class config(HasTraits):
uuid = traits.Str(desc="UUID")
# Directories
working_dir = Directory(mandatory=True, desc="Location of the Nipype working directory")
base_dir = Directory(os.path.abspath('.'),mandatory=True, desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True, desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False, desc="Location to store crash files")
# Execution
run_using_plugin = Bool(False, usedefault=True, desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS", "MultiProc", "SGE", "Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True, desc='Plugin arguments.')
test_mode = Bool(False, mandatory=False, usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. ')
timeout = traits.Float(14.0)
# Subjects
#subjects = traits.List(traits.Str, mandatory=True, usedefault=True,
# desc="Subject id's. Note: These MUST match the subject id's in the \
# Freesurfer directory. For simplicity, the subject id's should \
# also match with the location of individual functional files.")
#fwhm=traits.List(traits.Float())
#copes_template = traits.String('%s/preproc/output/fwhm_%s/cope*.nii.gz')
#varcopes_template = traits.String('%s/preproc/output/fwhm_%s/varcope*.nii.gz')
#contrasts = traits.List(traits.Str,desc="contrasts")
datagrabber = traits.Instance(Data, ())
# Regression
design_csv = traits.File(desc="design .csv file")
reg_contrasts = traits.Code(desc="function named reg_contrasts which takes in 0 args and returns contrasts")
#Normalization
norm_template = traits.File(mandatory=True,desc='Template of files')
#Correction:
run_correction = traits.Bool(False)
z_threshold = traits.Float(2.3)
connectivity = traits.Int(25)
do_randomize = traits.Bool(False)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
# Buttons
check_func_datagrabber = Button("Check")
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
sink_dir = Directory(os.path.abspath('.'),
mandatory=True,
desc="Location where the BIP will store the results")
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
# Subjects
#subjects= traits.List(traits.Str, mandatory=True, usedefault=True,
# desc="Subject id's. Note: These MUST match the subject id's in the \
# Freesurfer directory. For simplicity, the subject id's should \
# also match with the location of individual functional files.")
datagrabber = traits.Instance(Data, ())
# First Level
subjectinfo = traits.Code()
contrasts = traits.Code()
interscan_interval = traits.Float()
film_threshold = traits.Float()
input_units = traits.Enum('scans', 'secs')
is_sparse = traits.Bool(False)
model_hrf = traits.Bool(True)
stimuli_as_impulses = traits.Bool(True)
use_temporal_deriv = traits.Bool(True)
volumes_in_cluster = traits.Int(1)
ta = traits.Float()
tr = traits.Float()
hpcutoff = traits.Float()
scan_onset = traits.Int(0)
scale_regressors = traits.Bool(True)
#bases = traits.Dict({'dgamma':{'derivs': False}},use_default=True)
bases = traits.Dict(
{'dgamma': {
'derivs': False
}}, use_default=True
) #traits.Enum('dgamma','gamma','none'), traits.Enum(traits.Dict(traits.Enum('derivs',None), traits.Bool),None), desc="name of basis function and options e.g., {'dgamma': {'derivs': True}}")
# preprocessing info
preproc_config = traits.File(desc="preproc config file")
use_compcor = traits.Bool(desc="use noise components from CompCor")
#advanced_options
use_advanced_options = Bool(False)
advanced_options = traits.Code()
save_script_only = traits.Bool(False)
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
# Directories
base_dir = Directory(
os.path.abspath('.'),
mandatory=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
save_script_only = traits.Bool(False)
# Subjects
#subjects = traits.List(traits.Str, mandatory=True, usedefault=True,
# desc="Subject id's. Note: These MUST match the subject id's in the \
# Freesurfer directory. For simplicity, the subject id's should \
# also match with the location of individual functional files.")
#fwhm=traits.List(traits.Float())
#copes_template = traits.String('%s/preproc/output/fwhm_%s/cope*.nii.gz')
#varcopes_template = traits.String('%s/preproc/output/fwhm_%s/varcope*.nii.gz')
#contrasts = traits.List(traits.Str,desc="contrasts")
datagrabber = traits.Instance(Data, ())
# Regression
design_csv = traits.File(desc="design .csv file")
reg_contrasts = traits.Code(
desc=
"function named reg_contrasts which takes in 0 args and returns contrasts"
)
run_mode = traits.Enum("flame1", "ols", "flame12")
#Normalization
norm_template = traits.File(desc='Template of files')
use_mask = traits.Bool(False)
mask_file = traits.File()
#Correction:
run_correction = traits.Bool(False)
p_threshold = traits.Float(0.05)
z_threshold = traits.Float(2.3)
connectivity = traits.Int(26)
do_randomize = traits.Bool(False)
num_iterations = traits.Int(5000)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
# Buttons
check_func_datagrabber = Button("Check")
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
working_dir = Directory(mandatory=True, desc="Location of the Nipype working directory")
sink_dir = Directory(os.path.abspath('.'), mandatory=True, desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False, desc="Location to store crash files")
surf_dir = Directory(mandatory=True, desc= "Freesurfer subjects directory")
save_script_only = traits.Bool(False)
# Execution
run_using_plugin = Bool(False, usedefault=True, desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS", "MultiProc", "SGE", "Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True, desc='Plugin arguments.')
test_mode = Bool(False, mandatory=False, usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. ')
timeout = traits.Float(14.0)
datagrabber = traits.Instance(Data, ())
surface_template = traits.Enum("fsaverage","fsaverage5","fsaverage6","fsaverage4","subject")
test_name = traits.String('FS_one_sample_t_test')
# First Level
#advanced_options
use_advanced_options = Bool(False)
advanced_options = traits.Code()
class AutoRefreshDialog(traits.HasTraits):
minutes = traits.Float(1.0)
autoRefreshBool = traits.Bool()
emailAlertBool = traits.Bool(False)
soundAlertBool = traits.Bool(False)
linesOfDataFrame = traits.Range(1, 10)
alertCode = traits.Code(
DEFAULT_ALERT_CODE,
desc="python code for finding alert worthy elements")
basicGroup = traitsui.Group("minutes", "autoRefreshBool")
alertGroup = traitsui.VGroup(
traitsui.HGroup(traitsui.Item("emailAlertBool"),
traitsui.Item("soundAlertBool")),
traitsui.Item("linesOfDataFrame",
visible_when="emailAlertBool or soundAlertBool"),
traitsui.Item("alertCode",
visible_when="emailAlertBool or soundAlertBool"))
traits_view = traitsui.View(traitsui.VGroup(basicGroup, alertGroup),
title="auto refresh",
buttons=[OKButton],
kind='livemodal',
resizable=True)
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
# Directories
base_dir = Directory(os.path.abspath('.'),mandatory=True, desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True, desc="Location where the BIP will store the results")
# Subjects
subjects = traits.List(traits.Str, mandatory=True, usedefault=True,
desc="Subject id's. Note: These MUST match the subject id's in the \
Freesurfer directory. For simplicity, the subject id's should \
also match with the location of individual functional files.")
fwhm=traits.List(traits.Float())
inputs_template = traits.String('%s/preproc/output/fwhm_%s/*.nii.gz')
meanfunc_template = traits.String('%s/preproc/mean/*_mean.nii.gz')
fsl_mat_template = traits.String('%s/preproc/bbreg/*.mat')
unwarped_brain_template = traits.String('%s/smri/unwarped_brain/*.nii*')
affine_transformation_template = traits.String('%s/smri/affine_transformation/*.nii*')
warp_field_template = traits.String('%s/smri/warped_field/*.nii*')
#Normalization
standard_transform_template = traits.File(mandatory=True,desc='Standard template to warp to')
standard_warp_field_template = traits.String()
standard_affine_transformation_template = traits.String()
standard_norm_template = traits.File()
standard_warp_field_template = traits.File()
standard_affine_transformation_template = traits.File()
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
# Buttons
check_func_datagrabber = Button("Check")
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
# Directories
base_dir = Directory(os.path.abspath('.'),mandatory=True, desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True, desc="Location where the BIP will store the results")
datagrabber = traits.Instance(Data, ())
run_mode = traits.Enum("flame1","ols","flame12")
save_script_only = traits.Bool(False)
#Normalization
brain_mask = traits.File(mandatory=True,desc='Brain Mask')
name_of_project = traits.String("group_analysis",usedefault=True)
do_randomize = traits.Bool(True)
num_iterations = traits.Int(5000)
#Correction:
run_correction = traits.Bool(True)
z_threshold = traits.Float(2.3)
p_threshold = traits.Float(0.05)
connectivity = traits.Int(26)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
# Buttons
check_func_datagrabber = Button("Check")
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
save_script_only = traits.Bool(False)
sink_dir = Directory(mandatory=True, desc="Location to store results")
# Execution
run_using_plugin = Bool(
False,
usedefault=True,
desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS",
"PBSGraph",
"MultiProc",
"SGE",
"Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True,
desc='Plugin arguments.')
# Subjects
datagrabber = traits.Instance(Data, ())
name = traits.String('mean')
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
working_dir = Directory(mandatory=True, desc="Location of the Nipype working directory")
sink_dir = Directory(mandatory=True, desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False, desc="Location to store crash files")
# Execution
run_using_plugin = Bool(False, usedefault=True, desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS", "PBSGraph","MultiProc", "SGE", "Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True, desc='Plugin arguments.')
test_mode = Bool(False, mandatory=False, usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. ')
# Subjects
subjects= traits.List(traits.Str, mandatory=True, usedefault=True,
desc="Subject id's. Note: These MUST match the subject id's in the \
Freesurfer directory. For simplicity, the subject id's should \
also match with the location of individual functional files.")
# Preprocessing info
preproc_config = traits.File(desc="preproc json file")
#Advanced
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
save_script_only = traits.Bool(False)
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
working_dir = Directory(mandatory=True, desc="Location of the Nipype working directory")
crash_dir = Directory(mandatory=False, desc="Location to store crash files")
sink_dir = Directory(mandatory=True, desc="Location to store results")
save_script_only = traits.Bool(False)
# Execution
run_using_plugin = Bool(False, usedefault=True, desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS", "PBSGraph","MultiProc", "SGE", "Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True, desc='Plugin arguments.')
# Subjects
interpolation = traits.Enum('trilinear','nearestneighbour','sinc',usedefault=True)
name = traits.String('flirt_output',desc='name of folder to store flirt mats')
datagrabber_create = traits.Instance(Data, ())
datagrabber_apply = traits.Instance(Data, ())
create_transform = traits.Bool(True)
apply_transform = traits.Bool(False)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
working_dir = Directory(mandatory=True, desc="Location of the Nipype working directory")
sink_dir = Directory(os.path.abspath('.'), mandatory=True, desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False, desc="Location to store crash files")
surf_dir = Directory(mandatory=True, desc= "Freesurfer subjects directory")
# Execution
run_using_plugin = Bool(False, usedefault=True, desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS", "MultiProc", "SGE", "Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True, desc='Plugin arguments.')
test_mode = Bool(False, mandatory=False, usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. ')
timeout = traits.Float(14.0)
subjects = traits.List(desc="subjects")
split_files = traits.List(traits.File(),desc="""list of split files""")
# First Level
#advanced_options
use_advanced_options = Bool(False)
advanced_options = traits.Code()
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
# Directories
base_dir = Directory(
os.path.abspath('.'),
mandatory=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
surf_dir = Directory(os.environ['SUBJECTS_DIR'],
desc='Freesurfer subjects dir')
save_script_only = traits.Bool(False)
# Subjects
subjects = traits.List(
traits.Str,
mandatory=True,
usedefault=True,
desc="Subject id's. Note: These MUST match the subject id's in the \
Freesurfer directory. For simplicity, the subject id's should \
also match with the location of individual functional files."
)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
def getNode(_type,tr,config):
from bips.workflows.flexible_datagrabber import Data, DataBase
if _type == type(traits.Int()):
col_type = colander.SchemaNode(colander.Int(),
name=tr,description=config.trait(tr).desc)
elif _type == type(traits.Float()):
col_type = colander.SchemaNode(colander.Decimal(),name=tr)
elif _type == type(traits.String()) or _type==type(traits.Str()):
col_type = colander.SchemaNode(colander.String(),name=tr)
elif _type == type(traits.Enum('')):
values=config.trait(tr).trait_type.values
the_values = []
for v in values:
the_values.append((v,v))
col_type = colander.SchemaNode(
deform.Set(),
widget=deform.widget.SelectWidget(values=the_values),
name=tr)
elif _type == type(traits.Bool()):
col_type = colander.SchemaNode(colander.Boolean(),widget=deform.widget.CheckboxWidget(),name=tr)
elif _type == type(traits.Code()):
col_type = colander.SchemaNode(colander.String(),name=tr,widget=deform.widget.TextAreaWidget(cols=100,rows=20))
elif _type == type(traits.Instance(Data,())):
from bips.workflows.flexible_datagrabber import create_datagrabber_html_view
col_type = create_datagrabber_html_view()
elif _type == type(traits.List()):
col_type =get_list(_type,tr,config)
else:
print "type: ", _type, "not found!"
col_type = colander.SchemaNode(colander.String(),name=tr)
return col_type
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
sink_dir = Directory(os.path.abspath('.'),
mandatory=True,
desc="Location where the BIP will store the results")
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
save_script_only = traits.Bool(False)
datagrabber = traits.Instance(Data, ())
projection_stem = traits.Str('-projfrac-avg 0 1 0.1',
desc='how to project data onto the surface')
out_type = traits.Enum('mat', 'hdf5', desc='mat or hdf5')
hdf5_package = traits.Enum('h5py',
'pytables',
desc='which hdf5 package to use')
target_surf = traits.Enum('fsaverage4',
'fsaverage3',
'fsaverage5',
'fsaverage6',
'fsaverage',
'subject',
desc='which average surface to map to')
surface_fwhm = traits.List([5],
traits.Float(),
mandatory=True,
usedefault=True,
desc="How much to smooth on target surface")
roiname = traits.String('amygdala')
use_advanced_options = Bool(False)
advanced_options = traits.Code()
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
base_dir = Directory(
exists=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
field_dir = Directory(
exists=True,
desc="Base directory of field-map data (Should be subject-independent) \
Set this value to None if you don't want fieldmap distortion correction"
)
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
save_script_only = traits.Bool(False)
# Subjects
datagrabber = traits.Instance(Data, ())
TR = traits.Float(6.0)
preproc_config = traits.File(desc="preproc config file")
json_name = traits.String('preproc_metrics')
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
base_dir = Directory(
exists=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
field_dir = Directory(
exists=True,
desc="Base directory of field-map data (Should be subject-independent) \
Set this value to None if you don't want fieldmap distortion correction"
)
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
json_sink = Directory(mandatory=False, desc="Location to store json_files")
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
# Execution
run_using_plugin = Bool(
False,
usedefault=True,
desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS",
"PBSGraph",
"MultiProc",
"SGE",
"Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True,
desc='Plugin arguments.')
test_mode = Bool(
False,
mandatory=False,
usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. '
)
# Subjects
subjects = traits.List(
traits.Str,
mandatory=True,
usedefault=True,
desc=
"Subject id's. These subjects must match the ones that have been run in your preproc config"
)
preproc_config = traits.File(desc="preproc config file")
debug = traits.Bool(True)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(HasTraits):
uuid = traits.Str(desc="UUID")
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
base_dir = Directory(
os.path.abspath('.'),
mandatory=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
# Execution
run_using_plugin = Bool(
False,
usedefault=True,
desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS",
"MultiProc",
"SGE",
"Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True,
desc='Plugin arguments.')
test_mode = Bool(
False,
mandatory=False,
usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. '
)
timeout = traits.Float(14.0)
datagrabber = traits.Instance(Data, ())
run_mode = traits.Enum("flame1", "ols", "flame12")
save_script_only = traits.Bool(False)
#Normalization
brain_mask = traits.File(mandatory=True, desc='Brain Mask')
name_of_project = traits.String("group_analysis", usedefault=True)
do_randomize = traits.Bool(True)
num_iterations = traits.Int(5000)
#Correction:
run_correction = traits.Bool(True)
z_threshold = traits.Float(2.3)
p_threshold = traits.Float(0.05)
connectivity = traits.Int(26)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
# Buttons
check_func_datagrabber = Button("Check")
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
sink_dir = Directory(os.path.abspath('.'),
mandatory=True,
desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
# Execution
run_using_plugin = Bool(
False,
usedefault=True,
desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS",
"MultiProc",
"SGE",
"Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True,
desc='Plugin arguments.')
test_mode = Bool(
False,
mandatory=False,
usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. '
)
timeout = traits.Float(14.0)
datagrabber = traits.Instance(Data, ())
projection_stem = traits.Str('-projfrac-avg 0 1 0.1',
desc='how to project data onto the surface')
out_type = traits.Enum('mat', 'hdf5', desc='mat or hdf5')
hdf5_package = traits.Enum('h5py',
'pytables',
desc='which hdf5 package to use')
target_surf = traits.Enum('fsaverage4',
'fsaverage3',
'fsaverage5',
'fsaverage6',
'fsaverage',
'subject',
desc='which average surface to map to')
surface_fwhm = traits.List([5],
traits.Float(),
mandatory=True,
usedefault=True,
desc="How much to smooth on target surface")
roiname = traits.String('amygdala')
use_advanced_options = Bool(False)
advanced_options = traits.Code()
class config(HasTraits):
uuid = traits.Str(desc="UUID")
# Directories
working_dir = Directory(mandatory=True, desc="Location of the Nipype working directory")
base_dir = Directory(os.path.abspath('.'),mandatory=True, desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True, desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False, desc="Location to store crash files")
# Execution
run_using_plugin = Bool(False, usedefault=True, desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS", "MultiProc", "SGE", "Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True, desc='Plugin arguments.')
test_mode = Bool(False, mandatory=False, usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. ')
timeout = traits.Float(14.0)
# Subjects
datagrabber = traits.Instance(Data, ())
#Normalization
norm_template = traits.File(mandatory=True,desc='Template to warp to')
use_nearest = traits.Bool(False,desc="use nearest neighbor interpolation")
do_segment = traits.Bool(True)
surf_dir = traits.Directory()
moving_images_4D = traits.Bool(True, usedefault=True, desc="True if your moving image inputs \
are time series images, False if they are 3-dimensional")
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
save_script_only = traits.Bool(False)
# Buttons
check_func_datagrabber = Button("Check")
def _check_func_datagrabber_fired(self):
subs = self.subjects
template = [self.inputs_template,
self.meanfunc_template,
self.fsl_mat_template,
self.unwarped_brain_template,
self.affine_transformation_template,
self.warp_field_template]
for s in subs:
for t in template:
try:
temp = glob(os.path.join(self.base_dir,t%s))
except TypeError:
temp = []
for f in self.fwhm:
temp.append(glob(os.path.join(self.base_dir,t%(s,f))))
print temp
class config(HasTraits):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
sink_dir = Directory(mandatory=False,
desc="Location to store BIPS results")
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
save_script_only = traits.Bool(False)
# Execution
run_using_plugin = Bool(
False,
usedefault=True,
desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS",
"PBSGraph",
"MultiProc",
"SGE",
"Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q many"},
usedefault=True,
desc='Plugin arguments.')
# Subjects
datagrabber = traits.Instance(Data, ())
# Motion Correction
do_slicetiming = Bool(True,
usedefault=True,
desc="Perform slice timing correction")
SliceOrder = traits.List(traits.Int)
TR = traits.Float(1.0, mandatory=True, desc="TR of functional")
motion_correct_node = traits.Enum(
'nipy',
'fsl',
'spm',
'afni',
desc="motion correction algorithm to use",
usedefault=True,
)
use_metadata = traits.Bool(True)
order = traits.Enum('motion_slicetime',
'slicetime_motion',
use_default=True)
loops = traits.List([5], traits.Int(5), usedefault=True)
#between_loops = traits.Either("None",traits.List([5]),usedefault=True)
speedup = traits.List([5], traits.Int(5), usedefault=True)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
# Directories
base_dir = Directory(
os.path.abspath('.'),
mandatory=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
save_script_only = traits.Bool(False)
datagrabber = traits.Instance(Data, ())
# Regression
run_one_sample_T_test = traits.Bool(True)
run_regression = traits.Bool()
design_csv = traits.File(desc="design .csv file")
reg_contrasts = traits.Code(
desc=
"function named reg_contrasts which takes in 0 args and returns contrasts"
)
use_regressors = traits.Bool()
estimation_method = traits.Enum('Classical', 'Bayesian', 'Bayesian2')
include_intercept = traits.Bool(True)
#Normalization
norm_template = traits.File(desc='Template of files')
use_mask = traits.Bool(False)
mask_file = traits.File(desc='already binarized mask file to use')
#Correction:
p_threshold = traits.Float(0.05)
height_threshold = traits.Float(0.05)
min_cluster_size = traits.Int(25)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
# Buttons
check_func_datagrabber = Button("Check")
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
save_script_only = traits.Bool(False)
# Subjects
datagrabber = traits.Instance(Data, ())
dtype = traits.Enum('float', 'short', 'bool', 'int')
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
sink_dir = Directory(os.path.abspath('.'),
mandatory=True,
desc="Location where the BIP will store the results")
save_script_only = traits.Bool(False)
datagrabber = traits.Instance(Data, ())
use_advanced_options = Bool(False)
advanced_options = traits.Code()
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
save_script_only = traits.Bool(False)
sink_dir = Directory(mandatory=True, desc="Location to store results")
# Subjects
datagrabber = traits.Instance(Data, ())
name = traits.String('mean')
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(HasTraits):
uuid = traits.Str(desc="UUID")
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
base_dir = Directory(
os.path.abspath('.'),
mandatory=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
surf_dir = Directory(os.environ['SUBJECTS_DIR'],
desc='Freesurfer subjects dir')
save_script_only = traits.Bool(False)
# Execution
run_using_plugin = Bool(
False,
usedefault=True,
desc="True to run pipeline with plugin, False to run serially")
plugin = traits.Enum("PBS",
"MultiProc",
"SGE",
"Condor",
usedefault=True,
desc="plugin to use, if run_using_plugin=True")
plugin_args = traits.Dict({"qsub_args": "-q max10"},
usedefault=True,
desc='Plugin arguments.')
test_mode = Bool(
False,
mandatory=False,
usedefault=True,
desc='Affects whether where and if the workflow keeps its \
intermediary files. True to keep intermediary files. '
)
# Subjects
subjects = traits.List(
traits.Str,
mandatory=True,
usedefault=True,
desc="Subject id's. Note: These MUST match the subject id's in the \
Freesurfer directory. For simplicity, the subject id's should \
also match with the location of individual functional files."
)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
sink_dir = Directory(os.path.abspath('.'), mandatory=True, desc="Location where the BIP will store the results")
save_script_only = traits.Bool(False)
# Subjects
datagrabber = traits.Instance(Data, ())
# Stimulus Motion
subjectinfo = traits.Code()
is_sparse = traits.Bool(False)
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
# Directories
base_dir = Directory(
os.path.abspath('.'),
mandatory=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
# Subjects
datagrabber = traits.Instance(Data, ())
#Normalization
norm_template = traits.File(mandatory=True, desc='Template to warp to')
use_nearest = traits.Bool(False, desc="use nearest neighbor interpolation")
do_segment = traits.Bool(True)
surf_dir = traits.Directory()
moving_images_4D = traits.Bool(True,
usedefault=True,
desc="True if your moving image inputs \
are time series images, False if they are 3-dimensional"
)
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
save_script_only = traits.Bool(False)
# Buttons
check_func_datagrabber = Button("Check")
def _check_func_datagrabber_fired(self):
subs = self.subjects
template = [
self.inputs_template, self.meanfunc_template,
self.fsl_mat_template, self.unwarped_brain_template,
self.affine_transformation_template, self.warp_field_template
]
for s in subs:
for t in template:
try:
temp = glob(os.path.join(self.base_dir, t % s))
except TypeError:
temp = []
for f in self.fwhm:
temp.append(
glob(os.path.join(self.base_dir, t % (s, f))))
print temp
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc="Workflow Description")
# Directories
sink_dir = Directory(os.path.abspath('.'), mandatory=True, desc="Location where the BIP will store the results")
surf_dir = Directory(mandatory=True, desc= "Freesurfer subjects directory")
save_script_only = traits.Bool(False)
datagrabber = traits.Instance(Data, ())
surface_template = traits.Enum("fsaverage","fsaverage5","fsaverage6","fsaverage4","subject")
test_name = traits.String('FS_one_sample_t_test')
# First Level
#advanced_options
use_advanced_options = Bool(False)
advanced_options = traits.Code()
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
base_dir = Directory(
exists=True,
desc='Base directory of data. (Should be subject-independent)')
sink_dir = Directory(mandatory=True,
desc="Location where the BIP will store the results")
field_dir = Directory(
exists=True,
desc="Base directory of field-map data (Should be subject-independent) \
Set this value to None if you don't want fieldmap distortion correction"
)
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
json_sink = Directory(mandatory=False, desc="Location to store json_files")
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
# Subjects
subjects = traits.List(
traits.Str,
mandatory=True,
usedefault=True,
desc=
"Subject id's. These subjects must match the ones that have been run in your preproc config"
)
preproc_config = traits.File(desc="preproc config file")
debug = traits.Bool(True)
#Preprocessing Info
use_custom_ROI_list_file = Bool(
False,
usedefault=True,
desc=
"True to limit the produced TSNR table to a more selective list of ROIs"
)
custom_ROI_list_file = traits.File(
desc="Enter the full path to your customized FreeSurferColorLUT.txt")
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
save_script_only = traits.Bool(False)
class config(BaseWorkflowConfig):
uuid = traits.Str(desc="UUID")
desc = traits.Str(desc='Workflow description')
# Directories
working_dir = Directory(mandatory=True,
desc="Location of the Nipype working directory")
crash_dir = Directory(mandatory=False,
desc="Location to store crash files")
surf_dir = Directory(mandatory=True, desc="Freesurfer subjects directory")
save_script_only = traits.Bool(False)
# Subjects
interpolation = traits.Enum('trilin', 'nearest', usedefault=True)
datagrabber = traits.Instance(Data, ())
# Advanced Options
use_advanced_options = traits.Bool()
advanced_script = traits.Code()
