You can plot multiple lines from the data provided by an array in python using matplotlib. You can do it by specifying different columns of the array as the x and y-axis parameters in the matplotlib.pyplot.plot() function. You can select columns by slicing of the array. Let’s first pr...
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...
import matplotlib.pyplot as plt import numpy as np x = np.arange(0, 2*np.pi, 0.02) y = np.sin(x) y1 = np.sin(2*x) y2 = np.sin(3*x) ym1 = np.ma.masked_where(y1 > 0.5, y1) ym2 = np.ma.masked_where(y2 < -0.5, y2) lines = plt.plot(x, y, x, ...
3.方法解释 这里我利用的是matplotlib.pyplot.plot的工具来绘制折线图,这里先给出一个段代码和结果图: 1.代码 # -*- coding: UTF-8 -*- import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt #这里导入你自己的数据 #... #... #x_axix,train_pn_dis这些...
importmatplotlib.pyplotasplthelp(plt.plot) 以下是对帮助文档重要部分的翻译: plot函数的一般的调用形式: #单条线:plot([x],y,[fmt],data=None,**kwargs)#多条线一起画plot([x],y,[fmt],[x2],y2,[fmt2],...,**kwargs) 可选参数[fmt] 是一个字符串来定义图的基本属性如:颜色(color),点型...
python中matplotlib.pyplot.plot作图各种参数 importmatplotlib.pyplot as plt x= [1,2,3,4] y= [1,2,3,4] y2= [2,4,6,8]#maker/makersize/markerfacecolor/markeredgecolor/color(指的是linecolor)/linestyle/linewidth/markeredgewidth//plot函数有很多的参数可以选择//主要有线的类型linestyle//线的宽度...
matplotlib.pyplot.plot(*args,**kwargs)? Plot lines and/or markers to theAxes.argsis a variable length argument, allowing for multiplex,ypairs with an optional format string. For example, each of the following is legal: plot(x, y) # plot x and y using default line style and color ...
matplotlib.pyplot.plot(x, y, color=, linestyle=, linewidth=) color=: 线的颜色 linestyle=: 线的样式;"-","--","-."和":" linewidth=: 线的宽度 importnumpy as npimportmatplotlib.pyplot as plt aa=np.linspace(0,10,100)bb=np.sin(aa)plt.figure(figsize=(8,6))plt.plot(aa,bb,color='...
在上面的代码中,我们首先导入了matplotlib.pyplot和numpy库。然后,我们创建了一组x和y数据,其中x是0到10之间的等间距数字,y是每个x对应的正弦值。接下来,我们使用plt.plot()函数绘制了连线图,并通过plt.title(), plt.xlabel(),和 plt.ylabel()函数添加了标题和坐标轴标签。最后,我们使用plt.show()函数显示了...
import numpy as np#导八numpyfinancial模块 import numpy_financial as npf import matplotlib.pyplot as...