"""
'perceptron_demo.py'

David Pan, UAH
"""

import numpy as np
from sklearn.linear_model import Perceptron
x1 = np.array([3, 3])
x2 = np.array([1, 1])
X = np.vstack((x1, x2)) # Features are along the row
y = np.array([1,2])
clf = Perceptron()
clf.fit(X, y)
clf.coef_
clf.intercept_
clf.score(X, y)

# Classify handwritten digits
from sklearn.datasets import load_digits
digits = load_digits()
print(digits.data.shape)

% Display the images
import matplotlib.pyplot as plt
plt.gray()
plt.matshow(digits.images[9])

X, y = load_digits(return_X_y=True)
clf = Perceptron(tol=1e-3, random_state=0)
clf.fit(X, y)
clf.score(X, y)