示例4:使用axis()函数设置范围 importmatplotlib.pyplotaspltimportnumpyasnp x=np.linspace(0,10,100)y=x**2plt.plot(x,y,label='x^2')plt.axis([0,8,0,50])plt.title('Setting both axes limits with axis() - how2matplotlib.com')plt.legend()plt.show() Python Copy Output: 在这个示例中,p...
x=np.linspace(0,20,100)y=x**2plt.figure(figsize=(10,6))plt.plot(x,y,label='x^2')# 设置x轴范围和刻度plt.xlim(0,20)plt.xticks(np.arange(0,21,4))# 设置y轴范围和刻度plt.ylim(0,400)plt.yticks(np.arange(0,401,100))plt.title('Adjusting axis limits and ticks - how2matplotli...
# importing mplot3d toolkits, numpy and matplotlibfrommpl_toolkitsimportmplot3dimportnumpyasnpimportmatplotlib.pyplotasplt fig=plt.figure()# syntax for 3-D projectionax=plt.axes(projection='3d')# defining all 3 axisz=np.linspace(0,1,100)x=z*np.sin(25*z)y=z*np.cos(25*z)# plottingax...
from mpl_toolkitsimportmplot3dimportnumpyasnpimportmatplotlib.pyplotasplt #functionforz axis deff(x,y):returnnp.sin(np.sqrt(x**2+y**2))# x and y axis x=np.linspace(-1,5,10)y=np.linspace(-1,5,10)X,Y=np.meshgrid(x,y)Z=f(X,Y)fig=plt.figure()ax=plt.axes(projection='3d')...
Changed in version 1.0.0: Prior to Matplotlib 1.0.0, Axes3D needed to be directly instantiated with from mpl_toolkits.mplot3d import Axes3D; ax = Axes3D(fig). Changed in version 3.2.0: Prior to Matplotlib 3.2.0, it was necessary to explicitly import the mpl_toolkits.mplot3d module to...
也可以不创建Figure对象而直接调用接下来的plot()进行绘图,这时matplotlib会自动创建一个Figure对象。 figsize参数指定Figure对象的宽度和高 度,单位为英寸。 此外还可以用dpi参数指定Figure对象的分辨率,即每英寸所表示的像素数, 这里使用默认值80。 因此本例中所创建的Figure对象的宽度为8*80 = 640个像素 plt.figure...
plot(x, y, 'r--') subplot(1,2,2) plot(y, x, 'g*-'); pylab这种MATLAB格式的API有一个优点,对于MATLAB熟悉的用户能够非常容易上手,而且对于绘制简单图像而言不需要花费很多精力去学习。 然而,对于并不是特别简单的图像,并不推荐使用MATLAB类似的API,学习使用matplotlib面向对象的绘图API是一种更好更强大...
ax.set_zlabel('Z axis') plt.show() 3D拼图 import matplotlib.pyplot as plt from mpl_toolkits.mplot3d.axes3d import Axes3D, get_test_data from matplotlib import cm import numpy as np # set up a figure twice as wide as it is tall fig = plt.figure(figsize=plt.figaspect(0.5)) # ==...
plt.plot(X, S) plt.show() 4.2.2 示例的默认设置 Documentation Customizing matplotlib importnumpy as npimportmatplotlib.pyplot as plt#Create a figure of size 8x6 inches, 80 dots per inchplt.figure(figsize=(8, 6), dpi=80)#Create a new subplot from a grid of 1x1plt.subplot(1, 1, 1)...
only works (e.g. to draw round spheres) if it is accompanied by setting the 3 axis limits to be the same. If the axis limits are different then the drawing is distorted with or without use of set_aspect; this is the “rectangular coordinates problem” mentioned previously. Path forward?