common/lib/camera: Test docs

opencsp/common/lib/camera/ImageAcquisition_DCAM_color.py

@@ -76,6 +76,24 @@ def __init__(self, instance: int = 0, pixel_format: str = 'BayerRG12'):
         self._shutter_cal_values = np.linspace(shutter_min, shutter_max, 2**13).astype(int)
 
     def instance_matches(self, possible_matches: list[ImageAcquisitionAbstract]) -> bool:
+        """
+        Determine whether this camera instance matches any instance in the provided list.
+
+        This method checks if there is another camera instance in the `possible_matches`
+        list that has the same `basler_index` as the current instance.
+
+        Parameters
+        ----------
+        possible_matches : list[ImageAcquisitionAbstract]
+            A list of camera instances to check against. Each instance should be of
+            type `ImageAcquisitionAbstract` and may have a `basler_index` attribute.
+
+        Returns
+        -------
+        bool
+            True when the first matching instance is found; False otherwise.
+        """
+        # "ChatGPT 4o-mini" assisted with generating this docstring.
         for camera in possible_matches:
             if not hasattr(camera, 'basler_index'):
                 continue
@@ -84,6 +102,35 @@ def instance_matches(self, possible_matches: list[ImageAcquisitionAbstract]) ->
         return False
 
     def get_frame(self, encode: bool = True) -> np.ndarray:
+        """
+        Captures a single frame from the camera.
+
+        This method initiates the frame capture process and retrieves the image data
+        from the camera. The captured image can be returned in its raw Bayer format
+        or converted to an RGB format based on the `encode` parameter.
+
+        Parameters
+        ----------
+        encode : bool, optional
+            If True (default), the captured Bayer-encoded image will be converted to
+            a 3D RGB image using the `encode_RG_to_RGB` function. If False, the raw
+            Bayer-encoded image will be returned.
+
+        Returns
+        -------
+        np.ndarray
+            The captured image as a NumPy array. The shape of the array will depend
+            on the encoding:
+            - If `encode` is True, the shape will be (height, width, 3) for RGB images.
+            - If `encode` is False, the shape will be (height, width) for Bayer images.
+
+        Raises
+        ------
+        pylon.RuntimeException
+            If the frame grab is unsuccessful, an exception is raised indicating the
+            failure to capture the frame.
+        """
+        # "ChatGPT 4o-mini" assisted with generating this docstring.
         # Start frame capture
         self.cap.StartGrabbingMax(1)
         grabResult = self.cap.RetrieveResult(5000, pylon.TimeoutHandling_ThrowException)
@@ -147,6 +194,7 @@ def shutter_cal_values(self) -> np.ndarray:
         return self._shutter_cal_values
 
     def close(self):
+        """Closes the camera connection"""
         with et.ignored(Exception):
             super().close()
         with et.ignored(Exception):

opencsp/common/lib/camera/ImageAcquisition_DCAM_mono.py

@@ -100,6 +100,24 @@ def _check_pypylon_version(cls):
             cls._has_checked_pypylon_version = True
 
     def instance_matches(self, possible_matches: list[ImageAcquisitionAbstract]) -> bool:
+        """
+        Determine whether this camera instance matches any instance in the provided list.
+
+        This method checks if there is another camera instance in the `possible_matches`
+        list that has the same `basler_index` as the current instance.
+
+        Parameters
+        ----------
+        possible_matches : list[ImageAcquisitionAbstract]
+            A list of camera instances to check against. Each instance should be of
+            type `ImageAcquisitionAbstract` and may have a `basler_index` attribute.
+
+        Returns
+        -------
+        bool
+            True when the first matching instance is found; False otherwise.
+        """
+        # "ChatGPT 4o-mini" assisted with generating this docstring.
         for camera in possible_matches:
             if not hasattr(camera, 'basler_index'):
                 continue
@@ -108,6 +126,33 @@ def instance_matches(self, possible_matches: list[ImageAcquisitionAbstract]) ->
         return False
 
     def get_frame(self) -> np.ndarray:
+        """
+        Captures a single frame from the Basler DCAM monochromatic camera.
+
+        This method initiates the frame capture process and retrieves the image data
+        from the camera. The method waits for the frame to be captured and returns
+        the image data as a NumPy array.
+
+        Returns
+        -------
+        np.ndarray
+            The captured image as a NumPy array. The shape of the array will depend
+            on the pixel format set during initialization (e.g., Mono8, Mono12).
+
+        Raises
+        ------
+        pylon.RuntimeException
+            If the frame grab is unsuccessful, an exception is raised indicating the
+            failure to capture the frame.
+
+        Notes
+        -----
+        The method calculates the expected exposure time in milliseconds and uses
+        this value to set a timeout for the frame retrieval. The timeout is set to
+        1.5 times the expected image acquisition time to ensure that the frame is
+        captured successfully.
+        """
+        # "ChatGPT 4o-mini" assisted with generating this docstring.
         # Start frame capture
         self.cap.StartGrabbingMax(1)
         exposure_time_ms = self.cap.ExposureTimeRaw.Max / 1000  # exposure time, ms
@@ -170,6 +215,7 @@ def shutter_cal_values(self) -> np.ndarray:
         return self._shutter_cal_values
 
     def close(self):
+        """Closes the camera connection"""
         with et.ignored(Exception):
             super().close()
         with et.ignored(Exception):

opencsp/common/lib/camera/ImageAcquisition_MSMF.py

@@ -24,13 +24,60 @@ def __init__(self, instance: int = 0):
             raise IOError("Error opening webcam")
 
     def instance_matches(self, possible_matches: list[ImageAcquisitionAbstract]) -> bool:
+        """
+        Determine whether this camera instance matches any instance in the provided list.
+
+        This method checks if there is another instance of the `ImageAcquisition` class
+        in the `possible_matches` list. Since only one MSMF camera is supported,
+        the method returns True if any instance of `ImageAcquisition` is found; otherwise,
+        it returns False.
+
+        Parameters
+        ----------
+        possible_matches : list[ImageAcquisitionAbstract]
+            A list of camera instances to check against. Each instance should be of
+            type `ImageAcquisitionAbstract`.
+
+        Returns
+        -------
+        bool
+            True if a matching instance of `ImageAcquisition` is found; False otherwise.
+        """
+        # "ChatGPT 4o-mini" assisted with generating this docstring.
         for camera in possible_matches:
             if isinstance(camera, ImageAcquisition):
                 # only one MSMF camera is supported
                 return True
         return False
 
     def get_frame(self) -> np.ndarray:
+        """
+        Captures a single frame from the connected camera.
+
+        This method reads a frame from the camera and returns it as a NumPy array.
+        If the captured frame is in color (3-dimensional), it is converted to a
+        grayscale image by averaging the color channels. The method raises an
+        exception if the frame capture is unsuccessful.
+
+        Returns
+        -------
+        np.ndarray
+            The captured image as a NumPy array. The shape of the array will be:
+            - (height, width) for grayscale images.
+            - If the input frame is in color, it will be converted to grayscale
+            by averaging the channels.
+
+        Raises
+        ------
+        Exception
+            If the frame was not captured successfully, an exception is raised
+            indicating the failure to capture the frame.
+
+        ValueError
+            If the output frame does not have 2 or 3 dimensions, a ValueError
+            is raised indicating the incorrect number of dimensions.
+        """
+        # "ChatGPT 4o-mini" assisted with generating this docstring.
         # Capture image
         ret, frame = self.cap.read()
 
@@ -90,6 +137,7 @@ def shutter_cal_values(self) -> np.ndarray:
         raise ValueError('exposure_time cannot be adjusted with MSMF camera; adjust screen brightness instead.')
 
     def close(self):
+        """Closes the camera connection"""
         with et.ignored(Exception):
             super().close()
         with et.ignored(Exception):