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docs: document core spectrum, physical branch columns, CSV-driven plots

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unzhakov
2026-09-30 03:11:05 +03:00
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@@ -122,12 +122,19 @@ Defined in `beta_spectrum/spectrum.py`. Orchestrates the calculation:
In `beta_spectrum.output`. Provides debugging and visualization tools:
- `total_spectrum(normalize=True/False)` — computed spectrum array
- `total_spectrum(normalize=True/False)` — computed spectrum array; raises `ValueError` when every branch is degenerate (non-positive integral)
- `physical_branch_spectrum(i)` — physical spectrum of branch *i*: the core (phase space × Fermi function) times every enabled higher-order correction, clamped beyond the branch endpoint (unnormalized)
- `universal_factor()` — product of the components shared across all branches (Fermi function and the universal higher-order corrections)
- `plot_analysis(save_path=None, show_components=True)` — plot with two modes:
- `show_components=True` (debug mode): 4-panel figure (spectrum, components, cumulative effect, deviations)
- `show_components=False` (normal mode): single spectrum plot with nuclear data header
- All plots include commit hash and UTC timestamp for traceability
- `export_to_csv(filename)` — export via pandas DataFrame with YAML-style metadata header
- Plots are built *from the exported CSV file* (temporary full-verbosity export), so a plot always shows exactly the bytes the CSV export produces
- `export_to_csv(filename)` — export via pandas DataFrame with YAML-style metadata header:
- the basic spectrum is always the core `phase_space × fermi` (the header carries a `# core:` line); finite size, charge distribution, screening, exchange and radiative are higher-order corrections
- `branch_{i}_spectrum` columns contain the *physical* branch spectra weighted by intensity and normalized so that the sum of branch columns equals `total_spectrum`
- with `normalize_to_one=True` each branch column integrates to 1 (intensity ignored, no total column)
- `parse_spectrum_csv(path)` — read an exported CSV and its metadata header (module function in `beta_spectrum.output.visualization`)
- `get_data()` — return all numerical data for custom analysis
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