Best Python code snippet using assertpy_python
datareader_wave.py
Source: datareader_wave.py
1import os2import numpy as np3import pandas as pd4from dataframe import DataFrame5class DataReader(object):6 def __init__(self, data_dir):7 data_cols = [8 'data',9 'is_nan',10 'page_id',11 'project',12 'access',13 'agent',14 'test_data',15 'test_is_nan'16 ]17 data = [np.load(os.path.join(data_dir, '{}.npy'.format(i))) for i in data_cols]18 self.test_df = DataFrame(columns=data_cols, data=data)19 self.train_df, self.val_df = self.test_df.train_test_split(train_size=0.95)20 21 def describe(self, logger):22 logger.info('')23 logger.info('Data dimensions:')24 logger.info('train size', len(self.train_df))25 logger.info('val size', len(self.val_df))26 logger.info('test size', len(self.test_df))27 # logger.info(' [[data]] {}'.format(self.data.shape))28 #logger.info('Split seed = {}'.format(self.seed))29 logger.info('')30 def train_batch_generator(self, batch_size):31 return self.batch_generator(32 batch_size=batch_size,33 df=self.train_df,34 shuffle=True,35 num_epochs=10000,36 is_test=False37 )38 def val_batch_generator(self, batch_size):39 return self.batch_generator(40 batch_size=batch_size,41 df=self.val_df,42 shuffle=True,43 num_epochs=10000,44 is_test=False45 )46 def test_batch_generator(self, batch_size):47 return self.batch_generator(48 batch_size=batch_size,49 df=self.test_df,50 shuffle=True,51 num_epochs=1,52 is_test=True53 )54 def batch_generator(self, batch_size, df, shuffle=True, num_epochs=10000, is_test=False):55 batch_gen = df.batch_generator(56 batch_size=batch_size,57 shuffle=shuffle,58 num_epochs=num_epochs,59 allow_smaller_final_batch=is_test60 )61 data_col = 'test_data' if is_test else 'data'62 is_nan_col = 'test_is_nan' if is_test else 'is_nan'63 for batch in batch_gen:64 num_decode_steps = 6465 full_seq_len = batch[data_col].shape[1]66 max_encode_length = full_seq_len - num_decode_steps if not is_test else full_seq_len67 x_encode = np.zeros([len(batch), max_encode_length])68 y_decode = np.zeros([len(batch), num_decode_steps])69 is_nan_encode = np.zeros([len(batch), max_encode_length])70 is_nan_decode = np.zeros([len(batch), num_decode_steps])71 encode_len = np.zeros([len(batch)])72 decode_len = np.zeros([len(batch)])73 for i, (seq, nan_seq) in enumerate(zip(batch[data_col], batch[is_nan_col])):74 rand_len = np.random.randint(max_encode_length - 365 + 1, max_encode_length + 1)75 x_encode_len = max_encode_length if is_test else rand_len76 x_encode[i, :x_encode_len] = seq[:x_encode_len]77 is_nan_encode[i, :x_encode_len] = nan_seq[:x_encode_len]78 encode_len[i] = x_encode_len79 decode_len[i] = num_decode_steps80 if not is_test:81 y_decode[i, :] = seq[x_encode_len: x_encode_len + num_decode_steps]82 is_nan_decode[i, :] = nan_seq[x_encode_len: x_encode_len + num_decode_steps]83 batch['x_encode'] = x_encode84 batch['encode_len'] = encode_len85 batch['y_decode'] = y_decode86 batch['decode_len'] = decode_len87 batch['is_nan_encode'] = is_nan_encode88 batch['is_nan_decode'] = is_nan_decode...
my_mod_test.py
Source: my_mod_test.py
...7class TestMyMod(unittest.TestCase):8 def test_add_col(self):9 df.add_col('Name', ['Connecticut', 'Colorado', 'California', 'Texas'])10 self.assertTrue('Name'in df.df.columns.tolist())11 def test_is_nan(self):12 self.assertTrue(isinstance(df.df.isna().sum(), pd.Series))13 def test_split_df(self):14 train, test = df.split_df()15 self.assertTrue(type(train), pd.DataFrame)16 self.assertTrue(type(test), pd.DataFrame)17if __name__ == '__main__':...
test_core.py
Source: test_core.py
1import numpy as np2import unittest3from py_ebay import is_nan4class TestCore(unittest.TestCase):5 def test_is_nan(self):6 assert(is_nan(np.NAN))7 assert(not is_nan(1))8 assert(not is_nan('1'))...
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