shesha.ao.wfs Namespace Reference

On the fly modification of the WFS. More...

Functions
def	comp_new_pyr_ampl (int nwfs, float ampli, list p_wfss, conf.Param_tel p_tel, int npts_force=None)
	Set the pyramid modulation amplitude. More...
def	noise_cov (int nw, conf.Param_wfs p_wfs, conf.Param_atmos p_atmos, conf.Param_tel p_tel)
	Compute the diagonal of the noise covariance matrix for a SH WFS (arcsec^2) Photon (pi^2/2)*(1/Nphotons)*(d/r0)^2 / (2*pi*d/lambda)^2 Electronic (pi^2/3)*(wfs.noise^2/N^2photons)*wfs.npix^2*(wfs.npix*wfs.pixsize*d/lambda)^2 / (2*pi*d/lambda)^2. More...
def	comp_new_fstop (Sensors wfs, int n, conf.Param_wfs p_wfs, float fssize, bytes fstop)
	Compute a new field stop for pyrhr WFS. More...

Detailed Description

On the fly modification of the WFS.

Author

COMPASS Team https://github.com/ANR-COMPASS

Version

5.0.0

Date

2020/05/18

Copyright

GNU Lesser General Public License

This file is part of COMPASS https://anr-compass.github.io/compass/

Copyright (C) 2011-2019 COMPASS Team https://github.com/ANR-COMPASS All rights reserved. Distributed under GNU - LGPL

COMPASS is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

COMPASS: End-to-end AO simulation tool using GPU acceleration The COMPASS platform was designed to meet the need of high-performance for the simulation of AO systems.

The final product includes a software package for simulating all the critical subcomponents of AO, particularly in the context of the ELT and a real-time core based on several control approaches, with performances consistent with its integration into an instrument. Taking advantage of the specific hardware architecture of the GPU, the COMPASS tool allows to achieve adequate execution speeds to conduct large simulation campaigns called to the ELT.

The COMPASS platform can be used to carry a wide variety of simulations to both testspecific components of AO of the E-ELT (such as wavefront analysis device with a pyramid or elongated Laser star), and various systems configurations such as multi-conjugate AO.

COMPASS is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with COMPASS. If not, see https://www.gnu.org/licenses/lgpl-3.0.txt.

Function Documentation

comp_new_fstop()

def shesha.ao.wfs.comp_new_fstop	(	Sensors	wfs,
		int	n,
		conf.Param_wfs	p_wfs,
		float	fssize,
		bytes	fstop
	)

Compute a new field stop for pyrhr WFS.

:parameters:

n (int) : WFS index

wfs (Param_wfs) : WFS parameters

fssize (float) : field stop size [arcsec]

fstop (string) : "square" or "round" (field stop shape)

Definition at line 149 of file wfs.py.

        fstop : (string) : "square" or "round" (field stop shape)
    """
    fsradius_pixels = int(fssize / p_wfs._qpixsize / 2.)
    if (fstop == scons.FieldStopType.ROUND):
        p_wfs.fstop = fstop
        focmask = util.dist(p_wfs._Nfft, xc=p_wfs._Nfft / 2. - 0.5,
                            yc=p_wfs._Nfft / 2. - 0.5) < (fsradius_pixels)
        # fstop_area = np.pi * (p_wfs.fssize/2.)**2. #UNUSED
    elif (p_wfs.fstop == scons.FieldStopType.SQUARE):
        p_wfs.fstop = fstop
        y, x = np.indices((p_wfs._Nfft, p_wfs._Nfft))
        x -= (p_wfs._Nfft - 1.) / 2.
        y -= (p_wfs._Nfft - 1.) / 2.
        focmask = (np.abs(x) <= (fsradius_pixels)) * \
            (np.abs(y) <= (fsradius_pixels))
        # fstop_area = p_wfs.fssize**2. #UNUSED
    else:
        msg = "p_wfs " + str(n) + ". fstop must be round or square"
        raise ValueError(msg)
 
    # pyr_focmask = np.roll(focmask,focmask.shape[0]/2,axis=0)
    # pyr_focmask = np.roll(pyr_focmask,focmask.shape[1]/2,axis=1)
    pyr_focmask = focmask * 1.0  # np.fft.fftshift(focmask*1.0)
    p_wfs._submask = np.fft.fftshift(pyr_focmask).astype(np.float32)
    p_wfs_fssize = fssize
    wfs.d_wfs[n].set_submask(p_wfs._submask)

comp_new_pyr_ampl()

def shesha.ao.wfs.comp_new_pyr_ampl	(	int	nwfs,
		float	ampli,
		list	p_wfss,
		conf.Param_tel	p_tel,
		int	npts_force = None
	)

Set the pyramid modulation amplitude.

:parameters:

nwfs (int): WFS index

ampli (float) : new amplitude in units of lambda/D

p_wfss (list of Param_wfs) : list of wfs parameters

p_tel (Param_tel) : Telescope parameters

Definition at line 60 of file wfs.py.

        p_tel : (Param_tel) : Telescope parameters
    """
 
    pwfs = p_wfss[nwfs]
    nFace = pwfs.nPupils
 
    if npts_force is None:
        if ampli == 0.:
            pyr_npts = 1
        elif ampli < 2.:
            pyr_npts = int(np.ceil(int(2 * 2 * np.pi) / nFace) * nFace)
        else:
            pyr_npts = int(np.ceil(int(ampli * 2 * np.pi) / nFace) * nFace)
    else:
        pyr_npts = npts_force
 
    pixsize = pwfs._qpixsize * CONST.ARCSEC2RAD
    scale_fact = 2 * np.pi / pwfs._Nfft * (
            pwfs.Lambda * 1e-6 / p_tel.diam) / pixsize * ampli
    cx = scale_fact * \
        np.sin((np.arange(pyr_npts, dtype=np.float32)) * 2. * np.pi / pyr_npts)
    cy = scale_fact * \
        np.cos((np.arange(pyr_npts, dtype=np.float32)) * 2. * np.pi / pyr_npts)
 
    scale = pwfs.Lambda * 1e-6 / p_tel.diam * ampli * 180. / np.pi * 3600.
 
    return cx, cy, scale, pyr_npts
 
 

noise_cov()

def shesha.ao.wfs.noise_cov	(	int	nw,
		conf.Param_wfs	p_wfs,
		conf.Param_atmos	p_atmos,
		conf.Param_tel	p_tel
	)

Compute the diagonal of the noise covariance matrix for a SH WFS (arcsec^2) Photon (pi^2/2)*(1/Nphotons)*(d/r0)^2 / (2*pi*d/lambda)^2 Electronic (pi^2/3)*(wfs.noise^2/N^2photons)*wfs.npix^2*(wfs.npix*wfs.pixsize*d/lambda)^2 / (2*pi*d/lambda)^2.

:parameters:

nw wfs number

p_wfs (Param_wfs) : wfs settings

p_atmos (Param_atmos) : atmos settings

p_tel (Param_tel) : telescope settings

:return:

cov (np.ndarray(ndim=1,dtype=np.float64)) : noise covariance diagonal

Definition at line 107 of file wfs.py.

        cov : (np.ndarray(ndim=1,dtype=np.float64)) : noise covariance diagonal
    """
    cov = np.zeros(2 * p_wfs._nvalid)
    if (p_wfs.noise >= 0):
        ind = np.where(p_wfs._isvalid.T)
        flux = p_wfs._fluxPerSub[ind[1], ind[0]]
        Nph = flux * p_wfs._nphotons
 
        r0 = (p_wfs.Lambda / 0.5)**(6.0 / 5.0) * p_atmos.r0
 
        sig = (np.pi ** 2 / 2) * (1 / Nph) * \
            (1. / r0) ** 2  # Photon noise in m^-2
        # Noise variance in rad^2
        sig /= (2 * np.pi / (p_wfs.Lambda * 1e-6))**2
        sig *= CONST.RAD2ARCSEC**2
 
        Ns = p_wfs.npix  # Number of pixel
        Nd = (p_wfs.Lambda * 1e-6) * CONST.RAD2ARCSEC / p_wfs.pixsize
        sigphi = (np.pi ** 2 / 3.0) * (1 / Nph ** 2) * (p_wfs.noise) ** 2 * \
            Ns ** 2 * (Ns / Nd) ** 2  # Phase variance in m^-2
        # Noise variance in rad^2
        sigsh = sigphi / (2 * np.pi / (p_wfs.Lambda * 1e-6))**2
        sigsh *= CONST.RAD2ARCSEC**2  # Electronic noise variance in arcsec^2
 
        cov[:len(sig)] = sig + sigsh
        cov[len(sig):] = sig + sigsh
 
    return cov