def test_missing_frames(lt_ctx):
nav_shape = (16, 8)
ds = SEQDataSet(path=SEQ_TESTDATA_PATH, nav_shape=nav_shape)
ds.set_num_cores(4)
ds = ds.initialize(lt_ctx.executor)
ds.check_valid()
tileshape = Shape(
(4,) + tuple(ds.shape.sig),
sig_dims=ds.shape.sig.dims
)
tiling_scheme = TilingScheme.make_for_shape(
tileshape=tileshape,
dataset_shape=ds.shape,
)
for p in ds.get_partitions():
for t in p.get_tiles(tiling_scheme=tiling_scheme):
pass
assert p._start_frame == 96
assert p._num_frames == 32
assert p.slice.origin == (96, 0, 0)
assert p.slice.shape[0] == 32
assert t.tile_slice.origin == (60, 0, 0)
assert t.tile_slice.shape[0] == 4
def test_too_many_frames(lt_ctx):
nav_shape = (4, 8)
ds = SEQDataSet(path=SEQ_TESTDATA_PATH, nav_shape=nav_shape)
ds.set_num_cores(4)
ds = ds.initialize(lt_ctx.executor)
ds.check_valid()
tileshape = Shape((4, ) + tuple(ds.shape.sig), sig_dims=ds.shape.sig.dims)
tiling_scheme = TilingScheme.make_for_shape(
tileshape=tileshape,
dataset_shape=ds.shape,
)
for p in ds.get_partitions():
for t in p.get_tiles(tiling_scheme=tiling_scheme):
pass
def test_positive_sync_offset(default_seq, lt_ctx):
udf = SumSigUDF()
sync_offset = 2
ds_with_offset = SEQDataSet(
path=SEQ_TESTDATA_PATH, nav_shape=(8, 8), sync_offset=sync_offset
)
ds_with_offset.set_num_cores(4)
ds_with_offset = ds_with_offset.initialize(lt_ctx.executor)
ds_with_offset.check_valid()
p0 = next(ds_with_offset.get_partitions())
assert p0._start_frame == 2
assert p0.slice.origin == (0, 0, 0)
tileshape = Shape(
(4,) + tuple(ds_with_offset.shape.sig),
sig_dims=ds_with_offset.shape.sig.dims
)
tiling_scheme = TilingScheme.make_for_shape(
tileshape=tileshape,
dataset_shape=ds_with_offset.shape,
)
t0 = next(p0.get_tiles(tiling_scheme))
assert tuple(t0.tile_slice.origin) == (0, 0, 0)
for p in ds_with_offset.get_partitions():
for t in p.get_tiles(tiling_scheme=tiling_scheme):
pass
assert p.slice.origin == (48, 0, 0)
assert p.slice.shape[0] == 16
result = lt_ctx.run_udf(dataset=default_seq, udf=udf)
result = result['intensity'].raw_data[sync_offset:]
result_with_offset = lt_ctx.run_udf(dataset=ds_with_offset, udf=udf)
result_with_offset = result_with_offset['intensity'].raw_data[
:ds_with_offset._meta.image_count - sync_offset
]
assert np.allclose(result, result_with_offset)