def test_init_empty_file(self):
     with ArtificialND2('test_data/empty.nd2',
                        skip_blocks=['label_map_marker']):
         with self.assertRaises(EmptyFileError) as exception:
             with ND2Reader('test_data/empty.nd2'):
                 pass
         self.assertEqual(str(exception.exception),
                          "No axes were found for this .nd2 file.")
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    def test_read_chunk_fail_bad_header(self):
        with ArtificialND2(self.test_file) as artificial:
            fh = artificial.file_handle
            chunk_location = artificial.locations['image_attributes'][0]

            with self.assertRaises(ValueError) as context:
                read_chunk(fh, chunk_location + 1)

            self.assertEquals(str(context.exception), "The ND2 file seems to be corrupted.")
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    def test_get_frame_2D(self):
        # Best test we can do for now:
        # test everything up to the actual unpacking of the frame data
        with ArtificialND2('test_data/test_nd2_reader.nd2') as _:
            with ND2Reader('test_data/test_nd2_reader.nd2') as reader:

                with self.assertRaises(struct.error) as exception:
                    frame = reader.get_frame_2D(c=0, t=0, z=0, x=0, y=0, v=0)

                self.assertIn('unpack', str(exception.exception))
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    def test_init_and_init_axes(self):
        with ArtificialND2('test_data/test_nd2_reader.nd2') as artificial:
            with ND2Reader('test_data/test_nd2_reader.nd2') as reader:
                attributes = artificial.data['image_attributes']['SLxImageAttributes']
                self.assertEqual(reader.metadata['width'], attributes['uiWidth'])
                self.assertEqual(reader.metadata['height'], attributes['uiHeight'])

                self.assertEqual(reader.metadata['width'], reader.sizes['x'])
                self.assertEqual(reader.metadata['height'], reader.sizes['y'])

                self.assertEqual(reader.pixel_type, np.float64)
                self.assertEqual(reader.iter_axes, ['t'])
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 def test_init(self):
     with ArtificialND2('test_data/legacy.nd2'):
         with warnings.catch_warnings(record=True) as w:
             # Cause all warnings to always be triggered.
             warnings.simplefilter("always")
             with Nd2('test_data/legacy.nd2') as reader:
                 self.assertIsInstance(reader.reader, ND2Reader)
             self.assertTrue(issubclass(w[0].category, DeprecationWarning))
             self.assertEquals(
                 str(w[0].message),
                 "The 'Nd2' class is deprecated, please consider using the new"
                 + " ND2Reader interface which uses pims.")
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    def test_misc(self):
        with ArtificialND2('test_data/legacy.nd2'):
            with Nd2('test_data/legacy.nd2') as reader:
                representation = "\n".join([
                    "<Deprecated ND2 %s>" % reader.reader.filename,
                    "Created: Unknown",
                    "Image size: %sx%s (HxW)" % (reader.height, reader.width),
                    "Frames: %s" % len(reader.frames),
                    "Channels: %s" % ", ".join(
                        ["%s" % str(channel) for channel in reader.channels]),
                    "Fields of View: %s" % len(reader.fields_of_view),
                    "Z-Levels: %s" % len(reader.z_levels)
                ])
                self.assertEquals(representation, str(reader))

                # not implemented yet
                self.assertEquals(reader.pixel_microns, None)

                self.assertEquals(len(reader), 1)
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    def test_read_chunk(self):
        with ArtificialND2(self.test_file) as artificial:
            fh = artificial.file_handle
            chunk_location = artificial.locations['image_attributes'][0]

            chunk_read = read_chunk(fh, chunk_location)
            real_data = six.BytesIO(artificial.raw_text)

            real_data.seek(chunk_location)

            # The chunk metadata is always 16 bytes long
            chunk_metadata = real_data.read(16)
            header, relative_offset, data_length = struct.unpack("IIQ", chunk_metadata)
            self.assertEquals(header, 0xabeceda)

            # We start at the location of the chunk metadata, skip over the metadata, and then proceed to the
            # start of the actual data field, which is at some arbitrary place after the metadata.
            real_data.seek(chunk_location + 16 + relative_offset)

            real_chunk = real_data.read(data_length)

            self.assertEqual(real_chunk, chunk_read)
 def setUp(self):
     self.nd2 = ArtificialND2('test_data/test_nd2_raw_metadata001.nd2')
     self.raw_text, self.locations, self.file_data = self.nd2.raw_text, self.nd2.locations, self.nd2.data
     self.label_map = LabelMap(self.raw_text)
     self.metadata = RawMetadata(self.nd2.file_handle, self.label_map)
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 def create_test_nd2(self):
     with ArtificialND2(self.test_file) as artificial:
         self.assertIsNotNone(artificial.file_handle)
         artificial.close()
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 def test_get_timesteps(self):
     with ArtificialND2('test_data/test_nd2_reader.nd2') as _:
         with ND2Reader('test_data/test_nd2_reader.nd2') as reader:
             timesteps = reader.timesteps
             self.assertEquals(len(timesteps), 0)
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 def test_get_parser(self):
     with ArtificialND2('test_data/test_nd2_reader.nd2') as _:
         with ND2Reader('test_data/test_nd2_reader.nd2') as reader:
             self.assertIsInstance(reader.parser, Parser)
 def test_init_from_handler(self):
     with ArtificialND2('test_data/test_nd2_reader.nd2') as artificial:
         with open('test_data/test_nd2_reader.nd2', "rb") as FH:
             with ND2Reader(FH) as reader:
                 self.cmp_two_readers(artificial, reader)
 def test_init_and_init_axes(self):
     with ArtificialND2('test_data/test_nd2_reader.nd2') as artificial:
         with ND2Reader('test_data/test_nd2_reader.nd2') as reader:
             self.cmp_two_readers(artificial, reader)
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 def create_test_nd2(self):
     with ArtificialND2(self.test_file) as artificial:
         artificial.close()
 def setUp(self):
     self.nd2 = ArtificialND2('test_data/test_nd2_label_map001.nd2')
     self.raw_text, self.locations = self.nd2.raw_text, self.nd2.locations
     self.label_map = LabelMap(self.raw_text)