How to apply normalized colorbar to a figure with iterative line plots

Question

I have normalized the color bar according to my data

import matplotlib as mpl
fig,ax=plt.subplots(figsize=(6,1))
fig.subplots_adjust(bottom=0.5)
cmap=mpl.cm.jet
norm=mpl.colors.Normalize(vmin=np.min(epi_dist),vmax=np.max(epi_dist))
cb1=mpl.colorbar.ColorbarBase(ax,cmap=cmap,norm=norm,orientation='horizontal')
fig.show()

Now I need to plot multiple line plots through a for loop in a single figure with a variable representing the color according to this newly normalized colormap eg:

plt.plot(x,y,color=200,cmap='cmap')

here color represents the variable from data which represent the color according to the normalized cmap

Final figure will be like this with normalized colorbar if iterate the above code for multiple line plots

Looking forward to your valuable suggestions

Answer 1

You can use color=cmap(norm(value)) to extract the desired color from the colormap corresponding to a value on the scale shown in the colorbar.

import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np

epi_dist = np.linspace(0, 420, 20)

fig, (ax, cbar_ax) = plt.subplots(nrows=2, figsize=(10, 6), gridspec_kw={'height_ratios': [5, 1]})
cmap = plt.cm.jet
norm = plt.Normalize(vmin=np.min(epi_dist), vmax=np.max(epi_dist))
cb1 = mpl.colorbar.ColorbarBase(cbar_ax, cmap=cmap, norm=norm, orientation='horizontal')

x = np.linspace(0, 2 * np.pi, 200)
for epi in epi_dist:
    ax.plot(x, epi + 100 * np.sin(x), color=cmap(norm(epi)))

fig.show()