output = basename+'_fsc.dat'
else:
output = args.output
nf = len(args.files)
fscs = []
for i in range(nf):
fscs.append(np.loadtxt(args.files[i]))
fscs = np.array(fscs)
if nf==1:
fsc = fscs[0]
else:
fsc = np.mean(fscs,axis=0)
resn, x, y, resx = saxs.fsc2res(fsc, return_plot=True)
if np.min(fsc[:,1]) > 0.5:
print("Resolution: < %.1f A (maximum possible)" % resn)
else:
print("Resolution: %.1f A" % resn)
np.savetxt(output,fsc,delimiter=' ',fmt='%.5e',header="1/resolution, FSC")
if args.plot:
import matplotlib.pyplot as plt
plt.plot(fsc[:,0],fsc[:,0]*0+0.5,'k--')
for i in range(nf):
plt.plot(fscs[i,:,0],fscs[i,:,1],'k--',alpha=0.1)
plt.plot(fsc[:,0],fsc[:,1],'bo-')
#plt.plot(x,y,'k-')
plt.plot([resx],[0.5],'ro',label='Resolution = '+str(resn)+r'$\mathrm{\AA}$')
rhosum = rho
else:
rhosum += rho
print()
rhos = np.array(rhos)
average_rho = rhosum / nmaps
saxs.write_mrc(average_rho, side, output + "_avg.mrc")
print("%s_avg.mrc written." % output)
#rather than compare two halves, average all fsc's to the reference
fscs = []
resns = []
for calc_map in range(nmaps):
fsc_map = saxs.calc_fsc(rhos[calc_map], average_rho, side)
fscs.append(fsc_map)
resn_map = saxs.fsc2res(fsc_map)
resns.append(resn_map)
fscs = np.array(fscs)
resns = np.array(resns)
fsc = np.mean(fscs, axis=0)
resn, x, y, resx = saxs.fsc2res(fsc, return_plot=True)
resn_sd = np.std(resns)
if np.min(fsc[:, 1]) > 0.5:
print("Resolution: < %.1f +- %.1f A (maximum possible)" %
(resn, resn_sd))
else:
print("Resolution: %.1f +- %.1f A " % (resn, resn_sd))
np.savetxt(output + '_fsc.dat',
fsc,