lair.inversion.utils

Utility functions for inversion module.

Functions

dataframe_matrix_to_xarray(frame)	Convert a pandas DataFrame to an xarray DataArray.
integrate_over_time_bins(data, time_bins[, ...])	Integrate data over time bins.
round_index(index, decimals)	Rounds the values in a pandas Index or MultiIndex if the level's data type is a numpy floating type.

lair.inversion.utils.integrate_over_time_bins(data: DataFrame | Series, time_bins: IntervalIndex, time_dim: str = 'time') → DataFrame | Series

Integrate data over time bins.

Parameters:

datapd.DataFrame | pd.Series

Data to integrate.

time_binspd.IntervalIndex

Time bins for integration.

time_dimstr, optional

Time dimension name, by default ‘time’

Returns:

pd.DataFrame | pd.Series

Integrated footprint. The bin labels are set to the left edge of the bin.

lair.inversion.utils.round_index(index: Index | MultiIndex, decimals: int) → Index | MultiIndex

Rounds the values in a pandas Index or MultiIndex if the level’s data type is a numpy floating type.

Parameters:

indexpd.Index | pd.MultiIndex

Input index to round.

decimalsint

Number of decimal places to round to.

Returns:

pd.Index | pd.MultiIndex

Rounded index.

lair.inversion.utils.dataframe_matrix_to_xarray(frame: DataFrame) → DataArray

Convert a pandas DataFrame to an xarray DataArray.

If the DataFrame has a MultiIndex for columns, all levels of the MultiIndex are stacked into the index of the resulting DataArray.

Parameters:

framepd.DataFrame

DataFrame to convert.

Returns:

xr.DataArray

Converted DataArray.