Py lecture5 python plots

Py lecture5 python plots

• 2.
   python 2Dplotting library which produces publication quality figures in › a variety of hardcopy formats › interactive environments
• 3.
  import matplotlib.pyplot asplt # x data, y data, style plt.plot([1,2,3,4], [5,6,7,8], 'r-') # [x min, x max, y min, y max] plt.axis([0, 5, 0, 9]) plt.ylabel('some numbers') plt.show()
• 5.
   Draw thegraph(y = x^2).
• 6.
  x = range(100) y= [i * i for i in x] plt.plot(x, y, 'r-') plt.ylabel('y = x^2') plt.show()
• 7.
  import matplotlib.pyplot asplt data = [2, 7, 6, 4, 1, 10, 3, 2, 4, 5, 3, 1] plt.hist(data, bins=8, facecolor='blue') plt.show()
• 9.
  import matplotlib.pyplot asplt # The slices will be ordered and plotted counter-clockwise. labels = 'Fuji', 'Tsugaru', 'Orin', 'Jonagold', 'Other' sizes = [235500, 50600, 47100, 45700, 89100] colors = ['orangered', 'red', 'greenyellow', 'orangered', 'gold'] explode = (0, 0, 0.1, 0, 0) # only "explode" the 3rd slice (i.e. 'Orin') plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True, startangle=90, counterclock=False) # Set aspect ratio to be equal so that pie is drawn as a circle. plt.axis('equal') plt.show()
• 11.
  import numpy asnp # use numpy import matplotlib.pyplot as plt x = np.array(range(10)) # red line plt.plot(x, x, ls='-', c='red') # blue circles plt.plot(x, x**1.25, ls='', c='blue', marker='o') # green stars plt.plot(x, x**1.5, ls='', c='green', marker='*') plt.show()
• 13.
   For moreproperties, do › lines=plt.plot([1, 2, 3]) › plt.setp(lines)
• 14.
  import numpy asnp import matplotlib.pyplot as plt x = np.array(range(10)) # first figure plt.figure(1) # num of row, num of column, num of axis plt.subplot(2, 3, 1) plt.plot(x, x, 'r') plt.subplot(2, 3, 2) plt.plot(x, x, 'bo') plt.show()
• 16.
  import numpy asnp import matplotlib.pyplot as plt x = np.arange(0, 1, 0.001) y = x**1.5 plt.plot(x, y, 'r') plt.xlabel(r'$x$') plt.ylabel(r'$y=x^{1.5}$') plt.title(r'Graph of $y=x^{1.5}$') plt.text(0.3, 0.25, r'$y=x^{1.5}$') plt.grid(True) plt.show()
• 18.
   Draw thegraph of binary entropy function 𝐻 𝑝 = −𝑝log2 𝑝 − 1 − 𝑝 log2 1 − 𝑝 › Hint: use np.log2 to calculate log2
• 19.
  import numpy asnp import matplotlib.pyplot as plt p = np.arange(0, 1, 0.001) H = -p*np.log2(p) - (1-p)*np.log2(1-p) plt.plot(p, H, 'r') plt.xlabel(r'$p$') plt.ylabel(r'$H(p)=-p ¥log_{2}(p)-(1-p)¥log_{2}(1-p)$') plt.title('Binary Entropy Function') plt.grid(True) plt.show()
• 20.
   Matplotlib tutorial http://matplotlib.org/users/pyplot_tutorial.html りんご大学 - 品種別生産量の推移 http://www.ringodaigaku.com/study/statistics/ production_kind.html