File:Perlin noise with contour.svg

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English: 2-D Perlin noise with a contour line at zero, to show that the noise is zero at the intersections of the gradient mesh. The smootherstep function was used for interpolation.
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Source Own work
Author Morn
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with more contour lines
SVG development
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Source code
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Python code

Source code 
# Perlin noise plot with Matplotlib  from pylab import * import random  XDIM, YDIM = 11, 11     # gradient mesh size SCALE = 50              # noise grid size per gradient mesh unit size XDP, YDP = (XDIM - 2) * SCALE + 1, (YDIM - 2) * SCALE + 1  phi = zeros((YDIM, XDIM))   # gradient phase angles perlin = zeros((YDP, XDP))  # Perlin noise array  # make the plot reproducible by using a fixed random seed random.seed("Perlin")  # choose random phase angles for gradients for y in range(YDIM):     for x in range(XDIM):         phi[y,x] = 2 * pi * random.random()  def grad(x0, y0, dx, dy):     "Compute the dot product between the gradient and position vector"     gx, gy = cos(phi[y0,x0]), sin(phi[y0,x0])     return gx * dx + gy * dy  def inter(a, b, w):     "Interpolate between a and b using weight w"     return (b - a) * ((w * (w * 6 - 15) + 10) * w * w * w) + a  # smootherstep     #return (b - a) * (3 - 2 * w) * w * w + a   # smoothstep     #return (b - a) * w + a                     # linear  # compute Perlin noise for yi in range(YDP):     for xi in range(XDP):         x, y = xi / SCALE, yi / SCALE         x0, y0 = int(x), int(y)         dx, dy = x - x0, y - y0          g1 = grad(x0, y0, dx, dy)         g2 = grad(x0 + 1, y0, -1 + dx, dy)         g3 = grad(x0, y0 + 1, dx, -1 + dy)         g4 = grad(x0 + 1, y0 + 1, -1 + dx, -1 + dy)          perlin[yi,xi] = inter(inter(g1, g2, dx), inter(g3, g4, dx), dy)  print(f"Max {perlin.max()}, min {perlin.min()}")  # use Matplotlib to create a plot figure(figsize = (8, 9)) X = array([x / SCALE for x in range(XDP)]) Y = array([y / SCALE for y in range(YDP)]) imshow(perlin, interpolation = "bicubic", cmap = plt.cm.bwr, vmin = -.8, vmax = .8,   extent = (X.min(), X.max(), Y.max(), Y.min())) cb = colorbar(orientation = "horizontal") contour(X, Y, perlin, (0,), linewidths = 2, colors = "green") xticks(range(XDIM-1), labels = "" * XDIM) yticks(range(YDIM-1), labels = "" * YDIM) grid(lw = 1.2, color = "black", alpha = .8, ls = "dashed") gca().set_position([.1, .2, .8, .8]) cb.ax.set_position([.1, -.68, .8, .8]) title("2-D Perlin noise with contour line at zero") savefig("perlin_noise_with_contour.svg") show()

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Perlin noise

inception

30 November 2023

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