使用python中的Matplotlib绘图示例(续)

下面给出一些比较高级的例子:

注意:

代码中需要保存运行结果图, 需要事先在当前源码目录下创建一个figure文件夹来存放图片.

一.数学图形

#!/usr/bin/env python#encoding: utf-8#numpy is accessible via 'np' aliasfrom pylab import *figure(figsize=(8,5), dpi=80)subplot(111)X = np.linspace(-np.pi, np.pi, 256, endpoint=True)C,S = np.cos(X), np.sin(X)plot(X, C, color="blue", linewidth=2.5, linestyle='-', label='cosine')plot(X, S, color="red", linewidth=2.5, linestyle='-', label='sine')ax = gca()ax.spines['right'].set_color('none')ax.spines['top'].set_color('none')ax.xaxis.set_ticks_position('bottom')ax.spines['bottom'].set_position(('data', 0))ax.yaxis.set_ticks_position('left')ax.spines['left'].set_position(('data', 0))xlim(X.min()*1.1, X.max()*1.1)xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi], [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$'])ylim(C.min()*1.1, C.max()*1.1)yticks([-1, 0, +1], [r'$-1$', r'$0$', r'$+1$'])t = 2*np.pi/3plot([t,t], [0,np.cos(t)], color='blue', linewidth=1.5, linestyle='--')scatter([t,], [np.cos(t),], 50, color='blue')annotate(r'$\sin(\frac{2\pi}{3})=\frac{\sqrt{3}}{2}$', xy=(t, np.sin(t)), xycoords='data', xytext=(+10, +30),        textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle='arc3, rad=.2'))plot([t,t], [0,np.sin(t)], color='red', linewidth=1.5, linestyle='--')scatter([t,], [np.sin(t),], 50, color='red')annotate(r'$\cos(\frac{2\pi}{3})=\frac{1}{2}$', xy=(t, np.cos(t)), xycoords='data', xytext=(-90, -50),        textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle='arc3, rad=.2'))legend(loc='upper left');for label in ax.get_xticklabels() + ax.get_yticklabels():    label.set_fontsize(16)    label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.65))#must create dir in advancesavefig("figure/exercise_10.png", dpi=72)show()

二.散点图(scatter plots)

#!/usr/bin/env python#encoding: utf-8from pylab import *n = 1024X = np.random.normal(0, 1, n)Y = np.random.normal(0, 1, n)T = np.arctan2(Y, X)axes([0.025, 0.025, 0.95, 0.95])scatter(X, Y, s=75, c=T, alpha=.5)xlim(-1.5, 1.5), xticks([])ylim(-1.5, 1.5), yticks([])savefig('figure/scatter_ex.png', dpi=48)show()

三.等高线图(contour plots)

#!/usr/bin/env python#encoding: utf-8from pylab import *def f(x, y):    return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)n = 256x = np.linspace(-3, 3, n)y = np.linspace(-3, 3, n)X, Y = np.meshgrid(x, y)axes([0.025, 0.025, 0.95, 0.95])contourf(X, Y, f(X,Y), 8, alpha=.75, cmap=cm.hot)C = contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5)clabel(C, inline=1, fontsize=10)xticks([])yticks([])savefig('figure/contour_ex.png', dpi=48)show()

四.饼图(Pie charts)

#!/usr/bin/env python#encoding: utf-8from pylab import *n = 20Z = np.ones(n)Z[-1] *= 2axes([0.025, 0.025, 0.95, 0.95])pie(Z, explode=Z*.05, colors = ['%f' % (i/float(n)) for i in range(n)])gca().set_aspect('equal')xticks([])yticks([])savefig('figure/pie_ex.png', dpi=48)show()

五.极轴图

#!/usr/bin/env python#encoding: utf-8from pylab import *ax = axes([0.025, 0.025, 0.95, 0.95], polar=True)N = 20theta = np.arange(0.0, 2*np.pi, 2*np.pi/N)radii = 10*np.random.rand(N)width = np.pi/4*np.random.rand(N)bars = bar(theta, radii, width=width, bottom=0.0)for r,bar in zip(radii, bars):    bar.set_facecolor( cm.jet(r/10.))    bar.set_alpha(0.5)ax.set_xticklabels([])ax.set_yticklabels([])savefig('figure/polar_ex.png', dpi=48)show()

六.三维绘图

#!/usr/bin/env python#encoding: utf-8from pylab import *from mpl_toolkits.mplot3d import Axes3Dfig = figure()ax = Axes3D(fig)X = np.arange(-4, 4, 0.25)Y = np.arange(-4, 4, 0.25)X, Y = np.meshgrid(X, Y)R = np.sqrt(X**2 + Y**2)Z = np.sin(R)ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.hot)ax.contourf(X, Y, Z, zdir='z', offset=-2, cmap=cm.hot)ax.set_zlim(-2, 2)savefig('figure/plot3d_ex.png', dpi=48)show()

七.数学公式

#!/usr/bin/env python#encoding: utf-8from pylab import *eqs = []eqs.append(r"$W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2}\int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{ U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_{\rho_1\sigma_2} }{U^{0\beta}_{\rho_1 \sigma_2}}\right]$")eqs.append(r"$\frac{d\rho}{d t} + \rho \vec{v}\cdot\nabla\vec{v} = -\nabla p + \mu\nabla^2 \vec{v} + \rho \vec{g}$")eqs.append(r"$\int_{-\infty}^\infty e^{-x^2}}dx=\sqrt{\pi}$")eqs.append(r"$E = mc^2 = \sqrt{{m_0}^2c^4 + p^2c^2}$")eqs.append((r"$F_G = G\frac{m_1m_2}{r^2}$"))axes([0.025, 0.025, 0.95, 0.95])for i in range(24):    index = np.random.randint(0, len(eqs))    eq = eqs[index]    size = np.random.uniform(12, 32)    x, y = np.random.uniform(0, 1, 2)    alpha = np.random.uniform(0.25, 0.75)    text(x, y, eq, ha='center', va='center', color='#11557c', alpha=alpha, transform=gca().transAxes, fontsize=size,            clip_on=True)xticks([])yticks([])savefig('figure/text_ex.png', dpi=48)show()

参考文献

[1].http://reverland.org/python/2012/09/07/matplotlib-tutorial/