()
def _unset_FEC(self):
self.__FEC = YANGDynClass(base=RestrictedClassType(base_type=six.text_type, restriction_type="dict_key", restriction_arg={'SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:SD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'blueSPACE-DRoF-configuration:HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}, 'HD-FEC': {'@module': 'blueSPACE-DRoF-configuration', '@namespace': 'urn:blueSPACE-DRoF-configuration'}},), is_leaf=True, yang_name="FEC", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='identityref', is_config=True)
def _get_equalization(self):
"""
Getter method for equalization, mapped from YANG variable /DRoF_configuration/equalization (string)
"""
return self.__equalization
def _set_equalization(self, v, load=False):
"""
Setter method for equalization, mapped from YANG variable /DRoF_configuration/equalization (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_equalization is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_equalization() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="equalization", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """equalization must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="equalization", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)""",
})
self.__equalization = t
if hasattr(self, '_set'):
self._set()
def _unset_equalization(self):
self.__equalization = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="equalization", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=True)
def _get_monitor(self):
"""
Getter method for monitor, mapped from YANG variable /DRoF_configuration/monitor (list)
"""
return self.__monitor
def _set_monitor(self, v, load=False):
"""
Setter method for monitor, mapped from YANG variable /DRoF_configuration/monitor (list)
If this variable is read-only (config: false) in the
source YANG file, then _set_monitor is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_monitor() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=YANGListType("subcarrier_id",yc_monitor_blueSPACE_DRoF_configuration__DRoF_configuration_monitor, yang_name="monitor", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="monitor", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """monitor must be of a type compatible with list""",
'defined-type': "list",
'generated-type': """YANGDynClass(base=YANGListType("subcarrier_id",yc_monitor_blueSPACE_DRoF_configuration__DRoF_configuration_monitor, yang_name="monitor", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="monitor", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)""",
})
self.__monitor = t
if hasattr(self, '_set'):
self._set()
def _unset_monitor(self):
self.__monitor = YANGDynClass(base=YANGListType("subcarrier_id",yc_monitor_blueSPACE_DRoF_configuration__DRoF_configuration_monitor, yang_name="monitor", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='subcarrier-id', extensions=None), is_container='list', yang_name="monitor", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='list', is_config=True)
def _get_BER(self):
"""
Getter method for BER, mapped from YANG variable /DRoF_configuration/BER (string)
"""
return self.__BER
def _set_BER(self, v, load=False):
"""
Setter method for BER, mapped from YANG variable /DRoF_configuration/BER (string)
If this variable is read-only (config: false) in the
source YANG file, then _set_BER is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_BER() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=six.text_type, is_leaf=True, yang_name="BER", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
except (TypeError, ValueError):
raise ValueError({
'error-string': """BER must be of a type compatible with string""",
'defined-type': "string",
'generated-type': """YANGDynClass(base=six.text_type, is_leaf=True, yang_name="BER", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)""",
})
self.__BER = t
if hasattr(self, '_set'):
self._set()
def _unset_BER(self):
self.__BER = YANGDynClass(base=six.text_type, is_leaf=True, yang_name="BER", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='string', is_config=False)
status = __builtin__.property(_get_status, _set_status)
nominal_central_frequency = __builtin__.property(_get_nominal_central_frequency, _set_nominal_central_frequency)
constellation = __builtin__.property(_get_constellation, _set_constellation)
FEC = __builtin__.property(_get_FEC, _set_FEC)
equalization = __builtin__.property(_get_equalization, _set_equalization)
monitor = __builtin__.property(_get_monitor, _set_monitor)
BER = __builtin__.property(_get_BER)
_pyangbind_elements = OrderedDict([('status', status), ('nominal_central_frequency', nominal_central_frequency), ('constellation', constellation), ('FEC', FEC), ('equalization', equalization), ('monitor', monitor), ('BER', BER), ])
class blueSPACE_DRoF_configuration(PybindBase):
"""
This class was auto-generated by the PythonClass plugin for PYANG
from YANG module blueSPACE-DRoF-configuration - based on the path /blueSPACE-DRoF-configuration. Each member element of
the container is represented as a class variable - with a specific
YANG type.
YANG Description: Latest update to blueSPACE-DRoF-configuration YANG data model.
"""
__slots__ = ('_path_helper', '_extmethods', '__DRoF_configuration',)
_yang_name = 'blueSPACE-DRoF-configuration'
_yang_namespace = 'urn:blueSPACE-DRoF-configuration'
_pybind_generated_by = 'container'
def __init__(self, *args, **kwargs):
self._path_helper = False
self._extmethods = False
self.__DRoF_configuration = YANGDynClass(base=yc_DRoF_configuration_blueSPACE_DRoF_configuration__DRoF_configuration, is_container='container', yang_name="DRoF-configuration", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='container', is_config=True)
load = kwargs.pop("load", None)
if args:
if len(args) > 1:
raise TypeError("cannot create a YANG container with >1 argument")
all_attr = True
for e in self._pyangbind_elements:
if not hasattr(args[0], e):
all_attr = False
break
if not all_attr:
raise ValueError("Supplied object did not have the correct attributes")
for e in self._pyangbind_elements:
nobj = getattr(args[0], e)
if nobj._changed() is False:
continue
setmethod = getattr(self, "_set_%s" % e)
if load is None:
setmethod(getattr(args[0], e))
else:
setmethod(getattr(args[0], e), load=load)
def _path(self):
if hasattr(self, "_parent"):
return self._parent._path()+[self._yang_name]
else:
return []
def _get_DRoF_configuration(self):
"""
Getter method for DRoF_configuration, mapped from YANG variable /DRoF_configuration (container)
"""
return self.__DRoF_configuration
def _set_DRoF_configuration(self, v, load=False):
"""
Setter method for DRoF_configuration, mapped from YANG variable /DRoF_configuration (container)
If this variable is read-only (config: false) in the
source YANG file, then _set_DRoF_configuration is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_DRoF_configuration() directly.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=yc_DRoF_configuration_blueSPACE_DRoF_configuration__DRoF_configuration, is_container='container', yang_name="DRoF-configuration", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='container', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """DRoF_configuration must be of a type compatible with container""",
'defined-type': "container",
'generated-type': """YANGDynClass(base=yc_DRoF_configuration_blueSPACE_DRoF_configuration__DRoF_configuration, is_container='container', yang_name="DRoF-configuration", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='container', is_config=True)""",
})
self.__DRoF_configuration = t
if hasattr(self, '_set'):
self._set()
def _unset_DRoF_configuration(self):
self.__DRoF_configuration = YANGDynClass(base=yc_DRoF_configuration_blueSPACE_DRoF_configuration__DRoF_configuration, is_container='container', yang_name="DRoF-configuration", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions=None, namespace='urn:blueSPACE-DRoF-configuration', defining_module='blueSPACE-DRoF-configuration', yang_type='container', is_config=True)
DRoF_configuration = __builtin__.property(_get_DRoF_configuration, _set_DRoF_configuration)
_pyangbind_elements = OrderedDict([('DRoF_configuration', DRoF_configuration), ])
| 66.564841
| 1,122
| 0.745519
| 5,732
| 46,196
| 5.749302
| 0.035415
| 0.158883
| 0.183826
| 0.093218
| 0.916037
| 0.908967
| 0.908967
| 0.895069
| 0.889759
| 0.879078
| 0
| 0.000722
| 0.130336
| 46,196
| 693
| 1,123
| 66.660895
| 0.819564
| 0.148303
| 0
| 0.658768
| 0
| 0.030806
| 0.384144
| 0.235953
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111374
| false
| 0
| 0.035545
| 0
| 0.28436
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
cb35bb8f3b75f948a6e7b97e40b9143f7188f010
| 150
|
py
|
Python
|
chainerrl/envs/__init__.py
|
xinyuewang1/chainerrl
|
49425d09cb0749968f4e364e281670e752a46791
|
[
"MIT"
] | 923
|
2017-06-01T08:27:42.000Z
|
2022-03-24T02:17:04.000Z
|
chainerrl/envs/__init__.py
|
WhenTheyCry96/chainerrl
|
0f32aae2855dbb6288ae628be6271739ced6c42c
|
[
"MIT"
] | 374
|
2017-06-02T02:07:50.000Z
|
2021-06-29T22:05:38.000Z
|
chainerrl/envs/__init__.py
|
WhenTheyCry96/chainerrl
|
0f32aae2855dbb6288ae628be6271739ced6c42c
|
[
"MIT"
] | 253
|
2017-06-04T10:31:50.000Z
|
2022-03-19T15:20:51.000Z
|
from chainerrl.envs.multiprocess_vector_env import MultiprocessVectorEnv # NOQA
from chainerrl.envs.serial_vector_env import SerialVectorEnv # NOQA
| 50
| 80
| 0.866667
| 18
| 150
| 7
| 0.611111
| 0.206349
| 0.269841
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093333
| 150
| 2
| 81
| 75
| 0.926471
| 0.06
| 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
|
cb70c8469be2e69fd94befaa07f2b2e0d5cddc8e
| 121
|
py
|
Python
|
src/ctc/protocols/uniswap_v3_utils/__init__.py
|
fei-protocol/checkthechain
|
ec838f3d0d44af228f45394d9ba8d8eb7f677520
|
[
"MIT"
] | 94
|
2022-02-15T19:34:49.000Z
|
2022-03-26T19:26:22.000Z
|
src/ctc/protocols/uniswap_v3_utils/__init__.py
|
fei-protocol/checkthechain
|
ec838f3d0d44af228f45394d9ba8d8eb7f677520
|
[
"MIT"
] | 7
|
2022-03-03T02:58:47.000Z
|
2022-03-11T18:41:05.000Z
|
src/ctc/protocols/uniswap_v3_utils/__init__.py
|
fei-protocol/checkthechain
|
ec838f3d0d44af228f45394d9ba8d8eb7f677520
|
[
"MIT"
] | 7
|
2022-02-15T17:53:07.000Z
|
2022-03-17T19:14:17.000Z
|
from .uniswap_v3_crud import *
from .uniswap_v3_depth import *
from .uniswap_v3_spec import *
from .contracts import *
| 17.285714
| 31
| 0.785124
| 18
| 121
| 4.944444
| 0.444444
| 0.370787
| 0.438202
| 0.426966
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.029126
| 0.14876
| 121
| 6
| 32
| 20.166667
| 0.834951
| 0
| 0
| 0
| 0
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| 0
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| true
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| null | 1
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| 0
| 1
| 0
|
0
| 8
|
cb70d779edd1039a9d5655af9ed417ed89a74ef3
| 33,476
|
py
|
Python
|
misc/baxter/src_py_/JRzs.py
|
YoshimitsuMatsutaIe/rmp_test
|
a7c94ff68b518ef51821484795c308c2c8519c4c
|
[
"MIT"
] | null | null | null |
misc/baxter/src_py_/JRzs.py
|
YoshimitsuMatsutaIe/rmp_test
|
a7c94ff68b518ef51821484795c308c2c8519c4c
|
[
"MIT"
] | null | null | null |
misc/baxter/src_py_/JRzs.py
|
YoshimitsuMatsutaIe/rmp_test
|
a7c94ff68b518ef51821484795c308c2c8519c4c
|
[
"MIT"
] | null | null | null |
import numpy as np
from math import cos as c
from math import sin as s
from math import tan as ta
from math import sqrt as sq
def jrz_W0(q):
return numpy.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]])
def jrz_BR(q):
return numpy.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]])
def jrz_0(q):
return numpy.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]])
def jrz_1(q):
return numpy.array([[-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]), 0, 0, 0, 0, 0, 0], [0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]), 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]])
def jrz_2(q):
return numpy.array([[(0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0]), -(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0]), 0, 0, 0, 0, 0], [(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0]), -(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0]), 0, 0, 0, 0, 0], [0, -numpy.cos(q[1, 0]), 0, 0, 0, 0, 0]])
def jrz_3(q):
return numpy.array([[(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]), (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.cos(q[1, 0]), (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]), 0, 0, 0, 0], [(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]), (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.cos(q[1, 0]), (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]), 0, 0, 0, 0], [0, -numpy.sin(q[1, 0])*numpy.sin(q[2, 0]), numpy.cos(q[1, 0])*numpy.cos(q[2, 0]), 0, 0, 0, 0]])
def jrz_4(q):
return numpy.array([[((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]), (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[3, 0]), (-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[3, 0]), (-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]), 0, 0, 0], [((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]), -(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]), ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]), (-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]), 0, 0, 0], [0, numpy.sin(q[1, 0])*numpy.sin(q[3, 0])*numpy.cos(q[2, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[3, 0]), numpy.sin(q[2, 0])*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]), numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]), 0, 0, 0]])
def jrz_5(q):
return numpy.array([[(-((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.cos(q[4, 0]), ((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[4, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.cos(q[1, 0])*numpy.cos(q[4, 0]), -(-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0])*numpy.cos(q[3, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[4, 0]), ((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[4, 0]), (-(-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) - ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]), 0, 0], [(-((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.cos(q[4, 0]), ((0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[4, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.cos(q[1, 0])*numpy.cos(q[4, 0]), -((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.sin(q[4, 0])*numpy.cos(q[3, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[4, 0]), ((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[4, 0]), (-(-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) - ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]), 0, 0], [0, (-numpy.sin(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]) - numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[4, 0]) - numpy.sin(q[1, 0])*numpy.sin(q[2, 0])*numpy.cos(q[4, 0]), -numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]) + numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[4, 0]), (-numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) - numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]), (-numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) + numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[4, 0]) - numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0]), 0, 0]])
def jrz_6(q):
return numpy.array([[((((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), ((-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[4, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[5, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), ((-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.cos(q[3, 0])*numpy.cos(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[5, 0]), (-(-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0])*numpy.cos(q[4, 0]) + ((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[5, 0]), (-((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.cos(q[4, 0]))*numpy.sin(q[5, 0]), (((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.cos(q[5, 0]) - ((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0]), 0], [((((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), ((-(0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[4, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[5, 0]) + (-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.cos(q[5, 0]), ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[5, 0]) + (((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0])*numpy.cos(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]), (-(-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0])*numpy.cos(q[4, 0]) + ((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[5, 0]), (-((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.cos(q[4, 0]))*numpy.sin(q[5, 0]), (((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.cos(q[5, 0]) - ((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0]), 0], [0, ((numpy.sin(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]) + numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) - numpy.sin(q[1, 0])*numpy.sin(q[2, 0])*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (numpy.sin(q[1, 0])*numpy.sin(q[3, 0])*numpy.cos(q[2, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), (numpy.sin(q[2, 0])*numpy.cos(q[1, 0])*numpy.cos(q[3, 0])*numpy.cos(q[4, 0]) + numpy.sin(q[4, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.sin(q[5, 0]) + numpy.sin(q[2, 0])*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[5, 0]), (numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]) + (numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) + numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.sin(q[5, 0])*numpy.cos(q[4, 0]), (-(numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[4, 0]) + numpy.sin(q[2, 0])*numpy.cos(q[1, 0])*numpy.cos(q[4, 0]))*numpy.sin(q[5, 0]), ((numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[4, 0]) + numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[5, 0]) - (-numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) - numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.sin(q[5, 0]), 0]])
def jrz_ee(q):
return numpy.array([[((((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), ((-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[4, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[5, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), ((-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.cos(q[3, 0])*numpy.cos(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (-(-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[5, 0]), (-(-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0])*numpy.cos(q[4, 0]) + ((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[5, 0]), (-((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.cos(q[4, 0]))*numpy.sin(q[5, 0]), (((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.cos(q[5, 0]) - ((-(0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0]), 0], [((((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (((-0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), ((-(0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[4, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[5, 0]) + (-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.cos(q[5, 0]), ((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[5, 0]) + (((0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0])*numpy.cos(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) - (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]), (-(-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) + 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0])*numpy.cos(q[4, 0]) + ((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[5, 0]), (-((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.sin(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.cos(q[4, 0]))*numpy.sin(q[5, 0]), (((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.cos(q[3, 0]) - (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) + ((-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.sin(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[2, 0]))*numpy.sin(q[4, 0]))*numpy.cos(q[5, 0]) - ((-(-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[1, 0])*numpy.cos(q[2, 0]) + (0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.sin(q[2, 0]))*numpy.sin(q[3, 0]) + (-0.707106781186548*numpy.sin(q[0, 0]) - 0.707106781186548*numpy.cos(q[0, 0]))*numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[5, 0]), 0], [0, ((numpy.sin(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]) + numpy.sin(q[3, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[4, 0]) - numpy.sin(q[1, 0])*numpy.sin(q[2, 0])*numpy.sin(q[4, 0]))*numpy.sin(q[5, 0]) + (numpy.sin(q[1, 0])*numpy.sin(q[3, 0])*numpy.cos(q[2, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]), (numpy.sin(q[2, 0])*numpy.cos(q[1, 0])*numpy.cos(q[3, 0])*numpy.cos(q[4, 0]) + numpy.sin(q[4, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.sin(q[5, 0]) + numpy.sin(q[2, 0])*numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[5, 0]), (numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[5, 0]) + (numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) + numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.sin(q[5, 0])*numpy.cos(q[4, 0]), (-(numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.sin(q[4, 0]) + numpy.sin(q[2, 0])*numpy.cos(q[1, 0])*numpy.cos(q[4, 0]))*numpy.sin(q[5, 0]), ((numpy.sin(q[1, 0])*numpy.sin(q[3, 0]) - numpy.cos(q[1, 0])*numpy.cos(q[2, 0])*numpy.cos(q[3, 0]))*numpy.cos(q[4, 0]) + numpy.sin(q[2, 0])*numpy.sin(q[4, 0])*numpy.cos(q[1, 0]))*numpy.cos(q[5, 0]) - (-numpy.sin(q[1, 0])*numpy.cos(q[3, 0]) - numpy.sin(q[3, 0])*numpy.cos(q[1, 0])*numpy.cos(q[2, 0]))*numpy.sin(q[5, 0]), 0]])
| 1,287.538462
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0
| 15
|
cb807c5e70defcb113f7eed9a7d33215ac714d22
| 23,520
|
py
|
Python
|
desicos/abaqus/imperfections/uneven_edges.py
|
saullocastro/desicos
|
922db8ac4fb0fb4d09df18ce2a14011f207f6fa8
|
[
"BSD-3-Clause"
] | 1
|
2020-10-22T22:15:24.000Z
|
2020-10-22T22:15:24.000Z
|
desicos/abaqus/imperfections/uneven_edges.py
|
saullocastro/desicos
|
922db8ac4fb0fb4d09df18ce2a14011f207f6fa8
|
[
"BSD-3-Clause"
] | 1
|
2020-10-09T12:42:02.000Z
|
2020-10-09T12:42:02.000Z
|
desicos/abaqus/imperfections/uneven_edges.py
|
saullocastro/desicos
|
922db8ac4fb0fb4d09df18ce2a14011f207f6fa8
|
[
"BSD-3-Clause"
] | 2
|
2020-07-14T07:45:31.000Z
|
2020-12-29T00:22:41.000Z
|
from __future__ import absolute_import
import numpy as np
from numpy import deg2rad, rad2deg, pi
from desicos.conecylDB.interpolate import interp
class Shim(object):
"""Represents a shim added to one of the edges
============== =========================================================
Attributes Description
============== =========================================================
edge An object of the class :class:`.UnevenTopEdge`
thetadeg The circumferential position where the shim starts
thick The shim thickness
width The shim perimetrical width (along the shell perimeter)
============== =========================================================
"""
def __init__(self,thetadeg, thick, width, edge=None):
self.thetadeg = thetadeg
self.thick = thick
self.width = width
self.edge = edge
if edge is not None:
self.edge.shims.append(self)
class UnevenBottomEdge(object):
"""Uneven Bottom Edge
The following attributes are taken into account:
- misalignment of the bottom edge
- presence of shims
- measured uneven edge points
============== =========================================================
Attributes Description
============== =========================================================
uneven_plate ``bool``: If the unevenness should be applied to the
testing plate or to the test specimen
betadeg Misalignment of the bottom edge in degrees
omegadeg Azimuth angle of the bottom edge misalignment in degrees.
shims ``list`` of shims included to this edge
measured_u3s Measured points describing the edge imperfection
============== =========================================================
"""
def __init__(self, betadeg=None, omegadeg=None):
self.name = 'uneven_bottom_edge'
self.index = None
self.impconf = None
self.thetadegs = []
self.pts = []
self.shims = []
self.measured_u3s = None
self.scaling_factor = 1.
self.uneven_plate = True
# plotting options
self.xaxis = 'scaling_factor'
self.xaxis_label = 'Scaling factor'
def __nonzero__(self): # in Python 3 this method was renamed to __bool__
return self.__bool__()
def __bool__(self):
cc = self.impconf.conecyl
return (bool(self.shims) or bool(self.measured_u3s is not None) or
bool(cc.bc_gaps_bottom_edge))
def rebuild(self):
cc = self.impconf.conecyl
self.thetadegs = [s.thetadeg for s in self.shims]
self.thetadegs += [s.thetadeg + 360*s.width/(2*pi*cc.rbot)
for s in self.shims]
self.pts = []
def add_measured_u3s(self, thetadegs, u3s):
"""Adds measured data to the uneven bottom edge
The edge imperfection that actually goes for each node is a linear
interpolation of the measured values.
Parameters
----------
thetadegs : list
The circumferential positions where the imperfect bottom edge was
measured, in degrees.
u3s : list
The measured imperfections representing displacements along the
`X_3` axis :ref:`of the adopted model <figure_conecyl>`.
"""
if len(thetadegs) != len(u3s):
raise ValueError('thetadegs must have the same length of u3s!')
self.measured_u3s = np.array([thetadegs, u3s])
def add_shim(self, thetadeg, thick, width):
"""Adds a shim to the uneven bottom edge
Parameters
----------
thetadeg : float
Circumferential position where the shim starts.
thick : float
Thickness of the shim.
width : float
Perimetrical width of the shim (along the shell perimeter).
Returns
-------
shim : :class:`.Shim` object.
"""
shim = Shim(thetadeg, thick, width, edge=self)
return shim
def calc_amplitude(self):
return self.scaling_factor
def create(self):
r"""Creates the uneven bottom edge imperfections
The uneven bottom edge will be represented by many GAP elements
created in such a way to consider all the imperfections contained in
the current :class:`.UnevenBottomEdge` object.
The output file ``cc.model_name + '_bottom_edge.gaps'`` will be
created, where ``cc`` is the :class:`.ConeCyl` object that contains
this :class:`.UnevenBottomEdge` object.
The following steps are executed:
- get the `\theta` coordinate of the bottom nodes from the shell and
bottom resin rings
- get imperfection from the ``shims`` attribute
- get any additional imperfection of the bottom edge represented by
``measured_u3s``
Assumptions:
- for a given `\theta` coordinate the uneven displacement is the same
for all the shell and resin ring nodes
.. note:: Must be called from Abaqus
"""
from abaqus import mdb
from abaqusConstants import (PIN_MPC, DOF_MODE_MPC)
from regionToolset import Region
from desicos.abaqus.abaqus_functions import edit_keywords
cc = self.impconf.conecyl
mod = mdb.models[cc.model_name]
ra = mod.rootAssembly
def calc_gaps(nodes, yx=True):
# calculating gaps
# theta according to the assembly coordinate system
coords = np.array([n.coordinates for n in nodes])
if yx:
theta_nodes = np.arctan2(coords[:,1], coords[:,0])
else:
theta_nodes = np.arctan2(-coords[:,2], coords[:,0])
# contributions from measured edge imperfection
if self.measured_u3s is not None:
measured_u3s = np.asarray(self.measured_u3s)
else:
measured_u3s = np.zeros((2, 100))
measured_u3s[0, :] = np.linspace(0, 360, 100)
# calculating u3 for each node
u3_nodes = interp(rad2deg(theta_nodes), measured_u3s[0, :],
measured_u3s[1, :], period=360)
# contributions from shims
hs = np.zeros_like(theta_nodes)
for s in self.shims:
trad1 = deg2rad(s.thetadeg)
trad2 = deg2rad(s.thetadeg + 360*s.width/(2*pi*cc.rbot))
thetarads = [trad1-0.001, trad1, trad2, trad2+0.001]
u3s = [0, s.thick, s.thick, 0]
tmp = interp(theta_nodes, thetarads, u3s, period=2*pi)
hs += tmp
u3_nodes += hs
# applying scaling_factor
u3_nodes *= self.scaling_factor
# calculating gap values
gaps = u3_nodes.max() - u3_nodes
return gaps
if not self.uneven_plate:
# shell
part = mod.parts[cc.part_name_shell]
wdw = 2*cc.rbot
zmin = -0.001
zmax = cc.resin_bot_h*1.001
nodes = part.nodes.getByBoundingBox(-wdw, -wdw, zmin,
+wdw, +wdw, zmax)
coords = np.array([n.coordinates for n in nodes])
coords[:, 2] += calc_gaps(nodes)
labels = [n.label for n in nodes]
meshNodeArray = nodes.sequenceFromLabels(labels)
part.editNode(nodes=meshNodeArray, coordinates=coords)
# bottom inner ring
if cc.resin_add_TIR:
mesh_arrays = []
coords_list = []
part = mod.parts['Bottom_IR']
coords = np.array([n.coordinates for n in part.nodes])
gaps = calc_gaps(part.nodes, yx=False)
coords[:, 1] += gaps
part.editNode(nodes=part.nodes, coordinates=coords)
# bottom outer ring
if cc.resin_add_TOR:
mesh_arrays = []
coords_list = []
part = mod.parts['Bottom_OR']
coords = np.array([n.coordinates for n in part.nodes])
gaps = calc_gaps(part.nodes, yx=False)
coords[:, 1] += gaps
part.editNode(nodes=part.nodes, coordinates=coords)
nodes_shell = np.array(ra.sets['shell_bottom_edges'].nodes)
nodes_all = nodes_shell
tshell = sum(cc.plyts)
cosa = np.cos(cc.alpharad)
if cc.resin_add_BIR:
tmp = np.array(ra.sets['Bottom_IR_faces'].nodes)
coords = np.array([n.coordinates for n in tmp])
r_nodes = np.sqrt(coords[:,0]**2 + coords[:,1]**2)
# taking nodes that are not pinned to the shell
check = (r_nodes < (cc.rbot - cosa*0.51*tshell))
nodes_all = np.hstack((nodes_all, tmp[check]))
if cc.resin_add_BOR:
tmp = np.array(ra.sets['Bottom_OR_faces'].nodes)
coords = np.array([n.coordinates for n in tmp])
r_nodes = np.sqrt(coords[:,0]**2 + coords[:,1]**2)
# taking nodes that are not pinned to the shell
check = (r_nodes > (cc.rbot + cosa*0.51*tshell))
nodes_all = np.hstack((nodes_all, tmp[check]))
# creating GAP elements
rps_gap = []
text = ''
gaps = calc_gaps(nodes_all)
for node, gap in zip(nodes_all, gaps):
coord = list(node.coordinates)
coord[2] -= gap
rp = ra.ReferencePoint(point=coord)
inst_name = node.instanceName
#TODO really bad approach, but couldn' find any other way to
# get the actual node id that is printed in the .inp
# file
rp_id = int(rp.name.split('-')[1]) + 2
#
rps_gap.append(rp)
gap_name = 'gap_{0}_{1:d}'.format(inst_name, 1000000+node.label)
inst_node = '{0}.{1:d}'.format(inst_name, node.label)
text += ('\n*Element, type=GAPUNI, elset={0}'.format(gap_name))
text += ('\n{0:d},{1},{2:d}'.format(1000000+node.label, inst_node,
rp_id))
text += '\n*GAP, elset={0}'.format(gap_name)
text += '\n{0:f},0,0,-1\n'.format(gap)
bottom_name_gaps = '{0}_bottom_edge.gaps'.format(cc.model_name)
with open(bottom_name_gaps, 'w') as f:
f.write(text)
if not self.impconf.uneven_top_edge:
pattern = '*Instance'
text = '*INCLUDE, INPUT={0}'.format(bottom_name_gaps)
edit_keywords(mod=mod, text=text, before_pattern=pattern)
set_RP_bot=ra.sets['RP_bot']
rps = ra.referencePoints
rps_gap_datums = [rps[rp.id] for rp in rps_gap]
region = Region(referencePoints=rps_gap_datums)
ra_cyl_csys = ra.features['ra_cyl_csys']
ra_cyl_csys = ra.datums[ra_cyl_csys.id]
mod.MultipointConstraint(name='MPC_RP_GAPs_bot_edge',
controlPoint=set_RP_bot,
surface=region,
mpcType=PIN_MPC,
userMode=DOF_MODE_MPC,
userType=0, csys=ra_cyl_csys)
class UnevenTopEdge(object):
"""Uneven Top Edge
The following attributes are taken into account:
- misalignment of the top edge
- presence of shims
- measured uneven edge points
============== ==========================================================
Attributes Description
============== ==========================================================
uneven_plate ``bool``: If the unevenness should be applied to the
testing plate or to the test specimen
betadeg ``float``: Misalignment of the top edge in degrees
omegadeg ``float``: Azimuth angle of the top edge misalignment in
degrees
shims ``list`` of shims included to this edge
measured_u3s Measured points describing the edge imperfection
============== ==========================================================
"""
def __init__(self, betadeg=None, omegadeg=None):
self.name = 'uneven_top_edge'
self.index = None
self.impconf = None
self.betadeg = betadeg
self.omegadeg = omegadeg
self.thetadegs = []
self.pts = []
self.shims = []
self.measured_u3s = None
self.scaling_factor = 1.
self.uneven_plate = True
# plotting options
self.xaxis = 'scaling_factor'
self.xaxis_label = 'Scaling factor'
def __nonzero__(self): # in Python 3 this method was renamed to __bool__
return self.__bool__()
def __bool__(self):
cc = self.impconf.conecyl
return (bool(self.betadeg) or bool(self.shims) or
bool(self.measured_u3s is not None) or
bool(cc.bc_gaps_top_edge))
def rebuild(self):
cc = self.impconf.conecyl
self.thetadegs = [s.thetadeg for s in self.shims]
self.thetadegs += [s.thetadeg + 360*s.width/(2*pi*cc.rtop)
for s in self.shims]
self.pts = []
def add_measured_u3s(self, thetadegs, u3s):
"""Adds measured data to the uneven top edge
The edge imperfection that actually goes for each node is a linear
interpolation of the measured values.
Parameters
----------
thetadegs : list
The circumferential positions where the imperfect top edge was
measured, in degrees.
u3s : list
The measured imperfections representing displacements along the
`X_3` axis :ref:`of the adopted model <figure_conecyl>`.
"""
if len(thetadegs) != len(u3s):
raise ValueError('thetadegs must have the same length of u3s!')
self.measured_u3s = np.array([thetadegs, u3s])
def add_shim(self, thetadeg, thick, width):
"""Adds a shim to the uneven top edge
Parameters
----------
thetadeg : float
Circumferential position where the shim starts.
thick : float
Thickness of the shim.
width : float
Perimetrical width of the shim (along the shell perimeter).
Returns
-------
shim : :class:`.Shim` object.
"""
shim = Shim(thetadeg, thick, width, edge=self)
return shim
def calc_amplitude(self):
return self.scaling_factor
def create(self):
r"""Creates the uneven top edge imperfections
The uneven top edge will be represented by many GAP elements created
in such a way to consider all the imperfections contained in the
current :class:`.UnevenTopEdge` object.
The output file ``cc.model_name + '_top_edge.gaps'`` will be created,
where ``cc`` is the :class:`.ConeCyl` object that contains this
:class:`.UnevenTopEdge` object.
The following steps are executed:
- get the `\theta` coordinate of the top nodes from the shell and top
resin rings
- get imperfection from the ``shims`` attribute
- get any additional imperfection of the top edge represented by
``measured_u3s``
- include effect of the misalignment angle ``betadeg``
Assumptions:
- for a given `\theta` coordinate the uneven displacement is the same
for all the shell and resin ring nodes, but the load asymmetry angle
``self.betadeg`` may change this equality. The contribution due to
`\beta` is given by:
.. math::
\Delta u_3 = R_{top} tan(\beta) cos(\theta-\omega)
.. note:: Must be called from Abaqus
"""
from abaqus import mdb
from abaqusConstants import (PIN_MPC, DOF_MODE_MPC)
from regionToolset import Region
from desicos.abaqus.abaqus_functions import edit_keywords
cc = self.impconf.conecyl
mod = mdb.models[cc.model_name]
ra = mod.rootAssembly
def calc_gaps(nodes, yx=True):
# calculating gaps
# theta according to the assembly coordinate system
coords = np.array([n.coordinates for n in nodes])
if yx:
theta_nodes = np.arctan2(coords[:,1], coords[:,0])
else:
theta_nodes = np.arctan2(-coords[:,2], coords[:,0])
# contributions from measured edge imperfection
if self.measured_u3s is not None:
measured_u3s = np.asarray(self.measured_u3s)
else:
measured_u3s = np.zeros((2, 100))
measured_u3s[0, :] = np.linspace(0, 360, 100)
# calculating u3 for each node
u3_nodes = interp(rad2deg(theta_nodes), measured_u3s[0, :],
measured_u3s[1, :], period=360)
# applying load asymmetry according to cc.betarad and omega
betadeg = self.betadeg if self.betadeg is not None else 0.
betarad = deg2rad(betadeg)
omegadeg = self.omegadeg if self.omegadeg is not None else 0.
omegarad = deg2rad(omegadeg)
u3_nodes -= cc.rtop*np.tan(betarad)*np.cos(theta_nodes-omegarad)
# contributions from shims
hs = np.zeros_like(theta_nodes)
for s in self.shims:
trad1 = deg2rad(s.thetadeg)
trad2 = deg2rad(s.thetadeg + 360*s.width/(2*pi*cc.rtop))
thetarads = [trad1-0.001, trad1, trad2, trad2+0.001]
u3s = [0, s.thick, s.thick, 0]
tmp = interp(theta_nodes, thetarads, u3s, period=2*pi)
hs += tmp
u3_nodes -= hs
# applying scaling_factor
u3_nodes *= self.scaling_factor
# calculating gap values
gaps = u3_nodes - u3_nodes.min()
return gaps
if not self.uneven_plate:
# shell
part = mod.parts[cc.part_name_shell]
wdw = 2*cc.rtop
zmin = cc.H - cc.resin_top_h*1.001
zmax = 1.001*cc.H
nodes = part.nodes.getByBoundingBox(-wdw, -wdw, zmin,
+wdw, +wdw, zmax)
coords = np.array([n.coordinates for n in nodes])
coords[:, 2] -= calc_gaps(nodes)
labels = [n.label for n in nodes]
meshNodeArray = nodes.sequenceFromLabels(labels)
part.editNode(nodes=meshNodeArray, coordinates=coords)
# top inner ring
if cc.resin_add_TIR:
mesh_arrays = []
coords_list = []
part = mod.parts['Top_IR']
coords = np.array([n.coordinates for n in part.nodes])
gaps = calc_gaps(part.nodes, yx=False)
coords[:, 1] -= gaps
part.editNode(nodes=part.nodes, coordinates=coords)
# top outer ring
if cc.resin_add_TOR:
mesh_arrays = []
coords_list = []
part = mod.parts['Top_OR']
coords = np.array([n.coordinates for n in part.nodes])
gaps = calc_gaps(part.nodes, yx=False)
coords[:, 1] -= gaps
part.editNode(nodes=part.nodes, coordinates=coords)
nodes_shell = np.array(ra.sets['shell_top_edges'].nodes)
nodes_all = nodes_shell
tshell = sum(cc.plyts)
cosa = np.cos(cc.alpharad)
if cc.resin_add_TIR:
nodes_TIR_assembly = np.array(ra.sets['Top_IR_faces'].nodes)
coords = np.array([n.coordinates for n in nodes_TIR_assembly])
r_nodes = np.sqrt(coords[:,0]**2 + coords[:,1]**2)
# taking nodes that are not pinned to the shell
check = (r_nodes < (cc.rtop - cosa*0.51*tshell))
nodes_all = np.hstack((nodes_all, nodes_TIR_assembly[check]))
if cc.bc_fix_top_side_u3:
tmp = np.array(ra.sets['Top_IR_faces_side'].nodes)
coords = np.array([n.coordinates for n in tmp])
# taking nodes that are not on the top edge
check = (coords[:,2] < (cc.H-0.1))
nodes_all = np.hstack((nodes_all, tmp[check]))
if cc.resin_add_TOR:
nodes_TOR_assembly = np.array(ra.sets['Top_OR_faces'].nodes)
coords = np.array([n.coordinates for n in nodes_TOR_assembly])
r_nodes = np.sqrt(coords[:,0]**2 + coords[:,1]**2)
# taking nodes that are not pinned to the shell
check = (r_nodes > (cc.rtop + cosa*0.51*tshell))
nodes_all = np.hstack((nodes_all, nodes_TOR_assembly[check]))
if cc.bc_fix_top_side_u3:
tmp = np.array(ra.sets['Top_OR_faces_side'].nodes)
coords = np.array([n.coordinates for n in tmp])
# taking nodes that are not on the top edge
check = (coords[:,2] < (cc.H-0.1))
nodes_all = np.hstack((nodes_all, tmp[check]))
# creating GAP elements
rps_gap = []
text = ''
gaps = calc_gaps(nodes_all)
for node, gap in zip(nodes_all, gaps):
coord = list(node.coordinates)
coord[2] += gap
rp = ra.ReferencePoint(point=coord)
inst_name = node.instanceName
#TODO really bad approach, but couldn' find any other way to
# get the actual node id that is printed in the .inp
# file
rp_id = int(rp.name.split('-')[1]) + 2
#
rps_gap.append(rp)
gap_name = 'gap_{0}_{1:d}'.format(inst_name, 2000000+node.label)
inst_node = '{0}.{1:d}'.format(inst_name, node.label)
text += ('\n*Element, type=GAPUNI, elset={0}'.format(gap_name))
text += ('\n{0:d},{1:d},{2}'.format(2000000+node.label, rp_id,
inst_node))
text += '\n*GAP, elset={0}'.format(gap_name)
text += '\n{0:f},0,0,-1\n'.format(gap)
top_name_gaps = '{0}_top_edge.gaps'.format(cc.model_name)
with open(top_name_gaps, 'w') as f:
f.write(text)
pattern = '*Instance'
if self.impconf.uneven_bottom_edge:
bottom_name_gaps = '{0}_bottom_edge.gaps'.format(cc.model_name)
text = '*INCLUDE, INPUT={0}'.format(bottom_name_gaps)
text += '\n**\n*INCLUDE, INPUT={0}'.format(top_name_gaps)
else:
text = '*INCLUDE, INPUT={0}'.format(top_name_gaps)
edit_keywords(mod=mod, text=text, before_pattern=pattern, insert=True)
set_RP_top = ra.sets['RP_top']
rps = ra.referencePoints
rps_gap_datums = [rps[rp.id] for rp in rps_gap]
region = Region(referencePoints=rps_gap_datums)
ra_cyl_csys = ra.features['ra_cyl_csys']
ra_cyl_csys = ra.datums[ra_cyl_csys.id]
mod.MultipointConstraint(name='MPC_RP_GAPs_top_edge',
controlPoint=set_RP_top,
surface=region,
mpcType=PIN_MPC,
userMode=DOF_MODE_MPC,
userType=0, csys=ra_cyl_csys)
| 37.632
| 78
| 0.550425
| 2,821
| 23,520
| 4.451613
| 0.121588
| 0.022774
| 0.007645
| 0.015608
| 0.869724
| 0.850374
| 0.845596
| 0.830148
| 0.811276
| 0.810002
| 0
| 0.018799
| 0.328274
| 23,520
| 624
| 79
| 37.692308
| 0.776062
| 0.283078
| 0
| 0.724242
| 0
| 0
| 0.048564
| 0
| 0
| 0
| 0
| 0.003205
| 0
| 1
| 0.057576
| false
| 0
| 0.036364
| 0.012121
| 0.133333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
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| null | 0
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| 0
| 0
| 0
| 0
|
0
| 7
|
cbc793a272bf9c72445aa8a4c66d93d2340a8c90
| 27,928
|
py
|
Python
|
scripts/emptydriver_generator.py
|
luopan007/vktrace-arm
|
0b44f2ad599bff3707ca748179275085b8241a03
|
[
"Apache-2.0"
] | 8
|
2019-07-17T13:57:15.000Z
|
2022-01-21T03:49:27.000Z
|
scripts/emptydriver_generator.py
|
QPC-database/vktrace-arm
|
50300888e0254eaf2c3f35cc31fa9893d1628730
|
[
"Apache-2.0"
] | 2
|
2022-01-22T06:49:59.000Z
|
2022-01-22T06:56:35.000Z
|
scripts/emptydriver_generator.py
|
luopan007/vktrace-arm
|
0b44f2ad599bff3707ca748179275085b8241a03
|
[
"Apache-2.0"
] | 10
|
2019-10-31T12:02:43.000Z
|
2021-08-06T04:57:23.000Z
|
#!/usr/bin/python3 -i
#
# Copyright (c) 2015-2020, 2020 ARM Corporation
#
# 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.
#
import os,re,sys,string
import xml.etree.ElementTree as etree
import generator as gen
from generator import *
from collections import namedtuple
from common_codegen import *
EMPTYDRIVER_CODEGEN = """
/*
* (C) COPYRIGHT 2020 ARM Limited
* ALL RIGHTS RESERVED
*
* 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
*
* LICENSE-2.0" target="_blank" rel="nofollow">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.
*/
#include "vk_loader_platform.h"
#include "vulkan/vk_layer.h"
#include "vk_layer_config.h"
#include "vk_layer_table.h"
#include "vk_layer_extension_utils.h"
#include "vk_layer_utils.h"
#include "vktrace_emptydriver.h"
static uint64_t dummy_handle = 0x0000FFFF;
//============================= API EntryPoints =============================//
// Specifically implemented functions
@foreach function where('{funcName}' == 'vkCreateInstance')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
// Get the function pointer
VkLayerInstanceCreateInfo* chain_info = get_chain_info(pCreateInfo, VK_LAYER_LINK_INFO);
assert(chain_info->u.pLayerInfo != 0);
PFN_vkGetInstanceProcAddr fpGetInstanceProcAddr = chain_info->u.pLayerInfo->pfnNextGetInstanceProcAddr;
assert(fpGetInstanceProcAddr != 0);
PFN_vkCreateInstance fpCreateInstance = (PFN_vkCreateInstance) fpGetInstanceProcAddr(NULL, "vkCreateInstance");
if(fpCreateInstance == NULL) {{
return VK_ERROR_INITIALIZATION_FAILED;
}}
// Call the function and create the dispatch table
chain_info->u.pLayerInfo = chain_info->u.pLayerInfo->pNext;
{funcReturn} result = fpCreateInstance({funcNamedParams});
if(result == VK_SUCCESS) {{
initInstanceTable(*pInstance, fpGetInstanceProcAddr);
}}
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkDestroyInstance')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
// Destroy the dispatch table
dispatch_key key = get_dispatch_key({funcDispatchParam});
instance_dispatch_table({funcDispatchParam})->DestroyInstance({funcNamedParams});
destroy_instance_dispatch_table(key);
}}
@end function
@foreach function where('{funcName}' == 'vkCreateDevice')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
// Get the function pointer
VkLayerDeviceCreateInfo* chain_info = get_chain_info(pCreateInfo, VK_LAYER_LINK_INFO);
assert(chain_info->u.pLayerInfo != 0);
PFN_vkGetInstanceProcAddr fpGetInstanceProcAddr = chain_info->u.pLayerInfo->pfnNextGetInstanceProcAddr;
PFN_vkGetDeviceProcAddr fpGetDeviceProcAddr = chain_info->u.pLayerInfo->pfnNextGetDeviceProcAddr;
PFN_vkCreateDevice fpCreateDevice = (PFN_vkCreateDevice) fpGetInstanceProcAddr(NULL, "vkCreateDevice");
if(fpCreateDevice == nullptr) {{
return VK_ERROR_INITIALIZATION_FAILED;
}}
// Call the function and create the dispatch table
chain_info->u.pLayerInfo = chain_info->u.pLayerInfo->pNext;
{funcReturn} result = fpCreateDevice({funcNamedParams});
if(result == VK_SUCCESS) {{
initDeviceTable(*pDevice, fpGetDeviceProcAddr);
}}
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkDestroyDevice')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
// Destroy the dispatch table
dispatch_key key = get_dispatch_key({funcDispatchParam});
device_dispatch_table({funcDispatchParam})->DestroyDevice({funcNamedParams});
destroy_device_dispatch_table(key);
}}
@end function
@foreach function where('{funcName}' == 'vkEnumerateInstanceExtensionProperties')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = util_GetExtensionProperties(0, NULL, pPropertyCount, pProperties);
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkEnumerateInstanceLayerProperties')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
static const VkLayerProperties layerProperties[] = {{
{{
"VK_LAYER_ARM_emptydriver",
VK_MAKE_VERSION(1, 2, VK_HEADER_VERSION), // specVersion
VK_MAKE_VERSION(0, 2, 0), // implementationVersion
"layer: emptydriver",
}}
}};
{funcReturn} result = util_GetLayerProperties(ARRAY_SIZE(layerProperties), layerProperties, pPropertyCount, pProperties);
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkEnumerateDeviceLayerProperties')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
static const VkLayerProperties layerProperties[] = {{
{{
"VK_LAYER_ARM_emptydriver",
VK_MAKE_VERSION(1, 2, VK_HEADER_VERSION),
VK_MAKE_VERSION(0, 2, 0),
"layer: emptydriver",
}}
}};
{funcReturn} result = util_GetLayerProperties(ARRAY_SIZE(layerProperties), layerProperties, pPropertyCount, pProperties);
return result;
}}
@end function
// instance function begin
@foreach function where('{funcName}' == 'vkCreateDebugReportCallbackEXT')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pCallback = (VkDebugReportCallbackEXT)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateDebugUtilsMessengerEXT')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pMessenger = (VkDebugUtilsMessengerEXT)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkSubmitDebugUtilsMessageEXT')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
#ifndef USE_EMPTYDRIVER
instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
}}
@end function
@foreach function where('{funcName}' == 'vkDestroyDebugReportCallbackEXT')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
#ifndef USE_EMPTYDRIVER
instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
}}
@end function
@foreach function where('{funcName}' == 'vkDestroyDebugUtilsMessengerEXT')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
#ifndef USE_EMPTYDRIVER
instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
}}
@end function
@foreach function where('{funcName}' == 'vkDebugReportMessageEXT')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
#ifndef USE_EMPTYDRIVER
instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
}}
@end function
// instance function end
// device function begin
@foreach function where('{funcName}' == 'vkQueuePresentKHR')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateFramebuffer')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
else
dummy_handle++;
*pFramebuffer = (VkFramebuffer)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateRenderPass')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pRenderPass = (VkRenderPass)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateRenderPass2')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pRenderPass = (VkRenderPass)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateRenderPass2KHR')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pRenderPass = (VkRenderPass)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateComputePipelines')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pPipelines = (VkPipeline)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreatePipelineCache')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pPipelineCache = (VkPipelineCache)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreatePipelineLayout')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pPipelineLayout = (VkPipelineLayout)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateGraphicsPipelines')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pPipelines = (VkPipeline)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateRayTracingPipelinesNV')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pPipelines = (VkPipeline)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateShaderModule')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pShaderModule = (VkShaderModule)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkAcquireNextImageKHR')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
*pImageIndex = 1;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkAcquireNextImage2KHR')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pImageIndex = 1;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateDescriptorUpdateTemplate')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pDescriptorUpdateTemplate = (VkDescriptorUpdateTemplate)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateSamplerYcbcrConversion')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pYcbcrConversion = (VkSamplerYcbcrConversion)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateFence')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pFence = (VkFence)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateSampler')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pSampler = (VkSampler)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateIndirectCommandsLayoutNVX')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pIndirectCommandsLayout = (VkIndirectCommandsLayoutNVX)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateObjectTableNVX')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pObjectTable = (VkObjectTableNVX)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateSamplerYcbcrConversionKHR')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pYcbcrConversion = (VkSamplerYcbcrConversion)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateValidationCacheEXT')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pValidationCache = (VkValidationCacheEXT)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateDescriptorUpdateTemplateKHR')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pDescriptorUpdateTemplate = (VkDescriptorUpdateTemplate)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateAccelerationStructureNV')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pAccelerationStructure = (VkAccelerationStructureNV)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateSemaphore')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pSemaphore = (VkSemaphore)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateEvent')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pEvent = (VkEvent)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkCreateQueryPool')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#else
dummy_handle++;
*pQueryPool = (VkQueryPool)dummy_handle;
#endif
return result;
}}
@end function
@foreach function where('{funcName}' == 'vkGetEventStatus')
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_EVENT_SET;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
return result;
}}
@end function
// device function end
// Autogen instance functions
@foreach function where('{funcDispatchType}' == 'instance' and '{funcReturn}' != 'void' and '{funcName}' not in \
['vkCreateInstance', 'vkDestroyInstance', 'vkCreateDevice', 'vkGetInstanceProcAddr', 'vkEnumerateDeviceExtensionProperties', 'vkEnumerateDeviceLayerProperties', 'vkCreateDebugReportCallbackEXT', 'vkCreateDebugUtilsMessengerEXT'])
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
return result;
}}
@end function
@foreach function where('{funcDispatchType}' == 'instance' and '{funcReturn}' == 'void' and '{funcName}' not in \
['vkCreateInstance', 'vkDestroyInstance', 'vkCreateDevice', 'vkGetInstanceProcAddr', 'vkEnumerateDeviceExtensionProperties', 'vkEnumerateDeviceLayerProperties', 'vkSubmitDebugUtilsMessageEXT', 'vkDestroyDebugReportCallbackEXT', 'vkDestroyDebugUtilsMessengerEXT', 'vkDebugReportMessageEXT'])
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
instance_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
}}
@end function
// Autogen device functions
@foreach function where('{funcDispatchType}' == 'device' and '{funcReturn}' != 'void' and '{funcName}' not in \
['vkDestroyDevice', 'vkEnumerateInstanceExtensionProperties', 'vkEnumerateInstanceLayerProperties', 'vkQueuePresentKHR', 'vkGetDeviceProcAddr', \
'vkCreateFramebuffer', 'vkCreateRenderPass', 'vkCreateRenderPass2', 'vkCreateRenderPass2KHR', 'vkCreateComputePipelines', 'vkCreatePipelineCache', 'vkCreatePipelineLayout', 'vkCreateGraphicsPipelines', 'vkCreateRayTracingPipelinesNV', 'vkCreateSwapchainKHR', 'vkCreateSharedSwapchainsKHR', 'vkAllocateMemory', 'vkCreateImage', 'vkCreateImageView', 'vkCreateBuffer', 'vkCreateBufferView', 'vkCreateShaderModule', 'vkAcquireNextImageKHR', 'vkAcquireNextImage2KHR', \
'vkCreateDescriptorUpdateTemplate', 'vkCreateSamplerYcbcrConversion', 'vkCreateFence', 'vkCreateSampler', 'vkCreateIndirectCommandsLayoutNVX', 'vkCreateObjectTableNVX', 'vkCreateSamplerYcbcrConversionKHR', 'vkCreateValidationCacheEXT', 'vkCreateDescriptorUpdateTemplateKHR', 'vkCreateAccelerationStructureNV', 'vkCreateSemaphore', 'vkCreateEvent', 'vkCreateQueryPool', 'vkGetEventStatus', \
'vkBindBufferMemory2KHR', 'vkBindImageMemory2KHR', 'vkBindAccelerationStructureMemoryNV', 'vkBindBufferMemory2', 'vkBindImageMemory2', 'vkBindBufferMemory', 'vkBindImageMemory', 'vkMapMemory', 'vkGetSwapchainImagesKHR', 'vkCreateDescriptorPool', 'vkAllocateDescriptorSets', 'vkFreeDescriptorSets', 'vkCreateDescriptorSetLayout', 'vkCreateCommandPool', 'vkAllocateCommandBuffers', 'vkGetDeviceMemoryOpaqueCaptureAddressKHR', \
'vkGetDeviceMemoryOpaqueCaptureAddress', 'vkGetMemoryWin32HandleNV', 'vkGetMemoryHostPointerPropertiesEXT', 'vkGetMemoryWin32HandleKHR', 'vkGetMemoryWin32HandlePropertiesKHR', 'vkGetMemoryAndroidHardwareBufferANDROID', 'vkGetMemoryFdKHR', 'vkGetMemoryFdPropertiesKHR', 'vkGetBufferDeviceAddressKHR', 'vkGetBufferOpaqueCaptureAddressKHR', 'vkGetBufferDeviceAddress', 'vkGetBufferOpaqueCaptureAddress', 'vkGetBufferDeviceAddressEXT', \
'vkGetAndroidHardwareBufferPropertiesANDROID'])
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = VK_SUCCESS;
#ifndef USE_EMPTYDRIVER
result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
return result;
}}
@end function
@foreach function where('{funcDispatchType}' == 'device' and '{funcReturn}' != 'void' and '{funcName}' in \
['vkCreateSwapchainKHR', 'vkCreateSharedSwapchainsKHR', 'vkAllocateMemory', 'vkCreateImage', 'vkCreateImageView', 'vkCreateBuffer', 'vkCreateBufferView', \
'vkBindBufferMemory2KHR', 'vkBindImageMemory2KHR', 'vkBindAccelerationStructureMemoryNV', 'vkBindBufferMemory2', 'vkBindImageMemory2', 'vkBindBufferMemory', 'vkBindImageMemory', 'vkMapMemory', 'vkGetSwapchainImagesKHR', 'vkCreateDescriptorPool', 'vkAllocateDescriptorSets', 'vkFreeDescriptorSets', 'vkCreateDescriptorSetLayout', 'vkCreateCommandPool', 'vkAllocateCommandBuffers', 'vkGetDeviceMemoryOpaqueCaptureAddressKHR', \
'vkGetDeviceMemoryOpaqueCaptureAddress', 'vkGetMemoryWin32HandleNV', 'vkGetMemoryHostPointerPropertiesEXT', 'vkGetMemoryWin32HandleKHR', 'vkGetMemoryWin32HandlePropertiesKHR', 'vkGetMemoryAndroidHardwareBufferANDROID', 'vkGetMemoryFdKHR', 'vkGetMemoryFdPropertiesKHR', 'vkGetBufferDeviceAddressKHR', 'vkGetBufferOpaqueCaptureAddressKHR', 'vkGetBufferDeviceAddress', 'vkGetBufferOpaqueCaptureAddress', 'vkGetBufferDeviceAddressEXT', \
'vkGetAndroidHardwareBufferPropertiesANDROID'])
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
{funcReturn} result = device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
return result;
}}
@end function
@foreach function where('{funcDispatchType}' == 'device' and '{funcReturn}' == 'void' and '{funcName}' not in \
['vkDestroyDevice', 'vkEnumerateInstanceExtensionProperties', 'vkEnumerateInstanceLayerProperties', 'vkGetDeviceProcAddr', \
'vkFreeMemory', 'vkDestroyImage', 'vkDestroyImageView', 'vkDestroyBuffer', 'vkDestroyBufferView', 'vkUnmapMemory', 'vkDestroyDescriptorPool', 'vkDestroyDescriptorSetLayout', 'vkGetDeviceQueue', 'vkGetDeviceQueue2', 'vkFreeCommandBuffers', 'vkDestroyCommandPool', 'vkGetBufferMemoryRequirements', 'vkGetBufferMemoryRequirements2', \
'vkGetDeviceGroupPeerMemoryFeaturesKHR', 'vkGetDeviceGroupPeerMemoryFeatures', 'vkGetImageSparseMemoryRequirements2KHR', 'vkGetImageMemoryRequirements2', 'vkGetImageSparseMemoryRequirements2', 'vkGetImageMemoryRequirements2KHR', 'vkGetBufferMemoryRequirements2KHR', 'vkGetDeviceMemoryCommitment', 'vkGetAccelerationStructureMemoryRequirementsNV', \
'vkGetImageMemoryRequirements', 'vkGetImageSparseMemoryRequirements'])
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
#ifndef USE_EMPTYDRIVER
device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
#endif
}}
@end function
@foreach function where('{funcDispatchType}' == 'device' and '{funcReturn}' == 'void' and '{funcName}' in \
['vkFreeMemory', 'vkDestroyImage', 'vkDestroyImageView', 'vkDestroyBuffer', 'vkDestroyBufferView', 'vkUnmapMemory', 'vkDestroyDescriptorPool', 'vkDestroyDescriptorSetLayout', 'vkGetDeviceQueue', 'vkGetDeviceQueue2', 'vkFreeCommandBuffers', 'vkDestroyCommandPool', 'vkGetBufferMemoryRequirements', 'vkGetBufferMemoryRequirements2', \
'vkGetDeviceGroupPeerMemoryFeaturesKHR', 'vkGetDeviceGroupPeerMemoryFeatures', 'vkGetImageSparseMemoryRequirements2KHR', 'vkGetImageMemoryRequirements2', 'vkGetImageSparseMemoryRequirements2', 'vkGetImageMemoryRequirements2KHR', 'vkGetBufferMemoryRequirements2KHR', 'vkGetDeviceMemoryCommitment', 'vkGetAccelerationStructureMemoryRequirementsNV', \
'vkGetImageMemoryRequirements', 'vkGetImageSparseMemoryRequirements'])
VK_LAYER_EXPORT VKAPI_ATTR {funcReturn} VKAPI_CALL {funcName}({funcTypedParams})
{{
device_dispatch_table({funcDispatchParam})->{funcShortName}({funcNamedParams});
}}
@end function
VK_LAYER_EXPORT VKAPI_ATTR PFN_vkVoidFunction VKAPI_CALL vkGetInstanceProcAddr(VkInstance instance, const char* pName)
{{
@foreach function where('{funcType}' == 'instance' and '{funcName}' not in [ 'vkEnumerateDeviceExtensionProperties' ])
if(strcmp(pName, "{funcName}") == 0)
return reinterpret_cast<PFN_vkVoidFunction>({funcName});
@end function
if(instance_dispatch_table(instance)->GetInstanceProcAddr == NULL)
return NULL;
return instance_dispatch_table(instance)->GetInstanceProcAddr(instance, pName);
}}
VK_LAYER_EXPORT VKAPI_ATTR PFN_vkVoidFunction VKAPI_CALL vkGetDeviceProcAddr(VkDevice device, const char* pName)
{{
@foreach function where('{funcType}' == 'device')
if(strcmp(pName, "{funcName}") == 0)
return reinterpret_cast<PFN_vkVoidFunction>({funcName});
@end function
if(device_dispatch_table(device)->GetDeviceProcAddr == NULL)
return NULL;
return device_dispatch_table(device)->GetDeviceProcAddr(device, pName);
}}
"""
| 38.951185
| 468
| 0.765039
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| 27,928
| 8.488003
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| 0.777357
| 0.767104
| 0
| 0.003718
| 0.114079
| 27,928
| 717
| 469
| 38.951186
| 0.839867
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| 0.991912
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| 0.000366
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| false
| 0.011254
| 0.009646
| 0
| 0.081994
| 0
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| 0
| 0
| null | 0
| 0
| 0
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|
0
| 9
|
1deef41738b62988177f08f87f263409a6b9df4e
| 9,958
|
py
|
Python
|
tests/attributes/test_model_dict.py
|
yaal-coop/sheraf
|
774e3781bc6ff2e16c6cc39f268d475b5e64fcea
|
[
"MIT"
] | null | null | null |
tests/attributes/test_model_dict.py
|
yaal-coop/sheraf
|
774e3781bc6ff2e16c6cc39f268d475b5e64fcea
|
[
"MIT"
] | null | null | null |
tests/attributes/test_model_dict.py
|
yaal-coop/sheraf
|
774e3781bc6ff2e16c6cc39f268d475b5e64fcea
|
[
"MIT"
] | null | null | null |
import pytest
import sheraf
import tests
class AModel(tests.UUIDAutoModel):
name = sheraf.SimpleAttribute()
@pytest.mark.parametrize(
"model",
[
AModel,
f"{AModel.__module__}.{AModel.__name__}",
f"{AModel.__module__}.{AModel.__name__}".encode(),
],
)
def test_model_dict(sheraf_connection, model):
class AnotherModel(tests.UUIDAutoModel):
a_dict_for_test = sheraf.LargeDictAttribute(sheraf.ModelAttribute(model))
a = AModel.create()
b = AModel.create()
another = AnotherModel.create()
assert {} == dict(another.a_dict_for_test)
another.a_dict_for_test.clear()
assert {} == dict(another.a_dict_for_test)
assert 0 == len(another.a_dict_for_test)
with pytest.raises(KeyError):
another.a_dict_for_test["a"]
another.a_dict_for_test["a"] = a
another.a_dict_for_test["b"] = b
_another = AnotherModel.read(another.id)
assert _another.a_dict_for_test["a"] == a
assert _another.a_dict_for_test["b"] == b
assert {"a": a, "b": b} == dict(_another.a_dict_for_test)
assert 2 == len(_another.a_dict_for_test)
assert "a" in _another.a_dict_for_test
assert "b" in _another.a_dict_for_test
assert not ("c" in _another.a_dict_for_test)
assert ["a", "b"] == list(another.a_dict_for_test.keys())
assert [("a", a), ("b", b)] == list(another.a_dict_for_test.items())
assert [a, b] == list(another.a_dict_for_test.values())
c = iter(another.a_dict_for_test)
assert {"a", "b"} == {next(c), next(c)}
del _another.a_dict_for_test["a"]
assert {"b": b} == dict(_another.a_dict_for_test)
assert 1 == len(another.a_dict_for_test)
_another.a_dict_for_test.clear()
assert {} == dict(_another.a_dict_for_test)
another.a_dict_for_test = {"a": a, "b": b}
_another = AnotherModel.read(another.id)
assert {"a": a, "b": b} == dict(_another.a_dict_for_test)
def test_error_if_delete_a_nonexisting_key(sheraf_connection):
class _AnotherModel(tests.UUIDAutoModel):
a_dict_for_test = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
another = _AnotherModel.create()
with pytest.raises(KeyError):
del another.a_dict_for_test["a"]
def test_create(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "A"}, "b": {"name": "B"}})
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["a"], AModel)
assert isinstance(model.models["a"].mapping, sheraf.types.SmallDict)
assert "A" == model.models["a"].name
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["a"], AModel)
assert isinstance(model.models["a"].mapping, sheraf.types.SmallDict)
assert "A" == model.models["a"].name
def test_update_edition(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "c"}, "b": {"name": "c"}})
last_sub_id = model.models["a"].id
with sheraf.connection(commit=True):
model.edit(value={"models": {"a": {"name": "a"}, "b": {"name": "b"}}})
assert isinstance(model.models["a"], AModel)
assert isinstance(model.models["b"], AModel)
assert "a" == model.models["a"].name
assert "b" == model.models["b"].name
assert last_sub_id == model.models["a"].id
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.models["a"], AModel)
assert isinstance(model.models["b"], AModel)
assert "a" == model.models["a"].name
assert "b" == model.models["b"].name
assert last_sub_id == model.models["a"].id
def test_update_no_edition(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "c"}, "b": {"name": "c"}})
last_sub_id = model.models["a"].id
with sheraf.connection(commit=True):
old_submapping = model.models["a"].mapping
model.edit(
value={"models": {"a": {"name": "a"}, "b": {"name": "b"}}}, edition=False
)
new_submapping = model.models["a"].mapping
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["a"], AModel)
assert isinstance(new_submapping, sheraf.types.SmallDict)
assert "c" == model.models["a"].name
assert "c" == model.models["b"].name
assert old_submapping is new_submapping
assert last_sub_id == model.models["a"].id
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["a"], AModel)
assert isinstance(new_submapping, sheraf.types.SmallDict)
assert "c" == model.models["a"].name
assert "c" == model.models["b"].name
assert old_submapping is new_submapping
assert last_sub_id == model.models["a"].id
def test_update_replacement(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "c"}, "b": {"name": "c"}})
last_sub_id = model.models["a"].id
with sheraf.connection(commit=True):
old_submapping = model.models["a"].mapping
model.edit(
value={"models": {"a": {"name": "a"}, "b": {"name": "b"}}},
edition=True,
replacement=True,
)
new_submapping = model.models["a"].mapping
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["a"], AModel)
assert isinstance(new_submapping, sheraf.types.SmallDict)
assert "a" == model.models["a"].name
assert "b" == model.models["b"].name
assert old_submapping is not new_submapping
assert last_sub_id != model.models["a"].id
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["a"], AModel)
assert isinstance(new_submapping, sheraf.types.SmallDict)
assert "a" == model.models["a"].name
assert "b" == model.models["b"].name
assert old_submapping is not new_submapping
assert last_sub_id != model.models["a"].id
def test_update_addition(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "a"}})
with sheraf.connection(commit=True):
model.edit(value={"models": {"b": {"name": "b"}}}, addition=False)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert "b" not in model.models
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert "b" not in model.models
def test_update_no_addition(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "a"}})
with sheraf.connection(commit=True):
model.edit(value={"models": {"b": {"name": "b"}}}, addition=True)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["b"], AModel)
assert isinstance(model.models["b"].mapping, sheraf.types.SmallDict)
assert "a" == model.models["a"].name
assert "b" == model.models["b"].name
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert isinstance(model.models["b"], AModel)
assert isinstance(model.models["b"].mapping, sheraf.types.SmallDict)
assert "a" == model.models["a"].name
assert "b" == model.models["b"].name
def test_update_deletion(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "a"}})
with sheraf.connection(commit=True):
model.edit(value={"models": {}}, deletion=True)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert "a" not in model.models
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert "a" not in model.models
def test_update_no_deletion(sheraf_database):
class Model(tests.UUIDAutoModel):
models = sheraf.LargeDictAttribute(sheraf.ModelAttribute(AModel))
with sheraf.connection(commit=True):
model = Model.create(models={"a": {"name": "a"}})
with sheraf.connection(commit=True):
model.edit(value={"models": {}}, deletion=False)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert "a" in model.models
with sheraf.connection():
model = Model.read(model.id)
assert isinstance(model.mapping["models"], sheraf.types.LargeDict)
assert "a" in model.models
| 36.343066
| 85
| 0.649026
| 1,232
| 9,958
| 5.094968
| 0.0625
| 0.092879
| 0.063087
| 0.053529
| 0.926079
| 0.916361
| 0.907758
| 0.869205
| 0.845308
| 0.829536
| 0
| 0.000375
| 0.19763
| 9,958
| 273
| 86
| 36.47619
| 0.785232
| 0
| 0
| 0.678049
| 0
| 0
| 0.042077
| 0.007431
| 0
| 0
| 0
| 0
| 0.419512
| 1
| 0.04878
| false
| 0
| 0.014634
| 0
| 0.170732
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
1df6588efa370ab1b357512d92d5b8c8c15c8ae6
| 57
|
py
|
Python
|
automl/__init__.py
|
viriditycapital/automl
|
b30577dacdc570ffb180fce1487e3105f822f98e
|
[
"MIT"
] | null | null | null |
automl/__init__.py
|
viriditycapital/automl
|
b30577dacdc570ffb180fce1487e3105f822f98e
|
[
"MIT"
] | null | null | null |
automl/__init__.py
|
viriditycapital/automl
|
b30577dacdc570ffb180fce1487e3105f822f98e
|
[
"MIT"
] | null | null | null |
from .base import classifier
from .base import regressor
| 19
| 28
| 0.824561
| 8
| 57
| 5.875
| 0.625
| 0.340426
| 0.595745
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.140351
| 57
| 2
| 29
| 28.5
| 0.959184
| 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
|
1dfd932bd066c74aca55daa89cd6996cab717de7
| 4,567
|
py
|
Python
|
extract/tests/test_extract_maindisplay.py
|
SbastianGarzon/o2r-meta
|
ec5f7c6d432cbb43ab7df2985fc502e60fe7bcff
|
[
"Apache-2.0"
] | 2
|
2017-06-28T14:47:57.000Z
|
2020-11-10T01:59:11.000Z
|
extract/tests/test_extract_maindisplay.py
|
SbastianGarzon/o2r-meta
|
ec5f7c6d432cbb43ab7df2985fc502e60fe7bcff
|
[
"Apache-2.0"
] | 95
|
2016-07-14T13:21:52.000Z
|
2021-04-08T12:51:53.000Z
|
extract/tests/test_extract_maindisplay.py
|
SbastianGarzon/o2r-meta
|
ec5f7c6d432cbb43ab7df2985fc502e60fe7bcff
|
[
"Apache-2.0"
] | 4
|
2016-07-21T12:16:37.000Z
|
2021-10-04T13:31:40.000Z
|
# pylint: skip-file
import os
import json
def test_compendium(script_runner, tmpdir):
ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract',
'-i', 'extract/tests/compendium',
'-o', str(tmpdir),
'-xo', '-m')
print(ret.stdout)
print(ret.stderr)
assert ret.success, "process should return success"
assert ret.stderr == '', "stderr should be empty"
assert "total files processed: 1" in ret.stdout, "should process 1 file"
metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json')))
assert metadata['displayfile'] == "paper.html"
assert metadata['mainfile'] == "paper.rmd"
def test_compendium_basedir(script_runner, tmpdir):
ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract',
'-i', 'extract/tests/compendium',
'-o', str(tmpdir),
'-b', 'extract/tests/compendium',
'-xo', '-m')
print(ret.stdout)
print(ret.stderr)
assert ret.success, "process should return success"
assert ret.stderr == '', "stderr should be empty"
assert "total files processed: 1" in ret.stdout, "should process 1 file"
metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json')))
assert metadata['displayfile'] == "paper.html"
assert metadata['mainfile'] == "paper.rmd"
def test_minimal(script_runner, tmpdir):
ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract',
'-i', 'extract/tests/minimal',
'-o', str(tmpdir),
'-xo', '-m')
print(ret.stdout)
print(ret.stderr)
assert ret.success, "process should return success"
assert ret.stderr == '', "stderr should be empty"
assert "total files processed: 2" in ret.stdout, "should process 2 files"
metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json')))
assert metadata['displayfile'] == "extract/tests/minimal/display.html"
assert metadata['mainfile'] == "extract/tests/minimal/main.Rmd"
def test_minimal_basedir(script_runner, tmpdir):
ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract',
'-i', 'extract/tests/minimal',
'-o', str(tmpdir),
'-b', 'extract/tests/minimal',
'-xo', '-m')
print(ret.stdout)
print(ret.stderr)
assert ret.success, "process should return success"
assert ret.stderr == '', "stderr should be empty"
assert "total files processed: 2" in ret.stdout, "should process 2 files"
metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json')))
assert metadata['displayfile'] == "display.html", "displayfile path should be relative to basedir"
assert metadata['mainfile'] == "main.Rmd", "mainfile path should be relative to basedir"
def test_best_displayfile_candidate(script_runner, tmpdir):
ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract',
'-i', 'extract/tests/displayfiles/best_by_name',
'-o', str(tmpdir),
'-b', 'extract/tests/displayfiles/best_by_name',
'-xo', '-m')
print(ret.stdout)
print(ret.stderr)
assert ret.success, "process should return success"
assert ret.stderr == '', "stderr should be empty"
metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json')))
assert metadata['displayfile'] == "display.html", "best matching file should be displayfile"
assert len(metadata['displayfile_candidates']) == 7, "should have 7 candidates"
assert "display.pdf" not in metadata['displayfile_candidates'], "should not list pdf as displayfile candidate"
assert metadata['displayfile_candidates'][0] == "display.html", "best matching displayfile should be first in candidate list"
def test_best_mainfile_candidate(script_runner, tmpdir):
ret = script_runner.run('python3', 'o2rmeta.py', '-debug', 'extract',
'-i', 'extract/tests/displayfiles/best_by_name',
'-o', str(tmpdir),
'-b', 'extract/tests/displayfiles/best_by_name',
'-xo', '-m')
print(ret.stdout)
print(ret.stderr)
assert ret.success, "process should return success"
assert ret.stderr == '', "stderr should be empty"
metadata = json.load(open(os.path.join(str(tmpdir), 'metadata_raw.json')))
assert metadata['mainfile'] == "main.Rmd", "best matching file should be displayfile"
assert len(metadata['mainfile_candidates']) == 4, "should have 4 candidates"
assert metadata['mainfile_candidates'][0] == "main.Rmd", "best matching displayfile should be first in candidate list"
| 43.495238
| 129
| 0.659733
| 574
| 4,567
| 5.174216
| 0.132404
| 0.048485
| 0.036364
| 0.042424
| 0.834007
| 0.819192
| 0.790909
| 0.790909
| 0.790909
| 0.721549
| 0
| 0.006978
| 0.184147
| 4,567
| 105
| 130
| 43.495238
| 0.790123
| 0.003722
| 0
| 0.752941
| 0
| 0
| 0.411959
| 0.092548
| 0
| 0
| 0
| 0
| 0.364706
| 1
| 0.070588
| false
| 0
| 0.023529
| 0
| 0.094118
| 0.141176
| 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
|
3816f9c2b6a94347effb36f23509c183af7113ef
| 149
|
py
|
Python
|
dizge/__init__.py
|
erayerdin/dizge
|
873bc2a9e0a620d161fcc40c35384d58370c9470
|
[
"MIT"
] | null | null | null |
dizge/__init__.py
|
erayerdin/dizge
|
873bc2a9e0a620d161fcc40c35384d58370c9470
|
[
"MIT"
] | null | null | null |
dizge/__init__.py
|
erayerdin/dizge
|
873bc2a9e0a620d161fcc40c35384d58370c9470
|
[
"MIT"
] | null | null | null |
from dizge.tools.phonology import *
from dizge.competence.phonology import *
from dizge.competence.lexicon import *
from dizge.analyzer import *
| 29.8
| 41
| 0.791946
| 19
| 149
| 6.210526
| 0.421053
| 0.305085
| 0.381356
| 0.40678
| 0.576271
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.134228
| 149
| 4
| 42
| 37.25
| 0.914729
| 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
|
69dcee722b61115f574a36323deac7a3bce8b77f
| 86,866
|
py
|
Python
|
nova/tests/unit/api/openstack/compute/test_volumes.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/api/openstack/compute/test_volumes.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/api/openstack/compute/test_volumes.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | 2
|
2017-07-20T17:31:34.000Z
|
2020-07-24T02:42:19.000Z
|
begin_unit
comment|'# Copyright 2013 Josh Durgin'
nl|'\n'
comment|'# Copyright 2013 Red Hat, Inc.'
nl|'\n'
comment|'# All Rights Reserved.'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may'
nl|'\n'
comment|'# not use this file except in compliance with the License. You may obtain'
nl|'\n'
comment|'# a copy of the License at'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# http://www.apache.org/licenses/LICENSE-2.0'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Unless required by applicable law or agreed to in writing, software'
nl|'\n'
comment|'# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT'
nl|'\n'
comment|'# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the'
nl|'\n'
comment|'# License for the specific language governing permissions and limitations'
nl|'\n'
comment|'# under the License.'
nl|'\n'
nl|'\n'
name|'import'
name|'datetime'
newline|'\n'
nl|'\n'
name|'import'
name|'mock'
newline|'\n'
name|'from'
name|'oslo_serialization'
name|'import'
name|'jsonutils'
newline|'\n'
name|'from'
name|'six'
op|'.'
name|'moves'
name|'import'
name|'urllib'
newline|'\n'
name|'import'
name|'webob'
newline|'\n'
name|'from'
name|'webob'
name|'import'
name|'exc'
newline|'\n'
nl|'\n'
name|'from'
name|'nova'
op|'.'
name|'api'
op|'.'
name|'openstack'
name|'import'
name|'common'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'api'
op|'.'
name|'openstack'
op|'.'
name|'compute'
name|'import'
name|'assisted_volume_snapshots'
name|'as'
name|'assisted_snaps_v21'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'api'
op|'.'
name|'openstack'
op|'.'
name|'compute'
name|'import'
name|'volumes'
name|'as'
name|'volumes_v21'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'compute'
name|'import'
name|'api'
name|'as'
name|'compute_api'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'compute'
name|'import'
name|'flavors'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'compute'
name|'import'
name|'vm_states'
newline|'\n'
name|'import'
name|'nova'
op|'.'
name|'conf'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'context'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'exception'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'objects'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'objects'
name|'import'
name|'base'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'test'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
op|'.'
name|'api'
op|'.'
name|'openstack'
name|'import'
name|'fakes'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
name|'import'
name|'fake_block_device'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
name|'import'
name|'fake_instance'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'volume'
name|'import'
name|'cinder'
newline|'\n'
nl|'\n'
DECL|variable|CONF
name|'CONF'
op|'='
name|'nova'
op|'.'
name|'conf'
op|'.'
name|'CONF'
newline|'\n'
nl|'\n'
DECL|variable|FAKE_UUID
name|'FAKE_UUID'
op|'='
string|"'aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa'"
newline|'\n'
DECL|variable|FAKE_UUID_A
name|'FAKE_UUID_A'
op|'='
string|"'00000000-aaaa-aaaa-aaaa-000000000000'"
newline|'\n'
DECL|variable|FAKE_UUID_B
name|'FAKE_UUID_B'
op|'='
string|"'bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb'"
newline|'\n'
DECL|variable|FAKE_UUID_C
name|'FAKE_UUID_C'
op|'='
string|"'cccccccc-cccc-cccc-cccc-cccccccccccc'"
newline|'\n'
DECL|variable|FAKE_UUID_D
name|'FAKE_UUID_D'
op|'='
string|"'dddddddd-dddd-dddd-dddd-dddddddddddd'"
newline|'\n'
nl|'\n'
DECL|variable|IMAGE_UUID
name|'IMAGE_UUID'
op|'='
string|"'c905cedb-7281-47e4-8a62-f26bc5fc4c77'"
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_get_instance
name|'def'
name|'fake_get_instance'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'instance_id'
op|','
name|'want_objects'
op|'='
name|'False'
op|','
nl|'\n'
name|'expected_attrs'
op|'='
name|'None'
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'fake_instance'
op|'.'
name|'fake_instance_obj'
op|'('
name|'context'
op|','
op|'**'
op|'{'
string|"'uuid'"
op|':'
name|'instance_id'
op|'}'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_get_volume
dedent|''
name|'def'
name|'fake_get_volume'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'id'
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
op|'{'
string|"'id'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'status'"
op|':'
string|"'available'"
op|','
nl|'\n'
string|"'attach_status'"
op|':'
string|"'detached'"
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_attach_volume
dedent|''
name|'def'
name|'fake_attach_volume'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'instance'
op|','
name|'volume_id'
op|','
name|'device'
op|')'
op|':'
newline|'\n'
indent|' '
name|'pass'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_detach_volume
dedent|''
name|'def'
name|'fake_detach_volume'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'instance'
op|','
name|'volume'
op|')'
op|':'
newline|'\n'
indent|' '
name|'pass'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_swap_volume
dedent|''
name|'def'
name|'fake_swap_volume'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'instance'
op|','
nl|'\n'
name|'old_volume_id'
op|','
name|'new_volume_id'
op|')'
op|':'
newline|'\n'
indent|' '
name|'pass'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_create_snapshot
dedent|''
name|'def'
name|'fake_create_snapshot'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'volume'
op|','
name|'name'
op|','
name|'description'
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
op|'{'
string|"'id'"
op|':'
number|'123'
op|','
nl|'\n'
string|"'volume_id'"
op|':'
string|"'fakeVolId'"
op|','
nl|'\n'
string|"'status'"
op|':'
string|"'available'"
op|','
nl|'\n'
string|"'volume_size'"
op|':'
number|'123'
op|','
nl|'\n'
string|"'created_at'"
op|':'
string|"'2013-01-01 00:00:01'"
op|','
nl|'\n'
string|"'display_name'"
op|':'
string|"'myVolumeName'"
op|','
nl|'\n'
string|"'display_description'"
op|':'
string|"'myVolumeDescription'"
op|'}'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_delete_snapshot
dedent|''
name|'def'
name|'fake_delete_snapshot'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'snapshot_id'
op|')'
op|':'
newline|'\n'
indent|' '
name|'pass'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_compute_volume_snapshot_delete
dedent|''
name|'def'
name|'fake_compute_volume_snapshot_delete'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'volume_id'
op|','
name|'snapshot_id'
op|','
nl|'\n'
name|'delete_info'
op|')'
op|':'
newline|'\n'
indent|' '
name|'pass'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_compute_volume_snapshot_create
dedent|''
name|'def'
name|'fake_compute_volume_snapshot_create'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'volume_id'
op|','
nl|'\n'
name|'create_info'
op|')'
op|':'
newline|'\n'
indent|' '
name|'pass'
newline|'\n'
nl|'\n'
nl|'\n'
dedent|''
op|'@'
name|'classmethod'
newline|'\n'
DECL|function|fake_bdm_list_get_by_instance_uuid
name|'def'
name|'fake_bdm_list_get_by_instance_uuid'
op|'('
name|'cls'
op|','
name|'context'
op|','
name|'instance_uuid'
op|')'
op|':'
newline|'\n'
indent|' '
name|'db_list'
op|'='
op|'['
name|'fake_block_device'
op|'.'
name|'FakeDbBlockDeviceDict'
op|'('
nl|'\n'
op|'{'
string|"'id'"
op|':'
number|'1'
op|','
nl|'\n'
string|"'instance_uuid'"
op|':'
name|'instance_uuid'
op|','
nl|'\n'
string|"'device_name'"
op|':'
string|"'/dev/fake0'"
op|','
nl|'\n'
string|"'delete_on_termination'"
op|':'
string|"'False'"
op|','
nl|'\n'
string|"'source_type'"
op|':'
string|"'volume'"
op|','
nl|'\n'
string|"'destination_type'"
op|':'
string|"'volume'"
op|','
nl|'\n'
string|"'snapshot_id'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'volume_id'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'volume_size'"
op|':'
number|'1'
op|'}'
op|')'
op|','
nl|'\n'
name|'fake_block_device'
op|'.'
name|'FakeDbBlockDeviceDict'
op|'('
nl|'\n'
op|'{'
string|"'id'"
op|':'
number|'2'
op|','
nl|'\n'
string|"'instance_uuid'"
op|':'
name|'instance_uuid'
op|','
nl|'\n'
string|"'device_name'"
op|':'
string|"'/dev/fake1'"
op|','
nl|'\n'
string|"'delete_on_termination'"
op|':'
string|"'False'"
op|','
nl|'\n'
string|"'source_type'"
op|':'
string|"'volume'"
op|','
nl|'\n'
string|"'destination_type'"
op|':'
string|"'volume'"
op|','
nl|'\n'
string|"'snapshot_id'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'volume_id'"
op|':'
name|'FAKE_UUID_B'
op|','
nl|'\n'
string|"'volume_size'"
op|':'
number|'1'
op|'}'
op|')'
op|']'
newline|'\n'
name|'item_cls'
op|'='
name|'objects'
op|'.'
name|'BlockDeviceMapping'
newline|'\n'
name|'return'
name|'base'
op|'.'
name|'obj_make_list'
op|'('
name|'context'
op|','
name|'cls'
op|'('
op|')'
op|','
name|'item_cls'
op|','
name|'db_list'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|BootFromVolumeTest
dedent|''
name|'class'
name|'BootFromVolumeTest'
op|'('
name|'test'
op|'.'
name|'TestCase'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'BootFromVolumeTest'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'create'"
op|','
nl|'\n'
name|'self'
op|'.'
name|'_get_fake_compute_api_create'
op|'('
op|')'
op|')'
newline|'\n'
name|'fakes'
op|'.'
name|'stub_out_nw_api'
op|'('
name|'self'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|'='
name|'None'
newline|'\n'
name|'self'
op|'.'
name|'_legacy_bdm_seen'
op|'='
name|'True'
newline|'\n'
name|'self'
op|'.'
name|'flags'
op|'('
nl|'\n'
name|'osapi_compute_extension'
op|'='
op|'['
nl|'\n'
string|"'nova.api.openstack.compute.contrib.select_extensions'"
op|']'
op|','
nl|'\n'
name|'osapi_compute_ext_list'
op|'='
op|'['
string|"'Volumes'"
op|','
string|"'Block_device_mapping_v2_boot'"
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|_get_fake_compute_api_create
dedent|''
name|'def'
name|'_get_fake_compute_api_create'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
DECL|function|_fake_compute_api_create
indent|' '
name|'def'
name|'_fake_compute_api_create'
op|'('
name|'cls'
op|','
name|'context'
op|','
name|'instance_type'
op|','
nl|'\n'
name|'image_href'
op|','
op|'**'
name|'kwargs'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|'='
name|'kwargs'
op|'.'
name|'get'
op|'('
nl|'\n'
string|"'block_device_mapping'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_legacy_bdm_seen'
op|'='
name|'kwargs'
op|'.'
name|'get'
op|'('
string|"'legacy_bdm'"
op|')'
newline|'\n'
nl|'\n'
name|'inst_type'
op|'='
name|'flavors'
op|'.'
name|'get_flavor_by_flavor_id'
op|'('
number|'2'
op|')'
newline|'\n'
name|'resv_id'
op|'='
name|'None'
newline|'\n'
name|'return'
op|'('
op|'['
op|'{'
string|"'id'"
op|':'
number|'1'
op|','
nl|'\n'
string|"'display_name'"
op|':'
string|"'test_server'"
op|','
nl|'\n'
string|"'uuid'"
op|':'
name|'FAKE_UUID'
op|','
nl|'\n'
string|"'instance_type'"
op|':'
name|'inst_type'
op|','
nl|'\n'
string|"'access_ip_v4'"
op|':'
string|"'1.2.3.4'"
op|','
nl|'\n'
string|"'access_ip_v6'"
op|':'
string|"'fead::1234'"
op|','
nl|'\n'
string|"'image_ref'"
op|':'
name|'IMAGE_UUID'
op|','
nl|'\n'
string|"'user_id'"
op|':'
string|"'fake'"
op|','
nl|'\n'
string|"'project_id'"
op|':'
string|"'fake'"
op|','
nl|'\n'
string|"'created_at'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
number|'2010'
op|','
number|'10'
op|','
number|'10'
op|','
number|'12'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'updated_at'"
op|':'
name|'datetime'
op|'.'
name|'datetime'
op|'('
number|'2010'
op|','
number|'11'
op|','
number|'11'
op|','
number|'11'
op|','
number|'0'
op|','
number|'0'
op|')'
op|','
nl|'\n'
string|"'progress'"
op|':'
number|'0'
op|','
nl|'\n'
string|"'fixed_ips'"
op|':'
op|'['
op|']'
nl|'\n'
op|'}'
op|']'
op|','
name|'resv_id'
op|')'
newline|'\n'
dedent|''
name|'return'
name|'_fake_compute_api_create'
newline|'\n'
nl|'\n'
DECL|member|test_create_root_volume
dedent|''
name|'def'
name|'test_create_root_volume'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
name|'dict'
op|'('
name|'server'
op|'='
name|'dict'
op|'('
nl|'\n'
name|'name'
op|'='
string|"'test_server'"
op|','
name|'imageRef'
op|'='
name|'IMAGE_UUID'
op|','
nl|'\n'
name|'flavorRef'
op|'='
number|'2'
op|','
name|'min_count'
op|'='
number|'1'
op|','
name|'max_count'
op|'='
number|'1'
op|','
nl|'\n'
name|'block_device_mapping'
op|'='
op|'['
name|'dict'
op|'('
nl|'\n'
name|'volume_id'
op|'='
string|"'1'"
op|','
nl|'\n'
name|'device_name'
op|'='
string|"'/dev/vda'"
op|','
nl|'\n'
name|'virtual'
op|'='
string|"'root'"
op|','
nl|'\n'
name|'delete_on_termination'
op|'='
name|'False'
op|','
nl|'\n'
op|')'
op|']'
nl|'\n'
op|')'
op|')'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/fake/os-volumes_boot'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
name|'body'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'res'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'fakes'
op|'.'
name|'wsgi_app'
op|'('
nl|'\n'
name|'init_only'
op|'='
op|'('
string|"'os-volumes_boot'"
op|','
string|"'servers'"
op|')'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'202'
op|','
name|'res'
op|'.'
name|'status_int'
op|')'
newline|'\n'
name|'server'
op|'='
name|'jsonutils'
op|'.'
name|'loads'
op|'('
name|'res'
op|'.'
name|'body'
op|')'
op|'['
string|"'server'"
op|']'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'FAKE_UUID'
op|','
name|'server'
op|'['
string|"'id'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'CONF'
op|'.'
name|'password_length'
op|','
name|'len'
op|'('
name|'server'
op|'['
string|"'adminPass'"
op|']'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'1'
op|','
name|'len'
op|'('
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertTrue'
op|'('
name|'self'
op|'.'
name|'_legacy_bdm_seen'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'1'"
op|','
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|'['
number|'0'
op|']'
op|'['
string|"'volume_id'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'/dev/vda'"
op|','
nl|'\n'
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|'['
number|'0'
op|']'
op|'['
string|"'device_name'"
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_create_root_volume_bdm_v2
dedent|''
name|'def'
name|'test_create_root_volume_bdm_v2'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
name|'dict'
op|'('
name|'server'
op|'='
name|'dict'
op|'('
nl|'\n'
name|'name'
op|'='
string|"'test_server'"
op|','
name|'imageRef'
op|'='
name|'IMAGE_UUID'
op|','
nl|'\n'
name|'flavorRef'
op|'='
number|'2'
op|','
name|'min_count'
op|'='
number|'1'
op|','
name|'max_count'
op|'='
number|'1'
op|','
nl|'\n'
name|'block_device_mapping_v2'
op|'='
op|'['
name|'dict'
op|'('
nl|'\n'
name|'source_type'
op|'='
string|"'volume'"
op|','
nl|'\n'
name|'uuid'
op|'='
string|"'1'"
op|','
nl|'\n'
name|'device_name'
op|'='
string|"'/dev/vda'"
op|','
nl|'\n'
name|'boot_index'
op|'='
number|'0'
op|','
nl|'\n'
name|'delete_on_termination'
op|'='
name|'False'
op|','
nl|'\n'
op|')'
op|']'
nl|'\n'
op|')'
op|')'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/fake/os-volumes_boot'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
name|'body'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'res'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'fakes'
op|'.'
name|'wsgi_app'
op|'('
nl|'\n'
name|'init_only'
op|'='
op|'('
string|"'os-volumes_boot'"
op|','
string|"'servers'"
op|')'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'202'
op|','
name|'res'
op|'.'
name|'status_int'
op|')'
newline|'\n'
name|'server'
op|'='
name|'jsonutils'
op|'.'
name|'loads'
op|'('
name|'res'
op|'.'
name|'body'
op|')'
op|'['
string|"'server'"
op|']'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'FAKE_UUID'
op|','
name|'server'
op|'['
string|"'id'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'CONF'
op|'.'
name|'password_length'
op|','
name|'len'
op|'('
name|'server'
op|'['
string|"'adminPass'"
op|']'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'1'
op|','
name|'len'
op|'('
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertFalse'
op|'('
name|'self'
op|'.'
name|'_legacy_bdm_seen'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'1'"
op|','
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|'['
number|'0'
op|']'
op|'['
string|"'volume_id'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'0'
op|','
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|'['
number|'0'
op|']'
op|'['
string|"'boot_index'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'/dev/vda'"
op|','
nl|'\n'
name|'self'
op|'.'
name|'_block_device_mapping_seen'
op|'['
number|'0'
op|']'
op|'['
string|"'device_name'"
op|']'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|VolumeApiTestV21
dedent|''
dedent|''
name|'class'
name|'VolumeApiTestV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
DECL|variable|url_prefix
indent|' '
name|'url_prefix'
op|'='
string|"'/v2/fake'"
newline|'\n'
nl|'\n'
DECL|member|setUp
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'VolumeApiTestV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'fakes'
op|'.'
name|'stub_out_networking'
op|'('
name|'self'
op|')'
newline|'\n'
name|'fakes'
op|'.'
name|'stub_out_rate_limiting'
op|'('
name|'self'
op|'.'
name|'stubs'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|'"delete"'
op|','
name|'fakes'
op|'.'
name|'stub_volume_delete'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|'"get"'
op|','
name|'fakes'
op|'.'
name|'stub_volume_get'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|'"get_all"'
op|','
name|'fakes'
op|'.'
name|'stub_volume_get_all'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'flags'
op|'('
nl|'\n'
name|'osapi_compute_extension'
op|'='
op|'['
nl|'\n'
string|"'nova.api.openstack.compute.contrib.select_extensions'"
op|']'
op|','
nl|'\n'
name|'osapi_compute_ext_list'
op|'='
op|'['
string|"'Volumes'"
op|']'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'context'
op|'='
name|'context'
op|'.'
name|'get_admin_context'
op|'('
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'property'
newline|'\n'
DECL|member|app
name|'def'
name|'app'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'fakes'
op|'.'
name|'wsgi_app_v21'
op|'('
name|'init_only'
op|'='
op|'('
string|"'os-volumes'"
op|','
string|"'servers'"
op|')'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_create
dedent|''
name|'def'
name|'test_volume_create'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|'"create"'
op|','
name|'fakes'
op|'.'
name|'stub_volume_create'
op|')'
newline|'\n'
nl|'\n'
name|'vol'
op|'='
op|'{'
string|'"size"'
op|':'
number|'100'
op|','
nl|'\n'
string|'"display_name"'
op|':'
string|'"Volume Test Name"'
op|','
nl|'\n'
string|'"display_description"'
op|':'
string|'"Volume Test Desc"'
op|','
nl|'\n'
string|'"availability_zone"'
op|':'
string|'"zone1:host1"'
op|'}'
newline|'\n'
name|'body'
op|'='
op|'{'
string|'"volume"'
op|':'
name|'vol'
op|'}'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
name|'body'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'resp'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'self'
op|'.'
name|'app'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'200'
op|','
name|'resp'
op|'.'
name|'status_int'
op|')'
newline|'\n'
nl|'\n'
name|'resp_dict'
op|'='
name|'jsonutils'
op|'.'
name|'loads'
op|'('
name|'resp'
op|'.'
name|'body'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|"'volume'"
op|','
name|'resp_dict'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'vol'
op|'['
string|"'size'"
op|']'
op|','
name|'resp_dict'
op|'['
string|"'volume'"
op|']'
op|'['
string|"'size'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'vol'
op|'['
string|"'display_name'"
op|']'
op|','
nl|'\n'
name|'resp_dict'
op|'['
string|"'volume'"
op|']'
op|'['
string|"'displayName'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'vol'
op|'['
string|"'display_description'"
op|']'
op|','
nl|'\n'
name|'resp_dict'
op|'['
string|"'volume'"
op|']'
op|'['
string|"'displayDescription'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'vol'
op|'['
string|"'availability_zone'"
op|']'
op|','
nl|'\n'
name|'resp_dict'
op|'['
string|"'volume'"
op|']'
op|'['
string|"'availabilityZone'"
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|_test_volume_translate_exception
dedent|''
name|'def'
name|'_test_volume_translate_exception'
op|'('
name|'self'
op|','
name|'cinder_exc'
op|','
name|'api_exc'
op|')'
op|':'
newline|'\n'
indent|' '
string|'"""Tests that cinder exceptions are correctly translated"""'
newline|'\n'
DECL|function|fake_volume_create
name|'def'
name|'fake_volume_create'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'size'
op|','
name|'name'
op|','
name|'description'
op|','
nl|'\n'
name|'snapshot'
op|','
op|'**'
name|'param'
op|')'
op|':'
newline|'\n'
indent|' '
name|'raise'
name|'cinder_exc'
newline|'\n'
nl|'\n'
dedent|''
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|'"create"'
op|','
name|'fake_volume_create'
op|')'
newline|'\n'
nl|'\n'
name|'vol'
op|'='
op|'{'
string|'"size"'
op|':'
string|"'10'"
op|','
nl|'\n'
string|'"display_name"'
op|':'
string|'"Volume Test Name"'
op|','
nl|'\n'
string|'"display_description"'
op|':'
string|'"Volume Test Desc"'
op|','
nl|'\n'
string|'"availability_zone"'
op|':'
string|'"zone1:host1"'
op|'}'
newline|'\n'
name|'body'
op|'='
op|'{'
string|'"volume"'
op|':'
name|'vol'
op|'}'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'api_exc'
op|','
nl|'\n'
name|'volumes_v21'
op|'.'
name|'VolumeController'
op|'('
op|')'
op|'.'
name|'create'
op|','
name|'req'
op|','
nl|'\n'
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|"'get_snapshot'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|"'create'"
op|')'
newline|'\n'
DECL|member|test_volume_create_bad_snapshot_id
name|'def'
name|'test_volume_create_bad_snapshot_id'
op|'('
name|'self'
op|','
name|'mock_create'
op|','
name|'mock_get'
op|')'
op|':'
newline|'\n'
indent|' '
name|'vol'
op|'='
op|'{'
string|'"snapshot_id"'
op|':'
string|"'1'"
op|','
string|'"size"'
op|':'
number|'10'
op|'}'
newline|'\n'
name|'body'
op|'='
op|'{'
string|'"volume"'
op|':'
name|'vol'
op|'}'
newline|'\n'
name|'mock_get'
op|'.'
name|'side_effect'
op|'='
name|'exception'
op|'.'
name|'SnapshotNotFound'
op|'('
name|'snapshot_id'
op|'='
string|"'1'"
op|')'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPNotFound'
op|','
nl|'\n'
name|'volumes_v21'
op|'.'
name|'VolumeController'
op|'('
op|')'
op|'.'
name|'create'
op|','
name|'req'
op|','
nl|'\n'
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_create_bad_input
dedent|''
name|'def'
name|'test_volume_create_bad_input'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_test_volume_translate_exception'
op|'('
nl|'\n'
name|'exception'
op|'.'
name|'InvalidInput'
op|'('
name|'reason'
op|'='
string|"'fake'"
op|')'
op|','
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPBadRequest'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_create_bad_quota
dedent|''
name|'def'
name|'test_volume_create_bad_quota'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_test_volume_translate_exception'
op|'('
nl|'\n'
name|'exception'
op|'.'
name|'OverQuota'
op|'('
name|'overs'
op|'='
string|"'fake'"
op|')'
op|','
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPForbidden'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_index
dedent|''
name|'def'
name|'test_volume_index'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes'"
op|')'
newline|'\n'
name|'resp'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'self'
op|'.'
name|'app'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'200'
op|','
name|'resp'
op|'.'
name|'status_int'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_detail
dedent|''
name|'def'
name|'test_volume_detail'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes/detail'"
op|')'
newline|'\n'
name|'resp'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'self'
op|'.'
name|'app'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'200'
op|','
name|'resp'
op|'.'
name|'status_int'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_show
dedent|''
name|'def'
name|'test_volume_show'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes/123'"
op|')'
newline|'\n'
name|'resp'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'self'
op|'.'
name|'app'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'200'
op|','
name|'resp'
op|'.'
name|'status_int'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_show_no_volume
dedent|''
name|'def'
name|'test_volume_show_no_volume'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|'"get"'
op|','
name|'fakes'
op|'.'
name|'stub_volume_notfound'
op|')'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes/456'"
op|')'
newline|'\n'
name|'resp'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'self'
op|'.'
name|'app'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'404'
op|','
name|'resp'
op|'.'
name|'status_int'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|"'Volume 456 could not be found.'"
op|','
name|'resp'
op|'.'
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_delete
dedent|''
name|'def'
name|'test_volume_delete'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes/123'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'resp'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'self'
op|'.'
name|'app'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'202'
op|','
name|'resp'
op|'.'
name|'status_int'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_volume_delete_no_volume
dedent|''
name|'def'
name|'test_volume_delete_no_volume'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|'"delete"'
op|','
name|'fakes'
op|'.'
name|'stub_volume_notfound'
op|')'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
name|'self'
op|'.'
name|'url_prefix'
op|'+'
string|"'/os-volumes/456'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'resp'
op|'='
name|'req'
op|'.'
name|'get_response'
op|'('
name|'self'
op|'.'
name|'app'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'404'
op|','
name|'resp'
op|'.'
name|'status_int'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|"'Volume 456 could not be found.'"
op|','
name|'resp'
op|'.'
name|'body'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|VolumeAttachTestsV21
dedent|''
dedent|''
name|'class'
name|'VolumeAttachTestsV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
DECL|variable|validation_error
indent|' '
name|'validation_error'
op|'='
name|'exception'
op|'.'
name|'ValidationError'
newline|'\n'
nl|'\n'
DECL|member|setUp
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'VolumeAttachTestsV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stub_out'
op|'('
string|"'nova.objects.BlockDeviceMappingList'"
nl|'\n'
string|"'.get_by_instance_uuid'"
op|','
nl|'\n'
name|'fake_bdm_list_get_by_instance_uuid'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'get'"
op|','
name|'fake_get_instance'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'cinder'
op|'.'
name|'API'
op|','
string|"'get'"
op|','
name|'fake_get_volume'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'context'
op|'='
name|'context'
op|'.'
name|'get_admin_context'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'expected_show'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
nl|'\n'
op|'{'
string|"'device'"
op|':'
string|"'/dev/fake0'"
op|','
nl|'\n'
string|"'serverId'"
op|':'
name|'FAKE_UUID'
op|','
nl|'\n'
string|"'id'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
nl|'\n'
op|'}'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_set_up_controller'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|_set_up_controller
dedent|''
name|'def'
name|'_set_up_controller'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'attachments'
op|'='
name|'volumes_v21'
op|'.'
name|'VolumeAttachmentController'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show
dedent|''
name|'def'
name|'test_show'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'show'
op|'('
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'self'
op|'.'
name|'expected_show'
op|','
name|'result'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'get'"
op|','
nl|'\n'
name|'side_effect'
op|'='
name|'exception'
op|'.'
name|'InstanceNotFound'
op|'('
name|'instance_id'
op|'='
name|'FAKE_UUID'
op|')'
op|')'
newline|'\n'
DECL|member|test_show_no_instance
name|'def'
name|'test_show_no_instance'
op|'('
name|'self'
op|','
name|'mock_mr'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exc'
op|'.'
name|'HTTPNotFound'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'show'
op|','
nl|'\n'
name|'req'
op|','
nl|'\n'
name|'FAKE_UUID'
op|','
nl|'\n'
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'objects'
op|'.'
name|'BlockDeviceMappingList'
op|','
nl|'\n'
string|"'get_by_instance_uuid'"
op|','
name|'return_value'
op|'='
name|'None'
op|')'
newline|'\n'
DECL|member|test_show_no_bdms
name|'def'
name|'test_show_no_bdms'
op|'('
name|'self'
op|','
name|'mock_mr'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exc'
op|'.'
name|'HTTPNotFound'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'show'
op|','
nl|'\n'
name|'req'
op|','
nl|'\n'
name|'FAKE_UUID'
op|','
nl|'\n'
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show_bdms_no_mountpoint
dedent|''
name|'def'
name|'test_show_bdms_no_mountpoint'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'FAKE_UUID_NOTEXIST'
op|'='
string|"'00000000-aaaa-aaaa-aaaa-aaaaaaaaaaaa'"
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exc'
op|'.'
name|'HTTPNotFound'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'show'
op|','
nl|'\n'
name|'req'
op|','
nl|'\n'
name|'FAKE_UUID'
op|','
nl|'\n'
name|'FAKE_UUID_NOTEXIST'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_detach
dedent|''
name|'def'
name|'test_detach'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'detach_volume'"
op|','
nl|'\n'
name|'fake_detach_volume'
op|')'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'delete'
op|'('
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
comment|'# NOTE: on v2.1, http status code is set as wsgi_code of API'
nl|'\n'
comment|'# method instead of status_int in a response object.'
nl|'\n'
name|'if'
name|'isinstance'
op|'('
name|'self'
op|'.'
name|'attachments'
op|','
nl|'\n'
name|'volumes_v21'
op|'.'
name|'VolumeAttachmentController'
op|')'
op|':'
newline|'\n'
indent|' '
name|'status_int'
op|'='
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'delete'
op|'.'
name|'wsgi_code'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'status_int'
op|'='
name|'result'
op|'.'
name|'status_int'
newline|'\n'
dedent|''
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'202'
op|','
name|'status_int'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'common'
op|','
string|"'get_instance'"
op|')'
newline|'\n'
DECL|member|test_detach_vol_shelved_not_supported
name|'def'
name|'test_detach_vol_shelved_not_supported'
op|'('
name|'self'
op|','
name|'mock_get_instance'
op|')'
op|':'
newline|'\n'
indent|' '
name|'inst'
op|'='
name|'fake_instance'
op|'.'
name|'fake_instance_obj'
op|'('
name|'self'
op|'.'
name|'context'
op|','
nl|'\n'
op|'**'
op|'{'
string|"'uuid'"
op|':'
name|'FAKE_UUID'
op|'}'
op|')'
newline|'\n'
name|'inst'
op|'.'
name|'vm_state'
op|'='
name|'vm_states'
op|'.'
name|'SHELVED'
newline|'\n'
name|'mock_get_instance'
op|'.'
name|'return_value'
op|'='
name|'inst'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|','
name|'version'
op|'='
string|"'2.19'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPConflict'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'delete'
op|','
nl|'\n'
name|'req'
op|','
nl|'\n'
name|'FAKE_UUID'
op|','
nl|'\n'
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'detach_volume'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'common'
op|','
string|"'get_instance'"
op|')'
newline|'\n'
DECL|member|test_detach_vol_shelved_supported
name|'def'
name|'test_detach_vol_shelved_supported'
op|'('
name|'self'
op|','
nl|'\n'
name|'mock_get_instance'
op|','
nl|'\n'
name|'mock_detach'
op|')'
op|':'
newline|'\n'
indent|' '
name|'inst'
op|'='
name|'fake_instance'
op|'.'
name|'fake_instance_obj'
op|'('
name|'self'
op|'.'
name|'context'
op|','
nl|'\n'
op|'**'
op|'{'
string|"'uuid'"
op|':'
name|'FAKE_UUID'
op|'}'
op|')'
newline|'\n'
name|'inst'
op|'.'
name|'vm_state'
op|'='
name|'vm_states'
op|'.'
name|'SHELVED'
newline|'\n'
name|'mock_get_instance'
op|'.'
name|'return_value'
op|'='
name|'inst'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|','
name|'version'
op|'='
string|"'2.20'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'delete'
op|'('
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertTrue'
op|'('
name|'mock_detach'
op|'.'
name|'called'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_detach_vol_not_found
dedent|''
name|'def'
name|'test_detach_vol_not_found'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'detach_volume'"
op|','
nl|'\n'
name|'fake_detach_volume'
op|')'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exc'
op|'.'
name|'HTTPNotFound'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'delete'
op|','
nl|'\n'
name|'req'
op|','
nl|'\n'
name|'FAKE_UUID'
op|','
nl|'\n'
name|'FAKE_UUID_C'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'('
string|"'nova.objects.BlockDeviceMapping.is_root'"
op|','
nl|'\n'
name|'new_callable'
op|'='
name|'mock'
op|'.'
name|'PropertyMock'
op|')'
newline|'\n'
DECL|member|test_detach_vol_root
name|'def'
name|'test_detach_vol_root'
op|'('
name|'self'
op|','
name|'mock_isroot'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'mock_isroot'
op|'.'
name|'return_value'
op|'='
name|'True'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exc'
op|'.'
name|'HTTPForbidden'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'delete'
op|','
nl|'\n'
name|'req'
op|','
nl|'\n'
name|'FAKE_UUID'
op|','
nl|'\n'
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_detach_volume_from_locked_server
dedent|''
name|'def'
name|'test_detach_volume_from_locked_server'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
DECL|function|fake_detach_volume_from_locked_server
indent|' '
name|'def'
name|'fake_detach_volume_from_locked_server'
op|'('
name|'self'
op|','
name|'context'
op|','
nl|'\n'
name|'instance'
op|','
name|'volume'
op|')'
op|':'
newline|'\n'
indent|' '
name|'raise'
name|'exception'
op|'.'
name|'InstanceIsLocked'
op|'('
name|'instance_uuid'
op|'='
name|'instance'
op|'['
string|"'uuid'"
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'detach_volume'"
op|','
nl|'\n'
name|'fake_detach_volume_from_locked_server'
op|')'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPConflict'
op|','
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'delete'
op|','
nl|'\n'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume
dedent|''
name|'def'
name|'test_attach_volume'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'attach_volume'"
op|','
nl|'\n'
name|'fake_attach_volume'
op|')'
newline|'\n'
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|'}'
op|'}'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|'('
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'00000000-aaaa-aaaa-aaaa-000000000000'"
op|','
nl|'\n'
name|'result'
op|'['
string|"'volumeAttachment'"
op|']'
op|'['
string|"'id'"
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'common'
op|','
string|"'get_instance'"
op|')'
newline|'\n'
DECL|member|test_attach_vol_shelved_not_supported
name|'def'
name|'test_attach_vol_shelved_not_supported'
op|'('
name|'self'
op|','
name|'mock_get_instance'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|'}'
op|'}'
newline|'\n'
nl|'\n'
name|'inst'
op|'='
name|'fake_instance'
op|'.'
name|'fake_instance_obj'
op|'('
name|'self'
op|'.'
name|'context'
op|','
nl|'\n'
op|'**'
op|'{'
string|"'uuid'"
op|':'
name|'FAKE_UUID'
op|'}'
op|')'
newline|'\n'
name|'inst'
op|'.'
name|'vm_state'
op|'='
name|'vm_states'
op|'.'
name|'SHELVED'
newline|'\n'
name|'mock_get_instance'
op|'.'
name|'return_value'
op|'='
name|'inst'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|','
nl|'\n'
name|'version'
op|'='
string|"'2.19'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPConflict'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|','
nl|'\n'
name|'req'
op|','
nl|'\n'
name|'FAKE_UUID'
op|','
nl|'\n'
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'attach_volume'"
op|','
nl|'\n'
name|'return_value'
op|'='
string|"'/dev/myfake'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'common'
op|','
string|"'get_instance'"
op|')'
newline|'\n'
DECL|member|test_attach_vol_shelved_supported
name|'def'
name|'test_attach_vol_shelved_supported'
op|'('
name|'self'
op|','
nl|'\n'
name|'mock_get_instance'
op|','
nl|'\n'
name|'mock_attach'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|'}'
op|'}'
newline|'\n'
nl|'\n'
name|'inst'
op|'='
name|'fake_instance'
op|'.'
name|'fake_instance_obj'
op|'('
name|'self'
op|'.'
name|'context'
op|','
nl|'\n'
op|'**'
op|'{'
string|"'uuid'"
op|':'
name|'FAKE_UUID'
op|'}'
op|')'
newline|'\n'
name|'inst'
op|'.'
name|'vm_state'
op|'='
name|'vm_states'
op|'.'
name|'SHELVED'
newline|'\n'
name|'mock_get_instance'
op|'.'
name|'return_value'
op|'='
name|'inst'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|','
nl|'\n'
name|'version'
op|'='
string|"'2.20'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|'('
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'00000000-aaaa-aaaa-aaaa-000000000000'"
op|','
nl|'\n'
name|'result'
op|'['
string|"'volumeAttachment'"
op|']'
op|'['
string|"'id'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'/dev/myfake'"
op|','
name|'result'
op|'['
string|"'volumeAttachment'"
op|']'
op|'['
string|"'device'"
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'attach_volume'"
op|','
nl|'\n'
name|'return_value'
op|'='
string|"'/dev/myfake'"
op|')'
newline|'\n'
DECL|member|test_attach_volume_with_auto_device
name|'def'
name|'test_attach_volume_with_auto_device'
op|'('
name|'self'
op|','
name|'mock_attach'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
name|'None'
op|'}'
op|'}'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|'('
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'00000000-aaaa-aaaa-aaaa-000000000000'"
op|','
nl|'\n'
name|'result'
op|'['
string|"'volumeAttachment'"
op|']'
op|'['
string|"'id'"
op|']'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'/dev/myfake'"
op|','
name|'result'
op|'['
string|"'volumeAttachment'"
op|']'
op|'['
string|"'device'"
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume_to_locked_server
dedent|''
name|'def'
name|'test_attach_volume_to_locked_server'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
DECL|function|fake_attach_volume_to_locked_server
indent|' '
name|'def'
name|'fake_attach_volume_to_locked_server'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'instance'
op|','
nl|'\n'
name|'volume_id'
op|','
name|'device'
op|'='
name|'None'
op|')'
op|':'
newline|'\n'
indent|' '
name|'raise'
name|'exception'
op|'.'
name|'InstanceIsLocked'
op|'('
name|'instance_uuid'
op|'='
name|'instance'
op|'['
string|"'uuid'"
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'attach_volume'"
op|','
nl|'\n'
name|'fake_attach_volume_to_locked_server'
op|')'
newline|'\n'
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|'}'
op|'}'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPConflict'
op|','
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|','
nl|'\n'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume_bad_id
dedent|''
name|'def'
name|'test_attach_volume_bad_id'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'attach_volume'"
op|','
nl|'\n'
name|'fake_attach_volume'
op|')'
newline|'\n'
nl|'\n'
name|'body'
op|'='
op|'{'
nl|'\n'
string|"'volumeAttachment'"
op|':'
op|'{'
nl|'\n'
string|"'device'"
op|':'
name|'None'
op|','
nl|'\n'
string|"'volumeId'"
op|':'
string|"'TESTVOLUME'"
op|','
nl|'\n'
op|'}'
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'validation_error'
op|','
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|','
nl|'\n'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume_without_volumeId
dedent|''
name|'def'
name|'test_attach_volume_without_volumeId'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'attach_volume'"
op|','
nl|'\n'
name|'fake_attach_volume'
op|')'
newline|'\n'
nl|'\n'
name|'body'
op|'='
op|'{'
nl|'\n'
string|"'volumeAttachment'"
op|':'
op|'{'
nl|'\n'
string|"'device'"
op|':'
name|'None'
nl|'\n'
op|'}'
nl|'\n'
op|'}'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'validation_error'
op|','
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|','
nl|'\n'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_attach_volume_with_extra_arg
dedent|''
name|'def'
name|'test_attach_volume_with_extra_arg'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|','
nl|'\n'
string|"'extra'"
op|':'
string|"'extra_arg'"
op|'}'
op|'}'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/servers/id/os-volume_attachments'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'validation_error'
op|','
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'create'
op|','
nl|'\n'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|_test_swap
dedent|''
name|'def'
name|'_test_swap'
op|'('
name|'self'
op|','
name|'attachments'
op|','
name|'uuid'
op|'='
name|'FAKE_UUID_A'
op|','
nl|'\n'
name|'fake_func'
op|'='
name|'None'
op|','
name|'body'
op|'='
name|'None'
op|')'
op|':'
newline|'\n'
indent|' '
name|'fake_func'
op|'='
name|'fake_func'
name|'or'
name|'fake_swap_volume'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
nl|'\n'
string|"'swap_volume'"
op|','
nl|'\n'
name|'fake_func'
op|')'
newline|'\n'
name|'body'
op|'='
name|'body'
name|'or'
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_B'
op|'}'
op|'}'
newline|'\n'
nl|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/servers/id/os-volume_attachments/uuid'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'PUT'"
newline|'\n'
name|'req'
op|'.'
name|'body'
op|'='
name|'jsonutils'
op|'.'
name|'dump_as_bytes'
op|'('
op|'{'
op|'}'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'headers'
op|'['
string|"'content-type'"
op|']'
op|'='
string|"'application/json'"
newline|'\n'
name|'req'
op|'.'
name|'environ'
op|'['
string|"'nova.context'"
op|']'
op|'='
name|'self'
op|'.'
name|'context'
newline|'\n'
name|'return'
name|'attachments'
op|'.'
name|'update'
op|'('
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'uuid'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_swap_volume_for_locked_server
dedent|''
name|'def'
name|'test_swap_volume_for_locked_server'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|function|fake_swap_volume_for_locked_server
indent|' '
name|'def'
name|'fake_swap_volume_for_locked_server'
op|'('
name|'self'
op|','
name|'context'
op|','
name|'instance'
op|','
nl|'\n'
name|'old_volume'
op|','
name|'new_volume'
op|')'
op|':'
newline|'\n'
indent|' '
name|'raise'
name|'exception'
op|'.'
name|'InstanceIsLocked'
op|'('
name|'instance_uuid'
op|'='
name|'instance'
op|'['
string|"'uuid'"
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPConflict'
op|','
name|'self'
op|'.'
name|'_test_swap'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|','
nl|'\n'
name|'fake_func'
op|'='
name|'fake_swap_volume_for_locked_server'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_swap_volume
dedent|''
name|'def'
name|'test_swap_volume'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'result'
op|'='
name|'self'
op|'.'
name|'_test_swap'
op|'('
name|'self'
op|'.'
name|'attachments'
op|')'
newline|'\n'
comment|'# NOTE: on v2.1, http status code is set as wsgi_code of API'
nl|'\n'
comment|'# method instead of status_int in a response object.'
nl|'\n'
name|'if'
name|'isinstance'
op|'('
name|'self'
op|'.'
name|'attachments'
op|','
nl|'\n'
name|'volumes_v21'
op|'.'
name|'VolumeAttachmentController'
op|')'
op|':'
newline|'\n'
indent|' '
name|'status_int'
op|'='
name|'self'
op|'.'
name|'attachments'
op|'.'
name|'update'
op|'.'
name|'wsgi_code'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'status_int'
op|'='
name|'result'
op|'.'
name|'status_int'
newline|'\n'
dedent|''
name|'self'
op|'.'
name|'assertEqual'
op|'('
number|'202'
op|','
name|'status_int'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_swap_volume_no_attachment
dedent|''
name|'def'
name|'test_swap_volume_no_attachment'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exc'
op|'.'
name|'HTTPNotFound'
op|','
name|'self'
op|'.'
name|'_test_swap'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|','
name|'FAKE_UUID_C'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_swap_volume_without_volumeId
dedent|''
name|'def'
name|'test_swap_volume_without_volumeId'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|'}'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'validation_error'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_test_swap'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|','
nl|'\n'
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_swap_volume_with_extra_arg
dedent|''
name|'def'
name|'test_swap_volume_with_extra_arg'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|'}'
op|'}'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'validation_error'
op|','
nl|'\n'
name|'self'
op|'.'
name|'_test_swap'
op|','
nl|'\n'
name|'self'
op|'.'
name|'attachments'
op|','
nl|'\n'
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|CommonBadRequestTestCase
dedent|''
dedent|''
name|'class'
name|'CommonBadRequestTestCase'
op|'('
name|'object'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|variable|resource
indent|' '
name|'resource'
op|'='
name|'None'
newline|'\n'
DECL|variable|entity_name
name|'entity_name'
op|'='
name|'None'
newline|'\n'
DECL|variable|controller_cls
name|'controller_cls'
op|'='
name|'None'
newline|'\n'
DECL|variable|kwargs
name|'kwargs'
op|'='
op|'{'
op|'}'
newline|'\n'
DECL|variable|bad_request
name|'bad_request'
op|'='
name|'exc'
op|'.'
name|'HTTPBadRequest'
newline|'\n'
nl|'\n'
string|'"""\n Tests of places we throw 400 Bad Request from\n """'
newline|'\n'
nl|'\n'
DECL|member|setUp
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'CommonBadRequestTestCase'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'controller'
op|'='
name|'self'
op|'.'
name|'controller_cls'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|member|_bad_request_create
dedent|''
name|'def'
name|'_bad_request_create'
op|'('
name|'self'
op|','
name|'body'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/fake/'"
op|'+'
name|'self'
op|'.'
name|'resource'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
nl|'\n'
name|'kwargs'
op|'='
name|'self'
op|'.'
name|'kwargs'
op|'.'
name|'copy'
op|'('
op|')'
newline|'\n'
name|'kwargs'
op|'['
string|"'body'"
op|']'
op|'='
name|'body'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'bad_request'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'create'
op|','
name|'req'
op|','
op|'**'
name|'kwargs'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_create_no_body
dedent|''
name|'def'
name|'test_create_no_body'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'_bad_request_create'
op|'('
name|'body'
op|'='
name|'None'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_create_missing_volume
dedent|''
name|'def'
name|'test_create_missing_volume'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
string|"'foo'"
op|':'
op|'{'
string|"'a'"
op|':'
string|"'b'"
op|'}'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_bad_request_create'
op|'('
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_create_malformed_entity
dedent|''
name|'def'
name|'test_create_malformed_entity'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'body'
op|'='
op|'{'
name|'self'
op|'.'
name|'entity_name'
op|':'
string|"'string'"
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_bad_request_create'
op|'('
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
dedent|''
dedent|''
name|'class'
name|'BadRequestVolumeTestCaseV21'
op|'('
name|'CommonBadRequestTestCase'
op|','
nl|'\n'
DECL|class|BadRequestVolumeTestCaseV21
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|variable|resource
indent|' '
name|'resource'
op|'='
string|"'os-volumes'"
newline|'\n'
DECL|variable|entity_name
name|'entity_name'
op|'='
string|"'volume'"
newline|'\n'
DECL|variable|controller_cls
name|'controller_cls'
op|'='
name|'volumes_v21'
op|'.'
name|'VolumeController'
newline|'\n'
DECL|variable|bad_request
name|'bad_request'
op|'='
name|'exception'
op|'.'
name|'ValidationError'
newline|'\n'
nl|'\n'
nl|'\n'
dedent|''
name|'class'
name|'BadRequestSnapshotTestCaseV21'
op|'('
name|'CommonBadRequestTestCase'
op|','
nl|'\n'
DECL|class|BadRequestSnapshotTestCaseV21
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|variable|resource
indent|' '
name|'resource'
op|'='
string|"'os-snapshots'"
newline|'\n'
DECL|variable|entity_name
name|'entity_name'
op|'='
string|"'snapshot'"
newline|'\n'
DECL|variable|controller_cls
name|'controller_cls'
op|'='
name|'volumes_v21'
op|'.'
name|'SnapshotController'
newline|'\n'
DECL|variable|bad_request
name|'bad_request'
op|'='
name|'exception'
op|'.'
name|'ValidationError'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|AssistedSnapshotCreateTestCaseV21
dedent|''
name|'class'
name|'AssistedSnapshotCreateTestCaseV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
DECL|variable|assisted_snaps
indent|' '
name|'assisted_snaps'
op|'='
name|'assisted_snaps_v21'
newline|'\n'
DECL|variable|bad_request
name|'bad_request'
op|'='
name|'exception'
op|'.'
name|'ValidationError'
newline|'\n'
nl|'\n'
DECL|member|setUp
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'AssistedSnapshotCreateTestCaseV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'='
name|'self'
op|'.'
name|'assisted_snaps'
op|'.'
name|'AssistedVolumeSnapshotsController'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'volume_snapshot_create'"
op|','
nl|'\n'
name|'fake_compute_volume_snapshot_create'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_assisted_create
dedent|''
name|'def'
name|'test_assisted_create'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/fake/os-assisted-volume-snapshots'"
op|')'
newline|'\n'
name|'body'
op|'='
op|'{'
string|"'snapshot'"
op|':'
nl|'\n'
op|'{'
string|"'volume_id'"
op|':'
string|"'1'"
op|','
nl|'\n'
string|"'create_info'"
op|':'
op|'{'
string|"'type'"
op|':'
string|"'qcow2'"
op|','
nl|'\n'
string|"'new_file'"
op|':'
string|"'new_file'"
op|','
nl|'\n'
string|"'snapshot_id'"
op|':'
string|"'snapshot_id'"
op|'}'
op|'}'
op|'}'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'create'
op|'('
name|'req'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_assisted_create_missing_create_info
dedent|''
name|'def'
name|'test_assisted_create_missing_create_info'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/fake/os-assisted-volume-snapshots'"
op|')'
newline|'\n'
name|'body'
op|'='
op|'{'
string|"'snapshot'"
op|':'
op|'{'
string|"'volume_id'"
op|':'
string|"'1'"
op|'}'
op|'}'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'bad_request'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'create'
op|','
nl|'\n'
name|'req'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_assisted_create_with_unexpected_attr
dedent|''
name|'def'
name|'test_assisted_create_with_unexpected_attr'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/fake/os-assisted-volume-snapshots'"
op|')'
newline|'\n'
name|'body'
op|'='
op|'{'
nl|'\n'
string|"'snapshot'"
op|':'
op|'{'
nl|'\n'
string|"'volume_id'"
op|':'
string|"'1'"
op|','
nl|'\n'
string|"'create_info'"
op|':'
op|'{'
nl|'\n'
string|"'type'"
op|':'
string|"'qcow2'"
op|','
nl|'\n'
string|"'new_file'"
op|':'
string|"'new_file'"
op|','
nl|'\n'
string|"'snapshot_id'"
op|':'
string|"'snapshot_id'"
nl|'\n'
op|'}'
nl|'\n'
op|'}'
op|','
nl|'\n'
string|"'unexpected'"
op|':'
number|'0'
op|','
nl|'\n'
op|'}'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'POST'"
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'self'
op|'.'
name|'bad_request'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'create'
op|','
nl|'\n'
name|'req'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|AssistedSnapshotDeleteTestCaseV21
dedent|''
dedent|''
name|'class'
name|'AssistedSnapshotDeleteTestCaseV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
DECL|variable|assisted_snaps
indent|' '
name|'assisted_snaps'
op|'='
name|'assisted_snaps_v21'
newline|'\n'
nl|'\n'
DECL|member|_check_status
name|'def'
name|'_check_status'
op|'('
name|'self'
op|','
name|'expected_status'
op|','
name|'res'
op|','
name|'controller_method'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'expected_status'
op|','
name|'controller_method'
op|'.'
name|'wsgi_code'
op|')'
newline|'\n'
nl|'\n'
DECL|member|setUp
dedent|''
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'AssistedSnapshotDeleteTestCaseV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'='
name|'self'
op|'.'
name|'assisted_snaps'
op|'.'
name|'AssistedVolumeSnapshotsController'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'compute_api'
op|'.'
name|'API'
op|','
string|"'volume_snapshot_delete'"
op|','
nl|'\n'
name|'fake_compute_volume_snapshot_delete'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_assisted_delete
dedent|''
name|'def'
name|'test_assisted_delete'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'params'
op|'='
op|'{'
nl|'\n'
string|"'delete_info'"
op|':'
name|'jsonutils'
op|'.'
name|'dumps'
op|'('
op|'{'
string|"'volume_id'"
op|':'
string|"'1'"
op|'}'
op|')'
op|','
nl|'\n'
op|'}'
newline|'\n'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
nl|'\n'
string|"'/v2/fake/os-assisted-volume-snapshots?%s'"
op|'%'
nl|'\n'
name|'urllib'
op|'.'
name|'parse'
op|'.'
name|'urlencode'
op|'('
name|'params'
op|')'
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'result'
op|'='
name|'self'
op|'.'
name|'controller'
op|'.'
name|'delete'
op|'('
name|'req'
op|','
string|"'5'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'_check_status'
op|'('
number|'204'
op|','
name|'result'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'delete'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_assisted_delete_missing_delete_info
dedent|''
name|'def'
name|'test_assisted_delete_missing_delete_info'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"'/v2/fake/os-assisted-volume-snapshots'"
op|')'
newline|'\n'
name|'req'
op|'.'
name|'method'
op|'='
string|"'DELETE'"
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'webob'
op|'.'
name|'exc'
op|'.'
name|'HTTPBadRequest'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'delete'
op|','
nl|'\n'
name|'req'
op|','
string|"'5'"
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|TestAssistedVolumeSnapshotsPolicyEnforcementV21
dedent|''
dedent|''
name|'class'
name|'TestAssistedVolumeSnapshotsPolicyEnforcementV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'TestAssistedVolumeSnapshotsPolicyEnforcementV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'controller'
op|'='
op|'('
nl|'\n'
name|'assisted_snaps_v21'
op|'.'
name|'AssistedVolumeSnapshotsController'
op|'('
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"''"
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_create_assisted_volumes_snapshots_policy_failed
dedent|''
name|'def'
name|'test_create_assisted_volumes_snapshots_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-assisted-volume-snapshots:create"'
newline|'\n'
name|'self'
op|'.'
name|'policy'
op|'.'
name|'set_rules'
op|'('
op|'{'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
op|')'
newline|'\n'
name|'body'
op|'='
op|'{'
string|"'snapshot'"
op|':'
nl|'\n'
op|'{'
string|"'volume_id'"
op|':'
string|"'1'"
op|','
nl|'\n'
string|"'create_info'"
op|':'
op|'{'
string|"'type'"
op|':'
string|"'qcow2'"
op|','
nl|'\n'
string|"'new_file'"
op|':'
string|"'new_file'"
op|','
nl|'\n'
string|"'snapshot_id'"
op|':'
string|"'snapshot_id'"
op|'}'
op|'}'
op|'}'
newline|'\n'
name|'exc'
op|'='
name|'self'
op|'.'
name|'assertRaises'
op|'('
nl|'\n'
name|'exception'
op|'.'
name|'PolicyNotAuthorized'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'create'
op|','
name|'self'
op|'.'
name|'req'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
nl|'\n'
string|'"Policy doesn\'t allow %s to be performed."'
op|'%'
name|'rule_name'
op|','
nl|'\n'
name|'exc'
op|'.'
name|'format_message'
op|'('
op|')'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_delete_assisted_volumes_snapshots_policy_failed
dedent|''
name|'def'
name|'test_delete_assisted_volumes_snapshots_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-assisted-volume-snapshots:delete"'
newline|'\n'
name|'self'
op|'.'
name|'policy'
op|'.'
name|'set_rules'
op|'('
op|'{'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
op|')'
newline|'\n'
name|'exc'
op|'='
name|'self'
op|'.'
name|'assertRaises'
op|'('
nl|'\n'
name|'exception'
op|'.'
name|'PolicyNotAuthorized'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'delete'
op|','
name|'self'
op|'.'
name|'req'
op|','
string|"'5'"
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
nl|'\n'
string|'"Policy doesn\'t allow %s to be performed."'
op|'%'
name|'rule_name'
op|','
nl|'\n'
name|'exc'
op|'.'
name|'format_message'
op|'('
op|')'
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|TestVolumeAttachPolicyEnforcementV21
dedent|''
dedent|''
name|'class'
name|'TestVolumeAttachPolicyEnforcementV21'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
nl|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'TestVolumeAttachPolicyEnforcementV21'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'controller'
op|'='
name|'volumes_v21'
op|'.'
name|'VolumeAttachmentController'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'req'
op|'='
name|'fakes'
op|'.'
name|'HTTPRequest'
op|'.'
name|'blank'
op|'('
string|"''"
op|')'
newline|'\n'
nl|'\n'
DECL|member|_common_policy_check
dedent|''
name|'def'
name|'_common_policy_check'
op|'('
name|'self'
op|','
name|'rules'
op|','
name|'rule_name'
op|','
name|'func'
op|','
op|'*'
name|'arg'
op|','
op|'**'
name|'kwarg'
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'policy'
op|'.'
name|'set_rules'
op|'('
name|'rules'
op|')'
newline|'\n'
name|'exc'
op|'='
name|'self'
op|'.'
name|'assertRaises'
op|'('
nl|'\n'
name|'exception'
op|'.'
name|'PolicyNotAuthorized'
op|','
name|'func'
op|','
op|'*'
name|'arg'
op|','
op|'**'
name|'kwarg'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
nl|'\n'
string|'"Policy doesn\'t allow %s to be performed."'
op|'%'
name|'rule_name'
op|','
nl|'\n'
name|'exc'
op|'.'
name|'format_message'
op|'('
op|')'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_index_volume_attach_policy_failed
dedent|''
name|'def'
name|'test_index_volume_attach_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes-attachments:index"'
newline|'\n'
name|'rules'
op|'='
op|'{'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
nl|'\n'
name|'self'
op|'.'
name|'controller'
op|'.'
name|'index'
op|','
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_show_volume_attach_policy_failed
dedent|''
name|'def'
name|'test_show_volume_attach_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes-attachments:show"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'show'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes-attachments:show"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'show'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_create_volume_attach_policy_failed
dedent|''
name|'def'
name|'test_create_volume_attach_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes-attachments:create"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_A'
op|','
nl|'\n'
string|"'device'"
op|':'
string|"'/dev/fake'"
op|'}'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'create'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes-attachments:create"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'create'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_update_volume_attach_policy_failed
dedent|''
name|'def'
name|'test_update_volume_attach_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes-attachments:update"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'body'
op|'='
op|'{'
string|"'volumeAttachment'"
op|':'
op|'{'
string|"'volumeId'"
op|':'
name|'FAKE_UUID_B'
op|'}'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'update'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes-attachments:update"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'update'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|','
name|'body'
op|'='
name|'body'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_delete_volume_attach_policy_failed
dedent|''
name|'def'
name|'test_delete_volume_attach_policy_failed'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes-attachments:delete"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'delete'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
nl|'\n'
name|'rule_name'
op|'='
string|'"os_compute_api:os-volumes-attachments:delete"'
newline|'\n'
name|'rules'
op|'='
op|'{'
string|'"os_compute_api:os-volumes"'
op|':'
string|'"@"'
op|','
nl|'\n'
name|'rule_name'
op|':'
string|'"project:non_fake"'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'_common_policy_check'
op|'('
name|'rules'
op|','
name|'rule_name'
op|','
name|'self'
op|'.'
name|'controller'
op|'.'
name|'delete'
op|','
nl|'\n'
name|'self'
op|'.'
name|'req'
op|','
name|'FAKE_UUID'
op|','
name|'FAKE_UUID_A'
op|')'
newline|'\n'
dedent|''
dedent|''
endmarker|''
end_unit
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0
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69e47c91fedb31804f9e024beb25efbb4a228e46
| 2,847
|
py
|
Python
|
tests/test_services/test_disk_ovc/actions.py
|
openvcloud/ays_templates
|
7ce0bd5844ccfaefae554dd0dedeab2730a365cc
|
[
"Apache-2.0"
] | null | null | null |
tests/test_services/test_disk_ovc/actions.py
|
openvcloud/ays_templates
|
7ce0bd5844ccfaefae554dd0dedeab2730a365cc
|
[
"Apache-2.0"
] | 10
|
2017-10-25T13:23:23.000Z
|
2018-03-28T16:00:06.000Z
|
tests/test_services/test_disk_ovc/actions.py
|
openvcloud/ays_templates
|
7ce0bd5844ccfaefae554dd0dedeab2730a365cc
|
[
"Apache-2.0"
] | null | null | null |
def test_create(job):
"""
Test Create Disk
"""
import sys
RESULT_OK = 'OK : %s'
RESULT_ERROR = 'ERROR : %s %%s' % job.service.name
RESULT_FAIL = 'FAILED : %s %%s' % job.service.name
model = job.service.model
model.data.result = RESULT_OK % job.service.name
def _disk_found(disks, disk_srv):
result = False
for disk in disks:
if disk['name'] == disk_srv.name and disk['descr'] == disk_srv.model.data.description:
result = True
break
return result
try:
disk_srv = job.service.aysrepo.serviceGet(role='disk', instance=model.data.disk[0])
client_srv = disk_srv.producers.get('g8client')[0]
cli = j.clients.openvcloud.get(instance="{}_{}".format(client_srv.aysrepo.name, client_srv.instance),
create=False, die=True)
account = cli.account_get(name=client_srv.model.data.account, create=False)
disks = cli.api.cloudapi.disks.list(accountId=account.id, type=disk_srv.model.data.type)
if _disk_found(disks, disk_srv):
model.data.result = RESULT_OK % 'Disk Created Successfully'
else:
model.data.result = RESULT_FAIL % 'Expected to find disk matches the test disk. Found None'
except:
model.data.result = RESULT_ERROR % str(sys.exc_info()[:2])
finally:
job.service.save()
def test_delete(job):
"""
Test Delete Disk
"""
import sys
RESULT_OK = 'OK : %s'
RESULT_ERROR = 'ERROR : %s %%s' % job.service.name
RESULT_FAIL = 'FAILED : %s %%s' % job.service.name
model = job.service.model
model.data.result = RESULT_OK % job.service.name
def _disk_found(disks, disk_srv):
result = False
for disk in disks:
if disk['name'] == disk_srv.name and disk['descr'] == disk_srv.model.data.description:
result = True
break
return result
try:
disk_srv = job.service.aysrepo.serviceGet(role='disk', instance=model.data.disk[0])
client_srv = disk_srv.producers.get('g8client')[0]
cli = j.clients.openvcloud.get(instance="{}_{}".format(client_srv.aysrepo.name, client_srv.instance),
create=False, die=True)
account = cli.account_get(name=client_srv.model.data.account, create=False)
disks = cli.api.cloudapi.disks.list(accountId=account.id, type=disk_srv.model.data.type)
if _disk_found(disks, disk_srv):
model.data.result = RESULT_FAIL % 'Expected not to find disk matches the test disk. Found one'
else:
model.data.result = RESULT_OK % 'Disk Deleted Successfully'
except:
model.data.result = RESULT_ERROR % str(sys.exc_info()[:2])
finally:
job.service.save()
| 39
| 109
| 0.611872
| 369
| 2,847
| 4.579946
| 0.197832
| 0.085207
| 0.071006
| 0.099408
| 0.940828
| 0.936095
| 0.889941
| 0.889941
| 0.850888
| 0.850888
| 0
| 0.00382
| 0.264489
| 2,847
| 72
| 110
| 39.541667
| 0.803247
| 0.011591
| 0
| 0.896552
| 0
| 0
| 0.103126
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.068966
| false
| 0
| 0.034483
| 0
| 0.137931
| 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
|
69e53a6653d60440648c79811ddad8a8740acf2a
| 2,508
|
py
|
Python
|
test/test_model_vars.py
|
jan-g/psh
|
c2641c9d2d7051dacb41474123889dd04bdd2989
|
[
"Apache-2.0"
] | null | null | null |
test/test_model_vars.py
|
jan-g/psh
|
c2641c9d2d7051dacb41474123889dd04bdd2989
|
[
"Apache-2.0"
] | null | null | null |
test/test_model_vars.py
|
jan-g/psh
|
c2641c9d2d7051dacb41474123889dd04bdd2989
|
[
"Apache-2.0"
] | null | null | null |
import pytest
from psh.model import Word, ConstantString, VarRef, Id, VarOp
from psh.glob import STAR
from psh.local import make_env
@pytest.mark.parametrize(("pattern", "value", "expected"), (
(Word([VarRef(ConstantString("a"))]), "xx", "xx"),
(Word([VarRef(ConstantString("a"), double_quoted=True)], double_quoted=True), "xx yy", "xx yy"),
(Word([VarOp(VarRef(ConstantString("a")), '#', Word([Id("x")]))]), "xx123xx", "x123xx"),
(Word([VarOp(VarRef(ConstantString("a")), '#', Word([STAR, Id("x")]))]), "xx123xx", "x123xx"),
(Word([VarOp(VarRef(ConstantString("a")), '#', Word([Id("x"), STAR]))]), "xx123xx", "x123xx"),
(Word([VarOp(VarRef(ConstantString("a")), '#', Word([STAR, Id("x"), STAR]))]), "xx123xx", "x123xx"),
(Word([VarOp(VarRef(ConstantString("a")), '##', Word([Id("x")]))]), "xx123xx", "x123xx"),
(Word([VarOp(VarRef(ConstantString("a")), '##', Word([STAR, Id("x")]))]), "xx123xx", ""),
(Word([VarOp(VarRef(ConstantString("a")), '##', Word([Id("x"), STAR]))]), "xx123xx", ""),
(Word([VarOp(VarRef(ConstantString("a")), '##', Word([STAR, Id("x"), STAR]))]), "xx123xx", ""),
(Word([VarOp(VarRef(ConstantString("a")), '%', Word([Id("x")]))]), "xx123xx", "xx123x"),
(Word([VarOp(VarRef(ConstantString("a")), '%', Word([STAR, Id("x")]))]), "xx123xx", "xx123x"),
(Word([VarOp(VarRef(ConstantString("a")), '%', Word([Id("x"), STAR]))]), "xx123xx", "xx123x"),
(Word([VarOp(VarRef(ConstantString("a")), '%', Word([STAR, Id("x"), STAR]))]), "xx123xx", "xx123x"),
(Word([VarOp(VarRef(ConstantString("a")), '%%', Word([Id("x")]))]), "xx123xx", "xx123x"),
(Word([VarOp(VarRef(ConstantString("a")), '%%', Word([STAR, Id("x")]))]), "xx123xx", ""),
(Word([VarOp(VarRef(ConstantString("a")), '%%', Word([Id("x"), STAR]))]), "xx123xx", ""),
(Word([VarOp(VarRef(ConstantString("a")), '%%', Word([STAR, Id("x"), STAR]))]), "xx123xx", ""),
(Word([VarOp(VarRef(ConstantString("a")), '#', Word([STAR]))]), "xx123xx", "xx123xx"),
(Word([VarOp(VarRef(ConstantString("a")), '##', Word([STAR]))]), "xx123xx", ""),
(Word([VarOp(VarRef(ConstantString("a")), '%', Word([STAR]))]), "xx123xx", "xx123xx"),
(Word([VarOp(VarRef(ConstantString("a")), '%%', Word([STAR]))]), "xx123xx", ""),
))
def test_basic(pattern, value, expected):
env = make_env()
env['a'] = value
result = pattern.evaluate(env)
assert result == expected
| 57
| 108
| 0.54386
| 271
| 2,508
| 5.01476
| 0.132841
| 0.323767
| 0.339956
| 0.426784
| 0.752024
| 0.752024
| 0.752024
| 0.752024
| 0.752024
| 0.752024
| 0
| 0.04486
| 0.14673
| 2,508
| 43
| 109
| 58.325581
| 0.590187
| 0
| 0
| 0
| 0
| 0
| 0.126496
| 0
| 0
| 0
| 0
| 0
| 0.030303
| 1
| 0.030303
| false
| 0
| 0.121212
| 0
| 0.151515
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
2a025e3cd978928750fdc1b81a6102713ee3071f
| 5,394
|
py
|
Python
|
gsoc_application_projects/2020/influenza/model/src/test.py
|
Hephaestus12/applications
|
a7c875ef92324bee32a715ae364a49b1695d8f66
|
[
"BSD-3-Clause"
] | 3
|
2020-05-14T17:41:25.000Z
|
2021-01-02T10:47:50.000Z
|
gsoc_application_projects/2020/influenza/model/src/test.py
|
Hephaestus12/applications
|
a7c875ef92324bee32a715ae364a49b1695d8f66
|
[
"BSD-3-Clause"
] | 4
|
2020-05-16T02:08:16.000Z
|
2020-08-31T03:07:37.000Z
|
gsoc_application_projects/2020/influenza/model/src/test.py
|
Hephaestus12/applications
|
a7c875ef92324bee32a715ae364a49b1695d8f66
|
[
"BSD-3-Clause"
] | 2
|
2020-05-14T15:26:41.000Z
|
2020-06-15T16:43:16.000Z
|
from pathlib import Path
import pandas as pd
from scipy.stats import skew
from sklearn.preprocessing import PowerTransformer, StandardScaler
import process
COUNTRIES = ['austria', 'belgium', 'germany', 'italy', 'netherlands']
def power_transform():
path = Path.cwd()
cleaned_data_path = path.parent / 'data' / 'cleaned'
df = {}
lmbda = {'austria' : {}, 'belgium': {}, 'germany': {}, 'italy': {},
'netherlands': {}}
for country in COUNTRIES:
# read file
file_path = cleaned_data_path / (country + '.csv')
df[country] = pd.read_csv(file_path)
process.add_polynomial_features(country, df, 10)
numerical_features = df[country].select_dtypes(
exclude=["object"]).columns
numerical_features = numerical_features.drop('incidence')
skewness = df[country][numerical_features].apply(lambda x: skew(x))
skewness = skewness[abs(skewness) > 0.5]
skewed_features = skewness.index
process.hot_encode_weeks(country, df)
train = df[country].sample(frac=0.8, random_state=200)
test = df[country].drop(train.index)
train = train.sort_values(by="date")
test = test.sort_values(by="date")
train = train.drop(columns=['week', 'date'])
test = test.drop(columns=['week', 'date'])
y_train = pd.Series(train['incidence']).to_frame('incidence')
y_test = pd.Series(test['incidence']).to_frame('incidence')
X_train = train.drop(columns=['incidence'])
X_test = test.drop(columns=['incidence'])
pt = PowerTransformer()
pt.fit_transform(X_train, y_train.values)
params = pt.get_params()
pt.fit_transform(X_test)
means = {}
std_deviations = {}
process.train_std_normal(X_train, numerical_features, means,
std_deviations)
process.apply_std_normal(X_test, numerical_features, means,
std_deviations)
test_data_path = path.parent / 'data' / 'test' / country
x_train_file_path = test_data_path / 'X_train.csv'
y_train_file_path = test_data_path / 'y_train.csv'
x_test_file_path = test_data_path / 'X_test.csv'
y_test_file_path = test_data_path / 'y_test.csv'
X_train.to_csv(x_train_file_path, index=False)
y_train.to_csv(y_train_file_path, index=False)
X_test.to_csv(x_test_file_path, index=False)
y_test.to_csv(y_test_file_path, index=False)
def test_train_split():
path = Path.cwd()
cleaned_data_path = path.parent / 'data' / 'cleaned'
df = {}
lmbda = {'austria' : {}, 'belgium': {}, 'germany': {}, 'italy': {},
'netherlands': {}}
for country in COUNTRIES:
# read file
file_path = cleaned_data_path / (country + '.csv')
df[country] = pd.read_csv(file_path)
process.add_polynomial_features(country, df, 10)
numerical_features = df[country].select_dtypes(
exclude=["object"]).columns
numerical_features = numerical_features.drop('incidence')
skewness = df[country][numerical_features].apply(lambda x: skew(x))
skewness = skewness[abs(skewness) > 0.5]
skewed_features = skewness.index
process.hot_encode_weeks(country, df)
train = df[country].sample(frac=0.8, random_state=200)
test = df[country].drop(train.index)
train = train.sort_values(by="date")
test = test.sort_values(by="date")
train = train.drop(columns=['week', 'date'])
test = test.drop(columns=['week', 'date'])
y_train = pd.Series(train['incidence']).to_frame('incidence')
y_test = pd.Series(test['incidence']).to_frame('incidence')
X_train = train.drop(columns=['incidence'])
X_test = test.drop(columns=['incidence'])
X_train, lmbda[country] = process.train_leo_johnson(X_train,
lmbda[country],
skewed_features)
y_train, lmbda[country] = process.train_leo_johnson(y_train,
lmbda[country],
['incidence'])
means = {}
std_deviations = {}
process.train_std_normal(X_train, numerical_features, means,
std_deviations)
process.apply_leo_johnson(X_test, lmbda[country], skewed_features)
process.apply_leo_johnson(y_test, lmbda[country], ['incidence'])
process.apply_std_normal(X_test, numerical_features, means,
std_deviations)
X_train['bias'] = 1
X_test['bias'] = 1
# save to file.
test_data_path = path.parent / 'data' / 'test' / country
x_train_file_path = test_data_path / 'X_train.csv'
y_train_file_path = test_data_path / 'y_train.csv'
x_test_file_path = test_data_path / 'X_test.csv'
y_test_file_path = test_data_path / 'y_test.csv'
X_train.to_csv(x_train_file_path, index=False)
y_train.to_csv(y_train_file_path, index=False)
X_test.to_csv(x_test_file_path, index=False)
y_test.to_csv(y_test_file_path, index=False)
power_transform()
| 35.721854
| 76
| 0.600111
| 648
| 5,394
| 4.695988
| 0.141975
| 0.05258
| 0.039435
| 0.042064
| 0.849491
| 0.837332
| 0.837332
| 0.811699
| 0.811699
| 0.811699
| 0
| 0.005144
| 0.279199
| 5,394
| 150
| 77
| 35.96
| 0.777521
| 0.006118
| 0
| 0.8
| 0
| 0
| 0.084562
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.019048
| false
| 0
| 0.047619
| 0
| 0.066667
| 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
|
2a2b4b2092971e57560b507952a504d30a52b695
| 3,819
|
py
|
Python
|
extract_document/driving_licence.py
|
devdatta95/OCR_Documents_With_Flask
|
ddc45689fa9eaef4ca134625c46388ce96c3ebe7
|
[
"CNRI-Python",
"OML",
"Info-ZIP"
] | 3
|
2021-08-28T23:33:24.000Z
|
2022-03-30T04:44:57.000Z
|
extract_document/driving_licence.py
|
devdatta95/OCR_Documents_With_Flask
|
ddc45689fa9eaef4ca134625c46388ce96c3ebe7
|
[
"CNRI-Python",
"OML",
"Info-ZIP"
] | null | null | null |
extract_document/driving_licence.py
|
devdatta95/OCR_Documents_With_Flask
|
ddc45689fa9eaef4ca134625c46388ce96c3ebe7
|
[
"CNRI-Python",
"OML",
"Info-ZIP"
] | 3
|
2021-02-18T18:58:39.000Z
|
2021-07-08T08:55:59.000Z
|
import re
# extract labels from licence image
def get_licence_text(details):
imp = {}
# loop through all the details found line wise
for idx in range(len(details)):
try:
# if DL No is found save it
if 'DL No' in details[idx]:
try:
imp["DL NO"] = details[idx].split('DL No')[-1].strip()
except Exception as _:
imp["DL NO"] = "Not Found"
# if dob is found, use it as a hook and try finding other details relative to it
elif details[idx].startswith('DOB'):
# extract only dob from the text
dob = re.findall(r"([0-9]{2}\-[0-9]{2}\-[0-9]{4})", details[idx].split(' ', 1)[-1])[0]
imp["Date of Birth"] = dob
# next line is always name and father's name
imp["Name"] = details[idx + 1].split(' ', 1)[-1].strip()
try:
# split it from 'of' to get Father's Name
imp["Father's Name"] = details[idx + 2].split('of', 1)[1].strip()
except Exception as _:
# handle exception if O is capital in 'of'
imp["Father's Name"] = details[idx + 2].split('Of', 1)[1].strip()
i = 4
# split next line from Add for address
address = details[idx + 3].split('Add', 1)[1].strip()
# keep appending until PIN code is found or address is of more than 4 lines
while not details[idx + i].startswith('PIN') and i < 8:
if details[idx + i].isupper() != True:
i += 1
continue
address += ' ' + details[idx + i]
i += 1
imp["Address"] = address
try:
# get only pin code from the string
imp["Pin Code"] = re.findall(r"([0-9]{6})", details[idx + i].split(' ', 1)[1])[0]
except Exception as _:
pass
break
# if name is found, use it as a hook and try finding other details relative to it
elif details[idx].startswith('Name'):
# extract only dob from the text
dob = re.findall(r"([0-9]{2}\-[0-9]{2}\-[0-9]{4})", details[idx - 1].split(' ', 1)[1])[0]
imp["Date of Birth"] = dob
imp["Name"] = details[idx][4:].strip()
# next line is always name and father's name
try:
# split it from 'of' to get Father's Name
imp["Father's Name"] = details[idx + 2].split('of', 1)[1].strip()
except Exception as _:
# handle exception if O is capital in 'of'
imp["Father's Name"] = details[idx + 2].split('Of', 1)[1].strip()
i = 3
# split next line from Add for address
address = details[idx + 2].split('Add', 1)[1].strip()
# keep appending until PIN code is found or address is of more than 4 lines
while not details[idx + i].startswith('PIN') and i < 7:
if details[idx + i].isupper() != True:
i += 1
continue
address += ' ' + details[idx + i]
i += 1
imp["Address"] = address
try:
# get only pin code from the string
imp["Pin Code"] = re.findall(r"([0-9]{6})", details[idx + i].split(' ', 1)[1])[0]
except Exception as _:
pass
break
except Exception as _:
pass
return imp
| 39.78125
| 105
| 0.447499
| 474
| 3,819
| 3.588608
| 0.191983
| 0.129336
| 0.051734
| 0.047031
| 0.825397
| 0.811875
| 0.800705
| 0.800705
| 0.800705
| 0.731335
| 0
| 0.032081
| 0.428646
| 3,819
| 95
| 106
| 40.2
| 0.747479
| 0.225975
| 0
| 0.649123
| 0
| 0
| 0.088215
| 0.020436
| 0
| 0
| 0
| 0
| 0
| 1
| 0.017544
| false
| 0.052632
| 0.017544
| 0
| 0.052632
| 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
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
2a6c404b0c6145fdb44c7a2b05937a457a8d5339
| 1,905
|
py
|
Python
|
pyaz/security/va/sql/scans/__init__.py
|
py-az-cli/py-az-cli
|
9a7dc44e360c096a5a2f15595353e9dad88a9792
|
[
"MIT"
] | null | null | null |
pyaz/security/va/sql/scans/__init__.py
|
py-az-cli/py-az-cli
|
9a7dc44e360c096a5a2f15595353e9dad88a9792
|
[
"MIT"
] | null | null | null |
pyaz/security/va/sql/scans/__init__.py
|
py-az-cli/py-az-cli
|
9a7dc44e360c096a5a2f15595353e9dad88a9792
|
[
"MIT"
] | 1
|
2022-02-03T09:12:01.000Z
|
2022-02-03T09:12:01.000Z
|
'''
View Sql Vulnerability Assessment scan summaries.
'''
from ..... pyaz_utils import _call_az
def show(database_name, scan_id, server_name, vm_resource_id, workspace_id, agent_id=None, vm_name=None, vm_uuid=None):
'''
View Sql Vulnerability Assessment scan summaries.
Required Parameters:
- database_name -- The name of the scanned database
- scan_id -- The ID of the scan
- server_name -- The name of the scanned server
- vm_resource_id -- Resource ID of the scanned machine. For On-Premise machines, please provide your workspace resource ID
- workspace_id -- The ID of the workspace connected to the scanned machine
Optional Parameters:
- agent_id -- Provide the ID of the agent on the scanned machine, for On-Premise resources only
- vm_name -- Provide the name of the machine, for On-Premise resources only
- vm_uuid -- Provide the UUID of the scanned machine, for On-Premise resources only
'''
return _call_az("az security va sql scans show", locals())
def list(database_name, server_name, vm_resource_id, workspace_id, agent_id=None, vm_name=None, vm_uuid=None):
'''
List all Sql Vulnerability Assessment scan summaries.
Required Parameters:
- database_name -- The name of the scanned database
- server_name -- The name of the scanned server
- vm_resource_id -- Resource ID of the scanned machine. For On-Premise machines, please provide your workspace resource ID
- workspace_id -- The ID of the workspace connected to the scanned machine
Optional Parameters:
- agent_id -- Provide the ID of the agent on the scanned machine, for On-Premise resources only
- vm_name -- Provide the name of the machine, for On-Premise resources only
- vm_uuid -- Provide the UUID of the scanned machine, for On-Premise resources only
'''
return _call_az("az security va sql scans list", locals())
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aa9d6761b015c5d843daf4cdaa627d51e2bb4be2
| 65,582
|
py
|
Python
|
130-Surrounded-Regions/solution02.py
|
Eroica-cpp/LeetCode
|
07276bd11558f3d0e32bec768b09e886de145f9e
|
[
"CC-BY-3.0",
"MIT"
] | 7
|
2015-05-05T22:21:30.000Z
|
2021-03-13T04:04:15.000Z
|
130-Surrounded-Regions/solution02.py
|
Eroica-cpp/LeetCode
|
07276bd11558f3d0e32bec768b09e886de145f9e
|
[
"CC-BY-3.0",
"MIT"
] | null | null | null |
130-Surrounded-Regions/solution02.py
|
Eroica-cpp/LeetCode
|
07276bd11558f3d0e32bec768b09e886de145f9e
|
[
"CC-BY-3.0",
"MIT"
] | 2
|
2018-12-26T08:13:25.000Z
|
2020-07-18T20:18:24.000Z
|
#!/usr/bin/python
# ==============================================================================
# Author: Tao Li (taoli@ucsd.edu)
# Date: Jun 19, 2015
# Question: 130-Surrounded-Regions
# Link: https://leetcode.com/problems/surrounded-regions/
# ==============================================================================
# Given a 2D board containing 'X' and 'O', capture all regions surrounded by 'X'.
#
# A region is captured by flipping all 'O's into 'X's in that surrounded region.
#
# For example,
# X X X X
# X O O X
# X X O X
# X O X X
# After running your function, the board should be:
#
# X X X X
# X X X X
# X X X X
# X O X X
# ==============================================================================
# Method: Recusion; iteration
# Time Complexity: Exp
# Space Complexity: O(n^2)
# Note: using stack is a substitute of Recusion
# ==============================================================================
class Solution:
# @param {character[][]} board
# @return {void} Do not return anything, modify board in-place instead.
def solve(self, board):
if not board or not board[0]:
return
m, n = len(board), len(board[0])
stack = []
for i in xrange(m):
if board[i][0] == "O": stack.append((i,0))
if board[i][n-1] == "O": stack.append((i,n-1))
for j in xrange(1,n-1):
if board[0][j] == "O": stack.append((0,j))
if board[m-1][j] == "O": stack.append((m-1,j))
while stack:
i, j = stack.pop()
board[i][j] = "C"
if i+1<m and board[i+1][j] == "O": stack.append((i+1,j))
if i-1>=0 and board[i-1][j] == "O": stack.append((i-1,j))
if j+1<n and board[i][j+1] == "O": stack.append((i,j+1))
if j-1>=0 and board[i][j-1] == "O": stack.append((i,j-1))
for i in xrange(m):
for j in xrange(n):
if board[i][j] == "O":
board[i][j] = "X"
elif board[i][j] == "C":
board[i][j] = "O"
if __name__ == '__main__':
board = ["XOXX","XOXX","XXOX","XOXX", "XXXX"]
board = 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print len(board), len(board[0])
board = [[j for j in i] for i in board]
Solution().solve(board)
for i in board:
print i
| 936.885714
| 63,263
| 0.968848
| 586
| 65,582
| 108.414676
| 0.174061
| 0.495821
| 0.731926
| 0.975902
| 0.987408
| 0.985912
| 0.985676
| 0.985676
| 0.985676
| 0.985676
| 0
| 0.000585
| 0.009576
| 65,582
| 70
| 63,264
| 936.885714
| 0.977507
| 0.015096
| 0
| 0.060606
| 0
| 0
| 0.968682
| 0.968047
| 0
| 1
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.060606
| 0
| 0
| 1
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 16
|
aabaf2d33742afad008c7b2b827b05636b55e767
| 312
|
py
|
Python
|
three/helpers/__init__.py
|
jpiland16/three.py-packaged
|
53026f1637eff31bbdbeb32dac6bb4ec608ff4a6
|
[
"MIT"
] | null | null | null |
three/helpers/__init__.py
|
jpiland16/three.py-packaged
|
53026f1637eff31bbdbeb32dac6bb4ec608ff4a6
|
[
"MIT"
] | null | null | null |
three/helpers/__init__.py
|
jpiland16/three.py-packaged
|
53026f1637eff31bbdbeb32dac6bb4ec608ff4a6
|
[
"MIT"
] | null | null | null |
from three.helpers.AxesHelper import *
from three.helpers.GridHelper import *
from three.helpers.BoxHelper import *
from three.helpers.VertexNormalHelper import *
from three.helpers.DirectionalLightHelper import *
from three.helpers.PointLightHelper import *
from three.helpers.OrthographicCameraHelper import *
| 39
| 52
| 0.842949
| 35
| 312
| 7.514286
| 0.314286
| 0.239544
| 0.425856
| 0.501901
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.089744
| 312
| 7
| 53
| 44.571429
| 0.926056
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 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
| 7
|
aac054bbf46c8293c640d92b217f12c2ad4bc420
| 1,703
|
py
|
Python
|
authentication/decorators.py
|
ptrcktylr/splat-issue-tracker
|
8119a59d0982966708f83d83de27da68aafd8ef9
|
[
"MIT"
] | 1
|
2021-03-28T19:03:39.000Z
|
2021-03-28T19:03:39.000Z
|
authentication/decorators.py
|
ptrcktylr/splat-issue-tracker
|
8119a59d0982966708f83d83de27da68aafd8ef9
|
[
"MIT"
] | null | null | null |
authentication/decorators.py
|
ptrcktylr/splat-issue-tracker
|
8119a59d0982966708f83d83de27da68aafd8ef9
|
[
"MIT"
] | null | null | null |
from django.http import HttpRequest
from django.shortcuts import redirect
def unauthenticated_user(view_function):
def wrapper_function(request, *args, **kwargs):
if request.user.is_authenticated:
return redirect('dashboard')
else:
return view_function(request, *args, **kwargs)
return wrapper_function
def admin_user(view_function):
def wrapper_function(request, *args, **kwargs):
if request.user.groups.filter(name='admin').exists():
return view_function(request, *args, **kwargs)
else:
return redirect('dashboard')
return wrapper_function
def project_manager_user(view_function):
def wrapper_function(request, *args, **kwargs):
if request.user.groups.filter(name='project manager').exists() or request.user.groups.filter(name='admin').exists():
return view_function(request, *args, **kwargs)
else:
return redirect('dashboard')
return wrapper_function
def developer_user(view_function):
def wrapper_function(request, *args, **kwargs):
if request.user.groups.filter(name='developer').exists() or request.user.groups.filter(name='admin').exists():
return view_function(request, *args, **kwargs)
else:
return redirect('dashboard')
return wrapper_function
def submitter_user(view_function):
def wrapper_function(request, *args, **kwargs):
if request.user.groups.filter(name='submitter').exists() or request.user.groups.filter(name='admin').exists():
return view_function(request, *args, **kwargs)
else:
return redirect('dashboard')
return wrapper_function
| 39.604651
| 124
| 0.677041
| 193
| 1,703
| 5.834197
| 0.165803
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| 0.168739
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| 0.807282
| 0.776199
| 0.776199
| 0.776199
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| 0
| 0.204932
| 1,703
| 43
| 125
| 39.604651
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| 0
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| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 9
|
2ac588af966d575c5e609899f6b3dafe22c1a89f
| 3,448
|
py
|
Python
|
api/database/models.py
|
lads-ecp/ufma-api
|
25557f7b3c8670deb649ec8fdca38f61c2a187b5
|
[
"MIT"
] | 1
|
2019-11-23T01:07:58.000Z
|
2019-11-23T01:07:58.000Z
|
api/database/models.py
|
inovacampus/ufma-api
|
25557f7b3c8670deb649ec8fdca38f61c2a187b5
|
[
"MIT"
] | 2
|
2021-03-31T19:27:02.000Z
|
2021-12-13T20:36:17.000Z
|
api/database/models.py
|
inovacampus/ufma-api
|
25557f7b3c8670deb649ec8fdca38f61c2a187b5
|
[
"MIT"
] | 1
|
2020-04-11T09:50:02.000Z
|
2020-04-11T09:50:02.000Z
|
from database import db
from rdflib import Namespace
class Docente(db.Model):
siape = db.Column(db.Integer, primary_key=True)
nome = db.Column(db.String(30), unique=False, nullable=False)
departamento = db.Column(db.String(50), unique=False, nullable=True)
codigo_subunidade = db.Column(db.String(50), unique=False, nullable=True)
descricao = db.Column(db.Text, unique=False, nullable=True)
formacao = db.Column(db.Text, unique=False, nullable=True)
areas_interesse = db.Column(db.Text, unique=False, nullable=True)
lattes = db.Column(db.String(50), unique=False, nullable=True)
email = db.Column(db.String(50), unique=False, nullable=True)
telefone = db.Column(db.String(30), unique=False, nullable=True)
urlimg = db.Column(db.String(50), unique=False, nullable=True)
def __init__(self, dict):
self.__dict__.update(dict)
def json(self):
dic = dict(filter(lambda v: v[0] != "_sa_instance_state", self.__dict__.items()))
return dic
def save_to(self):
db.session.add(self)
db.session.commit()
def delete_(self):
db.session.delete(self)
db.session.commit()
class Subunidade(db.Model):
codigo = db.Column(db.String(15), primary_key=True)
nome = db.Column(db.String(30), unique=False, nullable=False)
def __init__(self, dict):
self.__dict__.update(dict)
def json(self):
dic = dict(filter(lambda v: v[0] != "_sa_instance_state", self.__dict__.items()))
return dic
def save_to(self):
db.session.add(self)
db.session.commit()
def delete_(self):
db.session.delete(self)
db.session.commit()
class Discente (db.Model):
matricula = db.Column(db.String(15), primary_key=True)
nome = db.Column(db.String(30), unique=False, nullable=False)
codigo_curso = db.Column(db.String(30), unique=False, nullable=True)
nome_curso = db.Column(db.String(30), unique=False, nullable=True)
def __init__(self, dict):
self.__dict__.update(dict)
def json(self):
dic = dict(filter(lambda v: v[0] != "_sa_instance_state", self.__dict__.items()))
return dic
class Curso (db.Model):
codigo = db.Column(db.String(15), primary_key=True)
nome = db.Column(db.String(30), unique=False, nullable=False)
modalidade = db.Column(db.String(30), unique=False, nullable=False)
municipio = db.Column(db.String(30), unique=False, nullable=False)
coordenador = db.Column(db.String(30), unique=False, nullable=False)
def __init__(self, dict):
self.__dict__.update(dict)
def json(self):
dic = dict(filter(lambda v: v[0] != "_sa_instance_state", self.__dict__.items()))
return dic
class Monografia (db.Model):
codigo = db.Column(db.String(15), primary_key=True)
codigo_curso = db.Column(db.String(30), unique=False, nullable=True)
titulo = db.Column(db.String(30), unique=False, nullable=True)
ano = db.Column(db.String(10), unique=False, nullable=True)
discente = db.Column(db.String(30), unique=False, nullable=True)
orientador = db.Column(db.String(30), unique=False, nullable=True)
siape_orientador = db.Column(db.String(30), unique=False, nullable=True)
def __init__(self, dict):
self.__dict__.update(dict)
def json(self):
dic = dict(filter(lambda v: v[0] != "_sa_instance_state", self.__dict__.items()))
return dic
| 34.828283
| 89
| 0.668503
| 487
| 3,448
| 4.548255
| 0.13963
| 0.10474
| 0.130926
| 0.180587
| 0.857336
| 0.857336
| 0.857336
| 0.857336
| 0.807223
| 0.631603
| 0
| 0.019573
| 0.185035
| 3,448
| 98
| 90
| 35.183673
| 0.768683
| 0
| 0
| 0.630137
| 0
| 0
| 0.02611
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.191781
| false
| 0
| 0.027397
| 0
| 0.753425
| 0
| 0
| 0
| 0
| null | 0
| 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
| 1
| 0
|
0
| 8
|
2afdc82421742e20ded31011114a56b2b4de2aff
| 9,441
|
py
|
Python
|
autoware.ai/src/autoware/core_perception/vision_darknet_detect/src/catkin_generated/generate_cached_setup.py
|
Jihwan-Kimm/Autoware_On_Embedded
|
dc45b70a355fdd26a65007e9c1d9246090f06373
|
[
"MIT"
] | 2
|
2021-07-12T06:44:37.000Z
|
2021-07-20T07:50:33.000Z
|
autoware.ai/src/autoware/core_perception/vision_darknet_detect/src/catkin_generated/generate_cached_setup.py
|
Jihwan-Kimm/Autoware_On_Embedded
|
dc45b70a355fdd26a65007e9c1d9246090f06373
|
[
"MIT"
] | null | null | null |
autoware.ai/src/autoware/core_perception/vision_darknet_detect/src/catkin_generated/generate_cached_setup.py
|
Jihwan-Kimm/Autoware_On_Embedded
|
dc45b70a355fdd26a65007e9c1d9246090f06373
|
[
"MIT"
] | 3
|
2021-07-12T06:38:00.000Z
|
2022-03-21T07:27:17.000Z
|
# -*- coding: utf-8 -*-
from __future__ import print_function
import os
import stat
import sys
# find the import for catkin's python package - either from source space or from an installed underlay
if os.path.exists(os.path.join('/opt/ros/melodic/share/catkin/cmake', 'catkinConfig.cmake.in')):
sys.path.insert(0, os.path.join('/opt/ros/melodic/share/catkin/cmake', '..', 'python'))
try:
from catkin.environment_cache import generate_environment_script
except ImportError:
# search for catkin package in all workspaces and prepend to path
for workspace in '/home/bkpark/autoware.ai/install/ymc;/home/bkpark/autoware.ai/install/xsens_driver;/home/bkpark/autoware.ai/install/wf_simulator;/home/bkpark/autoware.ai/install/lattice_planner;/home/bkpark/autoware.ai/install/waypoint_planner;/home/bkpark/autoware.ai/install/waypoint_maker;/home/bkpark/autoware.ai/install/way_planner;/home/bkpark/autoware.ai/install/vlg22c_cam;/home/bkpark/autoware.ai/install/vision_ssd_detect;/home/bkpark/autoware.ai/install/vision_segment_enet_detect;/home/bkpark/autoware.ai/install/vision_lane_detect;/home/bkpark/autoware.ai/install/vision_darknet_detect;/home/bkpark/autoware.ai/install/vision_beyond_track;/home/bkpark/autoware.ai/install/vel_pose_diff_checker;/home/bkpark/autoware.ai/install/vehicle_socket;/home/bkpark/autoware.ai/install/vehicle_sim_model;/home/bkpark/autoware.ai/install/vehicle_model;/home/bkpark/autoware.ai/install/vehicle_gazebo_simulation_launcher;/home/bkpark/autoware.ai/install/vehicle_gazebo_simulation_interface;/home/bkpark/autoware.ai/install/vehicle_engage_panel;/home/bkpark/autoware.ai/install/vehicle_description;/home/bkpark/autoware.ai/install/trafficlight_recognizer;/home/bkpark/autoware.ai/install/op_utilities;/home/bkpark/autoware.ai/install/op_simulation_package;/home/bkpark/autoware.ai/install/op_local_planner;/home/bkpark/autoware.ai/install/op_global_planner;/home/bkpark/autoware.ai/install/lidar_kf_contour_track;/home/bkpark/autoware.ai/install/op_ros_helpers;/home/bkpark/autoware.ai/install/ff_waypoint_follower;/home/bkpark/autoware.ai/install/dp_planner;/home/bkpark/autoware.ai/install/op_simu;/home/bkpark/autoware.ai/install/op_planner;/home/bkpark/autoware.ai/install/op_utility;/home/bkpark/autoware.ai/install/lidar_euclidean_cluster_detect;/home/bkpark/autoware.ai/install/vector_map_server;/home/bkpark/autoware.ai/install/road_occupancy_processor;/home/bkpark/autoware.ai/install/costmap_generator;/home/bkpark/autoware.ai/install/object_map;/home/bkpark/autoware.ai/install/naive_motion_predict;/home/bkpark/autoware.ai/install/lanelet_aisan_converter;/home/bkpark/autoware.ai/install/map_file;/home/bkpark/autoware.ai/install/libvectormap;/home/bkpark/autoware.ai/install/lane_planner;/home/bkpark/autoware.ai/install/imm_ukf_pda_track;/home/bkpark/autoware.ai/install/decision_maker;/home/bkpark/autoware.ai/install/vector_map;/home/bkpark/autoware.ai/install/vector_map_msgs;/home/bkpark/autoware.ai/install/vectacam;/home/bkpark/autoware.ai/install/udon_socket;/home/bkpark/autoware.ai/install/twist_generator;/home/bkpark/autoware.ai/install/twist_gate;/home/bkpark/autoware.ai/install/twist_filter;/home/bkpark/autoware.ai/install/twist2odom;/home/bkpark/autoware.ai/install/tablet_socket;/home/bkpark/autoware.ai/install/runtime_manager;/home/bkpark/autoware.ai/install/mqtt_socket;/home/bkpark/autoware.ai/install/tablet_socket_msgs;/home/bkpark/autoware.ai/install/state_machine_lib;/home/bkpark/autoware.ai/install/sound_player;/home/bkpark/autoware.ai/install/sick_lms5xx;/home/bkpark/autoware.ai/install/sick_ldmrs_tools;/home/bkpark/autoware.ai/install/sick_ldmrs_driver;/home/bkpark/autoware.ai/install/sick_ldmrs_msgs;/home/bkpark/autoware.ai/install/sick_ldmrs_description;/home/bkpark/autoware.ai/install/points2image;/home/bkpark/autoware.ai/install/rosinterface;/home/bkpark/autoware.ai/install/rosbag_controller;/home/bkpark/autoware.ai/install/pure_pursuit;/home/bkpark/autoware.ai/install/points_preprocessor;/home/bkpark/autoware.ai/install/mpc_follower;/home/bkpark/autoware.ai/install/lidar_localizer;/home/bkpark/autoware.ai/install/emergency_handler;/home/bkpark/autoware.ai/install/autoware_health_checker;/home/bkpark/autoware.ai/install/as;/home/bkpark/autoware.ai/install/ros_observer;/home/bkpark/autoware.ai/install/roi_object_filter;/home/bkpark/autoware.ai/install/range_vision_fusion;/home/bkpark/autoware.ai/install/pos_db;/home/bkpark/autoware.ai/install/points_downsampler;/home/bkpark/autoware.ai/install/pixel_cloud_fusion;/home/bkpark/autoware.ai/install/pcl_omp_registration;/home/bkpark/autoware.ai/install/pc2_downsampler;/home/bkpark/autoware.ai/install/oculus_socket;/home/bkpark/autoware.ai/install/obj_db;/home/bkpark/autoware.ai/install/nmea_navsat;/home/bkpark/autoware.ai/install/ndt_tku;/home/bkpark/autoware.ai/install/ndt_gpu;/home/bkpark/autoware.ai/install/ndt_cpu;/home/bkpark/autoware.ai/install/multi_lidar_calibrator;/home/bkpark/autoware.ai/install/mrt_cmake_modules;/home/bkpark/autoware.ai/install/microstrain_driver;/home/bkpark/autoware.ai/install/memsic_imu;/home/bkpark/autoware.ai/install/marker_downsampler;/home/bkpark/autoware.ai/install/map_tools;/home/bkpark/autoware.ai/install/map_tf_generator;/home/bkpark/autoware.ai/install/log_tools;/home/bkpark/autoware.ai/install/lidar_shape_estimation;/home/bkpark/autoware.ai/install/lidar_point_pillars;/home/bkpark/autoware.ai/install/lidar_naive_l_shape_detect;/home/bkpark/autoware.ai/install/lidar_fake_perception;/home/bkpark/autoware.ai/install/lidar_apollo_cnn_seg_detect;/home/bkpark/autoware.ai/install/libwaypoint_follower;/home/bkpark/autoware.ai/install/lgsvl_simulator_bridge;/home/bkpark/autoware.ai/install/lanelet2_extension;/home/bkpark/autoware.ai/install/lanelet2_validation;/home/bkpark/autoware.ai/install/lanelet2_examples;/home/bkpark/autoware.ai/install/lanelet2_python;/home/bkpark/autoware.ai/install/lanelet2_routing;/home/bkpark/autoware.ai/install/lanelet2_traffic_rules;/home/bkpark/autoware.ai/install/lanelet2_projection;/home/bkpark/autoware.ai/install/lanelet2_maps;/home/bkpark/autoware.ai/install/lanelet2_io;/home/bkpark/autoware.ai/install/lanelet2_core;/home/bkpark/autoware.ai/install/kvaser;/home/bkpark/autoware.ai/install/kitti_launch;/home/bkpark/autoware.ai/install/kitti_player;/home/bkpark/autoware.ai/install/kitti_box_publisher;/home/bkpark/autoware.ai/install/javad_navsat_driver;/home/bkpark/autoware.ai/install/integrated_viewer;/home/bkpark/autoware.ai/install/image_processor;/home/bkpark/autoware.ai/install/hokuyo;/home/bkpark/autoware.ai/install/graph_tools;/home/bkpark/autoware.ai/install/gnss_localizer;/home/bkpark/autoware.ai/install/gnss;/home/bkpark/autoware.ai/install/glviewer;/home/bkpark/autoware.ai/install/gazebo_world_description;/home/bkpark/autoware.ai/install/gazebo_imu_description;/home/bkpark/autoware.ai/install/gazebo_camera_description;/home/bkpark/autoware.ai/install/garmin;/home/bkpark/autoware.ai/install/freespace_planner;/home/bkpark/autoware.ai/install/fastvirtualscan;/home/bkpark/autoware.ai/install/ekf_localizer;/home/bkpark/autoware.ai/install/ds4_msgs;/home/bkpark/autoware.ai/install/ds4_driver;/home/bkpark/autoware.ai/install/detected_objects_visualizer;/home/bkpark/autoware.ai/install/decision_maker_panel;/home/bkpark/autoware.ai/install/data_preprocessor;/home/bkpark/autoware.ai/install/custom_msgs;/home/bkpark/autoware.ai/install/carla_autoware_bridge;/home/bkpark/autoware.ai/install/calibration_publisher;/home/bkpark/autoware.ai/install/autoware_system_msgs;/home/bkpark/autoware.ai/install/autoware_rviz_plugins;/home/bkpark/autoware.ai/install/autoware_quickstart_examples;/home/bkpark/autoware.ai/install/autoware_pointgrey_drivers;/home/bkpark/autoware.ai/install/autoware_driveworks_interface;/home/bkpark/autoware.ai/install/autoware_connector;/home/bkpark/autoware.ai/install/autoware_camera_lidar_calibrator;/home/bkpark/autoware.ai/install/astar_search;/home/bkpark/autoware.ai/install/amathutils_lib;/home/bkpark/autoware.ai/install/autoware_msgs;/home/bkpark/autoware.ai/install/autoware_map_msgs;/home/bkpark/autoware.ai/install/autoware_launcher_rviz;/home/bkpark/autoware.ai/install/autoware_launcher;/home/bkpark/autoware.ai/install/autoware_lanelet2_msgs;/home/bkpark/autoware.ai/install/autoware_external_msgs;/home/bkpark/autoware.ai/install/autoware_driveworks_gmsl_interface;/home/bkpark/autoware.ai/install/autoware_config_msgs;/home/bkpark/autoware.ai/install/autoware_can_msgs;/home/bkpark/autoware.ai/install/autoware_build_flags;/home/bkpark/autoware.ai/install/autoware_bag_tools;/home/bkpark/autoware.ai/install/adi_driver;/opt/ros/melodic'.split(';'):
python_path = os.path.join(workspace, 'lib/python2.7/dist-packages')
if os.path.isdir(os.path.join(python_path, 'catkin')):
sys.path.insert(0, python_path)
break
from catkin.environment_cache import generate_environment_script
code = generate_environment_script('/home/bkpark/autoware.ai/src/autoware/core_perception/vision_darknet_detect/src/devel/env.sh')
output_filename = '/home/bkpark/autoware.ai/src/autoware/core_perception/vision_darknet_detect/src/catkin_generated/setup_cached.sh'
with open(output_filename, 'w') as f:
# print('Generate script for cached setup "%s"' % output_filename)
f.write('\n'.join(code))
mode = os.stat(output_filename).st_mode
os.chmod(output_filename, mode | stat.S_IXUSR)
| 304.548387
| 8,124
| 0.843555
| 1,394
| 9,441
| 5.52726
| 0.209469
| 0.211551
| 0.380792
| 0.423102
| 0.777417
| 0.686308
| 0.246723
| 0.055289
| 0.027515
| 0.017391
| 0
| 0.002591
| 0.018854
| 9,441
| 30
| 8,125
| 314.7
| 0.829213
| 0.026586
| 0
| 0.095238
| 0
| 0.142857
| 0.917692
| 0.915732
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0.047619
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 8
|
2db08abc4692a788d519875fbd940ccd2497a057
| 32
|
py
|
Python
|
function_19373178.py
|
Charlotte-zq/ASMART-38
|
22c34a602f9ccba979bd3975c56cca5b79cc452d
|
[
"MIT"
] | null | null | null |
function_19373178.py
|
Charlotte-zq/ASMART-38
|
22c34a602f9ccba979bd3975c56cca5b79cc452d
|
[
"MIT"
] | null | null | null |
function_19373178.py
|
Charlotte-zq/ASMART-38
|
22c34a602f9ccba979bd3975c56cca5b79cc452d
|
[
"MIT"
] | null | null | null |
print('My student_id: 19373178')
| 32
| 32
| 0.78125
| 5
| 32
| 4.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.266667
| 0.0625
| 32
| 1
| 32
| 32
| 0.533333
| 0
| 0
| 0
| 0
| 0
| 0.69697
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 7
|
2dc33b9aaf8216d548c052f275e851a6b22da733
| 163
|
py
|
Python
|
python/non_buildable_2/number_returns/tests/test_gimmes.py
|
nagi49000/tutorial-memory-refs-and-folder-structures
|
bede74884fc96d89b9cfdd45fba3c69b3f9445c1
|
[
"MIT"
] | null | null | null |
python/non_buildable_2/number_returns/tests/test_gimmes.py
|
nagi49000/tutorial-memory-refs-and-folder-structures
|
bede74884fc96d89b9cfdd45fba3c69b3f9445c1
|
[
"MIT"
] | null | null | null |
python/non_buildable_2/number_returns/tests/test_gimmes.py
|
nagi49000/tutorial-memory-refs-and-folder-structures
|
bede74884fc96d89b9cfdd45fba3c69b3f9445c1
|
[
"MIT"
] | null | null | null |
import number_returns.gimmes
def test_gimme3():
assert number_returns.gimmes.gimme3() == 3
def test_gimme5():
assert number_returns.gimmes.gimme5() == 5
| 20.375
| 46
| 0.736196
| 22
| 163
| 5.227273
| 0.5
| 0.33913
| 0.495652
| 0.434783
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.043165
| 0.147239
| 163
| 7
| 47
| 23.285714
| 0.784173
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.4
| 1
| 0.4
| true
| 0
| 0.2
| 0
| 0.6
| 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
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
93357565cb0e56706ecf3398df74322f11552676
| 7,465
|
py
|
Python
|
tests/causal_world/envs/robot/test_real_robot.py
|
michaelfeil/CausalWorld
|
ff866159ef0ee9c407893ae204e93eb98dd68be2
|
[
"MIT"
] | 2
|
2021-09-22T08:20:12.000Z
|
2021-11-16T14:20:45.000Z
|
tests/causal_world/envs/robot/test_real_robot.py
|
michaelfeil/CausalWorld
|
ff866159ef0ee9c407893ae204e93eb98dd68be2
|
[
"MIT"
] | null | null | null |
tests/causal_world/envs/robot/test_real_robot.py
|
michaelfeil/CausalWorld
|
ff866159ef0ee9c407893ae204e93eb98dd68be2
|
[
"MIT"
] | null | null | null |
# import robot_fingers
# import robot_interfaces
#
#
# def perform_step_real_robot(frontend, position, repetitions):
# for i in range(repetitions):
# t = frontend.append_desired_action(
# robot_interfaces.trifinger.Action(position=position))
# frontend.wait_until_time_index(t)
# current_position = frontend.get_observation(t).position
# current_velocity = frontend.get_observation(t).velocity
# return current_position
#
#
# def perform_step_simulated_robot(env, position, repetitions):
# for _ in range(repetitions):
# obs, reward, done, info = env.step(position)
# return obs[:9]
#
#
# def test_pd_gains():
# # control the robot using pd controller
# from causal_world.envs.world import World
# from causal_world.tasks.task import Task
# import numpy as np
# np.random.seed(0)
# task = Task(task_generator_id='reaching')
# skip_frame = 1 #@250Hz
# threshold = 0.05
# env = World(task=task, enable_visualization=True, skip_frame=skip_frame, normalize_observations=False,
# normalize_actions=False, seed=0)
# robot = robot_fingers.Robot(robot_interfaces.trifinger,
# robot_fingers.create_trifinger_backend,
# "trifinger.yml")
# robot.initialize()
# frontend = robot.frontend
# zero_hold_real_robot = 1000
# zero_hold_simulator = 250
# obs = env.reset()
# #stay at the idle place for the zero hold
# desired_action = obs[:9]
# simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# if (np.abs(real_positions - simulated_positions) > threshold).any():
# raise AssertionError("staying at idle position failed")
#
# # checking upper bound limit
# #TODO: this fails! the stage position is not accurate for now
# # desired_action = env.action_space.high
# # simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator * 10)
# # real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot * 5)
# # if (np.abs(real_positions - simulated_positions) > threshold).any():
# # raise AssertionError("going to upper bound failed")
#
# #checking lower bound limit
# desired_action = env.action_space.low
# simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# if (np.abs(real_positions - simulated_positions) > threshold).any():
# raise AssertionError("going to lower bound failed")
#
# #test each finger by itself
# for i in range(3):
# #set all the fingers to low bound first
# default_desired_action = env.action_space.low
# simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# for j in range(100):
# desired_action = default_desired_action
# desired_action[i*3:(i+1)*3] = env.__robot.sample_joint_positions()[i * 3:(i + 1) * 3]
# simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# if (np.abs(real_positions - simulated_positions) > threshold).any():
# raise AssertionError("random position failed comparison")
#
# # check random positions now with possible collisions
# for i in range(100):
# desired_action = env.__robot.sample_joint_positions()
# simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# if (np.abs(real_positions - simulated_positions) > threshold).any():
# raise AssertionError("random position failed comparison")
#
# env.close()
#
#
# def test_pd_gains_2():
# # control the robot using pd controller
# from causal_world.envs.world import World
# from causal_world.tasks.task import Task
# import numpy as np
# np.random.seed(0)
# task = Task(task_generator_id='reaching')
# skip_frame = 1#@240Hz
# threshold = 0.05
# env = World(task=task, enable_visualization=True, skip_frame=skip_frame, normalize_observations=False,
# normalize_actions=False, seed=0)
# robot = robot_fingers.Robot(robot_interfaces.trifinger,
# robot_fingers.create_trifinger_backend,
# "trifinger.yml")
# robot.initialize()
# frontend = robot.frontend
# zero_hold_real_robot = 4
# zero_hold_simulator = 1
# obs = env.reset()
# #stay at the idle place for the zero hold
# desired_action = env.action_space.low
# # simulated_positions = perform_step_simulated_robot(env, desired_action_sim, zero_hold_simulator)
# # real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# # if (np.abs(real_positions - simulated_positions) > threshold).any():
# # raise AssertionError("staying at idle position failed")
# #
# # desired_action = env.action_space.low
# # simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# # real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# # if (np.abs(real_positions - simulated_positions) > threshold).any():
# # raise AssertionError("going to lower bound failed")
# for i in range(250):
# simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# #go to low space in both envs
# for _ in range(5000):
# simulated_positions = perform_step_simulated_robot(env, simulated_positions, zero_hold_simulator)
# real_positions = perform_step_real_robot(frontend, real_positions, zero_hold_real_robot)
# # desired_action = np.zeros([9,])
# # current_obs = np.around(obs[:9], decimals=2)
# # print("what I wanted to reach", current_obs + desired_action)
# # obs, reward, done, info = env.step(desired_action)
# # print("what I actually reached", np.around(obs[:9], decimals=2))
# # print("diff is", current_obs + desired_action - np.around(obs[:9], decimals=2))
# # # desired_action = obs[:9]
#
# # for j in range(100):
# # desired_action = default_desired_action
# # desired_action[i * 3:(i + 1) * 3] = env.robot.sample_joint_positions()[i * 3:(i + 1) * 3]
# # simulated_positions = perform_step_simulated_robot(env, desired_action, zero_hold_simulator)
# # real_positions = perform_step_real_robot(frontend, desired_action, zero_hold_real_robot)
# # if (np.abs(real_positions - simulated_positions) > threshold).any():
# # raise AssertionError("random position failed comparison")
#
#
# # test_pd_gains()
# # test_pd_gains_2()
| 51.840278
| 108
| 0.686805
| 916
| 7,465
| 5.278384
| 0.162664
| 0.10486
| 0.091003
| 0.082523
| 0.79938
| 0.771665
| 0.757394
| 0.737125
| 0.737125
| 0.737125
| 0
| 0.012106
| 0.214334
| 7,465
| 143
| 109
| 52.202797
| 0.812276
| 0.955526
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0.006993
| null | 1
| null | true
| 0
| 0
| null | null | null | 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 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
| 7
|
937ecb30b9672ce38e6f10a5fe0990456ca24899
| 5,021
|
py
|
Python
|
authors/apps/tests/test_comment_on_article.py
|
arthurarty/ah-backend-poseidon
|
d2b561e83ed1e9a585853f4a4e2e37805e86c35c
|
[
"BSD-3-Clause"
] | 1
|
2019-01-22T18:00:44.000Z
|
2019-01-22T18:00:44.000Z
|
authors/apps/tests/test_comment_on_article.py
|
arthurarty/ah-backend-poseidon
|
d2b561e83ed1e9a585853f4a4e2e37805e86c35c
|
[
"BSD-3-Clause"
] | 24
|
2018-11-27T10:11:13.000Z
|
2021-06-10T21:01:15.000Z
|
authors/apps/tests/test_comment_on_article.py
|
andela/ah-backend-poseidon
|
d2b561e83ed1e9a585853f4a4e2e37805e86c35c
|
[
"BSD-3-Clause"
] | 4
|
2019-05-29T12:08:52.000Z
|
2020-05-23T11:48:42.000Z
|
"""
Test articles app
"""
from django.urls import reverse
from rest_framework import status
from . import post_article, thread, comment, highlight_comment_1, highlight_comment_2
from authors.apps.tests.base import BaseTestCase
class TestComment(BaseTestCase):
"""
test class to contain functions to handle test for the commenting on an article
"""
def test_create_a_comment(self):
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
response = self.client.post(url, data=comment, format="json")
self.assertEqual(response.status_code, status.HTTP_201_CREATED)
def test_get_single_comment(self):
"This menthod tests getting a single comment"
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
res = self.client.post(url, data=comment, format="json")
comment_id = res.data['id']
response = self.client.get(
f'/api/{slug}/comments/{comment_id}', format="json")
self.assertEqual(response.status_code, status.HTTP_200_OK)
def test_post_reply_to_comment(self):
"""
method to test for a reply to a comment
"""
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
res = self.client.post(url, data=comment, format="json")
comment_id = res.data['id']
response = self.client.post(
f'/api/{slug}/comments/{comment_id}/thread',
data=thread,
format="json")
self.assertEqual(response.status_code, status.HTTP_201_CREATED)
def test_post_reply_to_comment_with_no_body(self):
"""
method to test for an empty reply.
"""
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
res = self.client.post(url, data=comment, format="json")
comment_id = res.data['id']
response = self.client.post(
f'/api/{slug}/comments/{comment_id}/thread',
format="json")
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_get_reply_to_comment(self):
"""
testing for a single reply
"""
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
res = self.client.post(url, data=comment, format="json")
comment_id = res.data['id']
response = self.client.post(
f'/api/{slug}/comments/{comment_id}/thread',
data=thread,
format="json")
self.assertEqual(response.status_code, status.HTTP_201_CREATED)
response = self.client.get(
f'/api/{slug}/comments/{comment_id}/thread', format="json")
self.assertEqual(response.status_code, status.HTTP_200_OK)
def test_create_a_comment_with_no_body(self):
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
response = self.client.post(url, format="json")
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_get_all_comments(self):
"""
test to get all comments
"""
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
response = self.client.get(url, data=comment, format="json")
self.assertEqual(response.status_code, status.HTTP_200_OK)
def test_delete_comment(self):
"""
tests to delete a comment
"""
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
res = self.client.post(url, data=comment, format="json")
comment_id = res.data['id']
response = self.client.delete(
f'/api/{slug}/comments/{comment_id}', data=thread, format="json")
self.assertEqual(response.status_code, status.HTTP_200_OK)
def test_error_when_no_data_highlighted(self):
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
response = self.client.post(
url, data=highlight_comment_1, format="json")
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_error_when_non_interger_used_to_highlight(self):
self.user_access()
self.posting_article(post_article)
slug = self.slugger()
url = f'/api/{slug}/comments/'
response = self.client.post(
url, data=highlight_comment_2, format="json")
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
| 35.609929
| 85
| 0.628162
| 623
| 5,021
| 4.850722
| 0.134831
| 0.021178
| 0.042356
| 0.084712
| 0.830576
| 0.799801
| 0.779616
| 0.779616
| 0.779616
| 0.779616
| 0
| 0.009843
| 0.251344
| 5,021
| 140
| 86
| 35.864286
| 0.794094
| 0.058554
| 0
| 0.752475
| 0
| 0
| 0.119983
| 0.094598
| 0
| 0
| 0
| 0
| 0.108911
| 1
| 0.09901
| false
| 0
| 0.039604
| 0
| 0.148515
| 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
|
fa96686cab6461843c90a4b2df6e5026cd85e5b3
| 19,015
|
py
|
Python
|
artific/artific.py
|
waasnipun/artific
|
ae6fedad9afdd75a21c5ce4badd8f4d86e76bf31
|
[
"MIT"
] | 2
|
2022-01-10T23:07:35.000Z
|
2022-03-13T00:41:27.000Z
|
artific/artific.py
|
waasnipun/artific
|
ae6fedad9afdd75a21c5ce4badd8f4d86e76bf31
|
[
"MIT"
] | null | null | null |
artific/artific.py
|
waasnipun/artific
|
ae6fedad9afdd75a21c5ce4badd8f4d86e76bf31
|
[
"MIT"
] | null | null | null |
"""Main module."""
import numpy as np
import seaborn as sb
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import imageio
import os
class BubbleSort:
def __init__(self, array):
self.n = len(array)
self.array = np.array(array).reshape(1, self.n)
self.iter = 0
self.input_shape = (1, 1)
self.fps = 1
self.dpi = 100
self.max_array_len = 8
self.rectangle_color_1 = 'gold'
self.rectangle_color_2 = 'red'
self.save_dir = 'gifs/'
self.custom_save_name = False
self.save_name = ''
self.saved_gif_path = ''
self._ims = []
self.sort()
def sort(self):
assert self.n != 0, 'Array length should be > 0'
self.iter = 0
for i in range(self.n):
for j in range(0, self.n - i - 1):
self.iter += 1
if self.array[0][j] > self.array[0][j + 1]:
self.array[0][j], self.array[0][j + 1] = self.array[0][j + 1], self.array[0][j]
self.create_gif(j, j + 1, is_swap=True)
else:
self.create_gif(j, j + 1, is_swap=False)
if not os.path.exists('gifs/'):
os.mkdir('gifs/')
imageio.mimsave(f'{self.save_dir}/bubble_sort_comparisons_{self.iter}.gif', self._ims, fps=self.fps)
self.saved_gif_path = f'{self.save_dir}/bubble_sort_comparisons_{self.iter}.gif'
self._ims = []
return self.array
def __str__(self) -> str:
return str(self.array[0].tolist())
def visualize(self):
import base64
from IPython import display
with open(self.saved_gif_path, 'rb') as fd:
b64 = base64.b64encode(fd.read()).decode('ascii')
return display.HTML(f'<img src="data:image/gif;base64,{b64}" />')
def create_gif(self, column_index_left_box, column_index_right_box, row_index_left_box=0, row_index_right_box=0,
is_swap=False):
if self.n % self.max_array_len == 0:
_gif_array = np.reshape(self.array, (-1, self.max_array_len))
row_index_left_box = int(column_index_left_box / self.max_array_len)
row_index_right_box = int(column_index_right_box / self.max_array_len)
column_index_left_box = column_index_left_box % self.max_array_len
column_index_right_box = column_index_right_box % self.max_array_len
else:
_gif_array = self.array
self.input_shape = (len(_gif_array), len(_gif_array[0]))
scale = 0.8
figsize = (self.input_shape[1] * scale, self.input_shape[0] * scale)
fig, ax = plt.subplots(figsize=figsize)
ax = sb.heatmap(_gif_array, square=True, cbar=False, xticklabels=False, yticklabels=False, annot=True,
cmap="cool", linewidths=4)
# adding rectangle
if is_swap:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
ax.add_patch(Rectangle((column_index_right_box, row_index_right_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
else:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
ax.add_patch(Rectangle((column_index_right_box, row_index_right_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
# create and save gif
if not os.path.exists('temp/'):
os.mkdir('temp/')
img_loc = 'temp/' + 'temp_image_{:d}'.format(self.iter + 1) + '.png'
plt.savefig(img_loc, bbox_inches='tight', dpi=self.dpi)
self._ims.append(imageio.imread(img_loc))
os.remove(img_loc)
plt.close()
class InsertionSort:
def __init__(self, array):
self.n = len(array)
self.array = np.array(array).reshape(1, self.n)
self.iter = 0
self.input_shape = (1, 1)
self.fps = 1
self.dpi = 100
self.max_array_len = 8
self.rectangle_color_1 = 'gold'
self.rectangle_color_2 = 'red'
self.save_dir = 'gifs/'
self.custom_save_name = False
self.save_name = ''
self.saved_gif_path = ''
self._ims = []
self.sort()
def sort(self):
assert self.n != 0, 'Array length should be > 0'
self.iter = 0
for i in range(1, self.n):
key = self.array[0][i]
j = i-1
while j >= 0 and key < self.array[0][j] :
self.array[0][j + 1] = self.array[0][j]
j -= 1
self.iter += 1
self.create_gif(i, j+1, is_swap=True)
self.array[0][j + 1] = key
if not os.path.exists('gifs/'):
os.mkdir('gifs/')
imageio.mimsave(f'{self.save_dir}/bubble_sort_comparisons_{self.iter}.gif', self._ims, fps=self.fps)
self.saved_gif_path = f'{self.save_dir}/bubble_sort_comparisons_{self.iter}.gif'
self._ims = []
return self.array
def __str__(self) -> str:
return str(self.array[0].tolist())
def visualize(self):
import base64
from IPython import display
with open(self.saved_gif_path, 'rb') as fd:
b64 = base64.b64encode(fd.read()).decode('ascii')
return display.HTML(f'<img src="data:image/gif;base64,{b64}" />')
def create_gif(self, column_index_left_box, column_index_right_box, row_index_left_box=0, row_index_right_box=0,
is_swap=False):
if self.n % self.max_array_len == 0:
_gif_array = np.reshape(self.array, (-1, self.max_array_len))
row_index_left_box = int(column_index_left_box / self.max_array_len)
row_index_right_box = int(column_index_right_box / self.max_array_len)
column_index_left_box = column_index_left_box % self.max_array_len
column_index_right_box = column_index_right_box % self.max_array_len
else:
_gif_array = self.array
self.input_shape = (len(_gif_array), len(_gif_array[0]))
scale = 0.8
figsize = (self.input_shape[1] * scale, self.input_shape[0] * scale)
fig, ax = plt.subplots(figsize=figsize)
ax = sb.heatmap(_gif_array, square=True, cbar=False, xticklabels=False, yticklabels=False, annot=True,
cmap="cool", linewidths=4)
# adding rectangle
if is_swap:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
ax.add_patch(Rectangle((column_index_right_box, row_index_right_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
else:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
ax.add_patch(Rectangle((column_index_right_box, row_index_right_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
# create and save gif
if not os.path.exists('temp/'):
os.mkdir('temp/')
img_loc = 'temp/' + 'temp_image_{:d}'.format(self.iter + 1) + '.png'
plt.savefig(img_loc, bbox_inches='tight', dpi=self.dpi)
self._ims.append(imageio.imread(img_loc))
os.remove(img_loc)
plt.close()
class HeapSort:
def __init__(self, array):
self.n = len(array)
self.array = np.array(array).reshape(1, self.n)
self.iter = 0
self.input_shape = (1, 1)
self.fps = 1
self.dpi = 100
self.max_array_len = 8
self.rectangle_color_1 = 'gold'
self.rectangle_color_2 = 'red'
self.save_dir = 'gifs/'
self.custom_save_name = False
self.save_name = ''
self.saved_gif_path = ''
self._ims = []
self.sort()
def heapify(self, n, i):
largest = i # Initialize largest as root
l = 2 * i + 1 # left = 2*i + 1
r = 2 * i + 2 # right = 2*i + 2
# See if left child of root exists and is
# greater than root
if l < n and self.array[0][largest] < self.array[0][l]:
largest = l
# See if right child of root exists and is
# greater than root
if r < n and self.array[0][largest] < self.array[0][r]:
largest = r
# Change root, if needed
if largest != i:
self.array[0][i], self.array[0][largest] = self.array[0][largest], self.array[0][i] # swap
self.create_gif(i, largest, is_swap=True)
# Heapify the root.
self.heapify( n, largest)
self.iter+=1
# The main function to sort an array of given size
def sort(self):
n = len(self.array[0])
# Build a maxheap.
for i in range(n//2 - 1, -1, -1):
self.heapify(n, i)
# One by one extract elements
for i in range(n-1, 0, -1):
self.array[0][i], self.array[0][0] = self.array[0][0], self.array[0][i] # swap
self.heapify(i, 0)
if not os.path.exists('gifs/'):
os.mkdir('gifs/')
imageio.mimsave(f'{self.save_dir}/bubble_sort_comparisons_{self.iter}.gif', self._ims, fps=self.fps)
self.saved_gif_path = f'{self.save_dir}/bubble_sort_comparisons_{self.iter}.gif'
self._ims = []
return self.array
def __str__(self) -> str:
return str(self.array[0].tolist())
def visualize(self):
import base64
from IPython import display
with open(self.saved_gif_path, 'rb') as fd:
b64 = base64.b64encode(fd.read()).decode('ascii')
return display.HTML(f'<img src="data:image/gif;base64,{b64}" />')
def create_gif(self, column_index_left_box, column_index_right_box, row_index_left_box=0, row_index_right_box=0,
is_swap=False):
if self.n % self.max_array_len == 0:
_gif_array = np.reshape(self.array, (-1, self.max_array_len))
row_index_left_box = int(column_index_left_box / self.max_array_len)
row_index_right_box = int(column_index_right_box / self.max_array_len)
column_index_left_box = column_index_left_box % self.max_array_len
column_index_right_box = column_index_right_box % self.max_array_len
else:
_gif_array = self.array
self.input_shape = (len(_gif_array), len(_gif_array[0]))
scale = 0.8
figsize = (self.input_shape[1] * scale, self.input_shape[0] * scale)
fig, ax = plt.subplots(figsize=figsize)
ax = sb.heatmap(_gif_array, square=True, cbar=False, xticklabels=False, yticklabels=False, annot=True,
cmap="cool", linewidths=4)
# adding rectangle
if is_swap:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
ax.add_patch(Rectangle((column_index_right_box, row_index_right_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
else:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
ax.add_patch(Rectangle((column_index_right_box, row_index_right_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
# create and save gif
if not os.path.exists('temp/'):
os.mkdir('temp/')
img_loc = 'temp/' + 'temp_image_{:d}'.format(self.iter + 1) + '.png'
plt.savefig(img_loc, bbox_inches='tight', dpi=self.dpi)
self._ims.append(imageio.imread(img_loc))
os.remove(img_loc)
plt.close()
class BinarySearch:
def __init__(self, array, value):
assert sorted(array) == array, 'Input array is not sorted!'
self.value = value
self.n = len(array)
self.array = array
self.iter = 0
self.input_shape = (1, 1)
self.fps = 1
self.dpi = 100
self.max_array_len = 8
self.rectangle_color_1 = 'gold'
self.rectangle_color_2 = 'red'
self.save_dir = 'gifs/'
self.custom_save_name = False
self.save_name = ''
self.saved_gif_path = ''
self._ims = []
def search(self, value):
valueExist = 'not found'
start = 0
end = len(self.array)-1
middle = 0
while(start<=end):
middle = int((start+end)/2)
self.create_gif(middle)
if self.array[middle] == value:
self.create_gif(middle, isFound=True)
valueExist = middle
break
else:
if self.array[middle]>value:
end = middle - 1
else:
start = middle + 1
if not os.path.exists('gifs/'):
os.mkdir('gifs/')
imageio.mimsave(f'{self.save_dir}/binary_search_{self.iter}.gif', self._ims, fps=self.fps)
self.saved_gif_path = f'{self.save_dir}/binary_search_{self.iter}.gif'
self._ims = []
return valueExist
def __str__(self) -> str:
val = self.search(value=self.value)
if val == 'not found':
return "Not Found"
else:
return str(val)
def visualize(self):
import base64
from IPython import display
with open(self.saved_gif_path, 'rb') as fd:
b64 = base64.b64encode(fd.read()).decode('ascii')
return display.HTML(f'<img src="data:image/gif;base64,{b64}" />')
def create_gif(self, column_index_left_box, row_index_left_box=0,
isFound=False):
if self.n % self.max_array_len == 0:
_gif_array = np.reshape(np.array(self.array).reshape(1, self.n), (-1, self.max_array_len))
row_index_left_box = int(column_index_left_box / self.max_array_len)
column_index_left_box = column_index_left_box % self.max_array_len
else:
_gif_array = np.array(self.array).reshape(1, self.n)
self.input_shape = (len(_gif_array), len(_gif_array[0]))
scale = 0.8
figsize = (self.input_shape[1] * scale, self.input_shape[0] * scale)
fig, ax = plt.subplots(figsize=figsize)
ax = sb.heatmap(_gif_array, square=True, cbar=False, xticklabels=False, yticklabels=False, annot=True,
cmap="cool", linewidths=4)
# adding rectangle
if isFound:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
else:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
# create and save gif
if not os.path.exists('temp/'):
os.mkdir('temp/')
img_loc = 'temp/' + 'temp_image_{:d}'.format(self.iter + 1) + '.png'
plt.savefig(img_loc, bbox_inches='tight', dpi=self.dpi)
self._ims.append(imageio.imread(img_loc))
os.remove(img_loc)
plt.close()
class LinearSearch:
def __init__(self, array, value):
self.value = value
self.n = len(array)
self.array = array
self.iter = 0
self.input_shape = (1, 1)
self.fps = 1
self.dpi = 100
self.max_array_len = 8
self.rectangle_color_1 = 'gold'
self.rectangle_color_2 = 'red'
self.save_dir = 'gifs/'
self.custom_save_name = False
self.save_name = ''
self.saved_gif_path = ''
self._ims = []
def search(self, value):
valueExist = 'not found'
for i in range(len(self.array)):
self.create_gif(i)
if self.array[i] == value:
valueExist = i
self.create_gif(i, isFound=True)
break
if not os.path.exists('gifs/'):
os.mkdir('gifs/')
imageio.mimsave(f'{self.save_dir}/binary_search_{self.iter}.gif', self._ims, fps=self.fps)
self.saved_gif_path = f'{self.save_dir}/binary_search_{self.iter}.gif'
self._ims = []
return valueExist
def __str__(self) -> str:
val = self.search(value=self.value)
if val == 'not found':
return "Not Found"
else:
return str(val)
def visualize(self):
import base64
from IPython import display
with open(self.saved_gif_path, 'rb') as fd:
b64 = base64.b64encode(fd.read()).decode('ascii')
return display.HTML(f'<img src="data:image/gif;base64,{b64}" />')
def create_gif(self, column_index_left_box, row_index_left_box=0,
isFound=False):
if self.n % self.max_array_len == 0:
_gif_array = np.reshape(np.array(self.array).reshape(1, self.n), (-1, self.max_array_len))
row_index_left_box = int(column_index_left_box / self.max_array_len)
column_index_left_box = column_index_left_box % self.max_array_len
else:
_gif_array = np.array(self.array).reshape(1, self.n)
self.input_shape = (len(_gif_array), len(_gif_array[0]))
scale = 0.8
figsize = (self.input_shape[1] * scale, self.input_shape[0] * scale)
fig, ax = plt.subplots(figsize=figsize)
ax = sb.heatmap(_gif_array, square=True, cbar=False, xticklabels=False, yticklabels=False, annot=True,
cmap="cool", linewidths=4)
# adding rectangle
if isFound:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_2, lw=4))
else:
ax.add_patch(Rectangle((column_index_left_box, row_index_left_box), 1, 1, fill=False,
edgecolor=self.rectangle_color_1, lw=4))
# create and save gif
if not os.path.exists('temp/'):
os.mkdir('temp/')
img_loc = 'temp/' + 'temp_image_{:d}'.format(self.iter + 1) + '.png'
plt.savefig(img_loc, bbox_inches='tight', dpi=self.dpi)
self._ims.append(imageio.imread(img_loc))
os.remove(img_loc)
plt.close()
| 36.779497
| 116
| 0.574126
| 2,585
| 19,015
| 3.974081
| 0.069246
| 0.048185
| 0.058406
| 0.045264
| 0.910055
| 0.896622
| 0.89487
| 0.88533
| 0.881437
| 0.875402
| 0
| 0.02333
| 0.305706
| 19,015
| 517
| 117
| 36.779497
| 0.75481
| 0.027242
| 0
| 0.84399
| 0
| 0
| 0.065353
| 0.036548
| 0.012788
| 0
| 0
| 0
| 0.007673
| 1
| 0.066496
| false
| 0
| 0.040921
| 0.007673
| 0.163683
| 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
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| null | 0
| 0
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| 0
| 0
| 0
| 0
|
0
| 7
|
8793f9dae14614e7f144531c0c88078a33745691
| 9,127
|
py
|
Python
|
KCIH/Kisumu/models.py
|
MERVIN-dev254/KCIH
|
de427f6e936839dad8cb9eaef6883656f531a254
|
[
"bzip2-1.0.6"
] | 1
|
2021-03-22T15:24:09.000Z
|
2021-03-22T15:24:09.000Z
|
KCIH/Kisumu/models.py
|
MERVIN-dev254/KCIH
|
de427f6e936839dad8cb9eaef6883656f531a254
|
[
"bzip2-1.0.6"
] | null | null | null |
KCIH/Kisumu/models.py
|
MERVIN-dev254/KCIH
|
de427f6e936839dad8cb9eaef6883656f531a254
|
[
"bzip2-1.0.6"
] | null | null | null |
from django.db import models
from passlib.hash import pbkdf2_sha256
class Constituency(models.Model):
name = models.CharField(max_length=255)
def __str__(self):
return self.name
class Ward(models.Model):
constituency = models.ForeignKey(Constituency, on_delete=models.CASCADE)
name = models.CharField(max_length=255)
def __str__(self):
return self.name
class Position(models.Model):
position = models.CharField(max_length=255)
def __str__(self):
return self.position
class Leader(models.Model):
fname = models.CharField(max_length=255)
lname = models.CharField(max_length=255)
image = models.FileField(upload_to='leaders')
idNo = models.IntegerField()
is_leader = models.BooleanField(default=True)
password = models.CharField(max_length=255)
position = models.ForeignKey(Position, on_delete=models.CASCADE)
def __str__(self):
return self.lname
def verify_password(self, rawpassword):
return pbkdf2_sha256.verify(rawpassword, self.password)
class MP(models.Model):
fname = models.CharField(max_length=255)
lname = models.CharField(max_length=255)
image = models.FileField(upload_to='mps')
idNo = models.IntegerField()
is_mp = models.BooleanField(default=True)
password = models.CharField(max_length=255)
constituency = models.ForeignKey(Constituency, on_delete=models.CASCADE)
def __str__(self):
return self.lname
def verify_password(self, rawpassword):
return pbkdf2_sha256.verify(rawpassword, self.password)
class MCA(models.Model):
fname = models.CharField(max_length=255)
lname = models.CharField(max_length=255)
image = models.FileField(upload_to='mcas')
idNo = models.IntegerField()
is_mca = models.BooleanField(default=True)
password = models.CharField(max_length=255)
ward = models.ForeignKey(Ward, on_delete=models.CASCADE)
def __str__(self):
return self.lname
def verify_password(self, rawpassword):
return pbkdf2_sha256.verify(rawpassword, self.password)
class Ministry(models.Model):
name = models.CharField(max_length=255)
image = models.FileField(upload_to='ministry_image')
address = models.CharField(max_length=255)
def __str__(self):
return self.name
class Union(models.Model):
name = models.CharField(max_length=255)
image = models.FileField(upload_to='union_image')
def __str__(self):
return self.name
class LeaderProject(models.Model):
leader = models.ForeignKey(Leader, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='leader_projects')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
estimate = models.IntegerField()
allocation = models.IntegerField()
description = models.TextField()
status = models.BooleanField(default=False)
def __str__(self):
return self.title
class MPProject(models.Model):
mp = models.ForeignKey(MP, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='mp_projects')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
estimate = models.IntegerField()
allocation = models.IntegerField()
description = models.TextField()
status = models.BooleanField(default=False)
def __str__(self):
return self.title
class MCAProject(models.Model):
mca = models.ForeignKey(MCA, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='mca_projects')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
estimate = models.IntegerField()
allocation = models.IntegerField()
description = models.TextField()
status = models.BooleanField(default=False)
def __str__(self):
return self.title
class MinistryProject(models.Model):
ministry = models.ForeignKey(Ministry, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='ministry_projects')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
estimate = models.IntegerField()
allocation = models.IntegerField()
description = models.TextField()
status = models.BooleanField(default=False)
def __str__(self):
return self.title
class LeaderUpdates(models.Model):
leader = models.ForeignKey(Leader, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='leader_updates')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
message = models.TextField()
def __str__(self):
return self.title
class MPUpdates(models.Model):
mp = models.ForeignKey(MP, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='mp_updates')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
message = models.TextField()
def __str__(self):
return self.title
class MCAUpdates(models.Model):
mca = models.ForeignKey(MCA, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='mca_updates')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
message = models.TextField()
def __str__(self):
return self.title
class MinistryUpdates(models.Model):
ministry = models.ForeignKey(Ministry, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='ministry_updates')
location = models.CharField(max_length=255)
day =models.DateTimeField(auto_now_add=True)
message = models.TextField()
def __str__(self):
return self.title
class UnionUpdates(models.Model):
union = models.ForeignKey(Union, on_delete=models.CASCADE)
title = models.CharField(max_length=255)
image = models.FileField(upload_to='union_updates')
location = models.CharField(max_length=255)
day = models.DateTimeField(auto_now_add=True)
message = models.TextField()
def __str__(self):
return self.title
class Admin(models.Model):
fname = models.CharField(max_length=255)
lname = models.CharField(max_length=255)
idNo = models.IntegerField()
password = models.CharField(max_length=255)
def __str__(self):
return self.lname
def verify_password(self, rawpassword):
return pbkdf2_sha256.verify(rawpassword, self.password)
class MinistryOfficial(models.Model):
fname = models.CharField(max_length=255)
lname = models.CharField(max_length=255)
idNo = models.IntegerField()
is_ministry_off = models.BooleanField(default=True)
password = models.CharField(max_length=255)
ministry = models.ForeignKey(Ministry, on_delete=models.CASCADE)
def __str__(self):
return self.lname
def verify_password(self, rawpassword):
return pbkdf2_sha256.verify(rawpassword, self.password)
class UnionOfficial(models.Model):
fname = models.CharField(max_length=255)
lname = models.CharField(max_length=255)
idNo = models.IntegerField()
is_union_off = models.BooleanField(default=True)
password = models.CharField(max_length=255)
union = models.ForeignKey(Union, on_delete=models.CASCADE)
def __str__(self):
return self.lname
def verify_password(self, rawpassword):
return pbkdf2_sha256.verify(rawpassword, self.password)
class MPUpdArchive(models.Model):
sponsor = models.CharField(max_length=255)
time_archived = models.DateTimeField(auto_now_add=True)
title = models.CharField(max_length=255)
message = models.TextField()
day = models.DateTimeField()
def __str__(self):
return self.title
class MPProjArchive(models.Model):
title = models.CharField(max_length=255)
time_archived = models.DateTimeField(auto_now_add=True)
estimate = models.IntegerField()
allocation = models.IntegerField()
location = models.CharField(max_length=255)
status = models.BooleanField()
def __str__(self):
return self.title
class LeaderUpdArchive(models.Model):
sponsor = models.CharField(max_length=255)
time_archived = models.DateTimeField(auto_now_add=True)
title = models.CharField(max_length=255)
message = models.TextField()
day = models.DateTimeField()
def __str__(self):
return self.title
class LeaderProjArchive(models.Model):
sponsor = models.CharField(max_length=255)
time_archived = models.DateTimeField(auto_now_add=True)
title = models.CharField(max_length=255)
estimate = models.IntegerField()
allocation = models.IntegerField()
location = models.CharField(max_length=255)
status = models.BooleanField()
def __str__(self):
return self.title
class MCAUpdArchive(models.Model):
sponsor = models.CharField(max_length=255)
time_archived = models.DateTimeField(auto_now_add=True)
title = models.CharField(max_length=255)
message = models.TextField()
day = models.DateTimeField()
def __str__(self):
return self.title
class MCAProjArchive(models.Model):
sponsor = models.CharField(max_length=255)
time_archived = models.DateTimeField(auto_now_add=True)
title = models.CharField(max_length=255)
estimate = models.IntegerField()
allocation = models.IntegerField()
location = models.CharField(max_length=255)
status = models.BooleanField()
def __str__(self):
return self.title
| 29.066879
| 73
| 0.779117
| 1,171
| 9,127
| 5.853971
| 0.076003
| 0.122538
| 0.147046
| 0.196061
| 0.914953
| 0.914953
| 0.913056
| 0.908826
| 0.880233
| 0.880233
| 0
| 0.024108
| 0.109236
| 9,127
| 314
| 74
| 29.066879
| 0.819065
| 0
| 0
| 0.782427
| 0
| 0
| 0.017309
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.133891
| false
| 0.079498
| 0.008368
| 0.133891
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
| 1
| 1
| 0
|
0
| 11
|
87ce5920108c98a5d499af15c4cb37cb3c157dda
| 4,219
|
py
|
Python
|
config/paths_catalog.py
|
tanghaoyu258/ACRM-for-moment-retrieval
|
a5757c3e33621cefc3489c13c260667882c82e34
|
[
"MIT"
] | 18
|
2020-09-24T06:31:52.000Z
|
2022-03-01T06:15:32.000Z
|
config/paths_catalog.py
|
tanghaoyu258/ACRM-for-moment-retrieval
|
a5757c3e33621cefc3489c13c260667882c82e34
|
[
"MIT"
] | 3
|
2020-09-24T13:41:50.000Z
|
2021-12-03T06:19:35.000Z
|
config/paths_catalog.py
|
tanghaoyu258/ACRM-for-moment-retrieval
|
a5757c3e33621cefc3489c13c260667882c82e34
|
[
"MIT"
] | 2
|
2020-09-28T06:53:43.000Z
|
2021-09-21T07:56:32.000Z
|
import os
from .settings import (
ANET_FEATURES_PATH,
CHARADES_FEATURES_PATH,
EMBEDDINGS_PATH,
ANNOTATIONS_PATH)
class DatasetCatalog(object):
DATA_DIR = "datasets"
DATASETS = {
"anet_cap_train": {
"feature_path": os.path.join(
ANET_FEATURES_PATH, 'anet-cap/anet_c3d.hdf5'),
"ann_file_path": os.path.join(
ANNOTATIONS_PATH, 'anet-cap/train.json'),
"embeddings_path": os.path.join(
EMBEDDINGS_PATH, 'glove.840B.300d.txt'),
},
"anet_cap_test": {
"feature_path": os.path.join(
ANET_FEATURES_PATH, 'anet-cap/anet_c3d.hdf5'),
"ann_file_path": os.path.join(
ANNOTATIONS_PATH, 'anet-cap/val_2.json'),
"embeddings_path":
os.path.join(
EMBEDDINGS_PATH, 'glove.840B.300d.txt'),
},
"charades_sta_train": {
"feature_path": os.path.join(
CHARADES_FEATURES_PATH, 'charades-sta/charades_i3d.hdf5'),
"ann_file_path":
os.path.join(
ANNOTATIONS_PATH, 'charades-sta/charades_sta_train_tokens.json'),
"embeddings_path": os.path.join(
EMBEDDINGS_PATH, 'glove.840B.300d.txt')
},
"charades_sta_test": {
"feature_path": os.path.join(
CHARADES_FEATURES_PATH, 'charades-sta/charades_i3d.hdf5'),
"ann_file_path": os.path.join(
ANNOTATIONS_PATH, 'charades-sta/charades_sta_test_tokens.json'),
"embeddings_path": os.path.join(
EMBEDDINGS_PATH, 'glove.840B.300d.txt')
},
"tacos_train": {
"feature_path": os.path.join(
ANET_FEATURES_PATH, 'tacos/tacos_c3d.hdf5'),
"ann_file_path": os.path.join(
ANNOTATIONS_PATH, 'tacos/tacos_train.json'),
"embeddings_path": os.path.join(
EMBEDDINGS_PATH, 'glove.840B.300d.txt'),
},
"tacos_test": {
"feature_path": os.path.join(
ANET_FEATURES_PATH, 'tacos/tacos_c3d.hdf5'),
"ann_file_path": os.path.join(
ANNOTATIONS_PATH, 'tacos/tacos_test.json'),
"embeddings_path":
os.path.join(
EMBEDDINGS_PATH, 'glove.840B.300d.txt'),
},
}
@staticmethod
def get(name):
if "charades_sta" in name:
data_dir = DatasetCatalog.DATA_DIR
attrs = DatasetCatalog.DATASETS[name]
args = dict(
# features_path=os.path.join(data_dir, attrs["feature_path"]),
features_path=attrs["feature_path"],
ann_file_path=os.path.join(data_dir, attrs["ann_file_path"]),
embeddings_path=os.path.join(data_dir, attrs["embeddings_path"]),
)
return dict(
factory="CHARADES_STA",
args=args,
)
if "anet_cap" in name:
data_dir = DatasetCatalog.DATA_DIR
attrs = DatasetCatalog.DATASETS[name]
args = dict(
# features_path=os.path.join(data_dir, attrs["feature_path"]),
features_path=attrs["feature_path"],
ann_file_path=os.path.join(data_dir, attrs["ann_file_path"]),
embeddings_path=os.path.join(data_dir, attrs["embeddings_path"]),
)
return dict(
factory="ANET_CAP",
args=args,
)
if "tacos" in name:
data_dir = DatasetCatalog.DATA_DIR
attrs = DatasetCatalog.DATASETS[name]
args = dict(
# features_path=os.path.join(data_dir, attrs["feature_path"]),
features_path=attrs["feature_path"],
ann_file_path=os.path.join(data_dir, attrs["ann_file_path"]),
embeddings_path=os.path.join(data_dir, attrs["embeddings_path"]),
)
return dict(
factory="TACOS",
args=args,
)
raise RuntimeError("Dataset not available: {}".format(name))
| 37.336283
| 85
| 0.542546
| 448
| 4,219
| 4.821429
| 0.118304
| 0.075
| 0.125
| 0.175
| 0.85463
| 0.85463
| 0.850463
| 0.850463
| 0.850463
| 0.84213
| 0
| 0.017626
| 0.341076
| 4,219
| 112
| 86
| 37.669643
| 0.759353
| 0.043138
| 0
| 0.56
| 0
| 0
| 0.235557
| 0.057525
| 0
| 0
| 0
| 0
| 0
| 1
| 0.01
| false
| 0
| 0.02
| 0
| 0.09
| 0
| 0
| 0
| 0
| null | 0
| 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
| 7
|
3558e8c7b1d137353bc0e5cfc63e254b203ce446
| 2,303
|
py
|
Python
|
tests/unit/regressions/test_issue362.py
|
mazzi/tartiflette
|
54ffdcb97f3ef0ea8b87ea3378790221cdb08e0b
|
[
"MIT"
] | 530
|
2019-06-04T11:45:36.000Z
|
2022-03-31T09:29:56.000Z
|
tests/unit/regressions/test_issue362.py
|
mazzi/tartiflette
|
54ffdcb97f3ef0ea8b87ea3378790221cdb08e0b
|
[
"MIT"
] | 242
|
2019-06-04T11:53:08.000Z
|
2022-03-28T07:06:27.000Z
|
tests/unit/regressions/test_issue362.py
|
mazzi/tartiflette
|
54ffdcb97f3ef0ea8b87ea3378790221cdb08e0b
|
[
"MIT"
] | 36
|
2019-06-21T06:40:27.000Z
|
2021-11-04T13:11:16.000Z
|
import pytest
@pytest.mark.asyncio
async def test_create_engine_no_loader():
import json
from tartiflette import create_engine
e = await create_engine(
sdl="""type A{ B:String } type Query { a:A }""",
schema_name="test_issue362_test_create_engine_no_loader",
)
assert e._schema.json_loader == json.loads
@pytest.mark.asyncio
async def test_create_engine_loader():
def my_loader(*_args, **__kwargs):
pass
from tartiflette import create_engine
e = await create_engine(
sdl="""type A{ B:String } type Query { a:A }""",
schema_name="test_issue362_test_create_engine_loader",
json_loader=my_loader,
)
assert e._schema.json_loader == my_loader
@pytest.mark.asyncio
async def test_engine_init_no_loader():
import json
from tartiflette import Engine
e = Engine(
sdl="""type A{ B:String } type Query { a:A }""",
schema_name="test_issue362_test_engine_init_no_loader",
)
await e.cook()
assert e._schema.json_loader == json.loads
@pytest.mark.asyncio
async def test_engine_init_loader():
def my_loader(*_args, **__kwargs):
pass
from tartiflette import Engine
e = Engine(
sdl="""type A{ B:String } type Query { a:A }""",
schema_name="test_issue362_test_engine_init_loader",
json_loader=my_loader,
)
await e.cook()
assert e._schema.json_loader == my_loader
@pytest.mark.asyncio
async def test_engine_cook_loader():
def my_loader(*_args, **__kwargs):
pass
from tartiflette import Engine
e = Engine(
sdl="""type A{ B:String } type Query { a:A }""",
schema_name="test_issue362_test_engine_cook_loader",
)
await e.cook(json_loader=my_loader)
assert e._schema.json_loader == my_loader
@pytest.mark.asyncio
async def test_engine__init__cook_loader():
def my_loader(*_args, **__kwargs):
pass
def my_loader2(*_args, **__kwargs):
pass
from tartiflette import Engine
e = Engine(
sdl="""type A{ B:String } type Query { a:A }""",
schema_name="test_issue362_test_engine__init__cook_loader",
json_loader=my_loader,
)
await e.cook(json_loader=my_loader2)
assert e._schema.json_loader == my_loader2
| 22.578431
| 67
| 0.665219
| 314
| 2,303
| 4.515924
| 0.10828
| 0.077574
| 0.076164
| 0.088858
| 0.970381
| 0.960508
| 0.938646
| 0.893512
| 0.784908
| 0.762341
| 0
| 0.011831
| 0.229266
| 2,303
| 101
| 68
| 22.80198
| 0.787042
| 0
| 0
| 0.661765
| 0
| 0
| 0.200174
| 0.103778
| 0
| 0
| 0
| 0
| 0.088235
| 1
| 0.073529
| false
| 0.073529
| 0.132353
| 0
| 0.205882
| 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
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
35c9dbcef22e71b3db27e3c651718f057aef72c9
| 1,564
|
py
|
Python
|
09/test.py
|
AlecRosenbaum/adventofcode2017
|
9214a64db77492790d30bbd22e835535d05abb25
|
[
"MIT"
] | null | null | null |
09/test.py
|
AlecRosenbaum/adventofcode2017
|
9214a64db77492790d30bbd22e835535d05abb25
|
[
"MIT"
] | null | null | null |
09/test.py
|
AlecRosenbaum/adventofcode2017
|
9214a64db77492790d30bbd22e835535d05abb25
|
[
"MIT"
] | null | null | null |
import unittest
from solution import solution_part_one, solution_part_two
class TestPartOne(unittest.TestCase):
def test_one(self):
self.assertEqual(solution_part_one(r"{}"), 1)
def test_two(self):
self.assertEqual(solution_part_one(r"{{{}}}"), 6)
def test_three(self):
self.assertEqual(solution_part_one(r"{{},{}}"), 5)
def test_four(self):
self.assertEqual(solution_part_one(r"{{{},{},{{}}}}"), 16)
def test_five(self):
self.assertEqual(solution_part_one(r"{<a>,<a>,<a>,<a>}"), 1)
def test_six(self):
self.assertEqual(solution_part_one(r"{{<ab>},{<ab>},{<ab>},{<ab>}}"), 9)
def test_seven(self):
self.assertEqual(solution_part_one(r"{{<!!>},{<!!>},{<!!>},{<!!>}}"), 9)
def test_eight(self):
self.assertEqual(solution_part_one(r"{{<a!>},{<a!>},{<a!>},{<ab>}}"), 3)
class TestPartTwo(unittest.TestCase):
def test_one(self):
self.assertEqual(solution_part_two(r"{<>}"), 0)
def test_two(self):
self.assertEqual(solution_part_two(r"{<random characters>}"), 17)
def test_three(self):
self.assertEqual(solution_part_two(r"{<<<<>}"), 3)
def test_four(self):
self.assertEqual(solution_part_two(r"{<{!>}>}"), 2)
def test_five(self):
self.assertEqual(solution_part_two(r"{<!!>}"), 0)
def test_six(self):
self.assertEqual(solution_part_two(r"{<!!!>>}"), 0)
def test_seven(self):
self.assertEqual(solution_part_two(r'{<{o"i!a,<{i<a>}'), 10)
if __name__ == "__main__":
unittest.main()
| 35.545455
| 80
| 0.607417
| 208
| 1,564
| 4.293269
| 0.197115
| 0.228443
| 0.319149
| 0.453527
| 0.804031
| 0.804031
| 0.804031
| 0.759239
| 0.322508
| 0.322508
| 0
| 0.013889
| 0.171356
| 1,564
| 43
| 81
| 36.372093
| 0.675154
| 0
| 0
| 0.388889
| 0
| 0
| 0.13491
| 0.055627
| 0
| 0
| 0
| 0
| 0.416667
| 1
| 0.416667
| false
| 0
| 0.055556
| 0
| 0.527778
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 10
|
ea991fb8c67fcf4347356191018c4f80061e7b87
| 62,655
|
py
|
Python
|
infoblox_netmri/api/broker/v3_6_0/netscreen_address_broker.py
|
IngmarVG-IB/infoblox-netmri
|
b0c725fd64aee1890d83917d911b89236207e564
|
[
"Apache-2.0"
] | null | null | null |
infoblox_netmri/api/broker/v3_6_0/netscreen_address_broker.py
|
IngmarVG-IB/infoblox-netmri
|
b0c725fd64aee1890d83917d911b89236207e564
|
[
"Apache-2.0"
] | null | null | null |
infoblox_netmri/api/broker/v3_6_0/netscreen_address_broker.py
|
IngmarVG-IB/infoblox-netmri
|
b0c725fd64aee1890d83917d911b89236207e564
|
[
"Apache-2.0"
] | null | null | null |
from ..broker import Broker
class NetscreenAddressBroker(Broker):
controller = "netscreen_addresses"
def index(self, **kwargs):
"""Lists the available netscreen addresses. Any of the inputs listed may be be used to narrow the list; other inputs will be ignored. Of the various ways to query lists, using this method is most efficient.
**Inputs**
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param DeviceID: The internal NetMRI identifier of each device from which netscreen address table entry was found.
:type DeviceID: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param DeviceID: The internal NetMRI identifier of each device from which netscreen address table entry was found.
:type DeviceID: Array of Integer
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Array of Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param DeviceGroupID: The internal NetMRI identifier of the device groups to which to limit the results.
:type DeviceGroupID: Array of Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param timestamp: The data returned will represent the netscreen addresses as of this date and time. If omitted, the result will indicate the most recently collected data.
:type timestamp: DateTime
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param methods: A list of netscreen address methods. The listed methods will be called on each netscreen address returned and included in the output. Available methods are: device.
:type methods: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param include: A list of associated object types to include in the output. The listed associations will be returned as outputs named according to the association name (see outputs below). Available includes are: device.
:type include: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` 0
:param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information.
:type start: Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` 1000
:param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000.
:type limit: Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` NSAddressID
:param sort: The data field(s) to use for sorting the output. Default is NSAddressID. Valid values are NSAddressID, DeviceID, NSAddressStartTime, NSAddressEndTime, NSAddressTimeStamp, NSAddressChangedCols, NSAddressIndex, NSAddressName, NSAddressZone, NSAddressIpDotted, NSAddressIpNumeric, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, DataSourceID.
:type sort: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` asc
:param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'.
:type dir: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param select: The list of attributes to return for each NetscreenAddress. Valid values are NSAddressID, DeviceID, NSAddressStartTime, NSAddressEndTime, NSAddressTimeStamp, NSAddressChangedCols, NSAddressIndex, NSAddressName, NSAddressZone, NSAddressIpDotted, NSAddressIpNumeric, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, DataSourceID. If empty or omitted, all attributes will be returned.
:type select: Array
| ``api version min:`` 2.8
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param goto_field: The field name for NIOS GOTO that is used for locating a row position of records.
:type goto_field: String
| ``api version min:`` 2.8
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records.
:type goto_value: String
**Outputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:return netscreen_addresses: An array of the NetscreenAddress objects that match the specified input criteria.
:rtype netscreen_addresses: Array of NetscreenAddress
"""
return self.api_list_request(self._get_method_fullname("index"), kwargs)
def show(self, **kwargs):
"""Shows the details for the specified netscreen address.
**Inputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` True
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param methods: A list of netscreen address methods. The listed methods will be called on each netscreen address returned and included in the output. Available methods are: device.
:type methods: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param include: A list of associated object types to include in the output. The listed associations will be returned as outputs named according to the association name (see outputs below). Available includes are: device.
:type include: Array of String
**Outputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:return netscreen_address: The netscreen address identified by the specified NSAddressID.
:rtype netscreen_address: NetscreenAddress
"""
return self.api_request(self._get_method_fullname("show"), kwargs)
def search(self, **kwargs):
"""Lists the available netscreen addresses matching the input criteria. This method provides a more flexible search interface than the index method, but searching using this method is more demanding on the system and will not perform to the same level as the index method. The input fields listed below will be used as in the index method, to filter the result, along with the optional query string and XML filter described below.
**Inputs**
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param DataSourceID: The internal NetMRI identifier for the collector NetMRI that collected this data record.
:type DataSourceID: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param DataSourceID: The internal NetMRI identifier for the collector NetMRI that collected this data record.
:type DataSourceID: Array of Integer
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param DeviceID: The internal NetMRI identifier of each device from which netscreen address table entry was found.
:type DeviceID: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param DeviceID: The internal NetMRI identifier of each device from which netscreen address table entry was found.
:type DeviceID: Array of Integer
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressChangedCols: The fields that changed between this revision of the record and the previous revision.
:type NSAddressChangedCols: String
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressChangedCols: The fields that changed between this revision of the record and the previous revision.
:type NSAddressChangedCols: Array of String
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressDomainDotted: The management Domain IP address of the netscreen address is dotted(or colon delimited for IPv6) format.
:type NSAddressDomainDotted: String
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressDomainDotted: The management Domain IP address of the netscreen address is dotted(or colon delimited for IPv6) format.
:type NSAddressDomainDotted: Array of String
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressDomainNumeric: The numerical value of Domain IP address in the netscreen address.
:type NSAddressDomainNumeric: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressDomainNumeric: The numerical value of Domain IP address in the netscreen address.
:type NSAddressDomainNumeric: Array of Integer
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressEndTime: The ending effective time of this record, or empty if still in effect.
:type NSAddressEndTime: DateTime
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressEndTime: The ending effective time of this record, or empty if still in effect.
:type NSAddressEndTime: Array of DateTime
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Array of Integer
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressIndex: The current index value of the local interface for the netscreen address.
:type NSAddressIndex: String
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressIndex: The current index value of the local interface for the netscreen address.
:type NSAddressIndex: Array of String
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressIpDotted: The management IP address of the netscreen address is dotted(or colon delimited for IPv6) format.
:type NSAddressIpDotted: String
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressIpDotted: The management IP address of the netscreen address is dotted(or colon delimited for IPv6) format.
:type NSAddressIpDotted: Array of String
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressIpNumeric: The numerical value of the remote IP address in the netscreen address.
:type NSAddressIpNumeric: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressIpNumeric: The numerical value of the remote IP address in the netscreen address.
:type NSAddressIpNumeric: Array of Integer
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressName: The name of the netscreen address.
:type NSAddressName: String
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressName: The name of the netscreen address.
:type NSAddressName: Array of String
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressNetmaskDotted: The management netmask IP address of netscreen address is dotted (or colon delimited for IPv6) format.
:type NSAddressNetmaskDotted: String
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressNetmaskDotted: The management netmask IP address of netscreen address is dotted (or colon delimited for IPv6) format.
:type NSAddressNetmaskDotted: Array of String
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressNetmaskNumeric: The numerical value of netmask in the netscreen address.
:type NSAddressNetmaskNumeric: Integer
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressNetmaskNumeric: The numerical value of netmask in the netscreen address.
:type NSAddressNetmaskNumeric: Array of Integer
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressStartTime: The starting effective time of this record.
:type NSAddressStartTime: DateTime
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressStartTime: The starting effective time of this record.
:type NSAddressStartTime: Array of DateTime
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressTimeStamp: The date and time of netscreen address was calculated or collected.
:type NSAddressTimeStamp: DateTime
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressTimeStamp: The date and time of netscreen address was calculated or collected.
:type NSAddressTimeStamp: Array of DateTime
| ``api version min:`` 2.4
| ``api version max:`` 2.4
| ``required:`` False
| ``default:`` None
:param NSAddressZone: The zone of the netscreen address.
:type NSAddressZone: String
| ``api version min:`` 2.5
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param NSAddressZone: The zone of the netscreen address.
:type NSAddressZone: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param DeviceGroupID: The internal NetMRI identifier of the device groups to which to limit the results.
:type DeviceGroupID: Array of Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param timestamp: The data returned will represent the netscreen addresses as of this date and time. If omitted, the result will indicate the most recently collected data.
:type timestamp: DateTime
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param methods: A list of netscreen address methods. The listed methods will be called on each netscreen address returned and included in the output. Available methods are: device.
:type methods: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param include: A list of associated object types to include in the output. The listed associations will be returned as outputs named according to the association name (see outputs below). Available includes are: device.
:type include: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` 0
:param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information.
:type start: Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` 1000
:param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000.
:type limit: Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` NSAddressID
:param sort: The data field(s) to use for sorting the output. Default is NSAddressID. Valid values are NSAddressID, DeviceID, NSAddressStartTime, NSAddressEndTime, NSAddressTimeStamp, NSAddressChangedCols, NSAddressIndex, NSAddressName, NSAddressZone, NSAddressIpDotted, NSAddressIpNumeric, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, DataSourceID.
:type sort: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` asc
:param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'.
:type dir: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param select: The list of attributes to return for each NetscreenAddress. Valid values are NSAddressID, DeviceID, NSAddressStartTime, NSAddressEndTime, NSAddressTimeStamp, NSAddressChangedCols, NSAddressIndex, NSAddressName, NSAddressZone, NSAddressIpDotted, NSAddressIpNumeric, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, DataSourceID. If empty or omitted, all attributes will be returned.
:type select: Array
| ``api version min:`` 2.8
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param goto_field: The field name for NIOS GOTO that is used for locating a row position of records.
:type goto_field: String
| ``api version min:`` 2.8
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records.
:type goto_value: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param query: This value will be matched against netscreen addresses, looking to see if one or more of the listed attributes contain the passed value. You may also surround the value with '/' and '/' to perform a regular expression search rather than a containment operation. Any record that matches will be returned. The attributes searched are: DataSourceID, DeviceID, NSAddressChangedCols, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressEndTime, NSAddressID, NSAddressIndex, NSAddressIpDotted, NSAddressIpNumeric, NSAddressName, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, NSAddressStartTime, NSAddressTimeStamp, NSAddressZone.
:type query: String
| ``api version min:`` 2.3
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param xml_filter: A SetFilter XML structure to further refine the search. The SetFilter will be applied AFTER any search query or field values, but before any limit options. The limit and pagination will be enforced after the filter. Remind that this kind of filter may be costly and inefficient if not associated with a database filtering.
:type xml_filter: String
**Outputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:return netscreen_addresses: An array of the NetscreenAddress objects that match the specified input criteria.
:rtype netscreen_addresses: Array of NetscreenAddress
"""
return self.api_list_request(self._get_method_fullname("search"), kwargs)
def find(self, **kwargs):
"""Lists the available netscreen addresses matching the input specification. This provides the most flexible search specification of all the query mechanisms, enabling searching using comparison operations other than equality. However, it is more complex to use and will not perform as efficiently as the index or search methods. In the input descriptions below, 'field names' refers to the following fields: DataSourceID, DeviceID, NSAddressChangedCols, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressEndTime, NSAddressID, NSAddressIndex, NSAddressIpDotted, NSAddressIpNumeric, NSAddressName, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, NSAddressStartTime, NSAddressTimeStamp, NSAddressZone.
**Inputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_DataSourceID: The operator to apply to the field DataSourceID. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. DataSourceID: The internal NetMRI identifier for the collector NetMRI that collected this data record. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_DataSourceID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_DataSourceID: If op_DataSourceID is specified, the field named in this input will be compared to the value in DataSourceID using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_DataSourceID must be specified if op_DataSourceID is specified.
:type val_f_DataSourceID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_DataSourceID: If op_DataSourceID is specified, this value will be compared to the value in DataSourceID using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_DataSourceID must be specified if op_DataSourceID is specified.
:type val_c_DataSourceID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_DeviceID: The operator to apply to the field DeviceID. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. DeviceID: The internal NetMRI identifier of each device from which netscreen address table entry was found. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_DeviceID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_DeviceID: If op_DeviceID is specified, the field named in this input will be compared to the value in DeviceID using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_DeviceID must be specified if op_DeviceID is specified.
:type val_f_DeviceID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_DeviceID: If op_DeviceID is specified, this value will be compared to the value in DeviceID using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_DeviceID must be specified if op_DeviceID is specified.
:type val_c_DeviceID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressChangedCols: The operator to apply to the field NSAddressChangedCols. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressChangedCols: The fields that changed between this revision of the record and the previous revision. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressChangedCols: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressChangedCols: If op_NSAddressChangedCols is specified, the field named in this input will be compared to the value in NSAddressChangedCols using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressChangedCols must be specified if op_NSAddressChangedCols is specified.
:type val_f_NSAddressChangedCols: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressChangedCols: If op_NSAddressChangedCols is specified, this value will be compared to the value in NSAddressChangedCols using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressChangedCols must be specified if op_NSAddressChangedCols is specified.
:type val_c_NSAddressChangedCols: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressDomainDotted: The operator to apply to the field NSAddressDomainDotted. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressDomainDotted: The management Domain IP address of the netscreen address is dotted(or colon delimited for IPv6) format. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressDomainDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressDomainDotted: If op_NSAddressDomainDotted is specified, the field named in this input will be compared to the value in NSAddressDomainDotted using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressDomainDotted must be specified if op_NSAddressDomainDotted is specified.
:type val_f_NSAddressDomainDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressDomainDotted: If op_NSAddressDomainDotted is specified, this value will be compared to the value in NSAddressDomainDotted using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressDomainDotted must be specified if op_NSAddressDomainDotted is specified.
:type val_c_NSAddressDomainDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressDomainNumeric: The operator to apply to the field NSAddressDomainNumeric. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressDomainNumeric: The numerical value of Domain IP address in the netscreen address. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressDomainNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressDomainNumeric: If op_NSAddressDomainNumeric is specified, the field named in this input will be compared to the value in NSAddressDomainNumeric using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressDomainNumeric must be specified if op_NSAddressDomainNumeric is specified.
:type val_f_NSAddressDomainNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressDomainNumeric: If op_NSAddressDomainNumeric is specified, this value will be compared to the value in NSAddressDomainNumeric using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressDomainNumeric must be specified if op_NSAddressDomainNumeric is specified.
:type val_c_NSAddressDomainNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressEndTime: The operator to apply to the field NSAddressEndTime. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressEndTime: The ending effective time of this record, or empty if still in effect. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressEndTime: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressEndTime: If op_NSAddressEndTime is specified, the field named in this input will be compared to the value in NSAddressEndTime using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressEndTime must be specified if op_NSAddressEndTime is specified.
:type val_f_NSAddressEndTime: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressEndTime: If op_NSAddressEndTime is specified, this value will be compared to the value in NSAddressEndTime using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressEndTime must be specified if op_NSAddressEndTime is specified.
:type val_c_NSAddressEndTime: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressID: The operator to apply to the field NSAddressID. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressID: The internal NetMRI identifier of netscreen address. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressID: If op_NSAddressID is specified, the field named in this input will be compared to the value in NSAddressID using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressID must be specified if op_NSAddressID is specified.
:type val_f_NSAddressID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressID: If op_NSAddressID is specified, this value will be compared to the value in NSAddressID using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressID must be specified if op_NSAddressID is specified.
:type val_c_NSAddressID: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressIndex: The operator to apply to the field NSAddressIndex. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressIndex: The current index value of the local interface for the netscreen address. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressIndex: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressIndex: If op_NSAddressIndex is specified, the field named in this input will be compared to the value in NSAddressIndex using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressIndex must be specified if op_NSAddressIndex is specified.
:type val_f_NSAddressIndex: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressIndex: If op_NSAddressIndex is specified, this value will be compared to the value in NSAddressIndex using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressIndex must be specified if op_NSAddressIndex is specified.
:type val_c_NSAddressIndex: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressIpDotted: The operator to apply to the field NSAddressIpDotted. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressIpDotted: The management IP address of the netscreen address is dotted(or colon delimited for IPv6) format. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressIpDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressIpDotted: If op_NSAddressIpDotted is specified, the field named in this input will be compared to the value in NSAddressIpDotted using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressIpDotted must be specified if op_NSAddressIpDotted is specified.
:type val_f_NSAddressIpDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressIpDotted: If op_NSAddressIpDotted is specified, this value will be compared to the value in NSAddressIpDotted using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressIpDotted must be specified if op_NSAddressIpDotted is specified.
:type val_c_NSAddressIpDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressIpNumeric: The operator to apply to the field NSAddressIpNumeric. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressIpNumeric: The numerical value of the remote IP address in the netscreen address. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressIpNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressIpNumeric: If op_NSAddressIpNumeric is specified, the field named in this input will be compared to the value in NSAddressIpNumeric using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressIpNumeric must be specified if op_NSAddressIpNumeric is specified.
:type val_f_NSAddressIpNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressIpNumeric: If op_NSAddressIpNumeric is specified, this value will be compared to the value in NSAddressIpNumeric using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressIpNumeric must be specified if op_NSAddressIpNumeric is specified.
:type val_c_NSAddressIpNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressName: The operator to apply to the field NSAddressName. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressName: The name of the netscreen address. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressName: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressName: If op_NSAddressName is specified, the field named in this input will be compared to the value in NSAddressName using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressName must be specified if op_NSAddressName is specified.
:type val_f_NSAddressName: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressName: If op_NSAddressName is specified, this value will be compared to the value in NSAddressName using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressName must be specified if op_NSAddressName is specified.
:type val_c_NSAddressName: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressNetmaskDotted: The operator to apply to the field NSAddressNetmaskDotted. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressNetmaskDotted: The management netmask IP address of netscreen address is dotted (or colon delimited for IPv6) format. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressNetmaskDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressNetmaskDotted: If op_NSAddressNetmaskDotted is specified, the field named in this input will be compared to the value in NSAddressNetmaskDotted using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressNetmaskDotted must be specified if op_NSAddressNetmaskDotted is specified.
:type val_f_NSAddressNetmaskDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressNetmaskDotted: If op_NSAddressNetmaskDotted is specified, this value will be compared to the value in NSAddressNetmaskDotted using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressNetmaskDotted must be specified if op_NSAddressNetmaskDotted is specified.
:type val_c_NSAddressNetmaskDotted: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressNetmaskNumeric: The operator to apply to the field NSAddressNetmaskNumeric. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressNetmaskNumeric: The numerical value of netmask in the netscreen address. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressNetmaskNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressNetmaskNumeric: If op_NSAddressNetmaskNumeric is specified, the field named in this input will be compared to the value in NSAddressNetmaskNumeric using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressNetmaskNumeric must be specified if op_NSAddressNetmaskNumeric is specified.
:type val_f_NSAddressNetmaskNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressNetmaskNumeric: If op_NSAddressNetmaskNumeric is specified, this value will be compared to the value in NSAddressNetmaskNumeric using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressNetmaskNumeric must be specified if op_NSAddressNetmaskNumeric is specified.
:type val_c_NSAddressNetmaskNumeric: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressStartTime: The operator to apply to the field NSAddressStartTime. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressStartTime: The starting effective time of this record. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressStartTime: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressStartTime: If op_NSAddressStartTime is specified, the field named in this input will be compared to the value in NSAddressStartTime using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressStartTime must be specified if op_NSAddressStartTime is specified.
:type val_f_NSAddressStartTime: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressStartTime: If op_NSAddressStartTime is specified, this value will be compared to the value in NSAddressStartTime using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressStartTime must be specified if op_NSAddressStartTime is specified.
:type val_c_NSAddressStartTime: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressTimeStamp: The operator to apply to the field NSAddressTimeStamp. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressTimeStamp: The date and time of netscreen address was calculated or collected. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressTimeStamp: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressTimeStamp: If op_NSAddressTimeStamp is specified, the field named in this input will be compared to the value in NSAddressTimeStamp using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressTimeStamp must be specified if op_NSAddressTimeStamp is specified.
:type val_f_NSAddressTimeStamp: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressTimeStamp: If op_NSAddressTimeStamp is specified, this value will be compared to the value in NSAddressTimeStamp using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressTimeStamp must be specified if op_NSAddressTimeStamp is specified.
:type val_c_NSAddressTimeStamp: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param op_NSAddressZone: The operator to apply to the field NSAddressZone. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. NSAddressZone: The zone of the netscreen address. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values.
:type op_NSAddressZone: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_f_NSAddressZone: If op_NSAddressZone is specified, the field named in this input will be compared to the value in NSAddressZone using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_NSAddressZone must be specified if op_NSAddressZone is specified.
:type val_f_NSAddressZone: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param val_c_NSAddressZone: If op_NSAddressZone is specified, this value will be compared to the value in NSAddressZone using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_NSAddressZone must be specified if op_NSAddressZone is specified.
:type val_c_NSAddressZone: String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param DeviceGroupID: The internal NetMRI identifier of the device groups to which to limit the results.
:type DeviceGroupID: Array of Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param timestamp: The data returned will represent the netscreen addresses as of this date and time. If omitted, the result will indicate the most recently collected data.
:type timestamp: DateTime
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param methods: A list of netscreen address methods. The listed methods will be called on each netscreen address returned and included in the output. Available methods are: device.
:type methods: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param include: A list of associated object types to include in the output. The listed associations will be returned as outputs named according to the association name (see outputs below). Available includes are: device.
:type include: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` 0
:param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information.
:type start: Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` 1000
:param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000.
:type limit: Integer
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` NSAddressID
:param sort: The data field(s) to use for sorting the output. Default is NSAddressID. Valid values are NSAddressID, DeviceID, NSAddressStartTime, NSAddressEndTime, NSAddressTimeStamp, NSAddressChangedCols, NSAddressIndex, NSAddressName, NSAddressZone, NSAddressIpDotted, NSAddressIpNumeric, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, DataSourceID.
:type sort: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` asc
:param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'.
:type dir: Array of String
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param select: The list of attributes to return for each NetscreenAddress. Valid values are NSAddressID, DeviceID, NSAddressStartTime, NSAddressEndTime, NSAddressTimeStamp, NSAddressChangedCols, NSAddressIndex, NSAddressName, NSAddressZone, NSAddressIpDotted, NSAddressIpNumeric, NSAddressDomainDotted, NSAddressDomainNumeric, NSAddressNetmaskDotted, NSAddressNetmaskNumeric, DataSourceID. If empty or omitted, all attributes will be returned.
:type select: Array
| ``api version min:`` 2.8
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param goto_field: The field name for NIOS GOTO that is used for locating a row position of records.
:type goto_field: String
| ``api version min:`` 2.8
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records.
:type goto_value: String
| ``api version min:`` 2.3
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:param xml_filter: A SetFilter XML structure to further refine the search. The SetFilter will be applied AFTER any search query or field values, but before any limit options. The limit and pagination will be enforced after the filter. Remind that this kind of filter may be costly and inefficient if not associated with a database filtering.
:type xml_filter: String
**Outputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:return netscreen_addresses: An array of the NetscreenAddress objects that match the specified input criteria.
:rtype netscreen_addresses: Array of NetscreenAddress
"""
return self.api_list_request(self._get_method_fullname("find"), kwargs)
def data_source(self, **kwargs):
"""The collector NetMRI that collected this data record.
**Inputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` True
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Integer
**Outputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:return : The collector NetMRI that collected this data record.
:rtype : DataSource
"""
return self.api_request(self._get_method_fullname("data_source"), kwargs)
def device(self, **kwargs):
"""The device from which this data was collected.
**Inputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` True
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Integer
**Outputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:return : The device from which this data was collected.
:rtype : Device
"""
return self.api_request(self._get_method_fullname("device"), kwargs)
def infradevice(self, **kwargs):
"""The device from which this data was collected.
**Inputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` True
| ``default:`` None
:param NSAddressID: The internal NetMRI identifier of netscreen address.
:type NSAddressID: Integer
**Outputs**
| ``api version min:`` None
| ``api version max:`` None
| ``required:`` False
| ``default:`` None
:return : The device from which this data was collected.
:rtype : InfraDevice
"""
return self.api_request(self._get_method_fullname("infradevice"), kwargs)
| 53.688946
| 714
| 0.620828
| 7,272
| 62,655
| 5.301018
| 0.041804
| 0.069003
| 0.044852
| 0.072842
| 0.949156
| 0.948326
| 0.917404
| 0.903577
| 0.894783
| 0.894783
| 0
| 0.004465
| 0.299322
| 62,655
| 1,167
| 715
| 53.688946
| 0.873625
| 0.823318
| 0
| 0
| 0
| 0
| 0.055323
| 0
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| 0
| 0
| 0
| 0
| 1
| 0.411765
| false
| 0
| 0.058824
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 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
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 9
|
17eb4d6ee58cb376bcc80643b642802edcbab936
| 427
|
py
|
Python
|
lambda/leaderboard_exceptions.py
|
nvidian7/aws-cdk-leaderboard
|
852762cf3c724d3c5d9f1cff4f1989af62b6628d
|
[
"MIT"
] | null | null | null |
lambda/leaderboard_exceptions.py
|
nvidian7/aws-cdk-leaderboard
|
852762cf3c724d3c5d9f1cff4f1989af62b6628d
|
[
"MIT"
] | null | null | null |
lambda/leaderboard_exceptions.py
|
nvidian7/aws-cdk-leaderboard
|
852762cf3c724d3c5d9f1cff4f1989af62b6628d
|
[
"MIT"
] | null | null | null |
class UserNotFoundException(Exception):
def __init__(self, msg):
self.msg = msg
def __str__(self):
return self.msg
class InvalidRequestException(Exception):
def __init__(self, msg):
self.msg = msg
def __str__(self):
return self.msg
class AccessDeniedException(Exception):
def __init__(self, msg):
self.msg = msg
def __str__(self):
return self.msg
| 17.791667
| 41
| 0.637002
| 48
| 427
| 5.166667
| 0.229167
| 0.254032
| 0.193548
| 0.241935
| 0.717742
| 0.717742
| 0.717742
| 0.717742
| 0.717742
| 0.717742
| 0
| 0
| 0.271663
| 427
| 23
| 42
| 18.565217
| 0.797428
| 0
| 0
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0
| 0
| 0.2
| 0.8
| 0
| 0
| 0
| 0
| null | 1
| 1
| 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
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 12
|
a4bc8dff83cd34931d9527aabb66850910fae2e7
| 4,027
|
py
|
Python
|
maintain_frontend/add_land_charge/routes.py
|
LandRegistry/maintain-frontend
|
d92446a9972ebbcd9a43a7a7444a528aa2f30bf7
|
[
"MIT"
] | 1
|
2019-10-03T13:58:29.000Z
|
2019-10-03T13:58:29.000Z
|
maintain_frontend/add_land_charge/routes.py
|
LandRegistry/maintain-frontend
|
d92446a9972ebbcd9a43a7a7444a528aa2f30bf7
|
[
"MIT"
] | null | null | null |
maintain_frontend/add_land_charge/routes.py
|
LandRegistry/maintain-frontend
|
d92446a9972ebbcd9a43a7a7444a528aa2f30bf7
|
[
"MIT"
] | 1
|
2021-04-11T05:24:57.000Z
|
2021-04-11T05:24:57.000Z
|
from flask import Blueprint
import maintain_frontend.add_land_charge.add_land_charge
import maintain_frontend.add_land_charge.additional_info
import maintain_frontend.add_land_charge.charge_date
import maintain_frontend.add_land_charge.charge_description
import maintain_frontend.add_land_charge.charge_type
import maintain_frontend.add_land_charge.sub_category
import maintain_frontend.add_land_charge.confirm_law
import maintain_frontend.add_land_charge.confirm_legal_document
import maintain_frontend.add_land_charge.confirm_law_and_document
import maintain_frontend.add_land_charge.originating_authority
import maintain_frontend.add_land_charge.charge_subcategories.subcategory_not_known
import maintain_frontend.add_land_charge.confirmation
import maintain_frontend.add_land_charge.expiry
import maintain_frontend.add_land_charge.address_for_charge
import maintain_frontend.add_land_charge.address_confirmation
import maintain_frontend.add_land_charge.location
import maintain_frontend.add_land_charge.location_confirmation
import maintain_frontend.add_land_charge.financial_charge
import maintain_frontend.add_land_charge.financial_charge_details
import maintain_frontend.add_land_charge.land_compensation_type
import maintain_frontend.add_land_charge.land_compensation_payment
import maintain_frontend.add_land_charge.land_compensation_owned
import maintain_frontend.add_land_charge.land_compensation_land_sold
import maintain_frontend.add_land_charge.review
import maintain_frontend.add_land_charge.upload_shapefile
# Blueprint Definition
add_land_charge_bp = Blueprint('add_land_charge', __name__,
static_url_path='/static/add-local-land-charge',
static_folder='static',
template_folder='templates')
maintain_frontend.add_land_charge.add_land_charge.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.review.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.charge_type.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.sub_category.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.confirm_law.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.confirm_legal_document.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.confirm_law_and_document.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.originating_authority.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.charge_description.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.additional_info.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.address_for_charge.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.address_confirmation.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.confirmation.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.expiry.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.location.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.location_confirmation.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.charge_date.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.financial_charge.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.financial_charge_details.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.land_compensation_type.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.land_compensation_payment.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.land_compensation_owned.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.land_compensation_land_sold.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.charge_subcategories.subcategory_not_known.register_routes(add_land_charge_bp)
maintain_frontend.add_land_charge.upload_shapefile.register_routes(add_land_charge_bp)
| 66.016393
| 112
| 0.903899
| 574
| 4,027
| 5.764808
| 0.092334
| 0.241765
| 0.310366
| 0.347537
| 0.951043
| 0.951043
| 0.910245
| 0.720459
| 0.559686
| 0.525234
| 0
| 0
| 0.046188
| 4,027
| 60
| 113
| 67.116667
| 0.861494
| 0.004966
| 0
| 0
| 0
| 0
| 0.014732
| 0.007241
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.472727
| 0
| 0.472727
| 0.036364
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 8
|
a4fc8bdd6aa79f34108016a162c78cca32702b4e
| 181
|
py
|
Python
|
mindsdb/libs/data_sources/__init__.py
|
aykuttasil/mindsdb
|
2c36b6f75f13d7104fe4d3dbb7ca307fa84f45ad
|
[
"MIT"
] | 1
|
2022-03-14T00:32:53.000Z
|
2022-03-14T00:32:53.000Z
|
mindsdb/libs/data_sources/__init__.py
|
aykuttasil/mindsdb
|
2c36b6f75f13d7104fe4d3dbb7ca307fa84f45ad
|
[
"MIT"
] | null | null | null |
mindsdb/libs/data_sources/__init__.py
|
aykuttasil/mindsdb
|
2c36b6f75f13d7104fe4d3dbb7ca307fa84f45ad
|
[
"MIT"
] | null | null | null |
from mindsdb.libs.data_sources.array_to_cols_ds import ArrayToColsDS
from mindsdb.libs.data_sources.file_ds import FileDS
from mindsdb.libs.data_sources.window_ds import WindowDS
| 30.166667
| 68
| 0.872928
| 29
| 181
| 5.172414
| 0.517241
| 0.22
| 0.3
| 0.38
| 0.52
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.077348
| 181
| 5
| 69
| 36.2
| 0.898204
| 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
|
103847fc32d761395bcb44694bb566a2400d4af8
| 17,869
|
py
|
Python
|
laceworkreports/cli/ReportHandlers/AgentCoverageHandler/AgentCoverageHandler.py
|
laceworkps/laceworkreports
|
43f5189d2da39fc54ca24dc3c6c96d320bc9f8a5
|
[
"BSD-3-Clause"
] | null | null | null |
laceworkreports/cli/ReportHandlers/AgentCoverageHandler/AgentCoverageHandler.py
|
laceworkps/laceworkreports
|
43f5189d2da39fc54ca24dc3c6c96d320bc9f8a5
|
[
"BSD-3-Clause"
] | 44
|
2022-01-30T04:24:46.000Z
|
2022-03-31T02:31:17.000Z
|
laceworkreports/cli/ReportHandlers/AgentCoverageHandler/AgentCoverageHandler.py
|
laceworkps/laceworkreports
|
43f5189d2da39fc54ca24dc3c6c96d320bc9f8a5
|
[
"BSD-3-Clause"
] | null | null | null |
"""
Report Handler
"""
from typing import Optional
import logging
from datetime import datetime, timedelta
from pathlib import Path
import typer
from laceworkreports import common
from laceworkreports.sdk.DataHandlers import DataHandlerTypes, ExportHandler
from laceworkreports.sdk.ReportHelpers import AgentQueries, ReportHelper
app = typer.Typer(no_args_is_help=True)
@app.command(no_args_is_help=True, help="Generate HTML report")
def html(
ctx: typer.Context,
start_time: datetime = typer.Option(
(datetime.utcnow() - timedelta(hours=25)).strftime(common.ISO_FORMAT),
formats=[common.ISO_FORMAT],
help="Start time for query period",
),
end_time: datetime = typer.Option(
(datetime.utcnow()).strftime(common.ISO_FORMAT),
formats=[common.ISO_FORMAT],
help="End time for query period",
),
subaccounts: bool = typer.Option(
False,
help="Enumerate subaccounts",
envvar=common.LACEWORK_REPORTS_SUBACCOUNTS,
),
file_path: str = typer.Option(
...,
help="Path to exported result",
envvar=common.LACEWORK_REPORTS_FILE_PATH,
),
template_path: str = typer.Option(
Path(__file__).resolve().parent.joinpath("agent_coverage.html.j2"),
help="Path to jinja2 template. Results will be passed as 'dataset' variable.",
envvar=common.LACEWORK_REPORTS_TEMPLATE_PATH,
),
) -> None:
"""
Set the command context
"""
# connect the lacework client
lw = common.config.connect()
# report details
report_title = "Agent Coverage"
db_table = "discovered_machines"
reportHelper = ReportHelper()
db_path = Path("database.db")
# db_path.unlink(missing_ok=True)
db_connection = f"sqlite:///{db_path.absolute()}?check_same_thread=False"
reportHelper.sqlite_drop_table(db_table, db_connection)
reportHelper.sqlite_drop_table("machines", db_connection)
reportHelper.sqlite_drop_table("cloud_accounts", db_connection)
reportHelper.sqlite_drop_table("discovered_machines", db_connection)
reportHelper.sqlite_drop_table("discovered_cloud_accounts", db_connection)
has_subaccounts = False
if subaccounts:
lwAccounts = reportHelper.get_subaccounts(client=lw)
if len(lwAccounts) == 0:
logging.error("Subaccounts specificed but none found")
raise Exception("Subaccounts specificed but none found")
else:
has_subaccounts = True
else:
lwAccounts = [{"accountName": lw._account}]
lacework_account_count = 0
for lwAccount in lwAccounts:
lacework_account_count += 1
if has_subaccounts:
logging.info(f"Switching to subaccount context: {lwAccount['accountName']}")
lw.set_subaccount(lwAccount["accountName"])
# sync cloud accounts with deployed agents
logging.info("Syncing cloud accounts with deployed agents")
reportHelper.get_discovered_cloud_accounts(
client=lw,
lwAccount=lwAccount["accountName"],
start_time=start_time,
end_time=end_time,
use_sqlite=True,
db_table="discovered_cloud_accounts",
db_connection=db_connection,
)
try:
result = reportHelper.sqlite_queries(
queries={
"cloud_account_query": """
SELECT
DISTINCT ACCOUNTID
FROM
:db_table
WHERE
ACCOUNTID IS NOT NULL
"""
},
db_connection=db_connection,
db_table="discovered_cloud_accounts",
)
discovered_cloud_accounts = [
x["ACCOUNTID"] for x in result["cloud_account_query"]
]
except Exception:
discovered_cloud_accounts = []
# get cloud accounts and sync to sqlite
cloud_accounts = reportHelper.get_cloud_accounts(
client=lw, lwAccount=lwAccount["accountName"]
)
ExportHandler(
format=DataHandlerTypes.SQLITE,
results=[{"data": cloud_accounts}],
file_path=file_path,
db_table="cloud_accounts",
db_connection=db_connection,
).export()
logging.info(
f"Discovered {len(discovered_cloud_accounts)} cloud accounts with agents deployed: {discovered_cloud_accounts}"
)
for cloud_account in cloud_accounts:
if (
cloud_account["enabled"] == 1
and cloud_account["accountId"] in discovered_cloud_accounts
):
# sync machines for this cloud account
logging.info(
f"Syncing machines for {lwAccount['accountName']}:{cloud_account['accountId']}"
)
# sync all machines with agents
reportHelper.get_active_machines(
client=lw,
lwAccount=lwAccount["accountName"],
cloud_account=cloud_account["accountId"],
start_time=start_time,
end_time=end_time,
use_sqlite=True,
db_table="machines",
db_connection=db_connection,
)
# sync all discovered ec2 and gce instances
reportHelper.get_discovered_machines(
client=lw,
lwAccount=lwAccount["accountName"],
cloud_account=cloud_account["accountId"],
start_time=start_time,
end_time=end_time,
use_sqlite=True,
db_table="discovered_machines",
db_connection=db_connection,
)
# ensure we have a machines table
if not reportHelper.sqlite_table_exists(
db_table="machines", db_connection=db_connection
):
machines_table = """
CREATE TABLE machines (
"LWACCOUNT" TEXT,
"ACCOUNTID" TEXT,
"TAG_HOSTNAME" TEXT,
"TAG_INSTANCEID" TEXT,
"TAG_ACCOUNTID" TEXT,
"TAG_PROJECTID" TEXT,
"TAG_VMPROVIDER" TEXT,
"LWTOKENSHORT" TEXT
)
"""
reportHelper.sqlite_execute(
query=machines_table, db_connection=db_connection
)
# ensure we have a discovered_machines table
if not reportHelper.sqlite_table_exists(
db_table="discovered_machines", db_connection=db_connection
):
discovered_machines_table = """
CREATE TABLE discovered_machines (
"LWACCOUNT" TEXT,
"ACCOUNTID" TEXT,
"INSTANCEID" TEXT,
"NAME" TEXT,
"STATE" TEXT,
"TAGS" TEXT
)
"""
reportHelper.sqlite_execute(
query=discovered_machines_table, db_connection=db_connection
)
else:
logging.info(
f"Skipping disabled or inactive account {lwAccount['accountName']}:{cloud_account['accountId']}"
)
# use sqlite query to generate final result
results = reportHelper.sqlite_queries(
queries=AgentQueries, db_table=db_table, db_connection=db_connection
)
if len(results["report"]) > 0:
report = results["report"]
# return additional stats under summary
stats = {}
for key in [x for x in results.keys() if x != "report"]:
stats[key] = results[key]
# write jinja template
ExportHandler(
format=DataHandlerTypes.JINJA2,
results=[
{
"data": [
{
"name": db_table,
"report": report,
"summary": {
"rows": len(report),
"reportTitle": report_title,
"stats": stats,
},
}
]
}
],
template_path=template_path,
file_path=file_path,
).export()
else:
logging.warn("No results found")
@app.command(name="csv", no_args_is_help=True, help="Generate CSV Report")
def csv_handler(
ctx: typer.Context,
start_time: datetime = typer.Option(
(datetime.utcnow() - timedelta(hours=25)).strftime(common.ISO_FORMAT),
formats=[common.ISO_FORMAT],
help="Start time for query period",
),
end_time: datetime = typer.Option(
(datetime.utcnow()).strftime(common.ISO_FORMAT),
formats=[common.ISO_FORMAT],
help="End time for query period",
),
subaccounts: bool = typer.Option(
False,
help="Enumerate subaccounts",
envvar=common.LACEWORK_REPORTS_SUBACCOUNTS,
),
summary_only: bool = typer.Option(
False,
help="Return only summary details",
envvar=common.LACEWORK_REPORTS_SUBACCOUNTS,
),
file_path: str = typer.Option(
...,
help="Path to exported result",
envvar=common.LACEWORK_REPORTS_FILE_PATH,
),
) -> None:
"""
Set the command context
"""
# connect the lacework client
lw = common.config.connect()
# report details
# trunk-ignore(flake8/F841)
report_title = "Agent Coverage"
db_table = "discovered_machines"
reportHelper = ReportHelper()
db_path = Path("database.db")
# db_path.unlink(missing_ok=True)
db_connection = f"sqlite:///{db_path.absolute()}?check_same_thread=False"
reportHelper.sqlite_drop_table(db_table, db_connection)
reportHelper.sqlite_drop_table("machines", db_connection)
reportHelper.sqlite_drop_table("cloud_accounts", db_connection)
reportHelper.sqlite_drop_table("discovered_machines", db_connection)
reportHelper.sqlite_drop_table("discovered_cloud_accounts", db_connection)
has_subaccounts = False
if subaccounts:
lwAccounts = reportHelper.get_subaccounts(client=lw)
if len(lwAccounts) == 0:
logging.error("Subaccounts specificed but none found")
raise Exception("Subaccounts specificed but none found")
else:
has_subaccounts = True
else:
lwAccounts = [{"accountName": lw._account}]
lacework_account_count = 0
for lwAccount in lwAccounts:
lacework_account_count += 1
if has_subaccounts:
logging.info(f"Switching to subaccount context: {lwAccount['accountName']}")
lw.set_subaccount(lwAccount["accountName"])
# sync cloud accounts with deployed agents
logging.info("Syncing cloud accounts with deployed agents")
reportHelper.get_discovered_cloud_accounts(
client=lw,
lwAccount=lwAccount["accountName"],
start_time=start_time,
end_time=end_time,
use_sqlite=True,
db_table="discovered_cloud_accounts",
db_connection=db_connection,
)
try:
result = reportHelper.sqlite_queries(
queries={
"cloud_account_query": """
SELECT
DISTINCT ACCOUNTID
FROM
:db_table
WHERE
ACCOUNTID IS NOT NULL
"""
},
db_connection=db_connection,
db_table="discovered_cloud_accounts",
)
discovered_cloud_accounts = [
x["ACCOUNTID"] for x in result["cloud_account_query"]
]
except Exception:
discovered_cloud_accounts = []
# get cloud accounts and sync to sqlite
cloud_accounts = reportHelper.get_cloud_accounts(
client=lw, lwAccount=lwAccount["accountName"]
)
ExportHandler(
format=DataHandlerTypes.SQLITE,
results=[{"data": cloud_accounts}],
file_path=file_path,
db_table="cloud_accounts",
db_connection=db_connection,
).export()
logging.info(
f"Discovered {len(discovered_cloud_accounts)} cloud accounts with agents deployed: {discovered_cloud_accounts}"
)
for cloud_account in cloud_accounts:
if (
cloud_account["enabled"] == 1
and cloud_account["accountId"] in discovered_cloud_accounts
):
# sync machines for this cloud account
logging.info(
f"Syncing machines for {lwAccount['accountName']}:{cloud_account['accountId']}"
)
# sync all machines with agents
reportHelper.get_active_machines(
client=lw,
lwAccount=lwAccount["accountName"],
cloud_account=cloud_account["accountId"],
start_time=start_time,
end_time=end_time,
use_sqlite=True,
db_table="machines",
db_connection=db_connection,
)
# sync all discovered ec2 and gce instances
reportHelper.get_discovered_machines(
client=lw,
lwAccount=lwAccount["accountName"],
cloud_account=cloud_account["accountId"],
start_time=start_time,
end_time=end_time,
use_sqlite=True,
db_table="discovered_machines",
db_connection=db_connection,
)
# ensure we have a machines table
if not reportHelper.sqlite_table_exists(
db_table="machines", db_connection=db_connection
):
machines_table = """
CREATE TABLE machines (
"LWACCOUNT" TEXT,
"ACCOUNTID" TEXT,
"TAG_HOSTNAME" TEXT,
"TAG_INSTANCEID" TEXT,
"TAG_ACCOUNTID" TEXT,
"TAG_PROJECTID" TEXT,
"TAG_VMPROVIDER" TEXT,
"LWTOKENSHORT" TEXT
)
"""
reportHelper.sqlite_execute(
query=machines_table, db_connection=db_connection
)
# ensure we have a discovered_machines table
if not reportHelper.sqlite_table_exists(
db_table="discovered_machines", db_connection=db_connection
):
discovered_machines_table = """
CREATE TABLE discovered_machines (
"LWACCOUNT" TEXT,
"ACCOUNTID" TEXT,
"INSTANCEID" TEXT,
"NAME" TEXT,
"STATE" TEXT,
"TAGS" TEXT
)
"""
reportHelper.sqlite_execute(
query=discovered_machines_table, db_connection=db_connection
)
else:
logging.info(
f"Skipping disabled or inactive account {lwAccount['accountName']}:{cloud_account['accountId']}"
)
# use sqlite query to generate final result
results = reportHelper.sqlite_queries(
queries=AgentQueries, db_table=db_table, db_connection=db_connection
)
if len(results["report"]) > 0:
report = results["report"]
if summary_only:
report = results["account_coverage"]
logging.info("Building CSV from resultant data...")
ExportHandler(
format=DataHandlerTypes.CSV,
results=[{"data": report}],
file_path=file_path,
).export()
else:
logging.warn("No results found")
if __name__ == "__main__":
app()
| 37.938429
| 123
| 0.510381
| 1,498
| 17,869
| 5.845127
| 0.128171
| 0.071265
| 0.035176
| 0.05482
| 0.886478
| 0.88191
| 0.88191
| 0.875514
| 0.875514
| 0.875514
| 0
| 0.002197
| 0.414013
| 17,869
| 470
| 124
| 38.019149
| 0.834018
| 0.050814
| 0
| 0.803109
| 0
| 0
| 0.320078
| 0.039647
| 0
| 0
| 0
| 0
| 0
| 1
| 0.005181
| false
| 0.002591
| 0.020725
| 0
| 0.025907
| 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
|
107ce7f5d46c9e309291783145bb8e3a8ace998b
| 7,609
|
py
|
Python
|
findy/vendor/baostock/corpreport/corp_performance.py
|
doncat99/FinanceDataCenter
|
1538c8347ed5bff9a99a3cca07507a7605108124
|
[
"MIT"
] | null | null | null |
findy/vendor/baostock/corpreport/corp_performance.py
|
doncat99/FinanceDataCenter
|
1538c8347ed5bff9a99a3cca07507a7605108124
|
[
"MIT"
] | null | null | null |
findy/vendor/baostock/corpreport/corp_performance.py
|
doncat99/FinanceDataCenter
|
1538c8347ed5bff9a99a3cca07507a7605108124
|
[
"MIT"
] | null | null | null |
# -*- coding:utf-8 -*-
"""
大类：公司公告，小类：公司业绩报告
@author: baostock.com
@group : baostock.com
@contact: baostock@163.com
@copyright: baostock System & alpha.All Rights Reserved.
"""
import datetime
import time
import zlib
import findy.vendor.baostock.data.resultset as rs
import findy.vendor.baostock.common.contants as cons
import findy.vendor.baostock.util.stringutil as strUtil
import findy.vendor.baostock.common.context as conx
import findy.vendor.baostock.util.socketutil as sock
import findy.vendor.baostock.data.messageheader as msgheader
def query_performance_express_report(code, start_date=None, end_date=None):
"""公司业绩快报。
@param code: 证券代码，不可为空
@param start_date: 开始日期，默认2015-01-01；发布日期或更新日期在这个范围内。
@param end_date: 结束日期，默认系统当前日期；发布日期或更新日期在这个范围内。
"""
data = rs.ResultData()
if code is None or code == "":
print("股票代码不能为空，请检查。")
data.error_msg = "股票代码不能为空，请检查。"
data.error_code = cons.BSERR_PARAM_ERR
return data
if len(code) != cons.STOCK_CODE_LENGTH:
print("股票代码应为" + str(cons.STOCK_CODE_LENGTH) + "位，请检查。格式示例：sh.600000。")
data.error_msg = "股票代码应为" + str(cons.STOCK_CODE_LENGTH) + "位，请检查。格式示例：sh.600000。"
data.error_code = cons.BSERR_PARAM_ERR
return data
code = code.lower()
if (code.endswith("sh") or code.endswith("sz")):
code = code[7:9].lower() + "." + code[0:6]
if start_date is None or start_date == "":
start_date = cons.DEFAULT_START_DATE
if end_date is None or end_date == "":
end_date = time.strftime("%Y-%m-%d", time.localtime())
if start_date != "" and start_date is not None and end_date != "" and end_date is not None:
if strUtil.is_valid_date(start_date) and strUtil.is_valid_date(end_date):
start_date_time = datetime.datetime.strptime(
start_date, '%Y-%m-%d')
end_date_time = datetime.datetime.strptime(end_date, '%Y-%m-%d')
if end_date_time < start_date_time:
print("起始日期大于终止日期，请修改。")
data.error_code = cons.BSERR_START_BIGTHAN_END
data.error_msg = "起始日期大于终止日期，请修改。"
return data
else:
print("日期格式不正确，请修改。")
return
user_id = ""
try:
user_id = getattr(conx, "user_id")
except Exception:
print("you don't login.")
data.error_code = cons.BSERR_NO_LOGIN
data.error_msg = "you don't login."
return data
param = "%s,%s,%s,%s,%s,%s,%s" % (
"query_performance_express_report", user_id, "1",
cons.BAOSTOCK_PER_PAGE_COUNT, code, start_date, end_date)
msg_body = strUtil.organize_msg_body(param)
msg_header = msgheader.to_message_header(
cons.MESSAGE_TYPE_QUERYPERFORMANCEEXPRESSREPORT_REQUEST, len(msg_body))
data.msg_type = cons.MESSAGE_TYPE_QUERYPERFORMANCEEXPRESSREPORT_REQUEST
data.msg_body = msg_body
head_body = msg_header + msg_body
crc32str = zlib.crc32(bytes(head_body, encoding='utf-8'))
receive_data = sock.send_msg(head_body + cons.MESSAGE_SPLIT + str(crc32str))
if receive_data is None or receive_data.strip() == "":
data.error_code = cons.BSERR_RECVSOCK_FAIL
data.error_msg = "网络接收错误。"
return data
msg_header = receive_data[0:cons.MESSAGE_HEADER_LENGTH]
msg_body = receive_data[cons.MESSAGE_HEADER_LENGTH:-1]
header_arr = msg_header.split(cons.MESSAGE_SPLIT)
body_arr = msg_body.split(cons.MESSAGE_SPLIT)
data.msg_body_length = header_arr[2]
data.error_code = body_arr[0]
data.error_msg = body_arr[1]
if cons.BSERR_SUCCESS == data.error_code:
data.method = body_arr[2]
data.user_id = body_arr[3]
data.cur_page_num = body_arr[4]
data.per_page_count = body_arr[5]
data.setData(body_arr[6])
data.code = body_arr[7]
data.start_date = body_arr[8]
data.end_date = body_arr[9]
data.setFields(body_arr[10])
return data
def query_forecast_report(code, start_date=None, end_date=None):
"""公司业绩预告，
@param code: 证券代码，不可为空
@param start_date: 开始日期，默认2015-01-01；发布日期或统计日期在这个范围内。
@param end_date: 结束日期，默认系统当前日期；发布日期或统计日期在这个范围内。
"""
data = rs.ResultData()
if code is None or code == "":
print("股票代码不能为空，请检查。")
data.error_msg = "股票代码不能为空，请检查。"
data.error_code = cons.BSERR_PARAM_ERR
return data
if len(code) != cons.STOCK_CODE_LENGTH:
print("股票代码应为" + str(cons.STOCK_CODE_LENGTH) + "位，请检查。格式示例：sh.600000。")
data.error_msg = "股票代码应为" + str(cons.STOCK_CODE_LENGTH) + "位，请检查。格式示例：sh.600000。"
data.error_code = cons.BSERR_PARAM_ERR
return data
code = code.lower()
if (code.endswith("sh") or code.endswith("sz")):
code = code[7:9].lower() + "." + code[0:6]
if start_date is None or start_date == "":
start_date = cons.DEFAULT_START_DATE
if end_date is None or end_date == "":
end_date = time.strftime("%Y-%m-%d", time.localtime())
if start_date != "" and start_date is not None and end_date != "" and end_date is not None:
if strUtil.is_valid_date(start_date) and strUtil.is_valid_date(end_date):
start_date_time = datetime.datetime.strptime(
start_date, '%Y-%m-%d')
end_date_time = datetime.datetime.strptime(end_date, '%Y-%m-%d')
if end_date_time < start_date_time:
print("起始日期大于终止日期，请修改。")
data.error_code = cons.BSERR_START_BIGTHAN_END
data.error_msg = "起始日期大于终止日期，请修改。"
return data
else:
print("日期格式不正确，请修改。")
return
user_id = ""
try:
user_id = getattr(conx, "user_id")
except Exception:
print("you don't login.")
data.error_code = cons.BSERR_NO_LOGIN
data.error_msg = "you don't login."
return data
param = "%s,%s,%s,%s,%s,%s,%s" % (
"query_forecast_report", user_id, "1",
cons.BAOSTOCK_PER_PAGE_COUNT, code, start_date, end_date)
msg_body = strUtil.organize_msg_body(param)
msg_header = msgheader.to_message_header(
cons.MESSAGE_TYPE_QUERYFORECASTREPORT_REQUEST, len(msg_body))
data.msg_type = cons.MESSAGE_TYPE_QUERYFORECASTREPORT_REQUEST
data.msg_body = msg_body
head_body = msg_header + msg_body
crc32str = zlib.crc32(bytes(head_body, encoding='utf-8'))
receive_data = sock.send_msg(head_body + cons.MESSAGE_SPLIT + str(crc32str))
if receive_data is None or receive_data.strip() == "":
data.error_code = cons.BSERR_RECVSOCK_FAIL
data.error_msg = "网络接收错误。"
return data
msg_header = receive_data[0:cons.MESSAGE_HEADER_LENGTH]
msg_body = receive_data[cons.MESSAGE_HEADER_LENGTH:-1]
header_arr = msg_header.split(cons.MESSAGE_SPLIT)
body_arr = msg_body.split(cons.MESSAGE_SPLIT)
data.msg_body_length = header_arr[2]
data.error_code = body_arr[0]
data.error_msg = body_arr[1]
if cons.BSERR_SUCCESS == data.error_code:
data.method = body_arr[2]
data.user_id = body_arr[3]
data.cur_page_num = body_arr[4]
data.per_page_count = body_arr[5]
data.setData(body_arr[6])
data.code = body_arr[7]
data.start_date = body_arr[8]
data.end_date = body_arr[9]
data.setFields(body_arr[10])
return data
| 37.482759
| 96
| 0.635563
| 1,050
| 7,609
| 4.342857
| 0.148571
| 0.055263
| 0.039912
| 0.037281
| 0.913158
| 0.842544
| 0.842544
| 0.842544
| 0.827632
| 0.827632
| 0
| 0.017178
| 0.25023
| 7,609
| 202
| 97
| 37.668317
| 0.782121
| 0.056906
| 0
| 0.890323
| 0
| 0
| 0.072089
| 0.019792
| 0
| 0
| 0
| 0
| 0
| 1
| 0.012903
| false
| 0
| 0.058065
| 0
| 0.16129
| 0.064516
| 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
|
10b139555b20b8e79f2f634e4823673bb3dd94d1
| 3,277
|
py
|
Python
|
home/tests/test_views.py
|
broadsinatlanta/higashi-hiroshima-tours-
|
5ae44056d4cb577eab2e5a0525a330b3ac19e122
|
[
"MIT"
] | null | null | null |
home/tests/test_views.py
|
broadsinatlanta/higashi-hiroshima-tours-
|
5ae44056d4cb577eab2e5a0525a330b3ac19e122
|
[
"MIT"
] | 14
|
2020-02-12T00:00:09.000Z
|
2022-03-11T23:44:27.000Z
|
home/tests/test_views.py
|
broadsinatlanta/higashi-hiroshima-tours-
|
5ae44056d4cb577eab2e5a0525a330b3ac19e122
|
[
"MIT"
] | null | null | null |
from django.test import TestCase, Client
from django.urls import reverse
class HomeViewsTestCase(TestCase):
def english_setting(self):
return self.settings(LANGUAGE_CODE='en')
def setUp(self):
client = Client()
def test_home_view_is_served(self):
response = self.client.get(reverse('home'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/home.html')
# Right text (Japanese)
self.assertContains(response, 'ようこそ')
def test_about_view_is_served(self):
response = self.client.get(reverse('about'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/about.html')
# Right text (Japanese)
self.assertContains(response, '東広島探訪講座')
def test_guide_view_is_served(self):
response = self.client.get(reverse('guide'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/guide.html')
# Right text (Japanese)
self.assertContains(response, 'ガイド派遣')
def test_saijo_view_is_served(self):
response = self.client.get(reverse('saijo'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/saijo.html')
# Right text (Japanese)
self.assertContains(response, '西条の観光')
def test_home_view_translation_works(self):
with self.english_setting():
response = self.client.get(reverse('home'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/home.html')
# Right text
self.assertContains(response, 'Higashi Hiroshima')
def test_about_view_translation_works(self):
with self.english_setting():
response = self.client.get(reverse('about'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/about.html')
# Right text
self.assertContains(response, 'Exploration Course')
def test_guide_view_translation_works(self):
with self.english_setting():
response = self.client.get(reverse('guide'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/guide.html')
# Right text
self.assertContains(response, 'Dispatch')
def test_saijo_view_translation_works(self):
with self.english_setting():
response = self.client.get(reverse('saijo'))
# Successful check
self.assertEqual(response.status_code, 200)
# Template check
self.assertTemplateUsed(response, 'home/saijo.html')
# Right text
self.assertContains(response, 'Sightseeing')
| 27.082645
| 64
| 0.627708
| 331
| 3,277
| 6.075529
| 0.163142
| 0.071606
| 0.071606
| 0.083541
| 0.833416
| 0.833416
| 0.781701
| 0.714073
| 0.714073
| 0.682248
| 0
| 0.01011
| 0.275557
| 3,277
| 120
| 65
| 27.308333
| 0.836984
| 0.118096
| 0
| 0.54902
| 0
| 0
| 0.081326
| 0
| 0
| 0
| 0
| 0
| 0.470588
| 1
| 0.196078
| false
| 0
| 0.039216
| 0.019608
| 0.27451
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
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