import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d


def plot_1d_data(data, line_length=4.8,path_1d='./field_pulse.png'):
    data = data

    plt.rcParams.update({'font.family': 'Times New Roman', 'font.size': 20})
    time = np.linspace(0, 200, len(data)) 

    plt.figure(figsize=(3, 5))
    plt.plot(data, time, color='black')  

    plt.tick_params(axis='both', direction='in', width=1)  
    plt.gca().spines['top'].set_linewidth(1) 
    plt.gca().spines['right'].set_linewidth(1)  
    plt.gca().spines['left'].set_linewidth(1)  
    plt.gca().spines['bottom'].set_linewidth(1) 


    plt.grid(False)
    plt.gca().invert_yaxis()
    plt.ylabel('Time (ns)', fontsize=20)
    plt.xlabel('Amplitude', fontsize=20)
    plt.yticks(np.arange(0, 201, 50))  
    plt.xticks([-1, 0, 1])  
    plt.tight_layout()
    plt.savefig(path_1d, dpi=300)


data=np.delete(np.loadtxt('./reflection_impulse_field_standard.csv', delimiter=",", skiprows=0), [0], axis=0) # 
window_size=10
data=np.convolve(data, np.ones(window_size)/window_size, mode='valid')
plot_1d_data(data, line_length=4.8,path_1d='./field_pulse.png')