def test_tracker_8():
"""
Test tracking over an empty frame.
"""
peaks = {"x" : numpy.array([1.0, 2.0, 3.0]),
"y" : numpy.array([1.0, 1.0, 1.0]),
"sum" : numpy.array([4.0, 4.0, 4.0])}
empty = {"x" : numpy.array([]),
"y" : numpy.array([]),
"sum" : numpy.array([])}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing = False) as h5:
h5.addLocalizations(peaks, 0)
h5.addLocalizations(empty, 1)
h5.addLocalizations(peaks, 2)
h5.addMovieInformation(FakeReader(n_frames = 3))
# Track.
tracker.tracker(h5_name, descriptor = "111", radius = 0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert(h5.getNTracks() == 6)
for t in h5.tracksIterator():
assert(numpy.allclose(numpy.ones(6), t["track_length"]))
def test_tracker_5():
"""
Test that nearest track is assigned to the nearest object.
"""
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing = False) as h5:
peaks = {"x" : numpy.array([1.0, 2.0, 3.0]),
"y" : numpy.array([1.0, 1.0, 1.0]),
"sum" : numpy.array([4.0, 4.0, 4.0])}
h5.addLocalizations(peaks, 0)
peaks = {"x" : numpy.array([2.0]),
"y" : numpy.array([1.0]),
"sum" : numpy.array([4.0])}
h5.addLocalizations(peaks, 1)
h5.addMovieInformation(FakeReader(n_frames = 2))
# Track.
tracker.tracker(h5_name, radius = 1.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert(h5.getNTracks() == 3)
for t in h5.tracksIterator():
assert(numpy.allclose(numpy.array([1,3,2]), t["x"]))
assert(numpy.allclose(numpy.array([0,2,1]), t["track_id"]))
assert(numpy.allclose(numpy.array([1,1,2]), t["track_length"]))
def test_tracker_6():
"""
Test max_gap parameter.
"""
peaks = {"x" : numpy.array([1.0, 2.0, 3.0]),
"y" : numpy.array([1.0, 1.0, 1.0]),
"sum" : numpy.array([4.0, 4.0, 4.0])}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing = False) as h5:
h5.addLocalizations(peaks, 0)
h5.addLocalizations(peaks, 2)
h5.addMovieInformation(FakeReader(n_frames = 3))
# Track.
tracker.tracker(h5_name, radius = 0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert(h5.getNTracks() == 6)
for t in h5.tracksIterator():
assert(numpy.allclose(t["track_length"], numpy.ones(6)))
# Redo the tracking allowing single frame gaps.
tracker.tracker(h5_name, max_gap = 1, radius = 0.1)
with saH5Py.SAH5Py(h5_name) as h5:
assert(h5.getNTracks() == 3)
for t in h5.tracksIterator():
assert(numpy.allclose(t["track_length"], 2.0*numpy.ones(3)))
def test_tracker_8():
"""
Test tracking over an empty frame.
"""
peaks = {
"x": numpy.array([1.0, 2.0, 3.0]),
"y": numpy.array([1.0, 1.0, 1.0]),
"sum": numpy.array([4.0, 4.0, 4.0])
}
empty = {
"x": numpy.array([]),
"y": numpy.array([]),
"sum": numpy.array([])
}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing=False) as h5:
h5.addLocalizations(peaks, 0)
h5.addLocalizations(empty, 1)
h5.addLocalizations(peaks, 2)
h5.addMovieInformation(FakeReader(n_frames=3))
# Track.
tracker.tracker(h5_name, descriptor="111", radius=0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert (h5.getNTracks() == 6)
for t in h5.tracksIterator():
assert (numpy.allclose(numpy.ones(6), t["track_length"]))
def trackDriftCorrect(h5_name, parameters):
"""
Does tracking and drift correction, as well as '3d' z
fitting (if requested).
"""
# Z fitting, '3d' model, localizations.
#
if parameters.hasAttr("do_zfit") and (parameters.getAttr("do_zfit", 0) !=
0):
if (parameters.getAttr("model", "") == "3d"):
print()
print("'3d' localization z fitting.")
zFitting(h5_name, parameters, False)
# Drift correction.
#
if (parameters.getAttr("drift_correction", 0) != 0):
print()
print("Drift Correction.")
driftCorrection(h5_name, parameters)
# Tracking and averaging.
#
# This also adds the category field to the localizations.
#
print()
print("Tracking.")
tracker.tracker(h5_name,
descriptor=parameters.getAttr("descriptor"),
max_gap=parameters.getAttr("max_gap", 0),
radius=parameters.getAttr("radius"))
# Z fitting, '3d' model, tracks.
#
if parameters.hasAttr("do_zfit") and (parameters.getAttr("do_zfit", 0) !=
0):
if (parameters.getAttr("model", "") == "3d"):
print()
print("'3d' tracks z fitting.")
zFitting(h5_name, parameters, True)
# Mark out of z range localizations and tracks as category 9.
#
print()
print("Checking z values.")
zCheck(h5_name, parameters)
def test_tracker_2():
"""
Test descriptor.
"""
peaks = {
"x": numpy.array([1.0, 2.0, 3.0]),
"y": numpy.array([1.0, 1.0, 1.0]),
"sum": numpy.array([4.0, 4.0, 4.0])
}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing=False) as h5:
for i in range(4):
temp = {}
for elt in peaks:
temp[elt] = peaks[elt][:i]
if (len(temp["x"]) > 0):
h5.addLocalizations(temp, i)
h5.addMovieInformation(FakeReader(n_frames=4))
# Track.
tracker.tracker(h5_name, descriptor="1212", radius=0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert (h5.getNTracks() == 3)
for t in h5.tracksIterator():
assert (numpy.allclose(peaks["x"], t["x"]))
assert (numpy.allclose(peaks["y"], t["y"]))
assert (numpy.allclose(numpy.array([1, 0, 1]), t["category"]))
# Check localization categories.
for fnum, locs in h5.localizationsIterator(fields=["category"]):
if (fnum == 1):
assert (numpy.allclose(numpy.array([1]), locs["category"]))
if (fnum == 2):
assert (numpy.allclose(numpy.array([0, 0]), locs["category"]))
if (fnum == 3):
assert (numpy.allclose(numpy.array([1, 1, 1]),
locs["category"]))
def trackDriftCorrect(h5_name, parameters):
"""
Does tracking and drift correction, as well as '3d' z
fitting (if requested).
"""
# Z fitting, '3d' model, localizations.
#
if parameters.hasAttr("do_zfit") and (parameters.getAttr("do_zfit", 0) != 0):
if (parameters.getAttr("model", "") == "3d"):
print()
print("'3d' localization z fitting.")
zFitting(h5_name, parameters, False)
# Drift correction.
#
if (parameters.getAttr("drift_correction", 0) != 0):
print()
print("Drift Correction.")
driftCorrection(h5_name, parameters)
# Tracking and averaging.
#
# This also adds the category field to the localizations.
#
print()
print("Tracking.")
tracker.tracker(h5_name,
descriptor = parameters.getAttr("descriptor"),
max_gap = parameters.getAttr("max_gap", 0),
radius = parameters.getAttr("radius"))
# Z fitting, '3d' model, tracks.
#
if parameters.hasAttr("do_zfit") and (parameters.getAttr("do_zfit", 0) != 0):
if (parameters.getAttr("model", "") == "3d"):
print()
print("'3d' tracks z fitting.")
zFitting(h5_name, parameters, True)
# Mark out of z range localizations and tracks as category 9.
#
print()
print("Checking z values.")
zCheck(h5_name, parameters)
def test_tracker_1():
"""
Basic tracking test.
"""
peaks = {
"x": numpy.array([1.0, 2.0, 3.0]),
"y": numpy.array([1.0, 1.0, 1.0]),
"sum": numpy.array([4.0, 4.0, 4.0])
}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing=False) as h5:
for i in range(3):
temp = {}
for elt in peaks:
temp[elt] = peaks[elt][i:]
h5.addLocalizations(temp, i)
h5.addMovieInformation(FakeReader(n_frames=3))
# Track.
tracker.tracker(h5_name, radius=0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
# Check that we have the right number of tracks.
assert (h5.getNTracks() == 3)
# Check tracks.
for t in h5.tracksIterator():
assert (numpy.allclose(peaks["x"], t["x"]))
assert (numpy.allclose(peaks["y"], t["y"]))
assert (numpy.allclose(numpy.array([0, 0, 0]), t["frame_number"]))
assert (numpy.allclose(numpy.array([1, 2, 3]), t["track_length"]))
# Check that the localizations 'track_id' field is correct.
for fnum, locs in h5.localizationsIterator(fields=["track_id"]):
assert (numpy.allclose(
numpy.array([0, 1, 2])[fnum:], locs["track_id"]))
def test_tracker_2():
"""
Test descriptor.
"""
peaks = {"x" : numpy.array([1.0, 2.0, 3.0]),
"y" : numpy.array([1.0, 1.0, 1.0]),
"sum" : numpy.array([4.0, 4.0, 4.0])}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing = False) as h5:
for i in range(4):
temp = {}
for elt in peaks:
temp[elt] = peaks[elt][:i]
if(len(temp["x"])>0):
h5.addLocalizations(temp, i)
h5.addMovieInformation(FakeReader(n_frames = 4))
# Track.
tracker.tracker(h5_name, descriptor = "1212", radius = 0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert(h5.getNTracks() == 3)
for t in h5.tracksIterator():
assert(numpy.allclose(peaks["x"], t["x"]))
assert(numpy.allclose(peaks["y"], t["y"]))
assert(numpy.allclose(numpy.array([1,0,1]), t["category"]))
# Check localization categories.
for fnum, locs in h5.localizationsIterator(fields = ["category"]):
if (fnum == 1):
assert(numpy.allclose(numpy.array([1]), locs["category"]))
if (fnum == 2):
assert(numpy.allclose(numpy.array([0, 0]), locs["category"]))
if (fnum == 3):
assert(numpy.allclose(numpy.array([1, 1, 1]), locs["category"]))
def test_tracker_1():
"""
Basic tracking test.
"""
peaks = {"x" : numpy.array([1.0, 2.0, 3.0]),
"y" : numpy.array([1.0, 1.0, 1.0]),
"sum" : numpy.array([4.0, 4.0, 4.0])}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing = False) as h5:
for i in range(3):
temp = {}
for elt in peaks:
temp[elt] = peaks[elt][i:]
h5.addLocalizations(temp, i)
h5.addMovieInformation(FakeReader(n_frames = 3))
# Track.
tracker.tracker(h5_name, radius = 0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
# Check that we have the right number of tracks.
assert(h5.getNTracks() == 3)
# Check tracks.
for t in h5.tracksIterator():
assert(numpy.allclose(peaks["x"], t["x"]))
assert(numpy.allclose(peaks["y"], t["y"]))
assert(numpy.allclose(numpy.array([0,0,0]), t["frame_number"]))
assert(numpy.allclose(numpy.array([1,2,3]), t["track_length"]))
# Check that the localizations 'track_id' field is correct.
for fnum, locs in h5.localizationsIterator(fields = ["track_id"]):
assert(numpy.allclose(numpy.array([0,1,2])[fnum:], locs["track_id"]))
def test_tracker_6():
"""
Test max_gap parameter.
"""
peaks = {
"x": numpy.array([1.0, 2.0, 3.0]),
"y": numpy.array([1.0, 1.0, 1.0]),
"sum": numpy.array([4.0, 4.0, 4.0])
}
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing=False) as h5:
h5.addLocalizations(peaks, 0)
h5.addLocalizations(peaks, 2)
h5.addMovieInformation(FakeReader(n_frames=3))
# Track.
tracker.tracker(h5_name, radius=0.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert (h5.getNTracks() == 6)
for t in h5.tracksIterator():
assert (numpy.allclose(t["track_length"], numpy.ones(6)))
# Redo the tracking allowing single frame gaps.
tracker.tracker(h5_name, max_gap=1, radius=0.1)
with saH5Py.SAH5Py(h5_name) as h5:
assert (h5.getNTracks() == 3)
for t in h5.tracksIterator():
assert (numpy.allclose(t["track_length"], 2.0 * numpy.ones(3)))
def test_tracker_5():
"""
Test that nearest track is assigned to the nearest object.
"""
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Write data.
with saH5Py.SAH5Py(h5_name, is_existing=False) as h5:
peaks = {
"x": numpy.array([1.0, 2.0, 3.0]),
"y": numpy.array([1.0, 1.0, 1.0]),
"sum": numpy.array([4.0, 4.0, 4.0])
}
h5.addLocalizations(peaks, 0)
peaks = {
"x": numpy.array([2.0]),
"y": numpy.array([1.0]),
"sum": numpy.array([4.0])
}
h5.addLocalizations(peaks, 1)
h5.addMovieInformation(FakeReader(n_frames=2))
# Track.
tracker.tracker(h5_name, radius=1.1)
# Tracking.
with saH5Py.SAH5Py(h5_name) as h5:
assert (h5.getNTracks() == 3)
for t in h5.tracksIterator():
assert (numpy.allclose(numpy.array([1, 3, 2]), t["x"]))
assert (numpy.allclose(numpy.array([0, 2, 1]), t["track_id"]))
assert (numpy.allclose(numpy.array([1, 1, 2]), t["track_length"]))