Repeat a scipy csr sparse matrix along axis 0
I wanted to repeat the rows of a scipy csr sparse matrix, but when I tried to call numpy's repeat method, it simply treats the sparse matrix like an object, and would only repeat it as an object in an ndarray. I looked through the documentation, but I couldn't find any utility to repeats the rows of a scipy csr sparse matrix.
I wrote the following code that operates on the internal data, which seems to work
def csr_repeat(csr, repeats):
if isinstance(repeats, int):
repeats = np.repeat(repeats, csr.shape)
repeats = np.asarray(repeats)
rnnz = np.diff(csr.indptr)
ndata = rnnz.dot(repeats)
if ndata == 0:
return sparse.csr_matrix((np.sum(repeats), csr.shape),
indmap = np.ones(ndata, dtype=np.int)
indmap = 0
rnnz_ = np.repeat(rnnz, repeats)
indptr_ = rnnz_.cumsum()
mask = indptr_ < ndata
indmap -= np.int_(np.bincount(indptr_[mask],
jumps = (rnnz * repeats).cumsum()
mask = jumps < ndata
indmap += np.int_(np.bincount(jumps[mask],
indmap = indmap.cumsum()
and be reasonably efficient, but I'd rather not monkey patch the class. Is there a better way to do this?
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