[De...] Posted October 27 Share Posted October 27 Alternative to 3D PDFs https://github.com/Devon-Kile/Colormap_Visualizer_addon.git https://github.com/Devon-Kile/Colormap_Visualizer.git 1 Link to comment https://qualityforum.zeiss.com/topic/27762-colormap-viewer/ Share on other sites More sharing options...
[Ma...] Posted November 3 Share Posted November 3 Great work, but for me it doesn't work 😞 Link to comment https://qualityforum.zeiss.com/topic/27762-colormap-viewer/#findComment-157760 Share on other sites More sharing options...
[De...] Posted Friday at 10:26 PM Author Share Posted Friday at 10:26 PM hmm.. maybe try it with a super basic project, CAD / Scan / Colormap. run it in the script editor? --> paste errors (if any) you can also run this script below to analyze the np.arrays. (just change the 'colormap' name to what you have in your project) import gom import numpy as np # Access surface comparison inspection element colormap = gom.app.project.inspection['Surface comparison 1'] # Extract NumPy arrays (preserve original dimensions) coordinates = np.asarray(colormap.data.coordinate) normals = np.asarray(colormap.data.normal) scalar_values = np.asarray(colormap.data.scalar_value) triangles = np.asarray(colormap.data.triangle) # --------------------------------------------------------- # ARRAY INSPECTION # --------------------------------------------------------- def inspect_array(name, array): print("\n" + "=" * 70) print("ARRAY:", name) print("=" * 70) print("Shape: ", array.shape) print("Dimensions: ", array.ndim) print("Data type: ", array.dtype) print("Total values:", array.size) print("\nFIRST 5 ROWS") print(array[0, :5]) # Inspect arrays inspect_array("COORDINATES", coordinates) inspect_array("NORMALS", normals) inspect_array("SCALAR VALUES", scalar_values) inspect_array("TRIANGLES", triangles) # --------------------------------------------------------- # SCALAR VALUE STATISTICS # --------------------------------------------------------- print("\n" + "=" * 70) print("SCALAR VALUE STATISTICS") print("=" * 70) for stage in range(scalar_values.shape[0]): values = scalar_values[stage].ravel() valid = np.isfinite(values) print("\nSTAGE:", stage) print("Total values: ", values.size) print("Valid values: ", np.count_nonzero(valid)) print("Invalid values:", np.count_nonzero(~valid)) if np.any(valid): print("Minimum: ", np.min(values[valid])) print("Maximum: ", np.max(values[valid])) print("Mean: ", np.mean(values[valid])) print("Median: ", np.median(values[valid])) print("Std Dev: ", np.std(values[valid])) # --------------------------------------------------------- # MESH VALIDATION # --------------------------------------------------------- print("\n" + "=" * 70) print("MESH VALIDATION") print("=" * 70) for stage in range(coordinates.shape[0]): vertex_count = coordinates.shape[1] triangle_count = triangles.shape[1] stage_triangles = triangles[stage] invalid_indices = np.count_nonzero( (stage_triangles < 0) | (stage_triangles >= vertex_count) ) print("\nSTAGE:", stage) print("Vertex count: ", vertex_count) print("Triangle count: ", triangle_count) print("Minimum index: ", stage_triangles.min()) print("Maximum index: ", stage_triangles.max()) print("Invalid indices:", invalid_indices) print("Coordinate/normal match:", coordinates[stage].shape == normals[stage].shape) print("Coordinate/scalar match:", coordinates[stage].shape[0] == scalar_values[stage].shape[0]) print("\nArray analysis complete.") Link to comment https://qualityforum.zeiss.com/topic/27762-colormap-viewer/#findComment-158038 Share on other sites More sharing options...
[Ma...] Posted 12 hours ago Share Posted 12 hours ago This is the result: ====================================================================== ARRAY: COORDINATES ====================================================================== Shape: (14, 1001483, 3) Dimensions: 3 Data type: float64 Total values: 42062286 FIRST 5 ROWS [[-3.77004521 -2.5909069 5.63548731] [-3.75618393 -2.57819015 5.61667638] [-3.74682975 -2.60982676 5.63127428] [-3.74232265 -2.56547339 5.59786546] [-3.73137834 -2.58936804 5.60604099]] ====================================================================== ARRAY: NORMALS ====================================================================== Shape: (14, 1001483, 3) Dimensions: 3 Data type: float64 Total values: 42062286 FIRST 5 ROWS [[0.51937824 0.47984293 0.70710468] [0.51937836 0.47984299 0.70710462] [0.5193944 0.47983545 0.70709789] [0.51939189 0.47983265 0.7071017 ] [0.51940525 0.47982848 0.70709467]] ====================================================================== ARRAY: SCALAR VALUES ====================================================================== Shape: (14, 1001483, 1) Dimensions: 3 Data type: float64 Total values: 14020762 FIRST 5 ROWS [[0.17371252] [0.19341013] [0.18066262] [0.21199106] [0.20574836]] ====================================================================== ARRAY: TRIANGLES ====================================================================== Shape: (14, 1728100, 3) Dimensions: 3 Data type: int32 Total values: 72580200 FIRST 5 ROWS [[1 0 2] [2 3 1] [2 4 3] [3 4 5] [4 2 7]] ====================================================================== SCALAR VALUE STATISTICS ====================================================================== STAGE: 0 Total values: 1001483 Valid values: 817004 Invalid values: 184479 Minimum: -0.9999836087226868 Maximum: 0.9999943971633911 Mean: 0.12506770972503356 Median: 0.007404788630083203 Std Dev: 0.33857524864327565 STAGE: 1 Total values: 1001483 Valid values: 810624 Invalid values: 190859 Minimum: -0.9997458457946777 Maximum: 0.9999995827674866 Mean: 0.12545123292840807 Median: 0.005641367053613067 Std Dev: 0.33820176809525915 STAGE: 2 Total values: 1001483 Valid values: 806167 Invalid values: 195316 Minimum: -0.9999976754188538 Maximum: 0.9999997615814209 Mean: 0.12822237201850964 Median: 0.008725213818252087 Std Dev: 0.33852532712616873 STAGE: 3 Total values: 1001483 Valid values: 799139 Invalid values: 202344 Minimum: -0.9999946355819702 Maximum: 0.9999998211860657 Mean: 0.11647757265726937 Median: 0.00733939977362752 Std Dev: 0.3346622895754618 STAGE: 4 Total values: 1001483 Valid values: 806319 Invalid values: 195164 Minimum: -0.999889612197876 Maximum: 0.9999955296516418 Mean: 0.12375207080038801 Median: 0.006627410184592009 Std Dev: 0.33557094342534866 STAGE: 5 Total values: 1001483 Valid values: 807133 Invalid values: 194350 Minimum: -0.9999645948410034 Maximum: 0.9999971389770508 Mean: 0.12766216929258173 Median: 0.012189929373562336 Std Dev: 0.34083237602395183 STAGE: 6 Total values: 1001483 Valid values: 805712 Invalid values: 195771 Minimum: -0.9999943375587463 Maximum: 0.9999861121177673 Mean: 0.1224781303949255 Median: 0.0034620233345776796 Std Dev: 0.34337158696471554 STAGE: 7 Total values: 1001483 Valid values: 810347 Invalid values: 191136 Minimum: -0.9998605847358704 Maximum: 0.9999995827674866 Mean: 0.1223609867846869 Median: 0.003429613308981061 Std Dev: 0.34028559250643153 STAGE: 8 Total values: 1001483 Valid values: 799807 Invalid values: 201676 Minimum: -0.9999169111251831 Maximum: 0.9999849796295166 Mean: 0.12175145579847788 Median: 0.009752480313181877 Std Dev: 0.3382057162990135 STAGE: 9 Total values: 1001483 Valid values: 804530 Invalid values: 196953 Minimum: -0.9998884797096252 Maximum: 0.9999997019767761 Mean: 0.1309860663740092 Median: 0.00888607557862997 Std Dev: 0.33682884009253805 STAGE: 10 Total values: 1001483 Valid values: 811783 Invalid values: 189700 Minimum: -0.9994982481002808 Maximum: 1.0 Mean: 0.12587793787982593 Median: 0.006889908574521542 Std Dev: 0.3386338362739185 STAGE: 11 Total values: 1001483 Valid values: 805351 Invalid values: 196132 Minimum: -0.9999029636383057 Maximum: 0.9999940991401672 Mean: 0.12458094398355302 Median: 0.007014192175120115 Std Dev: 0.3372293614642635 STAGE: 12 Total values: 1001483 Valid values: 813666 Invalid values: 187817 Minimum: -0.9999779462814331 Maximum: 0.9999937415122986 Mean: 0.12616119242940965 Median: 0.009973835200071335 Std Dev: 0.3362999554437092 STAGE: 13 Total values: 1001483 Valid values: 810213 Invalid values: 191270 Minimum: -0.99960857629776 Maximum: 0.9999967217445374 Mean: 0.12320137626659115 Median: 0.008159889839589596 Std Dev: 0.3383606201434212 ====================================================================== MESH VALIDATION ====================================================================== STAGE: 0 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 1 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 2 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 3 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 4 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 5 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 6 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 7 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 8 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 9 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 10 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 11 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 12 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True STAGE: 13 Vertex count: 1001483 Triangle count: 1728100 Minimum index: 0 Maximum index: 1001482 Invalid indices: 0 Coordinate/normal match: True Coordinate/scalar match: True Array analysis complete. Link to comment https://qualityforum.zeiss.com/topic/27762-colormap-viewer/#findComment-158080 Share on other sites More sharing options...
[Ma...] Posted 10 hours ago Share Posted 10 hours ago I tried with a new project and it works! One question: is not possible to use a personal legend bar? 1 Link to comment https://qualityforum.zeiss.com/topic/27762-colormap-viewer/#findComment-158086 Share on other sites More sharing options...
[De...] Posted 4 hours ago Author Share Posted 4 hours ago Hey Marco, Glad you got it working! you should be able to click the number in the top RH corner and either use the mousewheel or change the value to whatever you want. If you want to customize it beyond that, I Included a "Prompt_for_ai.md" - just download / extract the codebase from github, give Codex/Claude code access to that folder, copy the prompt and follow it up by "Id like to change the color legend to ........." give codex/claude some example pictures of what you're looking for. let us know how it goes! Link to comment https://qualityforum.zeiss.com/topic/27762-colormap-viewer/#findComment-158106 Share on other sites More sharing options...
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