This function returns a sparse matrix – not a sparse array. You are encouraged to use diags_array to take advantage of the sparse array functionality.

The result from diags_array is the sparse equivalent of: np.diag(diagonals[0], offsets[0]) + ... + np.diag(diagonals[k], offsets[k])

11 мая 2018 г. · I'm working on a problem which requires the generation of a tridiagonal matrix to solve an ordinary differential equation numerically using finite differences. Efficient way to create a diagonal sparse matrix - Stack Overflow scipy.sparse.diags: ValueError: Different number of diagonals ... Другие результаты с сайта stackoverflow.com

Identity matrix in sparse format. diags (diagonals[, offsets, shape, format, dtype]). Construct a sparse matrix from diagonals. spdiags (data, diags[, m, n, ... Diags · Sparse.csgraph · Sparse linear algebra · Coo_array

The following are 30 code examples of scipy.sparse.diags(). You can vote up the ones you like or vote down the ones you don't like, and go to the original ...

diagonals (sequence of array_like) – Sequence of arrays containing the matrix diagonals, corresponding to offsets . · shape (tuple of int) – Shape of the result.

This function returns a sparse matrix – not a sparse array. You are encouraged to use diags_array to take advantage of the sparse array functionality. See also.

Returns the kth diagonal of the array/matrix. k int, optional Which diagonal to get, corresponding to elements a[i, i+k]. Default: 0 (the main diagonal).

9 июн. 2016 г. · I havent looked too much into the code, but changing line 141 to except (TypeError, IndexError) seems like a quick fix. Python ...

12 дек. 2023 г. · It would be really handy to have native MLX support for creating sparse diagonal matrices (which are memory efficient for large problems) on ...