def test_map_interpolation(tolerance=0.1):
import logging
logger = logging.getLogger("condor")
logger.setLevel("DEBUG")
src = condor.Source(wavelength=10.0E-9,
pulse_energy=1E-3,
focus_diameter=1E-6)
det = condor.Detector(distance=1.0, pixel_size=300E-6, nx=256, ny=256)
par = condor.ParticleMap(diameter=600E-9,
material_type="cell",
geometry="custom",
map3d_filename=here + "/examples/map3d.h5",
map3d_dataset="data",
dx=5E-9)
s = "particle_map"
E = condor.Experiment(src, {s: par}, det)
res0 = E.propagate()
I0 = res0["entry_1"]["data_1"]["data"]
# Now without interpolation
print "NOW WITHOUT INTERPOLATION"
condor.particle.particle_map.ENABLE_MAP_INTERPOLATION = False
src = condor.Source(wavelength=10.0E-9,
pulse_energy=1E-3,
focus_diameter=1E-6)
det = condor.Detector(distance=1.0, pixel_size=300E-6, nx=256, ny=256)
par = condor.ParticleMap(diameter=600E-9,
material_type="cell",
geometry="custom",
map3d_filename=here + "/examples/map3d.h5",
map3d_dataset="data",
dx=5E-9)
s = "particle_map"
E = condor.Experiment(src, {s: par}, det)
res1 = E.propagate()
I1 = res1["entry_1"]["data_1"]["data"]
import matplotlib.pyplot as pypl
pypl.imsave("./Imap_interp.png", abs(I0), vmin=0, vmax=I0.max())
pypl.imsave("./Imap_no_interp.png", abs(I1), vmin=0, vmax=I0.max())
err = abs(I0 - I1).sum() / ((I0 + I1).sum() / 2.)
if err < tolerance:
print "\t=> Test successful (err = %e)" % err
return False
else:
print "\t=> Test failed (err = %e)" % err
return True
numpy.fft.ifftn(res["entry_1"]["data_1"]["data_fourier"]))
vmin = numpy.log10(res["entry_1"]["data_1"]["data"].max() / 10000.)
if plotting:
pypl.imsave(out_dir + "/%s_%2.2fdeg.png" % (s, angle_d),
numpy.log10(res["entry_1"]["data_1"]["data"]),
vmin=vmin)
pypl.imsave(out_dir + "/%s_rs_%2.2fdeg.png" % (s, angle_d),
abs(real_space))
if True:
# Map (spheroid)
#print("Simulating map (spheroid)")
par = condor.ParticleMap(diameter=spheroid_diameter,
material_type="water",
flattening=spheroid_flattening,
geometry="spheroid",
rotation_values=rotation_values,
rotation_formalism=rotation_formalism,
rotation_mode=rotation_mode)
s = "particle_map_spheroid"
E = condor.Experiment(src, {s: par}, det)
res = E.propagate()
real_space = numpy.fft.fftshift(
numpy.fft.ifftn(res["entry_1"]["data_1"]["data_fourier"]))
vmin = numpy.log10(res["entry_1"]["data_1"]["data"].max() / 10000.)
if plotting:
pypl.imsave(out_dir + "/%s_%2.2f.png" % (s, angle_d),
numpy.log10(res["entry_1"]["data_1"]["data"]),
vmin=vmin)
pypl.imsave(out_dir + "/%s_rs_%2.2f.png" % (s, angle_d),
abs(real_space))
#logger.setLevel("DEBUG")
#logger.setLevel("WARNING")
logger.setLevel("INFO")
N = 1
rotation_formalism="random"
rotation_values = None
# Source
src = condor.Source(wavelength=0.147E-9, pulse_energy=1E-3, focus_diameter=1E-6)
# Detector
det = condor.Detector(distance=0.9, pixel_size=400E-6, nx=250, ny=250)
# Map
#print("Simulating map")
par = condor.ParticleMap(diameter=None, material_type="poliovirus", geometry="custom",
emd_id="1144",
rotation_formalism=rotation_formalism, rotation_values=rotation_values)
s = "particle_map"
E = condor.Experiment(src, {s : par}, det)
W = condor.utils.cxiwriter.CXIWriter("./condor.cxi")
for i in range(N):
t = time.time()
res = E.propagate()
#print(time.time()-t)
if plotting:
real_space = numpy.fft.fftshift(numpy.fft.ifftn(res["entry_1"]["data_1"]["data_fourier"]))
pypl.imsave(this_dir + "/simple_test_%s_%i.png" % (s,i), numpy.log10(res["entry_1"]["data_1"]["data"]))
pypl.imsave(this_dir + "/simple_test_%s_%i_rs.png" % (s,i), abs(real_space))
W.write(res)
W.close()
pixelsize = 110e-6
distance = 2.4
dx = 3.76e-10
# Source
src = condor.Source(wavelength=wavelength,
pulse_energy=pulse_energy,
focus_diameter=focus_diameter)
# Detector
det = condor.Detector(distance=distance, pixel_size=pixelsize, nx=414, ny=414)
# Map
print "Simulating map"
par = condor.ParticleMap(diameter=40E-9,
material_type="poliovirus",
geometry="custom",
map3d_filename="../../map3d.h5",
map3d_dataset="data",
dx=dx,
rotation_formalism=rotation_formalism,
rotation_values=rotation_values)
s = "particle_map"
E = condor.Experiment(src, {s: par}, det)
W = condor.utils.cxiwriter.CXIWriter("./condor.cxi")
for i in range(N):
res = E.propagate()
real_space = numpy.fft.fftshift(
numpy.fft.ifftn(res["entry_1"]["data_1"]["data_fourier"]))
pypl.imsave(this_dir + "/simple_test_%s_%i.png" % (s, i),
numpy.log10(res["entry_1"]["data_1"]["data"]))
pypl.imsave(this_dir + "/simple_test_%s_%i_rs.png" % (s, i),
abs(real_space))
D = condor.Detector(pixel_size=75E-6, nx=1024, ny=1024, distance=0.15)
# Build 3D map for particle model
dx = 0.25*D.get_resolution_element_x(S.photon.get_wavelength())
N = int(numpy.round((1.2*diameter_core+2*thickness_shell)/dx))
assert (dx*N) > (1.1*diameter_core+2*thickness_shell)
map3d = numpy.zeros(shape=(2,N,N,N))
X,Y,Z = numpy.mgrid[:N,:N,:N]
R = numpy.sqrt((X-(N-1)/2.)**2+(Y-(N-1)/2.)**2+(Z-(N-1)/2.)**2)*dx
(map3d[0])[R <= diameter_core/2.] = 1.
if thickness_shell > dx:
(map3d[1])[(R > diameter_core/2.)*(R <= (diameter_core+thickness_shell*2)/2.)] = 1.
# Initialise particle class instance
P = condor.ParticleMap(geometry='custom',
material_type=['custom','custom'],
dx=dx, map3d=map3d,
atomic_composition=[atomic_composition_core, atomic_composition_shell],
massdensity=[massdensity_core, massdensity_shell])
# Initialise experiment class instance
E = condor.Experiment(source=S, particles={"particle_map": P}, detector=D)
# Calculate diffraction pattern
res = E.propagate()
# Images for plotting
img_intensities = res["entry_1"]["data_1"]["data"]
img_fourier = res["entry_1"]["data_1"]["data_fourier"]
real_space = numpy.fft.fftshift(numpy.fft.fft2(numpy.fft.fftshift(img_fourier)))
this_dir = os.path.dirname(os.path.realpath(__file__))
do_plot = False
if do_plot:
import matplotlib
matplotlib.use('TkAgg')
from matplotlib import pyplot
from matplotlib.colors import LogNorm
src = condor.Source(wavelength=0.1E-10, pulse_energy=1E-3, focus_diameter=1E-6)
ds = 16
det = condor.Detector(distance=2., pixel_size=110E-6*ds, nx=1024/ds+1, ny=1024/ds+1, solid_angle_correction=False)
psphere = {"particle_sphere": condor.ParticleSphere(diameter=1E-9, material_type="water")}
pmap = {"particle_map": condor.ParticleMap(diameter=1E-9, material_type="water", geometry="icosahedron")}
patoms = {"particle_atoms": condor.ParticleAtoms(pdb_filename="%s/../../DNA.pdb" % this_dir)}
particles = [psphere, pmap, patoms]
if do_plot:
fig, (axs1, axs2) = pyplot.subplots(2, len(particles), figsize=(3*len(particles), 3*2))
for i,par in enumerate(particles):
E = condor.Experiment(src, par, det)
res = E.propagate()
data = res["entry_1"]["data_1"]["data"]
if do_plot:
axs1[i].set_title("2D: " + par.keys()[0])
lims = (data.min(), data.max())
def test_compare_atoms_with_map(tolerance=0.1):
"""
Compare the output of two diffraction patterns, one simulated with descrete atoms (spsim) and the other one from a 3D refractive index map on a regular grid.
"""
src = condor.Source(wavelength=0.1E-9,
pulse_energy=1E-3,
focus_diameter=1E-6)
det = condor.Detector(distance=0.5,
pixel_size=750E-6,
nx=100,
ny=100,
cx=45,
cy=59)
angle_d = 72.
angle = angle_d / 360. * 2 * numpy.pi
rotation_axis = numpy.array([0.43, 0.643, 0.])
rotation_axis = rotation_axis / condor.utils.linalg.length(rotation_axis)
quaternion = condor.utils.rotation.quat(angle, rotation_axis[0],
rotation_axis[1], rotation_axis[2])
rotation_values = numpy.array([quaternion])
rotation_formalism = "quaternion"
rotation_mode = "extrinsic"
short_diameter = 25E-9 * 12 / 100.
long_diameter = 2 * short_diameter
N_long = 20
N_short = int(round(short_diameter / long_diameter * N_long))
dx = long_diameter / (N_long - 1)
massdensity = condor.utils.material.get_atomic_mass(
"H") * scipy.constants.value("atomic mass constant") / dx**3
# Map
map3d = numpy.zeros(shape=(N_long, N_long, N_long))
map3d[:N_short, :, :N_short] = 1.
map3d[N_short:N_short + N_short, :N_short, :N_short] = 1.
par = condor.ParticleMap(diameter=long_diameter,
material_type="custom",
massdensity=massdensity,
atomic_composition={"H": 1.},
geometry="custom",
map3d=map3d,
dx=dx,
rotation_values=rotation_values,
rotation_formalism=rotation_formalism,
rotation_mode=rotation_mode)
s = "particle_map_custom"
E = condor.Experiment(src, {s: par}, det)
res = E.propagate()
F_map = res["entry_1"]["data_1"]["data_fourier"]
# Atoms
Z1, Y1, X1 = numpy.meshgrid(numpy.linspace(0, short_diameter, N_short),
numpy.linspace(0, long_diameter, N_long),
numpy.linspace(0, short_diameter, N_short),
indexing="ij")
Z2, Y2, X2 = numpy.meshgrid(numpy.linspace(0, short_diameter, N_short) +
long_diameter / 2.,
numpy.linspace(0, short_diameter, N_short),
numpy.linspace(0, short_diameter, N_short),
indexing="ij")
Z = numpy.concatenate((Z1.ravel(), Z2.ravel()))
Y = numpy.concatenate((Y1.ravel(), Y2.ravel()))
X = numpy.concatenate((X1.ravel(), X2.ravel()))
atomic_positions = numpy.array(
[[x, y, z] for x, y, z in zip(X.ravel(), Y.ravel(), Z.ravel())])
atomic_numbers = numpy.ones(atomic_positions.size // 3, dtype=numpy.int16)
par = condor.ParticleAtoms(atomic_positions=atomic_positions,
atomic_numbers=atomic_numbers,
rotation_values=rotation_values,
rotation_formalism=rotation_formalism,
rotation_mode=rotation_mode)
s = "particle_atoms"
E = condor.Experiment(src, {s: par}, det)
res = E.propagate()
F_atoms = res["entry_1"]["data_1"]["data_fourier"]
# Compare
I_atoms = abs(F_atoms)**2
I_map = abs(F_map)**2
diff = I_atoms - I_map
err = abs(diff).sum() / ((I_atoms.sum() + I_map.sum()) / 2.)
if SAVE_OUTPUT:
import matplotlib.pyplot as pypl
pypl.imsave("./Iatoms_mol.png", abs(I_atoms))
pypl.imsave("./Iatoms_map.png", abs(I_map))
assert err < tolerance
def test_compare_spheroid_with_map(tolerance=0.15):
"""
Compare the output of two diffraction patterns, one simulated with the direct formula and the other one from a 3D refractive index map on a regular grid
"""
src = condor.Source(wavelength=0.1E-9,
pulse_energy=1E-3,
focus_diameter=1E-6)
det = condor.Detector(distance=0.5,
pixel_size=750E-6,
nx=100,
ny=100,
cx=45,
cy=59)
angle_d = 72.
angle = angle_d / 360. * 2 * numpy.pi
rotation_axis = numpy.array([0.43, 0.643, 0.])
rotation_axis = rotation_axis / condor.utils.linalg.length(rotation_axis)
quaternion = condor.utils.rotation.quat(angle, rotation_axis[0],
rotation_axis[1], rotation_axis[2])
rotation_values = numpy.array([quaternion])
rotation_formalism = "quaternion"
rotation_mode = "extrinsic"
short_diameter = 25E-9 * 12 / 100.
long_diameter = 2 * short_diameter
spheroid_diameter = condor.utils.spheroid_diffraction.to_spheroid_diameter(
short_diameter / 2., long_diameter / 2.)
spheroid_flattening = condor.utils.spheroid_diffraction.to_spheroid_flattening(
short_diameter / 2., long_diameter / 2.)
# Ideal spheroid
par = condor.ParticleSpheroid(diameter=spheroid_diameter,
material_type="water",
flattening=spheroid_flattening,
rotation_values=rotation_values,
rotation_formalism=rotation_formalism,
rotation_mode=rotation_mode)
s = "particle_spheroid"
E = condor.Experiment(src, {s: par}, det)
res = E.propagate()
F_ideal = res["entry_1"]["data_1"]["data_fourier"]
# Map (spheroid)
par = condor.ParticleMap(diameter=spheroid_diameter,
material_type="water",
flattening=spheroid_flattening,
geometry="spheroid",
rotation_values=rotation_values,
rotation_formalism=rotation_formalism,
rotation_mode=rotation_mode)
s = "particle_map_spheroid"
E = condor.Experiment(src, {s: par}, det)
res = E.propagate()
F_map = res["entry_1"]["data_1"]["data_fourier"]
# Compare
I_ideal = abs(F_ideal)**2
I_map = abs(F_map)**2
if SAVE_OUTPUT:
import matplotlib.pyplot as pypl
pypl.imsave("./Ispheroid_sph.png", abs(I_ideal))
pypl.imsave("./Ispheroid_map.png", abs(I_map))
diff = I_ideal - I_map
err = abs(diff).sum() / ((I_ideal.sum() + I_map.sum()) / 2.)
assert err < tolerance
# Save map
with h5py.File("emd_1144.h5", "w") as f:
f["/dn_map"] = dn_map3d
f["/dx"] = dx
f["/wavelength"] = wavelength
# Source
src = condor.Source(wavelength=wavelength,
pulse_energy=1E-3,
focus_diameter=0.1E-6)
# Detector
det = condor.Detector(distance=0.4, pixel_size=125E-6, nx=512, ny=512)
# Particle
par = condor.ParticleMap(diameter=1E-9,
geometry="custom",
map3d=dn_map3d,
dx=dx,
rotation_formalism="quaternion",
rotation_values=[0.01, 0.69, 0.69, -0.22])
E = condor.Experiment(src, {"particle_map_1144": par}, det)
res = E.propagate()
W = condor.utils.cxiwriter.CXIWriter("./condor.cxi")
W.write(res)
W.close()
if plotting:
real_space = numpy.fft.fftshift(
numpy.fft.ifftn(res["entry_1"]["data_1"]["data_fourier"]))
pypl.imsave(this_dir + "/intensities.png",
numpy.log10(res["entry_1"]["data_1"]["data"]))
import numpy as np
import scipy.interpolate
import condor
# Number of frames
N = 100
# Dimensions in diffraction space
nx, ny, nz = (100, 100, 100)
S = condor.Source(wavelength=1E-9, focus_diameter=1E-6, pulse_energy=1E-3)
P = condor.ParticleMap(geometry="icosahedron",
diameter=100E-9,
material_type="cell",
rotation_formalism="random")
D = condor.Detector(pixel_size=1000E-6, distance=0.5, nx=nx, ny=ny)
E = condor.Experiment(source=S, particles={"particle_map": P}, detector=D)
points = []
values = []
for i in range(N):
res = E.propagate()
img = res["entry_1"]["data_1"]["data_fourier"]
qmap = E.get_qmap_from_cache()
c = 2 * np.pi * D.pixel_size / (S.photon.get_wavelength() * D.distance)
points.append(qmap.reshape((qmap.shape[0] * qmap.shape[1], 3)) / c)
values.append(img.flatten())
points = np.array(points)
points = points.reshape((points.shape[0] * points.shape[1], 3))
values = np.array(values).flatten()