Variance calibration #2636

ctoennis · 2024-11-04T10:18:19Z

This PR adds a trait to the CameraCalibrator called "image_calibration_type". This trait allows to switch the method of calibration between "charge" and "variance", with the former being the calibration method for the existing image extractors and the latter being the method to calibrate variance images.

I also made some small adjustment to the variance extractor so that it works in the CameraCalibrator.

…se with Calibrator

TjarkMiener · 2024-11-04T13:16:00Z

thanks for putting this together @ctoennis! In case I'm not missing something, I think we can (maybe should) apply this sqrt operation before writing the coefficients. Therefore we do not need the different cases here in the code. Would that work?

ctoennis · 2024-11-04T13:20:07Z

@TjarkMiener Yes, that should work. The calibration events would only need the sqrt coeficcients. Only thing is that this needs to be documented somewhere.

ctoennis · 2024-11-04T13:21:04Z

Though, the changes to the variance extractor should then still be kept so that it works with the calibrator.

src/ctapipe/calib/camera/calibrator.py

mexanick · 2024-11-04T15:20:26Z

src/ctapipe/calib/camera/calibrator.py

@@ -73,6 +79,15 @@ class CameraCalibrator(TelescopeComponent):
        help="Name of the ImageExtractor subclass to be used.",
    ).tag(config=True)

+    image_calibration_type = CaselessStrEnum(


mexanick · 2024-11-04T15:21:27Z

src/ctapipe/calib/camera/calibrator.py

+            if (
+                self.apply_peak_time_shift.tel[tel_id]
+                and remaining_shift is not None
+                and self.image_calibration_type == "charge"


Do we really need to alter this condition?

The variance extractor has no peak time, so applying the peak time shift otherwise throws an error

Just check if dl1.peak_time is not None instead of a specific extractor.

@maxnoe that makes sense

src/ctapipe/calib/camera/calibrator.py

mexanick · 2024-11-04T15:22:32Z

src/ctapipe/calib/camera/tests/test_calibrator.py

+    calibrator(example_event)
+    image = example_event.dl1.tel[tel_id].image
+    assert image is not None
+    assert image.shape == (1764,)


from where this shape comes? What telescope is this?

That is from the example event. Not sure what telescope this is

FlashCam from the number of pixels

mexanick · 2024-11-04T15:24:08Z

src/ctapipe/image/extractor.py

@@ -1308,7 +1308,7 @@ def __call__(
        self, waveforms, tel_id, selected_gain_channel, broken_pixels
    ) -> DL1CameraContainer:
        container = DL1CameraContainer(
-            image=np.nanvar(waveforms, dtype="float32", axis=2),
+            image=np.nanvar(waveforms, dtype="float32", axis=2)[0],


We shall be able to work with multiple gains, why do you introduce this change?

np.nanvar was giving me an extra dimension on top of the gain. I think I can fix this with the keepdims parameter

TjarkMiener · 2024-11-04T15:24:54Z

src/ctapipe/calib/camera/calibrator.py

+                if self.image_calibration_type == "charge":
+                    dl1.image *= dl1_calib.relative_factor / dl1_calib.absolute_factor
+                elif self.image_calibration_type == "variance":
+                    dl1.image *= np.sqrt(
+                        dl1_calib.relative_factor / dl1_calib.absolute_factor
+                    )


You could check here if the extractor.__class__.__name__ is VarianceExtractor rather than passing the specific config parameter.

mexanick · 2024-11-05T10:28:54Z

src/ctapipe/image/extractor.py

@@ -1308,7 +1308,7 @@ def __call__(
        self, waveforms, tel_id, selected_gain_channel, broken_pixels
    ) -> DL1CameraContainer:
        container = DL1CameraContainer(
-            image=np.nanvar(waveforms, dtype="float32", axis=2),
+            image=np.nanvar(waveforms, dtype="float32", keepdims=False, axis=2),


A bit weird that you need to set keepdims=False explicitly, but ok.

i will check again if i make it work without that

Should work without it:

x = np.random.uniform(size=(2,1800, 1000)) In [1]: np.nanvar(x, axis=2).shape Out[2]: (2, 1800) In [2]: np.nanvar(x, axis=2, keepdims=True).shape Out[2]: (2, 1800, 1) In [3]: np.nanvar(x, axis=2, keepdims=False).shape Out[3]: (2, 1800)

mexanick · 2024-11-05T10:29:46Z

src/ctapipe/calib/camera/tests/test_calibrator.py

+    calibrator(example_event)
+    image = example_event.dl1.tel[tel_id].image
+    assert image is not None
+    assert image.shape == (


Add a test with the LST (two gains)

would it make sense to add a test for other extractor with the LST?

You could use a parametrized test here to test all telescope types. (@pytest.mark.parametrized). See for example the code in ctapipe/instrument/tests/test_telescope.py

src/ctapipe/calib/camera/calibrator.py

maxnoe · 2024-11-06T08:30:57Z

docs/changes/2636.features.rst

@@ -0,0 +1 @@
+Makes changes to the CameraCalibrator in ctapipe.calib.camera.calibrator that allows it to correctly variance images generated with the VarianceExtractor


Please describe the actual change, not just say "there are changes". Also there is a verb missing here (calibrate?)

i added some explanation

maxnoe · 2024-11-06T11:35:31Z

You still need the peak_time check, right?

ctoennis · 2024-11-06T11:37:10Z

Oh yes, that will be still needed

TjarkMiener · 2024-11-06T11:41:22Z

I discussed with @mexanick offline yesterday. We might not want to run the tool for computing camera calibration coefficients twice and store two separated files (one for comics; one for pointing calibration), just to square one column here. What do you think?

mexanick · 2024-11-06T13:09:04Z

at least for now, I would avoid recomputation of the calibrations just for variance. With the current code, we can always have this possibility to test, if needed.

src/ctapipe/calib/camera/calibrator.py

kosack · 2024-11-07T10:37:34Z

src/ctapipe/calib/camera/tests/test_calibrator.py

+    calibrator(example_event)
+    image = example_event.dl1.tel[tel_id].image
+    assert image is not None
+    assert image.shape == (


You could use a parametrized test here to test all telescope types. (@pytest.mark.parametrized). See for example the code in ctapipe/instrument/tests/test_telescope.py

ctoennis · 2024-11-07T11:20:24Z

i will change the test to check all cameras

ctoennis · 2024-11-07T12:43:33Z

@kosack I used the camera_geometry fixture instead to check for all cameras. In the end I just need the geometry, so that should work well.

ctoennis · 2024-11-07T12:47:58Z

I think there is an issue with the recent change to the changelog check (#2637).

ctoennis · 2024-11-08T14:37:29Z

i switched it to a parametrized test for the different cameras now and caught the other test for name and switched it to isinstance

…data for test

src/ctapipe/calib/camera/calibrator.py

src/ctapipe/calib/camera/tests/test_calibrator.py

docs/changes/2636.feature.rst

maxnoe · 2024-11-12T14:25:56Z

src/ctapipe/calib/camera/calibrator.py

+            if (
+                self.apply_peak_time_shift.tel[tel_id]
+                and remaining_shift is not None
+                and dl1.peak_time is not None


logically, I'd put the dl1.peak_time is not None check first

docs/changes/2636.feature.rst

Christoph Toennis added 4 commits November 1, 2024 16:54

Adding different method of applying calibration

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Adding tests for variance calibration, fixing VarianceExtractor for u…

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…se with Calibrator

improving docustring

dd3a59f

Fixing error in VarianceExtractor test

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ctoennis added the calibration label Nov 4, 2024

ctoennis requested review from maxnoe and kosack November 4, 2024 10:18

ctoennis self-assigned this Nov 4, 2024

adding changelog

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Implementing change suggested by max

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Fixing variance calibration and adding test with LST camera

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Rename changelog entry and update formatting

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Making test_dl1_variance_calib perform the test for all cameras

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Switching to isinstance to test for variance extractor

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Testing all cameras through test_subarray fixture now, creating mock …

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		@@ -0,0 +1 @@
		Makes changes to the CameraCalibrator in ctapipe.calib.camera.calibrator that allows it to correctly variance images generated with the VarianceExtractor

Variance calibration #2636

Are you sure you want to change the base?

Variance calibration #2636

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ctoennis commented Nov 4, 2024

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