(A, i, x)
Set the nonzeros in row i of BSR matrix A with the vector x.

    length(x) and nnz(A[i,:]) must be equivalent

    Parameters
    ----------
    A : bsr_matrix
        Matrix assumed to be in BSR format
    i : int
        Row number
    x : array
        Array of values to overwrite nonzeros in row i of A

    Returns
    -------
    A : bsr_matrix
        The nonzeros in row i of A have been
        overwritten with entries from x.  x must be same
        length as nonzeros of row i.  This is guaranteed
        when this routine is used with vectors derived form
        bsr_getrow

    Examples
    --------
    >>> from numpy import array
    >>> from scipy.sparse import bsr_matrix
    >>> from pyamg.util.bsr_utils import bsr_row_setvector
    >>> indptr  = array([0,2,3,6])
    >>> indices = array([0,2,2,0,1,2])
    >>> data    = array([1,2,3,4,5,6]).repeat(4).reshape(6,2,2)
    >>> B = bsr_matrix( (data,indices,indptr), shape=(6,6) )
    >>> bsr_row_setvector(B,5,array([11,22,33,44,55,66]))
Set the nonzeros in row i of BSR matrix A with the vector x.
Set the nonzeros in row i of BSR matrix A with the vector x .
def bsr_row_setvector(A, i, x):
    """Set the nonzeros in row i of BSR matrix A with the vector x.

    length(x) and nnz(A[i,:]) must be equivalent

    Parameters
    ----------
    A : bsr_matrix
        Matrix assumed to be in BSR format
    i : int
        Row number
    x : array
        Array of values to overwrite nonzeros in row i of A

    Returns
    -------
    A : bsr_matrix
        The nonzeros in row i of A have been
        overwritten with entries from x.  x must be same
        length as nonzeros of row i.  This is guaranteed
        when this routine is used with vectors derived form
        bsr_getrow

    Examples
    --------
    >>> from numpy import array
    >>> from scipy.sparse import bsr_matrix
    >>> from pyamg.util.bsr_utils import bsr_row_setvector
    >>> indptr  = array([0,2,3,6])
    >>> indices = array([0,2,2,0,1,2])
    >>> data    = array([1,2,3,4,5,6]).repeat(4).reshape(6,2,2)
    >>> B = bsr_matrix( (data,indices,indptr), shape=(6,6) )
    >>> bsr_row_setvector(B,5,array([11,22,33,44,55,66]))

    """
    blocksize = A.blocksize[0]
    BlockIndx = int(i/blocksize)
    rowstart = A.indptr[BlockIndx]
    rowend = A.indptr[BlockIndx+1]
    localRowIndx = i % blocksize

    # like matlab slicing:
    x = x.__array__().reshape((max(x.shape),))

    # counter = 0
    # for j in range(rowstart, rowend):
    #   indys = A.data[j,localRowIndx,:].nonzero()[0]
    #   increment = min(indys.shape[0], blocksize)
    #   A.data[j,localRowIndx,indys] = x[counter:(counter+increment), 0]
    #   counter += increment

    indys = A.data[rowstart:rowend, localRowIndx, :].nonzero()
    A.data[rowstart:rowend, localRowIndx, :][indys[0], indys[1]] = x
def bsr_row_setvector ( A , i , x ) : blocksize = A . blocksize [ 0 ] BlockIndx = int ( i / blocksize ) rowstart = A . indptr [ BlockIndx ] rowend = A . indptr [ BlockIndx + 1 ] localRowIndx = i % blocksize # like matlab slicing: x = x . __array__ ( ) . reshape ( ( max ( x . shape ) , ) ) # counter = 0 # for j in range(rowstart, rowend): #   indys = A.data[j,localRowIndx,:].nonzero()[0] #   increment = min(indys.shape[0], blocksize) #   A.data[j,localRowIndx,indys] = x[counter:(counter+increment), 0] #   counter += increment indys = A . data [ rowstart : rowend , localRowIndx , : ] . nonzero ( ) A . data [ rowstart : rowend , localRowIndx , : ] [ indys [ 0 ] , indys [ 1 ] ] = x