def process2(folder):
""" Post process data Delta"""
print(folder)
util.setup(folder)
params = ['Delta_qol', 'Delta_qol2', 'Delta_mobility', 'Delta_selfcare', 'Delta_activity', 'Delta_pain', 'Delta_anixety', 'Delta_kps']
image_ids = find_images()
result = util.post_calculations(image_ids)
print(len(result['all']))
util.avg_calculation(result['all'], 'all_N=112', None, True, folder, save_sum=True)
util.avg_calculation(result['img'], 'img_N=112', None, True, folder)
print("\n\n\n\n\n")
for qol_param in params:
if qol_param == "Delta_qol2":
(image_ids_with_qol, qol) = util.get_qol(image_ids, "Delta_qol")
qol = [-1 if _temp <= -0.15 else 0 if _temp < 0.15 else 1 for _temp in qol]
else:
(image_ids_with_qol, qol) = util.get_qol(image_ids, qol_param)
qol = [_temp * 100 for _temp in qol]
default_value = -300
print(qol_param, len(qol))
result = util.post_calculations(image_ids_with_qol)
for label in result:
if label == 'img':
continue
print(label)
# util.avg_calculation(result[label], label + '_' + qol_param, qol, True, folder, default_value=default_value)
util.median_calculation(result[label], label + '_' + qol_param, qol, True, folder, default_value=default_value)
def process3(folder):
""" Post process data """
print(folder)
util.setup(folder)
params = ['Mobility', 'Selfcare', 'Activity', 'Pain', 'Anxiety', 'karnofsky', 'Index_value']
image_ids = find_images()
result = util.post_calculations(image_ids)
print(len(result['all']))
# util.avg_calculation(result['all'], 'all_N=112', None, True, folder, save_sum=True)
# util.avg_calculation(result['img'], 'img_N=112', None, True, folder)
for qol_param in params:
if qol_param == "Delta_qol2":
(image_ids_with_qol, qol) = util.get_qol(image_ids, "Delta_qol")
qol = [-1 if _temp <= -0.15 else 0 if _temp < 0.15 else 1 for _temp in qol]
else:
(image_ids_with_qol, qol) = util.get_qol(image_ids, qol_param)
if qol_param not in ["karnofsky", "Delta_kps"]:
qol = [_temp * 100 for _temp in qol]
default_value = -100
print(qol_param)
print(len(qol))
result = util.post_calculations(image_ids_with_qol)
for label in result:
if label == 'img':
continue
print(label)
util.avg_calculation(result[label], label + '_' + qol_param + '_N=112', qol, True, folder, default_value=default_value)
util.median_calculation(result[label], label + '_' + qol_param + '_N=112', qol, True, folder, default_value=default_value)
def process(folder):
""" Post process data distribution and baseline"""
print(folder)
util.setup(folder)
params = ['Mobility', 'Selfcare', 'Activity', 'Pain', 'Anxiety', 'karnofsky', 'Index_value']
image_ids = find_images_163()
result = util.post_calculations(image_ids)
print(len(result['all']))
util.avg_calculation(result['all'], 'all_N=163', None, True, folder, save_sum=True)
util.avg_calculation(result['img'], 'img_N=163', None, True, folder)
image_ids = do_img_registration_GBM.find_images()
result = util.post_calculations(image_ids)
print(len(result['all']))
util.avg_calculation(result['all'], 'all_N=170', None, True, folder, save_sum=True)
util.avg_calculation(result['img'], 'img_N=170', None, True, folder)
for qol_param in params:
(image_ids_with_qol, qol) = util.get_qol(image_ids, qol_param)
if qol_param not in ["karnofsky", "Delta_kps"]:
qol = [_temp * 100 for _temp in qol]
default_value = -100
print(qol_param)
print(len(qol))
result = util.post_calculations(image_ids_with_qol)
for label in result:
if label == 'img':
continue
print(label)
# util.avg_calculation(result[label], label + '_' + qol_param, qol, True, folder, default_value=default_value)
util.median_calculation(result[label], label + '_' + qol_param, qol, True, folder, default_value=default_value)
def process_vlsm(folder, n_permutations):
""" Post process vlsm data """
print(folder)
util.setup(folder)
image_ids = find_images()
params = [
'Index_value', 'karnofsky', 'Mobility', 'Selfcare', 'Activity', 'Pain',
'Anxiety'
]
alternative = [
'less', 'less', 'greater', 'greater', 'greater', 'greater', 'greater'
]
stat_func = [
util.brunner_munzel_test, util.mannwhitneyu_test,
util.mannwhitneyu_test, util.mannwhitneyu_test, util.mannwhitneyu_test,
util.mannwhitneyu_test, util.mannwhitneyu_test
]
for (qol_param, stat_func_i, alternative_i) in zip(params, stat_func,
alternative):
(image_ids_with_qol, qol) = util.get_qol(image_ids, qol_param)
result = util.post_calculations(image_ids_with_qol)
for label in result:
print(label)
if label == 'img':
continue
util.vlsm(result[label],
label + '_' + qol_param,
stat_func_i,
qol,
folder,
n_permutations=n_permutations,
alternative=alternative_i)