Random Macro-nutrient selection (Python)

Question

I am currently attempting to build a code that randomly selects food items from a table (which have a macro nutrient breakdown).

What i would like to know is how do i tell Python "Print the index of the food you randomly selected as a list"?

One approach would be to search the item in the list (using the `index` method). But I guess it's much easier to simply randomly select an index, not an item - and then you have the index for free, and the item is easily accessed (using `[]` operator) — Neo, Jul 01 '20 at 15:11
It would be better to reframe the title of your post. Macro-nutrient isn't a Python construct and the problem that you are trying to solve is a programming one, not biochemistry. :) Could you tell us what have you tried so far? Code snippets will be helpful. — navneethc, Jul 01 '20 at 15:11

score 0 · Answer 1 · edited Jul 01 '20 at 15:51

Assume our input looks like:

import numpy as np

macro_nutrients = [
    'carbohydrates',
    'fats',
    'dietary_fiber',
    'minerals',
    'proteins',
    'vitamins',
    'water'
]

You have several options:

If your macro-nutrients are stored in a list-like structure, you can do:

el = np.random.choice(macro_nutrients)
idx = macro_nutrients.index(el)
print(el, ";  Is the index correct?:", el == macro_nutrients[idx])

# or you can just write:
idx = np.random.randint(0, len(macro_nutrients) - 1)
print(macro_nutrients[idx])

For [].index() you can check this SO answer for caveats.

If you have a table-like structure (e.g. numpy 2d array):

# we will simulate it by permuting the above list several times and adding the
# permutation as a row in the new 2d array:
mat = np.array([np.random.permutation(macro_nutrients.copy()),
               np.random.permutation(macro_nutrients.copy()),
               np.random.permutation(macro_nutrients.copy()),
               np.random.permutation(macro_nutrients.copy())])

# flatten() will convert your table back to 1d array
np.random.choice(mat.flatten())

# otherwise, you can use something like:
row = np.random.randint(0, mat.shape[0] - 1)
col = np.random.randint(0, mat.shape[1] - 1)
print(mat[row, col])

Random Macro-nutrient selection (Python)

1 Answers1