Slice Timing Tool
[+ show/hide code]# Pilot imports
from caps.toy_datasets import get_sample_data
from capsul.study_config import StudyConfig
from capsul.utils.sorted_dictionary import SortedDictionary
from nsap.lib.base import ensure_is_dir
# Get toy dataset
toy_dataset = get_sample_data("localizer")
# Create
st_pipeline = SliceTiming()
# Print Input Spec
print st_pipeline.get_input_spec()
# Initialize SliceTiming pipeline
st_pipeline.fmri_image = toy_dataset.fmri
st_pipeline.select_slicing = slicing_option
st_pipeline.force_repetition_time = toy_dataset.TR
st_pipeline.force_slice_times = list(range(40))
# Execute the pipeline
st_working_dir = os.path.join(working_dir, "slice_timing")
ensure_is_dir(st_working_dir)
default_config = SortedDictionary(
("output_directory", st_working_dir),
("fsl_config", "/etc/fsl/4.1/fsl.sh"),
("use_fsl", True),
("spm_directory", "/i2bm/local/spm8"),
("matlab_exec", "/neurospin/local/bin/matlab"),
("spm_exec_cmd", "/i2bm/local/bin/spm8"),
("use_spm_mcr", False),
("use_smart_caching", True),
("generate_logging", True)
)
study = StudyConfig(default_config)
study.run(st_pipeline)
# Print all pipeline outputs
print "\nOUTPUTS\n"
for trait_name, trait_value in st_pipeline.get_outputs().iteritems():
print "{0}: {1}".format(trait_name, trait_value)