Pythonmatplotlib_matplotlib中文手册

from pylab import *  X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) 

python exercise_1.py

from pylab import *  X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X)  plot(X,C) plot(X,S)  show() 

# 导入 matplotlib 的所有内容（nympy 可以用 np 这个名字来使用） from pylab import *  # 创建一个 8 * 6 点（point）的图，并设置分辨率为 80 figure(figsize=(8,6), dpi=80)  # 创建一个新的 1 * 1 的子图，接下来的图样绘制在其中的第 1 块（也是唯一的一块） subplot(1,1,1)  X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X)  # 绘制余弦曲线，使用蓝色的、连续的、宽度为 1 （像素）的线条 plot(X, C, color="blue", linewidth=1.0, linestyle="-")  # 绘制正弦曲线，使用绿色的、连续的、宽度为 1 （像素）的线条 plot(X, S, color="green", linewidth=1.0, linestyle="-")  # 设置横轴的上下限 xlim(-4.0,4.0)  # 设置横轴记号 xticks(np.linspace(-4,4,9,endpoint=True))  # 设置纵轴的上下限 ylim(-1.0,1.0)  # 设置纵轴记号 yticks(np.linspace(-1,1,5,endpoint=True))  # 以分辨率 72 来保存图片 # savefig("exercice_2.png",dpi=72)  # 在屏幕上显示 show() 

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figure(figsize=(10,6), dpi=80) plot(X, C, color="blue", linewidth=2.5, linestyle="-") plot(X, S, color="red", linewidth=2.5, linestyle="-") ... 

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xlim(X.min()*1.1, X.max()*1.1) ylim(C.min()*1.1, C.max()*1.1) ... 

xmin ,xmax = X.min(), X.max()
ymin, ymax = Y.min(), Y.max()  dx = (xmax - xmin) * 0.2 dy = (ymax - ymin) * 0.2  xlim(xmin - dx, xmax + dx) ylim(ymin - dy, ymax + dy) 

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xticks( [-np.pi, -np.pi/2, 0, np.pi/2, np.pi]) yticks([-1, 0, +1]) ... 

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xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],  [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$'])  yticks([-1, 0, +1],  [r'$-1$', r'$0$', r'$+1$']) ... 

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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)) ... 

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plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine") plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sine")  legend(loc='upper left') ... 

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 t = 2*np.pi/3 plot([t,t],[0,np.cos(t)], color ='blue', linewidth=2.5, 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=2.5, 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")) ... 

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for label in ax.get_xticklabels() + ax.get_yticklabels():  label.set_fontsize(16)  label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.65 )) ... 

from pylab import *  n = 256 X = np.linspace(-np.pi,np.pi,n,endpoint=True) Y = np.sin(2*X)  plot (X, Y+1, color='blue', alpha=1.00) plot (X, Y-1, color='blue', alpha=1.00) show() 

from pylab import *  n = 1024 X = np.random.normal(0,1,n) Y = np.random.normal(0,1,n)  scatter(X,Y) show() 

from pylab import *  n = 12 X = np.arange(n) Y1 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n) Y2 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n)  bar(X, +Y1, facecolor='#9999ff', edgecolor='white') bar(X, -Y2, facecolor='#ff9999', edgecolor='white')  for x,y in zip(X,Y1):  text(x+0.4, y+0.05, '%.2f' % y, ha='center', va= 'bottom')  ylim(-1.25,+1.25) show() 

from pylab import *  def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)  n = 256 x = np.linspace(-3,3,n) y = np.linspace(-3,3,n) X,Y = np.meshgrid(x,y)  contourf(X, Y, f(X,Y), 8, alpha=.75, cmap='jet') C = contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5) show() 

from pylab import *  def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)  n = 10 x = np.linspace(-3,3,4*n) y = np.linspace(-3,3,3*n) X,Y = np.meshgrid(x,y) imshow(f(X,Y)), show() 

from pylab import *  n = 20 Z = np.random.uniform(0,1,n) pie(Z), show() 

from pylab import *  n = 8 X,Y = np.mgrid[0:n,0:n] quiver(X,Y), show() 

from pylab import *  axes = gca() axes.set_xlim(0,4) axes.set_ylim(0,3) axes.set_xticklabels([]) axes.set_yticklabels([])  show() 

from pylab import *  subplot(2,2,1) subplot(2,2,3) subplot(2,2,4)  show() 

from pylab import *  axes([0,0,1,1])  N = 20 theta = 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)  show() 

from pylab import * from mpl_toolkits.mplot3d import Axes3D  fig = 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='hot')  show() 

>>> from pylab import * >>> help(plot) Help on function plot in module matplotlib.pyplot:  plot(*args, **kwargs)  Plot lines and/or markers to the  :class:`~matplotlib.axes.Axes`. *args* is a variable length  argument, allowing for multiple *x*, *y* pairs with an  optional format string. For example, each of the following is  legal::   plot(x, y) # plot x and y using default line style and color  plot(x, y, 'bo') # plot x and y using blue circle markers  plot(y) # plot y using x as index array 0..N-1  plot(y, 'r+') # ditto, but with red plusses   If *x* and/or *y* is 2-dimensional, then the corresponding columns  will be plotted.  ...