How to use test_matches method in avocado

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test_rule_reduction.py

Source:test_rule_reduction.py Github

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1import numpy as np2from scipy.sparse import csr_matrix3from knodle.transformation.rule_reduction import _get_merged_matrix, reduce_rule_matches, _get_rule_by_label_iterator4def test_reduction():5 # test rule iterator6 mapping_rule_class_t = np.array([7 [1, 0],8 [0, 1],9 [1, 0],10 [1, 0]])11 rule_iterator = list(_get_rule_by_label_iterator(mapping_rule_class_t))12 expected_iterator = [13 np.array([0, 2, 3]),14 np.array([1])15 ]16 assert len(rule_iterator) == len(expected_iterator)17 assert np.array_equal(rule_iterator[0], expected_iterator[0])18 assert np.array_equal(rule_iterator[1], expected_iterator[1])19 # test _get_merged_matrix20 rule_matches_z = np.array([21 [0, 1, 0, 1],22 [1, 0, 1, 1],23 [0, 0, 1, 0],24 [1, 0, 1, 0],25 [0, 0, 1, 0]])26 to_keep_mask = np.array([1, 2])27 merged_rule_matches_z = _get_merged_matrix(28 full_matches=rule_matches_z, to_keep_mask=to_keep_mask, label_rule_masks=expected_iterator)29 expected_merged = np.array([30 [1],31 [1],32 [0],33 [1],34 [0]])35 assert np.array_equal(merged_rule_matches_z, expected_merged)36 # test end-to-end merge37 test_rule_matches_z = np.array([38 [0, 1, 0, 0],39 [0, 0, 1, 0],40 [1, 0, 0, 0]])41 out = reduce_rule_matches(42 rule_matches_z=rule_matches_z, mapping_rules_labels_t=mapping_rule_class_t,43 rule_matches_rest={"test_matches": test_rule_matches_z},44 drop_rules=False, max_rules=2, min_coverage=1.0)45 expected = {46 "train_rule_matches_z": np.array([47 [1, 1],48 [1, 0],49 [1, 0],50 [1, 0],51 [1, 0]52 ]),53 "test_matches": np.array([54 [0, 1],55 [1, 0],56 [1, 0]57 ]),58 "mapping_rules_labels_t": np.array([59 [1, 0],60 [0, 1]61 ])62 }63 assert np.array_equal(out.get("train_rule_matches_z"), expected["train_rule_matches_z"])64 assert np.array_equal(out.get("test_matches"), expected["test_matches"])65 assert np.array_equal(out.get("mapping_rules_labels_t"), expected["mapping_rules_labels_t"])66 # test end-to-end by drop67 out = reduce_rule_matches(68 rule_matches_z=rule_matches_z, mapping_rules_labels_t=mapping_rule_class_t,69 rule_matches_rest={"test_matches": test_rule_matches_z},70 drop_rules=True, max_rules=2, min_coverage=0.0)71 expected = {72 "train_rule_matches_z": np.array([73 [0, 0],74 [1, 1],75 [0, 1],76 [1, 1],77 [0, 1]78 ]),79 "test_matches": np.array([80 [0, 0],81 [0, 1],82 [1, 0]83 ]),84 "mapping_rules_labels_t": np.array([85 [1, 0],86 [1, 0]87 ])88 }89 assert np.array_equal(out.get("train_rule_matches_z"), expected["train_rule_matches_z"])90 assert np.array_equal(out.get("test_matches"), expected["test_matches"])91 assert np.array_equal(out.get("mapping_rules_labels_t"), expected["mapping_rules_labels_t"])92def test_reduction_for_sparse():93 # test rule iterator94 mapping_rule_class_t = csr_matrix([95 [1, 0],96 [0, 1],97 [1, 0],98 [1, 0]])99 rule_iterator = list(_get_rule_by_label_iterator(mapping_rule_class_t))100 expected_iterator = [101 np.array([0, 2, 3]),102 np.array([1])103 ]104 assert len(rule_iterator) == len(expected_iterator)105 assert np.array_equal(rule_iterator[0], expected_iterator[0])106 assert np.array_equal(rule_iterator[1], expected_iterator[1])107 # test _get_merged_matrix108 rule_matches_z = csr_matrix([109 [0, 1, 0, 1],110 [1, 0, 1, 1],111 [0, 0, 1, 0],112 [1, 0, 1, 0],113 [0, 0, 1, 0]])114 to_keep_mask = np.array([1, 2])115 merged_rule_matches_z = _get_merged_matrix(116 full_matches=rule_matches_z, to_keep_mask=to_keep_mask, label_rule_masks=expected_iterator)117 expected_merged = csr_matrix([118 [1],119 [1],120 [0],121 [1],122 [0]])123 assert (merged_rule_matches_z != expected_merged).nnz == 0124 # test end-to-end merge125 test_rule_matches_z = csr_matrix([126 [0, 1, 0, 0],127 [0, 0, 1, 0],128 [1, 0, 0, 0]])129 out = reduce_rule_matches(130 rule_matches_z=rule_matches_z, mapping_rules_labels_t=mapping_rule_class_t,131 rule_matches_rest={"test_matches": test_rule_matches_z},132 drop_rules=False, max_rules=2, min_coverage=1.0)133 expected = {134 "train_rule_matches_z": csr_matrix([135 [1, 1],136 [1, 0],137 [1, 0],138 [1, 0],139 [1, 0]140 ]),141 "test_matches": csr_matrix([142 [0, 1],143 [1, 0],144 [1, 0]145 ]),146 "mapping_rules_labels_t": csr_matrix([147 [1, 0],148 [0, 1]149 ])150 }151 assert (out.get("train_rule_matches_z") != expected["train_rule_matches_z"]).nnz == 0152 assert (out.get("test_matches") != expected["test_matches"]).nnz == 0153 assert (out.get("mapping_rules_labels_t") != expected["mapping_rules_labels_t"]).nnz == 0154 assert isinstance(out.get("train_rule_matches_z"), csr_matrix)155 assert isinstance(out.get("mapping_rules_labels_t"), csr_matrix)156 # test end-to-end by drop with sparse matches and dense mapping T157 mapping_rule_class_t = np.array([158 [1, 0],159 [0, 1],160 [1, 0],161 [1, 0]])162 out = reduce_rule_matches(163 rule_matches_z=rule_matches_z, mapping_rules_labels_t=mapping_rule_class_t,164 rule_matches_rest={"test_matches": test_rule_matches_z},165 drop_rules=True, max_rules=2, min_coverage=0.0)166 expected = {167 "train_rule_matches_z": csr_matrix([168 [0, 0],169 [1, 1],170 [0, 1],171 [1, 1],172 [0, 1]173 ]),174 "test_matches": csr_matrix([175 [0, 0],176 [0, 1],177 [1, 0]178 ]),179 "mapping_rules_labels_t": np.array([180 [1, 0],181 [1, 0]182 ])183 }184 assert (out.get("train_rule_matches_z") != expected["train_rule_matches_z"]).nnz == 0185 assert (out.get("test_matches") != expected["test_matches"]).nnz == 0186 assert np.array_equal(out.get("mapping_rules_labels_t"), expected["mapping_rules_labels_t"])187 assert isinstance(out.get("train_rule_matches_z"), csr_matrix)...

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test_scoreboard.py

Source:test_scoreboard.py Github

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1from datetime import datetime, date2from hockeynor import scoreboard3TEST_DATA = """{"Matches": [ 4{ "MatchId": 7267686,5 "HomeTeamShortName": " Stavanger Ishockeyklubb ",6 "AwayTeamShortName": "Sparta Elite ",7 "HomeTeamScore": 5,8 "AwayTeamScore": 4,9 "FetchScoreFromRaven": false,10 "StartDate": "/Date(1603382400000)/",11 "FormattedDate": "22.10.2020",12 "FormattedShortDate": "22.10",13 "FormattedStartTime": "18:00"},14{ "MatchId": 7267685,15 "HomeTeamShortName": "Narvik",16 "AwayTeamShortName": "Manglerud Star Elite",17 "HomeTeamScore": 1,18 "AwayTeamScore": 3,19 "FetchScoreFromRaven": false,20 "StartDate": "/Date(1603384200000)/",21 "FormattedDate": "22.10.2020",22 "FormattedShortDate": "22.10",23 "FormattedStartTime": "18:30" },24{25 "MatchId": 7267710,26 "HomeTeamShortName": "Frisk Asker Elite ",27 "AwayTeamShortName": "Manglerud Star Elite",28 "HomeTeamScore": null,29 "AwayTeamScore": null,30 "FetchScoreFromRaven": false,31 "StartDate": "/Date(1605456000000)/",32 "FormattedDate": "15.11.2020",33 "FormattedShortDate": "15.11",34 "FormattedStartTime": "17:00"35 }36]}37"""38TEST_MATCHES = [39 {'away': 'SIL', 'away_score': 3, 'home': 'NH', 'home_score': 0, 'match_id': 7267711,40 'start_date': datetime(2020, 11, 14, 16, 0)},41 {'away': 'Grüner', 'away_score': 1, 'home': 'Stjernen Elite', 'home_score': 7, 'match_id': 7267712,42 'start_date': datetime(2020, 11, 14, 16, 0)},43 {'away': 'Oilers', 'away_score': 6, 'home': 'L.I.K', 'home_score': 1, 'match_id': 7267709,44 'start_date': datetime(2020, 11, 14, 18, 0)},45 {'away': 'M/S', 'away_score': 4, 'home': 'F/A', 'home_score': 5, 'match_id': 7267710,46 'start_date': datetime(2020, 11, 15, 17, 0)},47 {'away': 'L.I.K', 'away_score': 4, 'home': 'NH', 'home_score': 1, 'match_id': 7267855,48 'start_date': datetime(2020, 11, 17, 18, 30)},49 {'away': 'L.I.K', 'away_score': 4, 'home': 'NH', 'home_score': None, 'match_id': 7267856,50 'start_date': datetime(2020, 11, 18, 18, 30)},51 {'away': 'Oilers', 'away_score': None, 'home': 'SIL', 'home_score': None, 'match_id': 7267747,52 'start_date': datetime(2020, 12, 8, 19, 0)}]53def test_filter_date():54 result = scoreboard.filter_datetime(TEST_MATCHES, start=datetime(1977, 4, 29))55 assert isinstance(result, list)56 assert len(result) == 757def test_filter_datetime_for_future():58 future = scoreboard.filter_datetime(TEST_MATCHES, start=datetime(2020, 12, 8))59 assert len(future) == 160 assert future[0] == TEST_MATCHES[-1]61def test_filter_datetime_for_yesterday():62 yesterday = scoreboard.filter_datetime(TEST_MATCHES, start=datetime(2020, 11, 18, 0, 0), end=datetime(2020, 11, 18, 23, 59))63 assert len(yesterday) == 164 assert yesterday[0] == TEST_MATCHES[-2]65def test_filter_datetime_for_yesterday_with_no_time_set():66 yesterday = scoreboard.filter_datetime(TEST_MATCHES,67 start=datetime(2020, 11, 18),68 end=datetime(2020, 11, 18))69 assert len(yesterday) == 170 assert yesterday[0] == TEST_MATCHES[-2]71def test_filter_datetime_day_in_past():72 october14 = scoreboard.filter_datetime(TEST_MATCHES, day=datetime(2020, 11, 14))73 assert len(october14) == 374 assert TEST_MATCHES[0] in october1475 assert TEST_MATCHES[1] in october1476 assert TEST_MATCHES[2] in october1477def test_filter_today():78 matches = [79 {'away': 'SIL', 'away_score': 3, 'home': 'NH', 'home_score': 0, 'match_id': 7267711,80 'start_date': datetime(2020, 11, 14, 16, 0)},81 {'away': 'Grüner', 'away_score': 1, 'home': 'Stjernen Elite', 'home_score': 7, 'match_id': 42,82 'start_date': datetime.now()}]83 result = scoreboard.today(matches)84 assert isinstance(result, list)85 assert len(result) == 186 assert result[0]['match_id'] == 4287def test_filter_past():88 matches = [89 {'away': 'SIL', 'away_score': 3, 'home': 'NH', 'home_score': 0, 'match_id': 1,90 'start_date': datetime(2020, 11, 14, 16, 0)},91 {'away': 'Grüner', 'away_score': 1, 'home': 'Stjernen Elite', 'home_score': 7, 'match_id': 42,92 'start_date': datetime.now()}]93 result = scoreboard.past(matches)94 assert isinstance(result, list)95 assert len(result) == 196 assert result[0]['match_id'] == 197def test_filter_future():98 matches = [99 {'away': 'SIL', 'away_score': 3, 'home': 'NH', 'home_score': 0, 'match_id': 1,100 'start_date': datetime(2099, 11, 14, 16, 0)},101 {'away': 'Grüner', 'away_score': 1, 'home': 'Stjernen Elite', 'home_score': 7, 'match_id': 42,102 'start_date': datetime.now()}]103 result = scoreboard.future(matches)104 assert isinstance(result, list)105 assert len(result) == 1106 assert result[0]['match_id'] == 1107def test_transform():108 result = scoreboard.transform(TEST_DATA)109 assert isinstance(result, list)110 assert len(result) == 3111 assert result[0]['home'] == 'Stavanger Ishockeyklubb'112 assert result[0]['away'] == 'Sparta Elite'113 assert result[0]['home_score'] == 5114 assert result[0]['away_score'] == 4115 assert isinstance(result[0]['start_date'], datetime)116 assert result[1]['start_date'] == datetime(year=2020, month=10, day=22, hour=18, minute=30)117 assert result[2]['match_id'] == 7267710118def test_build_url():...

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test_league.py

Source:test_league.py Github

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1import unittest2import json3from src.app.process_data.league import LEC4from src.app.process_data.match import Match5from src.tests.test_data import matches_one_day, matches_two_days, head_to_head, wins_in_second_half6class TestLeague(unittest.TestCase):7 def test_create_standings_one_day(self):8 test_matches = []9 for match in matches_one_day:10 test_matches.append(Match(match['teams'], match['week'], match['result']))11 lec = LEC.from_matches(test_matches)12 lec.create_standings()13 self.assertIn('XL', lec.standings[1])14 self.assertIn('VIT', lec.standings[1])15 self.assertIn('S04', lec.standings[1])16 self.assertIn('RGE', lec.standings[1])17 self.assertIn('MAD', lec.standings[1])18 self.assertIn('SK', lec.standings[6])19 self.assertIn('OG', lec.standings[6])20 self.assertIn('G2', lec.standings[6])21 self.assertIn('MSF', lec.standings[6])22 self.assertIn('FNC', lec.standings[6])23 def test_create_standings_two_days(self):24 test_matches = []25 for match in matches_two_days:26 test_matches.append(Match(match['teams'], match['week'], match['result']))27 lec = LEC.from_matches(test_matches)28 lec.create_standings()29 self.assertIn('XL', lec.standings[3])30 self.assertIn('VIT', lec.standings[5])31 self.assertIn('S04', lec.standings[7])32 self.assertIn('RGE', lec.standings[1])33 self.assertIn('MAD', lec.standings[1])34 self.assertIn('SK', lec.standings[5])35 self.assertIn('OG', lec.standings[7])36 self.assertIn('G2', lec.standings[9])37 self.assertIn('MSF', lec.standings[9])38 self.assertIn('FNC', lec.standings[3])39 def test_create_standings_season(self):40 matches = Match.from_json('src/tests/lec_test.json')41 lec = LEC.from_matches(matches)42 lec.create_standings()43 self.assertIn('XL', lec.standings[6])44 self.assertIn('VIT', lec.standings[8])45 self.assertIn('S04', lec.standings[10])46 self.assertIn('RGE', lec.standings[2])47 self.assertIn('MAD', lec.standings[1])48 self.assertIn('SK', lec.standings[3])49 self.assertIn('OG', lec.standings[9])50 self.assertIn('G2', lec.standings[4])51 self.assertIn('MSF', lec.standings[7])52 self.assertIn('FNC', lec.standings[5])53 def test_create_table_one_day(self):54 test_matches = []55 for match in matches_one_day:56 test_matches.append(Match(match['teams'], match['week'], match['result']))57 lec = LEC.from_matches(test_matches)58 lec.create_table()59 self.assertEqual(lec.table['XL'], 1)60 self.assertEqual(lec.table['VIT'], 1)61 self.assertEqual(lec.table['S04'], 1)62 self.assertEqual(lec.table['RGE'], 1)63 self.assertEqual(lec.table['MAD'], 1)64 def test_create_table_two_days(self):65 test_matches = []66 for match in matches_two_days:67 test_matches.append(Match(match['teams'], match['week'], match['result']))68 lec = LEC.from_matches(test_matches)69 lec.create_table()70 self.assertEqual(lec.table['RGE'], 2)71 self.assertEqual(lec.table['MAD'], 2)72 self.assertEqual(lec.table['XL'], 1)73 self.assertEqual(lec.table['VIT'], 1)74 self.assertEqual(lec.table['S04'], 1)75 self.assertEqual(lec.table['OG'], 1)76 self.assertEqual(lec.table['FNC'], 1)77 self.assertEqual(lec.table['SK'], 1)78 def test_create_table_season(self):79 matches = Match.from_json('src/tests/lec_test.json')80 lec = LEC.from_matches(matches)81 lec.create_table()82 self.assertEqual(lec.table['RGE'], 11)83 self.assertEqual(lec.table['MAD'], 11)84 self.assertEqual(lec.table['XL'], 7)85 self.assertEqual(lec.table['VIT'], 6)86 self.assertEqual(lec.table['S04'], 5)87 self.assertEqual(lec.table['OG'], 6)88 self.assertEqual(lec.table['FNC'], 7)89 self.assertEqual(lec.table['SK'], 8)90 self.assertEqual(lec.table['G2'], 8)91 self.assertEqual(lec.table['MSF'], 6)92 def test_head_to_head(self):93 test_matches = []94 for match in head_to_head:95 test_matches.append(Match(match['teams'], match['week'], match['result']))96 lec = LEC.from_matches(test_matches)97 lec.create_standings()98 self.assertIn('OG', lec.standings[1])99 self.assertIn('G2', lec.standings[1])100 self.assertIn('FNC', lec.standings[1])101 def test_wins_in_second_half(self):102 test_matches = []103 for match in wins_in_second_half:104 test_matches.append(Match(match['teams'], match['week'], match['result']))105 lec = LEC.from_matches(test_matches)106 lec.create_standings()107 self.assertIn('FNC', lec.standings[1])108 self.assertIn('OG', lec.standings[2])...

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testspindex.py

Source:testspindex.py Github

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...12def test_build(spindex):13 for i,(x,y) in boxes:14 spindex.insert(i, [x,y,x+1,y+1])15 print('built')16def test_matches(spindex, matchbox):17 matches = list(spindex.intersects(matchbox))18 print('matches', len(matches))19################20d = pg.VectorData('data/ne_10m_admin_0_countries.shp')21matchbox = [1,1,20,20]22d.create_spatial_index()23print('default',d.spindex)24pg.vector.data.DEFAULT_SPATIAL_INDEX = 'rtree'25d.create_spatial_index()26print('default rtree',d.spindex)27print(len(list(d.quick_overlap(matchbox))))28pg.vector.data.DEFAULT_SPATIAL_INDEX = 'quadtree'29d.create_spatial_index()30print('default quadtree',d.spindex)31print(len(list(d.quick_overlap(matchbox))))32d.create_spatial_index('rtree')33print('specify rtree',d.spindex)34print(len(list(d.quick_overlap(matchbox))))35d.create_spatial_index('quadtree')36print('specify quadtree',d.spindex)37print(len(list(d.quick_overlap(matchbox))))38################39n = 1000040boxes = [(i, (uniform(-180,180),uniform(-90,90)) ) for i in range(n)]41matchbox = [1,1,20,20]42print('rtree')43spindex = test_rtree_init(None)44test_build(spindex)45test_matches(spindex, matchbox)46print('rtree, rtree backend')47spindex = test_rtree_init('rtree')48test_build(spindex)49test_matches(spindex, matchbox)50print('rtree, pyrtree backend')51spindex = test_rtree_init('pyrtree')52test_build(spindex)53test_matches(spindex, matchbox)54print('quadtree')55spindex = test_quadtree_init(None, bbox=[-180,-90,180,90])56test_build(spindex)57test_matches(spindex, matchbox)58print('quadtree, pyqtree backend')59spindex = test_quadtree_init('pyqtree', bbox=[-180,-90,180,90])60test_build(spindex)...

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