Building and updating a sparse matrix in python using scipy

Question

I\'m trying to build and update a sparse matrix as I read data from file. The matrix is of size 100000X40000

What is the most efficient way of updating

Answer 1

Creating a second matrix with 1s in your new coordinates and adding it to the existing one is a possible way of doing this:

>>> import scipy.sparse as sps
>>> shape = (1000, 2000)
>>> rows, cols = 1000, 2000
>>> sps_acc = sps.coo_matrix((rows, cols)) # empty matrix
>>> for j in xrange(100): # add 100 sets of 100 1's
...     r = np.random.randint(rows, size=100)
...     c = np.random.randint(cols, size=100)
...     d = np.ones((100,))
...     sps_acc = sps_acc + sps.coo_matrix((d, (r, c)), shape=(rows, cols))
... 
>>> sps_acc
<1000x2000 sparse matrix of type ''
    with 9985 stored elements in Compressed Sparse Row format>