本文整理汇总了Python中pyhrf.get_tmp_path函数的典型用法代码示例。如果您正苦于以下问题：Python get_tmp_path函数的具体用法？Python get_tmp_path怎么用？Python get_tmp_path使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了get_tmp_path函数的20个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: setUp
def setUp(self):
pyhrf.verbose.set_verbosity(0)
np.random.seed(8652761)
self.tmp_dir = pyhrf.get_tmp_path()
开发者ID:Solvi，项目名称:pyhrf，代码行数:7，代码来源:jdetest.py
示例2: _test_spm_option_parse
def _test_spm_option_parse(self, spm_ver):
"""
Test parsing of option "-s SPM.mat" with given SPM version (int)
"""
spm_file = op.join(pyhrf.get_tmp_path(), 'SPM.mat')
tools._io._zip.gunzip(pyhrf.get_data_file_name('SPM_v%d.mat.gz' % spm_ver),
outFileName=spm_file)
options = ['-s', spm_file]
from optparse import OptionParser
parser = OptionParser()
ptr.append_common_treatment_options(parser)
fd = ptr.parse_data_options(parser.parse_args(options)[0])
self.assertEqual(fd.tr, 2.4) # nb sessions
p = fd.paradigm
# nb sessions
self.assertEqual(len(p.stimOnsets[p.stimOnsets.keys()[0]]), 2)
npt.assert_almost_equal(p.stimOnsets['audio'][0],
ppar.onsets_loc_av['audio'][0])
npt.assert_almost_equal(p.stimOnsets['audio'][1],
ppar.onsets_loc_av['audio'][0])
npt.assert_almost_equal(p.stimOnsets['video'][1],
ppar.onsets_loc_av['video'][0])
开发者ID:ainafp，项目名称:pyhrf，代码行数:25，代码来源:test_treatment.py
示例3: remote_dir_is_writable
def remote_dir_is_writable(user, hosts, path):
"""
Test if *path* is writable from each host in *hosts*. Sending bash
commands to each host via ssh using the given *user* login.
Args:
"""
import os.path as op
import pyhrf
mode = 'dispatch'
cmds = ['bash -c "echo -n \"[write_test]:%d:\"; '\
'if [ -w %s ]; then echo \"OK\"; else echo \"NOTOK\"; fi;"' \
%(ih, path) for ih in range(len(hosts))]
tasks = read_tasks(cmds, mode)
timeslot = read_timeslot('allday')
tmp_dir = pyhrf.get_tmp_path()
brokenfile = op.join(tmp_dir, 'pyhrf-broken_cmd.batch')
logfile = op.join(tmp_dir, 'pyhrf-parallel.log')
run_grid(mode, hosts, 'rsa', tasks, timeslot, brokenfile,
logfile, user=user)
kill_threads()
log = open(logfile).readlines()
res = [False] * len(hosts)
for line in log:
if line.startswith('[write_test]'):
#print line
_,ih,r = line.strip('\n').split(':')
res[int(ih)] = ('OK' in r)
return res
开发者ID:Solvi，项目名称:pyhrf，代码行数:35，代码来源:grid.py
示例4: _test_load_regnames
def _test_load_regnames(self, spm_ver):
spm_file = op.join(pyhrf.get_tmp_path(), 'SPM.mat')
pio._zip.gunzip(pyhrf.get_data_file_name('SPM_v%d.mat.gz' % spm_ver),
outFileName=spm_file)
expected = ['Sn(1) audio*bf(1)', 'Sn(1) video*bf(1)',
'Sn(2) audio*bf(1)', 'Sn(2) video*bf(1)',
'Sn(1) constant', 'Sn(2) constant']
self.assertEqual(pio.spmio.load_regnames(spm_file), expected)
开发者ID:rcherbonnier，项目名称:pyhrf，代码行数:8，代码来源:iotest.py
示例5: setUp
def setUp(self):
cache_dir = tempfile.mkdtemp(prefix='pyhrf_validate',
dir=pyhrf.cfg['global']['tmp_path'])
mem = Memory(cache_dir)
np.random.seed(8652761)
self.tmp_dir = pyhrf.get_tmp_path()
self.clean_tmp = True
开发者ID:pyhrf，项目名称:pyhrf，代码行数:8，代码来源:valid_jde_vem_asl.py
示例6: setUp
def setUp(self):
self.tmp_dir = pyhrf.get_tmp_path()
simu = simulate_sessions(output_dir=self.tmp_dir,
snr_scenario='high_snr',
spatial_size='random_small')
self.data_simu = merge_fmri_sessions(simu)
开发者ID:ainafp，项目名称:pyhrf，代码行数:8，代码来源:jdetest.py
示例7: setUp
def setUp(self):
np.random.seed(8652761)
self.simu_dir = pyhrf.get_tmp_path()
# Parameters to setup a Sampler where all samplers are OFF and
# set to their true values.
# This is used by the function _test_specific_samplers,
# which will turn on specific samplers to test.
self.sampler_params_for_single_test = {
'nb_iterations': 40,
'smpl_hist_pace': -1,
'obs_hist_pace': -1,
# HRF by subject
'hrf_subj': jms.HRF_Sampler(do_sampling=False,
normalise=1.,
use_true_value=True,
zero_contraint=False,
prior_type='singleHRF'),
# HRF variance
'hrf_var_subj': jms.HRFVarianceSubjectSampler(do_sampling=False,
use_true_value=True),
# HRF group
'hrf_group': jms.HRF_Group_Sampler(do_sampling=False,
normalise=1.,
use_true_value=True,
zero_contraint=False,
prior_type='singleHRF'),
# HRF variance
'hrf_var_group': jms.RHGroupSampler(do_sampling=False,
use_true_value=True),
# neural response levels (stimulus-induced effects) by subject
'response_levels': jms.NRLs_Sampler(do_sampling=False,
use_true_value=True),
'labels': jms.LabelSampler(do_sampling=False,
use_true_value=True),
# drift
'drift': jms.Drift_MultiSubj_Sampler(do_sampling=False,
use_true_value=True),
# drift variance
'drift_var': jms.ETASampler_MultiSubj(do_sampling=False,
use_true_value=True),
# noise variance
'noise_var':
jms.NoiseVariance_Drift_MultiSubj_Sampler(do_sampling=False,
use_true_value=False),
# weights o fthe mixture
# parameters of the mixture
'mixt_params': jms.MixtureParamsSampler(do_sampling=False,
use_true_value=False),
#'alpha_subj' : Alpha_hgroup_Sampler(dict_alpha_single),
#'alpha_var_subj' : AlphaVar_Sampler(dict_alpha_var_single),
'check_final_value': 'none', # print or raise
}
开发者ID:pyhrf，项目名称:pyhrf，代码行数:57，代码来源:test_jde_multi_subj.py
示例8: setUp
def setUp(self):
tag = "subj0_%s.nii.gz"
self.func_file = pyhrf.get_data_file_name(tag % "bold_session0")
self.anatomy_file = pyhrf.get_data_file_name(tag % "anatomy")
self.roi_mask_file = pyhrf.get_data_file_name(tag % "parcellation")
self.ax_slice = 24
self.sag_slice = 7
self.cor_slice = 34
self.tmp_dir = pyhrf.get_tmp_path() #'./'
开发者ID:philouc，项目名称:pyhrf，代码行数:11，代码来源:test_plot.py
示例9: setUp
def setUp(self):
tag = 'subj0_%s.nii.gz'
self.func_file = pyhrf.get_data_file_name(tag%'bold_session0')
self.anatomy_file = pyhrf.get_data_file_name(tag%'anatomy')
self.roi_mask_file = pyhrf.get_data_file_name(tag%'parcellation')
self.ax_slice = 24
self.sag_slice = 7
self.cor_slice = 34
self.tmp_dir = pyhrf.get_tmp_path() #'./'
开发者ID:thomas-vincent，项目名称:pyhrf，代码行数:11，代码来源:test_plot.py
示例10: setUp
def setUp(self):
np.random.seed(8652761)
self.tmp_dir = pyhrf.get_tmp_path()
self.clean_tmp = True
self.sampler_params_for_single_test = {
'nb_iterations': 40,
'smpl_hist_pace': 1,
'obs_hist_pace': 1,
'brf': jasl.PhysioBOLDResponseSampler(do_sampling=False,
normalise=1.,
use_true_value=True,
zero_constraint=False),
'brf_var':
jasl.PhysioBOLDResponseVarianceSampler(do_sampling=False,
val_ini=np.array([0.1]),
use_true_value=False),
'prf': jasl.PhysioPerfResponseSampler(do_sampling=False,
normalise=1.,
use_true_value=True,
zero_constraint=False,
prior_type='physio_stochastic_regularized'),
'prf_var':
jasl.PhysioPerfResponseVarianceSampler(do_sampling=False,
val_ini=np.array(
[.001]),
use_true_value=False),
'noise_var': jasl.NoiseVarianceSampler(do_sampling=False,
use_true_value=True),
'drift_var': jasl.DriftVarianceSampler(do_sampling=False,
use_true_value=True),
'drift': jasl.DriftCoeffSampler(do_sampling=False,
use_true_value=True),
'bold_response_levels':
jasl.BOLDResponseLevelSampler(do_sampling=False,
use_true_value=True),
'perf_response_levels':
jasl.PerfResponseLevelSampler(do_sampling=False,
use_true_value=True),
'labels': jasl.LabelSampler(do_sampling=False,
use_true_value=True),
'bold_mixt_params': jasl.BOLDMixtureSampler(do_sampling=False,
use_true_value=True),
'perf_mixt_params': jasl.PerfMixtureSampler(do_sampling=False,
use_true_value=True),
'perf_baseline': jasl.PerfBaselineSampler(do_sampling=False,
use_true_value=True),
'perf_baseline_var':
jasl.PerfBaselineVarianceSampler(do_sampling=False,
use_true_value=True),
'check_final_value': 'raise', # print or raise
}
开发者ID:pyhrf，项目名称:pyhrf，代码行数:53，代码来源:valid_jde_asl_physio.py
示例11: dump_roi_datasets
def dump_roi_datasets(self, dry=False, output_dir=None):
pyhrf.verbose(1,'Loading data ...')
# if no file to dump (dry), assume it's only to get file names,
# then don't build the graph (could take some time ...)
if not dry:
self.data.build_graphs()
explData = self.analyser.split_data(self.data)
files = []
roiIds = []
if output_dir is not None:
roi_data_out_dir = output_dir
else:
if self.output_dir is not None:
roi_data_out_dir = op.join(self.output_dir, 'ROI_datasets')
else:
roi_data_out_dir = op.join(pyhrf.get_tmp_path(), 'ROI_datasets')
if not op.exists(roi_data_out_dir): os.makedirs(roi_data_out_dir)
assert op.exists(roi_data_out_dir)
if not dry:
pyhrf.verbose(1,'Dump roi data in dir %s' %roi_data_out_dir)
#data_order = sorted([d.get_nb_vox_in_mask() for d in explData])
pyhrf.verbose(1,'Dump of roi data, ordering by size ...')
cmp_size = lambda e1,e2:cmp(e1.get_nb_vox_in_mask(),
e2.get_nb_vox_in_mask())
for edata in sorted(explData, cmp=cmp_size, reverse=True):
roiId = edata.get_roi_id()
fn = op.abspath(op.join(roi_data_out_dir,
"roidata_%04d.pck" %roiId))
roiIds.append(roiId)
if not dry:
f = open(fn ,'w')
cPickle.dump(edata, f)
f.close()
files.append(fn)
pyhrf.verbose(1,'Dump of roi data done.')
return files, roiIds
开发者ID:pmesejo，项目名称:pyhrf，代码行数:43，代码来源:treatment.py
示例12: setUp
def setUp(self):
from pyhrf.ndarray import MRI3Daxes
self.tmp_dir = pyhrf.get_tmp_path()
self.p1 = np.array([[[1, 1, 1, 3],
[1, 1, 3, 3],
[0, 1, 2, 2],
[0, 2, 2, 2],
[0, 0, 2, 4]]], dtype=np.int32)
self.p1_fn = op.join(self.tmp_dir, 'p1.nii')
xndarray(self.p1, axes_names=MRI3Daxes).save(self.p1_fn)
self.p2 = self.p1 * 4.5
self.p2_fn = op.join(self.tmp_dir, 'p2.nii')
xndarray(self.p2, axes_names=MRI3Daxes).save(self.p2_fn)
self.mask = (self.p1 > 0).astype(np.int32)
self.mask_fn = op.join(self.tmp_dir, 'mask.nii')
xndarray(self.mask, axes_names=MRI3Daxes).save(self.mask_fn)
开发者ID:pyhrf，项目名称:pyhrf，代码行数:20，代码来源:test_parcellation.py
示例13: make_parcellation_cubed_blobs_from_file
def make_parcellation_cubed_blobs_from_file(parcellation_file, output_path,
roi_ids=None, bg_parcel=0,
skip_existing=False):
p,mp = read_volume(parcellation_file)
p = p.astype(np.int32)
if bg_parcel==0 and p.min() == -1:
p += 1 #set background to 0
if roi_ids is None:
roi_ids = np.unique(p)
pyhrf.verbose(1,'%d rois to extract' %(len(roi_ids)-1))
tmp_dir = pyhrf.get_tmp_path('blob_parcellation')
tmp_parcel_mask_file = op.join(tmp_dir, 'parcel_for_blob.nii')
out_files = []
for roi_id in roi_ids:
if roi_id != bg_parcel: #discard background
output_blob_file = op.join(output_path, 'parcel_%d_cubed_blob.arg'\
%roi_id)
out_files.append(output_blob_file)
if skip_existing and os.path.exists(output_blob_file):
continue
parcel_mask = (p==roi_id).astype(np.int32)
write_volume(parcel_mask, tmp_parcel_mask_file, mp)
pyhrf.verbose(3,'Extract ROI %d -> %s' %(roi_id,output_blob_file))
cmd = 'AimsGraphConvert -i %s -o %s --bucket' \
%(tmp_parcel_mask_file, output_blob_file)
pyhrf.verbose(3,'Cmd: %s' %(cmd))
os.system(cmd)
if op.exists(tmp_parcel_mask_file):
os.remove(tmp_parcel_mask_file)
return out_files
开发者ID:pmesejo，项目名称:pyhrf，代码行数:37，代码来源:parcellation.py
示例14: setUp
def setUp(self):
#pyhrf.verbose.set_verbosity(2)
np.random.seed(8652761)
# tmpDir = tempfile.mkdtemp(prefix='pyhrf_tests',
# dir=pyhrf.cfg['global']['tmp_path'])
self.tmp_outputs = True #save outputs in tmp dir
#if False then save in current dir
if not self.tmp_outputs:
self.tmp_dir_small = './JDE_MS_test_small_simu'
if not op.exists(self.tmp_dir_small): os.makedirs(self.tmp_dir_small)
self.tmp_dir_big = './JDE_MS_test_big_simu'
if not op.exists(self.tmp_dir_big): os.makedirs(self.tmp_dir_big)
else:
self.tmp_dir_small = pyhrf.get_tmp_path()
self.tmp_dir_big = pyhrf.get_tmp_path()
simu = simulate_sessions(output_dir = self.tmp_dir_small,
snr_scenario='high_snr', spatial_size='tiny')
self.data_small_simu = merge_fmri_sessions(simu)
simu = simulate_sessions(output_dir=self.tmp_dir_big,
snr_scenario='low_snr', spatial_size='normal')
self.data_simu = merge_fmri_sessions(simu)
# Parameters for multi-sessions sampler
dict_beta_single = {
BetaSampler.P_VAL_INI : np.array([0.5]),
BetaSampler.P_SAMPLE_FLAG : False,
BetaSampler.P_PARTITION_FUNCTION_METH : 'es',
BetaSampler.P_USE_TRUE_VALUE : False,
}
dict_hrf_single = {
HRF_MultiSess_Sampler.P_SAMPLE_FLAG : False,
HRF_MultiSess_Sampler.P_NORMALISE : 1., # normalise samples
HRF_MultiSess_Sampler.P_USE_TRUE_VALUE : True,
HRF_MultiSess_Sampler.P_ZERO_CONSTR : True,
#HRF_MultiSess_Sampler.P_PRIOR_TYPE : 'singleHRF',
}
dict_var_hrf_single = {
RHSampler.P_SAMPLE_FLAG : False,
RHSampler.P_VAL_INI : np.array([0.001]),
}
dict_nrl_sess_single = {
NRL_Multi_Sess_Sampler.P_SAMPLE_FLAG : False,
NRL_Multi_Sess_Sampler.P_USE_TRUE_VALUE : True,
}
dict_nrl_sess_var_single = {
Variance_GaussianNRL_Multi_Sess.P_SAMPLE_FLAG : False,
Variance_GaussianNRL_Multi_Sess.P_USE_TRUE_VALUE : True,
}
dict_nrl_bar_single = {
NRLsBar_Drift_Multi_Sess_Sampler.P_SAMPLE_FLAG : False,
NRLsBar_Drift_Multi_Sess_Sampler.P_USE_TRUE_NRLS : True,
NRLsBar_Drift_Multi_Sess_Sampler.P_SAMPLE_LABELS : False,
NRLsBar_Drift_Multi_Sess_Sampler.P_USE_TRUE_LABELS : True,
}
dict_drift_single = {
Drift_MultiSess_Sampler.P_SAMPLE_FLAG : False,
Drift_MultiSess_Sampler.P_USE_TRUE_VALUE : True,
}
dict_drift_var_single = {
ETASampler_MultiSess.P_SAMPLE_FLAG : False,
ETASampler_MultiSess.P_USE_TRUE_VALUE : True,
}
dict_noise_var_single = {
NoiseVariance_Drift_Multi_Sess_Sampler.P_SAMPLE_FLAG : False,
NoiseVariance_Drift_Multi_Sess_Sampler.P_USE_TRUE_VALUE : True,
}
dict_mixt_param_single = {
BiGaussMixtureParamsSampler.P_SAMPLE_FLAG : False,
BiGaussMixtureParamsSampler.P_USE_TRUE_VALUE : True,
BiGaussMixtureParamsSampler.P_HYPER_PRIOR : 'Jeffrey',
}
self.sampler_params_for_single_test = {
BMSS.P_NB_ITERATIONS : 100,
BMSS.P_SMPL_HIST_PACE : -1,
BMSS.P_OBS_HIST_PACE : -1,
# level of spatial correlation = beta
BMSS.P_BETA : BetaSampler(dict_beta_single),
# HRF
BMSS.P_HRF : HRF_MultiSess_Sampler(dict_hrf_single),
# HRF variance
BMSS.P_RH : RHSampler(dict_var_hrf_single),
# neural response levels (stimulus-induced effects) by session
#.........这里部分代码省略.........
开发者ID:pmesejo，项目名称:pyhrf，代码行数:101，代码来源:valid_jde_bold_mono_subj_multi_sess.py
示例15: setUp
def setUp(self):
np.random.seed(8652761)
self.tmp_dir = pyhrf.get_tmp_path()
开发者ID:pyhrf，项目名称:pyhrf，代码行数:3，代码来源:jdetest.py
示例16: project_fmri_from_kernels
def project_fmri_from_kernels(input_mesh, kernels_file, fmri_data_file, output_tex, bin_threshold=None):
logger.info("Project data onto mesh using kernels ...")
if 0:
print "Projecting ..."
print "func data:", fmri_data_file
print "Mesh file:", input_mesh
print "Save as:", output_tex
logger.info("Call AimsFunctionProjection -op 1 ...")
data_files = []
output_texs = []
p_ids = None
if bin_threshold is not None:
d, h = read_volume(fmri_data_file)
if np.allclose(d.astype(int), d):
tmp_dir = pyhrf.get_tmp_path()
p_ids = np.unique(d)
logger.info("bin threshold: %f", bin_threshold)
logger.info("pids(n=%d): %d...%d", len(p_ids), min(p_ids), max(p_ids))
for i, p_id in enumerate(p_ids):
if p_id != 0:
new_p = np.zeros_like(d)
new_p[np.where(d == p_id)] = i + 1 # 0 is background
ifn = op.join(tmp_dir, "pmask_%d.nii" % p_id)
write_volume(new_p, ifn, h)
data_files.append(ifn)
ofn = op.join(tmp_dir, "ptex_%d.gii" % p_id)
output_texs.append(ofn)
else:
data_files.append(fmri_data_file)
output_texs.append(output_tex)
else:
data_files.append(fmri_data_file)
output_texs.append(output_tex)
logger.info("input data files: %s", str(data_files))
logger.info("output data files: %s", str(output_texs))
for data_file, o_tex in zip(data_files, output_texs):
projection = [
"AimsFunctionProjection",
"-op",
"1",
"-d",
kernels_file,
"-d1",
data_file,
"-m",
input_mesh,
"-o",
o_tex,
]
cmd = " ".join(map(str, projection))
logger.info("cmd: %s", cmd)
os.system(cmd)
if bin_threshold is not None:
logger.info("Binary threshold of texture at %f", bin_threshold)
o_tex = output_texs[0]
data, data_gii = read_texture(o_tex)
data = (data > bin_threshold).astype(np.int32)
print "data:", data.dtype
if p_ids is not None:
for pid, o_tex in zip(p_ids[1:], output_texs[1:]):
pdata, pdata_gii = read_texture(o_tex)
data += (pdata > bin_threshold).astype(np.int32) * pid
# assert (np.unique(data) == p_ids).all()
write_texture(data, output_tex, intent="NIFTI_INTENT_LABEL")
开发者ID:pyhrf，项目名称:pyhrf，代码行数:73，代码来源:surface.py
示例17: setUp
def setUp(self):
self.tmp_dir = pyhrf.get_tmp_path() #'./'
开发者ID:Solvi，项目名称:pyhrf，代码行数:2，代码来源:test_xml.py
示例18: project_fmri_from_kernels
def project_fmri_from_kernels(input_mesh, kernels_file, fmri_data_file,
output_tex, bin_threshold=None, ):
pyhrf.verbose(2,'Project data onto mesh using kernels ...')
if 0:
print 'Projecting ...'
print 'func data:', fmri_data_file
print 'Mesh file:', input_mesh
print 'Save as:', output_tex
pyhrf.verbose(2,'Call AimsFunctionProjection -op 1 ...')
data_files = []
output_texs = []
p_ids = None
if bin_threshold is not None:
d,h = read_volume(fmri_data_file)
if np.allclose(d.astype(int), d):
tmp_dir = pyhrf.get_tmp_path()
p_ids = np.unique(d)
pyhrf.verbose(2, 'bin threshold: %f' %bin_threshold)
pyhrf.verbose(2, 'pids(n=%d): %d...%d' \
%(len(p_ids),min(p_ids),max(p_ids)))
for i,p_id in enumerate(p_ids):
if p_id != 0:
new_p = np.zeros_like(d)
new_p[np.where(d==p_id)] = i + 1 #0 is background
ifn = op.join(tmp_dir,'pmask_%d.nii'%p_id)
write_volume(new_p, ifn, h)
data_files.append(ifn)
ofn = op.join(tmp_dir,'ptex_%d.gii'%p_id)
output_texs.append(ofn)
else:
data_files.append(fmri_data_file)
output_texs.append(output_tex)
else:
data_files.append(fmri_data_file)
output_texs.append(output_tex)
pyhrf.verbose(3, 'input data files: %s' %str(data_files))
pyhrf.verbose(3, 'output data files: %s' %str(output_texs))
for data_file, o_tex in zip(data_files, output_texs):
projection = [
'AimsFunctionProjection',
'-op', '1',
'-d', kernels_file,
'-d1', data_file,
'-m', input_mesh,
'-o', o_tex
]
cmd = ' '.join(map(str,projection))
pyhrf.verbose(3, 'cmd: %s' %cmd)
os.system(cmd)
if bin_threshold is not None:
pyhrf.verbose(2, 'Binary threshold of texture at %f' %bin_threshold)
o_tex = output_texs[0]
data,data_gii = read_texture(o_tex)
data = (data>bin_threshold).astype(np.int32)
print 'data:', data.dtype
if p_ids is not None:
for pid, o_tex in zip(p_ids[1:], output_texs[1:]):
pdata,pdata_gii = read_texture(o_tex)
data += (pdata>bin_threshold).astype(np.int32) * pid
#assert (np.unique(data) == p_ids).all()
write_texture(data, output_tex, intent='NIFTI_INTENT_LABEL')
开发者ID:Solvi，项目名称:pyhrf，代码行数:70，代码来源:surface.py
示例19: Pipeline
from pyhrf import get_tmp_path
import numpy as np
import pyhrf.boldsynth.scenarios as simu
from pyhrf.tools import Pipeline
simulation_steps = {
'dt' : 0.6,
'dsf' : 4, #downsampling factor -> tr = dt * dsf = 2.4
'mask' : np.array([[[1,1,1,1,1,1,1]]]),
'labels' : np.array([[0,0,1,1,0,1,1]]),
'mean_act' : 3.,
'var_act' : 0.5,
'mean_inact' : 0.,
'var_inact' : 0.5,
'nrls' : simu.create_bigaussian_nrls,
'rastered_paradigm' : np.array([[0,0,1,0,0,0,1,0]]),
'hrf' : simu.create_canonical_hrf,
'v_noise' : 1.,
'bold_shape' : simu.get_bold_shape,
'noise' : simu.create_gaussian_noise,
'stim_induced_signal' : simu.create_stim_induced_signal,
'bold' : simu.create_bold,
}
simulation = Pipeline(simulation_steps)
simulation.resolve()
simulation_items = simulation.get_values()
output_dir = get_tmp_path()
print 'Save simulation to:', output_dir
simu.save_simulation(simulation_items, output_dir=output_dir)
开发者ID:Solvi，项目名称:pyhrf，代码行数:30，代码来源:artificial_data_dummy.py
示例20: setUp
def setUp(self):
pyhrf.verbose.set_verbosity(0)
np.random.seed(8652761)
#self.simu_dir = './simulation'
#if not op.exists(self.simu_dir): os.makedirs(self.simu_dir)
self.simu_dir = pyhrf.get_tmp_path()
# Parameters to setup a Sampler where all samplers are OFF and
# set to their true values.
# This is used by the function _test_specific_samplers,
# which will turn on specific samplers to test.
self.sampler_params_for_single_test = {
BMSS.P_NB_ITERATIONS : 40,
BMSS.P_SMPL_HIST_PACE : -1,
BMSS.P_OBS_HIST_PACE : -1,
# level of spatial correlation = beta
#BMSS.P_BETA : BetaSampler(dict_beta_single),
# HRF by subject
BMSS.P_HRF_SUBJ : jms.HRF_Sampler(do_sampling=False,
normalise=1.,
use_true_value=True,
zero_contraint=False,
prior_type='singleHRF'),
# HRF variance
BMSS.P_RH_SUBJ : jms.HRFVarianceSubjectSampler(do_sampling=False,
use_true_value=True),
# HRF group
BMSS.P_HRF_GROUP : jms.HRF_Group_Sampler(do_sampling=False,
normalise=1.,
use_true_value=True,
zero_contraint=False,
prior_type='singleHRF'),
# HRF variance
BMSS.P_RH_GROUP : jms.RHGroupSampler(do_sampling=False,
use_true_value=True),
# neural response levels (stimulus-induced effects) by subject
BMSS.P_NRLS_SUBJ : jms.NRLs_Sampler(do_sampling=False,
use_true_value=True),
BMSS.P_LABELS : jms.LabelSampler(do_sampling=False,
use_true_value=True),
# drift
BMSS.P_DRIFT : jms.Drift_MultiSubj_Sampler(do_sampling=False,
use_true_value=True),
#drift variance
BMSS.P_ETA : jms.ETASampler_MultiSubj(do_sampling=False,
use_true_value=True),
#noise variance
BMSS.P_NOISE_VAR_SUBJ : \
jms.NoiseVariance_Drift_MultiSubj_Sampler(do_sampling=False,
use_true_value=False),
#weights o fthe mixture
#parameters of the mixture
BMSS.P_MIXT_PARAM_NRLS : jms.MixtureParamsSampler(do_sampling=False,
use_true_value=False),
#BMSS.P_ALPHA_SUBJ : Alpha_hgroup_Sampler(dict_alpha_single),
#BMSS.P_ALPHA_VAR_SUBJ : AlphaVar_Sampler(dict_alpha_var_single),
BMSS.P_CHECK_FINAL_VALUE : 'none', #print or raise
}
开发者ID:Solvi，项目名称:pyhrf，代码行数:66，代码来源:test_jde_multi_subj.py
注：本文中的pyhrf.get_tmp_path函数示例由纯净天空整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。 |
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