Numpy Remove duplicates, apply function, then add it back

Question

We have an array x containing duplicates and a function f() that only accepts a 1-D array without duplicates. We need the results of f(x) as if the function can accept duplicate values.

If we had removed the duplicate values before passing it into the function, how can we add duplicated results to the array return by the function?

import numpy as np

def f(x):
    ''' assume this function cannot accept duplicates '''
    return -1 * x

x = np.array([1, 3, 5, 7, 7, 9, 9, 9, 11, 13, 13, 15, 17, 17, 19, 21, 21, 21, 23])
y = f(np.unique(x))

print(y)    # [ -1 -3 -5 -7 -9 -11 -13 -15 -17 -19 -21 -23 

# Needed: [ -1 -3 -5 -7 -7 -9 -9 -9 -11 -13 -13 -15 -17 -17 -19 -21 -21 -21 -23 ]

Divakar · Accepted Answer · 2020-06-14 15:11:24Z

2

Approach #1

Use return_inverse argument with it -

unq, tags  = np.unique(x, return_inverse=True)
out = f(unq)[tags]

Approach #2

We can skip the sorting with np.unique using pandas.factorize instead for perf. boost -

import pandas as pd

tags, unq = pd.factorize(x)
out = f(unq)[tags]

Assumption is that f is working on an elementwise-manner.

edited Jun 14, 2020 at 15:11

answered Jun 14, 2020 at 15:02

Divakar

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Comments

Red · Accepted Answer · 2020-06-14 15:00:01Z

0

Although a bit strange...

import numpy as np

def f(X):
    return -1 * x

x = np.array([1, 3, 5, 7, 7, 9, 9, 9, 11, 13, 13, 15, 17, 17, 19, 21, 21, 21, 23])
y = f(np.unique(x))

print(y)

Output:

[ -1  -3  -5  -7  -7  -9  -9  -9 -11 -13 -13 -15 -17 -17 -19 -21 -21 -21 -23]

answered Jun 14, 2020 at 15:00

Red

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10 Comments

Divakar Over a year ago

I am not getting that y. Are you sure you printing the y from your code?

Red Over a year ago

Yes. Try copying and pasting the whole thing.

Divakar Over a year ago

Your f has wrong syntax. It should be def f(x):. There's typo.

Divakar Over a year ago

You have def f(X):. Why are using x and not X inside the function?

Divakar Over a year ago

With def f(X): return -1 * x, it's picking x from globals(), not the function argument, which has X. I am assuming you are noticing the difference between X and x. f(np.unique(x)) is not supposed to work as OP showed in the question. Making a typo just to show an expected output isn't a solution.

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