def demo_spm_multimodal_fmri(output_dir="/tmp/spm_multimodal_fmri_output"):
"""Demo for SPM multimodal fmri (faces vs scrambled)
Parameters
----------
data_dir: string, optional
where the data is located on your disk, where it will be
downloaded to
output_dir: string, optional
where output will be written to
"""
# fetch data
spm_multimodal_fmri = fetch_spm_multimodal_fmri()
# subject data factory
def subject_factory():
subject_id = "sub001"
yield SubjectData(subject_id=subject_id,
func=spm_multimodal_fmri.func1,
output_dir=os.path.join(output_dir, subject_id))
# invoke demon to run de demo
_fmri_demo_runner(subject_factory(),
"SPM Multimodal fMRI faces vs scrambled session 1")
def demo_spm_multimodal_fmri(output_dir):
"""Demo for SPM multimodal fmri (faces vs scrambled)
Parameters
----------
output_dir: string
where output will be written to
"""
output_dir = os.path.join(output_dir, "spm_multimodal_fmri_output")
spm_multimodal_fmri = fetch_spm_multimodal_fmri()
subject_id = "sub001"
subjects = [SubjectData(subject_id=subject_id,
func=[spm_multimodal_fmri.func1,
spm_multimodal_fmri.func2],
output_dir=os.path.join(output_dir, subject_id))]
_demo_runner(subjects, "SPM Multimodal fMRI faces vs scrambled",
n_sessions=2)
def demo_spm_multimodal_fmri(output_dir="/tmp/spm_multimodal_fmri_output"):
"""Demo for SPM multimodal fmri (faces vs scrambled)
Parameters
----------
data_dir: string, optional
where the data is located on your disk, where it will be
downloaded to
output_dir: string, optional
where output will be written to
"""
spm_multimodal_fmri = fetch_spm_multimodal_fmri()
subject_id = "sub001"
subjects = [SubjectData(subject_id=subject_id,
func=[spm_multimodal_fmri.func1,
spm_multimodal_fmri.func2],
output_dir=os.path.join(output_dir, subject_id))]
_demo_runner(subjects, "SPM Multimodal fMRI faces vs scrambled",
n_sessions=2)
def demo_spm_multimodal_fmri(output_dir):
"""Demo for SPM multimodal fmri (faces vs scrambled)
Parameters
----------
output_dir: string
where output will be written to
"""
output_dir = os.path.join(output_dir, "spm_multimodal_fmri_output")
spm_multimodal_fmri = fetch_spm_multimodal_fmri()
subject_id = "sub001"
subjects = [
SubjectData(
subject_id=subject_id,
func=[spm_multimodal_fmri.func1, spm_multimodal_fmri.func2],
output_dir=os.path.join(output_dir, subject_id))
]
_demo_runner(subjects,
"SPM Multimodal fMRI faces vs scrambled",
n_sessions=2)
def demo_spm_multimodal_fmri(output_dir):
"""Demo for SPM multimodal fmri (faces vs scrambled)
Parameters
----------
output_dir: string
where output will be written to
"""
output_dir = os.path.join(output_dir, "spm_multimodal_fmri_output")
# fetch data
spm_multimodal_fmri = fetch_spm_multimodal_fmri()
# subject data factory
def subject_factory():
subject_id = "sub001"
yield SubjectData(subject_id=subject_id,
func=spm_multimodal_fmri.func1,
output_dir=os.path.join(output_dir, subject_id))
# invoke demon to run de demo
_fmri_demo_runner(output_dir, subject_factory(),
"SPM Multimodal fMRI faces vs scrambled session 1")
def demo_spm_multimodal_fmri(output_dir):
"""Demo for SPM multimodal fmri (faces vs scrambled)
Parameters
----------
output_dir: string
where output will be written to
"""
output_dir = os.path.join(output_dir, "spm_multimodal_fmri_output")
# fetch data
spm_multimodal_fmri = fetch_spm_multimodal_fmri()
# subject data factory
def subject_factory():
subject_id = "sub001"
yield SubjectData(subject_id=subject_id,
func=spm_multimodal_fmri.func1,
output_dir=os.path.join(output_dir, subject_id))
# invoke demon to run de demo
_fmri_demo_runner(output_dir, subject_factory(),
"SPM Multimodal fMRI faces vs scrambled session 1")
def demo_spm_multimodal_fmri(output_dir="/tmp/spm_multimodal_fmri_output"):
"""Demo for SPM multimodal fmri (faces vs scrambled)
Parameters
----------
data_dir: string, optional
where the data is located on your disk, where it will be
downloaded to
output_dir: string, optional
where output will be written to
"""
spm_multimodal_fmri = fetch_spm_multimodal_fmri()
subject_id = "sub001"
subjects = [
SubjectData(
subject_id=subject_id,
func=[spm_multimodal_fmri.func1, spm_multimodal_fmri.func2],
output_dir=os.path.join(output_dir, subject_id))
]
_demo_runner(subjects,
"SPM Multimodal fMRI faces vs scrambled",
n_sessions=2)
from pypreprocess.reporting.glm_reporter import generate_subject_stats_report
from pypreprocess.nipype_preproc_spm_utils import do_subject_preproc
from pypreprocess.subject_data import SubjectData
# file containing configuration for preprocessing the data
this_dir = os.path.abspath(os.path.dirname(sys.argv[0]))
jobfile = os.path.join(this_dir, "multimodal_faces_preproc.ini")
# set dataset dir
if len(sys.argv) > 1:
dataset_dir = sys.argv[1]
else:
dataset_dir = os.path.join(this_dir, "spm_multimodal_faces")
# fetch spm multimodal_faces data
subject_data = fetch_spm_multimodal_fmri()
dataset_dir = os.path.dirname(os.path.dirname(os.path.dirname(
subject_data.anat)))
# preprocess the data
subject_id = "sub001"
subject_data = SubjectData(
output_dir=os.path.join(dataset_dir, "pypreprocess_output", subject_id),
subject_id=subject_id, func=[subject_data.func1, subject_data.func2],
anat=subject_data.anat, trials_ses1=subject_data.trials_ses1,
trials_ses2=subject_data.trials_ses2, session_ids=["Session1", "Session2"])
subject_data = do_subject_preproc(subject_data, realign=True, coregister=True,
segment=True, normalize=True)
# experimental paradigm meta-params
stats_start_time = time.ctime()
"""
Author: DOHMATOB Elvis Dopgima elvis[dot]dohmatob[at]inria[dot]fr
Synopsis: single_subject_pipeline.py demo
"""
from pypreprocess.datasets import fetch_spm_multimodal_fmri
from pypreprocess.purepython_preproc_utils import do_subject_preproc
# fetch data
sd = fetch_spm_multimodal_fmri()
sd.output_dir = "/tmp/sub001"
sd.func = [sd.func1, sd.func2]
# preproc data
do_subject_preproc(sd.__dict__,
concat=False,
coregister=True,
stc=True,
tsdiffana=True,
realign=True,
report=True,
reslice=True)
"""
Author: DOHMATOB Elvis Dopgima elvis[dot]dohmatob[at]inria[dot]fr
Synopsis: single_subject_pipeline.py demo
"""
from pypreprocess.datasets import fetch_spm_multimodal_fmri
from pypreprocess.purepython_preproc_utils import do_subject_preproc
# fetch data
sd = fetch_spm_multimodal_fmri()
sd.output_dir = "/tmp/sub001"
sd.func = [sd.func1, sd.func2]
# preproc data
do_subject_preproc(sd.__dict__, concat=False, coregister=True, stc=True,
tsdiffana=True, realign=True, report=True, reslice=True)
line.append(1.)
condition, onset, duration, amplitude = line
conditions.append(condition)
onsets.append(float(onset))
durations.append(float(duration))
amplitudes.append(float(amplitude))
fd.close()
if not line_cnt > 0:
raise ValueError(
"Couldn't read any data from onset file: %s" % onset_file)
return map(np.array, [conditions, onsets, durations, amplitudes])
# fetch data
data_dir = "examples/spm_multimodal/"
subject_data = fetch_spm_multimodal_fmri(data_dir)
# XXX to be verified
tr = 2.
drift_model = 'Cosine'
hrf_model = 'Canonical With Derivative'
hfcut = 128.
time_units = "tr" # default if 1
if time_units == "tr":
time_units = tr
# re-write onset files into compatible format
for sess in xrange(2):
trials = getattr(subject_data, "trials_ses%i" % (sess + 1))
fd = open(trials.split(".")[0] + ".txt", 'w')
timing = scipy.io.loadmat(trials, squeeze_me=True, struct_as_record=False)
