Let's say I have many 1-dimensional vectors of the same dimension which I want to compare to each other. What I'm really looking for is to check whether they are all very similar, or not, and to derive a score based on the overall similarity (a mean of similarities?).
I don't need to try to align the vectors, I just want to correlate them from start to end to each other.
I have to perform this computation a large number of times, and it must be very fast. The vectors are small (100 units) and float-based. I am using Python. Is there a trick other than to compare each vector to each other vectors and take the worst correlation for each?