1 First plots with Matplotlib
简单的绘图1
简单的绘图2
简单的绘图3
2 网格 = grid
3 设置坐标轴的取值范围 = axis xlim ylim
方法1:整体设置
[xmin, xmax, ymin, ymax] ===》plt.axis([xmin, xmax, ymin, ymax])
方法2:分别设置
plt.xlim([xmin, xmax])
plt.ylim([ymin, ymax])
4 设置坐标含义标签 = label
5 设置图片的整体标题 = title
6 设置图例 = legend
方法2:
plt.plot(x, x*1.5)
plt.plot(x, x*3.0)
plt.plot(x, x/3.0)
plt.legend([‘Normal‘, ‘Fast‘, ‘Slow‘])
图例的位置参数:loc = Code
String | Code |
best | 0 |
upper right | 1 |
upper left | 2 |
lower left | 3 |
lower right | 4 |
right | 5 |
center left | 6 |
center right | 7 |
lower center | 8 |
upper center | 9 |
center | 10 |
7 一副完整的图像
8 保存图片 = savefig
import matplotlib.pyplot as plt plt.plot([1, 2, 3]) plt.savefig("plot123.png") plt.savefig(‘plot123_2.png‘, dpi=200) # import matplotlib as mpl mpl.rcParams[‘figure.figsize‘] mpl.rcParams[‘savefig.dpi‘] mpl.reParams[‘Agg‘]
9 本小结所有代码示例
import matplotlib.pyplot as plt plt.plot([1, 3, 2, 4]) plt.show() import matplotlib.pyplot as plt x = range(6) plt.plot(x, [xi**2 for xi in x]) plt.show() import matplotlib.pyplot as plt import numpy as np x = np.arange(0.0, 6.0, 0.01) plt.plot(x, [x**2 for x in x]) plt.show() import matplotlib.pyplot as plt import numpy as np x = np.arange(1, 5) plt.plot(x, x*1.5, x, x*3.0, x, x/3.0) plt.grid(True) plt.show() import matplotlib.pyplot as plt import numpy as np x = np.arange(1, 5) plt.plot(x, x*1.5, x, x*3.0, x, x/3.0) plt.axis() # 显示当前坐标轴的极限取值范围 x->(0.85, 4.15), y->(-0.25, 12.58) plt.axis([0, 5, -1, 13]) # 从新设置当前坐标轴的范围 plt.show() import matplotlib.pyplot as plt plt.plot([1, 3, 2, 4]) plt.xlabel(‘This is the X axis‘) #这个是x轴的标签 plt.ylabel(‘This is the Y axis‘) #这个是y轴的标签 plt.show() import matplotlib.pyplot as plt plt.plot([1, 3, 2, 4]) plt.title(‘Simple plot‘) # 图像的标题 plt.show() import matplotlib.pyplot as plt import numpy as np x = np.arange(1, 5) plt.plot(x, x*1.5, label="Normal") plt.plot(x, x*3.0, label="Fast") plt.plot(x, x/3.0, label="Slow") plt.legend() # 设置图例 plt.show() import matplotlib.pyplot as plt import numpy as np x = np.arange(1, 5) plt.plot(x, x*1.5, x, x*3.0, x, x/3.0) plt.grid(True) plt.title(‘Sample Growth of a Measure‘) plt.xlabel(‘Samples‘) plt.ylabel(‘Values Measured‘) plt.legend([‘Normal‘, ‘Fast‘, ‘Slow‘], loc = ‘upper left‘) plt.show() import matplotlib.pyplot as plt plt.plot([1, 2, 3]) plt.savefig("plot123.png") import matplotlib as mpl mpl.rcParams[‘figure.figsize‘] mpl.rcParams[‘savefig.dpi‘] plt.savefig(‘plot123_2.png‘, dpi=200)
知识在于点点滴滴的积累,我会在这个路上Go ahead,
有幸看到我博客的朋友们,若能学到知识,请多多关注以及讨论,让我们共同进步,扬帆起航。
后记:打油诗一首
适度锻炼,量化指标
考量天气,设定目标
科学锻炼,成就体标
高效科研,实现学标
原文地址:https://www.cnblogs.com/brightyuxl/p/9251258.html
时间: 2024-11-09 10:01:30