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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.
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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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