Array of indexes for each element alongs the first dimension in a 2D array (numpy., tensorflow)

Question

indexes = np.array([[0,1,3],[1,2,4 ]])
data = np.random.rand(2,5)

Now, i would like an array of shape (2,3), where

result[0] = data[0         


        

Answer 1

Here are NumPy and TensorFlow solutions:

import numpy as np
import tensorflow as tf

def gather_index_np(data, index):
    data = np.asarray(data)
    index = np.asarray(index)
    # Make open grid of all but last dimension indices
    grid = np.ogrid[tuple(slice(s) for s in index.shape[:-1])]
    # Add extra dimension in grid
    grid = [g[..., np.newaxis] for g in grid]
    # Complete index
    index_full = tuple(grid + [index])
    # Index data to get result
    result = data[index_full]
    return result

def gather_index_tf(data, index):
    data = tf.convert_to_tensor(data)
    index = tf.convert_to_tensor(index)
    index_shape = tf.shape(index)
    d = index.shape.ndims
    # Make grid of all dimension indices
    grid = tf.meshgrid(*(tf.range(index_shape[i]) for i in range(d)), indexing='ij')
    # Complete index
    index_full = tf.stack(grid[:-1] + [index], axis=-1)
    # Index data to get result
    result = tf.gather_nd(data, index_full)
    return result

Example:

import numpy as np
import tensorflow as tf

data = np.arange(10).reshape((2, 5))
index = np.array([[0, 1, 3], [1, 2, 4]])
print(gather_index_np(data, index))
# [[0 1 3]
#  [6 7 9]]
with tf.Session() as sess:
    print(sess.run(gather_index_tf(data, index)))
# [[0 1 3]
#  [6 7 9]]