# -*- coding: utf-8 -*-
"""
Created on Tue Mar 6 19:30:05 2018
@author: Erik
"""
import get_data as gd
import part2b_code as p2b
import part1c_code as p1c
import gradient_calculation as gc
X_test, y_test = gd.read_data_formatted('test_struct.txt')
X_train, y_train = gd.read_data_formatted('train_struct_1000.txt')
params = gd.get_params()
p2b.optimize(params, X_train, y_train, 1000, 'solution_1000_distortion')
params = p2b.get_optimal_params('solution_1000_distortion')
w = gc.w_matrix(params)
t = gc.t_matrix(params)
print("Function value: ")
print(p2b.func_to_minimize(params, X_train, y_train, 1000))
y_pred = p2b.predict(X_test, w, t)
print(p2b.accuracy(y_pred, y_test))
"""
import part2b_code as p2b
import gradient_calculation as gc
import get_data as gd
import part2b_code as p2b
X_train, y_train = gd.read_data_formatted('train_struct.txt')
X_test, y_test = gd.read_data_formatted('test_struct.txt')
params = gd.get_params()
#Run optimization, should take 3+ hours so commented out.
'''
cvals = [1, 10, 100, 1000]
for elt in cvals:
p2b.optimize(params, X_train, y_train, elt, 'solution' + str(elt))
print("done with" + str(elt))
'''
#check accuracy
cvals = [1, 10, 100, 1000]
for elt in cvals:
params = p2b.get_optimal_params('solution' + str(elt))
w = gc.w_matrix(params)
t = gc.t_matrix(params)
prediction = p2b.predict(X_test, w, t)
print("Accuracy for: " + str(elt))
print(p2b.accuracy(prediction, y_test))