monet.util.combinetool

Functions

combine_da_to_da(source, target, *[, merge, ...])

Combine xarray data array source with with point observations in second data array target, returning a new xarray object.

combine_da_to_df(da, df, *[, merge])

Combine xarray data array da with spatial information point observations in dataframe df, returning a new dataframe.

combine_da_to_df_xesmf(da, df, *[, suffix])

Combine xarray data array da with spatial information point observations in dataframe df, returning a new dataframe.

combine_da_to_df_xesmf_strat(da, daz, df, ...)

This function will combine an xarray data array with spatial information point observations in df.

combine_da_to_height_profile(da, dset, *[, ...])

This function will combine an xarray.DataArray to a 2d dataset with dimensions (time,z)
monet.util.combinetool.combine_da_to_da(source, target, *, merge=True, interp_time=False, **kwargs)

Combine xarray data array source with with point observations in second data array target, returning a new xarray object.

Uses pyresample nearest-neighbor via .monet.remap_nearest.

Parameters

  • source (xarray.DataArray or xarray.Dataset) – Gridded data.

  • target (xarray.DataArray) – Point observations.

  • merge (bool) – If false, only return the interpolated source data. If true, merge with the target data.

  • interp_time (bool) – Linearly interpolate to target.time.

  • kwargs (dict) – Passed on to remap_nearest().

Return type

xarray.Dataset

monet.util.combinetool.combine_da_to_df(da, df, *, merge=True, **kwargs)

Combine xarray data array da with spatial information point observations in dataframe df, returning a new dataframe.

Uses pyresample via .monet.remap_nearest.

Parameters

  • da (xarray.DataArray or xarray.Dataset) – Data to be interpolated to target grid points. Can be unstructured-grid data (detected by checking 'mio_has_unstructured_grid' attribute).

  • df (pandas.DataFrame) – Data on target points.

  • merge (bool) – Merge interpolated df data with da data. Otherwise, return interpolated da data only.

  • kwargs (dict) – Passed to remap_nearest() (if da is not unstructured-grid data).

Return type

pandas.DataFrame

monet.util.combinetool.combine_da_to_df_xesmf(da, df, *, suffix=None, **kwargs)

Combine xarray data array da with spatial information point observations in dataframe df, returning a new dataframe.

Uses resample_xesmf().

Parameters

  • da (xarray.DataArray or xarray.Dataset) – Data to be interpolated to target grid points.

  • df (pandas.DataFrame) – Data on target points.

  • suffix (str, optional) – Added to the name of the new variable, defaults to '_new'.

  • kwargs (dict) – Passed on to resample_xesmf() (and then to xesmf.Regridder).

Return type

pandas.DataFrame

monet.util.combinetool.combine_da_to_df_xesmf_strat(da, daz, df, **kwargs)

This function will combine an xarray data array with spatial information point observations in df.

Parameters

  • da (xarray.DataArray) – Data to interpolate.

  • daz (xarray.DataArray) – Vertical coordinate data variable. Must have same shape as da.

  • df (pandas.DataFrame) – Point data.

  • kwargs (dict) – Passed on to resample_xesmf() (and then to xesmf.Regridder).

Return type

pandas.DataFrame

monet.util.combinetool.combine_da_to_height_profile(da, dset, *, radius_of_influence=12000.0)

This function will combine an xarray.DataArray to a 2d dataset with dimensions (time,z)

Parameters

  • da (xarray.DataArray)

  • dset (xarray.Dataset)

Returns

Returns the xarray.Dataset with the da added as an additional variable.

Return type

xarray.Dataset