def test_sa_h5py_5():
"""
Test querying if the HDF5 file is a storm-analysis file.
"""
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Open empty file.
with saH5Py.SAH5Py(h5_name, is_existing=False) as h5:
pass
assert (saH5Py.isSAHDF5(h5_name))
# Create generic HDF5 file.
f = h5py.File(h5_name, "w")
f.close()
assert (not saH5Py.isSAHDF5(h5_name))
# Create Insight3 file.
with i3w.I3Writer(h5_name) as i3:
pass
assert not (saH5Py.isSAHDF5(h5_name))
def test_sa_h5py_5():
"""
Test querying if the HDF5 file is a storm-analysis file.
"""
filename = "test_sa_hdf5.hdf5"
h5_name = storm_analysis.getPathOutputTest(filename)
storm_analysis.removeFile(h5_name)
# Open empty file.
with saH5Py.SAH5Py(h5_name, is_existing = False) as h5:
pass
assert(saH5Py.isSAHDF5(h5_name))
# Create generic HDF5 file.
f = h5py.File(h5_name, "w")
f.close()
assert(not saH5Py.isSAHDF5(h5_name))
# Create Insight3 file.
with i3w.I3Writer(h5_name) as i3:
pass
assert not(saH5Py.isSAHDF5(h5_name))
def handleLoadLocs2(self):
list_filename = QtWidgets.QFileDialog.getOpenFileName(
self, "Load Localization List 2", self.directory,
"*.bin *.hdf5")[0]
if list_filename:
if self.locs2_list is not None:
self.locs2_list.cleanUp()
self.directory = os.path.dirname(list_filename)
if saH5Py.isSAHDF5(list_filename):
self.locs2_list = MoleculeListHDF5(filename=list_filename,
mtype="l2")
else:
self.locs2_list = MoleculeListI3(filename=list_filename,
mtype="l2")
self.locs2_table.showFields(self.locs2_list.getFields())
self.incCurFrame(0)
def handleLoadLocs2(self):
list_filename = QtWidgets.QFileDialog.getOpenFileName(self,
"Load Localization List 2",
self.directory,
"*.bin *.hdf5")[0]
if list_filename:
if self.locs2_list is not None:
self.locs2_list.cleanUp()
self.directory = os.path.dirname(list_filename)
if saH5Py.isSAHDF5(list_filename):
self.locs2_list = MoleculeListHDF5(filename = list_filename,
mtype = "l2")
else:
self.locs2_list = MoleculeListI3(filename = list_filename,
mtype = "l2")
self.locs2_table.showFields(self.locs2_list.getFields())
self.incCurFrame(0)
def getPeakLocations(peak_filename, margin, pixel_size, sigma):
"""
This is for if you already know where your want fitting to happen, as
for example in a bead calibration movie and you just want to use the
approximate locations as inputs for fitting.
There are two choices for peak_locations file format:
1. A text file with the peak x, y, height and background values as
white spaced columns (x and y positions are in pixels as determined
using visualizer).
1.0 2.0 1000.0 100.0
10.0 5.0 2000.0 200.0
...
2. An HDF5 format localization file. This is treated in a similar
fashion to the text file in that all of the locations are loaded.
If the fields 'xsigma' or 'ysigma' exist they will be used for
the initial X/Y sigma values of the localization.
"""
if os.path.exists(peak_filename):
print("Using peak starting locations specified in", peak_filename)
elif os.path.exists(os.path.basename(peak_filename)):
peak_filename = os.path.basename(peak_filename)
print("Using peak starting locations specified in", peak_filename)
# Check if the file is a storm-analysis HDF5 file.
#
if saH5Py.isSAHDF5(peak_filename):
peak_locations_type = "hdf5"
peak_locations = saH5Py.loadLocalizations(peak_filename)
if not "ysigma" in peak_locations:
if not "xsigma" in peak_locations:
peak_locations["xsigma"] = numpy.ones(
peak_locations["x"].size) * sigma
peak_locations["ysigma"] = peak_locations["xsigma"].copy()
else:
peak_locations_type = "text"
# Load peak x,y locations.
peak_locs = numpy.loadtxt(peak_filename, ndmin=2)
# Create peak dictionary.
peak_locations = {
"background": peak_locs[:, 3],
"height": peak_locs[:, 2],
"x": peak_locs[:, 0],
"y": peak_locs[:, 1]
}
peak_locations["xsigma"] = numpy.ones(peak_locations["x"].size) * sigma
peak_locations["ysigma"] = numpy.ones(peak_locations["x"].size) * sigma
peak_locations["z"] = numpy.zeros(peak_locations["x"].size)
# Adjust positions for finding/fitting margin.
peak_locations["x"] += margin
peak_locations["y"] += margin
print("Loaded", peak_locations["x"].size, "peak locations")
#
# We return is_text as the caller might want to do different things if
# the file is text, like initialize the Z value.
#
return [peak_locations, peak_locations_type]