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Coordinates¤

Spec

dLux.coordinates.Spec ¤

Bases: Base

Abstract base class for coordinate/sampling specifications.

UML

UML

Source code in src/dLux/coordinates.py
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class Spec(zdx.Base):
    """
    Abstract base class for coordinate/sampling specifications.

    ??? abstract "UML"
        ![UML](../assets/uml/Spec.png)
    """

    pass
PadSpec

dLux.coordinates.PadSpec ¤

Bases: Spec

Coordinate specification defined via integer padding and cropping factors relative to an input grid size.

UML

UML

Attributes:

Name Type Description
pad int

Factor by which to increase the grid size. The padded grid will have n * pad pixels along each axis.

crop int

Factor by which to reduce the grid size after processing. The cropped grid will have n_out // crop pixels along each axis.

c float

Centre coordinate of the grid, in metres.

Source code in src/dLux/coordinates.py
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class PadSpec(Spec):
    """
    Coordinate specification defined via integer padding and cropping factors
    relative to an input grid size.

    ??? abstract "UML"
        ![UML](../assets/uml/PadSpec.png)

    Attributes
    ----------
    pad : int
        Factor by which to increase the grid size. The padded grid will have
        ``n * pad`` pixels along each axis.
    crop : int
        Factor by which to reduce the grid size after processing. The cropped
        grid will have ``n_out // crop`` pixels along each axis.
    c : float
        Centre coordinate of the grid, in metres.
    """

    pad: int
    crop: int
    c: float

    def __init__(self, pad=1, crop=1, c=0.0):
        """
        Parameters
        ----------
        pad : int = 1
            Grid size increase factor.
        crop : int = 1
            Grid size reduction factor applied after processing.
        c : float = 0.0
            Centre coordinate of the grid, in metres.
        """
        self.pad = int(pad)
        self.crop = int(crop)
        self.c = np.asarray(c, float)

__init__(pad=1, crop=1, c=0.0) ¤

Parameters:

Name Type Description Default
pad int = 1

Grid size increase factor.

1
crop int = 1

Grid size reduction factor applied after processing.

1
c float = 0.0

Centre coordinate of the grid, in metres.

0.0
Source code in src/dLux/coordinates.py
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def __init__(self, pad=1, crop=1, c=0.0):
    """
    Parameters
    ----------
    pad : int = 1
        Grid size increase factor.
    crop : int = 1
        Grid size reduction factor applied after processing.
    c : float = 0.0
        Centre coordinate of the grid, in metres.
    """
    self.pad = int(pad)
    self.crop = int(crop)
    self.c = np.asarray(c, float)
CoordSpec

dLux.coordinates.CoordSpec ¤

Bases: Spec

Coordinate specification defined explicitly by number of pixels, pixel scale, and centre offset.

UML

UML

Attributes:

Name Type Description
n int

Number of pixels along each axis.

d float

Pixel scale (spacing between adjacent pixels), in metres.

c float

Centre coordinate of the grid, in metres.

xs (Array, property)

Derived pixel-centre coordinates along one axis, in metres.

fov (float, property)

Derived total field of view of the grid, in metres.

extent (tuple[float, float], property)

Derived coordinate range of the grid edges, in metres.

Source code in src/dLux/coordinates.py
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class CoordSpec(Spec):
    """
    Coordinate specification defined explicitly by number of pixels, pixel
    scale, and centre offset.

    ??? abstract "UML"
        ![UML](../assets/uml/CoordSpec.png)

    Attributes
    ----------
    n : int
        Number of pixels along each axis.
    d : float
        Pixel scale (spacing between adjacent pixels), in metres.
    c : float
        Centre coordinate of the grid, in metres.
    xs : Array, property
        Derived pixel-centre coordinates along one axis, in metres.
    fov : float, property
        Derived total field of view of the grid, in metres.
    extent : tuple[float, float], property
        Derived coordinate range of the grid edges, in metres.
    """

    n: int
    d: float
    c: float

    def __init__(self, n=None, d=None, c=0.0):
        """
        Parameters
        ----------
        n : int = None
            Number of pixels along each axis.
        d : float = None
            Pixel scale in metres.
        c : float = 0.0
            Centre coordinate of the grid, in metres.
        """
        self.n = n
        self.d = None if d is None else np.asarray(d, float)
        self.c = None if c is None else np.asarray(c, float)

    @property
    def xs(self):
        """
        1D array of pixel centre coordinates along one axis.

        Returns
        -------
        xs : Array
            Coordinates of pixel centres, in metres, centred on `c`.
        """
        if self.d is None:
            raise ValueError("d must be specified to calculate coordinates.")
        return self.c + (np.arange(self.n) - (self.n - 1) / 2) * self.d

    @property
    def fov(self):
        """
        Total field of view of the grid.

        Returns
        -------
        fov : float
            Field of view in metres, equal to ``n * d``.
        """
        if self.d is None:
            raise ValueError("d must be specified to calculate FOV.")
        return self.n * self.d

    @property
    def extent(self):
        """
        Coordinate range (min, max) of the grid edges.

        Returns
        -------
        extent : tuple[float, float]
            ``(lower_edge, upper_edge)`` coordinates in metres.
        """
        if self.d is None:
            raise ValueError("d must be specified to calculate extent.")
        return self.c - (self.n / 2) * self.d, self.c + (self.n / 2) * self.d

extent property ¤

Coordinate range (min, max) of the grid edges.

Returns:

Name Type Description
extent tuple[float, float]

(lower_edge, upper_edge) coordinates in metres.

fov property ¤

Total field of view of the grid.

Returns:

Name Type Description
fov float

Field of view in metres, equal to n * d.

xs property ¤

1D array of pixel centre coordinates along one axis.

Returns:

Name Type Description
xs Array

Coordinates of pixel centres, in metres, centred on c.

__init__(n=None, d=None, c=0.0) ¤

Parameters:

Name Type Description Default
n int = None

Number of pixels along each axis.

None
d float = None

Pixel scale in metres.

None
c float = 0.0

Centre coordinate of the grid, in metres.

0.0
Source code in src/dLux/coordinates.py
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def __init__(self, n=None, d=None, c=0.0):
    """
    Parameters
    ----------
    n : int = None
        Number of pixels along each axis.
    d : float = None
        Pixel scale in metres.
    c : float = 0.0
        Centre coordinate of the grid, in metres.
    """
    self.n = n
    self.d = None if d is None else np.asarray(d, float)
    self.c = None if c is None else np.asarray(c, float)
BaseCoordTransform

dLux.coordinates.BaseCoordTransform ¤

Bases: Base

Abstract base class for coordinate transformations.

Provides a common interface for applying transformations to coordinates, including a backwards-compatible apply method.

UML

UML

Source code in src/dLux/coordinates.py
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class BaseCoordTransform(zdx.Base):
    """
    Abstract base class for coordinate transformations.

    Provides a common interface for applying transformations to coordinates,
    including a backwards-compatible `apply` method.

    ??? abstract "UML"
        ![UML](../assets/uml/BaseCoordTransform.png)
    """

    def __init_subclass__(cls, **kwargs):
        """
        Automatically inherit __call__ docstrings and annotations from parent class.
        """
        super().__init_subclass__(**kwargs)
        dlu.helpers.inherit_docstrings(cls, ["__call__"])

    def calculate(self: BaseCoordTransform, npix: int, diameter: float) -> Array:
        """
        Generate and apply transformations to coordinates.

        Parameters
        ----------
        npix : int
            The number of pixels in the output array.
        diameter : float
            The diameter of the output array in metres.

        Returns
        -------
        coords : Array
            The transformed coordinates.
        """
        coords = dlu.pixel_coords(npix, diameter)
        return self(coords)

    @abstractmethod
    def __call__(self: BaseCoordTransform, coords: Array) -> Array:  # pragma: no cover
        """
        Apply the transformation to input coordinates.

        Parameters
        ----------
        coords : Array
            The input coordinates to be transformed.

        Returns
        -------
        coords : Array
            The transformed coordinates.
        """

    def apply(self: BaseCoordTransform, coords: Array) -> Array:
        """
        Backwards compatibility alias for `__call__`.

        Parameters
        ----------
        coords : Array
            The input coordinates to be transformed.

        Returns
        -------
        coords : Array
            The transformed coordinates.
        """
        return self(coords)

__call__(coords) abstractmethod ¤

Apply the transformation to input coordinates.

Parameters:

Name Type Description Default
coords Array

The input coordinates to be transformed.

required

Returns:

Name Type Description
coords Array

The transformed coordinates.

Source code in src/dLux/coordinates.py
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@abstractmethod
def __call__(self: BaseCoordTransform, coords: Array) -> Array:  # pragma: no cover
    """
    Apply the transformation to input coordinates.

    Parameters
    ----------
    coords : Array
        The input coordinates to be transformed.

    Returns
    -------
    coords : Array
        The transformed coordinates.
    """

__init_subclass__(**kwargs) ¤

Automatically inherit call docstrings and annotations from parent class.

Source code in src/dLux/coordinates.py
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def __init_subclass__(cls, **kwargs):
    """
    Automatically inherit __call__ docstrings and annotations from parent class.
    """
    super().__init_subclass__(**kwargs)
    dlu.helpers.inherit_docstrings(cls, ["__call__"])

apply(coords) ¤

Backwards compatibility alias for __call__.

Parameters:

Name Type Description Default
coords Array

The input coordinates to be transformed.

required

Returns:

Name Type Description
coords Array

The transformed coordinates.

Source code in src/dLux/coordinates.py
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def apply(self: BaseCoordTransform, coords: Array) -> Array:
    """
    Backwards compatibility alias for `__call__`.

    Parameters
    ----------
    coords : Array
        The input coordinates to be transformed.

    Returns
    -------
    coords : Array
        The transformed coordinates.
    """
    return self(coords)

calculate(npix, diameter) ¤

Generate and apply transformations to coordinates.

Parameters:

Name Type Description Default
npix int

The number of pixels in the output array.

required
diameter float

The diameter of the output array in metres.

required

Returns:

Name Type Description
coords Array

The transformed coordinates.

Source code in src/dLux/coordinates.py
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def calculate(self: BaseCoordTransform, npix: int, diameter: float) -> Array:
    """
    Generate and apply transformations to coordinates.

    Parameters
    ----------
    npix : int
        The number of pixels in the output array.
    diameter : float
        The diameter of the output array in metres.

    Returns
    -------
    coords : Array
        The transformed coordinates.
    """
    coords = dlu.pixel_coords(npix, diameter)
    return self(coords)
CoordTransform

dLux.coordinates.CoordTransform ¤

Bases: BaseCoordTransform

A simple class to handle coordinate transformations applied to dynamic aperture classes. Transformations are applied in the order: 1. Translation 2. Shear 3. Compression 4. Rotation

UML

UML

Attributes:

Name Type Description
translation Array

The (x, y) shift applied to the coords.

rotation Array

The clockwise rotation applied to the coords.

compression Array

The (x, y) compression applied to the coords.

shear Array

The (x, y) shear applied to the coords.

Source code in src/dLux/coordinates.py
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class CoordTransform(BaseCoordTransform):
    """
    A simple class to handle coordinate transformations applied to dynamic aperture
    classes. Transformations are applied in the order:
        1. Translation
        2. Shear
        3. Compression
        4. Rotation

    ??? abstract "UML"
        ![UML](../assets/uml/CoordTransform.png)

    Attributes
    ----------
    translation: Array
        The (x, y) shift applied to the coords.
    rotation: Array
        The clockwise rotation applied to the coords.
    compression: Array
        The (x, y) compression applied to the coords.
    shear: Array
        The (x, y) shear applied to the coords.
    """

    translation: Array
    rotation: Array
    compression: Array
    shear: Array

    def __init__(
        self: CoordTransform,
        translation: Array = None,
        rotation: float = None,
        compression: Array = None,
        shear: Array = None,
    ):
        """
        Parameters
        ----------
        translation: Array
            The (x, y) shift applied to the coords.
        rotation: float, radians
            The clockwise rotation applied to the coords.
        compression: Array
            The (x, y) compression applied to the coords.
        shear: Array
            The (x, y) shear applied to the coords.
        """
        if translation is not None:
            self.translation = np.asarray(translation, dtype=float)
            if self.translation.shape != (2,):
                raise ValueError("translation must have shape (2,).")
        else:
            self.translation = None

        if rotation is not None:
            self.rotation = np.asarray(rotation, dtype=float)
            if self.rotation.shape != ():
                raise ValueError("rotation must have shape ().")
        else:
            self.rotation = None

        if compression is not None:
            self.compression = np.asarray(compression, dtype=float)
            if self.compression.shape != (2,):
                raise ValueError("compression must have shape (2,).")
        else:
            self.compression = None

        if shear is not None:
            self.shear = np.asarray(shear, dtype=float)
            if self.shear.shape != (2,):
                raise ValueError("shear must have shape (2,).")
        else:
            self.shear = None

    def __call__(self, coords):
        if self.translation is not None:
            coords = dlu.translate_coords(coords, self.translation)
        if self.shear is not None:
            coords = dlu.shear_coords(coords, self.shear)
        if self.compression is not None:
            coords = dlu.compress_coords(coords, self.compression)
        if self.rotation is not None:
            coords = dlu.rotate_coords(coords, self.rotation)
        return coords

__init__(translation=None, rotation=None, compression=None, shear=None) ¤

Parameters:

Name Type Description Default
translation Array

The (x, y) shift applied to the coords.

None
rotation float

The clockwise rotation applied to the coords.

None
compression Array

The (x, y) compression applied to the coords.

None
shear Array

The (x, y) shear applied to the coords.

None
Source code in src/dLux/coordinates.py
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def __init__(
    self: CoordTransform,
    translation: Array = None,
    rotation: float = None,
    compression: Array = None,
    shear: Array = None,
):
    """
    Parameters
    ----------
    translation: Array
        The (x, y) shift applied to the coords.
    rotation: float, radians
        The clockwise rotation applied to the coords.
    compression: Array
        The (x, y) compression applied to the coords.
    shear: Array
        The (x, y) shear applied to the coords.
    """
    if translation is not None:
        self.translation = np.asarray(translation, dtype=float)
        if self.translation.shape != (2,):
            raise ValueError("translation must have shape (2,).")
    else:
        self.translation = None

    if rotation is not None:
        self.rotation = np.asarray(rotation, dtype=float)
        if self.rotation.shape != ():
            raise ValueError("rotation must have shape ().")
    else:
        self.rotation = None

    if compression is not None:
        self.compression = np.asarray(compression, dtype=float)
        if self.compression.shape != (2,):
            raise ValueError("compression must have shape (2,).")
    else:
        self.compression = None

    if shear is not None:
        self.shear = np.asarray(shear, dtype=float)
        if self.shear.shape != (2,):
            raise ValueError("shear must have shape (2,).")
    else:
        self.shear = None
DistortedCoords

dLux.coordinates.DistortedCoords ¤

Bases: BaseCoordTransform

A class to handle coordinates distorted by a 2D polynomial distortion.

UML

UML

Attributes:

Name Type Description
powers Array

Powers of the polynomial distortion.

distortion Array

Distortion coefficients.

Source code in src/dLux/coordinates.py
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class DistortedCoords(BaseCoordTransform):
    """
    A class to handle coordinates distorted by a 2D polynomial distortion.

    ??? abstract "UML"
        ![UML](../assets/uml/DistortedCoords.png)

    Attributes
    ----------
    powers : Array
        Powers of the polynomial distortion.
    distortion : Array
        Distortion coefficients.
    """

    powers: Array
    distortion: Array

    def __init__(
        self: DistortedCoords, order: int = 1, distortion: Array | None = None
    ):
        """
        Parameters
        ----------
        order : int
            Order of polynomial to use.
        distortion : Array | None
            Distortion coefficients, defaulting to 0.
        """
        self.powers = np.array(dlu.gen_powers(order + 1))[:, 1:]

        if distortion is None:
            distortion = np.zeros_like(self.powers)
        distortion = np.asarray(distortion, dtype=float)
        if distortion.shape != self.powers.shape:
            raise ValueError("distortion shape must match powers shape.")
        self.distortion = distortion

    def __call__(self, coords):
        return dlu.distort_coords(coords, self.distortion, self.powers)

__init__(order=1, distortion=None) ¤

Parameters:

Name Type Description Default
order int

Order of polynomial to use.

1
distortion Array | None

Distortion coefficients, defaulting to 0.

None
Source code in src/dLux/coordinates.py
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def __init__(
    self: DistortedCoords, order: int = 1, distortion: Array | None = None
):
    """
    Parameters
    ----------
    order : int
        Order of polynomial to use.
    distortion : Array | None
        Distortion coefficients, defaulting to 0.
    """
    self.powers = np.array(dlu.gen_powers(order + 1))[:, 1:]

    if distortion is None:
        distortion = np.zeros_like(self.powers)
    distortion = np.asarray(distortion, dtype=float)
    if distortion.shape != self.powers.shape:
        raise ValueError("distortion shape must match powers shape.")
    self.distortion = distortion