tams.data_in_contours

tams.data_in_contours(data, contours, *, agg=('mean', 'std', 'count'), method='sjoin', merge=False)

Compute statistics on data within the shapes of contours.

With the default settings, we calculate, for each shape (row) in the contours dataframe:

• the mean value of data within the shape

• the standard deviation of data within the shape

• the count of non-null values of data within the shape

Parameters

• data (xarray.DataArray | xarray.Dataset) – It should have 'lat' and 'lon' coordinates.

• contours (geopandas.GeoDataFrame) – For example, dataframe of CE or MCS shapes, e.g. from identify() or track().

• agg (sequence of str or callable()) – Suitable for passing to pandas.DataFrame.aggregate().

• method ({'sjoin', 'regionmask'}) – The regionmask method is suited for data on a structured grid, while the GeoPandas sjoin method works for scattered point data as well. The sjoin method is the default since it is more general and currently often faster.

• merge (bool) – Whether to merge the new data with contours or return a separate frame.

Return type

geopandas.GeoDataFrame

See also

Identify CEs using different CTT thresholds

A usage example.