transforms

Submodules

• transforms.climatology
• transforms.ensemble
• transforms.spatial
• transforms.temporal

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=None, how_kwargs=None, how_label=None, extra_reduce_dims=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.

• extra_reduce_dims (str or list of str, optional) – Extra dimensions to reduce over in addition to the resampling dimension. These dimensions will be reduced over using the same how method as the resampling dimension. Default is None (no extra dimensions).

• **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