# Add parent directory to beginning of path variable
DIR = dirname(abspath(__file__))
sys.path.insert(0, split(DIR)[0])
import odtbrain as odt
# use jobmanager if available
try:
import jobmanager as jm
jm.decorators.decorate_module_ProgressBar(odt,
decorator=jm.decorators.ProgressBarOverrideCount,
interval=.1)
except:
pass
datazip = get_file("mie_2d_noncentered_cylinder_A250_R2.zip")
# Get simulation data
arc = zipfile.ZipFile(datazip)
angles = np.loadtxt(arc.open("mie_angles.txt"))
# sinogram computed with mie
# computed with
# miefield.GetSinogramCylinderRotation(radius, nmed, ncyl, lD, lC, size, A, res)
sino_real = np.loadtxt(arc.open("sino_real.txt"))
sino_imag = np.loadtxt(arc.open("sino_imag.txt"))
sino = sino_real + 1j*sino_imag
A, size = sino_real.shape
# background sinogram computed with mie
`on figshare <https://doi.org/10.6084/m9.figshare.8055407.v1>`
(hl60_sinogram_qpi.h5).
"""
import pathlib
import tarfile
import tempfile
import matplotlib.pylab as plt
import numpy as np
import odtbrain as odt
import qpimage
from example_helper import get_file, extract_lzma
# ascertain the data
path = get_file("qlsi_3d_hl60-cell_A140.tar.lzma")
tarf = extract_lzma(path)
tdir = tempfile.mkdtemp(prefix="odtbrain_example_")
with tarfile.open(tarf) as tf:
tf.extract("series.h5", path=tdir)
angles = np.loadtxt(tf.extractfile("angles.txt"))
# extract the complex field sinogram from the qpimage series data
h5file = pathlib.Path(tdir) / "series.h5"
with qpimage.QPSeries(h5file=h5file, h5mode="r") as qps:
qp0 = qps[0]
meta = qp0.meta
sino = np.zeros((len(qps), qp0.shape[0], qp0.shape[1]), dtype=np.complex)
for ii in range(len(qps)):
sino[ii] = qps[ii].field
"without autofocusing.")
autofocus = False
else:
autofocus = True
# use jobmanager if available
try:
import jobmanager as jm
jm.decorators.decorate_module_ProgressBar(odt,
decorator=jm.decorators.ProgressBarOverrideCount,
interval=.1)
except:
pass
datazip = get_file("mie_3d_sphere_field.zip")
# Get simulation data
arc = zipfile.ZipFile(datazip)
Ex_real = np.loadtxt(arc.open("mie_sphere_real.txt"))
Ex_imag = np.loadtxt(arc.open("mie_sphere_imag.txt"))
Ex = Ex_real +1j*Ex_imag
# get nm, lD, res
with arc.open("mie_info.txt") as info:
cfg = {}
for l in info.readlines():
l = l.decode()
if l.count("=") == 1:
key, val = l.split("=")
cfg[key.strip()] = float(val.strip())
# Add parent directory to beginning of path variable
DIR = dirname(abspath(__file__))
sys.path.insert(0, split(DIR)[0])
import odtbrain as odt
# use jobmanager if available
try:
import jobmanager as jm
jm.decorators.decorate_module_ProgressBar(odt,
decorator=jm.decorators.ProgressBarOverrideCount,
interval=.1)
except:
pass
datazip = get_file("fdtd_2d_sino_A100_R13.zip")
# Get simulation data
arc = zipfile.ZipFile(datazip)
angles = np.loadtxt(arc.open("fdtd_angles.txt"))
phantom = np.loadtxt(arc.open("fdtd_phantom.txt"))
sino_real = np.loadtxt(arc.open("fdtd_real.txt"))
sino_imag = np.loadtxt(arc.open("fdtd_imag.txt"))
sino = sino_real +1j*sino_imag
# get nm, lD, res
with arc.open("fdtd_info.txt") as info:
cfg = {}
for l in info.readlines():
l = l.decode()
if l.count("=") == 1:
key, val = l.split("=")
DIR = dirname(abspath(__file__))
sys.path.insert(0, split(DIR)[0])
import odtbrain as odt
# use jobmanager if available
try:
import jobmanager as jm
jm.decorators.decorate_module_ProgressBar(odt,
decorator=jm.decorators.ProgressBarOverrideCount,
interval=.1)
except:
pass
lzmafile = get_file("fdtd_3d_sino_A180_R6.500.tar.lzma")
sino, angles, phantom, cfg = load_tar_lzma_data(lzmafile)
A = angles.shape[0]
print("Example: Backpropagation from 3d FDTD simulations")
print("Refractive index of medium:", cfg["nm"])
print("Measurement position from object center:", cfg["lD"])
print("Wavelength sampling:", cfg["res"])
print("Number of projections:", A)
print("Performing backpropagation.")
## Apply the Rytov approximation
sinoRytov = odt.sinogram_as_rytov(sino)
import odtbrain as odt
try:
# use jobmanager if available
import jobmanager as jm
jm.decorators.decorate_module_ProgressBar(odt,
decorator=jm.decorators.ProgressBarOverrideCount,
interval=.1)
except:
pass
lzmafile = get_file("fdtd_3d_sino_A220_R6.500_tiltyz0.2.tar.lzma")
sino, angles, phantom, cfg = load_tar_lzma_data(lzmafile)
# Perform titlt by -.42 rad in detector plane
rotang = -0.42
from scipy.ndimage import rotate
rotkwargs= {"mode":"constant",
"order":2,
"reshape":False,
}
for ii in range(len(sino)):
sino[ii].real = rotate(sino[ii].real, np.rad2deg(rotang), cval=1, **rotkwargs)
sino[ii].imag = rotate(sino[ii].imag, np.rad2deg(rotang), cval=0, **rotkwargs)
A = angles.shape[0]
