# -*- coding: utf-8 -*-
"""
Created on Fri Oct 23 14:45:21 2015

@author: Camil Staps, s4498062

This is Python 2 code.
"""

import sys
sys.path.insert(0, './packages')

import numpy as np
import scipy.io as sciio
from sklearn import cluster
from clusterPlot import clusterPlot
from clusterVal import clusterVal
import matplotlib.pyplot as plt

# 4.1.1
plt.figure(figsize=(16,10))
for n in range(1,5):
    synth = sciio.loadmat('./data/synth' + str(n) + '.mat')
    X = synth['X']
    y = synth['y']
    centroid, label, inertia = cluster.k_means(X, 4)
    plt.subplot(2, 2, n)
    clusterPlot(X, label, centroid, y)
plt.show()

n = 1    
synth = sciio.loadmat('./data/synth' + str(n) + '.mat')
X = synth['X']
y = synth['y']

# 4.1.2
entropies, purities, rands, jaccards = [], [], [], []
for i in range(1, 11):
    _, label, _ = cluster.k_means(X, i)
    entropy, purity, rand, jaccard = clusterVal(y, label)
    entropies.append(entropy)
    purities.append(purity)
    rands.append(rand)
    jaccards.append(jaccard)
    
x = np.arange(1,11)
plt.figure(figsize=(8,8))
plt.subplot(2,2,1)
plt.plot(x, entropies, label='Entropy')
plt.legend()
plt.subplot(2,2,2)
plt.plot(x, purities, label='Purity')
plt.legend(loc=4)
plt.subplot(2,2,3)
plt.plot(x, rands, label='Rand')
plt.legend(loc=4)
plt.subplot(2,2,4)
plt.plot(x, jaccards, label='Jaccard')
plt.legend(loc=4)
plt.show()

# 4.1.3
faces = sciio.loadmat('./data/wildfaces.mat')
X = faces['X']
k = 10
centroid, label, inertia = cluster.k_means(X, k)

n = 10
plt.figure(figsize=(n*2,4))
for k in range(0,n):
    plt.subplot(2, n, k + 1)
    plt.imshow(np.reshape(X[k,:], (3,40,40)).T)
    plt.axis('off')
    plt.subplot(2, n, k + 1 + n)
    plt.imshow(np.reshape(centroid[label[k],:], (3,40,40)).T)
    plt.axis('off')
plt.show()
    
# 4.1.4
digits = sciio.loadmat('./data/digits.mat')
X = digits['X']
k = 10

plt.figure(figsize=(6,4))
for k in range(0,24):
    plt.subplot(4, 6, k + 1)
    plt.imshow(np.reshape(X[k], (16,16)), cmap=plt.cm.binary)
    plt.axis('off')
plt.show()

centroid, label, inertia = cluster.k_means(X, k)

plt.figure(figsize=(6,4))
for k in range(0,24):
    plt.subplot(4, 6, k + 1)
    plt.imshow(np.reshape(centroid[label[k]], (16,16)), cmap=plt.cm.binary)
    plt.axis('off')
plt.show()