Revision as of 20:53, 22 November 2019 (view source) Ctsolakis (talk | contribs) (→‎OBS_ALU_Y50) ← Older edit		Revision as of 20:53, 22 November 2019 (view source) Ctsolakis (talk | contribs) (→‎OBS_ALU_Y50) Newer edit →
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	* Adapted  case:  1018  triangles		* Adapted  case:  1018  triangles
−	The 2D case created by extracting a 2D slice at Y=50 out of the 3D distribution 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

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Revision as of 20:53, 22 November 2019

2D Example Meshes

Synthetic Gaussian Data

• Input distribution size : 1,000,000 cells
• Uniform case: 30,949 triangles
• Adapted case: 3,788 triangles

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• 

Commands to generate meshes :

Uniform :

docker run -v $(pwd):/data/ cnf_tools tessellate2d  --input 2D_CASES/input/Gaussian2.vtk  --output 2D_CASES/output/Gaussian_me_10_uniform.vtk --uniform --min-edge=10

Adaptive :

docker run -v $(pwd):/data/ cnf_tools tessellate2d  --input 2D_CASES/input/Gaussian2.vtk  --output 2D_CASES/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 GPDGK16Numerical_140519

• Input distribution size : 10,000 cells
• Uniform case: 7587 triangles
• Adapted (min_edge = 2) case: 623 triangles
• Adapted (min_edge = 0.5) case: 1,409 triangles

• 
• 
• 

Commands to generate meshes :

Uniform :

docker run -v $(pwd):/data/ cnf_tools tessellate2d  --input 2D_CASES/input/GPDGK16Numerical_140519_X50.vtk --output 2D_CASES/output/GPDGK16Numerical_140519_me_2_uniform.vtk --min-edge=2 --uniform

Adaptive :(min_edge = 2)

docker run -v $(pwd):/data/ cnf_tools tessellate2d  --input 2D_CASES/input/GPDGK16Numerical_140519_X50.vtk --output 2D_CASES/output/GPDGK16Numerical_140519_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1

Adaptive :(min_edge = 0.5)

docker run -v $(pwd):/data/ cnf_tools tessellate2d  --input 2D_CASES/input/GPDGK16Numerical_140519_X50.vtk --output 2D_CASES/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 that the input pixels. Using values much smaller than 1 is not expected to help the discitization since we are esetially packing more element into a pixel which has constant value.

OBS_ALU_Y50

• Input distribution size : 10,000 cells
• Uniform case: 7587 triangles
• Adapted case: 1018 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 :

docker run -v $(pwd):/data/ cnf_tools tessellate2d  --input 2D_CASES/input/OBS_ALU_Y50.vtk --output 2D_CASES/output/OBS_ALU_Y50_me_2_uniform.vtk --min-edge=2 --uniform

Adaptive :

docker run -v $(pwd):/data/ cnf_tools tessellate2d  --input 2D_CASES/input/OBS_ALU_Y50.vtk --output 2D_CASES/output/OBS_ALU_Y50_me_2_wl_1e-1.vtk --min-edge=2 --weight-limit=0.1

3D Example Meshes

CFF_14052019

GPDGK16Numerical_140519: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_14052019/GPDGK16Numerical_140519.nrrd  --weight-limit 0.1 --min-edge 1 --output ./GPDGK16Numerical_140519,d=5,wl=0.1,me=1.vtk

GPDMMS13_140519: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_14052019/GPDMMS13_140519.nrrd  --weight-limit 0.05 --min-edge 1 --output ./GPDMMS13_140519,d=5,wl=0.05,me=1.vtk

GPDVGG99_140519: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_14052019/GPDVGG99_140519.nrrd  --weight-limit 0.05 --min-edge 1 --output ./GPDVGG99_140519,d=5,wl=0.05,me=1.vtk

NT_140519: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_14052019/NT_140519.nrrd  --weight-limit 0.07 --min-edge 1 --output ./NT_140519,d=5,wl=0.07,me=1.vtk

OBS_ALU_140519: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_14052019/OBS_ALU_140519.nrrd  --weight-limit 0.13 --min-edge 1 --output ./OBS_ALU_140519,d=5,wl=0.13,me=1.vtk

OBS_CS_140519: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_14052019/OBS_CS_140519.nrrd  --weight-limit 0.01 --min-edge 1 --output ./OBS_CS_140519,d=5,wl=0.01,me=1.vtk

CFF_DATA

cff_E.data_IM: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_DATA/cff_E.data_IM.nrrd  --weight-limit 0.01 --min-edge 1 --output ./cff_E.data_IM,d=10,wl=0.01,me=1.vtk

cff_E.data_REAL: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_DATA/cff_E.data_REAL.nrrd  --weight-limit 0.1 --min-edge 1 --output ./cff_E.data_REAL,d=10,wl=0.1,me=1.vtk

cff_H.data_IM: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_DATA/cff_H.data_IM.nrrd  --weight-limit 0.05 --min-edge 1 --output ./cff_H.data_IM,d=10,wl=0.05,me=1.vtk

cff_H.data_REAL: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_DATA/cff_H.data_REAL.nrrd  --weight-limit 0.1 --min-edge 1 --output ./cff_H.data_REAL,d=10,wl=0.1,me=1.vtk

cff_Ht.data_IM: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_DATA/cff_Ht.data_IM.nrrd  --weight-limit 0.1 --min-edge 1 --output ./cff_Ht.data_IM,d=10,wl=0.1,me=1.vtk

cff_Ht.data_REAL: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/CFF_DATA/cff_Ht.data_REAL.nrrd  --weight-limit 0.1 --min-edge 1 --output ./cff_Ht.data_REAL,d=10,wl=0.1,me=1.vtk

DATA_04252019

CFF_E_im: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/CFF_E_im.nrrd  --weight-limit 0.04 --min-edge 1 --output ./CFF_E_im,d=5,wl=0.04,me=1.vtk

CFF_E_re: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/CFF_E_re.nrrd  --weight-limit 0.08 --min-edge 1 --output ./CFF_E_re,d=5,wl=0.08,me=1.vtk

CFF_H_im: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/CFF_H_im.nrrd  --weight-limit 0.06 --min-edge 1 --output ./CFF_H_im,d=5,wl=0.06,me=1.vtk

CFF_H_re: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/CFF_H_re.nrrd  --weight-limit 0.13 --min-edge 1 --output ./CFF_H_re,d=5,wl=0.13,me=1.vtk

GPD_H_down: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/GPD_H_down.nrrd  --weight-limit 0.1 --min-edge 1 --output ./GPD_H_down,d=5,wl=0.1,me=1.vtk

GPD_H_up: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/GPD_H_up.nrrd  --weight-limit 0.1 --min-edge 1 --output ./GPD_H_up,d=5,wl=0.1,me=1.vtk

OBS_ALU: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/OBS_ALU.nrrd  --background-value 0 --weight-limit 0.07 --min-edge 1 --output ./OBS_ALU,d=5,bg=0,wl=0.07,me=1.vtk

OBS_ALU: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/DATA_04252019/OBS_ALU.nrrd --delta 2 --background-value 0 --uniform --output ./OBS_ALU,d=5,bg=0,uniform.vtk

phase_space_000

phase_space_000: Input Image Output Mesh

docker run -v $(pwd):/data/ cnf_tools tessellate3d --input ./CNF_SHARE/phase_space_000/phase_space_000.nrrd --delta 1.5 --weight-limit 0.005 --min-edge 1 --output ./phase_space_000,d=1.5,wl=0.005,me=1.vtk