def test_categories():
""" Verify predefined categories handle missing data """
proc = PreProcess(A)
out = proc.process_one_hot(convert_int=False)
assert (out.columns == ['f2', 'f3', 'f1_0', 'f1_1',
'f1_2', 'f1_3']).all()
# Verify columns are created for missing categories
# and that the new one-hot columns have names corresponding to their values
proc = PreProcess(A)
out0 = proc.process_one_hot(
convert_int=False, categories={'f1': ['a', 'b', 'c', 'd', 'missing']})
assert (out0.columns == ['f2', 'f3', 'a', 'b', 'c', 'd', 'missing']).all()
assert (out0['missing'] == np.zeros(7)).all()
# verify ordering works.
out1 = proc.process_one_hot(
convert_int=False, categories={'f1': ['missing', 'd', 'c', 'a', 'b']})
assert (out1.columns == ['f2', 'f3', 'missing', 'd', 'c', 'a', 'b']).all()
assert all(out0.a == out1.a)
assert all(out0.b == out1.b)
assert all(out0.c == out1.c)
assert all(out0.d == out1.d)
assert (out1['missing'] == np.zeros(7)).all()
assert out1.a.values[0] == 1
assert out1.a.values[1] == 0
assert out1.a.values[2] == 0
assert out1.a.values[3] == 0
assert out1.a.values[4] == 1
# Verify good error with bad categories input.
try:
proc.process_one_hot(categories={'f1': ['a', 'b', 'c']})
except ValueError as e:
assert 'Found unknown categories' in str(e)
def test_one_hot_encoding():
"""Process str and int one hot columns and verify outputs."""
proc = PreProcess(A)
out = proc.process_one_hot(convert_int=False)
assert (out.iloc[:, -4:].sum(axis=1) == np.ones(7)).all()
assert out['f1_0'].values[0] == 1.0
assert out['f1_0'].values[1] == 0.0
assert out['f1_0'].values[-3] == 1.0
assert out['f1_0'].values[-1] == 1.0
assert out['f1_1'].values[1] == 1.0
assert out['f1_1'].values[0] == 0.0
assert out['f1_2'].values[2] == 1.0
assert out['f1_2'].values[-2] == 1.0
assert out['f1_2'].values[-1] == 0.0
assert out['f1_3'].values[3] == 1.0
assert out['f1_3'].values[0] == 0.0
proc = PreProcess(A.values)
np_out = proc.process_one_hot(convert_int=False)
assert np.allclose(out, np_out)
proc = PreProcess(A)
out = proc.process_one_hot(convert_int=True)
assert 'f3' not in out
assert (out.iloc[:, 1:5].sum(axis=1) == np.ones(7)).all()
assert (out.iloc[:, 5:].sum(axis=1) == np.ones(7)).all()