scipy.interpolate.RegularGridInterpolator.__call__

RegularGridInterpolator.__call__(xi, method=None)

Interpolation at coordinates.

Parameters

xindarray of shape (…, ndim)

The coordinates to evaluate the interpolator at.

methodstr

The method of interpolation to perform. Supported are “linear” and “nearest”.

Examples

Here we define a nearest-neighbor interpolator of a simple function

>>> x, y = np.array([0, 1, 2]), np.array([1, 3, 7])
>>> def f(x, y):
...     return x**2 + y**2
>>> data = f(*np.meshgrid(x, y, indexing='ij', sparse=True))
>>> from scipy.interpolate import RegularGridInterpolator
>>> interp = RegularGridInterpolator((x, y), data, method='nearest')

By construction, the interpolator uses the nearest-neighbor interpolation

>>> interp([[1.5, 1.3], [0.3, 4.5]])
array([2., 9.])

We can however evaluate the linear interpolant by overriding the method parameter

>>> interp([[1.5, 1.3], [0.3, 4.5]], method='linear')
array([ 4.7, 24.3])