Module pyaurorax.tools.calibration

Perform various calibration procedures on image data.

Classes

class CalibrationManager

Expand source code

class CalibrationManager:
    """
    The CalibrationManager object is initialized within every PyAuroraX object. It acts as a way to access 
    the submodules and carry over configuration information in the super class.
    """

    def __init__(self):
        pass

    def rego(
        self,
        images: np.ndarray,
        cal_flatfield: Optional[Calibration] = None,
        cal_rayleighs: Optional[Calibration] = None,
        step_dark_frame_correction: bool = True,
        step_flatfield_calibration: bool = True,
        step_rayleighs_calibration: bool = True,
        exposure_length_sec: float = 2.0,
    ) -> np.ndarray:
        """
        Apply various calibration adjustments to a single or set of images raw images.

        Args:
            images (numpy.ndarray): 
                Raw images to perform calibration procedures on.
            cal_flatfield (pyaurorax.data.ucalgary.Calibration): 
                Calibration object containing the flatfield data to utilize. This field is required if
                the `step_flatfield_corection` is set to True.
            cal_rayleighs (pyaurorax.data.ucalgary.Calibration): 
                Calibration object containing the Rayleighs data to utilize. This field is required if 
                the `step_rayleighs_calibration` is set to True.
            step_dark_frame_correction (bool): 
                Perform the dark frame correction step by subtracting an average of a bottom corner grid from 
                the image (ie. 4x4.). Defaults to `True`.
            step_flatfield_calibration (bool): 
                Perform the flatfield correction step. Defaults to `True`. Note that the `cal_flatfield` parameter
                must be supplied if this is True.
            step_rayleighs_calibration (bool): 
                Perform the Rayleighs conversion step. Defaults to `True.` Note that the `cal_rayleighs` parameter
                must be supplied if this is True.
            exposure_length_sec (float): 
                Force the exposure length to be a certain value. Default is TREx NIR's nominal operating mode 
                exposure length of `2.0 seconds`. Adjusting this field should be done with caution.

        Returns:
            The calibrated images. 
            
            The shape of the calibrated data will be same as the input images. The dtype of the calibrated data 
            will depend on if the Rayleighs conversion was performed. If it was, a float32 array will be returned. 
            If it wasn't, the dtype will be the same as input images' dtype.

        Raises:
            ValueError: issues encountered with supplied parameters.
        """
        return func_rego(
            images,
            cal_flatfield,
            cal_rayleighs,
            step_dark_frame_correction,
            step_flatfield_calibration,
            step_rayleighs_calibration,
            exposure_length_sec,
        )

    def trex_nir(
        self,
        images: np.ndarray,
        cal_flatfield: Optional[Calibration] = None,
        cal_rayleighs: Optional[Calibration] = None,
        step_dark_frame_correction: bool = True,
        step_flatfield_calibration: bool = True,
        step_rayleighs_calibration: bool = True,
        exposure_length_sec: float = 5.0,
    ) -> np.ndarray:
        """
        Apply various calibration adjustments to a single or set of images raw images.

        Args:
            images (numpy.ndarray): 
                Raw images to perform calibration procedures on.
            cal_flatfield (pyaurorax.data.ucalgary.Calibration): 
                Calibration object containing the flatfield data to utilize. This field is required if
                the `step_flatfield_corection` is set to True.
            cal_rayleighs (pyaurorax.data.ucalgary.Calibration): 
                Calibration object containing the Rayleighs data to utilize. This field is required if 
                the `step_rayleighs_calibration` is set to True.
            step_dark_frame_correction (bool): 
                Perform the dark frame correction step. Defaults to `True`.
            step_flatfield_calibration (bool): 
                Perform the flatfield correction step. Defaults to `True`. Note that the `cal_flatfield` parameter
                must be supplied if this is True.
            step_rayleighs_calibration (bool): 
                Perform the Rayleighs conversion step. Defaults to `True.` Note that the `cal_rayleighs` parameter
                must be supplied if this is True.
            exposure_length_sec (float): 
                Force the exposure length to be a certain value. Default is TREx NIR's nominal operating mode 
                exposure length of `5.0 seconds`. Adjusting this field should be done with caution.

        Returns:
            The calibrated images. 
            
            The shape of the calibrated data will be same as the input images. The dtype of the calibrated data 
            will depend on if the Rayleighs conversion was performed. If it was, a float32 array will be returned. 
            If it wasn't, the dtype will be the same as input images' dtype.

        Raises:
            ValueError: issues encountered with supplied parameters.
        """
        return func_trex_nir(
            images,
            cal_flatfield,
            cal_rayleighs,
            step_dark_frame_correction,
            step_flatfield_calibration,
            step_rayleighs_calibration,
            exposure_length_sec,
        )

The CalibrationManager object is initialized within every PyAuroraX object. It acts as a way to access the submodules and carry over configuration information in the super class.

Methods

def rego(self,
images: numpy.ndarray,
cal_flatfield: pyucalgarysrs.data.classes.Calibration | None = None,
cal_rayleighs: pyucalgarysrs.data.classes.Calibration | None = None,
step_dark_frame_correction: bool = True,
step_flatfield_calibration: bool = True,
step_rayleighs_calibration: bool = True,
exposure_length_sec: float = 2.0) ‑> numpy.ndarray

Expand source code

def rego(
    self,
    images: np.ndarray,
    cal_flatfield: Optional[Calibration] = None,
    cal_rayleighs: Optional[Calibration] = None,
    step_dark_frame_correction: bool = True,
    step_flatfield_calibration: bool = True,
    step_rayleighs_calibration: bool = True,
    exposure_length_sec: float = 2.0,
) -> np.ndarray:
    """
    Apply various calibration adjustments to a single or set of images raw images.

    Args:
        images (numpy.ndarray): 
            Raw images to perform calibration procedures on.
        cal_flatfield (pyaurorax.data.ucalgary.Calibration): 
            Calibration object containing the flatfield data to utilize. This field is required if
            the `step_flatfield_corection` is set to True.
        cal_rayleighs (pyaurorax.data.ucalgary.Calibration): 
            Calibration object containing the Rayleighs data to utilize. This field is required if 
            the `step_rayleighs_calibration` is set to True.
        step_dark_frame_correction (bool): 
            Perform the dark frame correction step by subtracting an average of a bottom corner grid from 
            the image (ie. 4x4.). Defaults to `True`.
        step_flatfield_calibration (bool): 
            Perform the flatfield correction step. Defaults to `True`. Note that the `cal_flatfield` parameter
            must be supplied if this is True.
        step_rayleighs_calibration (bool): 
            Perform the Rayleighs conversion step. Defaults to `True.` Note that the `cal_rayleighs` parameter
            must be supplied if this is True.
        exposure_length_sec (float): 
            Force the exposure length to be a certain value. Default is TREx NIR's nominal operating mode 
            exposure length of `2.0 seconds`. Adjusting this field should be done with caution.

    Returns:
        The calibrated images. 
        
        The shape of the calibrated data will be same as the input images. The dtype of the calibrated data 
        will depend on if the Rayleighs conversion was performed. If it was, a float32 array will be returned. 
        If it wasn't, the dtype will be the same as input images' dtype.

    Raises:
        ValueError: issues encountered with supplied parameters.
    """
    return func_rego(
        images,
        cal_flatfield,
        cal_rayleighs,
        step_dark_frame_correction,
        step_flatfield_calibration,
        step_rayleighs_calibration,
        exposure_length_sec,
    )

Apply various calibration adjustments to a single or set of images raw images.

Args

images : numpy.ndarray

Raw images to perform calibration procedures on.

cal_flatfield : Calibration

Calibration object containing the flatfield data to utilize. This field is required if the step_flatfield_corection is set to True.

cal_rayleighs : Calibration

Calibration object containing the Rayleighs data to utilize. This field is required if the step_rayleighs_calibration is set to True.

step_dark_frame_correction : bool

Perform the dark frame correction step by subtracting an average of a bottom corner grid from the image (ie. 4x4.). Defaults to True.

step_flatfield_calibration : bool

Perform the flatfield correction step. Defaults to True. Note that the cal_flatfield parameter must be supplied if this is True.

step_rayleighs_calibration : bool

Perform the Rayleighs conversion step. Defaults to True. Note that the cal_rayleighs parameter must be supplied if this is True.

exposure_length_sec : float

Force the exposure length to be a certain value. Default is TREx NIR's nominal operating mode exposure length of 2.0 seconds. Adjusting this field should be done with caution.

Returns

The calibrated images.

The shape of the calibrated data will be same as the input images. The dtype of the calibrated data will depend on if the Rayleighs conversion was performed. If it was, a float32 array will be returned. If it wasn't, the dtype will be the same as input images' dtype.

Raises

ValueError

issues encountered with supplied parameters.

def trex_nir(self,
images: numpy.ndarray,
cal_flatfield: pyucalgarysrs.data.classes.Calibration | None = None,
cal_rayleighs: pyucalgarysrs.data.classes.Calibration | None = None,
step_dark_frame_correction: bool = True,
step_flatfield_calibration: bool = True,
step_rayleighs_calibration: bool = True,
exposure_length_sec: float = 5.0) ‑> numpy.ndarray

Expand source code

def trex_nir(
    self,
    images: np.ndarray,
    cal_flatfield: Optional[Calibration] = None,
    cal_rayleighs: Optional[Calibration] = None,
    step_dark_frame_correction: bool = True,
    step_flatfield_calibration: bool = True,
    step_rayleighs_calibration: bool = True,
    exposure_length_sec: float = 5.0,
) -> np.ndarray:
    """
    Apply various calibration adjustments to a single or set of images raw images.

    Args:
        images (numpy.ndarray): 
            Raw images to perform calibration procedures on.
        cal_flatfield (pyaurorax.data.ucalgary.Calibration): 
            Calibration object containing the flatfield data to utilize. This field is required if
            the `step_flatfield_corection` is set to True.
        cal_rayleighs (pyaurorax.data.ucalgary.Calibration): 
            Calibration object containing the Rayleighs data to utilize. This field is required if 
            the `step_rayleighs_calibration` is set to True.
        step_dark_frame_correction (bool): 
            Perform the dark frame correction step. Defaults to `True`.
        step_flatfield_calibration (bool): 
            Perform the flatfield correction step. Defaults to `True`. Note that the `cal_flatfield` parameter
            must be supplied if this is True.
        step_rayleighs_calibration (bool): 
            Perform the Rayleighs conversion step. Defaults to `True.` Note that the `cal_rayleighs` parameter
            must be supplied if this is True.
        exposure_length_sec (float): 
            Force the exposure length to be a certain value. Default is TREx NIR's nominal operating mode 
            exposure length of `5.0 seconds`. Adjusting this field should be done with caution.

    Returns:
        The calibrated images. 
        
        The shape of the calibrated data will be same as the input images. The dtype of the calibrated data 
        will depend on if the Rayleighs conversion was performed. If it was, a float32 array will be returned. 
        If it wasn't, the dtype will be the same as input images' dtype.

    Raises:
        ValueError: issues encountered with supplied parameters.
    """
    return func_trex_nir(
        images,
        cal_flatfield,
        cal_rayleighs,
        step_dark_frame_correction,
        step_flatfield_calibration,
        step_rayleighs_calibration,
        exposure_length_sec,
    )

Apply various calibration adjustments to a single or set of images raw images.

Args

images : numpy.ndarray

Raw images to perform calibration procedures on.

cal_flatfield : Calibration

Calibration object containing the flatfield data to utilize. This field is required if the step_flatfield_corection is set to True.

cal_rayleighs : Calibration

Calibration object containing the Rayleighs data to utilize. This field is required if the step_rayleighs_calibration is set to True.

step_dark_frame_correction : bool

Perform the dark frame correction step. Defaults to True.

step_flatfield_calibration : bool

Perform the flatfield correction step. Defaults to True. Note that the cal_flatfield parameter must be supplied if this is True.

step_rayleighs_calibration : bool

Perform the Rayleighs conversion step. Defaults to True. Note that the cal_rayleighs parameter must be supplied if this is True.

exposure_length_sec : float

Force the exposure length to be a certain value. Default is TREx NIR's nominal operating mode exposure length of 5.0 seconds. Adjusting this field should be done with caution.

Returns

The calibrated images.

The shape of the calibrated data will be same as the input images. The dtype of the calibrated data will depend on if the Rayleighs conversion was performed. If it was, a float32 array will be returned. If it wasn't, the dtype will be the same as input images' dtype.

Raises

ValueError

issues encountered with supplied parameters.