Function sum_per_block

Wrapping/Python/vtkmodules/numpy_interface/algorithms.py:336–368

Returns the sum of all values along a particular axis (dimension) for each block of an VTKCompositeDataArray. Given an array of m tuples and n components: * Default is to return the sum of all values in an array. * axis=0: Sum values of all components and return a one tuple, n

(array, axis=None, controller=None)

    return dsa.VTKCompositeDataArray(results, dataset=dataset)

def sum_per_block(array, axis=None, controller=None):
    """Returns the sum of all values along a particular axis (dimension) for
    each block of an VTKCompositeDataArray.

    Given an array of m tuples and n components:
    * Default is to return the sum of all values in an array.
    * axis=0: Sum values of all components and return a one tuple,
      n-component array.
    * axis=1: Sum values of all components of each tuple and return an
      m-tuple, 1-component array.

    When called in parallel, this function will sum across processes
    when a controller argument is passed or the global controller is
    defined. To disable parallel summing when running in parallel, pass
    a dummy controller as follows:

    sum_per_block(array, controller=vtkmodules.vtkParallelCore.vtkDummyController()).
    """
    class SumPerBlockImpl:
        def op(self):
            return sum

        def op2(self):
            return algs.sum

        def mpi_op(self):
            from mpi4py import MPI
            return MPI.SUM

        def default(self):
            return numpy.float64(0)

    return _global_per_block(SumPerBlockImpl(), array, axis, controller)

def count_per_block(array, axis=None, controller=None):
    """Return the number of elements of each block in a VTKCompositeDataArray