update docs

Author: josephmje

docs/dmriprep.workflows.fieldmap.rst

@@ -4,14 +4,6 @@ dmriprep.workflows.fieldmap package
 Submodules
 ----------
 
-dmriprep.workflows.fieldmap.ants module
----------------------------------------
-
-.. automodule:: dmriprep.workflows.fieldmap.ants
-   :members:
-   :undoc-members:
-   :show-inheritance:
-
 dmriprep.workflows.fieldmap.base module
 ---------------------------------------
 

docs/workflows.rst

@@ -12,26 +12,16 @@ A (very) high-level view of the simplest pipeline is presented below.
     from collections import namedtuple, OrderedDict
     from dmriprep.workflows.base import init_single_subject_wf
     BIDSLayout = namedtuple('BIDSLayout', ['root'])
-    wf = init_single_subject_wf(
-        subject_id='test',
-        session_list=[],
-        name='single_subject_wf',
-        layout=BIDSLayout,
-        output_dir='.',
-        work_dir='.',
-        ignore=[],
-        b0_thresh=5,
-        output_resolution=(1, 1, 1),
-        bet_dwi=0.3,
-        bet_mag=0.3,
-        omp_nthreads=1,
-        synb0_dir=''
-    )
+    wf = init_single_subject_wf(subject_id='test', session_list=[], name='single_subject_wf', layout=BIDSLayout, output_dir='.', work_dir='.', ignore=[], b0_thresh=5, output_resolution=(1, 1, 1), bet_dwi=0.3, bet_mag=0.3, omp_nthreads=1, synb0_dir='')
 
 T1w preprocessing
 -----------------
 :mod:`dmriprep.workflows.anatomical.init_anat_preproc_wf`
 
+The T1w preprocessing workflow skull strips the T1w scan for later use in
+tractography or susceptibility distortion correction if using ANTs or
+BrainSuite. It uses ``init_brain_extraction_wf`` from `niworkflows`
+
 .. workflow::
     :graph2use: orig
     :simple_form: yes
@@ -44,28 +34,16 @@ DWI preprocessing
 -----------------
 :mod:`dmriprep.workflows.dwi.base.init_dwi_preproc_wf`
 
+Preprocessing of DWI files is split into multiple sub-workflows described below.
+
 .. workflow::
     :graph2use: orig
     :simple_form: yes
 
     from collections import namedtuple
     from dmriprep.workflows.dwi import init_dwi_preproc_wf
     BIDSLayout = namedtuple('BIDSLayout', ['root'])
-    wf = init_dwi_preproc_wf(
-        layout=BIDSLayout('.'),
-        subject_id='dmripreptest',
-        dwi_file='/madeup/path/sub-01_dwi.nii.gz',
-        metadata={},
-        b0_thresh=5,
-        output_resolution=(1, 1, 1),
-        bet_dwi=0.3,
-        bet_mag=0.3,
-        omp_nthreads=1,
-        ignore=[],
-        synb0_dir='.'
-    )
-
-Preprocessing of DWI files is split into multiple sub-workflows described below.
+    wf = init_dwi_preproc_wf(layout=BIDSLayout('.'), subject_id='dmripreptest', dwi_file='/madeup/path/sub-01_dwi.nii.gz', metadata={'PhaseEncodingDirection': '-j', 'TotalReadoutTime': 0.001}, b0_thresh=5, output_resolution=(1, 1, 1), bet_dwi=0.3, bet_mag=0.3, omp_nthreads=1, ignore=[], synb0_dir='')
 
 Concatenating Scans
 ^^^^^^^^^^^^^^^^^^^
@@ -134,7 +112,7 @@ You can use it in this pipeline by generating the synb0s for the subject(s) and
 Once you have a directory of synb0s (recommended to place as derivatives of bids folder, ex. bids/derivatives/synb0/sub-XX), then you are ready to run the pipeline using them! Just run dmripreproc as you usually would, with bids_dir and output_dir, but now add "--synb0_dir <your_synb0_directory>" to your command.
 The synb0 acqp for topup and eddy will be automatically generated in the pipeline in the following format:
 
-..code-block:: console
+.. code-block:: console
 
     0 -1 0 <total_readout_time>
     0 1 0 0