Esempio n. 1
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    def ift_ical_sm(v, sm, g):
        assert isinstance(v, Visibility) or isinstance(v, BlockVisibility), v
        assert isinstance(sm, SkyModel), sm
        if g is not None:
            assert len(g) == 2, g
            assert isinstance(g[0], Image), g[0]
            assert isinstance(g[1], ConvolutionFunction), g[1]

        if docal and isinstance(sm.gaintable, GainTable):
            if isinstance(v, Visibility):
                bv = convert_visibility_to_blockvisibility(v)
                bv = apply_gaintable(bv, sm.gaintable)
                v = convert_blockvisibility_to_visibility(bv)
            else:
                v = apply_gaintable(v, sm.gaintable)

        result = invert_list_serial_workflow([v], [sm.image],
                                             context=context,
                                             vis_slices=vis_slices,
                                             facets=facets,
                                             gcfcf=[g],
                                             **kwargs)[0]
        if isinstance(sm.mask, Image):
            result[0].data *= sm.mask.data

        return result
    def ft_cal_sm(ov, sm):
        assert isinstance(ov, Visibility), ov
        assert isinstance(sm, SkyModel), sm
        v = copy_visibility(ov)

        v.data['vis'][...] = 0.0 + 0.0j

        if len(sm.components) > 0:

            if isinstance(sm.mask, Image):
                comps = copy_skycomponent(sm.components)
                comps = apply_beam_to_skycomponent(comps, sm.mask)
                v = predict_skycomponent_visibility(v, comps)
            else:
                v = predict_skycomponent_visibility(v, sm.components)

        if isinstance(sm.image, Image):
            if numpy.max(numpy.abs(sm.image.data)) > 0.0:
                if isinstance(sm.mask, Image):
                    model = copy_image(sm.image)
                    model.data *= sm.mask.data
                else:
                    model = sm.image
                v = predict_list_serial_workflow([v], [model],
                                                 context=context,
                                                 vis_slices=vis_slices,
                                                 facets=facets,
                                                 gcfcf=gcfcf,
                                                 **kwargs)[0]

        if docal and isinstance(sm.gaintable, GainTable):
            bv = convert_visibility_to_blockvisibility(v)
            bv = apply_gaintable(bv, sm.gaintable, inverse=True)
            v = convert_blockvisibility_to_visibility(bv)
        return v
Esempio n. 3
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    def corrupt_vis(vis, gt, **kwargs):
        if isinstance(vis, Visibility):
            bv = convert_visibility_to_blockvisibility(vis)
        else:
            bv = vis
        if gt is None:
            gt = create_gaintable_from_blockvisibility(bv, **kwargs)
            gt = simulate_gaintable(gt, seed=seed, **kwargs)
            bv = apply_gaintable(bv, gt)

        if isinstance(vis, Visibility):
            return convert_blockvisibility_to_visibility(bv)
        else:
            return bv
Esempio n. 4
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    def ft_cal_sm(obv, sm):
        assert isinstance(obv, BlockVisibility), obv
        bv = copy_visibility(obv)

        bv.data['vis'][...] = 0.0 + 0.0j

        assert len(sm.components) > 0

        if isinstance(sm.mask, Image):
            comps = copy_skycomponent(sm.components)
            comps = apply_beam_to_skycomponent(comps, sm.mask)
            bv = predict_skycomponent_visibility(bv, comps)
        else:
            bv = predict_skycomponent_visibility(bv, sm.components)

        if docal and isinstance(sm.gaintable, GainTable):
            bv = apply_gaintable(bv, sm.gaintable, inverse=True)

        return bv
    def ift_ical_sm(v, sm):
        assert isinstance(v, Visibility), v
        assert isinstance(sm.image, Image), sm.image

        if docal and isinstance(sm.gaintable, GainTable):
            bv = convert_visibility_to_blockvisibility(v)
            bv = apply_gaintable(bv, sm.gaintable)
            v = convert_blockvisibility_to_visibility(bv)

        result = invert_list_serial_workflow([v], [sm.image],
                                             context=context,
                                             vis_slices=vis_slices,
                                             facets=facets,
                                             gcfcf=gcfcf,
                                             **kwargs)[0]
        if isinstance(sm.mask, Image):
            result[0].data *= sm.mask.data

        return result
Esempio n. 6
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 def corrupt_vis(vis, gt, **kwargs):
     if gt is None:
         gt = create_gaintable_from_blockvisibility(vis, **kwargs)
         gt = simulate_gaintable(gt, **kwargs)
     return apply_gaintable(vis, gt)
    def actualSetup(self,
                    vnchan=1,
                    doiso=True,
                    ntimes=5,
                    flux_limit=2.0,
                    zerow=True,
                    fixed=False):

        nfreqwin = vnchan
        rmax = 300.0
        npixel = 512
        cellsize = 0.001
        frequency = numpy.linspace(0.8e8, 1.2e8, nfreqwin)
        if nfreqwin > 1:
            channel_bandwidth = numpy.array(nfreqwin *
                                            [frequency[1] - frequency[0]])
        else:
            channel_bandwidth = [0.4e8]
        times = numpy.linspace(-numpy.pi / 3.0, numpy.pi / 3.0, ntimes)

        phasecentre = SkyCoord(ra=-60.0 * u.deg,
                               dec=-60.0 * u.deg,
                               frame='icrs',
                               equinox='J2000')

        lowcore = create_named_configuration('LOWBD2', rmax=rmax)

        block_vis = create_blockvisibility(
            lowcore,
            times,
            frequency=frequency,
            channel_bandwidth=channel_bandwidth,
            weight=1.0,
            phasecentre=phasecentre,
            polarisation_frame=PolarisationFrame("stokesI"),
            zerow=zerow)

        block_vis.data['uvw'][..., 2] = 0.0
        self.beam = create_image_from_visibility(
            block_vis,
            npixel=npixel,
            frequency=[numpy.average(frequency)],
            nchan=nfreqwin,
            channel_bandwidth=[numpy.sum(channel_bandwidth)],
            cellsize=cellsize,
            phasecentre=phasecentre)

        self.components = create_low_test_skycomponents_from_gleam(
            flux_limit=flux_limit,
            phasecentre=phasecentre,
            frequency=frequency,
            polarisation_frame=PolarisationFrame('stokesI'),
            radius=npixel * cellsize)
        self.beam = create_low_test_beam(self.beam)
        self.components = apply_beam_to_skycomponent(self.components,
                                                     self.beam,
                                                     flux_limit=flux_limit)

        self.vis = copy_visibility(block_vis, zero=True)
        gt = create_gaintable_from_blockvisibility(block_vis, timeslice='auto')
        for i, sc in enumerate(self.components):
            if sc.flux[0, 0] > 10:
                sc.flux[...] /= 10.0
            component_vis = copy_visibility(block_vis, zero=True)
            gt = simulate_gaintable(gt,
                                    amplitude_error=0.0,
                                    phase_error=0.1,
                                    seed=None)
            component_vis = predict_skycomponent_visibility(component_vis, sc)
            component_vis = apply_gaintable(component_vis, gt)
            self.vis.data['vis'][...] += component_vis.data['vis'][...]

        # Do an isoplanatic selfcal
        self.model_vis = copy_visibility(self.vis, zero=True)
        self.model_vis = predict_skycomponent_visibility(
            self.model_vis, self.components)
        if doiso:
            gt = solve_gaintable(self.vis,
                                 self.model_vis,
                                 phase_only=True,
                                 timeslice='auto')
            self.vis = apply_gaintable(self.vis, gt, inverse=True)

        self.model_vis = convert_blockvisibility_to_visibility(self.model_vis)
        self.model_vis, _, _ = weight_visibility(self.model_vis, self.beam)
        self.dirty_model, sumwt = invert_list_arlexecute_workflow(
            self.model_vis, self.beam, context='2d')
        export_image_to_fits(
            self.dirty_model,
            "%s/test_modelpartition-model_dirty.fits" % self.dir)

        lvis = convert_blockvisibility_to_visibility(self.vis)
        lvis, _, _ = weight_visibility(lvis, self.beam)
        dirty, sumwt = invert_list_arlexecute_workflow(lvis,
                                                       self.beam,
                                                       context='2d')
        if doiso:
            export_image_to_fits(
                dirty,
                "%s/test_modelpartition-initial-iso-residual.fits" % self.dir)
        else:
            export_image_to_fits(
                dirty, "%s/test_modelpartition-initial-noiso-residual.fits" %
                self.dir)

        self.skymodels = [
            SkyModel(components=[cm], fixed=fixed) for cm in self.components
        ]