matplotlib - fill_between 没有填写正确的部分

Question

我为可见光范围创建了具有光谱颜色的普朗克曲线。

问题：我想在曲线下创建一个阴影区域。但我未能为曲线下的正确区域着色。非常感谢。

我试过了：

1. plt.fill_between(wavelengths,0,spectrum, color='w')，但这不起作用。2.我也试过 plt.fill_between(wavelengths,1e13-spectrum, color='w') 了，还是不行

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors
    
h = 6.626e-34
c = 3.0e+8
k = 1.38e-23

def planck(wav, T):
    a = 2.0*h*c**2
    wav = wav*1e-9
    b = h*c/(wav*k*T)
    intensity = a/ ( (wav**5) * (np.exp(b) - 1.0) )
    return intensity

def wavelength_to_rgb(wavelength, gamma=0.8):

    '''taken from http://www.noah.org/wiki/Wavelength_to_RGB_in_Python
    This converts a given wavelength of light to an 
    approximate RGB color value. The wavelength must be given
    in nanometers in the range from 380 nm through 750 nm
    (789 THz through 400 THz).

    Based on code by Dan Bruton
    http://www.physics.sfasu.edu/astro/color/spectra.html
    Additionally alpha value set to 0.5 outside range'''

    wavelength = float(wavelength)
    if wavelength >= 380 and wavelength <= 750:
        A = 1.
    else:
        A=0.5
    if wavelength < 380:
        wavelength = 380.
    if wavelength >750:
        wavelength = 750.
    if wavelength >= 380 and wavelength <= 440:
        attenuation = 0.3 + 0.7 * (wavelength - 380) / (440 - 380)
        R = ((-(wavelength - 440) / (440 - 380)) * attenuation) ** gamma
        G = 0.0
        B = (1.0 * attenuation) ** gamma
    elif wavelength >= 440 and wavelength <= 490:
        R = 0.0
        G = ((wavelength - 440) / (490 - 440)) ** gamma
        B = 1.0
    elif wavelength >= 490 and wavelength <= 510:
        R = 0.0
        G = 1.0
        B = (-(wavelength - 510) / (510 - 490)) ** gamma
    elif wavelength >= 510 and wavelength <= 580:
        R = ((wavelength - 510) / (580 - 510)) ** gamma
        G = 1.0
        B = 0.0
    elif wavelength >= 580 and wavelength <= 645:
        R = 1.0
        G = (-(wavelength - 645) / (645 - 580)) ** gamma
        B = 0.0
    elif wavelength >= 645 and wavelength <= 750:
        attenuation = 0.3 + 0.7 * (750 - wavelength) / (750 - 645)
        R = (1.0 * attenuation) ** gamma
        G = 0.0
        B = 0.0
    else:
        R = 0.0
        G = 0.0
        B = 0.0
    return (R,G,B,A)

clim=(350,780)
norm = plt.Normalize(*clim)
wl = np.arange(clim[0],clim[1]+1,2)
colorlist = list(zip(norm(wl),[wavelength_to_rgb(w) for w in wl]))
spectralmap = matplotlib.colors.LinearSegmentedColormap.from_list("spectrum", colorlist)
    
fig, axs = plt.subplots(1, 1, figsize=(8,4), tight_layout=True)
    
wavelengths = np.linspace(100, 4000, 1000)
spectrum = planck(wavelengths, 5778)
plt.plot(wavelengths, spectrum, color='darkred')
    
y = np.linspace(0, 3e13, 10)
X,Y = np.meshgrid(wavelengths, y)
    
extent=(np.min(wavelengths), np.max(wavelengths), np.min(y), np.max(y))
    
plt.imshow(X, clim=clim,  extent=extent, cmap=spectralmap, aspect='auto')
plt.xticks(fontsize =15)
plt.xlabel('Wavelength (nm)',fontsize =20)
    
plt.title('Shortwave radiation',fontsize =20)
plt.text(1000,2.5e13, 'Sun 5778K',fontsize =20)
plt.fill_between(wavelengths,0,spectrum, color='w')
plt.savefig('WavelengthColors.png', dpi=200)
ax = plt.gca()
#ax.axes.get_yaxis().set_visible(False)
right_side = ax.spines["right"]
right_side.set_visible(False)
left_side = ax.spines["left"]
left_side.set_visible(False)
top_side = ax.spines["top"]
top_side.set_visible(False)
plt.ylabel("Normalized spectral emittance",fontsize =20)
plt.show()

标签： matplotlib