Numpy Slicing: All Except One Array Entry

What is the best way to exclude exact one NumPy array entry from an operation? I have an array x containing n values and want to exclude the i-th entry when I call numpy.prod(x). I

Solution 1:

I think the simplest would be

np.prod(x[:i]) * np.prod(x[i+1:])

This should be fast and also works when you don't want to or can't modify x.

And in case x is multidimensional and i is a tuple:

x_f = x.ravel()
i_f = np.ravel_multi_index(i, x.shape)
np.prod(x_f[:i_f]) * np.prod(x_f[i_f+1:])

Solution 2:

You could use np.delete whch removes an element from a one-dimensional array:

import numpy as np
x = np.arange(1, 5)  
i = 2
y = np.prod(np.delete(x, i)) # gives 8

Solution 3:

I don't think there is any better way, honestly. Even without knowing the NumPy functions, I would do it like:

#I assume x is array of len n
temp = x[i] #where i is the index of the value you don't want to change

x = x * 5
#...do whatever with the array...

x[i] = temp

If I understand correctly, your problem is one dimensional? Even if not, you can do this the same way.

EDIT: I checked the prod function and in this case I think you can just replace the value u don't want to use with 1 (using temp approach I've given you above) and later just put in the right value. It is just a in-place change, so it's kinda efficient. The second way you can do this is just to divide the result by the x[i] value (assuming it's not 0, as commenters said).

Solution 4:

As np.prod is taking the product of all the elements in an array, if we want to exclude one element from the solution, we can set that element to 1 first in order to ignore it (as p * 1 = p).

So:

>>>n = 10>>>x = np.arange(10)>>>i = 0>>>x[i] = 1>>>np.prod(x)
362880

which, we can see, works:

>>> 1 * 2 * 3 * 4 * 5 * 6 * 7 * 8 * 9
362880

Solution 5:

You could use a list comprehension to index all the points but 1:

i = 2
np.prod(x[[val for val in range(len(x)) if val != i]])

or use a set difference:

np.prod(x[list(set(range(len(x)) - {i})])