def init_spaces(checkpoint=True):
"""Initialize the :attr:`~workflow.spaces` setting."""
from niworkflows.utils.spaces import Reference, SpatialReferences
spaces = execution.output_spaces or SpatialReferences()
if not isinstance(spaces, SpatialReferences):
spaces = SpatialReferences([
ref for s in spaces.split(" ") for ref in Reference.from_string(s)
])
if checkpoint and not spaces.is_cached():
spaces.checkpoint()
# # Add the default standard space if not already present (required by several sub-workflows)
# if "MNI152NLin2009cAsym" not in spaces.get_spaces(nonstandard=False, dim=(3,)):
# spaces.add(Reference("MNI152NLin2009cAsym", {}))
# Ensure user-defined spatial references for outputs are correctly parsed.
# Certain options require normalization to a space not explicitly defined by users.
# These spaces will not be included in the final outputs.
# if workflow.use_aroma:
# # Make sure there's a normalization to FSL for AROMA to use.
# spaces.add(Reference("MNI152NLin6Asym", {"res": "2"}))
cifti_output = workflow.cifti_output
if workflow.cifti_output:
# CIFTI grayordinates to corresponding FSL-MNI resolutions.
vol_res = "2" if cifti_output == "91k" else "1"
spaces.add(Reference("fsaverage", {"den": "164k"}))
spaces.add(Reference("MNI152NLin6Asym", {"res": vol_res}))
# Make the SpatialReferences object available
workflow.spaces = spaces
def init_spaces(checkpoint=True):
"""Initialize the :attr:`~workflow.spaces` setting."""
from niworkflows.utils.spaces import Reference, SpatialReferences
spaces = execution.output_spaces or SpatialReferences()
if not isinstance(spaces, SpatialReferences):
spaces = SpatialReferences([
ref for s in spaces.split(' ') for ref in Reference.from_string(s)
])
if checkpoint and not spaces.is_cached():
spaces.checkpoint()
# Make the SpatialReferences object available
workflow.spaces = spaces
def init_spaces(checkpoint=True):
"""Initialize the :attr:`~workflow.spaces` setting."""
from niworkflows.utils.spaces import Reference, SpatialReferences
spaces = execution.output_spaces or SpatialReferences()
if not isinstance(spaces, SpatialReferences):
spaces = SpatialReferences(
[ref for s in spaces.split(' ')
for ref in Reference.from_string(s)]
)
if checkpoint and not spaces.is_cached():
spaces.checkpoint()
# Add the default standard space if not already present (required by several sub-workflows)
if "Fischer344" not in spaces.get_spaces(nonstandard=False, dim=(3,)):
spaces.add(
Reference("Fischer344", {})
)
# Make the SpatialReferences object available
workflow.spaces = spaces
MergeColumns,
ApplyTransforms,
MakeResultdicts,
ResultdictDatasink,
Vals,
FilterRegressor,
)
from ...resource import get as getresource
from ...utils import firststr, loadints
from ..constants import constants
from ..memory import MemoryCalculator
spaces = SpatialReferences([Reference("MNI152NLin6Asym", {"res": "2"})])
if not spaces.is_cached():
spaces.checkpoint()
def _aroma_column_names(melodic_mix=None, aroma_noise_ics=None):
import numpy as np
from halfpipe.utils import ncol
ncomponents = ncol(melodic_mix)
leading_zeros = int(np.ceil(np.log10(ncomponents)))
column_names = []
for i in range(1, ncomponents + 1):
if i in aroma_noise_ics:
column_names.append(f"aroma_noise_{i:0{leading_zeros}d}")
else:
column_names.append(f"aroma_signal_{i:0{leading_zeros}d}")