How to identify linearity in Python programming

""" Author: Victoria Created on: 2017.9.15 11:45 """ import pandas as pd import numpy as np import matplotlib.pyplot as plt def LDA(X0, X1): """ Get the optimal params of LDA model given training data. Input: X0: np.array with shape [N1, d] X1: np.array with shape [N2, d] Return: omega: np.array with shape [1, d]. Optimal params of LDA. """ #shape [1, d] mean0 = np.mean(X0, axis=0, keepdims=True) mean1 = np.mean(X1, axis=0, keepdims=True) Sw = (X0-mean0).T.dot(X0-mean0) + (X1-mean1).T.dot(X1-mean1) omega = np.linalg.inv(Sw).dot((mean0-mean1).T) return omega if __name__=="__main__": #read data from xls work_book = pd.read_csv("../data/watermelon_3a.csv", header=None) positive_data = work_book.values[work_book.values[:, -1] == 1.0, :] negative_data = work_book.values[work_book.values[:, -1] == 0.0, :] print (positive_data) #LDA omega = LDA(negative_data[:, 1:-1], positive_data[:, 1:-1]) #plot plt.plot(positive_data[:, 1], positive_data[:, 2], "bo") plt.plot(negative_data[:, 1], negative_data[:, 2], "r+") lda_left = 0 lda_right = -(omega[0]*0.9) / omega[1] plt.plot([0, 0.9], [lda_left, lda_right], 'g-') plt.xlabel('density') plt.ylabel('sugar rate') plt.title("LDA") plt.show()