# -*- coding: utf-8 -*-
"""
Created on Thu Oct 31 15:17:01 2024

@author: ym
"""
import numpy as np
import matplotlib.pyplot as plt



def showHist(err, correct):
    err = np.array(err)
    correct = np.array(correct)

    fig, axs = plt.subplots(2, 1)
    axs[0].hist(err, bins=50, edgecolor='black')
    axs[0].set_xlim([0, 1])
    axs[0].set_title('err')

    axs[1].hist(correct, bins=50, edgecolor='black')
    axs[1].set_xlim([0, 1])
    axs[1].set_title('correct')
    # plt.show()
    
    return plt

def show_recall_prec(recall, prec, ths):
    # x = np.linspace(start=-0, stop=1, num=11, endpoint=True).tolist()
    fig = plt.figure(figsize=(10, 6))
    plt.plot(ths, recall, color='red', label='recall')
    plt.plot(ths, prec, color='blue', label='PrecisePos')
    plt.legend()
    plt.xlabel(f'threshold')
    # plt.ylabel('Similarity')
    plt.grid(True, linestyle='--', alpha=0.5)
    # plt.savefig('accuracy_recall_grid.png')
    # plt.show()
    # plt.close()
    
    return plt


def compute_recall_precision(err_similarity, correct_similarity):
    ths = np.linspace(0, 1, 51)
    recall, prec = [], []
    for th in ths:
        TP = len([num for num in correct_similarity if num >= th])
        FP = len([num for num in err_similarity if num >= th])
        if (TP+FP) == 0:
            prec.append(1)
            recall.append(0)
        else:
            prec.append(TP / (TP + FP))
            recall.append(TP / (len(err_similarity) + len(correct_similarity)))
    return recall, prec, ths