RayFunction¶

class kgpy.optics.rays.RayFunction(input=<factory>, output=<factory>, mask=None, distortion_polynomial_degree=2, vignetting_polynomial_degree=1)¶

Bases: Array[ObjectVector, RayVector]

Parameters:

input (ObjectVector) –
output (RayVector) –
mask (int | float | ndarray | Quantity | AbstractArray | AbstractArray | None) –
distortion_polynomial_degree (int) –
vignetting_polynomial_degree (int) –

__init__(input=<factory>, output=<factory>, mask=None, distortion_polynomial_degree=2, vignetting_polynomial_degree=1)¶

Parameters:

input (ObjectVector) –
output (RayVector) –
mask (int | float | ndarray | Quantity | AbstractArray | AbstractArray | None) –
distortion_polynomial_degree (int) –
vignetting_polynomial_degree (int) –

Return type:

None

Attributes

`distortion_polynomial_degree`
`effective_area`
`input_broadcasted`
`inverse`
`mask`
`output`
`output_broadcasted`
`output_position_apparent`
`shape`
`vignetting_polynomial_degree`
`input`

Methods

`__init__`([input, output, mask, ...])
`calc_labels`(name, grid)
`calc_mtf`(psf, limit_min, limit_max)
`colorgrid`(axis)	rtype: `numpy.ndarray`
`colormesh`(axis)	rtype: `numpy.ndarray`
`copy`()	rtype: `typing.TypeVar`(`CopyableT`, bound= Copyable)
`copy_shallow`()	rtype: `typing.TypeVar`(`CopyableT`, bound= Copyable)
`distortion`([polynomial_degree])	rtype: `kgpy.optics.aberrations.Distortion`
`from_pickle`([path])
`grid_labels`(axis)	rtype: `numpy.ndarray`
`interp_barycentric_linear`(input_new[, axis, ...])	Interpolate this function using barycentric interpolation.
`interp_barycentric_linear_scipy`(input_new)	rtype: `typing.TypeVar`(`ArrayT`, bound= Array)
`interp_linear`(input_new[, axis, damping])	rtype: `typing.TypeVar`(`ArrayT`, bound= Array)
`interp_nearest`(input_new[, axis])	rtype: `typing.TypeVar`(`ArrayT`, bound= Array)
`mtf`([bins, frequency_min, use_vignetted])
`pcolormesh`(axs, input_component_x, ...[, ...])	Plot this function using `matplotlib.pyplot.pcolormesh`.
`plot_pupil_hist2d_vs_field`([config_index, ...])
`plot_spot_size_vs_field`([axs, config_index, ...])	rtype: `typing.MutableSequence`[`matplotlib.axes._axes.Axes`]
`point_spread`([bins, use_vignetted, ...])
`pupil_hist2d`([bins, limit_min, limit_max, ...])
`to_pickle`(path)

Inheritance Diagram

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classmethod calc_labels(name, grid)¶

Parameters:

name (str) –
grid (Quantity) –

classmethod calc_mtf(psf, limit_min, limit_max)¶

Parameters:

psf (Quantity) –
limit_min (kgpy.vectors.Vector2D) –
limit_max (kgpy.vectors.Vector2D) –

Return type:

Tuple[Quantity, kgpy.vectors.Vector2D]

colorgrid(axis)¶

Return type:: numpy.ndarray
Parameters:: axis (int) –

colormesh(axis)¶

Return type:: numpy.ndarray
Parameters:: axis (int) –

copy()¶

Return type:: typing.TypeVar(CopyableT, bound= Copyable)
Parameters:: self (CopyableT) –

copy_shallow()¶

Return type:: typing.TypeVar(CopyableT, bound= Copyable)
Parameters:: self (CopyableT) –

distortion(polynomial_degree=1)¶

Return type:: kgpy.optics.aberrations.Distortion
Parameters:: polynomial_degree (int) –

classmethod from_pickle(path=None)¶

Parameters:: path (Path | None) –

grid_labels(axis)¶

Return type:: numpy.ndarray
Parameters:: axis (int) –

interp_barycentric_linear(input_new, axis=None, num_kernel=1)¶

Interpolate this function using barycentric interpolation.

Examples

import numpy as np
import matplotlib.pyplot as plt
import astropy.units as u
import kgpy.labeled
import kgpy.vectors
import kgpy.matrix
import kgpy.function

input = kgpy.vectors.Cartesian2D(
    x=kgpy.labeled.LinearSpace(-np.pi, np.pi, num=14, axis='x'),
    y=kgpy.labeled.LinearSpace(-np.pi, np.pi, num=14, axis='y'),
)

input_rotated = kgpy.matrix.Cartesian2D.rotation(30 * u.deg) @ input

f = kgpy.function.Array(
    input=input_rotated,
    output=np.cos(input.x * input.x * u.rad) * np.cos(input.y * input.y * u.rad),
)

fig, axs = plt.subplots(squeeze=False)
f.pcolormesh(
    axs=axs,
    input_component_x='x',
    input_component_y='y',
)

../_images/kgpy.optics.rays.RayFunction_0_0.png

input_large = kgpy.vectors.Cartesian2D(
    x=kgpy.labeled.LinearSpace(-2 * np.pi, 2 * np.pi, num=201, axis='x'),
    y=kgpy.labeled.LinearSpace(-2 * np.pi, 2 * np.pi, num=201, axis='y'),
)

g = f.interp_barycentric_linear(input_large)

fig_large, axs_large = plt.subplots(squeeze=False)
g.pcolormesh(
    axs=axs_large,
    input_component_x='x',
    input_component_y='y',
)
axs_large[0, 0].set_xlim(axs[0, 0].get_xlim());
axs_large[0, 0].set_ylim(axs[0, 0].get_ylim());

../_images/kgpy.optics.rays.RayFunction_1_1.png

Parameters:

input_new (typing.TypeVar(InputT, bound= typing.Union[int, float, numpy.ndarray, astropy.units.quantity.Quantity, kgpy.labeled.AbstractArray, kgpy.uncertainty.AbstractArray, VectorInterface])) –
self (ArrayT) –
axis (str | Sequence[str] | None) –
num_kernel (int) –

Returns:

A new instance of class

Return type:

kgpy.function.Array evaluated at the coordinates input_new.

interp_barycentric_linear_scipy(input_new)¶

Return type:

typing.TypeVar(ArrayT, bound= Array)

Parameters:

self (ArrayT) –
input_new (InputT) –

interp_linear(input_new, axis=None, damping=1)¶

Return type:

typing.TypeVar(ArrayT, bound= Array)

Parameters:

self (ArrayT) –
input_new (InputT) –
axis (str | Sequence[str] | None) –
damping (float) –

interp_nearest(input_new, axis=None)¶

Return type:

typing.TypeVar(ArrayT, bound= Array)

Parameters:

self (ArrayT) –
input_new (InputT) –
axis (str | Sequence[str] | None) –

mtf(bins=10, frequency_min=None, use_vignetted=False)¶

Parameters:

bins (int | kgpy.vectors.Vector2D) –
frequency_min (Quantity | kgpy.vector.Vector2D | None) –
use_vignetted (bool) –

Return type:

Tuple[Quantity, kgpy.vectors.Vector2D]

pcolormesh(axs, input_component_x, input_component_y, input_component_row=None, input_component_column=None, output_component_color=None, index=None, **kwargs)¶

Plot this function using matplotlib.pyplot.pcolormesh.

Examples

import numpy as np
import matplotlib.pyplot as plt
import astropy.units as u
import kgpy.labeled
import kgpy.vectors
import kgpy.matrix
import kgpy.function

a = kgpy.labeled.LinearSpace(0 * u.rad, np.pi * u.rad, num=2, axis='a')
b = kgpy.labeled.LinearSpace(0 * u.rad, np.pi * u.rad, num=2, axis='b')
x = kgpy.labeled.LinearSpace(0 * u.rad, 2 * np.pi * u.rad, num=11, axis='x')
y = kgpy.labeled.LinearSpace(0 * u.rad, 1 * np.pi * u.rad, num=11, axis='y')

x2 = 2 * x + y / 4
y2 = x / 5 + y

inputs = kgpy.vectors.CartesianND(dict(
    a=a,
    b=b,
    x=x2,
    y=y2,
))

f = kgpy.function.Array(
    input=inputs,
    output=np.cos(a) * np.cos(b) * np.cos(x2) * np.cos(y2),
)

fig, axs = plt.subplots(
    nrows=a.num,
    ncols=b.num,
    sharex=True,
    sharey=True,
    squeeze=False,
    figsize=(12, 12),
    constrained_layout=True,
)

f.pcolormesh(
    axs=axs,
    input_component_x='x',
    input_component_y='y',
    input_component_row='a',
    input_component_column='b',
)

../_images/kgpy.optics.rays.RayFunction_2_0.png

Parameters:

axs (Array of axes that the function will be plotted on) –
input_component_x (typing.Union[str, kgpy.vectors.ComponentAxis]) –
input_component_y (typing.Union[str, kgpy.vectors.ComponentAxis]) –
input_component_row (typing.Union[str, kgpy.vectors.ComponentAxis, None]) –
input_component_column (typing.Union[str, kgpy.vectors.ComponentAxis, None]) –
output_component_color (typing.Union[str, kgpy.vectors.ComponentAxis, None]) –
index (typing.Optional[typing.Dict[str, int]]) –
kwargs –
self (AbstractArrayT) –

plot_pupil_hist2d_vs_field(config_index=0, wavlen_index=0, velocity_los_index=0, bins=10, limit_min=None, limit_max=None, use_vignetted=False, relative_to_centroid=(True, True), norm=None, cmap='viridis', kwargs_colorbar=None)¶

Parameters:

config_index (int) –
wavlen_index (int) –
velocity_los_index (int) –
bins (int | Tuple[int, int]) –
limit_min (kgpy.vectors.Vector2D | None) –
limit_max (kgpy.vectors.Vector2D | None) –
use_vignetted (bool) –
relative_to_centroid (Tuple[bool, bool]) –
norm (Normalize | None) –
cmap (str) –
kwargs_colorbar (Dict[str, Any] | None) –

Return type:

Tuple[Figure, ndarray]

plot_spot_size_vs_field(axs=None, config_index=None, velocity_los_index=0, kwargs_colorbar=None, digits_after_decimal=3)¶

Return type:

typing.MutableSequence[matplotlib.axes._axes.Axes]

Parameters:

axs (MutableSequence[Axes] | None) –
config_index (int | Tuple[int, ...] | None) –
velocity_los_index (int) –
kwargs_colorbar (Dict[str, Any] | None) –
digits_after_decimal (int) –

point_spread(bins=None, use_vignetted=False, use_position_relative=True, use_position_apparent=False)¶

Parameters:

bins (Cartesian2D | None) –
use_vignetted (bool) –
use_position_relative (bool) –
use_position_apparent (bool) –

pupil_hist2d(bins=10, limit_min=None, limit_max=None, use_vignetted=False, relative_to_centroid=(False, False), use_position_apparent=False)¶