fix legend color

main/mhd-magfield_glyph/GS/mhd-magfield_glyph_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f4b40024a75558c00b6613fd74d9ef154246381d65c943230499de5adf15f970
-size 288472

main/mhd-magfield_glyph/GS/mhd-magfield_glyph_gs.py

@@ -1,51 +0,0 @@
-import os
-from paraview.simple import *
-
-SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'MHD_magfield_0010.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
-
-reader = XMLImageDataReader(FileName=[VTI_PATH])
-reader.UpdatePipeline()
-
-sliceFilter = Slice(Input=reader)
-sliceFilter.SliceType = 'Plane'
-sliceFilter.SliceType.Origin = [64.0, 63.5, 63.5]
-sliceFilter.SliceType.Normal = [1.0, 0.0, 0.0]
-sliceFilter.UpdatePipeline()
-
-glyph = Glyph(Input=sliceFilter, GlyphType='Arrow')
-glyph.OrientationArray = ['POINTS', 'vector']
-glyph.ScaleArray = ['POINTS', 'magnitude']
-glyph.ScaleFactor = 5.0
-glyph.MaximumNumberOfSamplePoints = 5000
-glyph.GlyphMode = 'Every Nth Point'
-glyph.Stride = 4
-glyph.UpdatePipeline()
-
-renderView = GetActiveViewOrCreate('RenderView')
-renderView.ViewSize = [1024, 1024]
-renderView.Background = [0.0, 0.0, 0.15]
-
-glyphDisplay = Show(glyph, renderView)
-glyphDisplay.Representation = 'Surface'
-ColorBy(glyphDisplay, ('POINTS', 'magnitude'))
-
-magLUT = GetColorTransferFunction('magnitude')
-magLUT.ApplyPreset('Plasma (matplotlib)', True)
-
-glyphDisplay.SetScalarBarVisibility(renderView, True)
-colorBar = GetScalarBar(magLUT, renderView)
-colorBar.Title = 'Magnetic Field Magnitude'
-colorBar.ComponentTitle = ''
-
-renderView.CameraPosition = [250.0, 63.5, 63.5]
-renderView.CameraFocalPoint = [64.0, 63.5, 63.5]
-renderView.CameraViewUp = [0.0, 0.0, 1.0]
-renderView.ResetCamera()
-Render()
-
-SaveScreenshot(OUTPUT_IMG, renderView, ImageResolution=[1024, 1024])
-SaveState(OUTPUT_STATE)
-print(f"Task 04 done: {OUTPUT_IMG}")

main/mhd-magfield_glyph/data/mhd-magfield_glyph.vti

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1b891955b70e72bcc6e0e8976a7f587ff08206a1b153e613617251170886d581
-size 78294594

main/mhd-magfield_glyph/task_description.txt

@@ -1,10 +0,0 @@
-Load the MHD magnetic field dataset from "mhd-magfield_glyph/data/mhd-magfield_glyph.vti" (VTI format, 128x128x128 grid with components bx, by, bz). 
-Create a slice at x=64 through the volume. 
-Place arrow glyphs oriented by the magnetic field vector and scaled by field magnitude (scale factor 5.0). 
-Color the arrows using the 'Plasma (matplotlib)' colormap mapped to magnitude. Use stride of 4. 
-Add a color bar labeled 'Magnetic Field Magnitude'. 
-Use a dark navy background (RGB: 0.0, 0.0, 0.15). Set camera to view along the negative x-axis. Render at 1024x1024.
-Save the paraview state as "mhd-magfield_glyph/results/{agent_mode}/mhd-magfield_glyph.pvsm".
-Save the visualization image as "mhd-magfield_glyph/results/{agent_mode}/mhd-magfield_glyph.png".
-(Optional, if use python script) Save the python script as "mhd-magfield_glyph/results/{agent_mode}/mhd-magfield_glyph.py".
-Do not save any other files, and always save the visualization image.

main/mhd-magfield_glyph/visualization_goals.txt

@@ -1,7 +0,0 @@
-1. Overall Visualization Goal: Does the result match the ground truth glyph visualization of the MHD magnetic field?
-
-2. Glyph Patterns: Do the arrow glyphs show similar orientation and spatial patterns as the ground truth?
-
-3. Glyph Scaling: Do the glyphs show similar size variations as the ground truth, reflecting the field magnitude patterns?
-
-4. Color Mapping: Is the color distribution across glyphs visually similar to the ground truth?

main/mhd-magfield_isosurface/GS/mhd-magfield_isosurface_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3cd46ff898531f2bb3b703a9b81b10b056852632d05531efc5934e907f71c1bf
-size 277547

main/mhd-magfield_isosurface/GS/mhd-magfield_isosurface_gs.py

@@ -1,41 +0,0 @@
-import os
-from paraview.simple import *
-
-SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'MHD_magfield_0060.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
-
-reader = XMLImageDataReader(FileName=[VTI_PATH])
-reader.UpdatePipeline()
-
-contour = Contour(Input=reader)
-contour.ContourBy = ['POINTS', 'magnitude']
-contour.Isosurfaces = [0.8]
-contour.UpdatePipeline()
-
-renderView = GetActiveViewOrCreate('RenderView')
-renderView.ViewSize = [1024, 1024]
-renderView.Background = [0.0, 0.0, 0.1]
-
-contourDisplay = Show(contour, renderView)
-contourDisplay.Representation = 'Surface'
-ColorBy(contourDisplay, ('POINTS', 'bx'))
-
-bxLUT = GetColorTransferFunction('bx')
-bxLUT.ApplyPreset('Turbo', True)
-
-contourDisplay.SetScalarBarVisibility(renderView, True)
-colorBar = GetScalarBar(bxLUT, renderView)
-colorBar.Title = 'Bx Component'
-colorBar.ComponentTitle = ''
-
-renderView.CameraPosition = [200.0, 200.0, 200.0]
-renderView.CameraFocalPoint = [63.5, 63.5, 63.5]
-renderView.CameraViewUp = [0.0, 0.0, 1.0]
-renderView.ResetCamera()
-Render()
-
-SaveScreenshot(OUTPUT_IMG, renderView, ImageResolution=[1024, 1024])
-SaveState(OUTPUT_STATE)
-print(f"Task 16 done: {OUTPUT_IMG}")

main/mhd-magfield_isosurface/data/mhd-magfield_isosurface.vti

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2d155a87cde138ba20a80ac91673e11e90f874504665085b9d34e9ea66c4c489
-size 78294594

main/mhd-magfield_isosurface/task_description.txt

@@ -1,8 +0,0 @@
-Load the MHD magnetic field dataset from "mhd-magfield_isosurface/data/mhd-magfield_isosurface.vti" (VTI format, 128x128x128). 
-Extract an isosurface of magnetic field magnitude at threshold 0.8. Color the isosurface by the bx component using 'Turbo' colormap. 
-Add a color bar labeled 'Bx Component'. 
-Dark navy background (RGB: 0.0, 0.0, 0.1). Isometric camera view. Render at 1024x1024.  
-Save the paraview state as "mhd-magfield_isosurface/results/{agent_mode}/mhd-magfield_isosurface.pvsm".
-Save the visualization image as "mhd-magfield_isosurface/results/{agent_mode}/mhd-magfield_isosurface.png".
-(Optional, if use python script) Save the python script as "mhd-magfield_isosurface/results/{agent_mode}/mhd-magfield_isosurface.py".
-Do not save any other files, and always save the visualization image.   

main/mhd-magfield_isosurface/visualization_goals.txt

@@ -1,7 +0,0 @@
-1. Overall Visualization Goal: Does the result match the ground truth isosurface visualization of the MHD magnetic field?
-
-2. Isosurface Structure: Does the isosurface show similar topology and shape as the ground truth?
-
-3. Surface Features: Are key features and structures on the isosurface similar to the ground truth?
-
-4. Color Mapping: Is the color distribution across the isosurface visually similar to the ground truth?

main/mhd-magfield_volvis/GS/mhd-magfield_volvis_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5fa7365acd796e0c92735e2fd76092b6d798342ed140f59c926285e22072c114
-size 218985

main/mhd-magfield_volvis/GS/mhd-magfield_volvis_gs.py

@@ -1,42 +0,0 @@
-import os
-from paraview.simple import *
-
-SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'MHD_magfield_0040.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
-
-reader = XMLImageDataReader(FileName=[VTI_PATH])
-reader.UpdatePipeline()
-
-renderView = GetActiveViewOrCreate('RenderView')
-renderView.ViewSize = [1024, 1024]
-renderView.Background = [0.0, 0.0, 0.05]
-
-display = Show(reader, renderView)
-display.Representation = 'Volume'
-ColorBy(display, ('POINTS', 'magnitude'))
-
-magLUT = GetColorTransferFunction('magnitude')
-magLUT.ApplyPreset('Cool to Warm', True)
-
-magPWF = GetOpacityTransferFunction('magnitude')
-magPWF.Points = [0.0, 0.0, 0.5, 0.0,
-                 0.5, 0.05, 0.5, 0.0,
-                 1.0, 0.4, 0.5, 0.0,
-                 1.5, 1.0, 0.5, 0.0]
-
-display.SetScalarBarVisibility(renderView, True)
-colorBar = GetScalarBar(magLUT, renderView)
-colorBar.Title = 'B Magnitude'
-colorBar.ComponentTitle = ''
-
-renderView.CameraPosition = [200.0, 200.0, 200.0]
-renderView.CameraFocalPoint = [63.5, 63.5, 63.5]
-renderView.CameraViewUp = [0.0, 0.0, 1.0]
-renderView.ResetCamera()
-Render()
-
-SaveScreenshot(OUTPUT_IMG, renderView, ImageResolution=[1024, 1024])
-SaveState(OUTPUT_STATE)
-print(f"Task 09 done: {OUTPUT_IMG}")

main/mhd-magfield_volvis/data/mhd-magfield_volvis.vti

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f5784edd7ad06e6defa543330de8fcc36fa1ac1d2258085322a024f79c9409bb
-size 78294594

main/mhd-magfield_volvis/task_description.txt

@@ -1,9 +0,0 @@
-Load the MHD magnetic field dataset from "mhd-magfield_volvis/data/mhd-magfield_volvis.vti" (VTI format, 128x128x128 grid). 
-Compute the magnetic field magnitude from components (bx, by, bz). Perform volume rendering of the magnitude field. 
-Use the 'Cool to Warm' colormap with an opacity transfer function that makes low-magnitude regions transparent and high-magnitude regions opaque. 
-Add a color bar labeled 'B Magnitude'. 
-Use a dark background (RGB: 0.0, 0.0, 0.05). Set an isometric camera view. Render at 1024x1024.
-Save the paraview state as "mhd-magfield_volvis/results/{agent_mode}/mhd-magfield_volvis.pvsm".
-Save the visualization image as "mhd-magfield_volvis/results/{agent_mode}/mhd-magfield_volvis.png".
-(Optional, if use python script) Save the python script as "mhd-magfield_volvis/results/{agent_mode}/mhd-magfield_volvis.py".
-Do not save any other files, and always save the visualization image.   

main/mhd-magfield_volvis/visualization_goals.txt

@@ -1,7 +0,0 @@
-1. Overall Visualization Goal: Does the result match the ground truth volume rendering of the MHD magnetic field magnitude?
-
-2. Volume Structure: Are the internal structures and features visible in the volume rendering similar to the ground truth?
-
-3. Opacity Distribution: Does the transparency/opacity distribution appear similar to the ground truth, showing the same depth and internal features?
-
-4. Color Mapping: Is the color distribution throughout the volume visually similar to the ground truth?

main/mhd-turbulence_glyph/GS/mhd-turbulence_glyph_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:98d7b71a0df23246ea06c9bfec9a520c4838404726b7ac71acc50a84cba88947
-size 237519

main/mhd-turbulence_glyph/GS/mhd-turbulence_glyph_gs.py

@@ -1,51 +0,0 @@
-import os
-from paraview.simple import *
-
-SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'MHD_velocity_0010.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
-
-reader = XMLImageDataReader(FileName=[VTI_PATH])
-reader.UpdatePipeline()
-
-sliceFilter = Slice(Input=reader)
-sliceFilter.SliceType = 'Plane'
-sliceFilter.SliceType.Origin = [63.5, 63.5, 64.0]
-sliceFilter.SliceType.Normal = [0.0, 0.0, 1.0]
-sliceFilter.UpdatePipeline()
-
-glyph = Glyph(Input=sliceFilter, GlyphType='Arrow')
-glyph.OrientationArray = ['POINTS', 'vector']
-glyph.ScaleArray = ['POINTS', 'magnitude']
-glyph.ScaleFactor = 5.0
-glyph.MaximumNumberOfSamplePoints = 5000
-glyph.GlyphMode = 'Every Nth Point'
-glyph.Stride = 4
-glyph.UpdatePipeline()
-
-renderView = GetActiveViewOrCreate('RenderView')
-renderView.ViewSize = [1024, 1024]
-renderView.Background = [0.1, 0.1, 0.15]
-
-glyphDisplay = Show(glyph, renderView)
-glyphDisplay.Representation = 'Surface'
-ColorBy(glyphDisplay, ('POINTS', 'magnitude'))
-
-magLUT = GetColorTransferFunction('magnitude')
-magLUT.ApplyPreset('Cool to Warm', True)
-
-glyphDisplay.SetScalarBarVisibility(renderView, True)
-colorBar = GetScalarBar(magLUT, renderView)
-colorBar.Title = 'Velocity Magnitude'
-colorBar.ComponentTitle = ''
-
-renderView.CameraPosition = [63.5, 63.5, 250.0]
-renderView.CameraFocalPoint = [63.5, 63.5, 64.0]
-renderView.CameraViewUp = [0.0, 1.0, 0.0]
-renderView.ResetCamera()
-Render()
-
-SaveScreenshot(OUTPUT_IMG, renderView, ImageResolution=[1024, 1024])
-SaveState(OUTPUT_STATE)
-print(f"Task 01 done: {OUTPUT_IMG}")

main/mhd-turbulence_glyph/data/mhd-turbulence_glyph.vti

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:823282fcbb627582c8d6bac7edc7cb8f87801ba65ff92d65a1d06df7444fd54e
-size 78294594

main/mhd-turbulence_glyph/task_description.txt

@@ -1,11 +0,0 @@
-Load the MHD turbulence velocity field dataset from "mhd-turbulence_glyph/data/mhd-turbulence_glyph.vti" (VTI format, 128x128x128 grid).
-Create a slice at z=64 through the volume. On this slice, place arrow glyphs oriented by the velocity vector field and scaled by velocity magnitude. 
-Color the arrows using the 'Cool to Warm' colormap mapped to velocity magnitude. 
-Use a sampling stride of 4 to avoid overcrowding. Set the glyph scale factor to 5.0. 
-Add a color bar labeled 'Velocity Magnitude'. 
-Use a dark background (RGB: 0.1, 0.1, 0.15). 
-Set the camera to a top-down view looking along the negative z-axis. Render at 1024x1024 resolution.
-Save the paraview state as "mhd-turbulence_glyph/results/{agent_mode}/mhd-turbulence_glyph.pvsm".
-Save the visualization image as "mhd-turbulence_glyph/results/{agent_mode}/mhd-turbulence_glyph.png".
-(Optional, if use python script) Save the python script as "mhd-turbulence_glyph/results/{agent_mode}/mhd-turbulence_glyph.py".
-Do not save any other files, and always save the visualization image.

main/mhd-turbulence_glyph/visualization_goals.txt

@@ -1,7 +0,0 @@
-1. Overall Visualization Goal: Does the result match the ground truth glyph visualization of the MHD turbulence velocity field?
-
-2. Glyph Patterns: Do the arrow glyphs show similar orientation and spatial patterns as the ground truth?
-
-3. Glyph Scaling: Do the glyphs show similar size variations as the ground truth, reflecting the velocity magnitude patterns?
-
-4. Color Mapping: Is the color distribution across glyphs visually similar to the ground truth?

main/mhd-turbulence_vorticity/GS/mhd-turbulence_vorticity_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cccdf68dc512311a488ad73f41c63b2ce921728d0de8e54b357da33a739d5c82
-size 278782

main/mhd-turbulence_vorticity/GS/mhd-turbulence_vorticity_gs.py

@@ -1,55 +0,0 @@
-import os
-from paraview.simple import *
-
-SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'MHD_velocity_0050.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
-
-reader = XMLImageDataReader(FileName=[VTI_PATH])
-reader.UpdatePipeline()
-
-gradient = GradientOfUnstructuredDataSet(Input=reader)
-gradient.ScalarArray = ['POINTS', 'vector']
-gradient.ComputeVorticity = 1
-gradient.ComputeGradient = 0
-gradient.VorticityArrayName = 'Vorticity'
-gradient.UpdatePipeline()
-
-calc = Calculator(Input=gradient)
-calc.Function = 'mag(Vorticity)'
-calc.ResultArrayName = 'VorticityMagnitude'
-calc.UpdatePipeline()
-
-renderView = GetActiveViewOrCreate('RenderView')
-renderView.ViewSize = [1024, 1024]
-renderView.Background = [0.0, 0.0, 0.0]
-
-display = Show(calc, renderView)
-display.Representation = 'Volume'
-ColorBy(display, ('POINTS', 'VorticityMagnitude'))
-
-vorLUT = GetColorTransferFunction('VorticityMagnitude')
-vorLUT.ApplyPreset('Plasma (matplotlib)', True)
-
-vorPWF = GetOpacityTransferFunction('VorticityMagnitude')
-vorPWF.Points = [0.0, 0.0, 0.5, 0.0,
-                 0.1, 0.0, 0.5, 0.0,
-                 0.3, 0.1, 0.5, 0.0,
-                 0.6, 0.5, 0.5, 0.0,
-                 1.0, 1.0, 0.5, 0.0]
-
-display.SetScalarBarVisibility(renderView, True)
-colorBar = GetScalarBar(vorLUT, renderView)
-colorBar.Title = 'Vorticity Magnitude'
-colorBar.ComponentTitle = ''
-
-renderView.CameraPosition = [200.0, 200.0, 200.0]
-renderView.CameraFocalPoint = [63.5, 63.5, 63.5]
-renderView.CameraViewUp = [0.0, 0.0, 1.0]
-renderView.ResetCamera()
-Render()
-
-SaveScreenshot(OUTPUT_IMG, renderView, ImageResolution=[1024, 1024])
-SaveState(OUTPUT_STATE)
-print(f"Task 12 done: {OUTPUT_IMG}")

main/mhd-turbulence_vorticity/data/mhd-turbulence_vorticity.vti

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a4052ecaeecb8d89bfd3559d89873b93847f899018e754083871bbb7d4f82d56
-size 78294594

main/mhd-turbulence_vorticity/task_description.txt

@@ -1,10 +0,0 @@
-Load the MHD turbulence velocity field dataset "mhd-turbulence_vorticity/data/mhd-turbulence_vorticity.vti" (VTI format, 128x128x128 grid).
-Compute the vorticity field (curl of velocity) using the Gradient filter with 'Compute Vorticity' enabled.
-Then compute vorticity magnitude. Perform volume rendering of vorticity magnitude using the 'Plasma (matplotlib)' colormap. 
-Set opacity to highlight high-vorticity regions. 
-Add a color bar labeled 'Vorticity Magnitude'. 
-Black background. Isometric camera. Render at 1024x1024.
-Save the paraview state as "mhd-turbulence_vorticity/results/{agent_mode}/mhd-turbulence_vorticity.pvsm".
-Save the visualization image as "mhd-turbulence_vorticity/results/{agent_mode}/mhd-turbulence_vorticity.png".
-(Optional, if use python script) Save the python script as "mhd-turbulence_vorticity/results/{agent_mode}/mhd-turbulence_vorticity.py".
-Do not save any other files, and always save the visualization image.

main/mhd-turbulence_vorticity/visualization_goals.txt

@@ -1,7 +0,0 @@
-1. Overall Visualization Goal: Does the result match the ground truth volume rendering of the MHD turbulence vorticity field?
-
-2. Vorticity Patterns: Are the vorticity structures and patterns visible in the result similar to the ground truth?
-
-3. Volume Features: Are high-vorticity regions highlighted with similar opacity and visibility as the ground truth?
-
-4. Color Mapping: Is the color distribution throughout the volume visually similar to the ground truth?

main/rti-velocity_divergence/GS/rti-velocity_divergence_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6c44c7ae1f4c43061ef3f1a96da69d20d30f22eaa8d36e438297f323c1fb6175
-size 225407

main/rti-velocity_divergence/GS/rti-velocity_divergence_gs.py

@@ -1,49 +0,0 @@
-import os
-from paraview.simple import *
-
-SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'RTI_velocity_0040.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
-
-reader = XMLImageDataReader(FileName=[VTI_PATH])
-reader.UpdatePipeline()
-
-gradient = GradientOfUnstructuredDataSet(Input=reader)
-gradient.ScalarArray = ['POINTS', 'vector']
-gradient.ComputeDivergence = 1
-gradient.ComputeGradient = 0
-gradient.DivergenceArrayName = 'Divergence'
-gradient.UpdatePipeline()
-
-sliceFilter = Slice(Input=gradient)
-sliceFilter.SliceType = 'Plane'
-sliceFilter.SliceType.Origin = [63.5, 63.5, 64.0]
-sliceFilter.SliceType.Normal = [0.0, 0.0, 1.0]
-sliceFilter.UpdatePipeline()
-
-renderView = GetActiveViewOrCreate('RenderView')
-renderView.ViewSize = [1024, 1024]
-renderView.Background = [1.0, 1.0, 1.0]
-
-sliceDisplay = Show(sliceFilter, renderView)
-sliceDisplay.Representation = 'Surface'
-ColorBy(sliceDisplay, ('POINTS', 'Divergence'))
-
-divLUT = GetColorTransferFunction('Divergence')
-divLUT.ApplyPreset('Cool to Warm', True)
-
-sliceDisplay.SetScalarBarVisibility(renderView, True)
-colorBar = GetScalarBar(divLUT, renderView)
-colorBar.Title = 'Velocity Divergence'
-colorBar.ComponentTitle = ''
-
-renderView.CameraPosition = [63.5, 63.5, 250.0]
-renderView.CameraFocalPoint = [63.5, 63.5, 64.0]
-renderView.CameraViewUp = [0.0, 1.0, 0.0]
-renderView.ResetCamera()
-Render()
-
-SaveScreenshot(OUTPUT_IMG, renderView, ImageResolution=[1024, 1024])
-SaveState(OUTPUT_STATE)
-print(f"Task 13 done: {OUTPUT_IMG}")

main/rti-velocity_divergence/data/rti-velocity_divergence.vti

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:d9e278b27f5ee9af8dfa9cc5073d865633ccf7dc9cc6c52d1ebbbf4c751ebec1
-size 78294594

main/rti-velocity_divergence/task_description.txt

@@ -1,9 +0,0 @@
-Load the Rayleigh-Taylor instability velocity field from "rti-velocity_divergence/data/rti-velocity_divergence.vti" (VTI format, 128x128x128). 
-Compute the divergence of the velocity field using the Gradient filter with 'Compute Divergence' enabled. 
-Extract a slice at z=64 and color it by divergence using the 'Cool to Warm' diverging colormap (centered at 0). 
-Add a color bar labeled 'Velocity Divergence'. 
-White background. Top-down camera view along negative z-axis. Render at 1024x1024.
-Save the paraview state as "rti-velocity_divergence/results/{agent_mode}/rti-velocity_divergence.pvsm".
-Save the visualization image as "rti-velocity_divergence/results/{agent_mode}/rti-velocity_divergence.png".
-(Optional, if use python script) Save the python script as "rti-velocity_divergence/results/{agent_mode}/rti-velocity_divergence.py".
-Do not save any other files, and always save the visualization image

main/rti-velocity_divergence/visualization_goals.txt

@@ -1,7 +0,0 @@
-1. Overall Visualization Goal: Does the result match the ground truth visualization of the RTI velocity divergence field?
-
-2. Divergence Patterns: Are the divergence patterns and structures visible in the result similar to the ground truth?
-
-3. Spatial Distribution: Does the spatial distribution of positive and negative divergence regions match the ground truth?
-
-4. Color Mapping: Is the color distribution visually similar to the ground truth, showing similar divergence values?

main/rti-velocity_glyph/GS/rti-velocity_glyph_gs.pvsm

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:96b220a805d0dec6cf8b6a8f9d54e2dc1d484a505e3982cba8202d257d5c68b7
-size 288526
+oid sha256:5d1e8b0d845ee37765be8fc08796cbe220dff6a4e9d8a5ed8aa7ca7aacc7d58a
+size 288017

main/rti-velocity_glyph/GS/rti-velocity_glyph_gs.py

@@ -2,9 +2,9 @@ import os
 from paraview.simple import *
 
 SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'RTI_velocity_0050.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
+VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'data', 'rti-velocity_glyph.vti')
+OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'rti-velocity_glyph_gs.png')
+OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'rti-velocity_glyph_gs.pvsm')
 
 reader = XMLImageDataReader(FileName=[VTI_PATH])
 reader.UpdatePipeline()
@@ -37,8 +37,10 @@ magLUT.ApplyPreset('Viridis (matplotlib)', True)
 
 glyphDisplay.SetScalarBarVisibility(renderView, True)
 colorBar = GetScalarBar(magLUT, renderView)
-colorBar.Title = 'Velocity Magnitude'
+colorBar.Title = ''
 colorBar.ComponentTitle = ''
+colorBar.TitleColor = [0.0, 0.0, 0.0]
+colorBar.LabelColor = [0.0, 0.0, 0.0]
 
 renderView.CameraPosition = [63.5, 250.0, 63.5]
 renderView.CameraFocalPoint = [63.5, 64.0, 63.5]

main/rti-velocity_streakline/GS/rti-velocity_streakline_gs.pvsm

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1707fc866f4a54463f8bb8d96ba83f650bf4107e8db4fbc148c4836cd6c760db
-size 850318
+oid sha256:a91b48041e5913c3e608996dcc5fca9822a03c519c2ad511ff2045f70a6daab1
+size 849385

main/rti-velocity_streakline/GS/rti-velocity_streakline_gs.py

@@ -3,9 +3,9 @@ import glob
 from paraview.simple import *
 
 SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_FILES = sorted(glob.glob(os.path.join(SCRIPT_DIR, 'RTI_velocity_*.vti')))
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
+VTI_FILES = sorted(glob.glob(os.path.join(SCRIPT_DIR, '..', 'data', 'rti-velocity_streakline_*.vti')))
+OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'rti-velocity_streakline_gs.png')
+OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'rti-velocity_streakline_gs.pvsm')
 
 # Streaklines: show streamlines from injection points at multiple timesteps
 
@@ -76,8 +76,10 @@ vyLUT.ApplyPreset('Cool to Warm', True)
 
 vyDisplay.SetScalarBarVisibility(renderView, True)
 colorBar = GetScalarBar(vyLUT, renderView)
-colorBar.Title = 'Vertical Velocity (vy)'
+colorBar.Title = ''
 colorBar.ComponentTitle = ''
+colorBar.TitleColor = [0.0, 0.0, 0.0]
+colorBar.LabelColor = [0.0, 0.0, 0.0]
 
 # Elevated camera
 import math

main/rti-velocity_streamline/GS/rti-velocity_streamline_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:32e8c07f9298d42f9e18c5a3cb490a5dd71ad2990575a9601cf7d390842ad6af
-size 230654

main/rti-velocity_streamline/GS/rti-velocity_streamline_gs.py

@@ -1,48 +0,0 @@
-import os
-from paraview.simple import *
-
-SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
-VTI_PATH = os.path.join(SCRIPT_DIR, '..', 'vti_data', 'RTI_velocity_0070.vti')
-OUTPUT_IMG = os.path.join(SCRIPT_DIR, 'gt_image.png')
-OUTPUT_STATE = os.path.join(SCRIPT_DIR, 'gt_state.pvsm')
-
-reader = XMLImageDataReader(FileName=[VTI_PATH])
-reader.UpdatePipeline()
-
-stream = StreamTracer(Input=reader, SeedType='Line')
-stream.SeedType.Point1 = [0.0, 64.0, 0.0]
-stream.SeedType.Point2 = [127.0, 64.0, 127.0]
-stream.SeedType.Resolution = 200
-stream.Vectors = ['POINTS', 'vector']
-stream.MaximumStreamlineLength = 200.0
-stream.UpdatePipeline()
-
-tube = Tube(Input=stream)
-tube.Radius = 0.4
-tube.UpdatePipeline()
-
-renderView = GetActiveViewOrCreate('RenderView')
-renderView.ViewSize = [1024, 1024]
-renderView.Background = [0.02, 0.02, 0.05]
-
-tubeDisplay = Show(tube, renderView)
-tubeDisplay.Representation = 'Surface'
-ColorBy(tubeDisplay, ('POINTS', 'vz'))
-
-vzLUT = GetColorTransferFunction('vz')
-vzLUT.ApplyPreset('Cool to Warm (Extended)', True)
-
-tubeDisplay.SetScalarBarVisibility(renderView, True)
-colorBar = GetScalarBar(vzLUT, renderView)
-colorBar.Title = 'Vz Component'
-colorBar.ComponentTitle = ''
-
-renderView.CameraPosition = [200.0, 200.0, 200.0]
-renderView.CameraFocalPoint = [63.5, 63.5, 63.5]
-renderView.CameraViewUp = [0.0, 0.0, 1.0]
-renderView.ResetCamera()
-Render()
-
-SaveScreenshot(OUTPUT_IMG, renderView, ImageResolution=[1024, 1024])
-SaveState(OUTPUT_STATE)
-print(f"Task 06 done: {OUTPUT_IMG}")

main/rti-velocity_streamline/data/rti-velocity_streamline.vti

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2d4e97f14322a56df10aa5bb46156b2f68af485df51513c07264bd0dc48f3d40
-size 78294594

main/rti-velocity_streamline/task_description.txt

@@ -1,9 +0,0 @@
-Load the Rayleigh-Taylor instability velocity field dataset from "rti-velocity_streamline/data/rti-velocity_streamline.vti" (VTI format, 128x128x128 grid). 
-Generate streamlines seeded from a plane at y=64 (using a Point Cloud seed with 200 points distributed on the xz-plane at y=64). 
-Color the streamlines by the vz component using a 'Cool to Warm (Extended)' diverging colormap. Render streamlines as tubes with radius 0.4. 
-Add a color bar labeled 'Vz Component'. 
-Dark background (RGB: 0.02, 0.02, 0.05). Use an isometric camera view. Render at 1024x1024.
-Save the paraview state as "rti-velocity_streamline/results/{agent_mode}/rti-velocity_streamline.pvsm".
-Save the visualization image as "rti-velocity_streamline/results/{agent_mode}/rti-velocity_streamline.png".
-(Optional, if use python script) Save the python script as "rti-velocity_streamline/results/{agent_mode}/rti-velocity_streamline.py".
-Do not save any other files, and always save the visualization image.

main/rti-velocity_streamline/visualization_goals.txt

@@ -1,5 +0,0 @@
-1) Streamlines seeded from y=64 plane region, with similar pattern compared to groundtruth
-2) Streamlines rendered as tubes
-3) Color by vz with Cool to Warm diverging colormap
-4) Color bar labeled 'Vz Component'
-5) Dark background, Isometric camera view, Output resolution 1024x1024

main/rti-velocity_streamribbon/GS/rti-velocity_streamribbon_gs.pvsm

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1a71e9fc46dfb14c4422e16f852496a57b59537457071eb93edb9bc55030ddb6
-size 229928
+oid sha256:27ffa5bd05e97f0376bf53e108958b5b1484fc683edc9ac60c84b4d131d998a2
+size 229459