neuralib.imaging.widefield.svd.compute_singular_vector
- neuralib.imaging.widefield.svd.compute_singular_vector(sequences, n_components=128, **kwargs)[source]
Performs truncated singular value decomposition (SVD) on a sequence of image frames to extract dominant spatial and temporal components.
- Parameters:
sequences (ndarray) – A numpy array representing a collection of image frames in a sequence. It has a shape of (n_frames, width, height) where ‘n_frames’ is the number of frames, and ‘width’ and ‘height’ are the dimensions of each frame.
n_components (int) – An integer representing the number of components for Truncated SVD. The default value is 128.
kwargs – Keyword arguments passed to
TruncatedSVD().
- Returns:
A SequenceSingularVector object containing the singular values, the transformed components, and the left singular vectors.
- Return type: