#!/usr/bin/env python
# -*- coding: utf-8 -*-
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
Base fieldmap estimation
------------------------
* Subject can have phase-difference data.
* Subject can have a fieldmap acquisition.
"""
from __future__ import print_function, division, absolute_import, unicode_literals
[docs]def init_fmap_estimator_wf(fmap_bids, reportlets_dir, omp_nthreads,
fmap_bspline):
"""
This workflow selects the fieldmap estimation data available for the subject and
returns the estimated fieldmap in mm, along with a corresponding reference image.
Current implementation applies the first type of fieldmap estimation found in the
following order of precedence:
* "Natural" fieldmaps
* Phase-difference fieldmaps
Outputs:
fmap
The estimated fieldmap itself IN UNITS OF Hz.
fmap_ref
the anatomical reference for the fieldmap (magnitude image, corrected SEm, etc.)
fmap_mask
a brain mask for the fieldmap
"""
# pybids type options: (phase1|phase2|phasediff|epi|fieldmap)
# https://github.com/INCF/pybids/blob/213c425d8ee820f4b7a7ae96e447a4193da2f359/bids/grabbids/bids_layout.py#L63
if fmap_bids['type'] == 'fieldmap':
from .fmap import init_fmap_wf
fmap_wf = init_fmap_wf(reportlets_dir=reportlets_dir,
omp_nthreads=omp_nthreads,
fmap_bspline=fmap_bspline)
# set inputs
fmap_wf.inputs.inputnode.fieldmap = fmap_bids['fieldmap']
fmap_wf.inputs.inputnode.magnitude = fmap_bids['magnitude']
return fmap_wf
if fmap_bids['type'] == 'phasediff':
from .phdiff import init_phdiff_wf
phdiff_wf = init_phdiff_wf(reportlets_dir=reportlets_dir)
# set inputs
phdiff_wf.inputs.inputnode.phasediff = fmap_bids['phasediff']
phdiff_wf.inputs.inputnode.magnitude = [
fmap_bids['magnitude1'],
fmap_bids['magnitude2']
]
return phdiff_wf
if fmap_bids['type'] in ['phase1', 'phase2', 'epi']:
raise NotImplementedError