Пример #1
0
def measure_MGPS(snr):
    sourcedir = "/media/data/Dropbox/MWA/SNR_search/confirm_candidates/regrid_all/MGPS/"
    fitsfile = sourcedir + snr.name + "_MGPS.fits"
    final_flux, total_flux, bkg_flux, rms_flux, nbeam = find_fluxes(
        snr.polygon, snr.sources, snr.exclude, fitsfile)
    make_single_plot(snr.polygon, snr.sources, snr.exclude, fitsfile)
    print "final flux, total flux, background flux, rms flux, number of beams"
    print final_flux, total_flux, bkg_flux, rms_flux, nbeam
    # In units of Jy
    return final_flux, total_flux, bkg_flux, rms_flux, nbeam
Пример #2
0
def do_fit(colors, snr):
    freqs = []
    fluxes = []
    bkg = []
    rms = []
    nbeams = []
    for color in colors:
        if color == "white":
            fitsfile = color + "/" + snr.name + ".fits"
        else:
            fitsfile = color + "/rpj/" + snr.name + ".fits"
        if os.path.exists(fitsfile):
            hdu = fits.open(fitsfile)
            freqs.append(hdu[0].header["FREQ"])
            final_flux, total_flux, bkg_flux, rms_flux, nbeam = find_fluxes(
                snr.polygon, snr.sources, snr.exclude, fitsfile)
            fluxes.append(final_flux)
            bkg.append(bkg_flux)
            rms.append(rms_flux)
            nbeams.append(nbeam)
        else:
            print "Unable to fit flux for {0} in {1}".format(snr.name, color)
    fluxes = np.array(fluxes)
    freqs = np.array(freqs)
    logfreqs = np.log([f / normfreq for f in freqs])
    logfluxes = np.log(fluxes)
    fluxerrors = [
        np.sqrt((0.02 * s)**2 + n * (r**2))
        for s, r, n in zip(fluxes, rms, nbeams)
    ]
    logfluxerrors = np.array([e / f for e, f in zip(fluxerrors, fluxes)])
    alpha, err_alpha, amp, err_amp, chi2red = fit_spectrum(
        logfreqs[np.where(fluxes > 0)], logfluxes[np.where(fluxes > 0)],
        logfluxerrors[np.where(fluxes > 0)])

    return snr, dict(zip(freqs, fluxes)), dict(zip(freqs, bkg)), dict(
        zip(freqs,
            rms)), dict(zip(freqs,
                            nbeams)), alpha, err_alpha, amp, err_amp, chi2red
Пример #3
0
def measure_E11(snr):
    sourcedir = "/media/data/Dropbox/MWA/SNR_search/confirm_candidates/regrid_all/E11/"
    fitsfile = sourcedir + snr.name + "_E11.fits"
    final_flux, total_flux, bkg_flux, rms_flux, nbeam = find_fluxes(
        snr.polygon, snr.sources, snr.exclude, fitsfile)
    hdu = fits.open(fitsfile)
    T = mK2K(final_flux)
    nu = WL2freq(cm2m(11.))  # Effelsberg 11cm survey
    bmaj = hdu[0].header["BMAJ"]
    bmin = hdu[0].header["BMIN"]
    make_single_plot(snr.polygon, snr.sources, snr.exclude, fitsfile)
    print "final temperature, total temperature, background temperature, rms temperature (all in K), number of beams"
    print mK2K(final_flux), mK2K(total_flux), mK2K(bkg_flux), mK2K(
        rms_flux), nbeam
    # In units of Jy
    S_11 = T2PFD(T, nu, bmaj, bmin)
    tot_11 = T2PFD(mK2K(total_flux), nu, bmaj, bmin)
    bkg_11 = T2PFD(mK2K(bkg_flux), nu, bmaj, bmin)
    rms_11 = T2PFD(mK2K(rms_flux), nu, bmaj, bmin)
    print "final flux, total flux, background flux, rms flux, number of beams"
    print S_11, tot_11, bkg_11, rms_11, nbeam
    return S_11, tot_11, bkg_11, rms_11, nbeam
Пример #4
0
def poly_plot(fitsfile, makeplots):
    print "Fitting polygons to " + fitsfile
    hdu = fits.open(fitsfile)
    data = hdu[0].data
    xmax = hdu[0].header["NAXIS1"]
    ymax = hdu[0].header["NAXIS2"]
    w = wcs.WCS(hdu[0].header)
    try:
        pix2deg = hdu[0].header["CD2_2"]
    except KeyError:
        pix2deg = hdu[0].header["CDELT2"]

    def update(val):
        vmin = svmin.val
        vmax = svmax.val
        img.set_clim([svmin.val, svmax.val])
        fig.canvas.draw()

    fig = plt.figure(figsize=(5, 5))
    ax = fig.add_axes([0.05, 0.15, 0.8, 0.8])
    img = ax.imshow(data, cmap="gray")
    cbaxes = fig.add_axes([0.85, 0.1, 0.03, 0.85])
    cb = plt.colorbar(img, cax=cbaxes, orientation="vertical")

    axcolor = 'white'
    axmin = fig.add_axes([0.05, 0.05, 0.2, 0.02], axisbg=axcolor)
    axmax = fig.add_axes([0.44, 0.05, 0.2, 0.02], axisbg=axcolor)

    vmin0 = np.min(data)
    vmax0 = np.max(data)
    # include the slider: cribbed from https://stackoverflow.com/questions/5611805/using-matplotlib-slider-widget-to-change-clim-in-image
    svmin = Slider(axmin, "vmin", -5.0, 1.0, valinit=vmin0)
    svmax = Slider(axmax, "vmax", -1.0, 10.0, valinit=vmax0)

    svmin.on_changed(update)
    svmax.on_changed(update)

    fig.suptitle(
        'Left-click = select source, middle-click = source subtract, right-click = select region to exclude from background calculation'
    )

    # If you don't do this, it automatically zooms out when you first click on the plot
    ax.set_xlim(0, xmax)
    ax.set_ylim(0, ymax)
    polypick = PolyPick(ax)

    plt.show()

    # Export pixel co-ordinates as WCS co-ordinates in order to use on any arbitrary image, and save for later
    polygon = Coords()
    sources = Coords()
    exclude = Coords()
    if len(polypick.points.x):
        sources.x, sources.y = w.wcs_pix2world(
            zip(polypick.points.x, polypick.points.y), 0).transpose()
    if len(polypick.exclude.x):
        exclude.x, exclude.y = w.wcs_pix2world(
            zip(polypick.exclude.x, polypick.exclude.y), 0).transpose()


# Now I have the co-ordinates...
# Go measure the flux densities
    if len(polypick.coords.x):
        polygon.x, polygon.y = w.wcs_pix2world(
            zip(polypick.coords.x, polypick.coords.y), 0).transpose()
        find_fluxes(polygon, sources, exclude, fitsfile)
        # And make nice plots
        if makeplots is True:
            make_single_plot(polygon, sources, exclude, fitsfile)
    else:
        print "Failed to draw any points; exiting."