pass tests

python/lsst/meas/algorithms/computeExPsf.py

@@ -1,6 +1,7 @@
 from lsst.pex.config import Config, Field
 from lsst.pipe.base import Task
 import treecorr
+import copy
 
 
 __all__ = (
@@ -76,10 +77,10 @@ def run(self, de1, de2, ra, dec, units="arcmin"):
         kk = treecorr.KKCorrelation(config_kk)
 
         kk.process(cat1)
-        kk_E1 = kk.xi
+        kk_E1 = copy.deepcopy(kk.xi[0])
         kk.process(cat2)
-        kk_E2 = kk.xi
+        kk_E2 = copy.deepcopy(kk.xi[0])
         kk.process(cat1, cat2)
-        kk_Ex = kk.xi
+        kk_Ex = copy.deepcopy(kk.xi[0])
 
         return kk_E1, kk_E2, kk_Ex

tests/test_computeExPsf.py

@@ -65,28 +65,27 @@ def generate_gaussian_random_field(
     correlation_length=10.0,
     white_noise=1.0,
     seed=42,
-    coord=None,
+    input_coord=None,
 ):
     """
     TO DO.
     """
     np.random.seed(seed)
 
-    if coord is not None:
-        npoints = len(coord[:, 0])
+    if input_coord is not None:
+        npoints = len(input_coord[:, 0])
 
     if npoints > nmax:
         ngenerated = nmax
     else:
         ngenerated = npoints
 
-    if coord is not None or npoints > nmax:
+    if input_coord is not None or npoints > nmax:
         x1 = np.random.uniform(xmin, xmax, ngenerated)
         x2 = np.random.uniform(ymin, ymax, ngenerated)
         coord1 = np.array([x1, x2]).T
     else:
-        coord1 = coord
-
+        coord1 = input_coord
     kernel = rbf_kernel(coord1, coord1, std, correlation_length)
     kernel += np.eye(ngenerated) * white_noise**2
 
@@ -97,10 +96,12 @@ def generate_gaussian_random_field(
     # and then interpolate it with a GP to do data augmentation.
 
     if npoints > nmax:
-        if coord is None:
+        if input_coord is None:
             x1 = np.random.uniform(xmin, xmax, npoints)
             x2 = np.random.uniform(ymin, ymax, npoints)
             coord = np.array([x1, x2]).T
+        else:
+            coord = input_coord
 
         tgp = GaussianProcessTreegp(
             std=std,
@@ -129,50 +130,59 @@ def setUp(self):
             "ymin": 0,
             "ymax": 2000,
             "npoints": 10000,
-            "nmax": 1000,
+            "nmax": 2000,
             "std": 1.0,
-            "white_noise": 0.1,
+            "white_noise": 0.01,
         }
 
         coord1, de1 = generate_gaussian_random_field(
-            correlation_length=100.0,
+            correlation_length=200.0,
             seed=42,
-            coord=None,
+            input_coord=None,
             **kwargs_grf,
         )
 
         coord2, de2 = generate_gaussian_random_field(
-            correlation_length=300.0,
-            seed=43,
-            coord=coord1,
+            correlation_length=100.0,
+            seed=44,
+            input_coord=coord1,
             **kwargs_grf,
         )
 
         self.coord1 = coord1
         self.coord2 = coord2
-        self.de1 = de1 * 1e-3
-        self.de2 = de2 * 1e-3
+        self.de1 = de1
+        self.de2 = de2
 
     def test_comp_ex_psf(self):
         """Test that ex metric are compute and make sense."""
 
         np.testing.assert_equal(self.coord1, self.coord2)
 
-        ra = self.coord1[:,0]
-        dec = self.coord1[:,1]
+        ra = self.coord1[:, 0]
+        dec = self.coord1[:, 1]
 
         config = ComputeExPsfTask.ConfigClass()
-        config.thetaMin = 0.0
+        config.thetaMin = 0.01
         config.thetaMax = 5.0
 
         task = ComputeExPsfTask(config)
-        k_E1, kk_E2, kk_Ex = task.run(self.de1, self.de2, ra, dec, units="arcmin")
+        kk_E1, kk_E2, kk_Ex = task.run(self.de1, self.de2, ra, dec, units="arcmin")
+
+        np.testing.assert_allclose(kk_E1, 1.0, atol=2e-1)
+        np.testing.assert_allclose(kk_E2, 1.0, atol=2e-1)
+        np.testing.assert_allclose(kk_Ex, 0.0, atol=1e-1)
+
+        config = ComputeExPsfTask.ConfigClass()
+        config.thetaMin = 600.0
+        config.thetaMax = 1000.0
+
+        task = ComputeExPsfTask(config)
+        kk_E1, kk_E2, kk_Ex = task.run(self.de1, self.de2, ra, dec, units="arcmin")
 
-        # dumb test to make sure I reach that point.
-        # TO DO: to remove, and add more complex tests.
-        TEST = 42
-        if TEST == 42:
-            raise ValueError("TEST == 42")
+        np.testing.assert_allclose(kk_E1, 0.0, atol=1e-1)
+        np.testing.assert_allclose(kk_E2, 0.0, atol=1e-1)
+        np.testing.assert_allclose(kk_Ex, 0.0, atol=1e-1)
 
 
 def setup_module(module):