def test_proj_ohtak1():
""" Tests projection of centroids using Ohtake's original method. Projects point-wise.
Repeats points by applying a small perturbation.
Blend disc object.
Uses a high resolution MC for checking the new projected points (black dots).
The original centroids are shon in red.
The failed projections are shown in Yello. Their number is writtn in output (9 points)"""
from stl_tests import make_mc_mesh_scikit
exname = "blend_example2_discs" # "blend_example2"
import example_objects
iobj = example_objects.make_example_vectorized(exname, 8.0)
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-2.*8, +4.*8, 0.4*8/5)
(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-16, +32, 0.64*3*2/2)
verts, faces = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE)
print verts.shape, faces.shape
average_edge = STEPSIZE
# verts = optimise_mesh(verts, faces, iobj)
c3 = np.mean(verts[faces[:], :], axis=1)
# add extra points
c3 = np.concatenate((c3, c3+STEPSIZE*0.1, c3+STEPSIZE*(-0.1)), axis=0)
c3 = np.concatenate((c3,), axis=0)
centroids = np.concatenate((c3, np.ones((c3.shape[0], 1))), axis=1)
new_centroids = centroids.copy()
set_centers_on_surface__ohtake(iobj, new_centroids, average_edge)
print
#print np.arange(nones_map.shape[0])[np.logical_not(nones_map)].shape
print np.sum(np.logical_not(nones_map)), "(success) + ", np.sum(nones_map), " (failed)"
new_centroids2 = new_centroids[np.logical_not(nones_map), :]
#todo: Use "None" for non-converging ones. (and visualise them)
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-16, +32, 0.64*3*2/2)
#verts2, faces2 = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE * 0.2/2.0) #15 million!
verts2, faces2 = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE * 0.2)
#m = m2stl_mesh(verts, faces)
#if ACTUALLY_SAVE:
# m.save('implicit6-blend.stl') # wow
centroids_failed = centroids[nones_map, :] #green ones
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids, new_centroids2], minmax=(RANGE_MIN, RANGE_MAX))
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids, new_centroids2, centroids_failed], minmax=(RANGE_MIN, RANGE_MAX))
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids_failed, new_centroids2], minmax=(RANGE_MIN, RANGE_MAX))
#best:
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids, new_centroids], minmax=(RANGE_MIN, RANGE_MAX))
display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids, new_centroids, centroids_failed], minmax=(RANGE_MIN, RANGE_MAX))
def load_example(self, example_name="ell_example1", res=1):
"""
res: controls step size of mc grid
example_name: name of example to build, available names can be
found in the file example_objects
"""
print "[Start] Loading example: %s" % example_name + ' ...'
from example_objects import make_example_vectorized
from stl_tests import make_mc_mesh_scikit
exname = example_name
self.iobj = make_example_vectorized(exname)
self.register_function(self.iobj.implicitFunction)
self.register_gradient(self.iobj.implicitGradient)
(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-2., 2., 0.1 / res) # non-spiky!!
self.vertices, self.faces = make_mc_mesh_scikit(
self.iobj, RANGE_MIN, RANGE_MAX, STEPSIZE)
self.centroids = np.mean(self.vertices[self.faces[:], :], axis=1)
self.centroids = np.c_[self.centroids,
np.ones((len(self.centroids), 1))]
self.triangles = self.vertices[self.faces]
self.build_neighbours()
self.name = exname
self.lamda = calc_avg_triangle_length(self.triangles) / 2
print "[End] Loading example: %s" % example_name + ' .'
def test_profiler():
#use for profiling only
exname = "blend_example2_discs" # "blend_example2"
import example_objects
iobj = example_objects.make_example_vectorized(exname, 8.0)
(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-16, +32, 0.64*3*2/2)
verts, faces = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE)
print verts.shape, faces.shape
average_edge = STEPSIZE
c3 = np.mean(verts[faces[:], :], axis=1)
c3 = np.concatenate( (c3,c3+STEPSIZE*0.1,c3+STEPSIZE*(-0.1)), axis=0)
centroids = np.concatenate((c3, np.ones((c3.shape[0], 1))), axis=1)
nones_map = centroids[:,0]*0 > 100
new_centroids = centroids.copy()
set_centers_on_surface__ohtake(iobj, new_centroids, average_edge, nones_map)
new_centroids2 = new_centroids[np.logical_not(nones_map),:]
verts2, faces2 = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE * 0.2/1.0)
def cyl_test_example1():
print("started")
sys.stdout.flush()
# c = cyl1()
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-16, +32, 1.92 * 0.2 * 10/ 2.0)
#c, (RANGE_MIN, RANGE_MAX, STEPSIZE) = cyl2()
##(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-32, +32, 1.92 / 4.0*1.5/ 1.5)
# #takes 15 sec!
c, (RANGE_MIN, RANGE_MAX, STEPSIZE) = cyl3()
##(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-32, +32, 1.92 / 4.0) #15 sec! 2.5 millions voxels
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-32/2, +32/2, 1.92 / 4.0) # 2.5 sec!
# spiral cage
#c, (RANGE_MIN, RANGE_MAX, STEPSIZE) = cyl4()
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-32/2, +32/2, 1.92 / 4.0)
c, dims = cyl4()
(RANGE_MIN, RANGE_MAX, STEPSIZE) = dims
print("made the function")
sys.stdout.flush()
from stl_tests import make_mc_mesh_scikit
with Timer() as t:
# @profile
verts, faces = make_mc_mesh_scikit(c, RANGE_MIN, RANGE_MAX, STEPSIZE)
print("made MC : done within ", t.interval) # takes 15 sec!!
sys.stdout.flush()
ACTUALLY_SAVE = False
#from stl_tests import optimise_mesh
#verts = optimise_mesh(verts, faces, c)
#Does not work yet
from stl_tests import m2stl_mesh
m = m2stl_mesh(verts, faces)
if ACTUALLY_SAVE:
m.save('stl/cage.stl') # wow
from mesh_utils import mesh_invariant
mesh_invariant(faces)
from ohtake_surface_projection import display_simple_using_mayavi_
print("mayavi start")
sys.stdout.flush()
display_simple_using_mayavi_([(verts, faces), ], [], minmax=(RANGE_MIN, RANGE_MAX))
print("mayavi done")
sys.stdout.flush()
def test_search1():
import math
from stl_tests import make_mc_mesh_scikit
dicesize = 8.
exname = "udice_vec"
import example_objects
iobj = example_objects.make_example_vectorized(exname, dicesize)
(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-11, +10., 0.8) # non-spiky!!
verts, faces = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE)
verts = my_process_1(verts, faces, iobj)
from stl_tests import display_simple_using_mayavi_vf1
display_simple_using_mayavi_vf1(verts, faces)
print(np.min(verts.ravel()), np.max(verts.ravel()))
plot_stlmesh(m)
def test_proj_ohtak2():
from stl_tests import make_mc_mesh_scikit
exname = "french_fries_vectorized"
import example_objects
iobj = example_objects.make_example_vectorized(exname, 8.0)
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-2.*8, +4.*8, 0.4*8/5)
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-16, +32, 0.64*3*2/2)
(RANGE_MIN, RANGE_MAX,
STEPSIZE) = (-2 * 8, +4 * 8, 0.64 * 3 * 2 / 2 / 4. * 8 * 0.2
) # / 8. #0.768
#STEPSIZE2 = STEPSIZE * 0.2
STEPSIZE, STEPSIZE2 = (1.5, 0.384)
verts, faces = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE)
print verts.shape, faces.shape
average_edge = STEPSIZE
# verts = optimise_mesh(verts, faces, iobj)
c3_0 = np.mean(verts[faces[:], :], axis=1)
# add extra points
offsets = [0]
print c3_0.shape
#offsets = [0,+0.1,-0.1]
#c3 = np.concatenate((c3, c3+STEPSIZE*0.1, c3+STEPSIZE*(-0.1)), axis=0)
c3 = np.zeros((0, 3))
for x in offsets:
c3 = np.concatenate((
c3,
c3_0 + STEPSIZE * x,
), axis=0)
#c3 = np.concatenate((c3,), axis=0)
centroids = np.concatenate((c3, np.ones((c3.shape[0], 1))), axis=1)
nones_map = centroids[:, 0] * 0 > 100
new_centroids = centroids.copy()
set_centers_on_surface__ohtake(iobj, new_centroids, average_edge,
nones_map)
print
#print np.arange(nones_map.shape[0])[np.logical_not(nones_map)].shape
print np.sum(np.logical_not(nones_map)), "(success) + ", np.sum(
nones_map), " (failed)"
new_centroids2 = new_centroids[np.logical_not(nones_map), :]
#todo: Use "None" for non-converging ones. (and visualise them)
if False:
#(RANGE_MIN, RANGE_MAX, STEPSIZE) = (-16, +32, 0.64*3*2/2)
#verts2, faces2 = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX, STEPSIZE * 0.2/2.0) #15 million!
verts2, faces2 = make_mc_mesh_scikit(iobj, RANGE_MIN, RANGE_MAX,
STEPSIZE2)
verts2, faces2 = None, None
#m = m2stl_mesh(verts, faces)
#if ACTUALLY_SAVE:
# m.save('implicit6-blend.stl') # wow
centroids_failed = centroids[nones_map, :] #green ones
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids, new_centroids2], minmax=(RANGE_MIN, RANGE_MAX))
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids, new_centroids2, centroids_failed], minmax=(RANGE_MIN, RANGE_MAX))
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids_failed, new_centroids2], minmax=(RANGE_MIN, RANGE_MAX))
#best:
#display_simple_using_mayavi_([(verts, faces), (verts2, faces2)], [centroids, new_centroids], minmax=(RANGE_MIN, RANGE_MAX))
display_simple_using_mayavi_([(verts, faces), (verts2, faces2)],
[centroids, new_centroids, centroids_failed],
minmax=(RANGE_MIN, RANGE_MAX))