import matplotlib.pyplot as plt import numpy as np #设置图的大小为(12,8),分辨率为100 plt.figure(figsize=(12,8),dpi=100) #画图,指定颜色,线宽,类型 x=np.linspace(-2*np.pi, 2*np.pi,1000) c,s=np.cos(x),np.sin(x) plt.plot(x,c,"b-", x,s,"r--",linewidth=3) #设置显示范...
1, 1000) x3 = np.random.normal(3, 2, 1000) kwargs = dict(histtype='stepfilled', alpha=...
import numpy as np import matplotlib.pyplot as plt x=np.linspace(-1,1,50) y1=x**2 y2=2*x+1 plt.figure() plt.plot(x,y1) plt.figure() plt.plot(x,y2) plt.show() 同时显示多张图时,在每一句 plt.plot(x,y) 前边添加 plt.figure() ,就可以画出多张图。 二、利用figure函数指定图...
# 使用lambda创建wave函数wave = lambda amp, angle, phase: amp * np.sin(angle + phase)# 设置参数值theta = np.linspace(0., 2 * np.pi, 100)amp = np.linspace(0, .5, 5)phase = np.linspace(0, .5, 5)# 创建主容器及其标题plt.figure()plt.title(r'Wave Function $y = \gamma \sin...
an 8x6inchesfigure with 100 DPI results in an 800x600 pixels image,这就是默认值 In [4]: plt.savefig('plot123_2.png', dpi=200) 这样图的分辨率,变为1600×1200 Decorate Graphs with Plot Styles Markers and line styles 上面画的线都是一样的,其实我们可以画出各种不同的线 ...
Simple Plot Multiple subplots in one figure Multiple axes (i.e. subplots) are created with thesubplot()function: ../../_images/sphx_glr_subplot_0011.png Subplot Images Matplotlib can display images (assuming equally spaced horizontal dimensions) using theimshow()function. ...
1.基础用法(figure,plot,show) plt.figure:定义一个figure图像窗口,可以有很多小图片 plt.plot:绘制曲线 plt.show:显示图像 import matplotlib.pyplot as plt import numpy as np 1. 2. x = np.linspace(-3,3,50) y1 = 2*x + 1 y2 = x**2 ...
from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as pltimport numpy as npcategories = ['Category A', 'Category B', 'Category C']values1 = [5, 7, 9]values2 = [3, 6, 8]fig = plt.figure()ax = fig.add_subplot(111, projection='3d')xpos = np.arange(len(categories...
plt.plot([1, 2, 3, 4], [1, 4, 9, 16]) plt.show() 会连续展现三张图,注意与下面subplot的区别。 对于只有一张图时,也有作用,例如设置尺寸和分辨率等: #创建一个8x6大小的figure,并设置每英寸80个像素点plt.figure(figsize=(8, 6), dpi=80) ...
import fastplot Usage with Jupyter Notebook In this way, you can runfastplotalso inside a Jupyter Notebook: Note: If you want to bothshow()andsavefig(), please dosavefig()before, to prevent matplotlib from clearing the figure. See the following example. ...