x, 1.2))np.random.seed(100)upper_stock = mean_stock + np.random.randint(N) * 0.02lower_stock = mean_stock - np.random.randint(N) * 0.015plt.plot(x, mean_stock, color = 'darkorchid', label = r'$y = \gamma \sin(\theta + \phi_0)$')plt.fill_between(x, upper_stock, lower...
import matplotlib.pyplot as plt import numpy as np x = np.linspace(0, 10, 100) y1 = np.sin(x) y2 = np.cos(x) plt.fill_between(x, y1, y2, color='skyblue', alpha=0.5) plt.plot(x, y1, label='sin(x)') plt.plot(x, y2, label='cos(x)') plt.legend() plt.show() 复...
matplotlib.pyplot.fill_between(<xt>,<yr1>[,<yr2>,<color>,**kwargs]) #参数说明:color/kwargs同上 xt:指定数据点的x/θ坐标 yr1:指定第1条折线上数据点的y/r坐标 yr2:指定第2条折线上数据点的y/r坐标;默认全部为0 #实例: >>> import matplotlib.pyplot as plt >>> x=[1,2,3,4,5] >>...
plt.fill(x, y, color="blue", alpha=0.5) plt.show() ``` 四、区别与对比 1.参数设置 - fill_between()函数需要指定两个函数,而fill()函数只需指定一组坐标点。 2.绘制效果 - fill_between()函数在两个函数之间填充,fill()函数在封闭区域内填充。 3.应用场景 - fill_between()函数适用于需要根据...
fill_between()填充两个函数曲线之间的部分: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 def wave_curve(): n=256 X=np.linspace(-np.pi,np.pi,n,endpoint=True) Y=np.sin(2*X) plt.plot(X,Y+1,color='blue',alpha=0.5) ...
效果(来自ref[2]): import pylab as pltimport numpy as npX = np.linspace(0,3,200)Y1 = X**2+3Y2 = np.exp(X) +2Y3 = np.cos(X)plt.plot(X,Y1,lw=4)plt.plot(X,Y2,lw=4)plt.plot(X,Y3,lw=4)plt.fill_between(X, Y1,Y2,color='k',alpha=.5)plt.fill_between(X, Y1,Y3,...
fill_between可以通过where参数进行判断, ax.fill_between(x, y1, y2, where=y2>=y1, facecolor="darkred", aphpa=0.7) 距离如下 from matplotlibimportpyplotaspltimportnumpyasnp x=np.linspace(0,2,500)y1=np.sin(2*np.pi*x)y2=1.1*np.cos(3*np.pi*x)fig,ax=plt.subplots(2,1,sharex="all...
return ax.fill_betweenx(edges, values, bottoms, **kwargs) elif orientation == 'v': """ 开始进行绘图 """ return ax.fill_between(edges, values, bottoms, **kwargs) else: raise AssertionError("you should never be here") """
可以通过使用`fill_between`函数来实现。`fill_between`函数可以在两个曲线之间填充颜色,创建一个区域。 具体步骤如下: 1. 导入Matplotlib库中的pyplot模块...
color='#444444',linestyle='--',label='All Devs')plt.plot(ages,py_salaries,label='Python')''' # 设置水平方向上的填充阈值 overall_median = 57287 plt.fill_between(ages, py_salaries, overall_median, where=(py_salaries > overall_median), interpolate=True,) '''# fill_between: fill_...