def make_source (ns,name,l,m,I=1):
  """Makes a source with a direction, using the current option set. 
  Returns None for sources out of the "sky". 
  (l^2+m^2>1)""";
  l = math.sin(l);
  m = math.sin(m);
  if l*l + m*m <= 1:
    srcdir = Meow.LMDirection(ns,name,l,m);
    if source_spi is not None:
      freq0 = source_freq0*1e+6 if source_freq0 else Meow.Context.observation.freq0();
      spi = source_spi if source_spi_2 is None else [ source_spi,source_spi_2 ];
    else:
      spi = freq0 = None;
    if source_pol:
      Q = I*source_qi;
      U = I*source_ui;
      V = I*source_vi;
    else:
      Q = U = V = None;
    if source_type == "point":
      return Meow.PointSource(ns,name,srcdir,I=I,Q=Q,U=U,V=V,spi=spi,freq0=freq0);
    elif source_type == "gaussian":
      s1,s2 = gauss_smaj*ARCSEC,gauss_smin*ARCSEC;
      pa = gauss_pa*DEG;
      return Meow.GaussianSource(ns,name,srcdir,I=I,Q=Q,U=U,V=V,spi=spi,freq0=freq0,
          lproj=s1*math.sin(pa),mproj=s1*math.cos(pa),ratio=s2/s1);
  # else fall through and return none
  return None;
Beispiel #2
0
def source_list(ns):
    # figure out spectral index parameters
    if spectral_index is not None:
        spi_def = Meow.Parm(spectral_index)
        freq0_def = ref_freq
    else:
        spi_def = freq0_def = None
    if spectral_index1 is not None:
        spi_def1 = Meow.Parm(spectral_index1)
        freq0_def1 = ref_freq
    else:
        spi_def1 = freq0_def1 = None
    # and flux parameters
    i_def = Meow.Parm(1)
    quv_def = Meow.Parm(0)

    dir1 = Meow.Direction(ns, "3C343.1", 4.356645791155902, 1.092208429052697)
    dir0 = Meow.Direction(ns, "3C343", 4.3396003966265599, 1.0953677174056471)

    src1 = Meow.PointSource(ns,
                            "3C343.1",
                            dir1,
                            I=Meow.Parm(6.02061051),
                            Q=Meow.Parm(0.0179716185),
                            U=quv_def,
                            V=quv_def,
                            spi=spi_def1,
                            freq0=freq0_def1)
    src0 = Meow.PointSource(ns,
                            "3C343",
                            dir0,
                            I=Meow.Parm(1.83336309),
                            Q=Meow.Parm(0.0241450607),
                            U=quv_def,
                            V=quv_def,
                            spi=spi_def1,
                            freq0=freq0_def1)

    ## define a parmgroup for source parameters
    pg_src = ParmGroup.ParmGroup("source",
                                 src1.coherency().search(tags="solvable") +
                                 src0.coherency().search(tags="solvable"),
                                 table_name="sources.mep")

    ParmGroup.SolveJob("cal_sources", "Calibrate sources", pg_src)

    return [src1, src0]
Beispiel #3
0
def transient_source (ns,name,l,m,tburst,duration,Ipeak=1):
  """shortcut for making a transient pointsource with a direction. Returns None for sources out of the "sky"
  (l^2+m^2>1)""";
  l = math.sin(l);
  m = math.sin(m);
  t_rel = ns.t_rel ** (Meq.Time() - (ns.time0 << 0))
  lc = ns.lc << Meq.Exp((-Meq.Pow(t_rel-tburst,2))/(2*duration**2))
  Ilc = ns.Ilc << Ipeak * lc
  if l*l + m*m <= 1:
    srcdir = Meow.LMDirection(ns,name,l,m);
    return Meow.PointSource(ns,name,srcdir,I=Ilc);
  else:
    return None;
Beispiel #4
0
def point_source(ns, name, l, m, I=1):
    """shortcut for making a pointsource with a direction. Returns None for sources out of the "sky"
    (l^2+m^2>1)"""
    l = math.sin(l)
    m = math.sin(m)
    if l * l + m * m <= 1:
        srcdir = Meow.LMDirection(ns, name, l, m)
        if source_spi is not None:
            freq0 = source_freq0 or Meow.Context.observation.freq0()
        else:
            freq0 = None
        return Meow.PointSource(ns, name, srcdir, I=I, spi=source_spi, freq0=freq0)
    else:
        return None
def make_source(ns, name, az, el, I=1):
    """Makes a source with a fixed azimuth/elevation direction """
    srcdir = Meow.AzElDirection(ns, name, az, el)
    if source_spi is not None:
        freq0 = source_freq0 * 1e+6 if source_freq0 else Meow.Context.observation.freq0(
        )
    else:
        freq0 = None
    if source_pol:
        Q = I * source_qi
        U = I * source_ui
        V = I * source_vi
    else:
        Q = U = V = None
    if source_type == "point":
        return Meow.PointSource(ns,
                                name,
                                srcdir,
                                I=I,
                                Q=Q,
                                U=U,
                                V=V,
                                spi=source_spi,
                                freq0=freq0)
    elif source_type == "gaussian":
        s1, s2 = gauss_smaj * ARCSEC, gauss_smin * ARCSEC
        pa = gauss_pa * DEG
        return Meow.GaussianSource(ns,
                                   name,
                                   srcdir,
                                   I=I,
                                   Q=Q,
                                   U=U,
                                   V=V,
                                   spi=source_spi,
                                   freq0=freq0,
                                   lproj=s1 * math.sin(pa),
                                   mproj=s1 * math.cos(pa),
                                   ratio=s2 / s1)
    # else fall through and return none
    return None
Beispiel #6
0
def source_list (ns,name="cps"):
  # figure out spectral index parameters
  if spectral_index is not None:
    spi_def = Meow.Parm(spectral_index);
    freq0_def  = ref_freq;
  else:
    spi_def = freq0_def = None;
  i_def = Meow.Parm(1);
  quv_def = Meow.Parm(0);

  srcdir = Meow.LMDirection(ns,name,0,0);
  src = Meow.PointSource(ns,name,srcdir,I=i_def,Q=quv_def,U=quv_def,V=quv_def,spi=spi_def,freq0=freq0_def);

  ## define a parmgroup for source parameters
  ## now make a solvejobs for the source
  #pg_src = ParmGroup("source",
              #src.coherency().search(tags="solvable"),
              #table_name="sources.mep",
              #individual=True,
              #bookmark=True);
  ## now make a solvejobs for the source
  #options.append(pg_src.make_solvejob_menu("Calibrate source fluxes"));

  return [ src ];
Beispiel #7
0
  def source_list (self,ns,max_sources=None,**kw):
    """Reads LSM and returns a list of Meow objects.
    ns is node scope in which they will be created.
    Keyword arguments may be used to indicate which of the source attributes are to be
    created as Parms, use e.g. I=Meow.Parm(tags="flux") for this.
    The use_parms option may override this.
    """;
    if self.filename is None:
      return [];
    if self.lsm is None:
      self.load(ns);
    # all=1 returns unsorted list, so use a large count instead, to get a sorted list
    plist = self.lsm.queryLSM(count=9999999);
    
    # parse the beam expression
    if self.beam_expr is not None:
      try:
        beam_func = eval("lambda r,fq:"+self.beam_expr);
      except:
        raise RuntimeError("invalid beam expression");
    else:
      beam_func = None;
    
    # make list of direction,punit,I,I_apparent tuples
    parm = Meow.Parm(tags="source solvable");
    srclist = [];
    for pu in plist:
      ra,dec,I,Q,U,V,spi,freq0,RM = pu.getEssentialParms(ns);
      if self.solve_pos:
        ra = parm.new(ra);
        dec = parm.new(dec);
      direction = Meow.Direction(ns,pu.name,ra,dec,static=not self.solve_pos);
      Iapp = I;
      if beam_func is not None:
      # if phase centre is already set (i.e. static), then lmn will be computed here, and we
      # can apply a beam expression
        lmn = direction.lmn_static();
        if lmn is not None:
          r = sqrt(lmn[0]**2+lmn[1]**2);
          Iapp = I*beam_func(r,freq0*1e-9 or 1.4);  # use 1.4 GHz if ref frequency not specified
      # append to list
      srclist.append((pu.name,direction,pu,I,Iapp));
    # sort list by decreasing apparent flux
    from past.builtins import cmp
    from functools import cmp_to_key
    srclist.sort(key=cmp_to_key(lambda a,b:cmp(b[4],a[4])));
    
    srclist_full = srclist;
    # extract active subset
    srclist = self._subset_parser.apply(self.lsm_subset,srclist_full,names=[src[0] for src in srclist_full]);
    # extract solvable subset
    solve_subset = self._subset_parser.apply(self.solve_subset,srclist_full,names=[src[0] for src in srclist_full]);
    solve_subset = set([src[0] for src in solve_subset]);

    # make copy of kw dict to be used for sources not in solvable set
    kw_nonsolve = dict(kw);
    # and update kw dict to be used for sources in solvable set
    if self.solvable_sources:
      if self.solve_I:
        kw.setdefault("I",parm);
      if self.solve_Q:
        kw.setdefault("Q",parm);
      if self.solve_U:
        kw.setdefault("U",parm);
      if self.solve_V:
        kw.setdefault("V",parm);
      if self.solve_spi:
        kw.setdefault("spi",parm);
      if self.solve_RM:
        kw.setdefault("RM",parm);
      if self.solve_pos:
        kw.setdefault("ra",parm);
        kw.setdefault("dec",parm);
      if self.solve_shape:
        kw.setdefault("sx",parm);
        kw.setdefault("sy",parm);
        kw.setdefault("phi",parm);

    # make Meow list
    source_model = []

  ## Note: conversion from AIPS++ componentlist Gaussians to Gaussian Nodes
  ### eX, eY : multiply by 2
  ### eP: change sign
    for name,direction,pu,I,Iapp in srclist:
#      print "%-20s %12f %12f"%(pu.name,I,Iapp);
      src = {};
      ( src['ra'],src['dec'],
        src['I'],src['Q'],src['U'],src['V'],
        src['spi'],src['freq0'],src['RM']    ) = pu.getEssentialParms(ns)
      (eX,eY,eP) = pu.getExtParms()
      # scale 2 difference
      src['sx'] = eX*2
      src['sy'] = eY*2
      src['phi'] = -eP
      # override zero values with None so that Meow can make smaller trees
      if not src['RM']:
        src['RM'] = None;
      if not src['spi']:
        src['spi'] = None;
        if src['RM'] is None:
          src['freq0'] = None;
      ## construct parms or constants for source attributes
      ## if source is in solvable set (solvable_source_set of None means all are solvable),
      ## use the kw dict, else use the nonsolve dict for source parameters
      if name in solve_subset:
        solvable = True;
        kwdict = kw;
      else:
        solvable = False;
        kwdict = kw_nonsolve;
      for key,value in src.items():
        meowparm = kwdict.get(key);
        if isinstance(meowparm,Meow.Parm):
          src[key] = meowparm.new(value);
        elif meowparm is not None:
          src[key] = value;

      if eX or eY or eP:
        # Gaussians
        if eY:
          size,phi = [src['sx'],src['sy']],src['phi'];
        else:
          size,phi = src['sx'],None;
        src = Meow.GaussianSource(ns,name=pu.name,
                I=src['I'],Q=src['Q'],U=src['U'],V=src['V'],
                direction=direction,
                spi=src['spi'],freq0=src['freq0'],RM=src['RM'],
                size=size,phi=phi);
      else:
        src = Meow.PointSource(ns,name=pu.name,
                I=src['I'],Q=src['Q'],U=src['U'],V=src['V'],
                direction=direction,
                spi=src['spi'],freq0=src['freq0'],RM=src['RM']);
                
      # check for beam LM
      if pu._lm is not None:
        src.set_attr('beam_lm',pu._lm);
              
      src.solvable = solvable;
      src.set_attr('Iapp',Iapp);
      source_model.append(src);
      
    return source_model;
Beispiel #8
0
    def source_list(self, ns, max_sources=None, **kw):
        """Reads LSM and returns a list of Meow objects.
        ns is node scope in which they will be created.
        Keyword arguments may be used to indicate which of the source attributes are to be
        created as Parms, use e.g. I=Meow.Parm(tags="flux") for this.
        The use_parms option may override this.
        """
        if self.filename is None:
            return []
        # load the sky model
        if self.lsm is None:
            self.lsm = Tigger.load(self.filename)

        # sort by brightness
        import functools
        from past.builtins import cmp
        from functools import cmp_to_key
        sources = sorted(
            self.lsm.sources,
            key=cmp_to_key(lambda a, b: cmp(b.brightness(), a.brightness())))

        # extract subset, if specified
        sources = SourceSubsetSelector.filter_subset(self.lsm_subset, sources,
                                                     self._getTagValue)
        # get nulls subset
        if self.null_subset:
            nulls = set([
                src.name for src in SourceSubsetSelector.filter_subset(
                    self.null_subset, sources)
            ])
        else:
            nulls = set()
        parm = Meow.Parm(tags="source solvable")
        # make copy of kw dict to be used for sources not in solvable set
        kw_nonsolve = dict(kw)
        # and update kw dict to be used for sources in solvable set
        # this will be a dict of lists of solvable subgroups
        parms = []
        subgroups = {}
        if self.solvable_sources:
            subgroup_order = []
            for sgname in _SubgroupOrder:
                if getattr(self, 'solve_%s' % sgname):
                    sg = subgroups[sgname] = []
                    subgroup_order.append(sgname)

        # make Meow list
        source_model = []

        for src in sources:
            is_null = src.name in nulls
            # this will be True if this source has solvable parms
            solvable = self.solvable_sources and not is_null and (
                not self.lsm_solvable_tag
                or getattr(src, self.lsm_solvable_tag, False))
            if solvable:
                # independent groups?
                if self.lsm_solve_group_tag:
                    independent_sg = sgname = "%s:%s" % (
                        self.lsm_solve_group_tag,
                        getattr(src, self.lsm_solve_group_tag, "unknown"))
                else:
                    independent_sg = ""
                    sgname = 'source:%s' % src.name
                if sgname in subgroups:
                    sgsource = subgroups[sgname]
                else:
                    sgsource = subgroups[sgname] = []
                    subgroup_order.append(sgname)
            # make dict of source parametrs: for each parameter we have a value,subgroup pair
            if is_null:
                attrs = dict(ra=src.pos.ra,
                             dec=src.pos.dec,
                             I=0,
                             Q=None,
                             U=None,
                             V=None,
                             RM=None,
                             spi=None,
                             freq0=None)
            else:
                attrs = dict(
                    ra=src.pos.ra,
                    dec=src.pos.dec,
                    I=src.flux.I,
                    Q=getattr(src.flux, 'Q', None),
                    U=getattr(src.flux, 'U', None),
                    V=getattr(src.flux, 'V', None),
                    RM=getattr(src.flux, 'rm', None),
                    freq0=getattr(src.flux, 'freq0', None)
                    or (src.spectrum and getattr(src.spectrum, 'freq0', None)),
                    spi=src.spectrum and getattr(src.spectrum, 'spi', None))
            if not is_null and isinstance(src.shape, ModelClasses.Gaussian):
                attrs['lproj'] = src.shape.ex * math.sin(src.shape.pa)
                attrs['mproj'] = src.shape.ex * math.cos(src.shape.pa)
                attrs['ratio'] = src.shape.ey / src.shape.ex
            # construct parms or constants for source attributes, depending on whether the source is solvable or not
            # If source is solvable and this particular attribute is solvable, replace
            # value in attrs dict with a Meq.Parm.
            if solvable:
                for parmname, value in list(attrs.items()):
                    sgname = _Subgroups.get(parmname, None)
                    if sgname in subgroups:
                        solvable = True
                        parm = attrs[parmname] = ns[src.name](
                            parmname) << Meq.Parm(value or 0,
                                                  tags=["solvable", sgname],
                                                  solve_group=independent_sg)
                        subgroups[sgname].append(parm)
                        sgsource.append(parm)
                        parms.append(parm)

            # construct a direction
            direction = Meow.Direction(ns,
                                       src.name,
                                       attrs['ra'],
                                       attrs['dec'],
                                       static=not solvable
                                       or not self.solve_pos)

            # construct a point source or gaussian or FITS image, depending on source shape class
            if src.shape is None or is_null:
                msrc = Meow.PointSource(ns,
                                        name=src.name,
                                        I=attrs['I'],
                                        Q=attrs['Q'],
                                        U=attrs['U'],
                                        V=attrs['V'],
                                        direction=direction,
                                        spi=attrs['spi'],
                                        freq0=attrs['freq0'],
                                        RM=attrs['RM'])
            elif isinstance(src.shape, ModelClasses.Gaussian):
                msrc = Meow.GaussianSource(ns,
                                           name=src.name,
                                           I=attrs['I'],
                                           Q=attrs['Q'],
                                           U=attrs['U'],
                                           V=attrs['V'],
                                           direction=direction,
                                           spi=attrs['spi'],
                                           freq0=attrs['freq0'],
                                           lproj=attrs['lproj'],
                                           mproj=attrs['mproj'],
                                           ratio=attrs['ratio'])
                if solvable and 'shape' in subgroups:
                    subgroups['pos'] += direction.get_solvables()
            elif isinstance(src.shape, ModelClasses.FITSImage):
                msrc = Meow.FITSImageComponent(ns,
                                               name=src.name,
                                               filename=src.shape.filename,
                                               direction=direction)
                msrc.set_options(fft_pad_factor=(src.shape.pad or 2))

            msrc.solvable = solvable

            # copy standard attributes from sub-objects
            for subobj in src.flux, src.shape, src.spectrum:
                if subobj:
                    for attr, val in src.flux.getAttributes():
                        msrc.set_attr(attr, val)
            # copy all extra attrs from source object
            for attr, val in src.getExtraAttributes():
                msrc.set_attr(attr, val)

            # make sure Iapp exists (init with I if it doesn't)
            if msrc.get_attr('Iapp', None) is None:
                msrc.set_attr('Iapp', src.flux.I)

            source_model.append(msrc)

        # if any solvable parms were made, make a parmgroup and solve job for them
        if parms:
            if os.path.isdir(self.filename):
                table_name = os.path.join(self.filename, "sources.fmep")
            else:
                table_name = os.path.splitext(self.filename)[0] + ".fmep"
            # make list of Subgroup objects for every non-empty subgroup
            sgs = []
            for sgname in subgroup_order:
                sglist = subgroups.get(sgname, None)
                if sglist:
                    sgs.append(Meow.ParmGroup.Subgroup(sgname, sglist))
            # make main parm group
            pg_src = Meow.ParmGroup.ParmGroup("source parameters",
                                              parms,
                                              subgroups=sgs,
                                              table_name=table_name,
                                              table_in_ms=False,
                                              bookmark=True)
            # now make a solvejobs for the source
            Meow.ParmGroup.SolveJob("cal_source",
                                    "Solve for source parameters", pg_src)

        return source_model