#! usr/bin/env python
# coding:utf-8

"""
__author__ = "LCG22"
__date__ = "2016-12-5"
"""

import numpy as np
import matplotlib.pyplot as plt

from sklearn import svm, datasets

iris = datasets.load_iris()
X = iris.data[:, :2]

y = iris.target

h = 0.02

C = 1.0
svc = svm.SVC(kernel="linear", C=C).fit(X, y)
rbf_svc = svm.SVC(kernel="rbf", gamma=0.7, C=C).fit(X, y)
poly_svc = svm.SVC(kernel="poly", degree=3, C=C).fit(X, y)
lin_svc = svm.LinearSVC(C=C).fit(X, y)

X_min, X_max = X[:, 0].min() - 1, X[:, 0].max() + 1
y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1
xx, yy = np.meshgrid(np.arange(X_min, X_max, h),
                     np.arange(y_min, y_max, h))

titles = ['SVC with linear kernel',
          'LinearSVC(linear kernel)',
          'SVC with RBF kernel',
          'SVC with polynomial(degree 3) kernel']

for i, clf in enumerate((svc, lin_svc, rbf_svc, poly_svc)):
    plt.subplot(2, 2, i+1)
    plt.subplots_adjust(wspace=0.4, hspace=0.4)

    test_x = np.c_[xx.ravel(), yy.ravel()]
    Z = clf.predict(test_x)

    Z = Z.reshape(xx.shape)
    plt.contourf(xx, yy, Z, cmap=plt.cm.coolwarm, alpha=0.8)

    plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.coolwarm)
    plt.xlabel("Sepal length")
    plt.ylabel("Sepal width")
    plt.xlim(xx.min(), xx.max())
    plt.ylim(yy.min(), yy.max())
    plt.xticks(())
    plt.yticks(())
    plt.title(titles[i])

plt.show()