#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 20 09:50:53 2021

@author: doug
"""


import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
import scipy.io

mat_contents = scipy.io.loadmat('HWMar26data.mat')
A = mat_contents['A']

# We don't need the other matrices yet.

kmeans = KMeans(n_clusters=3, random_state=0)
idx = kmeans.fit_predict(A)
kmeans.cluster_centers_.shape

idx1 = [i for (i, val) in enumerate(idx) if val == 0]
idx2 = [i for (i, val) in enumerate(idx) if val == 1]
idx3 = [i for (i, val) in enumerate(idx) if val == 2]

plt.scatter(A[idx1,0],A[idx1,1],marker='^')
plt.scatter(A[idx2,0],A[idx2,1],marker='o')
plt.scatter(A[idx3,0],A[idx3,1],marker='*')