def test_get_fits_wcs(tmpdir):
with ImageModel(FITS_FILE) as dm:
# Refer to the data array to initialize it.
dm.data = np.zeros((5, 5))
# Now continue with the test.
wcs1 = dm.get_fits_wcs()
dm2 = dm.copy()
wcs2 = dm2.get_fits_wcs()
x = np.random.rand(2**16, wcs1.wcs.naxis)
world1 = wcs1.all_pix2world(x, 1)
world2 = wcs2.all_pix2world(x, 1)
assert_array_almost_equal(world1, world2)
wcs1.wcs.crpix[0] = 42.0
dm2.set_fits_wcs(wcs1)
assert dm2.meta.wcsinfo.crpix1 == 42.0
with warnings.catch_warnings():
# Filter out warnings generated by WCSLIB>=7.1
warnings.simplefilter("ignore")
wcs2 = dm2.get_fits_wcs()
assert wcs2.wcs.crpix[0] == 42.0
dm2_tmp_fits = str(tmpdir.join("tmp_dm2.fits"))
dm2.to_fits(dm2_tmp_fits)
with ImageModel(dm2_tmp_fits) as dm3:
wcs3 = dm3.get_fits_wcs()
assert wcs3.wcs.crpix[0] == 42.0
x = np.random.rand(2**16, wcs1.wcs.naxis)
world1 = wcs1.all_pix2world(x, 1)
world2 = wcs3.all_pix2world(x, 1)
dm4 = ImageModel((10, 10))
dm4.set_fits_wcs(wcs3)
dm4_tmp_fits = str(tmpdir.join("tmp_dm4.fits"))
dm4.to_fits(dm4_tmp_fits, overwrite=True)
with ImageModel(dm4_tmp_fits) as dm5:
with warnings.catch_warnings():
# Filter out warnings generated by WCSLIB>=7.1
warnings.simplefilter("ignore")
wcs5 = dm5.get_fits_wcs()
assert wcs5.wcs.crpix[0] == 42.0
#add the var_poisson data and header
hdul_rate.append(fits.ImageHDU(header=header_vr, data=data_rnoise))
hdul_rate.info()
#save the file
hdul_rate.writeto('test_rate.fits', overwrite=True)
from astropy.wcs import WCS
w = WCS(slp_fname)
im = ImageModel(slp_fname)
#ra, dec, lam = im.meta.wcs(x, y)
#print(ra,dec,lam)
im.set_fits_wcs(w)
test = im.find_fits_keyword('V2_REF')
print(test)
test = im.find_fits_keyword('TELESCOP')
print(test)
test = im.find_fits_keyword('NAXIS')
print(test)
im.meta.wcsinfo.v2_ref = header_slp['V2_REF']
print(im.meta.wcsinfo.v2_ref)
im.meta.wcsinfo.v3_ref = header_slp['V3_REF']
print(im.meta.wcsinfo.v3_ref)
im.meta.wcsinfo.pa_v3 = header_slp['PA_V3']
print(im.meta.wcsinfo.pa_v3)
im.meta.wcsinfo.ra_ref = header_slp['RA_REF']
im.meta.wcsinfo.dec_ref = header_slp['DEC_REF']
im.meta.wcsinfo.roll_ref = header_slp['ROLL_REF']
