## Generated by Codox

# Propeller 0.3.2

# propeller.tools.metrics

Functions to measure things.

### argmax

`(argmax coll)`

returns the index of the maximum value in a list, randomly tiebreaking

### argmax-last

`(argmax-last coll)`

returns the index of the maximum value in a list, tiebreaking last

### argmins

`(argmins coll)`

returns the indice(s) of the minimum value of a list. Could be more efficient, probably

### compute-next-row

`(compute-next-row prev-row current-element other-seq pred)`

computes the next row using the prev-row current-element and the other seq

### hamming-distance

`(hamming-distance seq1 seq2)`

Calculates the Hamming distance between two sequences, including strings.

### levenshtein-distance

`(levenshtein-distance a b & {p :predicate, :or {p =}})`

Levenshtein Distance - http://en.wikipedia.org/wiki/Levenshtein_distance In Information Theory and Computer Science, the Levenshtein distance is a metric for measuring the amount of difference between two sequences. This is a functional implementation of the Levenshtein edit distance with as little mutability as possible. Still maintains the O(nm) guarantee.

### mean

`(mean coll)`

Returns the mean of a collection.

### mean-of-colls

`(mean-of-colls coll)`

returns the mean of multiple colls

### median

`(median coll)`

Returns the median of a collection.

### min-of-colls

`(min-of-colls coll)`

returns the smallest value of multiple colls

### multiset-distance

`(multiset-distance ms1 ms2)`

Returns the total of the differences between the counts of all items across the provided multisets.

### sequence-similarity

`(sequence-similarity seq1 seq2)`

Returns a number between 0 and 1, indicating how similar the sequences are as a normalized, inverted Levenshtein distance, with 1 indicating identity and 0 indicating no similarity.