# _*_ coding:utf-8 _*_ """ This file is about `matplotlib` Mainly cited from http://matplotlib.org/users/pyplot_tutorial.html """ import matplotlib.pyplot as plt import numpy as np import random def basic_linear(): y_lst = [1, 2, 3, 4] # y_lst = random.sample(range(80000), 500) plt.plot(y_lst) plt.ylabel('y axis value') plt.show() def plot_x1_y4(): """ plot a line x = 1 :return: """ plt.plot([0, 0], [0, 4], color='red', linewidth=3.0) plt.axis([-1, 1, -4, 4]) plt.show() def basic_curve(): x = np.linspace(0, 2, 11) print x y = x ** 3 - 5 * x ** 2 + 6 * x + 1 print y # plt.plot(x, y, 'r-') # plt.plot(x, y) lines = plt.plot([1, 2, 3, 4], [1, 4, 9, 16]) plt.setp(lines, color='r') plt.show() # plt.axis([0, 100, 0, 100]) def multi_curve(): t = np.arange(0., 5., 0.2) print t # plt.plot(t, t, 'r-', t, t**2, 'bs', t, t**3, 'g^') # plt.show() def f(t): return np.exp(-t) * np.cos(2 * np.pi * t) def multi_figure(): plt.figure(1) # the first figure plt.subplot(211) # the first subplot in the first figure plt.plot([1, 2, 3]) plt.subplot(212) # the second subplot in the first figure plt.plot([4, 5, 6, 7, 11]) plt.figure(2) # a second figure plt.plot([4, 5, 6]) # creates a subplot(111) by default plt.figure(1) # figure 1 current; subplot(212) still current plt.subplot(211) # make subplot(211) in figure1 current plt.title('Easy as 1, 2, 3') # subplot 211 title plt.show() def multi_figure_two(): t1 = np.arange(0., 5, 0.1) t2 = np.arange(0., 5, 0.02) plt.figure(1) plt.subplot(211) plt.plot(t1, f(t1), 'k') plt.subplot(212) plt.plot(t2, np.cos(2 * np.pi * t2), 'bo') plt.show() def histogram(): x_mul = [np.random.randn(n) for n in [1000, 1000, 1000]] print x_mul bin = 10 plt.hist(x_mul, bin) plt.show() def histogram_two(): x_mul = [random.sample(range(0, 100), n) for n in [60, 50, 70]] print x_mul[0] print x_mul[1] print x_mul[2] bin = 10 plt.hist(x_mul, bin) plt.show() def plot_2d(): x = [1, 2, 3, 4, 5, 6, 7] y = [2.6, 3.6, 8.3, 56, 12.7, 8.9, 5.3] plt.plot(x, y) # plot line # plt.scatter(x, y) # plot scatter plt.show() def plot_orthogonal(): arr = np.array([[-0.85389096, -0.52045195], [0.52045195, -0.85389096]]) # arr = np.array([[1, -1], [1, 1]]) v1_x, v2_x = [arr[:, 0][0], 0], [arr[:, 1][0], 0] v1_y, v2_y = [arr[:, 0][1], 0], [arr[:, 1][1], 0] plt.plot(v1_x, v1_y) plt.plot(v2_x, v2_y) # plt.axis([-1, 1, -1, 1]) # set the below bound, or the line won't seem orthogonal # plt.axis([-0.85389096, 0.52045195, -0.85389096, 0.52045195]) plt.show() if __name__ == '__main__': plot_orthogonal() # plot_2d() # basic_linear() # basic_curve() # multi_curve() # multi_figure() # multi_figure_two() # histogram() # histogram_two() pass