matplotlib · tacaswell · Nov 16, 2016 · Nov 12, 2016 · Nov 12, 2016 · Nov 12, 2016
diff --git a/examples/showcase/mandelbrot.py b/examples/showcase/mandelbrot.py
@@ -0,0 +1,64 @@
+# The mandelbrot set rendered with shading and renormalized count
+# for better rendering
+import numpy as np
+
+
+def mandelbrot_set(xmin, xmax, ymin, ymax, xn, yn, maxiter, horizon=2.0):
+    X = np.linspace(xmin, xmax, xn, dtype=np.float32)
+    Y = np.linspace(ymin, ymax, yn, dtype=np.float32)
+    C = X + Y[:, None]*1j
+    N = np.zeros(C.shape, dtype=int)
+    Z = np.zeros(C.shape, np.complex64)
+    for n in range(maxiter):
+        I = np.less(abs(Z), horizon)
+        N[I] = n
+        Z[I] = Z[I]**2 + C[I]
+    N[N == maxiter-1] = 0
+    return Z, N
+
+
+if __name__ == '__main__':
+    import time
+    import matplotlib
+    from matplotlib import colors
+    import matplotlib.pyplot as plt
+
+    xmin, xmax, xn = -2.25, +0.75, 3000/2
+    ymin, ymax, yn = -1.25, +1.25, 2500/2
+    maxiter = 200
+    horizon = 2.0 ** 40
+    log_horizon = np.log(np.log(horizon))/np.log(2)
+    Z, N = mandelbrot_set(xmin, xmax, ymin, ymax, xn, yn, maxiter, horizon)
+
+    # Normalized recount as explained in:
+    # http://linas.org/art-gallery/escape/smooth.html
+    # https://www.ibm.com/developerworks/community/blogs/jfp/entry/My_Christmas_Gift
+
+    # This line will generate warnings for null values but it is faster to
+    # process them afterwards using the nan_to_num
+    M = np.nan_to_num(N + 1 - np.log(np.log(abs(Z)))/np.log(2) + log_horizon)
+
+    dpi = 72
+    width = 10
+    height = 10*yn/xn
+    fig = plt.figure(figsize=(width, height), dpi=dpi)
+    ax = fig.add_axes([0.0, 0.0, 1.0, 1.0], frameon=False, aspect=1)
+
+    # Shaded rendering
+    light = colors.LightSource(azdeg=315, altdeg=10)
+    M = light.shade(M, cmap=plt.cm.hot, vert_exag=1.5,
+                    norm=colors.PowerNorm(0.3), blend_mode='hsv')
+    plt.imshow(M, extent=[xmin, xmax, ymin, ymax], interpolation="bicubic")
+    ax.set_xticks([])
+    ax.set_yticks([])
+
+    # Some advertisement for matplotlib
+    year = time.strftime("%Y")
+    major, minor, micro = matplotlib.__version__.split('.')
+    text = ("The Mandelbrot fractal set\n"
+            "Rendered with matplotlib %s.%s, %s — http://matplotlib.org"
+            % (major, minor, year))
+    ax.text(xmin+.025, ymin+.025, text, color="white", fontsize=12, alpha=0.5)
+
+    # plt.savefig("mandelbrot.png")
+    plt.show()