def test_df_to_matrix():
lr = LogisticRegression()
source_list = ['reach', 'sparser', 'signor']
cw = CountsScorer(lr, source_list)
x_arr = cw.df_to_matrix(test_df)
assert isinstance(x_arr, np.ndarray), 'x_arr should be a numpy array'
assert x_arr.shape == (len(test_df), len(source_list)), \
'stmt matrix dimensions should match test stmts'
assert x_arr.shape == (len(test_df), len(source_list))
# Try again with statement type
cw = CountsScorer(lr, source_list, use_stmt_type=True)
num_types = len(cw.stmt_type_map)
x_arr = cw.df_to_matrix(test_df)
assert x_arr.shape == (len(test_df), len(source_list) + num_types), \
'matrix should have a col for sources and other cols for every ' \
'statement type.'
def test_check_df_cols_noerr():
"""Test dataframe should not raise ValueError."""
lr = LogisticRegression()
source_list = ['reach', 'sparser', 'signor']
cw = CountsScorer(lr, source_list)
cw.df_to_matrix(test_df)
def test_check_df_cols_err():
"""Drop a required column and make sure we get a ValueError."""
lr = LogisticRegression()
source_list = ['reach', 'sparser', 'signor']
cw = CountsScorer(lr, source_list)
cw.df_to_matrix(test_df.drop('stmt_type', axis=1))
