Difference between revisions of "CNF Example Meshes"

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(3D Example Meshes)
(3D Example Meshes)
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'''Adapted (min edge = 1):''' [https://odu.box.com/s/zvuuq7e6bx1cqxqbna5rpfnxfaqezgqa Output Mesh]
 
'''Adapted (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 --weight-limit 0.1 --min-edge 1 --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>
  
 
'''Adapted (min edge = 2):''' [https://odu.box.com/s/ddyvbwcdqykta5b1nxi3gwxjzgdzz8yk Output Mesh]
 
'''Adapted (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 --weight-limit 0.1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/bcg7aw4lv9rvp4531va7pqg7j2os7tny Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/51rvexl5t83zr4svn2xuw221v16jmtph Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted (min edge = 1):''' [https://odu.box.com/s/1gviwtmh053fzqixo4thaueshjhgqdnq Output Mesh]
 
'''Adapted (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 --min-edge 1 --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>
  
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'''Adapted :''' [https://odu.box.com/s/gei8k0bjh7k090vr568xo30fulslnpi5 Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/j9zpcjp6fchtr82r6xk0dynf0qfkgi4d Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/knigkgmlzgrgov6no8j6b7qnsykkphr1 Output Mesh]
 
'''Adapted :''' [https://odu.box.com/s/knigkgmlzgrgov6no8j6b7qnsykkphr1 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 --weight-limit 0.1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/y90lrcbd2qtdjrc73tpqkn7rpissws9a Output Mesh]
 
'''Adapted :''' [https://odu.box.com/s/y90lrcbd2qtdjrc73tpqkn7rpissws9a 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 --weight-limit 0.1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/lvg21o3d1bviuuknhhfuzl30csq90a5e Output Mesh]
 
'''Adapted :''' [https://odu.box.com/s/lvg21o3d1bviuuknhhfuzl30csq90a5e 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 --weight-limit 0.1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/obz3uae6y392qlxqcrf5afgobrvibuew Output Mesh]
 
'''Adapted :''' [https://odu.box.com/s/obz3uae6y392qlxqcrf5afgobrvibuew 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 --weight-limit 0.1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/62hvu23fevbylbn8htm2os70adamxl3d Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/294puxiw7kg9ykeaanuojx7ha071ibn6 Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/6b8in611r4b0i345ymvpynif45j0pnt2 Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/40loorarxv19xn40qsvlo56hwpaac2xu Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
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'''Adapted :''' [https://odu.box.com/s/peljqrn1v8gf9mco4qrly85guxhyef0l Output Mesh]
 
'''Adapted :''' [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 --weight-limit 0.1 --min-edge 1 --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
 
</pre>
 
</pre>
  
Line 521: Line 521:
 
'''Adapted :'''[https://odu.box.com/s/nxrn5xnia27kd4b0kyditafd86atix7b Output Mesh]
 
'''Adapted :'''[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 --weight-limit 0.1 --min-edge 1 --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
 
</pre>
 
</pre>
  
Line 543: Line 543:
 
'''Adapted :''' [https://odu.box.com/s/sprttnvtuz5imm3cdrdd34cuasifv4n0 Output Mesh]
 
'''Adapted :''' [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 --min-edge 1 --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
 
</pre>
 
</pre>
  
Line 566: Line 566:
 
'''Adapted :''' [https://odu.box.com/s/bm23n0nb7cmvphayj2mivby628sqwzm6 Output Mesh]
 
'''Adapted :''' [https://odu.box.com/s/bm23n0nb7cmvphayj2mivby628sqwzm6 Output Mesh]
 
<pre>
 
<pre>
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/phase_space_000/phase_space_000.nrrd --delta 1.5 --cnf-adaptive --weight-limit 0.004 --min-edge 1 --output ./phase_space_000,d=1.5,bv=0,wl=0.004,me=1.vtk
+
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/phase_space_000/phase_space_000.nrrd --delta 1.5 --cnf-adaptive --weight-limit 0.004 --output ./phase_space_000,d=1.5,bv=0,wl=0.004,me=1.vtk
 
</pre>
 
</pre>

Revision as of 16:48, 27 February 2020

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
  • Adapted 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

Adapted : 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
  • Adapted (min edge = 2) case: 623 triangles
  • Adapted (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

Adapted (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


Adapted (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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted (min edge = 1) case: 273,716 tetrahedra
  • Adapted (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

Adapted (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

Adapted (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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted (min edge = 1) case: 253,965 tetrahedra
  • Adapted (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

Adapted (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

Adapted (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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted case: 358,637 tetrahedra
  • Adapted case: 358,637 tetrahedra (other side of the same adapted case)

cff_E.data_IM,d=10,wl=0.01,me=2.png cff_E.data_IM,d=10,wl=0.01,me=2,OtherSide.png

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

Adapted : 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
  • Adapted case: 1,433,247 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

Adapted : 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
  • Adapted case: 1,379,521 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

Adapted : 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
  • Adapted case: 1,699,757 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

Adapted : 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
  • Adapted case: 1,594,872 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

Adapted : 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
  • Adapted case: 1,821,299 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted : 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
  • Adapted 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

Adapted :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
  • Adapted 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

Adapted : 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: 26,410 tetrahedra
  • Adapted case: 21,392 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 0.5 --cnf-uniform --output ./phase_space_000,d=0.5,bv=0,uniform.vtk

Adapted : Output Mesh

docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/phase_space_000/phase_space_000.nrrd --delta 1.5 --cnf-adaptive --weight-limit 0.004 --output ./phase_space_000,d=1.5,bv=0,wl=0.004,me=1.vtk