5. 使用set_size_inches()方法 对于已经创建的Figure对象,你可以使用set_size_inches()方法来调整其大小。 importmatplotlib.pyplotasplt fig,ax=plt.subplots()ax.plot([1,2,3,4],[1,4,2,3])fig.set_size_inches(10,6)plt.title('Size changed using set_size_inches() - how2matplotlib.com')plt....
importmatplotlib.pyplotaspltimportnumpyasnp# 全局设置图形尺寸plt.rcParams['figure.figsize']=[10,8]# 创建图形(将使用默认尺寸)plt.figure()x=np.linspace(0,10,100)y=np.cos(x)plt.plot(x,y)plt.title('Global figure size setting - how2matplotlib.com')plt.xlabel('X-axis')plt.ylabel('Y-axi...
It's a shortcut string notation described in the *Notes* section below. >>> 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(...
plt.plot(x,y1,color='red',linewidth=1.0,linestyle='--',label='linear line') 1. 2. 添加如下代码 plt.legend(loc='upper right') 1. 下图中的右上角显示了每个图的名称 如果想修改label,除了在plot中修改以外,可以先将图像用变量存储起来 l2, = plt.plot(x,y2,label='square line') l1, = p...
dpi (default: 100.0): 代表每一英寸的打印点个数,即 分辨率。 The resolution of the figure in dots-per-inch. 字体大小 fontsize 是和 point 对应。参见If float, the fontsize in points. 线条粗细也是与 point 对应。参见Set the line width in points. ...
# 导入库import numpy as npimport matplotlib.pyplot as plt# 调整matplotlib参数plt.rcParams.update(plt.rcParamsDefault)plt.rcParams['text.usetex'] = Trueplt.rcParams['font.size'] = 18plt.rcParams['font.family'] = "serif"# 创建模拟数据r = 15theta = 5rw = 12gamma = 0.1err = np.arange(...
import matplotlib.pyplot as plt import numpy as np plt.rcParams.update({ 'font.family':'STSong', 'mathtext.fontset':'stix', 'figure.dpi':150 }) x = np.linspace(-2 * np.pi, 2 * np.pi, 100) y = np.sinc(x) fig, ax = plt.subplots(1, 2, figsize=(10, 4)) ax[0].plot(...
x = np.linspace(0, 2, 100)fig, ax = plt.subplots() # Create a figure and an axes.l1 = ax.plot(x, x, label="linear")l2 = ax.plot(x, x ** 2, label="quadratic")l3 = ax.plot(x, x ** 3, label="cubic")ax.set_title("Simple Plot")plt.show()这很简单，只需在axes...
plt.annotate(r"$\delta$",xy=(delta+0.2,-0.2),color="r",size=15) plt.plot(x,y) 设置3:增加X轴与Y轴间的间隔,向右移动X轴标注一点点即可 显示效果对比: 设置前: 设置后: 两张的图像的差别很明显,代码如下: # -*- coding: utf-8-*- ...
plt.figure(figsize=(5, 3))x = np.linspace(0, 10)y = np.sin(x)plt.plot(x, y)# ticks：刻度值，刻度大小# labels：显示刻度标签# ha：水平对齐方式（left,right,center）plt.xticks(ticks=np.arange(0, 11, 1), fontsize=20, color="red")plt.yticks(ticks=[-1, 0, 1], labels=["min...