transforms.tools

Attributes

GROUPBY_KWARGS
HOW_METHODS
WEIGHTED_HOW_METHODS
ALLOWED_LIBS
WEIGHTS_DICT
STANDARD_AXIS_KEYS

Functions

ensure_list(thing)
time_dim_decorator(func)
groupby_kwargs_decorator(func)
season_order_decorator(func)
nanaverage(data[, weights])	A merge of the functionality of np.nanmean and np.average.
standard_weights(dataarray, weights, **kwargs)	Implement any standard weights functions included in earthkit-transforms.
latitude_weights(dataarray[, lat_key])	xarray.DataArray wrapper for latitude_weights.
get_how(how[, how_methods])
get_dim_key(dataarray, axis)	Return the key of the dimension.
get_spatial_info(dataarray[, lat_key, lon_key])
groupby_time(dataarray[, frequency, bin_widths, ...])
groupby_bins(dataarray, frequency[, bin_widths, ...])

Module Contents

transforms.tools.ensure_list(thing)

transforms.tools.time_dim_decorator(func)

transforms.tools.GROUPBY_KWARGS = ['frequency', 'bin_widths', 'squeeze']

transforms.tools.groupby_kwargs_decorator(func)

transforms.tools.season_order_decorator(func)

transforms.tools.nanaverage(data, weights=None, **kwargs)

A merge of the functionality of np.nanmean and np.average.

Parameters:

• data (numpy array)

• weights (Weights to apply to the data for averaging.) – Weights will be normalised and must correspond to the shape of the numpy data array and axis/axes that is/are averaged over.

• axis (axis/axes to compute the nanaverage over.)

• kwargs (any other np.nansum kwargs)

Returns:

• numpy array mean of data (along axis) where nan-values are ignored

• and weights applied if provided.

transforms.tools.standard_weights(dataarray, weights, **kwargs)

Implement any standard weights functions included in earthkit-transforms.

transforms.tools.latitude_weights(dataarray, lat_key=None)

xarray.DataArray wrapper for latitude_weights.

Detects the spatial dimensions latitude must be a coordinate of the dataarray.

transforms.tools.HOW_METHODS

transforms.tools.WEIGHTED_HOW_METHODS

transforms.tools.ALLOWED_LIBS

transforms.tools.WEIGHTS_DICT

transforms.tools.get_how(how, how_methods=HOW_METHODS)

transforms.tools.STANDARD_AXIS_KEYS: dict[str, list[str]]

transforms.tools.get_dim_key(dataarray, axis)

Return the key of the dimension.

transforms.tools.get_spatial_info(dataarray, lat_key=None, lon_key=None)

transforms.tools.groupby_time(dataarray, frequency=None, bin_widths=None, squeeze=False, time_dim='time')

transforms.tools.groupby_bins(dataarray, frequency, bin_widths=1, squeeze=False, time_dim='time')