def normalizer(modelin,continuum,i): model = load_spec(modelin,'PHOENIX') cont = load_spec(continuum,'PHOENIXcont') specgrid =np.arange(3000,12000,0.01) a = modelin.split('-') print 'Normalizing model:', a[0], a[1],'K', ',Continuum scaling:', noscale[i] modelflux = np.interp(specgrid,model[:,0], model[:,1]) contflux = np.interp(specgrid,cont[:,0], cont[:,1]) normflux = modelflux/contflux convnormflux = convolve(normflux, 6, 0.01) convnormflux2 = convolve(convnormflux,2,0.01) normalflux = convnormflux2/noscale[i] end = len(a[3]) - 2 normalspec = array((specgrid,normalflux)).T np.savetxt('PHOENIXnorm/{}-{}-{}-{}.norm.conv.nonalpha.7'.format(a[0],a[1],a[2],a[3][0:end]) ,normalspec, fmt='%.18e')