Function mean_per_block

Wrapping/Python/vtkmodules/numpy_interface/algorithms.py:398–419

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

(array, axis=None, controller=None)

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

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

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

    When called in parallel, this function will compute the mean 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:

    mean(array, controller=vtkmodules.vtkParallelCore.vtkDummyController()).
    """
    if axis is None or axis == 0:
        return sum_per_block(array, axis, controller) / count_per_block(array, axis, controller)
    else:
        return sum(array, axis, controller)

def max_per_block(array, axis=None, controller=None):
    """Returns the max of all values along a particular axis (dimension)