So, I'm doing some Kmeans classification using numpy arrays that are quite sparse-- lots and lots of zeroes. I figured that I'd use scipy's 'sparse' package to reduce the storage ...
Suppose I have a 2d sparse array. In my real usecase both the number of rows and columns are much bigger (say 20000 and 50000) hence it cannot fit in memory ...
I have a 2D numpy array... there are some values in the image and rest is sparse. For linear imterpolation, I want to take the first column of the array. See ...
I want to multiply a sparse matrix A, with a matrix B which has 0, -1, or 1 as elements. To reduce the complexity of the matrix multiplication, I can ignore ...
In scipy, we can construct a sparse matrix using scipy.sparse.lil_matrix() etc. But the matrix is in 2d.
I am wondering if there is an existing data structure for sparse 3d matrix / ...
For Scipy sparse matrix, one can use todense() or toarray() to transform to Numpy.matrix or array. What are the functions to do the inverse?
I searched, but got no idea what keywords ...