import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import librosa
import librosa.display

# Definice color palety
color_pal = plt.rcParams["axes.prop_cycle"].by_key()["color"]

def process_signal_from_csv(csv_file_path):
    # Load signal from CSV
    df = pd.read_csv(csv_file_path)
    y = df.iloc[:, 0].values
    sr = 22050

    # Display raw signal
    pd.Series(y).plot(figsize=(10, 5),
                      lw=1,
                      title='Raw Signal Example',
                      color=color_pal[0])
    plt.show()

    # Spectrogram
    D = librosa.stft(y, n_fft=1024, hop_length=2, win_length=128)
    S_db = librosa.amplitude_to_db(np.abs(D), ref=np.max)

    # Plot spectrogram
    fig, ax = plt.subplots(figsize=(10, 5))
    img = librosa.display.specshow(S_db,
                                   y_axis='hz',
                                   fmin=0,
                                   fmax=17000,
                                   ax=ax)
    ax.set_title('Spectrogram', fontsize=20)
    fig.colorbar(img, ax=ax, format='%0.002f')
    plt.show()

    # Save spectrogram
    fig.savefig('Spectogram.png')

    return y, sr, S_db

# Pouziti
csv_file_path = #nacist CSV file
y, sr, spectrogram = process_signal_from_csv(csv_file_path)