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# Authored by Weisheng Jiang
# Book 4  |  From Basic Arithmetic to Machine Learning
# Published and copyrighted by Tsinghua University Press
# Beijing, China, 2022
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# Bk4_Ch2_10.py

from scipy.spatial import distance
from sklearn import datasets
import numpy as np

# import the iris data
iris = datasets.load_iris()

# Only use the first two features: sepal length, sepal width
X = iris.data[:, :]

# Extract 4 data points
x1_data = X[0,:]
x2_data = X[1,:]
x51_data = X[50,:]
x101_data = X[100,:]

# calculate cosine distance
x1_x2_cos_dist = distance.cosine(x1_data,x2_data)
x1_norm = np.linalg.norm(x1_data) 
x2_norm = np.linalg.norm(x2_data)
x1_dot_x2 = x1_data.T@x2_data
x1_x2_cos = x1_dot_x2/x1_norm/x2_norm


x1_x51_cos_dist = distance.cosine(x1_data,x51_data)

x1_x101_cos_dist = distance.cosine(x1_data,x101_data)