在包含其他数据类型的列表中查找最小 integer 值的索引

Question

I have a function which creates a list of integers. Under some circumstances it can happen (and will) that I can't determine a value to add to the list, so until now I added a float('nan') :

min_list = []
for obj in objects:
    try:
        min_list.append(obj.foo())
    except Exception as e:
        min_list.append(float('nan')) # I have to add something here, 
                                      # to get the correct index later

Then I want to find the index of the min value in the list:

index = min_list.index(min(min_list))

So, as you could imagine, appending float('nan') does not really work and I have no clue, how to solve this problem. Especially I also need to find the case, when every call of foo() raises a Exception(every value is a float('nan') ):

nan_list = [e for e in min_list if isinstance(e, float)]
if len(nan_list) == len(min_list):
    return None
else:
    return index

How can I achieve that the None value is returned, if I have the same count of exceptions and objects? (I could also raise a exception or return a negative value). And how can I satisfy the problem to find the correct index, even with a raised exception, when I can't add a correct value to the list?

Answer 1

You can do:

def get_min(min_list):
    try:
        return min_list.index(min([np.inf if val is None else val for val in min_list]))
    except ValueError:
        return None

list_a = [None, 3, 5, 7, None, 5]
list_b = [None, None, None]
print(get_min(list_a)) #OUTPUT 1
print(get_min(list_b)) #OUTPUT None

The benefit of this method is that you don't really have to use numpy for it, and just replace np.inf with a very high value, that you know there is no way it will be in the original list (like 99999999999)

Answer 2

Numpy-based solution using nanargmin

import numpy as np

min_list = []
for obj in objects:
    try:
        min_list.append(obj.foo())
    except Exception as e:
        min_list.append(np.nan)

# ....

try:
    # Case where there is at least one valid element
    min_i = np.nanargmin(min_list)
except ValueError as e:
    # Case where min_list is full of nan