Difference between revisions of "CNF Example Meshes"
From crtc.cs.odu.edu
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* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 30,949 triangles | * Uniform case: 30,949 triangles | ||
| − | * | + | * Adaptive case: 3,788 triangles |
<gallery mode="packed" heights=300px> | <gallery mode="packed" heights=300px> | ||
| Line 18: | Line 18: | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/Gaussian2.vtk --output Gaussian_me_10_uniform.vtk --uniform --min-edge=10 | docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/Gaussian2.vtk --output Gaussian_me_10_uniform.vtk --uniform --min-edge=10 | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/1omr8szilea3r6fde39w49gu7u5xyui8 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/Gaussian2.vtk --output Gaussian_me_10_wl_1e-1.vtk --weight-limit=0.05 --min-edge=10 | docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/Gaussian2.vtk --output Gaussian_me_10_wl_1e-1.vtk --weight-limit=0.05 --min-edge=10 | ||
| Line 28: | Line 28: | ||
* Input distribution size : 10,000 cells | * Input distribution size : 10,000 cells | ||
* Uniform case: 7,587 triangles | * Uniform case: 7,587 triangles | ||
| − | * | + | * Adaptive (min edge = 2) case: 623 triangles |
| − | * | + | * Adaptive (min edge = 0.5) case: 1,409 triangles |
| − | |||
<gallery mode="packed" heights=300px> | <gallery mode="packed" heights=300px> | ||
| Line 45: | Line 44: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive (min edge = 2):''' [https://odu.box.com/s/3yp9jod0hcjxipfu81ywk0jrxphonasa Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/GPDGK16Numerical_140519_X50.vtk --output GPDGK16Numerical_140519_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1 | docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/GPDGK16Numerical_140519_X50.vtk --output GPDGK16Numerical_140519_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1 | ||
| Line 51: | Line 50: | ||
| − | ''' | + | '''Adaptive (min edge = 0.5):''' [https://odu.box.com/s/7zuszll7jn8tt8bpge6vau2tkbatkihz Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/GPDGK16Numerical_140519_X50.vtk --output GPDGK16Numerical_140519_me_0.5_wl_1e-1.vtk --min-edge=0.5 --weight-limit=0.1 | docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/GPDGK16Numerical_140519_X50.vtk --output GPDGK16Numerical_140519_me_0.5_wl_1e-1.vtk --min-edge=0.5 --weight-limit=0.1 | ||
| Line 61: | Line 60: | ||
* Input distribution size : 10,000 cells | * Input distribution size : 10,000 cells | ||
* Uniform case: 7,587 triangles | * Uniform case: 7,587 triangles | ||
| − | * | + | * Adaptive case: 1,038 triangles |
The 2D case created by extracting a 2D slice at X=50 out of the 3D distribution (see 3D case below) NT_140519 | The 2D case created by extracting a 2D slice at X=50 out of the 3D distribution (see 3D case below) NT_140519 | ||
| Line 78: | Line 77: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/oytjqxeque11wvbxu62fhwc3830fbpcy Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/NT_140519_50_X.vtk --output NT_140519_X50_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1 | docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/NT_140519_50_X.vtk --output NT_140519_X50_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1 | ||
| Line 86: | Line 85: | ||
* Input distribution size : 10,000 cells | * Input distribution size : 10,000 cells | ||
* Uniform case: 7,587 triangles | * Uniform case: 7,587 triangles | ||
| − | * | + | * Adaptive case: 1,018 triangles |
The 2D case created by extracting a 2D slice at Y=50 out of the 3D distribution (see 3D case below) OBS_ALU | The 2D case created by extracting a 2D slice at Y=50 out of the 3D distribution (see 3D case below) OBS_ALU | ||
| Line 102: | Line 101: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/8369kd2q52weqp76811h6p54sax3nj37 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/OBS_ALU_Y50.vtk --output OBS_ALU_Y50_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1 | docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/OBS_ALU_Y50.vtk --output OBS_ALU_Y50_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1 | ||
| Line 113: | Line 112: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive (min edge = 1) case: 273,716 tetrahedra |
| − | * | + | * Adaptive (min edge = 2) case: 67,935 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 129: | Line 128: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive (min edge = 1):''' [https://odu.box.com/s/zvuuq7e6bx1cqxqbna5rpfnxfaqezgqa Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-adaptive --output ./GPDGK16Numerical_140519,d=5,wl=0.1,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-adaptive --output ./GPDGK16Numerical_140519,d=5,wl=0.1,me=1.vtk | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive (min edge = 2):''' [https://odu.box.com/s/ddyvbwcdqykta5b1nxi3gwxjzgdzz8yk Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-adaptive --min-edge 2 --output ./GPDGK16Numerical_140519,d=5,wl=0.1,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-adaptive --min-edge 2 --output ./GPDGK16Numerical_140519,d=5,wl=0.1,me=2.vtk | ||
| Line 142: | Line 141: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 264,762 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 156: | Line 155: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/bcg7aw4lv9rvp4531va7pqg7j2os7tny Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDMMS13_140519.nrrd --cnf-adaptive --weight-limit 0.05 --output ./GPDMMS13_140519,d=5,wl=0.05,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDMMS13_140519.nrrd --cnf-adaptive --weight-limit 0.05 --output ./GPDMMS13_140519,d=5,wl=0.05,me=1.vtk | ||
| Line 164: | Line 163: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 261,485 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 178: | Line 177: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/51rvexl5t83zr4svn2xuw221v16jmtph Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDVGG99_140519.nrrd --cnf-adaptive --weight-limit 0.05 --output ./GPDVGG99_140519,d=5,wl=0.05,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDVGG99_140519.nrrd --cnf-adaptive --weight-limit 0.05 --output ./GPDVGG99_140519,d=5,wl=0.05,me=1.vtk | ||
| Line 186: | Line 185: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive (min edge = 1) case: 253,965 tetrahedra |
| − | * | + | * Adaptive (min edge = 2) case: 120,168 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 202: | Line 201: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive (min edge = 1):''' [https://odu.box.com/s/1gviwtmh053fzqixo4thaueshjhgqdnq Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/NT_140519.nrrd --cnf-adaptive --weight-limit 0.07 --output ./NT_140519,d=5,wl=0.07,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/NT_140519.nrrd --cnf-adaptive --weight-limit 0.07 --output ./NT_140519,d=5,wl=0.07,me=1.vtk | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive (min edge = 2):''' [https://odu.box.com/s/ddllau93m3itsax55pcb9ifhljp7bd3u Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/NT_140519.nrrd --cnf-adaptive --weight-limit 0.07 --min-edge 2 --output ./NT_140519,d=5,wl=0.07,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/NT_140519.nrrd --cnf-adaptive --weight-limit 0.07 --min-edge 2 --output ./NT_140519,d=5,wl=0.07,me=2.vtk | ||
| Line 215: | Line 214: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 259,269 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 229: | Line 228: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/gei8k0bjh7k090vr568xo30fulslnpi5 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_ALU_140519.nrrd --cnf-adaptive --weight-limit 0.13 --output ./OBS_ALU_140519,d=5,wl=0.13,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_ALU_140519.nrrd --cnf-adaptive --weight-limit 0.13 --output ./OBS_ALU_140519,d=5,wl=0.13,me=1.vtk | ||
| Line 237: | Line 236: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 25,168 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 251: | Line 250: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/j9zpcjp6fchtr82r6xk0dynf0qfkgi4d Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_CS_140519.nrrd --cnf-adaptive --weight-limit 0.01 --output ./OBS_CS_140519,d=5,wl=0.01,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_CS_140519.nrrd --cnf-adaptive --weight-limit 0.01 --output ./OBS_CS_140519,d=5,wl=0.01,me=1.vtk | ||
| Line 260: | Line 259: | ||
* Input distribution size : 8,000,000 cells | * Input distribution size : 8,000,000 cells | ||
* Uniform case: 745,291 tetrahedra | * Uniform case: 745,291 tetrahedra | ||
| − | * | + | * Adaptive case: 358,637 tetrahedra |
| − | * | + | * Adaptive case: 358,637 tetrahedra (other side of the same adaptive case) |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 276: | Line 275: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/byo618ec2140sh6jopidyy1358nmk7ch Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_IM.nrrd --cnf-adaptive --weight-limit 0.01 --output ./cff_E.data_IM,d=10,wl=0.01,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_IM.nrrd --cnf-adaptive --weight-limit 0.01 --output ./cff_E.data_IM,d=10,wl=0.01,me=2.vtk | ||
| Line 284: | Line 283: | ||
* Input distribution size : 8,000,000 cells | * Input distribution size : 8,000,000 cells | ||
* Uniform case: 745,291 tetrahedra | * Uniform case: 745,291 tetrahedra | ||
| − | * | + | * Adaptive case: 314,990 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 298: | Line 297: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/m7kn4kcmatmx86mofb06f37j8kkc35e4 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_REAL.nrrd --cnf-adaptive --output ./cff_E.data_REAL,d=10,wl=0.1,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_REAL.nrrd --cnf-adaptive --output ./cff_E.data_REAL,d=10,wl=0.1,me=2.vtk | ||
| Line 306: | Line 305: | ||
* Input distribution size : 8,000,000 cells | * Input distribution size : 8,000,000 cells | ||
* Uniform case: 745,291 tetrahedra | * Uniform case: 745,291 tetrahedra | ||
| − | * | + | * Adaptive case: 289,855 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 320: | Line 319: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/ilbviax5y7vrji1anf3a4g8nd8v1wbdw Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_IM.nrrd --cnf-adaptive --weight-limit 0.05 --output ./cff_H.data_IM,d=10,wl=0.05,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_IM.nrrd --cnf-adaptive --weight-limit 0.05 --output ./cff_H.data_IM,d=10,wl=0.05,me=2.vtk | ||
| Line 328: | Line 327: | ||
* Input distribution size : 8,000,000 cells | * Input distribution size : 8,000,000 cells | ||
* Uniform case: 745,291 tetrahedra | * Uniform case: 745,291 tetrahedra | ||
| − | * | + | * Adaptive case: 372,016 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 342: | Line 341: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/3ww0semcpqqd36xk9eysczxzajwz56uu Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_REAL.nrrd --cnf-adaptive --output ./cff_H.data_REAL,d=10,wl=0.1,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_REAL.nrrd --cnf-adaptive --output ./cff_H.data_REAL,d=10,wl=0.1,me=2.vtk | ||
| Line 350: | Line 349: | ||
* Input distribution size : 8,000,000 cells | * Input distribution size : 8,000,000 cells | ||
* Uniform case: 745,291 tetrahedra | * Uniform case: 745,291 tetrahedra | ||
| − | * | + | * Adaptive case: 337,772 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 364: | Line 363: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/2g7n0thzu4uov8zhskykct9kohosqtzm Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_IM.nrrd --cnf-adaptive --output ./cff_Ht.data_IM,d=10,wl=0.1,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_IM.nrrd --cnf-adaptive --output ./cff_Ht.data_IM,d=10,wl=0.1,me=2.vtk | ||
| Line 372: | Line 371: | ||
* Input distribution size : 8,000,000 cells | * Input distribution size : 8,000,000 cells | ||
* Uniform case: 745,291 tetrahedra | * Uniform case: 745,291 tetrahedra | ||
| − | * | + | * Adaptive case: 394,632 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 386: | Line 385: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/laao7ehbda56xyrm17jfn9xw2sz407qi Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_REAL.nrrd --cnf-adaptive --output ./cff_Ht.data_REAL,d=10,wl=0.1,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_REAL.nrrd --cnf-adaptive --output ./cff_Ht.data_REAL,d=10,wl=0.1,me=2.vtk | ||
| Line 395: | Line 394: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 236,512 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 409: | Line 408: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/62hvu23fevbylbn8htm2os70adamxl3d Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_im.nrrd --cnf-adaptive --weight-limit 0.04 --output ./CFF_E_im,d=5,wl=0.04,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_im.nrrd --cnf-adaptive --weight-limit 0.04 --output ./CFF_E_im,d=5,wl=0.04,me=1.vtk | ||
| Line 417: | Line 416: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 260,349 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 431: | Line 430: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/294puxiw7kg9ykeaanuojx7ha071ibn6 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_re.nrrd --cnf-adaptive --weight-limit 0.08 --output ./CFF_E_re,d=5,wl=0.08,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_re.nrrd --cnf-adaptive --weight-limit 0.08 --output ./CFF_E_re,d=5,wl=0.08,me=1.vtk | ||
| Line 439: | Line 438: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 263,040 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 453: | Line 452: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/6b8in611r4b0i345ymvpynif45j0pnt2 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_im.nrrd --cnf-adaptive --weight-limit 0.06 --output ./CFF_H_im,d=5,wl=0.06,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_im.nrrd --cnf-adaptive --weight-limit 0.06 --output ./CFF_H_im,d=5,wl=0.06,me=1.vtk | ||
| Line 461: | Line 460: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 249,257 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 475: | Line 474: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/40loorarxv19xn40qsvlo56hwpaac2xu Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_re.nrrd --cnf-adaptive --weight-limit 0.13 --output ./CFF_H_re,d=5,wl=0.13,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_re.nrrd --cnf-adaptive --weight-limit 0.13 --output ./CFF_H_re,d=5,wl=0.13,me=1.vtk | ||
| Line 483: | Line 482: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 300,117 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 497: | Line 496: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/peljqrn1v8gf9mco4qrly85guxhyef0l Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_down.nrrd --cnf-adaptive --output ./GPD_H_down,d=5,wl=0.1,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_down.nrrd --cnf-adaptive --output ./GPD_H_down,d=5,wl=0.1,me=1.vtk | ||
| Line 505: | Line 504: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 768,033 tetrahedra | * Uniform case: 768,033 tetrahedra | ||
| − | * | + | * Adaptive case: 295,671 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 519: | Line 518: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :'''[https://odu.box.com/s/nxrn5xnia27kd4b0kyditafd86atix7b Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_up.nrrd --cnf-adaptive --output ./GPD_H_up,d=5,wl=0.1,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_up.nrrd --cnf-adaptive --output ./GPD_H_up,d=5,wl=0.1,me=1.vtk | ||
| Line 527: | Line 526: | ||
* Input distribution size : 1,000,000 cells | * Input distribution size : 1,000,000 cells | ||
* Uniform case: 301,772 tetrahedra | * Uniform case: 301,772 tetrahedra | ||
| − | * | + | * Adaptive case: 279,721 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 541: | Line 540: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/sprttnvtuz5imm3cdrdd34cuasifv4n0 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/OBS_ALU.nrrd --cnf-adaptive --background-value 0 --weight-limit 0.07 --output ./OBS_ALU,d=5,bv=0,wl=0.07,me=1.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/OBS_ALU.nrrd --cnf-adaptive --background-value 0 --weight-limit 0.07 --output ./OBS_ALU,d=5,bv=0,wl=0.07,me=1.vtk | ||
| Line 550: | Line 549: | ||
* Input distribution size : 15,625 cells | * Input distribution size : 15,625 cells | ||
* Uniform case: 17,961 tetrahedra | * Uniform case: 17,961 tetrahedra | ||
| − | * | + | * Adaptive case: 10,593 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 564: | Line 563: | ||
</pre> | </pre> | ||
| − | ''' | + | '''Adaptive :''' [https://odu.box.com/s/9k8b3wv9ejkvpf5b7xcbb2lc85zrz3b6 Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/phase_space_000/phase_space_000.nrrd --delta 2 --cnf-adaptive --weight-limit 0.004 --min-edge 2 --output ./phase_space_000,d=2,wl=0.004,me=2.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/phase_space_000/phase_space_000.nrrd --delta 2 --cnf-adaptive --weight-limit 0.004 --min-edge 2 --output ./phase_space_000,d=2,wl=0.004,me=2.vtk | ||
</pre> | </pre> | ||
Revision as of 15:56, 2 March 2020
Contents
2D Example Meshes
The directory containing the 2D input data is located in the 2D folder of CNF_Data.
Synthetic Gaussian Data
- Input distribution size : 1,000,000 cells
- Uniform case: 30,949 triangles
- Adaptive case: 3,788 triangles
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/Gaussian2.vtk --output Gaussian_me_10_uniform.vtk --uniform --min-edge=10
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/Gaussian2.vtk --output Gaussian_me_10_wl_1e-1.vtk --weight-limit=0.05 --min-edge=10
GPDGK16Numerical_140519
The 2D case created by extracting a 2D slice at X=50 out of the 3D distribution (see 3D case below) GPDGK16Numerical_140519
- Input distribution size : 10,000 cells
- Uniform case: 7,587 triangles
- Adaptive (min edge = 2) case: 623 triangles
- Adaptive (min edge = 0.5) case: 1,409 triangles
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/GPDGK16Numerical_140519_X50.vtk --output GPDGK16Numerical_140519_me_2_uniform.vtk --min-edge=2 --uniform
Adaptive (min edge = 2): Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/GPDGK16Numerical_140519_X50.vtk --output GPDGK16Numerical_140519_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1
Adaptive (min edge = 0.5): Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/GPDGK16Numerical_140519_X50.vtk --output GPDGK16Numerical_140519_me_0.5_wl_1e-1.vtk --min-edge=0.5 --weight-limit=0.1
Note: By using min-edge less than 1 we are essentially generating triangles with an edge smaller than the input pixels. Using values much smaller than 1 is not expected to help the discretization since we are essentially packing more element into a pixel which has a constant value.
NT_140519
- Input distribution size : 10,000 cells
- Uniform case: 7,587 triangles
- Adaptive case: 1,038 triangles
The 2D case created by extracting a 2D slice at X=50 out of the 3D distribution (see 3D case below) NT_140519
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/NT_140519_50_X.vtk --output NT_140519_X50_me_2_uniform.vtk --min-edge=2 --uniform
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/NT_140519_50_X.vtk --output NT_140519_X50_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1
OBS_ALU_Y50
- Input distribution size : 10,000 cells
- Uniform case: 7,587 triangles
- Adaptive case: 1,018 triangles
The 2D case created by extracting a 2D slice at Y=50 out of the 3D distribution (see 3D case below) OBS_ALU
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/OBS_ALU_Y50.vtk --output OBS_ALU_Y50_me_2_uniform.vtk --min-edge=2 --uniform
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate2d --input ./CNF_Data/2D/OBS_ALU_Y50.vtk --output OBS_ALU_Y50_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1
3D Example Meshes
The directory containing the 3D input data is located in the 3D folder of CNF_Data.
CFF_14052019
GPDGK16Numerical_140519
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive (min edge = 1) case: 273,716 tetrahedra
- Adaptive (min edge = 2) case: 67,935 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d -i ../../Data/3D/CNF_SHARE/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-uniform --output ./GPDGK16Numerical_140519,d=1,uniform.vtk
Adaptive (min edge = 1): Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-adaptive --output ./GPDGK16Numerical_140519,d=5,wl=0.1,me=1.vtk
Adaptive (min edge = 2): Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-adaptive --min-edge 2 --output ./GPDGK16Numerical_140519,d=5,wl=0.1,me=2.vtk
GPDMMS13_140519
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 264,762 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDMMS13_140519.nrrd --cnf-uniform --output ./GPDMMS13_140519,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDMMS13_140519.nrrd --cnf-adaptive --weight-limit 0.05 --output ./GPDMMS13_140519,d=5,wl=0.05,me=1.vtk
GPDVGG99_140519
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 261,485 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDVGG99_140519.nrrd --cnf-uniform --output ./GPDVGG99_140519,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDVGG99_140519.nrrd --cnf-adaptive --weight-limit 0.05 --output ./GPDVGG99_140519,d=5,wl=0.05,me=1.vtk
NT_140519
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive (min edge = 1) case: 253,965 tetrahedra
- Adaptive (min edge = 2) case: 120,168 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/NT_140519.nrrd --cnf-uniform --output ./NT_140519,d=1,uniform.vtk
Adaptive (min edge = 1): Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/NT_140519.nrrd --cnf-adaptive --weight-limit 0.07 --output ./NT_140519,d=5,wl=0.07,me=1.vtk
Adaptive (min edge = 2): Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/NT_140519.nrrd --cnf-adaptive --weight-limit 0.07 --min-edge 2 --output ./NT_140519,d=5,wl=0.07,me=2.vtk
OBS_ALU_140519
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 259,269 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_ALU_140519.nrrd --cnf-uniform --output ./OBS_ALU_140519,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_ALU_140519.nrrd --cnf-adaptive --weight-limit 0.13 --output ./OBS_ALU_140519,d=5,wl=0.13,me=1.vtk
OBS_CS_140519
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 25,168 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_CS_140519.nrrd --cnf-uniform --output ./OBS_CS_140519,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/OBS_CS_140519.nrrd --cnf-adaptive --weight-limit 0.01 --output ./OBS_CS_140519,d=5,wl=0.01,me=1.vtk
CFF_DATA
cff_E.data_IM
- Input distribution size : 8,000,000 cells
- Uniform case: 745,291 tetrahedra
- Adaptive case: 358,637 tetrahedra
- Adaptive case: 358,637 tetrahedra (other side of the same adaptive case)
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_IM.nrrd --cnf-uniform --output ./cff_E.data_IM,d=2,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_IM.nrrd --cnf-adaptive --weight-limit 0.01 --output ./cff_E.data_IM,d=10,wl=0.01,me=2.vtk
cff_E.data_REAL
- Input distribution size : 8,000,000 cells
- Uniform case: 745,291 tetrahedra
- Adaptive case: 314,990 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_REAL.nrrd --cnf-uniform --output ./cff_E.data_REAL,d=2,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_E.data_REAL.nrrd --cnf-adaptive --output ./cff_E.data_REAL,d=10,wl=0.1,me=2.vtk
cff_H.data_IM
- Input distribution size : 8,000,000 cells
- Uniform case: 745,291 tetrahedra
- Adaptive case: 289,855 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_IM.nrrd --cnf-uniform --output ./cff_H.data_IM,d=2,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_IM.nrrd --cnf-adaptive --weight-limit 0.05 --output ./cff_H.data_IM,d=10,wl=0.05,me=2.vtk
cff_H.data_REAL
- Input distribution size : 8,000,000 cells
- Uniform case: 745,291 tetrahedra
- Adaptive case: 372,016 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_REAL.nrrd --cnf-uniform --output ./cff_H.data_REAL,d=2,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_H.data_REAL.nrrd --cnf-adaptive --output ./cff_H.data_REAL,d=10,wl=0.1,me=2.vtk
cff_Ht.data_IM
- Input distribution size : 8,000,000 cells
- Uniform case: 745,291 tetrahedra
- Adaptive case: 337,772 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_IM.nrrd --cnf-uniform --output ./cff_Ht.data_IM,d=2,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_IM.nrrd --cnf-adaptive --output ./cff_Ht.data_IM,d=10,wl=0.1,me=2.vtk
cff_Ht.data_REAL
- Input distribution size : 8,000,000 cells
- Uniform case: 745,291 tetrahedra
- Adaptive case: 394,632 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_REAL.nrrd --cnf-uniform --output ./cff_Ht.data_REAL,d=2,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_DATA/cff_Ht.data_REAL.nrrd --cnf-adaptive --output ./cff_Ht.data_REAL,d=10,wl=0.1,me=2.vtk
DATA_04252019
CFF_E_im
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 236,512 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_im.nrrd --cnf-uniform --output ./CFF_E_im,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_im.nrrd --cnf-adaptive --weight-limit 0.04 --output ./CFF_E_im,d=5,wl=0.04,me=1.vtk
CFF_E_re
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 260,349 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_re.nrrd --cnf-uniform --output ./CFF_E_re,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_E_re.nrrd --cnf-adaptive --weight-limit 0.08 --output ./CFF_E_re,d=5,wl=0.08,me=1.vtk
CFF_H_im
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 263,040 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_im.nrrd --cnf-uniform --output ./CFF_H_im,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_im.nrrd --cnf-adaptive --weight-limit 0.06 --output ./CFF_H_im,d=5,wl=0.06,me=1.vtk
CFF_H_re
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 249,257 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_re.nrrd --cnf-uniform --output ./CFF_H_re,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/CFF_H_re.nrrd --cnf-adaptive --weight-limit 0.13 --output ./CFF_H_re,d=5,wl=0.13,me=1.vtk
GPD_H_down
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 300,117 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_down.nrrd --cnf-uniform --output ./GPD_H_down,d=1,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_down.nrrd --cnf-adaptive --output ./GPD_H_down,d=5,wl=0.1,me=1.vtk
GPD_H_up
- Input distribution size : 1,000,000 cells
- Uniform case: 768,033 tetrahedra
- Adaptive case: 295,671 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_up.nrrd --cnf-uniform --output ./GPD_H_up,d=1,uniform.vtk
Adaptive :Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/GPD_H_up.nrrd --cnf-adaptive --output ./GPD_H_up,d=5,wl=0.1,me=1.vtk
OBS_ALU
- Input distribution size : 1,000,000 cells
- Uniform case: 301,772 tetrahedra
- Adaptive case: 279,721 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/OBS_ALU.nrrd --cnf-uniform --background-value 0 --output ./OBS_ALU,d=1,bv=0,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/DATA_04252019/OBS_ALU.nrrd --cnf-adaptive --background-value 0 --weight-limit 0.07 --output ./OBS_ALU,d=5,bv=0,wl=0.07,me=1.vtk
phase_space_000
phase_space_000
- Input distribution size : 15,625 cells
- Uniform case: 17,961 tetrahedra
- Adaptive case: 10,593 tetrahedra
Commands to generate meshes :
Uniform : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/phase_space_000/phase_space_000.nrrd --delta 0.25 --cnf-uniform --output ./phase_space_000,d=0.25,uniform.vtk
Adaptive : Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/phase_space_000/phase_space_000.nrrd --delta 2 --cnf-adaptive --weight-limit 0.004 --min-edge 2 --output ./phase_space_000,d=2,wl=0.004,me=2.vtk
