shesha.ao.imats Namespace Reference

Computation implementations of interaction matrix. More...

Functions
np.ndarray	imat_geom (Sensors wfs, Dms dms, List[conf.Param_wfs] p_wfss, List[conf.Param_dm] p_dms, conf.Param_controller p_controller, int meth=0)
	Compute the interaction matrix with a geometric method. More...
None	imat_init (int ncontrol, Rtc rtc, Dms dms, list p_dms, Sensors wfs, list p_wfss, conf.Param_tel p_tel, conf.Param_controller p_controller, M2V=None, dict dataBase={}, bool use_DB=False)
	Initialize and compute the interaction matrix on the GPU. More...
np.ndarray	imat_geom_ts_multiple_direction (Sensors wfs, Dms dms, List[conf.Param_wfs] p_wfss, List[conf.Param_dm] p_dms, conf.Param_geom p_geom, int ind_TS, List ind_dmseen, conf.Param_tel p_tel, x, y, int meth=0)
	Compute the interaction matrix with a geometric method for multiple truth sensors (with different direction) More...
np.ndarray	imat_geom_ts (Sensors wfs, Dms dms, conf.Param_wfs p_wfss, int ind_TS, List[conf.Param_dm] p_dms, List[int] ind_DMs, int meth=0)
	Compute the interaction matrix with a geometric method for a single truth sensor. More...
def	get_metaD (sup, TS_xpos=None, TS_ypos=None, ind_TS=-1, save_metaD=False, nControl=0)
	Create an interaction matrix for the current simulation given TS position :parameters: sim current COMPASS simulation TS_xpos np.ndarray : TS position (x axis) TS_ypos np.ndarray : TS position (y axis) More...

Detailed Description

Computation implementations of interaction matrix.

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

get_metaD()

def shesha.ao.imats.get_metaD	(		sup,
			TS_xpos = None,
			TS_ypos = None,
			ind_TS = -1,
			save_metaD = False,
			nControl = 0
	)

Create an interaction matrix for the current simulation given TS position :parameters: sim current COMPASS simulation TS_xpos np.ndarray : TS position (x axis) TS_ypos np.ndarray : TS position (y axis)

:return: metaD np.ndarray :interaction matrix

Definition at line 315 of file imats.py.

    """
    if (TS_xpos is None):
        TS_xpos = np.array([t.xpos for t in sup.config.p_wfs_ts])
    elif (isinstance(TS_xpos, list)):
        TS_xpos = np.array(TS_xpos)
    elif (isinstance(TS_xpos, int) or isinstance(TS_xpos, float)):
        TS_xpos = np.array([TS_xpos]).astype(np.float32)
    if (TS_xpos.size < 1):
        TS_xpos = np.zeros((1))
 
    if (TS_ypos is None):
        TS_ypos = np.array([t.ypos for t in sup.config.p_wfs_ts])
    elif (isinstance(TS_ypos, list)):
        TS_ypos = np.array(TS_ypos)
    elif (isinstance(TS_ypos, int) or isinstance(TS_ypos, float)):
        TS_ypos = np.array([TS_ypos]).astype(np.float32)
    if (TS_ypos.size < 1):
        TS_ypos = np.zeros((1))
 
    return imat_geom_ts_multiple_direction(sup._sim.wfs, sup._sim.dms, sup.config.p_wfss,
                                           sup.config.p_dms, sup.config.p_geom, ind_TS,
                                           sup.config.p_controllers[nControl].ndm,
                                           sup.config.p_tel, TS_xpos, TS_ypos)

Here is the call graph for this function:

imat_geom()

np.ndarray shesha.ao.imats.imat_geom	(	Sensors	wfs,
		Dms	dms,
		List[conf.Param_wfs]	p_wfss,
		List[conf.Param_dm]	p_dms,
		conf.Param_controller	p_controller,
		int	meth = 0
	)

Compute the interaction matrix with a geometric method.

:parameters:

wfs (Sensors) : Sensors object

dms (Dms) : Dms object

p_wfss (list of Param_wfs) : wfs settings

p_dms (list of Param_dm) : dms settings

p_controller (Param_controller) : controller settings

meth (int) : (optional) method type (0 or 1)

Definition at line 70 of file imats.py.

 
        meth: (int) : (optional) method type (0 or 1)
    """
 
    nwfs = p_controller.nwfs.size
    ndm = p_controller.ndm.size
    imat_size1 = 0
    imat_size2 = 0
 
    for dm in dms.d_dms:
        dm.reset_shape()
 
    for nw in range(nwfs):
        nm = p_controller.nwfs[nw]
        imat_size1 += p_wfss[nm]._nvalid * 2
 
    for nmc in range(ndm):
        nm = p_controller.ndm[nmc]
        imat_size2 += p_dms[nm]._ntotact
 
    imat_cpu = np.zeros((imat_size1, imat_size2), dtype=np.float32)
    ind = 0
    cc = 0
    print("Doing imat geom...")
    for nmc in range(ndm):
        nm = p_controller.ndm[nmc]
        dms.d_dms[nm].reset_shape()
        for i in tqdm(range(p_dms[nm]._ntotact), desc="DM%d" % nmc):
            dms.d_dms[nm].comp_oneactu(i, p_dms[nm].push4imat)
            nslps = 0
            for nw in range(nwfs):
                n = p_controller.nwfs[nw]
                wfs.d_wfs[n].d_gs.raytrace(dms, rst=1)
                wfs.d_wfs[n].slopes_geom(meth)
                imat_cpu[nslps:nslps + p_wfss[n]._nvalid * 2, ind] = np.array(
                        wfs.d_wfs[n].d_slopes)
                nslps += p_wfss[n]._nvalid * 2
            imat_cpu[:, ind] = imat_cpu[:, ind] / p_dms[nm].push4imat
            ind = ind + 1
            cc = cc + 1
            dms.d_dms[nm].reset_shape()
 
    return imat_cpu
 
 

imat_geom_ts()

np.ndarray shesha.ao.imats.imat_geom_ts	(	Sensors	wfs,
		Dms	dms,
		conf.Param_wfs	p_wfss,
		int	ind_TS,
		List[conf.Param_dm]	p_dms,
		List[int]	ind_DMs,
		int	meth = 0
	)

Compute the interaction matrix with a geometric method for a single truth sensor.

:parameters:

wfs (Sensors) : Sensors object

dms (Dms) : Dms object

p_wfss (list of Param_wfs) : wfs settings

ind_TS (int) : index of the truth sensor in the wfs settings list

p_dms (list of Param_dm) : dms settings

ind_DMs (list of int) : indices of used DMs

p_controller (Param_controller) : controller settings

meth (int) : (optional) method type (0 or 1)

Definition at line 268 of file imats.py.

 
        meth: (int) : (optional) method type (0 or 1)
    """
 
    #nwfs = 1 #p_controller.nwfs.size # as parameter list of indices for wfs if several ts (only 1 ts for now)
    ndm = len(ind_DMs)  #p_controller.ndm.size # as parameter list of indices of used dms
    imat_size1 = p_wfss[ind_TS]._nvalid * 2  # as parameter (nvalid)
    imat_size2 = 0
 
    # for nw in range(nwfs):
    #     nm = p_controller.nwfs[nw]
    #     imat_size1 += p_wfss[nm]._nvalid * 2
 
    for dm in dms.d_dms:
        dm.reset_shape()
 
    imat_size2 = 0
    for nm in ind_DMs:
        imat_size2 += p_dms[nm]._ntotact
 
    imat_cpu = np.zeros((imat_size1, imat_size2), dtype=np.float64)
    ind = 0
    cc = 0
    for nm in tqdm(ind_DMs, desc="imat geom DM"):
        dms.d_dms[nm].reset_shape()
        for i in trange(p_dms[nm]._ntotact, desc="imat geom actu"):
            dms.d_dms[nm].comp_oneactu(i, p_dms[nm].push4imat)
            wfs.d_wfs[ind_TS].d_gs.raytrace(dms, rst=1)
            wfs.d_wfs[ind_TS].slopes_geom(meth)
            imat_cpu[:, ind] = np.array(wfs.d_wfs[ind_TS].d_slopes)
            imat_cpu[:, ind] = imat_cpu[:, ind] / p_dms[nm].push4imat
            ind = ind + 1
            cc = cc + 1
            dms.d_dms[nm].reset_shape()
 
    return imat_cpu
 
 

Here is the caller graph for this function:

imat_geom_ts_multiple_direction()

np.ndarray shesha.ao.imats.imat_geom_ts_multiple_direction	(	Sensors	wfs,
		Dms	dms,
		List[conf.Param_wfs]	p_wfss,
		List[conf.Param_dm]	p_dms,
		conf.Param_geom	p_geom,
		int	ind_TS,
		List	ind_dmseen,
		conf.Param_tel	p_tel,
			x,
			y,
		int	meth = 0
	)

Compute the interaction matrix with a geometric method for multiple truth sensors (with different direction)

:parameters:

wfs (Sensors) : Sensors object

dms (Dms) : Dms object

p_wfss (list of Param_wfs) : wfs settings

ind_TS (int) : index of the truth sensor in the wfs settings list

p_dms (list of Param_dm) : dms settings

ind_DMs (list of int) : indices of used DMs

p_controller (Param_controller) : controller settings

meth (int) : (optional) method type (0 or 1)

Definition at line 202 of file imats.py.

        p_controller: (Param_controller) : controller settings
 
        meth: (int) : (optional) method type (0 or 1)
    """
    p_wfs = p_wfss[ind_TS]
    imat_size2 = 0
    print("DMS_SEEN: ", ind_dmseen)
    for nm in ind_dmseen:
        imat_size2 += p_dms[nm]._ntotact
    imat_cpu = np.ndarray((0, imat_size2))
 
    for i in trange(x.size, desc="TS pos"):
        xpos = x[i]
        ypos = y[i]
        for k in ind_dmseen:
            dims = p_dms[k]._n2 - p_dms[k]._n1 + 1
            dim = p_geom._mpupil.shape[0]
            if (dim < dims):
                dim = dims
            xoff = xpos * CONST.ARCSEC2RAD * \
                    p_dms[k].alt / p_tel.diam * p_geom.pupdiam
            yoff = ypos * CONST.ARCSEC2RAD * \
                p_dms[k].alt / p_tel.diam * p_geom.pupdiam
            xoff = xoff + (dim - p_geom._n) / 2
            yoff = yoff + (dim - p_geom._n) / 2
            wfs.d_wfs[ind_TS].d_gs.add_layer(p_dms[k].type, k, xoff, yoff)
        imat_cpu = np.concatenate(
                (imat_cpu, imat_geom_ts(wfs, dms, p_wfss, ind_TS, p_dms, ind_dmseen,
                                        meth)), axis=0)
 
    for k in ind_dmseen:
        dims = p_dms[k]._n2 - p_dms[k]._n1 + 1
        dim = p_geom._mpupil.shape[0]
        if (dim < dims):
            dim = dims
        xoff = p_wfs.xpos * CONST.ARCSEC2RAD * \
            p_dms[k].alt / p_tel.diam * p_geom.pupdiam
        yoff = p_wfs.ypos * CONST.ARCSEC2RAD * \
            p_dms[k].alt / p_tel.diam * p_geom.pupdiam
        xoff = xoff + (dim - p_geom._n) / 2
        yoff = yoff + (dim - p_geom._n) / 2
        wfs.d_wfs[ind_TS].d_gs.add_layer(p_dms[k].type, k, xoff, yoff)
 
    return imat_cpu
 
 

Here is the call graph for this function:

Here is the caller graph for this function:

imat_init()

None shesha.ao.imats.imat_init	(	int	ncontrol,
		Rtc	rtc,
		Dms	dms,
		list	p_dms,
		Sensors	wfs,
		list	p_wfss,
		conf.Param_tel	p_tel,
		conf.Param_controller	p_controller,
			M2V = None,
		dict	dataBase = {},
		bool	use_DB = False
	)

Initialize and compute the interaction matrix on the GPU.

:parameters:

ncontrol (int) : controller's index

rtc (Rtc) : Rtc object

dms (Dms) : Dms object

p_dms (Param_dms) : dms settings

wfs (Sensors) : Sensors object

p_wfss (list of Param_wfs) : wfs settings

p_tel (Param_tel) : telescope settings

p_controller (Param_controller) : controller settings

M2V KL_matrix

dataBase (optional) dict containing paths to files to load

use_DB (optional) use dataBase flag

Definition at line 141 of file imats.py.

 
        use_DB:(bool) : (optional) use dataBase flag
    """
    # first check if wfs is using lgs
    # if so, load new lgs spot, just for imat
    for i in range(len(p_wfss)):
        if (p_wfss[i].gsalt > 0):
            # TODO: check that
            save_profile = p_wfss[i].proftype
            p_wfss[i].proftype = scons.ProfType.GAUSS1
            lgs.prep_lgs_prof(p_wfss[i], i, p_tel, wfs, imat=1)
 
    if "imat" in dataBase:
        imat = h5u.load_imat_from_dataBase(dataBase)
        rtc.d_control[ncontrol].set_imat(imat)
    else:
        t0 = time.time()
        if M2V is not None:
            p_controller._M2V = M2V.copy()
            rtc.do_imat_basis(ncontrol, dms, M2V.shape[1], M2V, p_controller.klpush)
        else:
            rtc.do_imat(ncontrol, dms)
        print("done in %f s" % (time.time() - t0))
        imat = np.array(rtc.d_control[ncontrol].d_imat)
        if use_DB:
            h5u.save_imat_in_dataBase(imat)
    p_controller.set_imat(imat)
 
    # Restore original profile in lgs spots
    for i in range(len(p_wfss)):
        if (p_wfss[i].gsalt > 0):
            p_wfss[i].proftype = save_profile
            lgs.prep_lgs_prof(p_wfss[i], i, p_tel, wfs)
 
 
#write imat_ts:
#   loop over ts directions
#   change WFS offset to direction
#   do imat geom