Commit 3903899f authored by Alessia Marcolini's avatar Alessia Marcolini
Browse files

Remove debug stuff

parent 2d97a800
......@@ -26,7 +26,7 @@ PIXEL_SPACING = [1.0, 2.0, 3.0, 4.0, 5.0]
#%%
DATADIR = Path('data') / DATASET / 'processed' / 'bbox' / BBOX
OUTDIR = Path('data') / DATASET / 'processed'
OUTFILE = f'radiomics_features_{BBOX}_radnew21.csv' # output file name
OUTFILE = f'radiomics_features_{BBOX}.csv' # output file name
clinical = pd.read_csv(Path('data') / DATASET / 'processed' / f'clinical_{DATASET}.csv')
......@@ -40,7 +40,7 @@ extractor_intensity = RadiomicsFeatureExtractor(params_intensity)
params_texture = '02_radiomics_features_extraction/texture_new.yaml' # param file to use to create the extractor
extractor_texture = RadiomicsFeatureExtractor(params_texture)
filenames = [f for f in os.listdir(DATADIR) if f.endswith('.npy')][:2]
filenames = [f for f in os.listdir(DATADIR) if f.endswith('.npy')]
exclude_list = []
......@@ -60,8 +60,6 @@ def process_file(filename):
curr_modality.SetSpacing(VOXEL_SPACING)
modalities.append(curr_modality)
# print(data[-1, :, :, :] == data[1, :, :, :])
# print(np.max(data[-1, :, :, :]))
has_label = np.max(data[-1, :, :, :]) > 0
if has_label:
......@@ -89,29 +87,32 @@ def process_file(filename):
for NB in N_BINS:
if not broken:
extractor_texture.settings['binCount'] = NB
# uniform binning
extractor_texture.settings['binMode'] = 'uniform'
result = extractor_texture.execute(
modality, segmentation
)
for key, value in result.items():
if not key.startswith("general_"):
feature[
f'{key}_{P}_{NB}_uniform_{name}'
] = result[key]
# equalized binning
extractor_texture.settings['binMode'] = 'equal'
result = extractor_texture.execute(
modality, segmentation
)
for key, value in result.items():
if not key.startswith("general_"):
feature[
f'{key}_{P}_{NB}_equalized_{name}'
] = result[key]
try:
# uniform binning
extractor_texture.settings['binMode'] = 'uniform'
result = extractor_texture.execute(
modality, segmentation
)
for key, value in result.items():
if not key.startswith("general_"):
feature[
f'{key}_{P}_{NB}_uniform_{name}'
] = result[key]
# equalized binning
extractor_texture.settings['binMode'] = 'equal'
result = extractor_texture.execute(
modality, segmentation
)
for key, value in result.items():
if not key.startswith("general_"):
feature[
f'{key}_{P}_{NB}_equalized_{name}'
] = result[key]
except Exception as e:
print(e)
broken = True
if not broken:
feature['filename'] = filename
......@@ -126,18 +127,16 @@ def process_file(filename):
#%% MULTIPROCESS
result = []
for file in filenames:
feat = process_file(file)
result.append(feat)
# result = []
# for file in filenames:
# feat = process_file(file)
# result.append(feat)
# %%
# multiproc = ListMultiprocessing(process_file, N_JOBS)
# multiproc.execute(filenames)
# result = multiproc.get_result()
multiproc = ListMultiprocessing(process_file, N_JOBS)
multiproc.execute(filenames)
result = multiproc.get_result()
# print('done')
#%% Save features in a Pandas df
......@@ -148,6 +147,4 @@ print('Number of files: ', features.shape[0])
print('Number of features: ', features.shape[1] - 1)
# %%
features.to_csv(OUTDIR / OUTFILE)
# %%
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