Numpy Indexing with Arrays

Question

I have 2 arrays [nx1] that store xpixel (sample) and ypixel (line) coordinates, respectively. I have another array [nxn] storing an image. What I would like to do is create a third array which stores the pixel values from the image array at the given coordinates. I have this working with the following, but wonder if a built-in numpy function would be more efficient.

#Create an empty array to store the values from the image.
newarr = numpy.zeros(len(xsam))

#Iterate by index and pull the value from the image.  
#xsam and ylin are the line and sample numbers.

for x in range(len(newarr)):
    newarr[x] = image[ylin[x]][xsam[x]]

print newarr

A random generator determines the length of xsam and ylin along with the direction of travel through the image. It is therefore totally different with each iteration.

Answer 1

If image is a numpy array and ylin, xsam are one dimensional:

newarr = image[ylin, xsam]

If ylin, xsam are two-dimensional with the second dimension being 1 e.g., ylin.shape == (n, 1) then convert them to one-dimensional form first:

newarr = image[ylin.reshape(-1), xsam.reshape(-1)]

Answer 2

You can use advanced indexing:

In [1]: import numpy as np
In [2]: image = np.arange(16).reshape(4, 4)
In [3]: ylin = np.array([0, 3, 2, 2])
In [4]: xsam = np.array([2, 3, 0, 1])
In [5]: newarr = image[ylin, xsam]
In [6]: newarr
array([ 2, 15,  8,  9])