np.set_printoptions(linewidth=np.nan)
vec1 = [71, 73, 75, 80, 80, 80, 78, 76, 75, 73, 71, 71, 71, 73, 75, 76, 76, 68, 76, 76, 75, 73, 71, 70, 70, 69, 68, 68, 72, 74, 78, 79, 80, 80, 78]
vec2 = [69, 69, 73, 75, 79, 80, 79, 78, 76, 73, 72, 71, 70, 70, 69, 69, 69, 71, 73, 75, 76, 76, 76, 76, 76, 75, 73, 71, 70, 70, 71, 73, 75, 80, 80, 80, 78]
t = np.array(vec1, np.double)
r = np.array(vec2, np.double)
f1 = plt.figure()
f2 = plt.figure()
f3 = plt.figure()
for f, case in [(f1, 1), (f2, 2), (f3, 3)]:
m = np.zeros((len(t), len(r)))
path, distance = dtw(t, r, case=case, start_anchor_slack=0, end_anchor_slack=0)
for point in path:
m[point[0], point[1]] = 1
np.set_printoptions(formatter={'all':lambda x: str('X') if x != 0 else str(' ')})
np.set_printoptions(precision=2)
distance[distance > 1e5] = np.inf
stretch = True
if stretch:
stretch = float(len(t))/len(r)
else:
window = 0.1
if len(sys.argv) > 1:
size = int(sys.argv[1])
if len(sys.argv) > 2:
window = float(sys.argv[2])
x = rand(size)
y = rand(size)
#x = np.array([1, 1, 2, 3, 2, 0])
#y = np.array([0, 1, 1, 2, 3, 2, 1])
print "Computing DTW distance...\n"
t0 = time.clock()
dist = dtw(x, y, window)
tf = time.clock()
print "DTW distance with window={}: {}".format(window, dist)
print "Took {} seconds.".format(tf - t0)
print "\nComputing DTW path...\n"
t0 = time.clock()
path = dtw_path(x, y, window)
tf = time.clock()
print path[:5]
print "..."
print path[-5:]
assert np.isclose(sum([abs(x[xi] - y[yi]) for xi, yi in path]), dist)
#print sum([abs(x[xi] - y[yi]) for xi, yi in path])
print "Took {} seconds.\n".format(tf - t0)
from __future__ import division
from _dtw import dtw
import numpy as np
import time
N = 1000
x = np.random.random(N)
y = np.random.random(N)
iterations = 100
t0 = time.clock()
for i in range(iterations):
dtw(x, y)
dt = (time.clock() - t0) / iterations * 1000
print "%.2f milliseconds per iteration (mean)" % dt
