CODEWITHSUNDEEP
pythonnumpy
Jason Strimpel
Jason Strimpel

Reputation: 15466

Combination of elements with numpy.array and scalars

I have a tuple which contains a numpy.array of arbitrary length along with scalars. Something like this:

(array([ 31.5,  31.6,  31.7,  31.8,  31.9,  32. ,  32.1,  32.2,  32.3,
    32.4,  32.5,  32.6,  32.7,  32.8,  32.9,  33. ,  33.1,  33.2,
    33.3,  33.4,  33.5,  33.6,  33.7,  33.8,  33.9,  34. ,  34.1,
    34.2,  34.3,  34.4,  34.5,  34.6,  34.7,  34.8,  34.9,  35. ,
    35.1,  35.2]), 30.0, 0.0025, 0.0, 0.0027, 0.2791, 1.5, 1.0, 100.0)

My result needs to pair each element of the numpy.array with all the other elements in the tuple. Challenge is that the numpy.array appears in an arbitrary location within the tuple such that I cannot index with a guarantee.

The result needs to be an iterable (preferably a tuple) of numpy.arrays, something like this:

(array([31.5, 30.0, 0.0025, 0.0, 0.0027, 0.2791, 1.5, 1.0, 100.0]),
array([31.6, 30.0, 0.0025, 0.0, 0.0027, 0.2791, 1.5, 1.0, 100.0]),
array([31.7, 30.0, 0.0025, 0.0, 0.0027, 0.2791, 1.5, 1.0, 100.0]),
array([31.8, 30.0, 0.0025, 0.0, 0.0027, 0.2791, 1.5, 1.0, 100.0]),
...
)

I have tried solutions presented here and here as well as itertools.product. The SE solutions assume two independent arrays and itertools.product is not the right solution either.

Upvotes: 1

Views: 163

Answers (3)

igavriil
igavriil

Reputation: 1021

This is another way to do it if you are certain that your tuple contains only one np.Array

C = [z for z in A if type(z) is not np.ndarray]
B = np.array([np.append(y,C) for y in [np.nditer(x) for x in A if type(x) is np.ndarray][0]]) 
#B can be a tuple or a list

Upvotes: 1

Alan
Alan

Reputation: 9610

import numpy as np
x = (np.array([ 31.5,  31.6,  31.7,  31.8,  31.9,  32. ,  32.1,  32.2,  32.3,
    32.4,  32.5,  32.6,  32.7,  32.8,  32.9,  33. ,  33.1,  33.2,
    33.3,  33.4,  33.5,  33.6,  33.7,  33.8,  33.9,  34. ,  34.1,
    34.2,  34.3,  34.4,  34.5,  34.6,  34.7,  34.8,  34.9,  35. ,
    35.1,  35.2]), 30.0, 0.0025, 0.0, 0.0027, 0.2791, 1.5, 1.0, 100.0)


components = sorted(x, key=lambda xi: np.isscalar(xi))
prefixes = components[0]
suffix = components[1:]
result = tuple(np.array([xi]+suffix) for xi in x)

Upvotes: 1

user707650
user707650

Reputation:

If you don't know the position of the array, you'll just have to find it. I would simply code it as follows:

from numpy import array, ndarray

a = (array([ 31.5,  31.6,  31.7,  31.8,  31.9,  32. ,  32.1,  32.2, 32.3,
    32.4,  32.5,  32.6,  32.7,  32.8,  32.9,  33. ,  33.1,  33.2,
    33.3,  33.4,  33.5,  33.6,  33.7,  33.8,  33.9,  34. ,  34.1,
    34.2,  34.3,  34.4,  34.5,  34.6,  34.7,  34.8,  34.9,  35. ,
    35.1,  35.2]), 30.0, 0.0025, 0.0, 0.0027, 0.2791, 1.5, 1.0, 100.0)

for i, aa in enumerate(a):
    if isinstance(aa, ndarray):
        break

t = tuple(s for j, s in enumerate(a) if j != i)

newlist = []
for aa in a[i]:
    newlist.append(array((aa,) + t)))
result = tuple(newlist)

Upvotes: 2

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