def main():
parser = argparse.ArgumentParser()
parser.add_argument('visits', nargs='+', type=str, help='the viscodes to be sampled')
parser.add_argument('-m', '--method', choices=DataHandler.get_method_choices(), default='all',
help='the method to collect data for')
parser.add_argument('-b', '--biomarkers', nargs='+', default=None, help='name of the biomarker to be plotted')
parser.add_argument('-p', '--phase', default=None, choices=DataHandler.get_phase_choices(),
help='the phase for which the model is to be trained')
parser.add_argument('--estimate_dprs', action='store_true', help='recompute the dpis estimations')
parser.add_argument('--recompute_estimates', action='store_true', help='recompute the dpis estimations')
parser.add_argument('--consistent_data', action='store_true', help='us only subjects with bl, m12 and m24 visits')
parser.add_argument('--no_plot', action='store_true', help='do not plot the results')
parser.add_argument('--plot_lines', action='store_true', help='plot graphs instead of matrix')
parser.add_argument('--plot_steps', type=int, default=15, help='number of steps for the DPI scale')
parser.add_argument('--plot_file', type=str, default=None, help='filename of the output file')
parser.add_argument('--plot_cmap_jet', action='store_true', help='use the colour map jet')
args = parser.parse_args()
# Get estimates
_, diagnoses, dpis, dprs, mean_min, mean_max = et.get_progress_estimates(
args.visits,
method=args.method,
biomarkers=args.biomarkers,
phase=args.phase,
estimate_dprs=args.estimate_dprs,
recompute_estimates=args.recompute_estimates,
select_test_set=True,
consistent_data=args.consistent_data)
# Plot results
if not args.no_plot:
plot_dpi_estimates(args, dpis, diagnoses, mean_min, mean_max)
if args.estimate_dprs:
plot_dpi_dpr_distribution(args, dpis, dprs, diagnoses)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('visits', nargs='+', type=str, help='the viscodes to be sampled')
parser.add_argument('-m', '--method', choices=DataHandler.get_method_choices(), default='all', help='the method to collect data for')
parser.add_argument('-b', '--biomarkers', nargs='+', default=None, help='name of the biomarker to be plotted')
parser.add_argument('-p', '--phase', default=None, choices=DataHandler.get_phase_choices(), help='the phase for which the model is to be trained')
parser.add_argument('-c', '--classifier', default='svm', choices=['lda', 'svm', 'lsvm', 'rf'], help='the approach used to classify the subjects')
parser.add_argument('--estimate_dprs', action='store_true', help='recompute the dpis estimations')
parser.add_argument('--recompute_estimates', action='store_true', help='recompute the dpis estimations')
parser.add_argument('--consistent_data', action='store_true', help='us only subjects with bl, m12 and m24 visits')
parser.add_argument('--num_folds', type=int, default=10, help='number of folds for the n-fold cross validation')
parser.add_argument('--latex_file', type=str, default=None, help='add output to a LaTeX file')
args = parser.parse_args()
# Get estimates
rids, diagnoses, dpis, dprs, _, _ = et.get_progress_estimates(
args.visits,
method=args.method,
biomarkers=args.biomarkers,
phase=args.phase,
estimate_dprs=args.estimate_dprs,
recompute_estimates=args.recompute_estimates,
consistent_data=args.consistent_data)
# Select converters and non-converters sets
rcds, non_rcds = get_rcds(args, rids, diagnoses, dpis, dprs)
rfds, non_rfds = get_rfds(args, rids, diagnoses, dpis, dprs)
# Analyse output
analyse_decline(args, rids, dpis, dprs, rcds, non_rcds)
analyse_decline(args, rids, dpis, dprs, rfds, non_rfds)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('-p', '--phase', default=None, choices=DataHandler.get_phase_choices(), help='the phase for which the model is to be trained')
parser.add_argument('--consistent_data', action='store_true', help='us only subjects with bl, m12 and m24 visits')
parser.add_argument('--estimate_dprs', action='store_true', help='estimate dpis and dprs')
parser.add_argument('--recompute_estimates', action='store_true', help='recompute the dpi / dpr estimations')
parser.add_argument('--recompute_predictions', action='store_true', help='recompute the biomarker predictions')
parser.add_argument('--exclude_cn', action='store_true', help='exclude healthy subjects from analysis')
args = parser.parse_args()
estimates = {}
methods = ['cog', 'vol', 'ml', 'img', 'all']
for method in methods:
estimates.update({method: {}})
for visits in [['bl'], ['m12'], ['m24'], ['bl', 'm12'], ['m12', 'm24']]:
_, diagnoses, dpis, _, _, _ = et.get_progress_estimates(visits,
method=method,
phase=args.phase,
estimate_dprs=args.estimate_dprs)
diagnoses = np.array(diagnoses)
dpis = np.array(dpis)
visits_string = '_'.join(visits)
estimates[method].update({visits_string: {}})
estimates[method][visits_string].update({'CN': np.mean(dpis[np.where(diagnoses == 0.0)])})
estimates[method][visits_string].update({'EMCI': np.mean(dpis[np.where(diagnoses == 0.25)])})
estimates[method][visits_string].update({'LMCI': np.mean(dpis[np.where(diagnoses == 0.75)])})
estimates[method][visits_string].update({'AD': np.mean(dpis[np.where(diagnoses == 1.0)])})
for method in methods:
print log.INFO, 'Results for {0}'.format(method)
for diagnosis in ['CN', 'EMCI', 'LMCI', 'AD']:
print log.RESULT, '{0: <4}: {1:.2f} {2:.2f} | {3:.2f} '.format(
diagnosis,
estimates[method]['m12'][diagnosis] - estimates[method]['bl'][diagnosis],
estimates[method]['m24'][diagnosis] - estimates[method]['m12'][diagnosis],
estimates[method]['m12_m24'][diagnosis] - estimates[method]['bl_m12'][diagnosis])
def main():
parser = argparse.ArgumentParser()
parser.add_argument('visits',
nargs='+',
type=str,
help='the viscodes to be sampled')
parser.add_argument('-m',
'--method',
choices=DataHandler.get_method_choices(),
default='all',
help='the method to collect data for')
parser.add_argument('-b',
'--biomarkers',
nargs='+',
default=None,
help='name of the biomarker to be plotted')
parser.add_argument('-p',
'--phase',
default=None,
choices=DataHandler.get_phase_choices(),
help='the phase for which the model is to be trained')
parser.add_argument('--estimate_dprs',
action='store_true',
help='recompute the dpis estimations')
parser.add_argument('--recompute_estimates',
action='store_true',
help='recompute the dpis estimations')
parser.add_argument('--consistent_data',
action='store_true',
help='us only subjects with bl, m12 and m24 visits')
parser.add_argument('--no_plot',
action='store_true',
help='do not plot the results')
parser.add_argument('--plot_lines',
action='store_true',
help='plot graphs instead of matrix')
parser.add_argument('--plot_steps',
type=int,
default=15,
help='number of steps for the DPI scale')
parser.add_argument('--plot_file',
type=str,
default=None,
help='filename of the output file')
parser.add_argument('--plot_cmap_jet',
action='store_true',
help='use the colour map jet')
args = parser.parse_args()
# Get estimates
_, diagnoses, dpis, dprs, mean_min, mean_max = et.get_progress_estimates(
args.visits,
method=args.method,
biomarkers=args.biomarkers,
phase=args.phase,
estimate_dprs=args.estimate_dprs,
recompute_estimates=args.recompute_estimates,
select_test_set=True,
consistent_data=args.consistent_data)
# Plot results
if not args.no_plot:
plot_dpi_estimates(args, dpis, diagnoses, mean_min, mean_max)
if args.estimate_dprs:
plot_dpi_dpr_distribution(args, dpis, dprs, diagnoses)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('visits',
nargs='+',
type=str,
help='the viscodes to be sampled')
parser.add_argument('-m',
'--method',
choices=DataHandler.get_method_choices(),
default='all',
help='the method to collect data for')
parser.add_argument('-b',
'--biomarkers',
nargs='+',
default=None,
help='name of the biomarker to be plotted')
parser.add_argument('-p',
'--phase',
default=None,
choices=DataHandler.get_phase_choices(),
help='the phase for which the model is to be trained')
parser.add_argument('-c',
'--classifier',
default='svm',
choices=['lda', 'svm', 'lsvm', 'rf'],
help='the approach used to classify the subjects')
parser.add_argument('--estimate_dprs',
action='store_true',
help='recompute the dpis estimations')
parser.add_argument('--recompute_estimates',
action='store_true',
help='recompute the dpis estimations')
parser.add_argument('--consistent_data',
action='store_true',
help='us only subjects with bl, m12 and m24 visits')
parser.add_argument('--num_folds',
type=int,
default=10,
help='number of folds for the n-fold cross validation')
parser.add_argument(
'--num_runs',
type=int,
default=1,
help='number of runs the x-fold cross-validation is performed')
parser.add_argument('--latex_file',
type=str,
default=None,
help='add output to a LaTeX file')
args = parser.parse_args()
# Get estimates
_, diagnoses, dpis, dprs, _, _ = et.get_progress_estimates(
args.visits,
method=args.method,
biomarkers=args.biomarkers,
phase=args.phase,
estimate_dprs=args.estimate_dprs,
recompute_estimates=args.recompute_estimates,
consistent_data=args.consistent_data)
# Analyse estimates
classify_diagnoses(args, dpis, dprs, diagnoses)