im_matplotlib September 26, 2021 1 matplotlib matplotlib is the most used to plot. It is the reference. Every plotting library works the same way: • We define axis (they boundaries can be adjusted based on thedata) • We add curves, points, surfaces (A). • We add legendes (B). • We convert the plot into an image. Step (A) and (B) can be repeated in any order. Curves and legends superimposed. documentation source installation tutorial gallery [1]: %matplotlib inline [2]: from jyquickhelper import add_notebook_menu add_notebook_menu() [2]: <IPython.core.display.HTML object> 1.1 Setup 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 recom- mend to use a precompiled version through conda install matplotlib or Unofficial Windows Binaries for Python Extension Packages sous Windows. [3]: import matplotlib.pyplot as plt 1.2 First example [4]: 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') 1 c = plt.scatter(theta, r, c=colors, s=area, cmap=plt.cm.hsv) c.set_alpha(0.75) 1.3 Animation To make it work: • Install ffmpeg on Windows or avconv on Linux • On Windows, open file matplotlibrc and update parameter animation.ffmpeg_path. On Linux, the same must be done for avconv. [5]: import matplotlib matplotlib.matplotlib_fname() [5]: 'c:\\Python36_x64\\lib\\site-packages\\matplotlib\\mpl-data\\matplotlibrc' [6]: import os matplotlib.rcParams['animation.ffmpeg_path'].replace(os.environ.get("USERPROFILE",␣ ,!"~"), "<user>") [6]: '<user>\\ffmpeg-20170821-d826951-win64-static\\bin\\ffmpeg.exe' [7]: import matplotlib.animation matplotlib.animation.writers.list() [7]: ['ffmpeg', 'ffmpeg_file'] Let’s take an example from matplotlib documentation bayes_update. 2 [8]: 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) 3 [9]: import os [_ for _ in os.listdir(".") if "mp4" in _] [9]: ['lines2.mp4'] Open question : how to display the video in the notebook? 1.4 Interactions Interaction can be done with the regular GUI. See poly_editor.py. Use javascript! [10]: [11]: 4.