Simulasi Gelombang n = f(x±ct)

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from IPython.display import HTML

# Parameter simulasi
c = 1.0           # Kecepatan gelombang
L = 20.0          # Panjang domain (diperbesar)
T = 10.0          # Waktu simulasi
dx = 0.02         # Resolusi spasial
dt = 0.02         # Interval waktu
x0 = 5.0          # Posisi awal pusat gelombang
sigma = 0.5       # Lebar gelombang Gaussian

# Fungsi bentuk gelombang
def wave_form(x, t):
    return np.exp(-((x - c*t - x0)**2)/(2*sigma**2))

# Membuat grid spasial
x = np.arange(0, L, dx)
total_frames = int(T/dt)

# Setup plot
fig, ax = plt.subplots(figsize=(10,5))
line, = ax.plot(x, wave_form(x, 0), lw=2, color='blue')
ax.set_xlim(0, L)
ax.set_ylim(-0.1, 1.1)
ax.set_xlabel('Posisi (x)')
ax.set_ylabel('Amplitudo')
ax.set_title('Gelombang Berjalan y = f(x - ct)')
ax.grid(True)

# Fungsi animasi
def animate(frame):
    t = frame * dt  # Waktu aktual
    line.set_ydata(wave_form(x, t))
    # line.set_color(plt.cm.viridis(frame%256/255))  # Animasi warna opsional
    # Untuk animasi monokrom:
    line.set_color('blue')  # Hapus efek warna dinamis
    return line,

# Mengurangi jumlah frame dengan frame_step
frame_step = 3  # Ubah nilai ini untuk kontrol ukuran file
ani = FuncAnimation(
    fig,
    animate,
    frames=range(0, total_frames, frame_step),
    interval=30,
    blit=True
)

plt.close()

# Tampilkan animasi
HTML(ani.to_jshtml())

Once Loop Reflect

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from IPython.display import HTML

# Parameter simulasi
c = 1.0           # Kecepatan gelombang
L = 20.0          # Panjang domain
T = 10.0          # Waktu simulasi
dx = 0.02         # Resolusi spasial
dt = 0.02         # Interval waktu
x0 = 5.0          # Posisi awal pusat gelombang
sigma = 0.8       # Lebar gelombang Gaussian

# Fungsi turunan Gaussian orde pertama
def wave_form(x, t):
    arg = (x - c*t - x0)
    return (-arg/(sigma**2)) * np.exp(-(arg**2)/(2*sigma**2))  # Turunan pertama Gaussian

# Membuat grid spasial
x = np.arange(0, L, dx)
total_frames = int(T/dt)

# Setup plot
fig, ax = plt.subplots(figsize=(10,5))
line, = ax.plot(x, wave_form(x, 0), lw=2, color='royalblue')
ax.set_xlim(0, L)
ax.set_ylim(-1.5, 1.5)  # Diadjust untuk amplitudo turunan Gaussian
ax.set_xlabel('Posisi (x)')
ax.set_ylabel('Amplitudo')
ax.set_title('Gelombang Berjalan Turunan Gaussian $\partial/\partial x(e^{-(x-ct)^2/2\sigma^2})$')
ax.grid(True)

# Fungsi animasi
def animate(frame):
    t = frame * dt  # Waktu aktual
    y = wave_form(x, t)
    
    # Update data dan efek visual
    line.set_ydata(y)
    line.set_color(plt.cm.coolwarm(0.5 + np.max(y)/3))  # Warna dinamis berdasarkan amplitudo
    
    return line,

# Konfigurasi frame
frame_step = 2  # Kontrol kehalusan animasi
ani = FuncAnimation(
    fig,
    animate,
    frames=range(0, total_frames, frame_step),
    interval=30,
    blit=True
)

plt.close()

# Tampilkan animasi
HTML(ani.to_jshtml())

Once Loop Reflect