class brainpy.math.event.csrmv(data, indices, indptr, events, *, shape, transpose=False)[source]#

Product of a sparse CSR matrix and a dense event vector.

This function supports JAX transformations, including jit(), grad(), vmap() and pmap().

  • data (ndarray, float) – An array of shape (nse,).

  • indices (ndarray) – An array of shape (nse,).

  • indptr (ndarray) – An array of shape (shape[0] + 1,) and dtype indices.dtype.

  • events (ndarray) – An array of shape (shape[0] if transpose else shape[1],) and dtype data.dtype.

  • shape (tuple) – A length-2 tuple representing the matrix shape.

  • transpose (bool) – A boolean specifying whether to transpose the sparse matrix before computing. If transpose=True, the operator will compute based on the event-driven property of the events vector.


y – The array of shape (shape[1] if transpose else shape[0],) representing the matrix vector product.

Return type: