for sess in Sessions:
paths['fmri'][sess] = paths['fmri'][sess][-nb_frames:]
misc = ConfigObj(paths['misc'])
misc["sessions"] = Sessions
misc["tasks"] = AllReg
misc['mask_url'] = paths['mask']
misc[model_id]={}
misc.write()
# step 2. Create one design matrix for each session
design_matrices = {}
for sess in Sessions:
design_matrices[sess] = glm_tools.design_matrix(
paths['misc'], paths['dmtx'][sess], sess, None,
frametimes, drift_model=drift_model, hfcut=hfcut,
model=model_id, add_regs=reg_matrix, add_reg_names=Reg[sess] )
# step 3. Compute the Mask
# fixme : it should be possible to provide a pre-computed mask
if side=='False':
print "Computing the Mask"
mask_array = compute_mask_files( paths['fmri'].values()[0][0],
paths['mask'], True, infTh, supTh)
# step 4. Creating Contrast File
print "Creating Contrasts"
clist = contrast_tools.ContrastList(
misc=ConfigObj(paths['misc']), model=model_id)
d = clist.dic
# step 1. set all the paths
basePath = os.sep.join((DBPath, s, "fMRI", a))
paths = glm_tools. generate_all_brainvisa_paths( basePath, Sessions,
fmri_wc, model_id)
misc = ConfigObj(paths['misc'])
misc["sessions"] = Sessions
misc["tasks"] = Conditions
misc["mask_url"] = paths["mask"]
misc.write()
# step 2. Create one design matrix for each session
design_matrices={}
for sess in Sessions:
design_matrices[sess] = glm_tools.design_matrix(
paths['misc'], paths['dmtx'][sess], sess, paths['paradigm'],
frametimes, hrf_model=hrf_model, drift_model=drift_model,
hfcut=hfcut, model=model_id)
# step 3. Compute the Mask
# fixme : it should be possible to provide a pre-computed mask
print "Computing the Mask"
mask_array = compute_mask_files(paths['fmri'].values()[0][0],
paths['mask'], False, infTh, supTh)
# step 4. Create Contrast Files
print "Creating Contrasts"
clist = contrast_tools.ContrastList(misc=misc)
d = clist.dic
d["SStSSp_minus_DStDSp"] = d["SSt-SSp"] - d["DSt-DSp"]
d["DStDSp_minus_SStSSp"] = d["DSt-DSp"] - d["SSt-SSp"]
d["DSt_minus_SSt"] = d["DSt-SSp"] + d["DSt-DSp"]\
misc = ConfigObj(paths["misc"])
misc["sessions"] = Sessions
misc["tasks"] = Conditions
misc["mask_url"] = paths["mask"]
misc.write()
# step 2. Create one design matrix for each session
design_matrices = {}
for sess in Sessions:
design_matrices[sess] = glm_tools.design_matrix(
paths["misc"],
paths["dmtx"][sess],
sess,
paths["paradigm"],
frametimes,
hrf_model=hrf_model,
drift_model=drift_model,
hfcut=hfcut,
model=model_id,
)
# step 3. Compute the Mask
# fixme : it should be possible to provide a pre-computed mask
print "Computing the Mask"
mask_array = compute_mask_files(paths["fmri"].values()[0][0], paths["mask"], True, infTh, supTh)
# step 4. Creating functional contrasts
print "Creating Contrasts"
clist = contrast_tools.ContrastList(misc=ConfigObj(paths["misc"]), model=model_id)
generate_localizer_contrasts(clist)
