py added

python/generate_sdf01.py

+#! /usr/bin/env python3
+
+import numpy as np
+
+
+def sdCircle(point, center, radius):
+    return np.linalg.norm(center - point) - radius
+
+
+def sdBox(point, center, dimensions):
+    d = abs(point - center) - np.array(dimensions) * 0.5
+    return np.linalg.norm(np.maximum(d, 0.0)) + min(np.max(d), 0.0)
+
+
+def smoothUnion(d1, d2, k):
+    h = max(k - abs(d1 - d2), 0.0)
+    return min(d1, d2) - h * h * 0.25 / k
+
+
+def sdf(x):
+    d = np.ndarray((x.shape[1],))
+
+    for t in range(x.shape[1]):
+        xt = x[:, t]
+        d[t] = sdCircle(xt, [0.3, 0.36], 0.2)
+        d[t] = smoothUnion(d[t], sdBox(xt, [0.5, 0.6], [0.4, 0.2]), 0.1)
+
+    return d
+
+
+
+nbDim = 40
+
+t = np.linspace(0, 1, nbDim)
+
+xv, yv = np.meshgrid(t, t)
+x = np.array([xv.flatten(), yv.flatten()])
+
+y = sdf(x)
+
+
+data = {
+    'nbDim': nbDim,
+    'x': x,
+    'y': y,
+}
+
+np.save('data/sdf01.npy', data)

python/generate_sdf3D01.py

+#! /usr/bin/env python3
+
+import numpy as np
+
+
+def sdCircle(point, center, radius):
+    return np.linalg.norm(center - point) - radius
+
+
+def sdBox(point, center, dimensions):
+    d = abs(center - point) - np.array(dimensions) * 0.5
+    return np.linalg.norm(np.maximum(d, 0.0)) + min(np.max(d), 0.0)
+
+
+def smoothUnion(d1, d2, k):
+    h = max(k - abs(d1 - d2), 0.0)
+    return min(d1, d2) - h * h * 0.25 / k
+
+
+def sdf(x):
+    d = np.ndarray((x.shape[1],))
+
+    for t in range(x.shape[1]):
+        xt = x[:, t]
+        d[t] = sdCircle(xt, [0.4, 0.43, 0.5], 0.1)
+        d[t] = smoothUnion(d[t], sdBox(xt, [0.5, 0.55, 0.6], [0.2, 0.1, 0.25]), 0.05)
+
+    return d
+
+
+
+nbDim = 80
+
+t = np.linspace(0, 1, nbDim)
+
+xv, yv, zv = np.meshgrid(t, t, t)
+x = np.array([zv.flatten(), xv.flatten(), yv.flatten()])
+
+y = sdf(x)
+
+
+data = {
+    'nbDim': nbDim,
+    'x': x,
+    'y': y,
+}
+
+np.save('data/sdf3D01.npy', data)