Function sum

Wrapping/Python/vtkmodules/numpy_interface/numpy_algorithms.py:149–188

Returns the sum of all values along a particular axis (dimension). 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 al

(array, axis=None, controller=None)

@dsa._override_numpy(numpy.sum)
def sum(array, axis=None, controller=None):
    """Returns the sum of all values along a particular axis (dimension).
    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(array, controller=vtkmodules.vtkParallelCore.vtkDummyController()).
    """
    from .algorithms import global_func
    class SumImpl:
        def op(self):
            return algs.sum

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

        def serial_composite(self, array, axis):
            res = None
            arrays = array.Arrays
            for a in arrays:
                if a is not dsa.NoneArray:
                    if res is None:
                        res = algs.sum(a, axis).astype(numpy.float64)
                    else:
                        res += algs.sum(a, axis)
            return res

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

    return global_func(SumImpl(), array, axis, controller)

@dsa._override_numpy(numpy.max)
def max(array, axis=None, controller=None):