def FitsImageNTuple( file, resample=2 ):
#
# open the image file
#
image = pyfits.open(file)
#
# The primary header contains the coordinate data
#
prihdr = image[0].header
#
# build the axis objects and arrays
#
xaxis = FitsAxis( "x-axis",
keywordVal(prihdr, 'crval1', 0),
keywordVal(prihdr, 'cdelt1'),
keywordVal(prihdr, 'naxis1'),
ctype = keywordVal(prihdr, 'ctype1', 'x'),
crpix = keywordVal(prihdr, 'crpix1') )
yaxis = FitsAxis( "y-axis",
keywordVal(prihdr, 'crval2', 0),
keywordVal(prihdr, 'cdelt2'),
keywordVal(prihdr, 'naxis2'),
ctype = keywordVal(prihdr, 'ctype2', 'y'),
crpix = keywordVal(prihdr, 'crpix2') )
xx = xaxis.array()
yy = yaxis.array()
#
# create the image NTuple and register it with HippoDraw
#
nt = hippo.NTuple()
ntc = hippo.NTupleController.instance()
ntc.registerNTuple(nt)
#
x = []
y = []
z = []
for i in range (0, xaxis.naxis, resample):
for j in range (0, yaxis.naxis, resample):
x.append(xx[i])
y.append(yy[j])
z.append(image[0].data[j][i])
nt.addColumn(xaxis.ctype, x)
nt.addColumn(yaxis.ctype, y)
#
# use a place-holder name for now
#
nt.addColumn("Z values", z)
return nt
def FitsImageNTuple(file, resample=2):
#
# open the image file
#
image = pyfits.open(file)
#
# The primary header contains the coordinate data
#
prihdr = image[0].header
#
# build the axis objects and arrays
#
xaxis = FitsAxis("x-axis",
keywordVal(prihdr, 'crval1', 0),
keywordVal(prihdr, 'cdelt1'),
keywordVal(prihdr, 'naxis1'),
ctype=keywordVal(prihdr, 'ctype1', 'x'),
crpix=keywordVal(prihdr, 'crpix1'))
yaxis = FitsAxis("y-axis",
keywordVal(prihdr, 'crval2', 0),
keywordVal(prihdr, 'cdelt2'),
keywordVal(prihdr, 'naxis2'),
ctype=keywordVal(prihdr, 'ctype2', 'y'),
crpix=keywordVal(prihdr, 'crpix2'))
xx = xaxis.array()
yy = yaxis.array()
#
# create the image NTuple and register it with HippoDraw
#
nt = hippo.NTuple()
ntc = hippo.NTupleController.instance()
ntc.registerNTuple(nt)
#
x = []
y = []
z = []
for i in range(0, xaxis.naxis, resample):
for j in range(0, yaxis.naxis, resample):
x.append(xx[i])
y.append(yy[j])
z.append(image[0].data[j][i])
nt.addColumn(xaxis.ctype, x)
nt.addColumn(yaxis.ctype, y)
#
# use a place-holder name for now
#
nt.addColumn("Z values", z)
return nt
def setAxis(self, axisObj, naxis):
axisObj.updateFitsHeader(self.hdu.header, naxis)
self.axes[naxis] = axisObj
def writeto(self, filename):
os.system("rm -f " + filename)
self.fitsobj = pyfits.HDUList()
self.fitsobj.append(self.hdu)
self.fitsobj.writeto(filename)
if __name__ == "__main__":
print "FitsAxis class tests: "
fitsobj = pyfits.HDUList()
hdu = pyfits.PrimaryHDU()
x = FitsAxis("x-axis", 0., 0.2, 10)
y = FitsAxis("y-axis", 0., 0.1, 20)
hdu.data = numarray.zeros((y.naxis, x.naxis)) # note the ordering
x.updateFitsHeader(hdu.header, 1)
y.updateFitsHeader(hdu.header, 2)
fitsobj.append(hdu)
os.system("rm -f test.fits")
fitsobj.writeto('test.fits')
print "FitsAxis class tests completed.\n"
print "FitsImageArray class tests:"
x = FitsAxis("x-axis", 0., 0.2, 5)
y = FitsAxis("y-axis", 0., 0.1, 10)
array1 = numarray.ones((y.naxis, x.naxis))
z = {}
z[1] = FitsImageArray(array1)
def setAxis(self, axisObj, naxis):
axisObj.updateFitsHeader(self.hdu.header, naxis)
self.axes[naxis] = axisObj
def writeto(self, filename):
os.system("rm -f " + filename)
self.fitsobj = pyfits.HDUList()
self.fitsobj.append(self.hdu)
self.fitsobj.writeto(filename)
if __name__ == "__main__":
print "FitsAxis class tests: "
fitsobj = pyfits.HDUList()
hdu = pyfits.PrimaryHDU()
x = FitsAxis("x-axis", 0.0, 0.2, 10)
y = FitsAxis("y-axis", 0.0, 0.1, 20)
hdu.data = numarray.zeros((y.naxis, x.naxis)) # note the ordering
x.updateFitsHeader(hdu.header, 1)
y.updateFitsHeader(hdu.header, 2)
fitsobj.append(hdu)
os.system("rm -f test.fits")
fitsobj.writeto("test.fits")
print "FitsAxis class tests completed.\n"
print "FitsImageArray class tests:"
x = FitsAxis("x-axis", 0.0, 0.2, 5)
y = FitsAxis("y-axis", 0.0, 0.1, 10)
array1 = numarray.ones((y.naxis, x.naxis))
z = {}
z[1] = FitsImageArray(array1)