def test_tdms2rtdc_update_roi_size():
pytest.importorskip("nptdms")
path_in = retrieve_data("fmt-tdms_fl-image_2016.zip")
# set wrong roi sizes
camin = path_in.with_name("M1_camera.ini")
with camin.open("r") as fd:
lines = fd.readlines()
lines = lines[:-2]
lines.append("width = 23\n")
lines.append("height = 24\n")
with camin.open("w") as fd:
fd.writelines(lines)
# same directory (will be cleaned up with path_in)
path_out = path_in.with_name("out.rtdc")
cli.tdms2rtdc(path_tdms=path_in,
path_rtdc=path_out,
compute_features=False,
skip_initial_empty_image=True)
with new_dataset(path_out) as dsj, new_dataset(path_in) as ds0:
assert ds0.config["imaging"]["roi size x"] == 23
assert ds0.config["imaging"]["roi size y"] == 24
assert dsj.config["imaging"]["roi size x"] == 256
assert dsj.config["imaging"]["roi size y"] == 96
wlog = "dclab-tdms2rtdc-warnings"
assert "LimitingExportSizeWarning" in dsj.logs[wlog]
def test_tdms2rtdc_bulk():
pytest.importorskip("nptdms")
path_data = retrieve_data("fmt-tdms_shapein-2.0.1-no-image_2017.zip")
path_wd = pathlib.Path(
tempfile.mkdtemp(prefix="tdms2rtdc_bulk_")).resolve()
path_in = path_wd / "input"
path_in.mkdir()
shutil.copytree(path_data.parent, path_in / "data_1")
shutil.copytree(path_data.parent, path_in / "data_2")
shutil.copytree(path_data.parent, path_in / "data_3")
(path_in / "data_nested").mkdir()
shutil.copytree(path_data.parent, path_in / "data_nested" / "data_4")
# same directory (will be cleaned up with path_in)
path_out = path_wd / "output"
path_out.mkdir()
cli.tdms2rtdc(path_tdms=path_in,
path_rtdc=path_out,
compute_features=False)
for pp in [path_out / "data_1" / "M1_data.rtdc",
path_out / "data_2" / "M1_data.rtdc",
path_out / "data_3" / "M1_data.rtdc",
path_out / "data_nested" / "data_4" / "M1_data.rtdc"]:
assert pp.exists()
with new_dataset(pp) as ds2, new_dataset(path_data) as ds1:
assert len(ds2)
assert set(ds1.features) == set(ds2.features)
# not all features are computed
assert set(ds2._events.keys()) < set(ds1.features)
for feat in ds1:
assert np.all(ds1[feat] == ds2[feat])
def test_tdms2rtdc_features():
pytest.importorskip("nptdms")
path_in = retrieve_data("fmt-tdms_shapein-2.0.1-no-image_2017.zip")
# same directory (will be cleaned up with path_in)
path_out = path_in.with_name("out.rtdc")
cli.tdms2rtdc(path_tdms=path_in,
path_rtdc=path_out,
compute_features=True)
with new_dataset(path_out) as ds2, new_dataset(path_in) as ds1:
assert len(ds2)
assert set(ds1.features) == set(ds2.features)
# features were computed
assert set(ds2._events.keys()) == set(ds1.features)
def test_tdms2rtdc_features():
pytest.importorskip("nptdms")
path_in = retrieve_data("fmt-tdms_shapein-2.0.1-no-image_2017.zip")
# same directory (will be cleaned up with path_in)
path_out = path_in.with_name("out.rtdc")
with mock.patch(
"sys.argv",
["", str(path_in),
str(path_out), "--compute-ancillary-features"]):
cli.tdms2rtdc()
with new_dataset(path_out) as ds2, new_dataset(path_in) as ds1:
assert len(ds2)
assert set(ds1.features) == set(ds2.features)
# features were computed
assert set(ds2._events.keys()) == set(ds1.features)
def test_tdms2rtdc_update_sample_per_events():
pytest.importorskip("nptdms")
path_in = retrieve_data("fmt-tdms_2fl-no-image_2017.zip")
# same directory (will be cleaned up with path_in)
path_out = path_in.with_name("out.rtdc")
# set wrong samples per event
with path_in.with_name("M1_para.ini").open("a") as fd:
fd.write("Samples Per Event = 1234")
with new_dataset(path_in) as ds:
assert ds.config["fluorescence"]["samples per event"] == 1234
cli.tdms2rtdc(path_tdms=path_in,
path_rtdc=path_out,
compute_features=True)
with new_dataset(path_out) as ds2:
assert ds2.config["fluorescence"]["samples per event"] == 566
def test_tdms2rtdc_remove_nan_image():
pytest.importorskip("nptdms")
imageio = pytest.importorskip("imageio")
path_in = retrieve_data("fmt-tdms_fl-image-bright_2017.zip")
# same directory (will be cleaned up with path_in)
path_out = path_in.with_name("out.rtdc")
# generate fake video
with new_dataset(path_in) as ds:
video_length = len(ds) - 1
vname = path_in.with_name("M4_0.040000ul_s_imaq.avi")
# remove contour data (not necessary for this test)
path_in.with_name("M4_0.040000ul_s_contours.txt").unlink()
imgs = imageio.mimread(vname)
with imageio.get_writer(vname) as writer:
for ii in range(video_length):
writer.append_data(imgs[ii % len(imgs)])
# without removal
cli.tdms2rtdc(path_tdms=path_in,
path_rtdc=path_out,
compute_features=False,
skip_initial_empty_image=False)
with new_dataset(path_out) as ds2, new_dataset(path_in) as ds1:
assert len(ds2) == len(ds1)
assert np.all(ds2["image"][0] == 0)
# with removal
cli.tdms2rtdc(path_tdms=path_in,
path_rtdc=path_out,
compute_features=False,
skip_initial_empty_image=True)
with new_dataset(path_out) as ds2, new_dataset(path_in) as ds1:
assert len(ds2) == video_length
assert not np.all(ds2["image"][0] == 0)
assert ds2.config["experiment"]["event count"] == video_length