chore: WASP-18 and NUTS reruns after the lineage fix on the laptop, juliet... (0f4dcbcd) · Commits · Gaetano Scandariato / PyAETNA

paper_benchmarks/common/warmup_test.py

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Changes for paper_benchmarks/common/warmup_test.py: 7 added lines, 3 removed lines.
Original line number	Diff line number	Diff line
		@@ -11,12 +11,13 @@ With an optional converged reference run (samples NPZ of nested sampling, or of
		each run is also compared with it, to tell whether either mode converged at all.

		usage: python warmup_test.py <benchmark dir> <config name> <burn steps of the direct runs> [<reference samples.npz>]
		writes <benchmark dir>/results/warmup_test.json
		writes <benchmark dir>/results/warmup_test.json (with WARMUP_TEST_DIR=<folder>: runs/<folder>, results/<folder>.json)
		"""

		from __future__ import annotations

		import json
		import os
		import re
		import sys
		from pathlib import Path
		@@ -57,7 +58,10 @@ def stats(chains: dict[str, np.ndarray], mask: np.ndarray) -> dict[str, tuple]:

		def main() -> None:
		bench, config, burn_direct = Path(sys.argv[1]), sys.argv[2], int(sys.argv[3])
		base = bench / "runs" / "warmup_test"
		folder = os.environ.get(
		"WARMUP_TEST_DIR", "warmup_test"
		) # e.g. warmup_test_err (WASP-18, binned errors)
		base = bench / "runs" / folder
		runs = sorted(p for p in base.iterdir() if (p / "done.txt").exists())
		chains, out = {}, {
		"benchmark": bench.name,
		@@ -103,7 +107,7 @@ def main() -> None:
		"width_ratio_min": min(s[k][1] / ref[k][1] for k in ref),
		"width_ratio_max": max(s[k][1] / ref[k][1] for k in ref),
		}
		dest = bench / "results" / "warmup_test.json"
		dest = bench / "results" / f"{folder}.json"
		dest.write_text(json.dumps(out, indent=1))
		for name, r in out["runs"].items():
		print(

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Changes for paper_benchmarks/cpu_scaling/juliet_rslice_laptop/K2-140_priors_fullcircular.dat: 27 added lines, 0 removed lines.
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		# Physical parameters of the transiting system:
		P_p1 Normal 6.5693,0.0001
		t0_p1 Normal 2457588.284,0.001
		a_p1 Uniform 1.0,30.0
		r1_p1 Uniform 0.0,1.0
		r2_p1 Uniform 0.0,1.0
		ecc_p1 FIXED 0.0
		omega_p1 FIXED 90.0
		K_p1 Uniform 0,1.0
		# Photometric priors for K2 photometry:
		q1_K2 Uniform 0.0,1.0
		q2_K2 Uniform 0.0,1.0
		mdilution_K2 FIXED 1.0
		sigma_w_K2 Jeffreys 1.,500
		mflux_K2 Normal 0.0,0.1
		# Photometric priors for LCOGT (including GP) photometry:
		q1_LCOGT Uniform 0.0,1.0
		mdilution_LCOGT FIXED 1.0
		sigma_w_LCOGT Jeffreys 1.,5000
		mflux_LCOGT Normal 0.0,0.1
		# RV priors:
		mu_CORALIE Normal 1.220,0.05
		sigma_w_rv_CORALIE Jeffreys 0.0001,0.1
		mu_FIES Normal 1.215,0.05
		sigma_w_rv_FIES Jeffreys 0.0001,0.1
		mu_HARPS Normal 1.240,0.05
		sigma_w_rv_HARPS Jeffreys 0.0001,0.1

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