예제 #1
0
    def __init__(self, *args, wimp_kwargs=None, **kwargs):
        # Compute the energy spectrum in a given time range
        # Times used by wimprates are J2000 timestamps
        assert self.n_time_bins >= 1, "Need >= 1 time bin"
        if hasattr(self, 'n_in'):
            raise RuntimeError(
                "n_in is gone! Use n_time_bins to control accuracy, or set "
                "pretend_wimps_dont_modulate to use a time-averaged spectrum.")

        times = np.linspace(wr.j2000(self.t_start.value),
                            wr.j2000(self.t_stop.value), self.n_time_bins + 1)
        time_centers = self.bin_centers(times)

        if wimp_kwargs is None:
            # No arguments given at all;
            # use default mass, xsec and energy range
            wimp_kwargs = dict(mw=self.mw,
                               sigma_nucleon=self.sigma_nucleon,
                               es=self.es)
        else:
            assert 'mw' in wimp_kwargs and 'sigma_nucleon' in wimp_kwargs, \
                "Pass at least 'mw' and 'sigma_nucleon' in wimp_kwargs"
            if 'es' not in wimp_kwargs:
                # Energies not given, use default energy bin edges
                wimp_kwargs['es'] = self.es

        es = wimp_kwargs['es']
        es_centers = self.bin_centers(es)
        del wimp_kwargs['es']  # To avoid confusion centers / edges

        # Transform wimp_kwargs to arguments that can be passed to wimprates
        # which means transforming es from edges to centers
        spectra = np.array([
            wr.rate_wimp_std(t=t, es=es_centers, **wimp_kwargs) * np.diff(es)
            for t in time_centers
        ])
        assert spectra.shape == (len(time_centers), len(es_centers))

        self.energy_hist = Histdd.from_histogram(spectra,
                                                 bin_edges=(times, es))

        if self.pretend_wimps_dont_modulate:
            self.energy_hist.histogram = (
                np.ones_like(self.energy_hist.histogram) *
                self.energy_hist.sum(axis=0).histogram.reshape(1, -1) /
                self.n_time_bins)

        # Initialize the rest of the source, needs to be after energy_hist is
        # computed because of _populate_tensor_cache
        super().__init__(*args, **kwargs)
예제 #2
0
    def __init__(self, *args, wimp_kwargs=None, **kwargs):
        # Compute the energy spectrum in a given time range
        # Times used by wimprates are J2000 timestamps
        assert self.n_in > 1, \
            f"Number of time bin edges needs to be at least 2"
        times = np.linspace(wr.j2000(date=self.t_start),
                            wr.j2000(date=self.t_stop), self.n_in)
        time_centers = self.bin_centers(times)

        if wimp_kwargs is None:
            # No arguments given at all;
            # use default mass, xsec and energy range
            wimp_kwargs = dict(mw=self.mw,
                               sigma_nucleon=self.sigma_nucleon,
                               es=self.es)
        else:
            assert 'mw' in wimp_kwargs and 'sigma_nucleon' in wimp_kwargs, \
                "Pass at least 'mw' and 'sigma_nucleon' in wimp_kwargs"
            if 'es' not in wimp_kwargs:
                # Energies not given, use default energy bin edges
                wimp_kwargs['es'] = self.es

        es = wimp_kwargs['es']
        es_centers = self.bin_centers(es)
        del wimp_kwargs['es']  # To avoid confusion centers / edges

        # Transform wimp_kwargs to arguments that can be passed to wimprates
        # which means transforming es from edges to centers
        spectra = np.array([
            wr.rate_wimp_std(t=t, es=es_centers, **wimp_kwargs) * np.diff(es)
            for t in time_centers
        ])
        assert spectra.shape == (len(time_centers), len(es_centers))

        self.energy_hist = Histdd.from_histogram(spectra,
                                                 bin_edges=(times, es))
        # Initialize the rest of the source, needs to be after energy_hist is
        # computed because of _populate_tensor_cache
        super().__init__(*args, **kwargs)