CHATGPT FTW

import numpy as np
from math import exp
from matplotlib import pyplot as plt

def run_fdtd(factor):
    ke = 200
    ex = np.zeros(ke)
    hy = np.zeros(ke)

    # pulse params
    kc = int(ke / 2)
    t0 = 40
    spread = 12

    boundary_low = [0, 0]
    boundary_high = [0, 0]

    nsteps = 250

    # Dictionary to keep track of plot points
    plotting_points = [
        {'num_steps': 20, 'data_to_plot': None, 'label': ''},
        {'num_steps': 225, 'data_to_plot': None, 'label': ''},
        {'num_steps': 250, 'data_to_plot': None, 'label': 'FDTDcells'},
    ]

    # main FDTD loop
    for time_step in range(1, nsteps + 1):
        # calculate Ex field
        for k in range(1, ke):
            ex[k] = ex[k] + factor * (hy[k - 1] - hy[k])

        # put a gaussian pulse at the low end
        pulse = exp(-0.5 * ((t0 - time_step) / spread) ** 2)
        ex[kc] = pulse

        # update boundary conditions
        ex[0] = boundary_low.pop(0)
        boundary_low.append(ex[1])

        ex[ke - 1] = boundary_high.pop(0)
        boundary_high.append(ex[ke - 2])

        # calculate the Hy field
        for k in range(ke - 1):
            hy[k] = hy[k] + factor * (ex[k] - ex[k + 1])

        # store data at specific time steps for plotting
        for plotting_point in plotting_points:
            if time_step == plotting_point['num_steps']:
                plotting_point['data_to_plot'] = np.copy(ex)

    return plotting_points

# Run simulations with factors 0.5, 1.0, 1.1, and 0.25
factors = [0.5, 1.0, 1.1, 0.25]
plot_data = {factor: run_fdtd(factor) for factor in factors}

# Plotting the results
plt.rcParams['font.size'] = 12
fig, axs = plt.subplots(len(factors), 3, figsize=(12, 12))

def plot_e_field(ax, data, timestep, label, factor):
    ax.plot(data, color='k', linewidth=1)
    ax.set_ylabel('E$_x$', fontsize=10)
    ax.set_xticks(np.arange(0, 199, step=20))
    ax.set_xlim(0, 199)
    ax.set_yticks(np.arange(-1.2, 1.2, step=1))
    ax.set_ylim(-1.2, 1.2)
    ax.text(100, 0.5, f'T = {timestep}', horizontalalignment='center', fontsize=9)
    ax.set_xlabel(f'{label} (Factor={factor})', fontsize=10)

for i, (factor, plots) in enumerate(plot_data.items()):
    for j, plotting_point in enumerate(plots):
        plot_e_field(axs[i, j],
                     plotting_point['data_to_plot'],
                     plotting_point['num_steps'],
                     plotting_point['label'],
                     factor)

plt.tight_layout()
plt.show()