| """Source of truth for the Table S8 notebook (Dataset Summary Statistics). Edit the cell sources |
| here, then regenerate: |
| |
| python3 build_nb_dataset_summary.py si_table_s08_summary |
| jupyter nbconvert --to notebook --execute --inplace ../si_tables/si_table_s08_summary.ipynb |
| |
| Regenerating overwrites the .ipynb (clearing its execution outputs). All real code lives in |
| dataset_summary.py (the counting logic and the PUBLISHED_S8 reference values); the notebook only |
| runs it over the released data/ files. The notebook lives in analysis/si_tables/ (grouped by role), not here. |
| |
| Run with no arguments to list the available notebook names. |
| """ |
| import os |
| import sys |
|
|
| from nb_build import md, code, save_notebook as _save |
|
|
|
|
| _BOOTSTRAP = r""" |
| import os, sys |
| |
| # make the in-repo modules importable (not pip-installed) |
| REPO = os.path.abspath("../..") |
| for _p in ("analysis/code", "analysis/code/shared"): |
| sys.path.insert(0, os.path.join(REPO, _p)) |
| """ |
|
|
| _IMPORTS = r""" |
| import pandas as pd |
| import dataset_summary |
| """ |
|
|
| _SETUP = r""" |
| DATA_DIR = os.path.join(REPO, "data") |
| |
| def document_path(name): |
| os.makedirs("documents", exist_ok=True) |
| return os.path.join("documents", name) |
| """ |
|
|
| si_table_s08_summary = [ |
| md(r""" |
| # Table S8: Dataset Summary Statistics |
| |
| Molecule and ¹H/¹³C site counts for each training dataset (site counts from each HDF5's |
| `atomic_numbers`, ¹H=1/¹³C=6; MagNET-Zero combines both sigma-pepper rounds with sigma-concentrate). |
| """), |
| code(_BOOTSTRAP), |
| code(_IMPORTS), |
| code(_SETUP), |
| code(r""" |
| table_s8 = dataset_summary.summary_table(DATA_DIR) |
| display(table_s8) |
| |
| # write the table to this notebook's documents/ folder |
| out = document_path("si_table_s08_summary.xlsx") |
| with pd.ExcelWriter(out) as writer: |
| table_s8.to_excel(writer, sheet_name="Table S8", index=False) |
| print("wrote", os.path.relpath(out, REPO)) |
| """), |
| md("## Exact-reproduction check"), |
| code(r""" |
| # every count should match the published SI Table S8 value exactly |
| for _, row in table_s8.iterrows(): |
| pub = dataset_summary.PUBLISHED_S8[row["dataset"]] |
| got = (row["molecules"], row["n_1H_sites"], row["n_13C_sites"]) |
| assert got == pub, f"{row['dataset']}: {got} != published {pub}" |
| print("all rows match the published SI Table S8 exactly") |
| """), |
| ] |
|
|
|
|
| |
| NOTEBOOKS = { |
| "si_table_s08_summary": (si_table_s08_summary, "analysis/si_tables/si_table_s08_summary.ipynb"), |
| } |
|
|
| if __name__ == "__main__": |
| here = os.path.dirname(os.path.abspath(__file__)) |
| repo = os.path.abspath(os.path.join(here, "..", "..")) |
| names = sys.argv[1:] |
| if not names: |
| print("available names:", ", ".join(NOTEBOOKS)) |
| sys.exit(0) |
| unknown = [n for n in names if n not in NOTEBOOKS] |
| if unknown: |
| raise SystemExit(f"unknown notebook name(s): {unknown}; available: {', '.join(NOTEBOOKS)}") |
| for name in names: |
| cells, relpath = NOTEBOOKS[name] |
| _save(cells, os.path.join(repo, relpath)) |
|
|
