I have a list of of tuples of three colors:
v = ([0.16091847477176702, 0.4337815920028113, 0.40529993322542174)
(0.15019057645364922, 0.40486281920262385, 0.44494660434372696)
(0.14017787135673926, 0.44453863125578225, 0.4152834973874785)
(0.13083267993295664, 0.41490272250539673, 0.45426459756164661)
(0.17697859494133705, 0.36303988219222216, 0.45998152286644078)
(0.16591743275750348, 0.40284988955520828, 0.43123267768728824)
(0.16591743275750348, 0.40284988955520828, 0.43123267768728824)
(0.16591743275750348, 0.40284988955520828, 0.43123267768728824)
(0.15406618756053894, 0.37407489744412198, 0.47185891499533911)
(0.20019069588580043, 0.32419824445157241, 0.47561105966262723)
(0.20019069588580043, 0.32419824445157241, 0.47561105966262723)
(0.17349860310102702, 0.34763847852469609, 0.47886291837427691)
(0.16193202956095856, 0.39112924662304965, 0.44693872381599176)]
Each value in the tuple I untuitively interpret as a color (for example: how yellow, how red, how blue), so together each tuple gives me a colour (as the mix of the first one, second and third one). Is it possible to plot the change of the colors using matplotlib? My initial idea was to use RGB, but RGB takes integers, and the precision of those number is quite important. Does anyone has any suggestions?
floats between 0 and 1 are good values for rgb in matplotlib. here's a small example
import numpy as np
import matplotlib.pyplot as plt
v = [(0.16091847477176702, 0.4337815920028113, 0.40529993322542174),
(0.15019057645364922, 0.40486281920262385, 0.44494660434372696),
(0.14017787135673926, 0.44453863125578225, 0.4152834973874785),
(0.13083267993295664, 0.41490272250539673, 0.45426459756164661),
(0.17697859494133705, 0.36303988219222216, 0.45998152286644078),
(0.16591743275750348, 0.40284988955520828, 0.43123267768728824),
(0.16591743275750348, 0.40284988955520828, 0.43123267768728824),
(0.16591743275750348, 0.40284988955520828, 0.43123267768728824),
(0.15406618756053894, 0.37407489744412198, 0.47185891499533911),
(0.20019069588580043, 0.32419824445157241, 0.47561105966262723),
(0.20019069588580043, 0.32419824445157241, 0.47561105966262723),
(0.17349860310102702, 0.34763847852469609, 0.47886291837427691),
(0.16193202956095856, 0.39112924662304965, 0.44693872381599176)]
y = np.arange(len(v))
for i in range(len(v)):
plt.plot(y[i], 0, marker='o', ls='', c=v[i], markersize=20)
plt.show()
and the result:

it's subtle but it works
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