def get_labels(kind, exclude_subjects={}):
labels = {}
subjects,tests = bbdp.load(kind)
exclude_subject_ids = []
for key,value in exclude_subjects.items():
exclude_subject_ids += [subject_id for subject_id,subject in subjects.items()\
if subject.__dict__[key]==value]
subjects = {subject_id:subject for subject_id,subject in subjects.items()\
if subject_id not in exclude_subject_ids}
tests = [test for test in tests if test.subject.case_id not in exclude_subject_ids]
n_ctrl = 0
for test in tests:
x = []
if test.subject.label == 'ctrl':
n_ctrl += 1
if kind == 'dugger':
x += [test.subject.label == 'pd']
#x += [test.subject.expired_age-90]
#x += [test.subject.gender]
#if hasattr(test.subject,'dementia'):
# x += [test.subject.dementia]
#x += [test.subject.stint]
if hasattr(test.subject,'other'):
x += test.subject.other
x = [float(_) for _ in x]
labels[test.subject] = x
labels = [labels[key] for key in \
sorted(labels.keys(),key=lambda x:x.case_id)]
return np.array(labels)
def get_labels(kind, exclude_subjects={}):
labels = {}
subjects,tests = bbdp.load(kind)
exclude_subject_ids = []
for key,value in exclude_subjects.items():
exclude_subject_ids += [subject_id for subject_id,subject in subjects.items()\
if subject.__dict__[key]==value]
subjects = {subject_id:subject for subject_id,subject in subjects.items()\
if subject_id not in exclude_subject_ids}
tests = [test for test in tests if test.subject.case_id not in exclude_subject_ids]
n_ctrl = 0
for test in tests:
x = []
if test.subject.label == 'ctrl':
n_ctrl += 1
if kind == 'dugger':
x += [test.subject.label == 'pd']
#x += [test.subject.expired_age-90]
#x += [test.subject.gender]
#if hasattr(test.subject,'dementia'):
# x += [test.subject.dementia]
#x += [test.subject.stint]
if hasattr(test.subject,'other'):
x += test.subject.other
x = [float(_) for _ in x]
labels[test.subject] = x
labels = [labels[key] for key in \
sorted(labels.keys(),key=lambda x:x.case_id)]
return np.array(labels)
def get_response_matrix(kind, options=['responses'], exclude_subjects={}):
responses = {}
subjects,tests = bbdp.load(kind)
exclude_subject_ids = []
for key,value in exclude_subjects.items():
exclude_subject_ids += [subject_id for subject_id,subject in subjects.items()\
if subject.__dict__[key]==value]
subjects = {subject_id:subject for subject_id,subject in subjects.items()\
if subject_id not in exclude_subject_ids}
tests = [test for test in tests if test.subject.case_id not in exclude_subject_ids]
question_nums = range(1,41)
possible_responses = [0,1,2,3]
for test in tests:
x = []
for q in question_nums:
if 'responses' in options:
response = []
actual_response = test.response_set.responses[q].choice_num
for possible_response in possible_responses:
if actual_response is possible_response:
x += [1]
else:
x += [0]
if 'responded' in options:
x += [test.response_set.responses[q].choice_num is not None]
if 'correct' in options:
x += [int(test.response_set.responses[q].correct)]
if 'total_correct' in options:
x += [sum([int(test.response_set.responses[q].correct) for q in question_nums])]
if 'fraction_correct' in options:
x += [sum([int(test.response_set.responses[q].correct) for q in question_nums])/40.0]
if 'total_responded' in options:
x += [sum([int(test.response_set.responses[q].choice_num is not None) for q in question_nums])]
if 'gender' in options:
x += [test.subject.gender]
if 'demented' in options:
try:
x += [test.subject.demented]
except:
x += [test.subject.dementia]
if 'expired_age' in options:
x += [test.subject.expired_age]
responses[test.subject] = x
ctrl = []
for key in sorted(responses.keys(),key=lambda x:x.case_id):
ctrl += [subjects[key.case_id].label == 'ctrl']
responses = np.array(list(responses[key] for key in \
sorted(responses.keys(),key=lambda x:x.case_id)),dtype='float')
if 'num_each_type' in options:
n = responses.shape[1]
for i in range(4):
responses = np.hstack((responses,responses[:,i:n:4].sum(axis=1).reshape(-1,1)))
return responses,ctrl
import ppmi
import bbdp
if __name__ == '__main__':
"""PPMI data"""
'''
ppmi_data = ppmi.load()
ppmi.plot_cumul_hist(ppmi_data,booklet=1)
ppmi.plot_cumul_hist(ppmi_data,booklet=2)
ppmi.plot_cumul_hist(ppmi_data,booklet=3)
ppmi.plot_cumul_hist(ppmi_data,booklet=4)
upsit.plt.show()
'''
"""BBDP data"""
subjects,tests = bbdp.load()
ctrl = []; pd = []
scores = {}
ctrl = []
pd = []
if 1:
for q in range(1,41):
scores[q] = {'ctrl':[],'pd':[]}
for test in tests:
correct = test.response_set.responses[q].correct
if test.is_control():
scores[q]['ctrl'].append(correct)
else:
scores[q]['pd'].append(correct)
def print_scores(kind):
import upsit
import ppmi
import bbdp
if __name__ == '__main__':
"""PPMI data"""
'''
ppmi_data = ppmi.load()
ppmi.plot_cumul_hist(ppmi_data,booklet=1)
ppmi.plot_cumul_hist(ppmi_data,booklet=2)
ppmi.plot_cumul_hist(ppmi_data,booklet=3)
ppmi.plot_cumul_hist(ppmi_data,booklet=4)
upsit.plt.show()
'''
"""BBDP data"""
subjects, tests = bbdp.load()
ctrl = []
pd = []
scores = {}
ctrl = []
pd = []
if 1:
for q in range(1, 41):
scores[q] = {'ctrl': [], 'pd': []}
for test in tests:
correct = test.response_set.responses[q].correct
if test.is_control():
scores[q]['ctrl'].append(correct)
else:
scores[q]['pd'].append(correct)
