Separate noises (#254)

* Separate the two noises * Updated tests * Possibility to choose which noise is drawn * Update doc and notebook * Changed lists to tuples * Fix test * Fix all tests * Updated notebooks * Revert change * Notebooks
LSSTDESC · Feb 25, 2022 · a3de7a6 · a3de7a6
1 parent 6afd759
commit a3de7a6
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Showing 11 changed files with 118 additions and 118 deletions.
diff --git a/btk/draw_blends.py b/btk/draw_blends.py
@@ -128,7 +128,7 @@ def __init__(
         stamp_size=24,
         cpus=1,
         verbose=False,
-        add_noise=True,
+        add_noise="all",
         shifts=None,
         indexes=None,
         channels_last=False,
@@ -146,7 +146,11 @@ def __init__(
             stamp_size (float): Size of the stamps, in arcseconds
             cpus (int): Number of cpus to use; defines the number of minibatches
             verbose (bool): Indicates whether additionnal information should be printed
-            add_noise (bool): Indicates if the blends should be generated with noise
+            add_noise (str): Indicates if the blends should be generated with noise.
+                            "all" indicates that all the noise should be applied,
+                            "background" adds only the background noise,
+                            "galaxy" only the galaxy noise, and "none" gives noiseless
+                            images.
             shifts (list): Contains arbitrary shifts to be applied instead of
                            random shifts. Must be of length batch_size. Must be used
                            with indexes. Used mostly for internal testing purposes.
@@ -416,12 +420,20 @@ def render_blend(self, blend_catalog, psf, filt, survey, seedseq_blend, extra_da
             _blend_image += single_image
 
         # add noise.
-        if self.add_noise:
+        if self.add_noise in ("galaxy", "all"):
             if self.verbose:
-                print("Noise added to blend image")
+                print("Galaxy noise added to blend image")
             generator = galsim.random.BaseDeviate(seed=seedseq_blend.generate_state(1))
-            noise = galsim.PoissonNoise(rng=generator, sky_level=mean_sky_level)
-            _blend_image.addNoise(noise)
+            galaxy_noise = galsim.PoissonNoise(rng=generator, sky_level=0.0)
+            _blend_image.addNoise(galaxy_noise)
+        if self.add_noise in ("background", "all"):
+            if self.verbose:
+                print("Background noise added to blend image")
+            generator = galsim.random.BaseDeviate(seed=seedseq_blend.generate_state(1))
+            background_noise = galsim.PoissonNoise(rng=generator, sky_level=mean_sky_level)
+            noise_image = galsim.Image(np.zeros((pix_stamp_size, pix_stamp_size)))
+            noise_image.addNoise(background_noise)
+            _blend_image += noise_image
 
         blend_image = _blend_image.array
         return blend_image, iso_image

diff --git a/docs/source/tutorials.rst b/docs/source/tutorials.rst
@@ -286,7 +286,7 @@ Now that we have all the objects at our disposal, we can create the DrawBlendsGe
       batch_size=8,
       stamp_size=stamp_size,
       cpus=1,
-      add_noise=True,
+      add_noise="all",
       seed=seed
   )
 
@@ -452,7 +452,7 @@ Saving the results can be automatically achieved by providing the save_path argu
       batch_size=100,
       stamp_size=stamp_size,
       cpus=1,
-      add_noise=True,
+      add_noise="all",
       save_path=save_path
   )
   meas_generator = btk.measure.MeasureGenerator(btk.measure.sep_measure,draw_generator,save_path=save_path)
@@ -500,7 +500,7 @@ We can now create the corresponding instance of ``DrawBlendsGenerator``. There i
           batch_size=batch_size,
           stamp_size=stamp_size,
           cpus=1,
-          add_noise=True,
+          add_noise="all",
           verbose=False,
       )
 

diff --git a/notebooks/00-intro.ipynb b/notebooks/00-intro.ipynb
diff --git a/notebooks/01a-cosmos_tutorial.ipynb b/notebooks/01a-cosmos_tutorial.ipynb
@@ -87,7 +87,7 @@
     "        batch_size=batch_size,\n",
     "        stamp_size=stamp_size,\n",
     "        cpus=1,\n",
-    "        add_noise=True,\n",
+    "        add_noise=\"all\",\n",
     "        verbose=False,\n",
     "    )"
    ]

diff --git a/notebooks/02a-multi-tutorial.ipynb b/notebooks/02a-multi-tutorial.ipynb
diff --git a/notebooks/02b-custom-tutorial.ipynb b/notebooks/02b-custom-tutorial.ipynb
diff --git a/tests/test_cosmos.py b/tests/test_cosmos.py
@@ -30,7 +30,7 @@ def test_cosmos_galaxies():
         batch_size=batch_size,
         stamp_size=stamp_size,
         cpus=1,
-        add_noise=True,
+        add_noise="all",
         verbose=True,
     )
 
@@ -51,7 +51,7 @@ def test_cosmos_ext_galaxies():
         batch_size=batch_size,
         stamp_size=stamp_size,
         cpus=1,
-        add_noise=True,
+        add_noise="all",
         verbose=True,
     )
 

diff --git a/tests/test_draw.py b/tests/test_draw.py
@@ -13,7 +13,7 @@
 def get_draw_generator(
     batch_size=8,
     cpus=1,
-    add_noise=True,
+    add_noise="all",
     fixed_parameters=False,
     sampling_function=None,
 ):
@@ -107,9 +107,9 @@ def match_blend_images_default(blend_images):
         the mean and std values in the batch. This is compared to the values
         measured a priori for the default input settings.
         """
-        test_batch_max = np.array([175.012, 1601.121, 7951.862, 11260.612, 9006.189, 5224.317])
-        test_batch_mean = 6.116279698020711
-        test_batch_std = 403.68242694018846
+        test_batch_max = np.array([172.012, 1372.121, 7881.862, 10346.612, 9120.189, 4965.317])
+        test_batch_mean = 6.123635022094785
+        test_batch_std = 403.7842461889957
         batch_max = blend_images.max(axis=(0, 2, 3))
         batch_mean = blend_images.mean()
         batch_std = blend_images.std()
@@ -138,7 +138,7 @@ def match_background_noise(blend_images):
         the r band. This is compared to the values measured a priori for the
         default input settings.
         """
-        test_batch_noise = 128667.07421875
+        test_batch_noise = 128664.3287115097
         batch_noise = np.var(blend_images[1, 2, 0:32, 0:32])
         np.testing.assert_almost_equal(
             batch_noise,

diff --git a/tests/test_group_sampling.py b/tests/test_group_sampling.py
@@ -44,6 +44,6 @@ def test_group_sampling():
     rel_diff1 = (test_batch_max - batch_max) / test_batch_max
     rel_diff2 = (batch_mean - test_batch_mean) / test_batch_mean
     rel_diff3 = (batch_std - test_batch_std) / test_batch_std
-    assert np.all(rel_diff1 <= 0.12)
-    assert np.all(rel_diff2 <= 0.12)
-    assert np.all(rel_diff3 <= 0.12)
+    assert np.all(rel_diff1 <= 0.15)
+    assert np.all(rel_diff2 <= 0.15)
+    assert np.all(rel_diff3 <= 0.15)
diff --git a/tests/test_metrics.py b/tests/test_metrics.py
@@ -105,7 +105,7 @@ def test_measure_kwargs(mock_show):
     )
     _, _, results = next(metrics_generator)
     average_precision = auc(results, "sep_measure", 2, plot=True)
-    assert average_precision == 0.375
+    assert average_precision == 0.4375
 
 
 def test_detection_eff_matrix():

diff --git a/tests/test_mr.py b/tests/test_mr.py
@@ -20,7 +20,7 @@ def test_multiresolution(mock_show):
     stamp_size = 24.0
     batch_size = 8
     cpus = 1
-    add_noise = True
+    add_noise = "all"
     surveys = get_surveys(["Rubin", "HSC"])
 
     catalog = CatsimCatalog.from_file(catalog_name)