add comments

python/lsst/meas/algorithms/computeExPsf.py

@@ -28,7 +28,7 @@
 import numpy.typing as npt
 
 
-__all__ = "ComputeExPsfTask"
+__all__ = ("ComputeExPsfTask")
 
 
 class ComputeExPsfTask(Task):
@@ -100,4 +100,4 @@ def run(
         kk.process(cat1, cat2)
         kk_Ex = copy.deepcopy(kk.xi[0])
 
-        return pipeBase.Struct(E1=kk_E1, E2=kk_E2, Ex=kk_Ex)
+        return pipeBase.Struct(metric_E1=kk_E1, metric_E2=kk_E2, metric_Ex=kk_Ex)

python/lsst/meas/algorithms/treecorrUtils.py

@@ -1,3 +1,25 @@
+# This file is part of meas_algorithms.
+#
+# Developed for the LSST Data Management System.
+# This product includes software developed by the LSST Project
+# (https://www.lsst.org).
+# See the COPYRIGHT file at the top-level directory of this distribution
+# for details of code ownership.
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+
 from lsst.pex.config import ChoiceField, Config, Field, FieldValidationError
 
 
@@ -16,8 +38,9 @@ class TreecorrConfig(Config):
 
     Notes
     -----
-    This is intended to be used in CalcRhoStatistics class. It only supports
-    some of the fields that are relevant for rho-statistics calculations.
+    This is intended to be used with correlations of PSF residuals. It only supports
+    some of the fields that are relevant for rho-statistics calculations and the likes
+    of it.
     """
 
     nbins = Field[int](

tests/test_computeExPsf.py

@@ -236,9 +236,9 @@ def test_comp_ex_psf(self) -> None:
         # to be close to the input variance for de1 and de2. Cross correlation
         # between de1 and de2 should be zeros are they are 2 indendant field.
 
-        np.testing.assert_allclose(output1.E1, 1.0, atol=2e-1)
-        np.testing.assert_allclose(output1.E2, 1.0, atol=2e-1)
-        np.testing.assert_allclose(output1.Ex, 0.0, atol=1e-1)
+        np.testing.assert_allclose(output1.metric_E1, 1.0, atol=2e-1)
+        np.testing.assert_allclose(output1.metric_E2, 1.0, atol=2e-1)
+        np.testing.assert_allclose(output1.metric_Ex, 0.0, atol=1e-1)
 
         config = ComputeExPsfTask.ConfigClass()
 
@@ -253,9 +253,9 @@ def test_comp_ex_psf(self) -> None:
         task = ComputeExPsfTask(config)
         output2 = task.run(self.de1, self.de2, ra, dec, units="arcmin")
 
-        np.testing.assert_allclose(output2.E1, 0.20, atol=1e-1)
-        np.testing.assert_allclose(output2.E2, 0.05, atol=1e-1)
-        np.testing.assert_allclose(output2.Ex, 0.0, atol=1e-1)
+        np.testing.assert_allclose(output2.metric_E1, 0.20, atol=1e-1)
+        np.testing.assert_allclose(output2.metric_E2, 0.05, atol=1e-1)
+        np.testing.assert_allclose(output2.metric_Ex, 0.0, atol=1e-1)
 
         config = ComputeExPsfTask.ConfigClass()
 
@@ -271,9 +271,9 @@ def test_comp_ex_psf(self) -> None:
         task = ComputeExPsfTask(config)
         output2 = task.run(self.de1, self.de2, ra, dec, units="arcmin")
 
-        np.testing.assert_allclose(output2.E1, 0.0, atol=1e-1)
-        np.testing.assert_allclose(output2.E2, 0.0, atol=1e-1)
-        np.testing.assert_allclose(output2.Ex, 0.0, atol=1e-1)
+        np.testing.assert_allclose(output2.metric_E1, 0.0, atol=1e-1)
+        np.testing.assert_allclose(output2.metric_E2, 0.0, atol=1e-1)
+        np.testing.assert_allclose(output2.metric_Ex, 0.0, atol=1e-1)
 
 
 def setup_module(module):