Note

This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the user guide for the big picture.

fmralign.methods.Procrustes¶

class fmralign.methods.Procrustes(scaling=True)[source]¶

Compute a orthogonal mixing matrix R and a scaling sc. These are calculated such that Frobenius norm ||sc RX - Y||^2 is minimized.

Parameters:

scalingboolean, optional: Determines whether a scaling parameter is applied to improve transform.

Attributes:

Rndarray (n_features, n_features): Optimal orthogonal transform
scale: float,: inferred scaling parameter

__init__(scaling=True)[source]¶

fit(X, Y)[source]¶

Fit orthogonal R s.t. ||sc XR - Y||^2

Parameters:

X: (n_samples, n_features) nd array: source data
Y: (n_samples, n_features) nd array: target data

fit_transform(X, y=None, **fit_params)¶

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.

Parameters:

Xarray-like of shape (n_samples, n_features): Input samples.
yarray-like of shape (n_samples,) or (n_samples, n_outputs), default=None: Target values (None for unsupervised transformations).
**fit_paramsdict: Additional fit parameters. Pass only if the estimator accepts additional params in its fit method.

Returns:

X_newndarray array of shape (n_samples, n_features_new): Transformed array.

get_metadata_routing()¶

Get metadata routing of this object.

Please check User Guide on how the routing mechanism works.

Returns:

routingMetadataRequest: A MetadataRequest encapsulating routing information.

get_params(deep=True)¶

Get parameters for this estimator.

Parameters:

deepbool, default=True: If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns:

paramsdict: Parameter names mapped to their values.

set_output(*, transform=None)¶

Set output container.

See Introducing the set_output API for an example on how to use the API.

Parameters:

transform{“default”, “pandas”, “polars”}, default=None

Configure output of transform and fit_transform.

“default”: Default output format of a transformer
“pandas”: DataFrame output
“polars”: Polars output
None: Transform configuration is unchanged

Added in version 1.4: “polars” option was added.

Returns:

selfestimator instance: Estimator instance.

set_params(**params)¶

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:

**paramsdict: Estimator parameters.

Returns:

selfestimator instance: Estimator instance.

transform(X)[source]¶: Transform X using optimal transform computed during fit.

Examples using `fmralign.methods.Procrustes`¶

Pairwise functional alignment.

Pairwise functional alignment on a ROI.

Alignment methods benchmark (template-based ROI case)

Pairwise surface alignment.

Alignment on simulated 2D data.

fmralign.methods.Procrustes¶

Examples using fmralign.methods.Procrustes¶

Examples using `fmralign.methods.Procrustes`¶