scopesim.effects.psfs module¶

class scopesim.effects.psfs.AnalyticalPSF(**kwargs)[source]¶: Bases: PSF

class scopesim.effects.psfs.AnisocadoConstPSF(**kwargs)[source]¶

Bases: SemiAnalyticalPSF

Makes a SCAO on-axis PSF with a desired Strehl ratio at a given wavelength

To make the PSFs a map connecting Strehl, Wavelength, and residual wavefront error is required

Parameters:

filenamestr: Path to Strehl map with axes (x, y) = (wavelength, wavefront error)
strehlfloat: Desired Strehl ratio. Either percentage [1, 100] or fractional [1e-3, 1]
wavelengthfloat: [um] The given strehl is valid for this wavelength
psf_side_lengthint: [pixel] Default is 512. Side length of the kernel images
offsettuple: [arcsec] SCAO guide star offset from centre (dx, dy)
rounded_edgesbool: Default is True. Sets all halo values below a threshold to zero. The threshold is determined from the max values of the edge rows of the kernel image

Other Parameters:

convolve_modestr: [“same”, “full”] convolution keywords from scipy.signal.convolve

Examples

Add an AnisocadoConstPSF with code:

from scopesim.effects import AnisocadoConstPSF
psf = AnisocadoConstPSF(filename="test_AnisoCADO_rms_map.fits",
                        strehl=0.5,
                        wavelength=2.15,
                        convolve_mode="same",
                        psf_side_length=512)

Add an AnisocadoConstPSF to a yaml file:

effects:
-   name: Ks_Stehl_40_PSF
    description: A 40% Strehl PSF over the field of view
    class: AnisocadoConstPSF
    kwargs:
        filename: "test_AnisoCADO_rms_map.fits"
        strehl: 0.5
        wavelength: 2.15
        convolve_mode: full
        psf_side_length: 512

get_kernel(fov)[source]¶

property nmRms¶

plot(obj=None, **kwargs)[source]¶

remake_kernel(x)[source]¶

Remake the kernel based on either a pixel_scale of FieldOfView

Parameters:

x: float, FieldOfView: [um] if float

property strehl_ratio¶

property wavelength¶

class scopesim.effects.psfs.DiscretePSF(**kwargs)[source]¶: Bases: PSF

class scopesim.effects.psfs.FieldConstantPSF(**kwargs)[source]¶

Bases: DiscretePSF

A PSF that is constant across the field.

For spectroscopy, the a wavelength-dependent PSF cube is built, where for each wavelength the reference PSF is scaled proportional to wavelength.

get_kernel(fov)[source]¶: Find nearest wavelength and build PSF kernel from file

make_psf_cube(fov)[source]¶: Create a wavelength-dependent psf cube

plot()[source]¶

class scopesim.effects.psfs.FieldVaryingPSF(**kwargs)[source]¶

Bases: DiscretePSF

Parameters:

sub_pixel_flagbool, optional
flux_accuracyfloat, optional: Default 1e-3. Level of flux conservation during rescaling of kernel

apply_to(fov, **kwargs)[source]¶: Apply the PSF

get_kernel(fov)[source]¶

plot()[source]¶

property strehl_imagehdu¶: The HDU containing the positional info for kernel layers

class scopesim.effects.psfs.GaussianDiffractionPSF(diameter, **kwargs)[source]¶

Bases: AnalyticalPSF

fov_grid(which='waveset', **kwargs)[source]¶

Returns the edges needed to generate FieldOfViews for an observation

Parameters:

whichstr: [“waveset”, “edges”, “shifts”] where: * waveset - wavelength bin extremes * edges - on sky coordinate edges for each FOV box * shifts - wavelength dependent FOV position offsets

Returns:

wavesetlist: [um] N+1 wavelengths that set edges of N spectral bins
edgeslist of lists: [arcsec] Contains a list of footprint lists
shiftslist of 3 lists: [wave, dx, dy] Contains lists corresponding to the (dx, dy) offset from the optical axis (0, 0) induced for each wavelength in (wave) [um, arcsec, arcsec]

get_kernel(fov)[source]¶

plot()[source]¶

update(**kwargs)[source]¶

class scopesim.effects.psfs.NonCommonPathAberration(**kwargs)[source]¶

Bases: AnalyticalPSF

Needed: pixel_scale Accepted: kernel_width, strehl_drift

fov_grid(which='waveset', **kwargs)[source]¶

Returns the edges needed to generate FieldOfViews for an observation

Parameters:

whichstr: [“waveset”, “edges”, “shifts”] where: * waveset - wavelength bin extremes * edges - on sky coordinate edges for each FOV box * shifts - wavelength dependent FOV position offsets

Returns:

wavesetlist: [um] N+1 wavelengths that set edges of N spectral bins
edgeslist of lists: [arcsec] Contains a list of footprint lists
shiftslist of 3 lists: [wave, dx, dy] Contains lists corresponding to the (dx, dy) offset from the optical axis (0, 0) induced for each wavelength in (wave) [um, arcsec, arcsec]

get_kernel(obj)[source]¶

plot()[source]¶

property total_wfe¶

class scopesim.effects.psfs.PSF(**kwargs)[source]¶

Bases: Effect

apply_to(obj, **kwargs)[source]¶: Apply the PSF

fov_grid(which='waveset', **kwargs)[source]¶

Returns the edges needed to generate FieldOfViews for an observation

Parameters:

whichstr: [“waveset”, “edges”, “shifts”] where: * waveset - wavelength bin extremes * edges - on sky coordinate edges for each FOV box * shifts - wavelength dependent FOV position offsets

Returns:

wavesetlist: [um] N+1 wavelengths that set edges of N spectral bins
edgeslist of lists: [arcsec] Contains a list of footprint lists
shiftslist of 3 lists: [wave, dx, dy] Contains lists corresponding to the (dx, dy) offset from the optical axis (0, 0) induced for each wavelength in (wave) [um, arcsec, arcsec]