How to use test_combined method in grail

Best Python code snippet using grail_python

keystroke_dynamics_model.py

Source:keystroke_dynamics_model.py Github

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1import numpy as np2import pandas as pd3import matplotlib.pyplot as plt4import seaborn as sns5from sklearn.metrics import accuracy_score6from sklearn.neighbors import KNeighborsClassifier7from sklearn.model_selection import StratifiedShuffleSplit8from sklearn.model_selection import GridSearchCV, StratifiedShuffleSplit9from xgboost.sklearn import XGBClassifier10import xgboost as xgb11train = pd.read_csv('model/train.csv')12test = pd.read_csv('model/test.csv')13test_Combined = None14train_Combined = None15nr_bins = 1016HDMax, RPDMax, PPDMax = None, None, None17HDBins, RPDBins, PPDBins = None, None, None18train_1 = train19for i in range(1, 13):20 train_1['PPD-' + str(i)] = train_1['press-' + str(i)] - train_1['press-' + str(i - 1)]21 train_1['RPD-' + str(i)] = train_1['release-' + str(i)] - train_1['press-' + str(i - 1)]22for i in range(13):23 train_1['HD-' + str(i)] = train_1['release-' + str(i)] - train_1['press-' + str(i)]24test_1 = test25for i in range(1, 13):26 test_1['PPD-' + str(i)] = test_1['press-' + str(i)] - test_1['press-' + str(i - 1)]27 test_1['RPD-' + str(i)] = test_1['release-' + str(i)] - test_1['press-' + str(i - 1)]28for i in range(13):29 test_1['HD-' + str(i)] = test_1['release-' + str(i)] - test_1['press-' + str(i)]30def train():31 # Training Data32 drop_cols_HD_analysis = ['PPD-' + str(i) for i in range(1, 13)] + ['RPD-' + str(i) for i in range(1, 13)] + ['release-' + str(i) for i in range(13)]33 train_HD_analysis = train_1.drop(columns = drop_cols_HD_analysis)34 train_HD_analysis['id'] = train_HD_analysis.index35 train_HD_analysis = pd.wide_to_long(train_HD_analysis, ['press-', 'HD-'],36 i = 'id', j = 'key_no').sort_values(by = ['user', 'id', 'key_no'])37 drop_cols_PPD_analysis = ['HD-' + str(i) for i in range(13)] + ['RPD-' + str(i) for i in range(1, 13)] + ['release-' + str(i) for i in range(13)] + ['press-0']38 train_PPD_analysis = train_1.drop(columns = drop_cols_PPD_analysis)39 train_PPD_analysis['id'] = train_PPD_analysis.index40 train_PPD_analysis = pd.wide_to_long(train_PPD_analysis, ['press-', 'PPD-'],41 i = 'id', j = 'key_no').sort_values(by =['user', 'id', 'key_no'])42 drop_cols_RPD_analysis = ['HD-'+str(i) for i in range(13)] + ['PPD-' + str(i) for i in range(1, 13)] + ['release-' + str(i) for i in range(13)] + ['press-0']43 44 train_RPD_analysis = train_1.drop(columns = drop_cols_RPD_analysis)45 train_RPD_analysis['id'] = train_RPD_analysis.index46 train_RPD_analysis = pd.wide_to_long(train_RPD_analysis, ['press-', 'RPD-'],47 i = 'id', j = 'key_no').sort_values(by =['user', 'id', 'key_no'])48 # Test Data49 test_HD_analysis = test_1.drop(columns = drop_cols_HD_analysis)50 test_HD_analysis['id'] = test_HD_analysis.index51 test_HD_analysis = pd.wide_to_long(test_HD_analysis, ['press-', 'HD-'],52 i = 'id', j = 'key_no').sort_values(53 by = ['id', 'key_no'])54 test_PPD_analysis = test_1.drop(columns = drop_cols_PPD_analysis)55 test_PPD_analysis['id'] = test_PPD_analysis.index56 test_PPD_analysis = pd.wide_to_long(test_PPD_analysis, ['press-', 'PPD-'],57 i = 'id', j = 'key_no').sort_values(58 by =['id', 'key_no'])59 test_RPD_analysis = test_1.drop(columns = drop_cols_RPD_analysis)60 test_RPD_analysis['id'] = test_RPD_analysis.index61 test_RPD_analysis = pd.wide_to_long(test_RPD_analysis, ['press-', 'RPD-'],62 i = 'id', j = 'key_no').sort_values(63 by =['id', 'key_no'])64 # Join these individual tables together65 test_Combined = test_HD_analysis.join(test_RPD_analysis.drop(columns = ['press-']), rsuffix = 'RPD_').join(test_PPD_analysis.drop(columns = ['press-']), rsuffix = 'PPD_')66 train_Combined = train_HD_analysis.join(train_RPD_analysis.drop(columns = ['user', 'press-']), rsuffix = 'RPD_').join(train_PPD_analysis.drop(columns = ['user', 'press-']), rsuffix = 'PPD_')67 #print('Max values in train are: HDMax: ', HDMax, 'RPDMax:',68 # RPDMax, 'PPDMax:', PPDMax)69 labels = [i for i in range(nr_bins)]70 train_Combined['HDEnc'], HDBins = pd.qcut(train_Combined['HD-'],71 retbins = True, labels = labels,72 q = nr_bins)73 train_Combined['PPDEnc'], RPDBins = pd.qcut(train_Combined['PPD-'],74 retbins = True, labels = labels,75 q = nr_bins)76 train_Combined['RPDEnc'], PPDBins = pd.qcut(train_Combined['RPD-'],77 retbins = True, labels = labels,78 q = nr_bins)79 train_Combined['HDEnc'] = train_Combined['HDEnc'].astype(str).replace('nan', -1).astype(int)80 train_Combined['PPDEnc'] = train_Combined['PPDEnc'].astype(str).replace('nan', -1).astype(float)81 train_Combined['RPDEnc'] = train_Combined['RPDEnc'].astype(str).replace('nan', -1).astype(float)82def predict(pressed_t, released_t):83 HDMax = test_Combined['HD-'].max()84 RPDMax = test_Combined['RPD-'].max()85 PPDMax = test_Combined['PPD-'].max()86 #print('Max values in test are: HDMax: ', HDMax, 'RPDMax:',87 # RPDMax, 'PPDMax:', PPDMax)88 labels = [i for i in range(nr_bins)]89 test_Combined['HDEnc'] = pd.cut(test_Combined['HD-'],90 labels = labels,91 bins = HDBins)92 test_Combined['PPDEnc'] = pd.cut(test_Combined['PPD-'],93 labels = labels,94 bins = RPDBins)95 test_Combined['RPDEnc'] = pd.cut(test_Combined['RPD-'],96 labels = labels,97 bins = PPDBins)98 test_Combined['HDEnc'] = test_Combined['HDEnc'].astype(str).replace('nan', -1).astype(float)99 test_Combined['PPDEnc'] = test_Combined['PPDEnc'].astype(str).replace('nan', -1).astype(float)100 test_Combined['RPDEnc'] = test_Combined['RPDEnc'].astype(str).replace('nan', -1).astype(float)101 train_Combined_HDAvg = train_Combined.reset_index().groupby(['user', 'key_no'])['HDEnc'].mean()102 train_Combined_PPDAvg = train_Combined.reset_index().groupby(['user', 'key_no'])['PPDEnc'].mean()103 train_Combined_RPDAvg = train_Combined.reset_index().groupby(['user', 'key_no'])['RPDEnc'].mean()104 temp = pd.DataFrame({'HD':train_Combined_HDAvg, 'PPD':train_Combined_PPDAvg, 105 'RPD':train_Combined_RPDAvg})106 train_HDProperties = temp.reset_index().groupby('user')['HD'].apply(np.array)107 train_PPDProperties = temp.reset_index().groupby('user')['PPD'].apply(np.array)108 train_RPDProperties = temp.reset_index().groupby('user')['RPD'].apply(np.array)109 train_UserProps = pd.DataFrame({'HD':train_HDProperties, 'PPD':train_PPDProperties,110 'RPD':train_RPDProperties})111 pressed_t = released_t112 released_t = pressed_t113 train_Combined_HDAvg = test_Combined.reset_index().groupby(['id', 'key_no'])['HDEnc'].mean()114 train_Combined_PPDAvg = test_Combined.reset_index().groupby(['id', 'key_no'])['PPDEnc'].mean()115 train_Combined_RPDAvg = test_Combined.reset_index().groupby(['id', 'key_no'])['RPDEnc'].mean()116 temp = pd.DataFrame({'HD':train_Combined_HDAvg, 'PPD':train_Combined_PPDAvg, 117 'RPD':train_Combined_RPDAvg})118 train_HDProperties = temp.reset_index().groupby('id')['HD'].apply(np.array)119 train_PPDProperties = temp.reset_index().groupby('id')['PPD'].apply(np.array)120 train_RPDProperties = temp.reset_index().groupby('id')['RPD'].apply(np.array)121 test_UserProps = pd.DataFrame({'HD':train_HDProperties, 'PPD':train_PPDProperties,122 'RPD':train_RPDProperties})123 test_UserProps = pd.DataFrame(test_UserProps.HD.tolist(),124 index = test_UserProps.index).add_prefix('HD_').join(125 pd.DataFrame(test_UserProps.PPD.tolist(), index = 126 test_UserProps.index).add_prefix('PPD_')).join(127 pd.DataFrame(test_UserProps.RPD.tolist(), index =128 test_UserProps.index).add_prefix('RPD_'))129 train_HDTemp = train_Combined.reset_index().groupby(['user', 'id'])['HDEnc'].apply(np.array)130 train_PPDTemp = train_Combined.reset_index().groupby(['user', 'id'])['PPDEnc'].apply(np.array)131 train_RPDTemp = train_Combined.reset_index().groupby(['user', 'id'])['RPDEnc'].apply(np.array)132 train_User_AllSampleProps = pd.DataFrame({'HD':train_HDTemp, 'PPD':train_PPDTemp,133 'RPD':train_RPDTemp})134 train_User_AllSampleProps = pd.DataFrame(train_User_AllSampleProps.HD.tolist(),135 index = train_User_AllSampleProps.index).add_prefix('HD_').join(136 pd.DataFrame(train_User_AllSampleProps.PPD.tolist(),137 index = train_User_AllSampleProps.index).add_prefix('PPD_')).join(138 pd.DataFrame(train_User_AllSampleProps.RPD.tolist(),139 index = train_User_AllSampleProps.index).add_prefix('RPD_')).reset_index().set_index('user').drop(columns = ['id'])140 train_HDTemp = test_Combined.reset_index().groupby(['id'])['HDEnc'].apply(np.array)141 train_PPDTemp = test_Combined.reset_index().groupby(['id'])['PPDEnc'].apply(np.array)142 train_RPDTemp = test_Combined.reset_index().groupby(['id'])['RPDEnc'].apply(np.array)143 test_User_AllSampleProps = pd.DataFrame({'HD':train_HDTemp, 'PPD':train_PPDTemp,144 'RPD':train_RPDTemp})145 test_User_AllSampleProps = pd.DataFrame(test_User_AllSampleProps.HD.tolist(),146 index = test_User_AllSampleProps.index).add_prefix('HD_').join(147 pd.DataFrame(test_User_AllSampleProps.PPD.tolist(),148 index = test_User_AllSampleProps.index).add_prefix('PPD_')).join(149 pd.DataFrame(test_User_AllSampleProps.RPD.tolist(),150 index = test_User_AllSampleProps.index).add_prefix('RPD_'))151 trainX_allSamples = train_User_AllSampleProps.reset_index().drop(columns = ['user'])152 trainY_allSamples = train_User_AllSampleProps.index153 model = xgb.XGBClassifier()154 model.load_model('keystroke_model.bst')155 testX_allSamples = test_User_AllSampleProps.reset_index().drop(columns = ['id'])156 pd.DataFrame({'idx': testX_allSamples.index},157 index = testX_allSamples.index).to_csv('submission_x.csv', index = False)...

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test.py

Source:test.py Github

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...18 '''19 single_word = SingleShortenedWord(text)20 single_word.generate()21 test_common(text, target_word, single_word)22def test_combined(text, target_word):23 '''短縮語（結合語）のテスト24 '''25 combined_word = CombinedShortenedWord(text)26 combined_word.generate()27 test_common(text, target_word, combined_word)28def test_yuragi(text, target_word):29 '''ゆらぎ語のテスト30 '''31 yuragi_word = Yuragi(text)32 yuragi_word.generate()33 test_common(text, target_word, yuragi_word)34def main():35 # # -------------------------------36 # # 単一語のテスト37 # # -------------------------------38 # # 単一語(分割)39 # test_single('CRISIS 公安機動捜査隊特捜班', 'CRISIS')40 # test_single('SRサイタマノラッパー~マイクの細道~', 'サイタマノラッパー')41 # test_single('中居正広のミになる図書館', 'ミになる図書館')42 # test_single('ファイナルファンタジーXIV　光のお父さん', '光のお父さん')43 # test_single('関ジャム　完全燃SHOW', '関ジャム')44 # # 単一語（分割して変換）45 # test_single('CRISIS 公安機動捜査隊特捜班', 'クライシス')46 # # 単一語（キャッチコピーを削除してそのまま）47 # test_single('1億人の大質問!?笑ってコラえて！', '笑ってコラえて')48 # # 単一語（主語をそのまま）49 # test_single('櫻子さんの足下には死体が埋まっている', '櫻子さん')50 # # 単一語（主語をそのまま）51 # test_single('警視庁捜査一課9係　season12', '9係')52 # # 単一語（カタカナ語をそのまま）53 # test_single('幸せ！ボンビーガール', 'ボンビーガール')54 # # 単一語（ノイズを除去して、カタカナ語をそのまま）55 # test_single('ユーリ!!! on ICE', 'ユーリ')56 # # 単一語（シリーズ名の除去）57 # test_single('進撃の巨人 Season 2」', '進撃の巨人')58 # # -------------------------------59 # # 結合語のテスト60 # # -------------------------------61 # # 結合語62 # # test_combined('マッサージ探偵　ジョー」', '探偵ジョー') # 失敗する、カタカナ3字は非対応だから63 # test_combined('ボク、運命の人です。', 'ボク運')64 # test_combined('真夜中のプリンス', '真夜プリ')65 # test_combined('緊急取調室 第2シリーズ」', 'キントリ')66 # test_combined('中居正広の金曜日のスマイルたちへ」', '金スマ')67 # test_combined('この素晴らしい世界に祝福を！2」', 'このすば')68 # test_combined('あなたのことはそれほど」', 'あなそれ')69 # test_combined('ボク、運命の人です。」', 'ボク運')70 # test_combined('人は見た目が100パーセント」', 'ひとパー')71 # test_combined('恋がヘタでも生きてます」', '恋ヘタ')72 # test_combined('あなたのことはそれほど」', 'あなそれ')73 # test_combined('3人のパパ」', '3パパ')74 # test_combined('警視庁捜査一課9係　season12」', '9係')75 # # 結合語（分解して変換して結合）76 # test_combined('鋼の錬金術師', 'ハガレン')77 # -------------------------------78 # ゆらぎ候補語のテスト79 # -------------------------------80 # 単一語(分割)81 test_yuragi('ダンジョンに出会いを求めるのは間違っているだろうか', 'ダンまち')82 test_yuragi('Re：ゼロから始める異世界生活', 'リゼロ')83 test_yuragi('転生したらスライムだった件', '転スラ')...

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test_meta_data.py

Source:test_meta_data.py Github

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1import anvil.meta_data as md2from base_test import TestBase3class TestBaseMetaData(TestBase):4 test_meta_data = {'foo': 'moo'}5 test_other_meta_data = {'bar': 'larp'}6 test_combined = {}7 test_combined.update(test_meta_data)8 test_combined.update(test_other_meta_data)9 test_total_meta_data_overwrite = {'foo': 'boo', 'bar': 'farp'}10 test_other_meta_data_overwrite = {'bar': 'marp'}11 test_overwritten = test_combined.copy()12 test_overwritten.update(test_other_meta_data_overwrite)13 def build_dependencies(cls):14 pass15class TestMetaDataMergeDicts(TestBaseMetaData):16 def test_meta_data_double(self):17 merged_dict = md.MetaData().merge(self.test_meta_data, self.test_other_meta_data)18 self.assertEquals(merged_dict, self.test_combined)19 def test_meta_data_single(self):20 merged_dict = md.MetaData().merge(self.test_meta_data)21 self.assertEquals(merged_dict, self.test_meta_data)22 def test_meta_data_empty(self):23 test_meta_data = {}24 actual = {}25 actual.update(test_meta_data)26 merged_dict = md.MetaData().merge(test_meta_data)27 self.assertEquals(merged_dict, actual)28 def test_meta_data_none(self):29 test_meta_data = None30 merged_dict = md.MetaData().merge(test_meta_data)31 self.assertEquals(merged_dict, {})32class TestKeys(TestBaseMetaData):33 def test_default_merge(self):34 meta_data_object = md.MetaData()35 meta_data_object.merge(self.test_meta_data, self.test_other_meta_data)36 self.assertEquals(meta_data_object.keys(), list(self.test_combined))37 def test_initialize_with_dicts(self):38 meta_data_object = md.MetaData(self.test_meta_data, self.test_other_meta_data)39 self.assertEquals(meta_data_object.keys(), list(self.test_combined))40 def test_initialize_with_dict_and_splat(self):41 meta_data_object = md.MetaData(self.test_meta_data, **self.test_other_meta_data)42 self.assertEquals(meta_data_object.keys(), list(self.test_combined))43class TestSplatting(TestBaseMetaData):44 @staticmethod45 def single_splat_returner(*args):46 return args47 @staticmethod48 def double_splat_returner(**kwargs):49 return kwargs50 def test_single_from_merge(self):51 meta_data_object = md.MetaData()52 meta_data_object.merge(self.test_meta_data, self.test_other_meta_data)53 self.assertEquals(tuple(meta_data_object.keys()), self.single_splat_returner(*meta_data_object))54 def test_double_from_init(self):55 meta_data_object = md.MetaData(self.test_meta_data, self.test_other_meta_data)56 self.assertEquals(meta_data_object, self.double_splat_returner(**meta_data_object.to_dict()))57class TestMerge(TestBaseMetaData):58 def test_default_merge(self):59 meta_data_object = md.MetaData()60 meta_data_object.merge(self.test_meta_data, self.test_other_meta_data)61 self.assertEquals(meta_data_object, self.test_combined)62 def test_initialize_with_dicts(self):63 meta_data_object = md.MetaData(self.test_meta_data, self.test_other_meta_data)64 self.assertEquals(meta_data_object, self.test_combined)65 def test_initialize_with_dict_and_splat(self):66 meta_data_object = md.MetaData(self.test_meta_data, **self.test_other_meta_data)67 self.assertEquals(meta_data_object, self.test_combined)68class TestProtection(TestBaseMetaData):69 def test_overwrite_merge(self):70 meta_data_object = md.MetaData(self.test_combined)71 meta_data_object.merge(self.test_other_meta_data_overwrite)72 self.assertEquals(meta_data_object, self.test_overwritten)73 def test_protected_merge_force(self):74 meta_data_object = md.MetaData(self.test_combined, protected='bar')75 meta_data_object.merge(self.test_other_meta_data_overwrite, force=True)76 self.assertEquals(meta_data_object, self.test_overwritten)77 def test_protected_multi_merge_force(self):78 meta_data_object = md.MetaData(self.test_combined, protected=['foo', 'bar'])79 meta_data_object.merge(self.test_total_meta_data_overwrite, force=True)80 self.assertEquals(meta_data_object, self.test_total_meta_data_overwrite)81 def test_protected_single_merge_force(self):82 meta_data_object = md.MetaData(self.test_combined, protected=['foo'])83 meta_data_object.merge(self.test_total_meta_data_overwrite, force=True)84 self.assertEquals(meta_data_object, self.test_total_meta_data_overwrite)85 def test_protected_merge(self):86 meta_data_object = md.MetaData(self.test_combined, protected='bar')87 meta_data_object.merge(self.test_other_meta_data_overwrite)88 self.assertEquals(meta_data_object, self.test_combined)89 def test_protected_merge_as_list(self):90 meta_data_object = md.MetaData(self.test_combined, protected=['bar'])91 meta_data_object.merge(self.test_other_meta_data_overwrite)92 self.assertEquals(meta_data_object, self.test_combined)93 def test_add_protection_via_method(self):94 meta_data_object = md.MetaData(self.test_combined, protected=['bar'])95 meta_data_object.merge(self.test_other_meta_data_overwrite)96 self.assertEquals(meta_data_object, self.test_combined)97 def test_add_protection_manually(self):98 meta_data_object = md.MetaData(self.test_combined)99 meta_data_object.protected |= {'bar'}100 meta_data_object.merge(self.test_other_meta_data_overwrite)101 self.assertEquals(meta_data_object, self.test_combined)102 def test_add_protection_manually_overwrite(self):103 meta_data_object = md.MetaData(self.test_combined)104 meta_data_object.protected = ['bar']105 meta_data_object.merge(self.test_other_meta_data_overwrite)...

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