def test_bezier_patch(self, cpoints):
cverts = [Vertex(p) for p in cpoints]
bzr_patch = compile_bezier_patch(cverts)
points = sample_func_2D(bzr_patch, 0.1)
estimated_points = fit_bezier_patch(points, bezier_patch_2_tuple)
estimaded_cverts = [Vertex(p) for p in estimated_points]
if VERBOSE:
print(".....................................")
print(cverts)
print(estimaded_cverts)
print(".....................................")
self.assertTrue(almost_equal_lists(cverts, estimaded_cverts))
def test_bezier_patch(self, cpoints):
cverts = [Vertex(p) for p in cpoints]
bzr_patch = compile_bezier_patch(cverts)
points = sample_func_2D(bzr_patch, 0.1)
estimated_points = fit_bezier_patch(points, bezier_patch_2_tuple)
estimaded_cverts = [Vertex(p) for p in estimated_points]
if VERBOSE:
print(".....................................")
print(cverts)
print(estimaded_cverts)
print(".....................................")
self.assertTrue(almost_equal_lists(cverts, estimaded_cverts))
def high_degree_approximation(verts):
'''Split the verts into four sets (separated on the average) and approximate each of them.'''
avgx = numpy.mean([v[0] for v in verts])
avgy = numpy.mean([v[1] for v in verts])
f1 = lambda v: v[0] <= avgx
f2 = lambda v: v[1] <= avgy
sub_verts = [None] * 4
sub_verts[0] = list(filter(lambda v: f1(v) and f2(v), verts))
sub_verts[1] = list(filter(lambda v: f1(v) and not f2(v), verts))
sub_verts[2] = list(filter(lambda v: not f1(v) and f2(v), verts))
sub_verts[3] = list(filter(lambda v: not f1(v) and not f2(v), verts))
sub_patches_cpoints = [0] * 4
for i,vs in enumerate(sub_verts):
sub_patches_cpoints[i] = [Vertex(x) for x in mymath.fit_bezier_patch(vs, mymath.bezier_patch_2_tuple)]
return sub_patches_cpoints
def high_degree_approximation(verts):
'''Split the verts into four sets (separated on the average) and approximate each of them.'''
avgx = numpy.mean([v[0] for v in verts])
avgy = numpy.mean([v[1] for v in verts])
f1 = lambda v: v[0] <= avgx
f2 = lambda v: v[1] <= avgy
sub_verts = [None] * 4
sub_verts[0] = list(filter(lambda v: f1(v) and f2(v), verts))
sub_verts[1] = list(filter(lambda v: f1(v) and not f2(v), verts))
sub_verts[2] = list(filter(lambda v: not f1(v) and f2(v), verts))
sub_verts[3] = list(filter(lambda v: not f1(v) and not f2(v), verts))
sub_patches_cpoints = [0] * 4
for i, vs in enumerate(sub_verts):
sub_patches_cpoints[i] = [
Vertex(x)
for x in mymath.fit_bezier_patch(vs, mymath.bezier_patch_2_tuple)
]
return sub_patches_cpoints
def simple_approximation(verts, func):
#Simply approximate the verts with the given function
cpoints = mymath.fit_bezier_patch(verts, func)
return [Vertex(cp) for cp in cpoints]
def test_double_patch(self):
points = [Vertex(p) for p in two_patches_points]
estimated_points = fit_bezier_patch(points, bezier_patch_2_tuple)
print(estimated_points)
def test_double_patch(self):
points = [Vertex(p) for p in two_patches_points]
estimated_points = fit_bezier_patch(points, bezier_patch_2_tuple)
print(estimated_points)
def simple_approximation(verts, func):
#Simply approximate the verts with the given function
cpoints = mymath.fit_bezier_patch(verts, func)
return [Vertex(cp) for cp in cpoints]
