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Mlarson/extended sources rewrite #7

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0729d03
First pass at folding the extended source stuff into the normal KingF…
mjlarson Jul 27, 2026
a4e6ae7
Remove old extended source class since extended sources are folded in…
mjlarson Jul 27, 2026
186d638
Update tests
mjlarson Jul 27, 2026
652ac0b
Fix up docs testing.
mjlarson Jul 30, 2026
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13 changes: 5 additions & 8 deletions docs/examples.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -141,7 +141,7 @@ bin.
)
results = fitter.fit_all_bins(verbose=True)

alpha_fit = results["alpha"] # shape (n_gamma, n_logE, n_dec)
alpha_fit = results["alpha"] # shape (n_extension, n_gamma, n_logE, n_dec)
beta_fit = results["beta"]

# Continuous evaluation between bin centers:
Expand Down Expand Up @@ -192,8 +192,9 @@ above:
from kingmaker.wrapper import KingSpatialLikelihood
import numpy as np

# Source catalog for the signal-subtraction (marginalized) path.
catalog_decs = np.radians(np.linspace(-60, 60, 13))
# Stand-in "data" events and a point-source position for one trial.
data_events = signal_events[:1000]
source_ra, source_dec = 0.5, 0.2

wrapper = KingSpatialLikelihood(
signal_events=signal_events,
Expand All @@ -202,14 +203,10 @@ above:
cache_parameters=False,
# Enable the RA-marginalized path for signal-subtraction likelihoods.
enable_marginalization=True,
marginalization_source_decs=catalog_decs,
marginalization_source_decs=np.array([source_dec]),
marginalization_angular_cutoff=np.radians(10.0),
)

# Stand-in "data" events and a point-source position for one trial.
data_events = signal_events[:1000]
source_ra, source_dec = 0.5, 0.2

# Per trial: cache per-event parameters once, then evaluate as needed.
# set_events precomputes both the standard and marginalized PDF matrices.
wrapper.set_events(
Expand Down
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