Menu
Is it possible to determine the byte size of a scipy.sparse matrix? In NumPy you can determine the size of an array by doing the following:
import numpy as np
print(np.zeros((100, 100, 100).nbytes)
8000000
571
Sparse matrix is a matrix which contains very few non-zero elements. When a sparse matrix is represented with a 2-dimensional array, we waste a lot of space to represent that matrix. For example, consider a matrix of size 100 X 100 containing only 10 non-zero elements.
One way to visualize sparse matrix is to use 2d plot. Python's matplotlib has a special function called Spy for visualizing sparse matrix. Spy is very similar to matplotlib's imshow, which is great for plotting a matrix or an array as an image. imshow works with dense matrix, while Spy works with sparse matrix.
Python's SciPy provides tools for creating sparse matrices using multiple data structures, as well as tools for converting a dense matrix to a sparse matrix. The sparse matrix representation outputs the row-column tuple where the matrix contains non-zero values along with those values.
Sparse Matrix/Sparse Array: 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.
A sparse matrix is constructed from regular numpy arrays, so you can get the byte count for any of these just as you would a regular array.
If you just want the number of bytes of the array elements:
>>> from scipy.sparse import csr_matrix >>> a = csr_matrix(np.arange(12).reshape((4,3))) >>> a.data.nbytes 88 If you want the byte counts of all arrays required to build the sparse matrix, then I think you want:
>>> print a.data.nbytes + a.indptr.nbytes + a.indices.nbytes 152 If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
