diff --git a/.DS_Store b/.DS_Store index 9bfeedee92eceddd9d025eee277ae59675644acf..d518eca75d35b15b9ff872d69b8d19ee0d6d385d 100644 Binary files a/.DS_Store and b/.DS_Store differ diff --git a/sci_volume_data/aneurism/task_description.txt b/sci_volume_data/aneurism/task_description.txt deleted file mode 100644 index 5ca1954820e134e6fec9141a51ddcbc51b7abbd4..0000000000000000000000000000000000000000 --- a/sci_volume_data/aneurism/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Aneurism dataset from "aneurism/data/aneurism_256x256x256_uint8.raw", the information about this dataset: -Aneurism -Description: Rotational C-arm x-ray scan of the arteries of the right half of a human head. A contrast agent was injected into the blood and an aneurism is present. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x256 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the blood vessels using: -1. Apply volume rendering with a transfer function that highlights the contrast-enhanced vessels -2. Use a red-to-white color map for blood vessels -3. Extract an isosurface at a value that clearly shows the aneurism or vessel structure (experiment with values around 100-150) -4. Adjust opacity to make internal structures visible (opacity around 0.6-0.8 for vessels) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "aneurism/results/aneurism.pvsm" \ No newline at end of file diff --git a/sci_volume_data/aneurism/visualization_goals.txt b/sci_volume_data/aneurism/visualization_goals.txt deleted file mode 100644 index 392ef52b88061e278a83223e053239741c447f4d..0000000000000000000000000000000000000000 --- a/sci_volume_data/aneurism/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the blood vessel network and highlight the aneurism or vascular structures? - -2. Transfer Function: Is the contrast agent properly highlighted with appropriate color mapping? - -3. Isosurface Quality: Does the isosurface accurately capture the vessel boundaries? - -4. Clinical Relevance: Can medical professionals identify the key anatomical features and any abnormalities? diff --git a/sci_volume_data/backpack/task_description.txt b/sci_volume_data/backpack/task_description.txt deleted file mode 100644 index 5a199e7e9eefacca6b52950ff8edb87981cb9e06..0000000000000000000000000000000000000000 --- a/sci_volume_data/backpack/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Backpack Scan dataset from "backpack/data/backpack_512x512x373_uint16.raw", the information about this dataset: -Backpack Scan -Description: CT scan of a backpack filled with items. -Data Type: uint16 -Data Byte Order: little Endian -Data Spacing: 0.9766x0.9766x1.25 -Data Extent: 512x512x373 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the backpack contents: -1. Apply volume rendering with different transfer functions for different materials -2. Create multiple isosurfaces for different density materials (metal, plastic, fabric) -3. Use distinct colors for different material types -4. Make the backpack exterior semi-transparent to reveal contents - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "backpack/results/backpack.pvsm \ No newline at end of file diff --git a/sci_volume_data/backpack/visualization_goals.txt b/sci_volume_data/backpack/visualization_goals.txt deleted file mode 100644 index 4ff0ebea98c43f4c3c35ef5c6a0897e4d25e80e3..0000000000000000000000000000000000000000 --- a/sci_volume_data/backpack/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Backpack Scan? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? \ No newline at end of file diff --git a/sci_volume_data/blunt_fin/task_description.txt b/sci_volume_data/blunt_fin/task_description.txt deleted file mode 100644 index b783537f9b13512b741ecd57b87e097434fb89f5..0000000000000000000000000000000000000000 --- a/sci_volume_data/blunt_fin/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Blunt Fin dataset from "blunt_fin/data/blunt_fin_256x128x64_uint8.raw", the information about this dataset: -Blunt Fin -Description: -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x0.75x1 -Data Extent: 256x128x64 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the scanned object: -1. Apply volume rendering with appropriate transfer function -2. Create an isosurface at the object boundary -3. Use realistic colors for the material -4. Add clipping or transparency to show internal structure - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "blunt_fin/results/blunt_fin.pvsm" \ No newline at end of file diff --git a/sci_volume_data/blunt_fin/visualization_goals.txt b/sci_volume_data/blunt_fin/visualization_goals.txt deleted file mode 100644 index e6ea7f42b47941eb5473f34100b68afd544a1b2c..0000000000000000000000000000000000000000 --- a/sci_volume_data/blunt_fin/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Blunt Fin? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? diff --git a/sci_volume_data/bonsai/GS/.DS_Store b/sci_volume_data/bonsai/GS/.DS_Store deleted file mode 100644 index 5008ddfcf53c02e82d7eee2e57c38e5672ef89f6..0000000000000000000000000000000000000000 Binary files a/sci_volume_data/bonsai/GS/.DS_Store and /dev/null differ diff --git a/sci_volume_data/bonsai/GS/bonsai_gs.pvsm b/sci_volume_data/bonsai/GS/bonsai_gs.pvsm deleted file mode 100644 index ac26f52d295649eb9853ed29fb0e6e5155b249f0..0000000000000000000000000000000000000000 --- a/sci_volume_data/bonsai/GS/bonsai_gs.pvsm +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:aa03b91b2e71ffbfef15c26dce85b93887ee4ffd1461759c11a46f640f604ac0 -size 235372 diff --git a/sci_volume_data/bonsai/GS/bonsai_gs.py b/sci_volume_data/bonsai/GS/bonsai_gs.py deleted file mode 100644 index 077ec38b1350b01dbe70b07c9af99963765cc12e..0000000000000000000000000000000000000000 --- a/sci_volume_data/bonsai/GS/bonsai_gs.py +++ /dev/null @@ -1,87 +0,0 @@ -#!/usr/bin/env pvpython - -import os -from paraview.simple import * - -def create_bonsai_visualization(): - # — Paths & setup — - base = os.path.abspath(os.path.join(__file__, '..', '..')) - raw_file = os.path.join(base, 'data', 'bonsai_256x256x256_uint8.raw') - state_dir = os.path.join(base, 'results', 'pvpython_state') - state = os.path.join(state_dir, 'bonsai.pvsm') - os.makedirs(state_dir, exist_ok=True) - if not os.path.isfile(raw_file): - raise FileNotFoundError(f"Missing raw: {raw_file}") - - # — 1) Load the RAW image — - reader = ImageReader(FileNames=[raw_file]) - reader.DataScalarType = 'unsigned char' - reader.DataByteOrder = 'LittleEndian' - reader.DataExtent = [0, 255, 0, 255, 0, 255] - reader.DataSpacing = [1.0, 1.0, 1.0] - reader.FileDimensionality = 3 - reader.UpdatePipeline() - - # — 2) Volume render setup — - view = GetActiveViewOrCreate('RenderView') - view.BackgroundColorMode = 'Single Color' - view.Background = [1, 1, 1] - - disp = Show(reader, view) - disp.SetRepresentationType('Volume') - disp.ColorArrayName = ['POINTS', 'ImageFile'] - view.ResetCamera() - - # — 3) Transfer functions from extracted GS state — - ctf = GetColorTransferFunction('ImageFile') - ctf.ColorSpace = 'RGB' - ctf.NumberOfTableValues = 1024 - ctf.RGBPoints = [ - 0.000, 0.780, 0.522, 0.000, - 37.564, 0.847, 0.565, 0.000, - 61.402, 0.796, 0.757, 0.722, - 88.853, 0.753, 0.753, 0.753, - 118.470, 0.804, 0.737, 0.694, - 129.306, 0.686, 0.357, 0.047, - 156.756, 0.678, 0.345, 0.024, - 239.108, 0.667, 0.333, 0.000, - 255.000, 0.706, 0.016, 0.149 - ] - - otf = GetOpacityTransferFunction('ImageFile') - otf.Points = [ - 0.000, 0.000, 0.5, 0.0, - 32.507, 0.000, 0.5, 0.0, - 32.507, 0.360, 0.5, 0.0, - 39.731, 0.455, 0.5, 0.0, - 41.176, 0.000, 0.5, 0.0, - 63.569, 0.000, 0.5, 0.0, - 63.569, 0.511, 0.5, 0.0, - 89.575, 0.412, 0.5, 0.0, - 100.411, 0.000, 0.5, 0.0, - 163.980, 0.002, 0.5, 0.0, - 163.980, 0.567, 0.5, 0.0, - 231.161, 0.649, 0.5, 0.0, - 241.275, 0.433, 0.5, 0.0, - 255.000, 1.000, 0.5, 0.0 - ] - - disp.LookupTable = ctf - disp.ScalarOpacityFunction = otf - - # — 4) Camera & save — - cam = view.GetActiveCamera() - cam.SetPosition(400, 350, 450) - cam.SetFocalPoint(128, 128, 128) - cam.SetViewUp(1, 0, 0) - view.ResetCamera() - cam.Elevation(15) - cam.Azimuth(30) - cam.Zoom(1.0) - - view.StillRender() - SaveState(state) - print(f"[✔] Saved gold‑standard PVSM:\n {state}") - -if __name__ == '__main__': - create_bonsai_visualization() diff --git a/sci_volume_data/bonsai/GS/gs_diagonal_view.png b/sci_volume_data/bonsai/GS/gs_diagonal_view.png deleted file mode 100644 index f1d944ae5214517a458ecb2fab9ac68a379a27c0..0000000000000000000000000000000000000000 --- a/sci_volume_data/bonsai/GS/gs_diagonal_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:f5deab399f55098d4f79d2ca799513e730e0d80cd5954c6d4b36bcdb1553fd3a -size 589653 diff --git a/sci_volume_data/bonsai/GS/gs_front_view.png b/sci_volume_data/bonsai/GS/gs_front_view.png deleted file mode 100644 index f118f43bd6943bfb55c2146b8d19e96b28cdcc3c..0000000000000000000000000000000000000000 --- a/sci_volume_data/bonsai/GS/gs_front_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:205de6ffecfe0ac97b9a05cb4e0e48b542e05a622d8e31766fe929617ad39097 -size 350780 diff --git a/sci_volume_data/bonsai/GS/gs_side_view.png b/sci_volume_data/bonsai/GS/gs_side_view.png deleted file mode 100644 index 1f13b925b7fce310f9a887690a832baae1c82ecb..0000000000000000000000000000000000000000 --- a/sci_volume_data/bonsai/GS/gs_side_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:ba458a49d0e1bba5fa6267b5582e314be755a633892a18d9d61bcec781c4dbaf -size 477066 diff --git a/sci_volume_data/bonsai/task_description.txt b/sci_volume_data/bonsai/task_description.txt deleted file mode 100644 index 04ddfe6c19f87db15cae657c8f85467643ef9a03..0000000000000000000000000000000000000000 --- a/sci_volume_data/bonsai/task_description.txt +++ /dev/null @@ -1,14 +0,0 @@ -Task: - -Load the bonsai dataset from "bonsai/data/bonsai_256x256x256_uint8.raw", the information about this dataset: -Bonsai (Scalar) -Data Scalar Type: unsigned char -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x256 - -Then visualize it with volume rendering, modify the transfer function and reach the visualization goal as: "A potted tree with brown pot silver branch and golden leaves." - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "bonsai/results/bonsai.pvsm" \ No newline at end of file diff --git a/sci_volume_data/bonsai/visualization_goals.txt b/sci_volume_data/bonsai/visualization_goals.txt deleted file mode 100644 index b5e0aee709559d873be862802839a4dc723adfbc..0000000000000000000000000000000000000000 --- a/sci_volume_data/bonsai/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Visualization Goal: How well does the result achieve the overall goal of showing a potted tree with the specified colors? - -2. Brown Pot Visualization: Does the result show the pot portion in brown color? - -3. Silver Branch Visualization: Does the result show the branch/trunk portion in silver color? - -4. Golden Leaves Visualization: Does the result show the leaves portion in golden color? \ No newline at end of file diff --git a/sci_volume_data/boston_teapot/task_description.txt b/sci_volume_data/boston_teapot/task_description.txt deleted file mode 100644 index 32dfd4a3f7722a28a8340fd3216b5231130f5af9..0000000000000000000000000000000000000000 --- a/sci_volume_data/boston_teapot/task_description.txt +++ /dev/null @@ -1,21 +0,0 @@ -Task: - -Load the Boston Teapot dataset from "boston_teapot/data/boston_teapot_256x256x178_uint8.raw", the information about this dataset: -Boston Teapot -Description: CT scan of the SIGGRAPH 1989 teapot with a small version of the AVS lobster inside. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x178 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the teapot and internal lobster: -1. Apply volume rendering with two distinct transfer functions -2. Create an isosurface for the bronze teapot exterior (higher value) -3. Create another isosurface for the lobster inside (lower value, different color) -4. Use bronze/copper color for teapot, red-orange for lobster -5. Make teapot semi-transparent to reveal the lobster - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "boston_teapot/results/boston_teapot.pvsm \ No newline at end of file diff --git a/sci_volume_data/boston_teapot/visualization_goals.txt b/sci_volume_data/boston_teapot/visualization_goals.txt deleted file mode 100644 index 89e9989768a5c212cd9c55d85b3fcc9ec0e4bcd6..0000000000000000000000000000000000000000 --- a/sci_volume_data/boston_teapot/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Boston Teapot? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? \ No newline at end of file diff --git a/sci_volume_data/bunny/task_description.txt b/sci_volume_data/bunny/task_description.txt deleted file mode 100644 index 37adef90256115ed2e015e5a2336965984ba1764..0000000000000000000000000000000000000000 --- a/sci_volume_data/bunny/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Bunny dataset from "bunny/data/bunny_512x512x361_uint16.raw", the information about this dataset: -Bunny -Description: A CT scan of the Stanford Bunny. The greyscale units are Hounsfield units, denoting electron-density of the subject; the scale units are in millimeters. The scan was completed 28 January 2000. -Data Type: uint16 -Data Byte Order: little Endian -Data Spacing: 0.337891x0.337891x0.5 -Data Extent: 512x512x361 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the scanned specimen: -1. Apply volume rendering to show the full structure -2. Create an isosurface at the specimen boundary -3. Use natural colors appropriate for the specimen -4. Adjust opacity to show internal features if present - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "bunny/results/bunny.pvsm \ No newline at end of file diff --git a/sci_volume_data/bunny/visualization_goals.txt b/sci_volume_data/bunny/visualization_goals.txt deleted file mode 100644 index 8d73577ec082c655f7b1e8e8077e6180a29aff00..0000000000000000000000000000000000000000 --- a/sci_volume_data/bunny/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Bunny? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? \ No newline at end of file diff --git a/sci_volume_data/carp/task_description.txt b/sci_volume_data/carp/task_description.txt deleted file mode 100644 index b52ea870f01b9616464fec451f7257702ef98294..0000000000000000000000000000000000000000 --- a/sci_volume_data/carp/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Carp dataset from "carp/data/carp_256x256x512_uint16.raw", the information about this dataset: -Carp -Description: CT scan of a carp fish -Data Type: uint16 -Data Byte Order: little Endian -Data Spacing: 0.78125x0.390625x1 -Data Extent: 256x256x512 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the scanned specimen: -1. Apply volume rendering to show the full structure -2. Create an isosurface at the specimen boundary -3. Use natural colors appropriate for the specimen -4. Adjust opacity to show internal features (skeleton, organs) if present - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "carp/results/carp.pvsm \ No newline at end of file diff --git a/sci_volume_data/carp/visualization_goals.txt b/sci_volume_data/carp/visualization_goals.txt deleted file mode 100644 index 5dbdf0fd0cd6829ac3db50d9d1ed425f28269af5..0000000000000000000000000000000000000000 --- a/sci_volume_data/carp/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Carp? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? \ No newline at end of file diff --git a/sci_volume_data/csafe_heptane/task_description.txt b/sci_volume_data/csafe_heptane/task_description.txt deleted file mode 100644 index 99ce030a1515156c9ca3020ff22f9f1051e20306..0000000000000000000000000000000000000000 --- a/sci_volume_data/csafe_heptane/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the CSAFE Heptane Gas dataset from "csafe_heptane/data/csafe_heptane_302x302x302_uint8.raw", the information about this dataset: -CSAFE Heptane Gas -Description: A single time step from a computational simulation of a jet of heptane gas undergoing combustion. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 302x302x302 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the combustion/fuel injection process: -1. Apply volume rendering with a hot colormap (black-red-yellow-white) to show temperature/density variations -2. Create an isosurface at the fuel-air mixture boundary (mid-range value) -3. Add a slice plane through the center to show the injection pattern -4. Adjust opacity to reveal the combustion core (opacity 0.4-0.6) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "csafe_heptane/results/csafe_heptane.pvsm" \ No newline at end of file diff --git a/sci_volume_data/csafe_heptane/visualization_goals.txt b/sci_volume_data/csafe_heptane/visualization_goals.txt deleted file mode 100644 index 45bdee529d4e4999d8e3c957d5b1bd78a4a2f224..0000000000000000000000000000000000000000 --- a/sci_volume_data/csafe_heptane/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively convey the physics/dynamics of the CSAFE Heptane Gas simulation? - -2. Feature Detection: Are the key features (shock fronts, vortices, mixing regions) clearly visible? - -3. Color Mapping: Does the colormap appropriately represent the physical quantity being visualized? - -4. Spatial Understanding: Do the isosurfaces and slices provide good insight into the 3D structure? diff --git a/sci_volume_data/duct/task_description.txt b/sci_volume_data/duct/task_description.txt deleted file mode 100644 index 9ef11f4a8bb94ee9def17ec83069782747f02712..0000000000000000000000000000000000000000 --- a/sci_volume_data/duct/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Duct Flow dataset from "duct/data/duct_193x194x1000_float32.raw", the information about this dataset: -Duct Flow -Description: A wall-bounded flow in a duct. -Data Type: float32 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 193x194x1000 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the flow dynamics: -1. Apply volume rendering to show the turbulent structures -2. Use a blue-to-red colormap to show vorticity or velocity magnitude -3. Create isosurfaces at multiple values to show different turbulence intensities -4. Add a contour on a slice plane to show flow patterns - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "duct/results/duct.pvsm" \ No newline at end of file diff --git a/sci_volume_data/duct/visualization_goals.txt b/sci_volume_data/duct/visualization_goals.txt deleted file mode 100644 index 95b73eeb79b64be71bfa5b947d59095d4525c787..0000000000000000000000000000000000000000 --- a/sci_volume_data/duct/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively convey the physics/dynamics of the Duct Flow simulation? - -2. Feature Detection: Are the key features (shock fronts, vortices, mixing regions) clearly visible? - -3. Color Mapping: Does the colormap appropriately represent the physical quantity being visualized? - -4. Spatial Understanding: Do the isosurfaces and slices provide good insight into the 3D structure? diff --git a/sci_volume_data/engine/task_description.txt b/sci_volume_data/engine/task_description.txt deleted file mode 100644 index d5fc7093b3689796440e8026e41ec6372245786e..0000000000000000000000000000000000000000 --- a/sci_volume_data/engine/task_description.txt +++ /dev/null @@ -1,21 +0,0 @@ -Task: - -Load the Engine dataset from "engine/data/engine_256x256x128_uint8.raw", the information about this dataset: -Engine -Description: CT scan of two cylinders of an engine block. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x128 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the engine block structure: -1. Apply volume rendering with a metallic transfer function -2. Create an isosurface for the metal parts (high density value ~200) -3. Use a gray-to-silver colormap for the metal -4. Add a clip plane to show the cylinder interiors -5. Apply appropriate lighting to enhance surface details - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "engine/results/engine.pvsm \ No newline at end of file diff --git a/sci_volume_data/engine/visualization_goals.txt b/sci_volume_data/engine/visualization_goals.txt deleted file mode 100644 index 3001c5561f5c61f6993a85a6db00b5ab17ed014c..0000000000000000000000000000000000000000 --- a/sci_volume_data/engine/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Engine? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? \ No newline at end of file diff --git a/sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272613.json b/sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272613.json deleted file mode 100644 index ca38923b1e40fc7eee8c2bfb7c3686a08a8b2689..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272613.json +++ /dev/null @@ -1,126 +0,0 @@ -{ - "status": "completed", - "case_name": "foot", - "model": "gpt-4o", - "evaluation_subtypes": [ - "vision" - ], - "subtype_results": { - "vision": { - "status": "completed", - "subtype": "vision", - "rubric": "- Successfully load the foot dataset\n- Enable volume rendering\n- Adjust opacity to show both bone and soft tissue structures\n- Apply appropriate color mapping for tissue differentiation\n- Use screenshot to verify foot bones (metatarsals, phalanges) and soft tissue are visible\n- Verify the colors match the instruction (white/beige for bone, reddish for soft tissue)", - "scores": { - "visualization_quality": 0, - "output_generation": 10, - "efficiency": 0, - "total_score": 18, - "max_possible_score": 20, - "percentage": 90.0 - }, - "image_metrics": { - "case_name": "foot", - "eval_mode": "mcp", - "calculation_time": "2025-09-30T18:50:13.895400", - "viewpoint_metrics": { - "diagonal": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "front": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "side": { - "psnr": null, - "ssim": null, - "lpips": null - } - }, - "averaged_metrics": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "valid_viewpoints": [], - "valid_viewpoint_count": 0, - "total_viewpoints": 3 - }, - "detailed_scores": { - "visualization_quality": { - "score": 0, - "max_score": 0, - "explanation": "Note: Ground truth state file not found (/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data/foot/GS/foot_gs.pvsm). Evaluation based on result screenshots only. The evaluation was conducted without ground truth images. The visualization shows a faint outline of the foot, indicating that the dataset was loaded and volume rendering was enabled, but the opacity is too high, obscuring details. The color mapping is partially correct with a reddish hue for soft tissue, but the bone structures are not clearly visible, and the expected white/beige color for bones is not evident. Improvements in opacity adjustment and color differentiation are needed.", - "llm_raw_response": { - "total_score": 15, - "overall_explanation": "The evaluation was conducted without ground truth images. The visualization shows a faint outline of the foot, indicating that the dataset was loaded and volume rendering was enabled, but the opacity is too high, obscuring details. The color mapping is partially correct with a reddish hue for soft tissue, but the bone structures are not clearly visible, and the expected white/beige color for bones is not evident. Improvements in opacity adjustment and color differentiation are needed.", - "evaluator_info": { - "evaluator_type": "llm", - "model": "gpt-4o", - "max_tokens": 1000, - "temperature": 0.1, - "provider": "openai", - "evaluator_version": "2.0.0", - "pricing_per_1m_tokens": { - "input": 2.5, - "cached_input": 1.25, - "output": 10.0, - "currency": "USD" - } - } - } - }, - "output_generation": { - "score": 10, - "max_score": 10, - "explanation": "ParaView state file generated successfully" - }, - "efficiency": { - "execution_time": { - "score": 4, - "max_score": 5, - "explanation": "Completed in 23.84 seconds (very good)" - }, - "token_usage": { - "score": 4, - "max_score": 5, - "explanation": "Total 514 tokens (efficient)" - } - } - }, - "evaluator_metadata": { - "evaluator_type": "mcp_auto", - "evaluator_version": "2.0.0", - "goals_count": 0, - "llm_evaluator": { - "evaluator_type": "llm", - "model": "gpt-4o", - "max_tokens": 1000, - "temperature": 0.1, - "provider": "openai", - "evaluator_version": "2.0.0", - "pricing_per_1m_tokens": { - "input": 2.5, - "cached_input": 1.25, - "output": 10.0, - "currency": "USD" - } - }, - "scoring_scheme": { - "visualization_quality": "0 points (10 per goal)", - "output_generation": "10 points", - "efficiency": "10 points", - "total_possible": "20 points" - } - } - } - }, - "scores": { - "total_score": 18, - "max_possible_score": 20, - "percentage": 90.0 - }, - "timestamp": "2025-09-30T18:50:13.897355" -} \ No newline at end of file diff --git a/sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272950.json b/sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272950.json deleted file mode 100644 index ef1eda97517795a76299cfcf238316f48954fd8a..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272950.json +++ /dev/null @@ -1,126 +0,0 @@ -{ - "status": "completed", - "case_name": "foot", - "model": "gpt-4o", - "evaluation_subtypes": [ - "vision" - ], - "subtype_results": { - "vision": { - "status": "completed", - "subtype": "vision", - "rubric": "- Successfully load the foot dataset\n- Enable volume rendering\n- Adjust opacity to show both bone and soft tissue structures\n- Apply appropriate color mapping for tissue differentiation\n- Use screenshot to verify foot bones (metatarsals, phalanges) and soft tissue are visible\n- Verify the colors match the instruction (white/beige for bone, reddish for soft tissue)", - "scores": { - "visualization_quality": 0, - "output_generation": 10, - "efficiency": 0, - "total_score": 14, - "max_possible_score": 20, - "percentage": 70.0 - }, - "image_metrics": { - "case_name": "foot", - "eval_mode": "mcp", - "calculation_time": "2025-09-30T18:55:50.731624", - "viewpoint_metrics": { - "diagonal": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "front": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "side": { - "psnr": null, - "ssim": null, - "lpips": null - } - }, - "averaged_metrics": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "valid_viewpoints": [], - "valid_viewpoint_count": 0, - "total_viewpoints": 3 - }, - "detailed_scores": { - "visualization_quality": { - "score": 0, - "max_score": 0, - "explanation": "Note: Ground truth state file not found (/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data/foot/GS/foot_gs.pvsm). Evaluation based on result screenshots only. The visualization appears to have successfully loaded the foot dataset, as indicated by the presence of a structure in the images. However, the volume rendering is not effectively showing the details of the foot, particularly the bones and soft tissue structures. The opacity settings seem too high, obscuring the internal structures. The color mapping is partially correct, with a reddish hue suggesting soft tissue, but the bone structures are not clearly visible or differentiated with white/beige colors. Overall, the visualization needs improvement in opacity adjustment and color mapping to better differentiate and display the anatomical structures.", - "llm_raw_response": { - "total_score": 15, - "overall_explanation": "The visualization appears to have successfully loaded the foot dataset, as indicated by the presence of a structure in the images. However, the volume rendering is not effectively showing the details of the foot, particularly the bones and soft tissue structures. The opacity settings seem too high, obscuring the internal structures. The color mapping is partially correct, with a reddish hue suggesting soft tissue, but the bone structures are not clearly visible or differentiated with white/beige colors. Overall, the visualization needs improvement in opacity adjustment and color mapping to better differentiate and display the anatomical structures.", - "evaluator_info": { - "evaluator_type": "llm", - "model": "gpt-4o", - "max_tokens": 1000, - "temperature": 0.1, - "provider": "openai", - "evaluator_version": "2.0.0", - "pricing_per_1m_tokens": { - "input": 2.5, - "cached_input": 1.25, - "output": 10.0, - "currency": "USD" - } - } - } - }, - "output_generation": { - "score": 10, - "max_score": 10, - "explanation": "ParaView state file generated successfully" - }, - "efficiency": { - "execution_time": { - "score": 1, - "max_score": 5, - "explanation": "Completed in 64.57 seconds (slow)" - }, - "token_usage": { - "score": 3, - "max_score": 5, - "explanation": "Total 1284 tokens (moderate)" - } - } - }, - "evaluator_metadata": { - "evaluator_type": "mcp_auto", - "evaluator_version": "2.0.0", - "goals_count": 0, - "llm_evaluator": { - "evaluator_type": "llm", - "model": "gpt-4o", - "max_tokens": 1000, - "temperature": 0.1, - "provider": "openai", - "evaluator_version": "2.0.0", - "pricing_per_1m_tokens": { - "input": 2.5, - "cached_input": 1.25, - "output": 10.0, - "currency": "USD" - } - }, - "scoring_scheme": { - "visualization_quality": "0 points (10 per goal)", - "output_generation": "10 points", - "efficiency": "10 points", - "total_possible": "20 points" - } - } - } - }, - "scores": { - "total_score": 14, - "max_possible_score": 20, - "percentage": 70.0 - }, - "timestamp": "2025-09-30T18:55:50.733365" -} \ No newline at end of file diff --git a/sci_volume_data/foot/evaluation_results/mcp/evaluation_results.json b/sci_volume_data/foot/evaluation_results/mcp/evaluation_results.json deleted file mode 100644 index c5706f57c7ef310b46f12917ef0c44d3d48ed8dd..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/evaluation_results/mcp/evaluation_results.json +++ /dev/null @@ -1,104 +0,0 @@ -{ - "case_name": "foot", - "evaluation_mode": "mcp", - "evaluation_time": "2025-09-30T18:55:40.426043", - "scores": { - "visualization_quality": { - "score": 0, - "max_score": 0, - "explanation": "Note: Ground truth state file not found (/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data/foot/GS/foot_gs.pvsm). Evaluation based on result screenshots only. The visualization appears to have successfully loaded the foot dataset, as indicated by the presence of a structure in the images. However, the volume rendering is not effectively showing the details of the foot, particularly the bones and soft tissue structures. The opacity settings seem too high, obscuring the internal structures. The color mapping is partially correct, with a reddish hue suggesting soft tissue, but the bone structures are not clearly visible or differentiated with white/beige colors. Overall, the visualization needs improvement in opacity adjustment and color mapping to better differentiate and display the anatomical structures.", - "llm_raw_response": { - "total_score": 15, - "overall_explanation": "The visualization appears to have successfully loaded the foot dataset, as indicated by the presence of a structure in the images. However, the volume rendering is not effectively showing the details of the foot, particularly the bones and soft tissue structures. The opacity settings seem too high, obscuring the internal structures. The color mapping is partially correct, with a reddish hue suggesting soft tissue, but the bone structures are not clearly visible or differentiated with white/beige colors. Overall, the visualization needs improvement in opacity adjustment and color mapping to better differentiate and display the anatomical structures.", - "evaluator_info": { - "evaluator_type": "llm", - "model": "gpt-4o", - "max_tokens": 1000, - "temperature": 0.1, - "provider": "openai", - "evaluator_version": "2.0.0", - "pricing_per_1m_tokens": { - "input": 2.5, - "cached_input": 1.25, - "output": 10.0, - "currency": "USD" - } - } - } - }, - "output_generation": { - "score": 10, - "max_score": 10, - "explanation": "ParaView state file generated successfully" - }, - "efficiency": { - "execution_time": { - "score": 1, - "max_score": 5, - "explanation": "Completed in 64.57 seconds (slow)" - }, - "token_usage": { - "score": 3, - "max_score": 5, - "explanation": "Total 1284 tokens (moderate)" - } - } - }, - "total_score": 14, - "max_possible_score": 20, - "image_metrics": { - "case_name": "foot", - "eval_mode": "mcp", - "calculation_time": "2025-09-30T18:55:50.731624", - "viewpoint_metrics": { - "diagonal": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "front": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "side": { - "psnr": null, - "ssim": null, - "lpips": null - } - }, - "averaged_metrics": { - "psnr": null, - "ssim": null, - "lpips": null - }, - "valid_viewpoints": [], - "valid_viewpoint_count": 0, - "total_viewpoints": 3 - }, - "evaluator_metadata": { - "evaluator_type": "mcp_auto", - "evaluator_version": "2.0.0", - "goals_count": 0, - "llm_evaluator": { - "evaluator_type": "llm", - "model": "gpt-4o", - "max_tokens": 1000, - "temperature": 0.1, - "provider": "openai", - "evaluator_version": "2.0.0", - "pricing_per_1m_tokens": { - "input": 2.5, - "cached_input": 1.25, - "output": 10.0, - "currency": "USD" - } - }, - "scoring_scheme": { - "visualization_quality": "0 points (10 per goal)", - "output_generation": "10 points", - "efficiency": "10 points", - "total_possible": "20 points" - } - } -} \ No newline at end of file diff --git a/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_diagonal_view.png b/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_diagonal_view.png deleted file mode 100644 index 41b4f864712a2c9e54968ef48580e0109aab43bc..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_diagonal_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e891abbc4cda61e5c429ec4eced20599abb63e1783c97ab8525668ddd8fffe8a -size 94322 diff --git a/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_front_view.png b/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_front_view.png deleted file mode 100644 index aa254eb1bcbbd9211470b0fca15fd0a87d35e6dc..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_front_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:1560b1d9da8959f62ab6aa0c60aa1a457d26edf6987f95a9b2859edc06f80db6 -size 81275 diff --git a/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_side_view.png b/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_side_view.png deleted file mode 100644 index c6b8326959154bd8f45f8198a322896bc1994077..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/evaluation_results/mcp/screenshots/result_side_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:9ee2b4a178edb002f4d92d9ebff58e413afc7776dd75f48f622cae788e0b99eb -size 57097 diff --git a/sci_volume_data/foot/results/mcp/foot.pvsm b/sci_volume_data/foot/results/mcp/foot.pvsm deleted file mode 100644 index 6515e118d85d704f4912c0642bd6a85f6bdebfbc..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/results/mcp/foot.pvsm +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:cb201f103bbd98a6b11bfe7cdeb6643e6301dc7f894cef4e7348f17971f8ce09 -size 231778 diff --git a/sci_volume_data/foot/task_description.txt b/sci_volume_data/foot/task_description.txt deleted file mode 100644 index 54944fca4827ddc8bb1fb2ff708f443cc8343bf4..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/task_description.txt +++ /dev/null @@ -1,19 +0,0 @@ -Task: - -Load the Foot dataset from "foot/data/foot_256x256x256_uint8.raw", the information about this dataset: -Foot -Description: Rotational C-arm x-ray scan of a human foot. Tissue and bone are present in the dataset. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x256 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the anatomical structures: -1. Create two isosurfaces: one for soft tissue (lower value ~50-80, semi-transparent red, opacity 0.3) and one for bone (higher value ~150-200, opaque white, opacity 0.9) -2. Apply volume rendering with a transfer function that distinguishes tissue types -3. Use appropriate lighting to enhance surface details - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "foot/results/foot.pvsm" \ No newline at end of file diff --git a/sci_volume_data/foot/test_results/mcp/test_result_1759272600.json b/sci_volume_data/foot/test_results/mcp/test_result_1759272600.json deleted file mode 100644 index efe4c5c16348e168eeaac0b390d7234103890a4e..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/test_results/mcp/test_result_1759272600.json +++ /dev/null @@ -1,31 +0,0 @@ -{ - "timestamp": "2025-09-30T18:50:00.397463", - "case_name": "foot", - "status": "completed", - "duration": 23.8377, - "token_usage": { - "input_tokens": 203, - "output_tokens": 311, - "total_tokens": 514 - }, - "response": "\n[Tool: list_allowed_directories] Allowed directories:\n/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 0 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: get_available_arrays] Available arrays:\n\nPoint data arrays:\n- ImageFile (1 components)\n\nCell data arrays:\n\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'ImageFile'.\n[Tool: set_color_map] Color transfer function updated for field 'ImageFile'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm\n[Tool: task_complete] ", - "task_description": "Your agent_mode is \"mcp\", use it when saving results. Your working directory is \"/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data\", and you should have access to it. In the following prompts, we will use relative path with respect to your working path. But remember, when you load or save any file, always stick to absolute path.\n\nClear the ParaView pipeline and load the data file \"foot/data/foot_256x256x256_uint8.raw\".\n1. Enable volume rendering to visualize the internal structures\n2. Adjust the opacity transfer function to reveal both bone and soft tissue (bone should be more opaque, soft tissue semi-transparent)\n3. Set an appropriate color map to differentiate tissue types (e.g., white/beige for bone, reddish for soft tissue)\nFinally, save the paraview state as \"foot/results/{agent_mode}/foot.pvsm\"", - "full_result": { - "case_name": "foot", - "status": "completed", - "start_time": "2025-09-30T18:49:36.558586", - "task_description": "Your agent_mode is \"mcp\", use it when saving results. Your working directory is \"/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data\", and you should have access to it. In the following prompts, we will use relative path with respect to your working path. But remember, when you load or save any file, always stick to absolute path.\n\nClear the ParaView pipeline and load the data file \"foot/data/foot_256x256x256_uint8.raw\".\n1. Enable volume rendering to visualize the internal structures\n2. Adjust the opacity transfer function to reveal both bone and soft tissue (bone should be more opaque, soft tissue semi-transparent)\n3. Set an appropriate color map to differentiate tissue types (e.g., white/beige for bone, reddish for soft tissue)\nFinally, save the paraview state as \"foot/results/{agent_mode}/foot.pvsm\"", - "llm_rubric": "- Successfully load the foot dataset\n- Enable volume rendering\n- Adjust opacity to show both bone and soft tissue structures\n- Apply appropriate color mapping for tissue differentiation\n- Use screenshot to verify foot bones (metatarsals, phalanges) and soft tissue are visible\n- Verify the colors match the instruction (white/beige for bone, reddish for soft tissue)", - "evaluation_subtype": "vision", - "is_vision_evaluation": true, - "response": "\n[Tool: list_allowed_directories] Allowed directories:\n/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 0 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: get_available_arrays] Available arrays:\n\nPoint data arrays:\n- ImageFile (1 components)\n\nCell data arrays:\n\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'ImageFile'.\n[Tool: set_color_map] Color transfer function updated for field 'ImageFile'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm\n[Tool: task_complete] ", - "error": null, - "token_usage": { - "input_tokens": 203, - "output_tokens": 311, - "total_tokens": 514 - }, - "end_time": "2025-09-30T18:50:00.396286", - "duration_seconds": 23.8377 - } -} \ No newline at end of file diff --git a/sci_volume_data/foot/test_results/mcp/test_result_1759272935.json b/sci_volume_data/foot/test_results/mcp/test_result_1759272935.json deleted file mode 100644 index 4608ae3bf92fe91afc877ebf80258bdcfe12d672..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/test_results/mcp/test_result_1759272935.json +++ /dev/null @@ -1,31 +0,0 @@ -{ - "timestamp": "2025-09-30T18:55:35.547643", - "case_name": "foot", - "status": "completed", - "duration": 64.567009, - "token_usage": { - "input_tokens": 203, - "output_tokens": 1081, - "total_tokens": 1284 - }, - "response": "\n[Tool: list_allowed_directories] Allowed directories:\n/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 0 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'Scalars'.\n[Tool: set_color_map] Color transfer function updated for field 'Scalars'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsmThe volume data has been loaded and visualized with volume rendering enabled. The opacity and color maps have been adjusted to highlight bone and soft tissue structures, with bones appearing more opaque and soft tissues in reddish tones. The ParaView state has been successfully saved at:\n\n`/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm`\n\nIf you need further assistance, feel free to ask!\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 1 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'ImageReader1'.\n[Tool: set_color_map] Color transfer function updated for field 'ImageReader1'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsmThe volume data for the foot has been successfully loaded and visualized with volume rendering enabled. The opacity and color maps are set to differentiate tissue types, highlighting bones with more opacity and soft tissues with reddish colors. The ParaView state has been saved at:\n\n`/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm`\n\nIf there's anything else you need, please feel free to ask!\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 1 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'Scalars'.\n[Tool: set_color_map] Color transfer function updated for field 'Scalars'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsmThe volume data has been loaded and visualized with volume rendering enabled. The opacity and color maps have been adjusted to highlight bone and soft tissue structures, with bones appearing more opaque and soft tissues in reddish tones. The ParaView state has been successfully saved at:\n\n`/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm`\n\nIf you need further assistance, feel free to ask!", - "task_description": "Your agent_mode is \"mcp\", use it when saving results. Your working directory is \"/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data\", and you should have access to it. In the following prompts, we will use relative path with respect to your working path. But remember, when you load or save any file, always stick to absolute path.\n\nClear the ParaView pipeline and load the data file \"foot/data/foot_256x256x256_uint8.raw\".\n1. Enable volume rendering to visualize the internal structures\n2. Adjust the opacity transfer function to reveal both bone and soft tissue (bone should be more opaque, soft tissue semi-transparent)\n3. Set an appropriate color map to differentiate tissue types (e.g., white/beige for bone, reddish for soft tissue)\nFinally, save the paraview state as \"foot/results/{agent_mode}/foot.pvsm\"", - "full_result": { - "case_name": "foot", - "status": "completed", - "start_time": "2025-09-30T18:54:30.980432", - "task_description": "Your agent_mode is \"mcp\", use it when saving results. Your working directory is \"/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/benchmark/../SciVisAgentBench-tasks/sci_volume_data\", and you should have access to it. In the following prompts, we will use relative path with respect to your working path. But remember, when you load or save any file, always stick to absolute path.\n\nClear the ParaView pipeline and load the data file \"foot/data/foot_256x256x256_uint8.raw\".\n1. Enable volume rendering to visualize the internal structures\n2. Adjust the opacity transfer function to reveal both bone and soft tissue (bone should be more opaque, soft tissue semi-transparent)\n3. Set an appropriate color map to differentiate tissue types (e.g., white/beige for bone, reddish for soft tissue)\nFinally, save the paraview state as \"foot/results/{agent_mode}/foot.pvsm\"", - "llm_rubric": "- Successfully load the foot dataset\n- Enable volume rendering\n- Adjust opacity to show both bone and soft tissue structures\n- Apply appropriate color mapping for tissue differentiation\n- Use screenshot to verify foot bones (metatarsals, phalanges) and soft tissue are visible\n- Verify the colors match the instruction (white/beige for bone, reddish for soft tissue)", - "evaluation_subtype": "vision", - "is_vision_evaluation": true, - "response": "\n[Tool: list_allowed_directories] Allowed directories:\n/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 0 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'Scalars'.\n[Tool: set_color_map] Color transfer function updated for field 'Scalars'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsmThe volume data has been loaded and visualized with volume rendering enabled. The opacity and color maps have been adjusted to highlight bone and soft tissue structures, with bones appearing more opaque and soft tissues in reddish tones. The ParaView state has been successfully saved at:\n\n`/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm`\n\nIf you need further assistance, feel free to ask!\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 1 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'ImageReader1'.\n[Tool: set_color_map] Color transfer function updated for field 'ImageReader1'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsmThe volume data for the foot has been successfully loaded and visualized with volume rendering enabled. The opacity and color maps are set to differentiate tissue types, highlighting bones with more opacity and soft tissues with reddish colors. The ParaView state has been saved at:\n\n`/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm`\n\nIf there's anything else you need, please feel free to ask!\n[Tool: clear_pipeline_and_reset] Pipeline cleared successfully. Removed 1 source(s) and reset all view settings.\n[Tool: load_data] Successfully loaded data from /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/data/foot_256x256x256_uint8.raw. Source registered as 'ImageReader1'.\n[Tool: toggle_volume_rendering] Volume rendering enabled. Source registered as 'ImageReader1'.\n[Tool: edit_volume_opacity] Opacity transfer function updated for field 'Scalars'.\n[Tool: set_color_map] Color transfer function updated for field 'Scalars'.\n[Tool: create_directory] Successfully created directory /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp\n[Tool: save_paraview_state] ParaView state saved successfully to: /Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsmThe volume data has been loaded and visualized with volume rendering enabled. The opacity and color maps have been adjusted to highlight bone and soft tissue structures, with bones appearing more opaque and soft tissues in reddish tones. The ParaView state has been successfully saved at:\n\n`/Users/kuangshiai/Documents/ND-VIS/Code/SciVisAgentBench/SciVisAgentBench-tasks/sci_volume_data/foot/results/mcp/foot.pvsm`\n\nIf you need further assistance, feel free to ask!", - "error": null, - "token_usage": { - "input_tokens": 203, - "output_tokens": 1081, - "total_tokens": 1284 - }, - "end_time": "2025-09-30T18:55:35.547441", - "duration_seconds": 64.567009 - } -} \ No newline at end of file diff --git a/sci_volume_data/foot/visualization_goals.txt b/sci_volume_data/foot/visualization_goals.txt deleted file mode 100644 index c7877a71743092589e2220e9331719fa4cda1ab8..0000000000000000000000000000000000000000 --- a/sci_volume_data/foot/visualization_goals.txt +++ /dev/null @@ -1,6 +0,0 @@ -- Successfully load the foot dataset -- Enable volume rendering -- Adjust opacity to show both bone and soft tissue structures -- Apply appropriate color mapping for tissue differentiation -- Use screenshot to verify foot bones (metatarsals, phalanges) and soft tissue are visible -- Verify the colors match the instruction (white/beige for bone, reddish for soft tissue) \ No newline at end of file diff --git a/sci_volume_data/frog/task_description.txt b/sci_volume_data/frog/task_description.txt deleted file mode 100644 index 581b5326f317439de8812d388ad99dbced93b88d..0000000000000000000000000000000000000000 --- a/sci_volume_data/frog/task_description.txt +++ /dev/null @@ -1,19 +0,0 @@ -Task: - -Load the Frog dataset from "frog/data/frog_256x256x44_uint8.raw", the information about this dataset: -Frog -Description: MRI scan of a frog as part of the Whole Frog Project. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 0.5x0.5x1 -Data Extent: 256x256x44 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the anatomical structures: -1. Apply volume rendering with appropriate transfer function for tissue differentiation -2. Create isosurfaces at two different density values to show different tissue types -3. Use contrasting colors for different structures (e.g., red for soft tissue, white for dense material) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "frog/results/frog.pvsm" \ No newline at end of file diff --git a/sci_volume_data/frog/visualization_goals.txt b/sci_volume_data/frog/visualization_goals.txt deleted file mode 100644 index c9927833d074e6568fff9611326de47ec17223b3..0000000000000000000000000000000000000000 --- a/sci_volume_data/frog/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the Frog dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures? diff --git a/sci_volume_data/fuel/task_description.txt b/sci_volume_data/fuel/task_description.txt deleted file mode 100644 index c78bcb3b8bce58af5f7ee8d8e21544531cc5672f..0000000000000000000000000000000000000000 --- a/sci_volume_data/fuel/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Fuel dataset from "fuel/data/fuel_64x64x64_uint8.raw", the information about this dataset: -Fuel -Description: Simulation of fuel injection into a combustion chamber. The higher the density value, the less presence of air. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 64x64x64 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the combustion/fuel injection process: -1. Apply volume rendering with a hot colormap (black-red-yellow-white) to show temperature/density variations -2. Create an isosurface at the fuel-air mixture boundary (mid-range value) -3. Add a slice plane through the center to show the injection pattern -4. Adjust opacity to reveal the combustion core (opacity 0.4-0.6) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "fuel/results/fuel.pvsm" \ No newline at end of file diff --git a/sci_volume_data/fuel/visualization_goals.txt b/sci_volume_data/fuel/visualization_goals.txt deleted file mode 100644 index c46995098937e2768191595bd37b9ca14140661d..0000000000000000000000000000000000000000 --- a/sci_volume_data/fuel/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively convey the physics/dynamics of the Fuel simulation? - -2. Feature Detection: Are the key features (shock fronts, vortices, mixing regions) clearly visible? - -3. Color Mapping: Does the colormap appropriately represent the physical quantity being visualized? - -4. Spatial Understanding: Do the isosurfaces and slices provide good insight into the 3D structure? diff --git a/sci_volume_data/hydrogen_atom/task_description.txt b/sci_volume_data/hydrogen_atom/task_description.txt deleted file mode 100644 index add03cf63bc8422c74bfea17d761eeff5a9e7712..0000000000000000000000000000000000000000 --- a/sci_volume_data/hydrogen_atom/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Hydrogen Atom dataset from "hydrogen_atom/data/hydrogen_atom_128x128x128_uint8.raw", the information about this dataset: -Hydrogen Atom -Description: Simulation of the spatial probability distribution of the electron in an hydrogen atom, residing in a strong magnetic field. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 128x128x128 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the electron probability distribution: -1. Apply volume rendering with a colormap showing probability density (purple-blue-cyan-yellow) -2. Create multiple isosurfaces at different probability levels (e.g., 30%, 60%, 90% of max) -3. Use semi-transparent rendering for outer orbitals (opacity 0.3) and more opaque for inner (opacity 0.7) -4. Add a slice plane through the center to show the wavefunction structure - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "hydrogen_atom/results/hydrogen_atom.pvsm" \ No newline at end of file diff --git a/sci_volume_data/hydrogen_atom/visualization_goals.txt b/sci_volume_data/hydrogen_atom/visualization_goals.txt deleted file mode 100644 index cb789a323d496499850b6e0cda4294fb66e0e4b3..0000000000000000000000000000000000000000 --- a/sci_volume_data/hydrogen_atom/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization accurately represent the molecular/atomic structure in the Hydrogen Atom dataset? - -2. Probability/Density: Are the probability distributions or electron densities clearly shown? - -3. Scientific Accuracy: Do the isosurfaces correspond to meaningful probability/density levels? - -4. Structure Clarity: Is the overall molecular/atomic arrangement clearly visible? diff --git a/sci_volume_data/lobster/task_description.txt b/sci_volume_data/lobster/task_description.txt deleted file mode 100644 index d96798dccd597c0055f99900bf01048a7b4d8f25..0000000000000000000000000000000000000000 --- a/sci_volume_data/lobster/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Lobster dataset from "lobster/data/lobster_301x324x56_uint8.raw", the information about this dataset: -Lobster -Description: CT scan of a lobster contained in a block of resin. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1.4 -Data Extent: 301x324x56 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the scanned specimen: -1. Apply volume rendering to show the full structure -2. Create an isosurface at the specimen boundary -3. Use natural colors appropriate for the specimen (red-orange for lobster) -4. Adjust opacity to show internal features if present - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "lobster/results/lobster.pvsm \ No newline at end of file diff --git a/sci_volume_data/lobster/visualization_goals.txt b/sci_volume_data/lobster/visualization_goals.txt deleted file mode 100644 index 50ee7a3b66f7d675561ae517746017b00f904320..0000000000000000000000000000000000000000 --- a/sci_volume_data/lobster/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Lobster? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? \ No newline at end of file diff --git a/sci_volume_data/marschner_lobb/task_description.txt b/sci_volume_data/marschner_lobb/task_description.txt deleted file mode 100644 index d14d6e8d90a698a337c388c2e833dc8828e196a8..0000000000000000000000000000000000000000 --- a/sci_volume_data/marschner_lobb/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Marschner-Lobb dataset from "marschner_lobb/data/marschner_lobb_41x41x41_uint8.raw", the information about this dataset: -Marschner-Lobb -Description: High frequencies where 99% of the sinusoids are right below the Nyquist frequency. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 41x41x41 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the simulation data: -1. Apply volume rendering with an appropriate colormap for the physical quantity -2. Create isosurfaces at key values to highlight important features -3. Add a slice plane to show internal distribution -4. Adjust transfer function to reveal gradients and boundaries - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "marschner_lobb/results/marschner_lobb.pvsm" \ No newline at end of file diff --git a/sci_volume_data/marschner_lobb/visualization_goals.txt b/sci_volume_data/marschner_lobb/visualization_goals.txt deleted file mode 100644 index 5f78786232376b05e8811e7ec637dcdd3092e2cc..0000000000000000000000000000000000000000 --- a/sci_volume_data/marschner_lobb/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively convey the physics/dynamics of the Marschner-Lobb simulation? - -2. Feature Detection: Are the key features (shock fronts, vortices, mixing regions) clearly visible? - -3. Color Mapping: Does the colormap appropriately represent the physical quantity being visualized? - -4. Spatial Understanding: Do the isosurfaces and slices provide good insight into the 3D structure? diff --git a/sci_volume_data/mri_ventricles/task_description.txt b/sci_volume_data/mri_ventricles/task_description.txt deleted file mode 100644 index 357bb5ab3586c8a3075b8084d3c86ec07129e2a9..0000000000000000000000000000000000000000 --- a/sci_volume_data/mri_ventricles/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Head MRI CISS dataset from "mri_ventricles/data/mri_ventricles_256x256x124_uint8.raw", the information about this dataset: -Head MRI CISS -Description: 1.5T MRT 3D CISS dataset of a human head that highlights the CSF (Cerebro-Spinal-Fluid) filled cavities of the head. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 0.9x0.9x0.9 -Data Extent: 256x256x124 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the brain structures: -1. Apply volume rendering with a grayscale-to-color transfer function -2. Create a clip plane to show internal brain structures -3. Extract an isosurface for the skull or brain boundary (value around 80-120) -4. Use semi-transparent rendering (opacity 0.5-0.7) to show layers - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "mri_ventricles/results/mri_ventricles.pvsm" \ No newline at end of file diff --git a/sci_volume_data/mri_ventricles/visualization_goals.txt b/sci_volume_data/mri_ventricles/visualization_goals.txt deleted file mode 100644 index 07825a0198779d4de4a36a1f4824fc5b9b2209a1..0000000000000000000000000000000000000000 --- a/sci_volume_data/mri_ventricles/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the Head MRI CISS dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures? diff --git a/sci_volume_data/mri_woman/task_description.txt b/sci_volume_data/mri_woman/task_description.txt deleted file mode 100644 index f52f08fc7b6cb05653215cc95b5e2530fb9fa4d1..0000000000000000000000000000000000000000 --- a/sci_volume_data/mri_woman/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the MRI Woman dataset from "mri_woman/data/mri_woman_256x256x109_uint16.raw", the information about this dataset: -MRI Woman -Description: MRI scan of a woman's head -Data Type: uint16 -Data Byte Order: little Endian -Data Spacing: 1x1x1.5 -Data Extent: 256x256x109 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the brain structures: -1. Apply volume rendering with a grayscale-to-color transfer function -2. Create a clip plane to show internal brain structures -3. Extract an isosurface for the skull or brain boundary (value around 80-120) -4. Use semi-transparent rendering (opacity 0.5-0.7) to show layers - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "mri_woman/results/mri_woman.pvsm" \ No newline at end of file diff --git a/sci_volume_data/mri_woman/visualization_goals.txt b/sci_volume_data/mri_woman/visualization_goals.txt deleted file mode 100644 index bdf67b6734b36fe99f2da85f9f2c44fb9ea5d478..0000000000000000000000000000000000000000 --- a/sci_volume_data/mri_woman/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the MRI Woman dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures? diff --git a/sci_volume_data/mrt_angio/task_description.txt b/sci_volume_data/mrt_angio/task_description.txt deleted file mode 100644 index f5fdce770242455a3d8ff93b77d7ceac4d20e883..0000000000000000000000000000000000000000 --- a/sci_volume_data/mrt_angio/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Head MRT Angiography dataset from "mrt_angio/data/mrt_angio_416x512x112_uint16.raw", the information about this dataset: -Head MRT Angiography -Description: 3T MRT Time-of-Flight Angiography dataset of a human head. The dataset has been resampled into an isotropic voxel grid (hence the peculiar slice size). -Data Type: uint16 -Data Byte Order: little Endian -Data Spacing: 0.412x0.412x0.412 -Data Extent: 416x512x112 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the blood vessels using: -1. Apply volume rendering with a transfer function that highlights the contrast-enhanced vessels -2. Use a red-to-white color map for blood vessels -3. Extract an isosurface at a value that clearly shows the aneurism or vessel structure (experiment with values around 100-150) -4. Adjust opacity to make internal structures visible (opacity around 0.6-0.8 for vessels) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "mrt_angio/results/mrt_angio.pvsm" \ No newline at end of file diff --git a/sci_volume_data/mrt_angio/visualization_goals.txt b/sci_volume_data/mrt_angio/visualization_goals.txt deleted file mode 100644 index 392ef52b88061e278a83223e053239741c447f4d..0000000000000000000000000000000000000000 --- a/sci_volume_data/mrt_angio/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the blood vessel network and highlight the aneurism or vascular structures? - -2. Transfer Function: Is the contrast agent properly highlighted with appropriate color mapping? - -3. Isosurface Quality: Does the isosurface accurately capture the vessel boundaries? - -4. Clinical Relevance: Can medical professionals identify the key anatomical features and any abnormalities? diff --git a/sci_volume_data/neghip/task_description.txt b/sci_volume_data/neghip/task_description.txt deleted file mode 100644 index b34e5fd71e45a1fcb7739ebc937430900217f9f2..0000000000000000000000000000000000000000 --- a/sci_volume_data/neghip/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Neghip dataset from "neghip/data/neghip_64x64x64_uint8.raw", the information about this dataset: -Neghip -Description: Simulation of the spatial probability distribution of the electrons in a high potential protein molecule. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 64x64x64 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the protein electron distribution: -1. Apply volume rendering for the electron density -2. Use a diverging colormap (blue for low, red for high potential) -3. Create isosurfaces at the molecular boundary -4. Adjust opacity to show internal charge distribution - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "neghip/results/neghip.pvsm" \ No newline at end of file diff --git a/sci_volume_data/neghip/visualization_goals.txt b/sci_volume_data/neghip/visualization_goals.txt deleted file mode 100644 index db6b84d420ed5d2f89affaf13e08a2c39600b2f6..0000000000000000000000000000000000000000 --- a/sci_volume_data/neghip/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization accurately represent the molecular/atomic structure in the Neghip dataset? - -2. Probability/Density: Are the probability distributions or electron densities clearly shown? - -3. Scientific Accuracy: Do the isosurfaces correspond to meaningful probability/density levels? - -4. Structure Clarity: Is the overall molecular/atomic arrangement clearly visible? diff --git a/sci_volume_data/neocortical_layer_1_axons/task_description.txt b/sci_volume_data/neocortical_layer_1_axons/task_description.txt deleted file mode 100644 index c41c6ef42628ef45a2b549291d3e7fc4638d0891..0000000000000000000000000000000000000000 --- a/sci_volume_data/neocortical_layer_1_axons/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Neocortical Layer 1 Axons dataset from "neocortical_layer_1_axons/data/neocortical_layer_1_axons_1464x1033x76_uint8.raw", the information about this dataset: -Neocortical Layer 1 Axons -Description: Axons in layer 1 of the mouse barrel cortex imaged in vivo. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x3.4 -Data Extent: 1464x1033x76 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the scanned object: -1. Apply volume rendering with appropriate transfer function -2. Create an isosurface at the object boundary -3. Use realistic colors for the material -4. Add clipping or transparency to show internal structure - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "neocortical_layer_1_axons/results/neocortical_layer_1_axons.pvsm" \ No newline at end of file diff --git a/sci_volume_data/neocortical_layer_1_axons/visualization_goals.txt b/sci_volume_data/neocortical_layer_1_axons/visualization_goals.txt deleted file mode 100644 index 32e25e66097a65c0f283615bc01a65dbc96a2aa1..0000000000000000000000000000000000000000 --- a/sci_volume_data/neocortical_layer_1_axons/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Neocortical Layer 1 Axons? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? diff --git a/sci_volume_data/nucleon/task_description.txt b/sci_volume_data/nucleon/task_description.txt deleted file mode 100644 index b24c3ac8c562e3d0d0452227e1753dcda145c49e..0000000000000000000000000000000000000000 --- a/sci_volume_data/nucleon/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Nucleon dataset from "nucleon/data/nucleon_41x41x41_uint8.raw", the information about this dataset: -Nucleon -Description: Simulation of the two-body distribution probability of a nucleon in the atomic nucleus 16O if a second nucleon is known to be positioned at r'=(2 fm,0,0). -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 41x41x41 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the nucleon distribution: -1. Apply volume rendering to show the probability distribution -2. Use a scientific colormap (viridis or plasma) for the density -3. Create isosurfaces at probability peaks -4. Add orthogonal slice planes to show the 3D distribution - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "nucleon/results/nucleon.pvsm" \ No newline at end of file diff --git a/sci_volume_data/nucleon/visualization_goals.txt b/sci_volume_data/nucleon/visualization_goals.txt deleted file mode 100644 index a159ac73d80213acf2ca03918b14405af610add8..0000000000000000000000000000000000000000 --- a/sci_volume_data/nucleon/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization accurately represent the molecular/atomic structure in the Nucleon dataset? - -2. Probability/Density: Are the probability distributions or electron densities clearly shown? - -3. Scientific Accuracy: Do the isosurfaces correspond to meaningful probability/density levels? - -4. Structure Clarity: Is the overall molecular/atomic arrangement clearly visible? diff --git a/sci_volume_data/pancreas/task_description.txt b/sci_volume_data/pancreas/task_description.txt deleted file mode 100644 index 88358eac5b661af5a81bc32586ab75b3df27dc36..0000000000000000000000000000000000000000 --- a/sci_volume_data/pancreas/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Pancreas dataset from "pancreas/data/pancreas_240x512x512_int16.raw", the information about this dataset: -Pancreas -Description: First scan. The National Institutes of Health Clinical Center performed 82 abdominal contrast enhanced 3D CT scans (~70 seconds after intravenous contrast injection in portal-venous) from 53 male and 27 female subjects. Seventeen of the subjects are healthy kidney donors scanned prior to nephrectomy. The remaining 65 patients were selected by a radiologist from patients who neither had major abdominal pathologies nor pancreatic cancer lesions. Subjects' ages range from 18 to 76 years with a mean age of 46.8 ± 16.7. The CT scans have resolutions of 512x512 pixels with varying pixel sizes and slice thickness between 1.5 - 2.5 mm, acquired on Philips and Siemens MDCT scanners (120 kVp tube voltage). A medical student manually performed slice-by-slice segmentations of the pancreas as ground-truth and these were verified/modified by an experienced radiologist. -Data Type: int16 -Data Byte Order: little Endian -Data Spacing: 1.16x1.0x1.0 -Data Extent: 240x512x512 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the organ structure: -1. Apply volume rendering to show the organ's internal structure -2. Create an isosurface at the organ boundary (experiment with threshold values) -3. Use a warm color map (red-orange) for the organ tissue -4. Add a cutting plane to reveal internal anatomy - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "pancreas/results/pancreas.pvsm \ No newline at end of file diff --git a/sci_volume_data/pancreas/visualization_goals.txt b/sci_volume_data/pancreas/visualization_goals.txt deleted file mode 100644 index 1b5c464b31b3d55666513dd3b348272a93cf7392..0000000000000000000000000000000000000000 --- a/sci_volume_data/pancreas/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the Pancreas dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures? \ No newline at end of file diff --git a/sci_volume_data/shockwave/task_description.txt b/sci_volume_data/shockwave/task_description.txt deleted file mode 100644 index 2a1e5f280053a6b29f72ef1c8c2e29a282e9a33b..0000000000000000000000000000000000000000 --- a/sci_volume_data/shockwave/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Shockwave dataset from "shockwave/data/shockwave_64x64x512_uint8.raw", the information about this dataset: -Shockwave -Description: Simulation of an unsteady interaction of a planar shockwave with a randomly-perturbed contact discontinuity. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 64x64x512 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the shockwave propagation: -1. Apply volume rendering with a sharp transfer function to capture the shock front -2. Use a diverging colormap (blue-white-red) to show pressure variations -3. Create an isosurface at the shock front location -4. Add multiple slice planes perpendicular to the shock direction - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "shockwave/results/shockwave.pvsm" \ No newline at end of file diff --git a/sci_volume_data/shockwave/visualization_goals.txt b/sci_volume_data/shockwave/visualization_goals.txt deleted file mode 100644 index 0d849a0195e5b11da99b3c876abbe539c5d0114d..0000000000000000000000000000000000000000 --- a/sci_volume_data/shockwave/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively convey the physics/dynamics of the Shockwave simulation? - -2. Feature Detection: Are the key features (shock fronts, vortices, mixing regions) clearly visible? - -3. Color Mapping: Does the colormap appropriately represent the physical quantity being visualized? - -4. Spatial Understanding: Do the isosurfaces and slices provide good insight into the 3D structure? diff --git a/sci_volume_data/silicium/task_description.txt b/sci_volume_data/silicium/task_description.txt deleted file mode 100644 index 7e432c33fa3a64db13a31d442eb83c636ff50b6f..0000000000000000000000000000000000000000 --- a/sci_volume_data/silicium/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Silicium dataset from "silicium/data/silicium_98x34x34_uint8.raw", the information about this dataset: -Silicium -Description: Simulation of a silicium grid. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 98x34x34 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the crystal lattice structure: -1. Apply volume rendering to show the atomic density -2. Create isosurfaces at atomic positions -3. Use a metallic colormap (silver-blue) -4. Add a clip plane to reveal the lattice arrangement - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "silicium/results/silicium.pvsm" \ No newline at end of file diff --git a/sci_volume_data/silicium/visualization_goals.txt b/sci_volume_data/silicium/visualization_goals.txt deleted file mode 100644 index bcbe025756cb9ca0fed57bd1cfeb288acef22106..0000000000000000000000000000000000000000 --- a/sci_volume_data/silicium/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization accurately represent the molecular/atomic structure in the Silicium dataset? - -2. Probability/Density: Are the probability distributions or electron densities clearly shown? - -3. Scientific Accuracy: Do the isosurfaces correspond to meaningful probability/density levels? - -4. Structure Clarity: Is the overall molecular/atomic arrangement clearly visible? diff --git a/sci_volume_data/skull/task_description.txt b/sci_volume_data/skull/task_description.txt deleted file mode 100644 index 22923eb6b535b6334564e823c619708e4ced84b8..0000000000000000000000000000000000000000 --- a/sci_volume_data/skull/task_description.txt +++ /dev/null @@ -1,19 +0,0 @@ -Task: - -Load the Skull dataset from "skull/data/skull_256x256x256_uint8.raw", the information about this dataset: -Skull -Description: Rotational C-arm x-ray scan of phantom of a human skull. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x256 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the anatomical structures: -1. Create two isosurfaces: one for soft tissue (lower value ~50-80, semi-transparent red, opacity 0.3) and one for bone (higher value ~150-200, opaque white, opacity 0.9) -2. Apply volume rendering with a transfer function that distinguishes tissue types -3. Use appropriate lighting to enhance surface details - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "skull/results/skull.pvsm" \ No newline at end of file diff --git a/sci_volume_data/skull/visualization_goals.txt b/sci_volume_data/skull/visualization_goals.txt deleted file mode 100644 index 9f2684734ad3410f1ab1c5c559ae53025da7ee78..0000000000000000000000000000000000000000 --- a/sci_volume_data/skull/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the Skull dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures? diff --git a/sci_volume_data/statue_leg/task_description.txt b/sci_volume_data/statue_leg/task_description.txt deleted file mode 100644 index 92db2ffdbc1544fb0abd1b32140ea84f5b4d3827..0000000000000000000000000000000000000000 --- a/sci_volume_data/statue_leg/task_description.txt +++ /dev/null @@ -1,19 +0,0 @@ -Task: - -Load the Leg of Statue dataset from "statue_leg/data/statue_leg_341x341x93_uint8.raw", the information about this dataset: -Leg of Statue -Description: CT scan of a leg of a bronze statue. -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x4 -Data Extent: 341x341x93 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the anatomical structures: -1. Apply volume rendering with appropriate transfer function for tissue differentiation -2. Create isosurfaces at two different density values to show different tissue types -3. Use contrasting colors for different structures (e.g., red for soft tissue, white for dense material) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "statue_leg/results/statue_leg.pvsm" \ No newline at end of file diff --git a/sci_volume_data/statue_leg/visualization_goals.txt b/sci_volume_data/statue_leg/visualization_goals.txt deleted file mode 100644 index eefa31c8bfbb2b323f894a2f74c17c68e9d05c8e..0000000000000000000000000000000000000000 --- a/sci_volume_data/statue_leg/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the Leg of Statue dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures? diff --git a/sci_volume_data/stent/task_description.txt b/sci_volume_data/stent/task_description.txt deleted file mode 100644 index d9b8f80aaf852685a073a1377ec17d3611fa1f5d..0000000000000000000000000000000000000000 --- a/sci_volume_data/stent/task_description.txt +++ /dev/null @@ -1,19 +0,0 @@ -Task: - -Load the Stented Abdominal Aorta dataset from "stent/data/stent_512x512x174_uint16.raw", the information about this dataset: -Stented Abdominal Aorta -Description: CT Scan of the abdomen and pelvis. The dataset contains also a stent in the abdominal aorta. No contrast agent was used to enhance the blood vessels. -Data Type: uint16 -Data Byte Order: little Endian -Data Spacing: 0.8398x0.8398x3.2 -Data Extent: 512x512x174 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the anatomical structures: -1. Apply volume rendering with appropriate transfer function for tissue differentiation -2. Create isosurfaces at two different density values to show different tissue types -3. Use contrasting colors for different structures (e.g., red for soft tissue, white for dense material) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "stent/results/stent.pvsm" \ No newline at end of file diff --git a/sci_volume_data/stent/visualization_goals.txt b/sci_volume_data/stent/visualization_goals.txt deleted file mode 100644 index 4dc93073bf66bc2b811a43a252fbbb086ebe011e..0000000000000000000000000000000000000000 --- a/sci_volume_data/stent/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the Stented Abdominal Aorta dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures? diff --git a/sci_volume_data/supernova/GS/gs_diagonal_view.png b/sci_volume_data/supernova/GS/gs_diagonal_view.png deleted file mode 100644 index ff1bc21fd5de24cf82bddd16abd5a7d61e35caf9..0000000000000000000000000000000000000000 --- a/sci_volume_data/supernova/GS/gs_diagonal_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:c09397358f712ef4da2a8ba31f3a6d474df7869c256fcc5d1231222338b1ef98 -size 278103 diff --git a/sci_volume_data/supernova/GS/gs_front_view.png b/sci_volume_data/supernova/GS/gs_front_view.png deleted file mode 100644 index 5a6b3d0f57a415d9813416be17a3850f07cb9504..0000000000000000000000000000000000000000 --- a/sci_volume_data/supernova/GS/gs_front_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:a4f79f852d76d0267e09517687c86b7ce4892b632ccdd078f524fd10bda8d796 -size 274309 diff --git a/sci_volume_data/supernova/GS/gs_side_view.png b/sci_volume_data/supernova/GS/gs_side_view.png deleted file mode 100644 index 440622d048185791b043fd0fc9eff02d19a13b28..0000000000000000000000000000000000000000 --- a/sci_volume_data/supernova/GS/gs_side_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:73d10622c11fa07dc2c30a9215e04cd0f7f32588fbbd3596baac96b0b44da3f1 -size 319932 diff --git a/sci_volume_data/supernova/GS/supernova_gs.pvsm b/sci_volume_data/supernova/GS/supernova_gs.pvsm deleted file mode 100644 index 65805d0a47d99bcf7765134ede3d2cfbf9dce0a7..0000000000000000000000000000000000000000 --- a/sci_volume_data/supernova/GS/supernova_gs.pvsm +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:22c09e249d30b845f08876fc48c05f0f338929e7c8f7a8e438f142900fa0dc11 -size 475414 diff --git a/sci_volume_data/supernova/task_description.txt b/sci_volume_data/supernova/task_description.txt deleted file mode 100644 index b1be0883c589229fdd424525d154eb03118913c2..0000000000000000000000000000000000000000 --- a/sci_volume_data/supernova/task_description.txt +++ /dev/null @@ -1,15 +0,0 @@ -Task: - -Load the supernova dataset from "supernova/data/supernova_256x256x256_float32.raw", the information about this dataset: -Supernova (Scalar) -Data Scalar Type: float -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x256 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Then visualize it and extract two isosurfaces. One of them use color red, showing areas with low density (isovalue 40 and opacity 0.4), while the other use color blue, showing areas with high density (isovalue 150 and opacity 0.8). - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. Only make the two isosurfaces visible. - -Finally, save the paraview state as "supernova/results/supernova.pvsm" \ No newline at end of file diff --git a/sci_volume_data/supernova/visualization_goals.txt b/sci_volume_data/supernova/visualization_goals.txt deleted file mode 100644 index a1a31d9c761c2d9c3b8edd1e431bc869d5752a59..0000000000000000000000000000000000000000 --- a/sci_volume_data/supernova/visualization_goals.txt +++ /dev/null @@ -1,5 +0,0 @@ -1. Overall Visualization Goal: How well does the result achieve the overall goal of showing the supernova structure with two distinct isosurfaces representing different density regions? - -2. Does the red isosurface show low density areas (outside regions) with lower opacity? - -3. Does the blue isosurface show high density areas (inside regions) with higher opacity? \ No newline at end of file diff --git a/sci_volume_data/tacc_turbulence/task_description.txt b/sci_volume_data/tacc_turbulence/task_description.txt deleted file mode 100644 index 0980d9615043721008609b7d64cec7bd103f211f..0000000000000000000000000000000000000000 --- a/sci_volume_data/tacc_turbulence/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Isotropic Turbulence dataset from "tacc_turbulence/data/tacc_turbulence_256x256x256_float32.raw", the information about this dataset: -Isotropic Turbulence -Description: The dataset represents a time step from an isotropic turbulence simulation. A single variable, enstrophy, is represented on a Cartesian grid. -Data Type: float32 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 256x256x256 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the flow dynamics: -1. Apply volume rendering to show the turbulent structures -2. Use a blue-to-red colormap to show vorticity or velocity magnitude -3. Create isosurfaces at multiple values to show different turbulence intensities -4. Add a contour on a slice plane to show flow patterns - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "tacc_turbulence/results/tacc_turbulence.pvsm" \ No newline at end of file diff --git a/sci_volume_data/tacc_turbulence/visualization_goals.txt b/sci_volume_data/tacc_turbulence/visualization_goals.txt deleted file mode 100644 index dc0d6fa2c8e1fec8dcb37b1aeb270e06620adc5c..0000000000000000000000000000000000000000 --- a/sci_volume_data/tacc_turbulence/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively convey the physics/dynamics of the Isotropic Turbulence simulation? - -2. Feature Detection: Are the key features (shock fronts, vortices, mixing regions) clearly visible? - -3. Color Mapping: Does the colormap appropriately represent the physical quantity being visualized? - -4. Spatial Understanding: Do the isosurfaces and slices provide good insight into the 3D structure? diff --git a/sci_volume_data/tooth/task_description.txt b/sci_volume_data/tooth/task_description.txt deleted file mode 100644 index b79ccd7a847978cbb96071c25deb107c32083a6d..0000000000000000000000000000000000000000 --- a/sci_volume_data/tooth/task_description.txt +++ /dev/null @@ -1,20 +0,0 @@ -Task: - -Load the Tooth dataset from "tooth/data/tooth_103x94x161_uint8.raw", the information about this dataset: -Tooth -Description: -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1x1x1 -Data Extent: 103x94x161 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the scanned object: -1. Apply volume rendering with appropriate transfer function -2. Create an isosurface at the object boundary -3. Use realistic colors for the material -4. Add clipping or transparency to show internal structure - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "tooth/results/tooth.pvsm" \ No newline at end of file diff --git a/sci_volume_data/tooth/visualization_goals.txt b/sci_volume_data/tooth/visualization_goals.txt deleted file mode 100644 index f2b0e0b0faad3f8241576606a25477fc750f6b45..0000000000000000000000000000000000000000 --- a/sci_volume_data/tooth/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization clearly show the structure and details of the Tooth? - -2. Material Differentiation: Are different materials or components distinguishable? - -3. Internal Structure: If applicable, are internal features or hidden contents visible? - -4. Surface Quality: Are surface details and boundaries well-defined? diff --git a/sci_volume_data/tornado/GS/.DS_Store b/sci_volume_data/tornado/GS/.DS_Store deleted file mode 100644 index 83c588db58fbdbfa77ff940ca6a9ae4c88711de5..0000000000000000000000000000000000000000 Binary files a/sci_volume_data/tornado/GS/.DS_Store and /dev/null differ diff --git a/sci_volume_data/tornado/GS/gs_diagonal_view.png b/sci_volume_data/tornado/GS/gs_diagonal_view.png deleted file mode 100644 index 5888077d9d77a267624064323d19a5c97ea4a979..0000000000000000000000000000000000000000 --- a/sci_volume_data/tornado/GS/gs_diagonal_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:49af2e632fd82221e826b74f9b88bfd8afb19d655d813b664c5f2da304a60a26 -size 484144 diff --git a/sci_volume_data/tornado/GS/gs_front_view.png b/sci_volume_data/tornado/GS/gs_front_view.png deleted file mode 100644 index b2646b3720bf044090480339dd6db565a9749f1d..0000000000000000000000000000000000000000 --- a/sci_volume_data/tornado/GS/gs_front_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:812375bd3867ebfa42188641ed2d94408d64d6be93387dd7e345a90a54dd8232 -size 597258 diff --git a/sci_volume_data/tornado/GS/gs_side_view.png b/sci_volume_data/tornado/GS/gs_side_view.png deleted file mode 100644 index 28a8f007c5fe310ee66a3961280387f36d8caa87..0000000000000000000000000000000000000000 --- a/sci_volume_data/tornado/GS/gs_side_view.png +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:16904f34f00c8d366ea2ba16e6fa1576b65fdd9b249f2dca75af7875b10af050 -size 311675 diff --git a/sci_volume_data/tornado/GS/tornado_gs.pvsm b/sci_volume_data/tornado/GS/tornado_gs.pvsm deleted file mode 100644 index 16201657bf71265f2e338f29988bbaa0aa7cf6cc..0000000000000000000000000000000000000000 --- a/sci_volume_data/tornado/GS/tornado_gs.pvsm +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:d0925273b0be89973865699b20ca9bc92214a10c0d69aa785bc7366ac96ec3e3 -size 597880 diff --git a/sci_volume_data/tornado/task_description.txt b/sci_volume_data/tornado/task_description.txt deleted file mode 100644 index 84d74157ead30e5cb0a9119988f1df56caba090e..0000000000000000000000000000000000000000 --- a/sci_volume_data/tornado/task_description.txt +++ /dev/null @@ -1,19 +0,0 @@ -Task: - -Load the tornado dataset from "tornado/data/tornado_64x64x64_float32_scalar3.raw", the information about this dataset: -Tornado (Vector) -Data Scalar Type: float -Data Byte Order: little Endian -Data Extent: 64x64x64 -Number of Scalar Components: 3 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Add a “glyph” filter under the tornado data to display velocity glyph, set an appropriate “Scale Factor” so the glyphs are visible. - -Then add a “stream tracer” filter under the tornado data to generate streamlines. Choose “Point Cloud” as “Seed Type”, and do not show sphere. - -Add a “tube” filter under the stream tracer you just created to generate tubes for visualizing the streamlines. Set an appropriate radius. Make the stream tracer invisible and the tube visible. At last, render the streamlines as tubes. - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "tornado/results/tornado.pvsm" \ No newline at end of file diff --git a/sci_volume_data/tornado/visualization_goals.txt b/sci_volume_data/tornado/visualization_goals.txt deleted file mode 100644 index 9383d8f9b6518512955ac3c9476b19c3ac75c574..0000000000000000000000000000000000000000 --- a/sci_volume_data/tornado/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Visualization Goal: How well does the result achieve the overall goal of showing tornado flow patterns with glyphs and streamlines? - -2. Glyph Visualization: Does the result show velocity glyphs that are appropriately sized and visible? - -3. Streamline Visualization: Does the result show streamlines that follow the flow patterns effectively? - -4. Tube Rendering: Are the streamlines rendered as tubes with appropriate thickness? \ No newline at end of file diff --git a/sci_volume_data/vis_male/task_description.txt b/sci_volume_data/vis_male/task_description.txt deleted file mode 100644 index 08a791a9670a058af01854578dcaf2b5a1549fca..0000000000000000000000000000000000000000 --- a/sci_volume_data/vis_male/task_description.txt +++ /dev/null @@ -1,19 +0,0 @@ -Task: - -Load the Head (Visible Male) dataset from "vis_male/data/vis_male_128x256x256_uint8.raw", the information about this dataset: -Head (Visible Male) -Description: Male head scan -Data Type: uint8 -Data Byte Order: little Endian -Data Spacing: 1.57774x0.995861x1.00797 -Data Extent: 128x256x256 -Data loading is very important, make sure you correctly load the dataset according to their features. - -Visualize the anatomical structures: -1. Apply volume rendering with appropriate transfer function for tissue differentiation -2. Create isosurfaces at two different density values to show different tissue types -3. Use contrasting colors for different structures (e.g., red for soft tissue, white for dense material) - -Please think step by step and make sure to fulfill all the visualization goals mentioned above. - -Finally, save the paraview state as "vis_male/results/vis_male.pvsm" \ No newline at end of file diff --git a/sci_volume_data/vis_male/visualization_goals.txt b/sci_volume_data/vis_male/visualization_goals.txt deleted file mode 100644 index 5ea3c7fc2a82d5a366ca34dfc6fef3e4f321c16a..0000000000000000000000000000000000000000 --- a/sci_volume_data/vis_male/visualization_goals.txt +++ /dev/null @@ -1,7 +0,0 @@ -1. Overall Goal: Does the visualization effectively distinguish between different tissue types in the Head (Visible Male) dataset? - -2. Tissue Differentiation: Are soft tissue and bone/dense structures clearly separated with appropriate colors? - -3. Anatomical Clarity: Are the key anatomical features clearly visible and properly rendered? - -4. Depth Perception: Does the opacity and lighting provide good 3D understanding of the structures?