# -*- coding: utf-8 -*-
"""
Created on Wed Nov 22 08:17:53 2017

@author: Miguel Almeida
"""
from sklearn.datasets import load_iris
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import f_classif
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
import numpy as np
from sklearn.cluster import KMeans
from mpl_toolkits.mplot3d import axes3d
from skimage.io import imsave,imread

def plot_iris(X,y,file_name):
    plt.figure(figsize=(7,7))
    plt.plot(X[y==0,0], X[y==0,1],'o', markersize=7, color='blue', alpha=0.5)
    plt.plot(X[y==1,0], X[y==1,1],'o', markersize=7, color='red', alpha=0.5)
    plt.plot(X[y==2,0], X[y==2,1],'o', markersize=7, color='green', alpha=0.5)
    plt.gca().set_aspect('equal', adjustable='box')
    plt.savefig(file_name,dpi=200,bbox_inches='tight')

iris = load_iris()
X = iris.data
y = iris.target

f, prob= f_classif(X,y)

# Create an SelectKBest object to select features with two best ANOVA F-Values
fvalue_selector = SelectKBest(f_classif, k=2)

# Apply the SelectKBest object to the features and target
#Selecionado as que tem menos probabilidade e maior F1-score (probabilidade de independencia dos dados ser maior)
X_kbest = fvalue_selector.fit_transform(X, y)


pca = PCA(n_components=2)
pca.fit(X)
print(pca.components_)
t_data = pca.transform(X)

####Terceiro Ex.

img = imread("vegetables.png")
w,h,d = img.shape
cols = np.reshape(img/255.0, (w * h, d))

nColors = 16

kmeans = KMeans(n_clusters= nColors, random_state=0)
kmeans.fit(cols)
labels = kmeans.predict(cols)
centroids = kmeans.cluster_centers_

c_cols = np.zeros(cols.shape)
for ix in range(cols.shape[0]):
    c_cols[ix,:] = centroids[labels[ix]]

final_img = np.reshape(c_cols,(w,h,3))
imsave('image.png',final_img)

#Gerar figura 3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(cols[:,0], cols[:,1], cols[:,2], c=cols,s=10)
ax.set_xlabel('Red')
ax.set_ylabel('Green')
ax.set_zlabel('Blue')
ax.set_xlim3d(0,1)
ax.set_ylim3d(0,1)
ax.set_zlim3d(0,1)
plt.savefig('T7-veg_rgb.png',dpi=200,bbox_inches='tight')






    
plot_iris(X_kbest,y,"terceiro.png")