pysteps.utils.dimension.aggregate_fields¶

pysteps.utils.dimension.aggregate_fields(data, window_size, axis=0, method='mean', trim=False)¶

Aggregate fields along a given direction.

It attempts to aggregate the given R axis in an integer number of sections of length = window_size. If such a aggregation is not possible, an error is raised unless trim set to True, in which case the axis is trimmed (from the end) to make it perfectly divisible”.

Parameters

data: array-like

Array of any shape containing the input fields.

window_size: int or tuple of ints

The length of the window that is used to aggregate the fields. If a single integer value is given, the same window is used for all the selected axis.

If window_size is a 1D array-like, each element indicates the length of the window that is used to aggregate the fields along each axis. In this case, the number of elements of ‘window_size’ must be the same as the elements in the axis argument.

axis: int or array-like of ints

Axis or axes where to perform the aggregation. If this is a tuple of ints, the aggregation is performed over multiple axes, instead of a single axis

method: string, optional

Optional argument that specifies the operation to use to aggregate the values within the window. Default to mean operator.

trim: bool

In case that the data is not perfectly divisible by window_size along the selected axis:

trim=True: the data will be trimmed (from the end) along that axis to make it perfectly divisible.
trim=False: a ValueError exception is raised.

Returns

new_array: array-like: The new aggregated array with shape[axis] = k, where k = R.shape[axis] / window_size.