s2spy.rgdr.utils
================

.. py:module:: s2spy.rgdr.utils

.. autoapi-nested-parse::

   Commonly used utility functions for s2spy.



Attributes
----------

.. autoapisummary::

   s2spy.rgdr.utils.XrType


Functions
---------

.. autoapisummary::

   s2spy.rgdr.utils.weighted_groupby
   s2spy.rgdr.utils.geographical_cluster_center
   s2spy.rgdr.utils.intervals_subtract


Module Contents
---------------

.. py:data:: XrType

.. py:function:: weighted_groupby(ds: XrType, groupby: str, weight: str, method: str = 'mean') -> XrType

   Apply a weighted reduction after a groupby call.

   xarray does not currently support combining `weighted` and `groupby`. An open PR
   adds supports for this functionality (https://github.com/pydata/xarray/pull/5480),
   but this branch was never merged.

   :param ds: Data containing the coordinates or variables
              specified in the `groupby` and `weight` kwargs.
   :param groupby: Coordinate which should be used to make the groups.
   :param weight: Variable in the Dataset containing the weights that should be used.
   :param method: Method that should be used to reduce the dataset, by default
                  'mean'. Supports any of xarray's builtin methods, e.g. 'median', 'min',
                  'max'.

   :returns:

             Dataset reduced using the `groupby` coordinate, using weights =
                 based on `ds[weight]`.
   :rtype: Same as input


.. py:function:: geographical_cluster_center(masked_data: xarray.DataArray, reduced_data: xarray.DataArray) -> xarray.DataArray

   Add the geographical centers to the clusters.

   :param masked_data: Precursor data before being reduced to clusters,
                       with the dimensions latitude and longitude, and cluster labels added.
   :type masked_data: xr.DataArray
   :param reduced_data: Data reduced to the clusters, to which the
                        geographical centers will be added
   :type reduced_data: xr.DataArray

   :returns:

             Reduced data with the latitude and longitude of the geographical
                 centers added as coordinates of the cluster labels.
   :rtype: xr.DataArray


.. py:function:: intervals_subtract(intervals: list[int], n: int) -> list[int]

   Subtracts n from the interval indices, skipping 0.