def get_features(data, peaks):
""" Uses peaks from DO only
"""
DO_masks = peaks_to_DO_masks(peaks)
arr = []
# loop over peak sources
for source, mask in DO_masks.items():
# peak object features
objects = feature_table(mask, mask, object_features)
# DO/sequencing features
table = build_feature_table(data, mask, peak_features, all_index)
table = objects.join(table)
table['source'] = source
arr += [table]
return pd.concat(arr)
def test_build_feature_table():
features = {
'mean': lambda region: region.intensity_image[region.image].mean(),
'median':
lambda region: np.median(region.intensity_image[region.image]),
'max': lambda region: region.intensity_image[region.image].max()
}
index = (('round', range(1,
4)), ('channel', ('DAPI', 'Cy3', 'A594', 'Cy5')))
data = read_stack(stack)
mask = read_stack(nuclei)
df = build_feature_table(data, mask, features, index)
df.index.name = 'cell'
df = df.set_index(['round', 'channel'],
append=True).stack().unstack('cell').T
df_ = pd.read_pickle(home('build_feature_table.pkl'))
assert (df == df_).all().all()