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Ben Cipollini
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fix: add blank line between file docstring and first import (needed for sphinx)
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build_docs.py

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python setup.py build_sphinx
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"""
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from __future__ import print_function
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# Standard library imports

doc/sphinxext/autosummary_generate.py

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./ext/autosummary_generate.py -o source/generated source/*.rst
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"""
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from __future__ import print_function
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import glob, re, inspect, os, optparse, pydoc
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from autosummary import import_by_name

doc/sphinxext/numpy_ext/docscrape.py

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"""Extract reference documentation from the NumPy source tree.
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"""
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from __future__ import print_function
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from future import standard_library
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standard_library.install_aliases()

doc/sphinxext/numpy_ext/numpydoc.py

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.. [1] https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt
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"""
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from __future__ import absolute_import
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from builtins import object
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examples/fmri_ants_openfmri.py

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python fmri_ants_openfmri.py --datasetdir ds107
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"""
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from __future__ import division
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from builtins import range
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examples/fmri_freesurfer_smooth.py

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=====================
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"""
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from __future__ import print_function
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from builtins import range
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examples/fmri_fsl.py

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First tell python where to find the appropriate functions.
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"""
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from __future__ import print_function
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from __future__ import division
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from builtins import range

examples/fmri_fsl_feeds.py

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You can find it at http://www.fmrib.ox.ac.uk/fsl/feeds/doc/index.html
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"""
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from __future__ import division
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from builtins import range
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fsl.FSLCommand.set_default_output_type('NIFTI_GZ')
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"""
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Experiment specific components
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------------------------------
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modelspec.inputs.time_repetition = TR
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modelspec.inputs.high_pass_filter_cutoff = 100
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modelspec.inputs.subject_info = [Bunch(conditions=['Visual','Auditory'],
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onsets=[list(range(0,int(180*TR),60)),list(range(0,int(180*TR),90))],
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durations=[[30], [45]],
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amplitudes=None,
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tmod=None,
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pmod=None,
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regressor_names=None,
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regressors=None)]
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onsets=[list(range(0,int(180*TR),60)),list(range(0,int(180*TR),90))],
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durations=[[30], [45]],
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amplitudes=None,
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tmod=None,
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pmod=None,
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regressor_names=None,
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regressors=None)]
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modelfit = create_modelfit_workflow(f_contrasts=True)
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modelfit.inputs.inputspec.interscan_interval = TR
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if __name__ == '__main__':
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l1pipeline.run()
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examples/fmri_fsl_reuse.py

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First tell python where to find the appropriate functions.
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"""
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from __future__ import print_function
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from __future__ import division
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from builtins import range

examples/fmri_nipy_glm.py

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python fmri_nipy_glm.py
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"""
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from __future__ import print_function
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from builtins import range
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