DM-13055 Add centroid CovarianceMatrix to TestDataset #105
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python/lsst/meas/base/tests.py
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| @@ -345,6 +348,9 @@ def addSource(self, flux, centroid, shape=None): | |||
| record = self.catalog.addNew() | |||
| record.set(self.keys["flux"], flux) | |||
| record.set(self.keys["centroid"], centroid) | |||
| offdiag = centroid[0]*centroid[1]*0.001 | |||
| covariance = np.matrix(((centroid[0]*0.01, offdiag), (offdiag, centroid[1]*0.01))) | |||
| record.set(self.keys["centroid_sigma"], covariance.astype(np.float32)) | |||
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Setting the centroid uncertainty to be proportional to the centroid is a little weird, as it gives the uncertainty a trend with position. Of course, the test data is highly artificial, and if you want such a trend to test something, I think that's fine - just wanted to see what you were thinking here.
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No deep thought process, I just needed to put something in for the errors. If you have something else you'd prefer, please let me know.
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If there's already an RNG near this code, maybe just make them random? If not, don't worry about it.
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Take a look at the change I just pushed and tell me what you think.
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