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Improve dynamic energy binning logging. #88

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Merged
gabemery merged 1 commit into from
Jun 2, 2026
Merged

Improve dynamic energy binning logging. #88

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14 changes: 11 additions & 3 deletions baccmod/base_acceptance_map_creator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@

from .bkg_collection import BackgroundCollectionZenith, BackgroundCollection, BackgroundCollectionZenithSplitAzimuth
from .exception import BackgroundModelFormatException
from .logging import MOREINFO
from .toolbox import (compute_rotation_speed_fov,
get_unique_wobble_pointings,
get_time_mini_irf,
Expand Down Expand Up @@ -608,6 +609,7 @@ def _compute_dynamic_energy_axis(self, base_energy_axis: MapAxis, data: np.ndarr
indexes_edges = [len(edges_energy_axis)-1]

# Evaluate bin edges fulfilling the dynamic criteria
maximum_wideness_hit = 0
while i > min_i:
# Index for the mean count criteria
j_counts = np.sum(rev_cumsumdata >= self.dynamic_energy_axis_target_statistics)-1
Expand All @@ -625,8 +627,7 @@ def _compute_dynamic_energy_axis(self, base_energy_axis: MapAxis, data: np.ndarr
j = j_counts
else:
j = j_maxw
logger.warning(
'Dynamic energy binning is unable to reach target statistics due to bin maximum bin wideness')
maximum_wideness_hit += 1
indexes_edges.append(j)
rev_cumsumdata -= rev_cumsumdata[j]
i = j
Expand All @@ -636,7 +637,13 @@ def _compute_dynamic_energy_axis(self, base_energy_axis: MapAxis, data: np.ndarr
if self.dynamic_energy_axis_merge_zeros_high_energy and len(zeros_highE)>0:
zeros_highE = np.array([i0], dtype=int)
indexes_edges=np.sort(np.concatenate([zeros_highE, indexes_edges, zeros_lowE], dtype=int))
return MapAxis.from_energy_edges(edges_energy_axis[np.array(indexes_edges, dtype=int)], name='energy')
energy_axis = MapAxis.from_energy_edges(edges_energy_axis[np.array(indexes_edges, dtype=int)], name='energy')
logger.log(MOREINFO,'Dynamic energy binning : %s', np.array_str(np.round(energy_axis.edges, 3)))
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logger.log(MOREINFO,'Number of bin limited by the maximum bin wideness : %d', maximum_wideness_hit)
logger.debug('Number of counts per spatial bin in each energy bin:\n%s', np.array_str(
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np.abs(np.append(np.diff(rev_cumsumdata[np.array(indexes_edges[:-1], dtype=int)]),
cumsumdata[-1]+rev_cumsumdata[indexes_edges[-2]]-rev_cumsumdata[0]))))
return energy_axis

@staticmethod
def _split_observations_azimuth(observations: Observations) -> Tuple[Observations, Observations, Dict[int, Dict[str, Any]]]:
Expand Down Expand Up @@ -910,6 +917,7 @@ def _create_acceptance_model(self,
"""
models={}
for key in off_observations.keys():
logger.info('Creating model for subset : %s', key)
if zenith_interpolation or zenith_binning:
models[key] = self._create_model_cos_zenith_binned(observations=off_observations[key])
else:
Expand Down
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