plotting.py 文件源码

def plotDistance(self):
        filename = self.config.mergefile
        logger.debug("Opening %s..."%filename)
        f = pyfits.open(filename)
        pixels,values = f[1].data['PIXEL'],2*f[1].data['LOG_LIKELIHOOD']
        if values.ndim == 1: values = values.reshape(-1,1)
        distances = f[2].data['DISTANCE_MODULUS']
        if distances.ndim == 1: distances = distances.reshape(-1,1)
        ts_map = healpy.UNSEEN * numpy.ones(healpy.nside2npix(self.nside))

        ndim = len(distances)
        nrows = int(numpy.sqrt(ndim))
        ncols = ndim // nrows + (ndim%nrows > 0)

        fig = pylab.figure()
        axes  = AxesGrid(fig, 111, nrows_ncols = (nrows, ncols),axes_pad=0,
                         label_mode='1', cbar_mode='single',cbar_pad=0,cbar_size='5%',
                         share_all=True,add_all=False)

        images = []
        for i,val in enumerate(values.T):
            ts_map[pixels] = val

            im = healpy.gnomview(ts_map,**self.gnom_kwargs)
            pylab.close()
            images.append(im)
        data = numpy.array(images); mask = (data == healpy.UNSEEN)
        images = numpy.ma.array(data=data,mask=mask)
        vmin = numpy.ma.min(images)
        vmax = numpy.ma.max(images)

        for i,val in enumerate(values.T):
            ax = axes[i]
            im = ax.imshow(images[i],origin='bottom',vmin=vmin,vmax=vmax)
            ax.cax.colorbar(im)

            #ax.annotate(r"$\mu = %g$"%distances[i],**self.label_kwargs)
            ax.annotate(r"$d = %.0f$ kpc"%mod2dist(distances[i]),**self.label_kwargs)
            ax.axis["left"].major_ticklabels.set_visible(False) 
            ax.axis["bottom"].major_ticklabels.set_visible(False) 
            fig.add_axes(ax)
            fig.add_axes(ax.cax)
        return fig,axes