matplotlib is the most used to plot. It is the reference.
Every plotting library works the same way:
Step (A) and (B) can be repeated in any order. Curves and legends superimposed.
%matplotlib inline
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Some parts of matplotlib are written in C and needs to be compiled. Thus the instruction pip install matplotlib
usually fails on Windows unless Visual Studio 2015 Community Edition is installed. I recommend to use a precompiled version through conda install matplotlib
or Unofficial Windows Binaries for Python Extension Packages sous Windows.
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.pyplot as plt
N = 150
r = 2 * np.random.rand(N)
theta = 2 * np.pi * np.random.rand(N)
area = 200 * r**2 * np.random.rand(N)
colors = theta
ax = plt.subplot(111, projection='polar')
c = plt.scatter(theta, r, c=colors, s=area, cmap=plt.cm.hsv)
c.set_alpha(0.75)
import matplotlib
matplotlib.matplotlib_fname()
'c:\\Python36_x64\\lib\\site-packages\\matplotlib\\mpl-data\\matplotlibrc'
import os
matplotlib.rcParams['animation.ffmpeg_path'].replace(os.environ.get("USERPROFILE", "~"), "<user>")
'<user>\\ffmpeg-20170821-d826951-win64-static\\bin\\ffmpeg.exe'
import matplotlib.animation
matplotlib.animation.writers.list()
['ffmpeg', 'ffmpeg_file']
Let's take an example from matplotlib documentation bayes_update.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def data_gen():
t = data_gen.t
cnt = 0
while cnt < 1000:
cnt+=1
t += 0.05
yield t, np.sin(2*np.pi*t) * np.exp(-t/10.)
data_gen.t = 0
fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
ax.set_ylim(-1.1, 1.1)
ax.set_xlim(0, 5)
ax.grid()
xdata, ydata = [], []
def run(data):
# update the data
t,y = data
xdata.append(t)
ydata.append(y)
xmin, xmax = ax.get_xlim()
if t >= xmax:
ax.set_xlim(xmin, 2*xmax)
ax.figure.canvas.draw()
line.set_data(xdata, ydata)
return line,
anim = animation.FuncAnimation(fig, run, data_gen, blit=True, interval=10, repeat=False)
# saves the video
from matplotlib.animation import writers
Writer = writers['ffmpeg']
writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)
anim.save('lines2.mp4', writer=writer)
import os
[_ for _ in os.listdir(".") if "mp4" in _]
['lines2.mp4']
Open question : how to display the video in the notebook?