Merge branch 'master' of github.com:Hodapp87/automata_scratch

README.md

@@ -8,6 +8,8 @@
 - https://en.wikipedia.org/wiki/Polygon_triangulation - do this to
   fix my wave example!
   - http://www.polygontriangulation.com/2018/07/triangulation-algorithm.html
+- Clean up examples.ram_horn_branch(). The way I clean it up might
+  help inform some cleaner designs.
 - I really need to standardize some of the behavior of fundamental
   operations (with regard to things like sizes they generate). This
   is behavior that, if it changes, will change a lot of things that I'm
@@ -58,6 +60,7 @@
   identical except that it is higher-resolution?
 - Use mixins to extend 3D transformations to things (matrices,
   cages, meshes, existing transformations)
+- I can transform a Cage.  Why not a CageGen?
   
 ## ????
 - Embed this in Blender?
@@ -75,3 +78,7 @@
 - Current system is very "generative".  Could I do basically L-system
   if I have rules for how a much is *refined*?  What about IFS?
 - Do this in Rust once I understand WTF I am doing
+
+## Other thoughts
+
+- Why do I never use the term "extruding" to describe what I'm doing?

cage.py

@@ -67,6 +67,20 @@ class Cage(object):
             trans_verts[2*i+1] = m
         trans_edges = [[7, 0, 1], [1, 2, 3], [3, 4, 5], [5, 6, 7]]
         return cages, trans_verts, trans_edges
+    def subdivide_x_deprecated(self):
+        mids = (self.verts + numpy.roll(self.verts, -1, axis=0)) / 2
+        centroid = numpy.mean(self.verts, axis=0)
+        arrs = [
+                [self.verts[0,:], mids[0,:],       mids[2,:],       self.verts[3,:]],
+                [mids[0,:],       self.verts[1,:], self.verts[2,:], mids[2,:]],
+        ]
+        cages = [Cage(numpy.array(a), self.splits) for a in arrs]
+        trans_verts = numpy.zeros((2*len(self.verts),3), dtype=self.verts.dtype)
+        for i,(v,m) in enumerate(zip(self.verts, mids)):
+            trans_verts[2*i] = v
+            trans_verts[2*i+1] = m
+        trans_edges = [[7, 0, 1], [1, 2, 3], [3, 4, 5], [5, 6, 7]]
+        return cages, trans_verts, trans_edges
     def is_fork(self):
         return False
     def transform(self, xform):

examples.py

@@ -2,6 +2,7 @@
 
 import itertools
 
+import math
 import numpy
 import stl.mesh
 import trimesh
@@ -148,22 +149,13 @@ def ram_horn_branch():
         for i in range(count):
             if i > 0:
                 c = cage1.transform(xf)
-                #print("DEBUG: recur, i={}, yield {}".format(i, c.verts))
                 yield c
             xf0 = xf
             xf = incr.compose(xf)
-        # .compose(opening_boundary(i))
         def xf_sub(i):
-            # yes, I can do this in a one-liner
-            # yes, it should be normalized, but I reused from something else
-            if i == 0:
-                dx, dy = 1, 1
-            elif i == 1:
-                dx, dy = -1, 1
-            elif i == 2:
-                dx, dy = -1, -1
-            elif i == 3:
-                dx, dy = 1, -1
+            # (dx,dy) should be normalized, but I reused from something else
+            dx = 1 if i == 0 or i == 1 else -1
+            dy = 1 if i == 0 or i == 3 else -1
             return meshutil.Transform().translate(0, 0, 0.5).rotate([-dy,dx,0], -numpy.pi/6)
         subdiv, trans_vs, trans_es = cage1.subdivide_deprecated()
         gens = [cage.CageGen(itertools.chain(
@@ -172,12 +164,6 @@ def ram_horn_branch():
                 for i,cage_sub in
                 enumerate(subdiv)]
         yield cage.CageFork(gens, xf.apply_to(trans_vs), trans_es)
-        # TODO: The starting cage needs to be one iteration *earlier*, and the
-        # subdivided cage is fine, but the generators likewise need to start
-        # one iteration earlier.  Look closely in Blender at the mesh,
-        # specifically just prior to the fork.
-        #
-        # xf0.apply_to(trans_vs) is identical to last cage yielded?
     cg = cage.CageGen(itertools.chain(
         [cage0],
         recur(meshutil.Transform(), cage0, 8),
@@ -186,6 +172,43 @@ def ram_horn_branch():
     mesh = cg.to_mesh(count=32, close_first=True, close_last=True)
     return mesh
 
+def dream_pendant():
+    center = meshutil.Transform().translate(-0.5, -0.5, 0)
+    cage0 = cage.Cage.from_arrays([
+        [0, 0, 0],
+        [1, 0, 0],
+        [1, 1, 0],
+        [0, 1, 0],
+    ]).transform(center)
+    incr = meshutil.Transform() \
+                   .scale(0.95, 1.0, 0.95) \
+                   .rotate([0,1,0], 0.2) \
+                   .translate(0,0,0.9)
+    def recur(xf, cage1, count):
+        for i in range(count):
+            if i > 0:
+                c = cage1.transform(xf)
+                yield c
+            xf0 = xf
+            xf = incr.compose(xf)
+        def xf_rot(a):
+            return meshutil.Transform().rotate([0,1,0], a)
+        subdiv, trans_vs, trans_es = cage1.subdivide_x_deprecated()
+        gens = [cage.CageGen(itertools.chain(
+                    [cage_sub.transform(xf)],
+                    recur(xf_rot(ang).compose(xf), cage_sub, 5)))
+                for cage_sub,ang in
+                zip(subdiv, [-0.2, 0.7])]
+        yield cage.CageFork(gens, xf.apply_to(trans_vs), trans_es)
+    cg = cage.CageGen(itertools.chain(
+        [cage0],
+        recur(meshutil.Transform(), cage0, 3),
+    ))
+    # TODO: if this is just a list it seems silly to require itertools
+    mesh1 = cg.to_mesh(count=32, close_first=False, close_last=True)
+    mesh2 = mesh1.transform(meshutil.Transform().rotate([0,1,0], math.pi))
+    return meshutil.FaceVertexMesh.concat_many([mesh1, mesh2])
+
 def branch_test():
     b0 = numpy.array([
         [0, 0, 0],
@@ -356,6 +379,7 @@ def main():
         # TODO: Fix
         #ram_horn3: "ramhorn3.stl",
         ram_horn_branch: "ramhorn_branch.stl",
+        dream_pendant: "dream_pendant.stl",
         twist: "twist.stl",
         twist_nonlinear: "twist_nonlinear.stl",
         twist_from_gen: "twist_from_gen.stl",