I want to translate the following group coloring octave function to python and use it with pyplot.
Function input:
x - Data matrix (m x n)
a - A parameter.
index - A vector of size "m" with values in range [: a]
(For example if a = 4, index can be [random.choice(range(4)) for i in range(m)]
The values in "index" indicate the number of the group the "m"th data point belongs to. The function should plot all the data points from x and color them in different colors (Number of different colors is "a").
The function in octave:
p = hsv(a); % This is a x 3 metrix
colors = p(index, :); % ****This is m x 3 metrix****
scatter(X(:,1), X(:,2), 10, colors);
I couldn't find a function like hsv in python, so I wrote it myself (I think I did..):
p = colors.hsv_to_rgb(numpy.column_stack((
numpy.linspace(0, 1, a), numpy.ones((a ,2)) )) )
But I can't figure out how to do the matrix selection p(index, :) in python (numpy). Specially because the size of "index" is bigger then "a".
Thanks in advance for your help.
So, you want to take an m x 3 of HSV values, and convert each row to RGB?
import numpy as np
import colorsys
mymatrix = np.matrix([[11,12,13],
[21,22,23],
[31,32,33]])
def to_hsv(x):
return colorsys.rgb_to_hsv(*x)
#Apply the to_hsv function to each matrix row.
print np.apply_along_axis(to_hsv, axis=1, arr=mymatrix)
This produces:
[[ 0.5 0. 13. ]
[ 0.5 0. 23. ]
[ 0.5 0. 33. ]]
Follow through on your comment:
If I understand you have a matrix p that is an a x 3 matrix, and you want to randomly select rows from the matrix over and over again, until you have a new matrix that is m x 3?
Ok. Let's say you have a matrix p defined as follows:
a = 5
p = np.random.randint(5, size=(a, 3))
Now, make a list of random integers between the range 0 -> 3 (index starts at 0 and ends to a-1), That is m in length:
m = 20
index = np.random.randint(a, size=m)
Now access the right indexes and plug them into a new matrix:
p_prime = np.matrix([p[i] for i in index])
Produces a 20 x 3 matrix.