def test_mode():
data = {"area_um": np.linspace(100.7, 110.9, 100)}
data2 = {"deform": np.linspace(.7, .8, 100)}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_replace_")
with RTDCWriter(rtdc_file, mode="reset") as hw:
for feat in data:
hw.store_feature(feat, data[feat])
with RTDCWriter(rtdc_file, mode="append") as hw:
for feat in data:
hw.store_feature(feat, data[feat])
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data1:
events1 = rtdc_data1["events"]
assert "area_um" in events1.keys()
assert len(events1["area_um"]) == 2 * len(data["area_um"])
with RTDCWriter(rtdc_file, mode="replace") as hw:
for feat in data:
hw.store_feature(feat, data[feat])
with RTDCWriter(rtdc_file, mode="replace") as hw:
for feat in data2:
hw.store_feature(feat, data2[feat])
with h5py.File(rtdc_file, mode="r") as rtdc_data2:
events2 = rtdc_data2["events"]
assert "area_um" in events2.keys()
assert "deform" in events2.keys()
assert len(events2["area_um"]) == len(data["area_um"])
def test_replace_contour():
num = 7
contour = []
contour2 = []
for ii in range(5, num + 5):
cii = np.arange(2 * ii).reshape(2, ii)
contour.append(cii)
contour2.append(cii * 2)
data1 = {"area_um": np.linspace(100.7, 110.9, num),
"contour": contour}
data2 = {"contour": contour2}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_replace_contour_")
with RTDCWriter(rtdc_file) as hw:
for feat in data1:
hw.store_feature(feat, data1[feat])
with RTDCWriter(rtdc_file, mode="replace") as hw:
for feat in data2:
hw.store_feature(feat, data2[feat])
# verify
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert "contour" in events.keys()
assert not np.allclose(events["contour"]["6"], contour[6])
assert np.allclose(events["contour"]["6"], contour2[6])
def test_ic_fmt_hdf5_image_bg():
h5path = retrieve_data("fmt-hdf5_fl_2018.zip")
# add a fake image_bg column
with h5py.File(h5path, "a") as h5:
image_bg = h5["events"]["image"][:] // 2
hw = RTDCWriter(h5)
hw.store_feature("image_bg", image_bg)
del h5["events/image_bg"].attrs["CLASS"]
with check.IntegrityChecker(h5path) as ic:
cues = ic.check_fmt_hdf5()
assert cues[0].category == "format HDF5"
assert cues[0].msg == "HDF5: '/image_bg': missing attribute 'CLASS'"
assert cues[0].level == "alert"
def test_rectify_metadata_ignore_empty_trace():
# test introduced in 0.39.7
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_error_")
with h5py.File(rtdc_file, "a") as h5:
h5.require_group("events")
h5.require_group("events/trace")
h5["events/deform"] = np.linspace(.1, .12, 7)
# Initialize writer
hw = RTDCWriter(h5, mode="append")
# in previous versions, this did not work, because of the empty trace
hw.rectify_metadata()
# make sure that something happened
assert h5.attrs["experiment:event count"] == 7
def test_meta():
data = {"area_um": np.linspace(100.7, 110.9, 100)}
meta = {"setup": {
"channel width": 20,
"chip region": "Channel", # should be made lower-case
},
"online_contour": {
"no absdiff": "True", # should be converted to bool
"image blur": 3.0,
},
}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_meta_")
with RTDCWriter(rtdc_file) as hw:
for feat in data:
hw.store_feature(feat, data[feat])
hw.store_metadata(meta)
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
abool = rtdc_data.attrs["online_contour:no absdiff"]
assert abool
assert isinstance(abool, (bool, np.bool_))
anint = rtdc_data.attrs["online_contour:image blur"]
assert isinstance(anint, numbers.Integral)
assert rtdc_data.attrs["setup:channel width"] == 20
assert rtdc_data.attrs["setup:chip region"] == "channel"
def test_bulk_logs():
log = ["This is a test log that contains two lines.",
"This is the second line.",
]
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_bulk_logs_")
hw = RTDCWriter(rtdc_file)
hw.store_log("testlog", log)
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
outlog = rtdc_data["logs"]["testlog"]
for ii in range(len(outlog)):
if isinstance(outlog[ii], bytes):
# h5py 3 reads strings as bytes by default
outii = outlog[ii].decode("utf-8")
else:
outii = outlog[ii]
assert outii == log[ii]
def test_meta_no_analysis():
"""The "filtering" section should not be written to the dataset"""
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_meta_no_analysis")
meta1 = {"filtering": {"enable filters": True}}
with RTDCWriter(rtdc_file) as hw:
hw.store_feature("area_um", np.linspace(100.7, 110.9, 100))
with pytest.raises(ValueError, match="filtering"):
hw.store_metadata(meta1)
def test_index_increment():
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_error_")
with RTDCWriter(rtdc_file) as hw:
hw.store_metadata({"experiment": {"sample": "test",
"run index": 1}})
hw.store_feature("index", np.arange(1, 11))
hw.store_feature("index", np.arange(1, 11))
with new_dataset(rtdc_file) as ds:
assert np.all(ds["index"] == np.arange(1, 21))
def test_version_branding_1_write_single_version():
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_branding_")
this_version = f"dclab {dclab.__version__}"
with RTDCWriter(rtdc_file) as hw:
hw.store_feature("deform", np.linspace(0.01, 0.02, 10))
with h5py.File(rtdc_file) as h5:
assert h5.attrs["setup:software version"] == this_version
def test_bulk_scalar():
data = {"area_um": np.linspace(100.7, 110.9, 100)}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_bulk_scalar_")
with RTDCWriter(rtdc_file) as hw:
for feat in data:
hw.store_feature(feat, data[feat])
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert "area_um" in events.keys()
assert np.all(events["area_um"][:] == data["area_um"])
def test_feat_image_bg():
path = retrieve_data("fmt-hdf5_fl_2017.zip")
# add a fake image_bg column
with RTDCWriter(path) as hw:
image_bg = hw.h5file["events"]["image"][:] // 2
hw.store_feature("image_bg", image_bg)
ds = new_dataset(path)
ds.filter.manual[0] = False
ds.filter.manual[2] = False
ch = new_dataset(ds)
assert np.all(ch["image_bg"][0] == ds["image_bg"][1])
assert np.all(ch["image_bg"][1] == ds["image_bg"][3])
def test_non_scalar_bad_shape():
h5path = retrieve_data("fmt-hdf5_image-bg_2020.zip")
exppath = h5path.with_name("exported.rtdc")
register_temporary_feature("peterpan", is_scalar=False)
with RTDCWriter(exppath, mode="append") as hw:
data = np.arange(10 * 3 * 5).reshape(10, 3, 5)
# This should work
hw.store_feature("peterpan", data, shape=(3, 5))
# This should not work
with pytest.raises(ValueError, match="Bad shape"):
hw.store_feature("peterpan", data, shape=(3, 6))
deregister_temporary_feature("peterpan") # cleanup
def test_data_error():
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_error_")
with pytest.raises(ValueError, match="unknown"):
RTDCWriter(rtdc_file, mode="unknown")
hw = RTDCWriter(rtdc_file)
with pytest.raises(ValueError, match="area_undefined"):
hw.store_feature("area_undefined", np.linspace(100.7, 110.9, 100))
with pytest.raises(ValueError, match="fl_unknown"):
hw.store_feature("trace", {"fl_unknown": np.arange(10)})
def test_contour_from_hdf5():
ds1 = new_dataset(retrieve_data("fmt-hdf5_image-bg_2020.zip"))
assert ds1["contour"].shape == (5, np.nan, 2)
edest = tempfile.mkdtemp()
f1 = join(edest, "dclab_test_export_hdf5_image.rtdc")
with RTDCWriter(f1) as hw:
hw.store_metadata({"setup": ds1.config["setup"],
"experiment": ds1.config["experiment"]})
hw.store_feature("deform", ds1["deform"])
hw.store_feature("contour", ds1["contour"])
ds2 = new_dataset(f1)
assert ds2["contour"].shape == (5, np.nan, 2)
def test_replace_logs():
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_replace_logs_")
hw = RTDCWriter(rtdc_file)
hw.store_log("log1", ["hans", "und"])
with h5py.File(rtdc_file, mode="r") as rtdc_data:
logs = rtdc_data["logs"]
assert len(logs["log1"]) == 2
hw = RTDCWriter(rtdc_file, mode="replace")
hw.store_log("log1", ["peter"])
with h5py.File(rtdc_file, mode="r") as rtdc_data:
logs = rtdc_data["logs"]
assert len(logs["log1"]) == 1
def test_logs_append():
log1 = ["This is a test log that contains two lines.",
"This is the second line.",
]
log2 = ["These are other logging events.",
"They are appended to the log.",
"And may have different lengths."
]
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_append_logs_")
hw = RTDCWriter(rtdc_file, mode="reset")
hw.store_log("testlog", log1)
hw.store_log("testlog", log2)
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
outlog = rtdc_data["logs"]["testlog"]
for ii in range(len(outlog)):
if isinstance(outlog[ii], bytes):
# h5py 3 reads strings as bytes by default
outii = outlog[ii].decode("utf-8")
else:
outii = outlog[ii]
assert outii == (log1 + log2)[ii]
def test_version_branding_2_dont_override_initial_version():
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_branding_")
this_version = f"dclab {dclab.__version__}"
with h5py.File(rtdc_file, "a") as h5:
h5.attrs["setup:software version"] = "Shape-In 1.2.3"
with RTDCWriter(rtdc_file) as hw:
hw.store_feature("deform", np.linspace(0.01, 0.02, 10))
expected_version = f"Shape-In 1.2.3 | {this_version}"
with h5py.File(rtdc_file) as h5:
assert h5.attrs["setup:software version"] == expected_version
def test_bulk_image():
num = 7
image = np.zeros((20, 90, 50))
image += np.arange(90).reshape(1, 90, 1)
data = {"area_um": np.linspace(100.7, 110.9, num),
"image": image}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_bulk_image_")
with RTDCWriter(rtdc_file) as hw:
for feat in data:
hw.store_feature(feat, data[feat])
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert "image" in events.keys()
assert np.allclose(events["image"][6], image[6])
def test_ic_fmt_hdf5_logs():
h5path = retrieve_data("fmt-hdf5_fl_2018.zip")
hw = RTDCWriter(h5path)
hw.store_log("test", ["asdasd" * 100])
hw.store_log("M1_para.ini", ["asdasd" * 100])
with check.IntegrityChecker(h5path) as ic:
cues = ic.check_fmt_hdf5()
assert len(cues) == 1
assert cues[0].category == "format HDF5"
assert cues[0].msg == 'Logs: test line 0 exceeds maximum line length 100'
assert cues[0].level == "alert"
def test_bulk_trace():
num = 20
trace = {"fl1_median": np.arange(num * 111).reshape(num, 111),
"fl1_raw": 13 + np.arange(num * 111).reshape(num, 111),
}
data = {"area_um": np.linspace(100.7, 110.9, num),
"trace": trace}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_bulk_trace_")
with RTDCWriter(rtdc_file) as hw:
for feat in data:
hw.store_feature(feat, data[feat])
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert "trace" in events.keys()
assert np.allclose(events["trace"]["fl1_raw"], trace["fl1_raw"])
def test_version_branding_4_dont_write_attribute():
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_branding_")
this_version = f"dclab {dclab.__version__}"
with h5py.File(rtdc_file, "a") as h5:
h5.attrs["setup:software version"] = "Shape-In 1.2.3"
with RTDCWriter(rtdc_file) as hw:
hw.store_feature("deform", np.linspace(0.01, 0.02, 10))
hw.version_brand(old_version="Peter 1.0", write_attribute=False)
expected_version = f"Shape-In 1.2.3 | {this_version}"
with h5py.File(rtdc_file) as h5:
assert h5.attrs["setup:software version"] == expected_version
def test_meta_error():
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_error_meta_")
meta1 = {"rediculous_section": {"a": 4}}
hw = RTDCWriter(rtdc_file)
with pytest.raises(ValueError, match="rediculous_section"):
hw.store_metadata(meta1)
meta2 = {"setup": {"rediculous_key": 4}}
with pytest.raises(ValueError, match="rediculous_key"):
hw.store_metadata(meta2)
def test_bulk_contour():
num = 7
contour = []
for ii in range(5, num + 5):
cii = np.arange(2 * ii).reshape(2, ii)
contour.append(cii)
data = {"area_um": np.linspace(100.7, 110.9, num),
"contour": contour}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_bulk_contour_")
with RTDCWriter(rtdc_file) as hw:
for feat in data:
hw.store_feature(feat, data[feat])
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert "contour" in events.keys()
assert np.allclose(events["contour"]["6"], contour[6])
assert events["contour"]["1"].shape == (2, 6)
def test_real_time():
# Create huge array
n = 116
# Writing 10 images at a time is faster than writing one image at a time
m = 4
assert n // m == np.round(n / m)
shx = 48
shy = 32
contours = [np.arange(20).reshape(10, 2)] * m
images = np.zeros((m, shy, shx), dtype=np.uint8)
masks = np.zeros((m, shy, shx), dtype=np.bool_)
traces = {"fl1_median": np.arange(m * 55).reshape(m, 55)}
axis1 = np.linspace(0, 1, m)
axis2 = np.arange(float(m))
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_realtime_")
with RTDCWriter(rtdc_file, mode="reset") as hw:
# simulate real time and write one image at a time
for ii in range(n // m):
# print(ii)
num_img = np.copy(images) + ii
data = {"area_um": axis1,
"area_cvx": axis2,
"image": num_img,
"contour": contours,
"mask": masks,
"trace": traces}
for feat in data:
hw.store_feature(feat, data[feat])
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert events["image"].shape == (n, shy, shx)
assert events["area_um"].shape == (n,)
assert events["contour"]["0"].shape == (10, 2)
assert events["trace"]["fl1_median"].shape == (n, 55)
assert np.dtype(events["area_um"]) == float
assert np.dtype(events["area_cvx"]) == float
def test_bulk_mask():
num = 7
mask = []
for ii in range(5, num + 5):
mii = np.zeros(200, dtype=bool)
mii[:ii] = True
mask.append(mii.reshape(20, 10))
data = {"area_um": np.linspace(100.7, 110.9, num),
"mask": mask}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_bulk_mask_")
with RTDCWriter(rtdc_file) as hw:
for feat in data:
hw.store_feature(feat, data[feat])
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert "mask" in events.keys()
# Masks are stored as uint8
assert np.allclose(events["mask"][6], mask[6]*255)
assert events["mask"][1].shape == (20, 10)
def test_meta_bytes():
data = {"area_um": np.linspace(100.7, 110.9, 100)}
meta = {
"setup": {
"channel width": 20,
"chip region": b"channel" # bytes should be converted to str
},
"experiment": {
"date": b"2020-08-12" # bytes should be converted to str
}}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_meta_")
with RTDCWriter(rtdc_file) as hw:
for feat in data:
hw.store_feature(feat, data[feat])
hw.store_metadata(meta)
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
assert rtdc_data.attrs["setup:channel width"] == 20
assert rtdc_data.attrs["setup:chip region"] == "channel"
assert rtdc_data.attrs["experiment:date"] == "2020-08-12"
def test_real_time_single():
# Create huge array
n = 33
shx = 30
shy = 10
image = np.zeros((shy, shx), dtype=np.uint8)
mask = np.zeros((shy, shx), dtype=np.bool_)
contour = np.arange(22).reshape(11, 2)
trace = {"fl1_median": np.arange(43)}
rtdc_file = tempfile.mktemp(suffix=".rtdc",
prefix="dclab_test_realtime_single_")
with RTDCWriter(rtdc_file, mode="reset") as hw:
# simulate real time and write one event at a time
for ii in range(n):
data = {"area_um": ii * .1,
"area_cvx": ii * 5.,
"image": image * ii,
"contour": contour,
"mask": mask,
"trace": trace}
for feat in data:
hw.store_feature(feat, data[feat])
hw.store_log("log1", f"line {ii}")
# Read the file:
with h5py.File(rtdc_file, mode="r") as rtdc_data:
events = rtdc_data["events"]
assert events["image"].shape == (n, shy, shx)
assert events["area_um"].shape == (n,)
assert events["contour"]["0"].shape == (11, 2)
assert events["trace"]["fl1_median"].shape == (n, 43)
assert np.dtype(events["area_um"]) == float
assert np.dtype(events["area_cvx"]) == float
logs = rtdc_data["logs"]
assert len(logs["log1"]) == n