I have a matrix and I want to check if it is sparse or not.
Things I have tried:
isinstance method:
if isinstance(<matrix>, scipy.sparse.csc.csc_matrix):
This works fine if I know exactly which sparse class I want to check.
But I want a way to know if matrix is sparse or not, and should work irrespective of which sparse class.
Kindly help me.
Calculate the size of the array by multiplying the number of rows with many columns of the array. If the count is greater than size/2, given matrix is the sparse matrix. That means, most of the elements of the array are zeroes. Else, the matrix is not a sparse matrix.
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).
SciPy has a module, scipy. sparse that provides functions to deal with sparse data. There are primarily two types of sparse matrices that we use: CSC - Compressed Sparse Column.
Representing a sparse matrix by a 2D array leads to wastage of lots of memory as zeroes in the matrix are of no use in most of the cases. So, instead of storing zeroes with non-zero elements, we only store non-zero elements. This means storing non-zero elements with triples- (Row, Column, value).
scipy.sparse.issparse(my_matrix)
You can do sparsity = 1.0 - count_nonzero(X) / X.size
This works for any matrices.
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