def test_cancel(self):
"""
try a bit the cancelling possibility
"""
# create a little complex streamTree
st = stream.StreamTree(streams=[
self.streams[2],
stream.StreamTree(streams=self.streams[0:2])
])
self.start = None
self.end = None
self.updates = 0
self.done = False
f = acq.acquire(st.getProjections())
f.add_update_callback(self.on_progress_update)
f.add_done_callback(self.on_done)
time.sleep(0.5) # make sure it's started
self.assertTrue(f.running())
f.cancel()
self.assertRaises(CancelledError, f.result, 1)
self.assertGreaterEqual(self.updates,
1) # at least one update at cancellation
self.assertLessEqual(self.end, time.time())
self.assertTrue(self.done)
self.assertTrue(f.cancelled())
def test_metadata(self):
"""
Check if extra metadata are saved
"""
settings_obs = SettingsObserver(model.getComponents())
self.ccd.binning.value = (
1, 1) # make sure we don't save the right metadata by accident
detvas = {'exposureTime', 'binning', 'gain'}
s1 = stream.FluoStream("fluo2",
self.ccd,
self.ccd.data,
self.light,
self.light_filter,
detvas=detvas)
s2 = stream.BrightfieldStream("bf",
self.ccd,
self.ccd.data,
self.light,
detvas=detvas)
# Set different binning values for each stream
s1.detBinning.value = (2, 2)
s2.detBinning.value = (4, 4)
st = stream.StreamTree(streams=[s1, s2])
f = acqmng.acquire(st.getProjections(), settings_obs=settings_obs)
data, e = f.result()
for s in data:
self.assertTrue(model.MD_EXTRA_SETTINGS in s.metadata,
"Stream %s didn't save extra metadata." % s)
self.assertEqual(
data[0].metadata[model.MD_EXTRA_SETTINGS][self.ccd.name]
['binning'], [(2, 2), 'px'])
self.assertEqual(
data[1].metadata[model.MD_EXTRA_SETTINGS][self.ccd.name]
['binning'], [(4, 4), 'px'])
def test_sync_sem_ccd(self):
"""
try acquisition with fairly complex SEM/CCD stream
"""
# Create the streams and streamTree
semsur = stream.SEMStream("test sem", self.sed, self.sed.data,
self.ebeam)
sems = stream.SEMStream("test sem cl", self.sed, self.sed.data,
self.ebeam)
ars = stream.ARSettingsStream("test ar", self.ccd, self.ccd.data,
self.ebeam)
semars = stream.SEMARMDStream("test SEM/AR", [sems, ars])
st = stream.StreamTree(streams=[semsur, semars])
# SEM survey settings are via the current hardware settings
self.ebeam.dwellTime.value = self.ebeam.dwellTime.range[0]
# SEM/AR settings are via the AR stream
ars.roi.value = (0.1, 0.1, 0.8, 0.8)
mx_brng = self.ccd.binning.range[1]
binning = tuple(min(4, mx) for mx in mx_brng) # try binning 4x4
self.ccd.binning.value = binning
self.ccd.exposureTime.value = 1 # s
ars.repetition.value = (2, 3)
num_ar = numpy.prod(ars.repetition.value)
est_time = acq.estimateTime(st.getProjections())
# prepare callbacks
self.start = None
self.end = None
self.updates = 0
self.done = 0
# Run acquisition
start = time.time()
f = acq.acquire(st.getProjections())
f.add_update_callback(self.on_progress_update)
f.add_done_callback(self.on_done)
data, e = f.result()
dur = time.time() - start
self.assertGreaterEqual(dur, est_time /
2) # Estimated time shouldn't be too small
self.assertIsInstance(data[0], model.DataArray)
self.assertIsNone(e)
self.assertEqual(len(data), num_ar + 2)
thumb = acq.computeThumbnail(st, f)
self.assertIsInstance(thumb, model.DataArray)
self.assertGreaterEqual(self.updates, 1) # at least one update at end
self.assertLessEqual(self.end, time.time())
self.assertTrue(not f.cancelled())
time.sleep(0.1)
self.assertEqual(self.done, 1)
def test_progress(self):
"""
Check we get some progress updates
"""
# create a little complex streamTree
st = stream.StreamTree(streams=[
self.streams[0],
stream.StreamTree(streams=self.streams[1:3])
])
self.past = None
self.left = None
self.updates = 0
f = acq.acquire(st.getStreams())
f.add_update_callback(self.on_progress_update)
data = f.result()
self.assertIsInstance(data[0], model.DataArray)
self.assertGreaterEqual(self.updates, 3) # at least one update per stream
def test_simple(self):
# create a simple streamTree
st = stream.StreamTree(streams=[self.streams[0]])
f = acq.acquire(st.getStreams())
data = f.result()
self.assertIsInstance(data[0], model.DataArray)
thumb = acq.computeThumbnail(st, f)
self.assertIsInstance(thumb, model.DataArray)
# let's do it a second time, "just for fun"
f = acq.acquire(st.getStreams())
data = f.result()
self.assertIsInstance(data[0], model.DataArray)
thumb = acq.computeThumbnail(st, f)
self.assertIsInstance(thumb, model.DataArray)
def _export_to_file(self, acq_future):
"""
return (list of DataArray, filename): data exported and filename
"""
streams = list(self._tab_data_model.acquisitionStreams)
st = stream.StreamTree(streams=streams)
thumb = acqmng.computeThumbnail(st, acq_future)
data, exp = acq_future.result()
filename = self.filename.value
if data:
exporter = dataio.get_converter(self.conf.last_format)
exporter.export(filename, data, thumb)
logging.info(u"Acquisition saved as file '%s'.", filename)
else:
logging.debug("Not saving into file '%s' as there is no data", filename)
return data, exp, filename
def test_leech(self):
"""
try acquisition with leech
"""
# Create the streams and streamTree
semsur = stream.SEMStream("test sem", self.sed, self.sed.data,
self.ebeam)
sems = stream.SEMStream("test sem cl", self.sed, self.sed.data,
self.ebeam)
ars = stream.ARSettingsStream("test ar", self.ccd, self.ccd.data,
self.ebeam)
semars = stream.SEMARMDStream("test SEM/AR", [sems, ars])
st = stream.StreamTree(streams=[semsur, semars])
pcd = Fake0DDetector("test")
pca = ProbeCurrentAcquirer(pcd)
sems.leeches.append(pca)
semsur.leeches.append(pca)
# SEM survey settings are via the current hardware settings
self.ebeam.dwellTime.value = self.ebeam.dwellTime.range[0]
# SEM/AR settings are via the AR stream
ars.roi.value = (0.1, 0.1, 0.8, 0.8)
mx_brng = self.ccd.binning.range[1]
binning = tuple(min(4, mx) for mx in mx_brng) # try binning 4x4
self.ccd.binning.value = binning
self.ccd.exposureTime.value = 1 # s
ars.repetition.value = (2, 3)
num_ar = numpy.prod(ars.repetition.value)
pca.period.value = 10 # Only at beginning and end
est_time = acq.estimateTime(st.getProjections())
# prepare callbacks
self.start = None
self.end = None
self.updates = 0
self.done = 0
# Run acquisition
start = time.time()
f = acq.acquire(st.getProjections())
f.add_update_callback(self.on_progress_update)
f.add_done_callback(self.on_done)
data, e = f.result()
dur = time.time() - start
self.assertGreaterEqual(dur, est_time /
2) # Estimated time shouldn't be too small
self.assertIsInstance(data[0], model.DataArray)
self.assertIsNone(e)
self.assertEqual(len(data), num_ar + 2)
thumb = acq.computeThumbnail(st, f)
self.assertIsInstance(thumb, model.DataArray)
self.assertGreaterEqual(self.updates, 1) # at least one update at end
self.assertLessEqual(self.end, time.time())
self.assertTrue(not f.cancelled())
time.sleep(0.1)
self.assertEqual(self.done, 1)
for da in data:
pcmd = da.metadata[model.MD_EBEAM_CURRENT_TIME]
self.assertEqual(len(pcmd), 2)
def test_sync_path_guess(self):
"""
try synchronized acquisition using the Optical Path Manager
"""
# Create the streams and streamTree
opmngr = path.OpticalPathManager(self.microscope)
semsur = stream.SEMStream("test sem", self.sed, self.sed.data,
self.ebeam)
sems = stream.SEMStream("test sem cl", self.sed, self.sed.data,
self.ebeam)
ars = stream.ARSettingsStream("test ar",
self.ccd,
self.ccd.data,
self.ebeam,
opm=opmngr)
semars = stream.SEMARMDStream("test SEM/AR", [sems, ars])
specs = stream.SpectrumSettingsStream("test spec",
self.spec,
self.spec.data,
self.ebeam,
opm=opmngr)
sps = stream.SEMSpectrumMDStream("test sem-spec", [sems, specs])
st = stream.StreamTree(streams=[semsur, semars, sps])
# SEM survey settings are via the current hardware settings
self.ebeam.dwellTime.value = self.ebeam.dwellTime.range[0]
# SEM/AR/SPEC settings are via the AR stream
ars.roi.value = (0.1, 0.1, 0.8, 0.8)
specs.roi.value = (0.2, 0.2, 0.7, 0.7)
mx_brng = self.ccd.binning.range[1]
binning = tuple(min(4, mx) for mx in mx_brng) # try binning 4x4
self.ccd.binning.value = binning
self.ccd.exposureTime.value = 1 # s
ars.repetition.value = (2, 3)
specs.repetition.value = (3, 2)
num_ar = numpy.prod(ars.repetition.value)
est_time = acq.estimateTime(st.getProjections())
# prepare callbacks
self.start = None
self.end = None
self.updates = 0
self.done = 0
# Run acquisition
start = time.time()
f = acq.acquire(st.getProjections())
f.add_update_callback(self.on_progress_update)
f.add_done_callback(self.on_done)
data, e = f.result()
dur = time.time() - start
self.assertGreaterEqual(dur, est_time /
2) # Estimated time shouldn't be too small
self.assertIsInstance(data[0], model.DataArray)
self.assertIsNone(e)
self.assertEqual(len(data), num_ar + 4)
thumb = acq.computeThumbnail(st, f)
self.assertIsInstance(thumb, model.DataArray)
self.assertGreaterEqual(self.updates, 1) # at least one update at end
self.assertLessEqual(self.end, time.time())
self.assertTrue(not f.cancelled())
# assert optical path configuration
exp_pos = path.SPARC_MODES["spectral"][1]
self.assertEqual(self.lenswitch.position.value, exp_pos["lens-switch"])
self.assertEqual(self.spec_det_sel.position.value,
exp_pos["spec-det-selector"])
self.assertEqual(self.ar_spec_sel.position.value,
exp_pos["ar-spec-selector"])
time.sleep(0.1)
self.assertEqual(self.done, 1)
