How to iterate over two dictionaries & do calculation with values, conditional on keys?

Question

I have two dictionaries, in both of which the keys are file names and the values are a array. dict_1 has 50 key value pairs, and dict_2 has 25, which are a subset of pairs from dict_1. I want to take each file in dict_1, and calculate the cosine between it's array and each array in dict_2, as long as the file name is not the same. Then take an average of these.

I have tried the following code:

for key in dict_1:
    cosines = []
    if key != dict_2[key]:
        cos = 1 - spatial.distance.cosine(dict_1[value],dict_2[value])
        cosines.append(cos)
        av = np.mean(cosines)

But I am getting the error 'TypeError: unhashable type: 'numpy.ndarray'. I'm not really sure if this isthe best approach anyway. I think I could use itertools.combinations() but I don't know how to exclude keys that are the same. Any help greatly appreciated!

Answer 1

Your comparisons of the keys doesn't accomplish what you want. if key != dict_2[key]: compares the key from dict_1 with a value from dict_2. It sounds like you instead want to compare keys.

Perhaps:

average = []
for key, value in dict_1.items():
    cosines = []
    for key2, value2 in dict_2.items():
        if key != key2:
            cos = # ...
            cosines.append(cos)
    averages.append(np.mean(cosines))