def test_pupilfn_8():
"""
Test that pupilfn.make_pupil_fn.makePupilFunction works as expected.
"""
pf_size = 30
zmn = [[1.3, 2, 2]]
z_offset = -0.3
# Create & save pupil function.
pf_file = storm_analysis.getPathOutputTest("pf_test.pfn")
makePupilFn.makePupilFunction(pf_file, pf_size, 0.1, zmn, z_offset = z_offset)
# Load PF.
with open(pf_file, "rb") as fp:
pf_data = pickle.load(fp)
test_pf = pf_data["pf"]
# Create comparison PF.
geo = pupilMath.GeometrySim(pf_size,
pf_data["pixel_size"],
pf_data["wavelength"],
pf_data["immersion_index"],
pf_data["numerical_aperture"])
ref_pf = geo.createFromZernike(1.0, zmn)
# Normalize reference to also have height 1.0 (at z = 0.0).
psf = pupilMath.intensity(pupilMath.toRealSpace(ref_pf))
ref_pf = ref_pf * 1.0/math.sqrt(numpy.max(psf))
# Test that they are the same.
for z in [-0.2, -0.1, 0.0, 0.1, 0.2]:
test_psf = pupilMath.intensity(pupilMath.toRealSpace(geo.changeFocus(test_pf, z)))
ref_psf = pupilMath.intensity(pupilMath.toRealSpace(geo.changeFocus(ref_pf, z - z_offset)))
#print(numpy.max(numpy.abs(test_psf - ref_psf)))
assert numpy.allclose(test_psf, ref_psf)
def configure():
# Create directory, if necessary.
if not os.path.exists(settings.wdir):
os.makedirs(settings.wdir)
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters()
params.toXMLFile("multiplane.xml")
# Create localization on a grid file.
#
print("Creating gridded localization.")
emittersOnGrid.emittersOnGrid("grid_list.hdf5", settings.nx, settings.ny,
1.5, 20, settings.test_z_range,
settings.test_z_offset)
# Create sCMOS camera calibration files.
#
numpy.save(os.path.join(settings.wdir, "calib.npy"), [
numpy.zeros(
(settings.y_size, settings.x_size)) + settings.camera_offset,
numpy.ones(
(settings.y_size, settings.x_size)) * settings.camera_variance,
numpy.ones((settings.y_size, settings.x_size)) * settings.camera_gain,
numpy.ones((settings.y_size, settings.x_size)), 2
])
shutil.copyfile(os.path.join(settings.wdir, "calib.npy"), "calib.npy")
# Create mapping file.
with open(os.path.join(settings.wdir, "map.map"), 'wb') as fp:
pickle.dump(settings.mappings, fp)
shutil.copyfile(os.path.join(settings.wdir, "map.map"), "map.map")
# Create pupil functions for 'pupilfn'.
print("Creating pupil functions.")
for i in range(len(settings.z_planes)):
fname = "c" + str(i + 1) + "_pupilfn.pfn"
makePupilFn.makePupilFunction(os.path.join(settings.wdir, fname),
settings.psf_size,
settings.pixel_size * 1.0e-3,
settings.pupil_fn,
z_offset=-settings.z_planes[i])
shutil.copyfile(os.path.join(settings.wdir, fname), fname)
# Calculate Cramer-Rao weighting.
#
print("Calculating weights.")
planeWeighting.runPlaneWeighting("multiplane.xml",
os.path.join(settings.wdir,
"weights.npy"),
[settings.photons[0]],
settings.photons[1],
no_plots=True)
def test_pupilfn_8():
"""
Test that pupilfn.make_pupil_fn.makePupilFunction works as expected.
"""
pf_size = 30
zmn = [[1.3, 2, 2]]
z_offset = -0.3
# Create & save pupil function.
pf_file = storm_analysis.getPathOutputTest("pf_test.pfn")
makePupilFn.makePupilFunction(pf_file,
pf_size,
0.1,
zmn,
z_offset=z_offset)
# Load PF.
with open(pf_file, "rb") as fp:
pf_data = pickle.load(fp)
test_pf = pf_data["pf"]
# Create comparison PF.
geo = pupilMath.GeometrySim(pf_size, pf_data["pixel_size"],
pf_data["wavelength"],
pf_data["immersion_index"],
pf_data["numerical_aperture"])
ref_pf = geo.createFromZernike(1.0, zmn)
# Normalize reference to also have height 1.0 (at z = 0.0).
psf = pupilMath.intensity(pupilMath.toRealSpace(ref_pf))
ref_pf = ref_pf * 1.0 / math.sqrt(numpy.max(psf))
# Test that they are the same.
for z in [-0.2, -0.1, 0.0, 0.1, 0.2]:
test_psf = pupilMath.intensity(
pupilMath.toRealSpace(geo.changeFocus(test_pf, z)))
ref_psf = pupilMath.intensity(
pupilMath.toRealSpace(geo.changeFocus(ref_pf, z - z_offset)))
#print(numpy.max(numpy.abs(test_psf - ref_psf)))
assert numpy.allclose(test_psf, ref_psf)
def configure(cal_file = None):
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters(cal_file = cal_file)
params.toXMLFile("pupilfn.xml")
# Create localization on a grid file.
#
print("Creating gridded localization.")
emittersOnGrid.emittersOnGrid("grid_list.hdf5",
settings.nx,
settings.ny,
1.5,
20,
settings.test_z_range,
settings.test_z_offset)
# Create randomly located localizations file.
#
print("Creating random localization.")
emittersUniformRandom.emittersUniformRandom("random_list.hdf5",
1.0,
settings.margin,
settings.x_size,
settings.y_size,
settings.test_z_range)
# Create the pupil function.
#
print("Creating pupil function.")
makePupilFn.makePupilFunction("pupil_fn.pfn",
settings.pupil_size,
settings.pixel_size * 1.0e-3,
settings.zmn)
def configure(psf_model, no_splines):
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters(psf_model)
params.toXMLFile("multiplane.xml")
# Create localization on a grid file.
#
print("Creating gridded localization.")
emittersOnGrid.emittersOnGrid("grid_list.hdf5", settings.nx, settings.ny,
1.5, 20, settings.test_z_range,
settings.test_z_offset)
# Create randomly located localizations file.
#
print("Creating random localization.")
emittersUniformRandom.emittersUniformRandom("random_list.hdf5", 1.0,
settings.margin,
settings.x_size,
settings.y_size,
settings.test_z_range)
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
emittersOnGrid.emittersOnGrid("psf_list.hdf5", 6, 3, 1.5, 40, 0.0, 0.0)
# Create sCMOS camera calibration files.
#
numpy.save("calib.npy", [
numpy.zeros(
(settings.y_size, settings.x_size)) + settings.camera_offset,
numpy.ones(
(settings.y_size, settings.x_size)) * settings.camera_variance,
numpy.ones((settings.y_size, settings.x_size)) * settings.camera_gain,
numpy.ones((settings.y_size, settings.x_size)), 2
])
# Create mapping file.
with open("map.map", 'wb') as fp:
pickle.dump(settings.mappings, fp)
if no_splines:
return
# Create pupil functions for 'pupilfn'.
if (psf_model == "pupilfn"):
print("Creating pupil functions.")
for i in range(len(settings.z_planes)):
makePupilFn.makePupilFunction("c" + str(i + 1) + "_pupilfn.pfn",
settings.psf_size,
settings.pixel_size * 1.0e-3,
settings.pupil_fn,
z_offset=-settings.z_planes[i])
# Both 'spline' and 'psf_fft' need measured PSFs.
else:
# Create localization files for PSF measurement.
#
locs = saH5Py.loadLocalizations("psf_list.hdf5")
for i, z_offset in enumerate(settings.z_planes):
cx = settings.mappings["0_" + str(i) + "_x"]
cy = settings.mappings["0_" + str(i) + "_y"]
locs_temp = {
"x": locs["x"].copy(),
"y": locs["y"].copy(),
"z": locs["z"].copy()
}
xi = locs_temp["x"]
yi = locs_temp["y"]
xf = cx[0] + cx[1] * xi + cx[2] * yi
yf = cy[0] + cy[1] * xi + cy[2] * yi
locs_temp["x"] = xf
locs_temp["y"] = yf
locs_temp["z"][:] = z_offset
saH5Py.saveLocalizations("c" + str(i + 1) + "_psf.hdf5", locs_temp)
# Create drift file, this is used to displace the localizations in the
# PSF measurement movie.
#
dz = numpy.arange(-settings.spline_z_range,
settings.spline_z_range + 0.001, 0.01)
drift_data = numpy.zeros((dz.size, 3))
drift_data[:, 2] = dz
numpy.savetxt("drift.txt", drift_data)
# Also create the z-offset file.
#
z_offset = numpy.ones((dz.size, 2))
z_offset[:, 1] = dz
numpy.savetxt("z_offset.txt", z_offset)
# Create simulated data for PSF measurements.
#
bg_f = lambda s, x, y, h5: background.UniformBackground(
s, x, y, h5, photons=10)
cam_f = lambda s, x, y, h5: camera.SCMOS(s, x, y, h5, "calib.npy")
drift_f = lambda s, x, y, h5: drift.DriftFromFile(
s, x, y, h5, "drift.txt")
pp_f = lambda s, x, y, h5: photophysics.AlwaysOn(s, x, y, h5, 20000.0)
psf_f = lambda s, x, y, h5: psf.PupilFunction(
s, x, y, h5, settings.pixel_size, settings.pupil_fn)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
drift_factory=drift_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=settings.x_size,
y_size=settings.y_size)
for i in range(len(settings.z_planes)):
sim.simulate("c" + str(i + 1) + "_zcal.dax",
"c" + str(i + 1) + "_psf.hdf5", dz.size)
# Measure the PSF.
#
print("Measuring PSFs.")
for i in range(len(settings.z_planes)):
psfZStack.psfZStack("c" + str(i + 1) + "_zcal.dax",
"c" + str(i + 1) + "_psf.hdf5",
"c" + str(i + 1) + "_zstack",
aoi_size=int(settings.psf_size / 2 + 1))
# Measure PSF and calculate spline for Spliner.
#
if (psf_model == "spline"):
# PSFs are independently normalized.
#
if settings.independent_heights:
for i in range(len(settings.z_planes)):
mpMeasurePSF.measurePSF("c" + str(i + 1) + "_zstack.npy",
"z_offset.txt",
"c" + str(i + 1) + "_psf_normed.psf",
z_range=settings.spline_z_range,
normalize=True)
# PSFs are normalized to each other.
#
else:
for i in range(len(settings.z_planes)):
mpMeasurePSF.measurePSF("c" + str(i + 1) + "_zstack.npy",
"z_offset.txt",
"c" + str(i + 1) + "_psf.psf",
z_range=settings.spline_z_range)
norm_args = ["c1_psf.psf"]
for i in range(len(settings.z_planes) - 1):
norm_args.append("c" + str(i + 2) + "_psf.psf")
normalizePSFs.normalizePSFs(norm_args)
# Measure the spline for Spliner.
#
print("Measuring Spline.")
for i in range(len(settings.z_planes)):
psfToSpline.psfToSpline("c" + str(i + 1) + "_psf_normed.psf",
"c" + str(i + 1) + "_psf.spline",
int(settings.psf_size / 2))
# Measure PSF and downsample for PSF FFT.
#
elif (psf_model == "psf_fft"):
# PSFs are independently normalized.
#
if settings.independent_heights:
for i in range(len(settings.z_planes)):
mpMeasurePSF.measurePSF("c" + str(i + 1) + "_zstack.npy",
"z_offset.txt",
"c" + str(i + 1) + "_psf_normed.psf",
z_range=settings.spline_z_range,
normalize=True)
# PSFs are normalized to each other.
#
else:
for i in range(len(settings.z_planes)):
mpMeasurePSF.measurePSF("c" + str(i + 1) + "_zstack.npy",
"z_offset.txt",
"c" + str(i + 1) + "_psf.psf",
z_range=settings.spline_z_range)
norm_args = ["c1_psf.psf"]
for i in range(len(settings.z_planes) - 1):
norm_args.append("c" + str(i + 2) + "_psf.psf")
normalizePSFs.normalizePSFs(norm_args)
# Calculate Cramer-Rao weighting.
#
print("Calculating weights.")
planeWeighting.runPlaneWeighting("multiplane.xml",
"weights.npy", [settings.photons[0][0]],
settings.photons[0][1],
no_plots=True)
def configure():
# Create PF for pupil function.
#
print("Creating pupil function.")
pf_size = 2 * (settings.spline_size - 1)
makePupilFn.makePupilFunction("pupilfn.pfn",
pf_size,
settings.pixel_size * 1.0e-3,
settings.zmn,
z_offset=settings.z_offset)
# Create PSF using pupil functions directly.
#
if False:
print("Creating (theoritical) psf.")
makePSFFromPF.makePSF("psf_fft.psf", settings.spline_size,
settings.pixel_size * 1.0e-3, settings.zmn,
settings.psf_fft_z_range,
settings.psf_fft_z_step)
exit()
# Localizations on a sparse parse grid for PSF
# measurement for Spliner and PSF FFT.
#
print("Creating data for PSF measurement.")
emittersOnGrid.emittersOnGrid("sparse_list.hdf5", 6, 3, 1.5, 40, 0.0,
settings.z_offset)
# Create beads.txt file for spline measurement.
#
with saH5Py.SAH5Py("sparse_list.hdf5") as h5:
locs = h5.getLocalizations()
numpy.savetxt("beads.txt",
numpy.transpose(numpy.vstack((locs['x'], locs['y']))))
# Create drift file, this is used to displace the localizations in the
# PSF measurement movie.
#
dz = numpy.arange(-settings.spline_z_range,
settings.spline_z_range + 0.001, 0.01)
drift_data = numpy.zeros((dz.size, 3))
drift_data[:, 2] = dz
numpy.savetxt("drift.txt", drift_data)
# Also create the z-offset file.
#
z_offset = numpy.ones((dz.size, 2))
z_offset[:, 1] = dz
numpy.savetxt("z_offset.txt", z_offset)
# Create simulated data for PSF measurement.
#
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=10)
cam_f = lambda s, x, y, i3: camera.Ideal(s, x, y, i3, 100.0)
drift_f = lambda s, x, y, i3: drift.DriftFromFile(s, x, y, i3, "drift.txt")
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(s, x, y, i3, 20000.0)
psf_f = lambda s, x, y, i3: psf.PupilFunction(
s, x, y, i3, settings.pixel_size, settings.zmn, pf_size=pf_size)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
drift_factory=drift_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=settings.x_size,
y_size=settings.y_size)
sim.simulate("psf.dax", "sparse_list.hdf5", dz.size)
# Create spline for Spliner
#
# Measure the PSF for Spliner
#
print("Measuring PSF.")
psf_name = "psf_spliner.psf"
measurePSFBeads.measurePSFBeads("psf.dax",
"z_offset.txt",
"beads.txt",
psf_name,
aoi_size=int(settings.spline_size + 1),
pixel_size=settings.pixel_size * 1.0e-3)
# Measure the Spline.
#
# This is slow, sometimes you don't want to do it.
if True:
print("Measuring Spline.")
psfToSpline.psfToSpline(psf_name, "psf.spline", settings.spline_size)
# Create measured PSF for PSF FFT.
#
# Measure the PSF using spliner/measure_psf_beads.py
#
print("Measuring PSF.")
measurePSFBeads.measurePSFBeads("psf.dax",
"z_offset.txt",
"beads.txt",
"psf_fft.psf",
aoi_size=int(settings.spline_size - 1),
pixel_size=settings.pixel_size * 1.0e-3,
z_range=settings.psf_fft_z_range,
z_step=settings.psf_fft_z_step)