unzhakov
330ebddaef
- Remove --mode, --transition-type, and --decay-index CLI flags
(parameters now come from ENSDF data or custom JSON input)
- Clarify energy units in all CLI help text (MeV throughout, keV for detector params)
- Enhance logging verbosity:
- -v (INFO): shows source, component initialization, workflow steps
- -vv (DEBUG): shows detailed internals of all spectrum components
(parameters, evaluation counts, input/output ranges)
- Improve CSV headers with element notation (e.g. Tc99 -> Ru99)
- Add CONVENTIONS.md documenting energy unit and logging conventions
- Update TODO.md with completion status
114 lines
3.4 KiB
Python
114 lines
3.4 KiB
Python
#!/usr/bin/env python3
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"""Execute notebooks and extract plots for LLM review.
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This script:
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1. Executes all notebooks (or specified ones) using nbconvert
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2. Saves executed notebooks with outputs
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3. Extracts PNG figures from cell outputs
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4. Reports plot locations for LLM analysis
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Usage:
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python scripts/run_notebooks.py # all notebooks
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python scripts/run_notebooks.py nb1.ipynb # specific notebook
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python scripts/run_notebooks.py notebooks/ # directory
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"""
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import json
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import os
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import sys
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import base64
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from pathlib import Path
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def execute_notebook(nb_path: str) -> bool:
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"""Execute a notebook using nbconvert and save outputs."""
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import nbformat
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from nbclient import NotebookClient
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nb = nbformat.read(str(nb_path), as_version=4)
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client = NotebookClient(nb, timeout=600, kernel_name="python3")
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try:
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client.execute()
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nbformat.write(nb, str(nb_path))
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return True
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except Exception as e:
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print(f" ERROR: {e}")
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return False
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def extract_plots(nb_path: str, output_dir: str = None) -> list:
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"""Extract PNG figures from an executed notebook's cell outputs."""
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nb_path = Path(nb_path)
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with open(nb_path) as f:
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nb = json.load(f)
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if output_dir is None:
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output_dir = nb_path.parent / "_plots"
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output_dir = Path(output_dir)
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output_dir.mkdir(exist_ok=True)
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plots = []
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nb_name = nb_path.stem
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for cell_idx, cell in enumerate(nb["cells"]):
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if cell["cell_type"] != "code":
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continue
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for output in cell.get("outputs", []):
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if output.get("output_type") != "display_data":
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continue
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data = output.get("data", {})
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png_b64 = data.get("image/png")
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if png_b64:
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plot_path = output_dir / f"{nb_name}_cell{cell_idx}.png"
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with open(plot_path, "wb") as f:
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f.write(base64.b64decode(png_b64))
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plots.append(str(plot_path))
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return plots
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def main():
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if len(sys.argv) < 2:
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print("Usage: python scripts/run_notebooks.py <notebook_or_dir> ...")
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sys.exit(1)
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all_plots = []
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failed = []
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for arg in sys.argv[1:]:
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p = Path(arg)
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if p.suffix == ".ipynb":
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print(f"Executing {p.name}...")
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if execute_notebook(str(p)):
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plots = extract_plots(str(p))
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all_plots.extend(plots)
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print(f" Extracted {len(plots)} plot(s)")
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else:
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failed.append(p.name)
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elif p.is_dir():
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for nb in sorted(p.glob("*.ipynb")):
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if nb.name.startswith("_") or nb.name == "conftest.py":
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continue
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print(f"Executing {nb.name}...")
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if execute_notebook(str(nb)):
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plots = extract_plots(str(nb))
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all_plots.extend(plots)
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print(f" Extracted {len(plots)} plot(s)")
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else:
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failed.append(nb.name)
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print()
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print(
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f"Done. {len(all_plots)} plot(s) extracted, {len(failed)} notebook(s) failed."
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)
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if all_plots:
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print()
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print("Plots saved to: notebooks/_plots/")
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print("To review with LLM, send the PNG paths using @ notation:")
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for p in all_plots:
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print(f" @{p}")
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if __name__ == "__main__":
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main()
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