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src/s/c/scipy-HEAD/scipy/sparse/bsr.py   scipy(Download)
        # ideally we'd take the GCDs of the blocksize dimensions
        # and explode self and other to match
        other = self.__class__(other, blocksize=self.blocksize)
 
        # e.g. bsr_plus_bsr, etc.
        data = data.reshape(-1,R,C)
 
        return self.__class__((data, indices, indptr), shape=self.shape)
 
    # needed by _data_matrix
        """
        if copy:
            return self.__class__((data,self.indices.copy(),self.indptr.copy()), \
                                   shape=self.shape,dtype=data.dtype)
        else:
            return self.__class__((data,self.indices,self.indptr), \

src/s/c/scipy-HEAD/scipy/sparse/csr.py   scipy(Download)
        shape =  (i1 - i0, j1 - j0)
 
        return self.__class__( (data,indices,indptr), shape=shape )