def testwritetoConvienceFunction(self):
"""Test the writeto convience function in both the fits and stpyfits
namespace."""
hdul = stpyfits.open(self.data('cdva2.fits'))
hdul1 = fits.open(self.data('cdva2.fits'))
header = hdul[0].header.copy()
header['NAXIS'] = 0
stpyfits.writeto(self.temp('new.fits'), hdul[0].data, header,
clobber=True)
fits.writeto(self.temp('new1.fits'), hdul1[0].data,hdul1[0].header,
clobber=True)
hdul.close()
hdul1.close()
info1 = fits.info(self.temp('new.fits'), output=False)
info2 = stpyfits.info(self.temp('new.fits'), output=False)
info3 = fits.info(self.temp('new1.fits'), output=False)
info4 = stpyfits.info(self.temp('new1.fits'), output=False)
assert_equal(info1, [(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', '')])
assert_equal(info2,
[(0, 'PRIMARY', 'PrimaryHDU', 6, (10, 10), 'int32', '')])
assert_equal(info3, [(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', '')])
assert_equal(info4,
[(0, 'PRIMARY', 'PrimaryHDU', 6, (10, 10), 'uint8', '')])
def testInfoConvienceFunction(self):
"""Test the info convience function in both the fits and stpyfits
namespace."""
assert_equal(
stpyfits.info(self.data('o4sp040b0_raw.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 215, (), '', ''),
(1, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(2, 'ERR', 'ImageHDU', 71, (62, 44), 'int16', ''),
(3, 'DQ', 'ImageHDU', 71, (62, 44), 'int16', ''),
(4, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(5, 'ERR', 'ImageHDU', 71, (62, 44), 'int16', ''),
(6, 'DQ', 'ImageHDU', 71, (62, 44), 'int16', '')])
assert_equal(
fits.info(self.data('o4sp040b0_raw.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 215, (), '', ''),
(1, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(2, 'ERR', 'ImageHDU', 71, (), '', ''),
(3, 'DQ', 'ImageHDU', 71, (), '', ''),
(4, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(5, 'ERR', 'ImageHDU', 71, (), '', ''),
(6, 'DQ', 'ImageHDU', 71, (), '', '')])
assert_equal(
stpyfits.info(self.data('cdva2.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (10, 10), 'int32', '')])
assert_equal(
fits.info(self.data('cdva2.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (), '', '')])
def testInfoConvienceFunction(self):
"""Test the info convience function in both the fits and stpyfits
namespace."""
assert_equal(
stpyfits.info(self.data('o4sp040b0_raw.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 215, (), '', ''),
(1, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(2, 'ERR', 'ImageHDU', 71, (62, 44), 'int16', ''),
(3, 'DQ', 'ImageHDU', 71, (62, 44), 'int16', ''),
(4, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(5, 'ERR', 'ImageHDU', 71, (62, 44), 'int16', ''),
(6, 'DQ', 'ImageHDU', 71, (62, 44), 'int16', '')])
assert_equal(fits.info(self.data('o4sp040b0_raw.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 215, (), '', ''),
(1, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(2, 'ERR', 'ImageHDU', 71, (), '', ''),
(3, 'DQ', 'ImageHDU', 71, (), '', ''),
(4, 'SCI', 'ImageHDU', 141, (62, 44), 'int16', ''),
(5, 'ERR', 'ImageHDU', 71, (), '', ''),
(6, 'DQ', 'ImageHDU', 71, (), '', '')])
assert_equal(stpyfits.info(self.data('cdva2.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (10, 10), 'int32', '')])
assert_equal(fits.info(self.data('cdva2.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (), '', '')])
def testwritetoConvienceFunction(self):
"""Test the writeto convience function in both the fits and stpyfits
namespace."""
hdul = stpyfits.open(self.data('cdva2.fits'))
hdul1 = fits.open(self.data('cdva2.fits'))
header = hdul[0].header.copy()
header['NAXIS'] = 0
stpyfits.writeto(self.temp('new.fits'),
hdul[0].data,
header,
clobber=True)
fits.writeto(self.temp('new1.fits'),
hdul1[0].data,
hdul1[0].header,
clobber=True)
hdul.close()
hdul1.close()
info1 = fits.info(self.temp('new.fits'), output=False)
info2 = stpyfits.info(self.temp('new.fits'), output=False)
info3 = fits.info(self.temp('new1.fits'), output=False)
info4 = stpyfits.info(self.temp('new1.fits'), output=False)
assert_equal(info1, [(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', '')])
assert_equal(info2,
[(0, 'PRIMARY', 'PrimaryHDU', 6, (10, 10), 'int32', '')])
assert_equal(info3, [(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', '')])
assert_equal(info4,
[(0, 'PRIMARY', 'PrimaryHDU', 6, (10, 10), 'uint8', '')])
def testHDUListFlushMethod(self):
"""Test the flush method of HDUList in both the fits and stpyfits
namespace."""
hdu = stpyfits.PrimaryHDU()
hdu1 = stpyfits.ImageHDU()
hdu.data = np.zeros((10, 10), dtype=np.int32)
hdu1.data = hdu.data + 2
hdu.header.set('BITPIX', 32)
hdu1.header.set('BITPIX', 32)
hdu.header.set('NAXIS', 2)
hdu.header.set('NAXIS1', 10, 'length of constant array axis 1',
after='NAXIS')
hdu.header.set('NAXIS2', 10, 'length of constant array axis 2',
after='NAXIS1')
hdu.header.set('PIXVALUE', 0, 'Constant pixel value')
hdu1.header.set('PIXVALUE', 2, 'Constant pixel value', after='GCOUNT')
hdu1.header.set('NAXIS', 2)
hdu1.header.set('NAXIS1', 10, 'length of constant array axis 1',
after='NAXIS')
hdu1.header.set('NAXIS2', 10, 'length of constant array axis 2',
after='NAXIS1')
hdul = stpyfits.HDUList([hdu, hdu1])
hdul.writeto(self.temp('new.fits'), clobber=True)
hdul = stpyfits.open(self.temp('new.fits'), 'update')
d = np.arange(10, dtype=np.int32)
d = d * 0
d = d + 3
hdul[0].data = d
hdul.flush()
hdul.close()
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (10,), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
hdul1 = stpyfits.open(self.temp('new.fits'))
hdul2 = fits.open(self.temp('new.fits'))
assert_equal(hdul1[0].header['NAXIS'], 1)
assert_equal(hdul1[0].header['NAXIS1'], 10)
assert_equal(hdul1[0].header['PIXVALUE'], 3)
assert_raises(KeyError, lambda: hdul1[0].header['NPIX1'])
assert_true((hdul1[0].data ==
(np.zeros(10, dtype=np.int32) + 3)).all())
assert_equal(hdul2[0].header['NAXIS'], 0)
assert_equal(hdul2[0].header['NPIX1'], 10)
assert_equal(hdul2[0].header['PIXVALUE'], 3)
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS1'])
assert_equal(hdul2[0].data, None)
hdul1.close()
hdul2.close()
hdul3 = stpyfits.open(self.temp('new.fits'), 'update')
d = np.arange(15, dtype=np.int32)
d = d * 0
d = d + 4
hdul3[0].data = d
hdul3.close() # Note that close calls flush
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (15,), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
hdul1 = stpyfits.open(self.temp('new.fits'))
hdul2 = fits.open(self.temp('new.fits'))
assert_equal(hdul1[0].header['NAXIS'], 1)
assert_equal(hdul1[0].header['NAXIS1'], 15)
assert_equal(hdul1[0].header['PIXVALUE'], 4)
assert_raises(KeyError, lambda: hdul1[0].header['NPIX1'])
assert_true((hdul1[0].data ==
(np.zeros(15, dtype=np.int32) + 4)).all())
assert_equal(hdul2[0].header['NAXIS'], 0)
assert_equal(hdul2[0].header['NPIX1'], 15)
assert_equal(hdul2[0].header['PIXVALUE'], 4)
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS1'])
assert_equal(hdul2[0].data, None)
hdul1.close()
hdul2.close()
def testHDUListWritetoMethod(self):
"""Test the writeto method of HDUList in both the fits and stpyfits
namespace."""
hdu = stpyfits.PrimaryHDU()
hdu1 = stpyfits.ImageHDU()
hdu.data = np.zeros((10, 10), dtype=np.int32)
hdu1.data = hdu.data + 2
hdu.header.set('BITPIX', 32)
hdu1.header.set('BITPIX', 32)
hdu.header.set('NAXIS', 2)
hdu.header.set('NAXIS1', 10, 'length of constant array axis 1',
after='NAXIS')
hdu.header.set('NAXIS2', 10, 'length of constant array axis 2',
after='NAXIS1')
hdu.header.set('PIXVALUE', 0, 'Constant pixel value')
hdu1.header.set('PIXVALUE', 2, 'Constant pixel value', after='GCOUNT')
hdu1.header.set('NAXIS', 2)
hdu1.header.set('NAXIS1', 10, 'length of constant array axis 1',
after='NAXIS')
hdu1.header.set('NAXIS2', 10, 'length of constant array axis 2',
after='NAXIS1')
hdul = stpyfits.HDUList([hdu,hdu1])
hdul.writeto(self.temp('new.fits'), clobber=True)
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (10, 10), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
hdul1 = stpyfits.open(self.temp('new.fits'))
hdul2 = fits.open(self.temp('new.fits'))
assert_equal(hdul1[0].header['NAXIS'], 2)
assert_equal(hdul1[0].header['NAXIS1'], 10)
assert_equal(hdul1[0].header['NAXIS2'], 10)
assert_equal(hdul1[0].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul1[0].header['NPIX1'])
assert_raises(KeyError, lambda: hdul1[0].header['NPIX2'])
assert_true((hdul1[0].data ==
np.zeros((10, 10), dtype=np.int32)).all())
assert_equal(hdul1[1].header['NAXIS'], 2)
assert_equal(hdul1[1].header['NAXIS1'], 10)
assert_equal(hdul1[1].header['NAXIS2'], 10)
assert_equal(hdul1[1].header['PIXVALUE'], 2)
assert_raises(KeyError, lambda: hdul1[1].header['NPIX1'])
assert_raises(KeyError, lambda: hdul1[1].header['NPIX2'])
assert_true((hdul1[1].data ==
(np.zeros((10, 10), dtype=np.int32) + 2)).all())
assert_equal(hdul2[0].header['NAXIS'], 0)
assert_equal(hdul2[0].header['NPIX1'], 10)
assert_equal(hdul2[0].header['NPIX2'], 10)
assert_equal(hdul2[0].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS1'])
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS2'])
assert_equal(hdul2[0].data, None)
assert_equal(hdul2[1].header['NAXIS'], 0)
assert_equal(hdul2[1].header['NPIX1'], 10)
assert_equal(hdul2[1].header['NPIX2'], 10)
assert_equal(hdul2[1].header['PIXVALUE'], 2)
assert_raises(KeyError, lambda: hdul2[1].header['NAXIS1'])
assert_raises(KeyError, lambda: hdul2[1].header['NAXIS2'])
hdul1.close()
hdul2.close()
def testupdateConvienceFunction(self):
"""Test the update convience function in both the fits and stpyfits
namespace."""
hdul = stpyfits.open(self.data('cdva2.fits'))
hdul1 = fits.open(self.data('cdva2.fits'))
header = hdul[0].header.copy()
header['NAXIS'] = 0
stpyfits.writeto(self.temp('new.fits'), hdul[0].data, header,
clobber=True)
hdu = stpyfits.ImageHDU()
hdu1 = fits.ImageHDU()
hdu.data = hdul[0].data
hdu1.data = hdul1[0].data
hdu.header.set('BITPIX', 32)
hdu1.header.set('BITPIX', 32)
hdu.header.set('NAXIS', 0)
hdu.header.set('PIXVALUE', 1, 'Constant pixel value', after='GCOUNT')
hdu1.header.set('PIXVALUE', 1, 'Constant pixel value', after='GCOUNT')
hdu.header.set('NPIX1', 10, 'length of constant array axis 1',
after='GCOUNT')
hdu.header.set('NPIX2', 10, 'length of constant array axis 2',
after='NPIX1')
stpyfits.append(self.temp('new.fits'), hdu.data, hdu.header)
d = hdu.data * 0
stpyfits.update(self.temp('new.fits'), d, hdu.header, 1)
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (10, 10), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
hdul7 = stpyfits.open(self.temp('new.fits'))
assert_equal(hdul7[1].header['NAXIS'], 2)
assert_equal(hdul7[1].header['NAXIS1'], 10)
assert_equal(hdul7[1].header['NAXIS2'], 10)
assert_equal(hdul7[1].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul7[1].header['NPIX1'])
assert_raises(KeyError, lambda: hdul7[1].header['NPIX2'])
assert_true((hdul7[1].data ==
np.zeros((10, 10), dtype=np.int32)).all())
hdul8 = fits.open(self.temp('new.fits'))
assert_equal(hdul8[1].header['NAXIS'], 0)
assert_equal(hdul8[1].header['NPIX1'], 10)
assert_equal(hdul8[1].header['NPIX2'], 10)
assert_equal(hdul8[1].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul8[1].header['NAXIS1'])
assert_raises(KeyError, lambda: hdul8[1].header['NAXIS2'])
assert_equal(hdul8[1].data, None)
hdul7.close()
hdul8.close()
hdul.close()
hdul1.close()
def testHDUListFlushMethod(self):
"""Test the flush method of HDUList in both the fits and stpyfits
namespace."""
hdu = stpyfits.PrimaryHDU()
hdu1 = stpyfits.ImageHDU()
hdu.data = np.zeros((10, 10), dtype=np.int32)
hdu1.data = hdu.data + 2
hdu.header.set('BITPIX', 32)
hdu1.header.set('BITPIX', 32)
hdu.header.set('NAXIS', 2)
hdu.header.set('NAXIS1',
10,
'length of constant array axis 1',
after='NAXIS')
hdu.header.set('NAXIS2',
10,
'length of constant array axis 2',
after='NAXIS1')
hdu.header.set('PIXVALUE', 0, 'Constant pixel value')
hdu1.header.set('PIXVALUE', 2, 'Constant pixel value', after='GCOUNT')
hdu1.header.set('NAXIS', 2)
hdu1.header.set('NAXIS1',
10,
'length of constant array axis 1',
after='NAXIS')
hdu1.header.set('NAXIS2',
10,
'length of constant array axis 2',
after='NAXIS1')
hdul = stpyfits.HDUList([hdu, hdu1])
hdul.writeto(self.temp('new.fits'), clobber=True)
hdul = stpyfits.open(self.temp('new.fits'), 'update')
d = np.arange(10, dtype=np.int32)
d = d * 0
d = d + 3
hdul[0].data = d
hdul.flush()
hdul.close()
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (10, ), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
hdul1 = stpyfits.open(self.temp('new.fits'))
hdul2 = fits.open(self.temp('new.fits'))
assert_equal(hdul1[0].header['NAXIS'], 1)
assert_equal(hdul1[0].header['NAXIS1'], 10)
assert_equal(hdul1[0].header['PIXVALUE'], 3)
assert_raises(KeyError, lambda: hdul1[0].header['NPIX1'])
assert_true(
(hdul1[0].data == (np.zeros(10, dtype=np.int32) + 3)).all())
assert_equal(hdul2[0].header['NAXIS'], 0)
assert_equal(hdul2[0].header['NPIX1'], 10)
assert_equal(hdul2[0].header['PIXVALUE'], 3)
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS1'])
assert_equal(hdul2[0].data, None)
hdul1.close()
hdul2.close()
hdul3 = stpyfits.open(self.temp('new.fits'), 'update')
d = np.arange(15, dtype=np.int32)
d = d * 0
d = d + 4
hdul3[0].data = d
hdul3.close() # Note that close calls flush
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (15, ), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 6, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
hdul1 = stpyfits.open(self.temp('new.fits'))
hdul2 = fits.open(self.temp('new.fits'))
assert_equal(hdul1[0].header['NAXIS'], 1)
assert_equal(hdul1[0].header['NAXIS1'], 15)
assert_equal(hdul1[0].header['PIXVALUE'], 4)
assert_raises(KeyError, lambda: hdul1[0].header['NPIX1'])
assert_true(
(hdul1[0].data == (np.zeros(15, dtype=np.int32) + 4)).all())
assert_equal(hdul2[0].header['NAXIS'], 0)
assert_equal(hdul2[0].header['NPIX1'], 15)
assert_equal(hdul2[0].header['PIXVALUE'], 4)
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS1'])
assert_equal(hdul2[0].data, None)
hdul1.close()
hdul2.close()
def testHDUListWritetoMethod(self):
"""Test the writeto method of HDUList in both the fits and stpyfits
namespace."""
hdu = stpyfits.PrimaryHDU()
hdu1 = stpyfits.ImageHDU()
hdu.data = np.zeros((10, 10), dtype=np.int32)
hdu1.data = hdu.data + 2
hdu.header.set('BITPIX', 32)
hdu1.header.set('BITPIX', 32)
hdu.header.set('NAXIS', 2)
hdu.header.set('NAXIS1',
10,
'length of constant array axis 1',
after='NAXIS')
hdu.header.set('NAXIS2',
10,
'length of constant array axis 2',
after='NAXIS1')
hdu.header.set('PIXVALUE', 0, 'Constant pixel value')
hdu1.header.set('PIXVALUE', 2, 'Constant pixel value', after='GCOUNT')
hdu1.header.set('NAXIS', 2)
hdu1.header.set('NAXIS1',
10,
'length of constant array axis 1',
after='NAXIS')
hdu1.header.set('NAXIS2',
10,
'length of constant array axis 2',
after='NAXIS1')
hdul = stpyfits.HDUList([hdu, hdu1])
hdul.writeto(self.temp('new.fits'), clobber=True)
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (10, 10), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
hdul1 = stpyfits.open(self.temp('new.fits'))
hdul2 = fits.open(self.temp('new.fits'))
assert_equal(hdul1[0].header['NAXIS'], 2)
assert_equal(hdul1[0].header['NAXIS1'], 10)
assert_equal(hdul1[0].header['NAXIS2'], 10)
assert_equal(hdul1[0].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul1[0].header['NPIX1'])
assert_raises(KeyError, lambda: hdul1[0].header['NPIX2'])
assert_true((hdul1[0].data == np.zeros((10, 10),
dtype=np.int32)).all())
assert_equal(hdul1[1].header['NAXIS'], 2)
assert_equal(hdul1[1].header['NAXIS1'], 10)
assert_equal(hdul1[1].header['NAXIS2'], 10)
assert_equal(hdul1[1].header['PIXVALUE'], 2)
assert_raises(KeyError, lambda: hdul1[1].header['NPIX1'])
assert_raises(KeyError, lambda: hdul1[1].header['NPIX2'])
assert_true((hdul1[1].data == (np.zeros(
(10, 10), dtype=np.int32) + 2)).all())
assert_equal(hdul2[0].header['NAXIS'], 0)
assert_equal(hdul2[0].header['NPIX1'], 10)
assert_equal(hdul2[0].header['NPIX2'], 10)
assert_equal(hdul2[0].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS1'])
assert_raises(KeyError, lambda: hdul2[0].header['NAXIS2'])
assert_equal(hdul2[0].data, None)
assert_equal(hdul2[1].header['NAXIS'], 0)
assert_equal(hdul2[1].header['NPIX1'], 10)
assert_equal(hdul2[1].header['NPIX2'], 10)
assert_equal(hdul2[1].header['PIXVALUE'], 2)
assert_raises(KeyError, lambda: hdul2[1].header['NAXIS1'])
assert_raises(KeyError, lambda: hdul2[1].header['NAXIS2'])
hdul1.close()
hdul2.close()
def testupdateConvienceFunction(self):
"""Test the update convience function in both the fits and stpyfits
namespace."""
hdul = stpyfits.open(self.data('cdva2.fits'))
hdul1 = fits.open(self.data('cdva2.fits'))
header = hdul[0].header.copy()
header['NAXIS'] = 0
stpyfits.writeto(self.temp('new.fits'),
hdul[0].data,
header,
clobber=True)
hdu = stpyfits.ImageHDU()
hdu1 = fits.ImageHDU()
hdu.data = hdul[0].data
hdu1.data = hdul1[0].data
hdu.header.set('BITPIX', 32)
hdu1.header.set('BITPIX', 32)
hdu.header.set('NAXIS', 0)
hdu.header.set('PIXVALUE', 1, 'Constant pixel value', after='GCOUNT')
hdu1.header.set('PIXVALUE', 1, 'Constant pixel value', after='GCOUNT')
hdu.header.set('NPIX1',
10,
'length of constant array axis 1',
after='GCOUNT')
hdu.header.set('NPIX2',
10,
'length of constant array axis 2',
after='NPIX1')
stpyfits.append(self.temp('new.fits'), hdu.data, hdu.header)
d = hdu.data * 0
stpyfits.update(self.temp('new.fits'), d, hdu.header, 1)
assert_equal(fits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (), '', ''),
(1, '', 'ImageHDU', 8, (), '', '')])
assert_equal(stpyfits.info(self.temp('new.fits'), output=False),
[(0, 'PRIMARY', 'PrimaryHDU', 7, (10, 10), 'int32', ''),
(1, '', 'ImageHDU', 8, (10, 10), 'int32', '')])
hdul7 = stpyfits.open(self.temp('new.fits'))
assert_equal(hdul7[1].header['NAXIS'], 2)
assert_equal(hdul7[1].header['NAXIS1'], 10)
assert_equal(hdul7[1].header['NAXIS2'], 10)
assert_equal(hdul7[1].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul7[1].header['NPIX1'])
assert_raises(KeyError, lambda: hdul7[1].header['NPIX2'])
assert_true((hdul7[1].data == np.zeros((10, 10),
dtype=np.int32)).all())
hdul8 = fits.open(self.temp('new.fits'))
assert_equal(hdul8[1].header['NAXIS'], 0)
assert_equal(hdul8[1].header['NPIX1'], 10)
assert_equal(hdul8[1].header['NPIX2'], 10)
assert_equal(hdul8[1].header['PIXVALUE'], 0)
assert_raises(KeyError, lambda: hdul8[1].header['NAXIS1'])
assert_raises(KeyError, lambda: hdul8[1].header['NAXIS2'])
assert_equal(hdul8[1].data, None)
hdul7.close()
hdul8.close()
hdul.close()
hdul1.close()
