def test_gen_valmaps_default(smalldf):
dtypes = ['continuous', 'categorical', 'categorical', 'continuous']
metadata = dict()
valmaps = du.gen_valmaps(smalldf, dtypes, metadata)
assert 0 not in valmaps
assert 3 not in valmaps
assert 1 in valmaps
assert 2 in valmaps
valmap_1 = valmaps[1]
valmap_2 = valmaps[2]
assert len(valmap_1['val2idx']) == 2
assert len(valmap_1['idx2val']) == 2
assert valmap_1['val2idx'][0] == 0
assert valmap_1['val2idx'][1] == 1
assert valmap_1['idx2val'][0] == 0
assert valmap_1['idx2val'][1] == 1
assert len(valmap_2['val2idx']) == 3
assert len(valmap_2['idx2val']) == 3
assert valmap_2['val2idx']['one'] == 0
assert valmap_2['val2idx']['three'] == 1
assert valmap_2['val2idx']['two'] == 2
assert valmap_2['idx2val'][0] == 'one'
assert valmap_2['idx2val'][1] == 'three'
assert valmap_2['idx2val'][2] == 'two'
def test_gen_valmaps_default_missing_vals(smalldf):
# Missing value NaN should not appear in the value map
dtypes = ['continuous', 'categorical', 'categorical', 'continuous']
metadata = dict()
smalldf.ix[0, 1] = float('NaN')
smalldf.ix[1, 2] = float('NaN')
valmaps = du.gen_valmaps(smalldf, dtypes, metadata)
assert 0 not in valmaps
assert 3 not in valmaps
assert 1 in valmaps
assert 2 in valmaps
valmap_1 = valmaps[1]
valmap_2 = valmaps[2]
assert len(valmap_1['val2idx']) == 2
assert len(valmap_1['idx2val']) == 2
assert valmap_1['val2idx'][0] == 0
assert valmap_1['val2idx'][1] == 1
assert valmap_1['idx2val'][0] == 0
assert valmap_1['idx2val'][1] == 1
assert len(valmap_2['val2idx']) == 3
assert len(valmap_2['idx2val']) == 3
assert valmap_2['val2idx']['one'] == 0
assert valmap_2['val2idx']['three'] == 1
assert valmap_2['val2idx']['two'] == 2
assert valmap_2['idx2val'][0] == 'one'
assert valmap_2['idx2val'][1] == 'three'
assert valmap_2['idx2val'][2] == 'two'
def test_dataframe_to_array_all_categorical_with_missing_vals():
s_1 = pd.Series([-1, 0, 2, 1, float('NaN')])
s_2 = pd.Series(['one', 'two', 'three', 'four', float('NaN')])
df = pd.concat([s_1, s_2], axis=1)
dtypes = ['categorical'] * 2
metadata = dict()
valmaps = du.gen_valmaps(df, dtypes, metadata)
data = du.dataframe_to_array(df, valmaps)
assert data.shape == df.shape
assert 'float' in str(data.dtype)
assert data[0, 0] == 0
assert data[1, 0] == 1
assert data[2, 0] == 3
assert data[3, 0] == 2
assert np.isnan(data[4, 0])
assert data[0, 1] == 1
assert data[1, 1] == 3
assert data[2, 1] == 2
assert data[3, 1] == 0
assert np.isnan(data[4, 1])
def test_gen_valmaps_default(smalldf):
dtypes = ['continuous', 'categorical', 'categorical', 'continuous']
metadata = dict()
valmaps = du.gen_valmaps(smalldf, dtypes, metadata)
assert 0 not in valmaps
assert 3 not in valmaps
assert 1 in valmaps
assert 2 in valmaps
valmap_1 = valmaps[1]
valmap_2 = valmaps[2]
assert len(valmap_1['val2idx']) == 2
assert len(valmap_1['idx2val']) == 2
assert valmap_1['val2idx'][0] == 0
assert valmap_1['val2idx'][1] == 1
assert valmap_1['idx2val'][0] == 0
assert valmap_1['idx2val'][1] == 1
assert len(valmap_2['val2idx']) == 3
assert len(valmap_2['idx2val']) == 3
assert valmap_2['val2idx']['one'] == 0
assert valmap_2['val2idx']['three'] == 1
assert valmap_2['val2idx']['two'] == 2
assert valmap_2['idx2val'][0] == 'one'
assert valmap_2['idx2val'][1] == 'three'
assert valmap_2['idx2val'][2] == 'two'
def test_dataframe_to_array_all_categorical_with_missing_vals():
s_1 = pd.Series([-1, 0, 2, 1, float('NaN')])
s_2 = pd.Series(['one', 'two', 'three', 'four', float('NaN')])
df = pd.concat([s_1, s_2], axis=1)
dtypes = ['categorical']*2
metadata = dict()
valmaps = du.gen_valmaps(df, dtypes, metadata)
data = du.dataframe_to_array(df, valmaps)
assert data.shape == df.shape
assert 'float' in str(data.dtype)
assert data[0, 0] == 0
assert data[1, 0] == 1
assert data[2, 0] == 3
assert data[3, 0] == 2
assert np.isnan(data[4, 0])
assert data[0, 1] == 1
assert data[1, 1] == 3
assert data[2, 1] == 2
assert data[3, 1] == 0
assert np.isnan(data[4, 1])
def test_gen_valmaps_default_missing_vals(smalldf):
# Missing value NaN should not appear in the value map
dtypes = ['continuous', 'categorical', 'categorical', 'continuous']
metadata = dict()
smalldf.ix[0, 1] = float('NaN')
smalldf.ix[1, 2] = float('NaN')
valmaps = du.gen_valmaps(smalldf, dtypes, metadata)
assert 0 not in valmaps
assert 3 not in valmaps
assert 1 in valmaps
assert 2 in valmaps
valmap_1 = valmaps[1]
valmap_2 = valmaps[2]
assert len(valmap_1['val2idx']) == 2
assert len(valmap_1['idx2val']) == 2
assert valmap_1['val2idx'][0] == 0
assert valmap_1['val2idx'][1] == 1
assert valmap_1['idx2val'][0] == 0
assert valmap_1['idx2val'][1] == 1
assert len(valmap_2['val2idx']) == 3
assert len(valmap_2['idx2val']) == 3
assert valmap_2['val2idx']['one'] == 0
assert valmap_2['val2idx']['three'] == 1
assert valmap_2['val2idx']['two'] == 2
assert valmap_2['idx2val'][0] == 'one'
assert valmap_2['idx2val'][1] == 'three'
assert valmap_2['idx2val'][2] == 'two'
def test_gen_valmaps_metadata(smalldf):
dtypes = ['continuous', 'categorical', 'categorical', 'continuous']
metadata = {}
metadata[1] = {
'dtype': 'categorical',
'values': [-1, 0, 1, 2, 99]}
metadata[2] = {
'dtype': 'categorical',
'values': ['zero', 'one', 'two', 'three']}
valmaps = du.gen_valmaps(smalldf, dtypes, metadata)
assert 0 not in valmaps
assert 3 not in valmaps
assert 1 in valmaps
assert 2 in valmaps
valmap_1 = valmaps[1]
valmap_2 = valmaps[2]
assert len(valmap_1['val2idx']) == 5
assert len(valmap_1['idx2val']) == 5
# col 2
assert valmap_1['val2idx'][-1] == 0
assert valmap_1['val2idx'][0] == 1
assert valmap_1['val2idx'][1] == 2
assert valmap_1['val2idx'][2] == 3
assert valmap_1['val2idx'][99] == 4
assert valmap_1['idx2val'][0] == -1
assert valmap_1['idx2val'][1] == 0
assert valmap_1['idx2val'][2] == 1
assert valmap_1['idx2val'][3] == 2
assert valmap_1['idx2val'][4] == 99
# col 2
assert valmap_2['val2idx']['one'] == 0
assert valmap_2['val2idx']['three'] == 1
assert valmap_2['val2idx']['two'] == 2
assert valmap_2['val2idx']['zero'] == 3
assert valmap_2['idx2val'][0] == 'one'
assert valmap_2['idx2val'][1] == 'three'
assert valmap_2['idx2val'][2] == 'two'
assert valmap_2['idx2val'][3] == 'zero'
def test_gen_valmaps_metadata(smalldf):
dtypes = ['continuous', 'categorical', 'categorical', 'continuous']
metadata = {}
metadata[1] = {'dtype': 'categorical', 'values': [-1, 0, 1, 2, 99]}
metadata[2] = {
'dtype': 'categorical',
'values': ['zero', 'one', 'two', 'three']
}
valmaps = du.gen_valmaps(smalldf, dtypes, metadata)
assert 0 not in valmaps
assert 3 not in valmaps
assert 1 in valmaps
assert 2 in valmaps
valmap_1 = valmaps[1]
valmap_2 = valmaps[2]
assert len(valmap_1['val2idx']) == 5
assert len(valmap_1['idx2val']) == 5
# col 2
assert valmap_1['val2idx'][-1] == 0
assert valmap_1['val2idx'][0] == 1
assert valmap_1['val2idx'][1] == 2
assert valmap_1['val2idx'][2] == 3
assert valmap_1['val2idx'][99] == 4
assert valmap_1['idx2val'][0] == -1
assert valmap_1['idx2val'][1] == 0
assert valmap_1['idx2val'][2] == 1
assert valmap_1['idx2val'][3] == 2
assert valmap_1['idx2val'][4] == 99
# col 2
assert valmap_2['val2idx']['one'] == 0
assert valmap_2['val2idx']['three'] == 1
assert valmap_2['val2idx']['two'] == 2
assert valmap_2['val2idx']['zero'] == 3
assert valmap_2['idx2val'][0] == 'one'
assert valmap_2['idx2val'][1] == 'three'
assert valmap_2['idx2val'][2] == 'two'
assert valmap_2['idx2val'][3] == 'zero'
