本文摘译了《Matplotlib_3.3.4.pdf》 的 User‘s Guide > Tutorials > Introductory 中关于 Matplotlib 的若干基本概念,如下。 Matplotlib graphs your data on Figures, each of which can contain one or more Axes (i.e., an area where points can be specified in terms of x-y coordinates (or theta-...
from matplotlibimportticker defsetup(ax,title):"""Set up common parameters for the Axes in the example."""# only show the bottom spine ax.yaxis.set_major_locator(ticker.NullLocator())ax.spines['right'].set_color('none')ax.spines['left'].set_color('none')ax.spines['top'].set_color(...
Create publication quality plots. Make interactive figures that can zoom, pan, update. Customize visual style and layout. Export to many file formats . Embed in JupyterLab and Graphical User Interfaces. Use a rich array of third-party packages built on Matplotlib. Matplotlib安装 Python包管理器pip...
x=np.linspace(0,10,20)y1=np.sin(x)y2=np.cos(x)plt.plot(x,y1,linestyle='--',marker='o',label='sin(x)')plt.plot(x,y2,ls='--',marker='s',label='cos(x)')plt.title('Dotted lines with markers - how2matplotlib.com')plt.xlabel('x')plt.ylabel('y')plt.legend()plt.show...
() plt.show() 收藏评论 镶嵌子图¶ 评论 https://matplotlib.org/stable/gallery/subplots_axes_and_figures/zoom_inset_axes.html 评论 In [2]: def get_demo_image(): z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True) # z is a numpy array of 15x15 return z, ...
plt.grid(True)#显示网格;plt.show()#显示出figure; 函数subplots() 地 plt.subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True, subplot_kw=None, **fig_kw)#作用:创建一个已有subplots的figures;参数: *nrows*: int ,指创建的sublots的行数,默认为1. ...
plt# 创建Figure对象fig=plt.figure(figsize=(8,6))# 设置Figure边框颜色为红色fig.set_edgecolor('red')# 添加一个子图ax=fig.add_subplot(111)ax.plot([1,2,3,4],[1,4,2,3],label='Data from how2matplotlib.com')ax.set_title('Figure with Red Edge Color')ax.legend()# 显示图形plt...
state-machine 会自动和以用户无感的方式创建 Figures(图)对象 和 axes (轴域),以实现所需的绘图操作。 具体一点: plt.plot() 的第一个调用将自动创建 Figure 和 Axes 对象,以实现所需的绘图。对 plt.plot() 后续的调用会重复使用当前 Axes 对象,并每次添加一行。设置 title 标题、legend 图例等,都会使用当...
plt.show()#draw 2.draw multiple figures with customized style import matplotlib.pyplot as plt import numpy as np x=np.linspace(-3,3,50) y1=2*x+1 y2=x**2 plt.figure()#draw the first figure plt.plot(x,y1) plt.figure(num="fucking name",figsize=(8,5))#num=define the title of...
show() def multiple_figures(): """ 多图 """ x = np.linspace(-1.4, 1.4, 30) plt.figure(1) plt.subplot(211) plt.plot(x, x ** 2) plt.title("Square and Cube") plt.subplot(212) plt.plot(x, x ** 3) plt.figure(2, figsize=(10, 5)) plt.subplot(121) plt.plot(x, x *...