import numpy as np
from flask import Flask, request, render_template
from sklearn.datasets import make_circles
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import matplotlib.pyplot as plt
from mlxtend.plotting import plot_decision_regions

app = Flask(__name__)

@app.route('/')
def home():
    return render_template('index.html')

@app.route('/compare_models', methods=['POST'])
def compare_models():
    # Генерация данных
    rs = 0
    X, y = make_circles(noise=0.2, factor=0.5, random_state=rs)
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=rs)

    # Персептрон
    perceptron = MLPClassifier(hidden_layer_sizes=(1,), max_iter=1000, alpha=0.01)
    perceptron.fit(X_train, y_train)
    perceptron_score = accuracy_score(y_test, perceptron.predict(X_test))

    # Многослойный персептрон с 10-ю нейронами в скрытом слое
    mlp_10 = MLPClassifier(hidden_layer_sizes=(10,), max_iter=1000, alpha=0.01)
    mlp_10.fit(X_train, y_train)
    mlp_10_score = accuracy_score(y_test, mlp_10.predict(X_test))

    # Многослойный персептрон со 100-ю нейронами в скрытом слое
    mlp_100 = MLPClassifier(hidden_layer_sizes=(100,), max_iter=1000, alpha=0.01)
    mlp_100.fit(X_train, y_train)
    mlp_100_score = accuracy_score(y_test, mlp_100.predict(X_test))

    # Создание графиков
    plt.figure(figsize=(12, 4))

    plt.subplot(131)
    plot_decision_regions(X_test, y_test, clf=perceptron, legend=2)
    plt.title('Персептрон\n(Accuracy: {:.2f})'.format(perceptron_score))

    plt.subplot(132)
    plot_decision_regions(X_test, y_test, clf=mlp_10, legend=2)
    plt.title('MLP (10 нейронов)\n(Accuracy: {:.2f})'.format(mlp_10_score))

    plt.subplot(133)
    plot_decision_regions(X_test, y_test, clf=mlp_100, legend=2)
    plt.title('MLP (100 нейронов)\n(Accuracy: {:.2f})'.format(mlp_100_score))

    plt.tight_layout()

    plt.savefig('static/models_comparison.png')

    return render_template('index.html', result=True)

if __name__ == '__main__':
    app.run(debug=True)