def test_LoadSubsetFromFile(self):
"""Calculate one feature family, store to sig, load sig, and use to create larger fs"""
img_filename = "lymphoma_eosin_channel_MCL_test_img_sj-05-3362-R2_001_E.tif"
orig_img_filepath = pychrm_test_dir + sep + img_filename
full_list = list((
'Pixel Intensity Statistics () [3]',
'Pixel Intensity Statistics (Fourier ()) [3]',
))
tempdir = mkdtemp()
from shutil import copy
try:
# copy the tiff to the tempdir so the .sig files end up there too
copy(orig_img_filepath, tempdir)
input_img_path = tempdir + sep + img_filename
kwargs = {}
kwargs['source_filepath'] = input_img_path
kwargs['tile_num_cols'] = 6
kwargs['tile_num_rows'] = 5
kwargs['tiling_scheme'] = '5x6'
kwargs['tile_col_index'] = 0
kwargs['tile_row_index'] = 0
kwargs['feature_names'] = full_list[1:]
fv1 = FeatureVector(**kwargs).GenerateFeatures(quiet=False)
# modify the sig value and write to sig file to make sure subsequent loading
# used the value from disk and not recalculated it:
fv1.values[0] = -9999
fv1.ToSigFile(quiet=False)
# Now, ask for more features:
kwargs['feature_names'] = full_list
fv2 = FeatureVector(**kwargs)
with self.assertRaises(IncompleteFeatureSetError):
fv2.LoadSigFile()
#import pdb; pdb.set_trace()
fv2.GenerateFeatures()
#self.assertEqual( fv1.values[0], fv2.values[0] )
finally:
rmtree(tempdir)
