Python Scikit learn: Create a 2-D array with ones on the diagonal and zeros elsewhere
Python Machine learning Iris Basic: Exercise-4 with Solution
Write a Python program to create a 2-D array with ones on the diagonal and zeros elsewhere. Now convert the NumPy array to a SciPy sparse matrix in CSR format.
From wikipedia :
In numerical analysis and scientific computing, a sparse matrix or sparse array is a matrix in which most of the elements are zero. By contrast, if most of the elements are nonzero, then the matrix is considered dense. The number of zero-valued elements divided by the total number of elements (e.g., m × n for an m × n matrix) is called the sparsity of the matrix (which is equal to 1 minus the density of the matrix). Using those definitions, a matrix will be sparse when its sparsity is greater than 0.5.
import numpy as np from scipy import sparse eye = np.eye(4) print("NumPy array:\n", eye) sparse_matrix = sparse.csr_matrix(eye) print("\nSciPy sparse CSR matrix:\n", sparse_matrix)
NumPy array: [[1. 0. 0. 0.] [0. 1. 0. 0.] [0. 0. 1. 0.] [0. 0. 0. 1.]] SciPy sparse CSR matrix: (0, 0) 1.0 (1, 1) 1.0 (2, 2) 1.0 (3, 3) 1.0
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