Function var

Wrapping/Python/vtkmodules/numpy_interface/numpy_algorithms.py:333–358

Returns the variance of all values along a particular axis (dimension). Given an array of m tuples and n components: * Default is to return the variance of all values in an array. * axis=0: Return the variance values of all components and return a one tuple, n-component array.

(array, axis=None, controller=None)

@dsa._override_numpy(numpy.var)
def var(array, axis=None, controller=None):
    """Returns the variance of all values along a particular axis (dimension).
    Given an array of m tuples and n components:
    * Default is to return the variance of all values in an array.
    * axis=0: Return the variance values of all components and return a one
      tuple, n-component array.
    * axis=1: Return the variance values of all components of each tuple and
      return an m-tuple, 1-component array.

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

    var(array, controller=vtkmodules.vtkParallelCore.vtkDummyController()).
    """
    from .algorithms import array_count
    if axis is None or axis == 0:
        size = array_count(array, axis, controller)
        tmp = array - mean(array, axis, controller, size)
        return sum(tmp*tmp, axis, controller) / size
    else:
        if type(array) == dsa.VTKCompositeDataArray:
            return apply_ufunc(algs.var, array, (axis,))
        else:
            return algs.var(array, axis)

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