Change colour of curve according to its y-value in matplotlib
color-mapping, matplotlib
Solution
The plot you've shown doesn't have the color set by the vertical axis of the plot (which is what I would consider the y-value). Instead, it just has 8 different plots overlain, each with a different color, without stating what the color means.
Here's an example of something that looks like your plot:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
# some fake data:
x = np.linspace(0, 2*np.pi, 1000)
fs = np.arange(1, 5.)
ys = np.sin(x*fs[:, None])
for y, f in zip(ys, fs):
plt.plot(x, y, lw=3, c=cm.hot(f/5))
If you actually want the color of one line to change with respect to its value, you have to kind of hack it, because any given `Line2D` object can only have one color, as far as I know. One way to do this is to make a scatter plot, where each dot can have any color.
x = np.linspace(0, 2*np.pi, 1000)
y = np.sin(2*x)
plt.scatter(x,y, c=cm.hot(np.abs(y)), edgecolor='none')
Notes:
- The color vector should range between `0` and `1`, so if `y.max() > 1`, then normalize by it: `c=cm.hot(y/y.max())` and make sure it's all positive.
- I used `edgecolor='none'` because by default the `scatter` markers have a black outline which makes the it look less like a uniform line.
- If your data is spaced too far, you'll have to interpolate the data if you don't want gaps between markers.
Problem
I'm trying to replicate the style of the attached figure using matplotlib's facilities. Basically, I want to change the colour of the curve according to its y-value using matplotlib.