Visualise response and Planck spectrum fits

2026-09-10 15:27:04 +01:00
parent d62864bd89
commit 192c595441
2 changed files with 110 additions and 0 deletions
@@ -0,0 +1,70 @@
+#!/usr/bin/env python
+"""Overlay one or more emission spectra, response-corrected, with Planck fits.
+
+For each spectrum CSV: optionally response-correct it (--response/--dark plus
+--integration, as grab_spectrum.py --response would), fit a Planck curve over
+--band, and plot the corrected spectrum with its fit and the fitted temperature.
+Reuses the correction and the fit from the rest of the project.
+
+Usage: python plot_emission.py f1.csv f2.csv ... [--response R.csv --dark D.csv
+                              --integration US] [--band LO HI] [--xlim LO HI]
+                              [--png fig.png]
+"""
+import argparse
+
+import numpy as np
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+from response import add_calibration_args, apply_response, dark_at, load_csv
+from fit_temperature import fit_planck
+
+p = argparse.ArgumentParser(description=__doc__,
+                            formatter_class=argparse.RawDescriptionHelpFormatter)
+p.add_argument("spectra", nargs="+", help="emission spectrum CSVs")
+p.add_argument("--integration", type=int, metavar="US",
+               help="integration time (us) the spectra were captured at; required with --dark")
+p.add_argument("--band", nargs=2, type=float, default=[650.0, 850.0],
+               metavar=("LO", "HI"), help="Planck fit band in nm (default: 650 850)")
+p.add_argument("--xlim", nargs=2, type=float, default=[560.0, 930.0],
+               metavar=("LO", "HI"), help="plot x-range in nm (default: 560 930)")
+p.add_argument("--png", default="emission_fit.png")
+add_calibration_args(p)
+args = p.parse_args()
+
+cal = load_csv(args.response) if args.response else None
+dark = None
+if args.dark:
+    if args.integration is None:
+        p.error("--integration US is required with --dark")
+    dark = dark_at(args.dark, args.integration)
+
+lo, hi = args.band
+fig, ax = plt.subplots(figsize=(9, 5))
+for f in args.spectra:
+    wl, y = load_csv(f)
+    if cal is not None:
+        y = apply_response(wl, y, cal, dark)
+    result = fit_planck(wl, y, (lo, hi))
+    m = (wl >= args.xlim[0]) & (wl <= args.xlim[1])
+    (base,) = ax.plot(wl[m], y[m], lw=0.5, alpha=0.35)
+    if result is None:
+        print(f"{f}: no fit in {lo:.0f}-{hi:.0f} nm")
+        continue
+    temperature, dT, predict = result
+    ax.plot(wl[m], predict(wl[m]), lw=2.0, color=base.get_color(),
+            label=f"{f}:  T = {temperature:.0f} K")
+    print(f"{f}: T = {temperature:.2f} +/- {dT:.2f} K")
+
+ax.axvspan(lo, hi, color="0.85", alpha=0.5, lw=0, zorder=0)
+ax.set_xlabel("wavelength (nm)")
+ax.set_ylabel("relative irradiance (response-corrected)")
+ax.set_title(f"Emission with Planck fit over {lo:.0f}-{hi:.0f} nm (shaded)")
+ax.set_xlim(*args.xlim)
+ax.set_ylim(bottom=0)
+ax.grid(alpha=0.3)
+ax.legend(fontsize=9, loc="upper left")
+fig.tight_layout()
+fig.savefig(args.png, dpi=130)
+print(f"wrote {args.png}")