shnitsel.analyze.generic

Attributes

get_standardized_pairwise_dists

Functions

norm(da[, dim, keep_attrs])

Calculate the 2-norm of a DataArray, reducing/squeezing the dimension with name dim

center(da[, dim, keep_attrs])

Subtract the mean of a DataArray along a specified dimension.

subtract_combinations(da, dim[, labels])

Calculate all possible pairwise differences over a given dimension

keep_norming(da[, exclude])

Function to calculate the norm of a variable across all dimensions except the ones denoted in exclude

replace_total(da, to_replace, value)

Replaces each occurence of to_replace in da with the corresponding element of value.

relativize(da, **sel)

Subtract the minimum of an xr.DataArray from all the array's elements

pwdists(atXYZ[, mean])

Compute pairwise distances and standardize it by removing the mean

Module Contents

norm(da, dim='direction', keep_attrs=None)

Calculate the 2-norm of a DataArray, reducing/squeezing the dimension with name dim

Parameters:

  • da (xarray.DataArray) – Array to calculate the norm of

  • dim (shnitsel.core.typedefs.DimName) – Dimension to calculate norm along (and therby reduce), by default ‘direction’

  • optional – Dimension to calculate norm along (and therby reduce), by default ‘direction’

  • keep_attrs (bool | str | None) – How to deal with attributes; passed to xr.apply_ufunc, by default None

  • optional – How to deal with attributes; passed to xr.apply_ufunc, by default None

Return type:

A DataArray with dimension dim reduced

center(da, dim='frame', keep_attrs=None)

Subtract the mean of a DataArray along a specified dimension.

Parameters:

  • da (DataArray) – Input array to be centered.

  • dim (str, optional) – Dimension along which to compute the mean, by default ‘frame’.

  • keep_attrs (bool or str or None, optional) – How to handle attributes; passed to xr.apply_ufunc, by default None.

Returns:

Centered DataArray with the same dimensions as input.

Return type:

DataArray

subtract_combinations(da, dim, labels=False)

Calculate all possible pairwise differences over a given dimension

Parameters:

  • da (xarray.DataArray) – Input DataArray; must contain dimension dim

  • dim (shnitsel.core.typedefs.DimName) – Dimension (of size $n$) to take pairwise differences over

  • labels (bool) – If True, label the pairwise differences based on the index of dim, by default False

  • optional – If True, label the pairwise differences based on the index of dim, by default False

Return type:

A DataArray with the dimension dim replaced by a dimension ‘`dim`comb’ of size $n(n-1)/2$

keep_norming(da, exclude=None)

Function to calculate the norm of a variable across all dimensions except the ones denoted in exclude

Parameters:

  • da (xr.DataArray) – The data array to norm across all non-excluded dimensions

  • exclude (Collection[DimName] | None, optional) – The dimensions to exclude/retain. Defaults to [‘state’, ‘statecomb’, ‘frame’].

Returns:

The resulting, normed array

Return type:

xr.DataArray

replace_total(da, to_replace, value)

Replaces each occurence of to_replace in da with the corresponding element of value. Replacement must be total, i.e. every element of da must be in to_replace. This permits a change of dtype between to_replace and value. This function is based on the snippets at https://github.com/pydata/xarray/issues/6377

Parameters:
Return type:

An xr.DataArray with dtype matching value.

relativize(da, **sel)

Subtract the minimum of an xr.DataArray from all the array’s elements

Parameters:

  • da (xarray.DataArray) – The xr.DataArray from which to subtract the minimum

  • **sel – If keyword parameters are present, the reference minimum is picked

Return type:

xarray.DataArray

:param from those elements that remain after running xarray.DataArray.sel(): :param using the keyword parameters as arguments.:

Return type:

The result of subtraction, with attrs intact.

Parameters:

da (xarray.DataArray)

pwdists(atXYZ, mean=False)

Compute pairwise distances and standardize it by removing the mean and L2-normalization (if your features are vectors and you want magnitudes only, to lose directional info)

Parameters:

  • atXYZ (shnitsel.core.typedefs.AtXYZ) – A DataArray containing the atomic positions; must have a dimension called ‘atom’

  • mean (bool) – subtract mean if true to center data

Return type:

A DataArray with the same dimensions as atXYZ but transposed

get_standardized_pairwise_dists