pythonnumpymatplotlibscikit-learnscatter
How to color clusters in scatter plot using an array?
I'm using sklearn noisy_circles function with 1500 points as they did in the link, to create 2 circles.
I have an array of points references, where every value is supposed to be a different cluster color:
nbrs_array = [ 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 973, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
973, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 984, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 992, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 972, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 992, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 984, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 972, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88, 88,
88, 88, 88, 88, 88]
There are 5 unique values in the array, hence there should be 5 different colors. But when I'm plotting it using:
plt.figure(figsize=(10,10))
plt.scatter(x,y, c=nbrs_array)
plt.show()
The output is 
Solution
Something like this should do the job:
import numpy as np
from matplotlib import cm
from matplotlib import pyplot as plt
from matplotlib.colors import Normalize, to_hex
from sklearn import datasets
def get_colors(arr, cmap='viridis'):
cmap = cm.get_cmap(cmap)
n = len(np.unique(arr))
colornorm = Normalize(vmin=1, vmax=n)
hex_map = dict()
for i, cl in enumerate(np.unique(arr)):
hex_map[cl] = to_hex(cmap(colornorm(i + 1)))
colors = list(map(lambda x: hex_map[x], arr))
return colors
n_samples = 1500
data, _ = datasets.make_circles(n_samples=n_samples, factor=.5, noise=.05)
x, y = data[:, 0], data[:, 1]
nbrs_array = [...]
plt.figure(figsize=(10, 10))
plt.scatter(x, y, c=get_colors(nbrs_array))
plt.show()