python-pyfits 1:3.2-1build2 / usr / lib / python2.7 / dist-packages / pyfits / tests / test_checksum.py

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from __future__ import division, with_statement  # confidence high

import warnings

import numpy as np

import pyfits as fits
from pyfits.tests import PyfitsTestCase


class TestChecksumFunctions(PyfitsTestCase):

    def setup(self):
        super(TestChecksumFunctions, self).setup()
        self._oldfilters = warnings.filters[:]
        warnings.filterwarnings(
            'error',
            message='Checksum verification failed')
        warnings.filterwarnings(
            'error',
            message='Datasum verification failed')

    def teardown(self):
        super(TestChecksumFunctions, self).teardown()
        warnings.filters = self._oldfilters

    def test_sample_file(self):
        hdul = fits.open(self.data('checksum.fits'), checksum=True)
        hdul.close()

    def test_image_create(self):
        n = np.arange(100)
        hdu = fits.PrimaryHDU(n)
        hdu.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul.close()

    def test_nonstandard_checksum(self):
        hdu = fits.PrimaryHDU(np.arange(10.0 ** 6))
        hdu.writeto(self.temp('tmp.fits'), clobber=True,
                    checksum='nonstandard')
        del hdu
        hdul = fits.open(self.temp('tmp.fits'), checksum='nonstandard')

    def test_scaled_data(self):
        hdul = fits.open(self.data('scale.fits'))
        orig_data = hdul[0].data.copy()
        hdul[0].scale('int16', 'old')
        hdul.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul1 = fits.open(self.temp('tmp.fits'), checksum=True)
        assert (hdul1[0].data == orig_data).all()
        hdul.close()
        hdul1.close()

    def test_uint16_data(self):
        hdul = fits.open(self.data('o4sp040b0_raw.fits'), uint=True)
        hdul.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul1 = fits.open(self.temp('tmp.fits'), uint=True, checksum=True)
        hdul.close()
        hdul1.close()

    def test_groups_hdu_data(self):
        imdata = np.arange(100.0)
        imdata.shape = (10, 1, 1, 2, 5)
        pdata1 = np.arange(10) + 0.1
        pdata2 = 42
        x = fits.hdu.groups.GroupData(imdata, parnames=['abc', 'xyz'],
                                      pardata=[pdata1, pdata2], bitpix=-32)
        hdu = fits.GroupsHDU(x)
        hdu.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul1 = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul1.close()

    def test_binary_table_data(self):
        a1 = np.array(['NGC1001', 'NGC1002', 'NGC1003'])
        a2 = np.array([11.1, 12.3, 15.2])
        col1 = fits.Column(name='target', format='20A', array=a1)
        col2 = fits.Column(name='V_mag', format='E', array=a2)
        cols = fits.ColDefs([col1, col2])
        tbhdu = fits.new_table(cols)
        tbhdu.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul.close()

    def test_variable_length_table_data(self):
        c1 = fits.Column(name='var', format='PJ()',
                         array=np.array([[45.0, 56], np.array([11, 12, 13])], 'O'))
        c2 = fits.Column(name='xyz', format='2I', array=[[11, 3], [12, 4]])
        tbhdu = fits.new_table([c1, c2])
        tbhdu.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul.close()

    def test_ascii_table_data(self):
        a1 = np.array(['abc', 'def'])
        r1 = np.array([11.0, 12.0])
        c1 = fits.Column(name='abc', format='A3', array=a1)
        c2 = fits.Column(name='def', format='E', array=r1, bscale=2.3,
                         bzero=0.6)
        c3 = fits.Column(name='t1', format='I', array=[91, 92, 93])
        x = fits.ColDefs([c1, c2, c3], tbtype='TableHDU')
        hdu = fits.new_table(x, tbtype='TableHDU')
        hdu.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul.close()

    def test_compressed_image_data(self):
        hdul = fits.open(self.data('comp.fits'))
        hdul.writeto(self.temp('tmp.fits'), clobber=True, checksum=True)
        hdul1 = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul1.close()
        hdul.close()

    def test_compressed_image_data_int16(self):
        n = np.arange(100, dtype='int16')
        hdu = fits.ImageHDU(n)
        comp_hdu = fits.CompImageHDU(hdu.data, hdu.header)
        comp_hdu.writeto(self.temp('tmp.fits'), checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul.close()

    def test_compressed_image_data_float32(self):
        n = np.arange(100, dtype='float32')
        comp_hdu = fits.CompImageHDU(n)
        comp_hdu.writeto(self.temp('tmp.fits'), checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)
        hdul.close()

    def test_open_with_no_keywords(self):
        hdul = fits.open(self.data('arange.fits'), checksum=True)
        hdul.close()

    def test_append(self):
        hdul = fits.open(self.data('tb.fits'))
        hdul.writeto(self.temp('tmp.fits'), clobber=True)
        n = np.arange(100)
        fits.append(self.temp('tmp.fits'), n, checksum=True)
        hdul.close()
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)
        assert hdul[0]._checksum is None
        hdul.close()

    def test_writeto_convenience(self):
        n = np.arange(100)
        fits.writeto(self.temp('tmp.fits'), n, clobber=True, checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)

        assert hasattr(hdul[0], '_datasum') and hdul[0]._datasum

        assert hasattr(hdul[0], '_checksum') and hdul[0]._checksum

        assert (hasattr(hdul[0], '_datasum_comment') and
                hdul[0]._datasum_comment)

        assert (hasattr(hdul[0], '_checksum_comment') and
                hdul[0]._checksum_comment)

        hdul.close()

    def test_hdu_writeto(self):
        n = np.arange(100, dtype='int16')
        hdu = fits.ImageHDU(n)
        hdu.writeto(self.temp('tmp.fits'), checksum=True)
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)

        assert hasattr(hdul[0], '_datasum') and hdul[0]._datasum

        assert hasattr(hdul[0], '_checksum') and hdul[0]._checksum

        assert (hasattr(hdul[0], '_datasum_comment') and
                hdul[0]._datasum_comment)

        assert (hasattr(hdul[0], '_checksum_comment') and
                hdul[0]._checksum_comment)

        hdul.close()

    def test_datasum_only(self):
        n = np.arange(100, dtype='int16')
        hdu = fits.ImageHDU(n)
        hdu.writeto(self.temp('tmp.fits'), clobber=True, checksum='datasum')
        hdul = fits.open(self.temp('tmp.fits'), checksum=True)

        assert hasattr(hdul[0], '_datasum') and hdul[0]._datasum

        assert hasattr(hdul[0], '_checksum') and not hdul[0]._checksum

        assert (hasattr(hdul[0], '_datasum_comment') and
                hdul[0]._datasum_comment)

        assert (hasattr(hdul[0], '_checksum_comment') and
                not hdul[0]._checksum_comment)

        hdul.close()

    def test_open_update_mode_preserve_checksum(self):
        """
        Regression test for https://trac.assembla.com/pyfits/ticket/148 where
        checksums are being removed from headers when a file is opened in
        update mode, even though no changes were made to the file.
        """

        self.copy_file('checksum.fits')

        with fits.open(self.temp('checksum.fits')) as hdul:
            data = hdul[1].data.copy()

        hdul = fits.open(self.temp('checksum.fits'), mode='update')
        hdul.close()

        with fits.open(self.temp('checksum.fits')) as hdul:
            assert 'CHECKSUM' in hdul[1].header
            assert 'DATASUM' in hdul[1].header
            assert (data == hdul[1].data).all()

    def test_open_update_mode_update_checksum(self):
        """
        Regression test for https://trac.assembla.com/pyfits/ticket/148, part
        2.  This ensures that if a file contains a checksum, the checksum is
        updated when changes are saved to the file, even if the file was opened
        with the default of checksum=False.

        An existing checksum and/or datasum are only stripped if the file is
        opened with checksum='remove'.
        """

        self.copy_file('checksum.fits')
        with fits.open(self.temp('checksum.fits')) as hdul:
            header = hdul[1].header.copy()
            data = hdul[1].data.copy()

        with fits.open(self.temp('checksum.fits'), mode='update') as hdul:
            hdul[1].header['FOO'] = 'BAR'
            hdul[1].data[0]['TIME'] = 42

        with fits.open(self.temp('checksum.fits')) as hdul:
            header2 = hdul[1].header
            data2 = hdul[1].data
            assert header2[:-3] == header[:-2]
            assert 'CHECKSUM' in header2
            assert 'DATASUM' in header2
            assert header2['FOO'] == 'BAR'
            assert (data2['TIME'][1:] == data['TIME'][1:]).all()
            assert data2['TIME'][0] == 42

        with fits.open(self.temp('checksum.fits'), mode='update',
                       checksum='remove') as hdul:
            pass

        with fits.open(self.temp('checksum.fits')) as hdul:
            header2 = hdul[1].header
            data2 = hdul[1].data
            assert header2[:-1] == header[:-2]
            assert 'CHECKSUM' not in header2
            assert 'DATASUM' not in header2
            assert header2['FOO'] == 'BAR'
            assert (data2['TIME'][1:] == data['TIME'][1:]).all()
            assert data2['TIME'][0] == 42

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