As title, I am working on time-series alignment, and a visualization of the alignment result is desired.
To this end, I want to draw lines connecting "anchor points" generated by the alignment algorithm.
np.random.seed(5)
x = np.random.rand(10) # time-series 1
y = np.random.rand(20) # time-series 2
ap = np.array(([0, 4, 9], # the anchor points
[0, 9, 19]))
fig = plt.figure(figsize=(10,5))
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.plot(x, 'r')
ax2.plot(y, 'g')
the anchor points ap
in the example specify the one-to-one "mapping" between the indices of two time series x
and y
, i.e., x[0]
is corresponding to y[0]
; x[4]
to y[9]
; and x[9]
to y[19]
. The goal is to draw lines between two separate plot to show the result of the alignment.
To connect two subplots in matplotlib you may use a ConnectionPatch
.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import ConnectionPatch
np.random.seed(5)
x = np.random.rand(21) # time-series 1
y = np.random.rand(21) # time-series 2
ap = np.array(([0, 5, 10], # the anchor points
[0,10, 20]))
fig = plt.figure(figsize=(10,5))
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.plot(x, 'r')
ax2.plot(y, 'g')
ls = ["-","--"]
c = ["gold", "blue"]
for i, row in enumerate(ap):
for j, ind in enumerate(row):
px = (ind, x[ind])
py = (ind, y[ind])
con = ConnectionPatch(py,px, coordsA="data", coordsB="data",
axesA=ax2, axesB=ax1, linestyle=ls[i], color=c[i])
ax2.add_artist(con)
plt.show()