def _run_interface(self, runtime):
cwd = os.getcwd()
fsf_header = load_template('feat_header_l1.tcl')
fsf_postscript = load_template('feat_nongui.tcl')
prewhiten = 0
if isdefined(self.inputs.model_serial_correlations):
prewhiten = int(self.inputs.model_serial_correlations)
basis_key = list(self.inputs.bases.keys())[0]
ev_parameters = dict(self.inputs.bases[basis_key])
session_info = self._format_session_info(self.inputs.session_info)
func_files = self._get_func_files(session_info)
n_tcon = 0
n_fcon = 0
if isdefined(self.inputs.contrasts):
for i, c in enumerate(self.inputs.contrasts):
if c[1] == 'T':
n_tcon += 1
elif c[1] == 'F':
n_fcon += 1
for i, info in enumerate(session_info):
do_tempfilter = 1
if info['hpf'] == np.inf:
do_tempfilter = 0
num_evs, cond_txt = self._create_ev_files(
cwd, info, i, ev_parameters, self.inputs.orthogonalization,
self.inputs.contrasts, do_tempfilter, basis_key)
nim = load(func_files[i])
(_, _, _, timepoints) = nim.shape
fsf_txt = fsf_header.substitute(
run_num=i,
interscan_interval=self.inputs.interscan_interval,
num_vols=timepoints,
prewhiten=prewhiten,
num_evs=num_evs[0],
num_evs_real=num_evs[1],
num_tcon=n_tcon,
num_fcon=n_fcon,
high_pass_filter_cutoff=info['hpf'],
temphp_yn=do_tempfilter,
func_file=func_files[i])
fsf_txt += cond_txt
fsf_txt += fsf_postscript.substitute(overwrite=1)
f = open(os.path.join(cwd, 'run%d.fsf' % i), 'w')
f.write(fsf_txt)
f.close()
return runtime
def _run_interface(self, runtime):
cwd = os.getcwd()
fsf_header = load_template("feat_header_l1.tcl")
fsf_postscript = load_template("feat_nongui.tcl")
prewhiten = 0
if isdefined(self.inputs.model_serial_correlations):
prewhiten = int(self.inputs.model_serial_correlations == "AR(1)")
usetd = 0
basis_key = self.inputs.bases.keys()[0]
if basis_key in ["dgamma", "gamma"]:
usetd = int(self.inputs.bases[basis_key]["derivs"])
session_info = self._get_session_info(self.inputs.session_info)
func_files = self._get_func_files(session_info)
n_tcon = 0
n_fcon = 0
for i, c in enumerate(self.inputs.contrasts):
if c[1] == "T":
n_tcon += 1
elif c[1] == "F":
n_fcon += 1
else:
print "unknown contrast type: %s" % str(c)
for i, info in enumerate(session_info):
num_evs, cond_txt = self._create_ev_files(cwd, info, i, usetd, self.inputs.contrasts)
nim = load(func_files[i])
(_, _, _, timepoints) = nim.get_shape()
fsf_txt = fsf_header.substitute(
run_num=i,
interscan_interval=self.inputs.interscan_interval,
num_vols=timepoints,
prewhiten=prewhiten,
num_evs=num_evs[0],
num_evs_real=num_evs[1],
num_tcon=n_tcon,
num_fcon=n_fcon,
high_pass_filter_cutoff=info["hpf"],
func_file=func_files[i],
)
fsf_txt += cond_txt
fsf_txt += fsf_postscript.substitute(overwrite=1)
f = open(os.path.join(cwd, "run%d.fsf" % i), "w")
f.write(fsf_txt)
f.close()
runtime.returncode = 0
return runtime
def run(self, **inputs):
self.inputs.set(**inputs)
runtime = Bunch(returncode=0, stdout=None, stderr=None)
fsf_header = load_template("featreg_header.tcl")
fsf_footer = load_template("feat_nongui.tcl")
fsf_dirs = load_template("feat_fe_featdirs.tcl")
num_runs = len(self.inputs.feat_dirs)
fsf_txt = fsf_header.substitute(num_runs=num_runs, regimage=self.inputs.reg_image, regdof=self.inputs.reg_dof)
for i, rundir in enumerate(filename_to_list(self.inputs.feat_dirs)):
fsf_txt += fsf_dirs.substitute(runno=i + 1, rundir=os.path.abspath(rundir))
fsf_txt += fsf_footer.substitute()
f = open(os.path.join(os.getcwd(), "register.fsf"), "wt")
f.write(fsf_txt)
f.close()
outputs = self.aggregate_outputs()
return InterfaceResult(deepcopy(self), runtime, outputs=outputs)
def _create_ev_files(self, cwd, runinfo, runidx, usetd, contrasts):
"""Creates EV files from condition and regressor information.
Parameters:
-----------
runinfo : dict
Generated by `SpecifyModel` and contains information
about events and other regressors.
runidx : int
Index to run number
usetd : int
Whether or not to use temporal derivatives for
conditions
contrasts : list of lists
Information on contrasts to be evaluated
"""
conds = {}
evname = []
ev_hrf = load_template('feat_ev_hrf.tcl')
ev_none = load_template('feat_ev_none.tcl')
ev_ortho = load_template('feat_ev_ortho.tcl')
contrast_header = load_template('feat_contrast_header.tcl')
contrast_prolog = load_template('feat_contrast_prolog.tcl')
contrast_element = load_template('feat_contrast_element.tcl')
contrast_ftest_element = load_template('feat_contrast_ftest_element.tcl')
contrastmask_header = load_template('feat_contrastmask_header.tcl')
contrastmask_footer = load_template('feat_contrastmask_footer.tcl')
contrastmask_element = load_template('feat_contrastmask_element.tcl')
ev_txt = ''
# generate sections for conditions and other nuisance
# regressors
num_evs = [0, 0]
for field in ['cond', 'regress']:
for i, cond in enumerate(runinfo[field]):
name = cond['name']
evname.append(name)
evfname = os.path.join(cwd, 'ev_%s_%d_%d.txt' % (name, runidx,
len(evname)))
evinfo = []
num_evs[0] += 1
num_evs[1] += 1
if field == 'cond':
for j, onset in enumerate(cond['onset']):
if len(cond['duration']) > 1:
evinfo.insert(j, [onset, cond['duration'][j], 1])
else:
evinfo.insert(j, [onset, cond['duration'][0], 1])
ev_txt += ev_hrf.substitute(ev_num=num_evs[0],
ev_name=name,
temporalderiv=usetd,
cond_file=evfname)
if usetd:
evname.append(name + 'TD')
num_evs[1] += 1
elif field == 'regress':
evinfo = [[j] for j in cond['val']]
ev_txt += ev_none.substitute(ev_num=num_evs[0],
ev_name=name,
cond_file=evfname)
ev_txt += "\n"
conds[name] = evfname
self._create_ev_file(evfname, evinfo)
# add orthogonalization
for i in range(1, num_evs[0] + 1):
for j in range(0, num_evs[0] + 1):
ev_txt += ev_ortho.substitute(c0=i, c1=j)
ev_txt += "\n"
# add t/f contrast info
ev_txt += contrast_header.substitute()
con_names = []
for j, con in enumerate(contrasts):
con_names.append(con[0])
con_map = {}
ftest_idx = []
ttest_idx = []
for j, con in enumerate(contrasts):
if con[1] == 'F':
ftest_idx.append(j)
for c in con[2]:
if c[0] not in con_map.keys():
con_map[c[0]] = []
con_map[c[0]].append(j)
else:
ttest_idx.append(j)
for ctype in ['real', 'orig']:
for j, con in enumerate(contrasts):
if con[1] == 'F':
continue
tidx = ttest_idx.index(j)+1
ev_txt += contrast_prolog.substitute(cnum=tidx,
ctype=ctype,
cname=con[0])
count = 0
for c in range(1, len(evname) + 1):
if evname[c - 1].endswith('TD') and ctype == 'orig':
continue
count = count + 1
if evname[c - 1] in con[2]:
val = con[3][con[2].index(evname[c - 1])]
else:
val = 0.0
ev_txt += contrast_element.substitute(cnum=tidx,
element=count,
ctype=ctype, val=val)
ev_txt += "\n"
if con[0] in con_map.keys():
for fconidx in con_map[con[0]]:
ev_txt += contrast_ftest_element.substitute(cnum=ftest_idx.index(fconidx)+1,
element=tidx,
ctype=ctype,
val=1)
ev_txt += "\n"
# add contrast mask info
ev_txt += contrastmask_header.substitute()
for j, _ in enumerate(contrasts):
for k, _ in enumerate(contrasts):
if j != k:
ev_txt += contrastmask_element.substitute(c1=j + 1,
c2=k + 1)
ev_txt += contrastmask_footer.substitute()
return num_evs, ev_txt
def _create_ev_files(self, cwd, runinfo, runidx, ev_parameters,
orthogonalization, contrasts, do_tempfilter,
basis_key):
"""Creates EV files from condition and regressor information.
Parameters:
-----------
runinfo : dict
Generated by `SpecifyModel` and contains information
about events and other regressors.
runidx : int
Index to run number
design_parameters : dict
A dictionary containing the model parameters for the
given design type.
contrasts : list of lists
Information on contrasts to be evaluated
"""
conds = {}
evname = []
if basis_key == "dgamma":
basis_key = "hrf"
elif basis_key == "gamma":
try:
_ = ev_parameters['gammasigma']
except KeyError:
ev_parameters['gammasigma'] = 3
try:
_ = ev_parameters['gammadelay']
except KeyError:
ev_parameters['gammadelay'] = 6
ev_template = load_template('feat_ev_' + basis_key + '.tcl')
ev_none = load_template('feat_ev_none.tcl')
ev_ortho = load_template('feat_ev_ortho.tcl')
ev_txt = ''
# generate sections for conditions and other nuisance
# regressors
num_evs = [0, 0]
for field in ['cond', 'regress']:
for i, cond in enumerate(runinfo[field]):
name = cond['name']
evname.append(name)
evfname = os.path.join(
cwd, 'ev_%s_%d_%d.txt' % (name, runidx, len(evname)))
evinfo = []
num_evs[0] += 1
num_evs[1] += 1
if field == 'cond':
for j, onset in enumerate(cond['onset']):
try:
amplitudes = cond['amplitudes']
if len(amplitudes) > 1:
amp = amplitudes[j]
else:
amp = amplitudes[0]
except KeyError:
amp = 1
if len(cond['duration']) > 1:
evinfo.insert(j, [onset, cond['duration'][j], amp])
else:
evinfo.insert(j, [onset, cond['duration'][0], amp])
ev_parameters['ev_num'] = num_evs[0]
ev_parameters['ev_name'] = name
ev_parameters['tempfilt_yn'] = do_tempfilter
ev_parameters['cond_file'] = evfname
try:
ev_parameters['temporalderiv'] = ev_parameters.pop(
'derivs')
except KeyError:
pass
else:
if ev_parameters['temporalderiv']:
evname.append(name + 'TD')
num_evs[1] += 1
ev_txt += ev_template.substitute(ev_parameters)
elif field == 'regress':
evinfo = [[j] for j in cond['val']]
ev_txt += ev_none.substitute(ev_num=num_evs[0],
ev_name=name,
tempfilt_yn=do_tempfilter,
cond_file=evfname)
ev_txt += "\n"
conds[name] = evfname
self._create_ev_file(evfname, evinfo)
# add ev orthogonalization
for i in range(1, num_evs[0] + 1):
for j in range(0, num_evs[0] + 1):
try:
orthogonal = int(orthogonalization[i][j])
except (ValueError, TypeError):
orthogonal = 0
ev_txt += ev_ortho.substitute(c0=i,
c1=j,
orthogonal=orthogonal)
ev_txt += "\n"
# add contrast info to fsf file
if isdefined(contrasts):
contrast_header = load_template('feat_contrast_header.tcl')
contrast_prolog = load_template('feat_contrast_prolog.tcl')
contrast_element = load_template('feat_contrast_element.tcl')
contrast_ftest_element = load_template(
'feat_contrast_ftest_element.tcl')
contrastmask_header = load_template('feat_contrastmask_header.tcl')
contrastmask_footer = load_template('feat_contrastmask_footer.tcl')
contrastmask_element = load_template(
'feat_contrastmask_element.tcl')
# add t/f contrast info
ev_txt += contrast_header.substitute()
con_names = []
for j, con in enumerate(contrasts):
con_names.append(con[0])
con_map = {}
ftest_idx = []
ttest_idx = []
for j, con in enumerate(contrasts):
if con[1] == 'F':
ftest_idx.append(j)
for c in con[2]:
if c[0] not in list(con_map.keys()):
con_map[c[0]] = []
con_map[c[0]].append(j)
else:
ttest_idx.append(j)
for ctype in ['real', 'orig']:
for j, con in enumerate(contrasts):
if con[1] == 'F':
continue
tidx = ttest_idx.index(j) + 1
ev_txt += contrast_prolog.substitute(cnum=tidx,
ctype=ctype,
cname=con[0])
count = 0
for c in range(1, len(evname) + 1):
if evname[c - 1].endswith('TD') and ctype == 'orig':
continue
count = count + 1
if evname[c - 1] in con[2]:
val = con[3][con[2].index(evname[c - 1])]
else:
val = 0.0
ev_txt += contrast_element.substitute(cnum=tidx,
element=count,
ctype=ctype,
val=val)
ev_txt += "\n"
for fconidx in ftest_idx:
fval = 0
if (con[0] in con_map.keys()
and fconidx in con_map[con[0]]):
fval = 1
ev_txt += contrast_ftest_element.substitute(
cnum=ftest_idx.index(fconidx) + 1,
element=tidx,
ctype=ctype,
val=fval)
ev_txt += "\n"
# add contrast mask info
ev_txt += contrastmask_header.substitute()
for j, _ in enumerate(contrasts):
for k, _ in enumerate(contrasts):
if j != k:
ev_txt += contrastmask_element.substitute(c1=j + 1,
c2=k + 1)
ev_txt += contrastmask_footer.substitute()
return num_evs, ev_txt
