def cml_refine_agls(Prj, Ori, delta):
from copy import deepcopy
from utilities import amoeba
global g_n_prj
scales = [delta] * (g_n_prj + 2)
for iprj in xrange(g_n_prj):
# init vec_in
vec_in = [Ori[4 * iprj], Ori[4 * iprj + 1], Ori[4 * iprj + 2]]
# prepare vec_data
vec_data = [Prj, deepcopy(Ori), iprj]
# simplex
optvec, disc, niter = amoeba(vec_in,
scales,
cml_refine_agls_wrap_dev,
data=vec_data)
# assign new angles refine
Ori[4 * iprj] = (optvec[0] + 360) % 360
Ori[4 * iprj + 1] = optvec[1]
Ori[4 * iprj + 2] = optvec[2]
print 'refine:', iprj, 'angles:', Ori[4 * iprj:4 * iprj +
4], 'disc:', -disc
return Ori
def fit_tanh(dres, low = 0.1): """ dres - list produced by the fsc funcion dres[0] - absolute frequencies dres[1] - fsc, because it was calculated from the dataset split into halves, convert it to full using rn = 2r/(1+r) dres[2] - number of points use to calculate fsc coeff low cutoff of the fsc curve return parameters of the tanh filter: freq - cutoff frequency at which filter value is 0.5, and fall_off, the 'width' of the filter """ def fit_tanh_func(args, data): from math import pi, tanh v = 0.0 if(data[1][0] < 0.0 ): data[1][0] *= -1.0 for i in xrange(len(data[0])): fsc = 2*data[1][i]/(1.0+data[1][i]) if args[0]==0 or args[1]==0: qt=0 else: qt = fsc - 0.5*( tanh(pi*(data[0][i]+args[0])/2.0/args[1]/args[0]) - tanh(pi*(data[0][i]-args[0])/2.0/args[1]/args[0]) ) v -= qt*qt #print args,v return v setzero = False for i in xrange(1,len(dres[0])): if not setzero: if(2*dres[1][i]/(1.0+dres[1][i]) <low): setzero = True if setzero: dres[1][i] = 0.0 freq = -1.0 for i in xrange(1,len(dres[0])-1): if ( (2*dres[1][i]/(1.0+dres[1][i]) ) < 0.5): freq = dres[0][i-1] break if freq < 0.0: # the curve never falls below 0.5, most likely something's wrong; however, return reasonable values freq = 0.4 fall_off = 0.2 return freq, fall_off from utilities import amoeba args = [freq, 0.1] scale = [0.05, 0.05] result = amoeba(args, scale, fit_tanh_func, data = dres) ''' args[0] = result[0][0] args[1] = result[0][1] #print args from math import pi, tanh for i in xrange(len(dres[0])): fsc = 2*dres[1][i]/(1.0+dres[1][i]) print i, dres[0][i],fsc , 0.5*( tanh(pi*(dres[0][i]+args[0])/2.0/args[1]/args[0]) - tanh(pi*(dres[0][i]-args[0])/2.0/args[1]/args[0]) ) #qt = fsc - 0.5*( tanh(pi*(dres[0][i]+args[0])/2.0/args[1]/args[0]) - tanh(pi*(dres[0][i]-args[0])/2.0/args[1]/args[0]) ) ''' return result[0][0], result[0][1]
def cml_refine_agls(Prj, Ori, delta): from copy import deepcopy from utilities import amoeba global g_n_prj scales = [delta] * (g_n_prj + 2) for iprj in xrange(g_n_prj): # init vec_in vec_in = [Ori[4*iprj], Ori[4*iprj+1], Ori[4*iprj+2]] # prepare vec_data vec_data = [Prj, deepcopy(Ori), iprj] # simplex optvec, disc, niter = amoeba(vec_in, scales, cml_refine_agls_wrap_dev, data = vec_data) # assign new angles refine Ori[4*iprj] = (optvec[0]+360)%360 Ori[4*iprj+1] = optvec[1] Ori[4*iprj+2] = optvec[2] print 'refine:', iprj, 'angles:', Ori[4*iprj:4*iprj+4], 'disc:', -disc return Ori
