Getting Started¶
COO
arrays can be constructed from numpy.ndarray
objects and
scipy.sparse.spmatrix
objects. For example, to generate the identity
matrix,
import numpy as np
import scipy.sparse
import sparse
sps_identity = scipy.sparse.eye(5)
identity = sparse.COO.from_scipy_sparse(sps_identity)
COO
arrays can have operations performed on them just like numpy.ndarray
objects. For example, to add two COO
arrays:
z = x + y
You can also apply any numpy.ufunc
to COO
arrays.
sin_x = np.sin(x)
However, operations which convert the sparse array into a dense one aren’t currently
supported. For example, the following raises a ValueError
.
y = x + 5
However, if you’re sure you want to convert a sparse array to a dense one, you can
do this (which will result in a numpy.ndarray
):
y = x.todense() + 5
That’s it! You can move on to the user manual to see what part of this library interests you, or you can jump straight in with the API reference.