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DM-45990: Create initial_pvi background metric #1114

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DM-45990: Create initial_pvi background metric #1114

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33 changes: 29 additions & 4 deletions python/lsst/pipe/tasks/computeExposureSummaryStats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -522,7 +522,11 @@ def update_background_stats(self, summary, background):
Parameters
----------
summary : `lsst.afw.image.ExposureSummaryStats`
Summary object to update in-place.
Summary object to update in-place. This method adds/updates the
following fields:
- `skyBg`: Median sky background value across background models.
- `skyBgNormRange`: Normalized range (max - min / median) of the
combined sky background, used to quantify spatial variation.
background : `lsst.afw.math.BackgroundList` or `None`
Background model. If `None`, all fields that depend on the
background will be reset (generally to NaN).
Expand All @@ -535,11 +539,32 @@ def update_background_stats(self, summary, background):
as well.
"""
if background is not None:
bgStats = (bg[0].getStatsImage().getImage().array
for bg in background)
summary.skyBg = float(sum(np.median(bg[np.isfinite(bg)]) for bg in bgStats))
bgStats = []
for bg in background:
statsImageF = bg[0].getStatsImage().getImage()
bgArray = statsImageF.array
bgArray[~np.isfinite(bgArray)] = np.nan
bgStats.append(bgArray)
summary.skyBg = float(sum(np.nanmedian(bg) for bg in bgStats))
shapes = [arr.shape for arr in bgStats]
if len(set(shapes)) != 1:
raise RuntimeError(
f"BackgroundList images from background models have different shapes: {shapes}"
f"bgStats: {bgStats}"
)
skyBgSumImage = np.sum(np.stack(bgStats), axis=0)

median = np.nanmedian(skyBgSumImage)
if median != 0 and np.isfinite(median):
summary.skyBgNormRange = float(
(np.nanmax(skyBgSumImage) - np.nanmin(skyBgSumImage)) / median
)
else:
summary.skyBgNormRange = float("nan")
else:
summary.skyBg = float("nan")
summary.skyBgNormRange = float("nan")
breakpoint()

def update_masked_image_stats(self, summary, masked_image):
"""Compute summary-statistic fields that depend on the masked image
Expand Down