Exemple #1
0
def setup_cube(ngroups, nrows, ncols):
    ''' Set up fake data to test.'''

    nints = 1

    data_model = RampModel()
    data_model.data = np.zeros(shape=(nints, ngroups, nrows, ncols), dtype=np.float32)
    data_model.pixeldq = np.zeros(shape=(nrows, ncols), dtype=np.int32)
    data_model.groupdq = np.zeros(shape=(nints, ngroups, nrows, ncols), dtype=np.float32)
    data_model.meta.subarray.xstart = 1
    data_model.meta.subarray.ystart = 1
    data_model.meta.subarray.xsize = ncols
    data_model.meta.subarray.ysize = nrows
    data_model.meta.exposure.ngroups = ngroups
    data_model.meta.instrument.name = 'NIRCAM'

    saturation_model = SaturationModel()
    saturation_model.data = np.zeros(shape=(2048, 2048), dtype=np.float32)
    saturation_model.dq = np.zeros(shape=(2048, 2048), dtype=np.int32)
    saturation_model.meta.subarray.xstart = 1
    saturation_model.meta.subarray.ystart = 1
    saturation_model.meta.subarray.xsize = 2048
    saturation_model.meta.subarray.ysize = 2048
    saturation_model.meta.instrument.name = 'NIRCAM'
    saturation_model.meta.description = 'Fake data.'
    saturation_model.meta.telescope = 'JWST'
    saturation_model.meta.reftype = 'SaturationModel'
    saturation_model.meta.author = 'Alicia'
    saturation_model.meta.pedigree = 'Dummy'
    saturation_model.meta.useafter = '2015-10-01T00:00:00'

    return data_model, saturation_model
Exemple #2
0
    def _cube():

        # create a JWST datamodel for NIRSPEC IRS2 data
        data_model = RampModel((1, 5, 3200, 2048))
        data_model.data = np.ones(((1, 5, 3200, 2048)))
        data_model.groupdq = np.zeros(((1, 5, 3200, 2048)))
        data_model.pixeldq = np.zeros(((3200, 2048)))
        data_model.meta.instrument.name = 'NIRSPEC'
        data_model.meta.instrument.detector = 'NRS1'
        data_model.meta.instrument.filter = 'F100LP'
        data_model.meta.observation.date = '2019-07-19'
        data_model.meta.observation.time = '23:23:30.912'
        data_model.meta.exposure.type = 'NRS_LAMP'
        data_model.meta.subarray.name = 'FULL'
        data_model.meta.subarray.xstart = 1
        data_model.meta.subarray.xsize = 2048
        data_model.meta.subarray.ystart = 1
        data_model.meta.subarray.ysize = 2048
        data_model.meta.exposure.nrs_normal = 16
        data_model.meta.exposure.nrs_reference = 4
        data_model.meta.exposure.readpatt = 'NRSIRS2RAPID'

        # create a saturation model for the saturation step
        saturation_model = SaturationModel((2048, 2048))
        saturation_model.data = np.ones(
            (2048, 2048)) * 60000  # saturation limit for every pixel is 60000
        saturation_model.meta.description = 'Fake data.'
        saturation_model.meta.telescope = 'JWST'
        saturation_model.meta.reftype = 'SaturationModel'
        saturation_model.meta.useafter = '2015-10-01T00:00:00'
        saturation_model.meta.instrument.name = 'NIRSPEC'
        saturation_model.meta.instrument.detector = 'NRS1'
        saturation_model.meta.author = 'Clare'
        saturation_model.meta.pedigree = 'Dummy'
        saturation_model.meta.subarray.xstart = 1
        saturation_model.meta.subarray.xsize = 2048
        saturation_model.meta.subarray.ystart = 1
        saturation_model.meta.subarray.ysize = 2048

        return data_model, saturation_model