metrics.py

import numpy as np
from dtw import *
from scipy.spatial import distance



def weighted_jaccard(process_A, process_B):
    if process_A != None and process_B != None:
        mi = float(0)
        ma = float(0)
        for a, b in zip(process_A,process_B):
            if not (a == 0 and b == 0):
                mi += min(a,b)
                ma += max(a,b)
                
        return 1 - float(mi / ma)
        #return float(distance.jaccard(process_A, process_B))
    return -100

def dtw_as_float(process_A, process_B):
    if process_A != None and process_B != None:
    #    print(dtw(process_A, process_B, keep_internals=True).distance)
        return float(dtw(process_A, process_B, keep_internals=True).distance)
    return -100
def euclidean_as_float(process_A, process_B):
    if process_A != None and process_B != None:
        
        return float(np.linalg.norm(np.array(process_A)-np.array(process_B)))
    return -100
def real_jaccard(process_A, process_B):
    if process_A != None and process_B != None:
        return float(distance.jaccard(process_A, process_B))
    return -100