Docker container for meshalyzer.
The purpose of the program is to quickly analyze and report on both general characteristics and four topological attributes of meshes. Running meshalyzer on a mesh file will provide enough information in a single report to determine if the mesh will fail as input to any of the manipulation processes described in this project.
The Docker image can be found here.
To pull the image from Dockerhub
docker pull icaoberg/meshalyzer
docker run -i -t icaoberg/meshalyzer -help
docker run -v /Users/icaoberg/code/docker-meshalyzer/mesh_tools/meshalyzer/examples/example0.mesh:/home/murphylab/example0.mesh -t icaoberg/meshalyzer example0.mesh
MESH FILE INTEGRITY
# orphan vertices: none
# missing vertices: none
# degenerate faces: none
# duplicate vertex indices: none
# duplicate face indices: none
contiguous vertex indexing from 1: no
contiguous vertex indexing from 1: bad index and +/- 2
contiguous vertex indexing from 1: NA NA 2 3 4
contiguous face indexing from 1: yes
MESH ATTRIBUTES
mesh is closed: yes
mesh is manifold: yes
mesh has consistently oriented face normals: yes
mesh has outward oriented face normals: yes
MESH CHARACTERISTICS
# vertices: 5400
# faces: 10796
# edges: 16194
# components: 1
# boundaries: none
# indistinguishable vertices: none
object area: [(data units)^2]
object area: 5.65393e+06
object volume: [(data units)^3]
object volume: 3.23708e+08
object genus: 0
bounding box: [data units]
bounding box: [xmin,ymin,zmin][xmax,ymax,zmax]
bounding box: [5177.54,1860.61,5282.46][6445.44,7514.34,6767.43]
# edges with indistinguishable vertices: none
# intersecting faces: none
Vertex adjacent face statistics [faces]:
min 4
max 10
median 6
mean 5.99778
variance 0.918684
Vertex adjacent face histogram [faces]:
0 - 0 : 0 | 8 - 8 : 273
1 - 1 : 0 | 9 - 9 : 35
2 - 2 : 0 | 10 - 10 : 6
3 - 3 : 0 | 11 - 11 : 0
4 - 4 : 174 | 12 - 12 : 0
5 - 5 : 1550 | 13 - 13 : 0
6 - 6 : 2151 | 14 - 14 : 0
7 - 7 : 1211 | 15 - 15 : 0
Face area statistics [(data units)^2]:
min 263.671
max 1514.96
median 498.289
mean 523.706
variance 19306.4
Face area histogram [(data units)^2]:
0 - 0 : 0 | 486.7 - 523.7 : 1200
0 - 264.3 : 1 | 523.7 - 560.8 : 1084
264.3 - 301.4 : 51 | 560.8 - 597.8 : 844
301.4 - 338.4 : 344 | 597.8 - 634.9 : 663
338.4 - 375.5 : 773 | 634.9 - 671.9 : 561
375.5 - 412.5 : 1171 | 671.9 - 709 : 382
412.5 - 449.6 : 1316 | 709 - 746 : 307
449.6 - 486.7 : 1332 | 746 - 1515 : 767
Face aspect ratio statistics [unitless]:
min 1.15902
max 9.02351
median 1.64641
mean 1.7489
variance 0.211206
Face aspect ratio histogram [unitless]:
1.155 - 1.5 : 3482 | 15 - 25 : 0
1.5 - 2 : 5075 | 25 - 50 : 0
2 - 2.5 : 1587 | 50 - 100 : 0
2.5 - 3 : 457 | 100 - 300 : 0
3 - 4 : 160 | 300 - 1000 : 0
4 - 6 : 27 | 1000 - 10000 : 0
6 - 10 : 8 | 10000 - 100000 : 0
10 - 15 : 0 | 100000 - : 0
(Aspect ratio is longest edge divided by shortest altitude)
Edge length statistics [data units]:
min 21.4836
max 94.4644
median 35.1986
mean 36.0494
variance 59.3395
Edge length histogram [data units]:
0 - 0 : 0 | 34 - 36.05 : 1705
0 - 21.67 : 3 | 36.05 - 38.1 : 1636
21.67 - 23.72 : 181 | 38.1 - 40.16 : 1408
23.72 - 25.78 : 833 | 40.16 - 42.21 : 1148
25.78 - 27.83 : 1223 | 42.21 - 44.27 : 956
27.83 - 29.89 : 1504 | 44.27 - 46.32 : 692
29.89 - 31.94 : 1609 | 46.32 - 48.37 : 507
31.94 - 34 : 1749 | 48.37 - 94.46 : 1040
Edge angle statistics [degress]:
min 93.215
max 313.614
median 180
mean 181.402
variance 116.359
Edge angle histogram [degress]:
0 - 0 : 0 | 178.5 - 181.4 : 8854
0 - 161.3 : 399 | 181.4 - 184.3 : 954
161.3 - 164.1 : 162 | 184.3 - 187.2 : 766
164.1 - 167 : 222 | 187.2 - 190 : 577
167 - 169.9 : 318 | 190 - 192.9 : 479
169.9 - 172.8 : 427 | 192.9 - 195.8 : 304
172.8 - 175.6 : 661 | 195.8 - 198.7 : 284
175.6 - 178.5 : 901 | 198.7 - 313.6 : 886
Support for CellOrganizer has been provided by grants GM075205, GM090033 and GM103712 from the National Institute of General Medical Sciences, grants MCB1121919 and MCB1121793 from the U.S. National Science Foundation, by a Forschungspreis from the Alexander von Humboldt Foundation, and by the Freiburg Institute for Advanced Studies.
Copyright © 2007-2019 by the Murphy Lab at the Computational Biology Department in Carnegie Mellon University