I implemented Mysha and Max comments

cta-observatory · Jul 16, 2024 · 3daec81 · 3daec81
1 parent d845d14
commit 3daec81
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Showing 2 changed files with 10 additions and 57 deletions.
diff --git a/src/ctapipe/containers.py b/src/ctapipe/containers.py
@@ -19,7 +19,6 @@
     "DL0Container",
     "DL1CameraCalibrationContainer",
     "DL1CameraContainer",
-    "DL1PedestalVarianceContainer",
     "DL1Container",
     "DL2Container",
     "EventCalibrationContainer",
@@ -168,12 +167,12 @@ class EventType(enum.Enum):
 
 
 class VarianceType(enum.Enum):
-    """Enum of variance types used for the DL1PedestalVarianceContainer"""
+    """Enum of variance types used for the VarianceContainer"""
 
     # Simple variance of waveform
-    SIMPLE = 0
+    WAVEFORM = 0
     # Variance of integrated samples of a waveform
-    SAMPLE = 1
+    INTEGRATED = 1
 
 
 class PixelStatus(enum.IntFlag):
@@ -487,17 +486,6 @@ class ImageParametersContainer(Container):
 
 
 class DL1CameraContainer(Container):
-    """
-    Storage of output of camera calibration e.g the final calibrated
-    image in intensity units and the pulse time.
-    """
-
-    image = Field(
-        None,
-        "Numpy array of camera image, after waveform extraction."
-        "Shape: (n_pixel) if n_channels is 1 or data is gain selected"
-        "else: (n_channels, n_pixel)",
-    )
     peak_time = Field(
         None,
         "Numpy array containing position of the peak of the pulse as determined by "
@@ -520,45 +508,11 @@ class DL1CameraContainer(Container):
             "pass only was returned."
         ),
     )
-
     parameters = Field(
         None, description="Image parameters", type=ImageParametersContainer
     )
 
 
-class DL1PedestalVarianceContainer(Container):
-    """
-    Storage of output of camera variance image e.g.
-    the variance of each pixel composed as an image.
-    """
-
-    image = Field(
-        None,
-        "Numpy array of camera variance image"
-        "Shape: (n_pixel) if n_channels is 1 or data is gain selected"
-        "else: (n_channels, n_pixel)",
-    )
-    time = Field(
-        None,
-        "Trigger time for this variance image" "Value is a float",
-    )
-    VarMethod = Field(
-        VarianceType.SIMPLE,
-        "Method by which the variance was calculated"
-        "This can either be a plain variance"
-        "or a variance of integrated samples",
-        type=VarianceType,
-    )
-    is_valid = Field(
-        False,
-        (
-            "True if image extraction succeeded, False if failed "
-            "or in the case of TwoPass methods, that the first "
-            "pass only was returned."
-        ),
-    )
-
-
 class DL1Container(Container):
     """DL1 Calibrated Camera Images and associated data"""
 

diff --git a/src/ctapipe/image/extractor.py b/src/ctapipe/image/extractor.py
@@ -36,7 +36,6 @@
 
 from ctapipe.containers import (
     DL1CameraContainer,
-    DL1PedestalVarianceContainer,
     VarianceType,
 )
 from ctapipe.core import TelescopeComponent
@@ -1307,14 +1306,14 @@ class VarianceExtractor(ImageExtractor):
 
     """
 
-    def __call__(self, waveforms, tel_id, trigger_time) -> DL1PedestalVarianceContainer:
-        variance = np.nanvar(waveforms, dtype="float32", axis=2)
-        return DL1PedestalVarianceContainer(
-            image=variance,
-            VarMethod=VarianceType.SIMPLE,
-            is_valid=True,
-            time=trigger_time,
+    def __call__(
+        self, waveforms, tel_id, selected_gain_channel, broken_pixels
+    ) -> DL1CameraContainer:
+        container = DL1CameraContainer(
+            image=np.nanvar(waveforms, dtype="float32", axis=2),
         )
+        container.meta["ExtractionMethod"] = str(VarianceType.WAVEFORM)
+        return container
 
 
 def deconvolution_parameters(