>>> import pyfits >>> tab = pyfits.getdata('fuse.fits') >>> tab.info() >>> flux = 10.**12*tab.field('flux') >>> error = 10.**12*tab.field('flux') >>> plot(flux, error,'.')
Exercise 2, 3:
>>> im = pyfits.getdata('pix.fits') >>> from numarray.convolve import boxcar >>> sim = boxcar(im, (31, 31)) >>> sim = 100*sim/sim.max() >>> contour(sim, contours= [90, 70, 50, 30, 10]) >>> imshow(im, vmax=500) >>> contour(sim, [90,70,50,30,10],hold=True)
>>> imshow(im, vmax=500) >>> gray() >>> text(380,72,'my hometown!',color='yellow' >>> savefig('fluxerror.ps')
- This example wasn't really doable with the level of knowledge given but a solution is given anyway (turned out overplotting with a transparent background on an image is not quite so simple).
>>> ax = subplot(111, frameon=False) # leads to a clear plot background so images show through >>> imshow(im, vmax=500) >>> sim = 500.*im/8000. # scale image to prevent shrinking image when plot value is larger than 512 >>> # no matter, image will still rescale due to auto ticking >>> def buttonclick(event): ... # left button, note use of int() to make position acceptable for indexing ... if event.button==1: plot(sim[int(event.ydata)], hold=True) ... if event.button==2: plot(sim[:,int(event.xdata)], hold=True) ... >>> cid=connect('button_press_event',buttonclick) >>> # click away. Note that old overplot remain. More work is needed to make this more useful, >>> # particularly with regard to plot scaling and keeping the image size unchanged. >>> disconnect(cid)