def makeData():
index = 1
# Ideal camera movies.
#
if True:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.UniformBackground(s, x, y, i3, photons = bg)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, photons)
if settings.use_dh:
psf_f = lambda s, x, y, i3 : psf.DHPSF(s, x, y, i3, 100.0, z_range = settings.spline_z_range)
else:
psf_f = lambda s, x, y, i3 : psf.PupilFunction(s, x, y, i3, 100.0, settings.zmn)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.tif", "grid_list.hdf5", settings.n_frames)
index += 1
def makeData(cal_file="calib.npy", dither=False, verbosity=1):
index = 1
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.SCMOS(s, x, y, i3, cal_file)
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3: psf.GaussianPSF(s, x, y, i3, settings.
pixel_size)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
dither=dither,
x_size=settings.x_size,
y_size=settings.y_size)
sim.simulate(wdir + "/test.tif",
"grid_list.hdf5",
settings.n_frames,
verbosity=verbosity)
index += 1
makeDataCommon.makePeakFile(settings)
def makeDataPupilFnCMOS(settings, cal_file, dither):
"""
Pupil function PSF, CMOS camera movies.
"""
index = 1
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.SCMOS(s, x, y, i3, cal_file)
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3: psf.PupilFunction(s, x, y, i3, settings.
pixel_size, settings.zmn)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
dither=dither,
x_size=settings.x_size,
y_size=settings.y_size)
sim.simulate(wdir + "/test.tif", "grid_list.hdf5", settings.n_frames)
index += 1
makePeakFile(settings)
def makeData():
index = 1
# Ideal camera movies.
#
if True:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.Ideal(s, x, y, i3, settings.
camera_offset)
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(
s, x, y, i3, photons)
psf_f = lambda s, x, y, i3: psf.PupilFunction(
s, x, y, i3, settings.pixel_size, settings.zmn)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=settings.x_size,
y_size=settings.y_size)
sim.simulate(wdir + "/test.dax", "grid_list.hdf5",
settings.n_frames)
index += 1
# Create "peak_locations" file if needed.
#
if hasattr(settings, "peak_locations") and (settings.peak_locations
is not None):
with saH5Py.SAH5Py("test_01/test_ref.hdf5") as h5:
locs = h5.getLocalizationsInFrame(0)
if settings.peak_locations.endswith(".hdf5"):
saH5Py.saveLocalizations(settings.peak_locations, locs)
else:
numpy.savetxt(
settings.peak_locations,
numpy.transpose(
numpy.vstack((locs['x'], locs['y'], locs['height'],
locs['background']))))
def test_simulate_1():
"""
No photo-physics, simple PSF, ideal camera.
"""
dax_name = storm_analysis.getPathOutputTest("test_sim1.dax")
bin_name = storm_analysis.getData("test/data/test_sim.hdf5")
sim = simulate.Simulate(background_factory = lambda settings, xs, ys, i3data : background.UniformBackground(settings, xs, ys, i3data),
camera_factory = lambda settings, xs, ys, i3data : camera.Ideal(settings, xs, ys, i3data, 100.0),
photophysics_factory = lambda settings, xs, ys, i3data : photophysics.AlwaysOn(settings, xs, ys, i3data, 1000.0),
psf_factory = lambda settings, xs, ys, i3data : psf.GaussianPSF(settings, xs, ys, i3data, 160.0),
x_size = 100, y_size = 75)
sim.simulate(dax_name, bin_name, 5)
def createMovie():
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.Ideal(s, x, y, i3, camera_offset)
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(s, x, y, i3, signal)
psf_f = lambda s, x, y, i3: psf.GaussianPSF(s, x, y, i3, pixel_size)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=x_size,
y_size=y_size)
sim.simulate("test.tif", "sim_locs.hdf5", n_frames)
def test_simulate_3():
"""
No photo-physics, spline PSF, sCMOS camera.
"""
dax_name = storm_analysis.getPathOutputTest("test_sim3.dax")
bin_name = storm_analysis.getData("test/data/test_sim_olist.bin")
cal_name = storm_analysis.getData("test/data/calib.npy")
spline_name = storm_analysis.getData("test/data/test_spliner_psf.spline")
sim = simulate.Simulate(lambda settings, xs, ys, i3data : background.UniformBackground(settings, xs, ys, i3data, photons = 20),
lambda settings, xs, ys, i3data : camera.SCMOS(settings, xs, ys, i3data, 100.0, cal_name),
lambda settings, xs, ys, i3data : photophysics.AlwaysOn(settings, xs, ys, i3data, 2000.0),
lambda settings, xs, ys, i3data : psf.Spline(settings, xs, ys, i3data, 160.0, spline_name))
sim.simulate(dax_name, bin_name, 5)
def test_simulate_3():
"""
No photo-physics, spline PSF, sCMOS camera.
"""
# Only test for Python3 due to pickle incompatibility issues.
if (sys.version_info < (3, 0)):
return
dax_name = storm_analysis.getPathOutputTest("test_sim3.dax")
bin_name = storm_analysis.getData("test/data/test_sim.hdf5")
cal_name = storm_analysis.getData("test/data/calib.npy")
spline_name = storm_analysis.getData("test/data/test_spliner_psf.spline")
sim = simulate.Simulate(background_factory = lambda settings, xs, ys, i3data : background.UniformBackground(settings, xs, ys, i3data, photons = 20),
camera_factory = lambda settings, xs, ys, i3data : camera.SCMOS(settings, xs, ys, i3data, cal_name),
photophysics_factory = lambda settings, xs, ys, i3data : photophysics.AlwaysOn(settings, xs, ys, i3data, 2000.0),
psf_factory = lambda settings, xs, ys, i3data : psf.Spline(settings, xs, ys, i3data, 160.0, spline_name))
sim.simulate(dax_name, bin_name, 5)
def createMovie(n_frames):
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.Ideal(s, x, y, i3, camera_offset)
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(s, x, y, i3, signal)
psf_f = lambda s, x, y, i3: psf.GaussianPSF(s, x, y, i3, pixel_size)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=x_size,
y_size=y_size)
sim.simulate("test.tif", "sim_locs.hdf5", n_frames)
# Also create file to use for peak locations.
with saH5Py.SAH5Py("test_ref.hdf5") as h5:
locs = h5.getLocalizationsInFrame(0)
saH5Py.saveLocalizations("peak_locs.hdf5", locs)
def createMovie(movie_name, use_dh=False):
# Create drift file, this is used to displace the localizations in the
# PSF measurement movie.
#
dz = numpy.arange(-z_range, 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_offsets.txt", z_offset)
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.Ideal(s, x, y, i3, camera_offset)
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, signal)
if use_dh:
psf_f = lambda s, x, y, i3: psf.DHPSF(s, x, y, i3, pixel_size)
else:
psf_f = lambda s, x, y, i3: psf.PupilFunction(s, x, y, i3, pixel_size,
[[1.3, 2, 2]])
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=x_size,
y_size=y_size)
sim.simulate(movie_name, "spliner_measure_psf.hdf5", dz.size)
type=int,
required=True,
help="The length of the movie in frames.")
parser.add_argument('--photons',
dest='photons',
type=float,
required=True,
help="The integral of a single emitter in photons.")
args = parser.parse_args()
sim = Simulate(
lambda settings, xs, ys, h5data: background.UniformBackground(
settings, xs, ys, h5data), lambda settings, xs, ys, h5data: camera.
Ideal(settings, xs, ys, h5data, 100.0),
lambda settings, xs, ys, h5data: photophysics.AlwaysOn(
settings, xs, ys, h5data, args.photons),
lambda settings, xs, ys, h5data: psf.GaussianPSF(
settings, xs, ys, h5data, 160.0))
sim.simulate(args.dax_file, args.hdf5, args.frames)
#
# The MIT License
#
# Copyright (c) 2016 Zhuang Lab, Harvard University
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
def measurePSF():
# Create sparse random localizations for PSF measurement.
#
print("Creating random localization.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call(["python", sim_path + "emitters_uniform_random.py",
"--bin", "sparse_random.hdf5",
"--density", "0.0002",
"--margin", str(settings.margin),
"--sx", str(settings.x_size),
"--sy", str(settings.y_size)])
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call(["python", sim_path + "emitters_on_grid.py",
"--bin", "sparse_grid.hdf5",
"--nx", "8",
"--ny", "3",
"--spacing", "40"])
# Create text files for PSF measurement.
#
locs = saH5Py.loadLocalizations("sparse_random.hdf5")
[xf, yf] = iaUtilsC.removeNeighbors(locs["x"], locs["y"], 2.0 * ((settings.psf_size/2)+1))
numpy.savetxt("sparse_random.txt", numpy.transpose(numpy.vstack((xf, yf))))
locs = saH5Py.loadLocalizations("sparse_grid.hdf5")
numpy.savetxt("sparse_grid.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.psf_z_range, settings.psf_z_range + 0.001, 0.010)
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)
z_offset[:,0] = 0
numpy.savetxt("z_offset_none_valid.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.)
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, 100.0, settings.zmn)
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)
if True:
sim.simulate("sparse_grid.dax", "sparse_grid.hdf5", dz.size)
sim.simulate("sparse_random.dax", "sparse_random.hdf5", dz.size)
# Measure the PSF using spliner/measure_psf_beads.py and multiplane/measure_psf.py
#
diff_detected = False
# Grid.
if True:
print("Measuring PSF (beads).")
spliner_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/spliner/"
subprocess.call(["python", spliner_path + "measure_psf_beads.py",
"--movie", "sparse_grid.dax",
"--zoffset", "z_offset.txt",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--beads", "sparse_grid.txt",
"--psf", "sparse_grid_beads.psf",
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
print("Measuring PSF (HDF5, with zoffset).")
subprocess.call(["python", spliner_path + "measure_psf.py",
"--movie", "sparse_grid.dax",
"--bin", "sparse_grid_ref.hdf5",
"--psf", "sparse_grid_hdf5_zo.psf",
"--zoffset", "z_offset.txt",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
print("Measuring PSF (HDF5).")
subprocess.call(["python", spliner_path + "measure_psf.py",
"--movie", "sparse_grid.dax",
"--bin", "sparse_grid_ref.hdf5",
"--psf", "sparse_grid_hdf5.psf",
"--zoffset", "",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
multiplane_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/multi_plane/"
print("Measure PSF (multiplane).")
subprocess.call(["python", multiplane_path + "psf_zstack.py",
"--movie", "sparse_grid.dax",
"--bin", "sparse_grid.hdf5",
"--zstack", "sparse_grid_zstack",
"--aoi_size", str(int(settings.psf_size/2)+1)])
subprocess.call(["python", multiplane_path + "measure_psf.py",
"--zstack", "sparse_grid_zstack.npy",
"--zoffsets", "z_offset.txt",
"--psf_name", "sparse_grid_hdf5_mp_zo.psf",
"--z_range", str(settings.psf_z_range),
"--z_step", str(settings.psf_z_step),
"--normalize", "True"])
# Check that the PSFs are the same.
psf_beads = numpy.load("sparse_grid_beads.psf")["psf"]
psf_hdf5_zo = numpy.load("sparse_grid_hdf5_zo.psf")["psf"]
psf_hdf5 = numpy.load("sparse_grid_hdf5.psf")["psf"]
psf_hdf5_mp_zo = numpy.load("sparse_grid_hdf5_mp_zo.psf")["psf"]
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5_zo)
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5)
# Here we are only checking they are close.
if (settings.psf_size >= 20):
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5_mp_zo, atol = 0.17, rtol = 0.17)
# Grid, no valid z offsets.
if True:
print("Measuring PSF (beads).")
spliner_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/spliner/"
try:
subprocess.check_output(["python", spliner_path + "measure_psf_beads.py",
"--movie", "sparse_grid.dax",
"--zoffset", "z_offset_none_valid.txt",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--beads", "sparse_grid.txt",
"--psf", "sparse_grid_beads.psf",
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
except subprocess.CalledProcessError:
pass
else:
assert False, "spliner.measure_psf_beads did not fail!"
print("Measuring PSF (HDF5, with zoffset).")
try:
subprocess.check_output(["python", spliner_path + "measure_psf.py",
"--movie", "sparse_grid.dax",
"--bin", "sparse_grid_ref.hdf5",
"--psf", "sparse_grid_hdf5_zo.psf",
"--zoffset", "z_offset_none_valid.txt",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
except subprocess.CalledProcessError:
pass
else:
assert False, "spliner.measure_psf did not fail!"
multiplane_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/multi_plane/"
print("Measure PSF (multiplane).")
try:
subprocess.check_output(["python", multiplane_path + "psf_zstack.py",
"--movie", "sparse_grid.dax",
"--bin", "sparse_grid.hdf5",
"--zstack", "sparse_grid_zstack",
"--aoi_size", str(int(settings.psf_size/2)+1)])
subprocess.check_output(["python", multiplane_path + "measure_psf.py",
"--zstack", "sparse_grid_zstack.npy",
"--zoffsets", "z_offset_none_valid.txt",
"--psf_name", "sparse_grid_hdf5_mp_zo.psf",
"--z_range", str(settings.psf_z_range),
"--z_step", str(settings.psf_z_step),
"--normalize", "True"])
except subprocess.CalledProcessError:
pass
else:
assert False, "multiplane PSF measurement did not fail!"
# Random.
if True:
print("Measuring PSF (beads).")
spliner_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/spliner/"
subprocess.call(["python", spliner_path + "measure_psf_beads.py",
"--movie", "sparse_random.dax",
"--zoffset", "z_offset.txt",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--beads", "sparse_random.txt",
"--psf", "sparse_random_beads.psf",
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
print("Measuring PSF (HDF5, with zoffset).")
subprocess.call(["python", spliner_path + "measure_psf.py",
"--movie", "sparse_random.dax",
"--bin", "sparse_random_ref.hdf5",
"--psf", "sparse_random_hdf5_zo.psf",
"--zoffset", "z_offset.txt",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
print("Measuring PSF (HDF5).")
subprocess.call(["python", spliner_path + "measure_psf.py",
"--movie", "sparse_random.dax",
"--bin", "sparse_random_ref.hdf5",
"--psf", "sparse_random_hdf5.psf",
"--zoffset", "",
"--aoi_size", str(int(settings.psf_size/2)+1),
"--zrange", str(settings.psf_z_range),
"--zstep", str(settings.psf_z_step)])
psf_beads = numpy.load("sparse_random_beads.psf")["psf"]
psf_hdf5_zo = numpy.load("sparse_random_hdf5_zo.psf")["psf"]
psf_hdf5 = numpy.load("sparse_random_hdf5.psf")["psf"]
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5_zo)
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5)
if diff_detected:
print("Difference detected in PSF measurements!")
else:
print("No differences detected, all good.")
if False:
with tifffile.TiffWriter("psf_diff.tif") as tf:
for i in range(psf_beads.shape[0]):
tf.save((psf_beads[i,:,:] - psf_hdf5_zo[i,:,:]).astype(numpy.float32))
# Ideal camera movies.
#
if True:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.Ideal(s, x, y, i3, settings.
camera_offset)
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(s, x, y, i3, photons)
if settings.use_dh:
psf_f = lambda s, x, y, i3: psf.DHPSF(
s, x, y, i3, 100.0, z_range=settings.spline_z_range)
else:
psf_f = lambda s, x, y, i3: psf.PupilFunction(
s, x, y, i3, 100.0, settings.zmn)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=settings.x_size,
y_size=settings.y_size)
sim.simulate(wdir + "/test.dax", "grid_list.hdf5", settings.n_frames)
def makeSampleData():
# Create sample bead data for PSF measurement.
#
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
emittersOnGrid.emittersOnGrid("psf_locs.hdf5", 6, 3, 1.5, 40, 0.0, 0.0)
# Create localization files for PSF measurement.
#
locs = saH5Py.loadLocalizations("psf_locs.hdf5")
for i, z_offset in enumerate(z_planes):
cx = mappings["0_" + str(i) + "_x"]
cy = 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(-spline_z_range, 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, pixel_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=x_size,
y_size=y_size)
for i in range(len(z_planes)):
sim.simulate("c" + str(i + 1) + "_zcal.dax",
"c" + str(i + 1) + "_psf.hdf5", dz.size)
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.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin", "grid_list.hdf5",
"--nx",
str(settings.nx), "--ny",
str(settings.ny), "--spacing", "20", "--zrange",
str(settings.test_z_range), "--zoffset",
str(settings.test_z_offset)
])
# Create randomly located localizations file.
#
print("Creating random localization.")
subprocess.call([
"python", sim_path + "emitters_uniform_random.py", "--bin",
"random_list.hdf5", "--density", "1.0", "--margin",
str(settings.margin), "--sx",
str(settings.x_size), "--sy",
str(settings.y_size), "--zrange",
str(settings.test_z_range)
])
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin", "psf_list.hdf5",
"--nx", "6", "--ny", "3", "--spacing", "40"
])
# 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
multiplane_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/multi_plane/"
# Create pupil functions for 'pupilfn'.
if (psf_model == "pupilfn"):
pupilfn_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/pupilfn/"
print("Creating pupil functions.")
for i in range(len(settings.z_planes)):
subprocess.call([
"python", pupilfn_path + "make_pupil_fn.py", "--filename",
"c" + str(i + 1) + "_pupilfn.pfn", "--size",
str(settings.psf_size), "--pixel-size",
str(settings.pixel_size), "--zmn",
str(settings.pupil_fn), "--z-offset",
str(-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.")
psf_fft_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/psf_fft/"
spliner_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/spliner/"
for i in range(len(settings.z_planes)):
subprocess.call([
"python", multiplane_path + "psf_zstack.py", "--movie",
"c" + str(i + 1) + "_zcal.dax", "--bin",
"c" + str(i + 1) + "_psf.hdf5", "--zstack",
"c" + str(i + 1) + "_zstack", "--scmos_cal", "calib.npy",
"--aoi_size",
str(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)):
subprocess.call([
"python", multiplane_path + "measure_psf.py", "--zstack",
"c" + str(i + 1) + "_zstack.npy", "--zoffsets",
"z_offset.txt", "--psf_name",
"c" + str(i + 1) + "_psf_normed.psf", "--z_range",
str(settings.spline_z_range), "--normalize", "True"
])
# PSFs are normalized to each other.
#
else:
for i in range(len(settings.z_planes)):
subprocess.call([
"python", multiplane_path + "measure_psf.py", "--zstack",
"c" + str(i + 1) + "_zstack.npy", "--zoffsets",
"z_offset.txt", "--psf_name",
"c" + str(i + 1) + "_psf.psf", "--z_range",
str(settings.spline_z_range)
])
norm_args = [
"python", multiplane_path + "normalize_psfs.py", "--psfs",
"c1_psf.psf"
]
for i in range(len(settings.z_planes) - 1):
norm_args.append("c" + str(i + 2) + "_psf.psf")
subprocess.call(norm_args)
# Measure the spline for Spliner.
#
print("Measuring Spline.")
for i in range(len(settings.z_planes)):
subprocess.call([
"python", spliner_path + "psf_to_spline.py", "--psf",
"c" + str(i + 1) + "_psf_normed.psf", "--spline",
"c" + str(i + 1) + "_psf.spline", "--spline_size",
str(settings.psf_size)
])
# 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)):
subprocess.call([
"python", multiplane_path + "measure_psf.py", "--zstack",
"c" + str(i + 1) + "_zstack.npy", "--zoffsets",
"z_offset.txt", "--psf_name",
"c" + str(i + 1) + "_psf_normed.psf", "--z_range",
str(settings.psf_z_range), "--z_step",
str(settings.psf_z_step), "--normalize", "True"
])
# PSFs are normalized to each other.
#
else:
for i in range(len(settings.z_planes)):
subprocess.call([
"python", multiplane_path + "measure_psf.py", "--zstack",
"c" + str(i + 1) + "_zstack.npy", "--zoffsets",
"z_offset.txt", "--psf_name",
"c" + str(i + 1) + "_psf.psf", "--z_range",
str(settings.psf_z_range), "--z_step",
str(settings.psf_z_step)
])
norm_args = [
"python", multiplane_path + "normalize_psfs.py", "--psfs",
"c1_psf.psf"
]
for i in range(len(settings.z_planes) - 1):
norm_args.append("c" + str(i + 2) + "_psf.psf")
subprocess.call(norm_args)
# Downsample the PSF to 1x for PSF FFT.
print("Downsampling PSF.")
for i in range(len(settings.z_planes)):
subprocess.call([
"python", psf_fft_path + "downsample_psf.py", "--spliner_psf",
"c" + str(i + 1) + "_psf_normed.psf", "--psf",
"c" + str(i + 1) + "_psf_fft.psf", "--pixel-size",
str(settings.pixel_size)
])
# Calculate Cramer-Rao weighting.
#
print("Calculating weights.")
subprocess.call([
"python", multiplane_path + "plane_weighting.py", "--background",
str(settings.photons[0][0]), "--photons",
str(settings.photons[0][1]), "--output", "weights.npy", "--xml",
"multiplane.xml", "--no_plots"
])
def makeData(dither = False):
index = 1
# Gaussian PSF, uniform background.
if True:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.UniformBackground(s, x, y, i3, photons = bg)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
dither = dither,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.dax", "grid_list.hdf5", settings.n_frames)
index += 1
# Pupil Function PSF.
if False:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.UniformBackground(s, x, y, i3, photons = bg)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3 : psf.PupilFunction(s, x, y, i3, settings.pixel_size, [])
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.dax", "grid_list.hdf5", settings.n_frames)
index += 1
# Gaussian non-uniform background, always on.
if False:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.GaussianBackground(s, x, y, i3, photons = bg)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.dax", "grid_list.hdf5", settings.n_frames)
index += 1
# Uniform background, STORM.
if False:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.UniformBackground(s, x, y, i3, photons = bg)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.SimpleSTORM(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.dax", "random_list.hdf5", settings.n_frames)
index += 1
# Gaussian non-uniform background, STORM.
if False:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.GaussianBackground(s, x, y, i3, photons = bg)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.SimpleSTORM(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.dax", "random_list.hdf5", settings.n_frames)
index += 1
# Sloped non-uniform background, always on.
if False:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.SlopedBackground(s, x, y, i3, slope = 0.4, offset = 10)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
dither = True,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.dax", "grid_list.hdf5", settings.n_frames)
index += 1
# Sine non-uniform background, always on.
if False:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3 : background.SineBackground(s, x, y, i3, photons = bg, period = 45)
cam_f = lambda s, x, y, i3 : camera.Ideal(s, x, y, i3, settings.camera_offset)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, photons)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
dither = True,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate(wdir + "/test.dax", "grid_list.hdf5", settings.n_frames)
index += 1
# Create "peak_locations" file if needed.
#
if hasattr(settings, "peak_locations") and (settings.peak_locations is not None):
with saH5Py.SAH5Py("test_01/test_ref.hdf5") as h5:
locs = h5.getLocalizationsInFrame(0)
if settings.peak_locations.endswith(".hdf5"):
saH5Py.saveLocalizations(settings.peak_locations, locs)
else:
numpy.savetxt(settings.peak_locations,
numpy.transpose(numpy.vstack((locs['x'],
locs['y'],
locs['height'],
locs['background']))))
def makeSampleData(mappings=None):
# Create sample bead data for mapping measurement.
#
# Create randomly located localizations file (for STORM movies).
#
print("Creating random localizations.")
emittersUniformRandom.emittersUniformRandom("random.hdf5", density, margin,
x_size, y_size, 0.0)
# Create mapping, if not specified.
#
if mappings is None:
mappings = {
"0_0_x": numpy.array([0.0, 1.0, 0.0]),
"0_0_y": numpy.array([0.0, 0.0, 1.0]),
"0_1_x": numpy.array([2.0, 1.0, 0.0]),
"0_1_y": numpy.array([5.0, 0.0, 1.0]),
"1_0_x": numpy.array([-2.0, 1.0, 0.0]),
"1_0_y": numpy.array([-5.0, 0.0, 1.0])
}
# Figure out number of planes in the mapping.
#
n_planes = 0
for elt in mappings:
[i, j] = map(int, elt.split("_")[:2])
if (i > n_planes):
n_planes = i
n_planes += 1
print(n_planes)
# Create localization files for PSF measurement.
#
locs = saH5Py.loadLocalizations("random.hdf5")
for i in range(n_planes):
cx = mappings["0_" + str(i) + "_x"]
cy = 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
saH5Py.saveLocalizations("c" + str(i + 1) + "_map.hdf5", locs_temp)
# 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")
pp_f = lambda s, x, y, h5: photophysics.AlwaysOn(s, x, y, h5, 10000.0)
psf_f = lambda s, x, y, h5: psf.PupilFunction(s, x, y, h5, pixel_size, [])
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=x_size,
y_size=y_size)
for i in range(n_planes):
sim.simulate("c" + str(i + 1) + "_map.dax",
"c" + str(i + 1) + "_map.hdf5", 2)
def configure():
# Create PF for pupil function.
#
pupilfn_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/pupilfn/"
print("Creating pupil function.")
subprocess.call([
"python", pupilfn_path + "make_pupil_fn.py", "--filename",
"pupilfn.pfn", "--size",
str(settings.spline_size), "--pixel-size",
str(settings.pixel_size), "--zmn",
str(settings.zmn), "--z-offset",
str(settings.z_offset)
])
# Create PSF using pupil functions directly.
#
if False:
psf_fft_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/psf_fft/"
print("Creating (theoritical) psf.")
subprocess.call([
"python", psf_fft_path + "make_psf_from_pf.py", "--filename",
"psf_fft.psf", "--size",
str(settings.spline_size), "--pixel-size",
str(settings.pixel_size), "--zrange",
str(settings.psf_fft_z_range), "--zstep",
str(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.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin",
"sparse_list.hdf5", "--nx", "6", "--ny", "3", "--spacing", "40",
"--zoffset",
str(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.)
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, 100.0, settings.
zmn)
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.")
spliner_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/spliner/"
subprocess.call([
"python", spliner_path + "measure_psf_beads.py", "--movie", "psf.dax",
"--zoffset", "z_offset.txt", "--aoi_size",
str(int(settings.spline_size / 2) + 1), "--beads", "beads.txt",
"--psf", "psf_spliner.psf"
])
# Measure the Spline.
#
# This is slow, sometimes you don't want to do it.
if True:
print("Measuring Spline.")
subprocess.call([
"python", spliner_path + "psf_to_spline.py", "--psf",
"psf_spliner.psf", "--spline", "psf.spline", "--spline_size",
str(settings.spline_size)
])
# Create measured PSF for PSF FFT.
#
# Measure the PSF using spliner/measure_psf_beads.py
#
print("Measuring PSF.")
subprocess.call([
"python", spliner_path + "measure_psf_beads.py", "--movie", "psf.dax",
"--zoffset", "z_offset.txt", "--aoi_size",
str(int(settings.spline_size / 2) + 1), "--beads", "beads.txt",
"--psf", "psf_fft_2x.psf", "--zrange",
str(settings.psf_fft_z_range), "--zstep",
str(settings.psf_fft_z_step)
])
# Downsample by 2x for use by PSF FFT.
#
psf_fft_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/psf_fft/"
print("Creating downsampled psf.")
subprocess.call([
"python", psf_fft_path + "downsample_psf.py", "--spliner_psf",
"psf_fft_2x.psf", "--psf", "psf_fft.psf", "--pixel-size",
str(settings.pixel_size)
])
def configure(no_splines):
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters()
params.toXMLFile("fdecon.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("sparse_list.hdf5", 6, 3, 1.5, 40, 0.0, 0.0)
if no_splines:
return
# 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.)
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)
if settings.use_dh:
psf_f = lambda s, x, y, i3: psf.DHPSF(
s, x, y, i3, 100.0, z_range=settings.spline_z_range)
else:
psf_f = lambda s, x, y, i3: psf.PupilFunction(s, x, y, i3, 100.0,
settings.zmn)
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("spline.dax", "sparse_list.hdf5", dz.size)
# Measure the PSF.
#
print("Measuring PSF.")
psf_name = "psf.psf"
measurePSFBeads.measurePSFBeads("spline.dax",
"z_offset.txt",
"beads.txt",
psf_name,
aoi_size=int(settings.spline_size + 1),
pixel_size=settings.pixel_size * 1.0e-3,
z_range=settings.spline_z_range)
# Measure the Spline.
#
if True:
print("Measuring Spline.")
psfToSpline.psfToSpline(psf_name, "psf.spline", settings.spline_size)
def makeData():
index = 1
# sCMOS calibration file.
if settings.random_variance:
variance = numpy.random.exponential(scale=settings.camera_variance,
size=(settings.y_size,
settings.x_size))
offset = settings.camera_offset + variance
numpy.save("calib.npy", [
offset, variance,
numpy.ones(
(settings.y_size, settings.x_size)) * settings.camera_gain, 1
])
else:
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, 1
])
# sCMOS camera movies.
#
# For these simulations we expect (approximately) these results:
#
# Analysis Summary:
# Total analysis time 10.64 seconds
# Recall 0.93726
# Noise 0.05972
# XY Error (nm):
# test_01 14.44 14.53
# test_02 8.26 8.24
#
# XY Width Error, Mean difference with truth, Standard deviation (pixels):
# test_01 0.029 0.116 0.029 0.116
# test_02 0.017 0.105 0.017 0.105
#
if True:
for [bg, photons] in settings.photons:
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.SCMOS(s, x, y, i3, "calib.npy")
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(
s, x, y, i3, photons)
psf_f = lambda s, x, y, i3: psf.GaussianPSF(
s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=settings.x_size,
y_size=settings.y_size)
sim.simulate(wdir + "/test.tif", "grid_list.hdf5",
settings.n_frames)
index += 1
def measurePSF():
# Create sparse random localizations for PSF measurement.
#
print("Creating random localization.")
emittersUniformRandom.emittersUniformRandom("sparse_random.hdf5", 0.0002,
settings.margin,
settings.x_size,
settings.y_size, 0.0)
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
emittersOnGrid.emittersOnGrid("sparse_grid.hdf5", 8, 3, 1.5, 40, 0.0, 0.0)
# Create text files for PSF measurement.
#
locs = saH5Py.loadLocalizations("sparse_random.hdf5")
[xf, yf] = iaUtilsC.removeNeighbors(locs["x"], locs["y"],
2.0 * ((settings.psf_size / 2) + 1))
numpy.savetxt("sparse_random.txt", numpy.transpose(numpy.vstack((xf, yf))))
locs = saH5Py.loadLocalizations("sparse_grid.hdf5")
numpy.savetxt("sparse_grid.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.psf_z_range, settings.psf_z_range + 0.001,
0.010)
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)
z_offset[:, 0] = 0
numpy.savetxt("z_offset_none_valid.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.)
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, 100.0, settings.
zmn)
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)
if True:
sim.simulate("sparse_grid.tif", "sparse_grid.hdf5", dz.size)
sim.simulate("sparse_random.tif", "sparse_random.hdf5", dz.size)
# Measure the PSF using spliner/measure_psf_beads.py and multiplane/measure_psf.py
#
diff_detected = False
# Grid.
if True:
# Remove old results.
for elt in [
"sparse_grid_beads.psf", "sparse_grid_hdf5_zo.psf",
"sparse_grid_hdf5.psf", "sparse_grid_hdf5_mp_zo.psf"
]:
if os.path.exists(elt):
os.remove(elt)
print("Measuring PSF (beads).")
measurePSFBeads.measurePSFBeads("sparse_grid.tif",
"z_offset.txt",
"sparse_grid.txt",
"sparse_grid_beads.psf",
aoi_size=int(settings.psf_size / 2 +
1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
print("Measuring PSF (HDF5, with zoffset).")
spMeasurePSF.measurePSF("sparse_grid.tif",
"z_offset.txt",
"sparse_grid_ref.hdf5",
"sparse_grid_hdf5_zo.psf",
aoi_size=int(settings.psf_size / 2 + 1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
print("Measuring PSF (HDF5).")
spMeasurePSF.measurePSF("sparse_grid.tif",
"",
"sparse_grid_ref.hdf5",
"sparse_grid_hdf5.psf",
aoi_size=int(settings.psf_size / 2 + 1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
multiplane_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/multi_plane/"
print("Measure PSF (multiplane).")
psfZStack.psfZStack("sparse_grid.tif",
"sparse_grid.hdf5",
"sparse_grid_zstack",
aoi_size=int(settings.psf_size / 2 + 1))
mpMeasurePSF.measurePSF("sparse_grid_zstack.npy",
"z_offset.txt",
"sparse_grid_hdf5_mp_zo.psf",
z_range=settings.psf_z_range,
z_step=settings.psf_z_step,
normalize=True)
# Check that the PSFs are the same.
psf_beads = numpy.load("sparse_grid_beads.psf",
allow_pickle=True)["psf"]
psf_hdf5_zo = numpy.load("sparse_grid_hdf5_zo.psf",
allow_pickle=True)["psf"]
psf_hdf5 = numpy.load("sparse_grid_hdf5.psf", allow_pickle=True)["psf"]
psf_hdf5_mp_zo = numpy.load("sparse_grid_hdf5_mp_zo.psf",
allow_pickle=True)["psf"]
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5_zo)
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5)
# Here we are only checking they are close.
if (settings.psf_size >= 20):
diff_detected = diff_detected or psfDiffCheck(
psf_beads, psf_hdf5_mp_zo, atol=0.17, rtol=0.17)
# Grid, no valid z offsets. These are supposed to fail.
#
if True:
print("Measuring PSF (beads).")
try:
measurePSFBeads.measurePSFBeads(
"sparse_grid.tif",
"z_offset_none_valid.txt",
"sparse_grid.txt",
"sparse_grid_beads.psf",
aoi_size=int(settings.psf_size / 2 + 1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
except AssertionError:
pass
else:
assert False, "spliner.measure_psf_beads did not fail!"
print("Measuring PSF (HDF5, with zoffset).")
try:
spMeasurePSF.measurePSF("sparse_grid.tif",
"z_offset_none_valid.txt",
"sparse_grid_ref.hdf5",
"sparse_grid_hdf5_zo.psf",
aoi_size=int(settings.psf_size / 2 + 1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
except AssertionError:
pass
else:
assert False, "spliner.measure_psf did not fail!"
print("Measure PSF (multiplane).")
try:
psfZStack.psfZStack("sparse_grid.tif",
"sparse_grid.hdf5",
"sparse_grid_zstack",
aoi_size=int(settings.psf_size / 2 + 1))
mpMeasurePSF.measurePSF("sparse_grid_zstack.npy",
"z_offset_none_valid.txt",
"sparse_grid_hdf5_mp_zo.psf",
z_range=settings.psf_z_range,
z_step=settings.psf_z_step,
normalize=True)
except AssertionError:
pass
else:
assert False, "multiplane PSF measurement did not fail!"
# Random.
if True:
# Remove old results.
for elt in [
"sparse_random_beads.psf", "sparse_random_hdf5_zo.psf",
"sparse_random_hdf5.psf"
]:
if os.path.exists(elt):
os.remove(elt)
print("Measuring PSF (beads).")
measurePSFBeads.measurePSFBeads("sparse_random.tif",
"z_offset.txt",
"sparse_random.txt",
"sparse_random_beads.psf",
aoi_size=int(settings.psf_size / 2 +
1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
print("Measuring PSF (HDF5, with zoffset).")
spMeasurePSF.measurePSF("sparse_random.tif",
"z_offset.txt",
"sparse_random_ref.hdf5",
"sparse_random_hdf5_zo.psf",
aoi_size=int(settings.psf_size / 2 + 1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
print("Measuring PSF (HDF5).")
spMeasurePSF.measurePSF("sparse_random.tif",
"",
"sparse_random_ref.hdf5",
"sparse_random_hdf5.psf",
aoi_size=int(settings.psf_size / 2 + 1),
z_range=settings.psf_z_range,
z_step=settings.psf_z_step)
psf_beads = numpy.load("sparse_random_beads.psf",
allow_pickle=True)["psf"]
psf_hdf5_zo = numpy.load("sparse_random_hdf5_zo.psf",
allow_pickle=True)["psf"]
psf_hdf5 = numpy.load("sparse_random_hdf5.psf",
allow_pickle=True)["psf"]
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5_zo)
diff_detected = diff_detected or psfDiffCheck(psf_beads, psf_hdf5)
if diff_detected:
print("Difference detected in PSF measurements!")
else:
print("No differences detected, all good.")
if False:
with tifffile.TiffWriter("psf_diff.tif") as tf:
for i in range(psf_beads.shape[0]):
tf.save((psf_beads[i, :, :] - psf_hdf5_zo[i, :, :]).astype(
numpy.float32))
def configure(no_splines):
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters()
params.toXMLFile("fdecon.xml")
# Create localization on a grid file.
#
print("Creating gridded localization.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin", "grid_list.hdf5",
"--nx",
str(settings.nx), "--ny",
str(settings.ny), "--spacing", "20", "--zrange",
str(settings.test_z_range), "--zoffset",
str(settings.test_z_offset)
])
# Create randomly located localizations file.
#
print("Creating random localization.")
subprocess.call([
"python", sim_path + "emitters_uniform_random.py", "--bin",
"random_list.hdf5", "--density", "1.0", "--sx",
str(settings.x_size), "--sy",
str(settings.y_size), "--zrange",
str(settings.test_z_range)
])
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin",
"sparse_list.hdf5", "--nx", "6", "--ny", "3", "--spacing", "40"
])
if no_splines:
return
# 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.)
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)
if settings.use_dh:
psf_f = lambda s, x, y, i3: psf.DHPSF(
s, x, y, i3, 100.0, z_range=settings.spline_z_range)
else:
psf_f = lambda s, x, y, i3: psf.PupilFunction(s, x, y, i3, 100.0,
settings.zmn)
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("spline.dax", "sparse_list.hdf5", dz.size)
# Measure the PSF.
#
print("Measuring PSF.")
spliner_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/spliner/"
subprocess.call([
"python", spliner_path + "measure_psf_beads.py", "--movie",
"spline.dax", "--zoffset", "z_offset.txt", "--beads", "beads.txt",
"--psf", "psf.psf"
])
# Measure the Spline.
#
print("Measuring Spline.")
subprocess.call([
"python", spliner_path + "psf_to_spline.py", "--psf", "psf.psf",
"--spline", "psf.spline", "--spline_size",
str(settings.spline_size)
])
def makeData():
index = 1
if True:
# Create .bin files for each plane.
h5_locs = saH5Py.loadLocalizations("grid_list.hdf5")
# Load channel to channel mapping file.
with open("map.map", 'rb') as fp:
mappings = pickle.load(fp)
for i, z_plane in enumerate(settings.z_planes):
cx = mappings["0_" + str(i) + "_x"]
cy = mappings["0_" + str(i) + "_y"]
xi = h5_locs["x"].copy()
yi = h5_locs["y"].copy()
zi = h5_locs["z"].copy()
xf = cx[0] + cx[1] * xi + cx[2] * yi
yf = cy[0] + cy[1] * xi + cy[2] * yi
zf = zi + z_plane
h5_temp = {"x": xf, "y": yf, "z": zf}
saH5Py.saveLocalizations("sim_input_c" + str(i + 1) + ".hdf5",
h5_temp)
# Create a movie for each plane.
for [bg, photons] in settings.photons:
# Adjust photons by the number of planes.
photons = photons / float(len(settings.z_planes))
wdir = "test_{0:02d}".format(index)
print(wdir)
if not os.path.exists(wdir):
os.makedirs(wdir)
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg)
cam_f = lambda s, x, y, i3: camera.SCMOS(s, x, y, i3, "calib.npy")
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(
s, x, y, i3, photons)
psf_f = lambda s, x, y, i3: psf.PupilFunction(
s, x, y, i3, settings.pixel_size, settings.pupil_fn)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_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(wdir + "/test_c" + str(i + 1) + ".dax",
"sim_input_c" + str(i + 1) + ".hdf5",
settings.n_frames)
index += 1
# Create "peak_locations" file if needed.
#
if hasattr(settings, "peak_locations") and (settings.peak_locations
is not None):
with saH5Py.SAH5Py("test_01/test_c1_ref.hdf5") as h5:
locs = h5.getLocalizationsInFrame(0)
if settings.peak_locations.endswith(".hdf5"):
saH5Py.saveLocalizations(settings.peak_locations, locs)
else:
numpy.savetxt(
settings.peak_locations,
numpy.transpose(
numpy.vstack((locs['x'], locs['y'], locs['height'],
locs['background']))))
def configure(cal_file = None):
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters(cal_file = cal_file)
params.toXMLFile("psf_fft.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("sparse_list.hdf5",
6,
3,
1.5,
40,
0.0,
0.0)
if False:
# Create PSF using pupil functions directly.
#
print("Creating (theoritical) psf.")
makePSFFromPF.makePSF("psf.psf",
settings.psf_size,
settings.pixel_size * 1.0e-3,
settings.zmn,
settings.psf_z_range,
settings.z_step)
else:
# Create beads.txt file for PSF 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.psf_z_range, settings.psf_z_range + 0.001, 0.010)
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.)
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, 100.0, settings.zmn)
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)
# Measure the PSF using spliner/measure_psf_beads.py
#
print("Measuring PSF.")
measurePSFBeads.measurePSFBeads("psf.dax",
"z_offset.txt",
"beads.txt",
"psf.psf",
aoi_size = int(settings.psf_size/2)+1,
pixel_size = settings.pixel_size * 1.0e-3,
z_range = settings.psf_z_range,
z_step = settings.z_step)
xf = cx[0] + cx[1] * xi + cx[2] * yi
yf = cy[0] + cy[1] * xi + cy[2] * yi
i3dtype.posSet(i3_temp, "x", xf)
i3dtype.posSet(i3_temp, "y", yf)
i3dtype.posSet(i3_temp, "z", z_plane + z_value)
with writeinsight3.I3Writer("sim_input_c" + str(i) + ".bin") as i3w:
i3w.addMolecules(i3_temp)
# Create simulator object.
bg_photons = int(100.0 / float(len(z_planes)))
signal = 6000.0 / float(len(z_planes))
bg_f = lambda s, x, y, i3: background.UniformBackground(
s, x, y, i3, photons=bg_photons)
cam_f = lambda s, x, y, i3: camera.SCMOS(s, x, y, i3, 0.0, "cam_cal_c0.npy")
pp_f = lambda s, x, y, i3: photophysics.AlwaysOn(s, x, y, i3, signal)
if (len(z_planes) > 1):
psf_f = lambda s, x, y, i3: psf.PupilFunction(s, x, y, i3, 100.0, [])
else:
psf_f = lambda s, x, y, i3: psf.PupilFunction(s, x, y, i3, 100.0,
[[1.3, 2, 2]])
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=x_size,
y_size=y_size)
for i in range(len(z_planes)):
def configure():
# Get relevant paths.
mm_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/micrometry/"
mp_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/multi_plane/"
sp_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/spliner/"
# Create analysis XML files.
#
print("Creating XML files.")
params = testingParametersSCMOS()
params.toXMLFile("scmos.xml")
params = testingParametersMC()
params.toXMLFile("multicolor.xml")
# Useful variables
aoi_size = int(settings.psf_size / 2) + 1
# Create sCMOS data and HDF5 files we'll need for the simulation.
#
if True:
# 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, 1
])
# Create localization on a grid file.
#
print("Creating gridded localizations.")
sim_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin",
"grid_list.hdf5", "--nx",
str(settings.nx), "--ny",
str(settings.ny), "--spacing", "20", "--zrange",
str(settings.test_z_range), "--zoffset",
str(settings.test_z_offset)
])
# Create randomly located localizations file (for STORM movies).
#
print("Creating random localizations.")
subprocess.call([
"python", sim_path + "emitters_uniform_random.py", "--bin",
"random_storm.hdf5", "--density", "1.0", "--margin",
str(settings.margin), "--sx",
str(settings.x_size), "--sy",
str(settings.y_size), "--zrange",
str(settings.test_z_range)
])
# Create randomly located localizations file (for mapping measurement).
#
print("Creating random localizations.")
subprocess.call([
"python", sim_path + "emitters_uniform_random.py", "--bin",
"random_map.hdf5", "--density", "0.0003", "--margin",
str(settings.margin), "--sx",
str(settings.x_size), "--sy",
str(settings.y_size)
])
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
sim_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin",
"psf_list.hdf5", "--nx", "6", "--ny", "3", "--spacing", "40"
])
## This part makes / tests measuring the mapping.
##
if True:
print("Measuring mapping.")
# Make localization files for simulations.
#
locs = saH5Py.loadLocalizations("random_map.hdf5")
locs["z"][:] = 1.0e-3 * settings.z_planes[0]
saH5Py.saveLocalizations("c1_random_map.hdf5", locs)
for i in range(1, 4):
locs["x"] += settings.dx
locs["y"] += settings.dy
locs["z"][:] = settings.z_planes[i]
saH5Py.saveLocalizations("c" + str(i + 1) + "_random_map.hdf5",
locs)
# Make localization files for simulations.
#
locs = saH5Py.loadLocalizations("random_map.hdf5")
locs["z"][:] = 1.0e-3 * settings.z_planes[0]
saH5Py.saveLocalizations("c1_random_map.hdf5", locs)
for i in range(1, 4):
locs["x"] += settings.dx
locs["y"] += settings.dy
locs["z"][:] = settings.z_planes[i]
saH5Py.saveLocalizations("c" + str(i + 1) + "_random_map.hdf5",
locs)
# Make simulated mapping data.
#
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")
pp_f = lambda s, x, y, h5: photophysics.AlwaysOn(s, x, y, h5, 20000.0)
psf_f = lambda s, x, y, i3: psf.GaussianPSF(s, x, y, i3, settings.
pixel_size)
sim = simulate.Simulate(background_factory=bg_f,
camera_factory=cam_f,
photophysics_factory=pp_f,
psf_factory=psf_f,
x_size=settings.x_size,
y_size=settings.y_size)
for i in range(4):
sim.simulate("c" + str(i + 1) + "_map.dax",
"c" + str(i + 1) + "_random_map.hdf5", 1)
# Analyze simulated mapping data
#
for i in range(4):
scmos.analyze("c" + str(i + 1) + "_map.dax",
"c" + str(i + 1) + "_map.hdf5", "scmos.xml")
# Measure mapping.
#
for i in range(3):
subprocess.call([
"python", mm_path + "micrometry.py", "--locs1", "c1_map.hdf5",
"--locs2", "c" + str(i + 2) + "_map.hdf5", "--results",
"c1_c" + str(i + 2) + "_map.map", "--no_plots"
])
# Merge mapping.
#
subprocess.call([
"python", mm_path + "merge_maps.py", "--results", "map.map",
"--maps", "c1_c2_map.map", "c1_c3_map.map", "c1_c4_map.map"
])
# Print mapping.
#
if True:
print("Mapping is:")
subprocess.call([
"python", mp_path + "print_mapping.py", "--mapping", "map.map"
])
print("")
# Check that mapping is close to what we expect (within 5%).
#
with open("map.map", 'rb') as fp:
mappings = pickle.load(fp)
for i in range(3):
if not numpy.allclose(mappings["0_" + str(i + 1) + "_x"],
numpy.array(
[settings.dx * (i + 1), 1.0, 0.0]),
rtol=0.05,
atol=0.05):
print("X mapping difference for channel", i + 1)
if not numpy.allclose(mappings["0_" + str(i + 1) + "_y"],
numpy.array(
[settings.dy * (i + 1), 0.0, 1.0]),
rtol=0.05,
atol=0.05):
print("Y mapping difference for channel", i + 1)
## This part measures / test the PSF measurement.
##
if True:
# Create drift file, this is used to displace the localizations in the
# PSF measurement movie.
#
dz = numpy.arange(-settings.psf_z_range, settings.psf_z_range + 0.05,
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, [])
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)
if True:
for i in range(4):
sim.simulate("c" + str(i + 1) + "_zcal.dax",
"c" + str(i + 1) + "_random_map.hdf5", dz.size)
# Get localizations to use for PSF measurement.
#
subprocess.call([
"python", mp_path + "psf_localizations.py", "--bin",
"c1_map_ref.hdf5", "--map", "map.map", "--aoi_size",
str(aoi_size)
])
# Create PSF z stacks.
#
for i in range(4):
subprocess.call([
"python", mp_path + "psf_zstack.py", "--movie",
"c" + str(i + 1) + "_zcal.dax", "--bin",
"c1_map_ref_c" + str(i + 1) + "_psf.hdf5", "--zstack",
"c" + str(i + 1) + "_zstack", "--scmos_cal", "calib.npy",
"--aoi_size",
str(aoi_size)
])
# Measure PSF.
#
for i in range(4):
subprocess.call([
"python", mp_path + "measure_psf.py", "--zstack",
"c" + str(i + 1) + "_zstack.npy", "--zoffsets", "z_offset.txt",
"--psf_name", "c" + str(i + 1) + "_psf_normed.psf",
"--z_range",
str(settings.psf_z_range), "--normalize"
])
## This part creates the splines.
##
if True:
print("Measuring Splines.")
for i in range(4):
subprocess.call([
"python", sp_path + "psf_to_spline.py", "--psf",
"c" + str(i + 1) + "_psf_normed.psf", "--spline",
"c" + str(i + 1) + "_psf.spline", "--spline_size",
str(settings.psf_size)
])
## This part measures the Cramer-Rao weights.
##
if True:
print("Calculating weights.")
subprocess.call([
"python", mp_path + "plane_weighting.py", "--background",
str(settings.photons[0][0]), "--photons",
str(settings.photons[0][1]), "--output", "weights.npy", "--xml",
"multicolor.xml", "--no_plots"
])
def configure(no_splines, cal_file = None):
# Create sCMOS calibration file if requested.
#
if cal_file is not None:
offset = numpy.zeros((settings.y_size, settings.x_size)) + settings.camera_offset
variance = numpy.ones((settings.y_size, settings.x_size))
gain = numpy.ones((settings.y_size, settings.x_size)) * settings.camera_gain
rqe = numpy.ones((settings.y_size, settings.x_size))
numpy.save(cal_file, [offset, variance, gain, rqe, 2])
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters(cal_file = cal_file)
params.toXMLFile("spliner.xml")
# Create localization on a grid file.
#
print("Creating gridded localization.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call(["python", sim_path + "emitters_on_grid.py",
"--bin", "grid_list.hdf5",
"--nx", str(settings.nx),
"--ny", str(settings.ny),
"--spacing", "20"])
# Create randomly located localizations file.
#
print("Creating random localization.")
subprocess.call(["python", sim_path + "emitters_uniform_random.py",
"--bin", "random_list.hdf5",
"--density", "1.0",
"--margin", str(settings.margin),
"--sx", str(settings.x_size),
"--sy", str(settings.y_size)])
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call(["python", sim_path + "emitters_on_grid.py",
"--bin", "sparse_list.hdf5",
"--nx", "6",
"--ny", "3",
"--spacing", "40"])
if no_splines:
return
# 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.)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, 20000.0)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
dither = True,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate("spline_2d.tif", "sparse_list.hdf5", 5)
# Measure the PSF.
#
print("Measuring PSF.")
spliner_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/spliner/"
subprocess.call(["python", spliner_path + "measure_psf.py",
"--movie", "spline_2d.tif",
"--bin", "spline_2d_ref.hdf5",
"--psf", "psf.psf",
"--want2d",
"--aoi_size", str(settings.spline_size+1)])
# Measure the Spline.
#
if True:
print("Measuring Spline.")
subprocess.call(["python", spliner_path + "psf_to_spline.py",
"--psf", "psf.psf",
"--spline", "psf.spline",
"--spline_size", str(settings.spline_size)])
def configure(no_splines, cal_file=None):
# Create sCMOS calibration file if requested.
#
if cal_file is not None:
offset = numpy.zeros(
(settings.y_size, settings.x_size)) + settings.camera_offset
variance = numpy.ones((settings.y_size, settings.x_size))
gain = numpy.ones(
(settings.y_size, settings.x_size)) * settings.camera_gain
rqe = numpy.ones((settings.y_size, settings.x_size))
numpy.save(cal_file, [offset, variance, gain, rqe, 2])
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters(cal_file=cal_file)
params.toXMLFile("spliner.xml")
# Create localization on a grid file.
#
print("Creating gridded localization.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin", "grid_list.hdf5",
"--nx",
str(settings.nx), "--ny",
str(settings.ny), "--spacing", "20", "--zrange",
str(settings.test_z_range), "--zoffset",
str(settings.test_z_offset)
])
# Create randomly located localizations file.
#
print("Creating random localization.")
subprocess.call([
"python", sim_path + "emitters_uniform_random.py", "--bin",
"random_list.hdf5", "--density", "1.0", "--margin",
str(settings.margin), "--sx",
str(settings.x_size), "--sy",
str(settings.y_size), "--zrange",
str(settings.test_z_range)
])
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
sim_path = os.path.dirname(inspect.getfile(storm_analysis)) + "/simulator/"
subprocess.call([
"python", sim_path + "emitters_on_grid.py", "--bin",
"sparse_list.hdf5", "--nx", "6", "--ny", "3", "--spacing", "40"
])
if no_splines:
return
# 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.)
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, 100.0, settings.
zmn)
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("spline.dax", "sparse_list.hdf5", dz.size)
# Measure the PSF.
#
print("Measuring PSF.")
psf_name = "psf.psf"
spliner_path = os.path.dirname(
inspect.getfile(storm_analysis)) + "/spliner/"
subprocess.call([
"python", spliner_path + "measure_psf_beads.py", "--movie",
"spline.dax", "--zoffset", "z_offset.txt", "--beads", "beads.txt",
"--psf", psf_name, "--aoi_size",
str(settings.spline_size + 1)
])
# Smooth the PSF if requested.
#
if settings.smooth_psf:
with open(psf_name, "rb") as fp:
psf_data = pickle.load(fp)
sm_psf = measurePSFUtils.smoothPSF(psf_data["psf"],
xy_sigma=settings.smooth_psf_sigma,
z_sigma=settings.smooth_psf_sigma)
psf_data["psf"] = sm_psf
psf_data["smoothed"] = True
psf_name = "psf_smooth.psf"
with open(psf_name, "wb") as fp:
pickle.dump(psf_data, fp)
# Measure the Spline.
#
if True:
print("Measuring Spline.")
subprocess.call([
"python", spliner_path + "psf_to_spline.py", "--psf", psf_name,
"--spline", "psf.spline", "--spline_size",
str(settings.spline_size)
])
def configure(no_splines, cal_file = None):
# Create sCMOS calibration file if requested.
#
if cal_file is not None:
offset = numpy.zeros((settings.y_size, settings.x_size)) + settings.camera_offset
variance = numpy.ones((settings.y_size, settings.x_size))
gain = numpy.ones((settings.y_size, settings.x_size)) * settings.camera_gain
rqe = numpy.ones((settings.y_size, settings.x_size))
numpy.save(cal_file, [offset, variance, gain, rqe, 2])
# Create parameters file for analysis.
#
print("Creating XML file.")
params = testingParameters(cal_file = cal_file)
params.toXMLFile("spliner.xml")
# Create localization on a grid file.
#
print("Creating gridded localization.")
emittersOnGrid.emittersOnGrid("grid_list.hdf5",
settings.nx,
settings.ny,
1.5,
20,
0.0,
0.0)
# Create randomly located localizations file.
#
print("Creating random localization.")
emittersUniformRandom.emittersUniformRandom("random_list.hdf5",
1.0,
settings.margin,
settings.x_size,
settings.y_size,
0.0)
# Create sparser grid for PSF measurement.
#
print("Creating data for PSF measurement.")
emittersOnGrid.emittersOnGrid("sparse_list.hdf5",
6,
3,
1.5,
40,
0.0,
0.0)
if no_splines:
return
# 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 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.)
pp_f = lambda s, x, y, i3 : photophysics.AlwaysOn(s, x, y, i3, 20000.0)
psf_f = lambda s, x, y, i3 : psf.GaussianPSF(s, x, y, i3, settings.pixel_size)
sim = simulate.Simulate(background_factory = bg_f,
camera_factory = cam_f,
photophysics_factory = pp_f,
psf_factory = psf_f,
dither = True,
x_size = settings.x_size,
y_size = settings.y_size)
sim.simulate("spline_2d.tif", "sparse_list.hdf5", 5)
# Measure the PSF.
#
print("Measuring PSF.")
psf_name = "psf.psf"
measurePSF.measurePSF("spline_2d.tif",
"na",
"sparse_list.hdf5",
psf_name,
want2d = True,
aoi_size = int(settings.spline_size + 1),
pixel_size = settings.pixel_size * 1.0e-3)
# Measure the Spline.
#
if True:
print("Measuring Spline.")
psfToSpline.psfToSpline(psf_name, "psf.spline", settings.spline_size)
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.)
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)
if settings.use_dh:
psf_f = lambda s, x, y, i3 : psf.DHPSF(s, x, y, i3, 100.0, z_range = settings.spline_z_range)
else:
psf_f = lambda s, x, y, i3 : psf.PupilFunction(s, x, y, i3, 100.0, settings.zmn)
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("spline.dax", "sparse_list.hdf5", dz.size)