Have Standardizers add obstime to LayeredImage (#525)

* Have fits and butler standardizers set obstimes

* Clean up unit tests

* Formatting fixes

* Fix comments

* Address comments

* Add type conversion back in for consistency

src/kbmod/standardizers/butler_standardizer.py

@@ -331,8 +331,13 @@ def toLayeredImage(self):
         psfs = self.standardizePSF()
 
         # guaranteed to exist, i.e. safe to access
-        mjds = meta["mjd"]
+        if isinstance(meta["mjd"], (list, tuple)):
+            mjds = meta["mjd"]
+        else:
+            mjds = (meta["mjd"] for e in self.processable)
+
         imgs = []
         for sci, var, mask, psf, t in zip(sciences, variances, masks, psfs, mjds):
-            imgs.append(LayeredImage(RawImage(sci), RawImage(var), RawImage(mask), t, psf))
+            mask = mask.astype(np.float32)
+            imgs.append(LayeredImage(RawImage(sci, t), RawImage(var, t), RawImage(mask, t), psf))
         return imgs

src/kbmod/standardizers/fits_standardizers/fits_standardizer.py

@@ -441,6 +441,7 @@ def toLayeredImage(self):
         # copy. TODO: fix when/if CPP stuff is fixed.
         imgs = []
         for sci, var, mask, psf, t in zip(sciences, variances, masks, psfs, mjds):
-            imgs.append(LayeredImage(RawImage(sci), RawImage(var), RawImage(mask.astype(np.float32)), psf))
-
+            # Converts nd array mask from bool to np.float32
+            mask = mask.astype(np.float32)
+            imgs.append(LayeredImage(RawImage(sci, t), RawImage(var, t), RawImage(mask, t), psf))
         return imgs

tests/test_butlerstd.py

@@ -333,6 +333,32 @@ def test_psf(self):
         self.assertIsInstance(psf, PSF)
         self.assertEqual(psf.get_std(), std.config["psf_std"])
 
+    def test_to_layered_image(self):
+        """Test ButlerStandardizer can create a LayeredImage."""
+        std = Standardizer.get(DatasetId(8), butler=self.butler)
+        self.assertIsInstance(std, ButlerStandardizer)
+
+        # Get the expected FITS files and extract the MJD from the header
+        fits = FitsFactory.get_fits(8, spoof_data=True)
+        hdr = fits["PRIMARY"].header
+        expected_mjd = Time(hdr["DATE-AVG"]).mjd
+
+        # Get list of layered images froom the standardizer
+        butler_imgs = std.toLayeredImage()
+        self.assertEqual(1, len(butler_imgs))
+        img = butler_imgs[0]
+
+        # Compare standardized images
+        np.testing.assert_equal(fits["IMAGE"].data, img.get_science().image)
+        np.testing.assert_equal(fits["VARIANCE"].data, img.get_variance().image)
+        np.testing.assert_equal(fits["MASK"].data, img.get_mask().image)
+
+        # Test that we correctly set metadata
+        self.assertEqual(expected_mjd, img.get_obstime())
+        self.assertEqual(expected_mjd, img.get_science().obstime)
+        self.assertEqual(expected_mjd, img.get_variance().obstime)
+        self.assertEqual(expected_mjd, img.get_mask().obstime)
+
 
 if __name__ == "__main__":
     unittest.main()

tests/test_standardizer.py

@@ -13,8 +13,6 @@
     KBMODV1,
     KBMODV1Config,
     FitsStandardizer,
-    SingleExtensionFits,
-    MultiExtensionFits,
 )
 
 
@@ -344,6 +342,31 @@ def test_psf(self):
         psf = next(std2.standardizePSF())
         self.assertEqual(psf.get_std(), std2.config["psf_std"][0])
 
+    def test_to_layered_image(self):
+        """Test that KBMODV1 standardizer can create LayeredImages."""
+        std = Standardizer.get(self.fits, force=KBMODV1)
+        self.assertIsInstance(std, KBMODV1)
+
+        # Get the expected FITS files and extract the MJD from the header
+        hdr = self.fits["PRIMARY"].header
+        expected_mjd = Time(hdr["DATE-AVG"], format="isot").mjd
+
+        # Get list of layered images from the standardizer
+        layered_imgs = std.toLayeredImage()
+        self.assertEqual(1, len(layered_imgs))
+        img = layered_imgs[0]
+
+        # Compare standardized images
+        np.testing.assert_equal(self.fits["IMAGE"].data, img.get_science().image)
+        np.testing.assert_equal(self.fits["VARIANCE"].data, img.get_variance().image)
+        np.testing.assert_equal(self.fits["MASK"].data, img.get_mask().image)
+
+        # Test that we correctly set metadata
+        self.assertEqual(expected_mjd, img.get_obstime())
+        self.assertEqual(expected_mjd, img.get_science().obstime)
+        self.assertEqual(expected_mjd, img.get_variance().obstime)
+        self.assertEqual(expected_mjd, img.get_mask().obstime)
+
 
 if __name__ == "__main__":
     unittest.main()