def test_add_argparse_options(write_chunks, write_files):
# Test default values
parser = argparse.ArgumentParser()
add_argparse_options(parser,
write_chunks=write_chunks,
write_files=write_files)
args = parser.parse_args([])
get_accessor_for_url(".", vars(args))
def test_precomputed_IO_validate_chunk_coords(tmpdir):
accessor = get_accessor_for_url(str(tmpdir))
# Minimal info file
io = get_IO_for_new_dataset(DUMMY_INFO, accessor)
good_chunk_coords = (0, 8, 0, 3, 0, 8)
bad_chunk_coords = (0, 8, 1, 4, 0, 8)
assert io.validate_chunk_coords("key", good_chunk_coords) is True
assert io.validate_chunk_coords("key", bad_chunk_coords) is False
def test_add_argparse_options():
import argparse
# Test default values
parser = argparse.ArgumentParser()
add_argparse_options(parser, write=False)
args = parser.parse_args([])
get_accessor_for_url(".", vars(args))
parser = argparse.ArgumentParser()
add_argparse_options(parser, write=True)
args = parser.parse_args([])
get_accessor_for_url(".", vars(args))
# Test correct parsing
parser = argparse.ArgumentParser()
add_argparse_options(parser, write=True)
args = parser.parse_args(["--flat"])
assert args.flat is True
args = parser.parse_args(["--no-gzip"])
assert args.gzip is False
def test_precomputed_IO_chunk_roundtrip(tmpdir):
accessor = get_accessor_for_url(str(tmpdir))
# Minimal info file
io = get_IO_for_new_dataset(DUMMY_INFO, accessor)
dummy_chunk = np.arange(8 * 3 * 7, dtype="uint16").reshape(1, 7, 3, 8)
chunk_coords = (0, 8, 0, 3, 8, 15)
io.write_chunk(dummy_chunk, "key", chunk_coords)
assert np.array_equal(io.read_chunk("key", chunk_coords), dummy_chunk)
io2 = get_IO_for_existing_dataset(accessor)
assert io2.info == DUMMY_INFO
assert np.array_equal(io2.read_chunk("key", chunk_coords), dummy_chunk)
def test_get_accessor_for_url(accessor_options):
assert isinstance(get_accessor_for_url(""), Accessor)
a = get_accessor_for_url(".", accessor_options)
assert isinstance(a, FileAccessor)
assert a.base_path == pathlib.Path(".")
a = get_accessor_for_url("file:///absolute", accessor_options)
assert isinstance(a, FileAccessor)
assert a.base_path == pathlib.Path("/absolute")
a = get_accessor_for_url("http://example/", accessor_options)
assert isinstance(a, HttpAccessor)
assert a.base_url == "http://example/"
with pytest.raises(URLError, match="scheme"):
get_accessor_for_url("weird://", accessor_options)
with pytest.raises(URLError, match="decod"):
get_accessor_for_url("file:///%ff", accessor_options)
def test_jpeg_encoding_lossy_info(tmpdir):
accessor = get_accessor_for_url(str(tmpdir))
io = get_IO_for_new_dataset(
{
"type":
"image",
"data_type":
"uint8",
"num_channels":
1,
"scales": [{
"key": "key",
"size": [8, 3, 15],
"resolution": [1e6, 1e6, 1e6],
"voxel_offset": [0, 0, 0],
"chunk_sizes": [[8, 8, 8]],
"encoding": "jpeg",
}]
}, accessor)
assert io.scale_is_lossy("key")
def test_precomputed_IO_info_error(tmpdir):
with (tmpdir / "info").open("w") as f:
f.write("invalid JSON")
accessor = get_accessor_for_url(str(tmpdir))
with pytest.raises(InvalidInfoError):
get_IO_for_existing_dataset(accessor)
def test_raw_encoding_lossy_info(tmpdir):
accessor = get_accessor_for_url(str(tmpdir))
# Minimal info file
io_raw = get_IO_for_new_dataset(DUMMY_INFO, accessor)
assert not io_raw.scale_is_lossy("key")
def _bootstrap(self):
accessor = get_accessor_for_url(self.url)
self._io = get_IO_for_existing_dataset(accessor)
self._scales_cached = sorted(
[NeuroglancerScale(self, i) for i in self._io.info["scales"]])