#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 23 17:07:40 2021

@author: doug
"""

import OLS   # This is the Python module we wrote for RBFs
import numpy as np
from sklearn.datasets import load_wine
from sklearn.model_selection import train_test_split
from sklearn.metrics import confusion_matrix
from sklearn.preprocessing import StandardScaler

Z=load_wine()
X=Z.data
t=Z.target
temp=np.identity(3)
T=temp[:,t]
scaler=StandardScaler()
Xs=scaler.fit_transform(X)


X_train, X_test, y_train, y_test = train_test_split(Xs, T.T, test_size=0.3, random_state=42)

NetParams=OLS.rbfOLS(X_train.T,y_train.T,0.1,70)
Ztest=OLS.rbfPredict(NetParams,X_test);

PredOut=np.argmax(Ztest,axis=0)
TrueOut=np.argmax(y_test.T,axis=0)
C_out=confusion_matrix(PredOut,TrueOut)
print(C_out)