How to use test_warnings method in green
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test_ma_scoring.py
Source:test_ma_scoring.py 
1import unittest2import sys3sys.path.append("..")4from main.express_score import (5 Scorer,6 MaScorer,7 Defaults8)9from main.schema import (10 JSONField,11 ScoreComponents12)13import pandas as pd14import numpy as np15from dateutil.parser import parse16import json17import os18from collections import Counter19EXPRESS_SCORE_HOME = os.path.abspath("..")20RESOURCE_PATH = os.path.join(EXPRESS_SCORE_HOME, "resources")21TEST_RESOURCE_PATH = os.path.join(RESOURCE_PATH, "test")22LB_MA_TEST_PATH = os.path.join(TEST_RESOURCE_PATH, "lb_ma_may_2018")23SA_MA_TEST_PATH = os.path.join(TEST_RESOURCE_PATH, "sa_ma_may_2018")24EG_MA_TEST_PATH = os.path.join(TEST_RESOURCE_PATH, "eg_ma_may_2018")25IQ_MA_TEST_PATH = os.path.join(TEST_RESOURCE_PATH, "iq_ma_may_2018")26SY_MA_TEST_PATH = os.path.join(TEST_RESOURCE_PATH, "sy_ma_may_2018")27LB_PER1_TEST_PATH = os.path.join(TEST_RESOURCE_PATH, "lb_ma_period1")28class ScorerTest(unittest.TestCase):29 def test_slope_score(self):30 min_value = 031 max_value = 10032 too_low = -533 too_high = 10534 just_right = 5035 result = Scorer.slope_score(too_low, min_value, max_value)36 self.assertAlmostEqual(result, 1)37 result = Scorer.slope_score(min_value, min_value, max_value)38 self.assertAlmostEqual(result, 1)39 result = Scorer.slope_score(just_right, min_value, max_value)40 self.assertAlmostEqual(result, 0.5)41 result = Scorer.slope_score(max_value, min_value, max_value)42 self.assertAlmostEqual(result, 0)43 result = Scorer.slope_score(too_high, min_value, max_value)44 self.assertAlmostEqual(result, 0)45 self.assertRaises(ValueError, Scorer.slope_score, just_right, min_value, min_value)46 self.assertRaises(ValueError, Scorer.slope_score, just_right, max_value, min_value)47 def test_f1(self):48 """49 Tests Scorer.f150 :return:51 """52 p, r = (0,0)53 expected = 054 result = Scorer.f1(p,r)55 self.assertAlmostEqual(result, expected, 3)56 p, r = (1,1)57 expected = 158 result = Scorer.f1(p, r)59 self.assertAlmostEqual(result, expected, 3)60 p, r = (1,1)61 expected = 162 result = Scorer.f1(p, r)63 self.assertAlmostEqual(result, expected, 3)64 p, r = (.5,.5)65 expected = .566 result = Scorer.f1(p, r)67 self.assertAlmostEqual(result, expected, 3)68 p, r = (0,1)69 expected = 070 result = Scorer.f1(p, r)71 self.assertAlmostEqual(result, expected, 3)72 p, r = (.25,.75)73 expected = 0.37574 result = Scorer.f1(p, r)75 self.assertAlmostEqual(result, expected, 3)76 p, r = (-.5, 1)77 self.assertRaises(ValueError, Scorer.f1, p, r)78 p, r = (2,1)79 self.assertRaises(ValueError, Scorer.f1, p, r)80 p, r = (.5, -.1)81 self.assertRaises(ValueError, Scorer.f1, p, r)82 p, r = (.5,2)83 self.assertRaises(ValueError, Scorer.f1, p, r)84 def test_date_diff(self):85 # Test when both are 086 warn_date = "2018-06-22"87 gsr_date_range = pd.date_range("2018-06-17", "2018-06-27")88 gsr_dates = [d.strftime("%Y-%m-%d") for d in gsr_date_range]89 expected_values = range(-5, 6)90 for i, d in enumerate(gsr_dates):91 result = Scorer.date_diff(warn_date, d)92 expected = expected_values[i]93 self.assertAlmostEqual(result, expected)94 def test_date_score(self):95 date_diffs = range(-6, 7)96 results = [Scorer.date_score(dd) for dd in date_diffs]97 expected = [0, 0, 0, .25, .5, .75, 1, .75, .5, .25, 0, 0, 0]98 for i, e in enumerate(expected):99 self.assertAlmostEqual(results[i], e, 3)100 max_date_diff = 5101 results = [Scorer.date_score(dd, max_date_diff) for dd in date_diffs]102 expected = [0, 0, .2, .4, .6, .8, 1, .8, .6, .4, .2, 0, 0]103 for i, e in enumerate(expected):104 self.assertAlmostEqual(results[i], e, 3)105 def test_make_index_mats(self):106 """107 Tests Scorer.make_index_mats method108 :return:109 """110 row_names = ["a", "b", "c", "d"]111 row_indices = list(range(len(row_names)))112 col_names = ["x", "y", "z"]113 col_indices = list(range(len(col_names)))114 row_array = np.array(row_indices*3).reshape(3,4).T115 col_array = np.array(col_indices*4).reshape(4,3)116 results = Scorer.make_index_mats(row_names, col_names)117 try:118 np.testing.assert_equal(row_array, results[0])119 test_res = True120 except AssertionError as e:121 test_res = False122 print(repr(e))123 self.assertTrue(test_res)124 try:125 np.testing.assert_equal(col_array, results[1])126 test_res = True127 except AssertionError as e:128 test_res = False129 print(repr(e))130 self.assertTrue(test_res)131 def test_make_combination_mats(self):132 """133 Tests Scorer.make_combination_mats method134 :return:135 """136 row_names = ["a", "b", "c", "d"]137 col_names = ["x", "y", "z"]138 row_array = np.array(row_names*3).reshape(3,4).T139 col_array = np.array(col_names*4).reshape(4,3)140 results = Scorer.make_combination_mats(row_names, col_names)141 try:142 np.testing.assert_equal(row_array, results[0])143 test_res = True144 except AssertionError as e:145 test_res = False146 print(repr(e))147 self.assertTrue(test_res)148 try:149 np.testing.assert_equal(col_array, results[1])150 test_res = True151 except AssertionError as e:152 test_res = False153 print(repr(e))154 self.assertTrue(test_res)155class MaScorerTest(unittest.TestCase):156 country = "Egypt"157 scorer = MaScorer(country=country)158 warn_dict = dict()159 warn_dict[JSONField.WARNING_ID] = "test_1"160 warn_dict[JSONField.EVENT_TYPE] = "Military Action"161 warn_dict[JSONField.COUNTRY] = country162 warn_dict[JSONField.EVENT_DATE] = "2018-05-27"163 warn_dict[JSONField.TIMESTAMP] = "20160324T00:01:01"164 gsr_dict = dict()165 gsr_dict[JSONField.EVENT_TYPE] = "Disease"166 gsr_dict[JSONField.EVENT_ID] = "Disease_Saudi_Arabia_MERS_2016-03-27"167 gsr_dict[JSONField.DISEASE] = "MERS"168 gsr_dict[JSONField.COUNTRY] = "Saudi Arabia"169 gsr_dict[JSONField.EVENT_DATE] = "2016-03-27"170 gsr_dict[JSONField.EARLIEST_REPORTED_DATE] = "2016-04-01"171 result_dict = dict()172 result_dict[JSONField.WARNING_ID] = "test_1"173 result_dict[JSONField.EVENT_ID] = "Disease_Saudi_Arabia_MERS_2016-03-27"174 def test_ls(self):175 result = MaScorer.location_score(0, is_approximate=False)176 expected = 1.0177 self.assertAlmostEqual(result, expected)178 result = MaScorer.location_score(0, is_approximate="False")179 expected = 1.0180 self.assertAlmostEqual(result, expected)181 # 22 km distance182 result = MaScorer.location_score(22)183 expected = 0.78184 self.assertAlmostEqual(result, expected, 2)185 result = MaScorer.location_score(22.17, is_approximate=True)186 expected = 0.934187 self.assertAlmostEqual(result, expected, 3)188 result = MaScorer.location_score(22.1, max_dist=44.2)189 expected = 0.50190 self.assertAlmostEqual(result, expected, 2)191 result = MaScorer.location_score(150)192 expected = 0.0193 self.assertAlmostEqual(result, expected)194 def test_make_dist_mat(self):195 """196 Tests MaScorer.make_dist_mat197 :return:198 """199 test_warn_filename = "ma_test_warnings.json"200 test_warn_path = os.path.join(TEST_RESOURCE_PATH, test_warn_filename)201 with open(test_warn_path, "r", encoding="utf8") as f:202 test_warnings = json.load(f)203 test_gsr_filename = "ma_test_gsr.json"204 test_gsr_path = os.path.join(TEST_RESOURCE_PATH, test_gsr_filename)205 with open(test_gsr_path, "r", encoding="utf8") as f:206 test_gsr = json.load(f)207 result = MaScorer.make_dist_mat(test_warnings, test_gsr)208 expected = np.array([156.672, 156.672, 22.173, 22.173]).reshape(4,1)209 try:210 np.testing.assert_allclose(result, expected, 3)211 test_res = True212 except AssertionError as e:213 test_res = False214 print(repr(e))215 self.assertTrue(test_res)216 test_gsr.append(test_warnings[-1])217 expected = np.array([156.672, 145.956, 156.672, 145.956, 22.173, 0, 22.173, 0]).reshape(4,2)218 result = MaScorer.make_dist_mat(test_warnings, test_gsr)219 try:220 np.testing.assert_allclose(result, expected, 3)221 test_res = True222 except AssertionError as e:223 test_res = False224 print(repr(e))225 self.assertTrue(test_res)226 test_warn_filename = "test_lb_warnings.json"227 test_warn_path = os.path.join(LB_MA_TEST_PATH, test_warn_filename)228 with open(test_warn_path, "r", encoding="utf8") as f:229 test_warnings = json.load(f)230 test_gsr_filename = "test_lb_gsr.json"231 test_gsr_path = os.path.join(LB_MA_TEST_PATH, test_gsr_filename)232 with open(test_gsr_path, "r", encoding="utf8") as f:233 test_gsr = json.load(f)234 dist_mat_filename = "test_lb_dist_matrix.csv"235 dist_mat_path = os.path.join(LB_MA_TEST_PATH, dist_mat_filename)236 expected = np.genfromtxt(dist_mat_path, delimiter=",", skip_header=True)[:, 1:]237 result = MaScorer.make_dist_mat(test_warnings, test_gsr)238 try:239 np.testing.assert_allclose(result, expected, 3)240 test_res = True241 except AssertionError as e:242 test_res = False243 print(repr(e))244 self.assertTrue(test_res)245 def test_make_ls_mat(self):246 """247 Tests MaScorer.make_ls_mat248 :return:249 """250 test_warn_filename = "ma_test_warnings.json"251 test_warn_path = os.path.join(TEST_RESOURCE_PATH, test_warn_filename)252 with open(test_warn_path, "r", encoding="utf8") as f:253 test_warnings = json.load(f)254 test_gsr_filename = "ma_test_gsr.json"255 test_gsr_path = os.path.join(TEST_RESOURCE_PATH, test_gsr_filename)256 with open(test_gsr_path, "r", encoding="utf8") as f:257 test_gsr = json.load(f)258 expected = np.array([0, 0, 0.778, 0.778]).reshape(4,1)259 result = MaScorer.make_ls_mat(test_warnings, test_gsr)260 try:261 np.testing.assert_allclose(result, expected, 3)262 test_res = True263 except AssertionError as e:264 test_res = False265 print(repr(e))266 self.assertTrue(test_res)267 test_gsr.append(test_warnings[-1])268 test_gsr[-1]["Approximate_Location"] = "False"269 expected = np.array([0, 0, 0, 0, 0.778, 1, 0.778, 1]).reshape(4,2)270 result = MaScorer.make_ls_mat(test_warnings, test_gsr)271 try:272 np.testing.assert_allclose(result, expected, 3)273 test_res = True274 except AssertionError as e:275 test_res = False276 print(repr(e))277 self.assertTrue(test_res)278 test_warn_filename = "test_lb_warnings.json"279 test_warn_path = os.path.join(LB_MA_TEST_PATH, test_warn_filename)280 with open(test_warn_path, "r", encoding="utf8") as f:281 test_warnings = json.load(f)282 test_gsr_filename = "test_lb_gsr.json"283 test_gsr_path = os.path.join(LB_MA_TEST_PATH, test_gsr_filename)284 with open(test_gsr_path, "r", encoding="utf8") as f:285 test_gsr = json.load(f)286 ls_mat_filename = "test_ls_matrix.csv"287 ls_mat_path = os.path.join(LB_MA_TEST_PATH, ls_mat_filename)288 expected = np.genfromtxt(ls_mat_path, delimiter=",", skip_header=True)[:, 1:]289 result = MaScorer.make_ls_mat(test_warnings, test_gsr)290 try:291 np.testing.assert_allclose(result, expected, 3)292 test_res = True293 except AssertionError as e:294 test_res = False295 print(repr(e))296 self.assertTrue(test_res)297 def test_make_ds_mat(self):298 """299 Tests MaScorer.make_ds_mat300 :return:301 """302 test_warn_filename = "ma_test_warnings.json"303 test_warn_path = os.path.join(TEST_RESOURCE_PATH, test_warn_filename)304 with open(test_warn_path, "r", encoding="utf8") as f:305 test_warnings = json.load(f)306 test_gsr_filename = "ma_test_gsr.json"307 test_gsr_path = os.path.join(TEST_RESOURCE_PATH, test_gsr_filename)308 with open(test_gsr_path, "r", encoding="utf8") as f:309 test_gsr = json.load(f)310 expected = np.array([0, .75, 0, .75]).reshape(4,1)311 result = MaScorer.make_ds_mat(test_warnings, test_gsr)312 try:313 np.testing.assert_allclose(result, expected, 3)314 test_res = True315 except AssertionError as e:316 test_res = False317 print(repr(e))318 self.assertTrue(test_res)319 test_warn_filename = "test_lb_warnings.json"320 test_warn_path = os.path.join(LB_MA_TEST_PATH, test_warn_filename)321 with open(test_warn_path, "r", encoding="utf8") as f:322 test_warnings = json.load(f)323 test_gsr_filename = "test_lb_gsr.json"324 test_gsr_path = os.path.join(LB_MA_TEST_PATH, test_gsr_filename)325 with open(test_gsr_path, "r", encoding="utf8") as f:326 test_gsr = json.load(f)327 ds_mat_filename = "test_ds_matrix.csv"328 ds_mat_path = os.path.join(LB_MA_TEST_PATH, ds_mat_filename)329 expected = np.genfromtxt(ds_mat_path, delimiter=",", skip_header=True)[:, 1:]330 result = MaScorer.make_ds_mat(test_warnings, test_gsr)331 try:332 np.testing.assert_allclose(result, expected, 3)333 test_res = True334 except AssertionError as e:335 test_res = False336 print(repr(e))337 self.assertTrue(test_res)338 def test_make_ess_mat(self):339 """340 Tests MaScorer.make_ess_mat341 :return:342 """343 test_warn_filename = "test_lb_warnings.json"344 test_warn_path = os.path.join(LB_MA_TEST_PATH, test_warn_filename)345 with open(test_warn_path, "r", encoding="utf8") as f:346 test_warnings = json.load(f)347 test_gsr_filename = "test_lb_gsr.json"348 test_gsr_path = os.path.join(LB_MA_TEST_PATH, test_gsr_filename)349 with open(test_gsr_path, "r", encoding="utf8") as f:350 test_gsr = json.load(f)351 ess_mat_filename = "test_es_match_matrix.csv"352 ess_mat_path = os.path.join(LB_MA_TEST_PATH, ess_mat_filename)353 expected = np.genfromtxt(ess_mat_path, delimiter=",", skip_header=True)[:, 1:]354 result = MaScorer.make_ess_mat(test_warnings, test_gsr)355 try:356 np.testing.assert_allclose(result, expected, 3)357 test_res = True358 except AssertionError as e:359 test_res = False360 print(repr(e))361 self.assertTrue(test_res)362 def test_make_as_mat(self):363 """364 Tests MaScorer.make_as_mat365 :return:366 """367 test_warn_filename = "test_lb_warnings.json"368 test_warn_path = os.path.join(LB_MA_TEST_PATH, test_warn_filename)369 with open(test_warn_path, "r", encoding="utf8") as f:370 test_warnings = json.load(f)371 test_gsr_filename = "test_lb_gsr.json"372 test_gsr_path = os.path.join(LB_MA_TEST_PATH, test_gsr_filename)373 with open(test_gsr_path, "r", encoding="utf8") as f:374 test_gsr = json.load(f)375 acs_mat_filename = "test_actor_match_matrix.csv"376 acs_mat_path = os.path.join(LB_MA_TEST_PATH, acs_mat_filename)377 expected = np.genfromtxt(acs_mat_path, delimiter=",", skip_header=True)[:, 1:]378 result = MaScorer.make_as_mat(test_warnings, test_gsr)379 try:380 np.testing.assert_allclose(result, expected, 3)381 test_res = True382 except AssertionError as e:383 test_res = False384 print(repr(e))385 self.assertTrue(test_res)386 def test_make_qs_mat(self):387 """388 Tests MaScorer.make_qs_df389 :return:390 """391 test_warn_filename = "test_lb_warnings.json"392 test_warn_path = os.path.join(LB_MA_TEST_PATH, test_warn_filename)393 with open(test_warn_path, "r", encoding="utf8") as f:394 test_warnings = json.load(f)395 test_gsr_filename = "test_lb_gsr.json"396 test_gsr_path = os.path.join(LB_MA_TEST_PATH, test_gsr_filename)397 with open(test_gsr_path, "r", encoding="utf8") as f:398 test_gsr = json.load(f)399 mat_filename = "test_qs_mat.csv"400 mat_path = os.path.join(LB_MA_TEST_PATH, mat_filename)401 expected = pd.read_csv(mat_path, index_col=0)402 result = MaScorer.make_qs_df(test_warnings, test_gsr)403 try:404 np.testing.assert_allclose(result, expected, 3)405 test_res = True406 except AssertionError as e:407 test_res = False408 print(repr(e))409 self.assertTrue(test_res)410 test_warn_filename = "test_cc_warnings.json"411 test_warn_path = os.path.join(EG_MA_TEST_PATH, test_warn_filename)412 with open(test_warn_path, "r", encoding="utf8") as f:413 test_warnings = json.load(f)414 test_gsr_filename = "test_cc_gsr.json"415 test_gsr_path = os.path.join(EG_MA_TEST_PATH, test_gsr_filename)416 with open(test_gsr_path, "r", encoding="utf8") as f:417 test_gsr = json.load(f)418 mat_filename = "test_qs_mat.csv"419 mat_path = os.path.join(EG_MA_TEST_PATH, mat_filename)420 expected = np.genfromtxt(mat_path, delimiter=",", skip_header=True)[:, 1:]421 result = MaScorer.make_qs_df(test_warnings, test_gsr)422 try:423 np.testing.assert_allclose(result, expected, 3)424 test_res = True425 except AssertionError as e:426 test_res = False427 print(repr(e))428 self.assertTrue(test_res)429 test_warn_filename = "test_cc_warnings.json"430 test_warn_path = os.path.join(SA_MA_TEST_PATH, test_warn_filename)431 with open(test_warn_path, "r", encoding="utf8") as f:432 test_warnings = json.load(f)433 test_gsr_filename = "test_cc_gsr.json"434 test_gsr_path = os.path.join(SA_MA_TEST_PATH, test_gsr_filename)435 with open(test_gsr_path, "r", encoding="utf8") as f:436 test_gsr = json.load(f)437 mat_filename = "test_qs_mat.csv"438 mat_path = os.path.join(SA_MA_TEST_PATH, mat_filename)439 expected = np.genfromtxt(mat_path, delimiter=",", skip_header=True)[:, 1:]440 result = MaScorer.make_qs_df(test_warnings, test_gsr)441 try:442 np.testing.assert_allclose(result, expected, 3)443 test_res = True444 except AssertionError as e:445 test_res = False446 print(repr(e))447 self.assertTrue(test_res)448 test_warn_filename = "test_cc_warnings.json"449 test_warn_path = os.path.join(IQ_MA_TEST_PATH, test_warn_filename)450 with open(test_warn_path, "r", encoding="utf8") as f:451 test_warnings = json.load(f)452 test_gsr_filename = "test_cc_gsr.json"453 test_gsr_path = os.path.join(IQ_MA_TEST_PATH, test_gsr_filename)454 with open(test_gsr_path, "r", encoding="utf8") as f:455 test_gsr = json.load(f)456 mat_filename = "test_qs_mat.csv"457 mat_path = os.path.join(IQ_MA_TEST_PATH, mat_filename)458 expected = np.genfromtxt(mat_path, delimiter=",", skip_header=True)[:, 1:]459 result = MaScorer.make_qs_df(test_warnings, test_gsr)460 try:461 np.testing.assert_allclose(result, expected, 3)462 test_res = True463 except AssertionError as e:464 test_res = False465 print(repr(e))466 self.assertTrue(test_res)467 def test_facet_score(self):468 """469 Tests Scorer.facet_score470 :return:471 """472 wildcards = ["Unspecified", "Wildcard"]473 warn_value = "Fred"474 gsr_value = "Ethel"475 expected = 0476 result = Scorer.facet_score(warn_value, gsr_value, wildcards)477 self.assertEqual(result, expected)478 gsr_value = wildcards[0]479 expected = 1480 result = Scorer.facet_score(warn_value, gsr_value, wildcards)481 self.assertEqual(result, expected)482 gsr_value = wildcards[1]483 expected = 1484 result = Scorer.facet_score(warn_value, gsr_value, wildcards)485 self.assertEqual(result, expected)486 warn_value = wildcards[0]487 gsr_value = "Ethel"488 expected = 0489 result = Scorer.facet_score(warn_value, gsr_value, wildcards)490 self.assertEqual(result, expected)491 warn_value = "Fred"492 gsr_value = ["Ethel", "Fred"]493 expected = 1494 result = Scorer.facet_score(warn_value, gsr_value, wildcards)495 self.assertEqual(result, expected)496 gsr_value = "Ethel;Fred"497 expected = 1498 result = Scorer.facet_score(warn_value, gsr_value, wildcards)499 self.assertEqual(result, expected)500 gsr_value = "Ethel,Fred"501 expected = 1502 result = Scorer.facet_score(warn_value, gsr_value, wildcards, gsr_value_delim=",")503 self.assertEqual(result, expected)504 def test_actor_score(self):505 """506 Test MaScorer.actor_score507 :return:508 """509 wildcards = ["Unspecified", "Wildcard"]510 legits = ["Fred", "Ethel"]511 warn_value = "Fred"512 gsr_value = "Ethel"513 expected = 0514 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards)515 self.assertEqual(result, expected)516 gsr_value = wildcards[0]517 expected = 1518 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards)519 self.assertEqual(result, expected)520 gsr_value = wildcards[1]521 expected = 1522 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards)523 self.assertEqual(result, expected)524 warn_value = wildcards[0]525 gsr_value = "Ethel"526 expected = 0527 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards)528 self.assertEqual(result, expected)529 warn_value = "Fred"530 gsr_value = ["Ethel", "Fred"]531 expected = 1532 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards)533 self.assertEqual(result, expected)534 warn_value = "Fred"535 gsr_value = "Ethel;Fred"536 expected = 1537 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards)538 self.assertEqual(result, expected)539 warn_value = "Fred"540 gsr_value = "Ethel,Fred"541 expected = 1542 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards, gsr_value_delim=",")543 self.assertEqual(result, expected)544 warn_value = "Lucy"545 gsr_value = ["Ethel", "Fred"]546 expected = 0547 result = MaScorer.actor_score(warn_value, gsr_value, legits, wildcards)548 self.assertEqual(result, expected)549 def test_subtype_score(self):550 """551 Test MaScorer.event_subtype_score552 :return:553 """554 warn_value = "Force Posture"555 gsr_value = "Conflict"556 expected = 0557 result = MaScorer.event_subtype_score(warn_value, gsr_value)558 self.assertEqual(result, expected)559 gsr_value = "Force Posture"560 expected = 1561 result = MaScorer.event_subtype_score(warn_value, gsr_value)562 self.assertEqual(result, expected)563 warn_value = "Sharpening Swords"564 expected = 0565 result = MaScorer.event_subtype_score(warn_value, gsr_value)566 self.assertEqual(result, expected)567 def test_score(self):568 """569 Tests MaScorer.score method570 :return:571 """572 test_warn_filename = "test_lb_warnings.json"573 test_warn_path = os.path.join(LB_MA_TEST_PATH, test_warn_filename)574 with open(test_warn_path, "r", encoding="utf8") as f:575 test_warnings = json.load(f)576 test_gsr_filename = "test_lb_gsr.json"577 test_gsr_path = os.path.join(LB_MA_TEST_PATH, test_gsr_filename)578 with open(test_gsr_path, "r", encoding="utf8") as f:579 test_gsr = json.load(f)580 result = MaScorer.score(test_warnings, test_gsr)581 expected_filename = "match_results.json"582 path_ = os.path.join(LB_MA_TEST_PATH, expected_filename)583 with open(path_, "r", encoding="utf8") as f:584 expected = json.load(f)585 expected_matches = sorted(set([(m["Warning"], m["Event"]) for m in expected["Matches"]]))586 expected_qs_ser = expected["Details"]["Quality Scores"]587 expected_qs_mean = expected["Quality Score"]588 expected_precision = expected["Precision"]589 expected_recall = expected["Recall"]590 expected_f1 = expected["F1"]591 expected_merc_score = expected["Mercury Score"]592 self.assertEqual(sorted(set(result["Matches"])), expected_matches)593 self.assertAlmostEqual(result["Quality Score"], expected_qs_mean, 3)594 self.assertAlmostEqual(result["Mercury Score"], expected_merc_score, 3)595 self.assertAlmostEqual(result["Precision"], expected_precision, 3)596 self.assertAlmostEqual(result["Recall"], expected_recall, 3)597 self.assertAlmostEqual(result["F1"], expected_f1, 3)598 for i, qs in enumerate(expected_qs_ser):599 res_qs = result["Details"]["Quality Scores"][i]600 self.assertAlmostEqual(res_qs, qs, 3)601 def test_match(self):602 """603 Tests MaScorer.match604 :return:605 """606 # Simple Matrix, 3 by 4607 test_matrix_filename = "test_qs_matrix_1.csv"608 path_ = os.path.join(TEST_RESOURCE_PATH, test_matrix_filename)609 test_mat = pd.read_csv(path_, index_col=0)610 expected_matches = [("warn_0", "evt_0"), ("warn_1", "evt_1"), ("warn_2", "evt_3")]611 expected_qs_ser = [1, 0.85, 0.8]612 expected_qs_mean = np.mean(expected_qs_ser)613 result = MaScorer.match(input_matrix=test_mat)614 self.assertEqual(result["Matches"], expected_matches)615 self.assertAlmostEqual(result["Quality Score"], expected_qs_mean, 3)616 self.assertAlmostEqual(result["Precision"], 1.0)617 self.assertAlmostEqual(result["Recall"], 0.75)618 self.assertAlmostEqual(result["F1"], 1.5/1.75)619 self.assertAlmostEqual(result["Mercury Score"], (expected_qs_mean + 1.5/1.75)/2.)620 self.assertAlmostEqual(result["Details"]["Quality Scores"], expected_qs_ser, 3)621 # Simple matrix, 4 by 3622 test_matrix_filename = "test_qs_matrix_2.csv"623 path_ = os.path.join(TEST_RESOURCE_PATH, test_matrix_filename)624 test_mat = pd.read_csv(path_, index_col=0)625 expected_matches = [("warn_0", "evt_0"), ("warn_1", "evt_1"), ("warn_3", "evt_2")]626 expected_qs_ser = [1, 0.85, 0.75]627 expected_qs_mean = np.mean(expected_qs_ser)628 result = MaScorer.match(input_matrix=test_mat)629 self.assertEqual(result["Matches"], expected_matches)630 self.assertAlmostEqual(result["Quality Score"], expected_qs_mean, 3)631 self.assertAlmostEqual(result["Precision"], 0.75)632 self.assertAlmostEqual(result["Recall"], 1.00)633 self.assertAlmostEqual(result["F1"], 1.5/1.75)634 self.assertAlmostEqual(result["Mercury Score"], (expected_qs_mean + 1.5/1.75)/2.)635 self.assertAlmostEqual(result["Details"]["Quality Scores"], expected_qs_ser, 3)636 # Null Matrix637 test_matrix_filename = "test_null_matrix.csv"638 path_ = os.path.join(TEST_RESOURCE_PATH, test_matrix_filename)639 test_mat = pd.read_csv(path_, index_col=0)640 expected_matches = []641 expected_qs_ser = []642 expected_qs_mean = 0643 result = MaScorer.match(input_matrix=test_mat)644 self.assertEqual(result["Matches"], expected_matches)645 self.assertAlmostEqual(result["Quality Score"], expected_qs_mean, 3)646 self.assertAlmostEqual(result["Precision"], 0)647 self.assertAlmostEqual(result["Recall"], 0)648 self.assertAlmostEqual(result["F1"], 0)649 self.assertAlmostEqual(result["Mercury Score"], 0)650 self.assertAlmostEqual(result["Details"]["Quality Scores"], expected_qs_ser, 3)651 # Matrix with negative entries652 test_matrix_filename = "test_neg_matrix.csv"653 path_ = os.path.join(TEST_RESOURCE_PATH, test_matrix_filename)654 test_mat = pd.read_csv(path_, index_col=0)655 expected_matches = [("warn_0", "evt_0"), ("warn_2", "evt_2")]656 expected_qs_ser = [0.75, 1.0]657 expected_qs_mean = 0.875658 result = MaScorer.match(input_matrix=test_mat)659 self.assertEqual(result["Matches"], expected_matches)660 self.assertAlmostEqual(result["Quality Score"], expected_qs_mean, 3)661 self.assertAlmostEqual(result["Precision"], 0.5)662 self.assertAlmostEqual(result["Recall"], 0.667, 3)663 self.assertAlmostEqual(result["F1"], 0.667/1.167, 3)664 self.assertAlmostEqual(result["Mercury Score"], (expected_qs_mean + 0.667/1.167)/2, 3)665 self.assertAlmostEqual(result["Details"]["Quality Scores"], expected_qs_ser, 3)666 # Matrix with Lebanon data667 test_matrix_filename = "test_qs_mat.csv"668 path_ = os.path.join(LB_MA_TEST_PATH, test_matrix_filename)669 test_mat = pd.read_csv(path_, index_col=0)670 expected_filename = "match_results.json"671 path_ = os.path.join(LB_MA_TEST_PATH, expected_filename)672 with open(path_, "r", encoding="utf8") as f:673 expected = json.load(f)674 expected_matches = sorted(set([(m["Warning"], m["Event"]) for m in expected["Matches"]]))675 expected_qs_ser = expected["Details"]["Quality Scores"]676 expected_qs_mean = expected["Quality Score"]677 expected_precision = expected["Precision"]678 expected_recall = expected["Recall"]679 expected_f1 = expected["F1"]680 result = MaScorer.match(input_matrix=test_mat)681 self.assertEqual(sorted(set(result["Matches"])), expected_matches)682 self.assertAlmostEqual(result["Quality Score"], expected_qs_mean, 3)683 self.assertAlmostEqual(result["Precision"], expected_precision, 3)684 self.assertAlmostEqual(result["Recall"], expected_recall, 3)685 self.assertAlmostEqual(result["F1"], expected_f1, 3)686 self.assertAlmostEqual(result["Mercury Score"], (expected["Quality Score"] + expected["F1"])/2, 3)687 for i, qs in enumerate(expected_qs_ser):688 res_qs = result["Details"]["Quality Scores"][i]689 self.assertAlmostEqual(res_qs, qs, 3)690 def test_score_one(self):691 """692 Test MaScorer.score_one weights input693 :return:694 """695 test_warn_filename = "ma_test_warnings.json"696 test_warn_path = os.path.join(TEST_RESOURCE_PATH, test_warn_filename)697 with open(test_warn_path, "r", encoding="utf8") as f:698 test_warnings= json.load(f)699 test_gsr_filename = "ma_test_gsr.json"700 test_gsr_path = os.path.join(TEST_RESOURCE_PATH, test_gsr_filename)701 with open(test_gsr_path, "r", encoding="utf8") as f:702 test_gsr = json.load(f)703 #print(test_gsr[0])704 LEGIT_ACTORS = ["Egyptian Police"]705 bad_weight = -1706 sub_weight = .5707 super_weight = 2708 # Test with default weights709 # Test with bad weights710 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,711 ls_weight=bad_weight)712 self.assertTrue("Errors" in result)713 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,714 ds_weight=bad_weight)715 self.assertTrue("Errors" in result)716 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,717 as_weight=bad_weight)718 self.assertTrue("Errors" in result)719 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,720 ess_weight=bad_weight)721 self.assertTrue("Errors" in result)722 # Test with weights summing to less than 4723 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,724 ls_weight=sub_weight)725 self.assertTrue("Notices" in result)726 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,727 ds_weight=sub_weight)728 self.assertTrue("Notices" in result)729 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,730 as_weight=sub_weight)731 self.assertTrue("Notices" in result)732 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,733 ess_weight=sub_weight)734 self.assertTrue("Notices" in result)735 # Test with weights summing to more than 4736 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,737 ls_weight=super_weight)738 self.assertTrue("Notices" in result)739 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,740 ds_weight=super_weight)741 self.assertTrue("Notices" in result)742 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,743 as_weight=super_weight)744 self.assertTrue("Notices" in result)745 result = MaScorer.score_one(test_warnings[0], test_gsr[0], legit_actors=LEGIT_ACTORS,746 ess_weight=super_weight)747 self.assertTrue("Notices" in result)748 print("Result using default weights")749 result = MaScorer.score_one(test_warnings[3], test_gsr[0])750 print(result)751 # Test a warning with LS = 0752 result = MaScorer.score_one(test_warnings[1], test_gsr[0])753 self.assertEqual(result[ScoreComponents.QS], 0)754 self.assertEqual(result[ScoreComponents.LS], 0)755 self.assertAlmostEqual(result[ScoreComponents.DS], 0.75)756 # Test a warning with DS = 0757 result = MaScorer.score_one(test_warnings[2], test_gsr[0])758 self.assertEqual(result[ScoreComponents.QS], 0)759 self.assertAlmostEqual(result[ScoreComponents.LS], 0.778, 3)760 self.assertEqual(result[ScoreComponents.DS], 0)761 # Test a legitimately matched warning762 result = MaScorer.score_one(test_warnings[3], test_gsr[0], legit_actors=LEGIT_ACTORS)763 self.assertEqual(result[ScoreComponents.AS], 1)764 self.assertEqual(result[ScoreComponents.ESS], 1)765 self.assertAlmostEqual(result[ScoreComponents.LS], 0.778, 3)766 self.assertAlmostEqual(result[ScoreComponents.DS], 0.75)767 self.assertAlmostEqual(result[ScoreComponents.QS], 0.882, 3)768 self.assertFalse("Notices" in result)769 self.assertFalse("Errors" in result)770 def test_duplicate_matches(self):771 """772 Tests if the same GSR event or warning are matched multiply.773 :return:774 """775 # Test using Lebanon for one participant. Known faiure case.776 test_warn_filename = "test_warn.json"777 test_warn_path = os.path.join(LB_PER1_TEST_PATH, test_warn_filename)778 with open(test_warn_path, "r", encoding="utf8") as f:779 test_warnings= json.load(f)780 test_gsr_filename = "test_gsr.json"781 test_gsr_path = os.path.join(LB_PER1_TEST_PATH, test_gsr_filename)782 with open(test_gsr_path, "r", encoding="utf8") as f:783 test_gsr = json.load(f)784 result = MaScorer.score(test_warnings, test_gsr)785 matches = result["Matches"]786 warn_ids = [m[0] for m in matches]787 warn_id_counter = Counter(warn_ids)788 max_warn_usage = warn_id_counter.most_common(1)[0][1]789 self.assertEqual(max_warn_usage, 1)790 gsr_ids = [m[1] for m in matches]791 gsr_id_counter = Counter(gsr_ids)792 max_gsr_usage = gsr_id_counter.most_common(1)[0][1]793 self.assertEqual(max_gsr_usage, 1)794 # Test using Syria, May 2018. This will take a while to run.795 test_warn_filename = "test_cc_warnings.json"796 test_warn_path = os.path.join(SY_MA_TEST_PATH, test_warn_filename)797 with open(test_warn_path, "r", encoding="utf8") as f:798 test_warnings= json.load(f)799 test_gsr_filename = "test_cc_gsr.json"800 test_gsr_path = os.path.join(SY_MA_TEST_PATH, test_gsr_filename)801 with open(test_gsr_path, "r", encoding="utf8") as f:802 test_gsr = json.load(f)803 result = MaScorer.score(test_warnings, test_gsr)804 matches = result["Matches"]805 warn_ids = [m[0] for m in matches]806 warn_id_counter = Counter(warn_ids)807 max_warn_usage = warn_id_counter.most_common(1)[0][1]808 self.assertEqual(max_warn_usage, 1)809 gsr_ids = [m[1] for m in matches]810 gsr_id_counter = Counter(gsr_ids)811 max_gsr_usage = gsr_id_counter.most_common(1)[0][1]812 self.assertEqual(max_gsr_usage, 1)813if __name__ == "__main__":...
test_warnings.py
Source:test_warnings.py
1# Copyright The PyTorch Lightning team.2#3# Licensed under the Apache License, Version 2.0 (the "License");4# you may not use this file except in compliance with the License.5# You may obtain a copy of the License at6#7# http://www.apache.org/licenses/LICENSE-2.08#9# Unless required by applicable law or agreed to in writing, software10# distributed under the License is distributed on an "AS IS" BASIS,11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.12# See the License for the specific language governing permissions and13# limitations under the License.14"""Test that the warnings actually appear and they have the correct `stacklevel`15Needs to be run outside of `pytest` as it captures all the warnings.16"""17import os18from contextlib import redirect_stderr19from io import StringIO20from pytorch_lightning.utilities.rank_zero import _warn, rank_zero_deprecation, rank_zero_warn21from pytorch_lightning.utilities.warnings import WarningCache22standalone = os.getenv("PL_RUN_STANDALONE_TESTS", "0") == "1"23if standalone and __name__ == "__main__":24 stderr = StringIO()25 # recording26 with redirect_stderr(stderr):27 _warn("test1")28 _warn("test2", category=DeprecationWarning)29 rank_zero_warn("test3")30 rank_zero_warn("test4", category=DeprecationWarning)31 rank_zero_deprecation("test5")32 cache = WarningCache()33 cache.warn("test6")34 cache.deprecation("test7")35 output = stderr.getvalue()36 assert "test_warnings.py:31: UserWarning: test1" in output37 assert "test_warnings.py:32: DeprecationWarning: test2" in output38 assert "test_warnings.py:34: UserWarning: test3" in output39 assert "test_warnings.py:35: DeprecationWarning: test4" in output40 assert "test_warnings.py:37: LightningDeprecationWarning: test5" in output41 assert "test_warnings.py:40: UserWarning: test6" in output42 assert "test_warnings.py:41: LightningDeprecationWarning: test7" in output43 # check that logging is properly configured44 import logging45 from pytorch_lightning import _DETAIL46 root_logger = logging.getLogger()47 lightning_logger = logging.getLogger("pytorch_lightning")48 # should have a `StreamHandler`49 assert lightning_logger.hasHandlers() and len(lightning_logger.handlers) == 150 # set our own stream for testing51 handler = lightning_logger.handlers[0]52 assert isinstance(handler, logging.StreamHandler)53 stderr = StringIO()54 # necessary with `propagate = False`55 lightning_logger.handlers[0].stream = stderr56 # necessary with `propagate = True`57 with redirect_stderr(stderr):58 # Lightning should not configure the root `logging` logger by default59 logging.info("test1")60 root_logger.info("test1")61 # but our logger instance62 lightning_logger.info("test2")63 # level is set to INFO64 lightning_logger.debug("test3")65 output = stderr.getvalue()66 assert output == "test2\n", repr(output)67 stderr = StringIO()68 lightning_logger.handlers[0].stream = stderr69 with redirect_stderr(stderr):70 # Lightning should not output DETAIL level logging by default71 lightning_logger.detail("test1")72 lightning_logger.setLevel(_DETAIL)73 lightning_logger.detail("test2")74 # logger should not output anything for DEBUG statements if set to DETAIL75 lightning_logger.debug("test3")76 output = stderr.getvalue()...
Test.py
Source:Test.py
1#2# LUMOS 3# $Header: /tmp/cvsroot/lumos/Test/Test.py,v 1.4 2008-12-31 00:13:32 steve Exp $4#5# Lumos Light Orchestration System6# Copyright (c) 2005, 2006, 2007, 2008 by Steven L. Willoughby, Aloha,7# Oregon, USA. All Rights Reserved. Licensed under the Open Software8# License version 3.0.9#10# This product is provided for educational, experimental or personal11# interest use, in accordance with the terms and conditions of the12# aforementioned license agreement, ON AN "AS IS" BASIS AND WITHOUT13# WARRANTY, EITHER EXPRESS OR IMPLIED, INCLUDING, WITHOUT LIMITATION,14# THE WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY OR FITNESS FOR A15# PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY OF THE ORIGINAL16# WORK IS WITH YOU. (See the license agreement for full details, 17# including disclaimer of warranty and limitation of liability.)18#19# Under no curcumstances is this product intended to be used where the20# safety of any person, animal, or property depends upon, or is at21# risk of any kind from, the correct operation of this software or22# the hardware devices which it controls.23#24# USE THIS PRODUCT AT YOUR OWN RISK.25# 26from unittest import TestSuite, findTestCases27import sys28TEST_WARNINGS={}29class SkipWarning (object):30 def __init__(self, msg):31 self.count=132 self.msg=msg33 def incr(self):34 self.count += 135 def __lt__(self, x):36 return self.count < x.count37def warn_once(tag, message):38 global TEST_WARNINGS39 if not already_warned_about(tag):40 TEST_WARNINGS[tag] = SkipWarning(message)41 sys.stderr.write("WARNING: "+message+"\n")42 sys.stderr.flush()43 else:44 TEST_WARNINGS[tag].incr()45def already_warned_about(tag):46 global TEST_WARNINGS47 return tag in TEST_WARNINGS48def accumulated_warnings():49 global TEST_WARNINGS50 return sorted(TEST_WARNINGS.values())51def reset_accumulated_warnings():52 global TEST_WARNINGS53 for i in TEST_WARNINGS:54 TEST_WARNINGS[i].count = 055def suite():56 modules_to_test = (57 'ChannelTest',58 'ControllersTest',59 'ControllerUnitTest',60 'DeviceTest',61 'DimmerVirtualChannelTest',62# 'EventTest', # DEPRECATED CLASS63 'FirecrackerX10ControllerUnitTest',64 'FireGodControllerUnitTest',65 'LCheckTest',66 'LumosTest',67 'LynX10ControllerUnitTest',68 'NetworkTest',69 'NetworksTest',70 'Olsen595ControllerUnitTest',71 'PowerSourceTest',72 'RenardControllerUnitTest',73 'RGBVirtualChannelTest',74 'ShowTest',75 'SerialNetworkTest', # XXX device tests?76 'ParallelBitNetworkTest', # XXX device tests?77 'SequenceTest',78 'SerialBitNetworkTest', # XXX device tests?79# 'SpectrumReaderboardUnitTest',80 'LumosControllerUnitTest',81 'TestNetworkTest',82 'TestParallelNetworkTest',83 'TimeRangeTest',84 'ValueEventTest',85 'VirtualChannelTest',86 'ToggleVirtualChannelTest',87 'VixenSequenceTest',88 'X10ControllerUnitTest'89 )90 suite = TestSuite()91 for module in map(__import__, modules_to_test):92 suite.addTest(findTestCases(module))93 return suite94# 95# $Log: not supported by cvs2svn $...
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