Delete csr python

import numpy as np
from scipy.sparse import csr_matrix

def delete_from_csr(mat, row_indices=[], col_indices=[]):
    """
    Remove the rows (denoted by ``row_indices``) and columns (denoted by ``col_indices``) from the CSR sparse matrix ``mat``.
    WARNING: Indices of altered axes are reset in the returned matrix
    """
    if not isinstance(mat, csr_matrix):
        raise ValueError("works only for CSR format -- use .tocsr() first")

    rows = []
    cols = []
    if row_indices:
        rows = list(row_indices)
    if col_indices:
        cols = list(col_indices)

    if len(rows) > 0 and len(cols) > 0:
        row_mask = np.ones(mat.shape[0], dtype=bool)
        row_mask[rows] = False
        col_mask = np.ones(mat.shape[1], dtype=bool)
        col_mask[cols] = False
        return mat[row_mask][:,col_mask]
    elif len(rows) > 0:
        mask = np.ones(mat.shape[0], dtype=bool)
        mask[rows] = False
        return mat[mask]
    elif len(cols) > 0:
        mask = np.ones(mat.shape[1], dtype=bool)
        mask[cols] = False
        return mat[:,mask]
    else:
        return mat

Source: stackoverflow.com

Delete csr python

A0 = J.T * B

Source: stackoverflow.com

Delete csr python

def delete_rows_csr(mat, indices):
    """
    Remove the rows denoted by ``indices`` form the CSR sparse matrix ``mat``.
    """
    if not isinstance(mat, scipy.sparse.csr_matrix):
        raise ValueError("works only for CSR format -- use .tocsr() first")
    indices = list(indices)
    mask = numpy.ones(mat.shape[0], dtype=bool)
    mask[indices] = False
    return mat[mask]

Source: stackoverflow.com

Delete csr python

scipy.sparse.vstack([X[:i, :], X[i:, :]])

Source: stackoverflow.com

Delete csr python

def delete_row_csr(mat, i):
    if not isinstance(mat, scipy.sparse.csr_matrix):
        raise ValueError("works only for CSR format -- use .tocsr() first")
    n = mat.indptr[i+1] - mat.indptr[i]
    if n > 0:
        mat.data[mat.indptr[i]:-n] = mat.data[mat.indptr[i+1]:]
        mat.data = mat.data[:-n]
        mat.indices[mat.indptr[i]:-n] = mat.indices[mat.indptr[i+1]:]
        mat.indices = mat.indices[:-n]
    mat.indptr[i:-1] = mat.indptr[i+1:]
    mat.indptr[i:] -= n
    mat.indptr = mat.indptr[:-1]
    mat._shape = (mat._shape[0]-1, mat._shape[1])

Source: stackoverflow.com

Similar codes

1 vote261 views1 answer
Django filter by category
Python
0 vote262 views1 answer
How to use drf pagination directly
Python
2 votes284 views1 answer
Python set a specific datetime
Python
39 votes244 views6 answers
Convert dict to dataframe
Python
0 vote215 views1 answer
All python versions
Python
18 votes275 views4 answers
Python get all combinations of list
Python
-1 vote304 views2 answers
This code is supposed to display "2 + 2 = 4" on the screen, but there is an error. Find the error in the code and fix it, so that the output is correct.
Python
0 vote261 views1 answer
Regex for repeating words python
Python
0 vote276 views1 answer
Reverse row order padnas
Python
1 vote241 views2 answers
Boxplot show values seaborn
Python