Пример #1
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 def test_read_mda_geo_resolution(self):
     from satpy.readers.hdfeos_base import HDFEOSGeoReader
     resolution_l1b = HDFEOSGeoReader.read_geo_resolution(
         HDFEOSGeoReader.read_mda(metadata_modisl1b))
     self.assertEqual(resolution_l1b, 1000)
     resolution_l2 = HDFEOSGeoReader.read_geo_resolution(
         HDFEOSGeoReader.read_mda(metadata_modisl2))
     self.assertEqual(resolution_l2, 5000)
Пример #2
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    def read_geo_resolution(metadata):
        """Parse metadata to find the geolocation resolution.

        It is implemented as a staticmethod to match read_mda pattern.

        """
        try:
            return HDFEOSGeoReader.read_geo_resolution(metadata)
        except RuntimeError:
            # most L2 products are 5000m
            return 5000
Пример #3
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    def get_dataset(self, dataset_id, dataset_info):

        dataset_name = dataset_id.name
        if dataset_name in HDFEOSGeoReader.DATASET_NAMES:
            return HDFEOSGeoReader.get_dataset(self, dataset_id, dataset_info)
        dataset_name_in_file = dataset_info['file_key']

        # The dataset asked correspond to a given set of bits of the HDF EOS dataset
        if 'bits' in dataset_info and 'byte' in dataset_info:

            def bits_strip(bit_start, bit_count, value):
                """Extract specified bit from bit representation of integer value.

                Parameters
                ----------
                bit_start : int
                    Starting index of the bits to extract (first bit has index 0)
                bit_count : int
                    Number of bits starting from bit_start to extract
                value : int
                    Number from which to extract the bits

                Returns
                -------
                int
                Value of the extracted bits
                """

                bit_mask = pow(2, bit_start + bit_count) - 1
                return np.right_shift(np.bitwise_and(value, bit_mask),
                                      bit_start)

            hdf_dataset = self.sd.select(dataset_name_in_file)
            dataset = xr.DataArray(from_sds(hdf_dataset, chunks=CHUNK_SIZE),
                                   dims=['i', 'y', 'x']).astype(np.uint8)
            bit_start = dataset_info['bits'][0]
            bit_count = dataset_info['bits'][1]
            dataset = bits_strip(bit_start, bit_count,
                                 dataset[dataset_info['byte'], :, :])
        else:
            dataset = self.load_dataset(dataset_name)

        return dataset
Пример #4
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    def get_dataset(self, dataset_id, dataset_info):
        """Get DataArray for specified dataset."""
        dataset_name = dataset_id['name']
        if self.is_geo_loadable_dataset(dataset_name):
            return HDFEOSGeoReader.get_dataset(self, dataset_id, dataset_info)
        dataset_name_in_file = dataset_info['file_key']
        if self.is_imapp_mask_byte1:
            dataset_name_in_file = dataset_info.get('imapp_file_key',
                                                    dataset_name_in_file)

        # The dataset asked correspond to a given set of bits of the HDF EOS dataset
        if 'byte' in dataset_info and 'byte_dimension' in dataset_info:
            dataset = self._extract_and_mask_category_dataset(
                dataset_id, dataset_info, dataset_name_in_file)
        else:
            # No byte manipulation required
            dataset = self.load_dataset(dataset_name_in_file,
                                        dataset_info.pop("category", False))

        self._add_satpy_metadata(dataset_id, dataset)
        return dataset
Пример #5
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    def get_dataset(self, dataset_id, dataset_info):

        dataset_name = dataset_id.name
        if dataset_name in HDFEOSGeoReader.DATASET_NAMES:
            return HDFEOSGeoReader.get_dataset(self, dataset_id, dataset_info)
        dataset_name_in_file = dataset_info['file_key']

        # The dataset asked correspond to a given set of bits of the HDF EOS dataset
        if 'byte' in dataset_info and 'byte_dimension' in dataset_info:
            byte_dimension = dataset_info['byte_dimension']  # Where the information is stored
            dataset = self._select_hdf_dataset(dataset_name_in_file, byte_dimension)

            byte_information = self._parse_resolution_info(dataset_info['byte'], dataset_id.resolution)
            # At which bit starts the information
            bit_start = self._parse_resolution_info(dataset_info['bit_start'], dataset_id.resolution)
            # How many bits store the information
            bit_count = self._parse_resolution_info(dataset_info['bit_count'], dataset_id.resolution)

            # Only one byte: select the byte information
            if isinstance(byte_information, int):
                byte_dataset = dataset[byte_information, :, :]

            # Two bytes: recombine the two bytes
            elif isinstance(byte_information, list) and len(byte_information) == 2:
                # We recombine the two bytes
                dataset_a = dataset[byte_information[0], :, :]
                dataset_b = dataset[byte_information[1], :, :]
                dataset_a = np.uint16(dataset_a)
                dataset_a = np.left_shift(dataset_a, 8)  # dataset_a << 8
                byte_dataset = np.bitwise_or(dataset_a, dataset_b).astype(np.uint16)
                shape = byte_dataset.shape
                # We replicate the concatenated byte with the right shape
                byte_dataset = np.repeat(np.repeat(byte_dataset, 4, axis=0), 4, axis=1)
                # All bits carry information, we update bit_start consequently
                bit_start = np.arange(16, dtype=np.uint16).reshape((4, 4))
                bit_start = np.tile(bit_start, (shape[0], shape[1]))

            # Compute the final bit mask
            dataset = bits_strip(bit_start, bit_count, byte_dataset)

            # Apply quality assurance filter
            if 'quality_assurance' in dataset_info:
                quality_assurance_required = self._parse_resolution_info(
                    dataset_info['quality_assurance'], dataset_id.resolution
                )
                if quality_assurance_required is True:
                    # Get quality assurance dataset recursively
                    from satpy import DatasetID
                    quality_assurance_dataset_id = DatasetID(
                        name='quality_assurance', resolution=1000
                    )
                    quality_assurance_dataset_info = {
                        'name': 'quality_assurance',
                        'resolution': [1000],
                        'byte_dimension': 2,
                        'byte': [0],
                        'bit_start': 0,
                        'bit_count': 1,
                        'file_key': 'Quality_Assurance'
                    }
                    quality_assurance = self.get_dataset(
                        quality_assurance_dataset_id, quality_assurance_dataset_info
                    )
                    # Duplicate quality assurance dataset to create relevant filter
                    duplication_factor = [int(dataset_dim / quality_assurance_dim)
                                          for dataset_dim, quality_assurance_dim
                                          in zip(dataset.shape, quality_assurance.shape)]
                    quality_assurance = np.tile(quality_assurance, duplication_factor)
                    # Replace unassured data by NaN value
                    dataset[np.where(quality_assurance == 0)] = np.NaN

        # No byte manipulation required
        else:
            dataset = self.load_dataset(dataset_name)

        return dataset
Пример #6
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 def get_dataset(self, key, info):
     """Get the dataset."""
     if key['name'] in HDFEOSGeoReader.DATASET_NAMES:
         return HDFEOSGeoReader.get_dataset(self, key, info)
     return HDFEOSBandReader.get_dataset(self, key, info)
Пример #7
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 def __init__(self, filename, filename_info, filetype_info, **kwargs):
     """Init the file handler."""
     HDFEOSGeoReader.__init__(self, filename, filename_info, filetype_info,
                              **kwargs)
     HDFEOSBandReader.__init__(self, filename, filename_info, filetype_info,
                               **kwargs)
Пример #8
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 def get_dataset(self, key, info):
     if key.name in HDFEOSGeoReader.DATASET_NAMES:
         return HDFEOSGeoReader.get_dataset(self, key, info)
     return HDFEOSBandReader.get_dataset(self, key, info)
Пример #9
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 def __init__(self, filename, filename_info, filetype_info):
     HDFEOSGeoReader.__init__(self, filename, filename_info, filetype_info)
     HDFEOSBandReader.__init__(self, filename, filename_info, filetype_info)