npxpy.nodes.misc.Capture

Bases: Node

A class to represent a capture node with attributes and methods for managing capture settings.

Attributes:

Name	Type	Description
capture_type	str	The type of capture (e.g., 'Camera', 'Confocal').
laser_power	float	The laser power for the capture.
scan_area_size	List[float]	The size of the scan area [width, height].
scan_area_res_factors	List[float]	The resolution factors for the scan area.

Source code in npxpy/nodes/misc.py

class Capture(Node):
    """
    A class to represent a capture node with attributes and methods for managing
    capture settings.

    Attributes:
        capture_type (str): The type of capture (e.g., 'Camera', 'Confocal').
        laser_power (float): The laser power for the capture.
        scan_area_size (List[float]): The size of the scan area [width, height].
        scan_area_res_factors (List[float]): The resolution factors for the scan area.
    """

    def __init__(self, name: str = "Capture"):
        """
        Initialize the capture node.

        Parameters:
            name (str): Name of the capture node.
        """
        super().__init__(node_type="capture", name=name)
        self.capture_type = "Camera"
        self._laser_power = None
        self._scan_area_size = None
        self._scan_area_res_factors = None
        self.laser_power = 0.5  # Using setter for validation
        self.scan_area_size = [100.0, 100.0]  # Using setter for validation
        self.scan_area_res_factors = [1.0, 1.0]  # Using setter for validation

    @property
    def laser_power(self):
        """Get the laser power."""
        return self._laser_power

    @laser_power.setter
    def laser_power(self, value: float):
        """
        Set the laser power.

        Parameters:
            value (float): The laser power, must be greater or equal to 0.

        Raises:
            ValueError: If laser_power is less than 0.
        """
        if not isinstance(value, (float, int)) or value < 0:
            raise ValueError("laser_power must be greater or equal to 0.")
        self._laser_power = value

    @property
    def scan_area_size(self):
        """Get the scan area size."""
        return self._scan_area_size

    @scan_area_size.setter
    def scan_area_size(self, value: List[float]):
        """
        Set the scan area size.

        Parameters:
            value (List[float]): The scan area size [width, height].

        Raises:
            ValueError: If any value in scan_area_size is less than 0.
        """
        if len(value) != 2 or not all(
            isinstance(size, (float, int)) for size in value
        ):
            raise TypeError(
                "scan_area_size must be a list of two numbers greater or equal to 0."
            )
        if any(size < 0 for size in value):
            raise ValueError(
                "All elements in scan_area_size must be greater or equal to 0."
            )
        self._scan_area_size = value

    @property
    def scan_area_res_factors(self):
        """Get the scan area resolution factors."""
        return self._scan_area_res_factors

    @scan_area_res_factors.setter
    def scan_area_res_factors(self, value: List[float]):
        """
        Set the scan area resolution factors.

        Parameters:
            value (List[float]): The scan area resolution factors [factor_x, factor_y].

        Raises:
            ValueError: If any value in scan_area_res_factors is less than or equal to 0.
        """
        if len(value) != 2 or not all(
            isinstance(factor, (float, int)) for factor in value
        ):
            raise TypeError(
                "scan_area_res_factors must be a list of two numbers greater than 0."
            )
        if any(factor <= 0 for factor in value):
            raise ValueError(
                "All elements in scan_area_res_factors must be greater than 0."
            )
        self._scan_area_res_factors = value

    def confocal(
        self,
        laser_power: float = 0.5,
        scan_area_size: List[float] = [100.0, 100.0],
        scan_area_res_factors: List[float] = [1.0, 1.0],
    ) -> "Capture":
        """
        Configure the capture node for confocal capture.

        Parameters:
            laser_power (float): The laser power, must be greater or equal to 0.
            scan_area_size (List[float]): The scan area size [width, height].
            scan_area_res_factors (List[float]): The resolution factors for the scan area.

        Returns:
            Capture: The updated Capture object.
        """
        self.laser_power = laser_power
        self.scan_area_size = scan_area_size
        self.scan_area_res_factors = scan_area_res_factors
        self.capture_type = "Confocal"
        return self

    def to_dict(self) -> Dict[str, Any]:
        """
        Convert the Capture object into a dictionary.

        Returns:
            Dict[str, Any]: Dictionary representation of the Capture object.
        """
        node_dict = super().to_dict()  # Get the basic dict from Node
        node_dict.update(
            {
                "capture_type": self.capture_type,
                "laser_power": self.laser_power,
                "scan_area_size": self.scan_area_size,
                "scan_area_res_factors": self.scan_area_res_factors,
            }
        )
        return node_dict

laser_power property writable

Get the laser power.

scan_area_res_factors property writable

Get the scan area resolution factors.

scan_area_size property writable

Get the scan area size.

__init__(name='Capture')

Initialize the capture node.

Parameters:

Name	Type	Description	Default
name	str	Name of the capture node.	'Capture'

Source code in npxpy/nodes/misc.py

def __init__(self, name: str = "Capture"):
    """
    Initialize the capture node.

    Parameters:
        name (str): Name of the capture node.
    """
    super().__init__(node_type="capture", name=name)
    self.capture_type = "Camera"
    self._laser_power = None
    self._scan_area_size = None
    self._scan_area_res_factors = None
    self.laser_power = 0.5  # Using setter for validation
    self.scan_area_size = [100.0, 100.0]  # Using setter for validation
    self.scan_area_res_factors = [1.0, 1.0]  # Using setter for validation

confocal(laser_power=0.5, scan_area_size=[100.0, 100.0], scan_area_res_factors=[1.0, 1.0])

Configure the capture node for confocal capture.

Parameters:

Name	Type	Description	Default
laser_power	float	The laser power, must be greater or equal to 0.	0.5
scan_area_size	List[float]	The scan area size [width, height].	[100.0, 100.0]
scan_area_res_factors	List[float]	The resolution factors for the scan area.	[1.0, 1.0]

Returns:

Name	Type	Description
Capture	Capture	The updated Capture object.

Source code in npxpy/nodes/misc.py

def confocal(
    self,
    laser_power: float = 0.5,
    scan_area_size: List[float] = [100.0, 100.0],
    scan_area_res_factors: List[float] = [1.0, 1.0],
) -> "Capture":
    """
    Configure the capture node for confocal capture.

    Parameters:
        laser_power (float): The laser power, must be greater or equal to 0.
        scan_area_size (List[float]): The scan area size [width, height].
        scan_area_res_factors (List[float]): The resolution factors for the scan area.

    Returns:
        Capture: The updated Capture object.
    """
    self.laser_power = laser_power
    self.scan_area_size = scan_area_size
    self.scan_area_res_factors = scan_area_res_factors
    self.capture_type = "Confocal"
    return self

to_dict()

Convert the Capture object into a dictionary.

Returns:

Type	Description
Dict[str, Any]	Dict[str, Any]: Dictionary representation of the Capture object.

Source code in npxpy/nodes/misc.py

def to_dict(self) -> Dict[str, Any]:
    """
    Convert the Capture object into a dictionary.

    Returns:
        Dict[str, Any]: Dictionary representation of the Capture object.
    """
    node_dict = super().to_dict()  # Get the basic dict from Node
    node_dict.update(
        {
            "capture_type": self.capture_type,
            "laser_power": self.laser_power,
            "scan_area_size": self.scan_area_size,
            "scan_area_res_factors": self.scan_area_res_factors,
        }
    )
    return node_dict