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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.
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
pip install xrscipy
FAQs
Scipy integrated into xarray
We found that xrscipy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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