I am trying to interpolate on a 2d array where the array has between its values zeros, which I want to replace these values with values that are close to or around these values, I have been reviewing several examples but I have not been successful in my search, I have tried the following interpolation code. import numpy as np from scipy import interpolate mymin,mymax = 0,3 X = np.linspace(mymin,mymax,4) Y = np.linspace(mymin,mymax,4) x,y = np.meshgrid(X,Y) test = np.array([[ 1.2514318 , 0, 1.25148472, 1.25151133], [ 1.25087456, 0, 1.25092764, 1.25095435], [ 1.25031581, 1.25034238, 1.25036907, 0], [ 0, 1.24978222, 0, 1.24983587]]) f = interpolate.interp2d(x,y,test,kind='linear') X_n = np.linspace(mymin,mymax,4) Y_n = np.linspace(mymin,mymax,4) test_n = f(X_n,Y_n) print (test_n) [[ 1.25143180e+00 2.77555756e-16 1.25148472e+00 1.25151133e+00] [ 1.25087456e+00 2.49800181e-16 1.25092764e+00 1.25095435e+00] [ 1.25031581e+00 1.25034238e+00 1.25036907e+00 1.38777878e-17] [ 5.33635770e-17 1.24978222e+00 -1.11022302e-16 1.24983587e+00]] As you can see if it works correctly but the places where the zeros were, it became a very small value that does not correspond to its values that are around it, would the way I am interpolating have a failure? Continue reading...
