Difference between revisions of "CNF Example Meshes"
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The directory containing the 2D input data is located in the 2D folder of [https://odu.box.com/s/wd0i18giti2zo330y19xhkqu8wjzgf7j CNF_Data]. | The directory containing the 2D input data is located in the 2D folder of [https://odu.box.com/s/wd0i18giti2zo330y19xhkqu8wjzgf7j CNF_Data]. | ||
== Synthetic Gaussian Data == | == Synthetic Gaussian Data == | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 30,949 triangles |
| − | * Adaptive | + | * Adaptive: 3,788 triangles |
<gallery mode="packed" heights=300px> | <gallery mode="packed" heights=300px> | ||
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Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/2ktd6ecfueq4zmbjzmpgujf3sxfucp5j Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/2ktd6ecfueq4zmbjzmpgujf3sxfucp5j Output Mesh] |
<pre> | <pre> | ||
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] | + | '''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 | ||
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The 2D case created by extracting a 2D slice at X=50 out of the 3D distribution (see 3D case below) 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 | + | * Input distribution size: 10,000 cells |
| − | * Uniform | + | * Uniform: 7,587 triangles |
| − | * Adaptive (min edge = 2) | + | * Adaptive (min edge = 2): 623 triangles |
| − | * Adaptive (min edge = 0.5) | + | * Adaptive (min edge = 0.5): 1,409 triangles |
<gallery mode="packed" heights=300px> | <gallery mode="packed" heights=300px> | ||
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Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/jgqtydxkdf33iji5c125j70xx5mvi7n6 Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/jgqtydxkdf33iji5c125j70xx5mvi7n6 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_uniform.vtk --min-edge=2 --uniform | 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 | ||
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== NT_140519 == | == NT_140519 == | ||
| − | * Input distribution size : 10,000 cells | + | * Input distribution size: 10,000 cells |
| − | * Uniform | + | * Uniform: 7,587 triangles |
| − | * Adaptive | + | * Adaptive: 1,038 triangles |
| − | The 2D | + | The 2D image was created by extracting a 2D slice at X=50 out of the 3D distribution (see 3D case below) NT_140519 |
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Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/87wruxwbks5k9q5wst9d7rx6z4eycwyz Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/87wruxwbks5k9q5wst9d7rx6z4eycwyz 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_uniform.vtk --min-edge=2 --uniform | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/oytjqxeque11wvbxu62fhwc3830fbpcy Output Mesh] | + | '''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 | ||
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== OBS_ALU_Y50 == | == OBS_ALU_Y50 == | ||
| − | * Input distribution size : 10,000 cells | + | * Input distribution size: 10,000 cells |
| − | * Uniform | + | * Uniform: 7,587 triangles |
| − | * Adaptive | + | * Adaptive: 1,018 triangles |
| − | The 2D | + | The 2D image was created by extracting a 2D slice at Y=50 out of the 3D distribution (see 3D case below) OBS_ALU |
<gallery mode="packed" heights=300px> | <gallery mode="packed" heights=300px> | ||
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Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/irrcuttg0ceogzgnn4x86mgf9eskk1wg Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/irrcuttg0ceogzgnn4x86mgf9eskk1wg 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_uniform.vtk --min-edge=2 --uniform | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/8369kd2q52weqp76811h6p54sax3nj37 Output Mesh] | + | '''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 | ||
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==CFF_14052019== | ==CFF_14052019== | ||
===GPDGK16Numerical_140519=== | ===GPDGK16Numerical_140519=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive (min edge = 1) | + | * Adaptive (min edge = 1): 273,716 tetrahedra |
| − | * Adaptive (min edge = 2) | + | * Adaptive (min edge = 2): 67,935 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 123: | Line 123: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/s26icsaf9dkvm3b6wmwbflpleqrar3qo Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/s26icsaf9dkvm3b6wmwbflpleqrar3qo Output Mesh] |
<pre> | <pre> | ||
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-uniform --output ./GPDGK16Numerical_140519,d=1,uniform.vtk | docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/CFF_14052019/GPDGK16Numerical_140519.nrrd --cnf-uniform --output ./GPDGK16Numerical_140519,d=1,uniform.vtk | ||
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===GPDMMS13_140519=== | ===GPDMMS13_140519=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 264,762 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 150: | Line 150: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/h48toji5cii2rk6xkmofptnw4nntt8zk Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/h48toji5cii2rk6xkmofptnw4nntt8zk Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/bcg7aw4lv9rvp4531va7pqg7j2os7tny Output Mesh] | + | '''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 | ||
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===GPDVGG99_140519=== | ===GPDVGG99_140519=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 261,485 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 172: | Line 172: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/gjg4t3u3gxmp5guq3saln26o7vybycrh Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/gjg4t3u3gxmp5guq3saln26o7vybycrh Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/51rvexl5t83zr4svn2xuw221v16jmtph Output Mesh] | + | '''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 | ||
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===NT_140519=== | ===NT_140519=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive (min edge = 1) | + | * Adaptive (min edge = 1): 253,965 tetrahedra |
| − | * Adaptive (min edge = 2) | + | * Adaptive (min edge = 2): 120,168 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 196: | Line 196: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/o3hv59auwjni9wv95af9div82jyap0el Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/o3hv59auwjni9wv95af9div82jyap0el Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
| Line 212: | Line 212: | ||
===OBS_ALU_140519=== | ===OBS_ALU_140519=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 259,269 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 223: | Line 223: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/1yjcx52p9jz6hvumpjt5sd9vi6aa3vry Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/1yjcx52p9jz6hvumpjt5sd9vi6aa3vry Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/gei8k0bjh7k090vr568xo30fulslnpi5 Output Mesh] | + | '''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 234: | Line 234: | ||
===OBS_CS_140519=== | ===OBS_CS_140519=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 25,168 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 245: | Line 245: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/n4taf4o43xajwg9cks6r35e90hg21p17 Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/n4taf4o43xajwg9cks6r35e90hg21p17 Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/j9zpcjp6fchtr82r6xk0dynf0qfkgi4d Output Mesh] | + | '''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 257: | Line 257: | ||
==CFF_DATA== | ==CFF_DATA== | ||
===cff_E.data_IM=== | ===cff_E.data_IM=== | ||
| − | * Input distribution size : 8,000,000 cells | + | * Input distribution size: 8,000,000 cells |
| − | * Uniform | + | * Uniform: 745,291 tetrahedra |
| − | * Adaptive | + | * Adaptive: 358,637 tetrahedra |
| − | * Adaptive | + | * Adaptive: 358,637 tetrahedra (other side of the same adaptive case) |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 270: | Line 270: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/5rfdhrmm0uj2ohxck4i08v9kds8hcxkr Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/5rfdhrmm0uj2ohxck4i08v9kds8hcxkr Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/byo618ec2140sh6jopidyy1358nmk7ch Output Mesh] | + | '''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 281: | Line 281: | ||
===cff_E.data_REAL=== | ===cff_E.data_REAL=== | ||
| − | * Input distribution size : 8,000,000 cells | + | * Input distribution size: 8,000,000 cells |
| − | * Uniform | + | * Uniform: 745,291 tetrahedra |
| − | * Adaptive | + | * Adaptive: 314,990 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 292: | Line 292: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/43qq7cl2ygw6dlx1penmeiqucxittyzm Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/43qq7cl2ygw6dlx1penmeiqucxittyzm Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/m7kn4kcmatmx86mofb06f37j8kkc35e4 Output Mesh] | + | '''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 303: | Line 303: | ||
===cff_H.data_IM=== | ===cff_H.data_IM=== | ||
| − | * Input distribution size : 8,000,000 cells | + | * Input distribution size: 8,000,000 cells |
| − | * Uniform | + | * Uniform: 745,291 tetrahedra |
| − | * Adaptive | + | * Adaptive: 289,855 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 314: | Line 314: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/pvz8oes781atu01namd42a2b4vezi8x4 Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/pvz8oes781atu01namd42a2b4vezi8x4 Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/ilbviax5y7vrji1anf3a4g8nd8v1wbdw Output Mesh] | + | '''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 325: | Line 325: | ||
===cff_H.data_REAL=== | ===cff_H.data_REAL=== | ||
| − | * Input distribution size : 8,000,000 cells | + | * Input distribution size: 8,000,000 cells |
| − | * Uniform | + | * Uniform: 745,291 tetrahedra |
| − | * Adaptive | + | * Adaptive: 372,016 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 336: | Line 336: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/ow7q9ec6w8n46zhzs45issz0powet2bp Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/ow7q9ec6w8n46zhzs45issz0powet2bp Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/3ww0semcpqqd36xk9eysczxzajwz56uu Output Mesh] | + | '''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 347: | Line 347: | ||
===cff_Ht.data_IM=== | ===cff_Ht.data_IM=== | ||
| − | * Input distribution size : 8,000,000 cells | + | * Input distribution size: 8,000,000 cells |
| − | * Uniform | + | * Uniform: 745,291 tetrahedra |
| − | * Adaptive | + | * Adaptive: 337,772 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 358: | Line 358: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/s8clpr339nzitwbamrhnja75wu030oqn Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/s8clpr339nzitwbamrhnja75wu030oqn Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/2g7n0thzu4uov8zhskykct9kohosqtzm Output Mesh] | + | '''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 369: | Line 369: | ||
===cff_Ht.data_REAL=== | ===cff_Ht.data_REAL=== | ||
| − | * Input distribution size : 8,000,000 cells | + | * Input distribution size: 8,000,000 cells |
| − | * Uniform | + | * Uniform: 745,291 tetrahedra |
| − | * Adaptive | + | * Adaptive: 394,632 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 380: | Line 380: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/ln4z1ncmjaekb9bapcq6zevp8m9w7v2t Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/ln4z1ncmjaekb9bapcq6zevp8m9w7v2t Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/laao7ehbda56xyrm17jfn9xw2sz407qi Output Mesh] | + | '''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 392: | Line 392: | ||
==DATA_04252019== | ==DATA_04252019== | ||
===CFF_E_im=== | ===CFF_E_im=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 236,512 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 403: | Line 403: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/7121pnrof8y2dtstctun35s2pm9nfz6b Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/7121pnrof8y2dtstctun35s2pm9nfz6b Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/62hvu23fevbylbn8htm2os70adamxl3d Output Mesh] | + | '''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 414: | Line 414: | ||
===CFF_E_re=== | ===CFF_E_re=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 260,349 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 425: | Line 425: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/7hc4oll2k15i5soe1u09j9imkf03uaol Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/7hc4oll2k15i5soe1u09j9imkf03uaol Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/294puxiw7kg9ykeaanuojx7ha071ibn6 Output Mesh] | + | '''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 436: | Line 436: | ||
===CFF_H_im=== | ===CFF_H_im=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 263,040 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 447: | Line 447: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/5s1i0rwh6lt4a0rgmgnpmf51yh8oawmv Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/5s1i0rwh6lt4a0rgmgnpmf51yh8oawmv Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/6b8in611r4b0i345ymvpynif45j0pnt2 Output Mesh] | + | '''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 458: | Line 458: | ||
===CFF_H_re=== | ===CFF_H_re=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 249,257 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 469: | Line 469: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/tbbrfxnata2hhfpzqmzuqfnmnjfajnph Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/tbbrfxnata2hhfpzqmzuqfnmnjfajnph Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/40loorarxv19xn40qsvlo56hwpaac2xu Output Mesh] | + | '''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 480: | Line 480: | ||
===GPD_H_down=== | ===GPD_H_down=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 300,117 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 491: | Line 491: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/02crgjhj81ztfdj1ts45lih02wl1aahw Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/02crgjhj81ztfdj1ts45lih02wl1aahw Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/peljqrn1v8gf9mco4qrly85guxhyef0l Output Mesh] | + | '''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 502: | Line 502: | ||
===GPD_H_up=== | ===GPD_H_up=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 768,033 tetrahedra |
| − | * Adaptive | + | * Adaptive: 295,671 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 513: | Line 513: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/ojhugubus797nc3e8kzztul5hnlqe1fx Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/ojhugubus797nc3e8kzztul5hnlqe1fx Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :'''[https://odu.box.com/s/nxrn5xnia27kd4b0kyditafd86atix7b Output Mesh] | + | '''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 524: | Line 524: | ||
===OBS_ALU=== | ===OBS_ALU=== | ||
| − | * Input distribution size : 1,000,000 cells | + | * Input distribution size: 1,000,000 cells |
| − | * Uniform | + | * Uniform: 301,772 tetrahedra |
| − | * Adaptive | + | * Adaptive: 279,721 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 535: | Line 535: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/ynpwegb1khqmjjwtz1rg0503mqbmjs9y Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/ynpwegb1khqmjjwtz1rg0503mqbmjs9y Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/sprttnvtuz5imm3cdrdd34cuasifv4n0 Output Mesh] | + | '''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 547: | Line 547: | ||
==phase_space_000== | ==phase_space_000== | ||
===phase_space_000=== | ===phase_space_000=== | ||
| − | * Input distribution size : 15,625 cells | + | * Input distribution size: 15,625 cells |
| − | * Uniform | + | * Uniform: 17,961 tetrahedra |
| − | * Adaptive | + | * Adaptive: 10,593 tetrahedra |
<gallery mode="packed" heights=350px> | <gallery mode="packed" heights=350px> | ||
| Line 558: | Line 558: | ||
Commands to generate meshes : | Commands to generate meshes : | ||
| − | '''Uniform :''' [https://odu.box.com/s/ype3j19yixez8uwy1k9mgc1585oepugq Output Mesh] | + | '''Uniform:''' [https://odu.box.com/s/ype3j19yixez8uwy1k9mgc1585oepugq Output Mesh] |
<pre> | <pre> | ||
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 | 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 | ||
</pre> | </pre> | ||
| − | '''Adaptive :''' [https://odu.box.com/s/9k8b3wv9ejkvpf5b7xcbb2lc85zrz3b6 Output Mesh] | + | '''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 20:12, 14 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: 30,949 triangles
- Adaptive: 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: 7,587 triangles
- Adaptive (min edge = 2): 623 triangles
- Adaptive (min edge = 0.5): 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: 7,587 triangles
- Adaptive: 1,038 triangles
The 2D image was 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: 7,587 triangles
- Adaptive: 1,018 triangles
The 2D image was 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: 768,033 tetrahedra
- Adaptive (min edge = 1): 273,716 tetrahedra
- Adaptive (min edge = 2): 67,935 tetrahedra
Commands to generate meshes :
Uniform: Output Mesh
docker run -v $(pwd):/data/ crtc_i2m tessellate3d --input ./CNF_Data/3D/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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive (min edge = 1): 253,965 tetrahedra
- Adaptive (min edge = 2): 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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 745,291 tetrahedra
- Adaptive: 358,637 tetrahedra
- Adaptive: 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: 745,291 tetrahedra
- Adaptive: 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: 745,291 tetrahedra
- Adaptive: 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: 745,291 tetrahedra
- Adaptive: 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: 745,291 tetrahedra
- Adaptive: 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: 745,291 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 768,033 tetrahedra
- Adaptive: 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: 301,772 tetrahedra
- Adaptive: 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: 17,961 tetrahedra
- Adaptive: 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
