transforms

Submodules

Attributes

tools

Functions

reduce(dataarray, *_args, **kwargs)

Reduce an xarray.dataarray or xarray.dataset using a specified how method.

resample(dataarray, frequency[, time_dim, how, ...])

Resample dataarray to a user-defined frequency using a user-defined "how" method.

rolling_reduce(dataarray, *_args, **kwargs)

Return reduced data using a moving window over which to apply the reduction.

Package Contents

transforms.reduce(dataarray, *_args, **kwargs)

Reduce an xarray.dataarray or xarray.dataset using a specified how method.

With the option to apply weights either directly or using a specified weights method.

Parameters:

  • dataarray (xr.DataArray or xr.Dataset) – Data object to reduce

  • how (str or callable) – Method used to reduce data. Default=’mean’, which will implement the xarray in-built mean. If string, it must be an in-built xarray reduce method, a earthkit how method or any numpy method. In the case of duplicate names, method selection is first in the order: xarray, earthkit, numpy. Otherwise it can be any function which can be called in the form f(x, axis=axis, **kwargs) to return the result of reducing an xp.ndarray over an integer valued axis

  • weights (str) – Choose a recognised method to apply weighting. Currently available methods are; ‘latitude’

  • how_label (str) – Label to append to the name of the variable in the reduced object

  • how_dropna (str) – Choose how to drop nan values. Default is None and na values are preserved. Options are ‘any’ and ‘all’.

  • **kwargs – kwargs recognised by the how :func: reduce

Return type:

A data array with reduce dimensions removed.

transforms.resample(dataarray, frequency, time_dim='time', how='mean', skipna=True, how_args=[], how_kwargs={}, how_label=None, **kwargs)

Resample dataarray to a user-defined frequency using a user-defined “how” method.

Parameters:

  • dataarray (xr.DataArray) – DataArray to be resampled.

  • frequency (str, int, float) – The frequency at which to resample the chosen dimension. The format must be applicable to the chosen dimension.

  • time_dim (str) – The dimension to resample along, default is time

  • how (str) – The reduction method for resampling, default is mean

  • how_label (str) – Label to append to the name of the variable in the reduced object, default is nothing

  • skipna (bool) – If True, exclude missing values (na values) from the reduction.

  • how_args (list) – List of arguments to be passed to the reduction method.

  • how_kwargs (dict) – Dictionary of keyword arguments to be passed to the reduction method.

  • **kwargs – Keyword arguments to be passed to resample(). Defaults have been set as: {“skipna”: True}

Return type:

xr.Dataset | xr.DataArray

transforms.rolling_reduce(dataarray, *_args, **kwargs)

Return reduced data using a moving window over which to apply the reduction.

Parameters:

  • dataarray (xr.DataArray or xr.Dataset) – Data over which the moving window is applied according to the reduction method.

  • windows – windows for the rolling groups, for example time=10 to perform a reduction in the time dimension with a bin size of 10. the rolling groups can be defined over any number of dimensions. see documentation for xarray.dataarray.rolling.

  • min_periods (integer) – The minimum number of observations in the window required to have a value (otherwise result is NaN). Default is to set min_periods equal to the size of the window. see documentation for xarray.dataarray.rolling

  • center (bool) – Set the labels at the centre of the window, see documentation for xarray.dataarray.rolling.

  • how_reduce (str,) – Function to be applied for reduction. Default is ‘mean’.

  • how_dropna (str) – Determine if dimension is removed from the output when we have at least one NaN or all NaN. how_dropna can be ‘None’, ‘any’ or ‘all’. Default is ‘any’.

  • **kwargs – Any kwargs that are compatible with the select how_reduce method.

Return type:

xr.DataArray or xr.Dataset (as provided)

transforms.tools