#3dplot

Dynamic 3D Data Visualization Insights

• Model: DaVinci2

• Size: 1152 X 864 (1.00 MP)

• Used settings:

  • Prompt: import numpy as np import matplotlib.pyplot as plt from matplotlib.colors import LinearSegmentedColormap def multibrot_raw(width, height, max_iter=512, power=np.pi*1.8778, bailout=np.pi*1.8778): x = np.linspace(-3.5, 3.5, width) # По-широк view y = np.linspace(-2.5, 2.5, height) X, Y = np.meshgrid(x, y) C = X + 1j * Y Z = np.zeros_like(C, dtype=complex) n_escape = np.full(C.shape, 0, dtype=float) # Start 0 mask = np.ones(C.shape, dtype=bool) for n in range(max_iter): Z[mask] = Z[mask] ** power + C[mask] escaped = np.abs(Z) > bailout new_escaped = escaped & mask n_escape[new_escaped] = n + 1 mask &= ~escaped # Interior stays 0 (black) # Normalize: Разтегни ниските n (scaling като в C++ примера) scale = 7.854458 * np.log(power) # ~44 за p=9 mu = np.clip(n_escape / scale, 0, 1) # n / scale за [0,1] return mu # Palette: black -> blue outer (low n) -> green spirals -> yellow -> pink/red bulbs (high n) colors = [ '#000000', '#00008B', '#4B0082', '#00BFFF', '#00CED1', '#008000', '#7FFF00', '#FFFF00', '#FF69B4', '#FF1493', '#FF0000' ] cmap = LinearSegmentedColormap.from_list('filled_vibe', colors, N=256) # Generate & plot img = multibrot_raw(800, 800) plt.figure(figsize=(12, 12)) plt.imshow(img, cmap=cmap, origin='lower', extent=(-2.5, 2.5, -1.5, 1.5)) plt.axis('on') plt.title('Ебанье сас путфръгънье и скубанье поди мишнѝцѝте') plt.show()
  • Using base image: No
  • Aspect Ratio: landscape