nimare.meta.kernel
.KernelTransformer
- class KernelTransformer[source]
Bases:
nimare.base.Transformer
Base class for modeled activation-generating methods in
kernel
.Coordinate-based meta-analyses leverage coordinates reported in neuroimaging papers to simulate the thresholded statistical maps from the original analyses. This generally involves convolving each coordinate with a kernel (typically a Gaussian or binary sphere) that may be weighted based on some additional measure, such as statistic value or sample size.
Notes
All extra (non-ijk) parameters for a given kernel should be overrideable as parameters to __init__, so we can access them with get_params() and also apply them to datasets with missing data.
- set_params(**params)[source]
Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form
<component>__<parameter>
so that it’s possible to update each component of a nested object.- Returns
self
- transform(dataset, masker=None, return_type='image')[source]
Generate modeled activation images for each Contrast in dataset.
- Parameters
dataset (
Dataset
orpandas.DataFrame
) – Dataset for which to make images. Can be a DataFrame if necessary.masker (img_like or None, optional) – Mask to apply to MA maps. Required if
dataset
is a DataFrame. If None (anddataset
is a Dataset), the Dataset’s masker attribute will be used. Default is None.return_type ({‘array’, ‘image’, ‘dataset’}, optional) – Whether to return a numpy array (‘array’), a list of niimgs (‘image’), or a Dataset with MA images saved as files (‘dataset’). Default is ‘image’.
- Returns
imgs ((C x V)
numpy.ndarray
orlist
ofnibabel.Nifti1Image
orDataset
) – If return_type is ‘array’, a 2D numpy array (C x V), where C is contrast and V is voxel. If return_type is ‘image’, a list of modeled activation images (one for each of the Contrasts in the input dataset). If return_type is ‘dataset’, a new Dataset object with modeled activation images saved to files and referenced in the Dataset.images attribute.- Variables