Choose smallest value in dictionary

Question

I have a dictionary given in the form {(i1,r1,m1):w, (i2,r2,m1):w, (i1,r1,m2):w ...} where i is the activity, r the type of resource, m the mode, and w is the resources of type r needed of activity i in mode m.

Now I would like to choose for every activity the mode, that requires the least resources (w). If possible, at the end in a list in the form [(i,m),...] for every i.

My tutor suggested to work with np.argmin(), but for this I have to convert the dictionary into an array. So I tried to convert the dictionary into an array:

w_list = list(w.items())
w_array = np.array(w_list)

print(w_array)

array([[(0, 1, 1), 0],
       [(0, 2, 1), 0],
       [(1, 1, 1), 9],
       [(1, 2, 1), 0], ...

However, this array arrangement cannot be used for np.argmin.

Does anyone have any other idea how I can get the desired list mentioned above?

Answer 1

Here's one trivial non-numpy solution - simply create a new dictionary, and fill it with the mode and lowest cost per activity by iterating over the original dict:

w = {(i1,r1,m1): w1, (i2,r2,m1): w2, (i1,r1,m2): w3} #your original dict

result = {}
for (activity, _, mode), requiredResources in w.items():
    if activity not in result or result[activity][1] > requiredResources:
        result[activity] = mode, requiredResources

Now result holds a mapping from i to a tuple of m and w for the lowest w. In case of ambiguous entries for some i, the first entry in the iteration order will win (and as dicts are unordered, the iteration order is an implementation detail and dependend on things such as the specific keys and the dict size).

If you want to turn this into a list of i and m tuples, simply use a list comprehension:

resultList = [(k, v[0]) for k, v in result.items()]

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An observation on the side: when confronted with any python problem, some people instantly recommend using numpy or similar libraries. IMO this is simply an expression of their own inexperience or ignorance - in many cases numpy is not just unneccessary, but actively detrimental if you don't know what you're doing.

If you're intending to seriously work with python, you would do well to first master the basics of the language (functions, classes, lists, dictionaries, loops, comprehensions, basic variable scoping rules), and get a rough overview of the vast python standard library - at least enough to know how to look up if something you need is readily available in some built-in module. Then next time when you need some functionality, you will be better equipped for deciding if this is something you can easily implement yourself (potentially with help from the standard lib), or if it makes sense to use functionality from external libraries such as numpy.