Interpolate each row of 2d array with same 1d array

Question

Question: How do you you linearly interpolate each row of a 2d array with the same 1d array?

I have 2 sets of x-coordinates and a matrix of y-coordinates, I want to do this without the loop:

for k in range(len(y[:,0]))
    y_want = np.interp(x_want,x_have,y_have[k,:])
    y_new.append(y_want)

Is there a built in numpy function that can do this?

Rory Yorke · Accepted Answer · 2014-05-18 06:29:03Z

3

Use scipy.interpolate.interp1d:

import numpy as np
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt

x=np.linspace(0,1,11)

y=np.vstack((np.sin(x),np.cos(x),np.log1p(x)))

xi=np.linspace(0,1,101)

intf= interp1d(x,y,axis=1)

yi=intf(xi)

plt.ioff()
plt.plot(x,y.T,'x',
         xi,yi.T)
plt.show()

answered May 18, 2014 at 6:29

Rory Yorke

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1 Comment

AnalogDigital Over a year ago

For some reason this took longer than my loop. But, it is possible I am doing something wrong.

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