cedalion.xrutils

Utility functions for xarray objects.

Functions

apply_mask(data_array, mask, operator, ...)	Apply a boolean mask to a DataArray according to the defined "operator".
convolve(data_array, kernel, dim)	Convolve a DataArray along a given dimension "dim" with a "kernel".
coords_from_other(source[, dims])	Create a dictionary of coordinates from source for matching dims in target.
mask(array, initval)	Create a boolean mask array with the same shape as the input array.
norm(array, dim)	Calculate the vector norm along a given dimension.
other_dim(data_array, *dims)	Get the dimension name not listed in *dims.
pinv(array)	Calculate the pseudoinverse of a 2D xr.DataArray.
unit_stripping_is_error([is_error])

cedalion.xrutils.pinv(array: DataArray) → DataArray

Calculate the pseudoinverse of a 2D xr.DataArray.

FIXME: handles unitless and quantified DataArrays but not

DataArrays with units in their attrs.

Parameters:

array (xr.DataArray) – Input array

Returns:

Pseudoinverse of the input array

Return type:

array_inv (xr.DataArray)

cedalion.xrutils.norm(

array: DataArray,

dim: str,

) → DataArray

Calculate the vector norm along a given dimension.

Extends the behavior of numpy.linalg.norm to xarray DataArrays.

Parameters:

• array (xr.DataArray) – Input array

• dim (str) – Dimension along which to calculate the norm

Returns:

Array with the norm along the specified dimension

Return type:

normed (xr.DataArray)

cedalion.xrutils.mask(

array: DataArray,

initval: bool,

) → DataArray

Create a boolean mask array with the same shape as the input array.

cedalion.xrutils.apply_mask(

data_array: DataArray,

mask: DataArray,

operator: str,

dim_collapse: str,

) → DataArray

Apply a boolean mask to a DataArray according to the defined “operator”.

Parameters:

• data_array – NDTimeSeries, input time series data xarray

• mask – input boolean mask array with a subset of dimensions matching data_array

• operator – operators to apply to the mask and data_array “nan”: inserts NaNs in the data_array where mask is False “drop”: drops value in the data_array where mask is False

• dim_collapse – Mask dimension to collapse to, merging boolean masks along all other dimensions. Can be skipped with “none”. Example: collapsing to “channel” dimension will drop or nan a channel if it is “False” along any other dimensions

Returns:

Input data_array with applied mask masked_elements: List of elements in data_array that were masked (e.g.

dropped or set to NaN)

Return type:

masked_data_array

cedalion.xrutils.convolve(

data_array: DataArray,

kernel: ndarray,

dim: str,

) → DataArray

Convolve a DataArray along a given dimension “dim” with a “kernel”.

cedalion.xrutils.other_dim(data_array: DataArray, *dims: str) → str

Get the dimension name not listed in *dims.

Checks that there is only one more dimension than given in dims and returns its name.

Parameters:

• data_array – an xr.DataArray

• *dims – names of dimensions

Returns:

The name of the dimension of data_array.

cedalion.xrutils.coords_from_other(

source: DataArray,

dims: list[str] = None,

**aux_coords,

) → dict[str, tuple[str, DataArray]]

Create a dictionary of coordinates from source for matching dims in target.

Parameters:

• source – the DataArray to copy the coordinates from.

• dims – a list of dimensions names. If specified, copy only coords for those dims.

• aux_coords – additional key-value pairs to add to the resulting coords dict.

Returns:

A dictionary that can be passed to DataArray.assign_coords.

cedalion.xrutils.unit_stripping_is_error(is_error: bool = True)