# Licensed under a 3-clause BSD style license - see LICENSE.rst # This module implements the base CCDData class. from __future__ import (absolute_import, division, print_function, unicode_literals) import textwrap import numpy as np import pytest from ...extern import six from ...io import fits from ..nduncertainty import StdDevUncertainty, MissingDataAssociationException from ... import units as u from ... import log from ...wcs import WCS, FITSFixedWarning from ...tests.helper import catch_warnings from ...utils import NumpyRNGContext from ...utils.data import (get_pkg_data_filename, get_pkg_data_filenames, get_pkg_data_contents) from ..ccddata import CCDData from astropy.table import Table # If additional pytest markers are defined the key in the dictionary below # should be the name of the marker. DEFAULTS = { 'seed': 123, 'data_size': 100, 'data_scale': 1.0, 'data_mean': 0.0 } DEFAULT_SEED = 123 DEFAULT_DATA_SIZE = 100 DEFAULT_DATA_SCALE = 1.0 def value_from_markers(key, request): try: val = request.keywords[key].args[0] except KeyError: val = DEFAULTS[key] return val @pytest.fixture def ccd_data(request): """ Return a CCDData object with units of ADU. The size of the data array is 100x100 but can be changed using the marker @pytest.mark.data_size(N) on the test function, where N should be the desired dimension. Data values are initialized to random numbers drawn from a normal distribution with mean of 0 and scale 1. The scale can be changed with the marker @pytest.marker.scale(s) on the test function, where s is the desired scale. The mean can be changed with the marker @pytest.marker.scale(m) on the test function, where m is the desired mean. """ size = value_from_markers('data_size', request) scale = value_from_markers('data_scale', request) mean = value_from_markers('data_mean', request) with NumpyRNGContext(DEFAULTS['seed']): data = np.random.normal(loc=mean, size=[size, size], scale=scale) fake_meta = {'my_key': 42, 'your_key': 'not 42'} ccd = CCDData(data, unit=u.adu) ccd.header = fake_meta return ccd def test_ccddata_empty(): with pytest.raises(TypeError): CCDData() # empty initializer should fail def test_ccddata_must_have_unit(): with pytest.raises(ValueError): CCDData(np.zeros([100, 100])) def test_ccddata_unit_cannot_be_set_to_none(ccd_data): with pytest.raises(TypeError): ccd_data.unit = None def test_ccddata_meta_header_conflict(): with pytest.raises(ValueError) as exc: CCDData([1, 2, 3], unit='', meta={1: 1}, header={2: 2}) assert "can't have both header and meta." in str(exc) @pytest.mark.data_size(10) def test_ccddata_simple(ccd_data): assert ccd_data.shape == (10, 10) assert ccd_data.size == 100 assert ccd_data.dtype == np.dtype(float) def test_ccddata_init_with_string_electron_unit(): ccd = CCDData(np.zeros((10, 10)), unit="electron") assert ccd.unit is u.electron @pytest.mark.data_size(10) def test_initialize_from_FITS(ccd_data, tmpdir): hdu = fits.PrimaryHDU(ccd_data) hdulist = fits.HDUList([hdu]) filename = tmpdir.join('afile.fits').strpath hdulist.writeto(filename) cd = CCDData.read(filename, unit=u.electron) assert cd.shape == (10, 10) assert cd.size == 100 assert np.issubdtype(cd.data.dtype, np.floating) for k, v in hdu.header.items(): assert cd.meta[k] == v def test_initialize_from_fits_with_unit_in_header(tmpdir): fake_img = np.random.random(size=(100, 100)) hdu = fits.PrimaryHDU(fake_img) hdu.header['bunit'] = u.adu.to_string() filename = tmpdir.join('afile.fits').strpath hdu.writeto(filename) ccd = CCDData.read(filename) # ccd should pick up the unit adu from the fits header...did it? assert ccd.unit is u.adu # An explicit unit in the read overrides any unit in the FITS file ccd2 = CCDData.read(filename, unit="photon") assert ccd2.unit is u.photon def test_initialize_from_fits_with_ADU_in_header(tmpdir): fake_img = np.random.random(size=(100, 100)) hdu = fits.PrimaryHDU(fake_img) hdu.header['bunit'] = 'ADU' filename = tmpdir.join('afile.fits').strpath hdu.writeto(filename) ccd = CCDData.read(filename) # ccd should pick up the unit adu from the fits header...did it? assert ccd.unit is u.adu def test_initialize_from_fits_with_invalid_unit_in_header(tmpdir): hdu = fits.PrimaryHDU(np.ones((2, 2))) hdu.header['bunit'] = 'definetely-not-a-unit' filename = tmpdir.join('afile.fits').strpath hdu.writeto(filename) with pytest.raises(ValueError): CCDData.read(filename) def test_initialize_from_fits_with_data_in_different_extension(tmpdir): fake_img = np.random.random(size=(100, 100)) hdu1 = fits.PrimaryHDU() hdu2 = fits.ImageHDU(fake_img) hdus = fits.HDUList([hdu1, hdu2]) filename = tmpdir.join('afile.fits').strpath hdus.writeto(filename) with catch_warnings(FITSFixedWarning) as w: ccd = CCDData.read(filename, unit='adu') assert len(w) == 0 # ccd should pick up the unit adu from the fits header...did it? np.testing.assert_array_equal(ccd.data, fake_img) # check that the header is the combined header assert hdu2.header + hdu1.header == ccd.header def test_initialize_from_fits_with_extension(tmpdir): fake_img1 = np.random.random(size=(100, 100)) fake_img2 = np.random.random(size=(100, 100)) hdu0 = fits.PrimaryHDU() hdu1 = fits.ImageHDU(fake_img1) hdu2 = fits.ImageHDU(fake_img2) hdus = fits.HDUList([hdu0, hdu1, hdu2]) filename = tmpdir.join('afile.fits').strpath hdus.writeto(filename) ccd = CCDData.read(filename, hdu=2, unit='adu') # ccd should pick up the unit adu from the fits header...did it? np.testing.assert_array_equal(ccd.data, fake_img2) def test_write_unit_to_hdu(ccd_data, tmpdir): ccd_unit = ccd_data.unit hdulist = ccd_data.to_hdu() assert 'bunit' in hdulist[0].header assert hdulist[0].header['bunit'] == ccd_unit.to_string() def test_initialize_from_FITS_bad_keyword_raises_error(ccd_data, tmpdir): # There are two fits.open keywords that are not permitted in ccdproc: # do_not_scale_image_data and scale_back filename = tmpdir.join('test.fits').strpath ccd_data.write(filename) with pytest.raises(TypeError): CCDData.read(filename, unit=ccd_data.unit, do_not_scale_image_data=True) with pytest.raises(TypeError): CCDData.read(filename, unit=ccd_data.unit, scale_back=True) def test_ccddata_writer(ccd_data, tmpdir): filename = tmpdir.join('test.fits').strpath ccd_data.write(filename) ccd_disk = CCDData.read(filename, unit=ccd_data.unit) np.testing.assert_array_equal(ccd_data.data, ccd_disk.data) def test_ccddata_meta_is_case_sensitive(ccd_data): key = 'SoMeKEY' ccd_data.meta[key] = 10 assert key.lower() not in ccd_data.meta assert key.upper() not in ccd_data.meta assert key in ccd_data.meta def test_ccddata_meta_is_not_fits_header(ccd_data): ccd_data.meta = {'OBSERVER': 'Edwin Hubble'} assert not isinstance(ccd_data.meta, fits.Header) def test_fromMEF(ccd_data, tmpdir): hdu = fits.PrimaryHDU(ccd_data) hdu2 = fits.PrimaryHDU(2 * ccd_data.data) hdulist = fits.HDUList(hdu) hdulist.append(hdu2) filename = tmpdir.join('afile.fits').strpath hdulist.writeto(filename) # by default, we reading from the first extension cd = CCDData.read(filename, unit=u.electron) np.testing.assert_array_equal(cd.data, ccd_data.data) # but reading from the second should work too cd = CCDData.read(filename, hdu=1, unit=u.electron) np.testing.assert_array_equal(cd.data, 2 * ccd_data.data) def test_metafromheader(ccd_data): hdr = fits.header.Header() hdr['observer'] = 'Edwin Hubble' hdr['exptime'] = '3600' d1 = CCDData(np.ones((5, 5)), meta=hdr, unit=u.electron) assert d1.meta['OBSERVER'] == 'Edwin Hubble' assert d1.header['OBSERVER'] == 'Edwin Hubble' def test_metafromdict(): dic = {'OBSERVER': 'Edwin Hubble', 'EXPTIME': 3600} d1 = CCDData(np.ones((5, 5)), meta=dic, unit=u.electron) assert d1.meta['OBSERVER'] == 'Edwin Hubble' def test_header2meta(): hdr = fits.header.Header() hdr['observer'] = 'Edwin Hubble' hdr['exptime'] = '3600' d1 = CCDData(np.ones((5, 5)), unit=u.electron) d1.header = hdr assert d1.meta['OBSERVER'] == 'Edwin Hubble' assert d1.header['OBSERVER'] == 'Edwin Hubble' def test_metafromstring_fail(): hdr = 'this is not a valid header' with pytest.raises(TypeError): CCDData(np.ones((5, 5)), meta=hdr, unit=u.adu) def test_setting_bad_uncertainty_raises_error(ccd_data): with pytest.raises(TypeError): # Uncertainty is supposed to be an instance of NDUncertainty ccd_data.uncertainty = 10 def test_setting_uncertainty_with_array(ccd_data): ccd_data.uncertainty = None fake_uncertainty = np.sqrt(np.abs(ccd_data.data)) ccd_data.uncertainty = fake_uncertainty.copy() np.testing.assert_array_equal(ccd_data.uncertainty.array, fake_uncertainty) def test_setting_uncertainty_wrong_shape_raises_error(ccd_data): with pytest.raises(ValueError): ccd_data.uncertainty = np.random.random(size=(3, 4)) def test_to_hdu(ccd_data): ccd_data.meta = {'observer': 'Edwin Hubble'} fits_hdulist = ccd_data.to_hdu() assert isinstance(fits_hdulist, fits.HDUList) for k, v in ccd_data.meta.items(): assert fits_hdulist[0].header[k] == v np.testing.assert_array_equal(fits_hdulist[0].data, ccd_data.data) def test_copy(ccd_data): ccd_copy = ccd_data.copy() np.testing.assert_array_equal(ccd_copy.data, ccd_data.data) assert ccd_copy.unit == ccd_data.unit assert ccd_copy.meta == ccd_data.meta @pytest.mark.parametrize('operation,affects_uncertainty', [ ("multiply", True), ("divide", True), ]) @pytest.mark.parametrize('operand', [ 2.0, 2 * u.dimensionless_unscaled, 2 * u.photon / u.adu, ]) @pytest.mark.parametrize('with_uncertainty', [ True, False]) @pytest.mark.data_unit(u.adu) def test_mult_div_overload(ccd_data, operand, with_uncertainty, operation, affects_uncertainty): if with_uncertainty: ccd_data.uncertainty = StdDevUncertainty(np.ones_like(ccd_data)) method = ccd_data.__getattribute__(operation) np_method = np.__getattribute__(operation) result = method(operand) assert result is not ccd_data assert isinstance(result, CCDData) assert (result.uncertainty is None or isinstance(result.uncertainty, StdDevUncertainty)) try: op_value = operand.value except AttributeError: op_value = operand np.testing.assert_array_equal(result.data, np_method(ccd_data.data, op_value)) if with_uncertainty: if affects_uncertainty: np.testing.assert_array_equal(result.uncertainty.array, np_method(ccd_data.uncertainty.array, op_value)) else: np.testing.assert_array_equal(result.uncertainty.array, ccd_data.uncertainty.array) else: assert result.uncertainty is None if isinstance(operand, u.Quantity): # Need the "1 *" below to force arguments to be Quantity to work around # astropy/astropy#2377 expected_unit = np_method(1 * ccd_data.unit, 1 * operand.unit).unit assert result.unit == expected_unit else: assert result.unit == ccd_data.unit @pytest.mark.parametrize('operation,affects_uncertainty', [ ("add", False), ("subtract", False), ]) @pytest.mark.parametrize('operand,expect_failure', [ (2.0, u.UnitsError), # fail--units don't match image (2 * u.dimensionless_unscaled, u.UnitsError), # same (2 * u.adu, False), ]) @pytest.mark.parametrize('with_uncertainty', [ True, False]) @pytest.mark.data_unit(u.adu) def test_add_sub_overload(ccd_data, operand, expect_failure, with_uncertainty, operation, affects_uncertainty): if with_uncertainty: ccd_data.uncertainty = StdDevUncertainty(np.ones_like(ccd_data)) method = ccd_data.__getattribute__(operation) np_method = np.__getattribute__(operation) if expect_failure: with pytest.raises(expect_failure): result = method(operand) return else: result = method(operand) assert result is not ccd_data assert isinstance(result, CCDData) assert (result.uncertainty is None or isinstance(result.uncertainty, StdDevUncertainty)) try: op_value = operand.value except AttributeError: op_value = operand np.testing.assert_array_equal(result.data, np_method(ccd_data.data, op_value)) if with_uncertainty: if affects_uncertainty: np.testing.assert_array_equal(result.uncertainty.array, np_method(ccd_data.uncertainty.array, op_value)) else: np.testing.assert_array_equal(result.uncertainty.array, ccd_data.uncertainty.array) else: assert result.uncertainty is None if isinstance(operand, u.Quantity): assert (result.unit == ccd_data.unit and result.unit == operand.unit) else: assert result.unit == ccd_data.unit def test_arithmetic_overload_fails(ccd_data): with pytest.raises(TypeError): ccd_data.multiply("five") with pytest.raises(TypeError): ccd_data.divide("five") with pytest.raises(TypeError): ccd_data.add("five") with pytest.raises(TypeError): ccd_data.subtract("five") def test_arithmetic_no_wcs_compare(): ccd = CCDData(np.ones((10, 10)), unit='') assert ccd.add(ccd, compare_wcs=None).wcs is None assert ccd.subtract(ccd, compare_wcs=None).wcs is None assert ccd.multiply(ccd, compare_wcs=None).wcs is None assert ccd.divide(ccd, compare_wcs=None).wcs is None def test_arithmetic_with_wcs_compare(): def return_diff_smaller_3(first, second): return abs(first - second) <= 3 ccd1 = CCDData(np.ones((10, 10)), unit='', wcs=2) ccd2 = CCDData(np.ones((10, 10)), unit='', wcs=5) assert ccd1.add(ccd2, compare_wcs=return_diff_smaller_3).wcs == 2 assert ccd1.subtract(ccd2, compare_wcs=return_diff_smaller_3).wcs == 2 assert ccd1.multiply(ccd2, compare_wcs=return_diff_smaller_3).wcs == 2 assert ccd1.divide(ccd2, compare_wcs=return_diff_smaller_3).wcs == 2 def test_arithmetic_with_wcs_compare_fail(): def return_diff_smaller_1(first, second): return abs(first - second) <= 1 ccd1 = CCDData(np.ones((10, 10)), unit='', wcs=2) ccd2 = CCDData(np.ones((10, 10)), unit='', wcs=5) with pytest.raises(ValueError): ccd1.add(ccd2, compare_wcs=return_diff_smaller_1).wcs with pytest.raises(ValueError): ccd1.subtract(ccd2, compare_wcs=return_diff_smaller_1).wcs with pytest.raises(ValueError): ccd1.multiply(ccd2, compare_wcs=return_diff_smaller_1).wcs with pytest.raises(ValueError): ccd1.divide(ccd2, compare_wcs=return_diff_smaller_1).wcs def test_arithmetic_overload_ccddata_operand(ccd_data): ccd_data.uncertainty = StdDevUncertainty(np.ones_like(ccd_data)) operand = ccd_data.copy() result = ccd_data.add(operand) assert len(result.meta) == 0 np.testing.assert_array_equal(result.data, 2 * ccd_data.data) np.testing.assert_array_equal(result.uncertainty.array, np.sqrt(2) * ccd_data.uncertainty.array) result = ccd_data.subtract(operand) assert len(result.meta) == 0 np.testing.assert_array_equal(result.data, 0 * ccd_data.data) np.testing.assert_array_equal(result.uncertainty.array, np.sqrt(2) * ccd_data.uncertainty.array) result = ccd_data.multiply(operand) assert len(result.meta) == 0 np.testing.assert_array_equal(result.data, ccd_data.data ** 2) expected_uncertainty = (np.sqrt(2) * np.abs(ccd_data.data) * ccd_data.uncertainty.array) np.testing.assert_allclose(result.uncertainty.array, expected_uncertainty) result = ccd_data.divide(operand) assert len(result.meta) == 0 np.testing.assert_array_equal(result.data, np.ones_like(ccd_data.data)) expected_uncertainty = (np.sqrt(2) / np.abs(ccd_data.data) * ccd_data.uncertainty.array) np.testing.assert_allclose(result.uncertainty.array, expected_uncertainty) def test_arithmetic_overload_differing_units(): a = np.array([1, 2, 3]) * u.m b = np.array([1, 2, 3]) * u.cm ccddata = CCDData(a) # TODO: Could also be parametrized. res = ccddata.add(b) np.testing.assert_array_almost_equal(res.data, np.add(a, b).value) assert res.unit == np.add(a, b).unit res = ccddata.subtract(b) np.testing.assert_array_almost_equal(res.data, np.subtract(a, b).value) assert res.unit == np.subtract(a, b).unit res = ccddata.multiply(b) np.testing.assert_array_almost_equal(res.data, np.multiply(a, b).value) assert res.unit == np.multiply(a, b).unit res = ccddata.divide(b) np.testing.assert_array_almost_equal(res.data, np.divide(a, b).value) assert res.unit == np.divide(a, b).unit def test_arithmetic_add_with_array(): ccd = CCDData(np.ones((3, 3)), unit='') res = ccd.add(np.arange(3)) np.testing.assert_array_equal(res.data, [[1, 2, 3]] * 3) ccd = CCDData(np.ones((3, 3)), unit='adu') with pytest.raises(ValueError): ccd.add(np.arange(3)) def test_arithmetic_subtract_with_array(): ccd = CCDData(np.ones((3, 3)), unit='') res = ccd.subtract(np.arange(3)) np.testing.assert_array_equal(res.data, [[1, 0, -1]] * 3) ccd = CCDData(np.ones((3, 3)), unit='adu') with pytest.raises(ValueError): ccd.subtract(np.arange(3)) def test_arithmetic_multiply_with_array(): ccd = CCDData(np.ones((3, 3)) * 3, unit=u.m) res = ccd.multiply(np.ones((3, 3)) * 2) np.testing.assert_array_equal(res.data, [[6, 6, 6]] * 3) assert res.unit == ccd.unit def test_arithmetic_divide_with_array(): ccd = CCDData(np.ones((3, 3)), unit=u.m) res = ccd.divide(np.ones((3, 3)) * 2) np.testing.assert_array_equal(res.data, [[0.5, 0.5, 0.5]] * 3) assert res.unit == ccd.unit def test_history_preserved_if_metadata_is_fits_header(tmpdir): fake_img = np.random.random(size=(100, 100)) hdu = fits.PrimaryHDU(fake_img) hdu.header['history'] = 'one' hdu.header['history'] = 'two' hdu.header['history'] = 'three' assert len(hdu.header['history']) == 3 tmp_file = tmpdir.join('temp.fits').strpath hdu.writeto(tmp_file) ccd_read = CCDData.read(tmp_file, unit="adu") assert ccd_read.header['history'] == hdu.header['history'] def test_infol_logged_if_unit_in_fits_header(ccd_data, tmpdir): tmpfile = tmpdir.join('temp.fits') ccd_data.write(tmpfile.strpath) log.setLevel('INFO') explicit_unit_name = "photon" with log.log_to_list() as log_list: ccd_from_disk = CCDData.read(tmpfile.strpath, unit=explicit_unit_name) assert explicit_unit_name in log_list[0].message def test_wcs_attribute(ccd_data, tmpdir): """ Check that WCS attribute gets added to header, and that if a CCDData object is created from a FITS file with a header, and the WCS attribute is modified, then the CCDData object is turned back into an hdu, the WCS object overwrites the old WCS information in the header. """ tmpfile = tmpdir.join('temp.fits') # This wcs example is taken from the astropy.wcs docs. wcs = WCS(naxis=2) wcs.wcs.crpix = np.array(ccd_data.shape) / 2 wcs.wcs.cdelt = np.array([-0.066667, 0.066667]) wcs.wcs.crval = [0, -90] wcs.wcs.ctype = ["RA---AIR", "DEC--AIR"] wcs.wcs.set_pv([(2, 1, 45.0)]) ccd_data.header = ccd_data.to_hdu()[0].header ccd_data.header.extend(wcs.to_header(), useblanks=False) ccd_data.write(tmpfile.strpath) # Get the header length after it has been extended by the WCS keywords original_header_length = len(ccd_data.header) ccd_new = CCDData.read(tmpfile.strpath) # WCS attribute should be set for ccd_new assert ccd_new.wcs is not None # WCS attribute should be equal to wcs above. assert ccd_new.wcs.wcs == wcs.wcs # Converting CCDData object with wcs to an hdu shouldn't # create duplicate wcs-related entries in the header. ccd_new_hdu = ccd_new.to_hdu()[0] assert len(ccd_new_hdu.header) == original_header_length # Making a CCDData with WCS (but not WCS in the header) should lead to # WCS information in the header when it is converted to an HDU. ccd_wcs_not_in_header = CCDData(ccd_data.data, wcs=wcs, unit="adu") hdu = ccd_wcs_not_in_header.to_hdu()[0] wcs_header = wcs.to_header() for k in wcs_header.keys(): # Skip these keywords if they are in the WCS header because they are # not WCS-specific. if k in ['', 'COMMENT', 'HISTORY']: continue # No keyword from the WCS should be in the header. assert k not in ccd_wcs_not_in_header.header # Every keyword in the WCS should be in the header of the HDU assert hdu.header[k] == wcs_header[k] # Now check that if WCS of a CCDData is modified, then the CCDData is # converted to an HDU, the WCS keywords in the header are overwritten # with the appropriate keywords from the header. # # ccd_new has a WCS and WCS keywords in the header, so try modifying # the WCS. ccd_new.wcs.wcs.cdelt *= 2 ccd_new_hdu_mod_wcs = ccd_new.to_hdu()[0] assert ccd_new_hdu_mod_wcs.header['CDELT1'] == ccd_new.wcs.wcs.cdelt[0] assert ccd_new_hdu_mod_wcs.header['CDELT2'] == ccd_new.wcs.wcs.cdelt[1] def test_wcs_keywords_removed_from_header(): """ Test, for the file included with the nddata tests, that WCS keywords are properly removed from header. """ from ..ccddata import _KEEP_THESE_KEYWORDS_IN_HEADER keepers = set(_KEEP_THESE_KEYWORDS_IN_HEADER) data_file = get_pkg_data_filename('data/sip-wcs.fits') ccd = CCDData.read(data_file) wcs_header = ccd.wcs.to_header() assert not (set(wcs_header) & set(ccd.meta) - keepers) # Make sure that exceptions are not raised when trying to remove missing # keywords. o4sp040b0_raw.fits of io.fits is missing keyword 'PC1_1'. data_file1 = get_pkg_data_filename('../../io/fits/tests/data/o4sp040b0_raw.fits') ccd = CCDData.read(data_file1, unit='count') def test_wcs_keyword_removal_for_wcs_test_files(): """ Test, for the WCS test files, that keyword removall works as expected. Those cover a much broader range of WCS types than test_wcs_keywords_removed_from_header """ from ..ccddata import _generate_wcs_and_update_header from ..ccddata import _KEEP_THESE_KEYWORDS_IN_HEADER keepers = set(_KEEP_THESE_KEYWORDS_IN_HEADER) wcs_headers = get_pkg_data_filenames('../../wcs/tests/data', pattern='*.hdr') for hdr in wcs_headers: # Skip the files that are expected to be bad... if 'invalid' in hdr or 'nonstandard' in hdr or 'segfault' in hdr: continue header_string = get_pkg_data_contents(hdr) wcs = WCS(header_string) header = wcs.to_header(relax=True) new_header, new_wcs = _generate_wcs_and_update_header(header) # Make sure all of the WCS-related keywords have been removed. assert not (set(new_header) & set(new_wcs.to_header(relax=True)) - keepers) # Check that the new wcs is the same as the old. new_wcs_header = new_wcs.to_header(relax=True) for k, v in new_wcs_header.items(): if isinstance(v, six.string_types): assert header[k] == v else: np.testing.assert_almost_equal(header[k], v) def test_read_wcs_not_creatable(tmpdir): # The following Header can't be converted to a WCS object. See also #6499. hdr_txt_example_WCS = textwrap.dedent(''' SIMPLE = T / Fits standard BITPIX = 16 / Bits per pixel NAXIS = 2 / Number of axes NAXIS1 = 1104 / Axis length NAXIS2 = 4241 / Axis length CRVAL1 = 164.98110962 / Physical value of the reference pixel X CRVAL2 = 44.34089279 / Physical value of the reference pixel Y CRPIX1 = -34.0 / Reference pixel in X (pixel) CRPIX2 = 2041.0 / Reference pixel in Y (pixel) CDELT1 = 0.10380000 / X Scale projected on detector (#/pix) CDELT2 = 0.10380000 / Y Scale projected on detector (#/pix) CTYPE1 = 'RA---TAN' / Pixel coordinate system CTYPE2 = 'WAVELENGTH' / Pixel coordinate system CUNIT1 = 'degree ' / Units used in both CRVAL1 and CDELT1 CUNIT2 = 'nm ' / Units used in both CRVAL2 and CDELT2 CD1_1 = 0.20760000 / Pixel Coordinate translation matrix CD1_2 = 0.00000000 / Pixel Coordinate translation matrix CD2_1 = 0.00000000 / Pixel Coordinate translation matrix CD2_2 = 0.10380000 / Pixel Coordinate translation matrix C2YPE1 = 'RA---TAN' / Pixel coordinate system C2YPE2 = 'DEC--TAN' / Pixel coordinate system C2NIT1 = 'degree ' / Units used in both C2VAL1 and C2ELT1 C2NIT2 = 'degree ' / Units used in both C2VAL2 and C2ELT2 RADECSYS= 'FK5 ' / The equatorial coordinate system ''') with catch_warnings(FITSFixedWarning): hdr = fits.Header.fromstring(hdr_txt_example_WCS, sep='\n') hdul = fits.HDUList([fits.PrimaryHDU(np.ones((4241, 1104)), header=hdr)]) filename = tmpdir.join('afile.fits').strpath hdul.writeto(filename) # The hdr cannot be converted to a WCS object because of an # InconsistentAxisTypesError but it should still open the file ccd = CCDData.read(filename, unit='adu') assert ccd.wcs is None def test_header(ccd_data): a = {'Observer': 'Hubble'} ccd = CCDData(ccd_data, header=a) assert ccd.meta == a def test_wcs_arithmetic(ccd_data): ccd_data.wcs = 5 result = ccd_data.multiply(1.0) assert result.wcs == 5 @pytest.mark.parametrize('operation', ['multiply', 'divide', 'add', 'subtract']) def test_wcs_arithmetic_ccd(ccd_data, operation): ccd_data2 = ccd_data.copy() ccd_data.wcs = 5 method = ccd_data.__getattribute__(operation) result = method(ccd_data2) assert result.wcs == ccd_data.wcs assert ccd_data2.wcs is None def test_wcs_sip_handling(): """ Check whether the ctypes RA---TAN-SIP and DEC--TAN-SIP survive a roundtrip unchanged. """ data_file = get_pkg_data_filename('data/sip-wcs.fits') def check_wcs_ctypes(header): expected_wcs_ctypes = { 'CTYPE1': 'RA---TAN-SIP', 'CTYPE2': 'DEC--TAN-SIP' } return [header[k] == v for k, v in expected_wcs_ctypes.items()] ccd_original = CCDData.read(data_file) # After initialization the keywords should be in the WCS, not in the # meta. with fits.open(data_file) as raw: good_ctype = check_wcs_ctypes(raw[0].header) assert all(good_ctype) ccd_new = ccd_original.to_hdu() good_ctype = check_wcs_ctypes(ccd_new[0].header) assert all(good_ctype) # Try converting to header with wcs_relax=False and # the header should contain the CTYPE keywords without # the -SIP ccd_no_relax = ccd_original.to_hdu(wcs_relax=False) good_ctype = check_wcs_ctypes(ccd_no_relax[0].header) assert not any(good_ctype) assert ccd_no_relax[0].header['CTYPE1'] == 'RA---TAN' assert ccd_no_relax[0].header['CTYPE2'] == 'DEC--TAN' @pytest.mark.parametrize('operation', ['multiply', 'divide', 'add', 'subtract']) def test_mask_arithmetic_ccd(ccd_data, operation): ccd_data2 = ccd_data.copy() ccd_data.mask = (ccd_data.data > 0) method = ccd_data.__getattribute__(operation) result = method(ccd_data2) np.testing.assert_equal(result.mask, ccd_data.mask) def test_write_read_multiextensionfits_mask_default(ccd_data, tmpdir): # Test that if a mask is present the mask is saved and loaded by default. ccd_data.mask = ccd_data.data > 10 filename = tmpdir.join('afile.fits').strpath ccd_data.write(filename) ccd_after = CCDData.read(filename) assert ccd_after.mask is not None np.testing.assert_array_equal(ccd_data.mask, ccd_after.mask) def test_write_read_multiextensionfits_uncertainty_default(ccd_data, tmpdir): # Test that if a uncertainty is present it is saved and loaded by default. ccd_data.uncertainty = StdDevUncertainty(ccd_data.data * 10) filename = tmpdir.join('afile.fits').strpath ccd_data.write(filename) ccd_after = CCDData.read(filename) assert ccd_after.uncertainty is not None np.testing.assert_array_equal(ccd_data.uncertainty.array, ccd_after.uncertainty.array) def test_write_read_multiextensionfits_not(ccd_data, tmpdir): # Test that writing mask and uncertainty can be disabled ccd_data.mask = ccd_data.data > 10 ccd_data.uncertainty = StdDevUncertainty(ccd_data.data * 10) filename = tmpdir.join('afile.fits').strpath ccd_data.write(filename, hdu_mask=None, hdu_uncertainty=None) ccd_after = CCDData.read(filename) assert ccd_after.uncertainty is None assert ccd_after.mask is None def test_write_read_multiextensionfits_custom_ext_names(ccd_data, tmpdir): # Test writing mask, uncertainty in another extension than default ccd_data.mask = ccd_data.data > 10 ccd_data.uncertainty = StdDevUncertainty(ccd_data.data * 10) filename = tmpdir.join('afile.fits').strpath ccd_data.write(filename, hdu_mask='Fun', hdu_uncertainty='NoFun') # Try reading with defaults extension names ccd_after = CCDData.read(filename) assert ccd_after.uncertainty is None assert ccd_after.mask is None # Try reading with custom extension names ccd_after = CCDData.read(filename, hdu_mask='Fun', hdu_uncertainty='NoFun') assert ccd_after.uncertainty is not None assert ccd_after.mask is not None np.testing.assert_array_equal(ccd_data.mask, ccd_after.mask) np.testing.assert_array_equal(ccd_data.uncertainty.array, ccd_after.uncertainty.array) def test_wcs(ccd_data): ccd_data.wcs = 5 assert ccd_data.wcs == 5 def test_recognized_fits_formats_for_read_write(ccd_data, tmpdir): # These are the extensions that are supposed to be supported. supported_extensions = ['fit', 'fits', 'fts'] for ext in supported_extensions: path = tmpdir.join("test.{}".format(ext)) ccd_data.write(path.strpath) from_disk = CCDData.read(path.strpath) assert (ccd_data.data == from_disk.data).all() def test_stddevuncertainty_compat_descriptor_no_parent(): with pytest.raises(MissingDataAssociationException): StdDevUncertainty(np.ones((10, 10))).parent_nddata def test_stddevuncertainty_compat_descriptor_no_weakref(): # TODO: Remove this test if astropy 1.0 isn't supported anymore # This test might create a Memoryleak on purpose, so the last lines after # the assert are IMPORTANT cleanup. ccd = CCDData(np.ones((10, 10)), unit='') uncert = StdDevUncertainty(np.ones((10, 10))) uncert._parent_nddata = ccd assert uncert.parent_nddata is ccd uncert._parent_nddata = None # https://github.com/astropy/astropy/issues/7595 def test_read_returns_image(tmpdir): # Test if CCData.read returns a image when reading a fits file containing # a table and image, in that order. tbl = Table(np.ones(10).reshape(5, 2)) img = np.ones((5, 5)) hdul = fits.HDUList(hdus=[fits.PrimaryHDU(), fits.TableHDU(tbl.as_array()), fits.ImageHDU(img)]) filename = tmpdir.join('table_image.fits').strpath hdul.writeto(filename) ccd = CCDData.read(filename, unit='adu') # Expecting to get (5, 5), the size of the image assert ccd.data.shape == (5, 5)