import matplotlib.pyplot as plt
import numpy as np


# creates horizontal bar plots based on the classification results

def horizontal_bar_plot(index, label):
    
    plt.rcParams["font.family"] = "Arial"

    fig, ax = plt.subplots()
    fig.set_size_inches(8, 0.9)
    
    ax.barh([0], [1], color='lightgray', edgecolor='black', linewidth=3)  

    if index == 0:
        i = 0.1
        color = 'green'
    elif index == 1:
        i = 0.5
        color = 'yellow'
    else:
        i = 0.9
        color = 'red'
    
    plt.title(label, fontsize=16, fontweight='light', color='black', loc='center')
    ax.scatter([i], [0], color=color, marker="s", s=2000, edgecolors='black', linewidth=2)


    ax.set_xlim(-0.2, 1.2)  # Adjust x-limits
    ax.set_ylim(-0.5, 0.5)
    ax.set_xticks([])
    ax.set_yticks([])

    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)
    ax.spines['bottom'].set_visible(False)
    ax.spines['left'].set_visible(False)

    return fig


def check_classification(array):
    feed = array[0]
    depth = array[1]
    wear = array[2]

    fig_feed = horizontal_bar_plot(feed, "Vorschub")
    fig_depth = horizontal_bar_plot(depth, "Schnitttiefe")
    fig_wear = horizontal_bar_plot(wear, "Werkzeugzustand")

    return fig_feed, fig_depth, fig_wear