def correspondence(Auto3dgmData, mirror, phase=1):
if phase == 1:
npoints = Auto3dgmData.phase1SampledPoints
else:
npoints = Auto3dgmData.phase2SampledPoints
meshes = Auto3dgmData.datasetCollection.datasets[npoints][npoints]
corr = Correspondence(meshes=meshes, mirror=mirror)
print("Correspondence compute for Phase " + str(phase))
return (corr)
def start(self):
### INITIAL STEPS ###
# check parameters look good before proceeding
self.validate_parameters()
self.__write_output_dirs()
### DATA LOAD AND SUBSAMPLE
#TODO: No ftype param
self.dataset = DatasetFactory.ds_from_dir(self.mesh_dir, ftype='ply')
# need to get both sets of subsample results
ss_points = [self.ss_points_i, self.ss_points_f]
#TODO: Should use named parameters as the constructor for Subsample, I'm not sure what ss_type refers to.
#TODO: init doesn't return anything, so I've encoded the results dictionary in subsample_res.ret
subsample_res = Subsample(
self.dataset['mesh'], ss_points, self.ss_type
) # dataset class should eventually support multiple named mesh sets and should be dict-style callable like this for mesh TODO: Currently does not support multiple named mesh sets, and the param is dataset.meshes
ss_meshes_i = subsample_res[ss_points[0]]['output'][
'results'] #TODO: Results isnt a list of meshes, its a dict
ss_meshes_f = subsample_res[ss_points[1]]['output']['results']
#TODO: Add mesh set doesnt exist as a method. Self.dataset isnt a dataset, its a data set collection, maybe create a method to instantiate a new data set, and add it to the Dataset COllection? THis naming is kind of bad
self.dataset.add_mesh_set(self.ss_label_i, ss_meshes_i)
self.dataset.add_mesh_set(self.ss_label_f, ss_meshes_f)
### INITIAL SUBSAMPLE POINTS ANALYSIS ###
ss_i_correspondence_res = Correspondence( # Correspondence should take an initial alignment object with d, p, and r arrays; also correspondence should handle bundling pairwise results into a single data structure
meshes=self.dataset[self.ss_label_i],
initial_alignment=None,
globalize=True,
mirror=self.allow_reflection)
# Correspondence data structure should be an object with the following attributes: local_align with d, p, and r arrays, mst with minimum spanning tree, and global_align with d, p, and r arrays
self.dataset.add_analysis_set(self.ss_label_i, ss_i_correspondence_res)
### FINAL SUBSAMPLE POINTS ANALYSIS ###
ss_f_correspondence_res = Correspondence( # Correspondence should take an initial alignment object with d, p, and r arrays; also correspondence should handle bundling pairwise results into a single data structure
meshes=self.dataset[self.ss_label_f],
initial_alignment=self.dataset.analysis_set[
self.ss_label_i].global_align,
globalize=True,
mirror=self.allow_reflection)
print(dc.datasets) print(dc.analysis_sets) # Why is the initial dataset copied as an analysis_set? # Generate two sets of subsamples with 100 and 200 points each subsample_points = [100, 200] subsample_results = Subsample(dc.datasets[0], subsample_points, 'FPS') # this absolutely does not work # Add these results as additional datasets to our DatasetCollection dc.add_dataset(subsample_results[100]['output']['results'], 'ss100') dc.add_dataset(subsample_results[200]['output']['results'], 'ss200') # Generate Correspondence results for first (100) subsample points dataset # Correspondence data structure should be an object with the following attributes: local_align with d, p, and r arrays, mst with minimum spanning tree, and global_align with d, p, and r arrays ss_100_correspondence_res = Correspondence( meshes=dc.datasets['ss100'], initial_alignment=None, globalize=True, mirror=True) dc.add_analysis_set(ss_100_correspondence_res, 'ss100') # Generate Correspondence results for second (200) subsample points dataset # Correspondence here takes an optional initial alignment object with d, p, and r arrays ss_200_correspondence_res = Correspondence( # Correspondence should take an initial alignment object with d, p, and r arrays; also correspondence should handle bundling pairwise results into a single data structure meshes=dc.datasets['ss200'], initial_alignment=dc.analysis_sets['ss100'].global_align, globalize=True, mirror=True) dc.add_analysis_set(ss_200_correspondence_res, 'ss200') # Alternative test flow: Subsample one resolution at a time
A = np.array([[3, 1, 2], [10, 7, 2], [7, 3, 3], [18, 3, 0]])
B = np.array([[2, 3, 1], [2, 10, 7], [3, 7, 3], [0, 18, 3]])
class Pseudomesh:
def __init__(self, A):
self.vertices = A
T = Pseudomesh(A)
D = Pseudomesh(B)
mesh1 = T
mesh2 = D
a = [T, D]
BB = Correspondence.best_pairwise_PCA_alignment(mesh1, mesh2, 0)
AA = Correspondence.locgpd(mesh1, mesh2, 0, 0, 5, 0)
print(BB)
'''
In [36]: BB
Out[36]:
(array([0, 1, 2, 3]),
array([[ 1.38777878e-16, 1.00000000e+00, 2.49800181e-16],
[ -1.11022302e-16, -3.60822483e-16, 1.00000000e+00],
[ 1.00000000e+00, -1.38777878e-17, 1.66533454e-16]]))
'''
print(AA[1])
'''
Out[40]: