def test_find_apertures_with_fake_data(seeing):
    """
    Creates a fake AD object with a gaussian profile in spacial direction with a
    fwhm defined by the seeing variable in arcsec. Then add some noise, and
    test if p.findAperture can find its position.
    """
    astrofaker = pytest.importorskip("astrofaker")

    gmos_fake_noise = 4  # adu
    gmos_plate_scale = 0.0807  # arcsec . px-1
    fwhm_to_stddev = 2 * np.sqrt(2 * np.log(2))

    ad = astrofaker.create('GMOS-S', mode='SPECT')
    ad.init_default_extensions()

    y0 = np.random.randint(low=100, high=ad[0].shape[0] - 100)
    fwhm = seeing / gmos_plate_scale
    stddev = fwhm / fwhm_to_stddev

    model = Gaussian1D(mean=y0, stddev=stddev, amplitude=50)
    rows, cols = np.mgrid[:ad.shape[0][0], :ad.shape[0][1]]

    for ext in ad:
        ext.data = model(rows)
        ext.data += np.random.poisson(ext.data)
        ext.data += (np.random.random(size=ext.data.shape) -
                     0.5) * gmos_fake_noise
        ext.mask = np.zeros_like(ext.data, dtype=np.uint)

    p = GMOSSpect([ad])
    _ad = p.findSourceApertures()[0]

    print(_ad.info)
Пример #2
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def test_find_apertures_with_fake_data(peak_position, peak_value, seeing, astrofaker):
    """
    Creates a fake AD object with a gaussian profile in spacial direction with a
    fwhm defined by the seeing variable in arcsec. Then add some noise, and
    test if p.findAperture can find its position.
    """
    np.random.seed(42)

    gmos_fake_noise = 4  # adu
    gmos_plate_scale = 0.0807  # arcsec . px-1
    fwhm_to_stddev = 2 * np.sqrt(2 * np.log(2))
    
    ad = astrofaker.create('GMOS-S', mode='SPECT')
    ad.init_default_extensions()

    fwhm = seeing / gmos_plate_scale
    stddev = fwhm / fwhm_to_stddev

    model = Gaussian1D(mean=peak_position, stddev=stddev, amplitude=peak_value)
    rows, cols = np.mgrid[:ad.shape[0][0], :ad.shape[0][1]]

    for ext in ad:
        ext.data = model(rows)
        ext.data += np.random.poisson(ext.data)
        ext.data += (np.random.random(size=ext.data.shape) - 0.5) * gmos_fake_noise
        ext.mask = np.zeros_like(ext.data, dtype=np.uint)

    p = GMOSSpect([ad])
    _ad = p.findSourceApertures(max_apertures=1)[0]

    for _ext in _ad:
        # ToDo - Could we improve the primitive to have atol=0.50 or less?
        np.testing.assert_allclose(_ext.APERTURE['c0'], peak_position, atol=0.6)
Пример #3
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def test_cosmics_on_mosaiced_data(path_to_inputs, caplog):
    ad = astrodata.open(os.path.join(path_to_inputs, TESFILE1))
    ext = ad[0]

    # add some additional fake cosmics
    size = 50
    np.random.seed(42)
    cr_x = np.random.randint(low=5, high=ext.shape[0] - 5, size=size)
    cr_y = np.random.randint(low=5, high=ext.shape[1] - 5, size=size)

    # Don't add cosmics in masked regions
    mask = binary_dilation(ext.mask > 0, iterations=3)
    sel = ~mask[cr_x, cr_y]
    cr_x = cr_x[sel]
    cr_y = cr_y[sel]
    cr_brightnesses = np.random.uniform(low=1000, high=5000, size=len(cr_x))
    ext.data[cr_x, cr_y] += cr_brightnesses

    # Store mask of CR to help debugging
    crmask = np.zeros(ext.shape, dtype=np.uint8)
    crmask[cr_x, cr_y] = 1
    ext.CRMASK = crmask

    debug = os.getenv('DEBUG') is not None
    p = GMOSSpect([ad])
    adout = p.flagCosmicRays(y_order=3, bkgfit_niter=5, debug=debug)[0]
    if debug:
        p.writeOutputs()
    mask = adout[0].mask
    # check some pixels with real cosmics
    for pix in [(496, 519), (138, 219), (420, 633), (297, 1871)]:
        assert (mask[pix] & DQ.cosmic_ray) == DQ.cosmic_ray

    # And check our fake cosmics.
    assert np.all(mask[np.where(ext.CRMASK)] & DQ.cosmic_ray == DQ.cosmic_ray)
def test_find_apertures_using_standard_star(ad_and_center):
    """
    Test that p.findApertures can find apertures in Standard Star (which are
    normally bright) observations.
    """
    ad, expected_center = ad_and_center
    p = GMOSSpect([ad])
    _ad = p.findSourceApertures(max_apertures=1).pop()

    assert hasattr(ad[0], 'APERTURE')
    assert len(ad[0].APERTURE) == 1
    np.testing.assert_allclose(ad[0].APERTURE['c0'], expected_center, 3)
def create_inputs_recipe():
    """
    Creates input data for tests using pre-processed standard star and its
    calibration files.

    The raw files will be downloaded and saved inside the path stored in the
    `$DRAGONS_TEST/raw_inputs` directory. Processed files will be stored inside
    a new folder called "dragons_test_inputs". The sub-directory structure
    should reflect the one returned by the `path_to_inputs` fixture.
    """
    import os
    from astrodata.testing import download_from_archive
    from geminidr.gmos.tests.spect import CREATED_INPUTS_PATH_FOR_TESTS
    from gempy.utils import logutils
    from recipe_system.reduction.coreReduce import Reduce

    module_name, _ = os.path.splitext(os.path.basename(__file__))
    path = os.path.join(CREATED_INPUTS_PATH_FOR_TESTS, module_name)
    os.makedirs(path, exist_ok=True)
    os.chdir(path)
    os.makedirs("inputs", exist_ok=True)
    cwd = os.getcwd()

    associated_arcs = {
        "N20180109S0287.fits":
        "N20180109S0315.fits",  # GN-2017B-FT-20-13-001 B600 0.505um
        "N20190302S0089.fits":
        "N20190302S0274.fits",  # GN-2019A-Q-203-7-001 B600 0.550um
        "N20190313S0114.fits":
        "N20190313S0132.fits",  # GN-2019A-Q-325-13-001 B600 0.482um
        "N20190427S0126.fits":
        "N20190427S0267.fits",  # GN-2019A-FT-206-7-004 R400 0.625um
        "N20190910S0028.fits":
        "N20190910S0279.fits",  # GN-2019B-Q-313-5-001 B600 0.550um
        "S20180919S0139.fits":
        "S20180919S0141.fits",  # GS-2018B-Q-209-13-003 B600 0.45um
        "S20191005S0051.fits":
        "S20191005S0147.fits",  # GS-2019B-Q-132-35-001 R400 0.73um
    }

    for sci_fname, arc_fname in associated_arcs.items():

        sci_path = download_from_archive(sci_fname)
        arc_path = download_from_archive(arc_fname)

        sci_ad = astrodata.open(sci_path)
        data_label = sci_ad.data_label()

        logutils.config(file_name='log_arc_{}.txt'.format(data_label))
        arc_reduce = Reduce()
        arc_reduce.files.extend([arc_path])
        # arc_reduce.ucals = normalize_ucals(arc_reduce.files, calibration_files)

        os.chdir("inputs/")
        arc_reduce.runr()
        arc_ad = arc_reduce.output_filenames.pop()

        logutils.config(file_name='log_{}.txt'.format(data_label))
        p = GMOSSpect([sci_ad])
        p.prepare()
        p.addDQ(static_bpm=None)
        p.addVAR(read_noise=True)
        p.overscanCorrect()
        p.ADUToElectrons()
        p.addVAR(poisson_noise=True)
        p.distortionCorrect(arc=arc_ad)
        p.writeOutputs()
        os.chdir("../")

    os.chdir(cwd)
Пример #6
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def create_inputs_recipe():
    """
    Creates input data for tests using pre-processed standard star and its
    calibration files.

    The raw files will be downloaded and saved inside the path stored in the
    `$DRAGONS_TEST/raw_inputs` directory. Processed files will be stored inside
    a new folder called "dragons_test_inputs". The sub-directory structure
    should reflect the one returned by the `path_to_inputs` fixture.
    """

    fnames = ["S20190808S0048.fits"]

    path = pathlib.Path('dragons_test_inputs')
    path = path / "geminidr" / "gmos" / "spect" / "test_cosmics" / "inputs"
    path.mkdir(exist_ok=True, parents=True)
    os.chdir(path)
    print('Current working directory:\n    {!s}'.format(path.cwd()))

    for fname in fnames:
        sci_ad = astrodata.open(download_from_archive(fname))
        data_label = sci_ad.data_label()

        print('===== Reducing pre-processed data =====')
        logutils.config(file_name=f'log_{data_label}.txt')
        p = GMOSSpect([sci_ad])
        p.prepare()
        p.addDQ(static_bpm=None)
        p.addVAR(read_noise=True)
        p.overscanCorrect()
        p.ADUToElectrons()
        p.addVAR(poisson_noise=True)
        p.writeOutputs()
        p.mosaicDetectors()
        p.writeOutputs()