def test_brls(self):
""" Validate estimation of BRLs at high SNR"""
pyhrf.verbose.set_verbosity(2)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['bold_response_levels'], fdata, nb_its=100,
check_fv='raise')
def test_prf(self):
""" Validate estimation of PRF """
pyhrf.verbose.set_verbosity(2)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['prf'], fdata, nb_its=100,
check_fv='raise')
def setUp(self):
np.random.seed(8652761)
tmpDir = tempfile.mkdtemp(prefix='pyhrf_tests',
dir=pyhrf.cfg['global']['tmp_path'])
self.tmp_dir = tmpDir
simu = simulate_asl(self.tmp_dir, spatial_size='random_small')
self.data_simu = FmriData.from_simulation_dict(simu)
def test_noise_var(self):
""" Validate estimation of noise variances at high SNR"""
pyhrf.verbose.set_verbosity(2)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['noise_var'], fdata, nb_its=100,
check_fv='raise')
def test_brf_physio_reg(self):
""" Validate estimation of BRF at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['brf'], fdata, nb_its=100,
check_fv='raise')
def test_prf(self):
""" Validate estimation of PRF """
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['prf'], fdata, simu, nItMax=20,
estimateG=True)
def test_perf_baseline(self):
""" Validate estimation of drift at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['perf_baseline'], fdata, nb_its=100,
check_fv='raise')
def test_prls(self):
""" Validate estimation of PRLs at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['perf_response_levels'], fdata, simu,
nItMax=100, estimateC=True)
def test_brf_physio_reg(self):
""" Validate estimation of BRF at high SNR"""
pyhrf.verbose.set_verbosity(2)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['brf'], fdata, nb_its=100,
check_fv='raise')
print 'pyhrf_view_qt3 %s/*brf*nii' %self.tmp_dir
def test_perf_baseline(self):
""" Validate estimation of drift at high SNR"""
pyhrf.verbose.set_verbosity(2)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['perf_baseline'], fdata, nb_its=100,
check_fv='raise')
print 'pyhrf_view_qt3 %s/*perf*nii' %self.tmp_dir
def test_prls(self):
""" Validate estimation of PRLs at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['perf_response_levels'], fdata, simu,
nItMax=100, estimateC=True)
def test_prf(self):
""" Validate estimation of PRF """
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['prf'], fdata, simu, nItMax=20,
estimateG=True)
def test_prf_var(self):
""" Validate estimation of PRF """
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['prf_var'], fdata, nb_its=20,
check_fv='raise')
def test_noise_var(self):
""" Validate estimation of noise variances at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['noise_var'], fdata, simu, nItMax=100,
estimateNoise=True)
print 'pyhrf_view %s/*noise*nii' % self.tmp_dir
def test_sigmaG(self):
""" Validate estimation of drift at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['sigma_G'], fdata, simu,
nItMax=100, estimateSigmaG=True)
print 'pyhrf_view %s/*mixt_params*perf*nii' % self.tmp_dir
def test_noise_var(self):
""" Validate estimation of noise variances at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['noise_var'], fdata, simu, nItMax=100,
estimateNoise=True)
print 'pyhrf_view %s/*noise*nii' % self.tmp_dir
def test_sigmaG(self):
""" Validate estimation of drift at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_parameters(['sigma_G'], fdata, simu,
nItMax=100, estimateSigmaG=True)
print 'pyhrf_view %s/*mixt_params*perf*nii' % self.tmp_dir
def test_brf_physio_nonreg(self):
""" Validate estimation of BRF at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['brf'], fdata, nb_its=100,
check_fv='raise',
rf_prior_type='physio_stochastic_not_regularized')
def test_prf_physio_det(self):
""" Validate estimation of BRF at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
print simu['prf'].shape
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['prf'], fdata, nb_its=100,
check_fv='raise',
rf_prior_type='physio_deterministic')
def test_prf_physio_nonreg(self):
""" Validate estimation of BRF at high SNR"""
pyhrf.verbose.set_verbosity(2)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
print simu['prf'].shape
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['prf'], fdata, nb_its=100,
check_fv='raise',
rf_prior_type='physio_stochastic_not_regularized')
print 'pyhrf_view_qt3 %s/*prf*nii' %self.tmp_dir
def test_all(self):
""" Validate estimation of full ASL model at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
np.random.seed(25430)
v = ['bold_response_levels', 'perf_response_levels', 'drift', 'drift_var',
'brf', 'brf_var', 'prf', 'labels', 'bold_mixt_params',
'perf_mixt_params', 'perf_baseline', 'perf_baseline_var']
self._test_specific_samplers(v, fdata, nb_its=500, check_fv='print')
def test_perfusion(self):
""" Validate estimation of perfusion component at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
np.random.seed(25430)
v = ['perf_response_levels', 'prf']
mem.cache(self._test_specific_parameters)(v, fdata, simu,
nItMax=100,
estimateG=True,
estimateC=True,
estimateSigmaG=True)
print 'pyhrf_view %s/*nii' % self.tmp_dir
def test_perf_baseline_var(self):
""" Validate estimation of drift at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
perf_baseline = simu['perf_baseline']
perf_baseline_mean = simu['perf_baseline_mean']
print 'perf_baseline_mean = ', perf_baseline_mean
print 'perf_baseline_mean emp = ', np.mean(perf_baseline)
perf_baseline_var = simu['perf_baseline_var']
print 'perf_baseline_var = ', perf_baseline_var
print 'perf_baseline_var emp = ', np.var(perf_baseline)
fdata = FmriData.from_simulation_dict(simu)
self._test_specific_samplers(['perf_baseline_var'], fdata, nb_its=15,
check_fv='raise')
def test_perfusion(self):
""" Validate estimation of perfusion component at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
np.random.seed(25430)
v = ['perf_response_levels', 'prf']
mem.cache(self._test_specific_parameters)(v, fdata, simu,
nItMax=100,
estimateG=True,
estimateC=True,
estimateSigmaG=True)
print 'pyhrf_view %s/*nii' % self.tmp_dir
def test_default_jde_small_simulation(self):
""" Test ASL sampler on small simulation with small nb of iterations.
Estimation accuracy is not tested.
"""
simu = simulate_asl(spatial_size='random_small')
fdata = FmriData.from_simulation_dict(simu)
sampler = jde_asl.ASLSampler()
analyser = JDEMCMCAnalyser(sampler=sampler, osfMax=4, dtMin=.4,
dt=.5, driftParam=4, driftType='polynomial',
outputPrefix='jde_mcmc_', randomSeed=None)
treatment = FMRITreatment(fmri_data=fdata, analyser=analyser,
output_dir=None)
treatment.run()
def test_all(self):
""" Validate estimation of full ASL model at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
np.random.seed(25430)
v = ['bold_response_levels', 'perf_response_levels',
'brf', 'brf_var', 'prf', 'labels', 'bold_mixt_params',
'perf_mixt_params', 'drift_perf_baseline']
self._test_specific_parameters(v, fdata, simu,
estimateSigmaH=False, nItMax=100,
nItMin=10, estimateBeta=True,
estimateSigmaG=True, PLOT=False,
constrained=True, fast=False,
estimateH=True, estimateG=True,
estimateA=True, estimateC=True,
estimateZ=True, estimateLA=True,
estimateMP=True)
print 'pyhrf_view %s/*nii' % self.tmp_dir
def test_all(self):
""" Validate estimation of full ASL model at high SNR"""
# pyhrf.verbose.set_verbosity(2)
pyhrf.logger.setLevel(logging.INFO)
from pyhrf.jde.asl import simulate_asl
simu = simulate_asl(self.tmp_dir, spatial_size='normal')
fdata = FmriData.from_simulation_dict(simu)
np.random.seed(25430)
v = ['bold_response_levels', 'perf_response_levels',
'brf', 'brf_var', 'prf', 'labels', 'bold_mixt_params',
'perf_mixt_params', 'drift_perf_baseline']
self._test_specific_parameters(v, fdata, simu,
estimateSigmaH=False, nItMax=100,
nItMin=10, estimateBeta=True,
estimateSigmaG=True, PLOT=False,
constrained=True, fast=False,
estimateH=True, estimateG=True,
estimateA=True, estimateC=True,
estimateZ=True, estimateLA=True,
estimateMP=True)
print 'pyhrf_view %s/*nii' % self.tmp_dir
def test_simulation(self):
# pyhrf.verbose.set_verbosity(0)
pyhrf.logger.setLevel(logging.WARNING)
simulate_asl(spatial_size='random_small')
def test_simulation(self):
pyhrf.verbose.set_verbosity(0)
simulate_asl(spatial_size='random_small')
def test_simulation(self):
simulate_asl(spatial_size='random_small')
