A reasonably fast interp2 for python.

interpgrid.py

# -*- coding: utf-8 -*-
"""
Created on Thu Feb  6 15:01:40 2020
@author: aslak grinsted
"""


import numpy as np
import matplotlib.pyplot as plt
from numpy import nan

def interpgrid(x, y, a, xi, yi):
    """ 2d linear interpolation
    - vectorized version.
    - with bounds checking.

    - does not check if input sizes are compatible. 
    - assumes numpy inputs
    """

    xi = (xi - x[0]) / (x[1] - x[0])
    yi = (yi - y[0]) / (y[1] - y[0])
    Ny, Nx = a.shape
    Ni = xi.shape

    inbounds = (xi>=0)&(xi<Nx)&(yi>=0)&(yi<Ny) #excludes points where xi=Ny
    ai = np.full(xi.shape,np.nan)

    xi = xi[inbounds]
    yi = yi[inbounds]

    x = xi.astype(int)
    y = yi.astype(int)
    xn = x + 1
    yn = y + 1

    a00 = a[y, x]
    a01 = a[y, xn]
    a10 = a[yn, x]
    a11 = a[yn, xn]
    xt = xi - x
    yt = yi - y
    a0 = a00 * (1 - xt) + a01 * xt
    a1 = a10 * (1 - xt) + a11 * xt
    ai[inbounds] = a0 * (1 - yt) + a1 * yt

    return ai


#testing...................
x=np.arange(100,1000,30)
y=np.arange(-1000,100,30)
a=np.outer(np.sin(x/60),np.cos(y/80))

plt.imshow(a)

xi=np.linspace(-100,300,10)
yi=np.linspace(-500,110,10)

new =interpgrid(x,y,a,xi,yi)
print(new)