Exemple #1
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    def get_default_sources(self):

        point_sources, diffuse_sources = [], []

        model = PowerLaw(index=self.powerlaw_index, e0=np.sqrt(self.emin*self.emax))
        model.set_flux(self.flux, emin=self.emin, emax=self.emax)
        ps = PointSource(
            name = 'source',
            model = model.copy(),
            skydir = self.roi_dir)
        point_sources.append(ps)

        if self.isotropic_bg:
            ds = get_sreekumar()
            diffuse_sources.append(ds)

        if self.nearby_source:
            ps = PointSource(
                name = 'nearby_source',
                model = model.copy(),
                skydir = SkyDir(self.roi_dir.ra(),self.roi_dir.dec()+3)
            )
            point_sources.append(ps)

        return point_sources, diffuse_sources
class PointSource(object):
    """ combine name, skydir, model """
    def __init__(self,
                 skydir,
                 name,
                 model=None,
                 free_parameters=True,
                 leave_parameters=False):
        self.name = name
        self.skydir = skydir
        self.model = PowerLaw() if model is None else model
        #if not free_parameters:
        if not leave_parameters:
            for i in xrange(len(self.model.free)):
                self.model.free[i] = free_parameters
        self.duplicate = False

    def __str__(self):
        return '\n'.join([
            '\n',
            '=' * 60,
            'Name:\t\t%s' % (self.name),
            'R.A. (J2000):\t%.5f' % (self.skydir.ra()),
            'Dec. (J2000):\t%.5f' % (self.skydir.dec()),
            'Model:\t\t%s' % (self.model.full_name()),
            '\t' + self.model.__str__(indent='\t'),
        ])

    def copy(self):
        """ Create a deep copy of the point source. """
        return PointSource(SkyDir(self.skydir.ra(), self.skydir.dec()),
                           self.name,
                           self.model.copy(),
                           leave_parameters=True)
Exemple #3
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    def get_default_sources(self):

        point_sources, diffuse_sources = [], []

        model = PowerLaw(index=self.powerlaw_index,
                         e0=np.sqrt(self.emin * self.emax))
        model.set_flux(self.flux, emin=self.emin, emax=self.emax)
        ps = PointSource(name='source',
                         model=model.copy(),
                         skydir=self.roi_dir)
        point_sources.append(ps)

        if self.isotropic_bg:
            ds = get_sreekumar()
            diffuse_sources.append(ds)

        if self.nearby_source:
            ps = PointSource(name='nearby_source',
                             model=model.copy(),
                             skydir=SkyDir(self.roi_dir.ra(),
                                           self.roi_dir.dec() + 3))
            point_sources.append(ps)

        return point_sources, diffuse_sources
Exemple #4
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        type = args.type,
        mc = dict(
            extension=extension_mc,
            gal=[ skydir_mc.l(), skydir_mc.b() ],
            cel=[ skydir_mc.ra(), skydir_mc.dec() ],
            model=spectrum_to_dict(model_mc),
            flux=pointlike_model_to_flux(model_mc, emin, emax),
        )
    )

    tempdir = mkdtemp()

    point = 'point'
    ps = PointSource(
        name=point,
        model=model_mc.copy(),
        skydir = skydir_mc
    )

    extended = 'extended_%f' % extension_mc
    if extension_mc > 0:
        sm = Disk(sigma=extension_mc, center=skydir_mc)
        es = ExtendedSource(
            name=extended,
            model=model_mc,
            spatial_model=sm,
        )
        sim_es = es
    else:
        # If the source has no extension,
        # simulate the source as point-like
Exemple #5
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    for fit_irf in ["P7SOURCE_V6", "P7SOURCE_V4"]:

        print "Using fit_irf %s" % fit_irf

        sa = SpectralAnalysis(
            ds,
            irf=fit_irf,
            roi_dir=skydir_mc,
            maxROI=10,
            minROI=10,
            event_class=0,  # not this is necessary for MC data
            emin=emin,
            emax=emax,
        )

        source_guess = PointSource(name=name_mc, skydir=skydir_mc, model=model_mc.copy())

        roi = sa.roi(
            roi_dir=skydir_mc, diffuse_sources=[j.copy() for j in diffuse_sources], point_sources=[source_guess]
        )

        print "bins = ", roi.bin_edges

        print "Fitting unmodified ROI"

        def fit():
            try:
                roi.fit(use_gradient=True)
            except Exception, err:
                print "\n\n\n\nERROR FITTING: %s\n\n\n" % (str(err))
Exemple #6
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class ExtendedSource(DiffuseSource):
    """ Class inherting from DiffuseSource but implementing a spatial source. 
        The main difference is the requirement of a spatial model to accomany 
        a spectral model. """

    defaults = (
        ('name', None, 'The name of the extended source.'),
        ('model', None, 'a Model object.'),
        ('spatial_model', None, """The spatial model to use. 
                                       This is a SpatialModel object."""),
    )

    @keyword_options.decorate(defaults)
    def __init__(self, **kwargs):
        """ Make the naming consistent with the PointSource object so that
            extended sources 'feel' like point sources.

            """
        keyword_options.process(self, kwargs)

        if self.model == None: self.model = PowerLaw()
        if self.spatial_model == None: self.spatial_model = Disk()

        if not isinstance(self.spatial_model, SpatialModel):
            raise Exception(
                "The diffuse_model passed to an Extended Source must inherit from SpatialModel."
            )

        super(ExtendedSource, self).__init__(diffuse_model=self.spatial_model,
                                             scaling_model=self.model,
                                             name=self.name)

        self.model.background = False

    @property
    def skydir(self):
        return self.spatial_model.center

    @property
    def smodel(self):
        """ No reason to keep a model & smodel. """
        return self.model

    @smodel.setter
    def smodel(self, value):
        self.model = value

    def __str__(self, indent=''):
        return indent + ('\n' + indent).join([
            '\n', '=' * 60,
            'Name:\t\t%s' % (self.name),
            'R.A. (J2000):\t\t%.5f' % (self.spatial_model.center.ra()),
            'Dec. (J2000):\t\t%.5f' % (self.spatial_model.center.dec()),
            'Model:\t\t%s' %
            (self.model.full_name()), '\t' + self.model.__str__(indent='\t'),
            'SpatialModel:\t%s' % (self.spatial_model.full_name()),
            '\t' + self.spatial_model.__str__(indent='\t')
        ])

    def copy(self):
        """ Create a deep copy of an extended source. """
        return ExtendedSource(name=self.name,
                              spatial_model=self.spatial_model.copy(),
                              model=self.model.copy())