Memory issue when create a diagonal numpy array
Question:
I have created a diagonal numpy array:
a = numpy.float32(numpy.random.rand(10))
a = numpy.diagonal(a)
However, I face MemoryError since my matrix is extremely large. Is there anyway to save the memory?
Answers:
The best way to handle this case is to create a sparse matrix using scipy.sparse.diags as follows:
a = numpy.float32(numpy.random.rand(10))
a = sparse.diags(a)
If the shape of your diagonal numpy array is n*n, utilizing sparse.diags would result in a matrix n times smaller. Almost all matrix operations are supported for sparse matrices.
I have created a diagonal numpy array:
a = numpy.float32(numpy.random.rand(10))
a = numpy.diagonal(a)
However, I face MemoryError since my matrix is extremely large. Is there anyway to save the memory?
The best way to handle this case is to create a sparse matrix using scipy.sparse.diags as follows:
a = numpy.float32(numpy.random.rand(10))
a = sparse.diags(a)
If the shape of your diagonal numpy array is n*n, utilizing sparse.diags would result in a matrix n times smaller. Almost all matrix operations are supported for sparse matrices.