sklearn.utils.sparsefuncs
.inplace_swap_row¶
- sklearn.utils.sparsefuncs.inplace_swap_row(X, m, n)[source]¶
Swap two rows of a CSC/CSR matrix in-place.
- Parameters:
- Xsparse matrix of shape (n_samples, n_features)
Matrix whose two rows are to be swapped. It should be of CSR or CSC format.
- mint
Index of the row of X to be swapped.
- nint
Index of the row of X to be swapped.
Examples
>>> from sklearn.utils import sparsefuncs >>> from scipy import sparse >>> import numpy as np >>> indptr = np.array([0, 2, 3, 3, 3]) >>> indices = np.array([0, 2, 2]) >>> data = np.array([8, 2, 5]) >>> csr = sparse.csr_matrix((data, indices, indptr)) >>> csr.todense() matrix([[8, 0, 2], [0, 0, 5], [0, 0, 0], [0, 0, 0]]) >>> sparsefuncs.inplace_swap_row(csr, 0, 1) >>> csr.todense() matrix([[0, 0, 5], [8, 0, 2], [0, 0, 0], [0, 0, 0]])