https://stackoverflow.com/questions/20643291
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Looking closely at the gg code - it looks like I had two problems. The first is the denominator should have been n+1, rather than n. The second problem is that I needed a hue-chroma-luma conversion tool; rather than the hue-luma-saturation approach I had been taking. Unfortunately, I was not aware of a hcl_to_rgb tool in python; so one was written.
My solution (below) addresses these two problems. To my eye, I think it replicates ggplot2's colours.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import math
import collections
def hcl_to_rgb(hue=0, chroma=0, luma=0) :
# Notes:
# coded from http://en.wikipedia.org/wiki/HSL_and_HSV#From_luma.2Fchroma.2Fhue
# with insights from gem.c in MagickCore 6.7.8
# http://www.imagemagick.org/api/MagickCore/gem_8c_source.html
# Assume:
# h, c, l all in range 0 .. 1 (cylindrical coordinates)
# Returns a tuple:
# r, g, b all in the range 0 .. 1 (cubic cartesian coordinates)
# sanity checks
hue = math.modf(float(hue))[0]
if hue < 0 or hue >= 1 :
raise ValueError('hue is a value greater than or equal to 0 and less than 1')
chroma = float(chroma)
if chroma < 0 or chroma > 1 :
raise ValueError('chroma is a value between 0 and 1')
luma = float(luma)
if luma < 0 or luma > 1 :
raise ValueError('luma is a value between 0 and 1')
# do the conversion
_h = hue * 6.0
x = chroma * ( 1 - abs((_h % 2) - 1) )
c = chroma
if 0 <= _h and _h < 1 :
r, g, b = (c, x, 0.0)
elif 1 <= _h and _h < 2 :
r, g, b = (x, c, 0.0)
elif 2 <= _h and _h < 3 :
r, g, b = (0.0, c, x)
elif 3 <= _h and _h < 4 :
r, g, b = (0.0, x, c)
elif 4 <= _h and _h < 5 :
r, g, b = (x, 0.0, c)
elif 5 <= _h and _h <= 6 :
r, g, b = (c, 0.0, x)
else :
r, g, b = (0.0, 0.0, 0.0)
m = luma - (0.298839*r + 0.586811*g + 0.114350*b)
z = 1.0
if m < 0.0 :
z = luma/(luma-m)
m = 0.0
elif m + c > 1.0 :
z = (1.0-luma)/(m+c-luma)
m = 1.0 - z * c
(r, g, b) = (z*r+m, z*g+m, z*b+m)
# clipping ...
(r, g, b) = (min(r, 1.0), min(g, 1.0), min(b, 1.0))
(r, g, b) = (max(r, 0.0), max(g, 0.0), max(b, 0.0))
return (r, g, b)
def ggColorSlice(n=12, hue=(0.004,1.00399), chroma=0.8, luma=0.6, skipHue=True) :
# Assume:
# n: integer >= 1
# hue[from, to]: all floats - red = 0; green = 0.33333 (or -0.66667) ; blue = 0.66667 (or -0.33333)
# chroma[from, to]: floats all in range 0 .. 1
# luma[from, to]: floats all in range 0 .. 1
# Returns a list of #rgb colour strings:
# convert stand alone values to ranges
if not isinstance(hue, collections.Iterable):
hue = (hue, hue)
if not isinstance(chroma, collections.Iterable):
chroma = (chroma, chroma)
if not isinstance(luma, collections.Iterable):
luma = (luma, luma)
# convert ints to floats
hue = [float(hue[y]) for y in (0, 1)]
chroma = [float(chroma[y]) for y in (0, 1)]
luma = [float(luma[y]) for y in (0, 1)]
# some sanity checks
n = int(n)
if n < 1 or n > 360 :
raise ValueError('n is a value between 1 and 360')
if any([chroma[y] < 0.0 or chroma[y] > 1.0 for y in (0, 1)]) :
raise ValueError('chroma is a value between 0 and 1')
if any([luma[y] < 0.0 or luma[y] > 1.0 for y in (0, 1)]) :
raise ValueError('luma is a value between 0 and 1')
# generate a list of hex colour strings
x = n + 1 if n % 2 else n
if n > 1 :
lDiff = (luma[1] - luma[0]) / float(n - 1.0)
cDiff = (chroma[1] - chroma[0]) / float(n - 1.0)
if skipHue :
hDiff = (hue[1] - hue[0]) / float(x)
else :
hDiff = (hue[1] - hue[0]) / float(x - 1.0)
else:
hDiff = 0.0
lDiff = 0.0
cDiff = 0.0
listOfColours = []
for i in range(n) :
c = chroma[0] + i * cDiff
l = luma[0] + i * lDiff
h = math.modf(hue[0] + i * hDiff)[0]
h = h + 1 if h < 0.0 else h
(h, c, l) = (min(h, 0.99999999999), min(c, 1.0), min(l, 1.0))
(h, c, l) = (max(h, 0.0), max(c, 0.0), max(l, 0.0))
(r, g, b) = hcl_to_rgb(h, c, l)
listOfColours.append( '#%02x%02x%02x' % (int(r*255), int(g*255), int(b*255)) )
return listOfColours
for i in range(1, 20) :
# made up data
x = np.array(range(20))
d = {}
for j in range(1, i+1) :
y = x * (1.0 + j/10.0) + j/10.0
d['y'+'%03.0d' % j] = pd.Series(data=y , index=x)
df = pd.DataFrame(d)
# plot example
plt.figure(num=1, figsize=(10,5), dpi=100) # set default image size
colours = ggColorSlice(n=i)
if len(colours) == 1:
colours = colours[0] # kludge
df.plot(linewidth=4.0, color=colours)
fig = plt.gcf()
f = 'test-'+str(i)+'.png'
print f
plt.title(f)
fig.savefig(f)
plt.close()
