AFQ.api.bundle_dict#

Module Contents#

Classes#

BundleDict

Create a bundle dictionary, needed for the segmentation.

PediatricBundleDict

Create a bundle dictionary, needed for the segmentation.
class AFQ.api.bundle_dict.BundleDict(bundle_info=BUNDLES, seg_algo='afq', resample_to=None, resample_subject_to=False, keep_in_memory=False)[source]#

Bases: collections.abc.MutableMapping

Create a bundle dictionary, needed for the segmentation.

Parameters
bundle_infolist or dict, optional

A list of the bundles to be used, or a dictionary defining custom bundles. See Defining Custom Bundle Dictionaries in the usage section of pyAFQ’s documentation for details. Default: AFQ.api.bundle_dict.BUNDLES

seg_algo: One of {“afq”, “reco”, “reco16”, “reco80”}
The bundle segmentation algorithm to use.

“afq” : Use waypoint ROIs + probability maps, as described in [Yeatman2012] “reco” / “reco16” : Use Recobundles [Garyfallidis2017] with a 16-bundle set. “reco80”: Use Recobundles with an 80-bundle set.

resample_toNifti1Image or bool, optional

If there are bundles in bundle_info with the ‘space’ attribute set to ‘template’, or with no ‘space’ attribute, their images (all ROIs and probability maps) will be resampled to the affine and shape of this image. If None, the MNI template will be used. If False, no resampling will be done. Default: None

resample_subject_toNifti1Image or bool, optional

If there are bundles in bundle_info with the ‘space’ attribute set to ‘subject’, their images (all ROIs and probability maps) will be resampled to the affine and shape of this image. If False, no resampling will be done. Default: None

keep_in_memorybool, optional

Whether, once loaded, all ROIs and probability maps will stay loaded in memory within this object. By default, ROIs are loaded into memory on demand and no references to ROIs are kept, other than their paths. The default 18 bundles use ~6GB when all loaded. Default: False

Examples

# import OR ROIs and create a custom bundle dict # from them import AFQ.data.fetch as afd or_rois = afd.read_or_templates()

bundles = BundleDict({
“L_OR”: {
“include”: [

or_rois[“left_OR_1”], # these can be paths to Nifti files or_rois[“left_OR_2”]], # or they can Nifti images

“exclude”: [

or_rois[“left_OP_MNI”], or_rois[“left_TP_MNI”], or_rois[“left_pos_thal_MNI”]],

“start”: or_rois[‘left_thal_MNI’], “end”: or_rois[‘left_V1_MNI’], “cross_midline”: False,

}, “R_OR”: {

“include”: [

or_rois[“right_OR_1”], or_rois[“right_OR_2”]],

“exclude”: [

or_rois[“right_OP_MNI”], or_rois[“right_TP_MNI”], or_rois[“right_pos_thal_MNI”]],

“start”: or_rois[‘right_thal_MNI’], “end”: or_rois[‘right_V1_MNI’], “cross_midline”: False

}

})

load_templates()[source]#

Loads templates for generating bundle dictionaries from bundle names.

_gen(bundle_name)[source]#

Given a bundle name, load its bundle’s dictionary describing the bundle.

gen_all()[source]#

If bundle_info is a list of names, this will load each bundle’s dictionary describing the bundle.

__getitem__(key)[source]#
__setitem__(key, item)[source]#
__len__()[source]#
__delitem__(key)[source]#
__iter__()[source]#
copy()[source]#

Generates a copy of this BundleDict where the internal dictionary is a copy of this BundleDict’s internal dictionary. Useful if you want to add or remove bundles from a copy of a BundleDict.

Returns
bundle_dictBundleDict

Euclidean norms of vectors.

apply_to_rois(b_name, func, *args, **kwargs)[source]#

Applies some transformation to all ROIs (include, exclude, end, start) and the prob_map in a given bundle.

Parameters
b_namename

bundle name of bundle whose ROIs will be transformed.

funcfunction

function whose first argument must be a Nifti1Image and which returns a Nifti1Image

*args

Additional arguments for func

**kwargs

Optional arguments for func

Returns
Dictionary containing the old values of all ROIs and prob_map
_resample_roi(b_name)[source]#

Given a bundle name, resample all ROIs and prob maps into either template or subject space for that bundle, depending on its “space” attribute.

Parameters
b_namestr

Name of the bundle to be resampled.

__add__(other)[source]#
class AFQ.api.bundle_dict.PediatricBundleDict(bundle_info=PEDIATRIC_BUNDLES, seg_algo='afq', resample_to=None, resample_subject_to=False, keep_in_memory=False)[source]#

Bases: BundleDict

Create a bundle dictionary, needed for the segmentation.

Parameters
bundle_infolist or dict, optional

A list of the bundles to be used, or a dictionary defining custom bundles. See Defining Custom Bundle Dictionaries in the usage section of pyAFQ’s documentation for details. Default: AFQ.api.bundle_dict.BUNDLES

seg_algo: One of {“afq”, “reco”, “reco16”, “reco80”}
The bundle segmentation algorithm to use.

“afq” : Use waypoint ROIs + probability maps, as described in [Yeatman2012] “reco” / “reco16” : Use Recobundles [Garyfallidis2017] with a 16-bundle set. “reco80”: Use Recobundles with an 80-bundle set.

resample_toNifti1Image or bool, optional

If there are bundles in bundle_info with the ‘space’ attribute set to ‘template’, or with no ‘space’ attribute, their images (all ROIs and probability maps) will be resampled to the affine and shape of this image. If None, the MNI template will be used. If False, no resampling will be done. Default: None

resample_subject_toNifti1Image or bool, optional

If there are bundles in bundle_info with the ‘space’ attribute set to ‘subject’, their images (all ROIs and probability maps) will be resampled to the affine and shape of this image. If False, no resampling will be done. Default: None

keep_in_memorybool, optional

Whether, once loaded, all ROIs and probability maps will stay loaded in memory within this object. By default, ROIs are loaded into memory on demand and no references to ROIs are kept, other than their paths. The default 18 bundles use ~6GB when all loaded. Default: False

Examples

# import OR ROIs and create a custom bundle dict # from them import AFQ.data.fetch as afd or_rois = afd.read_or_templates()

bundles = BundleDict({
“L_OR”: {
“include”: [

or_rois[“left_OR_1”], # these can be paths to Nifti files or_rois[“left_OR_2”]], # or they can Nifti images

“exclude”: [

or_rois[“left_OP_MNI”], or_rois[“left_TP_MNI”], or_rois[“left_pos_thal_MNI”]],

“start”: or_rois[‘left_thal_MNI’], “end”: or_rois[‘left_V1_MNI’], “cross_midline”: False,

}, “R_OR”: {

“include”: [

or_rois[“right_OR_1”], or_rois[“right_OR_2”]],

“exclude”: [

or_rois[“right_OP_MNI”], or_rois[“right_TP_MNI”], or_rois[“right_pos_thal_MNI”]],

“start”: or_rois[‘right_thal_MNI’], “end”: or_rois[‘right_V1_MNI’], “cross_midline”: False

}

})

load_templates()[source]#

Loads templates for generating bundle dictionaries from bundle names.