scipy for xarray

xr-scipy is a thin wrapper of scipy for the xarray eco-system. You can read the documentation here.

Many scipy functions, such as scipy.integrate.trapezoid requires coordinate array as an argument. xr-scipy wraps these functions to use native coordinate objects of xarray and returns an xarray object with the computed data. This enables more xarray-oriented data analysis with scipy.

Other usage/options are kept almost the same as the original scipy function.

Example

import xarray as xr
import numpy as np
import xrscipy.integrate

In[1]: da = xr.DataArray([0, 3, 2, 4, 6], coords={'x': np.linspace(0, 1, 5)})
In[2]: da
Out[2]:
<xarray.DataArray (x: 5)>
array([0, 3, 2, 4, 6])
Coordinates:
  * x        (x) float64 0.0 0.25 0.5 0.75 1.0

In[3]: xrscipy.integrate.cumulative_trapezoid(da, coord='x')
Out[3]:
<xarray.DataArray (x: 5)>
array([0.   , 0.375, 1.   , 1.75 , 3.   ])
Coordinates:
  * x        (x) float64 0.0 0.25 0.5 0.75 1.0

Installation

pip install xrscipy