下面是一个读入fits文件，画积分强度图，再把某个星表里的天体画到图上的python程序。
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#!/usr/bin/env python
import pyfits
import math
import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import mpl_toolkits
from matplotlib.patches import Ellipse
hdulist = pyfits.open('xxx.fits')
image = hdulist[0].data
nx = hdulist[0].header['naxis1']
ny = hdulist[0].header['naxis2']
nz = hdulist[0].header['naxis3']
crvalx = hdulist[0].header['crval1']
cdeltax = hdulist[0].header['cdelt1']
crpixx = hdulist[0].header['crpix1']
crvaly = hdulist[0].header['crval2']
cdeltay = hdulist[0].header['cdelt2']
crpixy = hdulist[0].header['crpix2']
crvalz = hdulist[0].header['crval3']
cdeltaz = hdulist[0].header['cdelt3']
crpixz = hdulist[0].header['crpix3']
x = np.arange(-crpixx*cdeltax+crvalx,(nx-1-crpixx)*cdeltax+crvalx,cdeltax)
y = np.arange(-crpixy*cdeltay+crvaly,(ny-1-crpixy)*cdeltay+crvaly,cdeltay)
# image[z,y,x]!!!! The first dimension is velocity channel!
Z = image[0,:,:]
Z = Z*0.0
for i in range(0,nz):
Z = Z+image[i,:,:]
# set negative value to zero
Z = (Z+abs(Z))/2.0
ax = plt.subplot(111)
im = plt.imshow(Z, cmap=cm.gist_yarg,
origin='lower', aspect='equal',
extent=[max(x),min(x),min(y),max(y)])
locs, labels = plt.xticks()
xtv = locs
for i in range(0,len(locs)):
xtv[i] = int((locs[i]-int(locs[i]/15.0)*15.0)/15.0*60.0)
x_ticks=[str(xtv[0]),str(xtv[1]),str(xtv[2]),str(xtv[3]),
str(xtv[4]),'04h '+str(xtv[5])+' m' ,'04h '+str(xtv[6])+' m']
plt.gca().set_xticklabels(x_ticks)
ra,dec,major,minor,angle = np.loadtxt('catalog.txt',unpack=True,usecols=[16,17,18,19,20])
xr = ra
yd = dec
angle=90.0-angle
for i in range(len(ra)):
yd[i] = dec[i]
xr[i] = (ra[i]-crvalx)*math.cos(dec[i]*3.1415926/180.0)+crvalx
ells = [Ellipse(xy=[xr[i],yd[i]],width=major[i]*2,height=minor[i]*2,angle=angle[i])
for i in xrange(len(ra))]
for e in ells:
ax.add_artist(e)
e.set_alpha(1.0)
e.set_clip_box(ax.bbox)
e.set_edgecolor([0.0,1.0,0.0])
e.set_fill(False)
e.set_linewidth(0.5)
plt.colorbar(im,orientation='vertical')
plt.show()
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