python - 更改函数中的变量以在同一轴上创建多个绘图

Question

我目前正在尝试绘制一个函数，该函数描述不同世界模型的宇宙学中的线性扰动增长。我希望能够将所有曲线放在同一组轴上，但在设置方面遇到了困难。

我的目标是绘制该函数 D 相对于 z 的图，但有多个具有不同密度参数 ($\Omega$) 的图。

我已经管理了两个解决方案，但都不能完美工作，第一个非常低效(为每组参数添加新函数):

z = np.arange(0.0,10,0.1)

#density parameters
MOm = 1.0
MOv = 0.0

COm = 0.3
COv = 0.7

H0 = 70

def Mf(z):
    A = (5/2)*MOm*(H0**2)
    H = H0 * np.sqrt( MOm*((1+z)**3) + MOv )
    return A * ((1+z)/(H**3))

def MF(z):
    res = np.zeros_like(z)
    for i,val in enumerate(z):
        y,err = integrate.quad(Mf,val,np.inf)
        res[i] = y
    return res

def MD(z):
    return (H0 * np.sqrt( MOm*((1+z)**3) + MOv )) * MF(z)

def Cf(z):
    A = (5/2)*COm*(H0**2)
    H = H0 * np.sqrt( COm*((1+z)**3) + COv )
    return A * ((1+z)/(H**3))

def CF(z):
    res = np.zeros_like(z)
    for i,val in enumerate(z):
        y,err = integrate.quad(Cf,val,np.inf)
        res[i] = y
    return res

def CD(z):
    return (H0 * np.sqrt( COm*((1+z)**3) + COv )) * CF(z) 


plt.plot(z,MD(z),label="Matter Dominated")
plt.plot(z,CD(z),label="Current Epoch")

因此，我尝试使用 for 循环使其变得更简单，但无法弄清楚如何向循环内的每个图添加标签:

Om = (1.0,0.3)
Ov = (0.0,0.7)

for param1,param2 in zip(Om,Ov):
    def f(z):
        A = (5/2)*param1*(H0**2)
        H = H0 * np.sqrt( param1*((1+z)**3) + param2 )
        return A * ((1+z)/(H**3))

    def F(z):
        res = np.zeros_like(z)
        for i,val in enumerate(z):
            y,err = integrate.quad(f,val,np.inf)
            res[i] = y
        return res

    def D(z):
        return (H0 * np.sqrt( param1*((1+z)**3) + param2 )) * F(z)

    plt.plot(z,D(z))

有人可以帮忙解释一下有效的方法吗？或者如何使用 for 循环将标签动态添加到绘图中。任何帮助将不胜感激。

Answer 1

So I tried to make it simpler with a for loop, but have been unable to work out how to add labels to each plot inside the loop

from scipy import integrate
from matplotlib import pyplot as plt

MOm = 1.0
MOv = 0.0

COm = 0.3
COv = 0.7

z = np.arange(0.0,10,0.1)
H0 = 70
Om = (1.0,0.3)
Ov = (0.0,0.7)

fig = plt.figure(1)
for param1,param2 in zip(Om,Ov):
    def f(z):
        A = (5/2)*param1*(H0**2)
        H = H0 * np.sqrt( param1*((1+z)**3) + param2 )
        return A * ((1+z)/(H**3))

    def F(z):
        res = np.zeros_like(z)
        for i,val in enumerate(z):
            y,err = integrate.quad(f,val,np.inf)
            res[i] = y
        return res

    def D(z):
        return (H0 * np.sqrt( param1*((1+z)**3) + param2 )) * F(z)

## Now define labels as you need and labels as follows:

    plt.plot(z,D(z),label = 'Om: {}, Ov: {}'.format(param1,param2))
    plt.legend()