Fix astropy tests

[astrofrog]

This fixes three of the four failing tests - the last one is:

    def test_comp_image_hcompress_image_stack(self):
        """
        Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/171

        Tests that data containing more than two dimensions can be
        compressed with HCOMPRESS_1 so long as the user-supplied tile size can
        be flattened to two dimensions.
        """

        cube = np.arange(300, dtype=np.float32).reshape(3, 10, 10)
        hdu = fits.CompImageHDU(
            data=cube,
            name="SCI",
            compression_type="HCOMPRESS_1",
            quantize_level=16,
            tile_size=[5, 5, 1],
        )
        hdu.writeto(self.temp("test.fits"))

        with fits.open(self.temp("test.fits")) as hdul:
            # HCOMPRESSed images are allowed to deviate from the original by
            # about 1/quantize_level of the RMS in each tile.
>           assert np.abs(hdul["SCI"].data - cube).max() < 1.0 / 15.0
E           AssertionError: assert 0.12690735 < (1.0 / 15.0)
E            +  where 0.12690735 = <built-in method max of numpy.ndarray object at 0x11054c390>()
E            +    where <built-in method max of numpy.ndarray object at 0x11054c390> = array([[[0.        , 0.04835784, 0.03432894, 0.01402903, 0.06238699,\n         0.02029991, 0.10298681, 0.07641602, 0.00...7, 0.01602173, 0.06439209,\n         0.11276245, 0.03005981, 0.07843018, 0.00427246, 0.0440979 ]]],\n      dtype=float32).max
E            +      where array([[[0.        , 0.04835784, 0.03432894, 0.01402903, 0.06238699,\n         0.02029991, 0.10298681, 0.07641602, 0.00...7, 0.01602173, 0.06439209,\n         0.11276245, 0.03005981, 0.07843018, 0.00427246, 0.0440979 ]]],\n      dtype=float32) = <ufunc 'absolute'>((array([[[  0.       ,   1.0483578,   1.9656711,   3.014029 ,\n           4.062387 ,   4.9797   ,   5.897013 ,   7.07641...02  ,\n         294.0644   , 295.11276  , 296.03006  , 297.07843  ,\n         297.99573  , 299.0441   ]]], dtype=float32) - array([[[  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.],\n        [ 10.,  11.,  12.,  13.,  14.,  15.,  16..., 286., 287., 288., 289.],\n        [290., 291., 292., 293., 294., 295., 296., 297., 298., 299.]]],\n      dtype=float32)))
E            +        where <ufunc 'absolute'> = np.abs
E            +        and   array([[[  0.       ,   1.0483578,   1.9656711,   3.014029 ,\n           4.062387 ,   4.9797   ,   5.897013 ,   7.07641...02  ,\n         294.0644   , 295.11276  , 296.03006  , 297.07843  ,\n         297.99573  , 299.0441   ]]], dtype=float32) = <astropy.io.fits.hdu.compressed.CompImageHDU object at 0x168aaa800>.data

I'll need to check at the C level what the HCOMPRESS and quantization functions are getting called with to see if any of the parameters differ.