def copy_missing_matrix(A, B, missing, missing_rows=False, missing_cols=False, is_diagonal=False, inplace=False, prefix=None):
 if (prefix is None):
  prefix = find_best_blas_type((A, B))[0]
 copy = prefix_copy_missing_matrix_map[prefix]
 if (not inplace):
  B = np.copy(B, order='F')
 try:
  if (not A.is_f_contig()):
   raise ValueError()
 except:
  A = np.asfortranarray(A)
 copy(A, B, np.asfortranarray(missing), missing_rows, missing_cols, is_diagonal)
 return B

def copy_missing_matrix ( A , B , missing , missing_rows = False , missing_cols = False , is_diagonal = False , inplace = False , prefix = None ) : if ( prefix is None ) : prefix = find_best_blas_type ( ( A , B ) ) [ 0 ] copy = prefix_copy_missing_matrix_map [ prefix ] if ( not inplace ) : B = np . copy ( B , order = 'F' ) try : if ( not A . is_f_contig ( ) ) : raise ValueError ( ) except : A = np . asfortranarray ( A ) copy ( A , B , np . asfortranarray ( missing ) , missing_rows , missing_cols , is_diagonal ) return B
copy the rows or columns of a time-varying matrix where all non-missing values are in the upper left corner of the matrix .