hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b2890df0b4917dd1bd48ce6f127b51ff8e374378
| 9,679
|
py
|
Python
|
levels.py
|
el-jeu/game
|
b19b7384d9b84daaa25509fb7989352a5f5a7fcb
|
[
"Unlicense"
] | null | null | null |
levels.py
|
el-jeu/game
|
b19b7384d9b84daaa25509fb7989352a5f5a7fcb
|
[
"Unlicense"
] | null | null | null |
levels.py
|
el-jeu/game
|
b19b7384d9b84daaa25509fb7989352a5f5a7fcb
|
[
"Unlicense"
] | null | null | null |
"""element : [type -b, -p, -m, -e (1 letter)]
[id [number for players and enemies (1)], [type for the different enemies (1)] (2)]
[path]"""
levelsMap = [
#level 1-1
("g1","f1",
[["m00a1","m00a3","m00a5","b00b1","m00m1","e00e1","m00m1","b00b1","m00a1","m00a3","m00a5"],
["m00a2", "m00a4","m00a6","b00b1","b00b1","b00b1","b00b1","b00b1","m00a2","m00a4","m00a6"],
["b00b1", "b00b1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","b00b1","b00b1"],
["m00m1", "b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","m00m1"],
["b00b1", "b00b1","m00m1","b00b1","m00a1","m00a3","m00a5","b00b1","m00m1","b00b1","b00b1"],
["b00b1", "b00b1","m00m1","b00b1","m00a2","m00a4","m00a6","p00p1","m00m1","b00b1","b00b1"],
["m00m1", "b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","m00m1"],
["b00b1", "b00b1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","b00b1","b00b1"],
["m00a1", "m00a3","m00a5","b00b1","b00b1","b00b1","b00b1","b00b1","m00a1","m00a3","m00a5"],
["m00a2", "m00a4","m00a6","b00b1","m00m1","e10e1","m00m1","b00b1","m00a2","m00a4","m00a6"]]),
#level 1-2
("g1","f1",
[["e00e1","b00b1","b00b1","b00b1","m00m1","b00b1","m00m1","b00b1","b00b1","b00b1","b00b1"],
["b00b1", "m00m1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","m00m1","b00b1"],
["b00b1", "m00m1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","m00m1","b00b1"],
["b00b1", "b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1"],
["m00m1", "m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","m00m1"],
["m00m1", "m00m1","b00b1","m00m1","b00b1","m00m1","p00p1","m00m1","b00b1","m00m1","m00m1"],
["b00b1", "b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1"],
["b00b1", "m00m1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","m00m1","b00b1"],
["b00b1", "m00m1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","m00m1","b00b1"],
["b00b1", "b00b1","b00b1","b00b1","m00m1","b00b1","m00m1","b00b1","b00b1","b00b1","e10e1"]]),
#level 1-3
("g1","f1",
[["b00b1","b00b1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00m1","b00b1"],
["b00b1", "m00m1","e00e1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","m00m1","b00b1"],
["b00b1", "m00m1","b00b1","m00m1","b00b1","m00m1","b00b1","m00a1","m00a3","m00a5","b00b1"],
["b00b1", "m00a1","m00a3","m00a5","b00b1","b00b1","b00b1","m00a2","m00a4","m00a6","b00b1"],
["b00b1", "m00a2","m00a4","m00a6","b00b1","m00m1","p00p1","b00b1","b00b1","b00b1","b00b1"],
["b00b1", "b00b1","b00b1","b00b1","b00b1","b00b1","m00m1","b00b1","m00m1","m00m1","b00b1"],
["b00b1", "m00m1","e10e1","m00m1","b00b1","m00m1","b00b1","b00b1","b00b1","e20e1","m00m1"],
["b00b1", "b00b1","m00m1","b00b1","m00m1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1"],
["b00b1", "m00m1","m00m1","b00b1","m00m1","b00b1","m00a1","m00a3","m00a5","b00b1","b00b1"],
["b00b1", "m00m1","m00m1","b00b1","m00m1","b00b1","m00a2","m00a4","m00a6","b00b1","m00m1"],
["b00b1", "b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1","b00b1"]]),
#level 2-1
("g1","f2",
[["e01e1","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","e11e1"],
["b00b2", "b00b2","b00b2","b00b2","m00m2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2"],
["m00t1", "m00t3","m00t5","b00b2","b00b2","b00b2","m00m2","b00b2","m00t1","m00t3","m00t5"],
["m00t2", "m00t4","m00t6","b00b2","b00b2","b00b2","b00b2","b00b2","m00t2","m00t4","m00t6"],
["b00b2", "m00m2","b00b2","b00b2","m00t1","m00t3","m00t5","b00b2","b00b2","m00m2","m00m2"],
["b00b2", "b00b2","b00b2","b00b2","m00t2","m00t4","m00t6","b00b2","b00b2","b00b2","b00b2"],
["m00t1", "m00t3","m00t5","b00b2","b00b2","m00m2","b00b2","b00b2","m00t1","m00t3","m00t5"],
["m00t2", "m00t4","m00t6","b00b2","b00b2","b00b2","b00b2","b00b2","m00t2","m00t4","m00t6"],
["b00b2", "b00b2","m00m2","b00b2","b00b2","b00b2","b00b2","m00m2","b00b2","b00b2","b00b2"],
["e21e1", "b00b2","b00b2","b00b2","b00b2","p00p2","b00b2","b00b2","b00b2","b00b2","e31e1"]]),
#level 2-2
("g1","f2",
[["e01e1","m00m2","m00m2","b00b2","m00m2","p00p2","m00m2","b00b2","m00m2","m00m2","b00b2"],
["b00b2", "b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2"],
["m00m2", "m00m2","b00b2","m00m2","m00m2","b00b2","m00m2","m00m2","e11e1","m00m2","m00m2"],
["b00b2", "b00b2","b00b2","b00b2","b00b2","m00m2","b00b2","b00b2","b00b2","b00b2","b00b2"],
["b00b2", "m00m2","m00m2","b00b2","m00m2","m00m2","b00b2","m00m2","m00m2","b00b2","m00m2"],
["e21e1", "m00m2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2","b00b2"],
["m00m2", "b00b2","m00m2","m00m2","b00b2","m00m2","m00m2","b00b2","m00m2","m00m2","b00b2"],
["b00b2", "b00b2","b00b2","b00b2","b00b2","b00b2","m00m2","b00b2","b00b2","m00m2","b00b2"],
["m00m2", "m00m2","b00b2","m00m2","m00m2","b00b2","m00m2","m00m2","b00b2","m00m2","m00m2"],
["e31e1", "b00b2","b00b2","m00m2","b00b2","b00b2","e41e1","m00m2","b00b2","b00b2","e51e1"]]),
#level 2-3
("g1","f2",
[["b00b2","b00b2","b00b2","b00b2","m00t1","m00t3","m00t5","b00b2","b00b2","b00b2","b00b2"],
["b00b2", "e01e1","b00b2","b00b2","m00t2","m00t4","m00t6","b00b2","b00b2","e11e1","b00b2"],
["b00b2", "b00b2","b00b2","b00b2","m00t1","m00t3","m00t5","b00b2","b00b2","b00b2","b00b2"],
["b00b2", "b00b2","b00b2","b00b2","m00t2","m00t4","m00t6","b00b2","b00b2","b00b2","b00b2"],
["m00t1", "m00t3","m00t5","b00b2","b00b2","b00b2","b00b2","b00b2","m00t1","m00t3","m00t5"],
["m00t2", "m00t4","m00t6","b00b2","b00b2","p00p2","b00b2","b00b2","m00t2","m00t4","m00t6"],
["b00b2", "b00b2","b00b2","b00b2","m00t1","m00t3","m00t5","b00b2","b00b2","b00b2","b00b2"],
["b00b2", "b00b2","b00b2","b00b2","m00t2","m00t4","m00t6","b00b2","b00b2","b00b2","b00b2"],
["b00b2", "e21e1","b00b2","b00b2","m00t1","m00t3","m00t5","b00b2","b00b2","e31e1","b00b2"],
["b00b2", "b00b2","b00b2","b00b2","m00t2","m00t4","m00t6","b00b2","b00b2","b00b2","b00b2"]]),
#level 3-1
("g1","f3",
[["v", "v", "v", "v", "m00m3","m00m3","m00m3","v", "v", "v", "v"],
["v", "v", "m00m3","m00m3","e02e1","m00m5","b00b3","m00m3","m00m3","v", "v"],
["v", "m00m3","b00b3","m00m5","b00b3","b00b3","b00b3","b00b3","b00b3","m00m3","v"],
["v", "m00m3","b00b3","b00b3","b00b3","m00m5","b00b3","m00m5","b00b3","m00m3","v"],
["m00m3","m00m5","b00b3","m00m5","b00b3","p00p3","b00b3","m00m5","b00b3","b00b3","m00m3"],
["m00m3","b00b3","b00b3","m00m5","b00b3","m00m5","b00b3","m00m5","m00m5","e12e1","m00m3"],
["v", "m00m3","m00m5","b00b3","m00m5","b00b3","b00b3","b00b3","b00b3","m00m3","v"],
["v", "m00m3","e22e1","b00b3","b00b3","m00m5","b00b3","m00m5","b00b3","m00m3","v"],
["v", "v", "m00m3","m00m3","b00b3","b00b3","b00b3","m00m3","m00m3","v", "v"],
["v", "v", "v", "v", "m00m3","m00m3","m00m3","v", "v", "v", "v"]]),
#level 3-2
("g1","f3",
[["v", "v", "v", "v", "m00m3","m00m3","m00m3","v", "v", "v", "v"],
["v", "v", "m00m3","m00m3","b00b3","e02e1","b00b3","m00m3","m00m3","v", "v"],
["v", "m00m3","b00b3","b00b3","b00b3","m00m5","b00b3","b00b3","b00b3","m00m3","v"],
["v", "m00m3","b00b3","m00m5","m00m5","m00m5","m00m5","m00m5","b00b3","m00m3","v"],
["m00m3","e12e1","b00b3","b00b3","m00m5","p00p3","b00b3","b00b3","b00b3","e22e1","m00m3"],
["m00m3","e32e1","b00b3","b00b3","b00b3","b00b3","m00m5","b00b3","b00b3","e42e1","m00m3"],
["v", "m00m3","b00b3","m00m5","m00m5","m00m5","m00m5","m00m5","b00b3","m00m3","v"],
["v", "m00m3","b00b3","b00b3","b00b3","m00m5","b00b3","b00b3","b00b3","m00m3","v"],
["v", "v", "m00m3","m00m3","b00b3","e52e1","b00b3","m00m3","m00m3","v", "v"],
["v", "v", "v", "v", "m00m3","m00m3","m00m3","v", "v", "v", "v"]]),
#level 3-3
("g1","f3",
[["v", "v", "v", "v", "m00m3","m00m3","m00m3","v", "v", "v", "v"],
["v", "v", "m00m3","m00m3","m00m5","e02e1","b00b3","m00m3","m00m3","v", "v"],
["v", "m00m3","e12e1","b00b3","b00b3","m00m5","b00b3","b00b3","e22e1","m00m3","v"],
["v", "m00m3","m00m5","m00m5","b00b3","m00m5","b00b3","m00m5","m00m5","m00m3","v"],
["m00m3","m00m5","b00b3","b00b3","b00b3","p00p3","b00b3","m00m5","b00b3","e32e1","m00m3"],
["m00m3","e42e1","b00b3","m00m5","b00b3","b00b3","b00b3","b00b3","b00b3","m00m5","m00m3"],
["v", "m00m3","m00m5","m00m5","b00b3","m00m5","b00b3","m00m5","m00m5","m00m3","v"],
["v", "m00m3","e52e1","b00b3","b00b3","m00m5","b00b3","b00b3","e62e1","m00m3","v"],
["v", "v", "m00m3","m00m3","b00b3","e72e1","m00m5","m00m3","m00m3","v", "v"],
["v", "v", "v", "v", "m00m3","m00m3","m00m3","v", "v", "v", "v"]])]
| 73.885496
| 102
| 0.497159
| 1,070
| 9,679
| 4.497196
| 0.060748
| 0.286783
| 0.296135
| 0.27847
| 0.902535
| 0.850582
| 0.788238
| 0.736492
| 0.615129
| 0.573566
| 0
| 0.338452
| 0.159004
| 9,679
| 130
| 103
| 74.453846
| 0.252703
| 0.022523
| 0
| 0.366337
| 0
| 0
| 0.501562
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
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| 0
| 1
| 0
| 0
| 0
| 0
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| 1
| 0
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| null | 0
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|
0
| 9
|
a22c1b4f13d5b59ec387f07ce71ca94f5b815b15
| 19,514
|
py
|
Python
|
xls/tools/eval_proc_main_test.py
|
netskink/xls
|
78d38c626a360cb835e1c59639a36c67f077769d
|
[
"Apache-2.0"
] | null | null | null |
xls/tools/eval_proc_main_test.py
|
netskink/xls
|
78d38c626a360cb835e1c59639a36c67f077769d
|
[
"Apache-2.0"
] | null | null | null |
xls/tools/eval_proc_main_test.py
|
netskink/xls
|
78d38c626a360cb835e1c59639a36c67f077769d
|
[
"Apache-2.0"
] | null | null | null |
# Lint as: python3
#
# Copyright 2020 The XLS Authors
#
# 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 subprocess
from absl import logging
from xls.common import runfiles
from absl.testing import absltest
EVAL_PROC_MAIN_PATH = runfiles.get_path("xls/tools/eval_proc_main")
PROC_IR = """package foo
chan in_ch(bits[64], id=1, kind=streaming, ops=receive_only, flow_control=ready_valid, metadata=\"\"\"\"\"\")
chan in_ch_2(bits[64], id=2, kind=streaming, ops=receive_only, flow_control=ready_valid, metadata=\"\"\"\"\"\")
chan out_ch(bits[64], id=3, kind=streaming, ops=send_only, flow_control=ready_valid, metadata=\"\"\"\"\"\")
chan out_ch_2(bits[64], id=4, kind=streaming, ops=send_only, flow_control=ready_valid, metadata=\"\"\"\"\"\")
proc test_proc(tkn: token, st: (bits[64]), init=(10)) {
receive.1: (token, bits[64]) = receive(tkn, channel_id=1, id=1)
literal.21: bits[64] = literal(value=10, id=21)
tuple_index.23: bits[64] = tuple_index(st, index=0, id=23)
literal.3: bits[1] = literal(value=1, id=3)
tuple_index.7: token = tuple_index(receive.1, index=0, id=7)
tuple_index.4: bits[64] = tuple_index(receive.1, index=1, id=4)
receive.9: (token, bits[64]) = receive(tuple_index.7, channel_id=2, id=9)
tuple_index.10: bits[64] = tuple_index(receive.9, index=1, id=10)
add.8: bits[64] = add(tuple_index.4, tuple_index.10, id=8)
add.24: bits[64] = add(add.8, tuple_index.23, id=24)
tuple_index.11: token = tuple_index(receive.9, index=0, id=11)
send.2: token = send(tuple_index.11, add.24, predicate=literal.3, channel_id=3, id=2)
literal.14: bits[64] = literal(value=55, id=14)
send.12: token = send(send.2, literal.14, predicate=literal.3, channel_id=4, id=12)
add.20: bits[64] = add(literal.21, tuple_index.23, id=20)
tuple.22: (bits[64]) = tuple(add.20, id=22)
next(send.12, tuple.22)
}
"""
BLOCK_IR = """package foo
block test_block(clk: clock, in_ch_data: bits[64], in_ch_2_data: bits[64], out_ch_data: bits[64], out_ch_2_data: bits[64], rst_n: bits[1], in_ch_vld: bits[1], in_ch_2_vld: bits[1], out_ch_vld: bits[1], out_ch_2_vld: bits[1], out_ch_rdy: bits[1], out_ch_2_rdy: bits[1], in_ch_rdy: bits[1], in_ch_2_rdy: bits[1]) {
reg p0_add_49(bits[64])
reg p1_add_49(bits[64])
reg p2_add_49(bits[64])
reg p3_add_49(bits[64])
reg p0_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg p1_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg p2_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg p3_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg st((bits[64]), reset_value=(10), asynchronous=false, active_low=true)
in_ch_data: bits[64] = input_port(name=in_ch_data, id=38)
in_ch_2_data: bits[64] = input_port(name=in_ch_2_data, id=41)
rst_n: bits[1] = input_port(name=rst_n, id=74)
in_ch_vld: bits[1] = input_port(name=in_ch_vld, id=75)
in_ch_2_vld: bits[1] = input_port(name=in_ch_2_vld, id=76)
out_ch_rdy: bits[1] = input_port(name=out_ch_rdy, id=92)
out_ch_2_rdy: bits[1] = input_port(name=out_ch_2_rdy, id=95)
literal.50: bits[64] = literal(value=10, id=50)
st__1: (bits[64]) = register_read(register=st, id=87)
add.46: bits[64] = add(in_ch_data, in_ch_2_data, id=46)
tuple_index.47: bits[64] = tuple_index(st__1, index=0, id=47)
add.51: bits[64] = add(literal.50, tuple_index.47, id=51)
tuple.52: (bits[64]) = tuple(add.51, id=52)
add.49: bits[64] = add(add.46, tuple_index.47, id=49)
not.127: bits[1] = not(rst_n, id=127)
p0_add_49: bits[64] = register_read(register=p0_add_49, id=55)
not.119: bits[1] = not(rst_n, id=119)
p1_add_49: bits[64] = register_read(register=p1_add_49, id=59)
not.111: bits[1] = not(rst_n, id=111)
p2_add_49: bits[64] = register_read(register=p2_add_49, id=63)
and.77: bits[1] = and(in_ch_vld, in_ch_2_vld, id=77)
not.103: bits[1] = not(rst_n, id=103)
p3_add_49: bits[64] = register_read(register=p3_add_49, id=67)
register_read.79: bits[1] = register_read(register=p0_valid, id=79)
register_read.81: bits[1] = register_read(register=p1_valid, id=81)
register_read.83: bits[1] = register_read(register=p2_valid, id=83)
register_read.85: bits[1] = register_read(register=p3_valid, id=85)
literal.70: bits[1] = literal(value=1, id=70)
literal.72: bits[64] = literal(value=55, id=72)
and.88: bits[1] = and(literal.70, register_read.85, id=88)
and.90: bits[1] = and(literal.70, register_read.85, id=90)
not.93: bits[1] = not(literal.70, id=93)
or.94: bits[1] = or(not.93, out_ch_rdy, id=94)
not.96: bits[1] = not(literal.70, id=96)
or.97: bits[1] = or(not.96, out_ch_2_rdy, id=97)
and.98: bits[1] = and(or.94, or.97, id=98)
p3_not_valid: bits[1] = not(register_read.85, id=99)
p3_enable: bits[1] = or(and.98, p3_not_valid, id=100)
p3_data_enable: bits[1] = and(p3_enable, register_read.83, id=102)
p3_load_en: bits[1] = or(p3_data_enable, not.103, id=104)
register_write.101: () = register_write(register_read.83, register=p3_valid, load_enable=p3_enable, reset=rst_n, id=101)
register_write.105: () = register_write(p2_add_49, register=p3_add_49, load_enable=p3_load_en, id=105)
p2_not_valid: bits[1] = not(register_read.83, id=107)
p2_enable: bits[1] = or(p3_enable, p2_not_valid, id=108)
p2_data_enable: bits[1] = and(p2_enable, register_read.81, id=110)
p2_load_en: bits[1] = or(p2_data_enable, not.111, id=112)
register_write.113: () = register_write(p1_add_49, register=p2_add_49, load_enable=p2_load_en, id=113)
register_write.109: () = register_write(register_read.81, register=p2_valid, load_enable=p2_enable, reset=rst_n, id=109)
p1_not_valid: bits[1] = not(register_read.81, id=115)
p1_enable: bits[1] = or(p2_enable, p1_not_valid, id=116)
p1_data_enable: bits[1] = and(p1_enable, register_read.79, id=118)
p1_load_en: bits[1] = or(p1_data_enable, not.119, id=120)
register_write.121: () = register_write(p0_add_49, register=p1_add_49, load_enable=p1_load_en, id=121)
register_write.117: () = register_write(register_read.79, register=p1_valid, load_enable=p1_enable, reset=rst_n, id=117)
p0_not_valid: bits[1] = not(register_read.79, id=123)
p0_enable: bits[1] = or(p1_enable, p0_not_valid, id=124)
next_state_enable: bits[1] = and(p0_enable, and.77, id=132)
register_write.133: () = register_write(tuple.52, register=st, load_enable=next_state_enable, reset=rst_n, id=133)
p0_data_enable: bits[1] = and(p0_enable, and.77, id=126)
p0_load_en: bits[1] = or(p0_data_enable, not.127, id=128)
register_write.129: () = register_write(add.49, register=p0_add_49, load_enable=p0_load_en, id=129)
register_write.125: () = register_write(and.77, register=p0_valid, load_enable=p0_enable, reset=rst_n, id=125)
out_ch_data: () = output_port(p3_add_49, name=out_ch_data, id=71)
out_ch_2_data: () = output_port(literal.72, name=out_ch_2_data, id=73)
out_ch_vld: () = output_port(and.88, name=out_ch_vld, id=89)
out_ch_2_vld: () = output_port(and.90, name=out_ch_2_vld, id=91)
in_ch_rdy: () = output_port(p0_enable, name=in_ch_rdy, id=134)
in_ch_2_rdy: () = output_port(p0_enable, name=in_ch_2_rdy, id=135)
}
"""
BLOCK_IR_BROKEN = """package foo
block test_block(clk: clock, in_ch_data: bits[64], in_ch_2_data: bits[64], out_ch_data: bits[64], out_ch_2_data: bits[64], rst_n: bits[1], in_ch_vld: bits[1], in_ch_2_vld: bits[1], out_ch_vld: bits[1], out_ch_2_vld: bits[1], out_ch_rdy: bits[1], out_ch_2_rdy: bits[1], in_ch_rdy: bits[1], in_ch_2_rdy: bits[1]) {
reg p0_add_49(bits[64])
reg p1_add_49(bits[64])
reg p2_add_49(bits[64])
reg p3_add_49(bits[64])
reg p0_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg p1_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg p2_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg p3_valid(bits[1], reset_value=0, asynchronous=false, active_low=true)
reg st((bits[64]), reset_value=(10), asynchronous=false, active_low=true)
in_ch_data: bits[64] = input_port(name=in_ch_data, id=38)
in_ch_2_data: bits[64] = input_port(name=in_ch_2_data, id=41)
rst_n: bits[1] = input_port(name=rst_n, id=74)
in_ch_vld: bits[1] = input_port(name=in_ch_vld, id=75)
in_ch_2_vld: bits[1] = input_port(name=in_ch_2_vld, id=76)
out_ch_rdy: bits[1] = input_port(name=out_ch_rdy, id=92)
out_ch_2_rdy: bits[1] = input_port(name=out_ch_2_rdy, id=95)
literal.50: bits[64] = literal(value=10, id=50)
st__1: (bits[64]) = register_read(register=st, id=87)
add.46: bits[64] = add(in_ch_data, in_ch_2_data, id=46)
tuple_index.47: bits[64] = tuple_index(st__1, index=0, id=47)
add.51: bits[64] = add(literal.50, tuple_index.47, id=51)
tuple.52: (bits[64]) = tuple(add.51, id=52)
add.49: bits[64] = add(add.46, tuple_index.47, id=49)
not.127: bits[1] = not(rst_n, id=127)
p0_add_49: bits[64] = register_read(register=p0_add_49, id=55)
not.119: bits[1] = not(rst_n, id=119)
p1_add_49: bits[64] = register_read(register=p1_add_49, id=59)
not.111: bits[1] = not(rst_n, id=111)
p2_add_49: bits[64] = register_read(register=p2_add_49, id=63)
and.77: bits[1] = and(in_ch_vld, in_ch_2_vld, id=77)
not.103: bits[1] = not(rst_n, id=103)
p3_add_49: bits[64] = register_read(register=p3_add_49, id=67)
register_read.79: bits[1] = register_read(register=p0_valid, id=79)
register_read.81: bits[1] = register_read(register=p1_valid, id=81)
register_read.83: bits[1] = register_read(register=p2_valid, id=83)
register_read.85: bits[1] = register_read(register=p3_valid, id=85)
literal.70: bits[1] = literal(value=1, id=70)
literal.72: bits[64] = literal(value=55, id=72)
and.88: bits[1] = and(literal.70, register_read.85, id=88)
and.90: bits[1] = and(literal.70, register_read.85, id=90)
not.93: bits[1] = not(literal.70, id=93)
or.94: bits[1] = or(not.93, out_ch_rdy, id=94)
not.96: bits[1] = not(literal.70, id=96)
or.97: bits[1] = or(not.96, out_ch_2_rdy, id=97)
and.98: bits[1] = and(or.94, or.97, id=98)
p3_not_valid: bits[1] = not(register_read.85, id=99)
p3_enable: bits[1] = or(and.98, p3_not_valid, id=100)
p3_data_enable: bits[1] = and(p3_enable, register_read.83, id=102)
p3_load_en: bits[1] = or(p3_data_enable, not.103, id=104)
register_write.101: () = register_write(register_read.83, register=p3_valid, load_enable=p3_enable, reset=rst_n, id=101)
register_write.105: () = register_write(p2_add_49, register=p3_add_49, load_enable=p3_load_en, id=105)
p2_not_valid: bits[1] = not(register_read.83, id=107)
p2_enable: bits[1] = or(p3_enable, p2_not_valid, id=108)
p2_data_enable: bits[1] = and(p2_enable, register_read.81, id=110)
p2_load_en: bits[1] = or(p2_data_enable, not.111, id=112)
register_write.113: () = register_write(p1_add_49, register=p2_add_49, load_enable=p2_load_en, id=113)
register_write.109: () = register_write(register_read.81, register=p2_valid, load_enable=p2_enable, reset=rst_n, id=109)
p1_not_valid: bits[1] = not(register_read.81, id=115)
p1_enable: bits[1] = or(p2_enable, p1_not_valid, id=116)
p1_data_enable: bits[1] = and(p1_enable, register_read.79, id=118)
p1_load_en: bits[1] = or(p1_data_enable, not.119, id=120)
register_write.121: () = register_write(p0_add_49, register=p1_add_49, load_enable=p1_load_en, id=121)
register_write.117: () = register_write(register_read.79, register=p1_valid, load_enable=p1_enable, reset=rst_n, id=117)
p0_not_valid: bits[1] = not(register_read.79, id=123)
p0_enable: bits[1] = or(p1_enable, p0_not_valid, id=124)
next_state_enable: bits[1] = and(p0_enable, and.77, id=132)
register_write.133: () = register_write(tuple.52, register=st, load_enable=next_state_enable, reset=rst_n, id=133)
p0_data_enable: bits[1] = and(p0_enable, and.77, id=126)
p0_load_en: bits[1] = or(p0_data_enable, not.127, id=128)
register_write.129: () = register_write(add.49, register=p0_add_49, load_enable=p0_load_en, id=129)
register_write.125: () = register_write(and.77, register=p0_valid, load_enable=p0_enable, reset=rst_n, id=125)
out_ch_data: () = output_port(p3_add_49, name=out_ch_data, id=71)
out_ch_2_data: () = output_port(literal.72, name=out_ch_2_data, id=73)
out_ch_vld: () = output_port(and.88, name=out_ch_vld, id=89)
literal.700: bits[1] = literal(value=0, id=700)
out_ch_2_vld: () = output_port(literal.700, name=out_ch_2_vld, id=91)
in_ch_rdy: () = output_port(p0_enable, name=in_ch_rdy, id=134)
in_ch_2_rdy: () = output_port(p0_enable, name=in_ch_2_rdy, id=135)
}
"""
BLOCK_SIGNATURE_TEXT = """
module_name: "foo"
data_ports {
direction: DIRECTION_INPUT
name: "in_ch_data"
width: 64
}
data_ports {
direction: DIRECTION_INPUT
name: "in_ch_2_data"
width: 64
}
data_ports {
direction: DIRECTION_OUTPUT
name: "out_ch_data"
width: 64
}
data_ports {
direction: DIRECTION_OUTPUT
name: "out_ch_2_data"
width: 64
}
data_ports {
direction: DIRECTION_INPUT
name: "in_ch_vld"
width: 1
}
data_ports {
direction: DIRECTION_INPUT
name: "in_ch_2_vld"
width: 1
}
data_ports {
direction: DIRECTION_OUTPUT
name: "out_ch_vld"
width: 1
}
data_ports {
direction: DIRECTION_OUTPUT
name: "out_ch_2_vld"
width: 1
}
data_ports {
direction: DIRECTION_INPUT
name: "out_ch_rdy"
width: 1
}
data_ports {
direction: DIRECTION_INPUT
name: "out_ch_2_rdy"
width: 1
}
data_ports {
direction: DIRECTION_OUTPUT
name: "in_ch_rdy"
width: 1
}
data_ports {
direction: DIRECTION_OUTPUT
name: "in_ch_2_rdy"
width: 1
}
clock_name: "clk"
reset {
name: "rst_n"
asynchronous: false
active_low: true
}
pipeline {
latency: 4
initiation_interval: 1
pipeline_control {
valid {
input_name: "input_valid"
output_name: "output_valid"
}
}
}
"""
def run_command(args):
"""Runs the command described by args and returns the completion object."""
# Don't use check=True because we want to print stderr/stdout on failure for a
# better error message.
# pylint: disable=subprocess-run-check
comp = subprocess.run(
args, stdout=subprocess.PIPE, stderr=subprocess.PIPE, encoding="utf-8")
if comp.returncode != 0:
logging.error("Failed to run: %s", " ".join(args))
logging.error("stderr: %s", comp.stderr)
logging.error("stdout: %s", comp.stdout)
comp.check_returncode()
return comp
class EvalProcTest(absltest.TestCase):
def test_basic(self):
ir_file = self.create_tempfile(content=PROC_IR)
input_file = self.create_tempfile(content="""
bits[64]:42
bits[64]:101
""")
input_file_2 = self.create_tempfile(content="""
bits[64]:10
bits[64]:6
""")
output_file = self.create_tempfile(content="""
bits[64]:62
bits[64]:127
""")
output_file_2 = self.create_tempfile(content="""
bits[64]:55
bits[64]:55
""")
shared_args = [
EVAL_PROC_MAIN_PATH, ir_file.full_path, "--ticks", "2", "-v=3",
"--logtostderr", "--inputs_for_channels",
"in_ch={infile1},in_ch_2={infile2}".format(
infile1=input_file.full_path,
infile2=input_file_2.full_path), "--expected_outputs_for_channels",
"out_ch={outfile},out_ch_2={outfile2}".format(
outfile=output_file.full_path, outfile2=output_file_2.full_path)
]
output = run_command(shared_args + ["--backend", "ir_interpreter"])
self.assertIn("Proc test_proc", output.stderr)
output = run_command(shared_args + ["--backend", "serial_jit"])
self.assertIn("Proc test_proc", output.stderr)
def test_reset_static(self):
ir_file = self.create_tempfile(content=PROC_IR)
input_file = self.create_tempfile(content="""
bits[64]:42
bits[64]:101
""")
input_file_2 = self.create_tempfile(content="""
bits[64]:10
bits[64]:6
""")
output_file = self.create_tempfile(content="""
bits[64]:62
bits[64]:117
""")
output_file_2 = self.create_tempfile(content="""
bits[64]:55
bits[64]:55
""")
shared_args = [
EVAL_PROC_MAIN_PATH, ir_file.full_path, "--ticks", "1,1", "-v=3",
"--logtostderr", "--inputs_for_channels",
"in_ch={infile1},in_ch_2={infile2}".format(
infile1=input_file.full_path,
infile2=input_file_2.full_path), "--expected_outputs_for_channels",
"out_ch={outfile},out_ch_2={outfile2}".format(
outfile=output_file.full_path, outfile2=output_file_2.full_path)
]
output = run_command(shared_args + ["--backend", "ir_interpreter"])
self.assertIn("Proc test_proc", output.stderr)
output = run_command(shared_args + ["--backend", "serial_jit"])
self.assertIn("Proc test_proc", output.stderr)
def test_block(self):
ir_file = self.create_tempfile(content=BLOCK_IR)
signature_file = self.create_tempfile(content=BLOCK_SIGNATURE_TEXT)
input_file = self.create_tempfile(content="""
bits[64]:42
bits[64]:101
""")
input_file_2 = self.create_tempfile(content="""
bits[64]:10
bits[64]:6
""")
output_file = self.create_tempfile(content="""
bits[64]:62
bits[64]:127
""")
output_file_2 = self.create_tempfile(content="""
bits[64]:55
bits[64]:55
""")
shared_args = [
EVAL_PROC_MAIN_PATH, ir_file.full_path, "--ticks", "2", "-v=3",
"--logtostderr", "--block_signature_proto", signature_file.full_path,
"--backend", "block_interpreter", "--inputs_for_channels",
"in_ch={infile1},in_ch_2={infile2}".format(
infile1=input_file.full_path,
infile2=input_file_2.full_path), "--expected_outputs_for_channels",
"out_ch={outfile},out_ch_2={outfile2}".format(
outfile=output_file.full_path, outfile2=output_file_2.full_path)
]
output = run_command(shared_args)
self.assertIn("Cycle[6]: resetting? false", output.stderr)
def test_block_no_output(self):
ir_file = self.create_tempfile(content=BLOCK_IR_BROKEN)
signature_file = self.create_tempfile(content=BLOCK_SIGNATURE_TEXT)
input_file = self.create_tempfile(content="""
bits[64]:42
bits[64]:101
""")
input_file_2 = self.create_tempfile(content="""
bits[64]:10
bits[64]:6
""")
output_file = self.create_tempfile(content="""
bits[64]:62
bits[64]:127
""")
output_file_2 = self.create_tempfile(content="""
bits[64]:55
bits[64]:55
""")
shared_args = [
EVAL_PROC_MAIN_PATH, ir_file.full_path, "--ticks", "2", "-v=3",
"--logtostderr", "--block_signature_proto", signature_file.full_path,
"--backend", "block_interpreter", "--inputs_for_channels",
"in_ch={infile1},in_ch_2={infile2}".format(
infile1=input_file.full_path,
infile2=input_file_2.full_path), "--expected_outputs_for_channels",
"out_ch={outfile},out_ch_2={outfile2}".format(
outfile=output_file.full_path, outfile2=output_file_2.full_path)
]
comp = subprocess.run(
shared_args,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
encoding="utf-8",
check=False)
self.assertNotEqual(comp.returncode, 0)
self.assertIn("Block didn't produce output", comp.stderr)
if __name__ == "__main__":
absltest.main()
| 40.401656
| 312
| 0.705698
| 3,416
| 19,514
| 3.745609
| 0.090457
| 0.041422
| 0.011723
| 0.042986
| 0.850723
| 0.83009
| 0.822118
| 0.822118
| 0.818757
| 0.806721
| 0
| 0.090239
| 0.138516
| 19,514
| 482
| 313
| 40.485477
| 0.67087
| 0.039818
| 0
| 0.7343
| 0
| 0.120773
| 0.785829
| 0.163941
| 0
| 0
| 0
| 0
| 0.016908
| 1
| 0.012077
| false
| 0
| 0.009662
| 0
| 0.02657
| 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
|
a255895a8a8212a3022234d1017094b701dd4917
| 16,970
|
py
|
Python
|
tests/comment_exclusions.py
|
loganswartz/vermin
|
55f159a229adf16690fed1d4f884594471f37abc
|
[
"MIT"
] | 261
|
2018-03-06T20:01:23.000Z
|
2022-03-25T15:37:41.000Z
|
tests/comment_exclusions.py
|
loganswartz/vermin
|
55f159a229adf16690fed1d4f884594471f37abc
|
[
"MIT"
] | 78
|
2018-03-07T10:12:29.000Z
|
2022-03-04T14:50:16.000Z
|
tests/comment_exclusions.py
|
loganswartz/vermin
|
55f159a229adf16690fed1d4f884594471f37abc
|
[
"MIT"
] | 20
|
2018-03-08T20:47:12.000Z
|
2022-03-08T16:26:30.000Z
|
from .testutils import VerminTest, current_version
class VerminCommentsExclusionsTests(VerminTest):
def test_import(self):
visitor = self.visit("# novm\nimport email.parser.FeedParser")
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
# Comment "novm" or "novermin" on its own refers to the next line.
self.assertIn(2, visitor.no_lines())
visitor = self.visit("# novermin\nimport email.parser.FeedParser")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
# Testing at end of line w/o spacing.
visitor = self.visit("import email.parser.FeedParser # novm")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("import email.parser.FeedParser #novm")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("import email.parser.FeedParser # novermin")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("import email.parser.FeedParser#novermin")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
# Testing multiple comment segments.
visitor = self.visit("import email.parser.FeedParser # noqa # novm")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("import email.parser.FeedParser # novm # noqa")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("import email.parser.FeedParser # noqa # novermin # nolint")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("import email.parser.FeedParser "
"# type: ignore[attr-defined] # novm # pylint: disable=no-member")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
# Testing multiple comment segments on its own refers to the next line.
visitor = self.visit("# noqa # novm # nolint\nimport email.parser.FeedParser")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("# noqa # novermin # nolint\nimport email.parser.FeedParser")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("# type: ignore[attr-defined] # novm # pylint: disable=no-member\n"
"import email.parser.FeedParser")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
# Detect comments on line that are indented, i.e. col != 0 but the comment is alone on the line.
visitor = self.visit("if 1:\n # novermin\n import email.parser.FeedParser")
self.assertIn(3, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("if 1:\n\t# novermin\n\timport email.parser.FeedParser")
self.assertIn(3, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("if 1:\n\tif 1:\n\t\t# novermin\n\t\timport email.parser.FeedParser")
self.assertIn(4, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_from_import(self):
visitor = self.visit("# novm\nfrom email.parser import FeedParser")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("# novermin\nfrom email.parser import FeedParser")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("from email.parser import FeedParser # novm")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("from email.parser import FeedParser # novermin")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_function(self):
visitor = self.visit("# novm\ndef foo():\n\tall([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("def foo(): # novm\n\tall([])")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
@VerminTest.skipUnlessVersion(3, 5)
def test_async_function(self):
visitor = self.visit("# novm\nasync def foo():\n\tall([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("async def foo(): #novm\n\tall([])")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_class(self):
visitor = self.visit("# novm\nclass foo():\n\tdef __init__(self):\n\t\tall([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("class foo(): # novm\n\tdef __init__(self):\n\t\tall([])")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_if(self):
visitor = self.visit("# novm\nif True:\n\tall([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("if True: # novm\n\tall([])")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_for(self):
visitor = self.visit("# novm\nfor a in [1,2,3]:\n\tall([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("for a in [1,2,3]: # novm\n\tall([])")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
@VerminTest.skipUnlessVersion(3, 6)
def test_async_for(self):
visitor = self.visit("""async def foo():
# novm
async for a in [1,2,3]:
all([])
""")
self.assertIn(3, visitor.no_lines())
self.assertOnlyIn((3, 5), visitor.minimum_versions())
visitor = self.visit("""async def foo():
async for a in [1,2,3]: # novm
all([])
""")
self.assertIn(2, visitor.no_lines())
self.assertOnlyIn((3, 5), visitor.minimum_versions())
def test_while(self):
visitor = self.visit("# novm\nwhile True:\n\tall([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("while True: # novm\n\tall([])")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_boolop(self):
visitor = self.visit("# novm\nFalse or all([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("False or all([]) # novm")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_call(self):
visitor = self.visit("# novm\nall([])")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("all([]) # novm")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_assign(self):
visitor = self.visit("""import ssl
tls_version = ssl.PROTOCOL_TLSv1
if hasattr(ssl, "PROTOCOL_TLS"):
tls_version = ssl.PROTOCOL_TLS # novermin
""")
self.assertIn(4, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_augassign(self):
visitor = self.visit("""import ssl
tls_version = ssl.PROTOCOL_TLSv1
if hasattr(ssl, "PROTOCOL_TLS"):
tls_version += ssl.PROTOCOL_TLS # novermin
""")
self.assertIn(4, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
@VerminTest.skipUnlessVersion(3, 6)
def test_annassign(self):
visitor = self.visit("""a : int = 1 # novermin
""")
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
@VerminTest.skipUnlessVersion(3, 5)
def test_coroutines_await(self):
self.config.set_verbose(2)
visitor = self.visit("""async def func():
await something() # novermin
""")
self.assertIn(2, visitor.no_lines())
# Since both `async def` and `await` require 3.5, and `await` must be in an `async def`, the
# verbose (2) output text is inspected.
self.assertTrue(visitor.coroutines())
self.assertOnlyIn((3, 5), visitor.minimum_versions())
self.assertNotIn("await", visitor.output_text())
@VerminTest.skipUnlessVersion(3, 8)
def test_namedexpr(self):
visitor = self.visit("""import ssl
(a := ssl.PROTOCOL_TLS) # novermin
""")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
@VerminTest.skipUnlessVersion(3, 3)
def test_yield_from(self):
visitor = self.visit("""def foo(x):
yield from range(x) # novermin
""")
self.assertIn(2, visitor.no_lines())
self.assertFalse(visitor.yield_from())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_yield(self):
visitor = self.visit("""import ssl
yield ssl.PROTOCOL_TLS # novermin
""")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_raise(self):
visitor = self.visit("""import ssl
raise ssl.PROTOCOL_TLS # novermin
""")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_excepthandler(self):
visitor = self.visit("""import ssl
try:
pass
except TypeError: # novermin
ssl.PROTOCOL_TLS
""")
self.assertIn(4, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_with(self):
visitor = self.visit("""import ssl
with 1 as a: # novermin
ssl.PROTOCOL_TLS
""")
self.assertIn(2, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_subscript(self):
visitor = self.visit("""import ssl
l = [1, 2, 3]
l[1:ssl.PROTOCOL_TLS.value] # novermin
""")
self.assertIn(3, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_newline_before_novm(self):
# Earlier, it wasn't checking for both `NL` and `NEWLINE` tokens to denote newlines, only the
# later.
visitor = self.visit("""import ssl
l = [1, 2, 3]
for a in l:
# novm
l[1:ssl.PROTOCOL_TLS.value]
""")
self.assertIn(6, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_function_decorator(self):
visitor = self.visit("""@staticmethod # novm
def foo(): pass
""")
self.assertFalse(visitor.function_decorators())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""@staticmethod #novm
@staticmethod #novm
def foo(): pass
""")
self.assertFalse(visitor.function_decorators())
self.assertEqual({1, 2}, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
# When not all function decorators are excluded, the function decorator version requirement is
# still in effect.
visitor = self.visit("""@staticmethod
@staticmethod #novm
def foo(): pass
""")
self.assertTrue(visitor.function_decorators())
self.assertEqual({2}, visitor.no_lines())
self.assertEqual([(2, 4), (3, 0)], visitor.minimum_versions())
visitor = self.visit("""@staticmethod #novm
@staticmethod
def foo(): pass
""")
self.assertEqual({1}, visitor.no_lines())
# The line numbers were not as precise before 3.8, so excluding the first decorator would
# exclude the whole function, too.
if current_version() < (3, 8):
self.assertFalse(visitor.function_decorators())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
else:
self.assertTrue(visitor.function_decorators())
self.assertEqual([(2, 4), (3, 0)], visitor.minimum_versions())
def test_class_decorator(self):
visitor = self.visit("""@somedeco # novm
class Foo: pass
""")
self.assertFalse(visitor.class_decorators())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""@somedeco #novm
@somedeco #novm
class Foo: pass
""")
self.assertFalse(visitor.class_decorators())
self.assertEqual({1, 2}, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
# When not all class decorators are excluded, the class decorator version requirement is still
# in effect.
visitor = self.visit("""@somedeco
@somedeco #novm
class Foo: pass
""")
self.assertTrue(visitor.class_decorators())
self.assertEqual({2}, visitor.no_lines())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
visitor = self.visit("""@somedeco #novm
@somedeco
class Foo: pass
""")
self.assertEqual({1}, visitor.no_lines())
# The line numbers were not as precise before 3.8, so excluding the first decorator would
# exclude the whole class, too.
if current_version() < (3, 8):
self.assertFalse(visitor.class_decorators())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
else:
self.assertTrue(visitor.class_decorators())
self.assertEqual([(2, 6), (3, 0)], visitor.minimum_versions())
def test_multiline(self):
visitor = self.visit('''foo = """
{}
""".format('bar') #novm
''')
self.assertFalse(visitor.format27())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit('''foo = """{}""".format('bar') #novm
''')
self.assertFalse(visitor.format27())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit('''foo = """{}
""".format('bar') #novm
''')
self.assertFalse(visitor.format27())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""foo = '''
{}
'''.format('bar') #novm
""")
self.assertFalse(visitor.format27())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""foo = '''{}'''.format('bar') #novm
""")
self.assertFalse(visitor.format27())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""foo = '''{}
'''.format('bar') #novm
""")
self.assertFalse(visitor.format27())
self.assertIn(1, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit('''#novm
foo = """
{}
""".format('bar')
''')
self.assertFalse(visitor.format27())
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit('''#novm
foo = """{}""".format('bar')
''')
self.assertFalse(visitor.format27())
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit('''#novm
foo = """{}
""".format('bar')
''')
self.assertFalse(visitor.format27())
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""#novm
foo = '''
{}
'''.format('bar')
""")
self.assertFalse(visitor.format27())
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""#novm
foo = '''{}'''.format('bar')
""")
self.assertFalse(visitor.format27())
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
visitor = self.visit("""#novm
foo = '''{}
'''.format('bar')
""")
self.assertFalse(visitor.format27())
self.assertIn(2, visitor.no_lines())
self.assertEqual([(0, 0), (0, 0)], visitor.minimum_versions())
def test_not_parsing_comments(self):
self.config.set_parse_comments(False)
visitor = self.visit("# novm\nimport email.parser.FeedParser")
self.assertEqual([(2, 4), (3, 0)], visitor.minimum_versions())
visitor = self.visit("import email.parser.FeedParser # novm")
self.assertEqual([(2, 4), (3, 0)], visitor.minimum_versions())
| 36.731602
| 100
| 0.651738
| 2,251
| 16,970
| 4.813416
| 0.08263
| 0.031011
| 0.031011
| 0.150715
| 0.889894
| 0.864882
| 0.82215
| 0.801846
| 0.776281
| 0.739179
| 0
| 0.030796
| 0.159988
| 16,970
| 461
| 101
| 36.81128
| 0.729288
| 0.057808
| 0
| 0.722222
| 0
| 0.005291
| 0.207188
| 0.038883
| 0
| 0
| 0
| 0
| 0.44709
| 1
| 0.071429
| false
| 0.02381
| 0.089947
| 0
| 0.164021
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
0c1556a961918dcc1da741d0dda277919abd6a9c
| 1,722
|
py
|
Python
|
Instanssi/common/auth.py
|
jpot/Instanssi.org
|
5b0e3d57e002a9e8f5bb32973d43884fbdbd6a7d
|
[
"MIT"
] | 6
|
2015-04-03T12:15:02.000Z
|
2019-05-29T07:56:11.000Z
|
Instanssi/common/auth.py
|
jpot/Instanssi.org
|
5b0e3d57e002a9e8f5bb32973d43884fbdbd6a7d
|
[
"MIT"
] | 52
|
2015-03-04T21:15:48.000Z
|
2022-03-21T20:16:24.000Z
|
Instanssi/common/auth.py
|
jpot/Instanssi.org
|
5b0e3d57e002a9e8f5bb32973d43884fbdbd6a7d
|
[
"MIT"
] | 6
|
2017-09-26T00:52:51.000Z
|
2020-02-17T17:24:21.000Z
|
# -*- coding: utf-8 -*-
from django.http import HttpResponseRedirect
from Instanssi.common.http import Http403
from django.urls import reverse
def user_access_required(view_func):
def _checklogin(request, *args, **kwargs):
if request.user.is_authenticated and request.user.is_active:
return view_func(request, *args, **kwargs)
return HttpResponseRedirect(reverse('users:login')+'?next='+request.get_full_path())
return _checklogin
def staff_access_required(view_func):
def _checklogin(request, *args, **kwargs):
if request.user.is_authenticated and request.user.is_active:
if request.user.is_staff:
return view_func(request, *args, **kwargs)
raise Http403
return HttpResponseRedirect(reverse('users:login')+'?next='+request.get_full_path())
return _checklogin
def su_access_required(view_func):
def _checklogin(request, *args, **kwargs):
if request.user.is_authenticated and request.user.is_active:
if request.user.is_staff and request.user.is_superuser:
return view_func(request, *args, **kwargs)
raise Http403
return HttpResponseRedirect(reverse('users:login')+'?next='+request.get_full_path())
return _checklogin
def infodesk_access_required(view_func):
def _checklogin(request, *args, **kwargs):
if request.user.is_authenticated and request.user.is_active:
if request.user.has_perm('store.change_storetransaction'):
return view_func(request, *args, **kwargs)
raise Http403
return HttpResponseRedirect(reverse('users:login')+'?next='+request.get_full_path())
return _checklogin
| 39.136364
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|
0
| 8
|
0c4ac92c3eac7374a601ba30f03dbc0cf18c4040
| 16,685
|
py
|
Python
|
tests.py
|
clb17151/Battlesnake
|
b6b260b60ad0a06efe484fa0c7a15904c73730be
|
[
"MIT"
] | null | null | null |
tests.py
|
clb17151/Battlesnake
|
b6b260b60ad0a06efe484fa0c7a15904c73730be
|
[
"MIT"
] | null | null | null |
tests.py
|
clb17151/Battlesnake
|
b6b260b60ad0a06efe484fa0c7a15904c73730be
|
[
"MIT"
] | null | null | null |
"""
Starter Unit Tests using the built-in Python unittest library.
See https://docs.python.org/3/library/unittest.html
You can expand these to cover more cases!
To run the unit tests, use the following command in your terminal,
in the folder where this file exists:
python tests.py -v
"""
import unittest
import moveLogic,Board,bestReply
class AvoidHeadCollisions(unittest.TestCase):
def test_head_collision_right(self):
# Arrange
board = [
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'st', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sh', 'x', 'sh'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'st'],
['x', 'x', 'x', 'x', 'x', 'f', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'st', 'sb', 'sb', 'x', 'x', 'x', 'x', 'f'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x']]
my_snake = {'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10}], 'head': {'x': 8, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}
snakes = [{'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10}], 'head': {'x': 8, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}, {'id': 'gs_dVkqFCCj4wv7StXwJP7TFdBG', 'name': 'Barry', 'latency': '60', 'health': 95, 'body': [{'x': 5, 'y': 3}, {'x': 5, 'y': 2}, {'x': 4, 'y': 2}, {'x': 3, 'y': 2}], 'head': {'x': 5, 'y': 4}, 'length': 4, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}, {'id': 'gs_VkYymmVCfGFSMMj3DSg7wYVV', 'name': 'Barry', 'latency': '59', 'health': 93, 'body': [{'x': 10, 'y': 8}, {'x': 10, 'y': 7}, {'x': 10, 'y': 6}], 'head': {'x': 10, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}]
possible_moves = ["up", "down", "left", "right"]
# Act
result_moves = moveLogic.checkForHeadCollision(my_snake,snakes,possible_moves,board)
# Assert
self.assertEqual(["up","down","left"], result_moves)
def test_head_collision_left(self):
# Arrange
board = [
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'st', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'x'],
['x', 'x', 'x', 'x', 'st', 'sb', 'sh', 'x', 'sh', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'f', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'st', 'sb', 'sb', 'x', 'x', 'x', 'x', 'f'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x']]
my_snake = {'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10}], 'head': {'x': 8, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}
snakes = [{'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10}], 'head': {'x': 8, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}, {'id': 'gs_dVkqFCCj4wv7StXwJP7TFdBG', 'name': 'Barry', 'latency': '60', 'health': 95, 'body': [{'x': 5, 'y': 3}, {'x': 5, 'y': 2}, {'x': 4, 'y': 2}, {'x': 3, 'y': 2}], 'head': {'x': 5, 'y': 4}, 'length': 4, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}, {'id': 'gs_VkYymmVCfGFSMMj3DSg7wYVV', 'name': 'Barry', 'latency': '59', 'health': 93, 'body': [{'x': 6, 'y': 8}, {'x': 5, 'y': 8}, {'x': 5, 'y': 8}], 'head': {'x':6, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}]
possible_moves = ["up", "down", "left", "right"]
# Act
result_moves = moveLogic.checkForHeadCollision(my_snake,snakes,possible_moves,board)
# Assert
self.assertEqual(["up","down","right"], result_moves)
def test_head_collision_down(self):
# Arrange
board = [
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'st', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'f', 'x', 'st', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'st', 'sb', 'sb', 'x', 'x', 'x', 'x', 'f'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x']]
my_snake = {'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10}], 'head': {'x': 8, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}
snakes = [{'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10}], 'head': {'x': 8, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}, {'id': 'gs_dVkqFCCj4wv7StXwJP7TFdBG', 'name': 'Barry', 'latency': '60', 'health': 95, 'body': [{'x': 5, 'y': 3}, {'x': 5, 'y': 2}, {'x': 4, 'y': 2}, {'x': 3, 'y': 2}], 'head': {'x': 5, 'y': 4}, 'length': 4, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}, {'id': 'gs_VkYymmVCfGFSMMj3DSg7wYVV', 'name': 'Barry', 'latency': '59', 'health': 93, 'body': [{'x': 7, 'y': 7}, {'x': 7, 'y': 6}, {'x': 7, 'y': 5}], 'head': {'x': 7, 'y': 7}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}]
possible_moves = ["up", "down", "left", "right"]
# Act
result_moves = moveLogic.checkForHeadCollision(my_snake,snakes,possible_moves,board)
# Assert
self.assertEqual(["up","right"], result_moves)
def test_head_collision_up(self):
# Arrange
board = [
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'st', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'f', 'x', 'st', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'st', 'sb', 'sb', 'x', 'x', 'x', 'x', 'f'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x']]
my_snake = {'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 7, 'y': 7}, {'x': 7, 'y': 6}, {'x': 7, 'y': 5}], 'head': {'x': 7, 'y':7}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}
snakes =[{'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 7, 'y': 7}, {'x': 7, 'y': 6}, {'x': 7, 'y': 5}], 'head': {'x': 7, 'y':7}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}, {'id': 'gs_dVkqFCCj4wv7StXwJP7TFdBG', 'name': 'Barry', 'latency': '60', 'health': 95, 'body': [{'x': 5, 'y': 3}, {'x': 5, 'y': 2}, {'x': 4, 'y': 2}, {'x': 3, 'y': 2}], 'head': {'x': 5, 'y': 4}, 'length': 4, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}, {'id': 'gs_VkYymmVCfGFSMMj3DSg7wYVV', 'name': 'Barry', 'latency': '59', 'health': 93, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10}], 'head': {'x':8, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}]
possible_moves = ["up", "down", "left", "right"]
# Act
result_moves = moveLogic.checkForHeadCollision(my_snake,snakes,possible_moves,board)
# Assert
self.assertEqual(["down","left"], result_moves)
def test_head_collision_bigger_snake(self):
# Arrange
board = [
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'st', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'x'],
['x', 'x', 'x', 'x', 'st', 'sb', 'sh', 'x', 'sh', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'f', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'sh', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'st', 'sb', 'sb', 'x', 'x', 'x', 'x', 'f'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x']]
my_snake = {'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10},{'x':9,'y':10}], 'head': {'x': 8, 'y': 8}, 'length': 4, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}
snakes = [{'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 8, 'y': 8}, {'x': 8, 'y': 9}, {'x': 8, 'y': 10},{'x':9,'y':10}], 'head': {'x': 8, 'y': 8}, 'length': 4, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}, {'id': 'gs_dVkqFCCj4wv7StXwJP7TFdBG', 'name': 'Barry', 'latency': '60', 'health': 95, 'body': [{'x': 5, 'y': 3}, {'x': 5, 'y': 2}, {'x': 4, 'y': 2}, {'x': 3, 'y': 2}], 'head': {'x': 5, 'y': 4}, 'length': 4, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}, {'id': 'gs_VkYymmVCfGFSMMj3DSg7wYVV', 'name': 'Barry', 'latency': '59', 'health': 93, 'body': [{'x': 6, 'y': 8}, {'x': 5, 'y': 8}, {'x': 5, 'y': 8}], 'head': {'x':6, 'y': 8}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}]
possible_moves = ["up", "down", "left", "right"]
# Act
result_moves = moveLogic.checkForHeadCollision(my_snake,snakes,possible_moves,board)
# Assert
self.assertEqual(["up","down","left","right"], result_moves)
def test_head_collision_up2(self):
# Arrange
board = [
['x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'x', 'x', 'x', 'sh', 'sb', 'x'],
['x', 'x', 'sb', 'sb', 'x', 'sb', 'x'],
['x', 'x', 'sb', 'sb', 'sh', 'sb', 'x'],
['x', 'x', 'st', 'x', 'x', 'sb', 'x'],
['x', 'x', 'x', 'st', 'sb', 'sb', 'x'],
['x', 'x', 'x', 'x', 'x', 'f', 'x']]
my_snake = {'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 4, 'y': 3}, {'x': 3, 'y': 3}, {'x': 3, 'y': 5}, {'x': 2, 'y': 5}, {'x': 2, 'y': 4}, {'x': 2, 'y': 3}], 'head': {'x': 4, 'y': 3}, 'length': 6, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}
snakes = [{'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 95, 'body': [{'x': 4, 'y': 6}, {'x': 3, 'y': 3}, {'x': 3, 'y': 5}, {'x': 2, 'y': 5}, {'x': 2, 'y': 4}, {'x': 2, 'y': 3}], 'head': {'x': 4, 'y': 3}, 'length': 6, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}, {'id': 'gs_VkYymmVCfGFSMMj3DSg7wYVV', 'name': 'Barry', 'latency': '59', 'health': 93, 'body': [{'x': 4, 'y': 5}, {'x': 5, 'y': 5}, {'x': 5, 'y': 4}, {'x': 5, 'y': 3}, {'x': 5, 'y': 2}, {'x': 5, 'y': 1}, {'x': 4, 'y': 1}, {'x': 3, 'y': 1}], 'head': {'x': 4, 'y': 5}, 'length': 8, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}]
possible_moves = ["up", "down", "left", "right"]
# Act
result_moves = moveLogic.checkForHeadCollision(my_snake,snakes,possible_moves,board)
# Assert
self.assertEqual(["down","left","right"], result_moves)
def test_eval(self):
# Arrange
board = [
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'sb', 'sb', 'sb', 'sb', 'sb', 'sb', 'sb', 'sh', 'sb', 'x'],
['x', 'sh', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'sb', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'x', 'sb', 'x', 'sb', 'x'],
['x', 'x', 'x', 'x', 'x', 'x', 'st', 'sb', 'x', 'sb', 'x'],
['f', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'st', 'sb', 'x'],
['sb', 'sb', 'st', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['sb', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['sb', 'sb', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'sb', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'],
['x', 'sh', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x']]
my_snake = {'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 67, 'body': [{'x': 1, 'y': 0}, {'x': 1, 'y': 1}, {'x': 1, 'y': 2}, {'x': 0, 'y': 2}, {'x': 0, 'y': 3}, {'x': 0, 'y': 4}, {'x': 1, 'y': 4}, {'x': 2, 'y': 4}], 'head': {'x': 1, 'y': 0}, 'length': 8, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}
snakes = [{'id': 'gs_6cKMCg9r6jP77WV6bbjqrFfX', 'name': 'ekans v1', 'latency': '147', 'health': 67, 'body': [{'x': 1, 'y': 0}, {'x': 1, 'y': 1}, {'x': 1, 'y': 2}, {'x': 0, 'y': 2}, {'x': 0, 'y': 3}, {'x': 0, 'y': 4}, {'x': 1, 'y': 4}], 'head': {'x': 1, 'y': 0}, 'length': 8, 'shout': '', 'squad': '', 'customizations': {'color': '#800080', 'head': 'safe', 'tail': 'small-rattle'}}, {'id': 'gs_dVkqFCCj4wv7StXwJP7TFdBG', 'name': 'Barry', 'latency': '60', 'health': 95, 'body': [{'x': 1, 'y': 8}, {'x': 1, 'y': 9}, {'x': 2, 'y': 9}, {'x': 3, 'y': 9}, {'x': 4, 'y': 9}, {'x': 5, 'y': 9}, {'x': 6, 'y': 9}, {'x': 7, 'y': 9}, {'x': 7, 'y': 8}, {'x': 7, 'y': 7}, {'x': 7, 'y': 6}, {'x': 6, 'y': 6}, {'x': 5, 'y': 6}], 'head': {'x': 1, 'y': 8}, 'length': 13, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}, {'id': 'gs_VkYymmVCfGFSMMj3DSg7wYVV', 'name': 'Barry', 'latency': '59', 'health': 93, 'body': [{'x': 8, 'y': 9}, {'x': 9, 'y': 9}, {'x': 9, 'y': 8}, {'x': 9, 'y': 7}, {'x': 9, 'y': 6}, {'x': 9, 'y': 5}, {'x': 8, 'y': 5}], 'head': {'x': 8, 'y': 9}, 'length': 3, 'shout': '', 'squad': '', 'customizations': {'color': '#fb6900', 'head': 'default', 'tail': 'default'}}]
food = [{"x":0,"y":5}]
Board.initialiseBoard(11, 11)
Board.fillGameBoard(snakes, food, 11)
pinf = float('inf')
ninf = float('-inf')
result = (bestReply.BRS(ninf,pinf,4,"Max",board,snakes,"initial",my_snake))
# Assert
self.assertEqual("right",result[1])
if __name__ == "__main__":
unittest.main()
| 74.486607
| 1,230
| 0.405694
| 2,321
| 16,685
| 2.876346
| 0.054718
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| 0.899341
| 0.894997
| 0.887657
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| 0.854104
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| 0.056747
| 0.217381
| 16,685
| 223
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| 0.044892
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| 1
| 0.053435
| false
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0
| 10
|
0c51fb4795172dfeed33e843a00cfaab4296e50b
| 24,497
|
py
|
Python
|
tests/formats/xml_doc.py
|
arianpasquali/ternip
|
09c5f5eb864a36ea229b96951f8590418038e8a1
|
[
"Apache-2.0"
] | null | null | null |
tests/formats/xml_doc.py
|
arianpasquali/ternip
|
09c5f5eb864a36ea229b96951f8590418038e8a1
|
[
"Apache-2.0"
] | null | null | null |
tests/formats/xml_doc.py
|
arianpasquali/ternip
|
09c5f5eb864a36ea229b96951f8590418038e8a1
|
[
"Apache-2.0"
] | null | null | null |
import unittest
import xml.dom.minidom
from ternip.formats.xml_doc import XmlDocument, BadNodeNameError
from ternip.timex import Timex
class _XmlDocument(XmlDocument):
_timex_tag_name = 'TIMEX'
def _timex_from_node(self, node):
return Timex()
def _annotate_node_from_timex(self, timex, node):
pass
@staticmethod
def create(sents, tok_offsets=None, add_S=False, add_LEX=False, pos_attr=False):
impl = xml.dom.minidom.getDOMImplementation()
doc = impl.createDocument(None, 'root', None)
# Add text to document
_XmlDocument._add_words_to_node_from_sents(doc, doc.documentElement, sents, tok_offsets)
# Create a document with just text nodes
x = _XmlDocument(doc)
# Now reconcile to add the S, LEX and TIMEX tags
x.reconcile(sents, add_S, add_LEX, pos_attr)
return x
class XmlDocumentTest(unittest.TestCase):
def test_strip_timexes(self):
t = _XmlDocument('<root>This is some <TIMEX attr="timex">annotated <TIMEX>embedded annotated </TIMEX>text</TIMEX>.</root>')
t.strip_timexes()
self.assertEqual(str(t), xml.dom.minidom.parseString('<root>This is some annotated embedded annotated text.</root>').toxml())
def test_to_sents(self):
t = _XmlDocument('<root>This is some <FOO attr="timex">annotated <FOO>embedded annotated </FOO>text</FOO>. This is the second sentence.</root>')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('some', 'DT', set()), ('annotated', 'JJ', set()),
('embedded', 'VBD', set()), ('annotated', 'JJ', set()), ('text', 'NN', set()),
('.', '.', set())], [('This', 'DT', set()), ('is', 'VBZ', set()), ('the', 'DT', set()),
('second', 'JJ', set()), ('sentence', 'NN', set()), ('.', '.', set())]])
def test_to_sents_only_node(self):
t = _XmlDocument('<root>This is outside of the body. <body>This is some <FOO attr="timex">annotated <FOO>embedded annotated </FOO>text</FOO>. This is the second sentence.</body></root>', nodename='body')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('some', 'DT', set()), ('annotated', 'JJ', set()), ('embedded', 'VBD', set()), ('annotated', 'JJ', set()), ('text', 'NN', set()), ('.', '.', set())], [('This', 'DT', set()), ('is', 'VBZ', set()), ('the', 'DT', set()), ('second', 'JJ', set()), ('sentence', 'NN', set()), ('.', '.', set())]])
def test_to_sents_only_single_node(self):
self.assertRaises(BadNodeNameError, _XmlDocument, '<root>This is outside of the body. <body>This is some <FOO attr="timex">annotated <FOO>embedded annotated </FOO>text</FOO>. This is the second sentence.</body><body>Oh dear.</body></root>', nodename='body')
def test_to_sents_tag_crossing_sentence_boundary(self):
t = _XmlDocument('<root>This is some <FOO attr="timex">annotated <FOO>embedded annotated </FOO>text. This is the second </FOO>sentence.</root>')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('some', 'DT', set()), ('annotated', 'JJ', set()), ('embedded', 'VBD', set()), ('annotated', 'JJ', set()), ('text', 'NN', set()), ('.', '.', set())], [('This', 'DT', set()), ('is', 'VBZ', set()), ('the', 'DT', set()), ('second', 'JJ', set()), ('sentence', 'NN', set()), ('.', '.', set())]])
def test_to_sents_tag_whole_sentence(self):
t = _XmlDocument('<root><a>This is some <FOO attr="timex">annotated <FOO>embedded annotated </FOO>text. </FOO></a>This is the second sentence.</root>')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('some', 'DT', set()), ('annotated', 'JJ', set()), ('embedded', 'VBD', set()), ('annotated', 'JJ', set()), ('text', 'NN', set()), ('.', '.', set())], [('This', 'DT', set()), ('is', 'VBZ', set()), ('the', 'DT', set()), ('second', 'JJ', set()), ('sentence', 'NN', set()), ('.', '.', set())]])
def test_to_sents_s_tags(self):
t = _XmlDocument('<root><s>This is sentence 1. This is the</s> <s>second sentence.</s></root>', has_S='s')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('sentence', 'JJ', set()), ('1', 'CD', set()), ('.', '.', set()), ('This', 'DT', set()), ('is', 'VBZ', set()), ('the', 'DT', set())], [('second', 'JJ', set()), ('sentence', 'NN', set()), ('.', '.', set())]])
def test_to_sents_lex_tags(self):
t = _XmlDocument('<root><s><lex>This</lex> <lex>is</lex> <lex>sentence 1.</lex> <lex>This</lex> <lex>is</lex> <lex>the</lex></s> <s><lex>second</lex> <lex>sentence.</lex></s></root>', has_S='s', has_LEX='lex')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('sentence 1.', 'JJ', set()), ('This', 'DT', set()), ('is', 'VBZ', set()), ('the', 'DT', set())], [('second', 'JJ', set()), ('sentence.', 'NN', set())]])
def test_to_sents_lex_tags_1sent(self):
t = _XmlDocument('<root><lex>This</lex> <lex>is</lex> <lex>sentence 1.</lex></root>', has_LEX='lex')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('sentence 1.', 'JJ', set())]])
def test_to_sents_lex_tags_no_S(self):
t = _XmlDocument('<root><lex>This</lex> <lex>is</lex> <lex>sentence 1.</lex> <lex>This</lex> <lex>is</lex> <lex>the</lex> <lex>second</lex> <lex>sentence.</lex></root>', has_LEX='lex')
self.assertEqual(t.get_sents(), [[('This', 'DT', set()), ('is', 'VBZ', set()), ('sentence 1.', 'JJ', set())], [('This', 'DT', set()), ('is', 'VBZ', set()), ('the', 'DT', set()), ('second', 'JJ', set()), ('sentence.', 'NN', set())]])
def test_to_sents_pos_attr(self):
t = _XmlDocument('<root><s><lex pos="POS1">This</lex> <lex pos="POS1">is</lex> <lex pos="POS1">sentence 1</lex><lex pos="POS2">.</lex> <lex pos="POS1">This</lex> <lex pos="POS1">is</lex> <lex pos="POS1">the</lex></s> <s><lex pos="POS1">second</lex> <lex pos="POS1">sentence.</lex></s></root>', has_S='s', has_LEX='lex', pos_attr='pos')
self.assertEqual(t.get_sents(), [[('This', 'POS1', set()), ('is', 'POS1', set()), ('sentence 1', 'POS1', set()), ('.', 'POS2', set()), ('This', 'POS1', set()), ('is', 'POS1', set()), ('the', 'POS1', set())], [('second', 'POS1', set()), ('sentence.', 'POS1', set())]])
def test_to_sents_timexes(self):
t = _XmlDocument('<root><s><lex pos="POS1">This</lex> <TIMEX><lex pos="POS1">is</lex> <TIMEX><lex pos="POS1">sentence 1</lex></TIMEX></TIMEX><lex pos="POS2">.</lex> <lex pos="POS1">This</lex> <lex pos="POS1">is</lex> <lex pos="POS1">the</lex></s> <s><TIMEX><lex pos="POS1">second</lex></TIMEX> <lex pos="POS1">sentence.</lex></s></root>', has_S='s', has_LEX='lex', pos_attr='pos')
self.assertEqual([[len(timexes) for (tok, pos, timexes) in sent] for sent in t.get_sents()], [[0, 1, 2, 0, 0, 0, 0], [1, 0]])
def test_to_sents_timexes_nonconsuming(self):
t = _XmlDocument('<root><TIMEX />This <TIMEX>is <TIMEX>sentence 1</TIMEX></TIMEX>. This is the <TIMEX>second</TIMEX> sentence.</root>')
sents = t.get_sents()
self.assertEqual([[len(timexes) for (tok, pos, timexes) in sent] for sent in sents], [[1, 1, 2, 2, 0], [0, 0, 0, 1, 0, 0]])
txnc = sents[0][0][2].pop()
txc = sents[1][3][2].pop()
self.assertTrue(txnc.non_consuming)
self.assertFalse(txc.non_consuming)
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><TIMEX />This <TIMEX>is <TIMEX>sentence 1</TIMEX></TIMEX>. This is the <TIMEX>second</TIMEX> sentence.</root>').toxml())
def test_to_sents_timexes_nonconsuming_outsideS(self):
t = _XmlDocument('<root><TIMEX /><s><lex pos="POS1">This</lex> <TIMEX><lex pos="POS1">is</lex> <TIMEX><lex pos="POS1">sentence 1</lex></TIMEX></TIMEX><lex pos="POS2">.</lex> <lex pos="POS1">This</lex> <lex pos="POS1">is</lex> <lex pos="POS1">the</lex></s> <s><TIMEX><lex pos="POS1">second</lex></TIMEX> <lex pos="POS1">sentence.</lex></s></root>', has_S='s', has_LEX='lex', pos_attr='pos')
sents = t.get_sents()
self.assertEqual([[len(timexes) for (tok, pos, timexes) in sent] for sent in sents], [[1, 1, 2, 0, 0, 0, 0], [1, 0]])
txnc = sents[0][0][2].pop()
txc = sents[1][0][2].pop()
self.assertTrue(txnc.non_consuming)
self.assertFalse(txc.non_consuming)
def test_reconcile_S(self):
t = _XmlDocument('<root>This is some annotated text.</root>')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())]], add_S='s')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><s>This is some annotated text.</s></root>').toxml())
def test_reconcile_S_strip(self):
t = _XmlDocument('<root><t>This is some annotated text.</t> <t>This is a second sentence.</t></root>', has_S='t')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set()),
('This', 'POS', set()), ('is', 'POS', set())], [('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]], add_S='s')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><s>This is some annotated text. This is</s> <s>a second sentence.</s></root>').toxml())
def test_reconcile_2S(self):
t = _XmlDocument('<root>This is some annotated text. This is a second sentence.</root>')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]], add_S='s')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><s>This is some annotated text.</s> <s>This is a second sentence.</s></root>').toxml())
def test_reconcile_2S1(self):
t = _XmlDocument('<root><reader>This is some annotated text.</reader> This is a second sentence.</root>')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]], add_S='s')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><reader><s>This is some annotated text.</s></reader> <s>This is a second sentence.</s></root>').toxml())
def test_reconcile_2S2(self):
t = _XmlDocument('<root><reader>This is some annotated</reader> text. This is a second sentence.</root>')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]], add_S='s')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><s><reader>This is some annotated</reader> text.</s> <s>This is a second sentence.</s></root>').toxml())
def test_reconcile_2S3(self):
t = _XmlDocument('<root>This is some <reader>annotated</reader> text. This is a second sentence.</root>')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]], add_S='s')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><s>This is some <reader>annotated</reader> text.</s> <s>This is a second sentence.</s></root>').toxml())
def test_reconcile_2S4(self):
t = _XmlDocument('<root><reader>This is some annotated text. This is a second sentence.</reader></root>')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()),
('sentence.', 'POS', set())]], add_S='s')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><reader><s>This is some annotated text.</s> <s>This is a second sentence.</s></reader></root>').toxml())
def test_reconcile_2S5(self):
s = _XmlDocument('<root>This is some <p>annotated</p> text. This is <b>a second timex.</b></root>')
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()),
('text', 'POS', set()), ('.', 'POS', set())], [('This', 'POS', set()), ('is', 'POS', set()),
('a', 'POS', set()), ('second', 'POS', set()), ('timex.', 'POS', set())]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s>This is some <p>annotated</p> text.</s> <s>This is <b>a second timex.</b></s></root>').toxml())
def test_reconcile_LEX_S(self):
t = _XmlDocument('<root>This is some annotated text.</root>')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()),
('text.', 'POS', set())]], add_S='s', add_LEX='lex')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><s><lex>This</lex> <lex>is</lex> <lex>some</lex> <lex>annotated</lex> <lex>text.</lex></s></root>').toxml())
def test_reconcile_LEX_strip(self):
t = _XmlDocument('<root><t>This</t> <t>is</t> <t>some</t> <t>annotated</t> <t>text</t><t>.</t></root>', has_LEX='t')
t.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()),
('text', 'POS', set()), ('.', 'POS', set())]], add_LEX='lex')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><lex>This</lex> <lex>is</lex> <lex>some</lex> <lex>annotated</lex> <lex>text</lex><lex>.</lex></root>').toxml())
def test_reconcile_POS(self):
t = _XmlDocument('<root>This is some annotated text.</root>')
t.reconcile([[('This', 'POS1', set()), ('is', 'POS2', set()), ('some', 'POS3', set()), ('annotated', 'POS4', set()),
('text.', 'POS5', set())]], add_LEX='lex', pos_attr='pos')
self.assertEqual(str(t), xml.dom.minidom.parseString('<root><lex pos="POS1">This</lex> <lex pos="POS2">is</lex> <lex pos="POS3">some</lex> <lex pos="POS4">annotated</lex> <lex pos="POS5">text.</lex></root>').toxml())
def test_reconcile_TIMEX(self):
s = _XmlDocument('<root>This is some annotated text.</root>')
t = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', {t}), ('annotated', 'POS', {t}), ('text', 'POS', {t}), ('.', 'POS', set())]])
self.assertEqual(str(s), xml.dom.minidom.parseString('<root>This is <TIMEX>some annotated text</TIMEX>.</root>').toxml())
def test_reconcile_TIMEX_S(self):
s = _XmlDocument('<root>This is some annotated text. This is a second timex.</root>')
t1 = Timex()
t2 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', {t1}), ('annotated', 'POS', {t1}),
('text', 'POS', {t1}), ('.', 'POS', set())], [('This', 'POS', set()), ('is', 'POS', set()),
('a', 'POS', {t2}), ('second', 'POS', {t2}), ('timex.', 'POS', {t2})]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s>This is <TIMEX>some annotated text</TIMEX>.</s> <s>This is <TIMEX>a second timex.</TIMEX></s></root>').toxml())
def test_reconcile_TIMEX_S_start(self):
s = _XmlDocument('<root>This is some annotated text. This is a second timex.</root>')
t1 = Timex()
t2 = Timex()
s.reconcile([[('This', 'POS', {t1}), ('is', 'POS', {t1}), ('some', 'POS', set()), ('annotated', 'POS', set()),
('text', 'POS', set()), ('.', 'POS', set())], [('This', 'POS', set()), ('is', 'POS', set()),
('a', 'POS', {t2}), ('second', 'POS', {t2}), ('timex.', 'POS', {t2})]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s><TIMEX>This is</TIMEX> some annotated text.</s> <s>This is <TIMEX>a second timex.</TIMEX></s></root>').toxml())
def test_reconcile_TIMEX_embedded(self):
s = _XmlDocument('<root>This is some <p>annotated</p> text. This is <b>a second timex.</b></root>')
t1 = Timex()
t2 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', {t1}),
('annotated', 'POS', {t1}), ('text', 'POS', {t1}), ('.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', {t2}), ('second', 'POS', {t2}),
('timex.', 'POS', {t2})]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s>This is <TIMEX>some <p>annotated</p> text</TIMEX>.</s> <s>This is <TIMEX><b>a second timex.</b></TIMEX></s></root>').toxml())
def test_reconcile_TIMEX_embedded_nonconsuming(self):
s = _XmlDocument('<root>This is some <p>annotated</p> text. This is <b>a second timex.</b></root>')
t1 = Timex()
t2 = Timex()
t3 = Timex()
t3.non_consuming = True
s.reconcile([[('This', 'POS', {t3}), ('is', 'POS', set()), ('some', 'POS', {t1}),
('annotated', 'POS', {t1}), ('text', 'POS', {t1}), ('.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', {t2}), ('second', 'POS', {t2}),
('timex.', 'POS', {t2})]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s><TIMEX />This is <TIMEX>some <p>annotated</p> text</TIMEX>.</s> <s>This is <TIMEX><b>a second timex.</b></TIMEX></s></root>').toxml())
def test_reconcile_TIMEX_embedded_start(self):
s = _XmlDocument('<root>This is some <p>annotated</p> text. This is <b>a second timex.</b></root>')
t1 = Timex()
t2 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', {t1}),
('text', 'POS', {t1}), ('.', 'POS', set())], [('This', 'POS', set()), ('is', 'POS', set()),
('a', 'POS', {t2}), ('second', 'POS', {t2}), ('timex.', 'POS', {t2})]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s>This is some <TIMEX><p>annotated</p> text</TIMEX>.</s> <s>This is <TIMEX><b>a second timex.</b></TIMEX></s></root>').toxml())
def test_reconcile_TIMEX_embedded_start_end(self):
s = _XmlDocument('<root>This is some <p>annotated</p> <p>text</p>. This is <b>a second timex.</b></root>')
t1 = Timex()
t2 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()),
('annotated', 'POS', {t1}), ('text', 'POS', {t1}), ('.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', {t2}),
('second', 'POS', {t2}), ('timex.', 'POS', {t2})]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s>This is some <TIMEX><p>annotated</p> <p>text</p></TIMEX>.</s> <s>This is <TIMEX><b>a second timex.</b></TIMEX></s></root>').toxml())
def test_reconcile_TIMEX_embedded_start_end_consec(self):
s = _XmlDocument('<root>This is <p>some</p> <p>annotated</p> <p>text</p>. This is <b>a second timex.</b></root>')
t1 = Timex()
t2 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', {t1}),
('text', 'POS', {t1}), ('.', 'POS', set())], [('This', 'POS', set()), ('is', 'POS', set()),
('a', 'POS', {t2}), ('second', 'POS', {t2}), ('timex.', 'POS', {t2})]], add_S='s')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root><s>This is <p>some</p> <TIMEX><p>annotated</p> <p>text</p></TIMEX>.</s> <s>This is <TIMEX><b>a second timex.</b></TIMEX></s></root>').toxml())
def test_reconcile_TIMEX_consecutive(self):
s = _XmlDocument('<root>This is <other>some annotated text</other> <TIMEX>and a second annotation</TIMEX>.</root>')
t2 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()),
('text', 'POS', set()), ('and', 'POS', {t2}), ('a', 'POS', {t2}), ('second', 'POS', {t2}),
('annotation', 'POS', {t2}), ('.', 'POS', set())]])
self.assertEqual(str(s), xml.dom.minidom.parseString('<root>This is <other>some annotated text</other> <TIMEX>and a second annotation</TIMEX>.</root>').toxml())
def test_reconcile_TIMEX_consecutive_timex(self):
s = _XmlDocument('<root>This is some annotated text and a second annotation.</root>')
t1 = Timex()
t2 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', {t1}),
('annotated', 'POS', {t1}), ('text', 'POS', {t1}), ('and', 'POS', {t2}),
('a', 'POS', {t2}), ('second', 'POS', {t2}), ('annotation', 'POS', {t2}), ('.', 'POS', set())]])
self.assertEqual(str(s), xml.dom.minidom.parseString('<root>This is <TIMEX>some annotated text</TIMEX> <TIMEX>and a second annotation</TIMEX>.</root>').toxml())
def test_create_from_sents(self):
s = _XmlDocument.create([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]])
self.assertEqual(str(s), xml.dom.minidom.parseString('<root>This is some annotated text. This is a second sentence.</root>').toxml())
def test_create_from_sents_with_offsets(self):
s = _XmlDocument.create([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]],
tok_offsets=[[2, 7, 11, 16, 28], [36, 41, 45, 46, 53]])
self.assertEqual(str(s), xml.dom.minidom.parseString('<root> This is some annotated text. This is asecond sentence.</root>').toxml())
def test_create_from_sents_with_offsets_tags(self):
sents = [[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()), ('annotated', 'POS', set()), ('text.', 'POS', set())],
[('This', 'POS', set()), ('is', 'POS', set()), ('a', 'POS', set()), ('second', 'POS', set()), ('sentence.', 'POS', set())]]
s = _XmlDocument.create(sents, tok_offsets=[[2, 7, 11, 16, 28], [36, 41, 45, 46, 53]], add_S='s', add_LEX='lex', pos_attr='pos')
self.assertEqual(str(s), xml.dom.minidom.parseString('<root> <s><lex pos="POS">This</lex> <lex pos="POS">is</lex> <lex pos="POS">some</lex> <lex pos="POS">annotated</lex> <lex pos="POS">text.</lex></s> <s><lex pos="POS">This</lex> <lex pos="POS">is</lex> <lex pos="POS">a</lex><lex pos="POS">second</lex> <lex pos="POS">sentence.</lex></s></root>').toxml())
self.assertEqual(sents, s.get_sents())
def test_parse_strip_and_reconcile(self):
s = _XmlDocument('<root>This is some <TIMEX>annotated</TIMEX> text.</root>')
s.strip_timexes()
t1 = Timex()
s.reconcile([[('This', 'POS', set()), ('is', 'POS', set()), ('some', 'POS', set()),
('annotated', 'POS', {t1}), ('text', 'POS', set()), ('.', 'POS', set())]])
self.assertEqual(str(s), xml.dom.minidom.parseString('<root>This is some <TIMEX>annotated</TIMEX> text.</root>').toxml())
| 85.355401
| 397
| 0.531779
| 3,287
| 24,497
| 3.881655
| 0.044113
| 0.080884
| 0.02508
| 0.03668
| 0.874206
| 0.857747
| 0.828592
| 0.794185
| 0.792303
| 0.767615
| 0
| 0.011088
| 0.190023
| 24,497
| 286
| 398
| 85.653846
| 0.631942
| 0.004327
| 0
| 0.32906
| 0
| 0.205128
| 0.376143
| 0.074999
| 0
| 0
| 0
| 0
| 0.192308
| 1
| 0.179487
| false
| 0.004274
| 0.017094
| 0.004274
| 0.217949
| 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
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
a76adbfa8b42dc30e3a84c564944c30c0dc17e5c
| 1,634
|
py
|
Python
|
tests/test_search.py
|
inimaz/Game
|
720f59ce66a48c3abf4968d10066716679773234
|
[
"BSD-2-Clause"
] | null | null | null |
tests/test_search.py
|
inimaz/Game
|
720f59ce66a48c3abf4968d10066716679773234
|
[
"BSD-2-Clause"
] | 1
|
2020-02-25T13:40:44.000Z
|
2020-02-25T13:40:44.000Z
|
tests/test_search.py
|
inimaz/Game
|
720f59ce66a48c3abf4968d10066716679773234
|
[
"BSD-2-Clause"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
This is to be run in the command line with
pytest *nameOfFile*
To run all
python -m pytest
or
py.test
if you would like to see details, use -v (verbose)
"""
#import sys
#import tests.context
#
#print(sys.path)
#tests.context.initialize()
#print(sys.path)
#
#from sample import helpers as h
#import numpy as np
#
##We define the variables
#current_player_id = 0
#n_players = 3
#h.g.initialize(n_players)
#world = np.array([[0,0,0],
# [1,2,1],
# [1,2,2]])
#
#
#def test_rand_num():
# assert h.rand_num() < 3
#
#def test_search():
# assert h.search(world,current_player_id,2,2) == -1
# assert h.search(world,current_player_id,0,2) == (1,2)
# -*- coding: utf-8 -*-
"""
This is to be run in the command line with
pytest *nameOfFile*
To run all
python -m pytest
or
py.test
if you would like to see details, use -v (verbose)
"""
import sys
import os
sys.path.insert(0, "C:\Users\iimazchacon\Documents\Python_projects\Game")
sys.path.insert(0, "C:\Users\iimazchacon\Documents\Python_projects\Game\sample")
import sample
from helpers import search,rand_num
import numpy as np
#We define the variables
current_player_id = 0
n_players = 3
initialize(n_players)
world = np.array([[0,0,0],
[1,2,1],
[1,2,2]])
def test_rand_num():
assert rand_num() < 3
def test_search():
assert search(world,current_player_id,2,2) == -1
assert search(world,current_player_id,0,2) == (1,2)
| 21.5
| 81
| 0.602203
| 248
| 1,634
| 3.858871
| 0.290323
| 0.081505
| 0.094044
| 0.066876
| 0.856844
| 0.856844
| 0.856844
| 0.798328
| 0.798328
| 0.662487
| 0
| 0.034913
| 0.26377
| 1,634
| 76
| 82
| 21.5
| 0.760599
| 0.347613
| 0
| 0
| 0
| 0
| 0.171384
| 0.171384
| 0
| 0
| 0
| 0
| 0.166667
| 0
| null | null | 0
| 0.277778
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
a77f3b5f9f7f7fa6024b348c897cefe4452f79b8
| 424,347
|
py
|
Python
|
breeze_resources.py
|
XLTools/BreezeStyleSheets
|
9ade91d4da1dd0eaf885793d61f8455ca08065d3
|
[
"MIT"
] | 42
|
2016-11-20T16:38:04.000Z
|
2018-12-16T10:39:19.000Z
|
breeze_resources.py
|
XLTools/BreezeStyleSheets
|
9ade91d4da1dd0eaf885793d61f8455ca08065d3
|
[
"MIT"
] | 7
|
2017-08-26T14:29:26.000Z
|
2018-12-20T00:00:44.000Z
|
breeze_resources.py
|
XLTools/BreezeStyleSheets
|
9ade91d4da1dd0eaf885793d61f8455ca08065d3
|
[
"MIT"
] | 13
|
2017-05-22T19:43:10.000Z
|
2018-12-03T13:04:35.000Z
|
# -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.15.2)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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qt_version = [int(v) for v in QtCore.qVersion().split('.')]
if qt_version < [5, 8, 0]:
rcc_version = 1
qt_resource_struct = qt_resource_struct_v1
else:
rcc_version = 2
qt_resource_struct = qt_resource_struct_v2
def qInitResources():
QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| 59.565834
| 129
| 0.72494
| 102,459
| 424,347
| 3.002059
| 0.002996
| 0.049313
| 0.034761
| 0.028441
| 0.780596
| 0.77687
| 0.775316
| 0.772917
| 0.772117
| 0.771191
| 0
| 0.404772
| 0.016993
| 424,347
| 7,123
| 130
| 59.574196
| 0.332609
| 0.000358
| 0
| 0.738005
| 0
| 0.867314
| 0.000002
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0.000281
| false
| 0
| 0.000141
| 0
| 0.000422
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| null | 1
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| 0
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| 0
| 0
| 0
| 0
|
0
| 10
|
a7b2561eed2fab83ab7a96f383a12200b02198dd
| 3,784
|
py
|
Python
|
src/Compiler/ASM/Codegen/expressions/objects.py
|
PetukhovVictor/compiler2
|
0bf87393ce9ecdd421393165fc14cb7f03f5e3b8
|
[
"MIT"
] | 3
|
2017-09-08T21:35:31.000Z
|
2019-04-24T11:48:59.000Z
|
src/Compiler/ASM/Codegen/expressions/objects.py
|
PetukhovVictor/compiler2
|
0bf87393ce9ecdd421393165fc14cb7f03f5e3b8
|
[
"MIT"
] | 1
|
2018-11-19T15:34:00.000Z
|
2018-11-19T15:35:52.000Z
|
src/Compiler/ASM/Codegen/expressions/objects.py
|
PetukhovVictor/compiler2
|
0bf87393ce9ecdd421393165fc14cb7f03f5e3b8
|
[
"MIT"
] | 4
|
2017-03-13T06:16:48.000Z
|
2019-04-24T11:49:00.000Z
|
from ...Core.types import Types
from ...Core.commands import Commands
from ...Core.registers import Registers
from copy import copy
from .call import call_statement as compile_call_statement
def object_val(compiler, node):
if node.object_name == 'this':
obj_var = compiler.environment.object_list[-1][0]
else:
if compiler.environment.current is not None:
obj_var = compiler.environment.get_object_name(compiler.environment.get_parent_local_var(node.object_name, as_object=False))
else:
obj_var = compiler.environment.get_object_name(compiler.environment.get_local_var(node.object_name))
if node.context == 'assign':
if node.object_name == 'this':
prop_var = compiler.environment.get_parent_local_var("var_%s_%s" % (obj_var, node.prop_name))
compiler.code.add(Commands.MOV, [Registers.EBX, "dword [%s]" % compiler.environment.object_list[-1][1]])
compiler.code.add(Commands.SUB, [Registers.EBX, prop_var['offset']])
compiler.code.add(Commands.POP, 'dword [%s]' % Registers.EBX)
else:
if compiler.environment.current is not None:
prop_var = compiler.environment.get_parent_local_var("var_%s_%s" % (obj_var, node.prop_name))
if prop_var is None:
prop_var = compiler.environment.add_parent_local_var(Types.INT, node.prop_name, object_namespace=obj_var)
compiler.code.add(Commands.MOV, [Registers.EBX, "dword [%s]" % compiler.environment.object_list[-1][1]])
compiler.code.add(Commands.SUB, [Registers.EBX, prop_var['offset']])
compiler.code.add(Commands.POP, ['dword [%s]' % Registers.EBX])
else:
prop_var = compiler.environment.get_local_var("var_%s_%s" % (obj_var, node.prop_name))
if prop_var is None:
prop_var = compiler.environment.add_local_var(Types.INT, node.prop_name, object_namespace=obj_var)
compiler.code.add(Commands.POP, prop_var)
else:
if node.object_name == 'this':
prop_var = compiler.environment.get_parent_local_var("var_%s_%s" % (obj_var, node.prop_name))
compiler.code.add(Commands.MOV, [Registers.EBX, "dword [%s]" % compiler.environment.object_list[-1][1]])
compiler.code.add(Commands.SUB, [Registers.EBX, prop_var['offset']])
compiler.code.add(Commands.PUSH, 'dword [%s]' % Registers.EBX)
else:
if compiler.environment.current is not None:
prop_var = compiler.environment.get_parent_local_var("var_%s_%s" % (obj_var, node.prop_name))
compiler.code.add(Commands.MOV, [Registers.EBX, "dword [%s]" % compiler.environment.object_list[-1][1]])
compiler.code.add(Commands.SUB, [Registers.EBX, prop_var['offset']])
compiler.code.add(Commands.PUSH, 'dword [%s]' % Registers.EBX)
else:
prop_var = compiler.environment.get_local_var("var_%s_%s" % (obj_var, node.prop_name))
compiler.code.add(Commands.PUSH, prop_var)
return compiler.types.set(Types.REFERENCE)
def object_method(compiler, node):
if node.object_name == 'this':
obj_var = compiler.environment.object_list[-1][0]
else:
if compiler.environment.current is not None:
obj_var = compiler.environment.get_object_name(compiler.environment.get_parent_local_var(node.object_name, as_object=False))
else:
obj_var = compiler.environment.get_object_name(compiler.environment.get_local_var(node.object_name))
new_node = copy(node)
new_node.name = "o%s!%s" % (obj_var, node.method_name)
return compile_call_statement(compiler, new_node)
| 53.295775
| 136
| 0.659884
| 498
| 3,784
| 4.7751
| 0.110442
| 0.207738
| 0.129521
| 0.135408
| 0.858284
| 0.850294
| 0.850294
| 0.850294
| 0.850294
| 0.850294
| 0
| 0.004038
| 0.214588
| 3,784
| 70
| 137
| 54.057143
| 0.796097
| 0
| 0
| 0.694915
| 0
| 0
| 0.049154
| 0
| 0
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| 0
| 1
| 0.033898
| false
| 0
| 0.084746
| 0
| 0.152542
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
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| 0
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| 0
| 0
| 0
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| 0
| null | 0
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| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
|
0
| 7
|
a7be7a3af92365f697ede862074fca84d0f28018
| 54,280
|
py
|
Python
|
src/evaluator/CodeBLEU/parser/DFG.py
|
natgen-team/NatGen
|
b1a7070caf3ff45cf2be1fc2196198e4e23cb30d
|
[
"MIT"
] | null | null | null |
src/evaluator/CodeBLEU/parser/DFG.py
|
natgen-team/NatGen
|
b1a7070caf3ff45cf2be1fc2196198e4e23cb30d
|
[
"MIT"
] | null | null | null |
src/evaluator/CodeBLEU/parser/DFG.py
|
natgen-team/NatGen
|
b1a7070caf3ff45cf2be1fc2196198e4e23cb30d
|
[
"MIT"
] | null | null | null |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from .utils import (tree_to_variable_index)
def DFG_python(root_node, index_to_code, states):
assignment = ['assignment', 'augmented_assignment', 'for_in_clause']
if_statement = ['if_statement']
for_statement = ['for_statement']
while_statement = ['while_statement']
do_first_statement = ['for_in_clause']
def_statement = ['default_parameter']
states = states.copy()
if (len(root_node.children) == 0 or root_node.type in ['string_literal', 'string',
'character_literal']) and root_node.type != 'comment':
idx, code = index_to_code[(root_node.start_point, root_node.end_point)]
if root_node.type == code:
return [], states
elif code in states:
return [(code, idx, 'comesFrom', [code], states[code].copy())], states
else:
if root_node.type == 'identifier':
states[code] = [idx]
return [(code, idx, 'comesFrom', [], [])], states
elif root_node.type in def_statement:
name = root_node.child_by_field_name('name')
value = root_node.child_by_field_name('value')
DFG = []
if value is None:
indexs = tree_to_variable_index(name, index_to_code)
for index in indexs:
idx, code = index_to_code[index]
DFG.append((code, idx, 'comesFrom', [], []))
states[code] = [idx]
return sorted(DFG, key=lambda x: x[1]), states
else:
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
temp, states = DFG_python(value, index_to_code, states)
DFG += temp
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'comesFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in assignment:
if root_node.type == 'for_in_clause':
right_nodes = [root_node.children[-1]]
left_nodes = [root_node.child_by_field_name('left')]
else:
if root_node.child_by_field_name('right') is None:
return [], states
left_nodes = [x for x in root_node.child_by_field_name('left').children if x.type != ',']
right_nodes = [x for x in root_node.child_by_field_name('right').children if x.type != ',']
if len(right_nodes) != len(left_nodes):
left_nodes = [root_node.child_by_field_name('left')]
right_nodes = [root_node.child_by_field_name('right')]
if len(left_nodes) == 0:
left_nodes = [root_node.child_by_field_name('left')]
if len(right_nodes) == 0:
right_nodes = [root_node.child_by_field_name('right')]
DFG = []
for node in right_nodes:
temp, states = DFG_python(node, index_to_code, states)
DFG += temp
for left_node, right_node in zip(left_nodes, right_nodes):
left_tokens_index = tree_to_variable_index(left_node, index_to_code)
right_tokens_index = tree_to_variable_index(right_node, index_to_code)
temp = []
for token1_index in left_tokens_index:
idx1, code1 = index_to_code[token1_index]
temp.append((code1, idx1, 'computedFrom', [index_to_code[x][1] for x in right_tokens_index],
[index_to_code[x][0] for x in right_tokens_index]))
states[code1] = [idx1]
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in if_statement:
DFG = []
current_states = states.copy()
others_states = []
tag = False
if 'else' in root_node.type:
tag = True
for child in root_node.children:
if 'else' in child.type:
tag = True
if child.type not in ['elif_clause', 'else_clause']:
temp, current_states = DFG_python(child, index_to_code, current_states)
DFG += temp
else:
temp, new_states = DFG_python(child, index_to_code, states)
DFG += temp
others_states.append(new_states)
others_states.append(current_states)
if tag is False:
others_states.append(states)
new_states = {}
for dic in others_states:
for key in dic:
if key not in new_states:
new_states[key] = dic[key].copy()
else:
new_states[key] += dic[key]
for key in new_states:
new_states[key] = sorted(list(set(new_states[key])))
return sorted(DFG, key=lambda x: x[1]), new_states
elif root_node.type in for_statement:
DFG = []
for i in range(2):
right_nodes = [x for x in root_node.child_by_field_name('right').children if x.type != ',']
left_nodes = [x for x in root_node.child_by_field_name('left').children if x.type != ',']
if len(right_nodes) != len(left_nodes):
left_nodes = [root_node.child_by_field_name('left')]
right_nodes = [root_node.child_by_field_name('right')]
if len(left_nodes) == 0:
left_nodes = [root_node.child_by_field_name('left')]
if len(right_nodes) == 0:
right_nodes = [root_node.child_by_field_name('right')]
for node in right_nodes:
temp, states = DFG_python(node, index_to_code, states)
DFG += temp
for left_node, right_node in zip(left_nodes, right_nodes):
left_tokens_index = tree_to_variable_index(left_node, index_to_code)
right_tokens_index = tree_to_variable_index(right_node, index_to_code)
temp = []
for token1_index in left_tokens_index:
idx1, code1 = index_to_code[token1_index]
temp.append((code1, idx1, 'computedFrom', [index_to_code[x][1] for x in right_tokens_index],
[index_to_code[x][0] for x in right_tokens_index]))
states[code1] = [idx1]
DFG += temp
if root_node.children[-1].type == "block":
temp, states = DFG_python(root_node.children[-1], index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in while_statement:
DFG = []
for i in range(2):
for child in root_node.children:
temp, states = DFG_python(child, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
else:
DFG = []
for child in root_node.children:
if child.type in do_first_statement:
temp, states = DFG_python(child, index_to_code, states)
DFG += temp
for child in root_node.children:
if child.type not in do_first_statement:
temp, states = DFG_python(child, index_to_code, states)
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
def DFG_java(root_node, index_to_code, states):
assignment = ['assignment_expression']
def_statement = ['variable_declarator']
increment_statement = ['update_expression']
if_statement = ['if_statement', 'else']
for_statement = ['for_statement']
enhanced_for_statement = ['enhanced_for_statement']
while_statement = ['while_statement']
do_first_statement = []
states = states.copy()
if (len(root_node.children) == 0 or root_node.type in ['string_literal', 'string',
'character_literal']) and root_node.type != 'comment':
idx, code = index_to_code[(root_node.start_point, root_node.end_point)]
if root_node.type == code:
return [], states
elif code in states:
return [(code, idx, 'comesFrom', [code], states[code].copy())], states
else:
if root_node.type == 'identifier':
states[code] = [idx]
return [(code, idx, 'comesFrom', [], [])], states
elif root_node.type in def_statement:
name = root_node.child_by_field_name('name')
value = root_node.child_by_field_name('value')
DFG = []
if value is None:
indexs = tree_to_variable_index(name, index_to_code)
for index in indexs:
idx, code = index_to_code[index]
DFG.append((code, idx, 'comesFrom', [], []))
states[code] = [idx]
return sorted(DFG, key=lambda x: x[1]), states
else:
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
temp, states = DFG_java(value, index_to_code, states)
DFG += temp
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'comesFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in assignment:
left_nodes = root_node.child_by_field_name('left')
right_nodes = root_node.child_by_field_name('right')
DFG = []
temp, states = DFG_java(right_nodes, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(left_nodes, index_to_code)
value_indexs = tree_to_variable_index(right_nodes, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in increment_statement:
DFG = []
indexs = tree_to_variable_index(root_node, index_to_code)
for index1 in indexs:
idx1, code1 = index_to_code[index1]
for index2 in indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in if_statement:
DFG = []
current_states = states.copy()
others_states = []
flag = False
tag = False
if 'else' in root_node.type:
tag = True
for child in root_node.children:
if 'else' in child.type:
tag = True
if child.type not in if_statement and flag is False:
temp, current_states = DFG_java(child, index_to_code, current_states)
DFG += temp
else:
flag = True
temp, new_states = DFG_java(child, index_to_code, states)
DFG += temp
others_states.append(new_states)
others_states.append(current_states)
if tag is False:
others_states.append(states)
new_states = {}
for dic in others_states:
for key in dic:
if key not in new_states:
new_states[key] = dic[key].copy()
else:
new_states[key] += dic[key]
for key in new_states:
new_states[key] = sorted(list(set(new_states[key])))
return sorted(DFG, key=lambda x: x[1]), new_states
elif root_node.type in for_statement:
DFG = []
for child in root_node.children:
temp, states = DFG_java(child, index_to_code, states)
DFG += temp
flag = False
for child in root_node.children:
if flag:
temp, states = DFG_java(child, index_to_code, states)
DFG += temp
elif child.type == "local_variable_declaration":
flag = True
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in enhanced_for_statement:
name = root_node.child_by_field_name('name')
value = root_node.child_by_field_name('value')
body = root_node.child_by_field_name('body')
DFG = []
for i in range(2):
temp, states = DFG_java(value, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
temp, states = DFG_java(body, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in while_statement:
DFG = []
for i in range(2):
for child in root_node.children:
temp, states = DFG_java(child, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
else:
DFG = []
for child in root_node.children:
if child.type in do_first_statement:
temp, states = DFG_java(child, index_to_code, states)
DFG += temp
for child in root_node.children:
if child.type not in do_first_statement:
temp, states = DFG_java(child, index_to_code, states)
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
def DFG_csharp(root_node, index_to_code, states):
assignment = ['assignment_expression']
def_statement = ['variable_declarator']
increment_statement = ['postfix_unary_expression']
if_statement = ['if_statement', 'else']
for_statement = ['for_statement']
enhanced_for_statement = ['for_each_statement']
while_statement = ['while_statement']
do_first_statement = []
states = states.copy()
if (len(root_node.children) == 0 or root_node.type in ['string_literal', 'string',
'character_literal']) and root_node.type != 'comment':
idx, code = index_to_code[(root_node.start_point, root_node.end_point)]
if root_node.type == code:
return [], states
elif code in states:
return [(code, idx, 'comesFrom', [code], states[code].copy())], states
else:
if root_node.type == 'identifier':
states[code] = [idx]
return [(code, idx, 'comesFrom', [], [])], states
elif root_node.type in def_statement:
if len(root_node.children) == 2:
name = root_node.children[0]
value = root_node.children[1]
else:
name = root_node.children[0]
value = None
DFG = []
if value is None:
indexs = tree_to_variable_index(name, index_to_code)
for index in indexs:
idx, code = index_to_code[index]
DFG.append((code, idx, 'comesFrom', [], []))
states[code] = [idx]
return sorted(DFG, key=lambda x: x[1]), states
else:
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
temp, states = DFG_csharp(value, index_to_code, states)
DFG += temp
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'comesFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in assignment:
left_nodes = root_node.child_by_field_name('left')
right_nodes = root_node.child_by_field_name('right')
DFG = []
temp, states = DFG_csharp(right_nodes, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(left_nodes, index_to_code)
value_indexs = tree_to_variable_index(right_nodes, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in increment_statement:
DFG = []
indexs = tree_to_variable_index(root_node, index_to_code)
for index1 in indexs:
idx1, code1 = index_to_code[index1]
for index2 in indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in if_statement:
DFG = []
current_states = states.copy()
others_states = []
flag = False
tag = False
if 'else' in root_node.type:
tag = True
for child in root_node.children:
if 'else' in child.type:
tag = True
if child.type not in if_statement and flag is False:
temp, current_states = DFG_csharp(child, index_to_code, current_states)
DFG += temp
else:
flag = True
temp, new_states = DFG_csharp(child, index_to_code, states)
DFG += temp
others_states.append(new_states)
others_states.append(current_states)
if tag is False:
others_states.append(states)
new_states = {}
for dic in others_states:
for key in dic:
if key not in new_states:
new_states[key] = dic[key].copy()
else:
new_states[key] += dic[key]
for key in new_states:
new_states[key] = sorted(list(set(new_states[key])))
return sorted(DFG, key=lambda x: x[1]), new_states
elif root_node.type in for_statement:
DFG = []
for child in root_node.children:
temp, states = DFG_csharp(child, index_to_code, states)
DFG += temp
flag = False
for child in root_node.children:
if flag:
temp, states = DFG_csharp(child, index_to_code, states)
DFG += temp
elif child.type == "local_variable_declaration":
flag = True
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in enhanced_for_statement:
name = root_node.child_by_field_name('left')
value = root_node.child_by_field_name('right')
body = root_node.child_by_field_name('body')
DFG = []
for i in range(2):
temp, states = DFG_csharp(value, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
temp, states = DFG_csharp(body, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in while_statement:
DFG = []
for i in range(2):
for child in root_node.children:
temp, states = DFG_csharp(child, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
else:
DFG = []
for child in root_node.children:
if child.type in do_first_statement:
temp, states = DFG_csharp(child, index_to_code, states)
DFG += temp
for child in root_node.children:
if child.type not in do_first_statement:
temp, states = DFG_csharp(child, index_to_code, states)
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
def DFG_ruby(root_node, index_to_code, states):
assignment = ['assignment', 'operator_assignment']
if_statement = ['if', 'elsif', 'else', 'unless', 'when']
for_statement = ['for']
while_statement = ['while_modifier', 'until']
do_first_statement = []
def_statement = ['keyword_parameter']
if (len(root_node.children) == 0 or root_node.type in ['string_literal', 'string',
'character_literal']) and root_node.type != 'comment':
states = states.copy()
idx, code = index_to_code[(root_node.start_point, root_node.end_point)]
if root_node.type == code:
return [], states
elif code in states:
return [(code, idx, 'comesFrom', [code], states[code].copy())], states
else:
if root_node.type == 'identifier':
states[code] = [idx]
return [(code, idx, 'comesFrom', [], [])], states
elif root_node.type in def_statement:
name = root_node.child_by_field_name('name')
value = root_node.child_by_field_name('value')
DFG = []
if value is None:
indexs = tree_to_variable_index(name, index_to_code)
for index in indexs:
idx, code = index_to_code[index]
DFG.append((code, idx, 'comesFrom', [], []))
states[code] = [idx]
return sorted(DFG, key=lambda x: x[1]), states
else:
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
temp, states = DFG_ruby(value, index_to_code, states)
DFG += temp
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'comesFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in assignment:
left_nodes = [x for x in root_node.child_by_field_name('left').children if x.type != ',']
right_nodes = [x for x in root_node.child_by_field_name('right').children if x.type != ',']
if len(right_nodes) != len(left_nodes):
left_nodes = [root_node.child_by_field_name('left')]
right_nodes = [root_node.child_by_field_name('right')]
if len(left_nodes) == 0:
left_nodes = [root_node.child_by_field_name('left')]
if len(right_nodes) == 0:
right_nodes = [root_node.child_by_field_name('right')]
if root_node.type == "operator_assignment":
left_nodes = [root_node.children[0]]
right_nodes = [root_node.children[-1]]
DFG = []
for node in right_nodes:
temp, states = DFG_ruby(node, index_to_code, states)
DFG += temp
for left_node, right_node in zip(left_nodes, right_nodes):
left_tokens_index = tree_to_variable_index(left_node, index_to_code)
right_tokens_index = tree_to_variable_index(right_node, index_to_code)
temp = []
for token1_index in left_tokens_index:
idx1, code1 = index_to_code[token1_index]
temp.append((code1, idx1, 'computedFrom', [index_to_code[x][1] for x in right_tokens_index],
[index_to_code[x][0] for x in right_tokens_index]))
states[code1] = [idx1]
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in if_statement:
DFG = []
current_states = states.copy()
others_states = []
tag = False
if 'else' in root_node.type:
tag = True
for child in root_node.children:
if 'else' in child.type:
tag = True
if child.type not in if_statement:
temp, current_states = DFG_ruby(child, index_to_code, current_states)
DFG += temp
else:
temp, new_states = DFG_ruby(child, index_to_code, states)
DFG += temp
others_states.append(new_states)
others_states.append(current_states)
if tag is False:
others_states.append(states)
new_states = {}
for dic in others_states:
for key in dic:
if key not in new_states:
new_states[key] = dic[key].copy()
else:
new_states[key] += dic[key]
for key in new_states:
new_states[key] = sorted(list(set(new_states[key])))
return sorted(DFG, key=lambda x: x[1]), new_states
elif root_node.type in for_statement:
DFG = []
for i in range(2):
left_nodes = [root_node.child_by_field_name('pattern')]
right_nodes = [root_node.child_by_field_name('value')]
assert len(right_nodes) == len(left_nodes)
for node in right_nodes:
temp, states = DFG_ruby(node, index_to_code, states)
DFG += temp
for left_node, right_node in zip(left_nodes, right_nodes):
left_tokens_index = tree_to_variable_index(left_node, index_to_code)
right_tokens_index = tree_to_variable_index(right_node, index_to_code)
temp = []
for token1_index in left_tokens_index:
idx1, code1 = index_to_code[token1_index]
temp.append((code1, idx1, 'computedFrom', [index_to_code[x][1] for x in right_tokens_index],
[index_to_code[x][0] for x in right_tokens_index]))
states[code1] = [idx1]
DFG += temp
temp, states = DFG_ruby(root_node.child_by_field_name('body'), index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in while_statement:
DFG = []
for i in range(2):
for child in root_node.children:
temp, states = DFG_ruby(child, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
else:
DFG = []
for child in root_node.children:
if child.type in do_first_statement:
temp, states = DFG_ruby(child, index_to_code, states)
DFG += temp
for child in root_node.children:
if child.type not in do_first_statement:
temp, states = DFG_ruby(child, index_to_code, states)
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
def DFG_go(root_node, index_to_code, states):
assignment = ['assignment_statement', ]
def_statement = ['var_spec']
increment_statement = ['inc_statement']
if_statement = ['if_statement', 'else']
for_statement = ['for_statement']
enhanced_for_statement = []
while_statement = []
do_first_statement = []
states = states.copy()
if (len(root_node.children) == 0 or root_node.type in ['string_literal', 'string',
'character_literal']) and root_node.type != 'comment':
idx, code = index_to_code[(root_node.start_point, root_node.end_point)]
if root_node.type == code:
return [], states
elif code in states:
return [(code, idx, 'comesFrom', [code], states[code].copy())], states
else:
if root_node.type == 'identifier':
states[code] = [idx]
return [(code, idx, 'comesFrom', [], [])], states
elif root_node.type in def_statement:
name = root_node.child_by_field_name('name')
value = root_node.child_by_field_name('value')
DFG = []
if value is None:
indexs = tree_to_variable_index(name, index_to_code)
for index in indexs:
idx, code = index_to_code[index]
DFG.append((code, idx, 'comesFrom', [], []))
states[code] = [idx]
return sorted(DFG, key=lambda x: x[1]), states
else:
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
temp, states = DFG_go(value, index_to_code, states)
DFG += temp
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'comesFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in assignment:
left_nodes = root_node.child_by_field_name('left')
right_nodes = root_node.child_by_field_name('right')
DFG = []
temp, states = DFG_go(right_nodes, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(left_nodes, index_to_code)
value_indexs = tree_to_variable_index(right_nodes, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in increment_statement:
DFG = []
indexs = tree_to_variable_index(root_node, index_to_code)
for index1 in indexs:
idx1, code1 = index_to_code[index1]
for index2 in indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in if_statement:
DFG = []
current_states = states.copy()
others_states = []
flag = False
tag = False
if 'else' in root_node.type:
tag = True
for child in root_node.children:
if 'else' in child.type:
tag = True
if child.type not in if_statement and flag is False:
temp, current_states = DFG_go(child, index_to_code, current_states)
DFG += temp
else:
flag = True
temp, new_states = DFG_go(child, index_to_code, states)
DFG += temp
others_states.append(new_states)
others_states.append(current_states)
if tag is False:
others_states.append(states)
new_states = {}
for dic in others_states:
for key in dic:
if key not in new_states:
new_states[key] = dic[key].copy()
else:
new_states[key] += dic[key]
for key in states:
if key not in new_states:
new_states[key] = states[key]
else:
new_states[key] += states[key]
for key in new_states:
new_states[key] = sorted(list(set(new_states[key])))
return sorted(DFG, key=lambda x: x[1]), new_states
elif root_node.type in for_statement:
DFG = []
for child in root_node.children:
temp, states = DFG_go(child, index_to_code, states)
DFG += temp
flag = False
for child in root_node.children:
if flag:
temp, states = DFG_go(child, index_to_code, states)
DFG += temp
elif child.type == "for_clause":
if child.child_by_field_name('update') is not None:
temp, states = DFG_go(child.child_by_field_name('update'), index_to_code, states)
DFG += temp
flag = True
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
else:
DFG = []
for child in root_node.children:
if child.type in do_first_statement:
temp, states = DFG_go(child, index_to_code, states)
DFG += temp
for child in root_node.children:
if child.type not in do_first_statement:
temp, states = DFG_go(child, index_to_code, states)
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
def DFG_php(root_node, index_to_code, states):
assignment = ['assignment_expression', 'augmented_assignment_expression']
def_statement = ['simple_parameter']
increment_statement = ['update_expression']
if_statement = ['if_statement', 'else_clause']
for_statement = ['for_statement']
enhanced_for_statement = ['foreach_statement']
while_statement = ['while_statement']
do_first_statement = []
states = states.copy()
if (len(root_node.children) == 0 or root_node.type in ['string_literal', 'string',
'character_literal']) and root_node.type != 'comment':
idx, code = index_to_code[(root_node.start_point, root_node.end_point)]
if root_node.type == code:
return [], states
elif code in states:
return [(code, idx, 'comesFrom', [code], states[code].copy())], states
else:
if root_node.type == 'identifier':
states[code] = [idx]
return [(code, idx, 'comesFrom', [], [])], states
elif root_node.type in def_statement:
name = root_node.child_by_field_name('name')
value = root_node.child_by_field_name('default_value')
DFG = []
if value is None:
indexs = tree_to_variable_index(name, index_to_code)
for index in indexs:
idx, code = index_to_code[index]
DFG.append((code, idx, 'comesFrom', [], []))
states[code] = [idx]
return sorted(DFG, key=lambda x: x[1]), states
else:
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
temp, states = DFG_php(value, index_to_code, states)
DFG += temp
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'comesFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in assignment:
left_nodes = root_node.child_by_field_name('left')
right_nodes = root_node.child_by_field_name('right')
DFG = []
temp, states = DFG_php(right_nodes, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(left_nodes, index_to_code)
value_indexs = tree_to_variable_index(right_nodes, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in increment_statement:
DFG = []
indexs = tree_to_variable_index(root_node, index_to_code)
for index1 in indexs:
idx1, code1 = index_to_code[index1]
for index2 in indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in if_statement:
DFG = []
current_states = states.copy()
others_states = []
flag = False
tag = False
if 'else' in root_node.type:
tag = True
for child in root_node.children:
if 'else' in child.type:
tag = True
if child.type not in if_statement and flag is False:
temp, current_states = DFG_php(child, index_to_code, current_states)
DFG += temp
else:
flag = True
temp, new_states = DFG_php(child, index_to_code, states)
DFG += temp
others_states.append(new_states)
others_states.append(current_states)
new_states = {}
for dic in others_states:
for key in dic:
if key not in new_states:
new_states[key] = dic[key].copy()
else:
new_states[key] += dic[key]
for key in states:
if key not in new_states:
new_states[key] = states[key]
else:
new_states[key] += states[key]
for key in new_states:
new_states[key] = sorted(list(set(new_states[key])))
return sorted(DFG, key=lambda x: x[1]), new_states
elif root_node.type in for_statement:
DFG = []
for child in root_node.children:
temp, states = DFG_php(child, index_to_code, states)
DFG += temp
flag = False
for child in root_node.children:
if flag:
temp, states = DFG_php(child, index_to_code, states)
DFG += temp
elif child.type == "assignment_expression":
flag = True
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in enhanced_for_statement:
name = None
value = None
for child in root_node.children:
if child.type == 'variable_name' and value is None:
value = child
elif child.type == 'variable_name' and name is None:
name = child
break
body = root_node.child_by_field_name('body')
DFG = []
for i in range(2):
temp, states = DFG_php(value, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
temp, states = DFG_php(body, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in while_statement:
DFG = []
for i in range(2):
for child in root_node.children:
temp, states = DFG_php(child, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
else:
DFG = []
for child in root_node.children:
if child.type in do_first_statement:
temp, states = DFG_php(child, index_to_code, states)
DFG += temp
for child in root_node.children:
if child.type not in do_first_statement:
temp, states = DFG_php(child, index_to_code, states)
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
def DFG_javascript(root_node, index_to_code, states):
assignment = ['assignment_pattern', 'augmented_assignment_expression']
def_statement = ['variable_declarator']
increment_statement = ['update_expression']
if_statement = ['if_statement', 'else']
for_statement = ['for_statement']
enhanced_for_statement = []
while_statement = ['while_statement']
do_first_statement = []
states = states.copy()
if (len(root_node.children) == 0 or root_node.type in ['string_literal', 'string',
'character_literal']) and root_node.type != 'comment':
idx, code = index_to_code[(root_node.start_point, root_node.end_point)]
if root_node.type == code:
return [], states
elif code in states:
return [(code, idx, 'comesFrom', [code], states[code].copy())], states
else:
if root_node.type == 'identifier':
states[code] = [idx]
return [(code, idx, 'comesFrom', [], [])], states
elif root_node.type in def_statement:
name = root_node.child_by_field_name('name')
value = root_node.child_by_field_name('value')
DFG = []
if value is None:
indexs = tree_to_variable_index(name, index_to_code)
for index in indexs:
idx, code = index_to_code[index]
DFG.append((code, idx, 'comesFrom', [], []))
states[code] = [idx]
return sorted(DFG, key=lambda x: x[1]), states
else:
name_indexs = tree_to_variable_index(name, index_to_code)
value_indexs = tree_to_variable_index(value, index_to_code)
temp, states = DFG_javascript(value, index_to_code, states)
DFG += temp
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'comesFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in assignment:
left_nodes = root_node.child_by_field_name('left')
right_nodes = root_node.child_by_field_name('right')
DFG = []
temp, states = DFG_javascript(right_nodes, index_to_code, states)
DFG += temp
name_indexs = tree_to_variable_index(left_nodes, index_to_code)
value_indexs = tree_to_variable_index(right_nodes, index_to_code)
for index1 in name_indexs:
idx1, code1 = index_to_code[index1]
for index2 in value_indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in increment_statement:
DFG = []
indexs = tree_to_variable_index(root_node, index_to_code)
for index1 in indexs:
idx1, code1 = index_to_code[index1]
for index2 in indexs:
idx2, code2 = index_to_code[index2]
DFG.append((code1, idx1, 'computedFrom', [code2], [idx2]))
states[code1] = [idx1]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in if_statement:
DFG = []
current_states = states.copy()
others_states = []
flag = False
tag = False
if 'else' in root_node.type:
tag = True
for child in root_node.children:
if 'else' in child.type:
tag = True
if child.type not in if_statement and flag is False:
temp, current_states = DFG_javascript(child, index_to_code, current_states)
DFG += temp
else:
flag = True
temp, new_states = DFG_javascript(child, index_to_code, states)
DFG += temp
others_states.append(new_states)
others_states.append(current_states)
if tag is False:
others_states.append(states)
new_states = {}
for dic in others_states:
for key in dic:
if key not in new_states:
new_states[key] = dic[key].copy()
else:
new_states[key] += dic[key]
for key in states:
if key not in new_states:
new_states[key] = states[key]
else:
new_states[key] += states[key]
for key in new_states:
new_states[key] = sorted(list(set(new_states[key])))
return sorted(DFG, key=lambda x: x[1]), new_states
elif root_node.type in for_statement:
DFG = []
for child in root_node.children:
temp, states = DFG_javascript(child, index_to_code, states)
DFG += temp
flag = False
for child in root_node.children:
if flag:
temp, states = DFG_javascript(child, index_to_code, states)
DFG += temp
elif child.type == "variable_declaration":
flag = True
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
elif root_node.type in while_statement:
DFG = []
for i in range(2):
for child in root_node.children:
temp, states = DFG_javascript(child, index_to_code, states)
DFG += temp
dic = {}
for x in DFG:
if (x[0], x[1], x[2]) not in dic:
dic[(x[0], x[1], x[2])] = [x[3], x[4]]
else:
dic[(x[0], x[1], x[2])][0] = list(set(dic[(x[0], x[1], x[2])][0] + x[3]))
dic[(x[0], x[1], x[2])][1] = sorted(list(set(dic[(x[0], x[1], x[2])][1] + x[4])))
DFG = [(x[0], x[1], x[2], y[0], y[1]) for x, y in sorted(dic.items(), key=lambda t: t[0][1])]
return sorted(DFG, key=lambda x: x[1]), states
else:
DFG = []
for child in root_node.children:
if child.type in do_first_statement:
temp, states = DFG_javascript(child, index_to_code, states)
DFG += temp
for child in root_node.children:
if child.type not in do_first_statement:
temp, states = DFG_javascript(child, index_to_code, states)
DFG += temp
return sorted(DFG, key=lambda x: x[1]), states
| 45.883347
| 113
| 0.538965
| 7,321
| 54,280
| 3.784319
| 0.01844
| 0.060928
| 0.076232
| 0.01617
| 0.967118
| 0.961595
| 0.954918
| 0.947085
| 0.93817
| 0.929219
| 0
| 0.025937
| 0.334451
| 54,280
| 1,182
| 114
| 45.922166
| 0.740962
| 0.001271
| 0
| 0.928139
| 0
| 0
| 0.039514
| 0.004501
| 0
| 0
| 0
| 0
| 0.000866
| 1
| 0.006061
| false
| 0
| 0.000866
| 0
| 0.074459
| 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
|
ac35f0087ae4a3ba86b9038b96557d61f8b361db
| 226
|
py
|
Python
|
common/models/__init__.py
|
littleweaver/wagtail-project-template
|
34d9b2f659fab2c530902b650e2fc76410b8a22f
|
[
"BSD-3-Clause"
] | 12
|
2018-04-20T20:06:48.000Z
|
2022-03-23T08:11:11.000Z
|
common/models/__init__.py
|
littleweaver/wagtail-project-template
|
34d9b2f659fab2c530902b650e2fc76410b8a22f
|
[
"BSD-3-Clause"
] | 16
|
2018-03-09T22:30:35.000Z
|
2021-09-07T23:36:05.000Z
|
common/models/__init__.py
|
littleweaver/wagtail-project-template
|
34d9b2f659fab2c530902b650e2fc76410b8a22f
|
[
"BSD-3-Clause"
] | 1
|
2019-08-02T20:17:35.000Z
|
2019-08-02T20:17:35.000Z
|
from common.models.customimage import * # noqa: F403, F401
from common.models.pages import * # noqa: F403, F401
from common.models.mixins import * # noqa: F403, F401
from common.models.settings import * # noqa: F403, F401
| 45.2
| 59
| 0.734513
| 32
| 226
| 5.1875
| 0.34375
| 0.240964
| 0.385542
| 0.433735
| 0.614458
| 0.614458
| 0.614458
| 0
| 0
| 0
| 0
| 0.126316
| 0.159292
| 226
| 4
| 60
| 56.5
| 0.747368
| 0.29646
| 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
|
ac6dd898df1b8a5fd4234c88dfb32eccd6db41b1
| 105
|
py
|
Python
|
fixed_vhd_writer/__init__.py
|
fujiawei-dev/fixed-vhd-writer
|
c3fcc53ae79313b7be44200a0172fbd55c619620
|
[
"MIT"
] | null | null | null |
fixed_vhd_writer/__init__.py
|
fujiawei-dev/fixed-vhd-writer
|
c3fcc53ae79313b7be44200a0172fbd55c619620
|
[
"MIT"
] | null | null | null |
fixed_vhd_writer/__init__.py
|
fujiawei-dev/fixed-vhd-writer
|
c3fcc53ae79313b7be44200a0172fbd55c619620
|
[
"MIT"
] | null | null | null |
'''
Date: 2022.02.04 21:34
Description: Omit
LastEditors: Rustle Karl
LastEditTime: 2022.02.04 21:34
'''
| 15
| 30
| 0.72381
| 17
| 105
| 4.470588
| 0.705882
| 0.157895
| 0.210526
| 0.263158
| 0.315789
| 0
| 0
| 0
| 0
| 0
| 0
| 0.26087
| 0.12381
| 105
| 6
| 31
| 17.5
| 0.565217
| 0.914286
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 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
|
ac7423033cf34eca20ea561b58ba6cbfb9e67bf6
| 3,556
|
py
|
Python
|
tests/test_logging_helpers_test.py
|
gift-surg/puma
|
58beae3459a0c8d96adfe9af323e26868428df4d
|
[
"Apache-2.0"
] | null | null | null |
tests/test_logging_helpers_test.py
|
gift-surg/puma
|
58beae3459a0c8d96adfe9af323e26868428df4d
|
[
"Apache-2.0"
] | 13
|
2020-05-04T14:14:58.000Z
|
2020-07-29T16:37:03.000Z
|
tests/test_logging_helpers_test.py
|
gift-surg/puma
|
58beae3459a0c8d96adfe9af323e26868428df4d
|
[
"Apache-2.0"
] | null | null | null |
import logging
from unittest import TestCase
from puma.helpers.testing.logging.decorator import assert_no_warnings_or_errors_logged
logger = logging.getLogger(__name__)
class TestLoggingHelpersTest(TestCase):
@assert_no_warnings_or_errors_logged
def test_assert_no_warnings_or_errors_logged_decorator_when_debug(self) -> None:
logger.debug("No problem")
@assert_no_warnings_or_errors_logged
def test_assert_no_warnings_or_errors_logged_decorator_when_debug_root(self) -> None:
logging.debug("No problem")
def test_assert_no_warnings_or_errors_logged_decorator_when_warning(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
self._should_assert_because_of_warning()
def test_assert_no_warnings_or_errors_logged_decorator_when_warning_root(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
self._should_assert_because_of_warning_root()
def test_assert_no_warnings_or_errors_logged_decorator_when_error(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
self._should_assert_because_of_error()
def test_assert_no_warnings_or_errors_logged_decorator_when_error_root(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
self._should_assert_because_of_error_root()
def test_assert_no_warnings_or_errors_logged_function_when_debug(self) -> None:
with assert_no_warnings_or_errors_logged(self):
logger.debug("No problem")
def test_assert_no_warnings_or_errors_logged_function_when_debug_root(self) -> None:
with assert_no_warnings_or_errors_logged(self):
logging.debug("No problem")
def test_assert_no_warnings_or_errors_logged_function_when_warning(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
with assert_no_warnings_or_errors_logged(self):
logger.warning("Problem")
def test_assert_no_warnings_or_errors_logged_function_when_warning_root(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
with assert_no_warnings_or_errors_logged(self):
logging.warning("Problem")
def test_assert_no_warnings_or_errors_logged_function_when_error(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
with assert_no_warnings_or_errors_logged(self):
logger.error("Big Problem")
def test_assert_no_warnings_or_errors_logged_function_when_error_root(self) -> None:
with self.assertRaisesRegex(AssertionError, "Unexpectedly raised warnings or errors"):
with assert_no_warnings_or_errors_logged(self):
logging.error("Big Problem")
@assert_no_warnings_or_errors_logged
def _should_assert_because_of_warning(self) -> None:
logger.warning("Problem")
@assert_no_warnings_or_errors_logged
def _should_assert_because_of_warning_root(self) -> None:
logging.warning("Problem")
@assert_no_warnings_or_errors_logged
def _should_assert_because_of_error(self) -> None:
logger.error("Big Problem")
@assert_no_warnings_or_errors_logged
def _should_assert_because_of_error_root(self) -> None:
logging.error("Big Problem")
| 46.181818
| 94
| 0.764061
| 448
| 3,556
| 5.558036
| 0.089286
| 0.13253
| 0.212048
| 0.180723
| 0.901205
| 0.894779
| 0.879518
| 0.879518
| 0.876707
| 0.871084
| 0
| 0
| 0.167604
| 3,556
| 76
| 95
| 46.789474
| 0.841216
| 0
| 0
| 0.561404
| 0
| 0
| 0.116985
| 0
| 0
| 0
| 0
| 0
| 0.719298
| 1
| 0.280702
| false
| 0
| 0.052632
| 0
| 0.350877
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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0
| 10
|
3bcba087b53458dfbd4e83bf8c4d4fe2d510e802
| 61,426
|
py
|
Python
|
tests/interactions/test_interactions.py
|
cad106uk/market-access-api
|
a357c33bbec93408b193e598a5628634126e9e99
|
[
"MIT"
] | null | null | null |
tests/interactions/test_interactions.py
|
cad106uk/market-access-api
|
a357c33bbec93408b193e598a5628634126e9e99
|
[
"MIT"
] | null | null | null |
tests/interactions/test_interactions.py
|
cad106uk/market-access-api
|
a357c33bbec93408b193e598a5628634126e9e99
|
[
"MIT"
] | null | null | null |
import json
import uuid
import pytest
from rest_framework import status
from rest_framework.reverse import reverse
from rest_framework.test import APITestCase
from api.core.test_utils import APITestMixin
from api.interactions.models import Document
from tests.barriers.factories import ReportFactory
class TestListInteractions(APITestMixin, APITestCase):
def _submit_report(self, report):
url = reverse("submit-report", kwargs={"pk": report.id})
return self.api_client.put(url, format="json", data={})
def setUp(self):
# NULL next_steps_summary as that creates an interaction when the report is submitted
self.report = ReportFactory(next_steps_summary="")
def test_no_interactions(self):
"""Test there are no barrier interactions using list"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
response = self.api_client.get(interactions_url)
assert response.status_code == status.HTTP_200_OK
assert response.data["count"] == 0
def test_add_interactions_no_pin(self):
"""Test there is one interaction without pinning"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "sample interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is False
assert int_response.data["results"][0]["is_active"] is True
def test_add_interactions_pinned(self):
"""Test there are one interaction with pinning"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "pinned": True},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is True
assert int_response.data["results"][0]["is_active"] is True
def test_add_interactions_multiple(self):
"""Test multiple interactions for barrier"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "first interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "second interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 2
def test_add_interactions_multiple_mixed_pinning(self):
"""Test multiple interactions with mixed pinning"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "first interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "second interaction notes", "pinned": True},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 2
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "third interaction notes", "pinned": False},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 3
def test_get_interaction(self):
"""Test retreiving an interaction"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "sample interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is False
assert int_response.data["results"][0]["is_active"] is True
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
def test_edit_interaction(self):
"""Test editing an interaction"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "sample interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is False
assert int_response.data["results"][0]["is_active"] is True
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
edit_int_response = self.api_client.put(
get_interaction_url,
format="json",
data={"text": "edited interaction notes"},
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "edited interaction notes"
def test_edit_interaction_pin_it(self):
"""Test edit interaction with pinning"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "sample interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is False
assert int_response.data["results"][0]["is_active"] is True
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
edit_int_response = self.api_client.put(
get_interaction_url, format="json", data={"pinned": True}
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["pinned"] is True
def test_edit_interaction_unpin_it(self):
"""Test edit interaction un pin it"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "pinned": True},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is True
assert int_response.data["results"][0]["is_active"] is True
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is True
assert get_int_response.data["is_active"] is True
edit_int_response = self.api_client.put(
get_interaction_url, format="json", data={"pinned": False}
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["pinned"] is False
def test_add_document(self):
"""Test add a new document, ready to be attached to an interaction"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
assert docs_list_report_response.data["original_filename"] == "somefile.pdf"
assert docs_list_report_response.data["id"] is not None
assert docs_list_report_response.data["size"] is None
assert docs_list_report_response.data["mime_type"] == ""
assert docs_list_report_response.data["url"] is not None
assert docs_list_report_response.data["status"] == "not_virus_scanned"
assert docs_list_report_response.data["signed_upload_url"] is not None
def test_add_document_with_size(self):
"""Test add a document with size"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url,
format="json",
data={"original_filename": "somefile.pdf", "size": 2},
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
assert docs_list_report_response.data["original_filename"] == "somefile.pdf"
assert docs_list_report_response.data["id"] is not None
assert docs_list_report_response.data["size"] == 2
assert docs_list_report_response.data["mime_type"] == ""
assert docs_list_report_response.data["url"] is not None
assert docs_list_report_response.data["status"] == "not_virus_scanned"
assert docs_list_report_response.data["signed_upload_url"] is not None
@pytest.mark.skip(reason="it was not being picked up by the runner due to the leading _")
def test_add_document_with__size_mime_type(self):
"""Test add a document with size and mime type"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url,
format="json",
data={"original_filename": "somefile.pdf", "size": 2, "mine_type": "mime"},
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
assert docs_list_report_response.data["original_filename"] == "somefile.pdf"
assert docs_list_report_response.data["id"] is not None
assert docs_list_report_response.data["size"] == 2
assert docs_list_report_response.data["mime_type"] == "mime"
assert docs_list_report_response.data["url"] is not None
assert docs_list_report_response.data["status"] == "not_virus_scanned"
assert docs_list_report_response.data["signed_upload_url"] is not None
def test_add_interactions_with_document(self):
"""Test add interaction with a document"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "documents": [document_id]},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(document_id)
def test_add_interactions_with_clear_documents(self):
"""Test add interaction with documents and edit to clear them"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "documents": [document_id]},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(document_id)
edit_int_response = self.api_client.put(
get_interaction_url, format="json", data={"documents": []}
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["documents"] == []
def test_add_interactions_change_document(self):
"""Test add interaction with document and edit to change document"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
somefile_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "anotherfile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
anotherfile_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "documents": [somefile_id]},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(somefile_id)
edit_int_response = self.api_client.put(
get_interaction_url, format="json", data={"documents": [anotherfile_id]}
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(anotherfile_id)
def test_add_interactions_with_multiple_documents(self):
"""Test add an interaction with multiple documents"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
somefile_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "otherfile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
otherfile_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={
"text": "sample interaction notes",
"documents": [somefile_id, otherfile_id],
},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(somefile_id)
assert get_int_response.data["documents"][1]["id"] == uuid.UUID(otherfile_id)
def test_add_interactions_change_multiple_documents(self):
"""Test add an interaction with multiple documents and change them to be different"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file1.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file1_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file2.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file2_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file3.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file3_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file4.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file4_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={
"text": "sample interaction notes",
"documents": [file1_id, file2_id],
},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(file1_id)
assert get_int_response.data["documents"][1]["id"] == uuid.UUID(file2_id)
edit_int_response = self.api_client.put(
get_interaction_url, format="json", data={"documents": [file3_id, file4_id]}
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(file3_id)
assert get_int_response.data["documents"][1]["id"] == uuid.UUID(file4_id)
def test_add_interactions_change_add_another_document(self):
"""Test add interaction with a document and edit to add one more document"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file1.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file1_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file2.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file2_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file3.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file3_id = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "file4.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
file4_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={
"text": "sample interaction notes",
"documents": [file1_id, file2_id],
},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(file1_id)
assert get_int_response.data["documents"][1]["id"] == uuid.UUID(file2_id)
edit_int_response = self.api_client.put(
get_interaction_url,
format="json",
data={"documents": [file1_id, file2_id, file3_id, file4_id]},
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(file1_id)
assert get_int_response.data["documents"][1]["id"] == uuid.UUID(file2_id)
assert get_int_response.data["documents"][2]["id"] == uuid.UUID(file3_id)
assert get_int_response.data["documents"][3]["id"] == uuid.UUID(file4_id)
def test_archive_interaction(self):
"""Test archiving an interaction"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "sample interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is False
assert int_response.data["results"][0]["is_active"] is True
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
delete_int_response = self.api_client.delete(get_interaction_url)
assert delete_int_response.status_code == status.HTTP_204_NO_CONTENT
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_404_NOT_FOUND
def test_archive_edited_interaction(self):
"""Test archiving an edited interaction"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url, format="json", data={"text": "sample interaction notes"}
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is False
assert int_response.data["results"][0]["is_active"] is True
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
edit_int_response = self.api_client.put(
get_interaction_url,
format="json",
data={"text": "edited interaction notes"},
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "edited interaction notes"
delete_int_response = self.api_client.delete(get_interaction_url)
assert delete_int_response.status_code == status.HTTP_204_NO_CONTENT
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_404_NOT_FOUND
def test_archive_interactions_with_document(self):
"""Test archive interaction with a document"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "documents": [document_id]},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(document_id)
delete_int_response = self.api_client.delete(get_interaction_url)
assert delete_int_response.status_code == status.HTTP_204_NO_CONTENT
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_404_NOT_FOUND
def test_add_interactions_null_document(self):
"""Test there is one interaction without pinning"""
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
json_string = u'{"text": "sample interaction notes", "documents":null}'
add_int_response = self.api_client.post(
interactions_url, format="json", data=json.loads(json_string)
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
assert int_response.data["results"][0]["text"] == "sample interaction notes"
assert int_response.data["results"][0]["kind"] == "Comment"
assert int_response.data["results"][0]["pinned"] is False
assert int_response.data["results"][0]["is_active"] is True
def test_add_interactions_with_edit_text_clear_documents_with_null(self):
"""Test add interaction with documents and edit to clear them"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "documents": [document_id]},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(document_id)
json_string = u'{"text": "edited sample interaction notes", "documents":null}'
edit_int_response = self.api_client.put(
get_interaction_url, format="json", data=json.loads(json_string)
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "edited sample interaction notes"
assert get_int_response.data["documents"] == []
def test_add_interactions_with_clear_documents_with_null(self):
"""Test add interaction with documents and edit to clear them"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "documents": [document_id]},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert get_int_response.data["documents"] is not None
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(document_id)
json_string = u'{"documents":null}'
edit_int_response = self.api_client.put(
get_interaction_url, format="json", data=json.loads(json_string)
)
assert edit_int_response.status_code == status.HTTP_200_OK
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["documents"] == []
def test_add_interactions_with_document_check_deleting_document(self):
"""
Test add interaction with a document
Attempt to delete the document while it was attached
to an interaction
It shouldn't be allowed, expect 400
"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={"text": "sample interaction notes", "documents": [document_id]},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) > 0
assert get_int_response.data["documents"][0]["id"] == uuid.UUID(document_id)
get_doc_url = reverse(
"barrier-document-item",
kwargs={"entity_document_pk": document_id}
)
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
get_doc_response = self.api_client.delete(get_doc_url)
assert get_doc_response.status_code == status.HTTP_400_BAD_REQUEST
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) == 1
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
doc = Document.objects.get(id=document_id)
assert doc.detached is False
def test_check_deleting_document_when_not_attached_to_interaction(self):
"""
Test deleting a document when it was not attached to an interaction
It should be deleted fully
"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id = docs_list_report_response.data["id"]
get_doc_url = reverse(
"barrier-document-item",
kwargs={"entity_document_pk": document_id}
)
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
get_doc_response = self.api_client.delete(get_doc_url)
assert get_doc_response.status_code == status.HTTP_204_NO_CONTENT
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_404_NOT_FOUND
def test_edit_interaction_remove_a_document_check_detach(self):
"""
Test add interaction with two documents
edit interaction, remove one of them
check if that document is now detached and the other is not
"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile1.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id_1 = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile2.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id_2 = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={
"text": "sample interaction notes",
"documents": [document_id_1, document_id_2]
},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) == 2
get_doc_url = reverse(
"barrier-document-item",
kwargs={"entity_document_pk": document_id_1}
)
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) == 2
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
doc = Document.objects.get(id=document_id_1)
assert doc.detached is False
doc = Document.objects.get(id=document_id_2)
assert doc.detached is False
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) == 2
int_id = int_response.data["results"][0]["id"]
json_string = u'{"documents":null}'
edit_int_response = self.api_client.put(
get_interaction_url,
format="json",
data={
"documents": [document_id_1]
},
)
assert edit_int_response.status_code == status.HTTP_200_OK
doc = Document.objects.get(id=document_id_1)
assert doc.detached is False
doc = Document.objects.get(id=document_id_2)
assert doc.detached is True
def test_delete_detached_document(self):
"""
Test add interaction with a document
Attempt to delete a detached document
It should not be deleted
"""
docs_list_url = reverse("barrier-documents")
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile1.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id_1 = docs_list_report_response.data["id"]
docs_list_report_response = self.api_client.post(
docs_list_url, format="json", data={"original_filename": "somefile2.pdf"}
)
assert docs_list_report_response.status_code == status.HTTP_201_CREATED
document_id_2 = docs_list_report_response.data["id"]
response = self._submit_report(self.report)
assert response.status_code == status.HTTP_200_OK
interactions_url = reverse("list-interactions", kwargs={"pk": self.report.id})
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 0
add_int_response = self.api_client.post(
interactions_url,
format="json",
data={
"text": "sample interaction notes",
"documents": [document_id_1, document_id_2]
},
)
assert add_int_response.status_code == status.HTTP_201_CREATED
int_response = self.api_client.get(interactions_url)
assert int_response.status_code == status.HTTP_200_OK
assert int_response.data["count"] == 1
int_id = int_response.data["results"][0]["id"]
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) == 2
get_doc_url = reverse(
"barrier-document-item",
kwargs={"entity_document_pk": document_id_1}
)
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) == 2
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
doc = Document.objects.get(id=document_id_1)
assert doc.detached is False
doc = Document.objects.get(id=document_id_2)
assert doc.detached is False
get_interaction_url = reverse("get-interaction", kwargs={"pk": int_id})
get_int_response = self.api_client.get(get_interaction_url)
assert get_int_response.status_code == status.HTTP_200_OK
assert get_int_response.data["text"] == "sample interaction notes"
assert get_int_response.data["kind"] == "Comment"
assert get_int_response.data["pinned"] is False
assert get_int_response.data["is_active"] is True
assert len(get_int_response.data["documents"]) == 2
int_id = int_response.data["results"][0]["id"]
json_string = u'{"documents":null}'
edit_int_response = self.api_client.put(
get_interaction_url,
format="json",
data={
"documents": [document_id_1]
},
)
assert edit_int_response.status_code == status.HTTP_200_OK
doc = Document.objects.get(id=document_id_1)
assert doc.detached is False
doc = Document.objects.get(id=document_id_2)
assert doc.detached is True
get_doc_url = reverse(
"barrier-document-item",
kwargs={"entity_document_pk": document_id_2}
)
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
get_doc_response = self.api_client.delete(get_doc_url)
assert get_doc_response.status_code == status.HTTP_204_NO_CONTENT
get_doc_response = self.api_client.get(get_doc_url)
assert get_doc_response.status_code == status.HTTP_200_OK
| 46.890076
| 93
| 0.680168
| 7,949
| 61,426
| 4.915838
| 0.023525
| 0.141033
| 0.095583
| 0.116696
| 0.957595
| 0.948331
| 0.942573
| 0.93789
| 0.933821
| 0.933335
| 0
| 0.015957
| 0.212369
| 61,426
| 1,309
| 94
| 46.925898
| 0.791716
| 0.027334
| 0
| 0.845854
| 0
| 0
| 0.119136
| 0.001766
| 0
| 0
| 0
| 0
| 0.439024
| 1
| 0.029268
| false
| 0
| 0.00878
| 0
| 0.04
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
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| 0
|
0
| 8
|
ce290294dd2971cd7a121cf707285af1af4f2c7b
| 25,179
|
py
|
Python
|
apis/nb/clients/inventory_manager_client/DiscoveryApi.py
|
CiscoDevNet/APIC-EM-Generic-Scripts-
|
74211d9488f1e77cf56ef86dba20ec8e8eb49cc1
|
[
"ECL-2.0",
"Apache-2.0"
] | 45
|
2016-06-09T15:41:25.000Z
|
2019-08-06T17:13:11.000Z
|
apis/nb/clients/inventory_manager_client/DiscoveryApi.py
|
CiscoDevNet/APIC-EM-Generic-Scripts
|
74211d9488f1e77cf56ef86dba20ec8e8eb49cc1
|
[
"ECL-2.0",
"Apache-2.0"
] | 36
|
2016-06-12T03:03:56.000Z
|
2017-03-13T18:20:11.000Z
|
apis/nb/clients/inventory_manager_client/DiscoveryApi.py
|
CiscoDevNet/APIC-EM-Generic-Scripts
|
74211d9488f1e77cf56ef86dba20ec8e8eb49cc1
|
[
"ECL-2.0",
"Apache-2.0"
] | 15
|
2016-06-22T03:51:37.000Z
|
2019-07-10T10:06:02.000Z
|
#!/usr/bin/env python
#pylint: skip-file
# This source code is licensed under the Apache license found in the
# LICENSE file in the root directory of this project.
import sys
import os
import urllib.request, urllib.parse, urllib.error
from .models import *
class DiscoveryApi(object):
def __init__(self, apiClient):
self.apiClient = apiClient
def updateDiscovery(self, **kwargs):
"""Updates an existing discovery specified by id - only for starting/stopping the discovery
Args:
discovery, DiscoveryNIO: Discovery request that holds the status of discovery as active / inactive (required)
Returns: TaskIdResult
"""
allParams = ['discovery']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method updateDiscovery" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'PUT'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('discovery' in params):
bodyParam = params['discovery']
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'TaskIdResult')
return responseObject
def insertDiscovery(self, **kwargs):
"""Starts a new discovery process and returns a task-id
Args:
request, InventoryRequest: Discovery request that holds the parameters required for discovery (required)
Returns: TaskIdResult
"""
allParams = ['request']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method insertDiscovery" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'POST'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('request' in params):
bodyParam = params['request']
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'TaskIdResult')
return responseObject
def deleteAllDiscovery(self, **kwargs):
"""Deletes all discovery
Args:
Returns: TaskIdResult
"""
allParams = []
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method deleteAllDiscovery" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'TaskIdResult')
return responseObject
def getDiscoveryCount(self, **kwargs):
"""Retrieves the number of discoveries
Args:
Returns: CountResult
"""
allParams = []
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getDiscoveryCount" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/count'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'CountResult')
return responseObject
def getDiscoveryJobsByIp(self, **kwargs):
"""Retrieves the list of discovery jobs for the given IP
Args:
offset, int: offset (required)
limit, int: limit (required)
ipAddress, str: ipAddress (required)
Returns: DiscoveryJobNIOListResult
"""
allParams = ['offset', 'limit', 'ipAddress']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getDiscoveryJobsByIp" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/job'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('offset' in params):
queryParams['offset'] = self.apiClient.toPathValue(params['offset'])
if ('limit' in params):
queryParams['limit'] = self.apiClient.toPathValue(params['limit'])
if ('ipAddress' in params):
queryParams['ipAddress'] = self.apiClient.toPathValue(params['ipAddress'])
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DiscoveryJobNIOListResult')
return responseObject
def getDiscoveryById(self, **kwargs):
"""Retrieves the discovery specified by id
Args:
id, str: Discovery ID (required)
Returns: DiscoveryNIOResult
"""
allParams = ['id']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getDiscoveryById" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{id}'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('id' in params):
replacement = str(self.apiClient.toPathValue(params['id']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'id' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DiscoveryNIOResult')
return responseObject
def deleteDiscoveryById(self, **kwargs):
"""Deletes the discovery specified by id
Args:
id, str: Discovery ID (required)
Returns: TaskIdResult
"""
allParams = ['id']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method deleteDiscoveryById" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{id}'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('id' in params):
replacement = str(self.apiClient.toPathValue(params['id']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'id' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'TaskIdResult')
return responseObject
def getDiscoveryJobsById(self, **kwargs):
"""Retrieves list of discovery jobs for the specified discovery id
Args:
id, str: Discovery ID (required)
offset, int: offset (required)
limit, int: limit (required)
ipAddress, str: ipAddress (required)
Returns: DiscoveryJobNIOListResult
"""
allParams = ['id', 'offset', 'limit', 'ipAddress']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getDiscoveryJobsById" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{id}/job'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('offset' in params):
queryParams['offset'] = self.apiClient.toPathValue(params['offset'])
if ('limit' in params):
queryParams['limit'] = self.apiClient.toPathValue(params['limit'])
if ('ipAddress' in params):
queryParams['ipAddress'] = self.apiClient.toPathValue(params['ipAddress'])
if ('id' in params):
replacement = str(self.apiClient.toPathValue(params['id']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'id' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DiscoveryJobNIOListResult')
return responseObject
def getNetworkDeviceByDiscoveryId(self, **kwargs):
"""Retrieves the network devices discovered in the discovery specified by id
Args:
taskId, str: taskId (required)
id, str: id (required)
Returns: NetworkDeviceNIOListResult
"""
allParams = ['taskId', 'id']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getNetworkDeviceByDiscoveryId" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{id}/network-device'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('taskId' in params):
queryParams['taskId'] = self.apiClient.toPathValue(params['taskId'])
if ('id' in params):
replacement = str(self.apiClient.toPathValue(params['id']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'id' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'NetworkDeviceNIOListResult')
return responseObject
def getNetworkDeviceCountByDiscoveryId(self, **kwargs):
"""Retrieves the number of network devices discovered in the discovery specified by id
Args:
taskId, str: taskId (required)
id, str: Discovery ID (required)
Returns: CountResult
"""
allParams = ['taskId', 'id']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getNetworkDeviceCountByDiscoveryId" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{id}/network-device/count'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('taskId' in params):
queryParams['taskId'] = self.apiClient.toPathValue(params['taskId'])
if ('id' in params):
replacement = str(self.apiClient.toPathValue(params['id']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'id' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'CountResult')
return responseObject
def getNetworkDeviceByDiscoveryIdByRange(self, **kwargs):
"""Retrieves the range of network devices discovered for the given discovery
Args:
taskId, str: taskId (required)
id, str: Discovery ID (required)
startIndex, int: Start index (required)
recordsToReturn, int: Number of records to return (required)
Returns: NetworkDeviceNIOListResult
"""
allParams = ['taskId', 'id', 'startIndex', 'recordsToReturn']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getNetworkDeviceByDiscoveryIdByRange" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{id}/network-device/{startIndex}/{recordsToReturn}'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('taskId' in params):
queryParams['taskId'] = self.apiClient.toPathValue(params['taskId'])
if ('id' in params):
replacement = str(self.apiClient.toPathValue(params['id']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'id' + '}',
replacement)
if ('startIndex' in params):
replacement = str(self.apiClient.toPathValue(params['startIndex']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'startIndex' + '}',
replacement)
if ('recordsToReturn' in params):
replacement = str(self.apiClient.toPathValue(params['recordsToReturn']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'recordsToReturn' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'NetworkDeviceNIOListResult')
return responseObject
def deleteDiscoveryByRange(self, **kwargs):
"""Deletes the discovery in the given range
Args:
startIndex, int: Start index (required)
recordsToDelete, int: Number of records to delete (required)
Returns: TaskIdResult
"""
allParams = ['startIndex', 'recordsToDelete']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method deleteDiscoveryByRange" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{startIndex}/{recordsToDelete}'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'DELETE'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('startIndex' in params):
replacement = str(self.apiClient.toPathValue(params['startIndex']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'startIndex' + '}',
replacement)
if ('recordsToDelete' in params):
replacement = str(self.apiClient.toPathValue(params['recordsToDelete']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'recordsToDelete' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'TaskIdResult')
return responseObject
def getDiscoveryByRange(self, **kwargs):
"""Retrieves the discovery in the given range
Args:
startIndex, int: Start index (required)
recordsToReturn, int: Number of records to return (required)
Returns: DiscoveryNIOListResult
"""
allParams = ['startIndex', 'recordsToReturn']
params = locals()
for (key, val) in list(params['kwargs'].items()):
if key not in allParams:
raise TypeError("Got an unexpected keyword argument '%s' to method getDiscoveryByRange" % key)
params[key] = val
del params['kwargs']
resourcePath = '/discovery/{startIndex}/{recordsToReturn}'
resourcePath = resourcePath.replace('{format}', 'json')
method = 'GET'
queryParams = {}
headerParams = {}
formParams = {}
files = {}
bodyParam = None
headerParams['Accept'] = 'application/json'
headerParams['Content-Type'] = 'application/json'
if ('startIndex' in params):
replacement = str(self.apiClient.toPathValue(params['startIndex']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'startIndex' + '}',
replacement)
if ('recordsToReturn' in params):
replacement = str(self.apiClient.toPathValue(params['recordsToReturn']))
replacement = urllib.parse.quote(replacement)
resourcePath = resourcePath.replace('{' + 'recordsToReturn' + '}',
replacement)
postData = (formParams if formParams else bodyParam)
response = self.apiClient.callAPI(resourcePath, method, queryParams,
postData, headerParams, files=files)
if not response:
return None
responseObject = self.apiClient.deserialize(response, 'DiscoveryNIOListResult')
return responseObject
| 27.220541
| 127
| 0.5252
| 1,939
| 25,179
| 6.817947
| 0.083032
| 0.048185
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| 0.86354
| 0.852345
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| 0.818003
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| 0
| 0.379443
| 25,179
| 924
| 128
| 27.25
| 0.84608
| 0.107471
| 0
| 0.857488
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| 0.147066
| 0.021298
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| 0
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| 0
| 1
| 0.033816
| false
| 0
| 0.009662
| 0
| 0.108696
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| 0
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| 0
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| 0
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| 1
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| null | 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
ce42830e7e83fc2f16742b8e48fd57470d26d0f9
| 1,909
|
py
|
Python
|
darkPy/message.py
|
darkracer/sound-bot
|
7ce72a912c13361b411107361c3cf37c86e56cf4
|
[
"MIT"
] | null | null | null |
darkPy/message.py
|
darkracer/sound-bot
|
7ce72a912c13361b411107361c3cf37c86e56cf4
|
[
"MIT"
] | null | null | null |
darkPy/message.py
|
darkracer/sound-bot
|
7ce72a912c13361b411107361c3cf37c86e56cf4
|
[
"MIT"
] | null | null | null |
from darkPy.guild import Attachment, Role
from darkPy.user import User
class Message:
def __init__(self, data):
for key in data:
if key == 'author':
setattr(self, key, User(data[key]))
elif key == 'mentions':
mentions = []
for userData in data[key]:
user = User(userData)
mentions.append(user)
setattr(self, key, mentions)
elif key == 'mention_roles':
roles = []
for roleData in data[key]:
role = Role(roleData)
roles.append(role)
setattr(self, key, roles)
elif key == 'attachments':
attachments = []
for attachmentData in data[key]:
attachments.append(Attachment(attachmentData))
setattr(self, key, attachments)
else:
setattr(self, key, data[key])
def update(self, data):
for key in data:
if key == 'author':
setattr(self, key, User(data[key]))
elif key == 'mentions':
mentions = []
for userData in data[key]:
user = User(userData)
mentions.append(user)
setattr(self, key, mentions)
elif key == 'mention_roles':
roles = []
for roleData in data[key]:
role = Role(roleData)
roles.append(role)
setattr(self, key, roles)
elif key == 'attachments':
attachments = []
for attachmentData in data[key]:
attachments.append(Attachment(attachmentData))
setattr(self, key, attachments)
else:
setattr(self, key, data[key])
| 36.018868
| 66
| 0.462546
| 171
| 1,909
| 5.128655
| 0.175439
| 0.125428
| 0.159635
| 0.031927
| 0.900798
| 0.900798
| 0.900798
| 0.900798
| 0.900798
| 0.900798
| 0
| 0
| 0.444212
| 1,909
| 52
| 67
| 36.711538
| 0.826579
| 0
| 0
| 0.897959
| 0
| 0
| 0.039811
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.040816
| false
| 0
| 0.040816
| 0
| 0.102041
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
020644f4ea27739affd56542af2c8fc17f4d57ea
| 68,574
|
py
|
Python
|
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_rr/cmp_zeusmp/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_rr/cmp_zeusmp/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_rr/cmp_zeusmp/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
power = {'BUSES': {'Area': 1.33155,
'Bus/Area': 1.33155,
'Bus/Gate Leakage': 0.00662954,
'Bus/Peak Dynamic': 0.0,
'Bus/Runtime Dynamic': 0.0,
'Bus/Subthreshold Leakage': 0.0691322,
'Bus/Subthreshold Leakage with power gating': 0.0259246,
'Gate Leakage': 0.00662954,
'Peak Dynamic': 0.0,
'Runtime Dynamic': 0.0,
'Subthreshold Leakage': 0.0691322,
'Subthreshold Leakage with power gating': 0.0259246},
'Core': [{'Area': 32.6082,
'Execution Unit/Area': 8.2042,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.239502,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.390804,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 1.17229,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.122718,
'Execution Unit/Instruction Scheduler/Area': 2.17927,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.656309,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 1.13649,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.651809,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 2.44461,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.469005,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 7.9905,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.221471,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0237917,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.266633,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.175954,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.488104,
'Execution Unit/Register Files/Runtime Dynamic': 0.199746,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.70991,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 1.63381,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155,
'Execution Unit/Runtime Dynamic': 5.07434,
'Execution Unit/Subthreshold Leakage': 1.83518,
'Execution Unit/Subthreshold Leakage with power gating': 0.709678,
'Gate Leakage': 0.372997,
'Instruction Fetch Unit/Area': 5.86007,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00125395,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00125395,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00108663,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000417618,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.0025276,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00612213,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0122211,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0590479,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.169149,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 6.43323,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.372803,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.574508,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 8.96874,
'Instruction Fetch Unit/Runtime Dynamic': 1.1348,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932587,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.233253,
'L2/Runtime Dynamic': 0.0591423,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80969,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 4.95918,
'Load Store Unit/Data Cache/Runtime Dynamic': 1.9396,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0351387,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.120417,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.120417,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 5.53013,
'Load Store Unit/Runtime Dynamic': 2.65388,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.296929,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.593858,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591622,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283406,
'Memory Management Unit/Area': 0.434579,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.105381,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.10887,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00813591,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.399995,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0611582,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.740677,
'Memory Management Unit/Runtime Dynamic': 0.170028,
'Memory Management Unit/Subthreshold Leakage': 0.0769113,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0399462,
'Peak Dynamic': 28.025,
'Renaming Unit/Area': 0.369768,
'Renaming Unit/FP Front End RAT/Area': 0.168486,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 3.33511,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.772662,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0437281,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925,
'Renaming Unit/Free List/Area': 0.0414755,
'Renaming Unit/Free List/Gate Leakage': 4.15911e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0401324,
'Renaming Unit/Free List/Runtime Dynamic': 0.0428577,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000670426,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987,
'Renaming Unit/Gate Leakage': 0.00863632,
'Renaming Unit/Int Front End RAT/Area': 0.114751,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.331389,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781,
'Renaming Unit/Peak Dynamic': 4.56169,
'Renaming Unit/Runtime Dynamic': 1.14691,
'Renaming Unit/Subthreshold Leakage': 0.070483,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779,
'Runtime Dynamic': 10.2391,
'Subthreshold Leakage': 6.21877,
'Subthreshold Leakage with power gating': 2.58311},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.118341,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.295639,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.578801,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.279849,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.451386,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.227844,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.959079,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.231327,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 5.33002,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.109348,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0117381,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.131637,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0868106,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.240985,
'Execution Unit/Register Files/Runtime Dynamic': 0.0985487,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.306914,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.71074,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 2.46938,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000622882,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000622882,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000542388,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.00020989,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00124704,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00303519,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00597716,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0834533,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 5.30834,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.183529,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.283445,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 7.78448,
'Instruction Fetch Unit/Runtime Dynamic': 0.559439,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.10826,
'L2/Runtime Dynamic': 0.0274427,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 3.09106,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.960175,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0599795,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0599794,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 3.3743,
'Load Store Unit/Runtime Dynamic': 1.31595,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.147899,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.295798,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0524899,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.054108,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.330053,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.03011,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.57633,
'Memory Management Unit/Runtime Dynamic': 0.0842181,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 20.7629,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.287644,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.0161266,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.138791,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.442562,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 4.899,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.119716,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.296719,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.585724,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.281175,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.453525,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.228924,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.963623,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.231783,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 5.3434,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.110656,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0117937,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.132574,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0872219,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.24323,
'Execution Unit/Register Files/Runtime Dynamic': 0.0990156,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.309233,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.710156,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 2.47489,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.000630798,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.000630798,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.000549242,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000212521,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00125295,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00306379,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.00605456,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0838486,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 5.3335,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.184037,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.284788,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 7.81086,
'Instruction Fetch Unit/Runtime Dynamic': 0.561792,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.119807,
'L2/Runtime Dynamic': 0.0306635,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 3.03818,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.943066,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0582685,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0582685,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 3.31333,
'Load Store Unit/Runtime Dynamic': 1.28869,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.14368,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.28736,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
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'Load Store Unit/Subthreshold Leakage': 0.591321,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
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'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
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'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
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'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.117074,
'L2/Runtime Dynamic': 0.0297263,
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'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
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'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
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'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
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'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
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'Memory Management Unit/Dtlb/Peak Dynamic': 0.0515795,
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'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
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'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
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'Memory Management Unit/Runtime Dynamic': 0.0834442,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 20.7501,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
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'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
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'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
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'Subthreshold Leakage with power gating': 2.55328}],
'DRAM': {'Area': 0,
'Gate Leakage': 0,
'Peak Dynamic': 1.8318365482629306,
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'Subthreshold Leakage': 4.252,
'Subthreshold Leakage with power gating': 4.252},
'L3': [{'Area': 61.9075,
'Gate Leakage': 0.0484137,
'Peak Dynamic': 0.217331,
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'Processor': {'Area': 191.908,
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'Total Cores/Gate Leakage': 1.4798,
'Total Cores/Peak Dynamic': 90.2902,
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'Total Cores/Subthreshold Leakage with power gating': 10.2429,
'Total L3s/Area': 61.9075,
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0
| 7
|
02190af874c4a6a0c0137f6b9f110a3cf2646f95
| 316
|
py
|
Python
|
temboo/core/Library/Facebook/OAuth/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 7
|
2016-03-07T02:07:21.000Z
|
2022-01-21T02:22:41.000Z
|
temboo/core/Library/Facebook/OAuth/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | null | null | null |
temboo/core/Library/Facebook/OAuth/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 8
|
2016-06-14T06:01:11.000Z
|
2020-04-22T09:21:44.000Z
|
from temboo.Library.Facebook.OAuth.FinalizeOAuth import FinalizeOAuth, FinalizeOAuthInputSet, FinalizeOAuthResultSet, FinalizeOAuthChoreographyExecution
from temboo.Library.Facebook.OAuth.InitializeOAuth import InitializeOAuth, InitializeOAuthInputSet, InitializeOAuthResultSet, InitializeOAuthChoreographyExecution
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0
| 8
|
02768201f0a0f2bb6a174006a90c32325f8a7f72
| 74
|
py
|
Python
|
backend/src/order/utils.py
|
NgoQuocBao1010/Shipping-System-Management
|
4b9f26c63f1db46ed1beac3b867f40756d0ba980
|
[
"MIT"
] | 4
|
2022-01-03T16:26:42.000Z
|
2022-01-04T02:55:52.000Z
|
backend/src/order/utils.py
|
NgoQuocBao1010/Shipping-System-Management
|
4b9f26c63f1db46ed1beac3b867f40756d0ba980
|
[
"MIT"
] | null | null | null |
backend/src/order/utils.py
|
NgoQuocBao1010/Shipping-System-Management
|
4b9f26c63f1db46ed1beac3b867f40756d0ba980
|
[
"MIT"
] | 1
|
2022-01-16T21:41:20.000Z
|
2022-01-16T21:41:20.000Z
|
import secrets
def customOrderId():
return secrets.token_urlsafe(4)
| 12.333333
| 35
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| 9
| 74
| 6.111111
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016129
| 0.162162
| 74
| 5
| 36
| 14.8
| 0.870968
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| true
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 7
|
5a10f7eec61ea40336698118342939470f73d052
| 2,870
|
py
|
Python
|
configs/_base_/datasets/pipelines/auto_aug.py
|
YuxinZou/mmclassification
|
2037260ea6c98a3b115e97727e1151a1c2c32f7a
|
[
"Apache-2.0"
] | 1,190
|
2020-07-10T01:16:01.000Z
|
2022-03-31T09:48:38.000Z
|
configs/_base_/datasets/pipelines/auto_aug.py
|
YuxinZou/mmclassification
|
2037260ea6c98a3b115e97727e1151a1c2c32f7a
|
[
"Apache-2.0"
] | 702
|
2020-07-13T13:31:33.000Z
|
2022-03-31T06:48:04.000Z
|
configs/_base_/datasets/pipelines/auto_aug.py
|
YuxinZou/mmclassification
|
2037260ea6c98a3b115e97727e1151a1c2c32f7a
|
[
"Apache-2.0"
] | 502
|
2020-07-10T02:40:55.000Z
|
2022-03-31T02:07:09.000Z
|
# Policy for ImageNet, refers to
# https://github.com/DeepVoltaire/AutoAugment/blame/master/autoaugment.py
policy_imagenet = [
[
dict(type='Posterize', bits=4, prob=0.4),
dict(type='Rotate', angle=30., prob=0.6)
],
[
dict(type='Solarize', thr=256 / 9 * 4, prob=0.6),
dict(type='AutoContrast', prob=0.6)
],
[dict(type='Equalize', prob=0.8),
dict(type='Equalize', prob=0.6)],
[
dict(type='Posterize', bits=5, prob=0.6),
dict(type='Posterize', bits=5, prob=0.6)
],
[
dict(type='Equalize', prob=0.4),
dict(type='Solarize', thr=256 / 9 * 5, prob=0.2)
],
[
dict(type='Equalize', prob=0.4),
dict(type='Rotate', angle=30 / 9 * 8, prob=0.8)
],
[
dict(type='Solarize', thr=256 / 9 * 6, prob=0.6),
dict(type='Equalize', prob=0.6)
],
[dict(type='Posterize', bits=6, prob=0.8),
dict(type='Equalize', prob=1.)],
[
dict(type='Rotate', angle=10., prob=0.2),
dict(type='Solarize', thr=256 / 9, prob=0.6)
],
[
dict(type='Equalize', prob=0.6),
dict(type='Posterize', bits=5, prob=0.4)
],
[
dict(type='Rotate', angle=30 / 9 * 8, prob=0.8),
dict(type='ColorTransform', magnitude=0., prob=0.4)
],
[
dict(type='Rotate', angle=30., prob=0.4),
dict(type='Equalize', prob=0.6)
],
[dict(type='Equalize', prob=0.0),
dict(type='Equalize', prob=0.8)],
[dict(type='Invert', prob=0.6),
dict(type='Equalize', prob=1.)],
[
dict(type='ColorTransform', magnitude=0.4, prob=0.6),
dict(type='Contrast', magnitude=0.8, prob=1.)
],
[
dict(type='Rotate', angle=30 / 9 * 8, prob=0.8),
dict(type='ColorTransform', magnitude=0.2, prob=1.)
],
[
dict(type='ColorTransform', magnitude=0.8, prob=0.8),
dict(type='Solarize', thr=256 / 9 * 2, prob=0.8)
],
[
dict(type='Sharpness', magnitude=0.7, prob=0.4),
dict(type='Invert', prob=0.6)
],
[
dict(
type='Shear',
magnitude=0.3 / 9 * 5,
prob=0.6,
direction='horizontal'),
dict(type='Equalize', prob=1.)
],
[
dict(type='ColorTransform', magnitude=0., prob=0.4),
dict(type='Equalize', prob=0.6)
],
[
dict(type='Equalize', prob=0.4),
dict(type='Solarize', thr=256 / 9 * 5, prob=0.2)
],
[
dict(type='Solarize', thr=256 / 9 * 4, prob=0.6),
dict(type='AutoContrast', prob=0.6)
],
[dict(type='Invert', prob=0.6),
dict(type='Equalize', prob=1.)],
[
dict(type='ColorTransform', magnitude=0.4, prob=0.6),
dict(type='Contrast', magnitude=0.8, prob=1.)
],
[dict(type='Equalize', prob=0.8),
dict(type='Equalize', prob=0.6)],
]
| 29.587629
| 73
| 0.515679
| 396
| 2,870
| 3.734848
| 0.113636
| 0.270453
| 0.085193
| 0.128465
| 0.870183
| 0.855984
| 0.848546
| 0.799865
| 0.760649
| 0.741041
| 0
| 0.08134
| 0.271777
| 2,870
| 96
| 74
| 29.895833
| 0.626316
| 0.03554
| 0
| 0.489362
| 0
| 0
| 0.15877
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 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
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
5a47304f536e36a52a27e005eaaa5cd70b53dd50
| 27,057
|
py
|
Python
|
tests/test_alarmclock.py
|
tangb/cleepapp-alarmclock
|
fab6a704400a55c6f91d762ff9b4e3f2218fc1c2
|
[
"MIT"
] | null | null | null |
tests/test_alarmclock.py
|
tangb/cleepapp-alarmclock
|
fab6a704400a55c6f91d762ff9b4e3f2218fc1c2
|
[
"MIT"
] | null | null | null |
tests/test_alarmclock.py
|
tangb/cleepapp-alarmclock
|
fab6a704400a55c6f91d762ff9b4e3f2218fc1c2
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import logging
import datetime
import sys
sys.path.append('../')
from backend.alarmclock import Alarmclock
from backend.alarmclockalarmtriggeredevent import AlarmclockAlarmTriggeredEvent
from backend.alarmclockalarmscheduledevent import AlarmclockAlarmScheduledEvent
from backend.alarmclockalarmstoppedevent import AlarmclockAlarmStoppedEvent
from cleep.exception import InvalidParameter, MissingParameter, CommandError, Unauthorized
from cleep.libs.tests import session
from mock import Mock, patch, MagicMock
class TestAlarmclock(unittest.TestCase):
def setUp(self):
logging.basicConfig(level=logging.FATAL, format=u'%(asctime)s %(name)s:%(lineno)d %(levelname)s : %(message)s')
self.session = session.TestSession(self)
def tearDown(self):
self.session.clean()
def init(self, start=True, mocks=True):
self.module = self.session.setup(Alarmclock)
if mocks:
self.module._set_today_is_non_working_day = Mock()
self.module._set_tomorrow_is_non_working_day = Mock()
if start:
self.session.start_module(self.module)
def test__on_start(self):
self.init(False)
self.module._schedule_alarm = Mock()
self.module.is_module_loaded = Mock(return_value=True)
self.session.start_module(self.module)
self.module._set_today_is_non_working_day.assert_called()
self.module._set_tomorrow_is_non_working_day.assert_called()
self.module._schedule_alarm.assert_called()
self.assertTrue(self.module.has_audioplayer)
def test__on_start_no_audioplayer(self):
self.init(False)
self.module._set_today_is_non_working_day = Mock()
self.module._set_tomorrow_is_non_working_day = Mock()
self.module._schedule_alarm = Mock()
self.module.is_module_loaded = Mock(return_value=False)
self.session.start_module(self.module)
self.assertFalse(self.module.has_audioplayer)
def test_on_event_unhandled_event(self):
self.init()
event = {
'event': 'an.unhandled.event',
}
self.module.on_event(event)
self.assertEqual(self.module._set_today_is_non_working_day.call_count, 1)
self.assertEqual(self.module._set_tomorrow_is_non_working_day.call_count, 1)
def test_on_event_time_event_not_midnight(self):
self.init()
event = {
'event': 'parameters.time.now',
'params': {
'hour': 10,
'minute': 10,
'weekday_literal': 'mon',
'weekday': 0,
}
}
self.module.on_event(event)
self.assertEqual(self.module._set_today_is_non_working_day.call_count, 1)
self.assertEqual(self.module._set_tomorrow_is_non_working_day.call_count, 1)
def test_on_event_time_event_midnight(self):
self.init()
event = {
'event': 'parameters.time.now',
'params': {
'hour': 0,
'minute': 0,
'weekday_literal': 'mon',
'weekday': 0,
}
}
self.module.on_event(event)
self.assertEqual(self.module._set_today_is_non_working_day.call_count, 2)
self.assertEqual(self.module._set_tomorrow_is_non_working_day.call_count, 2)
def test_add_alarm(self):
self.init()
self.module._add_device = Mock(return_value={'uuid': '12345678'})
time_ = {'hour': 1, 'minute': 1}
days = {'mon': True, 'tue': False, 'wed': True, 'thu': False, 'fri': True, 'sat': False, 'sun': True}
self.module.tomorrow = {
'date': datetime.date(2021, 12, 16),
'nonWorkingDay': False
}
result = self.module.add_alarm(time_, 10, days, False, 50)
self.assertEqual(result, '12345678')
self.module._add_device.assert_called_with({
'time': time_,
'timeout': 10,
'days': days,
'nonWorkingDays': False,
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'volume': 50,
})
def test_add_alarm_failed(self):
self.init()
self.module._add_device = Mock(return_value=None)
time_ = {'hour': 1, 'minute': 1}
days = {'mon': True, 'tue': False, 'wed': True, 'thu': False, 'fri': True, 'sat': False, 'sun': True}
with self.assertRaises(CommandError) as cm:
self.module.add_alarm(time_, 10, days, False, 50)
self.assertEqual(str(cm.exception), 'Error adding alarm')
def test_add_alarm_invalid_parameters(self):
self.init()
self.module._add_device = Mock(return_value=None)
time_ = {'hour': 1, 'minute': 1}
days = {'mon': True, 'tue': False, 'wed': True, 'thu': False, 'fri': True, 'sat': False, 'sun': True}
with self.assertRaises(MissingParameter) as cm:
self.module.add_alarm(None, 10, days, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "alarm_time" is missing')
with self.assertRaises(MissingParameter) as cm:
self.module.add_alarm(time_, None, days, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "timeout" is missing')
with self.assertRaises(MissingParameter) as cm:
self.module.add_alarm(time_, 10, None, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "days" is missing')
with self.assertRaises(MissingParameter) as cm:
self.module.add_alarm(time_, 10, days, None, 50)
self.assertEqual(str(cm.exception), 'Parameter "non_working_days" is missing')
with self.assertRaises(MissingParameter) as cm:
self.module.add_alarm(time_, 10, days, False, None)
self.assertEqual(str(cm.exception), 'Parameter "volume" is missing')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm({}, 10, days, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "alarm_time" is invalid (specified="{}")')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm({'hour':1, 'minutes': 1}, 10, days, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "alarm_time" is invalid (specified="{\'hour\': 1, \'minutes\': 1}")')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm({'hour':1, 'minutes': '1'}, 10, days, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "alarm_time" is invalid (specified="{\'hour\': 1, \'minutes\': \'1\'}")')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm(time_, 10, {'mon': True, 'other': True}, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "days" is invalid or no day is selected')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm(time_, 10, {'mon': False, 'tue': False, 'wed': False, 'thu': False, 'fri': False, 'sat': False, 'sun': False}, False, 50)
self.assertEqual(str(cm.exception), 'Parameter "days" is invalid or no day is selected')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm(time_, -2, days, False, 50)
self.assertEqual(str(cm.exception), 'Timeout must be greater or equal to 0')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm(time_, 10, days, False, 0)
self.assertEqual(str(cm.exception), 'Volume must be between 1 and 100')
with self.assertRaises(InvalidParameter) as cm:
self.module.add_alarm(time_, 10, days, False, 101)
self.assertEqual(str(cm.exception), 'Volume must be between 1 and 100')
def test_remove_alarm(self):
self.init()
self.module._get_device = Mock(return_value={})
self.module._delete_device = Mock(return_value=True)
self.module.remove_alarm('123456789')
self.module._delete_device.assert_called_with('123456789')
def test_remove_alarm_failed(self):
self.init()
self.module._get_device = Mock(return_value={})
self.module._delete_device = Mock(return_value=False)
with self.assertRaises(CommandError) as cm:
self.module.remove_alarm('123456789')
self.assertEqual(str(cm.exception), 'Error removing alarm')
def test_remove_alarm_check_parameters(self):
self.init()
self.module._get_device = Mock(return_value=None)
with self.assertRaises(InvalidParameter) as cm:
self.module.remove_alarm('123456789')
self.assertEqual(str(cm.exception), 'Alarm does not exist')
def test_toggle_alarm_disable(self):
self.init()
self.module._get_device = Mock(return_value={'enabled': True})
self.module._update_device = Mock(return_value=True)
enabled = self.module.toggle_alarm('123456789')
self.assertFalse(enabled)
self.module._update_device.assert_called_with('123456789', {'enabled': False})
def test_toggle_alarm_enable(self):
self.init()
self.module._get_device = Mock(return_value={'enabled': False})
self.module._update_device = Mock(return_value=True)
enabled = self.module.toggle_alarm('123456789')
self.assertTrue(enabled)
self.module._update_device.assert_called_with('123456789', {'enabled': True})
def test_toggle_alarm_failed(self):
self.init()
self.module._get_device = Mock(return_value={'enabled': True})
self.module._update_device = Mock(return_value=False)
with self.assertRaises(CommandError) as cm:
self.module.toggle_alarm('123456789')
self.assertEqual(str(cm.exception), 'Error updating alarm')
def test_toggle_alarm_check_parameters(self):
self.init()
self.module._get_device = Mock(return_value=None)
with self.assertRaises(InvalidParameter) as cm:
self.module.toggle_alarm('123456789')
self.assertEqual(str(cm.exception), 'Alarm does not exist')
def test__set_today_is_non_working_day(self):
self.init(start=False, mocks=False)
is_today_non_working_day_mock = self.session.make_mock_command('is_today_non_working_day', True)
self.session.add_mock_command(is_today_non_working_day_mock)
self.module._set_tomorrow_is_non_working_day = Mock()
self.session.start_module(self.module)
self.module._set_today_is_non_working_day()
self.assertTrue(self.module.today_is_non_working_day)
self.session.assert_command_called_with('is_today_non_working_day', None, to='parameters')
def test__set_today_is_non_working_day_failed(self):
self.init(start=False, mocks=False)
is_today_non_working_day_mock = self.session.make_mock_command('is_today_non_working_day', True, fail=True)
self.session.add_mock_command(is_today_non_working_day_mock)
self.module._set_tomorrow_is_non_working_day = Mock()
self.session.start_module(self.module)
self.module._set_tomorrow_is_non_working_day = Mock()
try:
self.module._set_today_is_non_working_day()
except:
self.fail('_set_today_is_non_working_day should not raise exception')
@patch('backend.alarmclock.date')
def test__set_tomorrow_is_non_working_day(self, date_mock):
today = datetime.date(2021,12,15)
date_mock.today.return_value = today
self.init(start=False, mocks=False)
is_module_loaded = self.session.make_mock_command('is_module_loaded', True)
self.session.add_mock_command(is_module_loaded)
is_non_working_day_mock = self.session.make_mock_command('is_non_working_day', True)
self.session.add_mock_command(is_non_working_day_mock)
self.module._set_today_is_non_working_day = Mock()
self.session.start_module(self.module)
self.module._set_tomorrow_is_non_working_day()
self.assertTrue(self.module.tomorrow['is_non_working_day'])
self.assertEqual(self.module.tomorrow['date'], datetime.date(2021, 12, 16))
self.session.assert_command_called_with('is_non_working_day', {'day': '2021-12-16'}, to='parameters')
@patch('backend.alarmclock.date')
def test__set_tomorrow_is_non_working_day_failed(self, date_mock):
today = datetime.date(2021,12,15)
date_mock.today.return_value = today
self.init(start=False, mocks=False)
is_module_loaded = self.session.make_mock_command('is_module_loaded', True)
self.session.add_mock_command(is_module_loaded)
is_non_working_day_mock = self.session.make_mock_command('is_non_working_day', True, fail=True)
self.session.add_mock_command(is_non_working_day_mock)
self.module._set_today_is_non_working_day = Mock()
self.session.start_module(self.module)
try:
self.module._set_tomorrow_is_non_working_day()
except:
self.fail('_set_tomorrow_is_non_working_day should not raise exception')
@patch('backend.alarmclock.Timer')
def test__trigger_alarm(self, timer_mock):
self.init()
alarm = self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'nonWorkingDays': True,
'time': {
'hour': 12,
'minute': 0,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
'volume': 50,
})
self.module.tomorrow = {
'date': datetime.date(2021, 12, 16),
'nonWorkingDay': False
}
self.module._trigger_alarm({'hour': 12, 'minute': 0}, 'tue')
self.session.assert_event_called_with('alarmclock.alarm.triggered', {
'hour': 12,
'minute': 0,
'timeout': 10,
'volume': 50,
})
timer_mock.assert_called_with(600, self.module._stop_alarm, [alarm['uuid']])
def test__trigger_alarm_with_alarm_disabled(self):
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': False,
'nonWorkingDays': True,
'time': {
'hour': 12,
'minute': 0,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
})
self.module.tomorrow = {
'date': datetime.date(2021, 12, 16),
'nonWorkingDay': False
}
self.module._trigger_alarm({'hour': 12, 'minute': 0}, 'tue')
self.assertEqual(self.session.event_call_count('alarmclock.alarm.triggered'), 0)
def test__trigger_alarm_with_not_good_time(self):
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'nonWorkingDays': True,
'time': {
'hour': 12,
'minute': 12,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
})
self.module.tomorrow = {
'date': datetime.date(2021, 12, 16),
'nonWorkingDay': False
}
self.module._trigger_alarm({'hour': 12, 'minute': 0}, 'tue')
self.assertEqual(self.session.event_call_count('alarmclock.alarm.triggered'), 0)
def test__trigger_alarm_on_working_day(self):
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'nonWorkingDays': False,
'time': {
'hour': 12,
'minute': 0,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
})
self.module.tomorrow = {
'date': datetime.date(2021, 12, 16),
'nonWorkingDay': False
}
self.module.today_is_non_working_day = True
self.module._trigger_alarm({'hour': 12, 'minute': 0}, 'tue')
self.assertEqual(self.session.event_call_count('alarmclock.alarm.triggered'), 0)
def test__trigger_alarm_on_disabled_day(self):
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'nonWorkingDays': True,
'time': {
'hour': 12,
'minute': 0,
},
'timeout': 10,
'days': {'mon': True, 'tue': False, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
})
self.module.tomorrow = {
'date': datetime.date(2021, 12, 16),
'nonWorkingDay': False
}
self.module.today_is_non_working_day = True
self.module._trigger_alarm({'hour': 12, 'minute': 0}, 'tue')
self.assertEqual(self.session.event_call_count('alarmclock.alarm.triggered'), 0)
def test__stop_alarm(self):
self.init()
device = {
'name': 'Alarm',
'type': 'alarmclock',
'time': {
'hour': 12,
'minute': 0,
},
'enabled': True,
'timeout': 10,
'volume': 50,
}
self.module._get_device = Mock(return_value=device)
timer_mock = Mock()
self.module.stop_timers['1234567789'] = timer_mock
self.module._stop_alarm('1234567789')
self.session.assert_event_called_with('alarmclock.alarm.stopped', {
'hour': 12,
'minute': 0,
'timeout': 10,
'snoozed': False,
'volume': 50,
})
timer_mock.cancel.assert_called()
self.assertEqual(len(self.module.stop_timers.keys()), 0)
def test__stop_alarm_alarm_not_found(self):
self.init()
self.module._get_device = Mock(return_value=None)
self.module._stop_alarm('1234567789')
self.assertEqual(self.session.event_call_count('alarmclock.alarm.stopped'), 0)
@patch('backend.alarmclock.datetime')
def test__schedule_alarm_for_today(self, datetime_mock):
datetime_mock.now.return_value = datetime.datetime(2021, 12, 16, 12, 0)
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'nonWorkingDays': False,
'time': {
'hour': 12,
'minute': 10,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
'volume': 50,
})
self.module.today_is_non_working_day = False
self.module.tomorrow = {
'date': datetime.date(2021, 12, 17),
'is_non_working_day': False
}
self.module._schedule_alarm()
self.session.assert_event_called_with('alarmclock.alarm.scheduled', {
'hour': 12,
'minute': 10,
'timeout': 10,
'volume': 50,
})
@patch('backend.alarmclock.datetime')
def test__schedule_alarm_for_today_but_disabled(self, datetime_mock):
datetime_mock.now.return_value = datetime.datetime(2021, 12, 16, 12, 0)
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': False,
'nonWorkingDays': False,
'time': {
'hour': 12,
'minute': 10,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
})
self.module.today_is_non_working_day = False
self.module.tomorrow = {
'date': datetime.date(2021, 12, 17),
'is_non_working_day': False
}
self.module._schedule_alarm()
self.assertEqual(self.session.event_call_count('alarmclock.alarm.scheduled'), 0)
@patch('backend.alarmclock.datetime')
def test__schedule_alarm_for_today_but_non_working_day(self, datetime_mock):
datetime_mock.now.return_value = datetime.datetime(2021, 12, 16, 12, 0)
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'nonWorkingDays': False,
'time': {
'hour': 12,
'minute': 10,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': True, 'fri': True, 'sat': True, 'sun': True},
})
self.module.today_is_non_working_day = True
self.module.tomorrow = {
'date': datetime.date(2021, 12, 17),
'is_non_working_day': True
}
self.module._schedule_alarm()
self.assertEqual(self.session.event_call_count('alarmclock.alarm.scheduled'), 0)
@patch('backend.alarmclock.datetime')
def test__schedule_alarm_for_tomorrow(self, datetime_mock):
datetime_mock.now.return_value = datetime.datetime(2021, 12, 16, 12, 0)
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': True,
'nonWorkingDays': False,
'time': {
'hour': 12,
'minute': 10,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': False, 'fri': True, 'sat': True, 'sun': True},
'volume': 50,
})
self.module.today_is_non_working_day = False
self.module.tomorrow = {
'date': datetime.date(2021, 12, 17),
'is_non_working_day': False
}
self.module._schedule_alarm()
self.session.assert_event_called_with('alarmclock.alarm.scheduled', {
'hour': 12,
'minute': 10,
'timeout': 10,
'volume': 50,
})
@patch('backend.alarmclock.datetime')
def test__schedule_alarm_for_tomorrow_but_disabled(self, datetime_mock):
datetime_mock.now.return_value = datetime.datetime(2021, 12, 16, 12, 0)
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': False,
'nonWorkingDays': False,
'time': {
'hour': 12,
'minute': 10,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': False, 'fri': True, 'sat': True, 'sun': True},
})
self.module.today_is_non_working_day = False
self.module.tomorrow = {
'date': datetime.date(2021, 12, 17),
'is_non_working_day': False
}
self.module._schedule_alarm()
self.assertEqual(self.session.event_call_count('alarmclock.alarm.scheduled'), 0)
@patch('backend.alarmclock.datetime')
def test__schedule_alarm_for_tomorrow_but_non_working_day(self, datetime_mock):
datetime_mock.now.return_value = datetime.datetime(2021, 12, 16, 12, 0)
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': False,
'nonWorkingDays': False,
'time': {
'hour': 12,
'minute': 10,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': False, 'fri': True, 'sat': True, 'sun': True},
})
self.module.today_is_non_working_day = False
self.module.tomorrow = {
'date': datetime.date(2021, 12, 17),
'is_non_working_day': True
}
self.module._schedule_alarm()
self.assertEqual(self.session.event_call_count('alarmclock.alarm.scheduled'), 0)
@patch('backend.alarmclock.datetime')
def test__schedule_alarm_no_alarm_for_today_and_tomorrow(self, datetime_mock):
datetime_mock.now.return_value = datetime.datetime(2021, 12, 16, 12, 0)
self.init()
self.module._add_device({
'type': 'alarmclock',
'name': 'Alarm',
'enabled': False,
'nonWorkingDays': True,
'time': {
'hour': 12,
'minute': 10,
},
'timeout': 10,
'days': {'mon': True, 'tue': True, 'wed': True, 'thu': False, 'fri': False, 'sat': True, 'sun': True},
})
self.module.tomorrow = {
'date': datetime.date(2021, 12, 17),
'is_non_working_day': False
}
self.module._schedule_alarm()
self.assertEqual(self.session.event_call_count('alarmclock.alarm.scheduled'), 0)
class TestAlarmclockAlarmTriggeredEvent(unittest.TestCase):
def setUp(self):
logging.basicConfig(level=logging.FATAL, format='%(asctime)s %(name)s:%(lineno)d %(levelname)s : %(message)s')
self.session = session.TestSession(self)
self.event = self.session.setup_event(AlarmclockAlarmTriggeredEvent)
def test_event_params(self):
self.assertEqual(self.event.EVENT_PARAMS, [
"hour",
"minute",
"timeout",
"volume",
])
class TestAlarmclockAlarmScheduledEvent(unittest.TestCase):
def setUp(self):
logging.basicConfig(level=logging.FATAL, format='%(asctime)s %(name)s:%(lineno)d %(levelname)s : %(message)s')
self.session = session.TestSession(self)
self.event = self.session.setup_event(AlarmclockAlarmScheduledEvent)
def test_event_params(self):
self.assertEqual(self.event.EVENT_PARAMS, [
"hour",
"minute",
"timeout",
"volume",
])
class TestAlarmclockAlarmStoppedEvent(unittest.TestCase):
def setUp(self):
logging.basicConfig(level=logging.FATAL, format='%(asctime)s %(name)s:%(lineno)d %(levelname)s : %(message)s')
self.session = session.TestSession(self)
self.event = self.session.setup_event(AlarmclockAlarmStoppedEvent)
def test_event_params(self):
self.assertEqual(self.event.EVENT_PARAMS, [
"hour",
"minute",
"timeout",
"snoozed",
"volume",
])
if __name__ == '__main__':
# coverage run --omit="*/lib/python*/*","test_*" --concurrency=thread test_alarmclock.py; coverage report -m -i
unittest.main()
| 37.268595
| 155
| 0.594707
| 3,085
| 27,057
| 4.969854
| 0.066451
| 0.088051
| 0.050874
| 0.049896
| 0.867923
| 0.855596
| 0.832703
| 0.814375
| 0.786264
| 0.775567
| 0
| 0.029745
| 0.271871
| 27,057
| 725
| 156
| 37.32
| 0.74849
| 0.005618
| 0
| 0.709516
| 0
| 0.006678
| 0.149134
| 0.027953
| 0
| 0
| 0
| 0
| 0.131886
| 1
| 0.070117
| false
| 0
| 0.018364
| 0
| 0.095159
| 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
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
5a59b6d3ffcb6d255b417a5c891c207f479b6aee
| 142
|
py
|
Python
|
temboo/core/Library/Flickr/People/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 7
|
2016-03-07T02:07:21.000Z
|
2022-01-21T02:22:41.000Z
|
temboo/core/Library/Flickr/People/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | null | null | null |
temboo/core/Library/Flickr/People/__init__.py
|
jordanemedlock/psychtruths
|
52e09033ade9608bd5143129f8a1bfac22d634dd
|
[
"Apache-2.0"
] | 8
|
2016-06-14T06:01:11.000Z
|
2020-04-22T09:21:44.000Z
|
from temboo.Library.Flickr.People.FindByEmail import FindByEmail, FindByEmailInputSet, FindByEmailResultSet, FindByEmailChoreographyExecution
| 71
| 141
| 0.901408
| 11
| 142
| 11.636364
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049296
| 142
| 1
| 142
| 142
| 0.948148
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 1
| 0
| true
| 0
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| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
5a7614606a78b19b2ac4c553e8c971426bd468d5
| 118
|
py
|
Python
|
philoseismos/segy/drawing/__init__.py
|
sir-dio/old-philoseismos
|
4c830971641313abd95693b24965ede261c6824b
|
[
"MIT"
] | 1
|
2019-10-27T14:03:00.000Z
|
2019-10-27T14:03:00.000Z
|
philoseismos/segy/drawing/__init__.py
|
sir-dio/old-philoseismos
|
4c830971641313abd95693b24965ede261c6824b
|
[
"MIT"
] | null | null | null |
philoseismos/segy/drawing/__init__.py
|
sir-dio/old-philoseismos
|
4c830971641313abd95693b24965ede261c6824b
|
[
"MIT"
] | null | null | null |
from philoseismos.segy.drawing.wiggle import wiggle_matrix
from philoseismos.segy.drawing.imshow import imshow_matrix
| 39.333333
| 58
| 0.881356
| 16
| 118
| 6.375
| 0.5
| 0.313725
| 0.392157
| 0.529412
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.067797
| 118
| 2
| 59
| 59
| 0.927273
| 0
| 0
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| true
| 0
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| 1
| 1
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| 0
| 1
| 0
|
0
| 8
|
ce56313f7fb743543c978bfd696ee80063e5c795
| 23,855
|
py
|
Python
|
api/tests/python/end_points/name_requests/test_nr_actions.py
|
sumesh-aot/namex
|
53e11aed5ea550b71b7b983f1b57b65db5a06766
|
[
"Apache-2.0"
] | 1
|
2020-02-21T05:49:14.000Z
|
2020-02-21T05:49:14.000Z
|
api/tests/python/end_points/name_requests/test_nr_actions.py
|
sumesh-aot/namex
|
53e11aed5ea550b71b7b983f1b57b65db5a06766
|
[
"Apache-2.0"
] | null | null | null |
api/tests/python/end_points/name_requests/test_nr_actions.py
|
sumesh-aot/namex
|
53e11aed5ea550b71b7b983f1b57b65db5a06766
|
[
"Apache-2.0"
] | null | null | null |
"""
Test HTTP endpoints for Name Requests.
"""
import pytest
import json
import datetime
from .configuration import API_BASE_URI
# Import token and claims if you need it
# from ..common import token_header, claims
from ..common.http import build_test_query, build_request_uri
from ..common.logging import log_request_path
from tests.python.common.test_name_request_utils import \
assert_field_is_mapped, assert_field_equals_value, assert_field_is_lt_value
from .test_setup_utils.test_helpers import \
assert_names_are_mapped_correctly, assert_applicant_is_mapped_correctly, \
create_draft_nr, create_approved_nr, create_cancelled_nr, patch_nr
from namex.models import State
from namex.constants import NameRequestActions
# Define our data
# Check NR number is the same because these are PATCH and call change_nr
def build_test_input_fields():
return {
'additionalInfo': '',
'consentFlag': None,
'consent_dt': None,
'corpNum': '',
'entity_type_cd': 'CR',
'expirationDate': None,
'furnished': 'N',
'hasBeenReset': False,
# 'lastUpdate': None,
'natureBusinessInfo': 'Test',
# 'nrNum': '',
# 'nwpta': '',
# 'previousNr': '',
# 'previousRequestId': '',
# 'previousStateCd': '',
'priorityCd': 'N',
# 'priorityDate': None,
'requestTypeCd': 'CR',
'request_action_cd': 'NEW',
# 'source': 'NAMEREQUEST',
# 'state': 'DRAFT',
# 'stateCd': 'DRAFT',
'submitCount': 1,
# 'submittedDate': None,
'submitter_userid': 'name_request_service_account',
'userId': 'name_request_service_account',
'xproJurisdiction': ''
}
@pytest.mark.skip
def test_create_draft_nr(client, jwt, app):
"""
TODO: Just a test stub that was moved from another file that was removed.
This needs to be completed at some point.
Create a basic draft NR.
:param client:
:param jwt:
:param app:
:return:
"""
request_uri = API_BASE_URI
test_params = [{}]
query = build_test_query(test_params)
path = build_request_uri(request_uri, query)
log_request_path(path)
response = client.get(path)
assert response.status_code == 200
payload = json.loads(response.data)
assert payload is not None
@pytest.mark.skip
def test_create_conditional_nr(client, jwt, app):
"""
TODO: Just a test stub that was moved from another file that was removed.
This needs to be completed at some point.
Create a basic conditional NR.
:param client:
:param jwt:
:param app:
:return:
"""
request_uri = API_BASE_URI
test_params = [{}]
query = build_test_query(test_params)
path = build_request_uri(request_uri, query)
log_request_path(path)
response = client.get(path)
assert response.status_code == 200
payload = json.loads(response.data)
assert payload is not None
@pytest.mark.skip
def test_create_reserved_nr(client, jwt, app):
"""
TODO: Just a test stub that was moved from another file that was removed.
This needs to be completed at some point.
Create a basic reserved NR
:param client:
:param jwt:
:param app:
:return:
"""
request_uri = API_BASE_URI
test_params = [{}]
query = build_test_query(test_params)
path = build_request_uri(request_uri, query)
log_request_path(path)
response = client.get(path)
assert response.status_code == 200
payload = json.loads(response.data)
assert payload is not None
def test_draft_patch_edit_data(client, jwt, app):
"""
Test the Name Request's data fields. Excludes associations 'names' and 'applicant' - we have other tests for those.
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr.get('stateCd') == 'PENDING_PAYMENT'
assert draft_nr is not None
# Take the response and edit it
# Add another name to the mix
nr_data = {
'names': draft_nr.get('names'),
'applicants': draft_nr.get('applicants'),
'entity_type_cd': 'FR',
'corpNum': 'TESTCORP123',
# 'homeJurisNum': 'TESTHOME123',
'additionalInfo': 'Testing additional info',
'natureBusinessInfo': 'Testing nature of business info',
'priorityCd': 'Y',
'requestTypeCd': 'CR'
}
added_names = [
{
'name': 'BLUE HERON ADVENTURE TOURS LTD.',
'choice': 2,
'designation': 'LTD.',
'name_type_cd': 'CO',
'consent_words': '',
'conflict1': 'BLUE HERON TOURS LTD.',
'conflict1_num': '0515211'
},
{
'name': 'BLUE HERON ISLAND TOURS LTD.',
'choice': 3,
'designation': 'LTD.',
'name_type_cd': 'CO',
'consent_words': '',
'conflict1': 'BLUE HERON TOURS LTD.',
'conflict1_num': '0515211'
}
]
nr_data['names'].extend(added_names)
# Change the designation, we'll check to make sure it's mapped in the response
nr_data['names'][0]['designation'] = 'INC.'
# TODO: More applicant testing
# updated_applicant = {}
# nr_data['applicant'] = updated_applicant
patch_response = patch_nr(client, NameRequestActions.EDIT.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
print('Assert that stateCd == DRAFT: ' + str(bool(patched_nr.get('stateCd') == 'DRAFT')))
assert patched_nr.get('stateCd') == 'PENDING_PAYMENT'
# Check names
assert_names_are_mapped_correctly(nr_data.get('names'), patched_nr.get('names'))
# Check applicant
assert_applicant_is_mapped_correctly(nr_data.get('applicants'), patched_nr.get('applicants'))
# Check data
expected_field_values = {
'additionalInfo': 'Testing additional info',
'consentFlag': None,
'consent_dt': None,
'corpNum': 'TESTCORP123',
# 'homeJurisNum': 'TESTHOME123',
'entity_type_cd': 'FR',
'requestTypeCd': 'CR',
'request_action_cd': 'NEW',
'expirationDate': None,
'furnished': 'N',
'hasBeenReset': False,
# 'lastUpdate': None,
'natureBusinessInfo': 'Testing nature of business info',
# 'nrNum': '',
# 'nwpta': '',
# 'previousNr': '',
# 'previousRequestId': '',
# 'previousStateCd': '',
'priorityCd': 'Y',
# 'priorityDate': None,
'source': 'NAMEREQUEST',
'state': 'PENDING_PAYMENT',
'stateCd': 'PENDING_PAYMENT',
'submitCount': 1,
# 'submittedDate': None,
'submitter_userid': 'name_request_service_account',
'userId': 'name_request_service_account',
'xproJurisdiction': ''
}
for key, value in expected_field_values.items():
assert_field_equals_value(patched_nr, key, value)
def test_draft_patch_edit_request_action_and_entity_type(client, jwt, app):
"""
This is not designed to test all combinations, for those tests see test_nr_request_combos.
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data, which is initially set to:
# test_input_fields = {
# 'request_action_cd': 'NEW'
# 'entity_type_cd': 'CR'
# 'requestTypeCd': 'CR'
# ...
# }
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
# Take the response and edit it
# Change the request action
nr_data = {
'request_action_cd': 'CHG',
'entity_type_cd': 'RLC', # Limited Liability Co.
'requestTypeCd': 'CLC' # From request_type_mapping in namex.constants
}
patch_response = patch_nr(client, NameRequestActions.EDIT.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
assert patched_nr.get('stateCd') == 'PENDING_PAYMENT'
# Check data
expected_field_values = {
'request_action_cd': 'CHG',
'entity_type_cd': 'RLC',
'requestTypeCd': 'CLC'
}
for key, value in expected_field_values.items():
assert_field_equals_value(patched_nr, key, value)
def test_draft_patch_edit_and_repatch(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
# Take the response and edit it
# Add another name to the mix
nr_data = {
'names': draft_nr.get('names'),
'applicants': draft_nr.get('applicants')
}
added_names = [
{
'name': 'BLUE HERON ADVENTURE TOURS LTD.',
'choice': 2,
'designation': 'LTD.',
'name_type_cd': 'CO',
'consent_words': '',
'conflict1': 'BLUE HERON TOURS LTD.',
'conflict1_num': '0515211'
},
{
'name': 'BLUE HERON ISLAND TOURS LTD.',
'choice': 3,
'designation': 'LTD.',
'name_type_cd': 'CO',
'consent_words': '',
'conflict1': 'BLUE HERON TOURS LTD.',
'conflict1_num': '0515211'
}
]
nr_data['names'].extend(added_names)
# updated_applicant = {}
# nr_data['applicant'] = updated_applicant
patch_response = patch_nr(client, NameRequestActions.EDIT.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response #1: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
assert patched_nr.get('stateCd') == 'PENDING_PAYMENT'
# TODO: Check applicant(s)
# Check names
assert_names_are_mapped_correctly(nr_data.get('names'), patched_nr.get('names'))
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
# Check actions (write a util for this)
"""
Patch the NR again with the response to make sure everything runs as expected
"""
patch_response = patch_nr(client, NameRequestActions.EDIT.value, patched_nr.get('id'), patched_nr)
patched_nr = json.loads(patch_response.data)
re_patched_nr = json.loads(patch_response.data)
assert re_patched_nr is not None
print('PATCH Response #2: \n' + json.dumps(re_patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
assert re_patched_nr.get('stateCd') == 'PENDING_PAYMENT'
# TODO: Check applicant(s)
# Check names
assert_names_are_mapped_correctly(patched_nr.get('names'), re_patched_nr.get('names'))
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
def test_draft_patch_upgrade(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
assert_field_equals_value(draft_nr, 'priorityCd', 'N')
# Take the response and edit it
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.UPGRADE.value, draft_nr.get('id'), nr_data)
assert patch_response.status_code == 200
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
assert patched_nr.get('stateCd') == State.PENDING_PAYMENT
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
# Check actions (write a util for this)
# assert_field_equals_value(patched_nr, 'payment_token', '')
assert_field_equals_value(patched_nr, 'priorityCd', 'Y')
# assert_field_equals_value(patched_nr, 'priorityDate', '')
def test_draft_patch_cancel(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
# Take the response and edit it
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.CANCEL.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
print('Assert that stateCd == CANCELLED: ' + str(bool(patched_nr.get('stateCd') == 'CANCELLED')))
assert patched_nr.get('stateCd') == State.CANCELLED
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
# Check actions (write a util for this)
@pytest.mark.skip
def test_draft_patch_cancel_with_invalid_states(client, jwt, app):
"""
TODO: This isn't working finish it!
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
custom_names = [{
'name': 'BLUE HERON TOURS LTD.',
'choice': 1,
'designation': 'LTD.',
'name_type_cd': 'CO',
'consent_words': '',
'conflict1': 'BLUE HERON TOURS LTD.',
'conflict1_num': '0515211',
# Custom name has a corp num to make it 'consumed'
'corpNum': '12345'
}]
input_fields['names'] = custom_names
test_nr = create_approved_nr(client, input_fields)
assert test_nr is not None
# Take the response and edit it
# Expect this to fail as we
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.CANCEL.value, test_nr.get('id'), nr_data)
# Ensure the request failed
print('Assert that the request failed: ' + str(bool(patch_response.status_code == 500)))
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
# There should be an error message in the response
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
assert isinstance(patched_nr.get('message'), str)
def test_draft_patch_cancel_with_consumed_name(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
custom_names = [{
'name': 'BLUE HERON TOURS LTD.',
'choice': 1,
'designation': 'LTD.',
'name_type_cd': 'CO',
'consent_words': '',
'conflict1': 'BLUE HERON TOURS LTD.',
'conflict1_num': '0515211',
# Custom name has a corp num to make it 'consumed'
'corpNum': '12345'
}]
input_fields['names'] = custom_names
test_nr = create_approved_nr(client, input_fields)
assert test_nr is not None
# Take the response and edit it
# Expect this to fail as we
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.CANCEL.value, test_nr.get('id'), nr_data)
# Ensure the request failed
print('Assert that the request failed: ' + str(bool(patch_response.status_code == 500)))
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
# There should be an error message in the response
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
assert isinstance(patched_nr.get('message'), str)
def test_draft_patch_cancel_with_expired_nr(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
# Set the expirationDate to a previous day
input_fields['expirationDate'] = datetime.date.today() - datetime.timedelta(days=2)
custom_names = [{
'name': 'BLUE HERON TOURS LTD.',
'choice': 1,
'designation': 'LTD.',
'name_type_cd': 'CO',
'consent_words': '',
'conflict1': 'BLUE HERON TOURS LTD.',
'conflict1_num': '0515211',
}]
input_fields['names'] = custom_names
test_nr = create_approved_nr(client, input_fields)
assert test_nr is not None
# Take the response and edit it
# Expect this to fail as we
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.CANCEL.value, test_nr.get('id'), nr_data)
# Ensure the request failed
print('Assert that the request failed: ' + str(bool(patch_response.status_code == 500)))
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
# There should be an error message in the response
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
assert isinstance(patched_nr.get('message'), str)
def test_draft_patch_refund(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
# Take the response and edit it
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.REQUEST_REFUND.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
assert patched_nr.get('stateCd') == State.REFUND_REQUESTED
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
def test_draft_patch_reapply(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
def do_reapply():
# Take the response and edit it
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.REAPPLY.value, draft_nr.get('id'), nr_data)
updated_nr = None
if patch_response.status_code == 200:
updated_nr = json.loads(patch_response.data)
assert updated_nr is not None
print('PATCH Response: \n' + json.dumps(updated_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
return updated_nr, patch_response.status_code
# Re-apply
patched_nr, status_code = do_reapply()
# Check state
assert patched_nr.get('stateCd') == draft_nr.get('stateCd')
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
assert_field_equals_value(patched_nr, 'submitCount', 2)
# assert_field_equals_value(patched_nr, 'expirationDate', '')
# Re-apply
patched_nr, status_code = do_reapply()
assert_field_equals_value(patched_nr, 'submitCount', 3)
# Re-apply
patched_nr, status_code = do_reapply()
# The submitCount should never be greater than 3, this should now fail with a 500
assert status_code == 500
def test_draft_patch_reapply_historical(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
# Take the response and edit it
nr_data = {
'request_action_cd': 'REH'
}
patch_response = patch_nr(client, NameRequestActions.REAPPLY.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
assert patched_nr.get('stateCd') == draft_nr.get('stateCd')
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
assert_field_is_lt_value(patched_nr, 'submitCount', 4)
# assert_field_equals_value(patched_nr, 'expirationDate', '')
# Take the response and edit it
nr_data = {
'request_action_cd': 'REST'
}
patch_response = patch_nr(client, NameRequestActions.REAPPLY.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
assert patched_nr.get('stateCd') == draft_nr.get('stateCd')
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
assert_field_is_lt_value(patched_nr, 'submitCount', 4)
# assert_field_equals_value(patched_nr, 'expirationDate', '')
def test_draft_patch_resend(client, jwt, app):
"""
Setup:
Test:
:param client:
:param jwt:
:param app:
:return:
"""
# Define our data
input_fields = build_test_input_fields()
post_response = create_draft_nr(client, input_fields)
# Assign the payload to new nr var
draft_nr = json.loads(post_response.data)
assert draft_nr is not None
# Take the response and edit it
nr_data = {}
patch_response = patch_nr(client, NameRequestActions.RESEND.value, draft_nr.get('id'), nr_data)
patched_nr = json.loads(patch_response.data)
assert patched_nr is not None
print('PATCH Response: \n' + json.dumps(patched_nr, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
# Check state
print('Assert that stateCd == DRAFT: ' + str(bool(patched_nr.get('stateCd') == 'DRAFT')))
assert patched_nr.get('stateCd') == draft_nr.get('stateCd')
# Check NR number is the same because these are PATCH and call change_nr
assert_field_is_mapped(draft_nr, patched_nr, 'nrNum')
| 30.388535
| 121
| 0.648166
| 3,070
| 23,855
| 4.801954
| 0.092182
| 0.053724
| 0.017705
| 0.0194
| 0.850631
| 0.827296
| 0.791005
| 0.77676
| 0.752883
| 0.742437
| 0
| 0.008054
| 0.234919
| 23,855
| 784
| 122
| 30.427296
| 0.799682
| 0.228757
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| 0.747283
| 0
| 0
| 0.166846
| 0.006356
| 0
| 0
| 0
| 0.008929
| 0.211957
| 1
| 0.046196
| false
| 0
| 0.027174
| 0.002717
| 0.078804
| 0.054348
| 0
| 0
| 0
| null | 0
| 0
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| 1
| 1
| 1
| 1
| 1
| 1
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| 1
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| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
ce5c163a64f3db595d407df3e55164d9d0dc1435
| 70
|
py
|
Python
|
python/examples/main.py
|
cat-in-the-dark/ludum_43_game
|
737bc08e6e2b7e3a92bb958b7c0a8ec0674d5a20
|
[
"MIT"
] | null | null | null |
python/examples/main.py
|
cat-in-the-dark/ludum_43_game
|
737bc08e6e2b7e3a92bb958b7c0a8ec0674d5a20
|
[
"MIT"
] | null | null | null |
python/examples/main.py
|
cat-in-the-dark/ludum_43_game
|
737bc08e6e2b7e3a92bb958b7c0a8ec0674d5a20
|
[
"MIT"
] | null | null | null |
import line_prisma_draw
def update(dt):
line_prisma_draw.draw(dt)
| 17.5
| 29
| 0.785714
| 12
| 70
| 4.25
| 0.583333
| 0.392157
| 0.54902
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128571
| 70
| 4
| 29
| 17.5
| 0.836066
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
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| 0
| null | 1
| 1
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
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| 1
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| 0
| null | 0
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| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
ce8e1fd419674cb9bc3dbe051f4a3e4ddc60acf7
| 2,312
|
py
|
Python
|
tests/fixtures/defxmlschema/chapter13/example1330.py
|
nimish/xsdata
|
7afe2781b66982428cc1731f53c065086acd35c1
|
[
"MIT"
] | null | null | null |
tests/fixtures/defxmlschema/chapter13/example1330.py
|
nimish/xsdata
|
7afe2781b66982428cc1731f53c065086acd35c1
|
[
"MIT"
] | null | null | null |
tests/fixtures/defxmlschema/chapter13/example1330.py
|
nimish/xsdata
|
7afe2781b66982428cc1731f53c065086acd35c1
|
[
"MIT"
] | null | null | null |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class BaseType:
"""
:ivar a:
:ivar b:
:ivar c:
:ivar d:
:ivar e:
:ivar f:
:ivar g:
:ivar x:
"""
a: Optional[int] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
b: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
c: str = field(
default="c",
metadata=dict(
type="Attribute"
)
)
d: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
e: str = field(
init=False,
default="e",
metadata=dict(
type="Attribute"
)
)
f: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
g: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
x: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
@dataclass
class DerivedType:
"""
:ivar a:
:ivar b:
:ivar c:
:ivar d:
:ivar e:
:ivar f:
:ivar g:
:ivar x:
"""
a: Optional[int] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
b: str = field(
default="b",
metadata=dict(
type="Attribute"
)
)
c: str = field(
default="c2",
metadata=dict(
type="Attribute"
)
)
d: str = field(
init=False,
default="d",
metadata=dict(
type="Attribute"
)
)
e: str = field(
init=False,
default="e",
metadata=dict(
type="Attribute"
)
)
f: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute",
required=True
)
)
g: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
x: Optional[str] = field(
default=None,
metadata=dict(
type="Attribute"
)
)
| 17.648855
| 40
| 0.435986
| 209
| 2,312
| 4.822967
| 0.15311
| 0.190476
| 0.253968
| 0.396825
| 0.863095
| 0.787698
| 0.787698
| 0.787698
| 0.731151
| 0.652778
| 0
| 0.000776
| 0.442474
| 2,312
| 130
| 41
| 17.784615
| 0.781226
| 0.061851
| 0
| 0.566038
| 0
| 0
| 0.072526
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.018868
| 0
| 0.188679
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
ce8f4774c8a9c4e06b577cff91f2beba52e74e7d
| 136
|
py
|
Python
|
DSA Coding/Trees/Implementations/InorderTraversal.py
|
prathimacode-hub/WIE-WoC
|
f412f297a57249af98213bf4a747c897f2d4c035
|
[
"MIT"
] | 8
|
2022-03-01T09:09:20.000Z
|
2022-03-03T05:36:01.000Z
|
DSA Coding/Trees/Implementations/InorderTraversal.py
|
prathimacode-hub/WIE-WoC
|
f412f297a57249af98213bf4a747c897f2d4c035
|
[
"MIT"
] | 52
|
2022-03-02T13:52:46.000Z
|
2022-03-04T03:03:17.000Z
|
DSA Coding/Trees/Implementations/InorderTraversal.py
|
prathimacode-hub/WIE-WoC
|
f412f297a57249af98213bf4a747c897f2d4c035
|
[
"MIT"
] | 23
|
2022-03-01T06:39:34.000Z
|
2022-03-03T09:24:40.000Z
|
def inorderTraversal(self, A):
return [] if not A else self.inorderTraversal(A.left) +[A.val] + self.inorderTraversal(A.right)
| 45.333333
| 104
| 0.698529
| 19
| 136
| 5
| 0.578947
| 0.421053
| 0.442105
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161765
| 136
| 2
| 105
| 68
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
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| null | 0
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| 0
| 0
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| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
ceb74dcd8c3ae3976a6e80a22a07664dba184684
| 165
|
py
|
Python
|
tests/test_issues.py
|
NextThought/umysqldb
|
67732d997e9d0c81f2e196590bff3fdd53b15021
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_issues.py
|
NextThought/umysqldb
|
67732d997e9d0c81f2e196590bff3fdd53b15021
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_issues.py
|
NextThought/umysqldb
|
67732d997e9d0c81f2e196590bff3fdd53b15021
|
[
"BSD-3-Clause"
] | null | null | null |
def test_issue_8():
"""umysqldb.converters should be available since Django 1.6 requires them."""
from umysqldb.converters import conversions, Thing2Literal
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| 0
| 1
| 0
|
0
| 7
|
cecab4b3ea21cbc33cbe1e2bce5082320952ff13
| 5,382
|
py
|
Python
|
test/test_Animation_init.py
|
toddrme2178/AnimateImages
|
d7a944f04d008d7ce652cfa4e6dc29cbf950b5dd
|
[
"MIT"
] | 1
|
2018-03-07T19:36:52.000Z
|
2018-03-07T19:36:52.000Z
|
test/test_Animation_init.py
|
toddrme2178/AnimateImages
|
d7a944f04d008d7ce652cfa4e6dc29cbf950b5dd
|
[
"MIT"
] | 125
|
2017-09-28T00:51:21.000Z
|
2020-05-03T16:10:27.000Z
|
test/test_Animation_init.py
|
toddrme2178/AnimateImages
|
d7a944f04d008d7ce652cfa4e6dc29cbf950b5dd
|
[
"MIT"
] | 2
|
2017-08-04T17:57:25.000Z
|
2019-01-25T16:15:00.000Z
|
import pytest
import numpy as np
from Animate.Movie import Movie
from Animate.Animation import Animation
import matplotlib as mpl
def test_ratio_2():
m = Movie(dt=1.0/14, height_ratio=2)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (1, 1)
assert a.gs.get_height_ratios() is None
m = Movie(dt=1.0/14, height_ratio=2)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
m.add_trace(np.arange(4))
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (2, 1)
assert a.gs.get_height_ratios() == (2, 1)
m = Movie(dt=1.0 / 14, height_ratio=2)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
m.add_trace(np.arange(4))
m.add_axis('x', 'y')
m.add_trace(np.arange(4), axis=1)
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (3, 1)
assert a.gs.get_height_ratios() == (4, 1, 1)
def test_ratio_1():
m = Movie(dt=1.0 / 14, height_ratio=1)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (1, 1)
assert a.gs.get_height_ratios() is None
m = Movie(dt=1.0 / 14, height_ratio=1)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
m.add_trace(np.arange(4))
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (2, 1)
assert a.gs.get_height_ratios() == (1, 1)
m = Movie(dt=1.0 / 14, height_ratio=1)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
m.add_trace(np.arange(4))
m.add_axis('x', 'y')
m.add_trace(np.arange(4), axis=1)
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (3, 1)
assert a.gs.get_height_ratios() == (2, 1, 1)
def test_ratio_1p5():
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (1, 1)
assert a.gs.get_height_ratios() is None
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
m.add_trace(np.arange(4))
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (2, 1)
assert a.gs.get_height_ratios() == (1.5, 1)
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
m.add_trace(np.arange(4))
m.add_axis('x', 'y')
m.add_trace(np.arange(4), axis=1)
a = Animation(m)
a._init_draw()
assert a.gs.get_geometry() == (3, 1)
assert a.gs.get_height_ratios() == (3, 1, 1)
def test_n_axis():
with pytest.raises(RuntimeError) as ex:
m = Movie(dt=1.0 / 14, height_ratio=1.5)
_ = Animation(m)
assert 'At least one image is needed' in str(ex.value)
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
a = Animation(m)
a._init_draw()
assert a.n_axes == 0
assert a.n_images == 1
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_image(img, style='dark_img')
a = Animation(m)
a._init_draw()
assert a.n_axes == 0
assert a.n_images == 2
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
with pytest.raises(RuntimeError) as ex:
a = Animation(m)
a._init_draw()
assert 'Axis 0 with no traces' in str(ex.value)
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
m.add_axis('x', 'y')
m.add_trace(np.arange(4))
a = Animation(m)
a._init_draw()
assert a.n_axes == 1
assert a.n_images == 1
def test_x_data():
m = Movie(dt=1.0 / 14, height_ratio=1.5)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
a = Animation(m)
assert np.allclose(a.x_data, np.arange(4) * 1.0 / 14)
m = Movie(dt=0.5, height_ratio=1.5)
img = np.arange(1000).reshape(40, 5, 5)
m.add_image(img, style='dark_img')
a = Animation(m)
assert np.allclose(a.x_data, np.arange(40) * 0.5)
m = Movie(dt=1)
img = np.arange(100).reshape(5, 20)
m.add_image(img, animation_type='window', window_size=5)
m.add_axis('x', 'y')
m.add_trace(np.arange(20))
a = Animation(m)
assert np.allclose(a.x_data, np.arange(20) - 5 // 2)
m = Movie(dt=1)
img = np.arange(100).reshape(5, 20)
m.add_image(img, animation_type='window', window_size=7, window_step=2)
m.add_axis('x', 'y')
m.add_trace(np.arange(20))
a = Animation(m)
assert np.allclose(a.x_data, np.arange(20) - 7 // 2)
def test_style():
_ = Movie(style='default')
assert mpl.rcParams['figure.facecolor'] == 'w'
_ = Movie(style='dark_background')
assert mpl.rcParams['figure.facecolor'] == 'black'
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| 75
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| 974
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| 3.165298
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| 181
| 76
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| 0
| 0
|
0
| 7
|
0c8054008a2103244cba214ea7b7d61c9da1114a
| 5,329
|
py
|
Python
|
u8g2/logisoso78_tn.py
|
tve/mpy-lib
|
9f102459c61a5be424291a277e421bd1fc16843a
|
[
"MIT"
] | 6
|
2020-02-27T11:17:54.000Z
|
2020-12-04T10:14:26.000Z
|
u8g2/logisoso78_tn.py
|
tve/mpy-lib
|
9f102459c61a5be424291a277e421bd1fc16843a
|
[
"MIT"
] | 4
|
2020-07-29T14:07:04.000Z
|
2021-05-19T05:10:33.000Z
|
u8g2/logisoso78_tn.py
|
tve/mpy-lib
|
9f102459c61a5be424291a277e421bd1fc16843a
|
[
"MIT"
] | 3
|
2020-05-16T08:15:16.000Z
|
2021-09-30T10:39:37.000Z
|
data=b'\x12\x00\x05\x05\x06\x07\x06\x07\x07\x2d\x5d\x00\xfb\x4e\xec\x4d\x00\x00\x00\x00\x00\x05\x15\x20\x07\x00\x00\x04\xca\x01\x2a\x42\xa1\x08\xb5\xc7\xdb\xa1\xcf\x83\xc3\x39\xce\x50\x0a\x73\x98\x82\x9c\x0d\x45\x1c\x42\x11\x5f\xf8\x80\x20\xba\xb2\xa1\x8b\x4d\x2f\x82\xd1\x9b\xd8\x85\xb6\xd2\x89\x0f\x08\xe1\x13\x8a\x38\x84\x32\x0e\x72\x22\x85\x39\x4c\x51\x86\x73\x9c\x01\x1e\xfa\xbc\x06\x00\x2b\x14\x9d\x47\x7d\xc6\x95\x32\xd5\xbf\xf4\x81\xff\x07\x16\xa5\x4c\xf5\x2f\x01\x2c\x16\xca\x23\xdd\x71\x07\x41\x8e\x81\x84\x24\x74\x02\x45\x0c\x33\x9c\xb1\x23\x0c\x00\x2d\x0a\x9d\x42\xcd\xc6\xc1\xff\x07\x16\x2e\x13\x8a\x22\x05\x72\x07\x41\x8e\x81\x84\x24\x74\x02\x11\x47\x21\x06\x00\x2f\x64\xa5\xd3\x04\xca\xb7\xa2\x57\x5a\xd1\x2b\xad\xe8\x95\x56\xf4\x4a\x2b\x7a\xd1\xca\x56\xf4\xa2\x95\xad\xe8\x45\x2b\x5b\xd1\x8b\x56\xf4\x4a\x2b\x7a\xa5\x15\xbd\xd2\x8a\x5e\x69\x45\xaf\xb4\xa2\x17\xad\x6c\x45\x2f\x5a\xd9\x8a\x5e\xb4\xb2\x15\xbd\x68\x65\x2b\x7a\xd1\x8a\x5e\x69\x45\xaf\xb4\xa2\x57\x5a\xd1\x8b\x56\xb6\xa2\x17\xad\x6c\x45\x2f\x5a\xd9\x8a\x5e\xb4\xb2\x15\xbd\x68\x65\x2b\x7a\xd1\x00\x30\x56\xa7\xb3\x04\xc6\x5f\xb2\x1f\x3b\x49\x0b\x66\x6d\x5b\x5d\xfa\xce\x07\x82\xf3\x01\xa1\x38\xa7\x29\xcc\x62\x06\xd3\x96\xb1\xbc\x45\x28\x51\x09\x4b\x54\x82\x32\x93\xa0\x4c\xfa\xff\xff\xff\xff\x7f\x33\x09\x4b\x54\x84\x12\x15\xb1\xbc\x45\x30\x6d\x21\xcc\x62\x88\x73\x1a\xf3\x01\xc1\x7c\x20\x40\x5f\xea\xd6\xd6\xb2\x67\xcd\xc9\x3e\x3b\x79\x00\x31\x23\x93\x33\x06\xca\x93\x3a\xb4\x3a\x2c\xd3\x14\x87\x3c\x03\x0a\x1f\xf8\x03\x50\x80\x86\x53\x16\xa4\x24\xf5\xff\xff\xff\xff\xff\xff\x03\x32\x78\xa7\xd3\x04\xca\x5f\xb2\x1f\x3b\x49\x0b\x66\x6d\x5b\x5d\xf2\xd0\x07\x82\xf3\x01\xa1\x38\xa7\x29\xcc\x62\x06\xd3\x96\xb1\xbc\x45\x28\x51\x09\x4b\x54\x82\x22\x95\xa0\x4c\xfa\x49\x45\x28\x51\x11\x49\x5c\x04\x12\x99\x51\xcc\x85\x0c\x94\x29\x01\x65\xf6\xb2\x99\xbd\xda\xcc\x5e\x36\xa3\x99\xbd\x6c\x46\x33\x7b\xd9\xcc\x5e\x36\xa3\x99\xbd\x6c\x46\x33\x7b\xd9\xcc\x5e\x36\xa3\x99\xbd\x6c\x46\x33\x7b\xd9\x8c\x66\x36\xa3\x99\xbd\x6c\x46\x33\x7b\xd9\x8c\x66\xf6\x07\xfe\xff\x80\x04\x33\x63\xa7\xd3\xfc\xc9\xc1\xff\x3f\x20\xed\x65\x33\x9a\xd9\xcb\x66\x34\xb3\x97\xcd\xec\xd5\x66\xf6\x6a\x33\x7b\xd9\x8c\x66\xf6\xb2\x19\xcd\x6c\x66\x3b\xf9\xc1\x91\x95\xea\x44\xa9\x59\xc9\x4a\x3b\x9b\xe1\x0c\x5f\xfa\xd2\x55\x3e\xf1\x4a\x57\xff\xc7\x95\xae\x20\x61\x2a\xa6\x88\x0b\x39\xe0\x32\x96\xc6\x88\x66\x35\xc3\x31\x0f\xf9\xc0\x60\x3e\x20\x9c\x2f\x75\x6b\x6b\xd9\xb3\xe6\x74\x1b\x5f\x48\x00\x34\x5a\xa7\xb3\x04\xca\x9b\xd2\xd5\xb8\xd2\xd5\xb8\xd2\xd5\xb8\xd2\xd5\xb8\xd2\x55\x7c\xe1\x4a\x57\xf1\x85\x2b\x5d\xc5\x17\xae\x74\x15\x57\xba\x1a\x57\xba\x1a\x57\x8c\xd2\x14\xa3\x34\xc5\x28\x4d\x31\x0a\x53\x8e\xc2\x94\xa3\x30\xe5\x28\x4c\x39\xca\x52\x90\xb2\x14\xa4\x2c\x05\x29\x4b\x41\x8a\x52\x92\xa2\x94\xa4\xa8\x0f\xfc\xff\x01\x69\x2a\x5d\xfd\x7f\x0a\x00\x35\x66\xa7\xb3\x04\xc6\xc1\xff\x3f\xc0\x75\xf5\xff\x57\x92\xa7\x88\x87\x75\xea\x43\x1f\x08\xce\x07\x04\xf3\x81\xa1\x7c\x80\x20\x1f\x20\xc8\x07\x8a\x01\x1d\x47\x38\x8b\x11\x4d\x5b\x04\xf3\x96\xb0\x44\x25\x28\x52\x09\xca\x4c\x82\x32\xa9\xa9\x74\xf5\xff\x3a\x35\x69\x33\x09\x8a\x54\x84\x12\x15\xb1\xbc\x45\x30\x6d\x21\xcc\x62\x88\x73\x9c\xf2\x01\xc1\x7c\x20\x40\x5f\xea\xd6\xd6\xb2\x77\xc9\xc9\x3e\x3b\x79\x00\x36\x80\xa7\xb3\x04\xc6\x1f\xc2\x1f\x3b\x49\x0b\x66\x6d\x5b\x5d\xfa\xce\x07\x82\xf3\x01\xa1\x38\xc7\x21\xcc\x62\x06\xd3\x96\xb1\xbc\x45\x28\x51\x09\x4b\x54\x82\x32\xe9\xba\xfa\xcf\x20\x4f\x11\x0f\xeb\x94\x97\x3e\x10\x9c\x0f\x08\xe6\x03\x43\xf9\xc0\x50\x3e\x40\x90\x0f\x14\x03\x32\xce\x70\x54\x23\x9a\xb6\x08\xe6\x2d\x61\x81\x4b\x58\xa2\x12\x14\xa9\x04\x65\xd2\xff\x9f\x54\xc2\x12\x15\xa1\x44\x45\x2c\x6f\x11\x4c\x5b\x08\xb3\x18\xe2\x9c\xc6\x7c\x40\x30\x1f\x08\x90\xa7\xba\xb5\xb5\xec\x59\x73\xb2\xcf\x4e\x1e\x00\x37\x5c\xa7\xb3\x04\xc6\xc1\x07\x8e\xf0\x81\xff\x1f\xa0\xe2\x12\x94\xb8\x04\x25\x2e\x41\x81\x8b\x50\xe0\x22\x14\xb8\x08\x05\x2e\x42\x79\xcb\x50\xde\x32\x12\xb8\xf0\x65\x2f\x7c\x6d\x2f\x7c\x6d\x2f\x7c\x6d\x2f\x7c\xb5\x99\xbd\xf0\xd5\x5e\xf8\xda\x5e\xf8\xda\x5e\xf8\xda\x5e\xf8\xda\x5e\xf8\x6a\x33\x7b\xe1\xab\xcd\xec\x85\xaf\xf6\xc2\xd7\xf6\xc2\xd7\xf6\xc2\x57\x12\x00\x38\x8e\xa7\xd3\x04\xca\x5f\xb2\x1f\x3b\x49\x0b\x66\x6d\x5b\x5d\xfa\xce\x07\x82\xf3\x01\xa1\x38\xa7\x29\xcc\x62\x06\xd3\x96\xb1\xbc\x45\x28\x51\x09\x4b\x54\x82\x22\x95\xa0\x4c\xfa\x9f\x54\xc2\x12\x15\xa1\x44\x45\x2c\x6f\x11\x4c\x5b\x08\xb3\x18\xe2\x9c\xc6\x7c\x40\x30\x1f\x08\xd0\x97\xba\xb5\xb1\x6d\x75\xc9\x43\x1f\x08\xce\x07\x84\xe2\x18\xa7\x30\x8b\x19\x4c\x5b\xc6\xf2\x16\xa1\x44\x25\x2c\x51\x09\x8a\x54\x82\x32\xe9\x7f\x52\x09\x4b\x54\x84\x12\x15\xb1\xbc\x45\x30\x6d\x21\xcc\x62\x88\x73\x1a\xf3\x01\xc1\x7c\x20\x40\x5f\xea\xd6\xd6\xb2\x67\xcd\xc9\x3e\x3b\x79\x00\x39\x81\xa7\xb3\x04\xc6\x5f\xb2\x1f\x3b\xc9\xeb\x65\x6d\x5b\x5d\xfa\xce\x07\x82\xf3\x01\xa1\x38\xa7\x29\xcc\x62\x06\xd3\x96\xb1\xbc\x45\x28\x51\x09\x4b\x54\x82\x22\x95\xa0\x4c\xfa\xff\x93\x56\x5c\x82\x12\x97\xb0\x3c\x26\x30\xad\x11\xcc\x72\x84\x73\xa0\xf1\x81\x62\x7c\xa0\x20\x1f\x20\xca\x07\x06\xf3\x01\xe1\x7c\x20\x40\x5f\xf2\x16\x24\x14\x97\x18\xa5\xab\x7f\x9d\x9a\xb4\x99\x04\x45\x2a\x42\x89\x8a\x58\xde\x22\x98\xb6\x10\x66\x31\xc4\x39\x4e\xf9\x80\x60\x3e\x10\xa0\x2f\x75\x6b\x6b\xd9\xbb\xe4\x64\x9f\x9d\x3c\x00\x3a\x20\x0a\x2b\x55\x72\x07\x41\x8e\x81\x84\x24\x74\x02\x11\x47\x21\x3e\xf8\x75\x82\x1c\x03\x09\x49\xe8\x04\x22\x8e\x42\x0c\x00\x00\x00\x00\x04\xff\xff\x00\x00'
| 2,664.5
| 5,328
| 0.749672
| 1,332
| 5,329
| 2.999249
| 0.178679
| 0.013517
| 0.018023
| 0.015019
| 0.427284
| 0.382979
| 0.377722
| 0.36796
| 0.344681
| 0.344681
| 0
| 0.335586
| 0.000188
| 5,329
| 1
| 5,329
| 5,329
| 0.414227
| 0
| 0
| 0
| 0
| 1
| 0.998311
| 0.998311
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
0c870562187279ce7dffd80b627760c007246db5
| 69
|
py
|
Python
|
Semester 5 (PIP)/assignment1/prog7.py
|
MartyMiniac/ITER-Assignment
|
a7b355f40cc52a337ad90bb8328e54c4a9534530
|
[
"MIT"
] | 14
|
2020-11-11T08:48:58.000Z
|
2022-02-26T03:59:05.000Z
|
Semester 5 (PIP)/assignment1/prog7.py
|
SKSTCODE42/ITER-Assignment
|
a7b355f40cc52a337ad90bb8328e54c4a9534530
|
[
"MIT"
] | 4
|
2020-11-12T13:31:14.000Z
|
2021-06-21T05:41:34.000Z
|
Semester 5 (PIP)/assignment1/prog7.py
|
SKSTCODE42/ITER-Assignment
|
a7b355f40cc52a337ad90bb8328e54c4a9534530
|
[
"MIT"
] | 10
|
2020-11-07T15:09:20.000Z
|
2022-02-26T03:56:50.000Z
|
r='1'
print(r)
r+='2'+r
print(r)
r+='3'+r
print(r)
r+='4'+r
print(r)
| 7.666667
| 8
| 0.507246
| 19
| 69
| 1.842105
| 0.315789
| 0.685714
| 0.6
| 0.457143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.065574
| 0.115942
| 69
| 9
| 9
| 7.666667
| 0.508197
| 0
| 0
| 0.5
| 0
| 0
| 0.057971
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 7
|
0cc5629108331b9a8de79b1cc834e85c145ffd8a
| 5,070
|
py
|
Python
|
lpd/metrics/tp_tn_fp_fn.py
|
RoySadaka/lpd
|
921454d9730d8228f4b0ca5349b0558ebd123c65
|
[
"MIT"
] | 4
|
2020-10-02T10:04:19.000Z
|
2022-01-19T12:45:02.000Z
|
lpd/metrics/tp_tn_fp_fn.py
|
RoySadaka/lpd
|
921454d9730d8228f4b0ca5349b0558ebd123c65
|
[
"MIT"
] | 1
|
2020-10-06T17:43:57.000Z
|
2020-10-06T17:47:43.000Z
|
lpd/metrics/tp_tn_fp_fn.py
|
RoySadaka/lpd
|
921454d9730d8228f4b0ca5349b0558ebd123c65
|
[
"MIT"
] | 1
|
2020-10-03T17:21:32.000Z
|
2020-10-03T17:21:32.000Z
|
import torch as T
from lpd.metrics.metric_base import MetricConfusionMatrixBase
from lpd.enums.confusion_matrix_based_metric import ConfusionMatrixBasedMetric as metric
class TruePositives(MetricConfusionMatrixBase):
"""
Agrs:
num_classes - The number of classes in the classification
labels - names of classes, for nice prints, if not provided, the class index will be the label
predictions_to_classes_convertor - (optional) a function that takes y_pred batch and y_true batch and converts it into class indices batch where
each index represents the chosen class
if None:
torch.max with indices will be used for multi-class.
threshold will be used for binary or multilabel.
threshold - for binary or multilable classification
"""
def __init__(self, num_classes, labels=None, predictions_to_classes_convertor=None, threshold=0.5, name='TruePositives'):
super(TruePositives, self).__init__(name, num_classes, labels, predictions_to_classes_convertor, threshold)
def __call__(self, y_pred: T.Tensor, y_true: T.Tensor):
result_per_class = self.get_stats(metric.TP)
return result_per_class
class TrueNegatives(MetricConfusionMatrixBase):
"""
Agrs:
num_classes - The number of classes in the classification
labels - names of classes, for nice prints, if not provided, the class index will be the label
predictions_to_classes_convertor - (optional) a function that takes y_pred batch and y_true batch and converts it into class indices batch where
each index represents the chosen class
if None:
torch.max with indices will be used for multi-class.
threshold will be used for binary or multilabel.
threshold - for binary or multilable classification
"""
def __init__(self, num_classes, labels=None, predictions_to_classes_convertor=None, threshold=0.5, name='TrueNegatives'):
super(TrueNegatives, self).__init__(name, num_classes, labels, predictions_to_classes_convertor, threshold)
def __call__(self, y_pred: T.Tensor, y_true: T.Tensor):
result_per_class = self.get_stats(metric.TN)
return result_per_class
class FalseNegatives(MetricConfusionMatrixBase):
"""
Agrs:
num_classes - The number of classes in the classification
labels - names of classes, for nice prints, if not provided, the class index will be the label
predictions_to_classes_convertor - (optional) a function that takes y_pred batch and y_true batch and converts it into class indices batch where
each index represents the chosen class
if None:
torch.max with indices will be used for multi-class.
threshold will be used for binary or multilabel.
threshold - for binary or multilable classification
"""
def __init__(self, num_classes, labels=None, predictions_to_classes_convertor=None, threshold=0.5, name='FalseNegatives'):
super(FalseNegatives, self).__init__(name, num_classes, labels, predictions_to_classes_convertor, threshold)
def __call__(self, y_pred: T.Tensor, y_true: T.Tensor):
result_per_class = self.get_stats(metric.FN)
return result_per_class
class FalsePositives(MetricConfusionMatrixBase):
"""
Agrs:
num_classes - The number of classes in the classification
labels - names of classes, for nice prints, if not provided, the class index will be the label
predictions_to_classes_convertor - (optional) a function that takes y_pred batch and y_true batch and converts it into class indices batch where
each index represents the chosen class
if None:
torch.max with indices will be used for multi-class.
threshold will be used for binary or multilabel.
threshold - for binary or multilable classification
"""
def __init__(self, num_classes, labels=None, predictions_to_classes_convertor=None, threshold=0.5, name='FalsePositives'):
super(FalsePositives, self).__init__(name, num_classes, labels, predictions_to_classes_convertor, threshold)
def __call__(self, y_pred: T.Tensor, y_true: T.Tensor):
result_per_class = self.get_stats(metric.FP)
return result_per_class
| 61.084337
| 156
| 0.620316
| 578
| 5,070
| 5.205882
| 0.153979
| 0.03988
| 0.079761
| 0.115653
| 0.879694
| 0.854769
| 0.854769
| 0.854769
| 0.854769
| 0.854769
| 0
| 0.002352
| 0.329191
| 5,070
| 83
| 157
| 61.084337
| 0.882388
| 0.550493
| 0
| 0.296296
| 0
| 0
| 0.027735
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.296296
| false
| 0
| 0.111111
| 0
| 0.703704
| 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
| 0
| 0
|
0
| 7
|
0cca5c4503bea48480a89825c905b04eaa33c6e0
| 18,551
|
py
|
Python
|
sdk/python/pulumi_proxmox/lxc_disk.py
|
huaxk/pulumi-proxmox
|
fbe5efdc000d12f35933a7cd53c360958c201baa
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
sdk/python/pulumi_proxmox/lxc_disk.py
|
huaxk/pulumi-proxmox
|
fbe5efdc000d12f35933a7cd53c360958c201baa
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
sdk/python/pulumi_proxmox/lxc_disk.py
|
huaxk/pulumi-proxmox
|
fbe5efdc000d12f35933a7cd53c360958c201baa
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
# 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
from . import outputs
from ._inputs import *
__all__ = ['LXCDiskArgs', 'LXCDisk']
@pulumi.input_type
class LXCDiskArgs:
def __init__(__self__, *,
container: pulumi.Input[str],
mp: pulumi.Input[str],
size: pulumi.Input[str],
slot: pulumi.Input[int],
storage: pulumi.Input[str],
acl: Optional[pulumi.Input[bool]] = None,
backup: Optional[pulumi.Input[bool]] = None,
mountoptions: Optional[pulumi.Input['LXCDiskMountoptionsArgs']] = None,
quota: Optional[pulumi.Input[bool]] = None,
replicate: Optional[pulumi.Input[bool]] = None,
shared: Optional[pulumi.Input[bool]] = None,
volume: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a LXCDisk resource.
"""
pulumi.set(__self__, "container", container)
pulumi.set(__self__, "mp", mp)
pulumi.set(__self__, "size", size)
pulumi.set(__self__, "slot", slot)
pulumi.set(__self__, "storage", storage)
if acl is not None:
pulumi.set(__self__, "acl", acl)
if backup is not None:
pulumi.set(__self__, "backup", backup)
if mountoptions is not None:
pulumi.set(__self__, "mountoptions", mountoptions)
if quota is not None:
pulumi.set(__self__, "quota", quota)
if replicate is not None:
pulumi.set(__self__, "replicate", replicate)
if shared is not None:
pulumi.set(__self__, "shared", shared)
if volume is not None:
pulumi.set(__self__, "volume", volume)
@property
@pulumi.getter
def container(self) -> pulumi.Input[str]:
return pulumi.get(self, "container")
@container.setter
def container(self, value: pulumi.Input[str]):
pulumi.set(self, "container", value)
@property
@pulumi.getter
def mp(self) -> pulumi.Input[str]:
return pulumi.get(self, "mp")
@mp.setter
def mp(self, value: pulumi.Input[str]):
pulumi.set(self, "mp", value)
@property
@pulumi.getter
def size(self) -> pulumi.Input[str]:
return pulumi.get(self, "size")
@size.setter
def size(self, value: pulumi.Input[str]):
pulumi.set(self, "size", value)
@property
@pulumi.getter
def slot(self) -> pulumi.Input[int]:
return pulumi.get(self, "slot")
@slot.setter
def slot(self, value: pulumi.Input[int]):
pulumi.set(self, "slot", value)
@property
@pulumi.getter
def storage(self) -> pulumi.Input[str]:
return pulumi.get(self, "storage")
@storage.setter
def storage(self, value: pulumi.Input[str]):
pulumi.set(self, "storage", value)
@property
@pulumi.getter
def acl(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "acl")
@acl.setter
def acl(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "acl", value)
@property
@pulumi.getter
def backup(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "backup")
@backup.setter
def backup(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "backup", value)
@property
@pulumi.getter
def mountoptions(self) -> Optional[pulumi.Input['LXCDiskMountoptionsArgs']]:
return pulumi.get(self, "mountoptions")
@mountoptions.setter
def mountoptions(self, value: Optional[pulumi.Input['LXCDiskMountoptionsArgs']]):
pulumi.set(self, "mountoptions", value)
@property
@pulumi.getter
def quota(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "quota")
@quota.setter
def quota(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "quota", value)
@property
@pulumi.getter
def replicate(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "replicate")
@replicate.setter
def replicate(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "replicate", value)
@property
@pulumi.getter
def shared(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "shared")
@shared.setter
def shared(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "shared", value)
@property
@pulumi.getter
def volume(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "volume")
@volume.setter
def volume(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "volume", value)
@pulumi.input_type
class _LXCDiskState:
def __init__(__self__, *,
acl: Optional[pulumi.Input[bool]] = None,
backup: Optional[pulumi.Input[bool]] = None,
container: Optional[pulumi.Input[str]] = None,
mountoptions: Optional[pulumi.Input['LXCDiskMountoptionsArgs']] = None,
mp: Optional[pulumi.Input[str]] = None,
quota: Optional[pulumi.Input[bool]] = None,
replicate: Optional[pulumi.Input[bool]] = None,
shared: Optional[pulumi.Input[bool]] = None,
size: Optional[pulumi.Input[str]] = None,
slot: Optional[pulumi.Input[int]] = None,
storage: Optional[pulumi.Input[str]] = None,
volume: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering LXCDisk resources.
"""
if acl is not None:
pulumi.set(__self__, "acl", acl)
if backup is not None:
pulumi.set(__self__, "backup", backup)
if container is not None:
pulumi.set(__self__, "container", container)
if mountoptions is not None:
pulumi.set(__self__, "mountoptions", mountoptions)
if mp is not None:
pulumi.set(__self__, "mp", mp)
if quota is not None:
pulumi.set(__self__, "quota", quota)
if replicate is not None:
pulumi.set(__self__, "replicate", replicate)
if shared is not None:
pulumi.set(__self__, "shared", shared)
if size is not None:
pulumi.set(__self__, "size", size)
if slot is not None:
pulumi.set(__self__, "slot", slot)
if storage is not None:
pulumi.set(__self__, "storage", storage)
if volume is not None:
pulumi.set(__self__, "volume", volume)
@property
@pulumi.getter
def acl(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "acl")
@acl.setter
def acl(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "acl", value)
@property
@pulumi.getter
def backup(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "backup")
@backup.setter
def backup(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "backup", value)
@property
@pulumi.getter
def container(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "container")
@container.setter
def container(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "container", value)
@property
@pulumi.getter
def mountoptions(self) -> Optional[pulumi.Input['LXCDiskMountoptionsArgs']]:
return pulumi.get(self, "mountoptions")
@mountoptions.setter
def mountoptions(self, value: Optional[pulumi.Input['LXCDiskMountoptionsArgs']]):
pulumi.set(self, "mountoptions", value)
@property
@pulumi.getter
def mp(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "mp")
@mp.setter
def mp(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "mp", value)
@property
@pulumi.getter
def quota(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "quota")
@quota.setter
def quota(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "quota", value)
@property
@pulumi.getter
def replicate(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "replicate")
@replicate.setter
def replicate(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "replicate", value)
@property
@pulumi.getter
def shared(self) -> Optional[pulumi.Input[bool]]:
return pulumi.get(self, "shared")
@shared.setter
def shared(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "shared", value)
@property
@pulumi.getter
def size(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "size")
@size.setter
def size(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "size", value)
@property
@pulumi.getter
def slot(self) -> Optional[pulumi.Input[int]]:
return pulumi.get(self, "slot")
@slot.setter
def slot(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "slot", value)
@property
@pulumi.getter
def storage(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "storage")
@storage.setter
def storage(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "storage", value)
@property
@pulumi.getter
def volume(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "volume")
@volume.setter
def volume(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "volume", value)
class LXCDisk(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
acl: Optional[pulumi.Input[bool]] = None,
backup: Optional[pulumi.Input[bool]] = None,
container: Optional[pulumi.Input[str]] = None,
mountoptions: Optional[pulumi.Input[pulumi.InputType['LXCDiskMountoptionsArgs']]] = None,
mp: Optional[pulumi.Input[str]] = None,
quota: Optional[pulumi.Input[bool]] = None,
replicate: Optional[pulumi.Input[bool]] = None,
shared: Optional[pulumi.Input[bool]] = None,
size: Optional[pulumi.Input[str]] = None,
slot: Optional[pulumi.Input[int]] = None,
storage: Optional[pulumi.Input[str]] = None,
volume: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
Create a LXCDisk resource with the given unique name, props, and options.
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: LXCDiskArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
Create a LXCDisk resource with the given unique name, props, and options.
:param str resource_name: The name of the resource.
:param LXCDiskArgs 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(LXCDiskArgs, 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,
acl: Optional[pulumi.Input[bool]] = None,
backup: Optional[pulumi.Input[bool]] = None,
container: Optional[pulumi.Input[str]] = None,
mountoptions: Optional[pulumi.Input[pulumi.InputType['LXCDiskMountoptionsArgs']]] = None,
mp: Optional[pulumi.Input[str]] = None,
quota: Optional[pulumi.Input[bool]] = None,
replicate: Optional[pulumi.Input[bool]] = None,
shared: Optional[pulumi.Input[bool]] = None,
size: Optional[pulumi.Input[str]] = None,
slot: Optional[pulumi.Input[int]] = None,
storage: Optional[pulumi.Input[str]] = None,
volume: 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__ = LXCDiskArgs.__new__(LXCDiskArgs)
__props__.__dict__["acl"] = acl
__props__.__dict__["backup"] = backup
if container is None and not opts.urn:
raise TypeError("Missing required property 'container'")
__props__.__dict__["container"] = container
__props__.__dict__["mountoptions"] = mountoptions
if mp is None and not opts.urn:
raise TypeError("Missing required property 'mp'")
__props__.__dict__["mp"] = mp
__props__.__dict__["quota"] = quota
__props__.__dict__["replicate"] = replicate
__props__.__dict__["shared"] = shared
if size is None and not opts.urn:
raise TypeError("Missing required property 'size'")
__props__.__dict__["size"] = size
if slot is None and not opts.urn:
raise TypeError("Missing required property 'slot'")
__props__.__dict__["slot"] = slot
if storage is None and not opts.urn:
raise TypeError("Missing required property 'storage'")
__props__.__dict__["storage"] = storage
__props__.__dict__["volume"] = volume
super(LXCDisk, __self__).__init__(
'proxmox:index/lXCDisk:LXCDisk',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
acl: Optional[pulumi.Input[bool]] = None,
backup: Optional[pulumi.Input[bool]] = None,
container: Optional[pulumi.Input[str]] = None,
mountoptions: Optional[pulumi.Input[pulumi.InputType['LXCDiskMountoptionsArgs']]] = None,
mp: Optional[pulumi.Input[str]] = None,
quota: Optional[pulumi.Input[bool]] = None,
replicate: Optional[pulumi.Input[bool]] = None,
shared: Optional[pulumi.Input[bool]] = None,
size: Optional[pulumi.Input[str]] = None,
slot: Optional[pulumi.Input[int]] = None,
storage: Optional[pulumi.Input[str]] = None,
volume: Optional[pulumi.Input[str]] = None) -> 'LXCDisk':
"""
Get an existing LXCDisk 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.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _LXCDiskState.__new__(_LXCDiskState)
__props__.__dict__["acl"] = acl
__props__.__dict__["backup"] = backup
__props__.__dict__["container"] = container
__props__.__dict__["mountoptions"] = mountoptions
__props__.__dict__["mp"] = mp
__props__.__dict__["quota"] = quota
__props__.__dict__["replicate"] = replicate
__props__.__dict__["shared"] = shared
__props__.__dict__["size"] = size
__props__.__dict__["slot"] = slot
__props__.__dict__["storage"] = storage
__props__.__dict__["volume"] = volume
return LXCDisk(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter
def acl(self) -> pulumi.Output[Optional[bool]]:
return pulumi.get(self, "acl")
@property
@pulumi.getter
def backup(self) -> pulumi.Output[Optional[bool]]:
return pulumi.get(self, "backup")
@property
@pulumi.getter
def container(self) -> pulumi.Output[str]:
return pulumi.get(self, "container")
@property
@pulumi.getter
def mountoptions(self) -> pulumi.Output[Optional['outputs.LXCDiskMountoptions']]:
return pulumi.get(self, "mountoptions")
@property
@pulumi.getter
def mp(self) -> pulumi.Output[str]:
return pulumi.get(self, "mp")
@property
@pulumi.getter
def quota(self) -> pulumi.Output[Optional[bool]]:
return pulumi.get(self, "quota")
@property
@pulumi.getter
def replicate(self) -> pulumi.Output[Optional[bool]]:
return pulumi.get(self, "replicate")
@property
@pulumi.getter
def shared(self) -> pulumi.Output[Optional[bool]]:
return pulumi.get(self, "shared")
@property
@pulumi.getter
def size(self) -> pulumi.Output[str]:
return pulumi.get(self, "size")
@property
@pulumi.getter
def slot(self) -> pulumi.Output[int]:
return pulumi.get(self, "slot")
@property
@pulumi.getter
def storage(self) -> pulumi.Output[str]:
return pulumi.get(self, "storage")
@property
@pulumi.getter
def volume(self) -> pulumi.Output[str]:
return pulumi.get(self, "volume")
| 36.09144
| 134
| 0.606921
| 2,046
| 18,551
| 5.290811
| 0.070381
| 0.113811
| 0.163233
| 0.095612
| 0.835196
| 0.801848
| 0.759815
| 0.728684
| 0.670485
| 0.641755
| 0
| 0.000074
| 0.270066
| 18,551
| 513
| 135
| 36.161793
| 0.79935
| 0.059458
| 0
| 0.771845
| 1
| 0
| 0.073477
| 0.01524
| 0
| 0
| 0
| 0
| 0
| 1
| 0.162621
| false
| 0.002427
| 0.01699
| 0.087379
| 0.276699
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
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| 0
| 0
| 0
| 0
|
0
| 7
|
0cf7e5b4c54bb7b95cfb8dd15f5397748eef32aa
| 5,266
|
py
|
Python
|
src/core/migrations/0009_auto_20171128_1543.py
|
mheppner/django-x10
|
8c80688ccd702e101b204b34f2b6722a3596db77
|
[
"MIT"
] | null | null | null |
src/core/migrations/0009_auto_20171128_1543.py
|
mheppner/django-x10
|
8c80688ccd702e101b204b34f2b6722a3596db77
|
[
"MIT"
] | null | null | null |
src/core/migrations/0009_auto_20171128_1543.py
|
mheppner/django-x10
|
8c80688ccd702e101b204b34f2b6722a3596db77
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.7 on 2017-11-28 20:43
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('core', '0008_auto_20171128_1215'),
]
operations = [
migrations.CreateModel(
name='OffScheduleConstraint',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('if_home', models.BooleanField(default=False, help_text='Only use this schedule if a real person is home')),
('schedule', models.ForeignKey(help_text='The schedule object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.Schedule')),
('unit', models.ForeignKey(help_text='The unit object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.Unit')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='OffSolarScheduleConstraint',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('if_home', models.BooleanField(default=False, help_text='Only use this schedule if a real person is home')),
('solarschedule', models.ForeignKey(help_text='The solar schedule object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.SolarSchedule')),
('unit', models.ForeignKey(help_text='The unit object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.Unit')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='OnScheduleConstraint',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('if_home', models.BooleanField(default=False, help_text='Only use this schedule if a real person is home')),
('schedule', models.ForeignKey(help_text='The schedule object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.Schedule')),
('unit', models.ForeignKey(help_text='The unit object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.Unit')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='OnSolarScheduleConstraint',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('if_home', models.BooleanField(default=False, help_text='Only use this schedule if a real person is home')),
('solarschedule', models.ForeignKey(help_text='The solar schedule object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.SolarSchedule')),
('unit', models.ForeignKey(help_text='The unit object for this relationship', on_delete=django.db.models.deletion.CASCADE, to='core.Unit')),
],
options={
'abstract': False,
},
),
migrations.AddField(
model_name='unit',
name='off_schedules',
field=models.ManyToManyField(blank=True, help_text='Automatic schedules to turn off the unit.', related_name='off_unit_set', through='core.OffScheduleConstraint', to='core.Schedule'),
),
migrations.AddField(
model_name='unit',
name='off_solar_schedules',
field=models.ManyToManyField(blank=True, help_text='Automatic solar schedules to turn off the unit.', related_name='off_unit_set', through='core.OffSolarScheduleConstraint', to='core.SolarSchedule'),
),
migrations.AddField(
model_name='unit',
name='on_schedules',
field=models.ManyToManyField(blank=True, help_text='Automatic schedules to turn on the unit.', related_name='on_unit_set', through='core.OnScheduleConstraint', to='core.Schedule'),
),
migrations.AddField(
model_name='unit',
name='on_solar_schedules',
field=models.ManyToManyField(blank=True, help_text='Automatic solar schedules to turn on the unit.', related_name='on_unit_set', through='core.OnSolarScheduleConstraint', to='core.SolarSchedule'),
),
migrations.AlterUniqueTogether(
name='onsolarscheduleconstraint',
unique_together=set([('solarschedule', 'unit')]),
),
migrations.AlterUniqueTogether(
name='onscheduleconstraint',
unique_together=set([('schedule', 'unit')]),
),
migrations.AlterUniqueTogether(
name='offsolarscheduleconstraint',
unique_together=set([('solarschedule', 'unit')]),
),
migrations.AlterUniqueTogether(
name='offscheduleconstraint',
unique_together=set([('schedule', 'unit')]),
),
]
| 52.138614
| 211
| 0.624193
| 544
| 5,266
| 5.90625
| 0.165441
| 0.039838
| 0.039216
| 0.061625
| 0.806411
| 0.78836
| 0.78836
| 0.766573
| 0.724868
| 0.694367
| 0
| 0.008357
| 0.250095
| 5,266
| 100
| 212
| 52.66
| 0.805267
| 0.012913
| 0
| 0.688172
| 1
| 0
| 0.285852
| 0.053705
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.032258
| 0
| 0.064516
| 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
|
0b34bcc60a7ba3507cd4daa4e5a9c2b1f58f0eeb
| 2,471
|
py
|
Python
|
alpyro_msgs/actionlib_tutorials/averagingaction.py
|
rho2/alpyro_msgs
|
b5a680976c40c83df70d61bb2db1de32a1cde8d3
|
[
"MIT"
] | 1
|
2020-12-13T13:07:10.000Z
|
2020-12-13T13:07:10.000Z
|
alpyro_msgs/actionlib_tutorials/averagingaction.py
|
rho2/alpyro_msgs
|
b5a680976c40c83df70d61bb2db1de32a1cde8d3
|
[
"MIT"
] | null | null | null |
alpyro_msgs/actionlib_tutorials/averagingaction.py
|
rho2/alpyro_msgs
|
b5a680976c40c83df70d61bb2db1de32a1cde8d3
|
[
"MIT"
] | null | null | null |
from typing import Final
from alpyro_msgs import RosMessage
from alpyro_msgs.actionlib_tutorials.averagingactionfeedback import AveragingActionFeedback
from alpyro_msgs.actionlib_tutorials.averagingactiongoal import AveragingActionGoal
from alpyro_msgs.actionlib_tutorials.averagingactionresult import AveragingActionResult
class AveragingAction(RosMessage):
__msg_typ__ = "actionlib_tutorials/AveragingAction"
__msg_def__ = "YWN0aW9ubGliX3R1dG9yaWFscy9BdmVyYWdpbmdBY3Rpb25Hb2FsIGFjdGlvbl9nb2FsCiAgc3RkX21zZ3MvSGVhZGVyIGhlYWRlcgogICAgdWludDMyIHNlcQogICAgdGltZSBzdGFtcAogICAgc3RyaW5nIGZyYW1lX2lkCiAgYWN0aW9ubGliX21zZ3MvR29hbElEIGdvYWxfaWQKICAgIHRpbWUgc3RhbXAKICAgIHN0cmluZyBpZAogIGFjdGlvbmxpYl90dXRvcmlhbHMvQXZlcmFnaW5nR29hbCBnb2FsCiAgICBpbnQzMiBzYW1wbGVzCmFjdGlvbmxpYl90dXRvcmlhbHMvQXZlcmFnaW5nQWN0aW9uUmVzdWx0IGFjdGlvbl9yZXN1bHQKICBzdGRfbXNncy9IZWFkZXIgaGVhZGVyCiAgICB1aW50MzIgc2VxCiAgICB0aW1lIHN0YW1wCiAgICBzdHJpbmcgZnJhbWVfaWQKICBhY3Rpb25saWJfbXNncy9Hb2FsU3RhdHVzIHN0YXR1cwogICAgdWludDggUEVORElORz0wCiAgICB1aW50OCBBQ1RJVkU9MQogICAgdWludDggUFJFRU1QVEVEPTIKICAgIHVpbnQ4IFNVQ0NFRURFRD0zCiAgICB1aW50OCBBQk9SVEVEPTQKICAgIHVpbnQ4IFJFSkVDVEVEPTUKICAgIHVpbnQ4IFBSRUVNUFRJTkc9NgogICAgdWludDggUkVDQUxMSU5HPTcKICAgIHVpbnQ4IFJFQ0FMTEVEPTgKICAgIHVpbnQ4IExPU1Q9OQogICAgYWN0aW9ubGliX21zZ3MvR29hbElEIGdvYWxfaWQKICAgICAgdGltZSBzdGFtcAogICAgICBzdHJpbmcgaWQKICAgIHVpbnQ4IHN0YXR1cwogICAgc3RyaW5nIHRleHQKICBhY3Rpb25saWJfdHV0b3JpYWxzL0F2ZXJhZ2luZ1Jlc3VsdCByZXN1bHQKICAgIGZsb2F0MzIgbWVhbgogICAgZmxvYXQzMiBzdGRfZGV2CmFjdGlvbmxpYl90dXRvcmlhbHMvQXZlcmFnaW5nQWN0aW9uRmVlZGJhY2sgYWN0aW9uX2ZlZWRiYWNrCiAgc3RkX21zZ3MvSGVhZGVyIGhlYWRlcgogICAgdWludDMyIHNlcQogICAgdGltZSBzdGFtcAogICAgc3RyaW5nIGZyYW1lX2lkCiAgYWN0aW9ubGliX21zZ3MvR29hbFN0YXR1cyBzdGF0dXMKICAgIHVpbnQ4IFBFTkRJTkc9MAogICAgdWludDggQUNUSVZFPTEKICAgIHVpbnQ4IFBSRUVNUFRFRD0yCiAgICB1aW50OCBTVUNDRUVERUQ9MwogICAgdWludDggQUJPUlRFRD00CiAgICB1aW50OCBSRUpFQ1RFRD01CiAgICB1aW50OCBQUkVFTVBUSU5HPTYKICAgIHVpbnQ4IFJFQ0FMTElORz03CiAgICB1aW50OCBSRUNBTExFRD04CiAgICB1aW50OCBMT1NUPTkKICAgIGFjdGlvbmxpYl9tc2dzL0dvYWxJRCBnb2FsX2lkCiAgICAgIHRpbWUgc3RhbXAKICAgICAgc3RyaW5nIGlkCiAgICB1aW50OCBzdGF0dXMKICAgIHN0cmluZyB0ZXh0CiAgYWN0aW9ubGliX3R1dG9yaWFscy9BdmVyYWdpbmdGZWVkYmFjayBmZWVkYmFjawogICAgaW50MzIgc2FtcGxlCiAgICBmbG9hdDMyIGRhdGEKICAgIGZsb2F0MzIgbWVhbgogICAgZmxvYXQzMiBzdGRfZGV2Cgo="
__md5_sum__ = "628678f2b4fa6a5951746a4a2d39e716"
action_goal: AveragingActionGoal
action_result: AveragingActionResult
action_feedback: AveragingActionFeedback
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0
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0b55dda43633af2b288c0e0319bca448e1ffe57e
| 84,705
|
py
|
Python
|
OED/d_shared_code_masked_skip_connection_seq2seq.py
|
adrianomundo/II2202-research-methodology-scientific-writing
|
39a7a07e1dabbd988f9b3e0c5c41a36a6d292df8
|
[
"Apache-2.0"
] | 1
|
2021-01-30T11:03:05.000Z
|
2021-01-30T11:03:05.000Z
|
OED/d_shared_code_masked_skip_connection_seq2seq.py
|
adrianomundo/II2202-research-methodology-scientific-writing
|
39a7a07e1dabbd988f9b3e0c5c41a36a6d292df8
|
[
"Apache-2.0"
] | null | null | null |
OED/d_shared_code_masked_skip_connection_seq2seq.py
|
adrianomundo/II2202-research-methodology-scientific-writing
|
39a7a07e1dabbd988f9b3e0c5c41a36a6d292df8
|
[
"Apache-2.0"
] | null | null | null |
import pathlib
import copy
import sys
import tensorflow as tf
import numpy as np
from tensorflow.python.ops import init_ops
from tensorflow.python.ops.rnn_cell_impl import _Linear, LSTMStateTuple, GRUCell, LSTMCell
from tensorflow.python.ops import variable_scope as vs
from utils import *
from tensorflow.contrib import seq2seq
class RLSTMCell(tf.nn.rnn_cell.BasicLSTMCell):
"""Basic LSTM recurrent network cell.
The implementation is based on: http://arxiv.org/abs/1409.2329.
We add forget_bias (default: 1) to the biases of the forget gate in order to
reduce the scale of forgetting in the beginning of the training.
It does not allow cell clipping, a projection layer, and does not
use peep-hole connections: it is the basic baseline.
For advanced models, please use the full @{tf.nn.rnn_cell.LSTMCell}
that follows.
"""
def __init__(self, num_units, forget_bias=1.0, state_is_tuple=True, activation=None, reuse=None, dense=None):
"""Initialize the basic LSTM cell.
Args:
num_units: int, The number of units in the LSTM cell.
forget_bias: float, The bias added to forget gates (see above).
Must set to `0.0` manually when restoring from CudnnLSTM-trained
checkpoints.
state_is_tuple: If True, accepted and returned states are 2-tuples of
the `c_state` and `m_state`. If False, they are concatenated
along the column axis. The latter behavior will soon be deprecated.
activation: Activation function of the inner states. Default: `tanh`.
reuse: (optional) Python boolean describing whether to reuse variables
in an existing scope. If not `True`, and the existing scope already has
the given variables, an error is raised.
When restoring from CudnnLSTM-trained checkpoints, must use
CudnnCompatibleLSTMCell instead.
"""
super(tf.nn.rnn_cell.BasicLSTMCell, self).__init__(_reuse=reuse)
if not state_is_tuple:
tf.logging.warn("%s: Using a concatenated state is slower and will soon be "
"deprecated. Use state_is_tuple=True.", self)
self._num_units = num_units
self._forget_bias = forget_bias
self._state_is_tuple = state_is_tuple
self._activation = activation or tf.nn.tanh
self._linear = None
self._dense = dense
def call(self, inputs, state):
"""Long short-term memory cell (LSTM).
Args:
inputs: `2-D` tensor with shape `[batch_size x input_size]`.
state: An `LSTMStateTuple` of state tensors, each shaped
`[batch_size x self.state_size]`, if `state_is_tuple` has been set to
`True`. Otherwise, a `Tensor` shaped
`[batch_size x 2 * self.state_size]`.
Returns:
A pair containing the new hidden state, and the new state (either a
`LSTMStateTuple` or a concatenated state, depending on
`state_is_tuple`).
"""
sigmoid = tf.sigmoid
# Parameters of gates are concatenated into one multiply for efficiency.
if self._state_is_tuple:
c, h = state
else:
c, h = tf.split(value=state, num_or_size_splits=2, axis=1)
if self._linear is None:
self._linear = _Linear([inputs, h], 4 * self._num_units, True)
i, j, f, o = tf.split(value=self._linear([inputs, h]), num_or_size_splits=4, axis=1)
new_c = (c * sigmoid(f + self._forget_bias) + sigmoid(i) * self._activation(j))
new_h_1 = self._activation(new_c) * sigmoid(o)
w_h, b_h = self.weight_bias([self._num_units, self._num_units], [self._num_units])
new_h_2 = sigmoid(tf.matmul(h, w_h) + b_h)
new_h = new_h_1 + new_h_2
if self._state_is_tuple:
new_state = LSTMStateTuple(new_c, new_h)
else:
new_state = tf.concat([new_c, new_h], 1)
return new_h, new_state
def weight_bias(self, W_shape, b_shape, bias_init=0.1):
"""Fully connected highway layer adopted from
https://github.com/fomorians/highway-fcn/blob/master/main.py
"""
W = tf.get_variable("weight_h_2", shape=W_shape, initializer=tf.truncated_normal_initializer(stddev=0.1))
b = tf.get_variable("bias_h_2", shape=b_shape)
return W, b
class RSLSTMCell(tf.nn.rnn_cell.BasicLSTMCell):
"""Basic LSTM recurrent network cell.
The implementation is based on: http://arxiv.org/abs/1409.2329.
We add forget_bias (default: 1) to the biases of the forget gate in order to
reduce the scale of forgetting in the beginning of the training.
It does not allow cell clipping, a projection layer, and does not
use peep-hole connections: it is the basic baseline.
For advanced models, please use the full @{tf.nn.rnn_cell.LSTMCell}
that follows.
"""
def __init__(self, num_units, forget_bias=1.0, state_is_tuple=True, activation=None, reuse=None, dense=None,
file_name='tweet', type='enc', component=1, partition=1):
"""Initialize the basic LSTM cell.
Args:
num_units: int, The number of units in the LSTM cell.
forget_bias: float, The bias added to forget gates (see above).
Must set to `0.0` manually when restoring from CudnnLSTM-trained
checkpoints.
state_is_tuple: If True, accepted and returned states are 2-tuples of
the `c_state` and `m_state`. If False, they are concatenated
along the column axis. The latter behavior will soon be deprecated.
activation: Activation function of the inner states. Default: `tanh`.
reuse: (optional) Python boolean describing whether to reuse variables
in an existing scope. If not `True`, and the existing scope already has
the given variables, an error is raised.
When restoring from CudnnLSTM-trained checkpoints, must use
CudnnCompatibleLSTMCell instead.
"""
super(tf.nn.rnn_cell.BasicLSTMCell, self).__init__(_reuse=reuse)
if not state_is_tuple:
tf.logging.warn("%s: Using a concatenated state is slower and will soon be "
"deprecated. Use state_is_tuple=True.", self)
self._num_units = num_units
self._forget_bias = forget_bias
self._state_is_tuple = state_is_tuple
self._activation = activation or tf.nn.tanh
self._linear = None
self._dense = dense
self._step = 0
self._file_name = file_name
self._type = type
self._component = component
self._partition = partition
if not os.path.exists('./weight/' + self._file_name):
os.makedirs('./weight/' + self._file_name)
if not os.path.exists('./weight/' + self._file_name + '/' + str(self._partition)):
os.makedirs('./weight/' + self._file_name + '/' + str(self._partition))
if not os.path.exists('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component)):
os.makedirs('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component))
if not os.path.exists('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(
self._component) + '/' + self._type):
os.makedirs('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(
self._component) + '/' + self._type)
def call(self, inputs, state):
"""Long short-term memory cell (LSTM).
Args:
inputs: `2-D` tensor with shape `[batch_size x input_size]`.
state: An `LSTMStateTuple` of state tensors, each shaped
`[batch_size x self.state_size]`, if `state_is_tuple` has been set to
`True`. Otherwise, a `Tensor` shaped
`[batch_size x 2 * self.state_size]`.
Returns:
A pair containing the new hidden state, and the new state (either a
`LSTMStateTuple` or a concatenated state, depending on
`state_is_tuple`).
"""
sigmoid = tf.sigmoid
self._step = self._step + 1
# Parameters of gates are concatenated into one multiply for efficiency.
if self._state_is_tuple:
c, h = state
else:
c, h = tf.split(value=state, num_or_size_splits=2, axis=1)
if self._linear is None:
self._linear = _Linear([inputs, h], 4 * self._num_units, True)
i, j, f, o = tf.split(value=self._linear([inputs, h]), num_or_size_splits=4, axis=1)
new_c = (c * sigmoid(f + self._forget_bias) + sigmoid(i) * self._activation(j))
new_h_1 = self._activation(new_c) * sigmoid(o)
w_h, b_h = self.weight_bias([self._num_units, self._num_units], [self._num_units])
new_h_2 = sigmoid(tf.matmul(h, w_h) + b_h)
masked_w1, masked_w2 = self.masked_weight(_load=False)
new_h = new_h_1 * masked_w1 + new_h_2 * masked_w2
if self._state_is_tuple:
new_state = LSTMStateTuple(new_c, new_h)
else:
new_state = tf.concat([new_c, new_h], 1)
return new_h, new_state
def weight_bias(self, W_shape, b_shape, bias_init=0.1):
"""Fully connected highway layer adopted from
https://github.com/fomorians/highway-fcn/blob/master/main.py
"""
W = tf.get_variable("weight_h_2", shape=W_shape, initializer=tf.truncated_normal_initializer(stddev=0.1))
b = tf.get_variable("bias_h_2", shape=b_shape)
return W, b
def masked_weight(self, _load=False):
if _load == False:
masked_W1 = np.random.randint(2, size=1)
if masked_W1 == 0:
masked_W2 = 1
else:
masked_W2 = np.random.randint(2, size=1)
np.save('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component) + '/'
+ self._type + '/W1_' + str(self._step), masked_W1)
np.save('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component) + '/'
+ self._type + '/W2_' + str(self._step), masked_W2)
else:
masked_W1 = np.load('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component)
+ '/' + str(self._type) + '/W1_' + str(self._step) + '.npy')
masked_W2 = np.load('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component)
+ '/' + str(self._type) + '/W2_' + str(self._step) + '.npy')
tf_mask_W1 = tf.constant(masked_W1, dtype=tf.float32)
tf_mask_W2 = tf.constant(masked_W2, dtype=tf.float32)
return tf_mask_W1, tf_mask_W2
class RKLSTMCell(tf.nn.rnn_cell.BasicLSTMCell):
"""Basic LSTM recurrent network cell.
The implementation is based on: http://arxiv.org/abs/1409.2329.
We add forget_bias (default: 1) to the biases of the forget gate in order to
reduce the scale of forgetting in the beginning of the training.
It does not allow cell clipping, a projection layer, and does not
use peep-hole connections: it is the basic baseline.
For advanced models, please use the full @{tf.nn.rnn_cell.LSTMCell}
that follows.
"""
def __init__(self, num_units, forget_bias=1.0, state_is_tuple=True, activation=None, reuse=None, dense=None,
file_name='tweet', type='enc', component=1, partition=1, skip_size=5):
"""Initialize the basic LSTM cell.
Args:
num_units: int, The number of units in the LSTM cell.
forget_bias: float, The bias added to forget gates (see above).
Must set to `0.0` manually when restoring from CudnnLSTM-trained
checkpoints.
state_is_tuple: If True, accepted and returned states are 2-tuples of
the `c_state` and `m_state`. If False, they are concatenated
along the column axis. The latter behavior will soon be deprecated.
activation: Activation function of the inner states. Default: `tanh`.
reuse: (optional) Python boolean describing whether to reuse variables
in an existing scope. If not `True`, and the existing scope already has
the given variables, an error is raised.
When restoring from CudnnLSTM-trained checkpoints, must use
CudnnCompatibleLSTMCell instead.
"""
super(tf.nn.rnn_cell.BasicLSTMCell, self).__init__(_reuse=reuse)
if not state_is_tuple:
tf.logging.warn("%s: Using a concatenated state is slower and will soon be "
"deprecated. Use state_is_tuple=True.", self)
self._num_units = num_units
self._forget_bias = forget_bias
self._state_is_tuple = state_is_tuple
self._activation = activation or tf.nn.tanh
self._linear = None
self._dense = dense
self._step = 0
self._file_name = file_name
self._type = type
self._component = component
self._partition = partition
self._skip_size = skip_size
if not os.path.exists('./weight/' + self._file_name):
os.makedirs('./weight/' + self._file_name)
if not os.path.exists('./weight/' + self._file_name + '/' + str(self._partition)):
os.makedirs('./weight/' + self._file_name + '/' + str(self._partition))
if not os.path.exists('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component)):
os.makedirs('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component))
if not os.path.exists('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component) + '/' + self._type):
os.makedirs('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component) + '/' + self._type)
def call(self, inputs, state):
"""Long short-term memory cell (LSTM).
Args:
inputs: `2-D` tensor with shape `[batch_size x input_size]`.
state: An `LSTMStateTuple` of state tensors, each shaped
`[batch_size x self.state_size]`, if `state_is_tuple` has been set to
`True`. Otherwise, a `Tensor` shaped
`[batch_size x 2 * self.state_size]`.
Returns:
A pair containing the new hidden state, and the new state (either a
`LSTMStateTuple` or a concatenated state, depending on
`state_is_tuple`).
"""
sigmoid = tf.sigmoid
self._step = self._step + 1
# Parameters of gates are concatenated into one multiply for efficiency.
if self._state_is_tuple:
c, h = state
else:
c, h = tf.split(value=state, num_or_size_splits=2, axis=1)
if self._linear is None:
self._linear = _Linear([inputs, h], 4 * self._num_units, True)
i, j, f, o = tf.split(value=self._linear([inputs, h]), num_or_size_splits=4, axis=1)
new_c = (c * sigmoid(f + self._forget_bias) + sigmoid(i) * self._activation(j))
new_h_cnt = self._activation(new_c) * sigmoid(o)
if self._step % self._skip_size == 0:
w_h_skip, b_h_skip = self.weight_bias([self._num_units, self._num_units], [self._num_units])
new_h_skip = sigmoid(tf.matmul(h, w_h_skip) + b_h_skip)
masked_w1, masked_w2 = self.masked_weight(_load=False)
new_h = new_h_cnt * masked_w1 + new_h_skip * masked_w2
else:
new_h = new_h_cnt
if self._state_is_tuple:
new_state = LSTMStateTuple(new_c, new_h)
else:
new_state = tf.concat([new_c, new_h], 1)
return new_h, new_state
def weight_bias(self, W_shape, b_shape, bias_init=0.1):
"""Fully connected highway layer adopted from
https://github.com/fomorians/highway-fcn/blob/master/main.py
"""
W = tf.get_variable("weight_h_2", shape=W_shape, initializer=tf.truncated_normal_initializer(stddev=0.1))
b = tf.get_variable("bias_h_2", shape=b_shape)
return W, b
def masked_weight(self, _load=False):
if _load==False:
masked_W1 = np.random.randint(2, size=1)
if masked_W1 == 0:
masked_W2 = 1
else:
masked_W2 = np.random.randint(2, size=1)
np.save('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component) + '/'
+ self._type + '/W1_' + str(self._step), masked_W1)
np.save('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component) + '/'
+ self._type + '/W2_' + str(self._step), masked_W2)
else:
masked_W1 = np.load('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component)
+ '/' + str(self._type) + '/W1_' + str(self._step) + '.npy')
masked_W2 = np.load('./weight/' + self._file_name + '/' + str(self._partition) + '/' + str(self._component)
+ '/' + str(self._type) + '/W2_' + str(self._step) + '.npy')
tf_mask_W1 = tf.constant(masked_W1, dtype=tf.float32)
tf_mask_W2 = tf.constant(masked_W2, dtype=tf.float32)
return tf_mask_W1, tf_mask_W2
class RSGRUCell(tf.nn.rnn_cell.GRUCell):
"""Gated Recurrent Unit cell (cf. http://arxiv.org/abs/1406.1078).
Args:
num_units: int, The number of units in the GRU cell.
activation: Nonlinearity to use. Default: `tanh`.
reuse: (optional) Python boolean describing whether to reuse variables
in an existing scope. If not `True`, and the existing scope already has
the given variables, an error is raised.
kernel_initializer: (optional) The initializer to use for the weight and
projection matrices.
bias_initializer: (optional) The initializer to use for the bias.
"""
def __init__(self, num_units, activation=None, reuse=None, kernel_initializer=None, bias_initializer=None):
super(tf.nn.rnn_cell.GRUCell, self).__init__(_reuse=reuse)
self._num_units = num_units
self._activation = activation or tf.nn.tanh
self._kernel_initializer = kernel_initializer
self._bias_initializer = bias_initializer
self._gate_linear = None
self._candidate_linear = None
@property
def state_size(self):
return self._num_units
@property
def output_size(self):
return self._num_units
def call(self, inputs, state):
"""Gated recurrent unit (GRU) with nunits cells."""
sigmoid = tf.sigmoid
if self._gate_linear is None:
bias_ones = self._bias_initializer
if self._bias_initializer is None:
bias_ones = init_ops.constant_initializer(1.0, dtype=inputs.dtype)
with vs.variable_scope("gates"): # Reset gate and update gate.
self._gate_linear = _Linear([inputs, state], 2 * self._num_units, True, bias_initializer=bias_ones,
kernel_initializer=self._kernel_initializer)
value = sigmoid(self._gate_linear([inputs, state]))
r, u = tf.split(value=value, num_or_size_splits=2, axis=1)
r_state = r * state
if self._candidate_linear is None:
with vs.variable_scope("candidate"):
self._candidate_linear = _Linear([inputs, r_state], self._num_units, True,
bias_initializer=self._bias_initializer,
kernel_initializer=self._kernel_initializer)
c = self._activation(self._candidate_linear([inputs, r_state]))
new_h = (u * state + (1 - u) * c)
return new_h, new_h
def weight_bias(self, W_shape, b_shape, bias_init=0.1):
"""Fully connected highway layer adopted from
https://github.com/fomorians/highway-fcn/blob/master/main.py
"""
W = tf.get_variable("weight_h_2", shape=W_shape, initializer=tf.truncated_normal_initializer(stddev=0.1))
b = tf.get_variable("bias_h_2", shape=b_shape)
return W, b
def Model(_abnormal_data, _abnormal_label, _hidden_num, _elem_num, _file_name, _partition):
tf.reset_default_graph()
g = tf.Graph()
with g.as_default():
# placeholder list
p_input = tf.placeholder(tf.float32, shape=(batch_num, _abnormal_data.shape[1], _abnormal_data.shape[2]))
# p_inputs = [tf.squeeze(t, [1]) for t in tf.split(p_input, _abnormal_data.shape[1], 1)]
# Regularizer signature
l1_regularizer = tf.contrib.layers.l1_regularizer(scale=0.005, scope=None)
# Projection layer
projection_layer = tf.layers.Dense(units=_elem_num, use_bias=True)
# with tf.device('/device:GPU:0'):
d_enc = {}
with tf.variable_scope('encoder'):
for j in range(ensemble_space):
# create RNN cell
if cell_type == 0:
enc_cell = tf.nn.rnn_cell.BasicRNNCell(_hidden_num)
if cell_type == 1:
pure_enc_cell = LSTMCell(_hidden_num)
residual_enc_cell = RLSTMCell(_hidden_num)
# enc_cell = RSLSTMCell(_hidden_num, file_name=_file_name, type='enc', partition=_partition,
# component=j, reuse=tf.AUTO_REUSE)
enc_cell = RKLSTMCell(_hidden_num, file_name=_file_name, type='enc', partition=_partition,
component=j, reuse=tf.AUTO_REUSE)
if cell_type == 2:
pure_enc_cell = GRUCell(_hidden_num)
enc_cell = RSGRUCell(_hidden_num)
if j == 0:
d_enc['enc_output_{0}'.format(j)], d_enc['enc_state_{0}'.format(j)] = tf.nn.dynamic_rnn(
pure_enc_cell, p_input, dtype=tf.float32)
elif j == 1:
d_enc['enc_output_{0}'.format(j)], d_enc['enc_state_{0}'.format(j)] = tf.nn.dynamic_rnn(
residual_enc_cell, p_input, dtype=tf.float32)
else:
d_enc['enc_output_{0}'.format(j)], d_enc['enc_state_{0}'.format(j)] = tf.nn.dynamic_rnn(enc_cell,
p_input,
dtype=tf.float32)
# shared_state_c = tf.concat([d_enc['enc_state_{0}'.format(j)].c for j in range(ensemble_space)], axis=1)
# shared_state_h = tf.concat([d_enc['enc_state_{0}'.format(j)].h for j in range(ensemble_space)], axis=1)
w_c = tf.Variable(tf.zeros([_hidden_num, _hidden_num]))
b_c = tf.Variable(tf.zeros([_hidden_num]))
w_h = tf.Variable(tf.zeros([_hidden_num, _hidden_num]))
b_h = tf.Variable(tf.zeros([_hidden_num]))
shared_state_c = tf.concat([tf.matmul(d_enc['enc_state_{0}'.format(j)].c, w_c) + b_c for j in range(ensemble_space)], axis=1)
shared_state_h = tf.concat([tf.matmul(d_enc['enc_state_{0}'.format(j)].h, w_h) + b_h for j in range(ensemble_space)], axis=1)
if compress:
compress_state = tf.layers.Dense(units=_hidden_num, activation=tf.tanh, use_bias=True)
shared_state_c = compress_state(shared_state_c)
shared_state_h = compress_state(shared_state_h)
shared_state = LSTMStateTuple(shared_state_c, shared_state_h)
# with tf.device('/device:GPU:1'):
d_dec = {}
with tf.variable_scope('decoder') as vs:
if decode_without_input:
dec_input = tf.zeros([p_input.shape[0], p_input.shape[1], p_input.shape[2]], dtype=tf.float32)
for k in range(ensemble_space):
# create RNN cell
if cell_type == 0:
dec_cell = tf.nn.rnn_cell.BasicRNNCell(_hidden_num)
if cell_type == 1:
if compress:
pure_dec_cell = LSTMCell(_hidden_num)
residual_dec_cell = RLSTMCell(_hidden_num)
dec_cell = RSLSTMCell(_hidden_num, file_name=_file_name, type='dec', partition=_partition,
component=k, reuse=tf.AUTO_REUSE)
else:
pure_dec_cell = LSTMCell(_hidden_num * ensemble_space)
residual_dec_cell = RLSTMCell(_hidden_num * ensemble_space)
dec_cell = RSLSTMCell(_hidden_num * ensemble_space, file_name=_file_name, type='dec',
partition=_partition, component=k, reuse=tf.AUTO_REUSE)
if cell_type == 2:
if compress:
pure_dec_cell = GRUCell(_hidden_num)
dec_cell = RSGRUCell(_hidden_num)
else:
pure_dec_cell = GRUCell(_hidden_num * ensemble_space)
dec_cell = RSGRUCell(_hidden_num * ensemble_space)
if k == 0:
d_dec['dec_output_{0}'.format(k)], d_dec['dec_state_{0}'.format(k)] = tf.nn.dynamic_rnn(
pure_dec_cell, dec_input, initial_state=shared_state, dtype=tf.float32)
elif k == 1:
d_dec['dec_output_{0}'.format(k)], d_dec['dec_state_{0}'.format(k)] = tf.nn.dynamic_rnn(
residual_dec_cell, dec_input, initial_state=shared_state, dtype=tf.float32)
else:
d_dec['dec_output_{0}'.format(k)], d_dec['dec_state_{0}'.format(k)] = tf.nn.dynamic_rnn(
dec_cell, dec_input, initial_state=shared_state, dtype=tf.float32)
if reverse:
d_dec['dec_output_{0}'.format(k)] = d_dec['dec_output_{0}'.format(k)][::-1]
else:
dec_input = tf.zeros([p_input.shape[0], p_input.shape[2]], dtype=tf.float32)
for k in range(ensemble_space):
# create RNN cell
if cell_type == 0:
dec_cell = tf.nn.rnn_cell.BasicRNNCell(_hidden_num)
if cell_type == 1:
if compress:
pure_dec_cell = LSTMCell(_hidden_num)
residual_dec_cell = RLSTMCell(_hidden_num)
# dec_cell = RSLSTMCell(_hidden_num, file_name=_file_name, type='dec', partition=_partition,
# component=k, reuse=tf.AUTO_REUSE)
dec_cell = RKLSTMCell(_hidden_num, file_name=_file_name, type='dec', partition=_partition,
component=k, reuse=tf.AUTO_REUSE)
else:
pure_dec_cell = LSTMCell(_hidden_num * ensemble_space)
residual_dec_cell = RLSTMCell(_hidden_num * ensemble_space)
# dec_cell = RSLSTMCell(_hidden_num * ensemble_space, file_name=_file_name, type='dec',
# partition=_partition, component=k, reuse=tf.AUTO_REUSE)
dec_cell = RKLSTMCell(_hidden_num * ensemble_space, file_name=_file_name, type='dec',
partition = _partition, component=k, reuse=tf.AUTO_REUSE)
if cell_type == 2:
if compress:
pure_dec_cell = GRUCell(_hidden_num)
dec_cell = RSGRUCell(_hidden_num)
else:
pure_dec_cell = GRUCell(_hidden_num * ensemble_space)
dec_cell = RSGRUCell(_hidden_num * ensemble_space)
inference_helper = tf.contrib.seq2seq.InferenceHelper(
sample_fn=lambda outputs: outputs,
sample_shape=[_elem_num],
sample_dtype=tf.float32,
start_inputs=dec_input,
end_fn=lambda sample_ids: False)
if k == 0:
inference_decoder = tf.contrib.seq2seq.BasicDecoder(pure_dec_cell, inference_helper,
shared_state, output_layer=projection_layer)
elif k == 1:
inference_decoder = tf.contrib.seq2seq.BasicDecoder(residual_dec_cell, inference_helper,
shared_state, output_layer=projection_layer)
else:
inference_decoder = tf.contrib.seq2seq.BasicDecoder(dec_cell, inference_helper, shared_state,
output_layer=projection_layer)
d_dec['dec_output_{0}'.format(k)], _, _ = tf.contrib.seq2seq.dynamic_decode(inference_decoder,
impute_finished=True,
maximum_iterations=
p_input.shape[1])
if reverse:
d_dec['dec_output_{0}'.format(k)] = d_dec['dec_output_{0}'.format(k)][::-1]
sum_of_difference = 0
for i in range(ensemble_space):
sum_of_difference += d_dec['dec_output_{0}'.format(i)][0] - p_input
loss = tf.reduce_mean(tf.square(sum_of_difference))
regularization_penalty = tf.contrib.layers.apply_regularization(l1_regularizer, [shared_state])
loss = loss + regularization_penalty
optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(loss)
# Add ops to save and restore all the variables.
saver = tf.train.Saver()
return g, p_input, d_dec, loss, optimizer, saver
def RunModel(_abnormal_data, _abnormal_label, _hidden_num, _elem_num, _file_name, _partition):
graph, p_input, d_dec, loss, optimizer, saver = Model(_abnormal_data, _abnormal_label, _hidden_num, _elem_num,
_file_name, _partition)
config = tf.ConfigProto()
# config.gpu_options.allow_growth = True
# Add ops to save and restore all the variables.
with tf.Session(graph=graph, config=config) as sess:
sess.run(tf.global_variables_initializer())
for i in range(iteration):
"""Random sequences.
Every sequence has size batch_num * step_num * elem_num
Each step number increases 1 by 1.
An initial number of each sequence is in the range from 0 to 19.
(ex. [8. 9. 10. 11. 12. 13. 14. 15])
"""
(loss_val, _) = sess.run([loss, optimizer], {p_input: _abnormal_data})
# print('iter %d:' % (i + 1), loss_val)
if save_model:
save_path = saver.save(sess, './saved_model/' + pathlib.Path(file_name).parts[
0] + '/shared_code_masked_skip_rnn_seq2seq_' + str(cell_type) + '_' + os.path.basename(
file_name) + '.ckpt')
print("Model saved in path: %s" % save_path)
result = {}
error = []
for k in range(ensemble_space):
(result['input_{0}'.format(k)], result['output_{0}'.format(k)]) = sess.run(
[p_input, d_dec['dec_output_{0}'.format(k)]], {p_input: _abnormal_data})
error.append(SquareErrorDataPoints(result['input_{0}'.format(k)], result['output_{0}'.format(k)][0]))
sess.close()
ensemble_errors = np.asarray(error)
anomaly_score = CalculateFinalAnomalyScore(ensemble_errors)
zscore = Z_Score(anomaly_score)
y_pred = CreateLabelBasedOnZscore(zscore, 3)
if not partition:
score_pred_label = np.c_[ensemble_errors, y_pred, _abnormal_label]
np.savetxt('./saved_result/' + pathlib.Path(file_name).parts[
0] + '/shared_code_masked_skip_rnn_seq2seq_' + os.path.basename(file_name) + '_score.txt', score_pred_label,
delimiter=',') # X is an array
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(_abnormal_label, y_pred)
if not partition:
PrintPrecisionRecallF1Metrics(precision, recall, f1)
fpr, tpr, roc_auc = CalculateROCAUCMetrics(_abnormal_label, anomaly_score)
# PlotROCAUC(fpr, tpr, roc_auc)
if not partition:
print('roc_auc=' + str(roc_auc))
precision_curve, recall_curve, average_precision = CalculatePrecisionRecallCurve(_abnormal_label, anomaly_score)
# PlotPrecisionRecallCurve(precision_curve, recall_curve, average_precision)
if not partition:
print('pr_auc=' + str(average_precision))
cks = CalculateCohenKappaMetrics(_abnormal_label, y_pred)
if not partition:
print('cks=' + str(cks))
return anomaly_score, precision, recall, f1, roc_auc, average_precision, cks
if __name__ == '__main__':
batch_num = 1
hidden_num = 16
# step_num = 8
iteration = 30
learning_rate = 1e-3
multivariate = True
reverse = True
decode_without_input = False
compress = False
partition = True
save_model = False
# cell type 0 => BasicRNN, 1 => LSTM, 2 => GRU
cell_type = 1
try:
sys.argv[1]
sys.argv[2]
except IndexError:
ensemble_space = 20
for n in range(1, 7):
# file name parameter
dataset = n
if dataset == 1:
file_name = './GD/data/Genesis_AnomalyLabels.csv'
print(file_name)
k_partition = 40
abnormal_data, abnormal_label = ReadGDDataset(file_name)
elem_num = 18
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label, _part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(splitted_data[i], splitted_label[i], hidden_num, elem_num)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data, abnormal_label, hidden_num, elem_num)
if dataset == 2:
file_name = './HSS/data/HRSS_anomalous_standard.csv'
print(file_name)
k_partition = 80
abnormal_data, abnormal_label = ReadHSSDataset(file_name)
elem_num = 18
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label, _part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(splitted_data[i], splitted_label[i], hidden_num, elem_num)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data, abnormal_label, hidden_num, elem_num)
if dataset == 3:
for root, dirs, _ in os.walk('./YAHOO/data'):
for dir in dirs:
k_partition = 10
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = ReadS5Dataset(file_name)
elem_num = 1
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data,
abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
if dataset == 4:
for root, dirs, _ in os.walk('./NAB/data'):
for dir in dirs:
k_partition = 10
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = ReadNABDataset(file_name)
elem_num = 1
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data,
abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
if dataset == 5:
for root, dirs, _ in os.walk('./2D/test'):
for dir in dirs:
k_partition = 3
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = Read2DDataset(file_name)
elem_num = 2
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data,
abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
if dataset == 6:
k_partition = 3
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for root, dirs, _ in os.walk('./UAH/'):
for dir in dirs:
folder_name = os.path.join(root, dir)
print(folder_name)
abnormal_data, abnormal_label = ReadUAHDataset(folder_name)
elem_num = 4
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num, _file_name=dir,
_partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
print('########################################')
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
print('########################################')
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data, abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
if dataset == 7:
for root, dirs, _ in os.walk('./ECG/'):
for dir in dirs:
k_partition = 3
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = ReadECGDataset(file_name)
elem_num = 3
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data,
abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
else:
# file name parameter
dataset = int(sys.argv[1])
ensemble_space = int(sys.argv[2])
if dataset == 1:
file_name = './GD/data/Genesis_AnomalyLabels.csv'
print(file_name)
k_partition = 40
abnormal_data, abnormal_label = ReadGDDataset(file_name)
elem_num = 18
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label, _part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(splitted_data[i], splitted_label[i], hidden_num, elem_num)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data, abnormal_label, hidden_num, elem_num)
if dataset == 2:
file_name = './HSS/data/HRSS_anomalous_standard.csv'
print(file_name)
k_partition = 80
abnormal_data, abnormal_label = ReadHSSDataset(file_name)
elem_num = 18
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label, _part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(splitted_data[i], splitted_label[i], hidden_num, elem_num)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data, abnormal_label, hidden_num, elem_num)
if dataset == 3:
for root, dirs, _ in os.walk('./YAHOO/data'):
for dir in dirs:
k_partition = 10
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = ReadS5Dataset(file_name)
elem_num = 1
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
if dataset == 4:
for root, dirs, _ in os.walk('./NAB/data'):
for dir in dirs:
k_partition = 10
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = ReadNABDataset(file_name)
elem_num = 1
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
if dataset == 5:
for root, dirs, _ in os.walk('./2D/test'):
for dir in dirs:
k_partition = 3
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = Read2DDataset(file_name)
elem_num = 2
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data,
abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
if dataset == 6:
k_partition = 3
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for root, dirs, _ in os.walk('./UAH/'):
for dir in dirs:
folder_name = os.path.join(root, dir)
print(folder_name)
abnormal_data, abnormal_label = ReadUAHDataset(folder_name)
elem_num = 4
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data, abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num, _file_name=dir, _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
print('########################################')
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
print('########################################')
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data, abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
if dataset == 7:
for root, dirs, _ in os.walk('./ECG/'):
for dir in dirs:
k_partition = 6
s_precision = []
s_recall = []
s_f1 = []
s_roc_auc = []
s_pr_auc = []
s_cks = []
for _, _, files in os.walk(root + '/' + dir):
for file in files:
file_name = os.path.join(root, dir, file)
print(file_name)
abnormal_data, abnormal_label = ReadECGDataset(file_name)
elem_num = 3
if multivariate:
abnormal_data = np.expand_dims(abnormal_data, axis=0)
if partition:
splitted_data, splitted_label = PartitionTimeSeriesKPart(abnormal_data,
abnormal_label,
_part_number=k_partition)
final_error = []
for i in range(k_partition):
error_partition, precision_partition, recall_partition, f1_partition, roc_auc_partition, pr_auc_partition, cks = RunModel(
splitted_data[i], splitted_label[i], hidden_num, elem_num,
_file_name=os.path.splitext(os.path.basename(file_name))[0], _partition=i)
final_error.append(error_partition)
# print('-----------------------------------------')
final_error = np.concatenate(final_error).ravel()
final_zscore = Z_Score(final_error)
y_pred = CreateLabelBasedOnZscore(final_zscore, 3)
precision, recall, f1 = CalculatePrecisionRecallF1Metrics(abnormal_label, y_pred)
PrintPrecisionRecallF1Metrics(precision, recall, f1)
_, _, roc_auc = CalculateROCAUCMetrics(abnormal_label, final_error)
print('roc_auc=' + str(roc_auc))
_, _, pr_auc = CalculatePrecisionRecallCurve(abnormal_label, final_error)
print('pr_auc=' + str(pr_auc))
cks = CalculateCohenKappaMetrics(abnormal_label, y_pred)
print('cohen_kappa=' + str(cks))
else:
error, precision, recall, f1, roc_auc, pr_auc, cks = RunModel(abnormal_data,
abnormal_label,
hidden_num, elem_num)
s_precision.append(precision)
s_recall.append(recall)
s_f1.append(f1)
s_roc_auc.append(roc_auc)
s_pr_auc.append(pr_auc)
s_cks.append(cks)
print('########################################')
avg_precision = CalculateAverageMetric(s_precision)
print('avg_precision=' + str(avg_precision))
avg_recall = CalculateAverageMetric(s_recall)
print('avg_recall=' + str(avg_recall))
avg_f1 = CalculateAverageMetric(s_f1)
print('avg_f1=' + str(avg_f1))
avg_roc_auc = CalculateAverageMetric(s_roc_auc)
print('avg_roc_auc=' + str(avg_roc_auc))
avg_pr_auc = CalculateAverageMetric(s_pr_auc)
print('avg_pr_auc=' + str(avg_pr_auc))
avg_cks = CalculateAverageMetric(s_cks)
print('avg_cks=' + str(avg_cks))
print('########################################')
| 57.194463
| 204
| 0.498152
| 8,358
| 84,705
| 4.727207
| 0.056832
| 0.02202
| 0.022779
| 0.028474
| 0.900709
| 0.88861
| 0.874462
| 0.866819
| 0.861579
| 0.854239
| 0
| 0.0115
| 0.401488
| 84,705
| 1,480
| 205
| 57.233108
| 0.767836
| 0.100714
| 0
| 0.840555
| 0
| 0
| 0.04525
| 0.015217
| 0
| 0
| 0
| 0
| 0
| 1
| 0.015598
| false
| 0
| 0.008666
| 0.001733
| 0.039861
| 0.123917
| 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
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| 0
| 0
| 0
| 0
|
0
| 7
|
0bbe6d8feba9ab0467b8ddabd76ec9660da20da3
| 11,500
|
py
|
Python
|
ensembler/tests/test_sampler.py
|
philthiel/Ensembler
|
943efac3c673eb40165927e81336386788e3a19f
|
[
"MIT"
] | 39
|
2020-05-19T08:45:27.000Z
|
2022-03-17T16:58:34.000Z
|
ensembler/tests/test_sampler.py
|
SchroederB/Ensembler
|
943efac3c673eb40165927e81336386788e3a19f
|
[
"MIT"
] | 38
|
2020-06-18T13:02:18.000Z
|
2022-02-25T14:29:17.000Z
|
ensembler/tests/test_sampler.py
|
SchroederB/Ensembler
|
943efac3c673eb40165927e81336386788e3a19f
|
[
"MIT"
] | 13
|
2020-05-19T08:45:57.000Z
|
2022-03-10T16:18:20.000Z
|
import os
import tempfile
import unittest
from ensembler import potentials as pot, system
from ensembler.samplers import _basicSamplers
from ensembler.samplers import stochastic, newtonian, optimizers
"""
STOCHASTIC INTEGRATORS
"""
class standard_IntegratorTests(unittest.TestCase):
integrator_class = _basicSamplers._samplerCls
tmp_test_dir: str = None
def setUp(self) -> None:
test_dir = os.getcwd()+"/tests_out"
if(not os.path.exists(test_dir)):
os.mkdir(test_dir)
if(__class__.tmp_test_dir is None):
__class__.tmp_test_dir = tempfile.mkdtemp(dir=test_dir, prefix="tmp_test_sampler")
_, self.tmp_out_path = tempfile.mkstemp(prefix="test_" + self.integrator_class.name, suffix=".obj", dir=__class__.tmp_test_dir)
def test_constructor(self):
integrator = self.integrator_class()
def test_save_integrator(self):
integrator = self.integrator_class()
integrator.save(self.tmp_out_path)
def test_load_integrator(self):
integrator = self.integrator_class()
integrator.save(self.tmp_out_path)
del integrator
integrator = self.integrator_class.load(self.tmp_out_path)
#print(integrator)
class test_MonteCarlo_Integrator(standard_IntegratorTests):
integrator_class = stochastic.metropolisMonteCarloIntegrator
def test_step(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, posShift, msg="Nothing happened here!")
def test_integrate(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
pass
class test_MetropolisMonteCarlo_Integrator(standard_IntegratorTests):
integrator_class = stochastic.metropolisMonteCarloIntegrator
def test_step(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, posShift, msg="Nothing happened here!")
def test_integrate(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
class test_Langevin_Integrator(standard_IntegratorTests):
integrator_class = stochastic.langevinIntegrator
def test_step(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, posShift, msg="Nothing happened here!")
def test_integrate(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
class test_LangevinVelocity_Integrator(standard_IntegratorTests):
integrator_class = stochastic.langevinVelocityIntegrator
def test_step(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, posShift, msg="Nothing happened here!")
def test_integrate(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
#print(sys.trajectory)
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
"""
NETOWNIAN
"""
class test_verlocityVerletIntegrator_Integrator(standard_IntegratorTests):
integrator_class = newtonian.velocityVerletIntegrator
def test_step(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, posShift, msg="Nothing happened here!")
def test_integrate(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
class test_positionVerletIntegrator_Integrator(standard_IntegratorTests):
integrator_class = newtonian.positionVerletIntegrator
def test_step(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
def test_integrate(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
class test_leapFrogIntegrator_Integrator(standard_IntegratorTests):
integrator_class = newtonian.leapFrogIntegrator
def test_step(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, posShift, msg="Nothing happened here!")
def test_integrate(self):
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
"""
Optimizer
"""
class test_cg_Integrator(standard_IntegratorTests):
integrator_class = optimizers.conjugate_gradient
def test_step(self):
position = 1
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
sys = system.system(potential=potent, sampler=integrator, start_position=position)
old_pos, oldForce = sys._currentPosition, sys._currentForce
newPos, _, posShift = integrator.step(system=sys)
self.assertNotEqual(old_pos, newPos, msg="Nothing happened here!")
def test_integrate(self):
position = 1
potent = pot.OneD.harmonicOscillatorPotential()
integrator = self.integrator_class()
steps = 42
sys = system.system(potential=potent, sampler=integrator, start_position=position)
old_pos, oldForce = sys._currentPosition, sys._currentForce
integrator.integrate(system=sys, steps=steps)
new_pos, new_Force = sys._currentPosition, sys._currentForce
self.assertEqual(steps + 1, len(sys.trajectory), msg="The simulation did not run or was too short!")
self.assertNotEqual(old_pos, new_pos, msg="Nothing happened here!")
self.assertNotEqual(oldForce, new_Force, msg="Nothing happened here!")
if __name__ == '__main__':
unittest.main()
| 38.720539
| 135
| 0.711217
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0
| 7
|
f0564a3d0806e509f3843f90f3d14906990f0a4a
| 201
|
py
|
Python
|
src/jnpr_nr_plugin/collectors/cmds.py
|
Juniper/juniper-newrelic-plugin
|
05ca131d80833b97560fa2ac9228a078fcdbbc06
|
[
"Apache-2.0"
] | 14
|
2015-02-13T14:45:57.000Z
|
2021-08-21T22:46:25.000Z
|
src/jnpr_nr_plugin/collectors/cmds.py
|
Juniper/juniper-newrelic-plugin
|
05ca131d80833b97560fa2ac9228a078fcdbbc06
|
[
"Apache-2.0"
] | 1
|
2015-05-13T07:15:31.000Z
|
2015-05-13T08:05:18.000Z
|
src/jnpr_nr_plugin/collectors/cmds.py
|
Juniper/juniper-newrelic-plugin
|
05ca131d80833b97560fa2ac9228a078fcdbbc06
|
[
"Apache-2.0"
] | 5
|
2015-04-27T21:58:04.000Z
|
2020-02-05T10:47:24.000Z
|
class Command(object):
def __init__(self, name):
self.name = name
class CommandResult(object):
def __init__(self, name, result):
self.name = name
self.result = result
| 20.1
| 37
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0
| 7
|
f07fe7490507d5a028ff9c94bf5c63794768fb93
| 12,614
|
py
|
Python
|
tests/integration/test_django_stack_trace_analyze.py
|
Duncan-Ireri/django-query-profiler
|
a704dc9c30e88d288e29315851ced3a01f458728
|
[
"BSD-3-Clause"
] | 97
|
2020-03-03T01:20:35.000Z
|
2022-03-23T14:06:09.000Z
|
tests/integration/test_django_stack_trace_analyze.py
|
Duncan-Ireri/django-query-profiler
|
a704dc9c30e88d288e29315851ced3a01f458728
|
[
"BSD-3-Clause"
] | 24
|
2020-03-06T17:35:08.000Z
|
2022-02-09T20:06:05.000Z
|
tests/integration/test_django_stack_trace_analyze.py
|
Duncan-Ireri/django-query-profiler
|
a704dc9c30e88d288e29315851ced3a01f458728
|
[
"BSD-3-Clause"
] | 9
|
2020-03-22T18:17:09.000Z
|
2022-01-31T18:59:11.000Z
|
from django.db.models import Prefetch
from django.test import TestCase
from tests.integration.fixtures import bulk_create_toppings_pizzas_restaurants
from tests.testapp.food.models import Pizza, Restaurant
from django_query_profiler.client.context_manager import QueryProfiler
from django_query_profiler.query_profiler_storage import QueryProfilerLevel, QuerySignatureAnalyzeResult
def run_twice_with_debug_toggled(test_func):
"""
This decorator runs the same test twice - one with DEBUG=True, and one with DEBUG=False
We want to do that because Django has two cursorWrapper - CursorWrapper and CursorDebugWrapper, and it
chooses the one based on the settings DEBUG attribute
"""
def wrapper(*args, **kwargs):
self: TestCase = args[0]
for debug in (True, False):
with self.subTest():
with self.settings(DEBUG=debug):
return test_func(*args, **kwargs)
return wrapper
class QueryProfilerCodeSuggestions(TestCase):
def setUp(self):
bulk_create_toppings_pizzas_restaurants()
@run_twice_with_debug_toggled
def test_missing_prefetch(self):
pizzas = Pizza.objects.all()
# Pizzas __str__ references toppings, which we have not prefetched
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_pizzas_without_prefetch:
for pizza in pizzas:
str(pizza) # We can also print it
query_signature_to_query_signature_statistics = \
qp_pizzas_without_prefetch.query_profiled_data.query_signature_to_query_signature_statistics
# The first query would be for pizzas, and second one would be the call to toppings
self.assertEqual(len(query_signature_to_query_signature_statistics), 2)
checked_for_table_pizza = checked_for_table_toppings = False
for query_signature, query_signature_statistics in query_signature_to_query_signature_statistics.items():
if query_signature_statistics.frequency == 1:
self.assertEqual(query_signature.analysis, QuerySignatureAnalyzeResult.UNKNOWN)
checked_for_table_pizza = True
elif query_signature_statistics.frequency == 3:
self.assertEqual(query_signature.analysis, QuerySignatureAnalyzeResult.MISSING_PREFETCH_RELATED)
checked_for_table_toppings = True
self.assertTrue(checked_for_table_pizza)
self.assertTrue(checked_for_table_toppings)
@run_twice_with_debug_toggled
def test_after_applying_prefetch(self):
pizzas = Pizza.objects.prefetch_related('toppings').all()
# Pizzas __str__ references toppings, which we have now prefetched
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_pizzas_with_prefetch:
for pizza in pizzas:
str(pizza) # We can also print it
query_signature_to_query_signature_statistics = \
qp_pizzas_with_prefetch.query_profiled_data.query_signature_to_query_signature_statistics
self.assertEqual(len(query_signature_to_query_signature_statistics), 2)
frequencies = {query_signature_statistics.frequency for query_signature_statistics in
query_signature_to_query_signature_statistics.values()}
query_signature_analysis = {query_signature.analysis for query_signature in
query_signature_to_query_signature_statistics.keys()}
self.assertSetEqual(frequencies, {1})
self.assertSetEqual(query_signature_analysis, {QuerySignatureAnalyzeResult.UNKNOWN,
QuerySignatureAnalyzeResult.PREFETCHED_RELATED})
@run_twice_with_debug_toggled
def test_spicy_toppings_db_filtering(self):
""" Test to verify that no amount of prefetching would help if we do db filtering"""
# STEP 1: Without any prefetching
pizzas = Pizza.objects.all()
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_pizzas_without_prefetch:
for pizza in pizzas:
pizza.spicy_toppings_db_filtering()
query_signature_to_query_signature_statistics = \
qp_pizzas_without_prefetch.query_profiled_data.query_signature_to_query_signature_statistics
self.assertEqual(len(query_signature_to_query_signature_statistics), 2)
checked_for_table_pizza = checked_for_table_toppings = False
for query_signature, query_signature_statistics in query_signature_to_query_signature_statistics.items():
if query_signature_statistics.frequency == 1:
self.assertEqual(query_signature.analysis, QuerySignatureAnalyzeResult.UNKNOWN)
checked_for_table_pizza = True
elif query_signature_statistics.frequency == 3:
self.assertEqual(query_signature.analysis, QuerySignatureAnalyzeResult.FILTER)
checked_for_table_toppings = True
self.assertTrue(checked_for_table_pizza)
self.assertTrue(checked_for_table_toppings)
# STEP 2: Lets try prefetching
pizzas = Pizza.objects.prefetch_related('toppings').all()
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_pizzas_wit_prefetch:
for pizza in pizzas:
pizza.spicy_toppings_db_filtering()
query_signature_to_query_signature_statistics = \
qp_pizzas_wit_prefetch.query_profiled_data.query_signature_to_query_signature_statistics
# Number of queries have increased by 1, since we did prefetching which could not be used
self.assertEqual(len(query_signature_to_query_signature_statistics), 3)
frequencies = [query_signature_statistics.frequency for query_signature_statistics in
query_signature_to_query_signature_statistics.values()]
query_signature_analysis = {query_signature.analysis for query_signature in
query_signature_to_query_signature_statistics.keys()}
self.assertListEqual(frequencies, [1, 1, 3])
self.assertSetEqual(query_signature_analysis, {QuerySignatureAnalyzeResult.FILTER,
QuerySignatureAnalyzeResult.PREFETCHED_RELATED,
QuerySignatureAnalyzeResult.UNKNOWN})
@run_twice_with_debug_toggled
def test_spicy_toppings_python_filtering(self):
""" Test to verify that if filtering is done in python, we have a chance to optimize """
# STEP 1: Without any prefetching
pizzas = Pizza.objects.all()
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_pizzas_without_prefetch:
for pizza in pizzas:
pizza.spicy_toppings_python_filtering()
query_signature_to_query_signature_statistics = \
qp_pizzas_without_prefetch.query_profiled_data.query_signature_to_query_signature_statistics
self.assertEqual(len(query_signature_to_query_signature_statistics), 2)
checked_for_table_pizza = checked_for_table_toppings = False
for query_signature, query_signature_statistics in query_signature_to_query_signature_statistics.items():
if query_signature_statistics.frequency == 1:
self.assertEqual(query_signature.analysis, QuerySignatureAnalyzeResult.UNKNOWN)
checked_for_table_pizza = True
elif query_signature_statistics.frequency == 3:
self.assertEqual(query_signature.analysis, QuerySignatureAnalyzeResult.MISSING_PREFETCH_RELATED)
checked_for_table_toppings = True
self.assertTrue(checked_for_table_pizza)
self.assertTrue(checked_for_table_toppings)
# STEP 2: Lets try prefetching
pizzas = Pizza.objects.prefetch_related('toppings').all()
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_pizzas_wit_prefetch:
for pizza in pizzas:
pizza.spicy_toppings_python_filtering()
query_signature_to_query_signature_statistics = \
qp_pizzas_wit_prefetch.query_profiled_data.query_signature_to_query_signature_statistics
# Number of queries have increased by 1, since we did prefetching which could not be used
self.assertEqual(len(query_signature_to_query_signature_statistics), 2)
frequencies = [query_signature_statistics.frequency for query_signature_statistics in
query_signature_to_query_signature_statistics.values()]
query_signature_analysis = {query_signature.analysis for query_signature in
query_signature_to_query_signature_statistics.keys()}
self.assertListEqual(frequencies, [1, 1])
self.assertSetEqual(query_signature_analysis, {QuerySignatureAnalyzeResult.UNKNOWN,
QuerySignatureAnalyzeResult.PREFETCHED_RELATED})
@run_twice_with_debug_toggled
def test_missing_select_related(self):
"""
This function tests various select_related and prefetch_related on the function
food.models.py#toppings_of_best_pizza_serving_restaurants
"""
# STEP 1: No select_related/prefetch_related
pizza = Pizza.objects.first()
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_no_prefetch_select_related:
str(pizza.toppings_of_best_pizza_serving_restaurants())
query_signature_to_query_signature_statistics = \
qp_no_prefetch_select_related.query_profiled_data.query_signature_to_query_signature_statistics
query_signature_analysis = [query_signature.analysis for query_signature in
query_signature_to_query_signature_statistics.keys()]
# We are missing prefetch to restaurants, which in turn is missing select_related to best_pizza, and then
# prefetch to toppings
expected_query_signature_analysis = [
QuerySignatureAnalyzeResult.MISSING_PREFETCH_RELATED,
QuerySignatureAnalyzeResult.MISSING_SELECT_RELATED,
QuerySignatureAnalyzeResult.MISSING_PREFETCH_RELATED]
self.assertListEqual(query_signature_analysis, expected_query_signature_analysis)
# STEP 2: Missing just the select_related to best_pizza and prefetch to toppings
pizza = Pizza.objects.prefetch_related('restaurants').first()
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_no_select_related:
str(pizza.toppings_of_best_pizza_serving_restaurants())
query_signature_to_query_signature_statistics = \
qp_no_select_related.query_profiled_data.query_signature_to_query_signature_statistics
query_signature_analysis = [query_signature.analysis for query_signature in
query_signature_to_query_signature_statistics.keys()]
# We have prefetch to restaurants, but restaurant is missing select_related to best_pizza, and then
# prefetch to toppings
expected_query_signature_analysis = [
QuerySignatureAnalyzeResult.MISSING_SELECT_RELATED,
QuerySignatureAnalyzeResult.MISSING_PREFETCH_RELATED]
self.assertListEqual(query_signature_analysis, expected_query_signature_analysis)
# STEP 3: Adding the select_related to best_pizza but still missing prefetch to toppings
pizza = Pizza.objects.prefetch_related(
Prefetch('restaurants', queryset=Restaurant.objects.select_related('best_pizza'))
).first()
with QueryProfiler(QueryProfilerLevel.QUERY_SIGNATURE) as qp_no_select_related:
str(pizza.toppings_of_best_pizza_serving_restaurants())
query_signature_to_query_signature_statistics = \
qp_no_select_related.query_profiled_data.query_signature_to_query_signature_statistics
query_signature_analysis = [query_signature.analysis for query_signature in
query_signature_to_query_signature_statistics.keys()]
# We have prefetch to restaurants, but restaurant is missing select_related to best_pizza, and then
# prefetch to toppings
expected_query_signature_analysis = [QuerySignatureAnalyzeResult.MISSING_PREFETCH_RELATED]
self.assertListEqual(query_signature_analysis, expected_query_signature_analysis)
# STEP 4: Now Adding the prefetch_related to toppings as well
# FIXME(Yash) How to do prefetch on the best_pizza
| 54.137339
| 113
| 0.727684
| 1,389
| 12,614
| 6.213103
| 0.12095
| 0.219003
| 0.141831
| 0.087601
| 0.840324
| 0.821321
| 0.795944
| 0.787601
| 0.761298
| 0.738586
| 0
| 0.002958
| 0.222768
| 12,614
| 232
| 114
| 54.37069
| 0.877295
| 0.141272
| 0
| 0.722581
| 0
| 0
| 0.005212
| 0
| 0
| 0
| 0
| 0.00431
| 0.174194
| 1
| 0.051613
| false
| 0
| 0.03871
| 0
| 0.109677
| 0
| 0
| 0
| 0
| null | 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
b2b1c29310e40d8563d3d6970becdeab35014060
| 3,397
|
py
|
Python
|
dress/actions/opencart_action.py
|
richard-ma/dress
|
86e892673635319c0a1860edb33cdba7ed22a7fb
|
[
"MIT"
] | 2
|
2019-10-23T09:06:47.000Z
|
2019-11-07T12:52:42.000Z
|
dress/actions/opencart_action.py
|
richard-ma/dress
|
86e892673635319c0a1860edb33cdba7ed22a7fb
|
[
"MIT"
] | 4
|
2017-12-28T01:44:42.000Z
|
2017-12-31T13:08:18.000Z
|
dress/actions/opencart_action.py
|
richard-ma/dress
|
86e892673635319c0a1860edb33cdba7ed22a7fb
|
[
"MIT"
] | 2
|
2019-10-15T07:42:33.000Z
|
2019-10-24T06:49:22.000Z
|
from dress.vendor.workflow import *
from dress.helper import *
class OpencartConfigAction(Action):
def run(self, *data):
data = data[0]
# config.php
data.append(
command_sed_helper("define('DB_DATABASE', '.*');",
"define('DB_DATABASE', '%s');" %
(self.params['target_database_name']),
"/home/wwwroot/%s/config.php" %
(self.params['target_domain'])))
data.append(
command_sed_helper("define('DB_USERNAME', '.*');",
"define('DB_USERNAME', '%s');" %
(self.params['target_database_user_name']),
"/home/wwwroot/%s/config.php" %
(self.params['target_domain'])))
data.append(
command_sed_helper("define('DB_PASSWORD', '.*');",
"define('DB_PASSWORD', '%s');" %
(self.params['target_database_password']),
"/home/wwwroot/%s/config.php" %
(self.params['target_domain'])))
data.append(
command_sed_helper(
self.params['source_domain'],
self.params['target_domain'],
"/home/wwwroot/%s/config.php" %
(self.params['target_domain']),
ignore_case=True))
# admin/config.php
data.append(
command_sed_helper("define('DB_DATABASE', '.*');",
"define('DB_DATABASE', '%s');" %
(self.params['target_database_name']),
"/home/wwwroot/%s/admin/config.php" %
(self.params['target_domain'])))
data.append(
command_sed_helper("define('DB_USERNAME', '.*');",
"define('DB_USERNAME', '%s');" %
(self.params['target_database_user_name']),
"/home/wwwroot/%s/admin/config.php" %
(self.params['target_domain'])))
data.append(
command_sed_helper("define('DB_PASSWORD', '.*');",
"define('DB_PASSWORD', '%s');" %
(self.params['target_database_password']),
"/home/wwwroot/%s/admin/config.php" %
(self.params['target_domain'])))
data.append(
command_sed_helper(
self.params['source_domain'],
self.params['target_domain'],
"/home/wwwroot/%s/admin/config.php" %
(self.params['target_domain']),
ignore_case=True))
return data
class OpencartOrderStartIdAction(Action):
def run(self, *data):
data = data[0]
# order_start_id is None: doing nothing
if self.params['order_start_id'] != None:
data.append(
command_mysql_helper(
self.params['target_database_root_password'],
"ALTER TABLE `%sorder` AUTO_INCREMENT = %s;"
% (self.params['table_prefix'],
self.params['order_start_id'])))
return data
| 44.116883
| 74
| 0.453636
| 290
| 3,397
| 5.075862
| 0.189655
| 0.149457
| 0.184783
| 0.149457
| 0.808424
| 0.778533
| 0.778533
| 0.778533
| 0.73913
| 0.699049
| 0
| 0.000993
| 0.407124
| 3,397
| 76
| 75
| 44.697368
| 0.729891
| 0.019135
| 0
| 0.850746
| 0
| 0
| 0.294772
| 0.185998
| 0
| 0
| 0
| 0
| 0
| 1
| 0.029851
| false
| 0.104478
| 0.029851
| 0
| 0.119403
| 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
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 9
|
b2bdad1ac3f1ac93578e6ab3a7b6e54c9839ff5e
| 11,583
|
py
|
Python
|
oslo/torch/distributed/_initializers/initializer_tensor_2p5d.py
|
lipovsek/oslo
|
c2cde6229068808bf691e200f8af8c97c1631eb4
|
[
"Apache-2.0"
] | 249
|
2021-12-21T05:25:53.000Z
|
2022-03-21T21:03:58.000Z
|
oslo/torch/distributed/_initializers/initializer_tensor_2p5d.py
|
lipovsek/oslo
|
c2cde6229068808bf691e200f8af8c97c1631eb4
|
[
"Apache-2.0"
] | 21
|
2021-12-22T13:22:18.000Z
|
2022-03-31T17:38:53.000Z
|
oslo/torch/distributed/_initializers/initializer_tensor_2p5d.py
|
lipovsek/oslo
|
c2cde6229068808bf691e200f8af8c97c1631eb4
|
[
"Apache-2.0"
] | 14
|
2021-12-21T10:28:36.000Z
|
2022-03-29T12:35:44.000Z
|
import math
import torch.distributed as dist
from oslo.torch.distributed._initializers.initializer import (
ProcessGroupInitializer,
)
from oslo.torch.distributed.parallel_mode import ParallelMode
# i row, j col, k dep
class _TensorParallel2p5DRowGroupInitializer(ProcessGroupInitializer):
"""
Process group initializer for row dimension of 2.5D tensor parallelism.
Args:
tesseract_dim (int): The dimension of tesseract
tesseract_dep (int): The dimension of depth
"""
def __init__(self, tesseract_dim: int, tesseract_dep: int, *args, **kwargs):
super().__init__(*args, **kwargs)
self.num_group = self.world_size // self.tensor_parallel_size
self.tesseract_dim = tesseract_dim
self.tesseract_dep = tesseract_dep
assert (
self.tensor_parallel_size == self.tesseract_dim**2 * self.tesseract_dep
), "Tensor parallel size should be depth * dim ** 2 in 2.5D parallel"
def init_dist_group(self):
"""
Initialize 2.5D tensor row parallel groups and assign local ranks and groups to each GPU.
Returns:
Dict: local_rank, group_world_size, process_group, ranks_in_group, mode
"""
local_rank = None
ranks_in_group = None
process_group = None
cpu_group = None
group_world_size = None
mode = ParallelMode.TENSOR_2P5D_ROW
for h in range(self.num_group):
for j in range(self.tesseract_dim):
for k in range(self.tesseract_dep):
ranks = [
h * self.tensor_parallel_size
+ i
+ self.tesseract_dim * (j + self.tesseract_dim * k)
for i in range(self.tesseract_dim)
]
group = dist.new_group(ranks)
group_cpu = (
dist.new_group(ranks, backend="gloo")
if dist.get_backend() != "gloo"
else group
)
if self.rank in ranks:
local_rank = ranks.index(self.rank)
group_world_size = len(ranks)
process_group = group
cpu_group = group_cpu
ranks_in_group = ranks
return {
"local_rank": local_rank,
"group_world_size": group_world_size,
"process_group": process_group,
"cpu_group": cpu_group,
"ranks_in_group": ranks_in_group,
"mode": mode,
}
class _TensorParallel2p5DColumnGroupInitializer(ProcessGroupInitializer):
"""
Process group initializer for column dimension of 2.5D tensor parallelism.
Args:
tesseract_dim (int): The dimension of tesseract
tesseract_dep (int): The dimension of depth
"""
def __init__(self, tesseract_dim: int, tesseract_dep: int, *args, **kwargs):
super().__init__(*args, **kwargs)
self.num_group = self.world_size // self.tensor_parallel_size
self.tesseract_dim = tesseract_dim
self.tesseract_dep = tesseract_dep
assert (
self.tensor_parallel_size == self.tesseract_dim**2 * self.tesseract_dep
), "Tensor parallel size should be depth * dim ** 2 in 2.5D parallel"
def init_dist_group(self):
"""
Initialize 2.5D tensor column parallel groups and assign local ranks and groups to each GPU.
Returns:
Dict: local_rank, group_world_size, process_group, ranks_in_group, mode
"""
local_rank = None
ranks_in_group = None
process_group = None
cpu_group = None
group_world_size = None
mode = ParallelMode.TENSOR_2P5D_COL
for h in range(self.num_group):
for i in range(self.tesseract_dim):
for k in range(self.tesseract_dep):
ranks = [
h * self.tensor_parallel_size
+ i
+ self.tesseract_dim * (j + self.tesseract_dim * k)
for j in range(self.tesseract_dim)
]
group = dist.new_group(ranks)
group_cpu = (
dist.new_group(ranks, backend="gloo")
if dist.get_backend() != "gloo"
else group
)
if self.rank in ranks:
local_rank = ranks.index(self.rank)
group_world_size = len(ranks)
process_group = group
cpu_group = group_cpu
ranks_in_group = ranks
return {
"local_rank": local_rank,
"group_world_size": group_world_size,
"process_group": process_group,
"cpu_group": cpu_group,
"ranks_in_group": ranks_in_group,
"mode": mode,
}
class _TensorParallel2p5DDepthGroupInitializer(ProcessGroupInitializer):
"""
Process group initializer for depth dimension of 2.5D tensor parallelism.
Args:
tesseract_dim (int): The dimension of tesseract
tesseract_dep (int): The dimension of depth
"""
def __init__(self, tesseract_dim: int, tesseract_dep: int, *args, **kwargs):
super().__init__(*args, **kwargs)
self.num_group = self.world_size // self.tensor_parallel_size
self.tesseract_dim = tesseract_dim
self.tesseract_dep = tesseract_dep
assert (
self.tensor_parallel_size == self.tesseract_dim**2 * self.tesseract_dep
), "Tensor parallel size should be depth * dim ** 2 in 2.5D parallel"
def init_dist_group(self):
"""
Initialize 2.5D tensor depth parallel groups and assign local ranks and groups to each GPU.
Returns:
Dict: local_rank, group_world_size, process_group, ranks_in_group, mode
"""
local_rank = None
ranks_in_group = None
process_group = None
cpu_group = None
group_world_size = None
mode = ParallelMode.TENSOR_2P5D_DEP
for h in range(self.num_group):
for i in range(self.tesseract_dim):
for j in range(self.tesseract_dim):
ranks = [
h * self.tensor_parallel_size
+ i
+ self.tesseract_dim * (j + self.tesseract_dim * k)
for k in range(self.tesseract_dep)
]
group = dist.new_group(ranks)
group_cpu = (
dist.new_group(ranks, backend="gloo")
if dist.get_backend() != "gloo"
else group
)
if self.rank in ranks:
local_rank = ranks.index(self.rank)
group_world_size = len(ranks)
process_group = group
cpu_group = group_cpu
ranks_in_group = ranks
return {
"local_rank": local_rank,
"group_world_size": group_world_size,
"process_group": process_group,
"cpu_group": cpu_group,
"ranks_in_group": ranks_in_group,
"mode": mode,
}
# i row, j col, k dep
class _TensorParallel2p5DXZGroupInitializer(ProcessGroupInitializer):
"""
Process group initializer for time depth dimension of 2.5D tensor parallelism.
Args:
tesseract_dim (int): The dimension of tesseract
tesseract_dep (int): The dimension of depth
"""
def __init__(self, tesseract_dim: int, tesseract_dep: int, *args, **kwargs):
super().__init__(*args, **kwargs)
self.num_group = self.world_size // self.tensor_parallel_size
self.tesseract_dep = tesseract_dep
self.tesseract_dim = tesseract_dim
assert (
self.tensor_parallel_size == self.tesseract_dim**2 * self.tesseract_dep
), "Tensor parallel size should be depth * dim ** 2 in 2.5D parallel"
def init_dist_group(self):
"""
Initialize 2.5D tensor column X depth parallel groups and assign local ranks and groups to each GPU.
Returns:
Dict: local_rank, group_world_size, process_group, ranks_in_group, mode
"""
local_rank = None
ranks_in_group = None
process_group = None
cpu_group = None
group_world_size = None
mode = ParallelMode.TENSOR_2P5D_XZ
for h in range(self.num_group):
for i in range(self.tesseract_dim):
ranks = [
h * self.tensor_parallel_size
+ i
+ self.tesseract_dim * (j + self.tesseract_dim * k)
for k in range(self.tesseract_dep)
for j in range(self.tesseract_dim)
]
group = dist.new_group(ranks)
group_cpu = (
dist.new_group(ranks, backend="gloo")
if dist.get_backend() != "gloo"
else group
)
if self.rank in ranks:
local_rank = ranks.index(self.rank)
group_world_size = len(ranks)
process_group = group
cpu_group = group_cpu
ranks_in_group = ranks
return {
"local_rank": local_rank,
"group_world_size": group_world_size,
"process_group": process_group,
"cpu_group": cpu_group,
"ranks_in_group": ranks_in_group,
"mode": mode,
}
class TensorParallel2p5DGroupInitializer(ProcessGroupInitializer):
"""Process group initializer for 2.5D tensor parallelism."""
def __init__(self, depth: int, *args, **kwargs):
super().__init__(*args, **kwargs)
self.num_group = self.world_size // self.tensor_parallel_size
self.tesseract_dim = int(math.sqrt(self.tensor_parallel_size / depth))
self.tesseract_dep = depth
assert (
self.tensor_parallel_size == self.tesseract_dim**2 * self.tesseract_dep
), "2.5D tesseract dim should equal to (tensor parallel size / tesseract dep) ^ 0.5"
self.col_initializer = _TensorParallel2p5DColumnGroupInitializer(
self.tesseract_dim, self.tesseract_dep, *args, **kwargs
)
self.row_initializer = _TensorParallel2p5DRowGroupInitializer(
self.tesseract_dim, self.tesseract_dep, *args, **kwargs
)
self.dep_initializer = _TensorParallel2p5DDepthGroupInitializer(
self.tesseract_dim, self.tesseract_dep, *args, **kwargs
)
self.xz_initializer = _TensorParallel2p5DXZGroupInitializer(
self.tesseract_dim, self.tesseract_dep, *args, **kwargs
)
def init_dist_group(self):
"""
Initialize 2.5D tensor parallel groups and assign local ranks and groups to each GPU.
Returns:
Dict: local_rank, group_world_size, process_group, ranks_in_group, mode
"""
return [
self.col_initializer.init_dist_group(),
self.row_initializer.init_dist_group(),
self.dep_initializer.init_dist_group(),
self.xz_initializer.init_dist_group(),
]
| 36.771429
| 108
| 0.569542
| 1,261
| 11,583
| 4.944489
| 0.068993
| 0.10842
| 0.087249
| 0.052927
| 0.872815
| 0.813152
| 0.813152
| 0.807217
| 0.796311
| 0.767923
| 0
| 0.008955
| 0.354053
| 11,583
| 314
| 109
| 36.888535
| 0.824379
| 0.148062
| 0
| 0.785047
| 0
| 0
| 0.066018
| 0
| 0
| 0
| 0
| 0
| 0.023364
| 1
| 0.046729
| false
| 0
| 0.018692
| 0
| 0.11215
| 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
|
6519fa05a1604cbcfb52d263233c938cf95f46ad
| 211
|
py
|
Python
|
apps/jobs/exceptions.py
|
kevingduck/transmission
|
c29ae529c02c885cdb0e64a35d7d4750ab1b8001
|
[
"Apache-2.0"
] | 19
|
2018-09-04T14:49:01.000Z
|
2020-06-09T22:13:10.000Z
|
apps/jobs/exceptions.py
|
kevingduck/transmission
|
c29ae529c02c885cdb0e64a35d7d4750ab1b8001
|
[
"Apache-2.0"
] | 50
|
2018-09-18T17:28:57.000Z
|
2021-01-09T16:18:45.000Z
|
apps/jobs/exceptions.py
|
kevingduck/transmission
|
c29ae529c02c885cdb0e64a35d7d4750ab1b8001
|
[
"Apache-2.0"
] | 4
|
2019-12-15T13:44:18.000Z
|
2021-06-09T20:39:54.000Z
|
class WalletInUseException(Exception):
"""The Wallet is currently in use by another AsyncJob"""
class TransactionCollisionException(Exception):
"""The Wallet is currently in use by another AsyncJob"""
| 30.142857
| 60
| 0.763033
| 24
| 211
| 6.708333
| 0.541667
| 0.149068
| 0.223602
| 0.248447
| 0.63354
| 0.63354
| 0.63354
| 0.63354
| 0.63354
| 0.63354
| 0
| 0
| 0.151659
| 211
| 6
| 61
| 35.166667
| 0.899441
| 0.478673
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 7
|
6521904aa42a2a3e012192e4c8d618acc71dfd0f
| 436
|
py
|
Python
|
pytorch_widedeep/models/__init__.py
|
cmcmaster1/pytorch-widedeep
|
d0feb29e56aa5612acdd3c60ce2c82ec04093110
|
[
"MIT"
] | null | null | null |
pytorch_widedeep/models/__init__.py
|
cmcmaster1/pytorch-widedeep
|
d0feb29e56aa5612acdd3c60ce2c82ec04093110
|
[
"MIT"
] | null | null | null |
pytorch_widedeep/models/__init__.py
|
cmcmaster1/pytorch-widedeep
|
d0feb29e56aa5612acdd3c60ce2c82ec04093110
|
[
"MIT"
] | null | null | null |
from pytorch_widedeep.models.wide import Wide
from pytorch_widedeep.models.tab_mlp import TabMlp
from pytorch_widedeep.models.deep_text import DeepText
from pytorch_widedeep.models.wide_deep import WideDeep
from pytorch_widedeep.models.deep_image import DeepImage
from pytorch_widedeep.models.tab_resnet import TabResnet
from pytorch_widedeep.models.tab_transformer import TabTransformer
from pytorch_widedeep.models.saint import SAINT
| 48.444444
| 66
| 0.889908
| 62
| 436
| 6.032258
| 0.306452
| 0.235294
| 0.406417
| 0.534759
| 0.534759
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.073395
| 436
| 8
| 67
| 54.5
| 0.925743
| 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
|
334164397a91a1a82b23691974b627767fb21346
| 131
|
py
|
Python
|
donkeypart_elecom_controller/__init__.py
|
coolerking/donkeypart_elecom_controller
|
192b52db655302703719cac1750178c4d7b278e3
|
[
"MIT"
] | null | null | null |
donkeypart_elecom_controller/__init__.py
|
coolerking/donkeypart_elecom_controller
|
192b52db655302703719cac1750178c4d7b278e3
|
[
"MIT"
] | null | null | null |
donkeypart_elecom_controller/__init__.py
|
coolerking/donkeypart_elecom_controller
|
192b52db655302703719cac1750178c4d7b278e3
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
'''
donkeycar.parts.controller.get_js_controller ラップ関数
'''
from .parts.controller import get_js_controller
| 21.833333
| 50
| 0.748092
| 17
| 131
| 5.529412
| 0.647059
| 0.319149
| 0.319149
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0.008475
| 0.099237
| 131
| 5
| 51
| 26.2
| 0.788136
| 0.557252
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 1
| 0
| 0
| null | 1
| 1
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| 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
|
684d2a1fefe96a805dc5d9e2d7fa4c53b43eb628
| 1,081
|
py
|
Python
|
sword-for-offer/ch3_string/Q14.py
|
GUTYL/algorithms
|
e1c956ff4823e1f9252b50d31893a5b2da930372
|
[
"MIT"
] | 1
|
2021-11-06T15:19:06.000Z
|
2021-11-06T15:19:06.000Z
|
sword-for-offer/ch3_string/Q14.py
|
GUTYL/algorithms
|
e1c956ff4823e1f9252b50d31893a5b2da930372
|
[
"MIT"
] | null | null | null |
sword-for-offer/ch3_string/Q14.py
|
GUTYL/algorithms
|
e1c956ff4823e1f9252b50d31893a5b2da930372
|
[
"MIT"
] | null | null | null |
from collections import defaultdict
class Solution:
def checkInclusion(self, s1: str, s2: str) -> bool:
if len(s2) < len(s1):
return False
dict_s1 = defaultdict(int)
for i in range(len(s1)):
dict_s1[s1[i]] += 1
dict_s1[s2[i]] -= 1
if any(dict_s1.values()) == 0:
return True
for i in range(len(s1), len(s2)):
dict_s1[s2[i]] -= 1
dict_s1[s2[i - len(s1)]] += 1
if any(dict_s1.values()) == 0:
return True
return False
def checkInclusion(self, s1: str, s2: str) -> bool:
if len(s2) < len(s1):
return False
dict_s1 = defaultdict(int)
for i in range(len(s1)):
dict_s1[s1[i]] += 1
dict_s1[s2[i]] -= 1
if not any(dict_s1.values()):
return True
for i in range(len(s1), len(s2)):
dict_s1[s2[i]] -= 1
dict_s1[s2[i - len(s1)]] += 1
if not any(dict_s1.values()):
return True
return False
| 30.027778
| 55
| 0.478261
| 152
| 1,081
| 3.309211
| 0.190789
| 0.166998
| 0.095427
| 0.107356
| 0.866799
| 0.866799
| 0.866799
| 0.866799
| 0.866799
| 0.691849
| 0
| 0.072508
| 0.387604
| 1,081
| 35
| 56
| 30.885714
| 0.687311
| 0
| 0
| 0.9375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.0625
| false
| 0
| 0.03125
| 0
| 0.375
| 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
|
6864e9bfed2603f5387fd48259378c3e1e9f85d7
| 14,776
|
py
|
Python
|
stubs/datapipeline.py
|
claytonbrown/troposphere
|
bf0f1e48b14f578de0221d50f711467ad716ca87
|
[
"BSD-2-Clause"
] | null | null | null |
stubs/datapipeline.py
|
claytonbrown/troposphere
|
bf0f1e48b14f578de0221d50f711467ad716ca87
|
[
"BSD-2-Clause"
] | null | null | null |
stubs/datapipeline.py
|
claytonbrown/troposphere
|
bf0f1e48b14f578de0221d50f711467ad716ca87
|
[
"BSD-2-Clause"
] | null | null | null |
from . import AWSObject, AWSProperty
from .validators import *
from .constants import *
# -------------------------------------------
class DataPipelineParameterAttribute(AWSProperty):
"""# ParameterAttribute - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects-attributes.html",
"Properties": {
"Key": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects-attributes.html#cfn-datapipeline-pipeline-parameterobjects-attribtues-key",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
},
"StringValue": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects-attributes.html#cfn-datapipeline-pipeline-parameterobjects-attribtues-stringvalue",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
}
}
}
"""
props = {
'Key': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects-attributes.html#cfn-datapipeline-pipeline-parameterobjects-attribtues-key'),
'StringValue': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects-attributes.html#cfn-datapipeline-pipeline-parameterobjects-attribtues-stringvalue')
}
# -------------------------------------------
class DataPipelinePipelineTag(AWSProperty):
"""# PipelineTag - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelinetags.html",
"Properties": {
"Key": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelinetags.html#cfn-datapipeline-pipeline-pipelinetags-key",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
},
"Value": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelinetags.html#cfn-datapipeline-pipeline-pipelinetags-value",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
}
}
}
"""
props = {
'Key': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelinetags.html#cfn-datapipeline-pipeline-pipelinetags-key'),
'Value': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelinetags.html#cfn-datapipeline-pipeline-pipelinetags-value')
}
# -------------------------------------------
class DataPipelinePipelineObject(AWSProperty):
"""# PipelineObject - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects.html",
"Properties": {
"Fields": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects.html#cfn-datapipeline-pipeline-pipelineobjects-fields",
"DuplicatesAllowed": true,
"ItemType": "Field",
"Required": true,
"Type": "List",
"UpdateType": "Mutable"
},
"Id": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects.html#cfn-datapipeline-pipeline-pipelineobjects-id",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
},
"Name": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects.html#cfn-datapipeline-pipeline-pipelineobjects-name",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
}
}
}
"""
props = {
'Fields': ([Field], True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects.html#cfn-datapipeline-pipeline-pipelineobjects-fields'),
'Id': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects.html#cfn-datapipeline-pipeline-pipelineobjects-id'),
'Name': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects.html#cfn-datapipeline-pipeline-pipelineobjects-name')
}
# -------------------------------------------
class DataPipelineParameterObject(AWSProperty):
"""# ParameterObject - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects.html",
"Properties": {
"Attributes": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects.html#cfn-datapipeline-pipeline-parameterobjects-attributes",
"DuplicatesAllowed": true,
"ItemType": "ParameterAttribute",
"Required": true,
"Type": "List",
"UpdateType": "Mutable"
},
"Id": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects.html#cfn-datapipeline-pipeline-parameterobject-id",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
}
}
}
"""
props = {
'Attributes': ([ParameterAttribute], True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects.html#cfn-datapipeline-pipeline-parameterobjects-attributes'),
'Id': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parameterobjects.html#cfn-datapipeline-pipeline-parameterobject-id')
}
# -------------------------------------------
class DataPipelineParameterValue(AWSProperty):
"""# ParameterValue - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parametervalues.html",
"Properties": {
"Id": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parametervalues.html#cfn-datapipeline-pipeline-parametervalues-id",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
},
"StringValue": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parametervalues.html#cfn-datapipeline-pipeline-parametervalues-stringvalue",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
}
}
}
"""
props = {
'Id': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parametervalues.html#cfn-datapipeline-pipeline-parametervalues-id'),
'StringValue': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-parametervalues.html#cfn-datapipeline-pipeline-parametervalues-stringvalue')
}
# -------------------------------------------
class DataPipelineField(AWSProperty):
"""# Field - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects-fields.html",
"Properties": {
"Key": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects-fields.html#cfn-datapipeline-pipeline-pipelineobjects-fields-key",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Mutable"
},
"RefValue": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects-fields.html#cfn-datapipeline-pipeline-pipelineobjects-fields-refvalue",
"PrimitiveType": "String",
"Required": false,
"UpdateType": "Mutable"
},
"StringValue": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects-fields.html#cfn-datapipeline-pipeline-pipelineobjects-fields-stringvalue",
"PrimitiveType": "String",
"Required": false,
"UpdateType": "Mutable"
}
}
}
"""
props = {
'Key': (basestring, True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects-fields.html#cfn-datapipeline-pipeline-pipelineobjects-fields-key'),
'RefValue': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects-fields.html#cfn-datapipeline-pipeline-pipelineobjects-fields-refvalue'),
'StringValue': (basestring, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-datapipeline-pipeline-pipelineobjects-fields.html#cfn-datapipeline-pipeline-pipelineobjects-fields-stringvalue')
}
# -------------------------------------------
class DataPipelinePipeline(AWSObject):
"""# AWS::DataPipeline::Pipeline - CloudFormationResourceSpecification version: 1.4.0
{
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html",
"Properties": {
"Activate": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-activate",
"PrimitiveType": "Boolean",
"Required": false,
"UpdateType": "Mutable"
},
"Description": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-description",
"PrimitiveType": "String",
"Required": false,
"UpdateType": "Immutable"
},
"Name": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-name",
"PrimitiveType": "String",
"Required": true,
"UpdateType": "Immutable"
},
"ParameterObjects": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-parameterobjects",
"DuplicatesAllowed": true,
"ItemType": "ParameterObject",
"Required": true,
"Type": "List",
"UpdateType": "Mutable"
},
"ParameterValues": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-parametervalues",
"DuplicatesAllowed": true,
"ItemType": "ParameterValue",
"Required": false,
"Type": "List",
"UpdateType": "Mutable"
},
"PipelineObjects": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-pipelineobjects",
"DuplicatesAllowed": true,
"ItemType": "PipelineObject",
"Required": false,
"Type": "List",
"UpdateType": "Mutable"
},
"PipelineTags": {
"Documentation": "http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-pipelinetags",
"DuplicatesAllowed": true,
"ItemType": "PipelineTag",
"Required": false,
"Type": "List",
"UpdateType": "Mutable"
}
}
}
"""
resource_type = "AWS::DataPipeline::Pipeline"
props = {
'Activate': (boolean, False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-activate'),
'Description': (basestring, False, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-description'),
'Name': (basestring, True, 'Immutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-name'),
'ParameterObjects': ([ParameterObject], True, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-parameterobjects'),
'ParameterValues': ([ParameterValue], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-parametervalues'),
'PipelineObjects': ([PipelineObject], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-pipelineobjects'),
'PipelineTags': ([PipelineTag], False, 'Mutable', 'http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-datapipeline-pipeline.html#cfn-datapipeline-pipeline-pipelinetags')
}
| 56.613027
| 253
| 0.674811
| 1,266
| 14,776
| 7.875197
| 0.055292
| 0.18656
| 0.054062
| 0.083551
| 0.880542
| 0.876329
| 0.850652
| 0.825577
| 0.820261
| 0.820261
| 0
| 0.001702
| 0.164727
| 14,776
| 260
| 254
| 56.830769
| 0.806109
| 0.643002
| 0
| 0.152174
| 0
| 0.456522
| 0.716307
| 0.005162
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.065217
| 0
| 0.391304
| 0
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| 0
| null | 0
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| 1
| 1
| 1
| 1
| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
688acf820347e3fe9cc3b03473dc5cd5c5a51bc0
| 1,035
|
py
|
Python
|
plugin/dbdriver/gen/DBDriverBase.py
|
lisugar/ray_build_tools
|
a304c8fc30ce9f61cbdc566d8dc193945f14883d
|
[
"MIT"
] | null | null | null |
plugin/dbdriver/gen/DBDriverBase.py
|
lisugar/ray_build_tools
|
a304c8fc30ce9f61cbdc566d8dc193945f14883d
|
[
"MIT"
] | null | null | null |
plugin/dbdriver/gen/DBDriverBase.py
|
lisugar/ray_build_tools
|
a304c8fc30ce9f61cbdc566d8dc193945f14883d
|
[
"MIT"
] | null | null | null |
import six
import abc
import os
@six.add_metaclass(abc.ABCMeta)
class BaseDBDriver(object):
@abc.abstractmethod
def create_resource(self, ctx, obj_type, request_dict):
raise NotImplementedError('BaseDBDriver should implement the method to execute') # pragma: no cover
@abc.abstractmethod
def read_resource(self, ctx, obj_type, id):
raise NotImplementedError('BaseDBDriver should implement the method to execute') # pragma: no cover
@abc.abstractmethod
def update_resource(self, ctx, obj_type, request_dict):
raise NotImplementedError('BaseDBDriver should implement the method to execute') # pragma: no cover
@abc.abstractmethod
def list_resource(self, ctx, obj_type, filter={}):
raise NotImplementedError('BaseDBDriver should implement the method to execute') # pragma: no cover
@abc.abstractmethod
def delete_resource(self, ctx, obj_type, id):
raise NotImplementedError('BaseDBDriver should implement the method to execute') # pragma: no cover
| 39.807692
| 108
| 0.73913
| 126
| 1,035
| 5.968254
| 0.293651
| 0.113032
| 0.132979
| 0.119681
| 0.832447
| 0.803191
| 0.803191
| 0.803191
| 0.803191
| 0.803191
| 0
| 0
| 0.182609
| 1,035
| 26
| 109
| 39.807692
| 0.888889
| 0.081159
| 0
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| 0
| 0.269556
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| 1
| 0.25
| false
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| 0.15
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| 1
| 1
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| 1
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
688e4a68bf705f4f990ef5850aba5ca67fc1d9c8
| 12,208
|
py
|
Python
|
test/vanilla/version-tolerant/Expected/AcceptanceTests/BodyDateVersionTolerant/bodydateversiontolerant/aio/operations/_operations.py
|
changlong-liu/autorest.python
|
1f03e4c6a11934d385fab050dc44041f1e91e9ff
|
[
"MIT"
] | null | null | null |
test/vanilla/version-tolerant/Expected/AcceptanceTests/BodyDateVersionTolerant/bodydateversiontolerant/aio/operations/_operations.py
|
changlong-liu/autorest.python
|
1f03e4c6a11934d385fab050dc44041f1e91e9ff
|
[
"MIT"
] | null | null | null |
test/vanilla/version-tolerant/Expected/AcceptanceTests/BodyDateVersionTolerant/bodydateversiontolerant/aio/operations/_operations.py
|
changlong-liu/autorest.python
|
1f03e4c6a11934d385fab050dc44041f1e91e9ff
|
[
"MIT"
] | null | null | null |
# pylint: disable=too-many-lines
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
import datetime
from typing import Any, Callable, Dict, Optional, TypeVar
from azure.core.exceptions import (
ClientAuthenticationError,
HttpResponseError,
ResourceExistsError,
ResourceNotFoundError,
map_error,
)
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import AsyncHttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator_async import distributed_trace_async
from ...operations._operations import (
build_date_get_invalid_date_request,
build_date_get_max_date_request,
build_date_get_min_date_request,
build_date_get_null_request,
build_date_get_overflow_date_request,
build_date_get_underflow_date_request,
build_date_put_max_date_request,
build_date_put_min_date_request,
)
T = TypeVar("T")
JSONType = Any
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
class DateOperations:
"""DateOperations async operations.
You should not instantiate this class directly. Instead, you should create a Client instance that
instantiates it for you and attaches it as an attribute.
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
"""
def __init__(self, client, config, serializer, deserializer) -> None:
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self._config = config
@distributed_trace_async
async def get_null(self, **kwargs: Any) -> Optional[datetime.date]:
"""Get null date value.
:return: date or None
:rtype: ~datetime.date or None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[Optional[datetime.date]]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
request = build_date_get_null_request()
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if response.content:
deserialized = response.json()
else:
deserialized = None
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
@distributed_trace_async
async def get_invalid_date(self, **kwargs: Any) -> datetime.date:
"""Get invalid date value.
:return: date
:rtype: ~datetime.date
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[datetime.date]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
request = build_date_get_invalid_date_request()
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if response.content:
deserialized = response.json()
else:
deserialized = None
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
@distributed_trace_async
async def get_overflow_date(self, **kwargs: Any) -> datetime.date:
"""Get overflow date value.
:return: date
:rtype: ~datetime.date
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[datetime.date]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
request = build_date_get_overflow_date_request()
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if response.content:
deserialized = response.json()
else:
deserialized = None
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
@distributed_trace_async
async def get_underflow_date(self, **kwargs: Any) -> datetime.date:
"""Get underflow date value.
:return: date
:rtype: ~datetime.date
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[datetime.date]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
request = build_date_get_underflow_date_request()
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if response.content:
deserialized = response.json()
else:
deserialized = None
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
@distributed_trace_async
async def put_max_date(self, date_body: datetime.date, **kwargs: Any) -> None:
"""Put max date value 9999-12-31.
:param date_body: date body.
:type date_body: ~datetime.date
:return: None
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[None]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
content_type = kwargs.pop("content_type", "application/json") # type: Optional[str]
_json = date_body
request = build_date_put_max_date_request(
content_type=content_type,
json=_json,
)
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if cls:
return cls(pipeline_response, None, {})
@distributed_trace_async
async def get_max_date(self, **kwargs: Any) -> datetime.date:
"""Get max date value 9999-12-31.
:return: date
:rtype: ~datetime.date
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[datetime.date]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
request = build_date_get_max_date_request()
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if response.content:
deserialized = response.json()
else:
deserialized = None
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
@distributed_trace_async
async def put_min_date(self, date_body: datetime.date, **kwargs: Any) -> None:
"""Put min date value 0000-01-01.
:param date_body: date body.
:type date_body: ~datetime.date
:return: None
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[None]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
content_type = kwargs.pop("content_type", "application/json") # type: Optional[str]
_json = date_body
request = build_date_put_min_date_request(
content_type=content_type,
json=_json,
)
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if cls:
return cls(pipeline_response, None, {})
@distributed_trace_async
async def get_min_date(self, **kwargs: Any) -> datetime.date:
"""Get min date value 0000-01-01.
:return: date
:rtype: ~datetime.date
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop("cls", None) # type: ClsType[datetime.date]
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop("error_map", {}))
request = build_date_get_min_date_request()
request.url = self._client.format_url(request.url)
pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
request, stream=False, **kwargs
)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if response.content:
deserialized = response.json()
else:
deserialized = None
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
| 36.660661
| 106
| 0.657274
| 1,323
| 12,208
| 5.854875
| 0.123205
| 0.041312
| 0.03718
| 0.026982
| 0.820811
| 0.820811
| 0.799897
| 0.75213
| 0.75213
| 0.75213
| 0
| 0.013892
| 0.239351
| 12,208
| 332
| 107
| 36.771084
| 0.820267
| 0.114024
| 0
| 0.71
| 0
| 0
| 0.016315
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.005
| false
| 0
| 0.04
| 0
| 0.12
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
d7f75de93c001c7fe9799a2078cb853bdda9b81d
| 218
|
py
|
Python
|
survol/sources_types/Azure/__init__.py
|
AugustinMascarelli/survol
|
7a822900e82d1e6f016dba014af5741558b78f15
|
[
"BSD-3-Clause"
] | null | null | null |
survol/sources_types/Azure/__init__.py
|
AugustinMascarelli/survol
|
7a822900e82d1e6f016dba014af5741558b78f15
|
[
"BSD-3-Clause"
] | null | null | null |
survol/sources_types/Azure/__init__.py
|
AugustinMascarelli/survol
|
7a822900e82d1e6f016dba014af5741558b78f15
|
[
"BSD-3-Clause"
] | null | null | null |
"""
Azure concepts
"""
def Graphic_shape():
return "egg"
def Graphic_colorfill():
return "#CCCC33"
def Graphic_colorbg():
return "#CCCC33"
def Graphic_border():
return 0
def Graphic_is_rounded():
return True
| 11.473684
| 25
| 0.711009
| 28
| 218
| 5.321429
| 0.535714
| 0.33557
| 0.201342
| 0.295302
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027174
| 0.155963
| 218
| 18
| 26
| 12.111111
| 0.782609
| 0.06422
| 0
| 0.2
| 0
| 0
| 0.086735
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 0
| 0.5
| 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
| 1
| 1
| 0
| 0
| 1
| 0
| 0
|
0
| 7
|
d7fae5992838a0aae6652b94dc8e50764f67f0f3
| 6,819
|
py
|
Python
|
tests/test_storage_model.py
|
chaostoolkit/chaosplatform-auth
|
35d99e4f87d6e1f07699ce7701b07391065fb3a7
|
[
"Apache-2.0"
] | null | null | null |
tests/test_storage_model.py
|
chaostoolkit/chaosplatform-auth
|
35d99e4f87d6e1f07699ce7701b07391065fb3a7
|
[
"Apache-2.0"
] | 2
|
2020-06-03T12:44:25.000Z
|
2020-06-22T09:32:01.000Z
|
tests/test_storage_model.py
|
chaostoolkit/chaosplatform-auth
|
35d99e4f87d6e1f07699ce7701b07391065fb3a7
|
[
"Apache-2.0"
] | null | null | null |
import uuid
from chaosplt_auth.storage import AuthStorage
from chaosplt_auth.storage.model import AccessToken, OAuthToken
from chaosplt_relational_storage.db import orm_session
def test_save_access_token(storage: AuthStorage):
with orm_session() as session:
token = AccessToken.save(
name=uuid.uuid4().hex,
user_id=uuid.uuid4(),
access_token="at-123456",
refresh_token="rt-123456",
session=session
)
session.commit()
assert uuid.UUID(hex=token.id.hex) == token.id
def test_get_access_token(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = AccessToken.save(
name=uuid.uuid4().hex,
user_id=user_id,
access_token="at-123456",
refresh_token="rt-123456",
session=session
)
session.commit()
fetched_token = AccessToken.load(user_id, token.id, session)
assert token == fetched_token
def test_get_access_token_for_user(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = AccessToken.save(
name=uuid.uuid4().hex,
user_id=user_id,
access_token="at-123456",
refresh_token="rt-123456",
session=session
)
session.commit()
fetched_tokens = AccessToken.load_by_user(user_id, session)
assert fetched_tokens == [token]
fetched_tokens = AccessToken.load_by_user(uuid.uuid4(), session)
assert fetched_tokens == []
def test_delete_access_token(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = AccessToken.save(
name=uuid.uuid4().hex,
user_id=user_id,
access_token="at-123456",
refresh_token="rt-123456",
session=session
)
session.commit()
fetched_token = AccessToken.load(user_id, token.id, session)
assert token == fetched_token
AccessToken.delete(user_id, token.id, session)
fetched_token = AccessToken.load(user_id, token.id, session)
assert fetched_token == None
def test_save_oauth2_token(storage: AuthStorage):
with orm_session() as session:
token = OAuthToken.save(
user_id=uuid.uuid4(),
provider="github",
provider_id=uuid.uuid4().hex,
token={"token": "a-token"},
session=session
)
session.commit()
assert token.token == {"token": "a-token"}
def test_get_oauth2_token(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = OAuthToken.save(
user_id=user_id,
provider="github",
provider_id=uuid.uuid4().hex,
token={"token": "a-token"},
session=session
)
session.commit()
fetched_token = OAuthToken.load(user_id, token.id, session)
assert token == fetched_token
def test_cannot_get_oauth2_token_for_different_user(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = OAuthToken.save(
user_id=user_id,
provider="github",
provider_id=uuid.uuid4().hex,
token={"token": "a-token"},
session=session
)
session.commit()
fetched_token = OAuthToken.load(user_id, token.id, session)
assert fetched_token == token
fetched_token = OAuthToken.load(uuid.uuid4(), token.id, session)
assert fetched_token == None
def test_get_oauth2_token_for_user(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = OAuthToken.save(
user_id=user_id,
provider="github",
provider_id=uuid.uuid4().hex,
token={"token": "a-token"},
session=session
)
session.commit()
fetched_token = OAuthToken.load_by_user(user_id, session)
assert fetched_token == token
fetched_token = OAuthToken.load_by_user(uuid.uuid4(), session)
assert fetched_token == None
def test_get_oauth2_token_by_provider(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
provider_id = uuid.uuid4().hex
token = OAuthToken.save(
user_id=user_id,
provider="github",
provider_id=provider_id,
token={"token": "a-token"},
session=session
)
session.commit()
fetched_token = OAuthToken.load_by_provider(
"github", provider_id, session)
assert fetched_token == token
fetched_token = OAuthToken.load_by_provider(
"bitbucket", provider_id, session)
assert fetched_token == None
def test_delete_oauth2_token(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = OAuthToken.save(
user_id=user_id,
provider="github",
provider_id=uuid.uuid4().hex,
token={"token": "a-token"},
session=session
)
session.commit()
fetched_token = OAuthToken.load(user_id, token.id, session)
assert token == fetched_token
OAuthToken.delete(user_id, token.id, session)
fetched_token = OAuthToken.load(user_id, token.id, session)
assert fetched_token == None
def test_delete_oauth2_token_by_user(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = OAuthToken.save(
user_id=user_id,
provider="github",
provider_id=uuid.uuid4().hex,
token={"token": "a-token"},
session=session
)
session.commit()
fetched_token = OAuthToken.load(user_id, token.id, session)
assert token == fetched_token
OAuthToken.delete_by_user(user_id, session)
fetched_token = OAuthToken.load(user_id, token.id, session)
assert fetched_token == None
def test_update_oauth2_token(storage: AuthStorage):
with orm_session() as session:
user_id = uuid.uuid4()
token = OAuthToken.save(
user_id=user_id,
provider="github",
provider_id=uuid.uuid4().hex,
token={"token": "a-token"},
session=session
)
session.commit()
OAuthToken.update_by_user(user_id, {"token": "b-token"}, session)
fetched_token = OAuthToken.load(user_id, token.id, session)
assert {"token": "a-token"} != fetched_token.token
assert {"token": "b-token"} == fetched_token.token
| 29.392241
| 74
| 0.604634
| 770
| 6,819
| 5.115584
| 0.063636
| 0.073115
| 0.055852
| 0.076161
| 0.886773
| 0.866464
| 0.842346
| 0.842346
| 0.808581
| 0.768469
| 0
| 0.017177
| 0.291392
| 6,819
| 231
| 75
| 29.519481
| 0.798013
| 0
| 0
| 0.735955
| 0
| 0
| 0.040915
| 0
| 0
| 0
| 0
| 0
| 0.11236
| 1
| 0.067416
| false
| 0
| 0.022472
| 0
| 0.089888
| 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
|
cc0c7de0bcb875b95347e16995a82f73837382e3
| 126
|
py
|
Python
|
discord_bot_eternal_dice/discord_bot_eternal_dice/util/app_config.py
|
lesteenman/discord-bot-eternal-dice
|
717d7ac10b8dbc3bef5d96dec417fd74154241e3
|
[
"MIT"
] | null | null | null |
discord_bot_eternal_dice/discord_bot_eternal_dice/util/app_config.py
|
lesteenman/discord-bot-eternal-dice
|
717d7ac10b8dbc3bef5d96dec417fd74154241e3
|
[
"MIT"
] | null | null | null |
discord_bot_eternal_dice/discord_bot_eternal_dice/util/app_config.py
|
lesteenman/discord-bot-eternal-dice
|
717d7ac10b8dbc3bef5d96dec417fd74154241e3
|
[
"MIT"
] | null | null | null |
import os
discord_public_key: str = os.getenv('DISCORD_PUBLIC_KEY')
discord_bot_token: str = os.getenv('DISCORD_BOT_TOKEN')
| 21
| 57
| 0.793651
| 20
| 126
| 4.6
| 0.45
| 0.282609
| 0.347826
| 0.391304
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.095238
| 126
| 5
| 58
| 25.2
| 0.807018
| 0
| 0
| 0
| 0
| 0
| 0.277778
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 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
|
cc21b0d6b73393a3ee37d6b000821a9cb07dce83
| 164
|
py
|
Python
|
python/bootcamp/modules/MyMainPackage/some_main_script.py
|
RodolfoDiaz/CodeLibrary
|
603ac9eee5b014bef8f04545bc4e73b0ec376131
|
[
"MIT"
] | 1
|
2018-10-11T14:29:40.000Z
|
2018-10-11T14:29:40.000Z
|
python/bootcamp/modules/MyMainPackage/some_main_script.py
|
RodolfoDiaz/CodeLibrary
|
603ac9eee5b014bef8f04545bc4e73b0ec376131
|
[
"MIT"
] | 2
|
2020-04-26T21:12:00.000Z
|
2020-10-28T21:10:03.000Z
|
python/bootcamp/modules/MyMainPackage/some_main_script.py
|
RodolfoDiaz/CodeLibrary
|
603ac9eee5b014bef8f04545bc4e73b0ec376131
|
[
"MIT"
] | null | null | null |
"""Docstring text for public module."""
def report_main():
"""Docstring text for public method."""
print("Hey I am in some_main_script in main package.")
| 23.428571
| 58
| 0.682927
| 24
| 164
| 4.541667
| 0.708333
| 0.238532
| 0.293578
| 0.40367
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.182927
| 164
| 6
| 59
| 27.333333
| 0.813433
| 0.408537
| 0
| 0
| 0
| 0
| 0.523256
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 0
| 0
| 0.5
| 0.5
| 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
| 0
| 1
|
0
| 8
|
cc299bdde52b29913d420de3b10def2a9e06522e
| 89
|
py
|
Python
|
tests/test_SiteStatusRequest.py
|
rodrigorf/crawler-mercadolivre
|
07cefe5a8389d6b665fe90f03ebcd54704c3c73d
|
[
"MIT"
] | 2
|
2021-09-17T00:41:00.000Z
|
2021-09-20T16:56:33.000Z
|
tests/test_SiteStatusRequest.py
|
rodrigorf/crawler-mercadolivre
|
07cefe5a8389d6b665fe90f03ebcd54704c3c73d
|
[
"MIT"
] | 1
|
2021-09-05T01:22:04.000Z
|
2021-09-05T01:22:04.000Z
|
tests/test_SiteStatusRequest.py
|
rodrigorf/crawler-mercadolivre
|
07cefe5a8389d6b665fe90f03ebcd54704c3c73d
|
[
"MIT"
] | 1
|
2021-09-17T00:42:11.000Z
|
2021-09-17T00:42:11.000Z
|
#TODO - create ML base tests
import pytest
def test_statuscode_200():
assert True
| 11.125
| 28
| 0.730337
| 13
| 89
| 4.846154
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.042857
| 0.213483
| 89
| 7
| 29
| 12.714286
| 0.857143
| 0.303371
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 0.333333
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
0bca6907d71f56e4a3605a6324fc6dac36a89649
| 2,153
|
py
|
Python
|
tests/exp_voxel_convolution_test.py
|
e3nn/e3nn-jax
|
5899e69684f00c0538d3597bbf6c12a45c090e5f
|
[
"Apache-2.0"
] | 14
|
2021-12-22T09:13:04.000Z
|
2022-03-24T13:32:56.000Z
|
tests/exp_voxel_convolution_test.py
|
e3nn/e3nn-jax
|
5899e69684f00c0538d3597bbf6c12a45c090e5f
|
[
"Apache-2.0"
] | 2
|
2022-03-17T05:00:25.000Z
|
2022-03-21T23:20:52.000Z
|
tests/exp_voxel_convolution_test.py
|
e3nn/e3nn-jax
|
5899e69684f00c0538d3597bbf6c12a45c090e5f
|
[
"Apache-2.0"
] | 1
|
2022-03-21T23:05:06.000Z
|
2022-03-21T23:05:06.000Z
|
import jax
import jax.numpy as jnp
import haiku as hk
from e3nn_jax import Irreps, IrrepsData
from e3nn_jax.experimental.voxel_convolution import Convolution
def test_convolution(keys):
irreps_in = Irreps("2x0e + 3x1e + 2x2e")
irreps_out = Irreps("0e + 2x1e + 2e")
irreps_sh = Irreps("0e + 1e + 2e")
@hk.without_apply_rng
@hk.transform
def c(x):
x = IrrepsData.from_contiguous(irreps_in, x)
x = Convolution(
irreps_out=irreps_out,
irreps_sh=irreps_sh,
diameter=3.9,
num_radial_basis={0: 3, 1: 2, 2: 1},
relative_starts={0: 0.0, 1: 0.0, 2: 0.5},
steps=(1.0, 1.0, 1.0),
)(x)
return x.contiguous
f = jax.jit(c.apply)
x0 = irreps_in.randn(next(keys), (3, 8, 8, 8, -1))
x0 = jnp.pad(x0, ((0, 0), (4, 4), (4, 4), (4, 4), (0, 0)))
w = c.init(next(keys), x0)
y0 = f(w, x0)
x1 = jnp.rot90(x0, axes=(2, 3))
x1 = irreps_in.transform_by_angles(x1, 0.0, jnp.pi / 2, 0.0)
y1 = f(w, x1)
y2 = jnp.rot90(y0, axes=(2, 3))
y2 = irreps_out.transform_by_angles(y2, 0.0, jnp.pi / 2, 0.0)
assert jnp.allclose(y1, y2, atol=1e-5)
def test_convolution_defaults(keys):
irreps_in = Irreps("2x0e + 3x1e + 2x2e")
irreps_out = Irreps("0e + 2x1e + 2e")
irreps_sh = Irreps("0e + 1e + 2e")
@hk.without_apply_rng
@hk.transform
def c(x):
x = IrrepsData.from_contiguous(irreps_in, x)
x = Convolution(
irreps_out=irreps_out,
irreps_sh=irreps_sh,
diameter=3.9,
num_radial_basis=3,
steps=(1.0, 1.0, 1.0),
)(x)
return x.contiguous
f = jax.jit(c.apply)
x0 = irreps_in.randn(next(keys), (3, 8, 8, 8, -1))
x0 = jnp.pad(x0, ((0, 0), (4, 4), (4, 4), (4, 4), (0, 0)))
w = c.init(next(keys), x0)
y0 = f(w, x0)
x1 = jnp.rot90(x0, axes=(2, 3))
x1 = irreps_in.transform_by_angles(x1, 0.0, jnp.pi / 2, 0.0)
y1 = f(w, x1)
y2 = jnp.rot90(y0, axes=(2, 3))
y2 = irreps_out.transform_by_angles(y2, 0.0, jnp.pi / 2, 0.0)
assert jnp.allclose(y1, y2, atol=1e-5)
| 26.9125
| 65
| 0.555039
| 362
| 2,153
| 3.171271
| 0.196133
| 0.026132
| 0.020906
| 0.020906
| 0.820557
| 0.820557
| 0.820557
| 0.820557
| 0.820557
| 0.820557
| 0
| 0.106959
| 0.279145
| 2,153
| 79
| 66
| 27.253165
| 0.632732
| 0
| 0
| 0.833333
| 0
| 0
| 0.040873
| 0
| 0
| 0
| 0
| 0
| 0.033333
| 1
| 0.066667
| false
| 0
| 0.083333
| 0
| 0.183333
| 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
|
0bcc1cf6768ff9ef8d2d3a9cffa90a3eb1c13b4a
| 932
|
py
|
Python
|
celery_sandbox/test_retries.py
|
karantan/celery-sandbox
|
ed46c7e72d87d5ac452899ef8323058cf881212a
|
[
"MIT"
] | null | null | null |
celery_sandbox/test_retries.py
|
karantan/celery-sandbox
|
ed46c7e72d87d5ac452899ef8323058cf881212a
|
[
"MIT"
] | null | null | null |
celery_sandbox/test_retries.py
|
karantan/celery-sandbox
|
ed46c7e72d87d5ac452899ef8323058cf881212a
|
[
"MIT"
] | null | null | null |
from celery_sandbox.retries import retries_exceeded
from celery_sandbox.retries import retries_exceeded_v2
from celery_sandbox.retries import retries_exceeded_return
def test_retries_exceeded(celery_app, celery_worker):
assert retries_exceeded.delay(3, 4).get() == 'Max retries exceeded...'
def test_retries_not_exceeded(celery_app, celery_worker):
assert retries_exceeded.delay(4, 4).get() == 8
def test_retries_v2_exceeded(celery_app, celery_worker):
assert retries_exceeded_v2.delay(3, 4).get() == 'Max retries exceeded...'
def test_retries_v2_not_exceeded(celery_app, celery_worker):
assert retries_exceeded_v2.delay(4, 4).get() == 8
def test_retries_exceeded_return(celery_app, celery_worker):
assert retries_exceeded_return.delay(3, 4).get() == 'Max retries exceeded...'
def test_retries_not_exceeded_return(celery_app, celery_worker):
assert retries_exceeded_return.delay(4, 4).get() == 8
| 33.285714
| 81
| 0.787554
| 136
| 932
| 5.036765
| 0.147059
| 0.306569
| 0.122628
| 0.183942
| 0.962044
| 0.953285
| 0.953285
| 0.756204
| 0.69781
| 0.551825
| 0
| 0.024096
| 0.109442
| 932
| 27
| 82
| 34.518519
| 0.801205
| 0
| 0
| 0
| 0
| 0
| 0.074034
| 0
| 0
| 0
| 0
| 0
| 0.4
| 1
| 0.4
| false
| 0
| 0.2
| 0
| 0.6
| 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
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 8
|
0bfc8501e8411e3ee0d15260d83d0c2a2fab9704
| 4,427
|
py
|
Python
|
tests/config/test_config_snips_mqtt.py
|
fossabot/snipskit
|
57fe329bf302f863bf190b2cfe1175e13d1d017e
|
[
"MIT"
] | 12
|
2019-03-18T13:03:46.000Z
|
2019-08-14T03:13:32.000Z
|
tests/config/test_config_snips_mqtt.py
|
fossabot/snipskit
|
57fe329bf302f863bf190b2cfe1175e13d1d017e
|
[
"MIT"
] | 4
|
2019-04-05T07:14:59.000Z
|
2019-12-06T23:51:31.000Z
|
tests/config/test_config_snips_mqtt.py
|
fossabot/snipskit
|
57fe329bf302f863bf190b2cfe1175e13d1d017e
|
[
"MIT"
] | 4
|
2019-05-01T07:56:20.000Z
|
2019-11-17T13:54:59.000Z
|
"""Tests for the MQTT connection settings of the `snipskit.config.SnipsConfig`
class.
"""
from snipskit.config import SnipsConfig
def test_snips_config_mqtt_default(fs):
"""Test whether a `SnipsConfig` object with default MQTT connection
settings is initialized correctly.
"""
config_file = '/etc/snips.toml'
fs.create_file(config_file,
contents='[snips-common]\n')
snips_config = SnipsConfig()
assert snips_config.mqtt.broker_address == 'localhost:1883'
assert snips_config.mqtt.auth.username is None
assert snips_config.mqtt.auth.password is None
assert snips_config.mqtt.auth.enabled is False
assert snips_config.mqtt.tls.hostname is None
assert snips_config.mqtt.tls.ca_file is None
assert snips_config.mqtt.tls.ca_path is None
assert snips_config.mqtt.tls.client_key is None
assert snips_config.mqtt.tls.client_cert is None
assert snips_config.mqtt.tls.disable_root_store is False
assert snips_config.mqtt.tls.enabled is False
def test_snips_config_mqtt_hostname(fs):
"""Test whether a `SnipsConfig` object with specified MQTT broker address
is initialized correctly.
"""
config_file = '/etc/snips.toml'
fs.create_file(config_file,
contents='[snips-common]\n'
'mqtt="mqtt.example.com:8883"\n')
snips_config = SnipsConfig()
assert snips_config.mqtt.broker_address == 'mqtt.example.com:8883'
assert snips_config.mqtt.auth.username is None
assert snips_config.mqtt.auth.password is None
assert snips_config.mqtt.auth.enabled is False
assert snips_config.mqtt.tls.hostname is None
assert snips_config.mqtt.tls.ca_file is None
assert snips_config.mqtt.tls.ca_path is None
assert snips_config.mqtt.tls.client_key is None
assert snips_config.mqtt.tls.client_cert is None
assert snips_config.mqtt.tls.disable_root_store is False
assert snips_config.mqtt.tls.enabled is False
def test_snips_config_mqtt_hostname_authentication(fs):
"""Test whether a `SnipsConfig` object with specified MQTT broker address
and authentication is initialized correctly.
"""
config_file = '/etc/snips.toml'
fs.create_file(config_file,
contents='[snips-common]\n'
'mqtt="mqtt.example.com:8883"\n'
'mqtt_username="foobar"\n'
'mqtt_password="secretpassword"\n')
snips_config = SnipsConfig()
assert snips_config.mqtt.broker_address == 'mqtt.example.com:8883'
assert snips_config.mqtt.auth.username == 'foobar'
assert snips_config.mqtt.auth.password == 'secretpassword'
assert snips_config.mqtt.auth.enabled is True
assert snips_config.mqtt.tls.hostname is None
assert snips_config.mqtt.tls.ca_file is None
assert snips_config.mqtt.tls.ca_path is None
assert snips_config.mqtt.tls.client_key is None
assert snips_config.mqtt.tls.client_cert is None
assert snips_config.mqtt.tls.disable_root_store is False
assert snips_config.mqtt.tls.enabled is False
def test_snips_config_mqtt_tls(fs):
"""Test whether a `SnipsConfig` object with specified MQTT broker address
and authentication and TLS settings is initialized correctly.
"""
config_file = '/etc/snips.toml'
fs.create_file(config_file,
contents='[snips-common]\n'
'mqtt="mqtt.example.com:4883"\n'
'mqtt_username="foobar"\n'
'mqtt_password="secretpassword"\n'
'mqtt_tls_hostname="mqtt.example.com"\n'
'mqtt_tls_cafile="/etc/ssl/certs/ca-certificates.crt"\n')
snips_config = SnipsConfig()
assert snips_config.mqtt.broker_address == 'mqtt.example.com:4883'
assert snips_config.mqtt.auth.username == 'foobar'
assert snips_config.mqtt.auth.password == 'secretpassword'
assert snips_config.mqtt.auth.enabled is True
assert snips_config.mqtt.tls.hostname == 'mqtt.example.com'
assert snips_config.mqtt.tls.ca_file == '/etc/ssl/certs/ca-certificates.crt'
assert snips_config.mqtt.tls.ca_path is None
assert snips_config.mqtt.tls.client_key is None
assert snips_config.mqtt.tls.client_cert is None
assert snips_config.mqtt.tls.disable_root_store is False
assert snips_config.mqtt.tls.enabled is True
| 42.980583
| 85
| 0.703411
| 607
| 4,427
| 4.943987
| 0.112026
| 0.190603
| 0.23992
| 0.307897
| 0.935688
| 0.928357
| 0.895368
| 0.873709
| 0.873709
| 0.843052
| 0
| 0.007975
| 0.206912
| 4,427
| 102
| 86
| 43.401961
| 0.846767
| 0.119268
| 0
| 0.756757
| 0
| 0
| 0.152503
| 0.101929
| 0
| 0
| 0
| 0
| 0.594595
| 1
| 0.054054
| false
| 0.081081
| 0.013514
| 0
| 0.067568
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 11
|
043b57bd040fdcb3c1d7ed04032a3fd8838f235b
| 5,606
|
py
|
Python
|
test/test_searches_api.py
|
greenpau/pycherwell
|
2a25446d5cf86d69e6158067faf27ce250aba966
|
[
"Apache-2.0"
] | 2
|
2020-04-09T16:41:25.000Z
|
2020-08-25T21:07:53.000Z
|
test/test_searches_api.py
|
greenpau/pycherwell
|
2a25446d5cf86d69e6158067faf27ce250aba966
|
[
"Apache-2.0"
] | 15
|
2020-02-12T14:57:30.000Z
|
2020-11-27T23:34:15.000Z
|
test/test_searches_api.py
|
greenpau/pycherwell
|
2a25446d5cf86d69e6158067faf27ce250aba966
|
[
"Apache-2.0"
] | 2
|
2020-02-12T14:57:38.000Z
|
2021-07-30T11:32:28.000Z
|
# coding: utf-8
"""
Cherwell REST API
Unofficial Python Cherwell REST API library. # noqa: E501
The version of the OpenAPI document: 9.3.2
Contact: See AUTHORS.
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import unittest
import pycherwell
from pycherwell.api.searches_api import SearchesApi # noqa: E501
from pycherwell.rest import ApiException
class TestSearchesApi(unittest.TestCase):
"""SearchesApi unit test stubs"""
def setUp(self):
self.api = pycherwell.api.searches_api.SearchesApi() # noqa: E501
def tearDown(self):
pass
def test_searches_get_quick_search_configuration_for_bus_obs_v1(self):
"""Test case for searches_get_quick_search_configuration_for_bus_obs_v1
Get a Quick Search from a list of Business Object IDs # noqa: E501
"""
pass
def test_searches_get_quick_search_configuration_for_bus_obs_with_view_rights_v1(self):
"""Test case for searches_get_quick_search_configuration_for_bus_obs_with_view_rights_v1
Get a Quick Search by Business Objects with view rights # noqa: E501
"""
pass
def test_searches_get_quick_search_results_v1(self):
"""Test case for searches_get_quick_search_results_v1
Execute a Quick Search from a list of Business Object IDs and search text # noqa: E501
"""
pass
def test_searches_get_quick_search_specific_results_v1(self):
"""Test case for searches_get_quick_search_specific_results_v1
Execute a Quick Search on a specific Business Object # noqa: E501
"""
pass
def test_searches_get_quick_search_specific_results_v2(self):
"""Test case for searches_get_quick_search_specific_results_v2
Execute a Quick Search on a specific Business Object # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_scope_scope_owner_folder_v1(self):
"""Test case for searches_get_search_items_by_association_scope_scope_owner_folder_v1
Get all saved searches by Folder ID # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_scope_scope_owner_folder_v2(self):
"""Test case for searches_get_search_items_by_association_scope_scope_owner_folder_v2
Get all saved searches by Folder ID # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_scope_scope_owner_v1(self):
"""Test case for searches_get_search_items_by_association_scope_scope_owner_v1
Get all saved searches by scope owner (sub scope) # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_scope_scope_owner_v2(self):
"""Test case for searches_get_search_items_by_association_scope_scope_owner_v2
Get all saved searches by scope owner (sub scope) # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_scope_v1(self):
"""Test case for searches_get_search_items_by_association_scope_v1
Get all saved searches by scope # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_scope_v2(self):
"""Test case for searches_get_search_items_by_association_scope_v2
Get all saved searches by scope # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_v1(self):
"""Test case for searches_get_search_items_by_association_v1
Get all saved searches by Business Object association # noqa: E501
"""
pass
def test_searches_get_search_items_by_association_v2(self):
"""Test case for searches_get_search_items_by_association_v2
Get all saved searches by Business Object association # noqa: E501
"""
pass
def test_searches_get_search_items_v1(self):
"""Test case for searches_get_search_items_v1
Get all saved searches by default Business Object association # noqa: E501
"""
pass
def test_searches_get_search_items_v2(self):
"""Test case for searches_get_search_items_v2
Get all saved searches by default Business Object association # noqa: E501
"""
pass
def test_searches_get_search_results_ad_hoc_v1(self):
"""Test case for searches_get_search_results_ad_hoc_v1
Run an ad-hoc search # noqa: E501
"""
pass
def test_searches_get_search_results_by_id_v1(self):
"""Test case for searches_get_search_results_by_id_v1
Run a saved search by internal ID # noqa: E501
"""
pass
def test_searches_get_search_results_by_name_v1(self):
"""Test case for searches_get_search_results_by_name_v1
Run a saved search by name # noqa: E501
"""
pass
def test_searches_get_search_results_export_ad_hoc_v1(self):
"""Test case for searches_get_search_results_export_ad_hoc_v1
Export an ad-hoc search # noqa: E501
"""
pass
def test_searches_get_search_results_export_by_id_v1(self):
"""Test case for searches_get_search_results_export_by_id_v1
Export a saved search by ID # noqa: E501
"""
pass
def test_searches_get_search_results_export_by_name_v1(self):
"""Test case for searches_get_search_results_export_by_name_v1
Export a saved search by name # noqa: E501
"""
pass
if __name__ == '__main__':
unittest.main()
| 30.802198
| 96
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| 0.425926
| false
| 0.407407
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| 0.537037
| 0
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| null | 0
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0
| 9
|
f0a02b05ae881985fff80afeba39b88024250c15
| 34,929
|
py
|
Python
|
dragonchain/lib/authorization_utest.py
|
cheeseandcereal/dragonchain
|
34d34e344b887c2a0eeb591ede2015cc2506a323
|
[
"Apache-2.0"
] | null | null | null |
dragonchain/lib/authorization_utest.py
|
cheeseandcereal/dragonchain
|
34d34e344b887c2a0eeb591ede2015cc2506a323
|
[
"Apache-2.0"
] | null | null | null |
dragonchain/lib/authorization_utest.py
|
cheeseandcereal/dragonchain
|
34d34e344b887c2a0eeb591ede2015cc2506a323
|
[
"Apache-2.0"
] | null | null | null |
# Copyright 2020 Dragonchain, Inc.
# Licensed under the Apache License, Version 2.0 (the "Apache License")
# with the following modification; you may not use this file except in
# compliance with the Apache License and the following modification to it:
# Section 6. Trademarks. is deleted and replaced with:
# 6. Trademarks. This License does not grant permission to use the trade
# names, trademarks, service marks, or product names of the Licensor
# and its affiliates, except as required to comply with Section 4(c) of
# the License and to reproduce the content of the NOTICE file.
# You may obtain a copy of the Apache License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the Apache License with the above modification is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the Apache License for the specific
# language governing permissions and limitations under the Apache License.
import json
import datetime
import unittest
from unittest.mock import patch, MagicMock
from dragonchain import test_env # noqa: F401
from dragonchain.lib import authorization
from dragonchain import exceptions
class TestAuthorization(unittest.TestCase):
def assertRaisesWithMessage(self, exception, msg, func, *args, **kwargs): # noqa N802
"""
Helper to assert a particular exception with a certain message is raised via our UserException
"""
try:
func(*args, **kwargs)
self.assertFail()
except exception as e:
self.assertEqual(str(e), msg)
def test_datetime(self):
self.assertIsInstance(authorization.get_now_datetime(), datetime.datetime)
@patch("dragonchain.lib.authorization.redis.set_sync")
def test_save_matchmaking_auth_key_calls_redis(self, mock_redis_set):
self.assertTrue(authorization.save_matchmaking_auth_key("key"))
mock_redis_set.assert_called_once_with("authorization:matchmaking", "key")
@patch("dragonchain.lib.authorization.redis.set_sync", side_effect=Exception)
def test_save_matchmaking_auth_returns_false_on_redis_error(self, mock_redis_set):
self.assertFalse(authorization.save_matchmaking_auth_key("key"))
@patch("dragonchain.lib.authorization.redis.get_sync", return_value="banana")
def test_get_matchmaking_key_returns_from_redis(self, mock_redis_get):
self.assertEqual(authorization.get_matchmaking_key(), "banana")
mock_redis_get.assert_called_once_with("authorization:matchmaking")
def test_get_hmac_string(self):
http_verb = "TEST"
full_path = "/somepath"
dcid = "test_dcid"
timestamp = "timestamp_str"
content_type = "mimetype"
content = b"some content"
hmac_hash_type = "SHA256"
hash_type = authorization.get_supported_hmac_hash(hmac_hash_type)
hmac_str = authorization.get_hmac_message_string(http_verb, full_path, dcid, timestamp, content_type, content, hash_type)
self.assertEqual(hmac_str, "TEST\n/somepath\ntest_dcid\ntimestamp_str\nmimetype\nKQ9JPET11j0Gs3TQpavSkvrji5LKsvrl7+/hsOk0f1Y=")
@patch("dragonchain.lib.authorization.get_hmac_message_string", return_value="hmac_string")
def test_get_authorization(self, mock_hmac_string):
self.assertEqual(
authorization.get_authorization("id", "key", "TEST", "/path", "dcid", "timestamp", "mimetype", b"content", "SHA256"),
"DC1-HMAC-SHA256 id:G0ufeozs9/jOZCvIAkEfWhwCxx0NBDrvapnqdqShxWA=",
)
@patch("dragonchain.lib.authorization.api_key_dao.save_api_key")
@patch("dragonchain.lib.authorization.api_key_model.new_from_scratch")
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.keys.get_my_keys", return_value=MagicMock(make_signature=MagicMock(return_value="sig")))
@patch("dragonchain.lib.authorization.requests.post", return_value=MagicMock(status_code=201))
@patch("dragonchain.lib.authorization.matchmaking.get_dragonchain_address", return_value="https://someurl")
def test_register_interchain_key_with_remote_returns_valid(self, mock_get_address, mock_post, mock_keys, mock_dcid, mock_new_key, mock_save):
remote_dcid = "remote"
url = "https://someurl/v1/interchain-auth-register"
expected_key = {"dcid": "test_dcid", "key": mock_new_key.return_value.key, "signature": "sig"}
self.assertEqual(authorization.register_new_interchain_key_with_remote(remote_dcid), mock_new_key.return_value)
mock_post.assert_called_with(url, json=expected_key, timeout=30)
mock_save.assert_called_once_with(mock_new_key.return_value)
@patch("dragonchain.lib.authorization.api_key_model.new_from_scratch")
@patch("dragonchain.lib.keys.get_public_id", return_value="z7S3WADvnjCyFkUmL48cPGqrSHDrQghNxLFMwBEwwtMa")
@patch("dragonchain.lib.authorization.keys.get_my_keys")
@patch("dragonchain.lib.authorization.requests.post", return_value=MagicMock(status_code=100))
@patch("dragonchain.lib.authorization.matchmaking.get_dragonchain_address", return_value="https://someurl")
def test_register_interchain_key_raises_with_bad_status_code(self, mock_get_address, mock_post, mock_keys, mock_get_id, mock_new_key):
self.assertRaises(RuntimeError, authorization.register_new_interchain_key_with_remote, "thing")
@patch("dragonchain.lib.authorization.api_key_model.new_from_scratch")
@patch("dragonchain.lib.keys.get_public_id", return_value="z7S3WADvnjCyFkUmL48cPGqrSHDrQghNxLFMwBEwwtMa")
@patch("dragonchain.lib.authorization.keys.get_my_keys")
@patch("dragonchain.lib.authorization.requests.post", side_effect=Exception)
@patch("dragonchain.lib.authorization.matchmaking.get_dragonchain_address", return_value="https://someurl")
def test_register_interchain_key_raises_with_bad_request_exception(self, mock_get_address, mock_post, mock_keys, mock_get_id, mock_new_key):
self.assertRaises(RuntimeError, authorization.register_new_interchain_key_with_remote, "thing")
@patch("dragonchain.lib.authorization.api_key_model.gen_auth_key", return_value="banana")
@patch("dragonchain.lib.keys.get_public_id", return_value="z7S3WADvnjCyFkUmL48cPGqrSHDrQghNxLFMwBEwwtMa")
@patch("dragonchain.lib.authorization.keys.get_my_keys", return_value=MagicMock(make_signature=MagicMock(return_value="signature")))
@patch("dragonchain.lib.authorization.requests.post", return_value=MagicMock(status_code=201))
@patch("dragonchain.lib.authorization.save_matchmaking_auth_key", return_value=True)
def test_register_with_matchmaking_returns_valid(self, mock_save_key, mock_post, mock_get_keys, mock_get_id, mock_gen_key):
self.assertEqual(authorization.register_new_key_with_matchmaking(), "banana")
@patch("dragonchain.lib.authorization.api_key_model.gen_auth_key", return_value="banana")
@patch("dragonchain.lib.keys.get_public_id", return_value="z7S3WADvnjCyFkUmL48cPGqrSHDrQghNxLFMwBEwwtMa")
@patch("dragonchain.lib.authorization.keys.get_my_keys", return_value=MagicMock(make_signature=MagicMock(return_value="signature")))
@patch("dragonchain.lib.authorization.requests.post", return_value=MagicMock(status_code=100))
@patch("dragonchain.lib.authorization.save_matchmaking_auth_key", return_value=True)
def test_register_with_matchmaking_raises_with_bad_status_code(self, mock_save_key, mock_post, mock_get_keys, mock_get_id, mock_gen_key):
self.assertRaises(RuntimeError, authorization.register_new_key_with_matchmaking)
@patch("dragonchain.lib.authorization.api_key_model.gen_auth_key", return_value="banana")
@patch("dragonchain.lib.keys.get_public_id", return_value="z7S3WADvnjCyFkUmL48cPGqrSHDrQghNxLFMwBEwwtMa")
@patch("dragonchain.lib.authorization.keys.get_my_keys", return_value=MagicMock(make_signature=MagicMock(return_value="signature")))
@patch("dragonchain.lib.authorization.requests.post", side_effect=Exception)
@patch("dragonchain.lib.authorization.save_matchmaking_auth_key", return_value=True)
def test_register_with_matchmaking_raises_with_request_exception(self, mock_save_key, mock_post, mock_get_keys, mock_get_id, mock_gen_key):
self.assertRaises(RuntimeError, authorization.register_new_key_with_matchmaking)
@patch("dragonchain.lib.authorization.api_key_model.gen_auth_key", return_value="banana")
@patch("dragonchain.lib.keys.get_public_id", return_value="z7S3WADvnjCyFkUmL48cPGqrSHDrQghNxLFMwBEwwtMa")
@patch("dragonchain.lib.authorization.keys.get_my_keys", return_value=MagicMock(make_signature=MagicMock(return_value="signature")))
@patch("dragonchain.lib.authorization.requests.post", return_value=MagicMock(status_code=200))
@patch("dragonchain.lib.authorization.save_matchmaking_auth_key", return_value=False)
def test_register_with_matchmaking_raises_with_bad_key_save(self, mock_save_key, mock_post, mock_get_keys, mock_get_id, mock_gen_key):
self.assertRaises(RuntimeError, authorization.register_new_key_with_matchmaking)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.register_new_interchain_key_with_remote", return_value=MagicMock(key="key"))
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=MagicMock(isoformat=MagicMock(return_value="timestamp")))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", side_effect=exceptions.NotFound)
def test_gen_interchain_request_dcid(self, mock_get_auth_key, date_mock, mock_register, mock_dcid):
dcid = "adcid"
full_path = "/path"
json_content = {"thing": "test"}
json_str = json.dumps(json_content, separators=(",", ":")).encode("utf-8")
expected_headers = {
"Content-Type": "application/json",
"timestamp": "timestampZ",
"dragonchain": dcid,
"Authorization": "DC1-HMAC-SHA256 test_dcid:1oJseWBqbZokioWGWjb2jq1iq493MkgUyc3FkQND5XM=",
}
# Test valid SHA256
headers, content = authorization.generate_authenticated_request("POST", dcid, full_path, json_content, "SHA256")
self.assertEqual(content, json_str)
self.assertDictEqual(headers, expected_headers)
# Test valid BLAKE2b512
headers, content = authorization.generate_authenticated_request("POST", dcid, full_path, json_content, "BLAKE2b512")
expected_headers[
"Authorization"
] = "DC1-HMAC-BLAKE2b512 test_dcid:JJiXbVuTjJ03/hNW8fZipw5DUiktO2lJSyml824eWS++mmilth7/BABgDYPvprAa99PHzFzYPA41iL45bI4p1w=="
self.assertEqual(content, json_str)
self.assertDictEqual(headers, expected_headers)
# Test valid SHA3-256
headers, content = authorization.generate_authenticated_request("POST", dcid, full_path, json_content, "SHA3-256")
expected_headers["Authorization"] = "DC1-HMAC-SHA3-256 test_dcid:ANsT9nToNzhWbxtoank/oLMDZoish5tFVuhAMzF/obo="
self.assertEqual(content, json_str)
self.assertDictEqual(headers, expected_headers)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.get_matchmaking_key", return_value=None)
@patch("dragonchain.lib.authorization.register_new_key_with_matchmaking", return_value="key")
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=MagicMock(isoformat=MagicMock(return_value="timestamp")))
def test_gen_interchain_request_matchmaking(self, date_mock, mock_register, mock_get, mock_dcid):
full_path = "/path"
json_content = {"thing": "test"}
json_str = json.dumps(json_content, separators=(",", ":")).encode("utf-8")
expected_headers = {
"Content-Type": "application/json",
"timestamp": "timestampZ",
"Authorization": "DC1-HMAC-SHA256 test_dcid:ab+hEQC0NNJB7mHwpqsfQqEcOyolNOmDEQe9gvUZTYI=",
}
headers, content = authorization.generate_authenticated_request("POST", "matchmaking", full_path, json_content, "SHA256")
self.assertEqual(content, json_str)
self.assertDictEqual(headers, expected_headers)
@patch("dragonchain.lib.authorization.redis.get_sync", return_value=True)
def test_sig_replay_returns_true_with_existing_replay(self, mock_get_sync):
self.assertTrue(authorization.signature_is_replay("thing"))
@patch("dragonchain.lib.authorization.redis.get_sync", return_value=False)
@patch("dragonchain.lib.authorization.redis.set_sync")
def test_sig_replay_returns_false_when_valid(self, mock_set, mock_get):
self.assertFalse(authorization.signature_is_replay("thing"))
mock_set.assert_called_once()
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_with_wrong_dc_id(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Incorrect Dragonchain ID",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
"not_matching",
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_with_unsupported_auth_version(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Unsupported DC Authorization Version",
authorization.verify_request_authorization,
"DC9-HMAC",
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_with_unsupported_hmac_hash(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Unsupported HMAC Hash Type",
authorization.verify_request_authorization,
"DC1-HMAC-INVALID thing",
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_with_old_timestamp(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Timestamp of request too skewed",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
dcid,
"2019-11-14T09:05:25Z",
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_with_malformed_authorization(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Malformed Authorization Header",
authorization.verify_request_authorization,
"DC1-HMAC-SHA256 thing",
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Malformed Authorization Header",
authorization.verify_request_authorization,
"bad_auth",
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_with_invalid_hmac(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Invalid HMAC Authentication",
authorization.verify_request_authorization,
"DC1-HMAC-SHA256 id:badsignaturemFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ=",
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_passes_when_valid(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
# Test valid SHA256
authorization.verify_request_authorization(
auth_str, http_verb, full_path, dcid, timestamp, "", b"", False, "api_keys", "create", "create_api_key"
)
# Test valid BLAKE2b512
authorization.verify_request_authorization(
"DC1-HMAC-BLAKE2b512 id:x1PrKtbs51CR1X6/NTIxyjwOPmZF3rxIXdtJARDialRV+H3FbmUxLmqDuCQvPKEOLN9rNUFhsZa3QZVf8+kXkA==",
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
# Test valid SHA3-256
authorization.verify_request_authorization(
"DC1-HMAC-SHA3-256 id:IjPhj3dzTyj0VhcI5oUl5vcFapX8/GpJaO5M82SD3dE=",
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=True)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_on_replay(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Previous matching request found (no replays allowed)",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=False)))
def test_verify_req_auth_raises_on_key_not_allowed(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.ActionForbidden,
"This key is not allowed to perform create_api_key",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch(
"dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(side_effect=Exception))
)
def test_verify_req_auth_raises_on_key_allowed_exception(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.ActionForbidden,
"This key is not allowed to perform create_api_key",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.should_rate_limit", return_value=True)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_verify_req_auth_raises_with_rate_limit(self, mock_get_auth_key, mock_date, mock_should_limit, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.APIRateLimitException,
f"API Rate Limit Exceeded. {authorization.RATE_LIMIT} requests allowed per minute.",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", side_effect=exceptions.NotFound)
def test_verify_req_auth_raises_with_no_key(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Invalid HMAC Authentication",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", side_effect=Exception)
def test_verify_req_auth_raises_on_get_key_error(self, mock_get_auth_key, mock_date, mock_is_replay, mock_dcid):
auth_str = "DC1-HMAC-SHA256 id:gr1FvIvTe1oOmFZqHgRQUhi6s/EyBvZmJWqH1oWV+UQ="
http_verb = "GET"
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
self.assertRaisesWithMessage(
exceptions.UnauthorizedException,
"Invalid HMAC Format",
authorization.verify_request_authorization,
auth_str,
http_verb,
full_path,
dcid,
timestamp,
"",
b"",
False,
"api_keys",
"create",
"create_api_key",
)
@patch("dragonchain.lib.authorization.keys.get_public_id", return_value="test_dcid")
@patch("dragonchain.lib.authorization.signature_is_replay", return_value=False)
@patch("dragonchain.lib.authorization.get_now_datetime", return_value=datetime.datetime(2018, 11, 14, 9, 5, 25, 128176))
@patch("dragonchain.lib.authorization.api_key_dao.get_api_key", return_value=MagicMock(key="key", is_key_allowed=MagicMock(return_value=True)))
def test_generated_authenticated_request_with_verifier(self, mock_get_auth_key, mock_date, mock_is_replay, mock_get_id):
"""
This is more of psuedo integration test, ensuring that
the generate_authenticated_request 'POST', will generate things are properly
validated by verify_request_authorization
If this test ever fails, it means that interchain communication will be broken
even if all other tests pass
"""
full_path = "/path"
dcid = "test_dcid"
timestamp = "2018-11-14T09:05:25.128176Z"
json_content = {"thing": "test"}
headers, content = authorization.generate_authenticated_request("POST", dcid, full_path, json_content, "SHA256")
auth_str = headers["Authorization"]
# Test with SHA256 HMAC Auth
authorization.verify_request_authorization(
auth_str, "POST", full_path, dcid, timestamp, "application/json", content, False, "api_keys", "create", "create_api_key"
)
headers, content = authorization.generate_authenticated_request("POST", dcid, full_path, json_content, "BLAKE2b512")
auth_str = headers["Authorization"]
# Test with BLAKE2b512 HMAC Auth
authorization.verify_request_authorization(
auth_str, "POST", full_path, dcid, timestamp, "application/json", content, False, "api_keys", "create", "create_api_key"
)
headers, content = authorization.generate_authenticated_request("POST", dcid, full_path, json_content, "SHA3-256")
auth_str = headers["Authorization"]
# Test with SHA3-256 HMAC Auth
authorization.verify_request_authorization(
auth_str, "POST", full_path, dcid, timestamp, "application/json", content, False, "api_keys", "create", "create_api_key"
)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 0)
@patch("dragonchain.lib.authorization.redis.lindex_sync")
def test_should_rate_limit_disabled_on_0(self, mock_lindex):
self.assertFalse(authorization.should_rate_limit("test"))
mock_lindex.assert_not_called()
@patch("dragonchain.lib.authorization.RATE_LIMIT", 1)
@patch("dragonchain.lib.authorization.redis.lindex_sync")
@patch("dragonchain.lib.authorization.redis.ltrim_sync")
@patch("dragonchain.lib.authorization.redis.lpush_sync")
@patch("dragonchain.lib.authorization.time.time", return_value=1554249099.7634845)
def test_should_rate_limit_calls_lpush_when_returning_false(self, mock_time, mock_lpush, mock_ltrim, mock_lindex):
self.assertFalse(authorization.should_rate_limit("test"))
mock_lpush.assert_called_once_with("request:test", "1554249099.7634845")
@patch("dragonchain.lib.authorization.RATE_LIMIT", 2)
@patch("dragonchain.lib.authorization.redis.lindex_sync")
@patch("dragonchain.lib.authorization.redis.lpush_sync")
@patch("dragonchain.lib.authorization.random.randint", return_value=0)
@patch("dragonchain.lib.authorization.redis.ltrim_sync")
def test_should_rate_limit_calls_ltrim(self, mock_ltrim, mock_rand, mock_lpush, mock_lindex):
authorization.should_rate_limit("test")
mock_ltrim.assert_called_once_with("request:test", 0, 1)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 2)
@patch("dragonchain.lib.authorization.redis.lpush_sync")
@patch("dragonchain.lib.authorization.redis.ltrim_sync")
@patch("dragonchain.lib.authorization.redis.lindex_sync")
def test_should_rate_limit_calls_lindex(self, mock_lindex, mock_ltrim, mock_lpush):
authorization.should_rate_limit("test")
mock_lindex.assert_called_once_with("request:test", 1, decode=False)
@patch("dragonchain.lib.authorization.RATE_LIMIT", 2)
@patch("dragonchain.lib.authorization.redis.lindex_sync", return_value=b"1554249095.7634845")
@patch("dragonchain.lib.authorization.redis.ltrim_sync")
@patch("dragonchain.lib.authorization.time.time", return_value=1554249099.7634845)
def test_should_rate_limit_returns_true_when_limited(self, mock_time, mock_ltrim, mock_lindex):
self.assertTrue(authorization.should_rate_limit("test"))
| 52.603916
| 148
| 0.701738
| 4,078
| 34,929
| 5.698627
| 0.084355
| 0.085546
| 0.11528
| 0.185894
| 0.820905
| 0.788545
| 0.754594
| 0.738285
| 0.730969
| 0.719222
| 0
| 0.03254
| 0.191446
| 34,929
| 663
| 149
| 52.683258
| 0.790312
| 0.047267
| 0
| 0.737201
| 0
| 0
| 0.332469
| 0.252615
| 0
| 0
| 0
| 0
| 0.087031
| 1
| 0.06314
| false
| 0.001706
| 0.011945
| 0
| 0.076792
| 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
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| 0
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| 0
| 0
| 0
| 0
|
0
| 8
|
f0d0795521b3c8899e943e127a5314e8bfd4867d
| 8,945
|
py
|
Python
|
augmentation.py
|
baoanh1310/zalo_2020
|
9575223bd3d3e4b5ec69a33f04769703ef15cbff
|
[
"Apache-2.0"
] | null | null | null |
augmentation.py
|
baoanh1310/zalo_2020
|
9575223bd3d3e4b5ec69a33f04769703ef15cbff
|
[
"Apache-2.0"
] | null | null | null |
augmentation.py
|
baoanh1310/zalo_2020
|
9575223bd3d3e4b5ec69a33f04769703ef15cbff
|
[
"Apache-2.0"
] | null | null | null |
import os
from data_aug.data_aug import *
from data_aug.bbox_util import *
from PIL import Image
import cv2
import numpy as np
import argparse
import json
from config import *
train_folder = TRAIN_FOLDER
train_json = TRAIN_JSON_FILE
augment_folder = AUGMENT_FOLDER
augment_json = AUGMENT_JSON_FILE
with open(augment_json, 'r') as f:
json_dict = json.load(f)
if not os.path.exists(augment_folder):
os.mkdir(augment_folder)
with open(train_json, "r") as file:
annotations = json.load(file)
bboxes = annotations['annotations']
images = annotations['images']
image_id_list = [image['id'] for image in images]
new_image_id = max(image_id_list)
old_bboxes = bboxes.copy()
old_images = images.copy()
# Scaling
for image in old_images:
new_image_id += 1
image_id = image['id']
width, height, street_id = image['width'], image['height'], image['street_id']
file_name = image['file_name']
img_path = os.path.join(train_folder, file_name)
img_dict = {'file_name': '{}.png'.format(new_image_id), 'height': height, 'width': width, 'id': new_image_id, 'street_id': street_id}
images.append(img_dict)
img = cv2.imread(img_path)[:, :, ::-1] # BGR -> RGB
for bbox in old_bboxes:
if bbox['image_id'] == image_id:
segmentation, area, iscrowd, category_id, id = bbox['segmentation'], bbox['area'], bbox['iscrowd'], bbox['category_id'], bbox['id']
anno_dict = {'segmentation': segmentation, 'area': area, 'iscrowd': iscrowd, 'category_id': category_id, 'id': id, 'image_id': new_image_id}
bb = bbox['bbox']
bb = [bb[0], bb[1], bb[0] + bb[2], bb[1] + bb[3]]
bb = np.array(bb)
bb.reshape(1, -1)
bb = np.expand_dims(bb, axis=0)
bb = bb.astype('float64')
img_, bboxes_ = RandomScale(0.1)(img.copy(), bb.copy())
bboxes_ = bboxes_.reshape(-1, 4)
if bboxes_.shape[0] != 1:
continue
bboxes_ = list(bboxes_.squeeze(axis=0))
bb1 = [bboxes_[0], bboxes_[1], bboxes_[2]-bboxes_[0], bboxes_[3]-bboxes_[1]]
anno_dict['bbox'] = bb1
bboxes.append(anno_dict)
# save augment image to augment folder
Image.fromarray(img_).save(os.path.join(augment_folder, '{}.png'.format(new_image_id)))
# Traslation
for image in old_images:
new_image_id += 1
image_id = image['id']
width, height, street_id = image['width'], image['height'], image['street_id']
file_name = image['file_name']
img_path = os.path.join(train_folder, file_name)
img_dict = {'file_name': '{}.png'.format(new_image_id), 'height': height, 'width': width, 'id': new_image_id, 'street_id': street_id}
images.append(img_dict)
img = cv2.imread(img_path)[:, :, ::-1] # BGR -> RGB
for bbox in old_bboxes:
if bbox['image_id'] == image_id:
segmentation, area, iscrowd, category_id, id = bbox['segmentation'], bbox['area'], bbox['iscrowd'], bbox['category_id'], bbox['id']
anno_dict = {'segmentation': segmentation, 'area': area, 'iscrowd': iscrowd, 'category_id': category_id, 'id': id, 'image_id': new_image_id}
bb = bbox['bbox']
bb = [bb[0], bb[1], bb[0] + bb[2], bb[1] + bb[3]]
bb = np.array(bb)
bb.reshape(1, -1)
bb = np.expand_dims(bb, axis=0)
bb = bb.astype('float64')
img_, bboxes_ = RandomTranslate(0.3, diff = True)(img.copy(), bb.copy())
bboxes_ = bboxes_.reshape(-1, 4)
if bboxes_.shape[0] != 1:
continue
bboxes_ = list(bboxes_.squeeze(axis=0))
bb1 = [bboxes_[0], bboxes_[1], bboxes_[2]-bboxes_[0], bboxes_[3]-bboxes_[1]]
anno_dict['bbox'] = bb1
bboxes.append(anno_dict)
# save augment image to augment folder
Image.fromarray(img_).save(os.path.join(augment_folder, '{}.png'.format(new_image_id)))
# Shearing
for image in old_images:
new_image_id += 1
image_id = image['id']
width, height, street_id = image['width'], image['height'], image['street_id']
file_name = image['file_name']
img_path = os.path.join(train_folder, file_name)
img_dict = {'file_name': '{}.png'.format(new_image_id), 'height': height, 'width': width, 'id': new_image_id, 'street_id': street_id}
images.append(img_dict)
img = cv2.imread(img_path)[:, :, ::-1] # BGR -> RGB
for bbox in old_bboxes:
if bbox['image_id'] == image_id:
segmentation, area, iscrowd, category_id, id = bbox['segmentation'], bbox['area'], bbox['iscrowd'], bbox['category_id'], bbox['id']
anno_dict = {'segmentation': segmentation, 'area': area, 'iscrowd': iscrowd, 'category_id': category_id, 'id': id, 'image_id': new_image_id}
bb = bbox['bbox']
bb = [bb[0], bb[1], bb[0] + bb[2], bb[1] + bb[3]]
bb = np.array(bb)
bb.reshape(1, -1)
bb = np.expand_dims(bb, axis=0)
bb = bb.astype('float64')
img_, bboxes_ = RandomShear(0.2)(img.copy(), bb.copy())
bboxes_ = bboxes_.reshape(-1, 4)
if bboxes_.shape[0] != 1:
continue
bboxes_ = list(bboxes_.squeeze(axis=0))
bb1 = [bboxes_[0], bboxes_[1], bboxes_[2]-bboxes_[0], bboxes_[3]-bboxes_[1]]
anno_dict['bbox'] = bb1
bboxes.append(anno_dict)
# save augment image to augment folder
Image.fromarray(img_).save(os.path.join(augment_folder, '{}.png'.format(new_image_id)))
# Rotating
for image in old_images:
new_image_id += 1
image_id = image['id']
width, height, street_id = image['width'], image['height'], image['street_id']
file_name = image['file_name']
img_path = os.path.join(train_folder, file_name)
img_dict = {'file_name': '{}.png'.format(new_image_id), 'height': height, 'width': width, 'id': new_image_id, 'street_id': street_id}
images.append(img_dict)
img = cv2.imread(img_path)[:, :, ::-1] # BGR -> RGB
for bbox in old_bboxes:
if bbox['image_id'] == image_id:
segmentation, area, iscrowd, category_id, id = bbox['segmentation'], bbox['area'], bbox['iscrowd'], bbox['category_id'], bbox['id']
anno_dict = {'segmentation': segmentation, 'area': area, 'iscrowd': iscrowd, 'category_id': category_id, 'id': id, 'image_id': new_image_id}
bb = bbox['bbox']
bb = [bb[0], bb[1], bb[0] + bb[2], bb[1] + bb[3]]
bb = np.array(bb)
bb.reshape(1, -1)
bb = np.expand_dims(bb, axis=0)
bb = bb.astype('float64')
img_, bboxes_ = RandomRotate(20)(img.copy(), bb.copy())
bboxes_ = bboxes_.reshape(-1, 4)
if bboxes_.shape[0] != 1:
continue
bboxes_ = list(bboxes_.squeeze(axis=0))
bb1 = [bboxes_[0], bboxes_[1], bboxes_[2]-bboxes_[0], bboxes_[3]-bboxes_[1]]
anno_dict['bbox'] = bb1
bboxes.append(anno_dict)
# save augment image to augment folder
Image.fromarray(img_).save(os.path.join(augment_folder, '{}.png'.format(new_image_id)))
# Resizing
for image in old_images:
new_image_id += 1
image_id = image['id']
width, height, street_id = image['width'], image['height'], image['street_id']
file_name = image['file_name']
img_path = os.path.join(train_folder, file_name)
img_dict = {'file_name': '{}.png'.format(new_image_id), 'height': height, 'width': width, 'id': new_image_id, 'street_id': street_id}
images.append(img_dict)
img = cv2.imread(img_path)[:, :, ::-1] # BGR -> RGB
for bbox in old_bboxes:
if bbox['image_id'] == image_id:
segmentation, area, iscrowd, category_id, id = bbox['segmentation'], bbox['area'], bbox['iscrowd'], bbox['category_id'], bbox['id']
anno_dict = {'segmentation': segmentation, 'area': area, 'iscrowd': iscrowd, 'category_id': category_id, 'id': id, 'image_id': new_image_id}
bb = bbox['bbox']
bb = [bb[0], bb[1], bb[0] + bb[2], bb[1] + bb[3]]
bb = np.array(bb)
bb.reshape(1, -1)
bb = np.expand_dims(bb, axis=0)
bb = bb.astype('float64')
img_, bboxes_ = Resize(608)(img.copy(), bb.copy())
bboxes_ = bboxes_.reshape(-1, 4)
if bboxes_.shape[0] != 1:
continue
bboxes_ = list(bboxes_.squeeze(axis=0))
bb1 = [bboxes_[0], bboxes_[1], bboxes_[2]-bboxes_[0], bboxes_[3]-bboxes_[1]]
anno_dict['bbox'] = bb1
bboxes.append(anno_dict)
# save augment image to augment folder
Image.fromarray(img_).save(os.path.join(augment_folder, '{}.png'.format(new_image_id)))
with open(augment_json, 'w') as file:
json_dict['images'] = images
json_dict['annotations'] = bboxes
json.dump(json_dict, file)
| 41.03211
| 152
| 0.596534
| 1,238
| 8,945
| 4.075121
| 0.076737
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| 153
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0
| 7
|
f0f2a26745b737e2c797fb48704576cb9af03fc1
| 12,197
|
py
|
Python
|
PSYC15_Project_static1/dictionary_img.py
|
fooledyouonce/FacialRecognition
|
df4ee623a4f06f7a4fda8a33449b783196a814d7
|
[
"Apache-2.0"
] | null | null | null |
PSYC15_Project_static1/dictionary_img.py
|
fooledyouonce/FacialRecognition
|
df4ee623a4f06f7a4fda8a33449b783196a814d7
|
[
"Apache-2.0"
] | null | null | null |
PSYC15_Project_static1/dictionary_img.py
|
fooledyouonce/FacialRecognition
|
df4ee623a4f06f7a4fda8a33449b783196a814d7
|
[
"Apache-2.0"
] | 1
|
2022-02-25T17:27:20.000Z
|
2022-02-25T17:27:20.000Z
|
import os
def getKey(pyimage):
trial_dict = {'pyimage1':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage2':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage3':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage4':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage5':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage6':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage7':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage8':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage9':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage10':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage11':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage12':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage13':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage14':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage15':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage16':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage17':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage18':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage19':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage20':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage21':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage22':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage23':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage24':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage25':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage26':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage27':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage28':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage29':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage30':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage31':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage32':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage33':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage34':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage35':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage36':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage37':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage38':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage39':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage40':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage41':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage42':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage43':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage44':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage45':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage46':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage47':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage48':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage49':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage50':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury'],\
'pyimage51':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage52':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage53':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage54':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted'],\
'pyimage55':['afraid','scared','fear','frightened','nervous','terrified','terror','alarm','dread','fright','fearful','alarmed'],\
'pyimage56':['angry','anger','mad','frustrated','upset','rage','enraged','furious','hate','hatred','fury','frustration','irritated','irritation','seething','infuriated','livid','pissed','pissed off'],\
'pyimage57':['disgust','disgusted','repulsed','horror','sickened','revulsion','detest','nausea','distaste','grossed out','contempt'],\
'pyimage58':['happy','glad','joyful','joy','content','satisfied','cheer','cheerful','smile','smiling','merry','elated','delighted','amused','enjoy','enjoyment','enjoyed','jublient'],\
'pyimage59':['sad','unhappy','depressed','down','gloomy','miserable','anguish','sorrowful','regret','desolate','inconsolable','sorrow','sadness','defeated','upset','grief','grieving','distraught','devastated','disheartened','heartbroken','downcast','despair'],\
'pyimage60':['surprise','surprised','shock','shocked','amazed','astonished','astound','stunned','startled','speechless','unbelievable','disbelief','realization','realize','dumbfounded','flabbergasted']}
values = trial_dict[pyimage]
return values
if __name__ == "__main__":
dictionary_img()
| 152.4625
| 276
| 0.63819
| 1,079
| 12,197
| 7.203892
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| 12,197
| 79
| 277
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| 0.015152
| false
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| null | 0
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| 0
|
0
| 8
|
0b17799639421d5cbbe0efcaaf403d03b6982c1d
| 226
|
py
|
Python
|
python/testData/quickFixes/PyTypeHintsQuickFixTest/functionAnnotationAndTypeComment.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 1
|
2018-10-03T12:35:12.000Z
|
2018-10-03T12:35:12.000Z
|
python/testData/quickFixes/PyTypeHintsQuickFixTest/functionAnnotationAndTypeComment.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/quickFixes/PyTypeHintsQuickFixTest/functionAnnotationAndTypeComment.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
def <warning descr="Type(s) specified both in type comment and annotation">b<caret>ar</warning>(a: int) -> int:
<warning descr="Type(s) specified both in type comment and annotation"># type: (int) -> int</warning>
pass
| 75.333333
| 111
| 0.699115
| 35
| 226
| 4.514286
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| 0.708861
| 0.708861
| 0.708861
| 0
| 0
| 0.150442
| 226
| 3
| 112
| 75.333333
| 0.822917
| 0.123894
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| null | null | 0.333333
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| null | 0
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| 0
|
0
| 10
|
50096ce1fba3bfe35e250ec59a078947424a2730
| 68,642
|
py
|
Python
|
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_ml/SystemIPC_2/cmp_perlbench/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_ml/SystemIPC_2/cmp_perlbench/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_spec_tugberk_ml/SystemIPC_2/cmp_perlbench/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
power = {'BUSES': {'Area': 1.33155,
'Bus/Area': 1.33155,
'Bus/Gate Leakage': 0.00662954,
'Bus/Peak Dynamic': 0.0,
'Bus/Runtime Dynamic': 0.0,
'Bus/Subthreshold Leakage': 0.0691322,
'Bus/Subthreshold Leakage with power gating': 0.0259246,
'Gate Leakage': 0.00662954,
'Peak Dynamic': 0.0,
'Runtime Dynamic': 0.0,
'Subthreshold Leakage': 0.0691322,
'Subthreshold Leakage with power gating': 0.0259246},
'Core': [{'Area': 32.6082,
'Execution Unit/Area': 8.2042,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 1.88938e-06,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.20269,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 1.01201e-05,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.122718,
'Execution Unit/Instruction Scheduler/Area': 2.17927,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.64285,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 1.11318,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.638442,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 2.39448,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.635429,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 6.14552,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 1.91191e-06,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0233038,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.168517,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.172346,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.168519,
'Execution Unit/Register Files/Runtime Dynamic': 0.19565,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.407206,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 1.0678,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155,
'Execution Unit/Runtime Dynamic': 4.266,
'Execution Unit/Subthreshold Leakage': 1.83518,
'Execution Unit/Subthreshold Leakage with power gating': 0.709678,
'Gate Leakage': 0.372997,
'Instruction Fetch Unit/Area': 5.86007,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.0063595,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.0063595,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00553084,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.00213655,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00247576,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.0207256,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0612699,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0590479,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.165681,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 6.43323,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.660929,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.562726,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 8.96874,
'Instruction Fetch Unit/Runtime Dynamic': 1.47133,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932587,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0452388,
'L2/Runtime Dynamic': 0.00864453,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80969,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 6.27403,
'Load Store Unit/Data Cache/Runtime Dynamic': 2.42301,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0351387,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.162956,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.162956,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 7.04668,
'Load Store Unit/Runtime Dynamic': 3.38961,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.401822,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.803643,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591622,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283406,
'Memory Management Unit/Area': 0.434579,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.142608,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.143001,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00813591,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.399995,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.109197,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.805035,
'Memory Management Unit/Runtime Dynamic': 0.252198,
'Memory Management Unit/Subthreshold Leakage': 0.0769113,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0399462,
'Peak Dynamic': 27.5729,
'Renaming Unit/Area': 0.369768,
'Renaming Unit/FP Front End RAT/Area': 0.168486,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 3.33511,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 7.39128e-06,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0437281,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925,
'Renaming Unit/Free List/Area': 0.0414755,
'Renaming Unit/Free List/Gate Leakage': 4.15911e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0401324,
'Renaming Unit/Free List/Runtime Dynamic': 0.0328719,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000670426,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987,
'Renaming Unit/Gate Leakage': 0.00863632,
'Renaming Unit/Int Front End RAT/Area': 0.114751,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.335266,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781,
'Renaming Unit/Peak Dynamic': 4.56169,
'Renaming Unit/Runtime Dynamic': 0.368146,
'Renaming Unit/Subthreshold Leakage': 0.070483,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779,
'Runtime Dynamic': 9.75593,
'Subthreshold Leakage': 6.21877,
'Subthreshold Leakage with power gating': 2.58311},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 2.83407e-06,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.202691,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 1.77103e-05,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.166607,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.26873,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.135646,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.570983,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.190547,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 4.19575,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 3.34585e-06,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00698823,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0505347,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0516822,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.050538,
'Execution Unit/Register Files/Runtime Dynamic': 0.0586704,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.106463,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.280483,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.5182,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00219166,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00219166,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00197022,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000796228,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000742419,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00709597,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0188237,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0496834,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 3.16029,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.195687,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.168747,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 5.53218,
'Instruction Fetch Unit/Runtime Dynamic': 0.440038,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0455798,
'L2/Runtime Dynamic': 0.00899491,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 2.92048,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.81294,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0544607,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0544608,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 3.17765,
'Load Store Unit/Runtime Dynamic': 1.13598,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.134291,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.268582,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
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'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
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'Memory Management Unit/Peak Dynamic': 0.434476,
'Memory Management Unit/Runtime Dynamic': 0.0809973,
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'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
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'Renaming Unit/FP Front End RAT/Runtime Dynamic': 8.31176e-06,
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'Renaming Unit/Free List/Area': 0.0340654,
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'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
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'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
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'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.0924962,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 3.27671,
'Subthreshold Leakage': 6.16288,
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'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 9.4469e-07,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.20269,
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'Execution Unit/Floating Point Units/Area': 4.6585,
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'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
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'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
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'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
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'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
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'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.621073,
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'Execution Unit/Peak Dynamic': 4.22847,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 1.91191e-06,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00760127,
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'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
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'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.0549689,
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'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
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'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.1158,
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'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.59736,
'Execution Unit/Subthreshold Leakage': 1.79543,
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'Instruction Fetch Unit/Area': 5.85939,
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'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
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'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
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'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
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'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000807549,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00759336,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0203073,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.054042,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 3.43753,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.212065,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.183551,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 5.82288,
'Instruction Fetch Unit/Runtime Dynamic': 0.477559,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0357829,
'L2/Runtime Dynamic': 0.00696773,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 2.99701,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.848868,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0569365,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0569365,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 3.26587,
'Load Store Unit/Runtime Dynamic': 1.1866,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.140396,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.280792,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0498269,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0501343,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.213733,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0354463,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.455436,
'Memory Management Unit/Runtime Dynamic': 0.0855806,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 17.3979,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 4.45596e-06,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
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'Renaming Unit/Free List/Runtime Dynamic': 0.0081763,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0924691,
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'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.10065,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 3.45472,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 9.4469e-07,
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'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
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'Execution Unit/Floating Point Units/Area': 4.6585,
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'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
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'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
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'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
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'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.274576,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
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'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.138597,
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'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.583403,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
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'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 4.20385,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
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'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 9.55956e-07,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.00714024,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.0516334,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0528064,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.0516344,
'Execution Unit/Register Files/Runtime Dynamic': 0.0599467,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.108777,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.286151,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 1.53757,
'Execution Unit/Subthreshold Leakage': 1.79543,
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'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.0022238,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.0022238,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00199729,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000806195,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.000758568,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00720345,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.019165,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0507642,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 3.22904,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.198317,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.172418,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 5.60426,
'Instruction Fetch Unit/Runtime Dynamic': 0.447868,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.038012,
'L2/Runtime Dynamic': 0.00738265,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 2.91872,
'Load Store Unit/Data Cache/Runtime Dynamic': 0.811618,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0544038,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0544038,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 3.17563,
'Load Store Unit/Runtime Dynamic': 1.13432,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.13415,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.268301,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0476104,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0479366,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.20077,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0332361,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.438665,
'Memory Management Unit/Runtime Dynamic': 0.0811727,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 17.0499,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 2.7582e-06,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.00768037,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.0868373,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.0945204,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 3.30283,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328}],
'DRAM': {'Area': 0,
'Gate Leakage': 0,
'Peak Dynamic': 0.8494222218557655,
'Runtime Dynamic': 0.8494222218557655,
'Subthreshold Leakage': 4.252,
'Subthreshold Leakage with power gating': 4.252},
'L3': [{'Area': 61.9075,
'Gate Leakage': 0.0484137,
'Peak Dynamic': 0.0825433,
'Runtime Dynamic': 0.0343386,
'Subthreshold Leakage': 6.80085,
'Subthreshold Leakage with power gating': 3.32364}],
'Processor': {'Area': 191.908,
'Gate Leakage': 1.53485,
'Peak Dynamic': 79.0784,
'Peak Power': 112.191,
'Runtime Dynamic': 19.8245,
'Subthreshold Leakage': 31.5774,
'Subthreshold Leakage with power gating': 13.9484,
'Total Cores/Area': 128.669,
'Total Cores/Gate Leakage': 1.4798,
'Total Cores/Peak Dynamic': 78.9958,
'Total Cores/Runtime Dynamic': 19.7902,
'Total Cores/Subthreshold Leakage': 24.7074,
'Total Cores/Subthreshold Leakage with power gating': 10.2429,
'Total L3s/Area': 61.9075,
'Total L3s/Gate Leakage': 0.0484137,
'Total L3s/Peak Dynamic': 0.0825433,
'Total L3s/Runtime Dynamic': 0.0343386,
'Total L3s/Subthreshold Leakage': 6.80085,
'Total L3s/Subthreshold Leakage with power gating': 3.32364,
'Total Leakage': 33.1122,
'Total NoCs/Area': 1.33155,
'Total NoCs/Gate Leakage': 0.00662954,
'Total NoCs/Peak Dynamic': 0.0,
'Total NoCs/Runtime Dynamic': 0.0,
'Total NoCs/Subthreshold Leakage': 0.0691322,
'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}
| 75.100656
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| 0
|
0
| 7
|
ac96b27acd35da2451e7930d1ff4d5ac01322345
| 147
|
py
|
Python
|
ETL-CSV-to-HDF5/client/hdflow/__init__.py
|
Bears-R-Us/arkouda-contrib
|
6965d6f8a274dd633ebf718b56b93c40562627fc
|
[
"MIT"
] | 2
|
2022-02-09T20:20:47.000Z
|
2022-02-10T01:00:14.000Z
|
ETL-CSV-to-HDF5/client/hdflow/__init__.py
|
Bears-R-Us/arkouda-contrib
|
6965d6f8a274dd633ebf718b56b93c40562627fc
|
[
"MIT"
] | 8
|
2022-02-24T12:52:34.000Z
|
2022-03-30T16:51:07.000Z
|
ETL-CSV-to-HDF5/client/hdflow/__init__.py
|
Bears-R-Us/arkouda-contrib
|
6965d6f8a274dd633ebf718b56b93c40562627fc
|
[
"MIT"
] | 2
|
2022-02-14T23:32:19.000Z
|
2022-03-25T14:59:39.000Z
|
__all__ = ["hdflow", "example_formats"]
from hdflow.converters import *
import hdflow.example_formats
from hdflow.example_formats import OPTIONS
| 24.5
| 42
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0
| 7
|
acca2e2a33a7499a365a4800624449cca6e15ebd
| 68,581
|
py
|
Python
|
benchmarks/SimResults/_bigLittle_hrrs_splash_tugberk_ml/ratio_based_results/cmp_cholesky/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_splash_tugberk_ml/ratio_based_results/cmp_cholesky/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
benchmarks/SimResults/_bigLittle_hrrs_splash_tugberk_ml/ratio_based_results/cmp_cholesky/power.py
|
TugberkArkose/MLScheduler
|
e493b6cbf7b9d29a2c9300d7dd6f0c2f102e4061
|
[
"Unlicense"
] | null | null | null |
power = {'BUSES': {'Area': 1.33155,
'Bus/Area': 1.33155,
'Bus/Gate Leakage': 0.00662954,
'Bus/Peak Dynamic': 0.0,
'Bus/Runtime Dynamic': 0.0,
'Bus/Subthreshold Leakage': 0.0691322,
'Bus/Subthreshold Leakage with power gating': 0.0259246,
'Gate Leakage': 0.00662954,
'Peak Dynamic': 0.0,
'Runtime Dynamic': 0.0,
'Subthreshold Leakage': 0.0691322,
'Subthreshold Leakage with power gating': 0.0259246},
'Core': [{'Area': 32.6082,
'Execution Unit/Area': 8.2042,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.199189,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.359141,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 1.08123,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.122718,
'Execution Unit/Instruction Scheduler/Area': 2.17927,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.328073,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.00115349,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.20978,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.591106,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.017004,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00962066,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00730101,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 1.00996,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00529112,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 2.07911,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 1.02358,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0800117,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0455351,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 4.84781,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.841232,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.000856399,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.55892,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.587053,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.0178624,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00897339,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 2.20174,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.114878,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.0641291,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.418518,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 7.64596,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.204267,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0214281,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.2293,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.158474,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.433566,
'Execution Unit/Register Files/Runtime Dynamic': 0.179902,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0442632,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00607074,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.608652,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 1.50426,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.0920413,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0345155,
'Execution Unit/Runtime Dynamic': 4.65042,
'Execution Unit/Subthreshold Leakage': 1.83518,
'Execution Unit/Subthreshold Leakage with power gating': 0.709678,
'Gate Leakage': 0.372997,
'Instruction Fetch Unit/Area': 5.86007,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00208945,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00208945,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00181581,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000700688,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00227649,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00827119,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0201798,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0590479,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.152345,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 6.43323,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.428601,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.517431,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 8.96874,
'Instruction Fetch Unit/Runtime Dynamic': 1.12683,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932587,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.408542,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0708227,
'L2/Runtime Dynamic': 0.012966,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80969,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 6.17997,
'Load Store Unit/Data Cache/Runtime Dynamic': 2.3841,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0351387,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.159913,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.159913,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 6.93819,
'Load Store Unit/Runtime Dynamic': 3.33265,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.394318,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.788635,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591622,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283406,
'Memory Management Unit/Area': 0.434579,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.139945,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.141001,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00813591,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.399995,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0702826,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.800431,
'Memory Management Unit/Runtime Dynamic': 0.211284,
'Memory Management Unit/Subthreshold Leakage': 0.0769113,
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'Renaming Unit/Area': 0.369768,
'Renaming Unit/FP Front End RAT/Area': 0.168486,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00489731,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 3.33511,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.71264,
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'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.024925,
'Renaming Unit/Free List/Area': 0.0414755,
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'Renaming Unit/Free List/Subthreshold Leakage': 0.000670426,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000377987,
'Renaming Unit/Gate Leakage': 0.00863632,
'Renaming Unit/Int Front End RAT/Area': 0.114751,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.00038343,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.86945,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.294744,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00611897,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00348781,
'Renaming Unit/Peak Dynamic': 4.56169,
'Renaming Unit/Runtime Dynamic': 1.04619,
'Renaming Unit/Subthreshold Leakage': 0.070483,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0362779,
'Runtime Dynamic': 10.3803,
'Subthreshold Leakage': 6.21877,
'Subthreshold Leakage with power gating': 2.58311},
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'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.0993889,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.280753,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.539963,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.267405,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.431314,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.217713,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.916432,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
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'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 5.20898,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.102011,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0112162,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.118185,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0829504,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.220196,
'Execution Unit/Register Files/Runtime Dynamic': 0.0941666,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.273836,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.683532,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 2.38026,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00117316,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00117316,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00102922,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000402472,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00119159,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00456713,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0109839,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0797424,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 5.0723,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.230971,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.270841,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 7.53698,
'Instruction Fetch Unit/Runtime Dynamic': 0.597105,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0360323,
'L2/Runtime Dynamic': 0.00703759,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 3.82706,
'Load Store Unit/Data Cache/Runtime Dynamic': 1.24991,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0837908,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0837906,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 4.22274,
'Load Store Unit/Runtime Dynamic': 1.74693,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.206614,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.413227,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0733279,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0738652,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.315377,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0378752,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.59745,
'Memory Management Unit/Runtime Dynamic': 0.11174,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 21.1917,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.268344,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.0153303,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.131481,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.415155,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 5.25823,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328},
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'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.0948384,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.277179,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.515002,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.263758,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.425432,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.214744,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.903935,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.222706,
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'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 5.16454,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.0972948,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0110632,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.115391,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0818192,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.212686,
'Execution Unit/Register Files/Runtime Dynamic': 0.0928824,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.266812,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.665542,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 2.34491,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.00121344,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.00121344,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00106397,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000415743,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00117534,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00466618,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0113819,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0786549,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 5.00312,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.231673,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.267147,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 7.46445,
'Instruction Fetch Unit/Runtime Dynamic': 0.593524,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0346938,
'L2/Runtime Dynamic': 0.00726734,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 3.76099,
'Load Store Unit/Data Cache/Runtime Dynamic': 1.21885,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0816531,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0816531,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 4.14657,
'Load Store Unit/Runtime Dynamic': 1.70319,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.201343,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.402685,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0714572,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.0719746,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.311076,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0379899,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.589936,
'Memory Management Unit/Runtime Dynamic': 0.109964,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 20.9897,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.255938,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.0150148,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.129868,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.400821,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 5.15968,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328},
{'Area': 32.0201,
'Execution Unit/Area': 7.68434,
'Execution Unit/Complex ALUs/Area': 0.235435,
'Execution Unit/Complex ALUs/Gate Leakage': 0.0132646,
'Execution Unit/Complex ALUs/Peak Dynamic': 0.0945342,
'Execution Unit/Complex ALUs/Runtime Dynamic': 0.27694,
'Execution Unit/Complex ALUs/Subthreshold Leakage': 0.20111,
'Execution Unit/Complex ALUs/Subthreshold Leakage with power gating': 0.0754163,
'Execution Unit/Floating Point Units/Area': 4.6585,
'Execution Unit/Floating Point Units/Gate Leakage': 0.0656156,
'Execution Unit/Floating Point Units/Peak Dynamic': 0.511867,
'Execution Unit/Floating Point Units/Runtime Dynamic': 0.304033,
'Execution Unit/Floating Point Units/Subthreshold Leakage': 0.994829,
'Execution Unit/Floating Point Units/Subthreshold Leakage with power gating': 0.373061,
'Execution Unit/Gate Leakage': 0.120359,
'Execution Unit/Instruction Scheduler/Area': 1.66526,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Area': 0.275653,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Gate Leakage': 0.000977433,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Peak Dynamic': 1.04181,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Runtime Dynamic': 0.263718,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage': 0.0143453,
'Execution Unit/Instruction Scheduler/FP Instruction Window/Subthreshold Leakage with power gating': 0.00810519,
'Execution Unit/Instruction Scheduler/Gate Leakage': 0.00568913,
'Execution Unit/Instruction Scheduler/Instruction Window/Area': 0.805223,
'Execution Unit/Instruction Scheduler/Instruction Window/Gate Leakage': 0.00414562,
'Execution Unit/Instruction Scheduler/Instruction Window/Peak Dynamic': 1.6763,
'Execution Unit/Instruction Scheduler/Instruction Window/Runtime Dynamic': 0.425368,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage': 0.0625755,
'Execution Unit/Instruction Scheduler/Instruction Window/Subthreshold Leakage with power gating': 0.0355964,
'Execution Unit/Instruction Scheduler/Peak Dynamic': 3.82262,
'Execution Unit/Instruction Scheduler/ROB/Area': 0.584388,
'Execution Unit/Instruction Scheduler/ROB/Gate Leakage': 0.00056608,
'Execution Unit/Instruction Scheduler/ROB/Peak Dynamic': 1.10451,
'Execution Unit/Instruction Scheduler/ROB/Runtime Dynamic': 0.214711,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage': 0.00906853,
'Execution Unit/Instruction Scheduler/ROB/Subthreshold Leakage with power gating': 0.00364446,
'Execution Unit/Instruction Scheduler/Runtime Dynamic': 0.903797,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage': 0.0859892,
'Execution Unit/Instruction Scheduler/Subthreshold Leakage with power gating': 0.047346,
'Execution Unit/Integer ALUs/Area': 0.47087,
'Execution Unit/Integer ALUs/Gate Leakage': 0.0265291,
'Execution Unit/Integer ALUs/Peak Dynamic': 0.223141,
'Execution Unit/Integer ALUs/Runtime Dynamic': 0.101344,
'Execution Unit/Integer ALUs/Subthreshold Leakage': 0.40222,
'Execution Unit/Integer ALUs/Subthreshold Leakage with power gating': 0.150833,
'Execution Unit/Peak Dynamic': 5.16073,
'Execution Unit/Register Files/Area': 0.570804,
'Execution Unit/Register Files/Floating Point RF/Area': 0.208131,
'Execution Unit/Register Files/Floating Point RF/Gate Leakage': 0.000232788,
'Execution Unit/Register Files/Floating Point RF/Peak Dynamic': 0.0967026,
'Execution Unit/Register Files/Floating Point RF/Runtime Dynamic': 0.0110615,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage': 0.00399698,
'Execution Unit/Register Files/Floating Point RF/Subthreshold Leakage with power gating': 0.00176968,
'Execution Unit/Register Files/Gate Leakage': 0.000622708,
'Execution Unit/Register Files/Integer RF/Area': 0.362673,
'Execution Unit/Register Files/Integer RF/Gate Leakage': 0.00038992,
'Execution Unit/Register Files/Integer RF/Peak Dynamic': 0.115326,
'Execution Unit/Register Files/Integer RF/Runtime Dynamic': 0.0818068,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage': 0.00614175,
'Execution Unit/Register Files/Integer RF/Subthreshold Leakage with power gating': 0.00246675,
'Execution Unit/Register Files/Peak Dynamic': 0.212029,
'Execution Unit/Register Files/Runtime Dynamic': 0.0928683,
'Execution Unit/Register Files/Subthreshold Leakage': 0.0101387,
'Execution Unit/Register Files/Subthreshold Leakage with power gating': 0.00423643,
'Execution Unit/Results Broadcast Bus/Area Overhead': 0.0390912,
'Execution Unit/Results Broadcast Bus/Gate Leakage': 0.00537402,
'Execution Unit/Results Broadcast Bus/Peak Dynamic': 0.266598,
'Execution Unit/Results Broadcast Bus/Runtime Dynamic': 0.661793,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage': 0.081478,
'Execution Unit/Results Broadcast Bus/Subthreshold Leakage with power gating': 0.0305543,
'Execution Unit/Runtime Dynamic': 2.34078,
'Execution Unit/Subthreshold Leakage': 1.79543,
'Execution Unit/Subthreshold Leakage with power gating': 0.688821,
'Gate Leakage': 0.368936,
'Instruction Fetch Unit/Area': 5.85939,
'Instruction Fetch Unit/Branch Predictor/Area': 0.138516,
'Instruction Fetch Unit/Branch Predictor/Chooser/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Chooser/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Chooser/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Chooser/Runtime Dynamic': 0.0012197,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Chooser/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/Gate Leakage': 0.000757657,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Area': 0.0435221,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Gate Leakage': 0.000278362,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Peak Dynamic': 0.0168831,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Runtime Dynamic': 0.0012197,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage': 0.00759719,
'Instruction Fetch Unit/Branch Predictor/Global Predictor/Subthreshold Leakage with power gating': 0.0039236,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Area': 0.0257064,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Gate Leakage': 0.000154548,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Peak Dynamic': 0.0142575,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Runtime Dynamic': 0.00106956,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage': 0.00384344,
'Instruction Fetch Unit/Branch Predictor/L1_Local Predictor/Subthreshold Leakage with power gating': 0.00198631,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Area': 0.0151917,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Gate Leakage': 8.00196e-05,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Peak Dynamic': 0.00527447,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Runtime Dynamic': 0.000417989,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage': 0.00181347,
'Instruction Fetch Unit/Branch Predictor/L2_Local Predictor/Subthreshold Leakage with power gating': 0.000957045,
'Instruction Fetch Unit/Branch Predictor/Peak Dynamic': 0.0597838,
'Instruction Fetch Unit/Branch Predictor/RAS/Area': 0.0105732,
'Instruction Fetch Unit/Branch Predictor/RAS/Gate Leakage': 4.63858e-05,
'Instruction Fetch Unit/Branch Predictor/RAS/Peak Dynamic': 0.0117602,
'Instruction Fetch Unit/Branch Predictor/RAS/Runtime Dynamic': 0.00117516,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage': 0.000932505,
'Instruction Fetch Unit/Branch Predictor/RAS/Subthreshold Leakage with power gating': 0.000494733,
'Instruction Fetch Unit/Branch Predictor/Runtime Dynamic': 0.00468412,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage': 0.0199703,
'Instruction Fetch Unit/Branch Predictor/Subthreshold Leakage with power gating': 0.0103282,
'Instruction Fetch Unit/Branch Target Buffer/Area': 0.64954,
'Instruction Fetch Unit/Branch Target Buffer/Gate Leakage': 0.00272758,
'Instruction Fetch Unit/Branch Target Buffer/Peak Dynamic': 0.177867,
'Instruction Fetch Unit/Branch Target Buffer/Runtime Dynamic': 0.0114368,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage': 0.0811682,
'Instruction Fetch Unit/Branch Target Buffer/Subthreshold Leakage with power gating': 0.0435357,
'Instruction Fetch Unit/Gate Leakage': 0.0589979,
'Instruction Fetch Unit/Instruction Buffer/Area': 0.0226323,
'Instruction Fetch Unit/Instruction Buffer/Gate Leakage': 6.83558e-05,
'Instruction Fetch Unit/Instruction Buffer/Peak Dynamic': 0.606827,
'Instruction Fetch Unit/Instruction Buffer/Runtime Dynamic': 0.0786429,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage': 0.00151885,
'Instruction Fetch Unit/Instruction Buffer/Subthreshold Leakage with power gating': 0.000701682,
'Instruction Fetch Unit/Instruction Cache/Area': 3.14635,
'Instruction Fetch Unit/Instruction Cache/Gate Leakage': 0.029931,
'Instruction Fetch Unit/Instruction Cache/Peak Dynamic': 5.00236,
'Instruction Fetch Unit/Instruction Cache/Runtime Dynamic': 0.22998,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage': 0.367022,
'Instruction Fetch Unit/Instruction Cache/Subthreshold Leakage with power gating': 0.180386,
'Instruction Fetch Unit/Instruction Decoder/Area': 1.85799,
'Instruction Fetch Unit/Instruction Decoder/Gate Leakage': 0.0222493,
'Instruction Fetch Unit/Instruction Decoder/Peak Dynamic': 1.37404,
'Instruction Fetch Unit/Instruction Decoder/Runtime Dynamic': 0.267107,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage': 0.442943,
'Instruction Fetch Unit/Instruction Decoder/Subthreshold Leakage with power gating': 0.166104,
'Instruction Fetch Unit/Peak Dynamic': 7.46365,
'Instruction Fetch Unit/Runtime Dynamic': 0.591851,
'Instruction Fetch Unit/Subthreshold Leakage': 0.932286,
'Instruction Fetch Unit/Subthreshold Leakage with power gating': 0.40843,
'L2/Area': 4.53318,
'L2/Gate Leakage': 0.015464,
'L2/Peak Dynamic': 0.0347294,
'L2/Runtime Dynamic': 0.00755925,
'L2/Subthreshold Leakage': 0.834142,
'L2/Subthreshold Leakage with power gating': 0.401066,
'Load Store Unit/Area': 8.80901,
'Load Store Unit/Data Cache/Area': 6.84535,
'Load Store Unit/Data Cache/Gate Leakage': 0.0279261,
'Load Store Unit/Data Cache/Peak Dynamic': 3.72234,
'Load Store Unit/Data Cache/Runtime Dynamic': 1.20114,
'Load Store Unit/Data Cache/Subthreshold Leakage': 0.527675,
'Load Store Unit/Data Cache/Subthreshold Leakage with power gating': 0.25085,
'Load Store Unit/Gate Leakage': 0.0350888,
'Load Store Unit/LoadQ/Area': 0.0836782,
'Load Store Unit/LoadQ/Gate Leakage': 0.00059896,
'Load Store Unit/LoadQ/Peak Dynamic': 0.0804029,
'Load Store Unit/LoadQ/Runtime Dynamic': 0.0804029,
'Load Store Unit/LoadQ/Subthreshold Leakage': 0.00941961,
'Load Store Unit/LoadQ/Subthreshold Leakage with power gating': 0.00536918,
'Load Store Unit/Peak Dynamic': 4.10202,
'Load Store Unit/Runtime Dynamic': 1.67807,
'Load Store Unit/StoreQ/Area': 0.322079,
'Load Store Unit/StoreQ/Gate Leakage': 0.00329971,
'Load Store Unit/StoreQ/Peak Dynamic': 0.19826,
'Load Store Unit/StoreQ/Runtime Dynamic': 0.39652,
'Load Store Unit/StoreQ/Subthreshold Leakage': 0.0345621,
'Load Store Unit/StoreQ/Subthreshold Leakage with power gating': 0.0197004,
'Load Store Unit/Subthreshold Leakage': 0.591321,
'Load Store Unit/Subthreshold Leakage with power gating': 0.283293,
'Memory Management Unit/Area': 0.4339,
'Memory Management Unit/Dtlb/Area': 0.0879726,
'Memory Management Unit/Dtlb/Gate Leakage': 0.00088729,
'Memory Management Unit/Dtlb/Peak Dynamic': 0.0703631,
'Memory Management Unit/Dtlb/Runtime Dynamic': 0.070881,
'Memory Management Unit/Dtlb/Subthreshold Leakage': 0.0155699,
'Memory Management Unit/Dtlb/Subthreshold Leakage with power gating': 0.00887485,
'Memory Management Unit/Gate Leakage': 0.00808595,
'Memory Management Unit/Itlb/Area': 0.301552,
'Memory Management Unit/Itlb/Gate Leakage': 0.00393464,
'Memory Management Unit/Itlb/Peak Dynamic': 0.311029,
'Memory Management Unit/Itlb/Runtime Dynamic': 0.0377125,
'Memory Management Unit/Itlb/Subthreshold Leakage': 0.0413758,
'Memory Management Unit/Itlb/Subthreshold Leakage with power gating': 0.0235842,
'Memory Management Unit/Peak Dynamic': 0.588009,
'Memory Management Unit/Runtime Dynamic': 0.108594,
'Memory Management Unit/Subthreshold Leakage': 0.0766103,
'Memory Management Unit/Subthreshold Leakage with power gating': 0.0398333,
'Peak Dynamic': 20.9386,
'Renaming Unit/Area': 0.303608,
'Renaming Unit/FP Front End RAT/Area': 0.131045,
'Renaming Unit/FP Front End RAT/Gate Leakage': 0.00351123,
'Renaming Unit/FP Front End RAT/Peak Dynamic': 2.51468,
'Renaming Unit/FP Front End RAT/Runtime Dynamic': 0.254381,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage': 0.0308571,
'Renaming Unit/FP Front End RAT/Subthreshold Leakage with power gating': 0.0175885,
'Renaming Unit/Free List/Area': 0.0340654,
'Renaming Unit/Free List/Gate Leakage': 2.5481e-05,
'Renaming Unit/Free List/Peak Dynamic': 0.0306032,
'Renaming Unit/Free List/Runtime Dynamic': 0.014994,
'Renaming Unit/Free List/Subthreshold Leakage': 0.000370144,
'Renaming Unit/Free List/Subthreshold Leakage with power gating': 0.000201064,
'Renaming Unit/Gate Leakage': 0.00708398,
'Renaming Unit/Int Front End RAT/Area': 0.0941223,
'Renaming Unit/Int Front End RAT/Gate Leakage': 0.000283242,
'Renaming Unit/Int Front End RAT/Peak Dynamic': 0.731965,
'Renaming Unit/Int Front End RAT/Runtime Dynamic': 0.12989,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage': 0.00435488,
'Renaming Unit/Int Front End RAT/Subthreshold Leakage with power gating': 0.00248228,
'Renaming Unit/Peak Dynamic': 3.58947,
'Renaming Unit/Runtime Dynamic': 0.399265,
'Renaming Unit/Subthreshold Leakage': 0.0552466,
'Renaming Unit/Subthreshold Leakage with power gating': 0.0276461,
'Runtime Dynamic': 5.12611,
'Subthreshold Leakage': 6.16288,
'Subthreshold Leakage with power gating': 2.55328}],
'DRAM': {'Area': 0,
'Gate Leakage': 0,
'Peak Dynamic': 1.9373880625547348,
'Runtime Dynamic': 1.9373880625547348,
'Subthreshold Leakage': 4.252,
'Subthreshold Leakage with power gating': 4.252},
'L3': [{'Area': 61.9075,
'Gate Leakage': 0.0484137,
'Peak Dynamic': 0.218987,
'Runtime Dynamic': 0.130814,
'Subthreshold Leakage': 6.80085,
'Subthreshold Leakage with power gating': 3.32364}],
'Processor': {'Area': 191.908,
'Gate Leakage': 1.53485,
'Peak Dynamic': 92.3248,
'Peak Power': 125.437,
'Runtime Dynamic': 26.0552,
'Subthreshold Leakage': 31.5774,
'Subthreshold Leakage with power gating': 13.9484,
'Total Cores/Area': 128.669,
'Total Cores/Gate Leakage': 1.4798,
'Total Cores/Peak Dynamic': 92.1058,
'Total Cores/Runtime Dynamic': 25.9243,
'Total Cores/Subthreshold Leakage': 24.7074,
'Total Cores/Subthreshold Leakage with power gating': 10.2429,
'Total L3s/Area': 61.9075,
'Total L3s/Gate Leakage': 0.0484137,
'Total L3s/Peak Dynamic': 0.218987,
'Total L3s/Runtime Dynamic': 0.130814,
'Total L3s/Subthreshold Leakage': 6.80085,
'Total L3s/Subthreshold Leakage with power gating': 3.32364,
'Total Leakage': 33.1122,
'Total NoCs/Area': 1.33155,
'Total NoCs/Gate Leakage': 0.00662954,
'Total NoCs/Peak Dynamic': 0.0,
'Total NoCs/Runtime Dynamic': 0.0,
'Total NoCs/Subthreshold Leakage': 0.0691322,
'Total NoCs/Subthreshold Leakage with power gating': 0.0259246}}
| 75.033917
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| 0.681953
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0
| 7
|
4a07db19fb38a0ae86fefce2f12e8482e213f03d
| 17,783
|
py
|
Python
|
test/test_individual_module_mounting_backend.py
|
nus-mtp/another-cs-study-planner
|
02b52871a34f580b779ede08750f2d4e887bcf65
|
[
"MIT"
] | 1
|
2017-04-30T17:59:08.000Z
|
2017-04-30T17:59:08.000Z
|
test/test_individual_module_mounting_backend.py
|
nus-mtp/another-cs-study-planner
|
02b52871a34f580b779ede08750f2d4e887bcf65
|
[
"MIT"
] | 87
|
2017-02-13T09:06:13.000Z
|
2017-04-14T09:23:08.000Z
|
test/test_individual_module_mounting_backend.py
|
nus-mtp/another-cs-study-planner
|
02b52871a34f580b779ede08750f2d4e887bcf65
|
[
"MIT"
] | 1
|
2017-04-11T05:26:00.000Z
|
2017-04-11T05:26:00.000Z
|
'''
test_individual_module_mounting_backend.py
Contains test cases related to backened functions for displaying an individual module's mounting
'''
from nose.tools import assert_equal, assert_true
from components.handlers.module_overview import ViewMod
from components.handlers.module_view_in_ay_sem import IndividualModule
from components import model
class TestCode(object):
'''
This class runs the test cases related to displaying an individual module's mounting.
'''
def __init__(self):
self.module_overview_handler = None
self.current_ay = None
self.next_ay = None
def get_next_ay(self, ay):
'''
Return the AY that comes after the current AY
'''
ay = ay.split(' ')[1].split('/')
return 'AY ' + str(int(ay[0])+1) + '/' + str(int(ay[1])+1)
def setUp(self):
'''
Add dummy modules and mountings into database
'''
self.module_overview_handler = ViewMod()
self.mounting_view_handler = IndividualModule()
self.current_ay = model.get_current_ay()
self.next_ay = self.get_next_ay(self.current_ay)
# Dummy modules
model.add_module('BB1001', 'Dummy Module 1',
'This module is mounted in both sems in both AYs.', 1, 'Active')
model.add_module('BB1002', 'Dummy Module 2',
'This module is mounted in sem 1 only, in both AYs.', 2, 'Active')
model.add_module('BB1003', 'Dummy Module 3',
'This module is mounted in sem 2 only, in both AYs.', 3, 'Active')
model.add_module('BB1004', 'Dummy Module 4',
'This module is not mounted in any sem, in both AYs.', 4, 'Active')
# Dummy fixed mountings
model.add_fixed_mounting('BB1001', self.current_ay+' Sem 1', 10)
model.add_fixed_mounting('BB1001', self.current_ay+' Sem 2', 20)
model.add_fixed_mounting('BB1002', self.current_ay+' Sem 1', 30)
model.add_fixed_mounting('BB1003', self.current_ay+' Sem 2', 40)
# Dummy tentative mountings
model.add_tenta_mounting('BB1001', self.next_ay+' Sem 1', 10)
model.add_tenta_mounting('BB1001', self.next_ay+' Sem 2', 20)
model.add_tenta_mounting('BB1002', self.next_ay+' Sem 1', 30)
model.add_tenta_mounting('BB1003', self.next_ay+' Sem 2', 40)
def tearDown(self):
'''
Clean up the database after all test cases are ran
'''
model.delete_fixed_mounting('BB1001', self.current_ay+' Sem 1')
model.delete_fixed_mounting('BB1001', self.current_ay+' Sem 2')
model.delete_fixed_mounting('BB1002', self.current_ay+' Sem 1')
model.delete_fixed_mounting('BB1003', self.current_ay+' Sem 2')
model.delete_tenta_mounting('BB1001', self.next_ay+' Sem 1')
model.delete_tenta_mounting('BB1001', self.next_ay+' Sem 2')
model.delete_tenta_mounting('BB1002', self.next_ay+' Sem 1')
model.delete_tenta_mounting('BB1003', self.next_ay+' Sem 2')
model.delete_module('BB1001')
model.delete_module('BB1002')
model.delete_module('BB1003')
model.delete_module('BB1004')
def test_mounted_in_both_sems(self):
'''
Tests that a module that is mounted in both sems in both AYs
will have the mounting values '1' and '1' for both AYs
'''
test_module_code = "BB1001"
self.module_overview_handler.load_fixed_mounting_plan(test_module_code)
self.module_overview_handler.load_tenta_mounting_plan(test_module_code)
fixed_mounting_plan = self.module_overview_handler.fixed_mounting_plan
tenta_mounting_plan = self.module_overview_handler.tenta_mounting_plan
assert_true(len(fixed_mounting_plan) == 2)
assert_true(len(tenta_mounting_plan) > 0)
fixed_sem_1_mounting_value = fixed_mounting_plan[0][1]
fixed_sem_2_mounting_value = fixed_mounting_plan[1][1]
fixed_sem_1_quota = fixed_mounting_plan[0][2]
fixed_sem_2_quota = fixed_mounting_plan[1][2]
assert_equal(fixed_sem_1_mounting_value, 1)
assert_equal(fixed_sem_2_mounting_value, 1)
assert_equal(fixed_sem_1_quota, 10)
assert_equal(fixed_sem_2_quota, 20)
tenta_sem_1_mounting_value = tenta_mounting_plan[0][1]
tenta_sem_2_mounting_value = tenta_mounting_plan[1][1]
tenta_sem_1_quota = tenta_mounting_plan[0][2]
tenta_sem_2_quota = tenta_mounting_plan[1][2]
assert_equal(tenta_sem_1_mounting_value, 1)
assert_equal(tenta_sem_2_mounting_value, 1)
assert_equal(tenta_sem_1_quota, 10)
assert_equal(tenta_sem_2_quota, 20)
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 10)
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 20)
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 10)
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 20)
def test_mounted_in_sem_1_only(self):
'''
Tests that a module that is mounted in sem 1 only, in both AYs,
will have the mounting values '1' and '-1' for both AYs
'''
test_module_code = "BB1002"
self.module_overview_handler.load_fixed_mounting_plan(test_module_code)
self.module_overview_handler.load_tenta_mounting_plan(test_module_code)
fixed_mounting_plan = self.module_overview_handler.fixed_mounting_plan
tenta_mounting_plan = self.module_overview_handler.tenta_mounting_plan
assert_true(len(fixed_mounting_plan) == 2)
assert_true(len(tenta_mounting_plan) > 0)
fixed_sem_1_mounting_value = fixed_mounting_plan[0][1]
fixed_sem_2_mounting_value = fixed_mounting_plan[1][1]
fixed_sem_1_quota = fixed_mounting_plan[0][2]
fixed_sem_2_quota = fixed_mounting_plan[1][2]
assert_equal(fixed_sem_1_mounting_value, 1)
assert_equal(fixed_sem_2_mounting_value, -1)
assert_equal(fixed_sem_1_quota, 30)
assert_equal(fixed_sem_2_quota, '-')
tenta_sem_1_mounting_value = tenta_mounting_plan[0][1]
tenta_sem_2_mounting_value = tenta_mounting_plan[1][1]
tenta_sem_1_quota = tenta_mounting_plan[0][2]
tenta_sem_2_quota = tenta_mounting_plan[1][2]
assert_equal(tenta_sem_1_mounting_value, 1)
assert_equal(tenta_sem_2_mounting_value, -1)
assert_equal(tenta_sem_1_quota, 30)
assert_equal(tenta_sem_2_quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 30)
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 30)
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
def test_mounted_in_sem_2_only(self):
'''
Tests that a module that is mounted in sem 2 only, in both AYs,
will have the mounting values '-1' and '1' for both AYs
'''
test_module_code = "BB1003"
self.module_overview_handler.load_fixed_mounting_plan(test_module_code)
self.module_overview_handler.load_tenta_mounting_plan(test_module_code)
fixed_mounting_plan = self.module_overview_handler.fixed_mounting_plan
tenta_mounting_plan = self.module_overview_handler.tenta_mounting_plan
assert_true(len(fixed_mounting_plan) == 2)
assert_true(len(tenta_mounting_plan) > 0)
fixed_sem_1_mounting_value = fixed_mounting_plan[0][1]
fixed_sem_2_mounting_value = fixed_mounting_plan[1][1]
fixed_sem_1_quota = fixed_mounting_plan[0][2]
fixed_sem_2_quota = fixed_mounting_plan[1][2]
assert_equal(fixed_sem_1_mounting_value, -1)
assert_equal(fixed_sem_2_mounting_value, 1)
assert_equal(fixed_sem_1_quota, '-')
assert_equal(fixed_sem_2_quota, 40)
tenta_sem_1_mounting_value = tenta_mounting_plan[0][1]
tenta_sem_2_mounting_value = tenta_mounting_plan[1][1]
tenta_sem_1_quota = tenta_mounting_plan[0][2]
tenta_sem_2_quota = tenta_mounting_plan[1][2]
assert_equal(tenta_sem_1_mounting_value, -1)
assert_equal(tenta_sem_2_mounting_value, 1)
assert_equal(tenta_sem_1_quota, '-')
assert_equal(tenta_sem_2_quota, 40)
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 40)
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 40)
def test_not_mounted(self):
'''
Tests that a module that is not mounted in any sem, in both AYs,
will have the mounting values '-1' and '-1' for both AYs
'''
test_module_code = "BB1004"
self.module_overview_handler.load_fixed_mounting_plan(test_module_code)
self.module_overview_handler.load_tenta_mounting_plan(test_module_code)
fixed_mounting_plan = self.module_overview_handler.fixed_mounting_plan
tenta_mounting_plan = self.module_overview_handler.tenta_mounting_plan
assert_true(len(fixed_mounting_plan) == 2)
assert_true(len(tenta_mounting_plan) > 0)
fixed_sem_1_mounting_value = fixed_mounting_plan[0][1]
fixed_sem_2_mounting_value = fixed_mounting_plan[1][1]
fixed_sem_1_quota = fixed_mounting_plan[0][2]
fixed_sem_2_quota = fixed_mounting_plan[1][2]
assert_equal(fixed_sem_1_mounting_value, -1)
assert_equal(fixed_sem_2_mounting_value, -1)
assert_equal(fixed_sem_1_quota, '-')
assert_equal(fixed_sem_2_quota, '-')
tenta_sem_1_mounting_value = tenta_mounting_plan[0][1]
tenta_sem_2_mounting_value = tenta_mounting_plan[1][1]
tenta_sem_1_quota = tenta_mounting_plan[0][2]
tenta_sem_2_quota = tenta_mounting_plan[1][2]
assert_equal(tenta_sem_1_mounting_value, -1)
assert_equal(tenta_sem_2_mounting_value, -1)
assert_equal(tenta_sem_1_quota, '-')
assert_equal(tenta_sem_2_quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, -1)
assert_equal(self.mounting_view_handler.quota, '-')
def test_unmounted_from_sem_1(self):
'''
Tests that a module that is unmounted from sem 1
will have the tentative-mounting value of '0' for sem 1
'''
test_module_code = "BB1002"
model.delete_tenta_mounting(test_module_code, self.next_ay+' Sem 1')
self.module_overview_handler.load_fixed_mounting_plan(test_module_code)
self.module_overview_handler.load_tenta_mounting_plan(test_module_code)
tenta_mounting_plan = self.module_overview_handler.tenta_mounting_plan
assert_true(len(tenta_mounting_plan) > 0)
tenta_sem_1_mounting_value = tenta_mounting_plan[0][1]
tenta_sem_1_quota = tenta_mounting_plan[0][2]
assert_equal(tenta_sem_1_mounting_value, 0)
assert_equal(tenta_sem_1_quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 30)
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 0)
assert_equal(self.mounting_view_handler.quota, '-')
model.add_tenta_mounting(test_module_code, self.next_ay+' Sem 1', 30)
def test_unmounted_from_sem_2(self):
'''
Tests that a module that is unmounted from sem 2
will have the tentative-mounting value of '0' for sem 2
'''
test_module_code = "BB1003"
model.delete_tenta_mounting(test_module_code, self.next_ay+' Sem 2')
self.module_overview_handler.load_fixed_mounting_plan(test_module_code)
self.module_overview_handler.load_tenta_mounting_plan(test_module_code)
tenta_mounting_plan = self.module_overview_handler.tenta_mounting_plan
assert_true(len(tenta_mounting_plan) > 0)
tenta_sem_2_mounting_value = tenta_mounting_plan[1][1]
tenta_sem_2_quota = tenta_mounting_plan[1][2]
assert_equal(tenta_sem_2_mounting_value, 0)
assert_equal(tenta_sem_2_quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 40)
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 0)
assert_equal(self.mounting_view_handler.quota, '-')
model.add_tenta_mounting(test_module_code, self.next_ay+' Sem 2', 40)
def test_unmounted_from_both_sems(self):
'''
Tests that a module that is unmounted from both sems
will have the tentative-mounting values '0' and '0'
'''
test_module_code = "BB1001"
model.delete_tenta_mounting(test_module_code, self.next_ay+' Sem 1')
model.delete_tenta_mounting(test_module_code, self.next_ay+' Sem 2')
self.module_overview_handler.load_fixed_mounting_plan(test_module_code)
self.module_overview_handler.load_tenta_mounting_plan(test_module_code)
tenta_mounting_plan = self.module_overview_handler.tenta_mounting_plan
assert_true(len(tenta_mounting_plan) > 0)
tenta_sem_1_mounting_value = tenta_mounting_plan[0][1]
tenta_sem_1_quota = tenta_mounting_plan[0][2]
tenta_sem_2_mounting_value = tenta_mounting_plan[1][1]
tenta_sem_2_quota = tenta_mounting_plan[1][2]
assert_equal(tenta_sem_1_mounting_value, 0)
assert_equal(tenta_sem_1_quota, '-')
assert_equal(tenta_sem_2_mounting_value, 0)
assert_equal(tenta_sem_2_quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 10)
self.mounting_view_handler.load_mounting_info(test_module_code, self.current_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 1)
assert_equal(self.mounting_view_handler.quota, 20)
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 1')
assert_equal(self.mounting_view_handler.mounting_status, 0)
assert_equal(self.mounting_view_handler.quota, '-')
self.mounting_view_handler.load_mounting_info(test_module_code, self.next_ay+' Sem 2')
assert_equal(self.mounting_view_handler.mounting_status, 0)
assert_equal(self.mounting_view_handler.quota, '-')
model.add_tenta_mounting(test_module_code, self.next_ay+' Sem 1', 10)
model.add_tenta_mounting(test_module_code, self.next_ay+' Sem 2', 20)
| 48.32337
| 100
| 0.714503
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| 17,783
| 4.573512
| 0.042964
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| 0.144704
| 0.897699
| 0.888219
| 0.871585
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| 0.792726
| 0
| 0.034169
| 0.196873
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| 367
| 101
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| 0
| 0.048429
| 0
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| 0.390625
| 1
| 0.042969
| false
| 0
| 0.015625
| 0
| 0.066406
| 0
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| 0
| null | 0
| 0
| 0
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| 1
| 1
| 1
| 1
| 1
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| null | 0
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| 0
| 0
| 0
|
0
| 7
|
c57a08a0e0c907988dd976b4fefeb9ca247e949e
| 7,738
|
py
|
Python
|
OSESMO/OSESMO Python/Import_Utility_Marginal_Cost_Data.py
|
nickolasclarke/dataJungle
|
1b388ecd7d56c770ea7d56c1c6757d39132f2c68
|
[
"MIT"
] | 1
|
2019-11-19T22:32:36.000Z
|
2019-11-19T22:32:36.000Z
|
OSESMO/OSESMO Python/Import_Utility_Marginal_Cost_Data.py
|
nickolasclarke/dataJungle
|
1b388ecd7d56c770ea7d56c1c6757d39132f2c68
|
[
"MIT"
] | 9
|
2019-12-04T06:19:21.000Z
|
2019-12-16T05:05:51.000Z
|
OSESMO/OSESMO Python/Import_Utility_Marginal_Cost_Data.py
|
nickolasclarke/dataJungle
|
1b388ecd7d56c770ea7d56c1c6757d39132f2c68
|
[
"MIT"
] | 2
|
2019-11-19T22:32:29.000Z
|
2019-11-19T22:32:46.000Z
|
def Import_Utility_Marginal_Cost_Data(Input_Output_Data_Directory_Location=None, OSESMO_Git_Repo_Directory=None, delta_t=None, Load_Profile_Name_Input=None):
# Load Python Packages
import os
import numpy as np
# Set Directory to Box Sync Folder
os.chdir(Input_Output_Data_Directory_Location)
if Load_Profile_Name_Input == "WattTime GreenButton Residential Berkeley":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "WattTime GreenButton Residential Long Beach":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "WattTime GreenButton Residential Coulterville":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "WattTime GreenButton Residential San Francisco":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "WattTime GreenButton Residential Oakland":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "PG&E GreenButton E-6 Residential":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "Custom Power Solar GreenButton PG&E Albany Residential with EV":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "Custom Power Solar GreenButton PG&E Crockett Residential with EV":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "PG&E GreenButton Central Valley Residential Non-CARE":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "PG&E GreenButton Central Valley Residential CARE":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "Avalon GreenButton East Bay Light Industrial":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "Stem GreenButton SCE GS-2B Hospitality":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "Stem GreenButton SCE TOU-8B Office":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "Stem GreenButton PG&E E-19 Office":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "Stem GreenButton SCE GS-3B Food Processing":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "Stem GreenButton SDG&E G-16 Manufacturing":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "Stem GreenButton SDG&E AL-TOU Education":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "Stem GreenButton PG&E E-19 Industrial":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "EnerNOC GreenButton Los Angeles Grocery":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "EnerNOC GreenButton Los Angeles Industrial":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "EnerNOC GreenButton San Diego Office":
Generation_Cost_Region = "SP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "EnerNOC GreenButton San Francisco Industrial":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "EnerNOC GreenButton San Francisco Office":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "PG&E GreenButton A-1 SMB":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "PG&E GreenButton A-6 SMB":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
elif Load_Profile_Name_Input == "PG&E GreenButton A-10S MLB":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Sonoma"
elif Load_Profile_Name_Input == "Avalon GreenButton South Bay Education":
Generation_Cost_Region = "NP15"
Representative_Distribution_Cost_Profile = "Mission"
# Import Generation Cost Data
if Generation_Cost_Region == "NP15":
if delta_t == (5 / 60):
Generation_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/5-Minute Data/Vector Format/NP15_5min_Generation_Cost_Vector.csv', delimiter=',')
elif delta_t == (15 / 60):
Generation_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/15-Minute Data/Vector Format/NP15_15min_Generation_Cost_Vector.csv', delimiter=',')
elif Generation_Cost_Region == "SP15":
if delta_t == (5 / 60):
Generation_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/5-Minute Data/Vector Format/SP15_5min_Generation_Cost_Vector.csv', delimiter=',')
elif delta_t == (15 / 60):
Generation_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/15-Minute Data/Vector Format/SP15_15min_Generation_Cost_Vector.csv', delimiter=',')
# Import Representative Distribution Cost Data
if Representative_Distribution_Cost_Profile == "Mission":
if delta_t == (5 / 60):
Representative_Distribution_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/5-Minute Data/Vector Format/Mission_5min_Distribution_Cost_Vector.csv', delimiter=',')
elif delta_t == (15 / 60):
Representative_Distribution_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/15-Minute Data/Vector Format/Mission_15min_Distribution_Cost_Vector.csv', delimiter=',')
elif Representative_Distribution_Cost_Profile == "Sonoma":
if delta_t == (5 / 60):
Representative_Distribution_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/5-Minute Data/Vector Format/Sonoma_5min_Distribution_Cost_Vector.csv', delimiter=',')
elif delta_t == (15 / 60):
Representative_Distribution_Cost_Data = np.genfromtxt(
'Utility Marginal Cost Data/Clean Utility Marginal Cost Data/15-Minute Data/Vector Format/Sonoma_15min_Distribution_Cost_Vector.csv', delimiter=',')
# Return to OSESMO Git Repository Directory
os.chdir(OSESMO_Git_Repo_Directory)
return Generation_Cost_Data, Representative_Distribution_Cost_Data
| 44.728324
| 165
| 0.730292
| 892
| 7,738
| 5.984305
| 0.126682
| 0.102286
| 0.196703
| 0.201012
| 0.885163
| 0.849007
| 0.819033
| 0.809667
| 0.803484
| 0.770888
| 0
| 0.021297
| 0.199018
| 7,738
| 173
| 166
| 44.728324
| 0.839948
| 0.021711
| 0
| 0.608696
| 0
| 0.069565
| 0.320687
| 0.048381
| 0
| 0
| 0
| 0
| 0
| 1
| 0.008696
| false
| 0
| 0.026087
| 0
| 0.043478
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
c597709d52b061847805ebadec00e1815b67ecd7
| 6,140
|
py
|
Python
|
dyp-app/dbController.py
|
wanero13/proj_dyp
|
3a02d3a7ad9377440399d3ee22447c567f413609
|
[
"MIT"
] | null | null | null |
dyp-app/dbController.py
|
wanero13/proj_dyp
|
3a02d3a7ad9377440399d3ee22447c567f413609
|
[
"MIT"
] | null | null | null |
dyp-app/dbController.py
|
wanero13/proj_dyp
|
3a02d3a7ad9377440399d3ee22447c567f413609
|
[
"MIT"
] | null | null | null |
import sqlite3
def insertUser(user_login, user_password, user_email):
try:
print("Trying to insert User")
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sqlite_insert_with_param = """INSERT INTO users
(user_login, user_password, user_email)
VALUES (?, ?, ?);"""
data_tuple = (user_login, user_password, user_email)
cursor.execute(sqlite_insert_with_param, data_tuple)
sqliteConnection.commit()
print("Python Variables inserted successfully into SqliteDb_developers table")
cursor.close()
except sqlite3.Error as error:
print("Failed to insert Python variable into sqlite table", error)
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The SQLite connection is closed")
def insertNote(user_id, note_private, note_title, note_text):
try:
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sqlite_insert_with_param = """INSERT INTO notes
(note_id, user_id, note_private, note_title, note_text)
VALUES (NULL, ?, ?, ?, ?);"""
data_tuple = (user_id, note_private, note_title, note_text)
cursor.execute(sqlite_insert_with_param, data_tuple)
sqliteConnection.commit()
print("Python Variables inserted successfully into SqliteDb_developers table")
cursor.close()
except sqlite3.Error as error:
print("Failed to insert Python variable into sqlite table", error)
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The SQLite connection is closed")
def getUserByLogin(user_login):
try:
print("Trying to get user")
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sqlite_select_query = """SELECT * from users where user_login = ?"""
cursor.execute(sqlite_select_query, (user_login,))
record = cursor.fetchone()
cursor.close()
return record
except sqlite3.Error as error:
print("Failed to read single row from sqlite table", error)
return None
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The SQLite connection is closed")
def getUserById(user_id):
try:
print("Trying to get user")
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sqlite_select_query = """SELECT * from users where user_id = ?"""
cursor.execute(sqlite_select_query, (user_id,))
record = cursor.fetchone()
cursor.close()
return record
except sqlite3.Error as error:
print("Failed to read single row from sqlite table", error)
return None
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The SQLite connection is closed")
def getAllPublicNotes():
try:
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sql_select_query = """select note_id, note_title from notes where note_private = ?"""
cursor.execute(sql_select_query, (0,))
records = cursor.fetchall()
cursor.close()
return records
except sqlite3.Error as error:
print("Failed to read data from sqlite table", error)
return None
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The SQLite connection is closed")
def getUserNotes(user_id):
try:
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sql_select_query = """select note_id, note_title, note_private from notes where user_id = ?"""
cursor.execute(sql_select_query, (user_id,))
records = cursor.fetchall()
cursor.close()
return records
except sqlite3.Error as error:
print("Failed to read data from sqlite table", error)
return None
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The SQLite connection is closed")
def getNote(note_id):
try:
print("Trying to get user")
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sqlite_select_query = """SELECT * from notes where note_id = ?"""
cursor.execute(sqlite_select_query, (note_id,))
record = cursor.fetchone()
cursor.close()
return record
except sqlite3.Error as error:
print("Failed to read single row from sqlite table", error)
return None
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The SQLite connection is closed")
def updatePassword(user_id, user_password):
try:
sqliteConnection = sqlite3.connect('SQLite_Python.db')
cursor = sqliteConnection.cursor()
print("Connected to SQLite")
sql_update_query = """Update users set user_password = ? where user_id = ?"""
data = (user_password, user_id)
cursor.execute(sql_update_query, data)
sqliteConnection.commit()
print("Record Updated successfully")
cursor.close()
except sqlite3.Error as error:
print("Failed to update sqlite table", error)
finally:
if (sqliteConnection):
sqliteConnection.close()
print("The sqlite connection is closed")
| 34.494382
| 103
| 0.614495
| 636
| 6,140
| 5.781447
| 0.125786
| 0.019581
| 0.065271
| 0.078325
| 0.880065
| 0.856405
| 0.804188
| 0.804188
| 0.776448
| 0.776448
| 0
| 0.004164
| 0.295928
| 6,140
| 177
| 104
| 34.689266
| 0.846403
| 0
| 0
| 0.765517
| 0
| 0
| 0.281255
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.055172
| false
| 0.041379
| 0.006897
| 0
| 0.131034
| 0.213793
| 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
|
c5b17209fc55b1acc3999fcd030a129689e9c4ae
| 139
|
py
|
Python
|
arcade/joysticks.py
|
philipbergen/arcade
|
d4741f6fcb82ca72de021bd71df17a8219da8549
|
[
"MIT"
] | 1
|
2018-11-01T14:40:35.000Z
|
2018-11-01T14:40:35.000Z
|
arcade/joysticks.py
|
philipbergen/arcade
|
d4741f6fcb82ca72de021bd71df17a8219da8549
|
[
"MIT"
] | null | null | null |
arcade/joysticks.py
|
philipbergen/arcade
|
d4741f6fcb82ca72de021bd71df17a8219da8549
|
[
"MIT"
] | null | null | null |
import pyglet.input
def get_joysticks():
return pyglet.input.get_joysticks()
def get_game_controllers():
return get_joysticks()
| 15.444444
| 39
| 0.755396
| 18
| 139
| 5.555556
| 0.5
| 0.36
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.151079
| 139
| 8
| 40
| 17.375
| 0.847458
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| true
| 0
| 0.2
| 0.4
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 7
|
c5b1caed48a7de3300b67ba4f834bece16c840b1
| 7,298
|
py
|
Python
|
Linear Models/tests/04_unittest_foldcounters_input/test.py
|
AxoyTO/ML-DL-DS-Python-Studies
|
ffef653190d1106e01244a4ea7f3f953b9d97882
|
[
"Unlicense"
] | null | null | null |
Linear Models/tests/04_unittest_foldcounters_input/test.py
|
AxoyTO/ML-DL-DS-Python-Studies
|
ffef653190d1106e01244a4ea7f3f953b9d97882
|
[
"Unlicense"
] | null | null | null |
Linear Models/tests/04_unittest_foldcounters_input/test.py
|
AxoyTO/ML-DL-DS-Python-Studies
|
ffef653190d1106e01244a4ea7f3f953b9d97882
|
[
"Unlicense"
] | 1
|
2021-12-08T13:00:41.000Z
|
2021-12-08T13:00:41.000Z
|
import numpy as np
import pandas as pd
from Task import MyOneHotEncoder, SimpleCounterEncoder, FoldCounters, weights
def test_imports():
with open('Task.py', 'r') as file:
lines = ' '.join(file.readlines())
assert 'import numpy' in lines
assert lines.count('import') == 1
assert 'sklearn' not in lines
assert 'get_dummies' not in lines
def test_kfold_counters_small():
data = {'col_1': [0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1],
'col_2': ['a', 'b', 'c', 'a', 'b', 'c', 'a', 'b', 'c', 'a', 'b', 'c'],
'col_3': [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4]}
df_test = pd.DataFrame.from_dict(data)
enc = FoldCounters(n_folds=2)
enc.fit(df_test[['col_1', 'col_2']], df_test['col_3'], seed=6)
counts = enc.transform(df_test[['col_1', 'col_2']], a=0, b=0)
ans = np.array([[7 / 3, 0.5, 14 / 3, 3, 1 / 3, 9],
[8 / 3, 0.5, 16 / 3, 2, 1 / 3, 6],
[5 / 3, 0.5, 10 / 3, 2.5, 1 / 3, 7.5],
[10 / 3, 0.5, 20 / 3, 2, 1 / 3, 6],
[5 / 3, 0.5, 10 / 3, 3, 1 / 3, 9],
[10 / 3, 0.5, 20 / 3, 2.5, 1 / 3, 7.5],
[7 / 3, 0.5, 14 / 3, 3, 1 / 3, 9],
[8 / 3, 0.5, 16 / 3, 2, 1 / 3, 6],
[7 / 3, 0.5, 14 / 3, 2.5, 1 / 3, 7.5],
[10 / 3, 0.5, 20 / 3, 2, 1 / 3, 6],
[5 / 3, 0.5, 10 / 3, 3, 1 / 3, 9],
[8 / 3, 0.5, 16 / 3, 2.5, 1 / 3, 7.5]])
assert len(counts.shape) == 2
assert counts.shape[0] == 12
assert counts.shape[1] == 6
assert np.allclose(counts, ans, atol=1e-8)
assert type(counts) == np.ndarray
def test_fold_counters_big():
data = {'col_1': [1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 2, 1, 2, 0, 2, 1, 2, 0, 0, 2, 0, 1, 2, 2, 0, 1, 1, 2, 0],
'col_2': [1, 1, 1, 1, 0, 4, 1, 0, 0, 3, 2, 1, 0, 3, 1, 1, 3, 4, 0, 1, 3, 4, 2, 4, 0, 3, 1, 2, 0, 4],
'col_3': [1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1],
"target": [1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0]}
df_test = pd.DataFrame.from_dict(data)
enc = FoldCounters(n_folds=3)
enc.fit(df_test[['col_1', 'col_2', 'col_3']], df_test['target'], seed=1)
counts = enc.transform(df_test[['col_1', 'col_2', 'col_3']], a=1, b=2)
ans = np.array([[0.3333333333333333, 0.3, 0.5797101449275363, 0.2857142857142857, 0.35, 0.547112462006079,
0.5384615384615384, 0.65, 0.5805515239477503],
[0.2857142857142857, 0.35, 0.547112462006079, 0.42857142857142855, 0.35, 0.60790273556231,
0.6666666666666666, 0.6, 0.641025641025641],
[0.2857142857142857, 0.35, 0.547112462006079, 0.42857142857142855, 0.35, 0.60790273556231, 0.5, 0.4,
0.625],
[0.7142857142857143, 0.35, 0.729483282674772, 0.5, 0.3, 0.6521739130434783, 0.6923076923076923,
0.65, 0.6386066763425254],
[0.7142857142857143, 0.35, 0.729483282674772, 1.0, 0.2, 0.9090909090909091, 0.6666666666666666, 0.6,
0.641025641025641],
[0.3333333333333333, 0.45, 0.5442176870748299, 0.3333333333333333, 0.15, 0.6201550387596899,
0.2857142857142857, 0.35, 0.547112462006079],
[0.2857142857142857, 0.35, 0.547112462006079, 0.42857142857142855, 0.35, 0.60790273556231,
0.6666666666666666, 0.6, 0.641025641025641],
[0.7142857142857143, 0.35, 0.729483282674772, 1.0, 0.2, 0.9090909090909091, 0.5, 0.4, 0.625],
[0.3333333333333333, 0.45, 0.5442176870748299, 0.25, 0.2, 0.5681818181818181, 0.2857142857142857,
0.35, 0.547112462006079],
[0.3333333333333333, 0.3, 0.5797101449275363, 1.0, 0.15, 0.9302325581395349, 0.5384615384615384,
0.65, 0.5805515239477503],
[0.375, 0.4, 0.5729166666666667, 1.0, 0.05, 0.9756097560975611, 0.6923076923076923, 0.65,
0.6386066763425254],
[0.8, 0.25, 0.8, 0.2857142857142857, 0.35, 0.547112462006079, 0.5384615384615384, 0.65,
0.5805515239477503],
[0.3333333333333333, 0.3, 0.5797101449275363, 0.25, 0.2, 0.5681818181818181, 0.2857142857142857,
0.35, 0.547112462006079],
[0.8333333333333334, 0.3, 0.7971014492753624, 1.0, 0.15, 0.9302325581395349, 0.6666666666666666,
0.6, 0.641025641025641],
[0.375, 0.4, 0.5729166666666667, 0.5, 0.3, 0.6521739130434783, 0.6923076923076923, 0.65,
0.6386066763425254],
[0.8, 0.25, 0.8, 0.2857142857142857, 0.35, 0.547112462006079, 0.2857142857142857, 0.35,
0.547112462006079],
[0.3333333333333333, 0.3, 0.5797101449275363, 1.0, 0.15, 0.9302325581395349, 0.5384615384615384,
0.65, 0.5805515239477503],
[0.6, 0.25, 0.7111111111111111, 0.0, 0.15, 0.46511627906976744, 0.6923076923076923, 0.65,
0.6386066763425254],
[0.2857142857142857, 0.35, 0.547112462006079, 1.0, 0.2, 0.9090909090909091, 0.6666666666666666, 0.6,
0.641025641025641],
[0.375, 0.4, 0.5729166666666667, 0.5, 0.3, 0.6521739130434783, 0.6923076923076923, 0.65,
0.6386066763425254],
[0.6, 0.25, 0.7111111111111111, 1.0, 0.2, 0.9090909090909091, 0.2857142857142857, 0.35,
0.547112462006079],
[0.375, 0.4, 0.5729166666666667, 0.0, 0.15, 0.46511627906976744, 0.2857142857142857, 0.35,
0.547112462006079],
[0.7142857142857143, 0.35, 0.729483282674772, 1.0, 0.05, 0.9756097560975611, 0.2857142857142857,
0.35, 0.547112462006079],
[0.8333333333333334, 0.3, 0.7971014492753624, 0.25, 0.2, 0.5681818181818181, 0.5, 0.4, 0.625],
[0.6, 0.25, 0.7111111111111111, 0.5, 0.3, 0.6521739130434783, 0.2857142857142857, 0.35,
0.547112462006079],
[0.2857142857142857, 0.35, 0.547112462006079, 1.0, 0.15, 0.9302325581395349, 0.6666666666666666,
0.6, 0.641025641025641],
[0.7142857142857143, 0.35, 0.729483282674772, 0.5, 0.3, 0.6521739130434783, 0.6923076923076923,
0.65, 0.6386066763425254],
[0.7142857142857143, 0.35, 0.729483282674772, 0.5, 0.1, 0.7142857142857143, 0.6666666666666666, 0.6,
0.641025641025641],
[0.8, 0.25, 0.8, 0.25, 0.2, 0.5681818181818181, 0.5384615384615384, 0.65, 0.5805515239477503],
[0.3333333333333333, 0.45, 0.5442176870748299, 0.3333333333333333, 0.15, 0.6201550387596899,
0.5384615384615384, 0.65, 0.5805515239477503]])
assert len(counts.shape) == 2
assert counts.shape[0] == 30
assert counts.shape[1] == 9
assert np.allclose(counts, ans, atol=1e-8)
assert type(counts) == np.ndarray
| 64.017544
| 120
| 0.527542
| 1,042
| 7,298
| 3.659309
| 0.105566
| 0.018358
| 0.026226
| 0.083923
| 0.870705
| 0.865985
| 0.843168
| 0.701285
| 0.683714
| 0.608707
| 0
| 0.596736
| 0.311592
| 7,298
| 113
| 121
| 64.584071
| 0.162221
| 0
| 0
| 0.433962
| 0
| 0
| 0.021102
| 0
| 0
| 0
| 0
| 0
| 0.132075
| 1
| 0.028302
| false
| 0
| 0.056604
| 0
| 0.084906
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
c5b456d2c8d1f38e1ede7e641605d3d83183aedb
| 2,810
|
py
|
Python
|
library/Ottoman.py
|
kausalyamahadevan/knitout-frontend-py
|
1a0414a88db698383dda7e9b45ec1293948b369b
|
[
"MIT"
] | null | null | null |
library/Ottoman.py
|
kausalyamahadevan/knitout-frontend-py
|
1a0414a88db698383dda7e9b45ec1293948b369b
|
[
"MIT"
] | null | null | null |
library/Ottoman.py
|
kausalyamahadevan/knitout-frontend-py
|
1a0414a88db698383dda7e9b45ec1293948b369b
|
[
"MIT"
] | null | null | null |
import numpy as np
def ottomanStitch(k,beg,fin,length,c,passes1,passesBoth=1,side='l',bed1='f'):
k.rack(0.25)
if bed1=='f':
bed0='b'
else:
bed0='f'
#account for starting position and add first row of knitting
if side == 'r':
start = 1
length = length+1
else:
start = 0
totalpasses=passes1+passesBoth
counter=passes1
for h in range(length):
if counter<passes1:
if h%2 ==0:
for s in range(beg,fin):
k.knit('+',(bed1,s),c)
else:
for s in range(fin-1,beg-1,-1):
k.knit('-',(bed1,s),c)
counter=counter+1
else:
if h%2 == 0:
for s in range(beg,fin):
k.knit('+',(bed1,s),c)
k.knit('+',(bed0,s),c)
else:
for s in range(fin-1,beg-1,-1):
k.knit('-',(bed0,s),c)
k.knit('-',(bed1,s),c)
counter=counter+1
if counter==totalpasses:
counter=0
def striperPattern(k,beg,fin,length,carriers,matrix,side='l',bed1='f'):
k.rack(0.25)
if bed1=='f':
bed0='b'
else:
bed0='f'
#account for starting position and add first row of knitting
if side == 'r':
start = 1
length = length+1
else:
start = 0
matrixL=np.shape(matrix)[0]
matrixW=np.shape(matrix)[1]
numCarriers=len(carriers)
# print(numCarriers)
for h in range(length):
for b in range(numCarriers):
if h%2 ==0:
for s in range(beg,fin):
if matrix[h%matrixL,s%matrixW]==b:
k.knit('+',(bed1,s),carriers[b])
k.knit('+',(bed0,s),carriers[b])
else:
for s in range(fin-1,beg-1,-1):
k.knit('-',(bed0,s),carriers[b])
if matrix[h%matrixL,s%matrixW]==b:
k.knit('-',(bed1,s),carriers[b])
def realStriperPattern(k,beg,fin,length,carriers,matrix,bed1='f'):
k.rack(0.25)
if bed1=='f':
bed0='b'
else:
bed0='f'
matrixL=np.shape(matrix)[0]
matrixW=np.shape(matrix)[1]
numCarriers=len(carriers)
for h in range(int(length/2)):
for b in range(numCarriers):
for s in range(beg,fin):
if matrix[h%matrixL,s%matrixW]==b:
k.knit('+',(bed1,s),carriers[b])
k.knit('+',(bed0,s),carriers[b])
for s in range(fin-1,beg-1,-1):
k.knit('-',(bed0,s),carriers[b])
if matrix[h%matrixL,s%matrixW]==b:
k.knit('-',(bed1,s),carriers[b])
| 26.018519
| 77
| 0.460854
| 374
| 2,810
| 3.462567
| 0.149733
| 0.054054
| 0.037066
| 0.067954
| 0.823938
| 0.755985
| 0.714286
| 0.714286
| 0.677992
| 0.677992
| 0
| 0.041356
| 0.380427
| 2,810
| 107
| 78
| 26.261682
| 0.70247
| 0.048754
| 0
| 0.85
| 0
| 0
| 0.011236
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.0375
| false
| 0.0625
| 0.0125
| 0
| 0.05
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 7
|
a8aea2a3cbbce7570a52540051a5d82a4e5571e0
| 187
|
py
|
Python
|
Recommendations/CF/Movies/movies-cf-app-python/data_ingest/views.py
|
javakishore-veleti/Data-Tech-Stack-Solutions
|
e60120d19a7b5be53da688b9c6ba7daa2a7e1b3d
|
[
"MIT"
] | null | null | null |
Recommendations/CF/Movies/movies-cf-app-python/data_ingest/views.py
|
javakishore-veleti/Data-Tech-Stack-Solutions
|
e60120d19a7b5be53da688b9c6ba7daa2a7e1b3d
|
[
"MIT"
] | null | null | null |
Recommendations/CF/Movies/movies-cf-app-python/data_ingest/views.py
|
javakishore-veleti/Data-Tech-Stack-Solutions
|
e60120d19a7b5be53da688b9c6ba7daa2a7e1b3d
|
[
"MIT"
] | null | null | null |
from flask import render_template
def data_ingest_list():
return "Hello World"
def download_movies_data():
return render_template('data_ingest/download_movies_data_msg.html')
| 18.7
| 71
| 0.791444
| 26
| 187
| 5.307692
| 0.615385
| 0.202899
| 0.26087
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.13369
| 187
| 9
| 72
| 20.777778
| 0.851852
| 0
| 0
| 0
| 0
| 0
| 0.278075
| 0.219251
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| true
| 0
| 0.2
| 0.4
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 8
|
a8ba2292aa66a6d049c58b0f10931b8349e78d65
| 18,976
|
py
|
Python
|
tensorflow_text/python/ops/ngrams_op_test.py
|
sun1638650145/text
|
c5c14d7739e4d3a0368f196e8a733e9654df6d20
|
[
"Apache-2.0"
] | 2
|
2021-10-31T03:30:37.000Z
|
2022-02-16T06:59:02.000Z
|
tensorflow_text/python/ops/ngrams_op_test.py
|
sun1638650145/text
|
c5c14d7739e4d3a0368f196e8a733e9654df6d20
|
[
"Apache-2.0"
] | null | null | null |
tensorflow_text/python/ops/ngrams_op_test.py
|
sun1638650145/text
|
c5c14d7739e4d3a0368f196e8a733e9654df6d20
|
[
"Apache-2.0"
] | null | null | null |
# coding=utf-8
# Copyright 2022 TF.Text Authors.
#
# 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.
# encoding=utf-8
"""Tests for ngram ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
import tensorflow_text as tf_text
from tensorflow.lite.python import interpreter
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import errors
from tensorflow.python.framework import test_util
from tensorflow.python.ops.ragged import ragged_factory_ops
from tensorflow.python.platform import test
from tensorflow_text.core.pybinds import tflite_registrar
from tensorflow_text.python.ops import ngrams_op
@test_util.run_all_in_graph_and_eager_modes
class NgramsOpTest(test_util.TensorFlowTestCase):
def testSumReduction(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[3.0, 5.0], [30.0, 50.0]]
self.assertAllEqual(expected_values, op)
def testRaggedSumReduction(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[3.0, 5.0, 7.0], [30.0, 50.0]]
self.assertAllEqual(expected_values, op)
def testRaggedSumReductionAxisZero(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0, 40.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=0, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[11.0, 22.0, 33.0, 44.0]]
self.assertAllEqual(expected_values, op)
def testMeanReduction(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=1, reduction_type=ngrams_op.Reduction.MEAN)
expected_values = [[1.5, 2.5], [15.0, 25.0]]
self.assertAllEqual(expected_values, op)
def testRaggedMeanReduction(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-1, reduction_type=ngrams_op.Reduction.MEAN)
expected_values = [[1.5, 2.5, 3.5], [15.0, 25.0]]
self.assertAllEqual(expected_values, op)
def testStringJoinReduction(self):
test_data = constant_op.constant([[b"a", b"b", b"c"],
[b"dd", b"ee", b"ff"]])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator=b"|")
expected_values = [[b"a|b", b"b|c"], [b"dd|ee", b"ee|ff"]]
self.assertAllEqual(expected_values, op)
def testStringJoinReductionAxisZero(self):
test_data = constant_op.constant([b"a", b"b", b"c"])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1, # The -1 axis is the zero axis here.
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator=b"|")
expected_values = [b"a|b", b"b|c"]
self.assertAllEqual(expected_values, op)
def testRaggedStringJoinReduction(self):
test_data = ragged_factory_ops.constant([[b"a", b"b", b"c"],
[b"dd", b"ee"]])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator=b"|")
expected_values = [[b"a|b", b"b|c"], [b"dd|ee"]]
self.assertAllEqual(expected_values, op)
def testReductionWithNegativeAxis(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[3.0, 5.0], [30.0, 50.0]]
self.assertAllEqual(expected_values, op)
def testReductionOnInnerAxis(self):
test_data = constant_op.constant([[[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]],
[[4.0, 5.0, 6.0], [40.0, 50.0, 60.0]]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-2, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[[11.0, 22.0, 33.0]], [[44.0, 55.0, 66.0]]]
self.assertAllEqual(expected_values, op)
def testRaggedReductionOnInnerAxis(self):
test_data = ragged_factory_ops.constant([[[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0, 40.0]],
[[100.0, 200.0], [300.0, 400.0]]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-2, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[[11.0, 22.0, 33.0, 44.0]], [[400.0, 600.0]]]
self.assertAllEqual(expected_values, op)
def testReductionOnAxisWithInsufficientValuesReturnsEmptySet(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=4, axis=-1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[], []]
self.assertAllEqual(expected_values, op)
def testRaggedReductionOnAxisWithInsufficientValuesReturnsEmptySet(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0],
[10.0, 20.0, 30.0, 40.0]])
op = ngrams_op.ngrams(
test_data, width=4, axis=1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[], [100.0]]
self.assertAllEqual(expected_values, op)
def testStringJoinReductionFailsWithImproperAxis(self):
with self.assertRaisesRegex(
errors.InvalidArgumentError,
r".*requires that ngrams' 'axis' parameter be -1."):
_ = ngrams_op.ngrams(
data=[],
width=2,
axis=0,
reduction_type=ngrams_op.Reduction.STRING_JOIN)
def testUnspecifiedReductionTypeFails(self):
with self.assertRaisesRegex(errors.InvalidArgumentError,
r"reduction_type must be specified."):
_ = ngrams_op.ngrams(data=[], width=2, axis=0)
def testBadReductionTypeFails(self):
with self.assertRaisesRegex(errors.InvalidArgumentError,
r"reduction_type must be a Reduction."):
_ = ngrams_op.ngrams(data=[], width=2, axis=0, reduction_type="SUM")
class NgramsV2OpTest(test_util.TensorFlowTestCase):
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testSumReduction(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[3.0, 5.0], [30.0, 50.0]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testRaggedSumReduction(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[3.0, 5.0, 7.0], [30.0, 50.0]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testRaggedSumReductionAxisZero(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0, 40.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=0, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[11.0, 22.0, 33.0, 44.0]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testMeanReduction(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=1, reduction_type=ngrams_op.Reduction.MEAN)
expected_values = [[1.5, 2.5], [15.0, 25.0]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testRaggedMeanReduction(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-1, reduction_type=ngrams_op.Reduction.MEAN)
expected_values = [[1.5, 2.5, 3.5], [15.0, 25.0]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testStringJoinReduction(self):
test_data = constant_op.constant([["a", "b", "c"], ["dd", "ee", "ff"]])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
expected_values = [[b"a|b", b"b|c"], [b"dd|ee", b"ee|ff"]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testStringJoinReductionRank3(self):
test_data = constant_op.constant([[["a", "b", "c"], ["z", "y", "x"]],
[["dd", "ee", "ff"], ["zz", "yy", "xx"]]])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
expected_values = [[[b"a|b", b"b|c"], [b"z|y", b"y|x"]],
[[b"dd|ee", b"ee|ff"], [b"zz|yy", b"yy|xx"]]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testStringJoinReductionAxisZero(self):
test_data = constant_op.constant(["a", "b", "c"])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1, # The -1 axis is the zero axis here.
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
expected_values = [b"a|b", b"b|c"]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testRaggedStringJoinReduction(self):
test_data = ragged_factory_ops.constant([["a", "b", "c"], ["dd", "ee"]])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
expected_values = [[b"a|b", b"b|c"], [b"dd|ee"]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testRaggedDeepStringJoinReduction(self):
test_data = ragged_factory_ops.constant([[[["a", "b", "c"]],
[["dd", "ee"]]],
[[["f", "g"], ["h", "i", "j"]],
[["k", "l"]]]])
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
expected_values = [[[[b"a|b", b"b|c"]], [[b"dd|ee"]]],
[[[b"f|g"], [b"h|i", b"i|j"]], [[b"k|l"]]]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testDoubleRaggedStringJoinReduction(self):
test_data = tf.constant([["a b c"], ["d e"]])
t = tf_text.WhitespaceTokenizer()
test_data = t.tokenize(test_data)
op = ngrams_op.ngrams(
test_data,
width=2,
axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
expected_values = [[[b"a|b", b"b|c"]], [[b"d|e"]]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testReductionWithNegativeAxis(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[3.0, 5.0], [30.0, 50.0]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testReductionOnInnerAxis(self):
test_data = constant_op.constant([[[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]],
[[4.0, 5.0, 6.0], [40.0, 50.0, 60.0]]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-2, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[[11.0, 22.0, 33.0]], [[44.0, 55.0, 66.0]]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testRaggedReductionOnInnerAxis(self):
test_data = ragged_factory_ops.constant([[[1.0, 2.0, 3.0, 4.0],
[10.0, 20.0, 30.0, 40.0]],
[[100.0, 200.0], [300.0, 400.0]]])
op = ngrams_op.ngrams(
test_data, width=2, axis=-2, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[[11.0, 22.0, 33.0, 44.0]], [[400.0, 600.0]]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testReductionOnAxisWithInsufficientValuesReturnsEmptySet(self):
test_data = constant_op.constant([[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]])
op = ngrams_op.ngrams(
test_data, width=4, axis=-1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[], []]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testRaggedReductionOnAxisWithInsufficientValuesReturnsEmptySet(self):
test_data = ragged_factory_ops.constant([[1.0, 2.0, 3.0],
[10.0, 20.0, 30.0, 40.0]])
op = ngrams_op.ngrams(
test_data, width=4, axis=1, reduction_type=ngrams_op.Reduction.SUM)
expected_values = [[], [100.0]]
self.assertAllEqual(expected_values, op)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testStringJoinReductionFailsWithImproperAxis(self):
with self.assertRaisesRegex(
errors.InvalidArgumentError,
r".*requires that ngrams' 'axis' parameter be -1."):
_ = ngrams_op.ngrams(
data=[],
width=2,
axis=0,
reduction_type=ngrams_op.Reduction.STRING_JOIN)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testUnspecifiedReductionTypeFails(self):
with self.assertRaisesRegex(errors.InvalidArgumentError,
r"reduction_type must be specified."):
_ = ngrams_op.ngrams(data=[], width=2, axis=0)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testBadReductionTypeFails(self):
with self.assertRaisesRegex(errors.InvalidArgumentError,
r"reduction_type must be a Reduction."):
_ = ngrams_op.ngrams(data=[], width=2, axis=0, reduction_type="SUM")
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testTfLite(self):
"""Checks TFLite conversion and inference."""
class NgramModel(tf.keras.Model):
def call(self, input_tensor, **kwargs):
return ngrams_op.ngrams(input_tensor, width=2, axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
# Test input data.
input_data = np.array(["a", "b", "c"])
# Define a Keras model.
model = NgramModel()
# Do TF.Text inference.
tf_result = model(tf.constant(input_data))
# Convert to TFLite.
converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS]
converter.allow_custom_ops = True
tflite_model = converter.convert()
# Do TFLite inference.
op = tflite_registrar.AddNgramsStringJoin
interp = interpreter.InterpreterWithCustomOps(
model_content=tflite_model,
custom_op_registerers=[op])
input_details = interp.get_input_details()
interp.resize_tensor_input(input_details[0]["index"], tf.shape(input_data))
interp.allocate_tensors()
interp.set_tensor(input_details[0]["index"], input_data)
interp.invoke()
output_details = interp.get_output_details()
tflite_result = interp.get_tensor(output_details[0]["index"])
# Assert the results are identical.
self.assertAllEqual(tflite_result, tf_result)
@test_util.with_forward_compatibility_horizons([2022, 11, 30])
def testTfLiteRagged(self):
"""Checks TFLite conversion and inference."""
class NgramModel(tf.keras.Model):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.tokenizer = tf_text.WhitespaceTokenizer()
@tf.function(input_signature=[
tf.TensorSpec(shape=[1], dtype=tf.string, name="input")
])
def call(self, input_tensor):
input_tensor = self.tokenizer.tokenize(input_tensor)
x = ngrams_op.ngrams(input_tensor, width=2, axis=-1,
reduction_type=ngrams_op.Reduction.STRING_JOIN,
string_separator="|")
return {"result": x.flat_values}
# Test input data.
input_data = np.array(["foo bar"])
# Define a Keras model.
model = NgramModel()
# Do TF.Text inference.
tf_result = model(tf.constant(input_data))["result"]
print(tf_result.shape)
# Convert to TFLite.
converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS]
converter.allow_custom_ops = True
tflite_model = converter.convert()
# Do TFLite inference.
interp = interpreter.InterpreterWithCustomOps(
model_content=tflite_model,
custom_op_registerers=tf_text.tflite_registrar.SELECT_TFTEXT_OPS)
print(interp.get_signature_list())
tn = interp.get_signature_runner("serving_default")
output = tn(input=input_data)
if tf.executing_eagerly():
tflite_result = output["result"]
else:
tflite_result = output["output_1"]
# Assert the results are identical.
self.assertAllEqual(tflite_result, tf_result)
if __name__ == "__main__":
test.main()
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0
| 7
|
765cb86745bee75e41b3729ee185504130b09f6c
| 36,685
|
py
|
Python
|
hubspot/crm/objects/api/basic_api.py
|
Ronfer/hubspot-api-python
|
1c87274ecbba4aa3c7728f890ccc6e77b2b6d2e4
|
[
"Apache-2.0"
] | 117
|
2020-04-06T08:22:53.000Z
|
2022-03-18T03:41:29.000Z
|
hubspot/crm/objects/api/basic_api.py
|
Ronfer/hubspot-api-python
|
1c87274ecbba4aa3c7728f890ccc6e77b2b6d2e4
|
[
"Apache-2.0"
] | 62
|
2020-04-06T16:21:06.000Z
|
2022-03-17T16:50:44.000Z
|
hubspot/crm/objects/api/basic_api.py
|
Ronfer/hubspot-api-python
|
1c87274ecbba4aa3c7728f890ccc6e77b2b6d2e4
|
[
"Apache-2.0"
] | 45
|
2020-04-06T16:13:52.000Z
|
2022-03-30T21:33:17.000Z
|
# coding: utf-8
"""
CRM Objects
CRM objects such as companies, contacts, deals, line items, products, tickets, and quotes are standard objects in HubSpot’s CRM. These core building blocks support custom properties, store critical information, and play a central role in the HubSpot application. ## Supported Object Types This API provides access to collections of CRM objects, which return a map of property names to values. Each object type has its own set of default properties, which can be found by exploring the [CRM Object Properties API](https://developers.hubspot.com/docs/methods/crm-properties/crm-properties-overview). |Object Type |Properties returned by default | |--|--| | `companies` | `name`, `domain` | | `contacts` | `firstname`, `lastname`, `email` | | `deals` | `dealname`, `amount`, `closedate`, `pipeline`, `dealstage` | | `products` | `name`, `description`, `price` | | `tickets` | `content`, `hs_pipeline`, `hs_pipeline_stage`, `hs_ticket_category`, `hs_ticket_priority`, `subject` | Find a list of all properties for an object type using the [CRM Object Properties](https://developers.hubspot.com/docs/methods/crm-properties/get-properties) API. e.g. `GET https://api.hubapi.com/properties/v2/companies/properties`. Change the properties returned in the response using the `properties` array in the request body. # noqa: E501
The version of the OpenAPI document: v3
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from hubspot.crm.objects.api_client import ApiClient
from hubspot.crm.objects.exceptions import ApiTypeError, ApiValueError # noqa: F401
class BasicApi(object):
"""NOTE: This class is auto generated by OpenAPI Generator
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def archive(self, object_type, object_id, **kwargs): # noqa: E501
"""Archive # noqa: E501
Move an Object identified by `{objectId}` to the recycling bin. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.archive(object_type, object_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param str object_id: (required)
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs["_return_http_data_only"] = True
return self.archive_with_http_info(object_type, object_id, **kwargs) # noqa: E501
def archive_with_http_info(self, object_type, object_id, **kwargs): # noqa: E501
"""Archive # noqa: E501
Move an Object identified by `{objectId}` to the recycling bin. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.archive_with_http_info(object_type, object_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param str object_id: (required)
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ["object_type", "object_id"]
all_params.extend(["async_req", "_return_http_data_only", "_preload_content", "_request_timeout"])
for key, val in six.iteritems(local_var_params["kwargs"]):
if key not in all_params:
raise ApiTypeError("Got an unexpected keyword argument '%s'" " to method archive" % key)
local_var_params[key] = val
del local_var_params["kwargs"]
# verify the required parameter 'object_type' is set
if self.api_client.client_side_validation and ("object_type" not in local_var_params or local_var_params["object_type"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_type` when calling `archive`") # noqa: E501
# verify the required parameter 'object_id' is set
if self.api_client.client_side_validation and ("object_id" not in local_var_params or local_var_params["object_id"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_id` when calling `archive`") # noqa: E501
collection_formats = {}
path_params = {}
if "object_type" in local_var_params:
path_params["objectType"] = local_var_params["object_type"] # noqa: E501
if "object_id" in local_var_params:
path_params["objectId"] = local_var_params["object_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(["*/*"]) # noqa: E501
# Authentication setting
auth_settings = ["hapikey", "oauth2", "oauth2_legacy"] # noqa: E501
return self.api_client.call_api(
"/crm/v3/objects/{objectType}/{objectId}",
"DELETE",
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get("async_req"),
_return_http_data_only=local_var_params.get("_return_http_data_only"), # noqa: E501
_preload_content=local_var_params.get("_preload_content", True),
_request_timeout=local_var_params.get("_request_timeout"),
collection_formats=collection_formats,
)
def create(self, object_type, simple_public_object_input, **kwargs): # noqa: E501
"""Create # noqa: E501
Create a CRM object with the given properties and return a copy of the object, including the ID. Documentation and examples for creating standard objects is provided. # 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(object_type, simple_public_object_input, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param SimplePublicObjectInput simple_public_object_input: (required)
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: SimplePublicObject
If the method is called asynchronously,
returns the request thread.
"""
kwargs["_return_http_data_only"] = True
return self.create_with_http_info(object_type, simple_public_object_input, **kwargs) # noqa: E501
def create_with_http_info(self, object_type, simple_public_object_input, **kwargs): # noqa: E501
"""Create # noqa: E501
Create a CRM object with the given properties and return a copy of the object, including the ID. Documentation and examples for creating standard objects is provided. # 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_with_http_info(object_type, simple_public_object_input, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param SimplePublicObjectInput simple_public_object_input: (required)
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(SimplePublicObject, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ["object_type", "simple_public_object_input"]
all_params.extend(["async_req", "_return_http_data_only", "_preload_content", "_request_timeout"])
for key, val in six.iteritems(local_var_params["kwargs"]):
if key not in all_params:
raise ApiTypeError("Got an unexpected keyword argument '%s'" " to method create" % key)
local_var_params[key] = val
del local_var_params["kwargs"]
# verify the required parameter 'object_type' is set
if self.api_client.client_side_validation and ("object_type" not in local_var_params or local_var_params["object_type"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_type` when calling `create`") # noqa: E501
# verify the required parameter 'simple_public_object_input' is set
if self.api_client.client_side_validation and ("simple_public_object_input" not in local_var_params or local_var_params["simple_public_object_input"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `simple_public_object_input` when calling `create`") # noqa: E501
collection_formats = {}
path_params = {}
if "object_type" in local_var_params:
path_params["objectType"] = local_var_params["object_type"] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if "simple_public_object_input" in local_var_params:
body_params = local_var_params["simple_public_object_input"]
# 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(["application/json"]) # noqa: E501 # noqa: E501
# Authentication setting
auth_settings = ["hapikey", "oauth2", "oauth2_legacy"] # noqa: E501
return self.api_client.call_api(
"/crm/v3/objects/{objectType}",
"POST",
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type="SimplePublicObject", # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get("async_req"),
_return_http_data_only=local_var_params.get("_return_http_data_only"), # noqa: E501
_preload_content=local_var_params.get("_preload_content", True),
_request_timeout=local_var_params.get("_request_timeout"),
collection_formats=collection_formats,
)
def get_by_id(self, object_type, object_id, **kwargs): # noqa: E501
"""Read # noqa: E501
Read an Object identified by `{objectId}`. `{objectId}` refers to the internal object ID by default, or optionally any unique property value as specified by the `idProperty` query param. Control what is returned via the `properties` query param. # 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_by_id(object_type, object_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param str object_id: (required)
:param list[str] properties: A comma separated list of the properties to be returned in the response. If any of the specified properties are not present on the requested object(s), they will be ignored.
:param list[str] associations: A comma separated list of object types to retrieve associated IDs for. If any of the specified associations do not exist, they will be ignored.
:param bool archived: Whether to return only results that have been archived.
:param str id_property: The name of a property whose values are unique for this object type
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: SimplePublicObjectWithAssociations
If the method is called asynchronously,
returns the request thread.
"""
kwargs["_return_http_data_only"] = True
return self.get_by_id_with_http_info(object_type, object_id, **kwargs) # noqa: E501
def get_by_id_with_http_info(self, object_type, object_id, **kwargs): # noqa: E501
"""Read # noqa: E501
Read an Object identified by `{objectId}`. `{objectId}` refers to the internal object ID by default, or optionally any unique property value as specified by the `idProperty` query param. Control what is returned via the `properties` query param. # 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_by_id_with_http_info(object_type, object_id, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param str object_id: (required)
:param list[str] properties: A comma separated list of the properties to be returned in the response. If any of the specified properties are not present on the requested object(s), they will be ignored.
:param list[str] associations: A comma separated list of object types to retrieve associated IDs for. If any of the specified associations do not exist, they will be ignored.
:param bool archived: Whether to return only results that have been archived.
:param str id_property: The name of a property whose values are unique for this object type
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(SimplePublicObjectWithAssociations, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ["object_type", "object_id", "properties", "associations", "archived", "id_property"]
all_params.extend(["async_req", "_return_http_data_only", "_preload_content", "_request_timeout"])
for key, val in six.iteritems(local_var_params["kwargs"]):
if key not in all_params:
raise ApiTypeError("Got an unexpected keyword argument '%s'" " to method get_by_id" % key)
local_var_params[key] = val
del local_var_params["kwargs"]
# verify the required parameter 'object_type' is set
if self.api_client.client_side_validation and ("object_type" not in local_var_params or local_var_params["object_type"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_type` when calling `get_by_id`") # noqa: E501
# verify the required parameter 'object_id' is set
if self.api_client.client_side_validation and ("object_id" not in local_var_params or local_var_params["object_id"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_id` when calling `get_by_id`") # noqa: E501
collection_formats = {}
path_params = {}
if "object_type" in local_var_params:
path_params["objectType"] = local_var_params["object_type"] # noqa: E501
if "object_id" in local_var_params:
path_params["objectId"] = local_var_params["object_id"] # noqa: E501
query_params = []
if "properties" in local_var_params and local_var_params["properties"] is not None: # noqa: E501
query_params.append(("properties", local_var_params["properties"])) # noqa: E501
collection_formats["properties"] = "multi" # noqa: E501
if "associations" in local_var_params and local_var_params["associations"] is not None: # noqa: E501
query_params.append(("associations", local_var_params["associations"])) # noqa: E501
collection_formats["associations"] = "multi" # noqa: E501
if "archived" in local_var_params and local_var_params["archived"] is not None: # noqa: E501
query_params.append(("archived", local_var_params["archived"])) # noqa: E501
if "id_property" in local_var_params and local_var_params["id_property"] is not None: # noqa: E501
query_params.append(("idProperty", local_var_params["id_property"])) # 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 = ["hapikey", "oauth2", "oauth2_legacy"] # noqa: E501
return self.api_client.call_api(
"/crm/v3/objects/{objectType}/{objectId}",
"GET",
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type="SimplePublicObjectWithAssociations", # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get("async_req"),
_return_http_data_only=local_var_params.get("_return_http_data_only"), # noqa: E501
_preload_content=local_var_params.get("_preload_content", True),
_request_timeout=local_var_params.get("_request_timeout"),
collection_formats=collection_formats,
)
def get_page(self, object_type, **kwargs): # noqa: E501
"""List # noqa: E501
Read a page of objects. Control what is returned via the `properties` query param. # 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_page(object_type, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param int limit: The maximum number of results to display per page.
:param str after: The paging cursor token of the last successfully read resource will be returned as the `paging.next.after` JSON property of a paged response containing more results.
:param list[str] properties: A comma separated list of the properties to be returned in the response. If any of the specified properties are not present on the requested object(s), they will be ignored.
:param list[str] associations: A comma separated list of object types to retrieve associated IDs for. If any of the specified associations do not exist, they will be ignored.
:param bool archived: Whether to return only results that have been archived.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: CollectionResponseSimplePublicObjectWithAssociationsForwardPaging
If the method is called asynchronously,
returns the request thread.
"""
kwargs["_return_http_data_only"] = True
return self.get_page_with_http_info(object_type, **kwargs) # noqa: E501
def get_page_with_http_info(self, object_type, **kwargs): # noqa: E501
"""List # noqa: E501
Read a page of objects. Control what is returned via the `properties` query param. # 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_page_with_http_info(object_type, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param int limit: The maximum number of results to display per page.
:param str after: The paging cursor token of the last successfully read resource will be returned as the `paging.next.after` JSON property of a paged response containing more results.
:param list[str] properties: A comma separated list of the properties to be returned in the response. If any of the specified properties are not present on the requested object(s), they will be ignored.
:param list[str] associations: A comma separated list of object types to retrieve associated IDs for. If any of the specified associations do not exist, they will be ignored.
:param bool archived: Whether to return only results that have been archived.
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(CollectionResponseSimplePublicObjectWithAssociationsForwardPaging, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ["object_type", "limit", "after", "properties", "associations", "archived"]
all_params.extend(["async_req", "_return_http_data_only", "_preload_content", "_request_timeout"])
for key, val in six.iteritems(local_var_params["kwargs"]):
if key not in all_params:
raise ApiTypeError("Got an unexpected keyword argument '%s'" " to method get_page" % key)
local_var_params[key] = val
del local_var_params["kwargs"]
# verify the required parameter 'object_type' is set
if self.api_client.client_side_validation and ("object_type" not in local_var_params or local_var_params["object_type"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_type` when calling `get_page`") # noqa: E501
collection_formats = {}
path_params = {}
if "object_type" in local_var_params:
path_params["objectType"] = local_var_params["object_type"] # noqa: E501
query_params = []
if "limit" in local_var_params and local_var_params["limit"] is not None: # noqa: E501
query_params.append(("limit", local_var_params["limit"])) # noqa: E501
if "after" in local_var_params and local_var_params["after"] is not None: # noqa: E501
query_params.append(("after", local_var_params["after"])) # noqa: E501
if "properties" in local_var_params and local_var_params["properties"] is not None: # noqa: E501
query_params.append(("properties", local_var_params["properties"])) # noqa: E501
collection_formats["properties"] = "multi" # noqa: E501
if "associations" in local_var_params and local_var_params["associations"] is not None: # noqa: E501
query_params.append(("associations", local_var_params["associations"])) # noqa: E501
collection_formats["associations"] = "multi" # noqa: E501
if "archived" in local_var_params and local_var_params["archived"] is not None: # noqa: E501
query_params.append(("archived", local_var_params["archived"])) # 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 = ["hapikey", "oauth2", "oauth2_legacy"] # noqa: E501
return self.api_client.call_api(
"/crm/v3/objects/{objectType}",
"GET",
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type="CollectionResponseSimplePublicObjectWithAssociationsForwardPaging", # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get("async_req"),
_return_http_data_only=local_var_params.get("_return_http_data_only"), # noqa: E501
_preload_content=local_var_params.get("_preload_content", True),
_request_timeout=local_var_params.get("_request_timeout"),
collection_formats=collection_formats,
)
def update(self, object_type, object_id, simple_public_object_input, **kwargs): # noqa: E501
"""Update # noqa: E501
Perform a partial update of an Object identified by `{objectId}`. `{objectId}` refers to the internal object ID by default, or optionally any unique property value as specified by the `idProperty` query param. Provided property values will be overwritten. Read-only and non-existent properties will be ignored. Properties values can be cleared by passing an empty string. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update(object_type, object_id, simple_public_object_input, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param str object_id: (required)
:param SimplePublicObjectInput simple_public_object_input: (required)
:param str id_property: The name of a property whose values are unique for this object type
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: SimplePublicObject
If the method is called asynchronously,
returns the request thread.
"""
kwargs["_return_http_data_only"] = True
return self.update_with_http_info(object_type, object_id, simple_public_object_input, **kwargs) # noqa: E501
def update_with_http_info(self, object_type, object_id, simple_public_object_input, **kwargs): # noqa: E501
"""Update # noqa: E501
Perform a partial update of an Object identified by `{objectId}`. `{objectId}` refers to the internal object ID by default, or optionally any unique property value as specified by the `idProperty` query param. Provided property values will be overwritten. Read-only and non-existent properties will be ignored. Properties values can be cleared by passing an empty string. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_with_http_info(object_type, object_id, simple_public_object_input, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str object_type: (required)
:param str object_id: (required)
:param SimplePublicObjectInput simple_public_object_input: (required)
:param str id_property: The name of a property whose values are unique for this object type
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(SimplePublicObject, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ["object_type", "object_id", "simple_public_object_input", "id_property"]
all_params.extend(["async_req", "_return_http_data_only", "_preload_content", "_request_timeout"])
for key, val in six.iteritems(local_var_params["kwargs"]):
if key not in all_params:
raise ApiTypeError("Got an unexpected keyword argument '%s'" " to method update" % key)
local_var_params[key] = val
del local_var_params["kwargs"]
# verify the required parameter 'object_type' is set
if self.api_client.client_side_validation and ("object_type" not in local_var_params or local_var_params["object_type"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_type` when calling `update`") # noqa: E501
# verify the required parameter 'object_id' is set
if self.api_client.client_side_validation and ("object_id" not in local_var_params or local_var_params["object_id"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `object_id` when calling `update`") # noqa: E501
# verify the required parameter 'simple_public_object_input' is set
if self.api_client.client_side_validation and ("simple_public_object_input" not in local_var_params or local_var_params["simple_public_object_input"] is None): # noqa: E501 # noqa: E501
raise ApiValueError("Missing the required parameter `simple_public_object_input` when calling `update`") # noqa: E501
collection_formats = {}
path_params = {}
if "object_type" in local_var_params:
path_params["objectType"] = local_var_params["object_type"] # noqa: E501
if "object_id" in local_var_params:
path_params["objectId"] = local_var_params["object_id"] # noqa: E501
query_params = []
if "id_property" in local_var_params and local_var_params["id_property"] is not None: # noqa: E501
query_params.append(("idProperty", local_var_params["id_property"])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if "simple_public_object_input" in local_var_params:
body_params = local_var_params["simple_public_object_input"]
# 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(["application/json"]) # noqa: E501 # noqa: E501
# Authentication setting
auth_settings = ["hapikey", "oauth2", "oauth2_legacy"] # noqa: E501
return self.api_client.call_api(
"/crm/v3/objects/{objectType}/{objectId}",
"PATCH",
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type="SimplePublicObject", # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get("async_req"),
_return_http_data_only=local_var_params.get("_return_http_data_only"), # noqa: E501
_preload_content=local_var_params.get("_preload_content", True),
_request_timeout=local_var_params.get("_request_timeout"),
collection_formats=collection_formats,
)
| 58.230159
| 1,327
| 0.652337
| 4,482
| 36,685
| 5.118251
| 0.072066
| 0.042546
| 0.067132
| 0.020924
| 0.915432
| 0.912903
| 0.910549
| 0.908413
| 0.896208
| 0.895074
| 0
| 0.014993
| 0.269102
| 36,685
| 629
| 1,328
| 58.322735
| 0.840562
| 0.506883
| 0
| 0.770677
| 0
| 0
| 0.227922
| 0.057012
| 0
| 0
| 0
| 0
| 0
| 1
| 0.041353
| false
| 0
| 0.018797
| 0
| 0.101504
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| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
4f13968f0dc867e236c8b835ee4551dfd2a581e3
| 164
|
py
|
Python
|
GPyOpt/core/errors.py
|
zhenwendai/GPyOpt
|
fd96875e7ec0cb0f78014d96813ece400648827d
|
[
"BSD-3-Clause"
] | 850
|
2015-05-31T21:12:41.000Z
|
2022-03-24T17:25:37.000Z
|
GPyOpt/core/errors.py
|
lakshaykc/GPyOpt
|
097ba66e81c7e22b5bf9fdbe64fd135753bc4a67
|
[
"BSD-3-Clause"
] | 340
|
2015-09-10T14:08:06.000Z
|
2022-03-28T20:35:26.000Z
|
GPyOpt/core/errors.py
|
lakshaykc/GPyOpt
|
097ba66e81c7e22b5bf9fdbe64fd135753bc4a67
|
[
"BSD-3-Clause"
] | 299
|
2015-07-30T13:18:37.000Z
|
2022-03-22T21:27:31.000Z
|
class InvalidConfigError(Exception):
pass
class FullyExploredOptimizationDomainError(Exception):
pass
class InvalidVariableNameError(Exception):
pass
| 18.222222
| 54
| 0.804878
| 12
| 164
| 11
| 0.5
| 0.295455
| 0.272727
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.140244
| 164
| 8
| 55
| 20.5
| 0.93617
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
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| 0
| 1
| null | 1
| 1
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| 0
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| null | 0
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| 0
| 0
| 0
| 0
|
0
| 7
|
4f7fd6f1237811a8f4207d37fc26afb8ee070545
| 23,643
|
py
|
Python
|
basemodels/BaseLayers.py
|
Zhaopudark/MRI-Trans-GAN
|
1af8f486202ded20328195ee636f2056894edebb
|
[
"MIT"
] | 3
|
2020-11-09T11:08:55.000Z
|
2021-05-09T07:49:40.000Z
|
basemodels/BaseLayers.py
|
Zhaopudark/MRI-Trans-GAN
|
1af8f486202ded20328195ee636f2056894edebb
|
[
"MIT"
] | 1
|
2020-11-29T04:11:14.000Z
|
2020-12-02T16:00:42.000Z
|
basemodels/BaseLayers.py
|
Zhaopudark/MRI-Trans-GAN
|
1af8f486202ded20328195ee636f2056894edebb
|
[
"MIT"
] | 1
|
2021-05-12T03:50:46.000Z
|
2021-05-12T03:50:46.000Z
|
"""
定义基本模型层
基于tf.keras.Model
"""
import tensorflow as tf
import os
import sys
base = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(base, '../'))
from utils.BuildHelper import Reconstruction
from utils.SnOption import SpectralNormalization
class Dense(tf.keras.layers.Layer):
def __init__(self,input_shape,
kernel_size,
kernel_initializer="glorot_uniform",
using_bias=False,
activation="relu",**kwargs):
"""
input_shape: list [None,shape] or [shape]
kernel_size: int
using_bias: bool
activation: string like "relu","sigmoid","leaky_relu","tanh"
"""
super(Dense,self).__init__()
self.initializer = Reconstruction.initializer(kernel_initializer)#定义初始化采用的方法
self.input_shape_zp = Reconstruction.remake_shape(shape=input_shape,dims=2)
self.w = tf.Variable(initial_value=self.initializer(shape=[self.input_shape_zp[-1],kernel_size],dtype=tf.float32),
trainable=True)
self.using_bias = using_bias
if using_bias :
self.b = tf.Variable(initial_value=tf.zeros(shape=(1,kernel_size),dtype=tf.float32),
trainable=True)#节点的偏置也是行向量 才可以正常计算 即对堆叠的batch 都是加载单个batch内
self.activation = Reconstruction.activation(activation)
def call(self,x,*args,**kwargs):
x = tf.matmul(x,self.w)
if self.using_bias:
x = x+self.b
y = self.activation(x)
return y
class Dropout(tf.keras.Model):
def __init__(self,rate=0.3,
noise_shape=None,
seed=None,**kwargs):
super(Dropout,self).__init__()
self.rate = rate
self.noise_shape = noise_shape
self.seed = seed
# print(kwargs)
def call(self,x,training=True,**kwargs):
if training == True:
y = tf.nn.dropout(x,rate=self.rate,noise_shape=self.noise_shape,seed=self.seed)
return y
else:
y = x
return y
class BatchNormalization(tf.keras.Model):
def __init__(self,input_shape,
epsilon=1e-3,
momentum=0.99):
super(BatchNormalization,self).__init__()
"""
input_shape 不考虑batch维度
"""
self.offset = tf.Variable(tf.zeros((1),dtype=tf.float32),trainable=True)
self.scale = tf.Variable(tf.ones((1),dtype=tf.float32),trainable=True)
self.mean = tf.Variable(tf.zeros(input_shape),dtype=tf.float32,trainable=False)#参与测试不参与训练
self.variance = tf.Variable(tf.ones(input_shape),dtype=tf.float32,trainable=False)#参与测试不参与训练
self.epsilon = epsilon
self.momentum = momentum
def call(self,x,training=True,**kwargs):
if training:
mean,variance = tf.nn.moments(x,axes=[0],keepdims=True)
self.mean.assign(self.mean*self.momentum+(1-self.momentum)*self.mean)
self.variance.assign(self.variance*self.momentum+(1-self.momentum)*self.variance)
y = tf.nn.batch_normalization(x,mean,variance,self.offset,self.scale,self.epsilon)
return y
else:
y = tf.nn.batch_normalization(x,self.mean,self.variance,self.offset,self.scale,self.epsilon)
return y
class InstanceNorm3D(tf.keras.Model):
def __init__(self,epsilon=1e-3):
"""
instance Norm
对于三通道彩图 是每个通道 每个batch 下做 WH的norm的
对于3D医学图像 是每个通道 每个batch下做 DWH的norm的
"""
super(InstanceNorm3D,self).__init__()
self.epsilon = epsilon
self.scale = tf.Variable(tf.ones((1),dtype=tf.float32),trainable=True)
self.offset = tf.Variable(tf.zeros((1),dtype=tf.float32),trainable=True)
def call(self,x):
mean,variance = tf.nn.moments(x,axes=[1,2,3],keepdims=True)
x_hat = (x-mean)/tf.sqrt(variance+self.epsilon)
y = self.scale*x_hat+self.offset
return y
class InstanceNorm2D(tf.keras.Model):
def __init__(self,epsilon=1e-3):
"""
instance Norm
对于三通道彩图 是每个通道 每个batch 下做 WH的norm的
对于3D医学图像 是每个通道 每个batch下做 DWH的norm的
"""
super(InstanceNorm2D,self).__init__()
self.epsilon = epsilon
self.scale = tf.Variable(tf.ones((1),dtype=tf.float32),trainable=True)
self.offset = tf.Variable(tf.zeros((1),dtype=tf.float32),trainable=True)
def call(self,x):
mean,variance = tf.nn.moments(x,axes=[1,2],keepdims=True)
x_hat = (x-mean)/tf.sqrt(variance+self.epsilon)
y = self.scale*x_hat+self.offset
return y
class Conv3D(tf.keras.Model):
def __init__(self,input_shape,filters,kernel_size,strides=[1,1,1],padding="SAME",using_bias=False,sn=False):
"""
将卷积统一为
计算参数量
自行padding
然后使用VALID卷积
这样就可以嵌入任意的padding模式了
则该层的输入shape对于SN而言，就需要加上padding_vect变成padding后的值
"""
super(Conv3D,self).__init__()
self.input_shape_zp = Reconstruction.remake_shape(input_shape,dims=5)#5维的输出张量
self.kernel_size_zp = Reconstruction.remake_kernel_size(kernel_size,dims=3)#3维卷积核 变为[1,x,x,x,1]5D形式
self.strides_zp = Reconstruction.remake_strides(strides,dims=3)#3维步长 变为[1,x,x,x,1]5D形式
self.output_shape_zp,self.padding,self.padding_vect = Reconstruction.ConvCalculation(self.input_shape_zp[1:-1],filters,self.kernel_size_zp[1:-1],self.strides_zp[1:-1],padding)
weight_shape = self.kernel_size_zp[1:-1]+[self.input_shape_zp[-1]]+[filters]#[D,H,W,IC,OC]
self.initializer = Reconstruction.initializer("random_normal",mean=0.0,stddev=0.02)
self.w = tf.Variable(initial_value=self.initializer(shape=weight_shape),
trainable=True,
dtype=tf.float32)
self.using_bias = using_bias
if using_bias == True:
self.b = tf.Variable(tf.zeros(self.output_shape_zp,dtype=tf.float32),trainable=True)
self.sn = sn
def call(self,x):
x = tf.pad(x,self.padding_vect,self.padding)
if self.sn:
sigma=self.w_bar
else:
sigma=1
print(self.w.shape)
w=self.w/sigma
print(w.shape)
y = tf.nn.conv3d(input=x,filters=w,strides=self.strides_zp,padding="VALID")
if self.using_bias == True:
return y+self.b
else:
return y
@property
def w_bar(self,iter_k=5):
sigma = SpectralNormalization.SN(self.w,iter_k=iter_k)
return sigma
class Conv3DTranspose(tf.keras.Model):
def __init__(self,input_shape,output_shape,filters,kernel_size,strides=[1,1,1],padding="SAME",using_bias=False,sn=False):
super(Conv3DTranspose,self).__init__()
self.input_shape_zp = Reconstruction.remake_shape(input_shape,dims=5)#变成5维的输出张量 None补充不足的维度(batch)
self.output_shape_zp = Reconstruction.remake_shape(output_shape+[filters],dims=5)#变成5维的输出张量
self.kernel_size_zp = Reconstruction.remake_kernel_size(kernel_size,dims=3)#3维卷积核 变为[1,x,x,x,1]5D形式
self.strides_zp = Reconstruction.remake_strides(strides,dims=3)#3维步长 变为[1,x,x,x,1]5D形式
self.padding = padding
Reconstruction.ConvTransCheck(input_shape=self.input_shape_zp[1:-1],
output_shape=self.output_shape_zp[1:-1],
filters=filters,
kernel_size=self.kernel_size_zp[1:-1],
strides=self.strides_zp[1:-1],
padding=self.padding)
weight_shape = self.kernel_size_zp[1:-1]+[filters]+[self.input_shape_zp[-1]]#[D,H,W,OC,IC]
self.initializer = Reconstruction.initializer("random_normal",mean=0.0,stddev=0.02)
self.w = tf.Variable(initial_value=self.initializer(shape=weight_shape),
trainable=True,
dtype=tf.float32)
self.using_bias = using_bias
if using_bias == True:
self.b = tf.Variable(tf.zeros(self.output_shape_zp[1:],dtype=tf.float32),trainable=True)
self.sn = sn
def call(self,x):
if self.sn:
sigma = self.w_bar
else:
sigma = 1
w=self.w/sigma #避免直接用assign修改
y = tf.nn.conv3d_transpose(input=x,
filters=w,
output_shape=[x.shape[0]]+self.output_shape_zp[1:],
strides=self.strides_zp,
padding=self.padding)
return y
@property
def w_bar(self,iter_k=5):
sigma = SpectralNormalization.SN(self.w,iter_k=iter_k)
return sigma
class Conv2D(tf.keras.Model):
def __init__(self,input_shape,filters,kernel_size,strides=[1,1],padding="SAME",using_bias=False,sn=False):
"""
将卷积统一为
计算参数量
自行padding
然后使用VALID卷积
这样就可以嵌入任意的padding模式了
则该层的输入shape对于SN而言，就需要加上padding_vect变成padding后的值
"""
super(Conv2D,self).__init__()
self.input_shape_zp = Reconstruction.remake_shape(input_shape,dims=4)#4维的输出张量
self.kernel_size_zp = Reconstruction.remake_kernel_size(kernel_size,dims=2)#2维卷积核 变为[1,x,x,1]4D形式
self.strides_zp = Reconstruction.remake_strides(strides,dims=2)#2维步长 变为[1,x,x,1]4D形式
self.output_shape_zp,self.padding,self.padding_vect = Reconstruction.ConvCalculation(self.input_shape_zp[1:-1],filters,self.kernel_size_zp[1:-1],self.strides_zp[1:-1],padding)
weight_shape = self.kernel_size_zp[1:-1]+[self.input_shape_zp[-1]]+[filters]#[H,W,IC,OC]
self.initializer = Reconstruction.initializer("random_normal",mean=0.0,stddev=0.02)
self.w = tf.Variable(initial_value=self.initializer(shape=weight_shape),
trainable=True,
dtype=tf.float32)
self.using_bias = using_bias
if using_bias == True:
self.b = tf.Variable(tf.zeros(self.output_shape_zp,dtype=tf.float32),trainable=True)
self.sn = sn
def call(self,x):
x = tf.pad(x,self.padding_vect,self.padding)
if self.sn:
sigma=self.w_bar
else:
sigma=1
print(self.w.shape)
w=self.w/sigma
print(w.shape)
y = tf.nn.conv2d(input=x,filters=w,strides=self.strides_zp,padding="VALID")
if self.using_bias == True:
return y+self.b
else:
return y
@property
def w_bar(self,iter_k=5):
sigma = SpectralNormalization.SN(self.w,iter_k=iter_k)
return sigma
class Conv2DTranspose(tf.keras.Model):
def __init__(self,input_shape,output_shape,filters,kernel_size,strides=[1,1],padding="SAME",using_bias=False,sn=False):
super(Conv2DTranspose,self).__init__()
self.input_shape_zp = Reconstruction.remake_shape(input_shape,dims=4)#变成4维的输出张量 None补充不足的维度(batch)
self.output_shape_zp = Reconstruction.remake_shape(output_shape+[filters],dims=4)#变成4维的输出张量
self.kernel_size_zp = Reconstruction.remake_kernel_size(kernel_size,dims=2)#2维卷积核 变为[1,x,x,1]4D形式
self.strides_zp = Reconstruction.remake_strides(strides,dims=2)#2维步长 变为[1,x,x,1]4D形式
self.padding = padding
Reconstruction.ConvTransCheck(input_shape=self.input_shape_zp[1:-1],
output_shape=self.output_shape_zp[1:-1],
filters=filters,
kernel_size=self.kernel_size_zp[1:-1],
strides=self.strides_zp[1:-1],
padding=self.padding)
weight_shape = self.kernel_size_zp[1:-1]+[filters]+[self.input_shape_zp[-1]]#[D,H,W,OC,IC]
self.initializer = Reconstruction.initializer("random_normal",mean=0.0,stddev=0.02)
self.w = tf.Variable(initial_value=self.initializer(shape=weight_shape),
trainable=True,
dtype=tf.float32)
self.using_bias = using_bias
if using_bias == True:
self.b = tf.Variable(tf.zeros(self.output_shape_zp[1:],dtype=tf.float32),trainable=True)
self.sn = sn
def call(self,x):
if self.sn:
sigma = self.w_bar
else:
sigma = 1
w=self.w/sigma #避免直接用assign修改
y = tf.nn.conv2d_transpose(input=x,
filters=w,
output_shape=[x.shape[0]]+self.output_shape_zp[1:],
strides=self.strides_zp,
padding=self.padding)
return y
@property
def w_bar(self,iter_k=5):
sigma = SpectralNormalization.SN(self.w,iter_k=iter_k)
return sigma
######################################################################################################################
class UpSampaleConv2D(tf.keras.layers.Layer):
"""
将转至卷积变成上采样和卷积的组合
input_shape
output_shape
strides
padding
之间必须满足符合一般转至卷积的计算逻辑
"""
def __init__(self,input_shape,output_shape,filters,kernel_size,strides=[2,2],padding="SAME",using_bias=False,sn=False):#输出的深度已经给出 只要给出每个通道的H,W即可
super(UpSampaleConv2D,self).__init__()
self.input_shape_zp = Reconstruction.remake_shape(input_shape,dims=4)#变成4维的输出张量 None补充不足的维度(batch)
self.output_shape_zp = Reconstruction.remake_shape(output_shape+[filters],dims=4)#变成4维的输出张量
self.kernel_size_zp = Reconstruction.remake_kernel_size(kernel_size,dims=2)#2维卷积核 变为[1,x,x,1]4D形式
self.strides_zp = Reconstruction.remake_strides(strides,dims=2)#2维步长 变为[1,x,x,1]4D形式
self.padding = padding
self.padding,self.padding_vect,self.cut_flag = Reconstruction.Trans2UpsampleCal(self.input_shape_zp[1:-1],
self.output_shape_zp[1:-1],
filters,
self.kernel_size_zp[1:-1],
self.strides_zp[1:-1],
self.padding)
self.up_size = self.strides_zp[1:-1]
self.up_op = tf.keras.layers.UpSampling2D(size=self.up_size)#上采样只对非通道和非batch进行 剔除冗余维度
self.strides_zp = Reconstruction.remake_strides([1,1],dims=2)
self.initializer = Reconstruction.initializer("random_normal",mean=0.0,stddev=0.02)
weight_shape = self.kernel_size_zp[1:-1]+[self.input_shape_zp[-1]]+[filters]#[H,W,IC,OC]
self.w = tf.Variable(initial_value=self.initializer(shape=weight_shape),
trainable=True,
dtype=tf.float32)
self.using_bias = using_bias
if using_bias == True:
self.b = tf.Variable(tf.zeros(self.output_shape_zp[1:],dtype=tf.float32),trainable=True)
self.sn = sn
def call(self,x):
x = self.up_op(x)
if self.cut_flag:
x = x[0-self.padding_vect[0][0]:int(x.shape[0])+self.padding_vect[0][1],
0-self.padding_vect[1][0]:int(x.shape[1])+self.padding_vect[1][1],
0-self.padding_vect[2][0]:int(x.shape[2])+self.padding_vect[2][1],
0-self.padding_vect[3][0]:int(x.shape[3])+self.padding_vect[3][1]]
else:
x = tf.pad(x,self.padding_vect,"CONSTANT")
if self.sn == True:
sigmma = self.w_bar
else:
sigmma = 1
w=self.w/sigmma #避免直接用assign修改
y = tf.nn.conv2d(input=x,filters=w,strides=self.strides_zp,padding="VALID")
return y
@property
def w_bar(self,iter_k=5):
sigma = SpectralNormalization.SN(self.w,iter_k=iter_k)
return sigma
class UpSampaleConv3D(tf.keras.layers.Layer):
"""
将转至卷积变成上采样和卷积的组合
input_shape
output_shape
strides
padding
之间必须满足符合一般转至卷积的计算逻辑
"""
def __init__(self,input_shape,output_shape,filters,kernel_size,strides=[2,2,2],padding="SAME",using_bias=False,sn=False):#输出的深度已经给出 只要给出每个通道的H,W即可
super(UpSampaleConv3D,self).__init__()
self.input_shape_zp = Reconstruction.remake_shape(input_shape,dims=5)#变成5维的输出张量 None补充不足的维度(batch)
self.output_shape_zp = Reconstruction.remake_shape(output_shape+[filters],dims=5)#变成5维的输出张量
self.kernel_size_zp = Reconstruction.remake_kernel_size(kernel_size,dims=3)#3维卷积核 变为[1,x,x,x,1]5D形式
self.strides_zp = Reconstruction.remake_strides(strides,dims=3)#3维步长 变为[1,x,x,x,1]4D形式
self.padding = padding
self.padding,self.padding_vect,self.cut_flag = Reconstruction.Trans2UpsampleCal(self.input_shape_zp[1:-1],
self.output_shape_zp[1:-1],
filters,
self.kernel_size_zp[1:-1],
self.strides_zp[1:-1],
self.padding)
self.up_size = self.strides_zp[1:-1]
self.up_op = tf.keras.layers.UpSampling3D(size=self.up_size)#上采样只对非通道和非batch进行 剔除冗余维度
self.strides_zp = Reconstruction.remake_strides([1,1,1],dims=3)
self.initializer = Reconstruction.initializer("random_normal",mean=0.0,stddev=0.02)
weight_shape = self.kernel_size_zp[1:-1]+[self.input_shape_zp[-1]]+[filters]#[D,H,W,IC,OC]
self.w = tf.Variable(initial_value=self.initializer(shape=weight_shape),
trainable=True,
dtype=tf.float32)
self.using_bias = using_bias
if using_bias == True:
self.b = tf.Variable(tf.zeros(self.output_shape_zp[1:],dtype=tf.float32),trainable=True)
self.sn = sn
def call(self,x):
x = self.up_op(x)
if self.cut_flag:
x = x[0-self.padding_vect[0][0]:int(x.shape[0])+self.padding_vect[0][1],
0-self.padding_vect[1][0]:int(x.shape[1])+self.padding_vect[1][1],
0-self.padding_vect[2][0]:int(x.shape[2])+self.padding_vect[2][1],
0-self.padding_vect[3][0]:int(x.shape[3])+self.padding_vect[3][1],
0-self.padding_vect[4][0]:int(x.shape[4])+self.padding_vect[4][1]]
else:
x = tf.pad(x,self.padding_vect,"CONSTANT")
if self.sn == True:
sigmma = self.w_bar
else:
sigmma = 1
w=self.w/sigmma #避免直接用assign修改
y = tf.nn.conv3d(input=x,filters=w,strides=self.strides_zp,padding="VALID")
return y
@property
def w_bar(self,iter_k=5):
sigma = SpectralNormalization.SN(self.w,iter_k=iter_k)
return sigma
# ###########################################################################################################
# if __name__ == "__main__":
# from tensorflow.keras.mixed_precision import experimental as mixed_precision
# policy = mixed_precision.Policy('mixed_float16')
# mixed_precision.set_policy(policy)
# a = UpSampaleConv2D([4,4,5],[10,10],1,kernel_size=(3,3),strides=(2,2),padding="VALID",sn=True)
# x = tf.constant(tf.random.normal((1,4,4,5),dtype=tf.float16))
# y = a(x)
# print(y.shape,y.dtype)
# print(len(a.trainable_variables))
# print(a.output_shape_zp)
if __name__ == "__main__":
physical_devices = tf.config.experimental.list_physical_devices(device_type='GPU')
tf.config.experimental.set_memory_growth(physical_devices[0], True)
x = tf.random.normal(shape=[5,2], mean=0.0, stddev=1.0)
a_ = tf.keras.layers.Dense(3)
a = Dense([2],3)
print(a(x))
print(a.trainable_variables)
a = Dense([2],3)
print(a(x))
print(a.trainable_variables)
a = Dense(2,3)
print(a(x))
print(a.trainable_variables)
a = Dense(2,3,kernel_initializer="glorot_uniform",
using_bias=True,
activation="relu")
print(a.trainable_variables)
print(a(x))
# b = tf.constant([[1.0,1.0],[2.0,2.0]])
b = tf.random.normal(shape=[7,3], mean=0.0, stddev=1.0)
bn = BatchNormalization(3)
print(tmp1:=bn(b))
print(tmp2:=bn(b,training=False))
print(tmp1-tmp2)
print(x:=tf.random.normal(shape=[5,10], mean=0.0, stddev=1.0))
dp = Dropout(rate=0.2,noise_shape=[5,1])#在非1维度随机出0 然后在是1维度广播
print(dp(x))
dp = Dropout(rate=0.2,noise_shape=[1,10])
print(dp(x))
print(dp(x))
print(dp(x))
print(x:=tf.constant([[1.0,1.0],[1.0,1.0]]))
dp = Dropout(rate=0.2,noise_shape=[2,2])
print(dp(x))
dp = Dropout(rate=0.5,noise_shape=[1,2])
print(dp(x))
dp = Dropout(rate=0.5,noise_shape=[2,1])
print(dp(x))
dp = Dropout(drop_rate=0.5,noise_shape=[2,1])
print(x:=tf.reshape(tf.range(27.0),[1,3,3,3,1]))
i_n = InstanceNorm3D()
print(i_n(x))
print(x:=tf.reshape(tf.range(27.0),[1,3,3,3]))
i_n = InstanceNorm2D()
print(i_n(x))
cv3d = Conv3D(input_shape=[64,64,64,3],filters=16,kernel_size=[3,3,3],strides=[1,1,1],padding="SAME",using_bias=False,sn=True)
print(x:=tf.reshape(tf.range(64*64*64*3.0),[1,64,64,64,3]))
print(cv3d(x).shape)
a = Conv3DTranspose([4,4,4,5],[8,8,8],100,kernel_size=(3,3,3),strides=(2,2,2),padding="SAME",sn=True)
x = tf.constant(tf.random.normal((1,4,4,4,5)))
print(a(x).shape)
print(len(a.trainable_variables))
print(a.output_shape_zp)
a = Conv2DTranspose([4,4,5],[7,7],1,kernel_size=(3,3),strides=(2,2),padding="SAME",sn=True)
x = tf.constant(tf.random.normal((1,4,4,5)))
print(a(x).shape)
print(len(a.trainable_variables))
print(a.output_shape_zp)
cv2d = Conv2D(input_shape=[4,4,1],filters=4,kernel_size=[2,2],strides=[1,1],sn=True)
x = tf.random.normal((1,4,4,1))
print(cv2d(x).shape)
for item in cv2d.trainable_variables:
print(item.name)
a = UpSampaleConv2D([4,4,5],[10,10],1,kernel_size=(3,3),strides=(2,2),padding="VALID",sn=True)
x = tf.constant(tf.random.normal((1,4,4,5)))
print(a(x).shape)
print(len(a.trainable_variables))
print(a.output_shape_zp)
a = UpSampaleConv2D([4,4,5],[10,10],1,kernel_size=(2,2),strides=(3,3),padding="SAME",sn=True)
x = tf.constant(tf.random.normal((1,4,4,5)))
print(a(x).shape)
print(len(a.trainable_variables))
print(a.output_shape_zp)
a = UpSampaleConv3D([4,4,4,5],[10,10,10],1,kernel_size=(2,2,2),strides=(3,3,3),padding="SAME",sn=True)
x = tf.constant(tf.random.normal((1,4,4,4,5)))
print(a(x).shape)
print(len(a.trainable_variables))
print(a.output_shape_zp)
a = UpSampaleConv3D([4,4,4,5],[7,7,7],1,kernel_size=(4,4,4),strides=(2,2,2),padding="SAME",sn=True)
x = tf.constant(tf.random.normal((1,4,4,4,5)))
print(a(x).shape)
print(len(a.trainable_variables))
print(a.output_shape_zp)
a = UpSampaleConv3D([4,4,4,5],[7,7,7],1,kernel_size=(2,2,2),strides=(2,2,2),padding="SAME",sn=True)
x = tf.constant(tf.random.normal((1,4,4,4,5)))
print(a(x).shape)
print(len(a.trainable_variables))
print(a.output_shape_zp)
| 46.910714
| 184
| 0.594468
| 3,206
| 23,643
| 4.214598
| 0.073612
| 0.038484
| 0.008881
| 0.023683
| 0.83807
| 0.828523
| 0.798919
| 0.787004
| 0.774645
| 0.74556
| 0
| 0.038437
| 0.260542
| 23,643
| 504
| 185
| 46.910714
| 0.734428
| 0.082858
| 0
| 0.705314
| 0
| 0
| 0.010508
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.067633
| false
| 0
| 0.012077
| 0
| 0.157005
| 0.128019
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
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|
0
| 7
|
96facba94ed9d53771093147d576884435d9a3af
| 20,831
|
py
|
Python
|
code/third_party/smoothadv.py
|
jh-jeong/smoothing-consistency
|
a11954aa91adb9924eecf49aaca74051e79bbb86
|
[
"MIT"
] | 28
|
2020-06-09T03:49:09.000Z
|
2022-03-19T00:27:12.000Z
|
code/third_party/smoothadv.py
|
jh-jeong/smoothing-consistency
|
a11954aa91adb9924eecf49aaca74051e79bbb86
|
[
"MIT"
] | null | null | null |
code/third_party/smoothadv.py
|
jh-jeong/smoothing-consistency
|
a11954aa91adb9924eecf49aaca74051e79bbb86
|
[
"MIT"
] | 2
|
2021-03-19T07:25:15.000Z
|
2021-08-12T08:41:16.000Z
|
# this file is copied from
# https://github.com/Hadisalman/smoothing-adversarial
# originally written by Hadi Salman.
from abc import ABCMeta, abstractmethod
import numpy as np
import torch
from torch.autograd import Variable
from torch.nn import CrossEntropyLoss
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from typing import Optional
class Attacker(metaclass=ABCMeta):
@abstractmethod
def attack(self, model, inputs, labels):
raise NotImplementedError
# Modification of the code from https://github.com/jeromerony/fast_adversarial
class PGD_L2(Attacker):
"""
PGD attack
Parameters
----------
steps : int
Number of steps for the optimization.
max_norm : float or None, optional
If specified, the norms of the perturbations will not be greater than this value which might lower success rate.
device : torch.device, optional
Device on which to perform the attack.
"""
def __init__(self,
steps: int,
random_start: bool = True,
max_norm: Optional[float] = None,
device: torch.device = torch.device('cpu')) -> None:
super(PGD_L2, self).__init__()
self.steps = steps
self.random_start = random_start
self.max_norm = max_norm
self.device = device
def attack(self, model: nn.Module, inputs: torch.Tensor, labels: torch.Tensor,
noise: torch.Tensor = None, num_noise_vectors=1, targeted: bool = False, no_grad=False) -> torch.Tensor:
if num_noise_vectors == 1:
return self._attack(model, inputs, labels, noise, targeted)
else:
if no_grad:
with torch.no_grad():
return self._attack_mutlinoise_no_grad(model, inputs, labels, noise, num_noise_vectors, targeted)
else:
return self._attack_mutlinoise(model, inputs, labels, noise, num_noise_vectors, targeted)
def _attack(self, model: nn.Module, inputs: torch.Tensor, labels: torch.Tensor,
noise: torch.Tensor = None, targeted: bool = False) -> torch.Tensor:
"""
Performs the attack of the model for the inputs and labels.
Parameters
----------
model : nn.Module
Model to attack.
inputs : torch.Tensor
Batch of samples to attack. Values should be in the [0, 1] range.
labels : torch.Tensor
Labels of the samples to attack if untargeted, else labels of targets.
targeted : bool, optional
Whether to perform a targeted attack or not.
Returns
-------
torch.Tensor
Batch of samples modified to be adversarial to the model.
"""
if inputs.min() < 0 or inputs.max() > 1: raise ValueError('Input values should be in the [0, 1] range.')
batch_size = inputs.shape[0]
multiplier = 1 if targeted else -1
delta = torch.zeros_like(inputs, requires_grad=True)
# Setup optimizers
optimizer = optim.SGD([delta], lr=self.max_norm / self.steps * 2)
for i in range(self.steps):
adv = inputs + delta
if noise is not None:
adv = adv + noise
logits = model(adv)
pred_labels = logits.argmax(1)
ce_loss = F.cross_entropy(logits, labels, reduction='sum')
loss = multiplier * ce_loss
optimizer.zero_grad()
loss.backward()
# renorming gradient
grad_norms = delta.grad.view(batch_size, -1).norm(p=2, dim=1)
delta.grad.div_(grad_norms.view(-1, 1, 1, 1))
# avoid nan or inf if gradient is 0
if (grad_norms == 0).any():
delta.grad[grad_norms == 0] = torch.randn_like(delta.grad[grad_norms == 0])
optimizer.step()
delta.data.add_(inputs)
delta.data.clamp_(0, 1).sub_(inputs)
delta.data.renorm_(p=2, dim=0, maxnorm=self.max_norm)
return inputs + delta
def _attack_mutlinoise(self, model: nn.Module, inputs: torch.Tensor, labels: torch.Tensor,
noise: torch.Tensor = None, num_noise_vectors: int = 1,
targeted: bool = False) -> torch.Tensor:
"""
Performs the attack of the model for the inputs and labels.
Parameters
----------
model : nn.Module
Model to attack.
inputs : torch.Tensor
Batch of samples to attack. Values should be in the [0, 1] range.
labels : torch.Tensor
Labels of the samples to attack if untargeted, else labels of targets.
targeted : bool, optional
Whether to perform a targeted attack or not.
Returns
-------
torch.Tensor
Batch of samples modified to be adversarial to the model.
"""
if inputs.min() < 0 or inputs.max() > 1: raise ValueError('Input values should be in the [0, 1] range.')
batch_size = labels.shape[0]
multiplier = 1 if targeted else -1
delta = torch.zeros((len(labels), *inputs.shape[1:]), requires_grad=True, device=self.device)
# Setup optimizers
optimizer = optim.SGD([delta], lr=self.max_norm / self.steps * 2)
for i in range(self.steps):
adv = inputs + delta.repeat(1, num_noise_vectors, 1, 1).view_as(inputs)
if noise is not None:
adv = adv + noise
logits = model(adv)
pred_labels = logits.argmax(1).reshape(-1, num_noise_vectors).mode(1)[0]
# safe softamx
softmax = F.softmax(logits, dim=1)
# average the probabilities across noise
average_softmax = softmax.reshape(-1, num_noise_vectors, logits.shape[-1]).mean(1, keepdim=True).squeeze(1)
logsoftmax = torch.log(average_softmax.clamp(min=1e-20))
ce_loss = F.nll_loss(logsoftmax, labels)
loss = multiplier * ce_loss
optimizer.zero_grad()
loss.backward()
# renorming gradient
grad_norms = delta.grad.view(batch_size, -1).norm(p=2, dim=1)
delta.grad.div_(grad_norms.view(-1, 1, 1, 1))
# avoid nan or inf if gradient is 0
if (grad_norms == 0).any():
delta.grad[grad_norms == 0] = torch.randn_like(delta.grad[grad_norms == 0])
optimizer.step()
delta.data.add_(inputs[::num_noise_vectors])
delta.data.clamp_(0, 1).sub_(inputs[::num_noise_vectors])
delta.data.renorm_(p=2, dim=0, maxnorm=self.max_norm)
return inputs + delta.repeat(1, num_noise_vectors, 1, 1).view_as(inputs)
def _attack_mutlinoise_no_grad(self, model: nn.Module, inputs: torch.Tensor, labels: torch.Tensor,
noise: torch.Tensor = None, num_noise_vectors: int = 1,
targeted: bool = False) -> torch.Tensor:
"""
Performs the attack of the model for the inputs and labels.
Parameters
----------
model : nn.Module
Model to attack.
inputs : torch.Tensor
Batch of samples to attack. Values should be in the [0, 1] range.
labels : torch.Tensor
Labels of the samples to attack if untargeted, else labels of targets.
targeted : bool, optional
Whether to perform a targeted attack or not.
Returns
-------
torch.Tensor
Batch of samples modified to be adversarial to the model.
"""
if inputs.min() < 0 or inputs.max() > 1: raise ValueError('Input values should be in the [0, 1] range.')
batch_size = labels.shape[0]
multiplier = 1 if targeted else -1
delta = torch.zeros((len(labels), *inputs.shape[1:]), requires_grad=True, device=self.device)
# Setup optimizers
optimizer = optim.SGD([delta], lr=self.max_norm / self.steps * 2)
for i in range(self.steps):
adv = inputs + delta.repeat(1, num_noise_vectors, 1, 1).view_as(inputs)
if noise is not None:
adv = adv + noise
logits = model(adv)
pred_labels = logits.argmax(1).reshape(-1, num_noise_vectors).mode(1)[0]
# safe softamx
softmax = F.softmax(logits, dim=1)
grad = F.nll_loss(softmax,
labels.unsqueeze(1).repeat(1, 1, num_noise_vectors).view(batch_size * num_noise_vectors),
reduction='none').repeat(*noise.shape[1:], 1).permute(3, 0, 1, 2) * noise
grad = grad.reshape(-1, num_noise_vectors, *inputs.shape[1:]).mean(1)
# average the probabilities across noise
grad_norms = grad.view(batch_size, -1).norm(p=2, dim=1)
grad.div_(grad_norms.view(-1, 1, 1, 1))
# avoid nan or inf if gradient is 0
if (grad_norms == 0).any():
grad[grad_norms == 0] = torch.randn_like(grad[grad_norms == 0])
# optimizer.step()
delta = delta + grad * self.max_norm / self.steps * 2
delta.data.add_(inputs[::num_noise_vectors])
delta.data.clamp_(0, 1).sub_(inputs[::num_noise_vectors])
delta.data.renorm_(p=2, dim=0, maxnorm=self.max_norm)
return inputs + delta.repeat(1, num_noise_vectors, 1, 1).view_as(inputs)
# Source code from https://github.com/jeromerony/fast_adversarial
class DDN(Attacker):
"""
DDN attack: decoupling the direction and norm of the perturbation to achieve a small L2 norm in few steps.
Parameters
----------
steps : int
Number of steps for the optimization.
gamma : float, optional
Factor by which the norm will be modified. new_norm = norm * (1 + or - gamma).
init_norm : float, optional
Initial value for the norm.
quantize : bool, optional
If True, the returned adversarials will have quantized values to the specified number of levels.
levels : int, optional
Number of levels to use for quantization (e.g. 256 for 8 bit images).
max_norm : float or None, optional
If specified, the norms of the perturbations will not be greater than this value which might lower success rate.
device : torch.device, optional
Device on which to perform the attack.
callback : object, optional
Visdom callback to display various metrics.
"""
def __init__(self,
steps: int,
gamma: float = 0.05,
init_norm: float = 1.,
quantize: bool = True,
levels: int = 256,
max_norm: Optional[float] = None,
device: torch.device = torch.device('cpu'),
callback: Optional = None) -> None:
super(DDN, self).__init__()
self.steps = steps
self.gamma = gamma
self.init_norm = init_norm
self.quantize = quantize
self.levels = levels
self.max_norm = max_norm
self.device = device
self.callback = callback
def attack(self, model: nn.Module, inputs: torch.Tensor, labels: torch.Tensor,
noise: torch.Tensor = None, num_noise_vectors=1, targeted: bool = False, no_grad=False) -> torch.Tensor:
if num_noise_vectors == 1:
return self._attack(model, inputs, labels, noise, targeted)
# return self._attack_mutlinoise(model, inputs, labels, noise, num_noise_vectors, targeted)
else:
if no_grad:
raise NotImplementedError
else:
return self._attack_mutlinoise(model, inputs, labels, noise, num_noise_vectors, targeted)
def _attack(self, model: nn.Module, inputs: torch.Tensor, labels: torch.Tensor,
noise: torch.Tensor = None, targeted: bool = False) -> torch.Tensor:
"""
Performs the attack of the model for the inputs and labels.
Parameters
----------
model : nn.Module
Model to attack.
inputs : torch.Tensor
Batch of samples to attack. Values should be in the [0, 1] range.
labels : torch.Tensor
Labels of the samples to attack if untargeted, else labels of targets.
targeted : bool, optional
Whether to perform a targeted attack or not.
Returns
-------
torch.Tensor
Batch of samples modified to be adversarial to the model.
"""
if inputs.min() < 0 or inputs.max() > 1: raise ValueError('Input values should be in the [0, 1] range.')
batch_size = inputs.shape[0]
multiplier = 1 if targeted else -1
delta = torch.zeros_like(inputs, requires_grad=True)
norm = torch.full((batch_size,), self.init_norm, device=self.device, dtype=torch.float)
worst_norm = torch.max(inputs, 1 - inputs).view(batch_size, -1).norm(p=2, dim=1)
# Setup optimizers
optimizer = optim.SGD([delta], lr=1)
scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=self.steps, eta_min=0.01)
best_l2 = worst_norm.clone()
best_delta = torch.zeros_like(inputs)
adv_found = torch.zeros(inputs.size(0), dtype=torch.uint8, device=self.device)
for i in range(self.steps):
scheduler.step()
l2 = delta.data.view(batch_size, -1).norm(p=2, dim=1)
adv = inputs + delta
if noise is not None:
adv = adv + noise
logits = model(adv)
pred_labels = logits.argmax(1)
ce_loss = F.cross_entropy(logits, labels, reduction='sum')
loss = multiplier * ce_loss
is_adv = (pred_labels == labels) if targeted else (pred_labels != labels)
is_smaller = l2 < best_l2
is_both = is_adv * is_smaller
adv_found[is_both] = 1
best_l2[is_both] = l2[is_both]
best_delta[is_both] = delta.data[is_both]
optimizer.zero_grad()
loss.backward()
# renorming gradient
grad_norms = delta.grad.view(batch_size, -1).norm(p=2, dim=1)
delta.grad.div_(grad_norms.view(-1, 1, 1, 1))
# avoid nan or inf if gradient is 0
if (grad_norms == 0).any():
delta.grad[grad_norms == 0] = torch.randn_like(delta.grad[grad_norms == 0])
if self.callback:
cosine = F.cosine_similarity(-delta.grad.view(batch_size, -1),
delta.data.view(batch_size, -1), dim=1).mean().item()
self.callback.scalar('ce', i, ce_loss.item() / batch_size)
self.callback.scalars(
['max_norm', 'l2', 'best_l2'], i,
[norm.mean().item(), l2.mean().item(),
best_l2[adv_found].mean().item() if adv_found.any() else norm.mean().item()]
)
self.callback.scalars(['cosine', 'lr', 'success'], i,
[cosine, optimizer.param_groups[0]['lr'], adv_found.float().mean().item()])
optimizer.step()
norm.mul_(1 - (2 * is_adv.float() - 1) * self.gamma)
norm = torch.min(norm, worst_norm)
delta.data.mul_((norm / delta.data.view(batch_size, -1).norm(2, 1)).view(-1, 1, 1, 1))
delta.data.add_(inputs)
if self.quantize:
delta.data.mul_(self.levels - 1).round_().div_(self.levels - 1)
delta.data.clamp_(0, 1).sub_(inputs)
if self.max_norm is not None:
best_delta.renorm_(p=2, dim=0, maxnorm=self.max_norm)
if self.quantize:
best_delta.mul_(self.levels - 1).round_().div_(self.levels - 1)
return inputs + best_delta
def _attack_mutlinoise(self, model: nn.Module, inputs: torch.Tensor, labels: torch.Tensor,
noise: torch.Tensor = None, num_noise_vectors: int = 1,
targeted: bool = False) -> torch.Tensor:
"""
Performs the attack of the model for the inputs and labels.
Parameters
----------
model : nn.Module
Model to attack.
inputs : torch.Tensor
Batch of samples to attack. Values should be in the [0, 1] range.
labels : torch.Tensor
Labels of the samples to attack if untargeted, else labels of targets.
targeted : bool, optional
Whether to perform a targeted attack or not.
Returns
-------
torch.Tensor
Batch of samples modified to be adversarial to the model.
"""
if inputs.min() < 0 or inputs.max() > 1: raise ValueError('Input values should be in the [0, 1] range.')
batch_size = labels.shape[0]
multiplier = 1 if targeted else -1
delta = torch.zeros((len(labels), *inputs.shape[1:]), requires_grad=True, device=self.device)
norm = torch.full((batch_size,), self.init_norm, device=self.device, dtype=torch.float)
worst_norm = torch.max(inputs[::num_noise_vectors], 1 - inputs[::num_noise_vectors]).view(batch_size, -1).norm(
p=2, dim=1)
# Setup optimizers
optimizer = optim.SGD([delta], lr=1)
scheduler = optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=self.steps, eta_min=0.01)
best_l2 = worst_norm.clone()
best_delta = torch.zeros_like(inputs[::num_noise_vectors])
adv_found = torch.zeros(inputs[::num_noise_vectors].size(0), dtype=torch.uint8, device=self.device)
for i in range(self.steps):
scheduler.step()
l2 = delta.data.view(batch_size, -1).norm(p=2, dim=1)
adv = inputs + delta.repeat(1, num_noise_vectors, 1, 1).view_as(inputs)
if noise is not None:
adv = adv + noise
logits = model(adv)
pred_labels = logits.argmax(1).reshape(-1, num_noise_vectors).mode(1)[0]
# safe softamx
softmax = F.softmax(logits, dim=1)
# average the probabilities across noise
average_softmax = softmax.reshape(-1, num_noise_vectors, logits.shape[-1]).mean(1, keepdim=True).squeeze(1)
logsoftmax = torch.log(average_softmax.clamp(min=1e-20))
ce_loss = F.nll_loss(logsoftmax, labels)
loss = multiplier * ce_loss
is_adv = (pred_labels == labels) if targeted else (pred_labels != labels)
is_smaller = l2 < best_l2
is_both = is_adv * is_smaller
adv_found[is_both] = 1
best_l2[is_both] = l2[is_both]
best_delta[is_both] = delta.data[is_both]
optimizer.zero_grad()
loss.backward()
# renorming gradient
grad_norms = delta.grad.view(batch_size, -1).norm(p=2, dim=1)
delta.grad.div_(grad_norms.view(-1, 1, 1, 1))
# avoid nan or inf if gradient is 0
if (grad_norms == 0).any():
delta.grad[grad_norms == 0] = torch.randn_like(delta.grad[grad_norms == 0])
if self.callback:
cosine = F.cosine_similarity(-delta.grad.view(batch_size, -1),
delta.data.view(batch_size, -1), dim=1).mean().item()
self.callback.scalar('ce', i, ce_loss.item() / batch_size)
self.callback.scalars(
['max_norm', 'l2', 'best_l2'], i,
[norm.mean().item(), l2.mean().item(),
best_l2[adv_found].mean().item() if adv_found.any() else norm.mean().item()]
)
self.callback.scalars(['cosine', 'lr', 'success'], i,
[cosine, optimizer.param_groups[0]['lr'], adv_found.float().mean().item()])
optimizer.step()
norm.mul_(1 - (2 * is_adv.float() - 1) * self.gamma)
norm = torch.min(norm, worst_norm)
delta.data.mul_((norm / delta.data.view(batch_size, -1).norm(2, 1)).view(-1, 1, 1, 1))
delta.data.add_(inputs[::num_noise_vectors])
if self.quantize:
delta.data.mul_(self.levels - 1).round_().div_(self.levels - 1)
delta.data.clamp_(0, 1).sub_(inputs[::num_noise_vectors])
if self.max_norm is not None:
best_delta.renorm_(p=2, dim=0, maxnorm=self.max_norm)
if self.quantize:
best_delta.mul_(self.levels - 1).round_().div_(self.levels - 1)
return inputs + best_delta.repeat(1, num_noise_vectors, 1, 1).view_as(inputs)
| 40.845098
| 120
| 0.579569
| 2,671
| 20,831
| 4.385623
| 0.090603
| 0.040379
| 0.044818
| 0.017927
| 0.878948
| 0.867936
| 0.855045
| 0.846508
| 0.840703
| 0.819276
| 0
| 0.020456
| 0.310067
| 20,831
| 510
| 121
| 40.845098
| 0.794601
| 0.21276
| 0
| 0.802974
| 0
| 0
| 0.019477
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.037175
| false
| 0
| 0.033457
| 0
| 0.118959
| 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
|
96fdff79494b34cb3d248986bf9ac79c9c0d573b
| 1,692
|
py
|
Python
|
src/spanishconjugator/tenses/indicative/imperfect.py
|
shrutiichandra/spanish-conjugator
|
2ebf41b92c14c3e47a873c52fdf4ce1d17bff5e0
|
[
"MIT"
] | null | null | null |
src/spanishconjugator/tenses/indicative/imperfect.py
|
shrutiichandra/spanish-conjugator
|
2ebf41b92c14c3e47a873c52fdf4ce1d17bff5e0
|
[
"MIT"
] | null | null | null |
src/spanishconjugator/tenses/indicative/imperfect.py
|
shrutiichandra/spanish-conjugator
|
2ebf41b92c14c3e47a873c52fdf4ce1d17bff5e0
|
[
"MIT"
] | null | null | null |
# -*- coding: iso-8859-15 -*-
def indicative_imperfect(root_verb, pronoun):
if pronoun == "yo":
if root_verb[-2:] == "ar":
conjugation = root_verb[:-2] + "aba"
return conjugation
if root_verb[-2:] == "er" or "ir":
conjugation = root_verb[:-2] + "ía"
return conjugation
if pronoun == "tu":
if root_verb[-2:] == "ar":
conjugation = root_verb[:-2] + "abas"
return conjugation
if root_verb[-2:] == "er" or "ir":
conjugation = root_verb[:-2] + "ías"
return conjugation
if pronoun == "usted":
if root_verb[-2:] == "ar":
conjugation = root_verb[:-2] + "aba"
return conjugation
if root_verb[-2:] == "er" or "ir":
conjugation = root_verb[:-2] + "ía"
return conjugation
if pronoun == "nosotros":
if root_verb[-2:] == "ar":
conjugation = root_verb[:-2] + "ábamos"
return conjugation
if root_verb[-2:] == "er" or "ir":
conjugation = root_verb[:-2] + "íamos"
return conjugation
if pronoun == "vosotros":
if root_verb[-2:] == "ar":
conjugation = root_verb[:-2] + "abais"
return conjugation
if root_verb[-2:] == "er" or "ir":
conjugation = root_verb[:-2] + "íais"
return conjugation
if pronoun == "ustedes":
if root_verb[-2:] == "ar":
conjugation = root_verb[:-2] + "aban"
return conjugation
if root_verb[-2:] == "er" or "ir":
conjugation = root_verb[:-2] + "ían"
return conjugation
| 34.530612
| 51
| 0.491726
| 184
| 1,692
| 4.380435
| 0.184783
| 0.248139
| 0.26799
| 0.163772
| 0.724566
| 0.724566
| 0.724566
| 0.724566
| 0.724566
| 0.560794
| 0
| 0.027473
| 0.35461
| 1,692
| 49
| 52
| 34.530612
| 0.710623
| 0.015957
| 0
| 0.651163
| 0
| 0
| 0.067308
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.023256
| false
| 0
| 0
| 0
| 0.302326
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 1
| 1
| 1
| 1
| 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
| 0
| 0
| 0
| 0
|
0
| 7
|
96fe6e8532376500d8048bb25a59ea25d176e140
| 4,089
|
py
|
Python
|
Posi-Nega-Neutra_Tagged-Sentence-Parsing.py
|
elisa-aleman/Entropy-Based-SVM
|
b67a056a3bae3c8b2a9e330693878ffd0bd31772
|
[
"MIT"
] | 1
|
2021-12-19T02:07:27.000Z
|
2021-12-19T02:07:27.000Z
|
Posi-Nega-Neutra_Tagged-Sentence-Parsing.py
|
elisa-aleman/Entropy-Based-SVM
|
b67a056a3bae3c8b2a9e330693878ffd0bd31772
|
[
"MIT"
] | null | null | null |
Posi-Nega-Neutra_Tagged-Sentence-Parsing.py
|
elisa-aleman/Entropy-Based-SVM
|
b67a056a3bae3c8b2a9e330693878ffd0bd31772
|
[
"MIT"
] | null | null | null |
#-*- coding: utf-8 -*-
####################################
########## Training Data ##########
####################################
def PosiNegaSentences(comment):
'''
Input is "word word <positive> word word word </positive> <negative> word word word </negative> word ..."
Returns a list of sentences in the format ['word word word',1] if positive or ['word word word', 0] if negative
'''
comment = comment.split()
# The comment has been reduced to a list of words including the tags
sentences = []
sentence = []
att = 0
positive = False
negative = False
for current_word in comment:
skip = False
if (current_word == '<positive>'):
positive = True
negative = False
skip = True
if (current_word == '</positive>'):
positive = True
skip = True
if (current_word == '<negative>'):
positive = False
negative = True
skip = True
if (current_word == '</negative>'):
negative = True
skip = True
if not skip:
if positive or negative:
sentence.append(current_word)
else:
if len(sentence)>0:
if positive and not negative:
att = 1
sentence = " ".join(sentence).strip()
sentences.append([sentence,att])
positive = False
elif negative and not positive:
att = 0
sentence = " ".join(sentence).strip()
sentences.append([sentence,att])
negative = False
sentence = []
return sentences
def PosiNegaNeutraSentences(comment):
'''
Input is "<neutral> word word </neutral> <positive> word word word </positive> <negative> word word word </negative> word ..."
Returns a list of sentences in the format
['word word word', 1] if positive
or ['word word word', 0] if neutral
or ['word word word', -1] if negative
'''
comment = comment.split()
# The comment has been reduced to a list of words including the tags
sentences = []
sentence = []
att = 0
positive = False
negative = False
neutral = False
for current_word in comment:
skip = False
if (current_word == '<positive>'):
positive = True
negative = False
neutral = False
skip = True
if (current_word == '</positive>'):
positive = True
skip = True
if (current_word == '<negative>'):
positive = False
neutral = False
negative = True
skip = True
if (current_word == '</negative>'):
negative = True
skip = True
if (current_word == '<neutral>'):
positive = False
neutral = True
negative = False
skip = True
if (current_word == '</neutral>'):
neutral = True
skip = True
if not skip:
if positive or negative or neutral:
sentence.append(current_word)
else:
if len(sentence)>0:
if positive and not negative and not neutral:
att = 1
sentence = " ".join(sentence).strip()
sentences.append([sentence,att])
positive = False
elif negative and not positive and not neutral:
att = -1
sentence = " ".join(sentence).strip()
sentences.append([sentence,att])
negative = False
elif neutral and not positive and not negative:
att = 0
sentence = " ".join(sentence).strip()
sentences.append([sentence,att])
neutral = False
sentence = []
return sentences
if __name__ == '__main__':
pass
| 33.516393
| 130
| 0.488383
| 390
| 4,089
| 5.064103
| 0.138462
| 0.081013
| 0.065823
| 0.068861
| 0.860759
| 0.84
| 0.832911
| 0.827342
| 0.808101
| 0.808101
| 0
| 0.00611
| 0.399609
| 4,089
| 121
| 131
| 33.793388
| 0.798371
| 0.164832
| 0
| 0.857143
| 0
| 0
| 0.035561
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.020408
| false
| 0.010204
| 0
| 0
| 0.040816
| 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
|
8c178de8d85ee1b6747f4086ba20b9af813f9c91
| 161
|
py
|
Python
|
boa3_test/test_sc/native_test/stdlib/SerializeBool.py
|
OnBlockIO/neo3-boa
|
cb317292a67532a52ed26f2b0f0f7d0b10ac5f5f
|
[
"Apache-2.0"
] | 25
|
2020-07-22T19:37:43.000Z
|
2022-03-08T03:23:55.000Z
|
boa3_test/test_sc/native_test/stdlib/SerializeBool.py
|
OnBlockIO/neo3-boa
|
cb317292a67532a52ed26f2b0f0f7d0b10ac5f5f
|
[
"Apache-2.0"
] | 419
|
2020-04-23T17:48:14.000Z
|
2022-03-31T13:17:45.000Z
|
boa3_test/test_sc/native_test/stdlib/SerializeBool.py
|
OnBlockIO/neo3-boa
|
cb317292a67532a52ed26f2b0f0f7d0b10ac5f5f
|
[
"Apache-2.0"
] | 15
|
2020-05-21T21:54:24.000Z
|
2021-11-18T06:17:24.000Z
|
from boa3.builtin import public
from boa3.builtin.nativecontract.stdlib import StdLib
@public
def serialize_bool() -> bytes:
return StdLib.serialize(True)
| 20.125
| 53
| 0.78882
| 21
| 161
| 6
| 0.619048
| 0.126984
| 0.238095
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.014286
| 0.130435
| 161
| 7
| 54
| 23
| 0.885714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 0
| 0.4
| 0.2
| 0.8
| 0
| 1
| 0
| 0
| null | 0
| 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
| 1
| 1
| 0
|
0
| 7
|
8c3759a523ce1c92d319eff1b5a83f36388114f0
| 614
|
py
|
Python
|
lib2/pin.py
|
offdhymaz/wa
|
fc05f1f7be443c45182f47c8d13a870149dbdd17
|
[
"MIT"
] | 37
|
2020-10-05T17:12:02.000Z
|
2022-03-07T14:53:35.000Z
|
lib2/pin.py
|
INIDboyzz/Juliana
|
b768e7d4aa13eb1a97e8d8df7e331b99b8b082fb
|
[
"MIT"
] | 24
|
2020-10-08T15:56:18.000Z
|
2022-03-15T00:16:25.000Z
|
lib2/pin.py
|
INIDboyzz/Juliana
|
b768e7d4aa13eb1a97e8d8df7e331b99b8b082fb
|
[
"MIT"
] | 44
|
2020-10-10T12:58:24.000Z
|
2022-02-09T13:58:01.000Z
|
import re, requests
def pinterest(url):
m=requests.get(url)
if re.search("https://v.pinimg.com/videos/mc/(.*?).mp4",m.text):
if '"' in re.search("https://v.pinimg.com/videos/mc/(.*?).mp4",m.text)[0]:
return re.search("https://i.pinimg.com/originals/(.*?)\" as\=\"image\"",m.text)[0][:-12]
else:
return re.search("https://v.pinimg.com/videos/mc/(.*?).mp4",m.text)[0]
elif re.search("https://i.pinimg.com/originals/(.*?)\" as\=\"image\"",m.text):
return re.search("https://i.pinimg.com/originals/(.*?)\" as\=\"image\"",m.text)[0][:-12]
else:
''
| 51.166667
| 100
| 0.552117
| 91
| 614
| 3.725275
| 0.307692
| 0.141593
| 0.230089
| 0.123894
| 0.817109
| 0.817109
| 0.817109
| 0.817109
| 0.817109
| 0.817109
| 0
| 0.021277
| 0.15798
| 614
| 12
| 101
| 51.166667
| 0.634429
| 0
| 0
| 0.333333
| 0
| 0
| 0.406504
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.083333
| false
| 0
| 0.083333
| 0
| 0.416667
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
4fff0639bc18f31a1d23cff6dd8c185ed2d0c6fb
| 37,012
|
py
|
Python
|
nova/tests/unit/virt/disk/vfs/test_localfs.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/virt/disk/vfs/test_localfs.py
|
bopopescu/nova-token
|
ec98f69dea7b3e2b9013b27fd55a2c1a1ac6bfb2
|
[
"Apache-2.0"
] | null | null | null |
nova/tests/unit/virt/disk/vfs/test_localfs.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 (C) 2012 Red Hat, Inc.'
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|'tempfile'
newline|'\n'
nl|'\n'
name|'import'
name|'mock'
newline|'\n'
name|'from'
name|'oslo_concurrency'
name|'import'
name|'processutils'
newline|'\n'
nl|'\n'
name|'from'
name|'nova'
name|'import'
name|'exception'
newline|'\n'
name|'from'
name|'nova'
name|'import'
name|'test'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'tests'
op|'.'
name|'unit'
name|'import'
name|'utils'
name|'as'
name|'tests_utils'
newline|'\n'
name|'import'
name|'nova'
op|'.'
name|'utils'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'virt'
op|'.'
name|'disk'
op|'.'
name|'mount'
name|'import'
name|'nbd'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'virt'
op|'.'
name|'disk'
op|'.'
name|'vfs'
name|'import'
name|'localfs'
name|'as'
name|'vfsimpl'
newline|'\n'
name|'from'
name|'nova'
op|'.'
name|'virt'
op|'.'
name|'image'
name|'import'
name|'model'
name|'as'
name|'imgmodel'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|variable|dirs
name|'dirs'
op|'='
op|'['
op|']'
newline|'\n'
DECL|variable|files
name|'files'
op|'='
op|'{'
op|'}'
newline|'\n'
DECL|variable|commands
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|fake_execute
name|'def'
name|'fake_execute'
op|'('
op|'*'
name|'args'
op|','
op|'**'
name|'kwargs'
op|')'
op|':'
newline|'\n'
indent|' '
name|'commands'
op|'.'
name|'append'
op|'('
op|'{'
string|'"args"'
op|':'
name|'args'
op|','
string|'"kwargs"'
op|':'
name|'kwargs'
op|'}'
op|')'
newline|'\n'
nl|'\n'
name|'if'
name|'args'
op|'['
number|'0'
op|']'
op|'=='
string|'"readlink"'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'args'
op|'['
number|'1'
op|']'
op|'=='
string|'"-nm"'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'args'
op|'['
number|'2'
op|']'
name|'in'
op|'['
string|'"/scratch/dir/some/file"'
op|','
nl|'\n'
string|'"/scratch/dir/some/dir"'
op|','
nl|'\n'
string|'"/scratch/dir/other/dir"'
op|','
nl|'\n'
string|'"/scratch/dir/other/file"'
op|']'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'args'
op|'['
number|'2'
op|']'
op|','
string|'""'
newline|'\n'
dedent|''
dedent|''
name|'elif'
name|'args'
op|'['
number|'1'
op|']'
op|'=='
string|'"-e"'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'args'
op|'['
number|'2'
op|']'
name|'in'
name|'files'
op|':'
newline|'\n'
indent|' '
name|'return'
name|'args'
op|'['
number|'2'
op|']'
op|','
string|'""'
newline|'\n'
nl|'\n'
dedent|''
dedent|''
name|'return'
string|'""'
op|','
string|'"No such file"'
newline|'\n'
dedent|''
name|'elif'
name|'args'
op|'['
number|'0'
op|']'
op|'=='
string|'"mkdir"'
op|':'
newline|'\n'
indent|' '
name|'dirs'
op|'.'
name|'append'
op|'('
name|'args'
op|'['
number|'2'
op|']'
op|')'
newline|'\n'
dedent|''
name|'elif'
name|'args'
op|'['
number|'0'
op|']'
op|'=='
string|'"chown"'
op|':'
newline|'\n'
indent|' '
name|'owner'
op|'='
name|'args'
op|'['
number|'1'
op|']'
newline|'\n'
name|'path'
op|'='
name|'args'
op|'['
number|'2'
op|']'
newline|'\n'
name|'if'
name|'path'
name|'not'
name|'in'
name|'files'
op|':'
newline|'\n'
indent|' '
name|'raise'
name|'Exception'
op|'('
string|'"No such file: "'
op|'+'
name|'path'
op|')'
newline|'\n'
nl|'\n'
dedent|''
name|'sep'
op|'='
name|'owner'
op|'.'
name|'find'
op|'('
string|"':'"
op|')'
newline|'\n'
name|'if'
name|'sep'
op|'!='
op|'-'
number|'1'
op|':'
newline|'\n'
indent|' '
name|'user'
op|'='
name|'owner'
op|'['
number|'0'
op|':'
name|'sep'
op|']'
newline|'\n'
name|'group'
op|'='
name|'owner'
op|'['
name|'sep'
op|'+'
number|'1'
op|':'
op|']'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'user'
op|'='
name|'owner'
newline|'\n'
name|'group'
op|'='
name|'None'
newline|'\n'
nl|'\n'
dedent|''
name|'if'
name|'user'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'user'
op|'=='
string|'"fred"'
op|':'
newline|'\n'
indent|' '
name|'uid'
op|'='
number|'105'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'uid'
op|'='
number|'110'
newline|'\n'
dedent|''
name|'files'
op|'['
name|'path'
op|']'
op|'['
string|'"uid"'
op|']'
op|'='
name|'uid'
newline|'\n'
dedent|''
name|'if'
name|'group'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'group'
op|'=='
string|'"users"'
op|':'
newline|'\n'
indent|' '
name|'gid'
op|'='
number|'500'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'gid'
op|'='
number|'600'
newline|'\n'
dedent|''
name|'files'
op|'['
name|'path'
op|']'
op|'['
string|'"gid"'
op|']'
op|'='
name|'gid'
newline|'\n'
dedent|''
dedent|''
name|'elif'
name|'args'
op|'['
number|'0'
op|']'
op|'=='
string|'"chgrp"'
op|':'
newline|'\n'
indent|' '
name|'group'
op|'='
name|'args'
op|'['
number|'1'
op|']'
newline|'\n'
name|'path'
op|'='
name|'args'
op|'['
number|'2'
op|']'
newline|'\n'
name|'if'
name|'path'
name|'not'
name|'in'
name|'files'
op|':'
newline|'\n'
indent|' '
name|'raise'
name|'Exception'
op|'('
string|'"No such file: "'
op|'+'
name|'path'
op|')'
newline|'\n'
nl|'\n'
dedent|''
name|'if'
name|'group'
op|'=='
string|'"users"'
op|':'
newline|'\n'
indent|' '
name|'gid'
op|'='
number|'500'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'gid'
op|'='
number|'600'
newline|'\n'
dedent|''
name|'files'
op|'['
name|'path'
op|']'
op|'['
string|'"gid"'
op|']'
op|'='
name|'gid'
newline|'\n'
dedent|''
name|'elif'
name|'args'
op|'['
number|'0'
op|']'
op|'=='
string|'"chmod"'
op|':'
newline|'\n'
indent|' '
name|'mode'
op|'='
name|'args'
op|'['
number|'1'
op|']'
newline|'\n'
name|'path'
op|'='
name|'args'
op|'['
number|'2'
op|']'
newline|'\n'
name|'if'
name|'path'
name|'not'
name|'in'
name|'files'
op|':'
newline|'\n'
indent|' '
name|'raise'
name|'Exception'
op|'('
string|'"No such file: "'
op|'+'
name|'path'
op|')'
newline|'\n'
nl|'\n'
dedent|''
name|'files'
op|'['
name|'path'
op|']'
op|'['
string|'"mode"'
op|']'
op|'='
name|'int'
op|'('
name|'mode'
op|','
number|'8'
op|')'
newline|'\n'
dedent|''
name|'elif'
name|'args'
op|'['
number|'0'
op|']'
op|'=='
string|'"cat"'
op|':'
newline|'\n'
indent|' '
name|'path'
op|'='
name|'args'
op|'['
number|'1'
op|']'
newline|'\n'
name|'if'
name|'path'
name|'not'
name|'in'
name|'files'
op|':'
newline|'\n'
indent|' '
name|'files'
op|'['
name|'path'
op|']'
op|'='
op|'{'
nl|'\n'
string|'"content"'
op|':'
string|'"Hello World"'
op|','
nl|'\n'
string|'"gid"'
op|':'
number|'100'
op|','
nl|'\n'
string|'"uid"'
op|':'
number|'100'
op|','
nl|'\n'
string|'"mode"'
op|':'
number|'0o700'
nl|'\n'
op|'}'
newline|'\n'
dedent|''
name|'return'
name|'files'
op|'['
name|'path'
op|']'
op|'['
string|'"content"'
op|']'
op|','
string|'""'
newline|'\n'
dedent|''
name|'elif'
name|'args'
op|'['
number|'0'
op|']'
op|'=='
string|'"tee"'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'args'
op|'['
number|'1'
op|']'
op|'=='
string|'"-a"'
op|':'
newline|'\n'
indent|' '
name|'path'
op|'='
name|'args'
op|'['
number|'2'
op|']'
newline|'\n'
name|'append'
op|'='
name|'True'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'path'
op|'='
name|'args'
op|'['
number|'1'
op|']'
newline|'\n'
name|'append'
op|'='
name|'False'
newline|'\n'
dedent|''
name|'if'
name|'path'
name|'not'
name|'in'
name|'files'
op|':'
newline|'\n'
indent|' '
name|'files'
op|'['
name|'path'
op|']'
op|'='
op|'{'
nl|'\n'
string|'"content"'
op|':'
string|'"Hello World"'
op|','
nl|'\n'
string|'"gid"'
op|':'
number|'100'
op|','
nl|'\n'
string|'"uid"'
op|':'
number|'100'
op|','
nl|'\n'
string|'"mode"'
op|':'
number|'0o700'
op|','
nl|'\n'
op|'}'
newline|'\n'
dedent|''
name|'if'
name|'append'
op|':'
newline|'\n'
indent|' '
name|'files'
op|'['
name|'path'
op|']'
op|'['
string|'"content"'
op|']'
op|'+='
name|'kwargs'
op|'['
string|'"process_input"'
op|']'
newline|'\n'
dedent|''
name|'else'
op|':'
newline|'\n'
indent|' '
name|'files'
op|'['
name|'path'
op|']'
op|'['
string|'"content"'
op|']'
op|'='
name|'kwargs'
op|'['
string|'"process_input"'
op|']'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|VirtDiskVFSLocalFSTestPaths
dedent|''
dedent|''
dedent|''
name|'class'
name|'VirtDiskVFSLocalFSTestPaths'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'VirtDiskVFSLocalFSTestPaths'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'real_execute'
op|'='
name|'processutils'
op|'.'
name|'execute'
newline|'\n'
nl|'\n'
DECL|function|nonroot_execute
name|'def'
name|'nonroot_execute'
op|'('
op|'*'
name|'cmd_parts'
op|','
op|'**'
name|'kwargs'
op|')'
op|':'
newline|'\n'
indent|' '
name|'kwargs'
op|'.'
name|'pop'
op|'('
string|"'run_as_root'"
op|','
name|'None'
op|')'
newline|'\n'
name|'return'
name|'real_execute'
op|'('
op|'*'
name|'cmd_parts'
op|','
op|'**'
name|'kwargs'
op|')'
newline|'\n'
nl|'\n'
dedent|''
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'nonroot_execute'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'rawfile'
op|'='
name|'imgmodel'
op|'.'
name|'LocalFileImage'
op|'('
string|'"/dummy.img"'
op|','
nl|'\n'
name|'imgmodel'
op|'.'
name|'FORMAT_RAW'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_check_safe_path
dedent|''
name|'def'
name|'test_check_safe_path'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'not'
name|'tests_utils'
op|'.'
name|'coreutils_readlink_available'
op|'('
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'skipTest'
op|'('
string|'"coreutils readlink(1) unavailable"'
op|')'
newline|'\n'
dedent|''
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'rawfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/foo"'
newline|'\n'
name|'ret'
op|'='
name|'vfs'
op|'.'
name|'_canonical_path'
op|'('
string|"'etc/something.conf'"
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'ret'
op|','
string|"'/foo/etc/something.conf'"
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_check_unsafe_path
dedent|''
name|'def'
name|'test_check_unsafe_path'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'if'
name|'not'
name|'tests_utils'
op|'.'
name|'coreutils_readlink_available'
op|'('
op|')'
op|':'
newline|'\n'
indent|' '
name|'self'
op|'.'
name|'skipTest'
op|'('
string|'"coreutils readlink(1) unavailable"'
op|')'
newline|'\n'
dedent|''
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'rawfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/foo"'
newline|'\n'
name|'self'
op|'.'
name|'assertRaises'
op|'('
name|'exception'
op|'.'
name|'Invalid'
op|','
nl|'\n'
name|'vfs'
op|'.'
name|'_canonical_path'
op|','
nl|'\n'
string|"'etc/../../../something.conf'"
op|')'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|class|VirtDiskVFSLocalFSTest
dedent|''
dedent|''
name|'class'
name|'VirtDiskVFSLocalFSTest'
op|'('
name|'test'
op|'.'
name|'NoDBTestCase'
op|')'
op|':'
newline|'\n'
DECL|member|setUp
indent|' '
name|'def'
name|'setUp'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'super'
op|'('
name|'VirtDiskVFSLocalFSTest'
op|','
name|'self'
op|')'
op|'.'
name|'setUp'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'qcowfile'
op|'='
name|'imgmodel'
op|'.'
name|'LocalFileImage'
op|'('
string|'"/dummy.qcow2"'
op|','
nl|'\n'
name|'imgmodel'
op|'.'
name|'FORMAT_QCOW2'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'rawfile'
op|'='
name|'imgmodel'
op|'.'
name|'LocalFileImage'
op|'('
string|'"/dummy.img"'
op|','
nl|'\n'
name|'imgmodel'
op|'.'
name|'FORMAT_RAW'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_makepath
dedent|''
name|'def'
name|'test_makepath'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'global'
name|'dirs'
op|','
name|'commands'
newline|'\n'
name|'dirs'
op|'='
op|'['
op|']'
newline|'\n'
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'fake_execute'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/scratch/dir"'
newline|'\n'
name|'vfs'
op|'.'
name|'make_path'
op|'('
string|'"/some/dir"'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'make_path'
op|'('
string|'"/other/dir"'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'dirs'
op|','
nl|'\n'
op|'['
string|'"/scratch/dir/some/dir"'
op|','
string|'"/scratch/dir/other/dir"'
op|']'
op|')'
op|','
newline|'\n'
nl|'\n'
name|'root_helper'
op|'='
name|'nova'
op|'.'
name|'utils'
op|'.'
name|'get_root_helper'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'commands'
op|','
nl|'\n'
op|'['
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/dir'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'mkdir'"
op|','
string|"'-p'"
op|','
nl|'\n'
string|"'/scratch/dir/some/dir'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/other/dir'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'mkdir'"
op|','
string|"'-p'"
op|','
nl|'\n'
string|"'/scratch/dir/other/dir'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_append_file
dedent|''
name|'def'
name|'test_append_file'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'global'
name|'files'
op|','
name|'commands'
newline|'\n'
name|'files'
op|'='
op|'{'
op|'}'
newline|'\n'
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'fake_execute'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/scratch/dir"'
newline|'\n'
name|'vfs'
op|'.'
name|'append_file'
op|'('
string|'"/some/file"'
op|','
string|'" Goodbye"'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|'"/scratch/dir/some/file"'
op|','
name|'files'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"content"'
op|']'
op|','
nl|'\n'
string|'"Hello World Goodbye"'
op|')'
newline|'\n'
nl|'\n'
name|'root_helper'
op|'='
name|'nova'
op|'.'
name|'utils'
op|'.'
name|'get_root_helper'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'commands'
op|','
nl|'\n'
op|'['
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'tee'"
op|','
string|"'-a'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'process_input'"
op|':'
string|"' Goodbye'"
op|','
nl|'\n'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_replace_file
dedent|''
name|'def'
name|'test_replace_file'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'global'
name|'files'
op|','
name|'commands'
newline|'\n'
name|'files'
op|'='
op|'{'
op|'}'
newline|'\n'
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'fake_execute'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/scratch/dir"'
newline|'\n'
name|'vfs'
op|'.'
name|'replace_file'
op|'('
string|'"/some/file"'
op|','
string|'"Goodbye"'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertIn'
op|'('
string|'"/scratch/dir/some/file"'
op|','
name|'files'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"content"'
op|']'
op|','
nl|'\n'
string|'"Goodbye"'
op|')'
newline|'\n'
nl|'\n'
name|'root_helper'
op|'='
name|'nova'
op|'.'
name|'utils'
op|'.'
name|'get_root_helper'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'commands'
op|','
nl|'\n'
op|'['
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'tee'"
op|','
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'process_input'"
op|':'
string|"'Goodbye'"
op|','
nl|'\n'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_read_file
dedent|''
name|'def'
name|'test_read_file'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'global'
name|'commands'
op|','
name|'files'
newline|'\n'
name|'files'
op|'='
op|'{'
op|'}'
newline|'\n'
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'fake_execute'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/scratch/dir"'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'vfs'
op|'.'
name|'read_file'
op|'('
string|'"/some/file"'
op|')'
op|','
string|'"Hello World"'
op|')'
newline|'\n'
nl|'\n'
name|'root_helper'
op|'='
name|'nova'
op|'.'
name|'utils'
op|'.'
name|'get_root_helper'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'commands'
op|','
nl|'\n'
op|'['
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'cat'"
op|','
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_has_file
dedent|''
name|'def'
name|'test_has_file'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'global'
name|'commands'
op|','
name|'files'
newline|'\n'
name|'files'
op|'='
op|'{'
op|'}'
newline|'\n'
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'fake_execute'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/scratch/dir"'
newline|'\n'
name|'vfs'
op|'.'
name|'read_file'
op|'('
string|'"/some/file"'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertTrue'
op|'('
name|'vfs'
op|'.'
name|'has_file'
op|'('
string|'"/some/file"'
op|')'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertFalse'
op|'('
name|'vfs'
op|'.'
name|'has_file'
op|'('
string|'"/other/file"'
op|')'
op|')'
newline|'\n'
nl|'\n'
name|'root_helper'
op|'='
name|'nova'
op|'.'
name|'utils'
op|'.'
name|'get_root_helper'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'commands'
op|','
nl|'\n'
op|'['
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'cat'"
op|','
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-e'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/other/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-e'"
op|','
nl|'\n'
string|"'/scratch/dir/other/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_set_permissions
dedent|''
name|'def'
name|'test_set_permissions'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'global'
name|'commands'
op|','
name|'files'
newline|'\n'
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
name|'files'
op|'='
op|'{'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'fake_execute'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/scratch/dir"'
newline|'\n'
name|'vfs'
op|'.'
name|'read_file'
op|'('
string|'"/some/file"'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'.'
name|'set_permissions'
op|'('
string|'"/some/file"'
op|','
number|'0o777'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"mode"'
op|']'
op|','
number|'0o777'
op|')'
newline|'\n'
nl|'\n'
name|'root_helper'
op|'='
name|'nova'
op|'.'
name|'utils'
op|'.'
name|'get_root_helper'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'commands'
op|','
nl|'\n'
op|'['
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'cat'"
op|','
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'chmod'"
op|','
string|"'777'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|']'
op|')'
newline|'\n'
nl|'\n'
DECL|member|test_set_ownership
dedent|''
name|'def'
name|'test_set_ownership'
op|'('
name|'self'
op|')'
op|':'
newline|'\n'
indent|' '
name|'global'
name|'commands'
op|','
name|'files'
newline|'\n'
name|'commands'
op|'='
op|'['
op|']'
newline|'\n'
name|'files'
op|'='
op|'{'
op|'}'
newline|'\n'
name|'self'
op|'.'
name|'stubs'
op|'.'
name|'Set'
op|'('
name|'processutils'
op|','
string|"'execute'"
op|','
name|'fake_execute'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'imgdir'
op|'='
string|'"/scratch/dir"'
newline|'\n'
name|'vfs'
op|'.'
name|'read_file'
op|'('
string|'"/some/file"'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"uid"'
op|']'
op|','
number|'100'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"gid"'
op|']'
op|','
number|'100'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'.'
name|'set_ownership'
op|'('
string|'"/some/file"'
op|','
string|'"fred"'
op|','
name|'None'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"uid"'
op|']'
op|','
number|'105'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"gid"'
op|']'
op|','
number|'100'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'.'
name|'set_ownership'
op|'('
string|'"/some/file"'
op|','
name|'None'
op|','
string|'"users"'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"uid"'
op|']'
op|','
number|'105'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"gid"'
op|']'
op|','
number|'500'
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'.'
name|'set_ownership'
op|'('
string|'"/some/file"'
op|','
string|'"joe"'
op|','
string|'"admins"'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"uid"'
op|']'
op|','
number|'110'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'files'
op|'['
string|'"/scratch/dir/some/file"'
op|']'
op|'['
string|'"gid"'
op|']'
op|','
number|'600'
op|')'
newline|'\n'
nl|'\n'
name|'root_helper'
op|'='
name|'nova'
op|'.'
name|'utils'
op|'.'
name|'get_root_helper'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
name|'commands'
op|','
nl|'\n'
op|'['
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'cat'"
op|','
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'chown'"
op|','
string|"'fred'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'chgrp'"
op|','
string|"'users'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'readlink'"
op|','
string|"'-nm'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|','
nl|'\n'
op|'{'
string|"'args'"
op|':'
op|'('
string|"'chown'"
op|','
string|"'joe:admins'"
op|','
nl|'\n'
string|"'/scratch/dir/some/file'"
op|')'
op|','
nl|'\n'
string|"'kwargs'"
op|':'
op|'{'
string|"'run_as_root'"
op|':'
name|'True'
op|','
nl|'\n'
string|"'root_helper'"
op|':'
name|'root_helper'
op|'}'
op|'}'
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'nova'
op|'.'
name|'utils'
op|','
string|"'execute'"
op|')'
newline|'\n'
DECL|member|test_get_format_fs
name|'def'
name|'test_get_format_fs'
op|'('
name|'self'
op|','
name|'execute'
op|')'
op|':'
newline|'\n'
indent|' '
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'rawfile'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'setup'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'teardown'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
nl|'\n'
DECL|function|fake_setup
name|'def'
name|'fake_setup'
op|'('
op|')'
op|':'
newline|'\n'
indent|' '
name|'vfs'
op|'.'
name|'mount'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'mount'
op|'.'
name|'device'
op|'='
name|'None'
newline|'\n'
name|'vfs'
op|'.'
name|'mount'
op|'.'
name|'get_dev'
op|'.'
name|'side_effect'
op|'='
name|'fake_get_dev'
newline|'\n'
nl|'\n'
DECL|function|fake_teardown
dedent|''
name|'def'
name|'fake_teardown'
op|'('
op|')'
op|':'
newline|'\n'
indent|' '
name|'vfs'
op|'.'
name|'mount'
op|'.'
name|'device'
op|'='
name|'None'
newline|'\n'
nl|'\n'
DECL|function|fake_get_dev
dedent|''
name|'def'
name|'fake_get_dev'
op|'('
op|')'
op|':'
newline|'\n'
indent|' '
name|'vfs'
op|'.'
name|'mount'
op|'.'
name|'device'
op|'='
string|"'/dev/xyz'"
newline|'\n'
name|'return'
name|'True'
newline|'\n'
nl|'\n'
dedent|''
name|'vfs'
op|'.'
name|'setup'
op|'.'
name|'side_effect'
op|'='
name|'fake_setup'
newline|'\n'
name|'vfs'
op|'.'
name|'teardown'
op|'.'
name|'side_effect'
op|'='
name|'fake_teardown'
newline|'\n'
name|'execute'
op|'.'
name|'return_value'
op|'='
op|'('
string|"'ext3\\n'"
op|','
string|"''"
op|')'
newline|'\n'
nl|'\n'
name|'vfs'
op|'.'
name|'setup'
op|'('
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertEqual'
op|'('
string|"'ext3'"
op|','
name|'vfs'
op|'.'
name|'get_image_fs'
op|'('
op|')'
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'teardown'
op|'('
op|')'
newline|'\n'
name|'vfs'
op|'.'
name|'mount'
op|'.'
name|'get_dev'
op|'.'
name|'assert_called_once_with'
op|'('
op|')'
newline|'\n'
name|'execute'
op|'.'
name|'assert_called_once_with'
op|'('
string|"'blkid'"
op|','
string|"'-o'"
op|','
nl|'\n'
string|"'value'"
op|','
string|"'-s'"
op|','
nl|'\n'
string|"'TYPE'"
op|','
string|"'/dev/xyz'"
op|','
nl|'\n'
name|'run_as_root'
op|'='
name|'True'
op|','
nl|'\n'
name|'check_exit_code'
op|'='
op|'['
number|'0'
op|','
number|'2'
op|']'
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'tempfile'
op|','
string|"'mkdtemp'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'nbd'
op|','
string|"'NbdMount'"
op|')'
newline|'\n'
DECL|member|test_setup_mount
name|'def'
name|'test_setup_mount'
op|'('
name|'self'
op|','
name|'NbdMount'
op|','
name|'mkdtemp'
op|')'
op|':'
newline|'\n'
indent|' '
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
nl|'\n'
name|'mounter'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'mkdtemp'
op|'.'
name|'return_value'
op|'='
string|"'tmp/'"
newline|'\n'
name|'NbdMount'
op|'.'
name|'return_value'
op|'='
name|'mounter'
newline|'\n'
nl|'\n'
name|'vfs'
op|'.'
name|'setup'
op|'('
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertTrue'
op|'('
name|'mkdtemp'
op|'.'
name|'called'
op|')'
newline|'\n'
name|'NbdMount'
op|'.'
name|'assert_called_once_with'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|','
string|'"tmp/"'
op|','
name|'None'
op|')'
newline|'\n'
name|'mounter'
op|'.'
name|'do_mount'
op|'.'
name|'assert_called_once_with'
op|'('
op|')'
newline|'\n'
nl|'\n'
dedent|''
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'tempfile'
op|','
string|"'mkdtemp'"
op|')'
newline|'\n'
op|'@'
name|'mock'
op|'.'
name|'patch'
op|'.'
name|'object'
op|'('
name|'nbd'
op|','
string|"'NbdMount'"
op|')'
newline|'\n'
DECL|member|test_setup_mount_false
name|'def'
name|'test_setup_mount_false'
op|'('
name|'self'
op|','
name|'NbdMount'
op|','
name|'mkdtemp'
op|')'
op|':'
newline|'\n'
indent|' '
name|'vfs'
op|'='
name|'vfsimpl'
op|'.'
name|'VFSLocalFS'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|')'
newline|'\n'
nl|'\n'
name|'mounter'
op|'='
name|'mock'
op|'.'
name|'MagicMock'
op|'('
op|')'
newline|'\n'
name|'mkdtemp'
op|'.'
name|'return_value'
op|'='
string|"'tmp/'"
newline|'\n'
name|'NbdMount'
op|'.'
name|'return_value'
op|'='
name|'mounter'
newline|'\n'
nl|'\n'
name|'vfs'
op|'.'
name|'setup'
op|'('
name|'mount'
op|'='
name|'False'
op|')'
newline|'\n'
nl|'\n'
name|'self'
op|'.'
name|'assertTrue'
op|'('
name|'mkdtemp'
op|'.'
name|'called'
op|')'
newline|'\n'
name|'NbdMount'
op|'.'
name|'assert_called_once_with'
op|'('
name|'self'
op|'.'
name|'qcowfile'
op|','
string|'"tmp/"'
op|','
name|'None'
op|')'
newline|'\n'
name|'self'
op|'.'
name|'assertFalse'
op|'('
name|'mounter'
op|'.'
name|'do_mount'
op|'.'
name|'called'
op|')'
newline|'\n'
dedent|''
dedent|''
endmarker|''
end_unit
| 11.660996
| 88
| 0.561818
| 5,438
| 37,012
| 3.771423
| 0.045605
| 0.131357
| 0.092642
| 0.052026
| 0.905407
| 0.879516
| 0.846653
| 0.808669
| 0.792238
| 0.774099
| 0
| 0.00353
| 0.104453
| 37,012
| 3,173
| 89
| 11.664671
| 0.615218
| 0
| 0
| 0.965648
| 0
| 0
| 0.339187
| 0.040365
| 0
| 0
| 0
| 0
| 0.011031
| 0
| null | null | 0
| 0.003152
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
8b0d8b6383463c62ba7885c6001e897ee1396db4
| 1,032
|
py
|
Python
|
buggy/enums.py
|
fusionbox/buggy
|
fb6f4a34f6896b65c843ebe711f5bf3279d33049
|
[
"BSD-3-Clause"
] | 2
|
2017-05-08T23:11:41.000Z
|
2017-05-22T19:27:36.000Z
|
buggy/enums.py
|
fusionbox/buggy
|
fb6f4a34f6896b65c843ebe711f5bf3279d33049
|
[
"BSD-3-Clause"
] | 4
|
2017-05-03T17:46:47.000Z
|
2017-05-08T17:13:57.000Z
|
buggy/enums.py
|
Hakob/Buggy
|
5facb2835c5716466fcdf95e368bf842729f26f3
|
[
"BSD-3-Clause"
] | 2
|
2017-05-22T19:28:21.000Z
|
2017-05-26T17:24:51.000Z
|
from enumfields import IntEnum, Enum
class Priority(IntEnum):
HOLD = 1
NORMAL = 2
URGENT = 3
class Labels:
HOLD = 'hold'
NORMAL = 'normal'
URGENT = 'urgent'
class State(Enum):
NEW = 'new'
CLOSED = 'closed'
ENTRUSTED = 'entrusted'
VERIFIED = 'verified'
REOPENED = 'reopened'
LIVE = 'live'
RESOLVED_FIXED = 'resolved-fixed'
RESOLVED_UNREPRODUCIBLE = 'resolved-unreproducible'
RESOLVED_DUPLICATE = 'resolved-duplicate'
RESOLVED_IMPOSSIBLE = 'resolved-impossible'
RESOLVED_NOT_A_BUG = 'resolved-notabug'
class Labels:
NEW = 'new'
CLOSED = 'closed'
ENTRUSTED = 'entrusted'
VERIFIED = 'verified'
REOPENED = 'reopened'
LIVE = 'live'
RESOLVED_FIXED = 'resolved - fixed'
RESOLVED_UNREPRODUCIBLE = 'resolved - unreproducible'
RESOLVED_DUPLICATE = 'resolved - duplicate'
RESOLVED_IMPOSSIBLE = 'resolved - impossible'
RESOLVED_NOT_A_BUG = 'resolved - not a bug'
| 25.8
| 61
| 0.624031
| 97
| 1,032
| 6.494845
| 0.309278
| 0.08254
| 0.133333
| 0.071429
| 0.75873
| 0.75873
| 0.75873
| 0.75873
| 0.75873
| 0.75873
| 0
| 0.004049
| 0.281977
| 1,032
| 39
| 62
| 26.461538
| 0.846154
| 0
| 0
| 0.727273
| 0
| 0
| 0.275194
| 0.022287
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.030303
| 0
| 0.575758
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 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
| 1
| 0
|
0
| 7
|
8b1c297893bab1c0c834e170cafcbe039e00dac3
| 224
|
py
|
Python
|
src/api/pdi/domain/base/aps/__init__.py
|
ahmetcagriakca/pythondataintegrator
|
079b968d6c893008f02c88dbe34909a228ac1c7b
|
[
"MIT"
] | 1
|
2020-12-18T21:37:28.000Z
|
2020-12-18T21:37:28.000Z
|
src/api/pdi/domain/base/aps/__init__.py
|
ahmetcagriakca/pythondataintegrator
|
079b968d6c893008f02c88dbe34909a228ac1c7b
|
[
"MIT"
] | null | null | null |
src/api/pdi/domain/base/aps/__init__.py
|
ahmetcagriakca/pythondataintegrator
|
079b968d6c893008f02c88dbe34909a228ac1c7b
|
[
"MIT"
] | 1
|
2020-12-18T21:37:31.000Z
|
2020-12-18T21:37:31.000Z
|
from pdi.domain.base.aps.ApSchedulerEventBase import ApSchedulerEventBase
from pdi.domain.base.aps.ApSchedulerJobBase import ApSchedulerJobBase
from pdi.domain.base.aps.ApSchedulerJobEventBase import ApSchedulerJobEventBase
| 56
| 79
| 0.892857
| 24
| 224
| 8.333333
| 0.375
| 0.105
| 0.195
| 0.255
| 0.3
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.053571
| 224
| 3
| 80
| 74.666667
| 0.943396
| 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
|
8b270af056461ab9afae403f8e0b0b811d49af4f
| 3,990
|
py
|
Python
|
stv/tests/logics/atl/test_atl_ir_model.py
|
wp777/stv-compute
|
313b574c43ef87b629e70c25c38dbb7b24d1f130
|
[
"MIT"
] | 2
|
2021-07-11T09:52:59.000Z
|
2022-02-13T17:34:59.000Z
|
stv/tests/logics/atl/test_atl_ir_model.py
|
wp777/stv-compute
|
313b574c43ef87b629e70c25c38dbb7b24d1f130
|
[
"MIT"
] | 3
|
2020-07-26T13:49:59.000Z
|
2021-01-19T18:04:10.000Z
|
stv/tests/logics/atl/test_atl_ir_model.py
|
wp777/stv-compute
|
313b574c43ef87b629e70c25c38dbb7b24d1f130
|
[
"MIT"
] | null | null | null |
from stv.logics.atl import ATLIrModel, ATLirModel
import unittest
class ATLIrModelTestSuite(unittest.TestCase):
atl_Ir_model = None
def setUp(self):
self.create_test_model()
def create_test_model(self):
self.atl_Ir_model = ATLIrModel(number_of_agents=2)
self.atl_Ir_model.add_action(0, 'Wait')
self.atl_Ir_model.add_action(0, 'Push')
self.atl_Ir_model.add_action(1, 'Wait')
self.atl_Ir_model.add_action(1, 'Push')
self.atl_Ir_model.add_transition(0, 1, ['Push', 'Wait'])
self.atl_Ir_model.add_transition(0, 2, ['Wait', 'Push'])
self.atl_Ir_model.add_transition(1, 2, ['Push', 'Wait'])
self.atl_Ir_model.add_transition(1, 0, ['Wait', 'Push'])
self.atl_Ir_model.add_transition(2, 0, ['Push', 'Wait'])
self.atl_Ir_model.add_transition(2, 1, ['Wait', 'Push'])
self.atl_Ir_model.add_transition(0, 0, ['Wait', 'Wait'])
self.atl_Ir_model.add_transition(1, 1, ['Wait', 'Wait'])
self.atl_Ir_model.add_transition(2, 2, ['Wait', 'Wait'])
self.atl_Ir_model.add_transition(0, 0, ['Push', 'Push'])
self.atl_Ir_model.add_transition(1, 1, ['Push', 'Push'])
self.atl_Ir_model.add_transition(2, 2, ['Push', 'Push'])
def test_minimum_formula_one_agent(self):
result = self.atl_Ir_model.minimum_formula_one_agent(0, {1})
self.assertEqual(1, len(result))
def test_maximum_formula_one_agent(self):
result = self.atl_Ir_model.maximum_formula_one_agent(0, {2})
self.assertEqual(0, len(result))
def test_minimum_formula_many_agents(self):
result = self.atl_Ir_model.minimum_formula_many_agents([0, 1], {1})
self.assertEqual(3, len(result))
def test_maximum_formula_many_agents(self):
result = self.atl_Ir_model.maximum_formula_many_agents([0, 1], {0, 2})
self.assertEqual(2, len(result))
def test_minimum_formula_no_agents(self):
result = self.atl_Ir_model.minimum_formula_no_agents({1})
self.assertEqual(3, len(result))
def test_maximum_formula_no_agents(self):
result = self.atl_Ir_model.maximum_formula_no_agents({0, 1})
self.assertEqual(2, len(result))
class ATLirModelTestSuite(unittest.TestCase):
atl_ir_model = None
def setUp(self):
self.create_test_model()
def create_test_model(self):
self.atl_ir_model = ATLirModel(number_of_agents=2)
self.atl_ir_model.add_action(0, 'Wait')
self.atl_ir_model.add_action(0, 'Push')
self.atl_ir_model.add_action(1, 'Wait')
self.atl_ir_model.add_action(1, 'Push')
self.atl_ir_model.add_transition(0, 1, ['Push', 'Wait'])
self.atl_ir_model.add_transition(0, 2, ['Wait', 'Push'])
self.atl_ir_model.add_transition(1, 2, ['Push', 'Wait'])
self.atl_ir_model.add_transition(1, 0, ['Wait', 'Push'])
self.atl_ir_model.add_transition(2, 0, ['Push', 'Wait'])
self.atl_ir_model.add_transition(2, 1, ['Wait', 'Push'])
self.atl_ir_model.add_transition(0, 0, ['Wait', 'Wait'])
self.atl_ir_model.add_transition(1, 1, ['Wait', 'Wait'])
self.atl_ir_model.add_transition(2, 2, ['Wait', 'Wait'])
self.atl_ir_model.add_transition(0, 0, ['Push', 'Push'])
self.atl_ir_model.add_transition(1, 1, ['Push', 'Push'])
self.atl_ir_model.add_transition(2, 2, ['Push', 'Push'])
self.atl_ir_model.finish_model()
self.atl_ir_model.add_epistemic_class(agent_id=0, epistemic_class={0, 1})
self.atl_ir_model.add_epistemic_class(agent_id=1, epistemic_class={0, 2})
def test_minimum_formula_one_agent(self):
result = self.atl_ir_model.minimum_formula_one_agent(0, {2})
self.assertEqual(1, len(result))
def test_minimum_formula_many_agents(self):
result = self.atl_ir_model.minimum_formula_many_agents([0, 1], {0, 2})
self.assertEqual(3, len(result))
if __name__ == '__main__':
unittest.main()
| 42.446809
| 81
| 0.666667
| 598
| 3,990
| 4.095318
| 0.076923
| 0.095958
| 0.191915
| 0.257248
| 0.941609
| 0.926909
| 0.908942
| 0.878726
| 0.873009
| 0.747244
| 0
| 0.028334
| 0.186216
| 3,990
| 93
| 82
| 42.903226
| 0.725901
| 0
| 0
| 0.226667
| 0
| 0
| 0.058145
| 0
| 0
| 0
| 0
| 0
| 0.106667
| 1
| 0.16
| false
| 0
| 0.026667
| 0
| 0.24
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
8b3fbee09b534a78ec15ccd38d9542baa7610c4d
| 89
|
py
|
Python
|
ErocoolAPI/__init__.py
|
Dotinkasra/ErocoolAPI
|
1ba9d36e6af81698c546f02e37b229fc7d1ea974
|
[
"MIT"
] | null | null | null |
ErocoolAPI/__init__.py
|
Dotinkasra/ErocoolAPI
|
1ba9d36e6af81698c546f02e37b229fc7d1ea974
|
[
"MIT"
] | null | null | null |
ErocoolAPI/__init__.py
|
Dotinkasra/ErocoolAPI
|
1ba9d36e6af81698c546f02e37b229fc7d1ea974
|
[
"MIT"
] | null | null | null |
from ErocoolAPI.modules.erocool import Erocool
from ErocoolAPI.modules.caffe import Caffe
| 44.5
| 46
| 0.876404
| 12
| 89
| 6.5
| 0.5
| 0.358974
| 0.538462
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.078652
| 89
| 2
| 47
| 44.5
| 0.95122
| 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
|
50b6bab904cc79d3810f0b53977ab70e70969cea
| 46
|
py
|
Python
|
multilingual_t5/gu_en/__init__.py
|
sumanthd17/mt5
|
c99b4e3ad1c69908c852c730a1323ccb52d48f58
|
[
"Apache-2.0"
] | null | null | null |
multilingual_t5/gu_en/__init__.py
|
sumanthd17/mt5
|
c99b4e3ad1c69908c852c730a1323ccb52d48f58
|
[
"Apache-2.0"
] | null | null | null |
multilingual_t5/gu_en/__init__.py
|
sumanthd17/mt5
|
c99b4e3ad1c69908c852c730a1323ccb52d48f58
|
[
"Apache-2.0"
] | null | null | null |
"""gu_en dataset."""
from .gu_en import GuEn
| 11.5
| 23
| 0.673913
| 8
| 46
| 3.625
| 0.75
| 0.275862
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152174
| 46
| 3
| 24
| 15.333333
| 0.74359
| 0.304348
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 7
|
50e7803c51aa30ec01ef206fe54a5fd70505503f
| 1,432
|
py
|
Python
|
Create_all_figures.py
|
Asafgendler/RSCP
|
ece81192adf3edd51acbbfd846499a7c18e4fa85
|
[
"MIT"
] | null | null | null |
Create_all_figures.py
|
Asafgendler/RSCP
|
ece81192adf3edd51acbbfd846499a7c18e4fa85
|
[
"MIT"
] | null | null | null |
Create_all_figures.py
|
Asafgendler/RSCP
|
ece81192adf3edd51acbbfd846499a7c18e4fa85
|
[
"MIT"
] | null | null | null |
import subprocess
process = subprocess.Popen("python ./Create_Figures/Motivation.py", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Trivial_Sets.py", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Main_Results.py", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Effect_of_sigma_smooth.py --comparison", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Effect_of_sigma_smooth.py --dataset CIFAR100", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Effect_of_n_smooth.py --comparison", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Effect_of_n_smooth.py --dataset CIFAR10", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/DenseNet_Results.py --dataset CIFAR100", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/DenseNet_Results.py --dataset CIFAR10", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Clean_Data_Results.py", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Salman_model.py", shell=True)
process.communicate()
process = subprocess.Popen("python ./Create_Figures/Conditioned_on_y.py --dataset CIFAR10", shell=True)
process.communicate()
| 55.076923
| 110
| 0.804469
| 179
| 1,432
| 6.251397
| 0.184358
| 0.182306
| 0.235925
| 0.300268
| 0.932976
| 0.932976
| 0.896336
| 0.857909
| 0.857909
| 0.857909
| 0
| 0.008915
| 0.060056
| 1,432
| 26
| 111
| 55.076923
| 0.822437
| 0
| 0
| 0.48
| 0
| 0
| 0.442428
| 0.301465
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.04
| 0
| 0.04
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
50fcaed9bb52afd8a924ddbb1b5ad654ec17fcac
| 121
|
py
|
Python
|
aluno_exatas/__init__.py
|
EricoNR/aluno_exatas
|
4527bb4e30ec14001c18a1da00b952e041472ae8
|
[
"MIT"
] | 1
|
2018-09-26T06:44:07.000Z
|
2018-09-26T06:44:07.000Z
|
aluno_exatas/__init__.py
|
EricoNR/aluno_exatas
|
4527bb4e30ec14001c18a1da00b952e041472ae8
|
[
"MIT"
] | null | null | null |
aluno_exatas/__init__.py
|
EricoNR/aluno_exatas
|
4527bb4e30ec14001c18a1da00b952e041472ae8
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
import aluno_exatas.fis_exp
import aluno_exatas.calc_num
import aluno_exatas.circuitos_eletricos
| 24.2
| 39
| 0.809917
| 18
| 121
| 5.111111
| 0.666667
| 0.358696
| 0.554348
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009091
| 0.090909
| 121
| 5
| 39
| 24.2
| 0.827273
| 0.173554
| 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
|
0fa64c0927078641ff72e0c3dda828e641c8e763
| 6,347
|
py
|
Python
|
maxIslandArea.py
|
passionzhan/LeetCode
|
c4d33b64b9da15ca7a9b0d41e645d86a697694fe
|
[
"MIT"
] | 1
|
2019-08-29T01:12:47.000Z
|
2019-08-29T01:12:47.000Z
|
maxIslandArea.py
|
passionzhan/LeetCode
|
c4d33b64b9da15ca7a9b0d41e645d86a697694fe
|
[
"MIT"
] | null | null | null |
maxIslandArea.py
|
passionzhan/LeetCode
|
c4d33b64b9da15ca7a9b0d41e645d86a697694fe
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @File : maxIslandArea.py
# @Author: Zhan
# @Date : 4/30/2019
# @Desc :
from collections import deque
class Solution(object):
def neighbors(selef,grid, iRow, iClo):
for (nr, nc) in ((iRow - 1, iClo), (iRow + 1, iClo), (iRow, iClo - 1), (iRow, iClo + 1)):
if 0 <= nr < len(grid) and 0 <= nc < len(grid[0]):
yield (nr, nc)
def maxAreaOfIsland(self, grid):
seen = set()
maxArea = 0
for i, row in enumerate(grid):
for j, v in enumerate(row):
if v and (i,j) not in seen:
# maxArea = max(maxArea, self.dfs(grid, seen, i, j))
maxArea = max(maxArea, self.bfs(grid, seen, i, j))
return maxArea
# 深度优先搜索
def dfs(self, grid, seen, i, j):
area = 0
seen.add((i,j))
area = 1
for nei_i,nei_j in self.neighbors(grid,i,j):
if grid[nei_i][nei_j] and (nei_i,nei_j) not in seen:
area += self.dfs(grid, seen, nei_i, nei_j)
return area
# 宽度优先搜索
def bfs(self, grid, seen, i, j):
area = 0
myque = deque()
myque.append((i,j))
seen.add((i,j))
while myque:
cur_i,cur_j = myque.popleft()
area += 1
for nei_i,nei_j in self.neighbors(grid,cur_i,cur_j):
if grid[nei_i][nei_j] and (nei_i,nei_j) not in seen:
seen.add((nei_i, nei_j))
myque.append((nei_i,nei_j))
return area
if __name__ == '__main__':
grid = [[1, 1, 0, 0, 0],
[1, 1, 0, 0, 0],
[0, 0, 0, 1, 1],
[0, 0, 0, 1, 1]]
grid = [[1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1],
[1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1],
[0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1],
[1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1],
[0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1],
[1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1],
[1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0],
[1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1],
[1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1],
[0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0],
[0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1],
[0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1],
[1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1],
[0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0],
[1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1],
[1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1],
[1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0],
[1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0],
[0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1],
[1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1],
[1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0],
[1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0],
[1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1],
[0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1],
[0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1],
[1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1],
[0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1],
[0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1],
[1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0],
[1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0],
[1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1],
[0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1],
[1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0],
[1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1],
[0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1],
[0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0],
[1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0]]
maxIslandArea = Solution().maxAreaOfIsland(grid)
print(maxIslandArea)
| 57.7
| 98
| 0.337325
| 1,512
| 6,347
| 1.396164
| 0.044974
| 0.316438
| 0.262909
| 0.195168
| 0.706774
| 0.702984
| 0.685931
| 0.66793
| 0.66793
| 0.665088
| 0
| 0.343633
| 0.408539
| 6,347
| 109
| 99
| 58.229358
| 0.2187
| 0.027572
| 0
| 0.086957
| 0
| 0
| 0.001321
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.043478
| false
| 0
| 0.01087
| 0
| 0.097826
| 0.01087
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
e8a8b7ff3997dd4f27900afecf23791de5f715ee
| 146
|
py
|
Python
|
guet/config/already_initialized.py
|
sapphon/guet
|
60872bfb149ad16a3c5309e283a6b886080a13dc
|
[
"Apache-2.0"
] | null | null | null |
guet/config/already_initialized.py
|
sapphon/guet
|
60872bfb149ad16a3c5309e283a6b886080a13dc
|
[
"Apache-2.0"
] | null | null | null |
guet/config/already_initialized.py
|
sapphon/guet
|
60872bfb149ad16a3c5309e283a6b886080a13dc
|
[
"Apache-2.0"
] | null | null | null |
from os.path import isdir
from guet.config import configuration_directory
def already_initialized():
return isdir(configuration_directory)
| 18.25
| 47
| 0.821918
| 18
| 146
| 6.5
| 0.722222
| 0.376068
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130137
| 146
| 7
| 48
| 20.857143
| 0.92126
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0
| 0.5
| 0.25
| 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
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 8
|
e8c162c0e61615c5c57ba8d996f05dcce3a6c384
| 227
|
py
|
Python
|
tccli/services/yunjing/__init__.py
|
hapsyou/tencentcloud-cli-intl-en
|
fa8ba71164484f9a2be4b983080a1de08606c0b0
|
[
"Apache-2.0"
] | null | null | null |
tccli/services/yunjing/__init__.py
|
hapsyou/tencentcloud-cli-intl-en
|
fa8ba71164484f9a2be4b983080a1de08606c0b0
|
[
"Apache-2.0"
] | null | null | null |
tccli/services/yunjing/__init__.py
|
hapsyou/tencentcloud-cli-intl-en
|
fa8ba71164484f9a2be4b983080a1de08606c0b0
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
from tccli.services.yunjing.yunjing_client import register_arg
from tccli.services.yunjing.yunjing_client import get_actions_info
from tccli.services.yunjing.yunjing_client import AVAILABLE_VERSION_LIST
| 45.4
| 72
| 0.845815
| 32
| 227
| 5.75
| 0.53125
| 0.146739
| 0.277174
| 0.391304
| 0.701087
| 0.701087
| 0.701087
| 0
| 0
| 0
| 0
| 0.004762
| 0.07489
| 227
| 4
| 73
| 56.75
| 0.871429
| 0.092511
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 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
|
2cf0dd837df63bdc6263a62743d0fbd78a14ed1c
| 9,655
|
py
|
Python
|
tests/test_allrelevant.py
|
ThomasBury/arfs
|
887a5946a7eef25aefd964092fcbb0e0e3d90987
|
[
"MIT"
] | 26
|
2020-11-28T16:43:55.000Z
|
2022-03-09T04:51:29.000Z
|
tests/test_allrelevant.py
|
ThomasBury/arfs
|
887a5946a7eef25aefd964092fcbb0e0e3d90987
|
[
"MIT"
] | 11
|
2020-12-25T13:56:50.000Z
|
2022-03-11T10:15:39.000Z
|
tests/test_allrelevant.py
|
ThomasBury/arfs
|
887a5946a7eef25aefd964092fcbb0e0e3d90987
|
[
"MIT"
] | 3
|
2021-04-09T18:44:09.000Z
|
2022-02-09T09:20:16.000Z
|
import pytest
import numpy as np
import lightgbm as lgb
from arfs.allrelevant import Leshy, BoostAGroota, GrootCV
from arfs.utils import generated_corr_dataset_regr, generated_corr_dataset_classification
from arfs.utils import LightForestClassifier, LightForestRegressor
class TestLeshy:
"""
Test suite for all-relevant FS boruta-like method: Leshy
"""
def test_borutaPy_vs_leshy_with_rfc_and_native_feature_importance(self):
# too slow for circleci to run them in a reasonable time
# takes 2 min on laptop, 1h or more on circleci
# sklearn random forest implementation
# X, y, w = _generated_corr_dataset_classification()
# rfc = RandomForestClassifier(max_features='sqrt', max_samples=0.632, n_estimators=100)
# bt = BorutaPy(rfc)
# bt.fit(X.values, y)
# borutapy_rfc_list = sorted(list(X.columns[bt.support_]))
# lightGBM random forest implementation
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_classification(size=100)
n_feat = X.shape[1]
rfc = LightForestClassifier(n_feat)
# RandomForestClassifier(max_features='sqrt', max_samples=0.632, n_estimators=100) # --> too slow
arfs = Leshy(rfc, verbose=0, max_iter=10, random_state=42, importance='native')
arfs.fit(X, y)
leshy_rfc_list = sorted(arfs.support_names_)
# assert borutapy_rfc_list == leshy_rfc_list, "same selected features are expected"
assert bool(set(baseline_list) & set(leshy_rfc_list)), "expect non-empty intersection"
def test_borutaPy_vs_leshy_with_rfr_and_native_feature_importance(self):
# too slow for circleci to run them in a reasonable time
# takes 2 min on laptop, 1h or more on circleci
# # sklearn random forest implementation
# X, y, w = _generated_corr_dataset_regr()
# rfr = RandomForestRegressor(max_features=0.3, max_samples=0.632, n_estimators=100)
# bt = BorutaPy(rfr)
# bt.fit(X.values, y)
# borutapy_rfc_list = sorted(list(X.columns[bt.support_]))
# lightGBM random forest implementation
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_regr(size=100)
n_feat = X.shape[1]
rfr = LightForestRegressor(n_feat)
# rfr = RandomForestRegressor(max_features=0.3, max_samples=0.632, n_estimators=10)
arfs = Leshy(rfr, verbose=0, max_iter=10, random_state=42, importance='native')
arfs.fit(X, y)
leshy_rfc_list = sorted(arfs.support_names_)
# assert borutapy_rfc_list == leshy_rfc_list, "same selected features are expected"
assert bool(set(baseline_list) & set(leshy_rfc_list)), "expect non-empty intersection"
def test_borutaPy_vs_leshy_with_rfc_and_shap_feature_importance(self):
# too slow for circleci to run them in a reasonable time
# takes 2 min on laptop, 1h or more on circleci
# # sklearn random forest implementation
# X, y, w = _generated_corr_dataset_classification()
# rfc = RandomForestClassifier(max_features='sqrt', max_samples=0.632, n_estimators=100)
# bt = BorutaPy(rfc)
# bt.fit(X.values, y)
# borutapy_rfc_list = sorted(list(X.columns[bt.support_]))
# lightGBM random forest implementation
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_classification(size=100)
n_feat = X.shape[1]
model = LightForestClassifier(n_feat)
arfs = Leshy(model, verbose=0, max_iter=10, random_state=42, importance='shap')
arfs.fit(X, y)
leshy_rfc_list = sorted(arfs.support_names_)
# assert borutapy_rfc_list == leshy_rfc_list, "same selected features are expected"
assert bool(set(baseline_list) & set(leshy_rfc_list)), "expect non-empty intersection"
def test_borutaPy_vs_leshy_with_rfr_and_shap_feature_importance(self):
# too slow for circleci to run them in a reasonable time
# takes 2 min on laptop, 1h or more on circleci
# # sklearn random forest implementation
# X, y, w = _generated_corr_dataset_regr()
# rfr = RandomForestRegressor(max_features=0.3, max_samples=0.632, n_estimators=100)
# bt = BorutaPy(rfr)
# bt.fit(X.values, y)
# borutapy_rfc_list = sorted(list(X.columns[bt.support_]))
# lightGBM random forest implementation
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_regr(size=500)
n_feat = X.shape[1]
model = LightForestRegressor(n_feat)
arfs = Leshy(model, verbose=0, max_iter=10, random_state=42, importance='shap')
arfs.fit(X, y)
leshy_rfc_list = sorted(arfs.support_names_)
# assert borutapy_rfc_list == leshy_rfc_list, "same selected features are expected"
assert bool(set(baseline_list) & set(leshy_rfc_list)), "expect non-empty intersection"
def test_leshy_clf_with_lgb_and_shap_feature_importance_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_classification(size=500)
model = lgb.LGBMClassifier(verbose=-1, force_col_wise=True, n_estimators=10)
arfs = Leshy(model, verbose=0, max_iter=10, random_state=42, importance='shap')
arfs.fit(X, y, w)
leshy_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(leshy_list)), "expect non-empty intersection"
def test_leshy_regr_with_lgb_and_shap_feature_importance_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4', 'var5']
X, y, w = generated_corr_dataset_classification(size=500)
model = lgb.LGBMRegressor(verbose=-1, force_col_wise=True, n_estimators=10)
arfs = Leshy(model, verbose=0, max_iter=10, random_state=42, importance='shap')
arfs.fit(X, y, w)
leshy_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(leshy_list)), "expect non-empty intersection"
class TestBoostAGroota:
"""
Test suite for all-relevant FS boruta-like method: Leshy
"""
def test_boostagroota_clf_with_lgb_and_shap_feature_importance_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_classification(size=500)
model = lgb.LGBMClassifier(verbose=-1, force_col_wise=True, n_estimators=10)
arfs = BoostAGroota(est=model, cutoff=1, iters=3, max_rounds=3, delta=0.1, silent=False, importance='shap')
arfs.fit(X, y, w)
leshy_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(leshy_list)), "expect non-empty intersection"
def test_boostagroota_clf_with_lgb_and_pimp_feature_importance_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_classification(size=500)
model = lgb.LGBMClassifier(verbose=-1, force_col_wise=True, n_estimators=10)
arfs = BoostAGroota(est=model, cutoff=1, iters=3, max_rounds=3, delta=0.1, silent=False, importance='pimp')
arfs.fit(X, y, w)
leshy_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(leshy_list)), "expect non-empty intersection"
def test_boostagroota_rgr_with_lgb_and_shap_feature_importance_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4', 'var5']
X, y, w = generated_corr_dataset_regr(size=500)
model = lgb.LGBMRegressor(verbose=-1, force_col_wise=True, n_estimators=10)
arfs = BoostAGroota(est=model, cutoff=1, iters=3, max_rounds=3, delta=0.1, silent=False, importance='shap')
arfs.fit(X, y, w)
leshy_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(leshy_list)), "expect non-empty intersection"
def test_boostagroota_regr_with_lgb_and_pimp_feature_importance_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4', 'var5']
X, y, w = generated_corr_dataset_regr(size=500)
model = lgb.LGBMRegressor(verbose=-1, force_col_wise=True, n_estimators=10)
arfs = BoostAGroota(est=model, cutoff=1, iters=3, max_rounds=3, delta=0.1, silent=False, importance='pimp')
arfs.fit(X, y, w)
leshy_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(leshy_list)), "expect non-empty intersection"
class TestGrootCV:
"""
Test suite for all-relevant FS boruta-like method: Leshy
"""
def test_grootcv_classification_with_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4']
X, y, w = generated_corr_dataset_classification(size=100)
arfs = GrootCV(objective='binary', cutoff=1, n_folds=3, n_iter=3, silent=False)
arfs.fit(X, y, w)
grootcv_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(grootcv_list)), "expect non-empty intersection"
def test_grootcv_regression_with_and_sample_weight(self):
baseline_list = ['var0', 'var1', 'var2', 'var3', 'var4', 'var5']
X, y, w = generated_corr_dataset_regr(size=100)
arfs = GrootCV(objective='l2', cutoff=1, n_folds=3, n_iter=3, silent=False)
arfs.fit(X, y, w)
grootcv_list = sorted(arfs.support_names_)
assert bool(set(baseline_list) & set(grootcv_list)), "expect non-empty intersection"
| 48.034826
| 115
| 0.683791
| 1,319
| 9,655
| 4.744503
| 0.108415
| 0.008949
| 0.011505
| 0.030681
| 0.928092
| 0.919942
| 0.916427
| 0.910994
| 0.905401
| 0.903963
| 0
| 0.030421
| 0.203314
| 9,655
| 200
| 116
| 48.275
| 0.783151
| 0.237286
| 0
| 0.728972
| 1
| 0
| 0.090197
| 0
| 0
| 0
| 0
| 0
| 0.11215
| 1
| 0.11215
| false
| 0
| 0.242991
| 0
| 0.383178
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 1
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|
0
| 8
|
2cf7f6b2928f86d1f84234d08c984942c37e3c4b
| 31,618
|
py
|
Python
|
tests/test_storage_github.py
|
JGoutin/rfs
|
6e68968fada828adab7fd7011893871a3bd58ecd
|
[
"Apache-2.0"
] | 5
|
2020-07-25T16:52:22.000Z
|
2021-07-22T02:03:15.000Z
|
tests/test_storage_github.py
|
JGoutin/rfs
|
6e68968fada828adab7fd7011893871a3bd58ecd
|
[
"Apache-2.0"
] | 27
|
2020-01-13T21:16:23.000Z
|
2021-11-09T11:18:17.000Z
|
tests/test_storage_github.py
|
JGoutin/rfs
|
6e68968fada828adab7fd7011893871a3bd58ecd
|
[
"Apache-2.0"
] | 1
|
2022-03-25T13:32:13.000Z
|
2022-03-25T13:32:13.000Z
|
"""Test airfs.storage.github"""
import json
import pickle
from os.path import realpath, join
import requests
import pytest
UNSUPPORTED_OPERATIONS = (
"copy",
"mkdir",
"remove",
"write",
"shareable_url",
"list_locator",
)
#: Set to True and run tests to update mock test responses with real test responses
UPDATE_MOCK = False
#: Directory where are saved cached responses from GitHub API to use with mock
MOCK_DIR = realpath(join(__file__, "../resources/github_mock_responses"))
class MockResponse:
"""Mocked request.Response"""
def __init__(self, url, headers, status_code, content, reason):
self.headers = headers
self.status_code = status_code
self.content = content
self.url = url
self.reason = reason
def json(self):
"""Mocked Json result"""
return json.loads(self.content)
@property
def text(self):
"""Mocked Text result"""
return self.content.decode()
def raise_for_status(self):
"""Mocked exception"""
if self.status_code >= 400:
raise requests.HTTPError(
f"{self.status_code} Error: {self.reason} for: {self.url}",
response=self,
)
def test_mocked_storage():
"""Tests airfs.github with a mock"""
pytest.skip(
"Unable to test using the generic test scenario due to "
"fixed virtual filesystem tree."
)
def test_github_storage(tmpdir):
"""Tests airfs.github specificities"""
from airfs._core.storage_manager import _DEFAULTS
try:
assert _DEFAULTS["github"]["storage_parameters"]["token"]
except (KeyError, AssertionError):
pytest.skip("GitHub test with real API require a configured API token.")
if UPDATE_MOCK:
# Save all requests response to use them with mock
from os import remove, listdir
from airfs._core import cache
from airfs._core.storage_manager import get_instance
for file in listdir(MOCK_DIR):
remove(join(MOCK_DIR, file))
system = get_instance("https://github.com")
request = system.client._request
def request_save(method, url, *args, params=None, **kwargs):
"""Performs requests and save result"""
resp = request(method, url, *args, params=params, **kwargs)
resp_dict = dict(
url=resp.url,
headers=resp.headers,
status_code=resp.status_code,
content=resp.content,
reason=resp.reason,
)
with open(
join(MOCK_DIR, cache._hash_name(url + json.dumps(params or dict()))),
"wb",
) as resp_cache:
pickle.dump(resp_dict, resp_cache)
return MockResponse(**resp_dict)
cache_dir = cache.CACHE_DIR
cache.CACHE_DIR = str(tmpdir.ensure_dir("cache"))
system.client._request = request_save
system.client.session.request = request_save
try:
github_storage_scenario()
finally:
if UPDATE_MOCK:
system.client.session.request = request
system.client._request = request
cache.CACHE_DIR = cache_dir
def test_github_mocked_storage(tmpdir):
"""Tests airfs.github specificities with a mock"""
if UPDATE_MOCK:
pytest.skip("Mock is updating...")
from collections import OrderedDict
import airfs._core.storage_manager as storage_manager
from airfs._core import cache
cache_dir = cache.CACHE_DIR
cache.CACHE_DIR = str(tmpdir.ensure_dir("cache"))
mounted = storage_manager.MOUNTED
storage_manager.MOUNTED = OrderedDict()
def request_load(_, url, *__, params=None, **___):
"""Loads request result"""
try:
with open(
join(MOCK_DIR, cache._hash_name(url + json.dumps(params or dict()))),
"rb",
) as resp_cache:
return MockResponse(**pickle.load(resp_cache))
except FileNotFoundError:
pytest.fail("Please, update mock responses (see UPDATE_MOCK)")
try:
# Loads requests responses from previously cached responses
storage = storage_manager.mount(storage="github", name="github_test")
client = storage["github"]["system_cached"].client
client._request = request_load
client.session.request = request_load
# Tests
github_storage_scenario()
finally:
storage_manager.MOUNTED = mounted
cache.CACHE_DIR = cache_dir
def github_storage_scenario():
"""
Test scenario. Called from both mocked and non-mocked tests.
"""
exists_scenario()
listdir_scenario()
stat_scenario()
symlink_scenario()
get_scenario()
def listdir_scenario():
"""
Tests listing
"""
from io import UnsupportedOperation
import airfs
# Users
with pytest.raises(UnsupportedOperation):
airfs.listdir("https://github.com/")
# Repos
assert "airfs" in airfs.listdir("https://github.com/jgoutin"), "List repos"
assert sorted(airfs.listdir("https://github.com/jgoutin/airfs")) == [
"HEAD",
"archive",
"blob",
"branches",
"commits",
"refs",
"releases",
"tags",
"tree",
], "List repo content"
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/not_exists")
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/not_exists")
assert sorted(airfs.listdir("https://github.com/jgoutin/airfs/refs")) == [
"heads",
"tags",
], "List refs"
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/refs/not_exists")
# HEAD
assert "LICENSE" in airfs.listdir(
"https://github.com/jgoutin/airfs/HEAD"
), "List HEAD"
with pytest.raises(NotADirectoryError):
airfs.listdir("https://github.com/jgoutin/airfs/HEAD/LICENSE")
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/HEAD/not_exists")
assert "_core" in airfs.listdir(
"https://github.com/jgoutin/airfs/HEAD/airfs"
), "List HEAD subdirectory"
# Branches
assert "master" in airfs.listdir(
"https://github.com/jgoutin/airfs/branches"
), "List branches"
assert "master" in airfs.listdir(
"https://github.com/jgoutin/airfs/refs/heads"
), "List branches in refs"
assert "LICENSE" in airfs.listdir(
"https://github.com/jgoutin/airfs/branches/master"
), "List branch content"
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/branches/not_exists")
# Commits
commit_id = airfs.listdir("https://github.com/jgoutin/airfs/commits")[0]
assert len(commit_id) == 40, "List commits"
assert "LICENSE" in airfs.listdir(
f"https://github.com/jgoutin/airfs/commits/{commit_id}"
), "List commit content"
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/commits/not_exists")
# Tags
assert "1.4.0" in airfs.listdir(
"https://github.com/jgoutin/airfs/tags"
), "List tags"
assert "1.4.0" in airfs.listdir(
"https://github.com/jgoutin/airfs/refs/tags"
), "List tags in refs"
assert "LICENSE" in airfs.listdir(
"https://github.com/jgoutin/airfs/tags/1.4.0"
), "List tag content"
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/tags/not_exists")
# Archives
assert "1.4.0.tar.gz" in airfs.listdir(
"https://github.com/jgoutin/airfs/archive"
), "List tar.gz archives"
assert "1.4.0.zip" in airfs.listdir(
"https://github.com/jgoutin/airfs/archive"
), "List zip archives"
with pytest.raises(NotADirectoryError):
airfs.listdir("https://github.com/jgoutin/airfs/archive/1.4.0.tar.gz")
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/archive/1.4.0.tar.xz")
# Releases
assert "latest" in airfs.listdir(
"https://github.com/jgoutin/airfs/releases"
), "List releases"
assert "1.4.0" in airfs.listdir(
"https://github.com/jgoutin/airfs/releases/tag"
), "List release tags"
assert sorted(
airfs.listdir("https://github.com/jgoutin/airfs/releases/tag/1.4.0")
) == ["archive", "assets", "tree"], "List release content"
with pytest.raises(FileNotFoundError):
airfs.listdir("https://github.com/jgoutin/airfs/releases/tag/not_exists")
assert sorted(
airfs.listdir("https://github.com/jgoutin/airfs/releases/latest")
) == ["archive", "assets", "tree"], "List latest release content"
assert sorted(
airfs.listdir("https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive")
) == ["source_code.tar.gz", "source_code.zip"], "List release archive"
with pytest.raises(FileNotFoundError):
airfs.listdir(
"https://github.com/jgoutin/airfs/releases/tag/not_exists/archive"
)
with pytest.raises(NotADirectoryError):
airfs.listdir(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive/"
"source_code.tar.gz"
)
assert sorted(
airfs.listdir("https://github.com/jgoutin/airfs/releases/latest/archive")
) == ["source_code.tar.gz", "source_code.zip"], "List latest release archive"
with pytest.raises(NotADirectoryError):
airfs.listdir(
"https://github.com/jgoutin/airfs/releases/latest/archive/"
"source_code.tar.gz"
)
assert sorted(
airfs.listdir("https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets")
) == ["airfs-1.4.0-py3-none-any.whl"], "List release assets"
with pytest.raises(NotADirectoryError):
airfs.listdir(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets/"
"airfs-1.4.0-py3-none-any.whl"
)
with pytest.raises(FileNotFoundError):
airfs.listdir(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets/not_exists"
)
def symlink_scenario():
"""
Tests symbolic links
"""
from io import UnsupportedOperation
import airfs
# Git tree
assert airfs.islink("https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink")
assert airfs.exists("https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink")
assert airfs.lexists(
"https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink"
)
assert not airfs.isdir(
"https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink"
)
assert airfs.isfile("https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink")
assert not airfs.islink("https://github.com/jgoutin/airfs/HEAD/LICENSE")
assert not airfs.islink("https://github.com/jgoutin/airfs/HEAD/tests")
assert (
airfs.readlink("https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink")
== "../../airfs/_core/exceptions.py"
)
assert (
airfs.realpath("https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink")
== "https://github.com/jgoutin/airfs/HEAD/airfs/_core/exceptions.py"
)
assert (
airfs.realpath(
"https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink_to_symlink"
)
== "https://github.com/jgoutin/airfs/HEAD/airfs/_core/exceptions.py"
)
with pytest.raises(UnsupportedOperation):
airfs.symlink(
"https://github.com/jgoutin/airfs/HEAD/airfs/_core/exceptions.py",
"https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink_2",
)
with pytest.raises(OSError):
airfs.readlink("https://github.com/jgoutin/airfs/HEAD/LICENSE")
# HEAD
assert airfs.islink("https://github.com/jgoutin/airfs/HEAD")
assert (
airfs.readlink("https://github.com/jgoutin/airfs/HEAD")
== "https://github.com/jgoutin/airfs/branches/master"
)
assert airfs.realpath("https://github.com/jgoutin/airfs/HEAD").startswith(
"https://github.com/jgoutin/airfs/commits/"
)
# Branches
assert airfs.readlink(
"https://github.com/jgoutin/airfs/branches/master"
).startswith("https://github.com/jgoutin/airfs/commits/")
assert airfs.realpath(
"https://github.com/jgoutin/airfs/branches/master"
).startswith("https://github.com/jgoutin/airfs/commits/")
assert airfs.readlink(
"https://github.com/jgoutin/airfs/refs/heads/master"
).startswith("https://github.com/jgoutin/airfs/commits/")
assert airfs.readlink("https://github.com/jgoutin/airfs/blob/master").startswith(
"https://github.com/jgoutin/airfs/commits/"
)
assert airfs.readlink("https://github.com/jgoutin/airfs/tree/master").startswith(
"https://github.com/jgoutin/airfs/commits/"
)
# Tags
assert airfs.readlink("https://github.com/jgoutin/airfs/tags/1.4.0").startswith(
"https://github.com/jgoutin/airfs/commits/"
)
assert airfs.realpath("https://github.com/jgoutin/airfs/tags/1.4.0").startswith(
"https://github.com/jgoutin/airfs/commits/"
)
assert airfs.readlink(
"https://github.com/jgoutin/airfs/refs/tags/1.4.0"
).startswith("https://github.com/jgoutin/airfs/commits/")
assert airfs.readlink("https://github.com/jgoutin/airfs/blob/1.4.0").startswith(
"https://github.com/jgoutin/airfs/commits/"
)
assert airfs.readlink("https://github.com/jgoutin/airfs/tree/1.4.0").startswith(
"https://github.com/jgoutin/airfs/commits/"
)
# Releases
assert airfs.readlink(
"https://github.com/jgoutin/airfs/releases/latest"
).startswith("https://github.com/jgoutin/airfs/releases/tag/")
def exists_scenario():
"""
Tests exists, isdir, isfile
"""
import airfs
# Root
assert airfs.exists("https://github.com")
assert airfs.isdir("https://github.com")
assert not airfs.isfile("https://github.com")
# User
assert airfs.exists("https://github.com/jgoutin")
assert airfs.isdir("https://github.com/jgoutin")
assert not airfs.isfile("https://github.com/jgoutin")
# Repos
assert airfs.exists("https://github.com/jgoutin/airfs")
assert airfs.isdir("https://github.com/jgoutin/airfs")
assert not airfs.isfile("https://github.com/jgoutin/airfs")
assert not airfs.exists("https://github.com/jgoutin/not_exists")
assert not airfs.isdir("https://github.com/jgoutin/not_exists")
assert not airfs.isfile("https://github.com/jgoutin/not_exists")
assert not airfs.exists("https://github.com/jgoutin/airfs/refs/not_exists")
assert not airfs.isdir("https://github.com/jgoutin/airfs/refs/not_exists")
assert not airfs.isfile("https://github.com/jgoutin/airfs/refs/not_exists")
assert airfs.exists("https://raw.githubusercontent.com/jgoutin/airfs")
assert airfs.isdir("https://raw.githubusercontent.com/jgoutin/airfs")
assert not airfs.isfile("https://raw.githubusercontent.com/jgoutin/airfs")
# HEAD
assert airfs.exists("https://github.com/jgoutin/airfs/HEAD")
assert airfs.isdir("https://github.com/jgoutin/airfs/HEAD")
assert not airfs.isfile("https://github.com/jgoutin/airfs/HEAD")
assert airfs.exists("https://github.com/jgoutin/airfs/tree/HEAD")
assert airfs.isdir("https://github.com/jgoutin/airfs/tree/HEAD")
assert not airfs.isfile("https://github.com/jgoutin/tree/HEAD")
assert airfs.exists("https://github.com/jgoutin/airfs/blob/HEAD")
assert airfs.isdir("https://github.com/jgoutin/airfs/blob/HEAD")
assert not airfs.isfile("https://github.com/jgoutin/blob/HEAD")
assert airfs.exists("https://raw.githubusercontent.com/jgoutin/airfs/HEAD")
assert airfs.isdir("https://raw.githubusercontent.com/jgoutin/airfs/HEAD")
assert not airfs.isfile("https://raw.githubusercontent.com/jgoutin/airfs/HEAD")
# Branches
assert airfs.exists("https://github.com/jgoutin/airfs/branches")
assert airfs.isdir("https://github.com/jgoutin/airfs/branches")
assert not airfs.isfile("https://github.com/jgoutin/airfs/branches")
assert airfs.exists("https://github.com/jgoutin/airfs/branches/master")
assert airfs.isdir("https://github.com/jgoutin/airfs/branches/master")
assert not airfs.isfile("https://github.com/jgoutin/airfs/branches/master")
assert airfs.exists("https://github.com/jgoutin/airfs/refs/heads/master")
assert airfs.isdir("https://github.com/jgoutin/airfs/refs/heads/master")
assert not airfs.isfile("https://github.com/jgoutin/airfs/refs/heads/master")
assert airfs.exists("https://github.com/jgoutin/airfs/tree/master")
assert airfs.isdir("https://github.com/jgoutin/airfs/tree/master")
assert not airfs.isfile("https://github.com/jgoutin/tree/master")
assert airfs.exists("https://github.com/jgoutin/airfs/blob/master")
assert airfs.isdir("https://github.com/jgoutin/airfs/blob/master")
assert not airfs.isfile("https://github.com/jgoutin/blob/master")
assert airfs.exists("https://raw.githubusercontent.com/jgoutin/airfs/master")
assert airfs.isdir("https://raw.githubusercontent.com/jgoutin/airfs/master")
assert not airfs.isfile("https://raw.githubusercontent.com/jgoutin/airfs/master")
assert not airfs.exists("https://github.com/jgoutin/airfs/branches/not_exists")
assert not airfs.isdir("https://github.com/jgoutin/airfs/branches/not_exists")
assert not airfs.isfile("https://github.com/jgoutin/airfs/branches/not_exists")
# Tags
assert airfs.exists("https://github.com/jgoutin/airfs/tags")
assert airfs.isdir("https://github.com/jgoutin/airfs/tags")
assert not airfs.isfile("https://github.com/jgoutin/airfs/tags")
assert airfs.exists("https://github.com/jgoutin/airfs/tags/1.4.0")
assert airfs.isdir("https://github.com/jgoutin/airfs/tags/1.4.0")
assert not airfs.isfile("https://github.com/jgoutin/airfs/tags/1.4.0")
assert airfs.exists("https://github.com/jgoutin/airfs/refs/tags/1.4.0")
assert airfs.isdir("https://github.com/jgoutin/airfs/refs/tags/1.4.0")
assert not airfs.isfile("https://github.com/jgoutin/airfs/refs/tags/1.4.0")
assert airfs.exists("https://github.com/jgoutin/airfs/tree/1.4.0")
assert airfs.isdir("https://github.com/jgoutin/airfs/tree/1.4.0")
assert not airfs.isfile("https://github.com/jgoutin/tree/1.4.0")
assert airfs.exists("https://github.com/jgoutin/airfs/blob/1.4.0")
assert airfs.isdir("https://github.com/jgoutin/airfs/blob/1.4.0")
assert not airfs.isfile("https://github.com/jgoutin/blob/1.4.0")
assert airfs.exists("https://raw.githubusercontent.com/jgoutin/airfs/1.4.0")
assert airfs.isdir("https://raw.githubusercontent.com/jgoutin/airfs/1.4.0")
assert not airfs.isfile("https://raw.githubusercontent.com/jgoutin/airfs/1.4.0")
assert not airfs.exists("https://github.com/jgoutin/airfs/tags/not_exists")
assert not airfs.isdir("https://github.com/jgoutin/airfs/tags/not_exists")
assert not airfs.isfile("https://github.com/jgoutin/airfs/tags/not_exists")
# Commits
assert airfs.exists("https://github.com/jgoutin/airfs/commits")
assert airfs.isdir("https://github.com/jgoutin/airfs/commits")
assert not airfs.isfile("https://github.com/jgoutin/airfs/commits")
commit_id = airfs.listdir("https://github.com/jgoutin/airfs/commits")[0]
assert airfs.exists(f"https://github.com/jgoutin/airfs/commits/{commit_id}")
assert airfs.isdir(f"https://github.com/jgoutin/airfs/commits/{commit_id}")
assert not airfs.isfile(f"https://github.com/jgoutin/airfs/commits/{commit_id}")
assert airfs.exists(f"https://github.com/jgoutin/airfs/tree/{commit_id}")
assert airfs.isdir(f"https://github.com/jgoutin/airfs/tree/{commit_id}")
assert not airfs.isfile(f"https://github.com/jgoutin/tree/{commit_id}")
assert airfs.exists(f"https://github.com/jgoutin/airfs/blob/{commit_id}")
assert airfs.isdir(f"https://github.com/jgoutin/airfs/blob/{commit_id}")
assert not airfs.isfile(f"https://github.com/jgoutin/blob/{commit_id}")
assert airfs.exists(f"https://raw.githubusercontent.com/jgoutin/airfs/{commit_id}")
assert airfs.isdir(f"https://raw.githubusercontent.com/jgoutin/airfs/{commit_id}")
assert not airfs.isfile(
f"https://raw.githubusercontent.com/jgoutin/airfs/{commit_id}"
)
assert not airfs.exists("https://github.com/jgoutin/airfs/commits/not_exists")
assert not airfs.isdir("https://github.com/jgoutin/airfs/commits/not_exists")
assert not airfs.isfile("https://github.com/jgoutin/airfs/commits/not_exists")
# Git Tree
assert airfs.exists("https://github.com/jgoutin/airfs/HEAD/tests")
assert airfs.isdir("https://github.com/jgoutin/airfs/HEAD/tests")
assert not airfs.isfile("https://github.com/jgoutin/airfs/HEAD/tests")
assert airfs.exists("https://github.com/jgoutin/airfs/HEAD/LICENSE")
assert not airfs.isdir("https://github.com/jgoutin/airfs/HEAD/LICENSE")
assert airfs.isfile("https://github.com/jgoutin/airfs/HEAD/LICENSE")
assert airfs.exists("https://raw.githubusercontent.com/jgoutin/airfs/HEAD/LICENSE")
assert not airfs.isdir(
"https://raw.githubusercontent.com/jgoutin/airfs/HEAD/LICENSE"
)
assert airfs.isfile("https://raw.githubusercontent.com/jgoutin/airfs/HEAD/LICENSE")
assert not airfs.exists("https://github.com/jgoutin/airfs/HEAD/not_exists")
assert not airfs.isdir("https://github.com/jgoutin/airfs/HEAD/not_exists")
assert not airfs.isfile("https://github.com/jgoutin/airfs/HEAD/not_exists")
# Archives
assert airfs.exists("https://github.com/jgoutin/airfs/archive")
assert airfs.isdir("https://github.com/jgoutin/airfs/archive")
assert not airfs.isfile("https://github.com/jgoutin/airfs/archive")
assert airfs.exists("https://github.com/jgoutin/airfs/archive/1.4.0.tar.gz")
assert not airfs.isdir("https://github.com/jgoutin/airfs/archive/1.4.0.tar.gz")
assert airfs.isfile("https://github.com/jgoutin/airfs/archive/1.4.0.tar.gz")
assert not airfs.exists("https://github.com/jgoutin/airfs/archive/not_exists")
assert not airfs.isdir("https://github.com/jgoutin/airfs/archive/not_exists")
assert not airfs.isfile("https://github.com/jgoutin/airfs/archive/not_exists")
# Releases
assert airfs.exists("https://github.com/jgoutin/airfs/releases")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases")
assert not airfs.isfile("https://github.com/jgoutin/airfs/releases")
assert airfs.exists("https://github.com/jgoutin/airfs/releases/tag")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases/tag")
assert not airfs.isfile("https://github.com/jgoutin/airfs/releases/tag")
assert airfs.exists("https://github.com/jgoutin/airfs/releases/tag/1.4.0")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases/tag/1.4.0")
assert not airfs.isfile("https://github.com/jgoutin/airfs/releases/tag/1.4.0")
assert airfs.exists("https://github.com/jgoutin/airfs/releases/latest")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases/latest")
assert not airfs.isfile("https://github.com/jgoutin/airfs/releases/latest")
assert airfs.exists("https://github.com/jgoutin/airfs/releases/latest/assets")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases/latest/assets")
assert not airfs.isfile("https://github.com/jgoutin/airfs/releases/latest/assets")
assert airfs.exists("https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets")
assert not airfs.isfile(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets"
)
assert airfs.exists(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets/"
"airfs-1.4.0-py3-none-any.whl"
)
assert not airfs.isdir(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets/"
"airfs-1.4.0-py3-none-any.whl"
)
assert airfs.isfile(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets/"
"airfs-1.4.0-py3-none-any.whl"
)
assert airfs.exists("https://github.com/jgoutin/airfs/releases/latest/archive")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases/latest/archive")
assert not airfs.isfile("https://github.com/jgoutin/airfs/releases/latest/archive")
assert airfs.exists("https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive")
assert airfs.isdir("https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive")
assert not airfs.isfile(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive"
)
assert airfs.exists(
"https://github.com/jgoutin/airfs/releases/latest/archive/source_code.tar.gz"
)
assert not airfs.isdir(
"https://github.com/jgoutin/airfs/releases/latest/archive/source_code.tar.gz"
)
assert airfs.isfile(
"https://github.com/jgoutin/airfs/releases/latest/archive/source_code.tar.gz"
)
assert airfs.exists(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive/source_code.tar.gz"
)
assert not airfs.isdir(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive/source_code.tar.gz"
)
assert airfs.isfile(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive/source_code.tar.gz"
)
def stat_scenario():
"""
Test stat.
"""
import airfs
from stat import S_IFDIR, S_IFREG, S_IFLNK
file = S_IFREG + 0o644
file_exec = S_IFREG + 0o755
directory = S_IFDIR + 0o644
link = S_IFLNK + 0o644
# User
stat = airfs.stat("https://github.com/jgoutin")
assert stat.st_mode == directory
assert stat.st_mtime > 0
assert stat.st_ctime > 0
# Repos
stat = airfs.stat("https://github.com/jgoutin/airfs")
assert stat.st_mode == directory
assert stat.st_mtime > 0
assert stat.st_ctime > 0
stat = airfs.stat("https://github.com/jgoutin/airfs/refs")
assert stat.st_mode == directory
stat = airfs.stat("https://github.com/jgoutin/airfs/refs/heads")
assert stat.st_mode == directory
stat = airfs.stat("https://github.com/jgoutin/airfs/refs/tags")
assert stat.st_mode == directory
with pytest.raises(FileNotFoundError):
airfs.stat("https://github.com/jgoutin/not_exists")
with pytest.raises(FileNotFoundError):
airfs.stat("https://github.com/jgoutin/airfs/refs/not_exists")
# HEAD
stat = airfs.lstat("https://github.com/jgoutin/airfs/HEAD")
assert stat.st_mode == link
assert stat.st_mtime > 0
assert stat.sha # noqa
# Branches
stat = airfs.stat("https://github.com/jgoutin/airfs/branches")
assert stat.st_mode == directory
stat = airfs.lstat("https://github.com/jgoutin/airfs/branches/master")
assert stat.st_mode == link
assert stat.st_mtime > 0
assert stat.sha # noqa
stat = airfs.stat("https://github.com/jgoutin/airfs/branches/master")
assert stat.st_mode == directory
assert stat.st_mtime > 0
assert stat.sha # noqa
stat = airfs.lstat("https://github.com/jgoutin/airfs/refs/heads/master")
assert stat.st_mode == link
assert stat.st_mtime > 0
assert stat.sha # noqa
# Tags
stat = airfs.stat("https://github.com/jgoutin/airfs/tags")
assert stat.st_mode == directory
stat = airfs.lstat("https://github.com/jgoutin/airfs/tags/1.4.0")
assert stat.st_mode == link
assert stat.st_mtime > 0
assert stat.sha # noqa
stat = airfs.lstat("https://github.com/jgoutin/airfs/refs/tags/1.4.0")
assert stat.st_mode == link
assert stat.st_mtime > 0
assert stat.sha # noqa
# Commits
stat = airfs.stat("https://github.com/jgoutin/airfs/commits")
assert stat.st_mode == directory
commit_id = airfs.listdir("https://github.com/jgoutin/airfs/commits")[0]
stat = airfs.stat(f"https://github.com/jgoutin/airfs/commits/{commit_id}")
assert stat.st_mode == directory
assert stat.st_mtime > 0
assert stat.sha # noqa
# Git Tree
stat = airfs.stat("https://github.com/jgoutin/airfs/HEAD/tests")
assert stat.st_mode == directory
assert stat.st_mtime > 0
assert stat.st_size == 0
assert stat.sha # noqa
stat = airfs.stat("https://github.com/jgoutin/airfs/HEAD/LICENSE")
assert stat.st_mode == file
assert stat.st_mtime > 0
assert stat.st_size > 0
assert stat.sha # noqa
stat = airfs.stat("https://github.com/jgoutin/airfs/HEAD/setup.py")
assert stat.st_mode == file_exec
assert stat.st_mtime > 0
assert stat.st_size > 0
assert stat.sha # noqa
symlink_stat = airfs.lstat(
"https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink"
)
assert symlink_stat.st_mode == link
assert symlink_stat.st_mtime > 0
assert symlink_stat.st_size > 0
assert symlink_stat.sha # noqa
stat = airfs.stat("https://github.com/jgoutin/airfs/HEAD/tests/resources/symlink")
assert stat.st_mode == file
assert stat.st_mtime > 0
assert stat.st_size > 0
assert stat.st_size > symlink_stat.st_size
assert stat.sha # noqa
with pytest.raises(FileNotFoundError):
airfs.stat("https://github.com/jgoutin/airfs/HEAD/not_exists")
# Releases
stat = airfs.stat(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive/source_code.tar.gz"
)
assert stat.st_mode == file
assert stat.st_size > 0
assert stat.st_mtime > 0
assert stat.sha # noqa
stat = airfs.stat(
"https://github.com/jgoutin/airfs/releases/latest/archive/source_code.tar.gz"
)
assert stat.st_mode == file
assert stat.st_size > 0
assert stat.st_mtime > 0
assert stat.sha # noqa
stat = airfs.stat(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets/"
"airfs-1.4.0-py3-none-any.whl"
)
assert stat.st_mode == file
assert stat.st_size > 0
assert stat.st_mtime > 0
assert stat.sha # noqa
def get_scenario():
"""
Test get files.
"""
import airfs
from airfs.storage.github import GithubBufferedIO, GithubRawIO
with airfs.open(
"https://github.com/jgoutin/airfs/releases/latest/archive/source_code.tar.gz",
buffering=0,
) as file:
assert isinstance(file, GithubRawIO)
assert file.read()
with airfs.open(
"https://github.com/jgoutin/airfs/releases/latest/archive/source_code.tar.gz"
) as file:
assert isinstance(file, GithubBufferedIO)
assert file.read()
with airfs.open(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/archive/"
"source_code.tar.gz",
buffering=0,
) as file:
assert file.read()
with airfs.open(
"https://github.com/jgoutin/airfs/releases/tag/1.4.0/assets/"
"airfs-1.4.0-py3-none-any.whl",
buffering=0,
) as file:
assert file.read()
with airfs.open(
"https://github.com/jgoutin/airfs/HEAD/LICENSE",
buffering=0,
) as file:
assert file.read()
with airfs.open(
"https://raw.githubusercontent.com/jgoutin/airfs/HEAD/LICENSE",
buffering=0,
) as file:
assert file.read()
| 36.21764
| 88
| 0.671232
| 4,171
| 31,618
| 5.026373
| 0.056102
| 0.121631
| 0.160935
| 0.236394
| 0.840591
| 0.818889
| 0.800525
| 0.783115
| 0.749964
| 0.634629
| 0
| 0.00997
| 0.178348
| 31,618
| 872
| 89
| 36.259174
| 0.797028
| 0.031216
| 0
| 0.361199
| 0
| 0.050473
| 0.45069
| 0.008574
| 0
| 0
| 0
| 0
| 0.419558
| 1
| 0.023659
| false
| 0
| 0.033123
| 0
| 0.064669
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
fa12a4bca87b97c371fe819b6bdc7cd8893947c9
| 6,014
|
py
|
Python
|
datasets/transform.py
|
GIShkl/GAOFEN2021_CHANGEDETECTION
|
5b7251cb1e951a04c7effacab6c1233232158472
|
[
"MIT"
] | 3
|
2021-12-12T09:45:41.000Z
|
2022-03-10T08:34:22.000Z
|
datasets/transform.py
|
lyp19/GAOFEN2021_CHANGEDETECTION
|
5b7251cb1e951a04c7effacab6c1233232158472
|
[
"MIT"
] | null | null | null |
datasets/transform.py
|
lyp19/GAOFEN2021_CHANGEDETECTION
|
5b7251cb1e951a04c7effacab6c1233232158472
|
[
"MIT"
] | 1
|
2021-11-13T05:40:18.000Z
|
2021-11-13T05:40:18.000Z
|
import numpy as np
from PIL import Image
import random
# class RandomFlipOrRotate(object):
# def __call__(self, sample):
# img1, img2, mask1, mask2, mask_bin = \
# sample['img1'], sample['img2'], sample['mask1'], sample['mask2'], sample['mask_bin']
# # random() 方法返回随机生成的一个实数，它在[0,1)范围内
# rand = random.random()
# if rand < 1 / 6:
# img1 = img1.transpose(Image.FLIP_LEFT_RIGHT)
# mask1 = mask1.transpose(Image.FLIP_LEFT_RIGHT)
# img2 = img2.transpose(Image.FLIP_LEFT_RIGHT)
# mask2 = mask2.transpose(Image.FLIP_LEFT_RIGHT)
# mask_bin = mask_bin.transpose(Image.FLIP_LEFT_RIGHT)
# elif rand < 2 / 6:
# img1 = img1.transpose(Image.FLIP_TOP_BOTTOM)
# mask1 = mask1.transpose(Image.FLIP_TOP_BOTTOM)
# img2 = img2.transpose(Image.FLIP_TOP_BOTTOM)
# mask2 = mask2.transpose(Image.FLIP_TOP_BOTTOM)
# mask_bin = mask_bin.transpose(Image.FLIP_TOP_BOTTOM)
# elif rand < 3 / 6:
# img1 = img1.transpose(Image.ROTATE_90)
# mask1 = mask1.transpose(Image.ROTATE_90)
# img2 = img2.transpose(Image.ROTATE_90)
# mask2 = mask2.transpose(Image.ROTATE_90)
# mask_bin = mask_bin.transpose(Image.ROTATE_90)
# elif rand < 4 / 6:
# img1 = img1.transpose(Image.ROTATE_180)
# mask1 = mask1.transpose(Image.ROTATE_180)
# img2 = img2.transpose(Image.ROTATE_180)
# mask2 = mask2.transpose(Image.ROTATE_180)
# mask_bin = mask_bin.transpose(Image.ROTATE_180)
# elif rand < 5 / 6:
# img1 = img1.transpose(Image.ROTATE_270)
# mask1 = mask1.transpose(Image.ROTATE_270)
# img2 = img2.transpose(Image.ROTATE_270)
# mask2 = mask2.transpose(Image.ROTATE_270)
# mask_bin = mask_bin.transpose(Image.ROTATE_270)
# return {'img1': img1, 'img2': img2, 'mask1': mask1, 'mask2': mask2, 'mask_bin': mask_bin}
class RandomFlipOrRotate(object):
def __call__(self, sample):
img, label = sample['img'], sample['label']
# random() 方法返回随机生成的一个实数，它在[0,1)范围内
rand = random.random()
if rand < 1 / 6:
img = img.transpose(Image.FLIP_LEFT_RIGHT)
label = label.transpose(Image.FLIP_LEFT_RIGHT)
elif rand < 2 / 6:
img = img.transpose(Image.FLIP_TOP_BOTTOM)
label = label.transpose(Image.FLIP_TOP_BOTTOM)
elif rand < 3 / 6:
img = img.transpose(Image.ROTATE_90)
label = label.transpose(Image.ROTATE_90)
elif rand < 4 / 6:
img = img.transpose(Image.ROTATE_180)
label = label.transpose(Image.ROTATE_180)
elif rand < 5 / 6:
img = img.transpose(Image.ROTATE_270)
label = label.transpose(Image.ROTATE_270)
return {'img': img, 'label': label}
#
# class RandomFlipOrRotate(object):
# def __call__(self, sample):
# img1, img2, mask1, mask2, mask_bin, edge1, edge2, edge_bin = sample['img1'], sample[
# 'img2'], sample['mask1'], sample['mask2'], sample['mask_bin'], sample['edge1'], sample['edge2'], sample['edge_bin']
# # random() 方法返回随机生成的一个实数，它在[0,1)范围内
# rand = random.random()
# if rand < 1 / 6:
# img1 = img1.transpose(Image.FLIP_LEFT_RIGHT)
# mask1 = mask1.transpose(Image.FLIP_LEFT_RIGHT)
# img2 = img2.transpose(Image.FLIP_LEFT_RIGHT)
# mask2 = mask2.transpose(Image.FLIP_LEFT_RIGHT)
# mask_bin = mask_bin.transpose(Image.FLIP_LEFT_RIGHT)
# edge1 = edge1.transpose(Image.FLIP_LEFT_RIGHT)
# edge2 = edge2.transpose(Image.FLIP_LEFT_RIGHT)
# edge_bin = edge_bin.transpose(Image.FLIP_LEFT_RIGHT)
# elif rand < 2 / 6:
# img1 = img1.transpose(Image.FLIP_TOP_BOTTOM)
# mask1 = mask1.transpose(Image.FLIP_TOP_BOTTOM)
# img2 = img2.transpose(Image.FLIP_TOP_BOTTOM)
# mask2 = mask2.transpose(Image.FLIP_TOP_BOTTOM)
# mask_bin = mask_bin.transpose(Image.FLIP_TOP_BOTTOM)
# edge1 = edge1.transpose(Image.FLIP_TOP_BOTTOM)
# edge2 = edge2.transpose(Image.FLIP_TOP_BOTTOM)
# edge_bin = edge_bin.transpose(Image.FLIP_TOP_BOTTOM)
# elif rand < 3 / 6:
# img1 = img1.transpose(Image.ROTATE_90)
# mask1 = mask1.transpose(Image.ROTATE_90)
# img2 = img2.transpose(Image.ROTATE_90)
# mask2 = mask2.transpose(Image.ROTATE_90)
# mask_bin = mask_bin.transpose(Image.ROTATE_90)
# edge1 = edge1.transpose(Image.ROTATE_90)
# edge2 = edge2.transpose(Image.ROTATE_90)
# edge_bin = edge_bin.transpose(Image.ROTATE_90)
# elif rand < 4 / 6:
# img1 = img1.transpose(Image.ROTATE_180)
# mask1 = mask1.transpose(Image.ROTATE_180)
# img2 = img2.transpose(Image.ROTATE_180)
# mask2 = mask2.transpose(Image.ROTATE_180)
# mask_bin = mask_bin.transpose(Image.ROTATE_180)
# edge1 = edge1.transpose(Image.ROTATE_180)
# edge2 = edge2.transpose(Image.ROTATE_180)
# edge_bin = edge_bin.transpose(Image.ROTATE_180)
# elif rand < 5 / 6:
# img1 = img1.transpose(Image.ROTATE_270)
# mask1 = mask1.transpose(Image.ROTATE_270)
# img2 = img2.transpose(Image.ROTATE_270)
# mask2 = mask2.transpose(Image.ROTATE_270)
# mask_bin = mask_bin.transpose(Image.ROTATE_270)
# edge1 = edge1.transpose(Image.ROTATE_270)
# edge2 = edge2.transpose(Image.ROTATE_270)
# edge_bin = edge_bin.transpose(Image.ROTATE_270)
# return {'img1': img1, 'img2': img2, 'mask1': mask1, 'mask2': mask2,
# 'mask_bin': mask_bin, 'edge1': edge1, 'edge2': edge2, 'edge_bin': edge_bin}
| 46.620155
| 129
| 0.598603
| 718
| 6,014
| 4.792479
| 0.069638
| 0.305144
| 0.261552
| 0.095902
| 0.943912
| 0.820401
| 0.783784
| 0.754432
| 0.735542
| 0.714037
| 0
| 0.068582
| 0.282341
| 6,014
| 128
| 130
| 46.984375
| 0.728684
| 0.812604
| 0
| 0
| 0
| 0
| 0.015504
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.043478
| false
| 0
| 0.130435
| 0
| 0.26087
| 0
| 0
| 0
| 0
| null | 1
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 9
|
fa30998d7d404169793fae27fcf543fba1aa26e6
| 91
|
py
|
Python
|
src_old/tests/scripts/vectors.py
|
toddrme2178/pyccel
|
deec37503ab0c5d0bcca1a035f7909f7ce8ef653
|
[
"MIT"
] | null | null | null |
src_old/tests/scripts/vectors.py
|
toddrme2178/pyccel
|
deec37503ab0c5d0bcca1a035f7909f7ce8ef653
|
[
"MIT"
] | null | null | null |
src_old/tests/scripts/vectors.py
|
toddrme2178/pyccel
|
deec37503ab0c5d0bcca1a035f7909f7ce8ef653
|
[
"MIT"
] | null | null | null |
# coding: utf-8
y1 = vector(1, 3)
y2 = vector((1,1), (3,3))
y3 = vector((1,1,1), (3,3,3))
| 15.166667
| 29
| 0.505495
| 21
| 91
| 2.190476
| 0.428571
| 0.456522
| 0.347826
| 0.173913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.213333
| 0.175824
| 91
| 5
| 30
| 18.2
| 0.4
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 7
|
fa71e7dd4dd27597471eb0a8827fb8b25fbfa1ac
| 45,844
|
py
|
Python
|
tests/apis/test_submit_review_api.py
|
Fozia-Zafar/Device-Registration-Subsystem
|
7854dd314c2f5cb09d722d16ca0114c4cd9907b6
|
[
"BSD-3-Clause-Clear"
] | null | null | null |
tests/apis/test_submit_review_api.py
|
Fozia-Zafar/Device-Registration-Subsystem
|
7854dd314c2f5cb09d722d16ca0114c4cd9907b6
|
[
"BSD-3-Clause-Clear"
] | null | null | null |
tests/apis/test_submit_review_api.py
|
Fozia-Zafar/Device-Registration-Subsystem
|
7854dd314c2f5cb09d722d16ca0114c4cd9907b6
|
[
"BSD-3-Clause-Clear"
] | null | null | null |
"""
module for review submit-review api tests
Copyright (c) 2018 Qualcomm Technologies, Inc.
All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted (subject to the
limitations in the disclaimer below) provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this list of conditions and the following
disclaimer.
* Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following
disclaimer in the documentation and/or other materials provided with the distribution.
* Neither the name of Qualcomm Technologies, Inc. nor the names of its contributors may be used to endorse or promote
products derived from this software without specific prior written permission.
NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE. THIS SOFTWARE IS PROVIDED BY
THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR
TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.
"""
import json
from tests._helpers import create_dummy_request, create_assigned_dummy_request, create_dummy_devices
from app.api.v1.models.approvedimeis import ApprovedImeis
from app.api.v1.models.regcomments import RegComments
from app.api.v1.models.deregcomments import DeRegComments
from app.api.v1.models.notification import Notification
from app.api.v1.models.devicequota import DeviceQuota
# api urls
SUBMIT_REVIEW_API = 'api/v1/review/submit-review'
def test_invalid_input_params(flask_app):
"""Verify that api responds properly when invalid input supplied."""
# str instead of int in request_id field
headers = {'Content-Type': 'application/json'}
body_data = {
'request_id': 'abcd',
'request_type': 'registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 422
data = json.loads(rv.data.decode('utf-8'))
assert data['request_id'] == ["Bad 'request_id':'abcd' argument format. Accepts only integer"]
# int instead of str in request_type
body_data['request_id'] = 1
body_data['request_type'] = 2
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 422
data = json.loads(rv.data.decode('utf-8'))
assert data['request_type'] == ["Bad 'request_type':'2' argument format. Accepts only one of ["
"'registration_request', 'de_registration_request']"]
# other str than registration_request/de_registration_request in request_type
body_data['request_type'] = 'abcd'
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 422
data = json.loads(rv.data.decode('utf-8'))
assert data['request_type'] == ["Bad 'request_type':'abcd' argument format. Accepts only one of ["
"'registration_request', 'de_registration_request']"]
# int instead of str in reviewer_id
body_data['request_type'] = 'registration_request'
body_data['reviewer_id'] = 1
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 422
data = json.loads(rv.data.decode('utf-8'))
assert data['reviewer_id'] == ["Bad 'reviewer_id':'1' argument format."]
def test_null_input_params(flask_app):
"""Verify that the api returns proper error response when no params are given."""
headers = {'Content-Type': 'application/json'}
# no request id argument
body_data = {
'request_type': 'registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 422
data = json.loads(rv.data.decode('utf-8'))
assert data['error'] == ["request_id is required"]
# no request_type argument
body_data['request_id'] = 1
del body_data['request_type']
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 422
data = json.loads(rv.data.decode('utf-8'))
assert data['error'] == ["request_type is required"]
# no reviewer_id argument
body_data['request_type'] = 'registration_request'
del body_data['reviewer_id']
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 422
data = json.loads(rv.data.decode('utf-8'))
assert data['error'] == ["reviewer_id is required"]
def test_request_not_exists(flask_app, db): # pylint: disable=unused-argument
"""Verify that api responds for request which does not exists in system."""
# registration_request test
headers = {'Content-Type': 'application/json'}
body_data = {
'request_id': 37284234802304802384,
'request_type': 'registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 204
# de registration request
body_data['request_type'] = 'de_registration_request'
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 204
def test_submitted_registration_requests(flask_app, db): # pylint: disable=unused-argument
"""Verify that the api reponds properly when request is already
approved, ejected or closed.
"""
# approved request
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['86834403015010']]",
'm_location': 'local',
'user_name': 'assign rev user 1',
'user_id': 'assign-rev-user-1'
}
# registration request test, creating dummy request
request = create_dummy_request(data, 'Registration', 'Approved')
assert request
assert request.status == 6
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['Request cannot be entertained, '
'request is already approved']
# closed request
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['86834403015010']]",
'm_location': 'local',
'user_name': 'assign rev user 1',
'user_id': 'assign-rev-user-1'
}
# registration request test, creating dummy request
request = create_dummy_request(data, 'Registration', 'Closed')
assert request
assert request.status == 8
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['Request cannot be entertained, '
'request is already closed']
# rejected request
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['86834403015010']]",
'm_location': 'local',
'user_name': 'assign rev user 1',
'user_id': 'assign-rev-user-1'
}
# registration request test, creating dummy request
request = create_dummy_request(data, 'Registration', 'Rejected')
assert request
assert request.status == 7
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['Request cannot be entertained, '
'request is already rejected']
def test_submitted_de_registration_requests(flask_app, db): # pylint: disable=unused-argument
"""Verify that the api reponds properly when request is already
approved, ejected or closed."""
# approved request
headers = {'Content-Type': 'application/json'}
data = {
'file': 'de-reg-test-file',
'device_count': 1,
'user_id': 'assign-rev-user-1',
'user_name': 'assign rev user 1',
'reason': 'because we have to run tests successfully'
}
request = create_dummy_request(data, 'De-Registration', 'Approved')
assert request
assert request.status == 6
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['Request cannot be entertained, '
'request is already approved']
# closed request
data = {
'file': 'de-reg-test-file',
'device_count': 1,
'user_id': 'assign-rev-user-1',
'user_name': 'assign rev user 1',
'reason': 'because we have to run tests successfully'
}
request = create_dummy_request(data, 'De-Registration', 'Closed')
assert request
assert request.status == 8
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['Request cannot be entertained, '
'request is already closed']
# rejected request
data = {
'file': 'de-reg-test-file',
'device_count': 1,
'user_id': 'assign-rev-user-1',
'user_name': 'assign rev user 1',
'reason': 'because we have to run tests successfully'
}
request = create_dummy_request(data, 'De-Registration', 'Rejected')
assert request
assert request.status == 7
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['Request cannot be entertained, '
'request is already rejected']
def test_invalid_reviewer_id(flask_app, db): # pylint: disable=unused-argument
"""Verify that only assigned reviewer can submit the review and api responds properly"""
# registration request
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['86834403015010']]",
'm_location': 'local',
'user_name': 'assign rev user 1',
'user_id': 'assign-rev-user-1'
}
request = create_assigned_dummy_request(data, 'Registration', 'rev230987', 'rev 230987')
assert request
assert request.reviewer_id == 'rev230987'
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['invalid reviewer rev1']
# de registration request
data = {
'file': 'de-reg-test-file',
'device_count': 1,
'user_id': 'assign-rev-user-1',
'user_name': 'assign rev user 1',
'reason': 'because we have to run tests successfully'
}
request = create_assigned_dummy_request(data, 'De-Registration', 'rev342567', 'rev 23')
assert request
assert request.reviewer_id == 'rev342567'
request_id = request.id
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'rev1'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
assert json.loads(rv.data.decode('utf-8'))['error'] == ['invalid reviewer rev1']
def test_registration_request_rejected_section(flask_app, db): # pylint: disable=unused-argument
"""Verify that the registration request gets rejected when anyone of the section
is marked as rejected, imeis are removed from approvedimeis and notification is
being generated.
"""
# only one section is reviewed and rejected
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['23010403010533']]",
'm_location': 'local',
'user_name': '23423423rev user 1',
'user_id': 'assign-rev23442342-user-1'
}
request = create_assigned_dummy_request(data, 'Registration', 'rev230987', 'rev 230987')
assert request
request_id = request.id
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request.id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# add one section with rejected status
RegComments.add('device_quota', 'test comment on section', 'rev230987', 'rev 230987', 7, request_id)
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'rev230987'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
response = json.loads(rv.data.decode('utf-8'))
assert response['status'] == 7
assert response['request_id'] == request_id
assert response['message'] == 'case {0} updated successfully'.format(request_id)
assert response['request_type'] == 'registration_request'
imei = ApprovedImeis.get_imei('23010403010533')
assert imei.status == 'removed'
assert imei.delta_status == 'remove'
assert Notification.exist_users('assign-rev23442342-user-1')
def test_de_registration_request_rejected_section(flask_app, db, app):
"""Verify that the de_registration request gets rejected when anyone of the section
is marked as rejected, imeis are removed from approvedimeis and notification is
being generated.
"""
# de registration request
headers = {'Content-Type': 'application/json'}
de_registration_data = {
'file': 'de-reg-test-file.txt',
'device_count': 1,
'user_id': 'dereg-section-submit-assign-rev-user-1',
'user_name': 'submit assign rev user 1',
'reason': 'because we have to run tests successfully'
}
request = create_assigned_dummy_request(de_registration_data, 'De_Registration', 'dereg-rejected-section-rev',
'de reg rev')
device_data = {
'devices': """[
{
"tac": "95762201",
"model_name": "TA-1034",
"brand_name": "NOKIA",
"model_num": "TA-1034",
"technology": "NONE",
"device_type": "Mobile Phone/Feature phone",
"count": 2,
"operating_system": "N/A"
}
]""",
'dereg_id': request.id
}
request = create_dummy_devices(device_data, 'De_Registration', request, db, file_content=['957622010005119'],
file_path='{0}/{1}/{2}'.format(app.config['DRS_UPLOADS'], request.tracking_id,
de_registration_data.get('file')))
assert request
request_id = request.id
DeRegComments.add('device_description', 'test comment on section', 'dereg-rejected-section-rev', 'rev 230987', 7,
request_id)
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'dereg-rejected-section-rev'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
response = json.loads(rv.data.decode('utf-8'))
assert response['status'] == 7
assert response['request_id'] == request_id
assert response['message'] == 'case {0} updated successfully'.format(request_id)
assert response['request_type'] == 'de_registration_request'
assert Notification.exist_users('dereg-section-submit-assign-rev-user-1')
def test_registration_request_approval(flask_app, db): # pylint: disable=unused-argument
"""Verify that the api behave properly upon approval of the request."""
# only one section is reviewed and rejected
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['94310813016000']]",
'm_location': 'local',
'user_name': 'reg req approve rev user 5',
'user_id': 'reg-req-approve-rev-user-5'
}
request = create_assigned_dummy_request(data, 'Registration',
'reg-req-approve-rev-user-5', 'reg req approve rev user 5')
assert request
request_id = request.id
user_id = request.user_id
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request.id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# create user quota
quota = DeviceQuota.create(user_id, 'individual')
assert quota
user_reg_quota = quota.reg_quota
# approve all sections manually
RegComments.add('device_quota', 'test comment on section', 'reg-req-approve-rev-user-5',
'reg req approve rev user 5', 6, request_id)
RegComments.add('device_description', 'test comment on section', 'reg-req-approve-rev-user-5',
'reg req approve rev user 5', 6, request_id)
RegComments.add('imei_classification', 'test comment on section', 'reg-req-approve-rev-user-5',
'reg req approve rev user 5', 6, request_id)
RegComments.add('imei_registration', 'test comment on section', 'reg-req-approve-rev-user-5',
'reg req approve rev user 5', 6, request_id)
RegComments.add('approval_documents', 'test comment on section', 'reg-req-approve-rev-user-5',
'reg req approve rev user 5', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'reg-req-approve-rev-user-5'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
data = json.loads(rv.data.decode('utf-8'))
assert data['status'] == 6
assert data['request_id'] == request_id
assert data['message'] == 'case {0} updated successfully'.format(request_id)
assert data['request_type'] == 'registration_request'
imei = ApprovedImeis.get_imei('94310813016000')
assert imei.status == 'whitelist'
assert imei.delta_status == 'update'
assert Notification.exist_users(user_id)
assert DeviceQuota.get(user_id).reg_quota == user_reg_quota - 1
def test_registration_request_duplicated_imeis(flask_app, db): # pylint: disable=unused-argument
"""Verify that the system does not allow the request approval when
there are duplicated imeis in the request and responds properly.
"""
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['00010673016999']]",
'm_location': 'local',
'user_name': 'reg req approve rev user 6',
'user_id': 'reg-req-approve-rev-user-6'
}
request = create_assigned_dummy_request(data, 'Registration',
'reg-req-approve-rev-user-6', 'reg req approve rev user 6')
assert request
request_id = request.id
user_id = request.user_id
# add duplicated imei to approvedimeis
approved_imei = ApprovedImeis('00010673016999', 673739, 'whitelist', 'update')
approved_imei.add()
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request.id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# create user quota
quota = DeviceQuota.create(user_id, 'individual')
assert quota
# approve all sections manually
RegComments.add('device_quota', 'test comment on section', 'reg-req-approve-rev-user-6',
'reg req approve rev user 6', 6, request_id)
RegComments.add('device_description', 'test comment on section', 'reg-req-approve-rev-user-6',
'reg req approve rev user 6', 6, request_id)
RegComments.add('imei_classification', 'test comment on section', 'reg-req-approve-rev-user-6',
'reg req approve rev user 6', 6, request_id)
RegComments.add('imei_registration', 'test comment on section', 'reg-req-approve-rev-user-6',
'reg req approve rev user 6', 6, request_id)
RegComments.add('approval_documents', 'test comment on section', 'reg-req-approve-rev-user-6',
'reg req approve rev user 6', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'reg-req-approve-rev-user-6'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
data = json.loads(rv.data.decode('utf-8'))
assert data['error'] == ['unable to approve case {0}, duplicated imeis found'.format(request_id)]
def test_registration_request_information_requested(flask_app, db): # pylint: disable=unused-argument
"""Verify that when any of the section is marked as information requested the
system automatically mark the whole request as information requested.
"""
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['11110673016888']]",
'm_location': 'local',
'user_name': 'reg req approve rev user 7',
'user_id': 'reg-req-approve-rev-user-7'
}
request = create_assigned_dummy_request(data, 'Registration',
'reg-req-approve-rev-user-7', 'reg req approve rev user 7')
assert request
request_id = request.id
user_id = request.user_id
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request.id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# create user quota
quota = DeviceQuota.create(user_id, 'individual')
assert quota
# approve all sections manually
RegComments.add('device_quota', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 6, request_id)
RegComments.add('device_description', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 6, request_id)
RegComments.add('imei_classification', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 5, request_id)
RegComments.add('imei_registration', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 6, request_id)
RegComments.add('approval_documents', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'reg-req-approve-rev-user-7'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
data = json.loads(rv.data.decode('utf-8'))
assert data['status'] == 5
assert data['request_id'] == request_id
assert data['message'] == 'case {0} updated successfully'.format(request_id)
assert data['request_type'] == 'registration_request'
assert Notification.exist_users(user_id)
def test_registration_request_any_section_none(flask_app, db): # pylint: disable=unused-argument
"""Verify that the system does not allow to submit the review when any
of the section is not reviewed or status is none.
"""
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['22210376016777']]",
'm_location': 'local',
'user_name': 'reg req approve rev user 8',
'user_id': 'reg-req-approve-rev-user-8'
}
request = create_assigned_dummy_request(data, 'Registration',
'reg-req-approve-rev-user-8', 'reg req approve rev user 8')
assert request
request_id = request.id
user_id = request.user_id
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request.id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# create user quota
quota = DeviceQuota.create(user_id, 'individual')
assert quota
# approve only 2 section, leave rest of them none
RegComments.add('device_quota', 'test comment on section', 'reg-req-approve-rev-user-8',
'reg req approve rev user 8', 6, request_id)
RegComments.add('device_description', 'test comment on section', 'reg-req-approve-rev-user-8',
'reg req approve rev user 8', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'reg-req-approve-rev-user-8'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
data = json.loads(rv.data.decode('utf-8'))
assert data['error'] == ['unable to update case {0}, complete review process'.format(request_id)]
def test_registration_request_rejected_status_priority(flask_app, db): # pylint: disable=unused-argument
"""Verify that the rejected section status have highest priority means
even if the first section is rejected, remaining are not reviewed, the
system allows the review submission and mark the request as rejected.
"""
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['33310001016666']]",
'm_location': 'local',
'user_name': 'reg req approve rev user 9',
'user_id': 'reg-req-approve-rev-user-9'
}
request = create_assigned_dummy_request(data, 'Registration',
'reg-req-approve-rev-user-9', 'reg req approve rev user 9')
assert request
request_id = request.id
user_id = request.user_id
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request.id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# create user quota
quota = DeviceQuota.create(user_id, 'individual')
assert quota
# reject device quota and mark device_description as info-requested
RegComments.add('device_quota', 'test comment on section', 'reg-req-approve-rev-user-9',
'reg req approve rev user 9', 7, request_id)
RegComments.add('device_description', 'test comment on section', 'reg-req-approve-rev-user-9',
'reg req approve rev user 9', 5, request_id)
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'reg-req-approve-rev-user-9'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
data = json.loads(rv.data.decode('utf-8'))
assert data['status'] == 7
assert data['request_id'] == request_id
def test_registration_request_info_requested_status_priority(flask_app, db): # pylint: disable=unused-argument
"""Verify that the information requested section status has the 2nd highest priority means
when any of the section is marked as information requested the whole case will be marked as
information requested regardless of other section statuses.
"""
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['44414441016777']]",
'm_location': 'local',
'user_name': 'reg req approve rev user 10',
'user_id': 'reg-req-approve-rev-user-10'
}
request = create_assigned_dummy_request(data, 'Registration',
'reg-req-approve-rev-user-10', 'reg req approve rev user 10')
assert request
request_id = request.id
user_id = request.user_id
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request.id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# create user quota
quota = DeviceQuota.create(user_id, 'individual')
assert quota
# mark only one section as information requested
RegComments.add('device_quota', 'test comment on section', 'reg-req-approve-rev-user-10',
'reg req approve rev user 10', 6, request_id)
RegComments.add('device_description', 'test comment on section', 'reg-req-approve-rev-user-10',
'reg req approve rev user 10', 6, request_id)
RegComments.add('imei_classification', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 5, request_id)
RegComments.add('imei_registration', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 6, request_id)
RegComments.add('approval_documents', 'test comment on section', 'reg-req-approve-rev-user-7',
'reg req approve rev user 7', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'registration_request',
'reviewer_id': 'reg-req-approve-rev-user-10'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
data = json.loads(rv.data.decode('utf-8'))
assert data['status'] == 5
assert data['request_id'] == request_id
def test_de_registration_request_approval(flask_app, db, app):
"""Verify that the system approves the request when all the sections are approved
and de-register imeis successfully.
"""
headers = {'Content-Type': 'application/json'}
data = {
'device_count': 1,
'imei_per_device': 1,
'imeis': "[['121621090005119']]",
'm_location': 'local',
'user_name': 'reg req approve rev user 9',
'user_id': 'reg-req-approve-rev-user-9'
}
request = create_assigned_dummy_request(data, 'Registration',
'dereg-req-approve-rev-user-10', 'dereg req approve rev user 10')
assert request
request_id = request.id
user_id = request.user_id
device_data = {
'brand': 'samsung',
'operating_system': 'android',
'model_name': 's9',
'model_num': '30jjd',
'device_type': 'Smartphone',
'technologies': '2G,3G,4G',
'reg_id': request_id
}
request = create_dummy_devices(device_data, 'Registration', request)
assert request
# create user quota
quota = DeviceQuota.create(user_id, 'individual')
assert quota
de_registration_data = {
'file': 'de-reg-test-file.txt',
'device_count': 1,
'user_id': 'dereg-req-approve-rev-user-10',
'user_name': 'dereg req approve rev user 10',
'reason': 'because we have to run tests successfully'
}
request = create_assigned_dummy_request(de_registration_data, 'De_Registration', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10')
device_data = {
'devices': """[
{
"tac": "12162109",
"model_name": "TA-1034",
"brand_name": "NOKIA",
"model_num": "TA-1034",
"technology": "NONE",
"device_type": "Mobile Phone/Feature phone",
"count": 2,
"operating_system": "N/A"
}
]""",
'dereg_id': request.id
}
request = create_dummy_devices(device_data, 'De_Registration', request, db, file_content=['121621090005119'],
file_path='{0}/{1}/{2}'.format(app.config['DRS_UPLOADS'], request.tracking_id,
de_registration_data.get('file')))
assert request
request_id = request.id
# add imei to approvedimeis as whitelist to de register
approved_imei = ApprovedImeis.get_imei('12162109000511')
approved_imei.status = 'whitelist'
approved_imei.delta_status = 'update'
ApprovedImeis.bulk_insert_imeis([approved_imei])
DeRegComments.add('device_description', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
DeRegComments.add('imei_classification', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
DeRegComments.add('imei_registration', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
DeRegComments.add('approval_documents', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'dereg-req-approve-rev-user-10'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
response = json.loads(rv.data.decode('utf-8'))
imei = ApprovedImeis.get_imei('12162109000511')
assert response['request_type'] == 'de_registration_request'
assert response['status'] == 6
assert response['request_id'] == request_id
assert imei.status == 'removed'
def test_de_registration_request_invalid_imeis(flask_app, db, app):
"""Verify that the system does not allow a de registration request"""
headers = {'Content-Type': 'application/json'}
de_registration_data = {
'file': 'de-reg-test-file.txt',
'device_count': 1,
'user_id': 'dereg-req-approve-rev-user-10',
'user_name': 'dereg req approve rev user 10',
'reason': 'because we have to run tests successfully'
}
request = create_assigned_dummy_request(de_registration_data, 'De_Registration', 'dereg-req-approve-rev-user-11',
'dereg req approve rev user 11')
device_data = {
'devices': """[
{
"tac": "12162119",
"model_name": "TA-1034",
"brand_name": "NOKIA",
"model_num": "TA-1034",
"technology": "NONE",
"device_type": "Mobile Phone/Feature phone",
"count": 2,
"operating_system": "N/A"
}
]""",
'dereg_id': request.id
}
request = create_dummy_devices(device_data, 'De_Registration', request, db, file_content=['121621191115009'],
file_path='{0}/{1}/{2}'.format(app.config['DRS_UPLOADS'], request.tracking_id,
de_registration_data.get('file')))
assert request
request_id = request.id
DeRegComments.add('device_description', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
DeRegComments.add('imei_classification', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
DeRegComments.add('imei_registration', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
DeRegComments.add('approval_documents', 'test comment on section', 'dereg-req-approve-rev-user-10',
'dereg req approve rev user 10', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'dereg-req-approve-rev-user-11'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
response = json.loads(rv.data.decode('utf-8'))
assert response['error'] == ['Unable to approve, invalid imeis found']
def test_de_registration_request_info_requested(flask_app, db, app):
"""Verify that the system mark the request as information requested even when only one of the
sections is marked as information requested.
"""
headers = {'Content-Type': 'application/json'}
de_registration_data = {
'file': 'de-reg-test-file.txt',
'device_count': 1,
'user_id': 'dereg-req-approve-rev-user-12',
'user_name': 'dereg req approve rev user 12',
'reason': 'because we have to run tests successfully'
}
request = create_assigned_dummy_request(de_registration_data, 'De_Registration', 'dereg-req-approve-rev-user-12',
'dereg req approve rev user 12')
device_data = {
'devices': """[
{
"tac": "12000009",
"model_name": "TA-1034",
"brand_name": "NOKIA",
"model_num": "TA-1034",
"technology": "NONE",
"device_type": "Mobile Phone/Feature phone",
"count": 2,
"operating_system": "N/A"
}
]""",
'dereg_id': request.id
}
request = create_dummy_devices(device_data, 'De_Registration', request, db, file_content=['120000091115009'],
file_path='{0}/{1}/{2}'.format(app.config['DRS_UPLOADS'], request.tracking_id,
de_registration_data.get('file')))
assert request
request_id = request.id
DeRegComments.add('device_description', 'test comment on section', 'dereg-req-approve-rev-user-12',
'dereg req approve rev user 12', 6, request_id)
DeRegComments.add('imei_classification', 'test comment on section', 'dereg-req-approve-rev-user-12',
'dereg req approve rev user 12', 5, request_id)
DeRegComments.add('imei_registration', 'test comment on section', 'dereg-req-approve-rev-user-12',
'dereg req approve rev user 12', 6, request_id)
DeRegComments.add('approval_documents', 'test comment on section', 'dereg-req-approve-rev-user-12',
'dereg req approve rev user 12', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'dereg-req-approve-rev-user-12'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 201
response = json.loads(rv.data.decode('utf-8'))
assert response['request_id'] == request_id
assert response['status'] == 5
def test_de_registration_request_none_status_section(flask_app, db, app):
"""Verify that if any status is none the the system does not allow
submission and api responds accordingly.
"""
headers = {'Content-Type': 'application/json'}
de_registration_data = {
'file': 'de-reg-test-file.txt',
'device_count': 1,
'user_id': 'dereg-req-approve-rev-user-13',
'user_name': 'dereg req approve rev user 13',
'reason': 'because we have to run tests successfully'
}
request = create_assigned_dummy_request(de_registration_data, 'De_Registration', 'dereg-req-approve-rev-user-13',
'dereg req approve rev user 13')
device_data = {
'devices': """[
{
"tac": "12111119",
"model_name": "TA-1034",
"brand_name": "NOKIA",
"model_num": "TA-1034",
"technology": "NONE",
"device_type": "Mobile Phone/Feature phone",
"count": 2,
"operating_system": "N/A"
}
]""",
'dereg_id': request.id
}
request = create_dummy_devices(device_data, 'De_Registration', request, db, file_content=['121111191115009'],
file_path='{0}/{1}/{2}'.format(app.config['DRS_UPLOADS'], request.tracking_id,
de_registration_data.get('file')))
assert request
request_id = request.id
DeRegComments.add('device_description', 'test comment on section', 'dereg-req-approve-rev-user-13',
'dereg req approve rev user 13', 6, request_id)
body_data = {
'request_id': request_id,
'request_type': 'de_registration_request',
'reviewer_id': 'dereg-req-approve-rev-user-13'
}
rv = flask_app.put(SUBMIT_REVIEW_API, data=json.dumps(body_data), headers=headers)
assert rv.status_code == 400
response = json.loads(rv.data.decode('utf-8'))
assert response['error'] == ['unable to update case {0}, complete the review process'.format(request_id)]
def test_post_method_not_allowed(flask_app):
"""Verify that POST method is not allowed on api."""
rv = flask_app.post(SUBMIT_REVIEW_API)
assert rv.status_code == 405
data = json.loads(rv.data.decode('utf-8'))
assert data.get('message') == 'method not allowed'
def test_delete_method_not_allowed(flask_app):
"""Verify that DELETE method is not allowed on api."""
rv = flask_app.delete(SUBMIT_REVIEW_API)
assert rv.status_code == 405
data = json.loads(rv.data.decode('utf-8'))
assert data.get('message') == 'method not allowed'
def test_get_method_not_allowed(flask_app):
"""Verify that PUT method is not allowed on api."""
rv = flask_app.get(SUBMIT_REVIEW_API)
assert rv.status_code == 405
data = json.loads(rv.data.decode('utf-8'))
assert data.get('message') == 'method not allowed'
| 43.330813
| 118
| 0.623658
| 5,587
| 45,844
| 4.939323
| 0.069268
| 0.054138
| 0.060299
| 0.078852
| 0.849761
| 0.82454
| 0.807834
| 0.781599
| 0.764531
| 0.75221
| 0
| 0.03041
| 0.255431
| 45,844
| 1,057
| 119
| 43.371807
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| 0
| 0.712941
| 0
| 0
| 0.388408
| 0.063138
| 0
| 0
| 0
| 0
| 0.156471
| 1
| 0.024706
| false
| 0
| 0.008235
| 0
| 0.032941
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
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0
| 7
|
d716aa8923876ed64530552a0acdb1fd327a94e4
| 61,152
|
py
|
Python
|
xphm.py
|
nathaniel-leslie/modebymode-relative-binning
|
2a7346046e91fbec5dc2a9677c378439eaf7d473
|
[
"MIT"
] | null | null | null |
xphm.py
|
nathaniel-leslie/modebymode-relative-binning
|
2a7346046e91fbec5dc2a9677c378439eaf7d473
|
[
"MIT"
] | null | null | null |
xphm.py
|
nathaniel-leslie/modebymode-relative-binning
|
2a7346046e91fbec5dc2a9677c378439eaf7d473
|
[
"MIT"
] | null | null | null |
import lal
import lalsimulation as lalsim
import numpy as np
def L0_func(params):
"""
Computes the magnitude of the initial angular momentum L0.
params: parameter dictionary
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
m1 = params['mass_1']
m2 = params['mass_2']
M = m1 + m2
eta = (m1*m2)/(M**2)
s1z = params['chi_1z']
s2z = params['chi_2z']
fref = params['f_ref']
Omega_o = np.pi*fref
x = (M*Omega_o*lal.MTSUN_SI)**(2/3)
delta = np.sqrt(1 - 4*eta)
chi1L = s1z
chi2L = s2z
L0 = 1
L1 = 3.0/2. + eta/6.0
L2 = (81 + (-57 + eta)*eta)/24.
L3 = (10935. + eta*(-62001 + 1674*eta + 7*eta**2 + 2214*np.pi**2))/1296.
L32 = (-7*(chi1L + chi2L + chi1L*delta - chi2L*delta) + 5*(chi1L + chi2L)*eta)/6.
L52 = (-1650*(chi1L + chi2L + chi1L*delta - chi2L*delta) + 1336*(chi1L + chi2L)*eta
+ 511*(chi1L - chi2L)*delta*eta + 28*(chi1L + chi2L)*eta**2)/600.
PNexp = L0 + L1*x + L2*x**2 + L3*x**3 + L32*x**(3/2) + L52*x**(5/2)
return eta*x**(-1/2)*PNexp
def thetaJL_func(params):
"""
Computes thetaJL, the angle between the total angular momentum J and the initial angular momentum L0.
params: parameter dictionary
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
m1 = params['mass_1']
m2 = params['mass_2']
M = m1 + m2
s1x = params['chi_1x']
s1y = params['chi_1y']
s1z = params['chi_1z']
s2x = params['chi_2x']
s2y = params['chi_2y']
s2z = params['chi_2z']
# Components in L0 frame
Jx = (m1/M)**2*s1x + (m2/M)**2*s2x
Jy = (m1/M)**2*s1y + (m2/M)**2*s2y
Jz = (m1/M)**2*s1z + (m2/M)**2*s2z + L0_func(params)
J = np.array([Jx, Jy, Jz])
return np.arccos(Jz/np.linalg.norm(J))
def phiJL_func(params):
"""
Computes phiJL, the azimuthal angle of the total angular momentum J in the L0 frame.
params: parameter dictionary
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
m1 = params['mass_1']
m2 = params['mass_2']
M = m1 + m2
s1x = params['chi_1x']
s1y = params['chi_1y']
s1z = params['chi_1z']
s2x = params['chi_2x']
s2y = params['chi_2y']
s2z = params['chi_2z']
# Components in L0 frame
Jx = (m1/M)**2*s1x + (m2/M)**2*s2x
Jy = (m1/M)**2*s1y + (m2/M)**2*s2y
Jz = (m1/M)**2*s1z + (m2/M)**2*s2z + L0_func(params)
J = np.array([Jx, Jy, Jz])
return np.arctan2(Jy, Jx)
def rotate_z(V, theta):
"""
Rotates the vector V by an angle theta around the z-axis.
V: 1-D array with 3 components
theta: angle
"""
Vx = V[0]
Vy = V[1]
Vz = V[2]
c = np.cos(theta)
s = np.sin(theta)
return np.array([Vx*c - Vy*s, Vx*s + Vy*c, Vz])
def rotate_y(V, theta):
"""
Rotates the vector V by an angle theta around the y-axis.
V: 1-D array with 3 components
theta: angle
"""
Vx = V[0]
Vy = V[1]
Vz = V[2]
c = np.cos(theta)
s = np.sin(theta)
return np.array([Vx*c + Vz*s, Vy, -Vx*s + Vz*c])
def zeta_polarization(params):
"""
Computes zeta, the polarization angle between the N frame where the x axis is aligned with L0's projection into the x-y plane and the spherical harmonic N frame where the y axis is aligned with J x N. This angle is needed to rotate the mode decomposition that we computed in the J frame into the frame aligned with L0 that convention dictates.
params: parameter dictionary
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
m1 = params['mass_1']
m2 = params['mass_2']
M = m1 + m2
s1x = params['chi_1x']
s1y = params['chi_1y']
s1z = params['chi_1z']
s2x = params['chi_2x']
s2y = params['chi_2y']
s2z = params['chi_2z']
thetaJN = params['thetaJN']
kappa = params['kappa']
thetaJL = thetaJL_func(params)
# Components in J frame
xp_x = np.cos(thetaJN)
xp_y = 0.
xp_z = -np.sin(thetaJN)
xp = np.array([xp_x, xp_y, xp_z])
yp_x = 0.
yp_y = 1.
yp_z = 0.
yp = np.array([yp_x, yp_y, yp_z])
N_x = np.sin(thetaJN)
N_y = 0
N_z = np.cos(thetaJN)
N = np.array([N_x, N_y, N_z])
L0_L0 = np.array([0, 0, 1]) # direction of L0 in L0 frame
L0 = rotate_z(rotate_y(L0_L0, -thetaJL), -kappa)
x = L0 - np.dot(L0, N)*N
return np.arctan2(np.dot(x, yp), np.dot(x, xp))
def m2Ylm(l, m, thetaJN):
"""
Computes the -2 spin weighted spherical harmonic evaluated at theta = thetaJN, phi = 0.
l: l index
m: m index
thetaJN: thetaJN angle
"""
m = int(m)
l = int(l)
return lal.SpinWeightedSphericalHarmonic(thetaJN, 0, -2, l, m) # kappa + np.pi
def wignerd_slow(l, m, mprime, beta):
"""
Computes the wigner d matrix element with indices l, m, mprime, evaluated at angle beta. Only works for cases enumerated.
l: l index
m: m index
mprime: mprime index
beta: Euler angle beta
"""
if mprime < 0:
c = np.cos((np.pi - beta)/2)
s = np.sin((np.pi - beta)/2)
pf = (-1)**(l+m)
mprime *= -1
else:
c = np.cos(beta/2)
s = np.sin(beta/2)
pf = 1
if l == 2:
if mprime == 2:
if m == 2:
f = c**4
elif m == 1:
f = 2*c**3*s
elif m == 0:
f = np.sqrt(6)*c**2*s**2
elif m == -1:
f = 2*c*s**3
elif m == -2:
f = s**4
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 1:
if m == 2:
f = -2*c**3*s
elif m == 1:
f = c**2*(c**2-3*s**2)
elif m == 0:
f = np.sqrt(6)*(c**3*s-c*s**3)
elif m == -1:
f = s**2*(3*c**2-s**2)
elif m == -2:
f = 2*c*s**3
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif l == 3:
if mprime == 3:
if m == 3:
f = c**6
elif m == 2:
f = np.sqrt(6)*c**6*s
elif m == 1:
f = np.sqrt(15)*c**4*s**2
elif m == 0:
f = 2*np.sqrt(5)*c**3*s**3
elif m == -1:
f = np.sqrt(15)*c**2*s**4
elif m == -2:
f = np.sqrt(6)*c*s**5
elif m == -3:
f = s**6
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 2:
if m == 3:
f = -np.sqrt(6)*c**5*s
elif m == 2:
f = c**4*(c**2-5*s**2)
elif m == 1:
f = np.sqrt(10)*c**3*(c**2*s-2*s**3)
elif m == 0:
f = np.sqrt(30)*c**2*s**2*(c**2-s**2)
elif m == -1:
f = np.sqrt(10)*s**3*(2*c**3-c*s**2)
elif m == -2:
f = s**4*(5*c**2-s**2)
elif m == -3:
f = np.sqrt(6)*c*s**5
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 1:
f = 0
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif l == 4:
if mprime == 4:
if m == 4:
f = c**8
elif m == 3:
f = 2*np.sqrt(2)*c**7*s
elif m == 2:
f = 2*np.sqrt(7)*c**6*s**2
elif m == 1:
f = 2*np.sqrt(14)*c**5*s**3
elif m == 0:
f = np.sqrt(70)*c**4*s**4
elif m == -1:
f = 2*np.sqrt(14)*c**3*s**5
elif m == -2:
f = 2*np.sqrt(7)*c**2*s**6
elif m == -3:
f = 2*np.sqrt(2)*c*s**7
elif m == -4:
f = s**8
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 3:
f = 0
elif mprime == 2:
f = 0
elif mprime == 1:
f = 0
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
return f*pf
def wignerd(l, m, mprime, eibetaover2):
"""
Computes the wigner d matrix element with indices l, m, mprime, evaluated at angle beta. Only works for cases enumerated.
l: l index
m: m index
mprime: mprime index
eibetaover2: exp(i*beta/2)
"""
if mprime < 0:
c = np.imag(eibetaover2)
s = np.real(eibetaover2)
pf = (-1)**(l+m)
mprime *= -1
else:
c = np.real(eibetaover2)
s = np.imag(eibetaover2)
pf = 1
if l == 2:
if mprime == 2:
if m == 2:
f = c**4
elif m == 1:
f = 2*c**3*s
elif m == 0:
f = np.sqrt(6)*c**2*s**2
elif m == -1:
f = 2*c*s**3
elif m == -2:
f = s**4
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 1:
if m == 2:
f = -2*c**3*s
elif m == 1:
f = c**2*(c**2-3*s**2)
elif m == 0:
f = np.sqrt(6)*(c**3*s-c*s**3)
elif m == -1:
f = s**2*(3*c**2-s**2)
elif m == -2:
f = 2*c*s**3
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif l == 3:
if mprime == 3:
if m == 3:
f = c**6
elif m == 2:
f = np.sqrt(6)*c**6*s
elif m == 1:
f = np.sqrt(15)*c**4*s**2
elif m == 0:
f = 2*np.sqrt(5)*c**3*s**3
elif m == -1:
f = np.sqrt(15)*c**2*s**4
elif m == -2:
f = np.sqrt(6)*c*s**5
elif m == -3:
f = s**6
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 2:
if m == 3:
f = -np.sqrt(6)*c**5*s
elif m == 2:
f = c**4*(c**2-5*s**2)
elif m == 1:
f = np.sqrt(10)*c**3*(c**2*s-2*s**3)
elif m == 0:
f = np.sqrt(30)*c**2*s**2*(c**2-s**2)
elif m == -1:
f = np.sqrt(10)*s**3*(2*c**3-c*s**2)
elif m == -2:
f = s**4*(5*c**2-s**2)
elif m == -3:
f = np.sqrt(6)*c*s**5
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 1:
f = 0
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif l == 4:
if mprime == 4:
if m == 4:
f = c**8
elif m == 3:
f = 2*np.sqrt(2)*c**7*s
elif m == 2:
f = 2*np.sqrt(7)*c**6*s**2
elif m == 1:
f = 2*np.sqrt(14)*c**5*s**3
elif m == 0:
f = np.sqrt(70)*c**4*s**4
elif m == -1:
f = 2*np.sqrt(14)*c**3*s**5
elif m == -2:
f = 2*np.sqrt(7)*c**2*s**6
elif m == -3:
f = 2*np.sqrt(2)*c*s**7
elif m == -4:
f = s**8
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
elif mprime == 3:
f = 0
elif mprime == 2:
f = 0
elif mprime == 1:
f = 0
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
else:
raise ValueError('Function wignerd not defined for (l, m, m\')=', l, m, mprime)
return f*pf
def Atransfer_slow(l, m, mprime, alpha, beta, thetaJN):
"""
Computes the mode-by-mode transfer function A defined in equation 3.7 of https://arxiv.org/pdf/2004.06503.pdf.
l: l index
m: m index
mprime: mprime index
alpha: Euler angle alpha
beta: Euler angle beta
thetaJN: angle thetaJN
"""
return np.exp(-1j*m*alpha)*wignerd_slow(l, m, mprime, beta)*m2Ylm(l, m, thetaJN)
def Atransfer(l, m, mprime, eiabsmalpha, eibetaover2, thetaJN):
"""
Computes the mode-by-mode transfer function A defined in equation 3.7 of https://arxiv.org/pdf/2004.06503.pdf.
l: l index
m: m index
mprime: mprime index
eiabsmalpha: exp(i*|m|*alpha)
eibetaover2: exp(i*beta/2)
thetaJN: angle thetaJN
"""
if m > 0:
return np.conj(eiabsmalpha)*wignerd(l, m, mprime, eibetaover2)*m2Ylm(l, m, thetaJN)
else:
return eiabsmalpha*wignerd(l, m, mprime, eibetaover2)*m2Ylm(l, m, thetaJN)
def twist_factor_slow(l, mprime, alpha, beta, gamma, thetaJN, pol):
"""
Computes the coefficients that twist the L frame modes into the plus and cross polarizations without the 1/2 or 1/2i. Seen in equations 3.5, 3.6 of https://arxiv.org/pdf/2004.06503.pdf.
l: l index
m: m index
mprime: mprime index
alpha: Euler angle alpha
beta: Euler angle beta
gamma: Euler angle gamma
thetaJN: angle thetaJN
pol: string, indicates polarization, accepted values are '+' and 'x'.
"""
m_arr = np.arange(2*l+1)-l
if pol == '+':
summand = [Atransfer_slow(l, m, -mprime, alpha, beta, thetaJN) + (-1)**l*np.conj(Atransfer_slow(l, m, mprime, alpha, beta, thetaJN)) for m in m_arr]
elif pol == 'x':
summand = [Atransfer_slow(l, m, -mprime, alpha, beta, thetaJN) - (-1)**l*np.conj(Atransfer_slow(l, m, mprime, alpha, beta, thetaJN)) for m in m_arr]
else:
raise ValueError('Only + or x polarizations allowed.')
return np.exp(1j*mprime*gamma)*np.sum(summand, axis=0)
def twist_factor(l, mprime, eimalpha, eibetaover2, eimprimegamma, thetaJN, pol):
"""
Computes the coefficients that twist the L frame modes into the plus and cross polarizations without the 1/2 or 1/2i. Seen in equations 3.5, 3.6 of https://arxiv.org/pdf/2004.06503.pdf.
l: l index
m: m index
mprime: mprime index
eimalpha: exp(i*m*alpha) array, index 0 is m, ranges from 0 to max_l
eibetaover2: exp(i*beta/2)
eimprimegamma: exp(i*mprime*gamma)
thetaJN: angle thetaJN
pol: string, indicates polarization, accepted values are '+' and 'x'.
"""
m_arr = np.arange(2*l+1)-l
if pol == '+':
summand = [Atransfer(l, m, -mprime, eimalpha[abs(m)], eibetaover2, thetaJN) + (-1)**l*np.conj(Atransfer(l, m, mprime, eimalpha[abs(m)], eibetaover2, thetaJN)) for m in m_arr]
elif pol == 'x':
summand = [Atransfer(l, m, -mprime, eimalpha[abs(m)], eibetaover2, thetaJN) - (-1)**l*np.conj(Atransfer(l, m, mprime, eimalpha[abs(m)], eibetaover2, thetaJN)) for m in m_arr]
else:
raise ValueError('Only + or x polarizations allowed.')
return eimprimegamma*np.sum(summand, axis=0)
def h_Lframe(params, f_seq, l, m):
"""
Computes the (l, m) L frame mode evaluated for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
l: l index
m: m index
"""
m = int(m)
l = int(l)
lal_dict_L = lal.CreateDict()
lalsim.SimInspiralWaveformParamsInsertPhenomXPHMPrecModes(lal_dict_L,1); # 1 chooses L frame instead of J frame
h_posf_L, _ = lalsim.SimIMRPhenomXPHMOneModeFrequencySequence(f_seq, l, m,
params['mass_1'] * lal.MSUN_SI,
params['mass_2'] * lal.MSUN_SI,
params['chi_1x'],
params['chi_1y'],
params['chi_1z'],
params['chi_2x'],
params['chi_2y'],
params['chi_2z'],
params['distance'],
0., #phiref doesn't matter
params['f_ref'],
lal_dict_L
)
return h_posf_L.data.data
def euler_angles(params, f_seq, mprime, backupNNLO = True):
"""
Computes the (l, m) euler angles alpha, beta, and gamma evaluated for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
mprime: mprime index
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
"""
mprime = int(mprime)
fs = f_seq.data
phiz_of_f = lal.CreateREAL8Sequence(len(fs))
zeta_of_f = lal.CreateREAL8Sequence(len(fs))
costhetaL_of_f = lal.CreateREAL8Sequence(len(fs))
phiz_of_f.data = np.zeros(len(fs))
zeta_of_f.data = np.zeros(len(fs))
costhetaL_of_f.data = np.zeros(len(fs))
lalDict_MSA = lal.CreateDict();
if not backupNNLO:
# change flag to return an error if MSA fails
lalsim.SimInspiralWaveformParamsInsertPhenomXPrecVersion(lalDict_MSA, 222)
lalsim.SimIMRPhenomXPMSAAngles(phiz_of_f, zeta_of_f, costhetaL_of_f, f_seq,
params['mass_1'] * lal.MSUN_SI,
params['mass_2'] * lal.MSUN_SI,
params['chi_1x'], params['chi_1y'], params['chi_1z'],
params['chi_2x'], params['chi_2y'], params['chi_2z'],
params['f_ref'], params['f_min'], params['f_max'], mprime,
lalDict_MSA);
alpha = phiz_of_f.data + np.pi - params['kappa']
beta = np.unwrap(np.arccos(costhetaL_of_f.data))
epsilon = zeta_of_f.data # gamma = -epsilon
return alpha, beta, -epsilon
def hpc_slow(params, f_seq, backupNNLO = True, modelist = np.array([[2,1], [2,2], [3,2], [3,3], [4,4]]) ):
"""
Computes the plus and cross polarizations for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
modelist: array of modes to use (l, m)
"""
thetaJN = params['thetaJN']
n_freq = len(f_seq.data)
hplus_J = np.zeros(n_freq, dtype=complex)
hcross_J = np.zeros(n_freq, dtype=complex)
mprime_arr = np.unique(modelist[:, 1])
eulerangles = np.array([euler_angles(params, f_seq, mprime, backupNNLO) for mprime in mprime_arr])
for mode in modelist:
mpind = np.where(mprime_arr == mode[1])[0][0]
hL = h_Lframe(params, f_seq, mode[0], -mode[1])
hplus_J += 1/2*hL*twist_factor_slow(mode[0], mode[1], eulerangles[mpind, 0], eulerangles[mpind, 1], eulerangles[mpind, 2], thetaJN, '+')
hcross_J += 1j/2*hL*twist_factor_slow(mode[0], mode[1], eulerangles[mpind, 0], eulerangles[mpind, 1], eulerangles[mpind, 2], thetaJN, 'x')
zeta = zeta_polarization(params)
hplus = np.cos(2*zeta)*hplus_J + np.sin(2*zeta)*hcross_J
hcross = np.cos(2*zeta)*hcross_J - np.sin(2*zeta)*hplus_J
return hplus, hcross
# def create_cosmalpha_arr(cosalpha, max_l):
# if max_l == 2:
# return np.array([0*cosalpha+1, cosalpha, 2*cosalpha*cosalpha - 1])
# elif max_l == 3:
# cosalpha2 = cosalpha*cosalpha
# return np.array([0*cosalpha+1, cosalpha, 2*cosalpha2 - 1, 4*cosalpha2*cosalpha - 3*cosalpha])
# elif max_l == 4:
# cosalpha2 = cosalpha*cosalpha
# return np.array([0*cosalpha+1, cosalpha, 2*cosalpha2 - 1, 4*cosalpha2*cosalpha - 3*cosalpha, 8*cosalpha2*cosalpha2 - 8*cosalpha2 + 1])
# else:
# raise ValueError('This code currently only supports modes up to mprime=4, l=4 and requires the quadrupole mode.')
# def cosntheta(costheta, n):
# if n == 0:
# return 0*costheta + 1
# elif n == 1:
# return costheta
# elif n == 2:
# return 2*costheta*costheta - 1
# elif n == 3:
# costheta2 = costheta*costheta
# return 4*costheta2*costheta - 3*costheta
# elif n == 4:
# costheta2 = costheta*costheta
# return 8*costheta2*costheta2 - 8*costheta2 + 1
# def create_cosmprimegamma_arr(cosgamma, mprime_arr):
# return np.array([cosntheta(cosgamma[i], mprime_arr[i]) for i in range(len(mprime_arr))])
# def sinfromthetacos(theta, costheta):
# thetam2pi = theta % (2*np.pi)
# return np.where(thetam2pi < np.pi, np.sqrt(1-costheta*costheta), -np.sqrt(1-costheta*costheta))
# # if thetam2pi < np.pi:
# # return np.sqrt(1-costheta*costheta)
# # else:
# # return -np.sqrt(1-costheta*costheta)
# def cosfromthetasin(theta, sintheta):
# thetampiover2m2pi = (theta-np.pi/2) % (2*np.pi)
# return np.where(thetampiover2m2pi < np.pi, -np.sqrt(1-sintheta*sintheta), np.sqrt(1-sintheta*sintheta))
# # if thetampiover2m2pi < np.pi:
# # return -np.sqrt(1-sintheta*sintheta)
# # else:
# # return np.sqrt(1-sintheta*sintheta)
def create_eimalpha(alpha, max_l):
eialpha = np.exp(1j*alpha)
if max_l == 2:
return np.array([0*alpha+1, eialpha, eialpha*eialpha])
elif max_l == 3:
eialpha2 = eialpha*eialpha
return np.array([0*alpha+1, eialpha, eialpha2, eialpha2*eialpha])
elif max_l == 4:
eialpha2 = eialpha*eialpha
return np.array([0*alpha+1, eialpha, eialpha2, eialpha2*eialpha, eialpha2*eialpha2])
else:
raise ValueError('This code currently only supports modes up to mprime=4, l=4 and requires the quadrupole mode.')
def eintheta(theta, n):
eitheta = np.exp(1j*theta)
if n == 0:
return 0*eitheta + 1
elif n == 1:
return eitheta
elif n == 2:
return eitheta*eitheta
elif n == 3:
return eitheta*eitheta*eitheta
elif n == 4:
eitheta2 = eitheta*eitheta
return eitheta2*eitheta2
def create_eimprimegamma(gamma, mprime_arr):
return np.array([eintheta(gamma[i], mprime_arr[i]) for i in range(len(mprime_arr))])
def hpc(params, f_seq, backupNNLO = True, modelist = np.array([[2,1], [2,2], [3,2], [3,3], [4,4]]) ):
"""
Computes the plus and cross polarizations for the parameters in the dict params at the frequencies in f_seq more quickly.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
modelist: array of modes to use (l, m)
"""
thetaJN = params['thetaJN']
n_freq = len(f_seq.data)
hplus_J = np.zeros(n_freq, dtype=complex)
hcross_J = np.zeros(n_freq, dtype=complex)
mprime_arr = np.unique(modelist[:, 1])
eulerangles = np.array([euler_angles(params, f_seq, mprime, backupNNLO) for mprime in mprime_arr])
max_l = np.max(modelist[:,0])
eimalpha = create_eimalpha(eulerangles[:, 0], max_l)
eibetaover2 = np.exp(eulerangles[:, 1]*1j/2)
eimprimegamma = create_eimprimegamma(eulerangles[:, 2], mprime_arr)
for mode in modelist:
mpind = np.where(mprime_arr == mode[1])[0][0]
hL = h_Lframe(params, f_seq, mode[0], -mode[1])
hplus_J += 1/2*hL*twist_factor(mode[0], mode[1], eimalpha[:, mpind], eibetaover2[mpind], eimprimegamma[mpind], thetaJN, '+')
hcross_J += 1j/2*hL*twist_factor(mode[0], mode[1], eimalpha[:, mpind], eibetaover2[mpind], eimprimegamma[mpind], thetaJN, 'x')
zeta = zeta_polarization(params)
hplus = np.cos(2*zeta)*hplus_J + np.sin(2*zeta)*hcross_J
hcross = np.cos(2*zeta)*hcross_J - np.sin(2*zeta)*hplus_J
return hplus, hcross
def hpc_component(params, f_seq, l, mprime, backupNNLO = True):
"""
Computes the (l, mprime) component of plus and cross polarizations for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
l: l index
mprime: mprime index
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
"""
thetaJN = params['thetaJN']
n_freq = len(f_seq.data)
hplus_J = np.zeros(n_freq, dtype=complex)
hcross_J = np.zeros(n_freq, dtype=complex)
eulerangles = euler_angles(params, f_seq, mprime, backupNNLO)
hL = h_Lframe(params, f_seq, l, -mprime)
hplus_J = 1/2*hL*twist_factor_slow(l, mprime, eulerangles[0], eulerangles[1], eulerangles[2], thetaJN, '+')
hcross_J = 1j/2*hL*twist_factor_slow(l, mprime, eulerangles[0], eulerangles[1], eulerangles[2], thetaJN, 'x')
zeta = zeta_polarization(params)
hplus = np.cos(2*zeta)*hplus_J + np.sin(2*zeta)*hcross_J
hcross = np.cos(2*zeta)*hcross_J - np.sin(2*zeta)*hplus_J
return hplus, hcross
def hpc_component_fast(params, f_seq, l, mprime, backupNNLO = True):
"""
DOES NOT YET WORK!
Computes the (l, mprime) component of plus and cross polarizations for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
l: l index
mprime: mprime index
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
"""
thetaJN = params['thetaJN']
n_freq = len(f_seq.data)
hplus_J = np.zeros(n_freq, dtype=complex)
hcross_J = np.zeros(n_freq, dtype=complex)
eulerangles = euler_angles(params, f_seq, mprime, backupNNLO)
eimalpha = create_eimalpha(eulerangles[0], l)
eibetaover2 = np.exp(eulerangles[1]*1j/2)
eimprimegamma = create_eimprimegamma(eulerangles[2], mprime)
hL = h_Lframe(params, f_seq, l, -mprime)
hplus_J += 1/2*hL*twist_factor(l, mprime, eimalpha, eibetaover2, eimprimegamma, thetaJN, '+')
hcross_J += 1j/2*hL*twist_factor(l, mprime, eimalpha, eibetaover2, eimprimegamma, thetaJN, 'x')
zeta = zeta_polarization(params)
hplus = np.cos(2*zeta)*hplus_J + np.sin(2*zeta)*hcross_J
hcross = np.cos(2*zeta)*hcross_J - np.sin(2*zeta)*hplus_J
return hplus, hcross
def lal_hpc(params, f_seq):
"""
Computes the plus and cross polarizations for the parameters in the dict params at the frequencies in f_seq by calling lal for the polarizations directly.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
"""
pdict = {'DL': params['distance'],
'phiref': params['phi_ref'],
'f_ref': params['f_ref'],
'inclination': params['inclination'],
'm1': params['mass_1'] * lal.MSUN_SI, 'm2': params['mass_2'] * lal.MSUN_SI,
's1x': params['chi_1x'], 's1y': params['chi_1y'], 's1z': params['chi_1z'],
's2x': params['chi_2x'], 's2y': params['chi_2y'], 's2z': params['chi_2z']}
PARAMNAMES = ['phiref', 'm1', 'm2', 's1x', 's1y', 's1z',
's2x', 's2y', 's2z', 'f_ref', 'DL', 'inclination']
# Tidal deformabilities are zero for black holes
lal_pars = lal.CreateDict()
lalsim.SimInspiralWaveformParamsInsertTidalLambda1(lal_pars, 0.)
lalsim.SimInspiralWaveformParamsInsertTidalLambda2(lal_pars, 0.)
# Parameters in the order that LAL takes, give approximant for the IMRPhenomXPHM model
wfparams = [pdict[p] for p in PARAMNAMES] \
+ [lal_pars, lalsim.GetApproximantFromString("IMRPhenomXPHM"), f_seq]
# Generate hplus, hcross
hplus, hcross = lalsim.SimInspiralChooseFDWaveformSequence(
*wfparams)
return hplus.data.data, hcross.data.data
def compute_response_coeffs(params, detstrings = ['H1', 'L1', 'V1']):
"""
Computes the detector response coefficients for the parameters in the dict params.
params: parameter dictionary
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
det_response = [lal.CachedDetectors[DET_CODE[det_name]].response
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
X = np.array([-np.cos(psi)*np.sin(gha)-np.sin(psi)*np.cos(gha)*np.sin(dec),
-np.cos(psi)*np.cos(gha)+np.sin(psi)*np.sin(gha)*np.sin(dec),
np.sin(psi)*np.cos(dec)])
Y = np.array([np.sin(psi)*np.sin(gha)-np.cos(psi)*np.cos(gha)*np.sin(dec),
np.sin(psi)*np.cos(gha)+np.cos(psi)*np.sin(gha)*np.sin(dec),
np.cos(psi)*np.cos(dec)])
Fplus = np.zeros(ndet)
Fcross = np.zeros(ndet)
for i_det in range(ndet):
for i in range(3):
for j in range(3):
Fplus[i_det] += X[j]*det_response[i_det][j][i]*X[i] - Y[j]*det_response[i_det][j][i]*Y[i]
Fcross[i_det] += X[j]*det_response[i_det][j][i]*Y[i] + Y[j]*det_response[i_det][j][i]*X[i]
return Fplus, Fcross
def compute_strain(params, f_seq, backupNNLO = True, modelist = np.array([[2,1], [2,2], [3,2], [3,3], [4,4]]), uselal = False, detstrings = ['H1', 'L1', 'V1']):
"""
Computes the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
modelist: array of modes to use (l, m)
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
if uselal:
try:
hplus, hcross = lal_hpc(params, f_seq)
except:
hplus, hcross = lal_hpc(add_op(params), f_seq)
else:
hplus, hcross = hpc(params, f_seq, backupNNLO, modelist)
ra = params['ra']
dec = params['dec']
tgps = params['tgps']
tc = params['tc']
tcoarse = params['tcoarse']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_location = [lal.CachedDetectors[DET_CODE[det_name]].location
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
esrc = np.array([np.cos(dec)*np.cos(gha), -np.cos(dec)*np.sin(gha), np.sin(dec)])
time_delay_offset = np.array([-np.dot(esrc, det_location[i_det]) / lal.C_SI for i_det in range(ndet)])
time_delay_offset_refdet = time_delay_offset[i_refdet]
time_delay = time_delay_offset - time_delay_offset_refdet
Fplus, Fcross = compute_response_coeffs(params, detstrings)
# Detector strain
return ((Fplus[:, np.newaxis] * hplus
+ Fcross[:, np.newaxis] * hcross)
* np.exp(-2j * np.pi * f_seq.data
* (tcoarse + tc + time_delay[:, np.newaxis])))
def compute_strain_component(params, f_seq, l, mprime, backupNNLO = True, detstrings = ['H1', 'L1', 'V1']):
"""
Computes the (l, mprime) component of the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
l: l index
mprime: mprime index
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
hplus, hcross = hpc_component(params, f_seq, l, mprime, backupNNLO)
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
tc = params['tc']
tcoarse = params['tcoarse']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_location = [lal.CachedDetectors[DET_CODE[det_name]].location
for det_name in detstrings]
det_response = [lal.CachedDetectors[DET_CODE[det_name]].response
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
esrc = np.array([np.cos(dec)*np.cos(gha), -np.cos(dec)*np.sin(gha), np.sin(dec)])
time_delay_offset = np.array([-np.dot(esrc, det_location[i_det]) / lal.C_SI for i_det in range(ndet)])
time_delay_offset_refdet = time_delay_offset[i_refdet]
time_delay = time_delay_offset - time_delay_offset_refdet
X = np.array([-np.cos(psi)*np.sin(gha)-np.sin(psi)*np.cos(gha)*np.sin(dec),
-np.cos(psi)*np.cos(gha)+np.sin(psi)*np.sin(gha)*np.sin(dec),
np.sin(psi)*np.cos(dec)])
Y = np.array([np.sin(psi)*np.sin(gha)-np.cos(psi)*np.cos(gha)*np.sin(dec),
np.sin(psi)*np.cos(gha)+np.cos(psi)*np.sin(gha)*np.sin(dec),
np.cos(psi)*np.cos(dec)])
Fplus = np.zeros(ndet)
Fcross = np.zeros(ndet)
for i_det in range(ndet):
for i in range(3):
for j in range(3):
Fplus[i_det] += X[j]*det_response[i_det][j][i]*X[i] - Y[j]*det_response[i_det][j][i]*Y[i]
Fcross[i_det] += X[j]*det_response[i_det][j][i]*Y[i] + Y[j]*det_response[i_det][j][i]*X[i]
# Detector strain
return ((Fplus[:, np.newaxis] * hplus
+ Fcross[:, np.newaxis] * hcross)
* np.exp(-2j * np.pi * f_seq.data
* (tcoarse + tc + time_delay[:, np.newaxis])))
def compute_strain_components(params, f_seq, backupNNLO = True, modelist = np.array([[2,1], [2,2], [3,2], [3,3], [4,4]]), detstrings = ['H1', 'L1', 'V1']):
"""
Computes all components of the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
modelist: array of modes to use (l, m)
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
hpc = np.array([hpc_component(params, f_seq, mode[0], mode[1], backupNNLO) for mode in modelist])
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
tc = params['tc']
tcoarse = params['tcoarse']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_location = [lal.CachedDetectors[DET_CODE[det_name]].location
for det_name in detstrings]
det_response = [lal.CachedDetectors[DET_CODE[det_name]].response
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
esrc = np.array([np.cos(dec)*np.cos(gha), -np.cos(dec)*np.sin(gha), np.sin(dec)])
time_delay_offset = np.array([-np.dot(esrc, det_location[i_det]) / lal.C_SI for i_det in range(ndet)])
time_delay_offset_refdet = time_delay_offset[i_refdet]
time_delay = time_delay_offset - time_delay_offset_refdet
X = np.array([-np.cos(psi)*np.sin(gha)-np.sin(psi)*np.cos(gha)*np.sin(dec),
-np.cos(psi)*np.cos(gha)+np.sin(psi)*np.sin(gha)*np.sin(dec),
np.sin(psi)*np.cos(dec)])
Y = np.array([np.sin(psi)*np.sin(gha)-np.cos(psi)*np.cos(gha)*np.sin(dec),
np.sin(psi)*np.cos(gha)+np.cos(psi)*np.sin(gha)*np.sin(dec),
np.cos(psi)*np.cos(dec)])
Fplus = np.zeros(ndet)
Fcross = np.zeros(ndet)
for i_det in range(ndet):
for i in range(3):
for j in range(3):
Fplus[i_det] += X[j]*det_response[i_det][j][i]*X[i] - Y[j]*det_response[i_det][j][i]*Y[i]
Fcross[i_det] += X[j]*det_response[i_det][j][i]*Y[i] + Y[j]*det_response[i_det][j][i]*X[i]
# (detector, mode, frequency)
return ((Fplus[:, np.newaxis, np.newaxis] * hpc[np.newaxis, :, 0, :]
+ Fcross[:, np.newaxis, np.newaxis] * hpc[np.newaxis, :, 1, :])
* np.exp(-2j * np.pi * f_seq.data[np.newaxis, np.newaxis, :]
* (tcoarse + tc + time_delay[:, np.newaxis, np.newaxis])))
def compute_old_C_prefactor(params, f_seq, l, mprime, backupNNLO = True, detstrings = ['H1', 'L1', 'V1']):
"""
Computes the prefactor of the (l, mprime) L frame mode of the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
l: l index
mprime: mprime index
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
thetaJN = params['thetaJN']
n_freq = len(f_seq.data)
eulerangles = euler_angles(params, f_seq, mprime, backupNNLO)
Cplus_J = 1/2*twist_factor_slow(l, mprime, eulerangles[0], eulerangles[1], eulerangles[2], thetaJN, '+')
Ccross_J = 1j/2*twist_factor_slow(l, mprime, eulerangles[0], eulerangles[1], eulerangles[2], thetaJN, 'x')
zeta = zeta_polarization(params)
Cplus = np.cos(2*zeta)*Cplus_J + np.sin(2*zeta)*Ccross_J
Ccross = np.cos(2*zeta)*Ccross_J - np.sin(2*zeta)*Cplus_J
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
tc = params['tc']
tcoarse = params['tcoarse']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_location = [lal.CachedDetectors[DET_CODE[det_name]].location
for det_name in detstrings]
det_response = [lal.CachedDetectors[DET_CODE[det_name]].response
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
esrc = np.array([np.cos(dec)*np.cos(gha), -np.cos(dec)*np.sin(gha), np.sin(dec)])
time_delay_offset = np.array([-np.dot(esrc, det_location[i_det]) / lal.C_SI for i_det in range(ndet)])
time_delay_offset_refdet = time_delay_offset[i_refdet]
time_delay = time_delay_offset - time_delay_offset_refdet
X = np.array([-np.cos(psi)*np.sin(gha)-np.sin(psi)*np.cos(gha)*np.sin(dec),
-np.cos(psi)*np.cos(gha)+np.sin(psi)*np.sin(gha)*np.sin(dec),
np.sin(psi)*np.cos(dec)])
Y = np.array([np.sin(psi)*np.sin(gha)-np.cos(psi)*np.cos(gha)*np.sin(dec),
np.sin(psi)*np.cos(gha)+np.cos(psi)*np.sin(gha)*np.sin(dec),
np.cos(psi)*np.cos(dec)])
Fplus = np.zeros(ndet)
Fcross = np.zeros(ndet)
for i_det in range(ndet):
for i in range(3):
for j in range(3):
Fplus[i_det] += X[j]*det_response[i_det][j][i]*X[i] - Y[j]*det_response[i_det][j][i]*Y[i]
Fcross[i_det] += X[j]*det_response[i_det][j][i]*Y[i] + Y[j]*det_response[i_det][j][i]*X[i]
# (detector, frequency)
return ((Fplus[:, np.newaxis] * Cplus
+ Fcross[:, np.newaxis] * Ccross)
* np.exp(-2j * np.pi * f_seq.data
* (tcoarse + tc + time_delay[:, np.newaxis])))
def compute_C_prefactor(params, f_seq, l, mprime, backupNNLO = True, detstrings = ['H1', 'L1', 'V1']):
"""
Computes the prefactor of the (l, mprime) time-dependent L frame mode of the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
l: l index
mprime: mprime index
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
thetaJN = params['thetaJN']
n_freq = len(f_seq.data)
eulerangles = euler_angles(params, f_seq, mprime, backupNNLO)
Cplus_J = 1/2*twist_factor_slow(l, mprime, eulerangles[0], eulerangles[1], eulerangles[2], thetaJN, '+')
Ccross_J = 1j/2*twist_factor_slow(l, mprime, eulerangles[0], eulerangles[1], eulerangles[2], thetaJN, 'x')
zeta = zeta_polarization(params)
Cplus = np.cos(2*zeta)*Cplus_J + np.sin(2*zeta)*Ccross_J
Ccross = np.cos(2*zeta)*Ccross_J - np.sin(2*zeta)*Cplus_J
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_response = [lal.CachedDetectors[DET_CODE[det_name]].response
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
X = np.array([-np.cos(psi)*np.sin(gha)-np.sin(psi)*np.cos(gha)*np.sin(dec),
-np.cos(psi)*np.cos(gha)+np.sin(psi)*np.sin(gha)*np.sin(dec),
np.sin(psi)*np.cos(dec)])
Y = np.array([np.sin(psi)*np.sin(gha)-np.cos(psi)*np.cos(gha)*np.sin(dec),
np.sin(psi)*np.cos(gha)+np.cos(psi)*np.sin(gha)*np.sin(dec),
np.cos(psi)*np.cos(dec)])
Fplus = np.zeros(ndet)
Fcross = np.zeros(ndet)
for i_det in range(ndet):
for i in range(3):
for j in range(3):
Fplus[i_det] += X[j]*det_response[i_det][j][i]*X[i] - Y[j]*det_response[i_det][j][i]*Y[i]
Fcross[i_det] += X[j]*det_response[i_det][j][i]*Y[i] + Y[j]*det_response[i_det][j][i]*X[i]
# (detector, frequency)
return (Fplus[:, np.newaxis] * Cplus
+ Fcross[:, np.newaxis] * Ccross)
def compute_td_L_frame_mode(params, f_seq, l, mprime, detstrings = ['H1', 'L1', 'V1']):
"""
Computes the time-dependent (l, mprime) L frame mode of the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
l: l index
mprime: mprime index
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
hL = h_Lframe(params, f_seq, l, -mprime)
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
tc = params['tc']
tcoarse = params['tcoarse']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_location = [lal.CachedDetectors[DET_CODE[det_name]].location
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
esrc = np.array([np.cos(dec)*np.cos(gha), -np.cos(dec)*np.sin(gha), np.sin(dec)])
time_delay_offset = np.array([-np.dot(esrc, det_location[i_det]) / lal.C_SI for i_det in range(ndet)])
time_delay_offset_refdet = time_delay_offset[i_refdet]
time_delay = time_delay_offset - time_delay_offset_refdet
# (detector, frequency)
return hL * np.exp(-2j * np.pi * f_seq.data
* (tcoarse + tc + time_delay[:, np.newaxis]))
def compute_C_prefactors(params, f_seq, modelist = np.array([[2,1], [2,2], [3,2], [3,3], [4,4]]), backupNNLO = True, detstrings = ['H1', 'L1', 'V1']):
"""
Computes all prefactors of the time-dependent L frame modes of the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
modelist: array of modes to use (l, m)
backupNNLO: boolean, if True: uses NNLO (next to next to leading order) angles as a backup to MSA (multiple scale analysis) angles if the MSA prescription fails
if False: raises an error if the MSA prescription fails
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
thetaJN = params['thetaJN']
n_freq = len(f_seq.data)
eulerangles = np.array([euler_angles(params, f_seq, mode[1], backupNNLO) for mode in modelist])
Cplus_J = np.array([1/2*twist_factor_slow(modelist[i,0], modelist[i,1], eulerangles[i, 0], eulerangles[i, 1], eulerangles[i, 2], thetaJN, '+') for i in range(modelist.shape[0])])
Ccross_J = np.array([1j/2*twist_factor_slow(modelist[i,0], modelist[i,1], eulerangles[i, 0], eulerangles[i, 1], eulerangles[i, 2], thetaJN, 'x') for i in range(modelist.shape[0])])
zeta = zeta_polarization(params)
Cplus = np.cos(2*zeta)*Cplus_J + np.sin(2*zeta)*Ccross_J
Ccross = np.cos(2*zeta)*Ccross_J - np.sin(2*zeta)*Cplus_J
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_response = [lal.CachedDetectors[DET_CODE[det_name]].response
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
X = np.array([-np.cos(psi)*np.sin(gha)-np.sin(psi)*np.cos(gha)*np.sin(dec),
-np.cos(psi)*np.cos(gha)+np.sin(psi)*np.sin(gha)*np.sin(dec),
np.sin(psi)*np.cos(dec)])
Y = np.array([np.sin(psi)*np.sin(gha)-np.cos(psi)*np.cos(gha)*np.sin(dec),
np.sin(psi)*np.cos(gha)+np.cos(psi)*np.sin(gha)*np.sin(dec),
np.cos(psi)*np.cos(dec)])
Fplus = np.zeros(ndet)
Fcross = np.zeros(ndet)
for i_det in range(ndet):
for i in range(3):
for j in range(3):
Fplus[i_det] += X[j]*det_response[i_det][j][i]*X[i] - Y[j]*det_response[i_det][j][i]*Y[i]
Fcross[i_det] += X[j]*det_response[i_det][j][i]*Y[i] + Y[j]*det_response[i_det][j][i]*X[i]
# (detector, mode, frequency)
return (Fplus[:, np.newaxis, np.newaxis] * Cplus[np.newaxis, :, :]
+ Fcross[:, np.newaxis, np.newaxis] * Ccross[np.newaxis, :, :])
def compute_td_L_frame_modes(params, f_seq, modelist = np.array([[2,1], [2,2], [3,2], [3,3], [4,4]]), detstrings = ['H1', 'L1', 'V1']):
"""
Computes all time-dependent L frame modes of the strain in the detectors in detstrings for the parameters in the dict params at the frequencies in f_seq.
params: parameter dictionary
f_seq: REAL8Sequence LAL object that contains a frequency array
modelist: array of modes to use (l, m)
detstrings: an array of strings specifying the detectors to use in the analysis: H1: LIGO Hanford, L1: LIGO Livingston, V1: Virgo, uses all by default
"""
hL = np.array([h_Lframe(params, f_seq, mode[0], -mode[1]) for mode in modelist])
ra = params['ra']
dec = params['dec']
psi = params['psi']
tgps = params['tgps']
tc = params['tc']
tcoarse = params['tcoarse']
DET_CODE = {'H1': lal.LHO_4K_DETECTOR,
'L1': lal.LLO_4K_DETECTOR,
'V1': lal.VIRGO_DETECTOR}
ndet = len(detstrings)
try:
i_refdet = detstrings.index('L1') # Livingston is the reference detector
except:
try:
i_refdet = detstrings.index('H1') # If no Livingston, Hanford is the reference detector
except:
try:
i_refdet = detstrings.index('V1') # If no Livingston or Hanford, Virgo is the reference detector
except:
raise ValueError('detstring must contain H1, L1, or V1')
det_location = [lal.CachedDetectors[DET_CODE[det_name]].location
for det_name in detstrings]
gmst = lal.GreenwichMeanSiderealTime(tgps)
gha = gmst - ra
esrc = np.array([np.cos(dec)*np.cos(gha), -np.cos(dec)*np.sin(gha), np.sin(dec)])
time_delay_offset = np.array([-np.dot(esrc, det_location[i_det]) / lal.C_SI for i_det in range(ndet)])
time_delay_offset_refdet = time_delay_offset[i_refdet]
time_delay = time_delay_offset - time_delay_offset_refdet
# (detector, mode, frequency)
return hL[np.newaxis, :, :] * np.exp(-2j * np.pi * f_seq.data[np.newaxis, np.newaxis, :]
* (tcoarse + tc + time_delay[:, np.newaxis, np.newaxis]))
# Functions for switching between new and old parameters
def thetaJN_func_op(params):
"""
Computes thetaJN, the angle between the total angular momentum J and the line of sight normal vector N.
params: parameter dictionary that has the old angle parameters iota/inclination and phiref
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
m1 = params['mass_1']
m2 = params['mass_2']
M = m1 + m2
s1x = params['chi_1x']
s1y = params['chi_1y']
s1z = params['chi_1z']
s2x = params['chi_2x']
s2y = params['chi_2y']
s2z = params['chi_2z']
iota = params['inclination']
phiref = params['phi_ref']
# Components in L0 frame
Jx = (m1/M)**2*s1x + (m2/M)**2*s2x
Jy = (m1/M)**2*s1y + (m2/M)**2*s2y
Jz = (m1/M)**2*s1z + (m2/M)**2*s2z + L0_func(params)
J = np.array([Jx, Jy, Jz])
Nx = np.sin(iota)*np.cos((np.pi/2)-phiref)
Ny = np.sin(iota)*np.sin((np.pi/2)-phiref)
Nz = np.cos(iota)
N = np.array([Nx, Ny, Nz])
return np.arccos(np.dot(J, N)/np.linalg.norm(J))
def kappa_func_op(params):
"""
Computes kappa, the final Euler angle between the L0 and J frames.
params: parameter dictionary that has the old angle parameters iota/inclination and phiref
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
iota = params['inclination']
phiref = params['phi_ref']
# Components in L0 frame
Nx = np.sin(iota)*np.cos((np.pi/2)-phiref)
Ny = np.sin(iota)*np.sin((np.pi/2)-phiref)
Nz = np.cos(iota)
N = np.array([Nx, Ny, Nz])
# Rotate to J prime frame
phiJL = phiJL_func(params)
thetaJL = thetaJL_func(params)
N_Jp = rotate_y(rotate_z(N, -phiJL), -thetaJL)
Nx_Jp = N_Jp[0]
Ny_Jp = N_Jp[1]
return np.arctan2(Ny_Jp, Nx_Jp)
def iota_func_np(params):
"""
Computes iota, the angle between initial angular momentum L0 and the line of sight normal vector N.
params: parameter dictionary that has the new angle parameters thetaJN and kappa
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
thetaJN = params['thetaJN']
kappa = params['kappa']
# Components in J frame
Nx = np.sin(thetaJN)
# Ny = 0
Nz = np.cos(thetaJN)
N = np.array([Nx, 0, Nz])
# Rotate to L0 frame
phiJL = phiJL_func(params)
thetaJL = thetaJL_func(params)
NL0 = rotate_z(rotate_y(rotate_z(N, kappa), thetaJL), phiJL)
return np.arccos(NL0[2])
def phiref_func_np(params):
"""
Computes phiref, the azimuthal angle of N in the L0 frame.
params: parameter dictionary that has the new angle parameters thetaJN and kappa
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
thetaJN = params['thetaJN']
kappa = params['kappa']
# Components in J frame
Nx = np.sin(thetaJN)
# Ny = 0
Nz = np.cos(thetaJN)
N = np.array([Nx, 0, Nz])
# Rotate to L0 frame
phiJL = phiJL_func(params)
thetaJL = thetaJL_func(params)
NL0 = rotate_z(rotate_y(rotate_z(N, kappa), thetaJL), phiJL)
return np.pi/2 - np.arctan2(NL0[1], NL0[0])
def add_np(params):
"""
Computes and adds the new parameters thetaJN and kappa to the parameter dictionary (given a valid parameter dictionary that has inclination (iota) and phiref)
params: parameter dictionary that has the old angle parameters iota/inclination and phiref
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
m1 = params['mass_1']
m2 = params['mass_2']
M = m1 + m2
s1x = params['chi_1x']
s1y = params['chi_1y']
s1z = params['chi_1z']
s2x = params['chi_2x']
s2y = params['chi_2y']
s2z = params['chi_2z']
iota = params['inclination']
phiref = params['phi_ref']
# Components in L0 frame
Jx = (m1/M)**2*s1x + (m2/M)**2*s2x
Jy = (m1/M)**2*s1y + (m2/M)**2*s2y
Jz = (m1/M)**2*s1z + (m2/M)**2*s2z + L0_func(params)
J = np.array([Jx, Jy, Jz])
Nx = np.sin(iota)*np.cos((np.pi/2)-phiref)
Ny = np.sin(iota)*np.sin((np.pi/2)-phiref)
Nz = np.cos(iota)
N = np.array([Nx, Ny, Nz])
params['thetaJN'] = np.arccos(np.dot(J, N)/np.linalg.norm(J))
# Rotate N to J prime frame
phiJL = phiJL_func(params)
thetaJL = thetaJL_func(params)
N_Jp = rotate_y(rotate_z(N, -phiJL), -thetaJL)
Nx_Jp = N_Jp[0]
Ny_Jp = N_Jp[1]
params['kappa'] = np.arctan2(Ny_Jp, Nx_Jp)
return params
def add_op(params):
"""
Computes and adds the old parameters inclination (iota) and phiref to the parameter dictionary (given a valid parameter dictionary that has the thetaJN and kappa).
params: parameter dictionary that has the new angle parameters thetaJN and kappa
"""
if params['mass_1'] < params['mass_2']:
temp = params['mass_1']
params['mass_1'] = params['mass_2']
params['mass_2'] = temp
thetaJN = params['thetaJN']
kappa = params['kappa']
# Components in J frame
Nx = np.sin(thetaJN)
# Ny = 0
Nz = np.cos(thetaJN)
N = np.array([Nx, 0, Nz])
# Rotate to L0 frame
phiJL = phiJL_func(params)
thetaJL = thetaJL_func(params)
NL0 = rotate_z(rotate_y(rotate_z(N, kappa), thetaJL), phiJL)
params['inclination'] = np.arccos(NL0[2])
params['phi_ref'] = np.pi/2 - np.arctan2(NL0[1], NL0[0])
return params
| 41.179798
| 347
| 0.583808
| 9,030
| 61,152
| 3.859136
| 0.048726
| 0.017505
| 0.009642
| 0.014635
| 0.864354
| 0.841426
| 0.821396
| 0.809487
| 0.801194
| 0.798123
| 0
| 0.031106
| 0.278732
| 61,152
| 1,485
| 348
| 41.179798
| 0.758973
| 0.259942
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| 0.786772
| 0
| 0.003949
| 0.060372
| 0
| 0
| 0
| 0
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| 0
| 1
| 0.037512
| false
| 0
| 0.002962
| 0.000987
| 0.084896
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
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|
0
| 7
|
d74853b56b840d040ed80e2a286984baaf237468
| 35,560
|
py
|
Python
|
appengine/monorail/search/test/ast2select_test.py
|
mcgreevy/chromium-infra
|
09064105713603f7bf75c772e8354800a1bfa256
|
[
"BSD-3-Clause"
] | 1
|
2018-01-02T05:47:07.000Z
|
2018-01-02T05:47:07.000Z
|
appengine/monorail/search/test/ast2select_test.py
|
mcgreevy/chromium-infra
|
09064105713603f7bf75c772e8354800a1bfa256
|
[
"BSD-3-Clause"
] | null | null | null |
appengine/monorail/search/test/ast2select_test.py
|
mcgreevy/chromium-infra
|
09064105713603f7bf75c772e8354800a1bfa256
|
[
"BSD-3-Clause"
] | null | null | null |
# Copyright 2016 The Chromium Authors. All rights reserved.
# Use of this source code is govered by a BSD-style
# license that can be found in the LICENSE file or at
# https://developers.google.com/open-source/licenses/bsd
"""Tests for the ast2select module."""
import datetime
import time
import unittest
from framework import sql
from proto import ast_pb2
from proto import tracker_pb2
from search import ast2select
from search import query2ast
from tracker import tracker_bizobj
BUILTIN_ISSUE_FIELDS = query2ast.BUILTIN_ISSUE_FIELDS
ANY_FIELD = query2ast.BUILTIN_ISSUE_FIELDS['any_field']
class AST2SelectTest(unittest.TestCase):
def setUp(self):
self.config = tracker_bizobj.MakeDefaultProjectIssueConfig(789)
def testBuildSQLQuery_EmptyAST(self):
ast = ast_pb2.QueryAST(conjunctions=[ast_pb2.Conjunction()]) # No conds
left_joins, where = ast2select.BuildSQLQuery(ast)
self.assertEqual([], left_joins)
self.assertEqual([], where)
def testBuildSQLQuery_Normal(self):
owner_field = BUILTIN_ISSUE_FIELDS['owner']
reporter_id_field = BUILTIN_ISSUE_FIELDS['reporter_id']
conds = [
ast_pb2.MakeCond(
ast_pb2.QueryOp.TEXT_HAS, [owner_field], ['example.com'], []),
ast_pb2.MakeCond(
ast_pb2.QueryOp.EQ, [reporter_id_field], [], [111L])]
ast = ast_pb2.QueryAST(conjunctions=[ast_pb2.Conjunction(conds=conds)])
left_joins, where = ast2select.BuildSQLQuery(ast)
self.assertEqual(
[('User AS Cond0 ON (Issue.owner_id = Cond0.user_id '
'OR Issue.derived_owner_id = Cond0.user_id)', [])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('(LOWER(Cond0.email) LIKE %s)', ['%example.com%']),
('Issue.reporter_id = %s', [111L])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockingIDCond_SingleValue(self):
fd = BUILTIN_ISSUE_FIELDS['blocking_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.EQ, [fd], ['1'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [1L])
for cond, expected in ((txt_cond, '1'), (num_cond, 1L)):
left_joins, where = ast2select._ProcessBlockingIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.dst_issue_id AND '
'Cond1.kind = %s AND Cond1.issue_id = %s',
['blockedon', expected])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.dst_issue_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockingIDCond_NegatedSingleValue(self):
fd = BUILTIN_ISSUE_FIELDS['blocking_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.NE, [fd], ['1'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [1L])
for cond, expected in ((txt_cond, '1'), (num_cond, 1L)):
left_joins, where = ast2select._ProcessBlockingIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.dst_issue_id AND '
'Cond1.kind = %s AND Cond1.issue_id = %s',
['blockedon', expected])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.dst_issue_id IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockingIDCond_MultiValue(self):
fd = BUILTIN_ISSUE_FIELDS['blocking_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.EQ, [fd], ['1', '2', '3'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [1L, 2L, 3L])
for cond, expected in ((txt_cond, ['1', '2', '3']),
(num_cond, [1L, 2L, 3L])):
left_joins, where = ast2select._ProcessBlockingIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.dst_issue_id AND '
'Cond1.kind = %s AND Cond1.issue_id IN (%s,%s,%s)',
['blockedon'] + expected)],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.dst_issue_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockingIDCond_NegatedMultiValue(self):
fd = BUILTIN_ISSUE_FIELDS['blocking_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.NE, [fd], ['1', '2', '3'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [1L, 2L, 3L])
for cond, expected in ((txt_cond, ['1', '2', '3']),
(num_cond, [1L, 2L, 3L])):
left_joins, where = ast2select._ProcessBlockingIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.dst_issue_id AND '
'Cond1.kind = %s AND Cond1.issue_id IN (%s,%s,%s)',
['blockedon'] + expected)],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.dst_issue_id IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockedOnIDCond_SingleValue(self):
fd = BUILTIN_ISSUE_FIELDS['blockedon_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.EQ, [fd], ['1'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [1L])
for cond, expected in ((txt_cond, '1'), (num_cond, 1L)):
left_joins, where = ast2select._ProcessBlockedOnIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.kind = %s AND Cond1.dst_issue_id = %s',
['blockedon', expected])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.issue_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockedOnIDCond_NegatedSingleValue(self):
fd = BUILTIN_ISSUE_FIELDS['blockedon_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.NE, [fd], ['1'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [1L])
for cond, expected in ((txt_cond, '1'), (num_cond, 1L)):
left_joins, where = ast2select._ProcessBlockedOnIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.kind = %s AND Cond1.dst_issue_id = %s',
['blockedon', expected])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.issue_id IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockedIDCond_MultiValue(self):
fd = BUILTIN_ISSUE_FIELDS['blockedon_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.EQ, [fd], ['1', '2', '3'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [1L, 2L, 3L])
for cond, expected in ((txt_cond, ['1', '2', '3']),
(num_cond, [1L, 2L, 3L])):
left_joins, where = ast2select._ProcessBlockedOnIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.kind = %s AND Cond1.dst_issue_id IN (%s,%s,%s)',
['blockedon'] + expected)],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.issue_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testBlockedIDCond_NegatedMultiValue(self):
fd = BUILTIN_ISSUE_FIELDS['blockedon_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.NE, [fd], ['1', '2', '3'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [1L, 2L, 3L])
for cond, expected in ((txt_cond, ['1', '2', '3']),
(num_cond, [1L, 2L, 3L])):
left_joins, where = ast2select._ProcessBlockedOnIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.kind = %s AND Cond1.dst_issue_id IN (%s,%s,%s)',
['blockedon'] + expected)],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.issue_id IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testMergedIntoIDCond_MultiValue(self):
fd = BUILTIN_ISSUE_FIELDS['mergedinto_id']
txt_cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.EQ, [fd], ['1', '2', '3'], [])
num_cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [1L, 2L, 3L])
for cond, expected in ((txt_cond, ['1', '2', '3']),
(num_cond, [1L, 2L, 3L])):
left_joins, where = ast2select._ProcessMergedIntoIDCond(
cond, 'Cond1', 'Issue1')
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.kind = %s AND Cond1.dst_issue_id IN (%s,%s,%s)',
['mergedinto'] + expected)],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.issue_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testHasBlockedCond(self):
for op, expected in ((ast_pb2.QueryOp.IS_DEFINED, 'IS NOT NULL'),
(ast_pb2.QueryOp.IS_NOT_DEFINED, 'IS NULL')):
fd = BUILTIN_ISSUE_FIELDS['blockedon_id']
cond = ast_pb2.MakeCond(op, [fd], [], [])
left_joins, where = ast2select._ProcessBlockedOnIDCond(
cond, 'Cond1', None)
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.kind = %s', ['blockedon'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual([('Cond1.issue_id %s' % expected, [])], where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testHasBlockingCond(self):
for op, expected in ((ast_pb2.QueryOp.IS_DEFINED, 'IS NOT NULL'),
(ast_pb2.QueryOp.IS_NOT_DEFINED, 'IS NULL')):
fd = BUILTIN_ISSUE_FIELDS['blocking_id']
cond = ast_pb2.MakeCond(op, [fd], [], [])
left_joins, where = ast2select._ProcessBlockingIDCond(cond, 'Cond1', None)
self.assertEqual(
[('IssueRelation AS Cond1 ON Issue.id = Cond1.dst_issue_id AND '
'Cond1.kind = %s', ['blockedon'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual([('Cond1.dst_issue_id %s' % expected, [])], where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessOwnerCond(self):
fd = BUILTIN_ISSUE_FIELDS['owner']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.TEXT_HAS, [fd], ['example.com'], [])
left_joins, where = ast2select._ProcessOwnerCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('User AS Cond1 ON (Issue.owner_id = Cond1.user_id '
'OR Issue.derived_owner_id = Cond1.user_id)', [])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('(LOWER(Cond1.email) LIKE %s)', ['%example.com%'])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessOwnerIDCond(self):
fd = BUILTIN_ISSUE_FIELDS['owner_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [111L])
left_joins, where = ast2select._ProcessOwnerIDCond(cond, 'Cond1', 'User1')
self.assertEqual([], left_joins)
self.assertEqual(
[('(Issue.owner_id = %s OR Issue.derived_owner_id = %s)',
[111L, 111L])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessOwnerLastVisitCond(self):
fd = BUILTIN_ISSUE_FIELDS['ownerlastvisit']
NOW = 1234567890
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.LT, [fd], [], [NOW])
left_joins, where = ast2select._ProcessOwnerLastVisitCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('User AS Cond1 ON (Issue.owner_id = Cond1.user_id OR '
'Issue.derived_owner_id = Cond1.user_id)',
[])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.last_visit_timestamp < %s',
[NOW])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessIsOwnerBouncing(self):
fd = BUILTIN_ISSUE_FIELDS['ownerbouncing']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [])
left_joins, where = ast2select._ProcessIsOwnerBouncing(
cond, 'Cond1', 'User1')
self.assertEqual(
[('User AS Cond1 ON (Issue.owner_id = Cond1.user_id OR '
'Issue.derived_owner_id = Cond1.user_id)',
[])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('(Cond1.email_bounce_timestamp IS NOT NULL AND'
' Cond1.email_bounce_timestamp != %s)',
[0])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessReporterCond(self):
fd = BUILTIN_ISSUE_FIELDS['reporter']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.TEXT_HAS, [fd], ['example.com'], [])
left_joins, where = ast2select._ProcessReporterCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('User AS Cond1 ON Issue.reporter_id = Cond1.user_id', [])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('(LOWER(Cond1.email) LIKE %s)', ['%example.com%'])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessReporterIDCond(self):
fd = BUILTIN_ISSUE_FIELDS['reporter_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [111L])
left_joins, where = ast2select._ProcessReporterIDCond(
cond, 'Cond1', 'User1')
self.assertEqual([], left_joins)
self.assertEqual(
[('Issue.reporter_id = %s', [111L])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCcCond_SinglePositive(self):
fd = BUILTIN_ISSUE_FIELDS['cc']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.TEXT_HAS, [fd], ['example.com'], [])
left_joins, where = ast2select._ProcessCcCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('(Issue2Cc AS Cond1 JOIN User AS User1 '
'ON Cond1.cc_id = User1.user_id AND (LOWER(User1.email) LIKE %s)) '
'ON Issue.id = Cond1.issue_id AND Issue.shard = Cond1.issue_shard',
['%example.com%'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('User1.email IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCcCond_MultiplePositive(self):
fd = BUILTIN_ISSUE_FIELDS['cc']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.TEXT_HAS, [fd], ['.com', '.org'], [])
left_joins, where = ast2select._ProcessCcCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('(Issue2Cc AS Cond1 JOIN User AS User1 '
'ON Cond1.cc_id = User1.user_id AND '
'(LOWER(User1.email) LIKE %s OR LOWER(User1.email) LIKE %s)) '
'ON Issue.id = Cond1.issue_id AND Issue.shard = Cond1.issue_shard',
['%.com%', '%.org%'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('User1.email IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCcCond_SingleNegative(self):
fd = BUILTIN_ISSUE_FIELDS['cc']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.NOT_TEXT_HAS, [fd], ['example.com'], [])
left_joins, where = ast2select._ProcessCcCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('(Issue2Cc AS Cond1 JOIN User AS User1 '
'ON Cond1.cc_id = User1.user_id AND (LOWER(User1.email) LIKE %s)) '
'ON Issue.id = Cond1.issue_id AND Issue.shard = Cond1.issue_shard',
['%example.com%'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('User1.email IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCcCond_Multiplenegative(self):
fd = BUILTIN_ISSUE_FIELDS['cc']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.NOT_TEXT_HAS, [fd], ['.com', '.org'], [])
left_joins, where = ast2select._ProcessCcCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('(Issue2Cc AS Cond1 JOIN User AS User1 '
'ON Cond1.cc_id = User1.user_id AND '
'(LOWER(User1.email) LIKE %s OR LOWER(User1.email) LIKE %s)) '
'ON Issue.id = Cond1.issue_id AND Issue.shard = Cond1.issue_shard',
['%.com%', '%.org%'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('User1.email IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCcIDCond(self):
fd = BUILTIN_ISSUE_FIELDS['cc_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [111L])
left_joins, where = ast2select._ProcessCcIDCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2Cc AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.cc_id = %s',
[111L])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.cc_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessStarredByCond(self):
fd = BUILTIN_ISSUE_FIELDS['starredby']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.TEXT_HAS, [fd], ['example.com'], [])
left_joins, where = ast2select._ProcessStarredByCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('(IssueStar AS Cond1 JOIN User AS User1 '
'ON Cond1.user_id = User1.user_id AND (LOWER(User1.email) LIKE %s)) '
'ON Issue.id = Cond1.issue_id', ['%example.com%'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('User1.email IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessStarredByIDCond(self):
fd = BUILTIN_ISSUE_FIELDS['starredby_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [111L])
left_joins, where = ast2select._ProcessStarredByIDCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('IssueStar AS Cond1 ON Issue.id = Cond1.issue_id '
'AND Cond1.user_id = %s', [111L])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.user_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCommentByCond(self):
fd = BUILTIN_ISSUE_FIELDS['commentby']
cond = ast_pb2.MakeCond(
ast_pb2.QueryOp.TEXT_HAS, [fd], ['example.com'], [])
left_joins, where = ast2select._ProcessCommentByCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('(Comment AS Cond1 JOIN User AS User1 '
'ON Cond1.commenter_id = User1.user_id '
'AND (LOWER(User1.email) LIKE %s)) '
'ON Issue.id = Cond1.issue_id AND Cond1.deleted_by IS NULL',
['%example.com%'])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('User1.email IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCommentByIDCond_EqualsUserID(self):
fd = BUILTIN_ISSUE_FIELDS['commentby_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [111L])
left_joins, where = ast2select._ProcessCommentByIDCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Comment AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.commenter_id = %s AND Cond1.deleted_by IS NULL',
[111L])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.commenter_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCommentByIDCond_QuickOr(self):
fd = BUILTIN_ISSUE_FIELDS['commentby_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [111L, 222L])
left_joins, where = ast2select._ProcessCommentByIDCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Comment AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.commenter_id IN (%s,%s) '
'AND Cond1.deleted_by IS NULL',
[111L, 222L])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.commenter_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCommentByIDCond_NotEqualsUserID(self):
fd = BUILTIN_ISSUE_FIELDS['commentby_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [111L])
left_joins, where = ast2select._ProcessCommentByIDCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Comment AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.commenter_id = %s AND Cond1.deleted_by IS NULL',
[111L])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.commenter_id IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessStatusIDCond(self):
fd = BUILTIN_ISSUE_FIELDS['status_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [2])
left_joins, where = ast2select._ProcessStatusIDCond(cond, 'Cond1', 'User1')
self.assertEqual([], left_joins)
self.assertEqual(
[('(Issue.status_id = %s OR Issue.derived_status_id = %s)', [2, 2])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessLabelIDCond_NoValue(self):
fd = BUILTIN_ISSUE_FIELDS['label_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [])
with self.assertRaises(ast2select.NoPossibleResults):
ast2select._ProcessLabelIDCond(cond, 'Cond1', 'User1')
def testProcessLabelIDCond_SingleValue(self):
fd = BUILTIN_ISSUE_FIELDS['label_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [1])
left_joins, where = ast2select._ProcessLabelIDCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2Label AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.label_id = %s', [1])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.label_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessLabelIDCond_MultipleValue(self):
fd = BUILTIN_ISSUE_FIELDS['label_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [1, 2])
left_joins, where = ast2select._ProcessLabelIDCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2Label AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.label_id IN (%s,%s)', [1, 2])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.label_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessLabelIDCond_NegatedNoValue(self):
fd = BUILTIN_ISSUE_FIELDS['label_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [])
left_joins, where = ast2select._ProcessLabelIDCond(cond, 'Cond1', 'User1')
self.assertEqual([], left_joins)
self.assertEqual([], where)
def testProcessLabelIDCond_NegatedSingleValue(self):
fd = BUILTIN_ISSUE_FIELDS['label_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [1])
left_joins, where = ast2select._ProcessLabelIDCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2Label AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.label_id = %s', [1])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.label_id IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessLabelIDCond_NegatedMultipleValue(self):
fd = BUILTIN_ISSUE_FIELDS['label_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.NE, [fd], [], [1, 2])
left_joins, where = ast2select._ProcessLabelIDCond(cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2Label AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.label_id IN (%s,%s)', [1, 2])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.label_id IS NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessComponentIDCond(self):
fd = BUILTIN_ISSUE_FIELDS['component_id']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [101])
left_joins, where = ast2select._ProcessComponentIDCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2Component AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.component_id = %s', [101])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.component_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCustomFieldCond_IntType(self):
fd = tracker_pb2.FieldDef(
field_id=1, project_id=789, field_name='EstDays',
field_type=tracker_pb2.FieldTypes.INT_TYPE)
val = 42
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [val])
left_joins, where = ast2select._ProcessCustomFieldCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2FieldValue AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.field_id = %s AND '
'Cond1.int_value = %s', [1, val])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.field_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCustomFieldCond_StrType(self):
fd = tracker_pb2.FieldDef(
field_id=1, project_id=789, field_name='Nickname',
field_type=tracker_pb2.FieldTypes.STR_TYPE)
val = 'Fuzzy'
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [val], [])
left_joins, where = ast2select._ProcessCustomFieldCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2FieldValue AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.field_id = %s AND '
'Cond1.str_value = %s', [1, val])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.field_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCustomFieldCond_UserType_ByID(self):
fd = tracker_pb2.FieldDef(
field_id=1, project_id=789, field_name='ExecutiveProducer',
field_type=tracker_pb2.FieldTypes.USER_TYPE)
val = 111L
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [val])
left_joins, where = ast2select._ProcessCustomFieldCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2FieldValue AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.field_id = %s AND '
'Cond1.user_id = %s', [1, val])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.field_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCustomFieldCond_UserType_ByEmail(self):
fd = tracker_pb2.FieldDef(
field_id=1, project_id=789, field_name='ExecutiveProducer',
field_type=tracker_pb2.FieldTypes.USER_TYPE)
val = 'exec@example.com'
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [val], [])
left_joins, where = ast2select._ProcessCustomFieldCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('User AS User1 ON Cond1.user_id = User1.user_id AND '
'LOWER(User1.email) = %s', [val]),
('Issue2FieldValue AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.field_id = %s', [1])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.field_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessCustomFieldCond_DateType(self):
fd = tracker_pb2.FieldDef(
field_id=1, project_id=789, field_name='Deadline',
field_type=tracker_pb2.FieldTypes.DATE_TYPE)
val = int(time.mktime(datetime.datetime(2016, 10, 5).timetuple()))
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.EQ, [fd], [], [val])
left_joins, where = ast2select._ProcessCustomFieldCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Issue2FieldValue AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Issue.shard = Cond1.issue_shard AND '
'Cond1.field_id = %s AND '
'Cond1.date_value = %s', [1, val])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('Cond1.field_id IS NOT NULL', [])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessAttachmentCond_HasAttachment(self):
fd = BUILTIN_ISSUE_FIELDS['attachment']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.IS_DEFINED, [fd], [], [])
left_joins, where = ast2select._ProcessAttachmentCond(
cond, 'Cond1', 'User1')
self.assertEqual([], left_joins)
self.assertEqual(
[('(Issue.attachment_count IS NOT NULL AND '
'Issue.attachment_count != %s)',
[0])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.IS_NOT_DEFINED, [fd], [], [])
left_joins, where = ast2select._ProcessAttachmentCond(
cond, 'Cond1', 'User1')
self.assertEqual([], left_joins)
self.assertEqual(
[('(Issue.attachment_count IS NULL OR '
'Issue.attachment_count = %s)',
[0])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testProcessAttachmentCond_TextHas(self):
fd = BUILTIN_ISSUE_FIELDS['attachment']
cond = ast_pb2.MakeCond(ast_pb2.QueryOp.TEXT_HAS, [fd], ['jpg'], [])
left_joins, where = ast2select._ProcessAttachmentCond(
cond, 'Cond1', 'User1')
self.assertEqual(
[('Attachment AS Cond1 ON Issue.id = Cond1.issue_id AND '
'Cond1.deleted = %s',
[False])],
left_joins)
self.assertTrue(sql._IsValidJoin(left_joins[0][0]))
self.assertEqual(
[('(Cond1.filename LIKE %s)', ['%jpg%'])],
where)
self.assertTrue(sql._IsValidWhereCond(where[0][0]))
def testCompare_IntTypes(self):
val_type = tracker_pb2.FieldTypes.INT_TYPE
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.IS_DEFINED, val_type, 'col', [1, 2])
self.assertEqual('(Alias.col IS NOT NULL AND Alias.col != %s)', cond_str)
self.assertEqual([0], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.EQ, val_type, 'col', [1])
self.assertEqual('Alias.col = %s', cond_str)
self.assertEqual([1], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.EQ, val_type, 'col', [1, 2])
self.assertEqual('Alias.col IN (%s,%s)', cond_str)
self.assertEqual([1, 2], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.NE, val_type, 'col', [])
self.assertEqual('TRUE', cond_str)
self.assertEqual([], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.NE, val_type, 'col', [1])
self.assertEqual('(Alias.col IS NULL OR Alias.col != %s)', cond_str)
self.assertEqual([1], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.NE, val_type, 'col', [1, 2])
self.assertEqual('(Alias.col IS NULL OR Alias.col NOT IN (%s,%s))',
cond_str)
self.assertEqual([1, 2], cond_args)
def testCompare_STRTypes(self):
val_type = tracker_pb2.FieldTypes.STR_TYPE
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.IS_DEFINED, val_type, 'col', ['a', 'b'])
self.assertEqual('(Alias.col IS NOT NULL AND Alias.col != %s)', cond_str)
self.assertEqual([''], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.EQ, val_type, 'col', ['a'])
self.assertEqual('Alias.col = %s', cond_str)
self.assertEqual(['a'], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.EQ, val_type, 'col', ['a', 'b'])
self.assertEqual('Alias.col IN (%s,%s)', cond_str)
self.assertEqual(['a', 'b'], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.NE, val_type, 'col', [])
self.assertEqual('TRUE', cond_str)
self.assertEqual([], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.NE, val_type, 'col', ['a'])
self.assertEqual('(Alias.col IS NULL OR Alias.col != %s)', cond_str)
self.assertEqual(['a'], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.NE, val_type, 'col', ['a', 'b'])
self.assertEqual('(Alias.col IS NULL OR Alias.col NOT IN (%s,%s))',
cond_str)
self.assertEqual(['a', 'b'], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.TEXT_HAS, val_type, 'col', ['a'])
self.assertEqual('(Alias.col LIKE %s)', cond_str)
self.assertEqual(['%a%'], cond_args)
cond_str, cond_args = ast2select._Compare(
'Alias', ast_pb2.QueryOp.NOT_TEXT_HAS, val_type, 'col', ['a'])
self.assertEqual('(Alias.col IS NULL OR Alias.col NOT LIKE %s)', cond_str)
self.assertEqual(['%a%'], cond_args)
def testCompareAlreadyJoined(self):
cond_str, cond_args = ast2select._CompareAlreadyJoined(
'Alias', ast_pb2.QueryOp.EQ, 'col')
self.assertEqual('Alias.col IS NOT NULL', cond_str)
self.assertEqual([], cond_args)
cond_str, cond_args = ast2select._CompareAlreadyJoined(
'Alias', ast_pb2.QueryOp.NE, 'col')
self.assertEqual('Alias.col IS NULL', cond_str)
self.assertEqual([], cond_args)
| 40.826636
| 80
| 0.632508
| 4,372
| 35,560
| 4.934812
| 0.060156
| 0.036987
| 0.063824
| 0.041761
| 0.900301
| 0.88292
| 0.851217
| 0.842132
| 0.822758
| 0.805794
| 0
| 0.03268
| 0.215214
| 35,560
| 870
| 81
| 40.873563
| 0.740424
| 0.006271
| 0
| 0.741071
| 0
| 0.002551
| 0.21398
| 0.00867
| 0
| 0
| 0
| 0
| 0.260204
| 0
| null | null | 0
| 0.01148
| null | null | 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 8
|
d77cbaf73d523ef87327b690c2f0ef6c3a6aa600
| 163
|
py
|
Python
|
meta_ultra/cli/__init__.py
|
dcdanko/MetaUltra
|
600df03dd4aaf95268bf0062de2ad3d9ac480842
|
[
"MIT"
] | null | null | null |
meta_ultra/cli/__init__.py
|
dcdanko/MetaUltra
|
600df03dd4aaf95268bf0062de2ad3d9ac480842
|
[
"MIT"
] | null | null | null |
meta_ultra/cli/__init__.py
|
dcdanko/MetaUltra
|
600df03dd4aaf95268bf0062de2ad3d9ac480842
|
[
"MIT"
] | 1
|
2018-11-02T14:14:38.000Z
|
2018-11-02T14:14:38.000Z
|
from .cli import *
from .cli_add import *
from .cli_run import *
from .cli_remove import *
from .cli_sync import *
from .cli_view import *
from .cli_edit import *
| 20.375
| 25
| 0.742331
| 27
| 163
| 4.259259
| 0.333333
| 0.426087
| 0.678261
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.171779
| 163
| 7
| 26
| 23.285714
| 0.851852
| 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
|
ad84f09994f53892a6450f7e8ef5585ae416ff12
| 3,038
|
py
|
Python
|
utils/scripts/OOOlevelGen/src/levels/Eifel_Brought_Us_Tower.py
|
fullscreennl/monkeyswipe
|
c56192e202674dd5ab18023f6cf14cf51e95fbd0
|
[
"MIT"
] | null | null | null |
utils/scripts/OOOlevelGen/src/levels/Eifel_Brought_Us_Tower.py
|
fullscreennl/monkeyswipe
|
c56192e202674dd5ab18023f6cf14cf51e95fbd0
|
[
"MIT"
] | null | null | null |
utils/scripts/OOOlevelGen/src/levels/Eifel_Brought_Us_Tower.py
|
fullscreennl/monkeyswipe
|
c56192e202674dd5ab18023f6cf14cf51e95fbd0
|
[
"MIT"
] | null | null | null |
import LevelBuilder
from sprites import *
def render(name,bg):
lb = LevelBuilder.LevelBuilder(name+".plist",background=bg)
lb.addObject(Beam.BeamSprite(x=249, y=219,width=126,height=4,angle='95',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=231, y=219,width=126,height=4,angle='-95',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=240, y=151,width=44,height=7,angle='0',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=265, y=120,width=53,height=14,angle='-75',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=215, y=120,width=53,height=14,angle='75',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=240, y=84,width=82,height=17,angle='0',restitution=0.2,static='true',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=304, y=40,width=82,height=17,angle='120',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=176, y=40,width=82,height=17,angle='-120',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=240, y=287,width=15,height=7,angle='0',restitution=0.2,static='false',friction=0.9,density=20 ).setName('Beam'))
lb.addObject(Beam.BeamSprite(x=240, y=299,width=15,height=3,angle='90' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Star.StarSprite(x=240, y=109,width=32,height=32))
lb.addObject(Enemy.EnemySprite(x=240, y=166,width=20,height=20,angle='0',restitution=0.2,static='false',friction=0.5,density=5 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=240, y=185,width=17,height=17,angle='0',restitution=0.2,static='false',friction=0.5,density=5 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=240, y=201,width=15,height=15,angle='0',restitution=0.2,static='false',friction=0.5,density=5 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=240, y=215,width=12,height=12,angle='0',restitution=0.2,static='false',friction=0.5,density=5 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=240, y=226,width=11,height=11,angle='0',restitution=0.2,static='false',friction=0.5,density=5 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=240, y=236,width=8,height=8,angle='0',restitution=0.2,static='false',friction=0.5,density=5 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=240, y=244,width=7,height=7,angle='0',restitution=0.2,static='false',friction=0.5,density=5 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=133, y=17,width=32,height=32,angle='0',restitution=0.2,static='true',friction=0.5,density=20 ).setName('Enemy'))
lb.addObject(Enemy.EnemySprite(x=347, y=17,width=32,height=32,angle='0',restitution=0.2,static='true',friction=0.5,density=20 ).setName('Enemy'))
lb.addObject(Hero.HeroSprite(x=27, y=16,width=32,height=32))
lb.render()
| 3,038
| 3,038
| 0.741935
| 534
| 3,038
| 4.220974
| 0.14794
| 0.102484
| 0.109583
| 0.16016
| 0.852263
| 0.822538
| 0.822538
| 0.800799
| 0.7937
| 0.762644
| 0
| 0.112509
| 0.0316
| 3,038
| 1
| 3,038
| 3,038
| 0.653637
| 0
| 0
| 0
| 0
| 0
| 0.069102
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.038462
| false
| 0
| 0.076923
| 0
| 0.115385
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 10
|
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