def crs_toccs(n_row, n_col, n_tube, Ap, Aj, Ak, Ax):
"""
Compute B = A for CRS matrix A, CSC matrix B
Also, with the appropriate arguments can also be used to:
- compute B = A^t for CRS matrix A, CRS matrix B
- compute B = A^t for CSC matrix A, CSC matrix B
- convert CSC->CRS
Input Arguments:
I n_row - number of rows in A
I n_col - number of columns in A
I Ap[n_row+1] - row pointer
I Aj[nnz(A)] - column indices
T Ax[nnz(A)] - nonzeros
Output Arguments:
I Bp[n_col+1] - column pointer
I Bj[nnz(A)] - row indices
T Bx[nnz(A)] - nonzeros
Note:
Output arrays Bp, Bj, Bx must be preallocated
Note:
Input: column indices *are not* assumed to be in sorted order
Output: row indices *will be* in sorted order
Complexity: Linear. Specifically O(nnz(A) + max(n_row,n_col))
Note:
Adapted from scipy.sparse.
"""
nnz = Ap[n_row]
Bp = cumsumdups(Aj, n_col+1)
Bi = [0] * nnz
Bk = [0] * nnz
Bx = [0] * nnz
for row in range(n_row):
for jj in range(Ap[row], Ap[row+1]):
col = Aj[jj]
dest = Bp[col]
Bi[dest] = row
Bk[dest] = Ak[jj]
Bx[dest] = Ax[jj]
Bp[col] += 1
Bp = [0] + [Bp[i] for i in range(n_col-1)]
return Bp, Bi, Bk, Bx
def coo_tocrs(n_row, n_col, n_tube, Ai, Aj, Ak, Ax):
"""
Compute B = A for COO matrix A, CRS matrix B
Input Arguments:
I n_row - number of rows in A
I n_col - number of columns in A
I nnz - number of nonzeros in A
I Ai[nnz(A)] - row indices
I Aj[nnz(A)] - column indices
T Ax[nnz(A)] - nonzeros
Output Arguments:
I Bp - row pointer
I Bj - column indices
T Bx - nonzeros
Note:
Output arrays Bp, Bj, and Bx must be preallocated
Note:
Input: row and column indices *are not* assumed to be ordered
Note:
Duplicate entries are carried over to the CRS represention
Complexity: Linear. Specifically O(nnz(A) + max(n_row,n_col))
Note:
Adapted from scipy.sparse.
"""
nnz = len(Ax)
Bp = cumsumdups(Ai, n_row)
Bj = [0] * nnz
Bk = [0] * nnz
Bx = [0] * nnz
for n in range(nnz):
row = Ai[n]
dest = Bp[row]
Bj[dest] = Aj[n]
Bk[dest] = Ak[n]
Bx[dest] = Ax[n]
Bp[row] += 1
Bp = [0] + [Bp[i] for i in range(n_row-1)]
return Bp, Bj, Bk, Bx
