def ssnr_sequential___individual_data_collect(self, r, op):
if (self is None):
get_mrc_func = IV.get_mrc
else:
get_mrc_func = self.cache.get_mrc
v = get_mrc_func(r['subtomogram'])
if ('angle' in r):
v = GR.rotate_pad_mean(v, angle=N.array(r['angle'], dtype=N.float), loc_r=N.array(r['loc'], dtype=N.float))
if ((op is not None) and ('segmentation_tg' in op) and ('template' in r) and ('segmentation' in r['template'])):
phi = IV.read_mrc_vol(r['template']['segmentation'])
phi_m = (phi > 0.5)
del phi
(ang_inv, loc_inv) = AAL.reverse_transform_ang_loc(r['angle'], r['loc'])
phi_mr = GR.rotate(phi_m, angle=ang_inv, loc_r=loc_inv, default_val=0)
del phi_m
del ang_inv, loc_inv
import aitom.tomominer.pursuit.multi.util as PMU
v_s = PMU.template_guided_segmentation(v=v, m=phi_mr, op=op['segmentation_tg'])
del phi_mr
if (v_s is not None):
v_f = N.isfinite(v_s)
if (v_f.sum() > 0):
v_s[N.logical_not(v_f)] = v_s[v_f].mean()
v = v_s
del v_s
v = NF.fftshift(NF.fftn(v))
m = get_mrc_func(r['mask'])
if ('angle' in r):
m = GR.rotate_mask(m, angle=N.array(r['angle'], dtype=N.float))
v[(m < op['mask_cutoff'])] = 0.0
return {'v': v, 'm': m, }
def transform(phi, A_fourier, n, inv=False):
A_real = inv_fourier_transform(A_fourier)
ang = [phi['q_rot'], phi['q_tilt'], phi['q_psi']]
loc = [phi['q_x'], phi['q_y'], phi['q_z']]
if inv:
ang, loc = ang_loc.reverse_transform_ang_loc(ang, loc)
A_real_rot = rotate.rotate_pad_mean(A_real, angle=ang, loc_r=loc)
result = fourier_transform(A_real_rot)
return result
def inv_transform_mask(phi, w, n):
ang = [phi['q_rot'], phi['q_tilt'], phi['q_psi']]
loc = [0.0, 0.0, 0.0]
ang, loc = ang_loc.reverse_transform_ang_loc(ang, loc)
w_rot = rotate.rotate_pad_zero(w, angle=ang, loc_r=loc)
return w_rot