def compute_operator(self,interp_params,inds=None):
if inds is None:
Rs = np.array([[geometry.rotmat3D_dir(d,t)[:,0:2] for t in self.thetas] for d in self.dirs])
Rs = Rs.reshape((-1,3,2))
else:
N_I = len(self.thetas)
Rs = np.array([geometry.rotmat3D_dir(self.dirs[i/N_I],self.thetas[np.mod(i,N_I)])[:,0:2] for i in inds])
return cops.compute_projection_matrix(Rs,sym=self.sym,projdirtype='rots',**interp_params)
def compute_projection_matrix(projdirs, N, kern, kernsize, rad, projdirtype='dirs', sym=None, onlyRs=False, **kwargs):
projdirs = np.asarray(projdirs, dtype=np.float32)
if projdirtype == 'dirs':
# Input is a set of projection directions
dirhash = hash(projdirs.tostring())
if onlyRs and dirhash in precomputed_Rs:
Rs = precomputed_Rs[dirhash]
else:
Rs = np.vstack(
[geometry.rotmat3D_dir(d)[:, 0:2].reshape((1, 3, 2)) for d in projdirs])
if onlyRs:
precomputed_Rs[dirhash] = Rs
elif projdirtype == 'rots':
# Input is a set of rotation matrices mapping image space to protein
# space
Rs = projdirs
else:
assert False, 'Unknown projdirtype, must be either dirs or rots'
if sym is None:
symRs = None
else:
symRs = np.vstack([np.require(R, dtype=np.float32).reshape(
(1, 3, 3)) for R in sym.get_rotations()])
if onlyRs:
return Rs
else:
return sincint.compute_interpolation_matrix(Rs, N, N, rad, kern, kernsize, symRs)
def compute_operator(self, interp_params, inds=None):
if inds is None:
Rs = np.array(
[[geometry.rotmat3D_dir(d, t)[:, 0:2] for t in self.thetas]
for d in self.dirs])
Rs = Rs.reshape((-1, 3, 2))
else:
N_I = len(self.thetas)
Rs = np.array([
geometry.rotmat3D_dir(self.dirs[i / N_I],
self.thetas[np.mod(i, N_I)])[:, 0:2]
for i in inds
])
return cops.compute_projection_matrix(Rs,
sym=self.sym,
projdirtype='rots',
**interp_params)
def compute_projection_matrix(projdirs,
N,
kern,
kernsize,
rad,
projdirtype='dirs',
sym=None,
onlyRs=False,
**kwargs):
projdirs = np.asarray(projdirs, dtype=np.float32)
if projdirtype == 'dirs':
# Input is a set of projection directions
dirhash = hash(projdirs.tostring())
if onlyRs and dirhash in precomputed_Rs:
Rs = precomputed_Rs[dirhash]
else:
Rs = np.vstack([
geometry.rotmat3D_dir(d)[:, 0:2].reshape((1, 3, 2))
for d in projdirs
])
if onlyRs:
precomputed_Rs[dirhash] = Rs
elif projdirtype == 'rots':
# Input is a set of rotation matrices mapping image space to protein
# space
Rs = projdirs
else:
assert False, 'Unknown projdirtype, must be either dirs or rots'
if sym is None:
symRs = None
else:
symRs = np.vstack([
np.require(R, dtype=np.float32).reshape((1, 3, 3))
for R in sym.get_rotations()
])
if onlyRs:
return Rs
else:
return sincint.compute_interpolation_matrix(Rs, N, N, rad, kern,
kernsize, symRs)
def plot_figures():
oversampling_factor = 6
psize = 3 * oversampling_factor
freq = 0.05
rad = 0.5 * 2.0 * psize
beamstop_freq = 0.005
beamstop_rad = beamstop_freq * 2.0 * psize
# M = mrc.readMRC('particle/EMD-6044-cropped.mrc')
# M[M < 0] = 0
# M_totalmass = 2000000
# if M_totalmass is not None:
# M *= M_totalmass / M.sum()
# fM = density.real_to_fspace_with_oversampling(M, oversampling_factor=oversampling_factor)
# fM = fM.real ** 2 + fM.imag ** 2
# mrc.writeMRC("particle/EMD-6044-cropped_fM_totalmass_%d_oversampling_%d.mrc" % (M_totalmass, oversampling_factor), fM, psz=psize)
# exit()
fM = mrc.readMRC(
'particle/EMD-6044-cropped_fM_totalmass_2000000_oversampling_6.mrc')
N = fM.shape[0]
TtoF = sincint.gentrunctofull(N=N, rad=rad, beamstop_rad=beamstop_rad)
theta = np.arange(0, 2 * np.pi, 2 * np.pi / 60)
degree_R, resolution_R = SK97Quadrature.compute_degree(N, 0.3, 1.0)
dirs, weights = SK97Quadrature.get_quad_points(degree_R, None)
Rs = np.vstack([
geometry.rotmat3D_dir(vec)[:, 0:2].reshape((1, 3, 2)) for vec in dirs
])
N_R = dirs.shape[0]
N_I = theta.shape[0]
N_T = TtoF.shape[1]
# generate slicing operators
dir_slice_interp = {
'projdirs': dirs,
'N': N,
'kern': 'lanczos',
'kernsize': 6,
'projdirtype': 'dirs',
'onlyRs': True,
'rad': rad,
'sym': None
} # 'zeropad': 0, 'dopremult': True
R_slice_interp = {
'projdirs': Rs,
'N': N,
'kern': 'lanczos',
'kernsize': 6,
'projdirtype': 'rots',
'onlyRs': True,
'rad': rad,
'sym': None
} # 'zeropad': 0, 'dopremult': True
inplane_interp = {
'thetas': theta,
'N': N,
'kern': 'lanczos',
'kernsize': 6,
'onlyRs': True,
'rad': rad
} # 'zeropad': 1, 'dopremult': True
inplane_interp['N_src'] = N # zp_N
slice_ops = cryoops.compute_projection_matrix(**dir_slice_interp)
inplane_ops = cryoops.compute_inplanerot_matrix(**inplane_interp)
# generate slices and inplane-rotated slices
slices_sampled = cryoem.getslices_interp(
fM, slice_ops, rad, beamstop_rad=beamstop_rad).reshape((N_R, N_T))
curr_img = TtoF.dot(slices_sampled[0]).reshape(N, N)
rotd_sampled = cryoem.getslices_interp(curr_img,
inplane_ops,
rad,
beamstop_rad=beamstop_rad).reshape(
(N_I, N_T))
## plot figures
fig, axes = plt.subplots(3, 4, figsize=(9.6, 7.2))
for i, ax in enumerate(axes.flatten()):
img = TtoF.dot(slices_sampled[i]).reshape(N, N)
ax.imshow(img, origin='lower')
fig.suptitle('slices_sampled')
fig, axes = plt.subplots(3, 4, figsize=(9.6, 7.2))
for i, ax in enumerate(axes.flatten()):
img = TtoF.dot(slices_sampled[i]).reshape(N, N)
ax.imshow(img, origin='lower')
fig.suptitle('rotd_sampled')
plt.show()
psize = 3.0 * 3
freq = 0.005
rad = freq * 2.0 * psize
beamstop_freq = 0.003
beamstop_rad = beamstop_freq * 2.0 * psize
fM = mrc.readMRC('../particle/EMD-6044-cropped-non-negative-256.mrc')
N = fM.shape[0]
TtoF = sincint.gentrunctofull(N=N, rad=rad, beamstop_rad=beamstop_rad)
theta = np.arange(0, 2 * np.pi, 2 * np.pi / 12)
degree_R, resolution_R = SK97Quadrature.compute_degree(N, rad, 1.0)
dirs, weights = SK97Quadrature.get_quad_points(degree_R, None)
Rs = np.vstack([
geometry.rotmat3D_dir(vec)[:, 0:2].reshape((1, 3, 2)) for vec in dirs
])
N_R = dirs.shape[0]
N_I = theta.shape[0]
N_T = TtoF.shape[1]
print(N_R, N_I, N_T)
# generate slicing operators
dir_slice_interp = {
'projdirs': dirs,
'N': N,
'kern': 'lanczos',
'kernsize': 6,
'projdirtype': 'dirs',
'onlyRs': True,