Question

I have a lot of graphs I want to plot in one plot. I’ve just started with matplotlib and can’t find a good way to generate a lot of distinguishable colors 🙁 Maybe cycling over HSV with SV at maximum?

I’m thinking of something like

args=[]
for i,(x,y) in enumerate(data):
    args.extend([x,y,hsv(i)])
plot(*args)

Any suggestions? 🙂

Answer 1

I think you have the right idea, except that the colors will be more distinguishable if you pass the colormap hsv numbers which are spread out over the range (0,1):

hsv = plt.get_cmap('hsv')
hsv(float(i)/(len(data)-1))

or, using NumPy:

colors = hsv(np.linspace(0, 1.0, len(kinds)))

For example:

import datetime as DT
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import scipy.interpolate as interpolate

dates = [DT.date(year, 9, 1) for year in range(2003, 2009)]
t = list(map(mdates.date2num, dates))
jec = (100, 70, 125, 150, 300, 250)
plt.plot(dates, jec, 'k.', markersize = 20)
new_t = np.linspace(min(t), max(t), 80)
new_dates = map(mdates.num2date, new_t)
kinds = ('cubic', 'quadratic', 'slinear', 'nearest', 'linear', 'zero', 4, 5)
cmap = plt.get_cmap('jet')
colors = cmap(np.linspace(0, 1.0, len(kinds)))
for kind, color in zip(kinds, colors):
    new_jec = interpolate.interp1d(t, jec, kind=kind)(new_t)
    plt.plot(new_t, new_jec, '-', label=str(kind), color=color)
plt.legend(loc = 'best')
plt.show()