delete trash tasks from sci_volume_data

sci_volume_data/aneurism/task_description.txt

@@ -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"

sci_volume_data/aneurism/visualization_goals.txt

@@ -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?

sci_volume_data/backpack/task_description.txt

@@ -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

sci_volume_data/backpack/visualization_goals.txt

@@ -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?

sci_volume_data/blunt_fin/task_description.txt

@@ -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"

sci_volume_data/blunt_fin/visualization_goals.txt

@@ -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?

sci_volume_data/bonsai/GS/bonsai_gs.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:aa03b91b2e71ffbfef15c26dce85b93887ee4ffd1461759c11a46f640f604ac0
-size 235372

sci_volume_data/bonsai/GS/bonsai_gs.py

@@ -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()

sci_volume_data/bonsai/task_description.txt

@@ -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"

sci_volume_data/bonsai/visualization_goals.txt

@@ -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?

sci_volume_data/boston_teapot/task_description.txt

@@ -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

sci_volume_data/boston_teapot/visualization_goals.txt

@@ -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?

sci_volume_data/bunny/task_description.txt

@@ -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

sci_volume_data/bunny/visualization_goals.txt

@@ -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?

sci_volume_data/carp/task_description.txt

@@ -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

sci_volume_data/carp/visualization_goals.txt

@@ -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?

sci_volume_data/csafe_heptane/task_description.txt

@@ -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"

sci_volume_data/csafe_heptane/visualization_goals.txt

@@ -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?

sci_volume_data/duct/task_description.txt

@@ -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"

sci_volume_data/duct/visualization_goals.txt

@@ -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?

sci_volume_data/engine/task_description.txt

@@ -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

sci_volume_data/engine/visualization_goals.txt

@@ -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?

sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272613.json

@@ -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"
-}

sci_volume_data/foot/evaluation_results/mcp/evaluation_result_1759272950.json

@@ -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"
-}

sci_volume_data/foot/evaluation_results/mcp/evaluation_results.json

@@ -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"
-    }
-  }
-}

sci_volume_data/foot/results/mcp/foot.pvsm

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cb201f103bbd98a6b11bfe7cdeb6643e6301dc7f894cef4e7348f17971f8ce09
-size 231778

sci_volume_data/foot/task_description.txt

@@ -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"

sci_volume_data/foot/test_results/mcp/test_result_1759272600.json

@@ -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
-  }
-}

sci_volume_data/foot/test_results/mcp/test_result_1759272935.json

@@ -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
-  }
-}

sci_volume_data/foot/visualization_goals.txt

@@ -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)

sci_volume_data/frog/task_description.txt

@@ -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"

sci_volume_data/frog/visualization_goals.txt

@@ -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?

sci_volume_data/fuel/task_description.txt

@@ -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"

sci_volume_data/fuel/visualization_goals.txt

@@ -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?

sci_volume_data/hydrogen_atom/task_description.txt

@@ -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"

sci_volume_data/hydrogen_atom/visualization_goals.txt

@@ -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?

sci_volume_data/lobster/task_description.txt

@@ -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

sci_volume_data/lobster/visualization_goals.txt

@@ -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?

sci_volume_data/marschner_lobb/task_description.txt

@@ -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"

sci_volume_data/marschner_lobb/visualization_goals.txt

@@ -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?

sci_volume_data/mri_ventricles/task_description.txt

@@ -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"

sci_volume_data/mri_ventricles/visualization_goals.txt

@@ -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?