Beispiel #1
0
def test_create_typical_browse_metadata():
    class TestDriver(drivers.DatasetDriver):
        def browse_image_bands(self, d):
            return '5', '1', '3'

    d = write_files({})
    dataset = browseimage.create_typical_browse_metadata(
        TestDriver(), ptype.DatasetMetadata(), d)

    expected = ptype.DatasetMetadata(
        browse={
            'full':
            ptype.BrowseMetadata(path=d.joinpath('browse.fr.jpg'),
                                 file_type='image/jpg',
                                 red_band='5',
                                 green_band='1',
                                 blue_band='3'),
            'medium':
            ptype.BrowseMetadata(
                path=d.joinpath('browse.jpg'),
                # Default medium size.
                shape=ptype.Point(1024, None),
                file_type='image/jpg',
                red_band='5',
                green_band='1',
                blue_band='3')
        })

    expected.id_, dataset.id_ = None, None
    assert_same(expected, dataset)
Beispiel #2
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def create_typical_browse_metadata(dataset_driver, dataset,
                                   destination_directory):
    """
    Create browse metadata.
    :type dataset_driver: eodatasets.package.DatasetDriver
    :type dataset: ptype.DatasetMetadata
    :type destination_directory: Path
    :return:
    """
    rgb_bands = dataset_driver.browse_image_bands(dataset)
    if len(rgb_bands) == 3:
        r, g, b = rgb_bands
    elif len(rgb_bands) == 1:
        band = rgb_bands[0]
        r, g, b = band, band, band
    else:
        raise ValueError('Unexpected number of bands (%s). Received %r' %
                         (len(rgb_bands), rgb_bands))

    dataset.browse = {
        'medium':
        ptype.BrowseMetadata(
            path=destination_directory.joinpath('browse.jpg'),
            file_type='image/jpg',
            # cell_size=output_res,
            shape=ptype.Point(1024, None),
            red_band=r,
            green_band=g,
            blue_band=b),
        'full':
        ptype.BrowseMetadata(
            path=destination_directory.joinpath('browse.fr.jpg'),
            file_type='image/jpg',
            # cell_size=output_res,
            red_band=r,
            green_band=g,
            blue_band=b)
    }
    return dataset
Beispiel #3
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def _build_ls8_ortho():
    _reset_runtime_id()
    return ptype.DatasetMetadata(
        id_=uuid.UUID('17b92c16-51d3-11e4-909d-005056bb6972'),
        ga_label='LS8_OLITIRS_OTH_P51_GALPGS01-002_101_078_20141012',
        product_type='GAORTHO01',
        creation_dt=dateutil.parser.parse('2014-10-12 05:46:20'),
        size_bytes=2386550 * 1024,
        platform=ptype.PlatformMetadata(code='LANDSAT-8'),
        instrument=ptype.InstrumentMetadata(name='OLI_TIRS',
                                            type_="Multi-Spectral",
                                            operation_mode='PUSH-BROOM'),
        format_=ptype.FormatMetadata(name='GeoTiff', version=1),
        extent=ptype.ExtentMetadata(
            reference_system='WGS84',
            coord=ptype.CoordPolygon(ul=ptype.Coord(lat=-24.97, lon=133.97969),
                                     ur=ptype.Coord(lat=-24.96826,
                                                    lon=136.24838),
                                     lr=ptype.Coord(lat=-26.96338,
                                                    lon=136.26962),
                                     ll=ptype.Coord(lat=-26.96528,
                                                    lon=133.96233)),
            from_dt=dateutil.parser.parse("2014-10-12T00:55:54"),
            center_dt=dateutil.parser.parse("2014-10-12T00:56:06"),
            to_dt=dateutil.parser.parse("2014-10-12T00:56:18"),
        ),
        grid_spatial=ptype.GridSpatialMetadata(
            dimensions=[
                ptype.DimensionMetadata(name='sample',
                                        resolution=25.0,
                                        size=9161),
                ptype.DimensionMetadata(name='line',
                                        resolution=25.0,
                                        size=9161)
            ],
            projection=ptype.ProjectionMetadata(
                centre_point=ptype.Point(511512.500000, 7127487.500000),
                geo_ref_points=ptype.PointPolygon(
                    ul=ptype.Point(397012.5, 7237987.5),
                    ur=ptype.Point(626012.5, 7237987.5),
                    ll=ptype.Point(397012.5, 7016987.5),
                    lr=ptype.Point(626012.5, 7016987.5)),
                datum='GDA94',
                ellipsoid='GRS80',
                point_in_pixel='UL',
                map_projection='UTM',
                resampling_option='CUBIC_CONVOLUTION',
                zone=-53)),
        browse={
            'medium':
            ptype.BrowseMetadata(path=Path(
                'product/LS8_OLITIRS_OTH_P51_GALPGS01-032_101_078_20141012.jpg'
            ),
                                 file_type='image/jpg',
                                 cell_size=219.75,
                                 red_band=7,
                                 green_band=5,
                                 blue_band=1),
            'full':
            ptype.BrowseMetadata(path=Path(
                'LS8_OLITIRS_OTH_P51_GALPGS01-032_101_078_20141012_FR.jpg'),
                                 file_type='image/jpg',
                                 cell_size=25.0,
                                 red_band=7,
                                 green_band=5,
                                 blue_band=1)
        },
        image=ptype.ImageMetadata(
            satellite_ref_point_start=ptype.Point(101, 78),
            cloud_cover_percentage=0,
            cloud_cover_details=None,
            sun_elevation=58.00268508,
            sun_azimuth=59.41814014,
            ground_control_points_model=420,
            geometric_rmse_model=4.610,
            geometric_rmse_model_x=3.527,
            geometric_rmse_model_y=2.968,

            # TODO: What are these two?
            viewing_incidence_angle_long_track=0,
            viewing_incidence_angle_x_track=0,
            bands={
                'coastal_aerosol':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B1.TIF'),
                    number=1,
                    type_='reflective',
                    cell_size=25.0,
                ),
                'visible_blue':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B2.TIF'),
                    number=2,
                    type_='reflective',
                    cell_size=25.0,
                ),
                'visible_green':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B3.TIF'),
                    number=3,
                    type_='reflective',
                    cell_size=25.0,
                ),
                'visible_red':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B4.TIF'),
                    number=4,
                    type_='reflective',
                    cell_size=25.0,
                ),
                'near_infrared':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B5.TIF'),
                    number=5,
                    type_='reflective',
                    cell_size=25.0,
                ),
                'short_wave_infrared1':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B6.TIF'),
                    number=6,
                    type_='reflective',
                    cell_size=25.0,
                ),
                'short_wave_infrared2':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B7.TIF'),
                    number=7,
                    type_='reflective',
                    cell_size=25.0,
                ),
                'panchromatic':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B8.TIF'),
                    number=8,
                    type_='panchromatic',
                    cell_size=12.50,
                    shape=ptype.Point(17761, 18241),
                ),
                'cirrus':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B9.TIF'),
                    number=9,
                    type_='atmosphere',
                ),
                'thermal_infrared1':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B10.TIF'),
                    number=10,
                    type_='thermal',
                    cell_size=25.0,
                    shape=ptype.Point(8881, 9121),
                ),
                'thermal_infrared2':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_B11.TIF'),
                    number=11,
                    type_='thermal',
                    cell_size=25.0,
                    shape=ptype.Point(8881, 9121),
                ),
                'quality':
                ptype.BandMetadata(
                    path=Path('product/LC81010782014285LGN00_BQA.TIF'),
                    number='QA',
                    type_='quality',
                )
            }),
        lineage=ptype.LineageMetadata(
            algorithm=ptype.AlgorithmMetadata(
                name='Pinkmatter Landsat Processor',
                version='3.3.3104',
                parameters={
                    'resampling': 'CC',
                    'radiometric_correction': 'CPF',
                    'orientation': 'NUP',
                    'hemisphere': 'S',
                }),
            machine=ptype.MachineMetadata(
                hostname='rhe-jm-prod08.prod.lan',
                type_id='jobmanager',
                uname=
                'Linux rhe-jm-dev08.dev.lan 2.6.32-279.22.1.el6.x86_64 #1 SMP Sun Oct '
                '12 '
                '09:21:40 EST 2014 x86_64 x86_64 x86_64 GNU/Linux'),
            ancillary={
                'cpf':
                ptype.AncillaryMetadata(
                    name='L8CPF20141001_20141231.01',
                    uri=
                    '/eoancillarydata/sensor-specific/LANDSAT8/CalibrationParameterFile'
                    '/L8CPF20141001_20141231.01'),
                'bpf_tirs':
                ptype.AncillaryMetadata(
                    name='LT8BPF20141012002432_20141012020301.01',
                    uri=
                    '/eoancillarydata/sensor-specific/LANDSAT8/BiasParameterFile/2014/10'
                    '/LT8BPF20141012002432_20141012020301.01'),
                'bpf_oli':
                ptype.AncillaryMetadata(
                    name='LO8BPF20141012002825_20141012011100.01',
                    uri=
                    '/eoancillarydata/sensor-specific/LANDSAT8/BiasParameterFile/2014/10'
                    '/LT8BPF20141012002432_20141012020301.01'),
                'rlut':
                ptype.AncillaryMetadata(name='L8RLUT20130211_20431231v09.h5')
            },
            source_datasets={'satellite_telemetry_data': _build_ls8_raw()}))
Beispiel #4
0
def _build_ls8_nbar():
    _reset_runtime_id()
    nbar = ptype.DatasetMetadata(
        id_=uuid.UUID("249ae098-bd88-11e4-beaa-1040f381a756"),
        size_bytes=622208 * 1024,
        ga_label='LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012',
        product_type='GANBAR01',
        platform=ptype.PlatformMetadata(code='LANDSAT-8'),
        instrument=ptype.InstrumentMetadata(name='OLI_TIRS',
                                            type_="Multi-Spectral",
                                            operation_mode='PUSH-BROOM'),
        # acquisition=ptype.AcquisitionMetadata(),
        format_=ptype.FormatMetadata(name='GeoTiff', version=1),
        extent=ptype.ExtentMetadata(
            reference_system='WGS84',
            coord=ptype.CoordPolygon(ul=ptype.Coord(lat=-24.97, lon=133.97969),
                                     ur=ptype.Coord(lat=-24.96826,
                                                    lon=136.24838),
                                     lr=ptype.Coord(lat=-26.96338,
                                                    lon=136.26962),
                                     ll=ptype.Coord(lat=-26.96528,
                                                    lon=133.96233)),
            from_dt=dateutil.parser.parse("2014-10-12T00:55:54"),
            to_dt=dateutil.parser.parse("2014-10-12T00:56:18"),
        ),
        grid_spatial=ptype.GridSpatialMetadata(
            dimensions=[
                ptype.DimensionMetadata(name='sample',
                                        resolution=25.0,
                                        size=9161),
                ptype.DimensionMetadata(name='line',
                                        resolution=25.0,
                                        size=9161)
            ],
            projection=ptype.ProjectionMetadata(
                centre_point=ptype.Point(511512.500000, 7127487.500000),
                geo_ref_points=ptype.PointPolygon(
                    ul=ptype.Point(397012.5, 7237987.5),
                    ur=ptype.Point(626012.5, 7237987.5),
                    ll=ptype.Point(397012.5, 7016987.5),
                    lr=ptype.Point(626012.5, 7016987.5)),
                datum='GDA94',
                ellipsoid='GRS80',
                point_in_pixel='UL',
                map_projection='UTM',
                resampling_option='CUBIC_CONVOLUTION',
                zone=-53)),
        browse={
            'medium':
            ptype.BrowseMetadata(path=Path(
                'LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012.tif'),
                                 file_type='image/jpg',
                                 cell_size=219.75,
                                 red_band=7,
                                 green_band=5,
                                 blue_band=2),
            'full':
            ptype.BrowseMetadata(path=Path(
                'LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_FR.tif'),
                                 file_type='image/jpg',
                                 cell_size=25.0,
                                 red_band=7,
                                 green_band=5,
                                 blue_band=2)
        },
        image=ptype.ImageMetadata(
            satellite_ref_point_start=ptype.Point(101, 78),
            cloud_cover_percentage=0.01,
            cloud_cover_details=None,

            # TODO: What are these two?
            viewing_incidence_angle_long_track=0,
            viewing_incidence_angle_x_track=0,
            bands={
                '1':
                ptype.BandMetadata(path=Path(
                    'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B1.tif'
                ), ),
                '2':
                ptype.BandMetadata(path=Path(
                    'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B2.tif'
                ), ),
                '3':
                ptype.BandMetadata(path=Path(
                    'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B3.tif'
                ), ),
                '4':
                ptype.BandMetadata(path=Path(
                    'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B4.tif'
                ), ),
                '5':
                ptype.BandMetadata(path=Path(
                    'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B5.tif'
                ), ),
                '6':
                ptype.BandMetadata(path=Path(
                    'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B6.tif'
                ), ),
                '7':
                ptype.BandMetadata(path=Path(
                    'product/LS8_OLI_TIRS_NBAR_P54_GANBAR01-015_101_078_20141012_B7.tif'
                ), )
            }),
        lineage=ptype.LineageMetadata(
            algorithm=ptype.AlgorithmMetadata(name='GANBAR',
                                              version='3.2.1',
                                              parameters={}),
            machine=ptype.MachineMetadata(),
            source_datasets={'level1': _build_ls8_ortho()},
            ancillary={}))
    return nbar