RegularGridInterpolator.__call__(self, xi, method=None)
In the case that xi.ndim == 1 a new axis is inserted into the 0 position of the returned array, values_x, so its shape is instead (1,) + values.shape[ndim:].
The coordinates to evaluate the interpolator at.
The method of interpolation to perform. Supported are "linear", "nearest", "slinear", "cubic", "quintic" and "pchip". Default is the method chosen when the interpolator was created.
Interpolated values at xi. See notes for behaviour when xi.ndim == 1.
Interpolation at coordinates.
import numpy as np
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')
interp([[1.5, 1.3], [0.3, 4.5]])
interp([[1.5, 1.3], [0.3, 4.5]], method='linear')
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