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KozaiLidov/lib/plots.py
2021-10-30 16:42:12 +02:00

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Python
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#!/usr/bin/python
# -*- coding:utf-8 -*-
"""
Implementation of the plotting and visualization functions.
"""
import numpy as np
import time
import matplotlib.pyplot as plt
class DynamicUpdate():
#Suppose we know the x range
min_x = -10
max_x = 10
plt.ion()
def on_launch(self):
#Set up plot
self.figure, self.ax = plt.subplots()
self.lines, = self.ax.plot([],[],'o')
#Autoscale on unknown axis and known lims on the other
self.ax.set_autoscaley_on(True)
self.ax.set_xlim(self.min_x, self.max_x)
self.ax.set_ylim(self.min_x, self.max_x)
#Other stuff
self.ax.grid()
self.ax.set_aspect('equal')
def on_running(self, xdata, ydata, step=None, label=None):
#Update data (with the new _and_ the old points)
self.lines.set_xdata(xdata)
self.lines.set_ydata(ydata)
if not label is None:
self.ax.set_title(label)
#Need both of these in order to rescale
self.ax.relim()
self.ax.autoscale_view()
#We need to draw *and* flush
self.figure.canvas.draw()
self.figure.canvas.flush_events()
if not step is None and step%10==0:
self.figure.savefig("tmp/{0:05d}.png".format(step),bbox_inches="tight")
#Example
def __call__(self):
import numpy as np
import time
self.on_launch()
xdata = []
ydata = []
for x in np.arange(0,10,0.5):
xdata.append(x)
ydata.append(np.exp(-x**2)+10*np.exp(-(x-7)**2))
self.on_running(xdata, ydata)
time.sleep(1)
return xdata, ydata