def individual_reports(settings, name='ReportsWorkflow'):
"""Encapsulates nodes writing plots"""
from mriqc.interfaces import PlotMosaic
from mriqc.reports import individual_html
verbose = settings.get('verbose_reports', False)
pages = 2
extra_pages = 0
if verbose:
extra_pages = 7
workflow = pe.Workflow(name=name)
inputnode = pe.Node(niu.IdentityInterface(fields=[
'orig', 'brainmask', 'headmask', 'airmask', 'artmask', 'segmentation',
'inu_corrected', 'noisefit', 'in_iqms', 'mni_report'
]),
name='inputnode')
# T1w mosaic plot
mosaic_zoom = pe.Node(PlotMosaic(out_file='plot_anat_mosaic1_zoomed.svg',
title='T1w - zoomed',
cmap='Greys_r'),
name='PlotMosaicZoomed')
mosaic_noise = pe.Node(PlotMosaic(out_file='plot_anat_mosaic2_noise.svg',
title='T1w - noise enhanced',
only_noise=True,
cmap='viridis_r'),
name='PlotMosaicNoise')
mplots = pe.Node(niu.Merge(pages + extra_pages), name='MergePlots')
rnode = pe.Node(niu.Function(input_names=['in_iqms', 'in_plots'],
output_names=['out_file'],
function=individual_html),
name='GenerateReport')
# Link images that should be reported
dsplots = pe.Node(nio.DataSink(base_directory=settings['output_dir'],
parameterization=False),
name='dsplots')
dsplots.inputs.container = 'reports'
workflow.connect([
(inputnode, rnode, [('in_iqms', 'in_iqms')]),
(inputnode, mosaic_zoom, [('orig', 'in_file'),
('brainmask', 'bbox_mask_file')]),
(inputnode, mosaic_noise, [('orig', 'in_file')]),
(mosaic_zoom, mplots, [('out_file', "in1")]),
(mosaic_noise, mplots, [('out_file', "in2")]),
(mplots, rnode, [('out', 'in_plots')]),
(rnode, dsplots, [('out_file', "@html_report")]),
])
if not verbose:
return workflow
from mriqc.interfaces.viz import PlotContours
from mriqc.interfaces.viz_utils import plot_bg_dist
plot_bgdist = pe.Node(niu.Function(input_names=['in_file'],
output_names=['out_file'],
function=plot_bg_dist),
name='PlotBackground')
plot_segm = pe.Node(PlotContours(display_mode='z',
levels=[.5, 1.5, 2.5],
cut_coords=10,
colors=['r', 'g', 'b']),
name='PlotSegmentation')
plot_bmask = pe.Node(PlotContours(display_mode='z',
levels=[.5],
colors=['r'],
cut_coords=10,
out_file='bmask'),
name='PlotBrainmask')
plot_airmask = pe.Node(PlotContours(display_mode='x',
levels=[.5],
colors=['r'],
cut_coords=6,
out_file='airmask'),
name='PlotAirmask')
plot_headmask = pe.Node(PlotContours(display_mode='x',
levels=[.5],
colors=['r'],
cut_coords=6,
out_file='headmask'),
name='PlotHeadmask')
plot_artmask = pe.Node(PlotContours(display_mode='z',
levels=[.5],
colors=['r'],
cut_coords=10,
out_file='artmask',
saturate=True),
name='PlotArtmask')
workflow.connect([
(inputnode, plot_segm, [('orig', 'in_file'),
('segmentation', 'in_contours')]),
(inputnode, plot_bmask, [('orig', 'in_file'),
('brainmask', 'in_contours')]),
(inputnode, plot_headmask, [('orig', 'in_file'),
('headmask', 'in_contours')]),
(inputnode, plot_airmask, [('orig', 'in_file'),
('airmask', 'in_contours')]),
(inputnode, plot_artmask, [('orig', 'in_file'),
('artmask', 'in_contours')]),
(inputnode, plot_bgdist, [('noisefit', 'in_file')]),
(inputnode, mplots, [('mni_report', "in%d" % (pages + 1))]),
(plot_bmask, mplots, [('out_file', 'in%d' % (pages + 2))]),
(plot_segm, mplots, [('out_file', 'in%d' % (pages + 3))]),
(plot_artmask, mplots, [('out_file', 'in%d' % (pages + 4))]),
(plot_headmask, mplots, [('out_file', 'in%d' % (pages + 5))]),
(plot_airmask, mplots, [('out_file', 'in%d' % (pages + 6))]),
(plot_bgdist, mplots, [('out_file', 'in%d' % (pages + 7))])
])
return workflow
def individual_reports(settings, name='ReportsWorkflow'):
"""Encapsulates nodes writing plots"""
from mriqc.interfaces import PlotMosaic, PlotSpikes
from mriqc.reports import individual_html
verbose = settings.get('verbose_reports', False)
pages = 5
extra_pages = 0
if verbose:
extra_pages = 3
workflow = pe.Workflow(name=name)
inputnode = pe.Node(niu.IdentityInterface(fields=[
'in_iqms', 'orig', 'epi_mean', 'brainmask', 'hmc_fd', 'epi_parc',
'in_dvars', 'in_stddev', 'outliers', 'in_spikes', 'exclude_index',
'mni_report']),
name='inputnode')
spmask = pe.Node(niu.Function(
input_names=['in_file', 'in_mask'], output_names=['out_file', 'out_plot'],
function=spikes_mask), name='SpikesMask')
spikes = pe.Node(Spikes(), name='SpikesFinder')
spikes_bg = pe.Node(Spikes(no_zscore=True, detrend=False), name='SpikesFinderBgMask')
bigplot = pe.Node(niu.Function(
input_names=['in_func', 'in_mask', 'in_segm', 'in_spikes', 'in_spikes_bg',
'fd', 'dvars', 'outliers'],
output_names=['out_file'], function=_big_plot), name='BigPlot')
workflow.connect([
(inputnode, spikes_bg, [('orig', 'in_file')]),
(inputnode, spikes, [('orig', 'in_file'),
('brainmask', 'in_mask')]),
(inputnode, spmask, [('orig', 'in_file')]),
(inputnode, bigplot, [('orig', 'in_func'),
('brainmask', 'in_mask'),
('hmc_fd', 'fd'),
('in_dvars', 'dvars'),
('epi_parc', 'in_segm'),
('outliers', 'outliers')]),
(spikes, bigplot, [('out_tsz', 'in_spikes')]),
(spikes_bg, bigplot, [('out_tsz', 'in_spikes_bg')]),
(spmask, spikes_bg, [('out_file', 'in_mask')]),
])
mosaic_mean = pe.Node(PlotMosaic(
out_file='plot_func_mean_mosaic1.svg',
title='EPI mean session',
cmap='Greys_r'),
name='PlotMosaicMean')
mosaic_stddev = pe.Node(PlotMosaic(
out_file='plot_func_stddev_mosaic2_stddev.svg',
title='EPI SD session',
cmap='viridis'), name='PlotMosaicSD')
mosaic_spikes = pe.Node(PlotSpikes(
out_file='plot_spikes.svg', cmap='viridis',
title='High-Frequency spikes'),
name='PlotSpikes')
mplots = pe.Node(niu.Merge(pages + extra_pages), name='MergePlots')
rnode = pe.Node(niu.Function(
input_names=['in_iqms', 'in_plots', 'exclude_index', 'wf_details'],
output_names=['out_file'], function=individual_html), name='GenerateReport')
wf_details = []
if settings.get('hmc_afni', False):
wf_details.append('Framewise Displacement was computed using AFNI <code>3dvolreg</code>')
else:
wf_details.append('Framewise Displacement was computed using FSL <code>mcflirt</code>')
rnode.inputs.wf_details = wf_details
# Link images that should be reported
dsplots = pe.Node(nio.DataSink(
base_directory=settings['output_dir'], parameterization=False), name='dsplots')
dsplots.inputs.container = 'reports'
workflow.connect([
(inputnode, rnode, [('in_iqms', 'in_iqms'),
('exclude_index', 'exclude_index')]),
(inputnode, mosaic_mean, [('epi_mean', 'in_file')]),
(inputnode, mosaic_stddev, [('in_stddev', 'in_file')]),
(inputnode, mosaic_spikes, [('orig', 'in_file'),
('in_spikes', 'in_spikes')]),
(mosaic_mean, mplots, [('out_file', 'in1')]),
(mosaic_stddev, mplots, [('out_file', 'in2')]),
(bigplot, mplots, [('out_file', 'in3')]),
(mosaic_spikes, mplots, [('out_file', 'in4')]),
(inputnode, mplots, [('mni_report', 'in5')]),
(mplots, rnode, [('out', 'in_plots')]),
(rnode, dsplots, [('out_file', '@html_report')]),
])
if not verbose:
return workflow
mosaic_zoom = pe.Node(PlotMosaic(
out_file='plot_anat_mosaic1_zoomed.svg',
title='Zoomed-in EPI mean',
cmap='Greys_r'), name='PlotMosaicZoomed')
mosaic_noise = pe.Node(PlotMosaic(
out_file='plot_anat_mosaic2_noise.svg',
title='Enhanced noise in EPI mean',
only_noise=True, cmap='viridis_r'), name='PlotMosaicNoise')
# Verbose-reporting goes here
from mriqc.interfaces.viz import PlotContours
from mriqc.interfaces.viz_utils import plot_bg_dist
plot_bmask = pe.Node(PlotContours(
display_mode='z', levels=[.5], colors=['r'], cut_coords=10,
out_file='bmask'), name='PlotBrainmask')
workflow.connect([
(inputnode, plot_bmask, [('epi_mean', 'in_file'),
('brainmask', 'in_contours')]),
(inputnode, mosaic_zoom, [('epi_mean', 'in_file'),
('brainmask', 'bbox_mask_file')]),
(inputnode, mosaic_noise, [('epi_mean', 'in_file')]),
(mosaic_zoom, mplots, [('out_file', 'in%d' % (pages + 1))]),
(mosaic_noise, mplots, [('out_file', 'in%d' % (pages + 2))]),
(plot_bmask, mplots, [('out_file', 'in%d' % (pages + 3))])
])
return workflow