def test_dense_stream(lazy):
    arr = np.random.randint(0, 65535, size=(2, 3, 4, 5)).astype("uint16")
    stream = array_to_stream(arr)
    if lazy:
        arrs = stream_to_sparse_COO_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        arrs = arrs.compute()
        assert (arrs == arr).all()
    else:
        arrs = stream_to_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        assert (arrs == arr).all()
def test_empty_stream(lazy):
    arr = np.zeros((2, 3, 4, 5), dtype="uint16")
    stream = array_to_stream(arr)
    if lazy:
        arrs = stream_to_sparse_COO_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        arrs = arrs.compute()
        assert not arrs.any()
    else:
        arrs = stream_to_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        assert not arrs.any()
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def test_empty_stream(lazy):
    arr = np.zeros((2, 3, 4, 5), dtype="uint16")
    stream = array_to_stream(arr)
    if lazy:
        arrs = da.from_array(stream_to_sparse_COO_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2), chunks=(1, 1, 2, 5))
        arrs = arrs.compute()
        assert not arrs.any()
    else:
        arrs = stream_to_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        assert not arrs.any()
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def test_dense_stream(lazy):
    arr = np.random.randint(0, 65535, size=(2, 3, 4, 5)).astype("uint16")
    stream = array_to_stream(arr)
    if lazy:
        arrs = da.from_array(stream_to_sparse_COO_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2), chunks=(1, 1, 2, 5))
        arrs = arrs.compute()
        assert (arrs == arr).all()
    else:
        arrs = stream_to_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        assert (arrs == arr).all()
def test_sparse_stream(lazy):
    arr = np.zeros((2, 3, 4, 5), dtype="uint16")
    arr[0, 0, 0, 0] = 1
    arr[-1, -1, -1, -1] = 2
    arr[1, 1, 3, 3] = 3
    stream = array_to_stream(arr)
    if lazy:
        arrs = stream_to_sparse_COO_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        arrs = arrs.compute()
        assert (arrs == arr).all()
    else:
        arrs = stream_to_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        assert (arrs == arr).all()
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def test_sparse_stream(lazy):
    arr = np.zeros((2, 3, 4, 5), dtype="uint16")
    arr[0, 0, 0, 0] = 1
    arr[-1, -1, -1, -1] = 2
    arr[1, 1, 3, 3] = 3
    stream = array_to_stream(arr)
    if lazy:
        arrs = da.from_array(stream_to_sparse_COO_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2), chunks=(1, 1, 2, 5))
        arrs = arrs.compute()
        assert (arrs == arr).all()
    else:
        arrs = stream_to_array(
            stream, spatial_shape=(3, 4), sum_frames=False, channels=5,
            last_frame=2)
        assert (arrs == arr).all()
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    def stream_to_sparse_array(self, stream_data):
        """Convert stream in sparse array

        Parameters
        ----------
        stream_data: array

        """
        # Here we load the stream data into memory, which is fine is the
        # arrays are small. We could load them lazily when lazy.
        stream_data = self.stream_group['Data'][:].T[0]
        sparse_array = stream_readers.stream_to_sparse_COO_array(
            stream_data=stream_data,
            spatial_shape=self.reader.spatial_shape,
            first_frame=self.reader.first_frame,
            last_frame=self.reader.last_frame,
            channels=self.bin_count,
            sum_frames=self.reader.sum_frames,
            rebin_energy=self.reader.rebin_energy,
        )
        return sparse_array
def test_empty_stream(lazy):
    arr = np.zeros((2, 3, 4, 5), dtype="uint16")
    stream = array_to_stream(arr)
    if lazy:
        if not sparse_installed:
            pytest.skip("The sparse package is not installed")
        arrs = da.from_array(stream_to_sparse_COO_array(stream,
                                                        spatial_shape=(3, 4),
                                                        sum_frames=False,
                                                        channels=5,
                                                        last_frame=2),
                             chunks=(1, 1, 2, 5))
        arrs = arrs.compute()
        assert not arrs.any()
    else:
        arrs = stream_to_array(stream,
                               spatial_shape=(3, 4),
                               sum_frames=False,
                               channels=5,
                               last_frame=2)
        assert not arrs.any()
def test_dense_stream(lazy):
    arr = np.random.randint(0, 65535, size=(2, 3, 4, 5)).astype("uint16")
    stream = array_to_stream(arr)
    if lazy:
        if not sparse_installed:
            pytest.skip("The sparse package is not installed")
        arrs = da.from_array(stream_to_sparse_COO_array(stream,
                                                        spatial_shape=(3, 4),
                                                        sum_frames=False,
                                                        channels=5,
                                                        last_frame=2),
                             chunks=(1, 1, 2, 5))
        arrs = arrs.compute()
        assert (arrs == arr).all()
    else:
        arrs = stream_to_array(stream,
                               spatial_shape=(3, 4),
                               sum_frames=False,
                               channels=5,
                               last_frame=2)
        assert (arrs == arr).all()