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README.md

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+# fisr_algorithm_dataset
+
+## Fast Inverse Square Root Algorithm Visualization Dataset
+
+Generated with UNDERGROUND: FISR by webXOS
+Educational visualization of the Quake III Arena optimization algorithm
+
+### Algorithm Details
+- Magic Number: 0x5f23aac5
+- Newton Iterations: 3
+- Input Range: 0.1 to 1000
+- Maximum Error: 1.1742636926798086e+287%
+- RMS Error: Infinity%
+
+### Files Included
+frames
+metadata
+data
+algorithm
+
+### Educational Value
+This dataset demonstrates:
+1. The Fast Inverse Square Root algorithm implementation
+2. Error analysis of the approximation
+3. 3D visualization of mathematical functions
+4. Bit-level manipulation techniques
+
+### Usage for Training
+1. Use frames/ for visual sequence learning
+2. Use numerical_data.csv for regression tasks
+3. Use metadata.json for conditional generation
+4. Train models to understand optimization algorithms
+
+### Citation
+If you use this dataset, please cite:
+UNDERGROUND: FISR by webXOS, 2024
+
+### License
+Creative Commons Attribution 4.0 International (CC BY 4.0)

algorithm_analysis.json

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+{
+  "explanation": "The Fast Inverse Square Root algorithm computes 1/√x using bit manipulation and Newton's method.",
+  "original_use": "Used in Quake III Arena for lighting and reflection calculations.",
+  "performance": "Approximately 30x faster than standard floating-point division and square root.",
+  "steps": [
+    "1. Treat the floating-point number as an integer",
+    "2. Right shift the integer by 1 bit",
+    "3. Subtract from the magic number (0x5f3759df)",
+    "4. Treat the result as a floating-point number",
+    "5. Apply one iteration of Newton's method: y = y * (1.5 - (x2 * y * y))"
+  ],
+  "mathematical_basis": "The algorithm exploits the linear relationship between the logarithm of a number and its floating-point representation.",
+  "magic_number_derivation": "The magic number is derived from the IEEE 754 floating-point format and provides a good initial approximation."
+}

dataset_info.json

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+{
+  "description": "Fast Inverse Square Root algorithm visualization dataset for machine learning training",
+  "license": "CC BY 4.0",
+  "features": {
+    "frames": {
+      "dtype": "image",
+      "id": null
+    },
+    "metadata": {
+      "dtype": "string",
+      "id": null
+    },
+    "numerical_data": {
+      "dtype": "string",
+      "id": null
+    },
+    "algorithm_analysis": {
+      "dtype": "string",
+      "id": null
+    }
+  },
+  "homepage": "https://github.com/webXOS/UNDERGROUND-FISR",
+  "citation": "@misc{underground-fisr-2024,\n  author = {webXOS},\n  title = {Fast Inverse Square Root Algorithm Visualization Dataset},\n  year = {2024},\n  publisher = {GitHub},\n  journal = {GitHub repository}\n}"
+}