Hi,
I ran this code using the most update binaries on OSX 10.9.1:
3dQwarp -verb -prefix ${subj}.anat.uni.strip.mni.2in1 \
-duplo -useweight -blur 0 3 -base MNI_1mm_brain+tlrc -allineate \
-allineate_opts '-twopass -cost nmi -autoweight -fineblur 3 -cmass -source_automask -automask' \
-source ${subj}.anat.uni.strip+orig
Most of the output from -verb is for the 3DAllineate part which completes fine but outputs files with weird names:
XYZ_Q-l48r2Mwu3O5DM8j6Q5Ag.aff12.1D
XYZ_Q-l48r2Mwu3O5DM8j6Q5Ag.nii.gz
++ OpenMP thread count = 8
++ 3dQwarp: AFNI version=AFNI_2011_12_21_1014 (Jan 30 2014) [64-bit]
++ Authored by: Zhark the (Hermite) Cubically Warped
++ Starting 3dAllineate (affine register) command:
3dAllineate -base MNI_1mm_brain+tlrc -source CID.0341.anat.uni.strip+orig -prefix XYZ_Q-l48r2Mwu3O5DM8j6Q5Ag.nii -1Dmatrix_save XYZ_Q-l48r2Mwu3O5DM8j6Q5Ag -cmass -final wsinc5 -float -master BASE -verb -twopass -cost nmi -autoweight -fineblur 3 -cmass -source_automask -automask
++ ###########################################################
++ 3dAllineate: AFNI version=AFNI_2011_12_21_1014 (Jan 30 2014) [64-bit]
++ Authored by: Zhark the Registrator
++ Source dataset: ./CID.0341.anat.uni.strip+orig.HEAD
++ Base dataset: ./MNI_1mm_brain+tlrc.HEAD
++ Loading datasets
++ 1387105 voxels in -source_automask
++ Zero-pad: zbot=3 ztop=0
++ Computing -automask
+ Weightize: xfade=12 yfade=13 zfade=12
+ Weightize: (unblurred) top clip=9120.94
+ Weightize: (blurred) bot clip=625.379
+ Weightize: binarizing
++ -automask net CPU time = 1.6 s
++ 2259159 voxels [30.8%] in weight mask
++ Number of points for matching = 1061804
+ 12 free parameters
++ Normalized convergence radius = 0.000359
++ OpenMP thread count = 8
++ ======= Allineation of 1 sub-bricks using Normalized MI [H(b,s)/(H(b)+H(s))] =======
++ ========== sub-brick #0 ========== [total CPU to here=4.6 s]
++ *** Coarse pass begins ***
+ - Search for coarse starting parameters
+ - Testing (64+37)*64 params:#oo++.+.-.oo.+-+-o+o..o.oo..+.++$+-o+o+.oo- + - best 23 costs found:
0 v= 0.991325: -5.54 -43.71 -17.68 0.00 0.00 0.00 [grid]
1 v= 0.993367: -22.39 -35.78 -23.43 16.35 19.66 -17.40 [rand]
2 v= 0.993497: -22.39 -51.65 -11.93 16.35 19.66 -17.40 [rand]
3 v= 0.994426: 11.31 -51.65 -23.43 -16.35 19.66 -17.40 [rand]
4 v= 0.994428: 11.31 -51.65 -11.93 -16.35 19.66 17.40 [rand]
5 v= 0.994466: 11.31 -35.78 -23.43 -16.35 19.66 17.40 [rand]
6 v= 0.994530: -22.39 -51.65 -23.43 16.35 19.66 17.40 [rand]
7 v= 0.994590: -22.39 -51.65 -23.43 16.35 19.66 -17.40 [rand]
8 v= 0.994608: -22.39 -35.78 -11.93 16.35 19.66 -17.40 [rand]
9 v= 0.994801: 11.31 -35.78 -11.93 -16.35 19.66 17.40 [rand]
10 v= 0.994854: 11.31 -35.78 -23.43 -16.35 19.66 -17.40 [rand]
11 v= 0.994917: -22.39 -35.78 -23.43 -16.35 19.66 -17.40 [rand]
12 v= 0.995043: 11.31 -51.65 -11.93 -16.35 19.66 -17.40 [rand]
13 v= 0.995126: -51.79 -64.25 -21.73 -15.54 -2.18 26.98 [rand]
14 v= 0.995137: 13.83 -66.93 2.01 -20.00 10.00 10.00 [grid]
15 v= 0.995185: -26.17 -27.25 -24.82 10.66 9.02 -19.95 [rand]
16 v= 0.995191: 11.31 -51.65 -23.43 -16.35 19.66 17.40 [rand]
17 v= 0.995273: -51.79 -64.25 -21.73 -15.54 2.18 26.98 [rand]
18 v= 0.995382: -20.54 6.46 4.48 -20.45 -11.86 -13.68 [rand]
19 v= 0.995394: -22.39 -35.78 -11.93 16.35 19.66 17.40 [rand]
20 v= 0.995534: -22.39 -51.65 -11.93 16.35 19.66 17.40 [rand]
21 v= 0.995573: 15.09 -60.18 -24.82 -10.66 9.02 -19.95 [rand]
22 v= 0.995589: -26.17 -60.18 -10.53 -10.66 -9.02 19.95 [rand]
+ - costs of the above after a little optimization:
0 v= 0.981927: -4.89 -51.99 -13.20 0.83 0.92 4.76 [grid]
1 v= 0.990843: -17.31 -34.08 -21.68 15.36 19.25 -18.97 [rand]
2 v= 0.987572: -10.45 -46.99 -11.17 11.15 22.08 -15.78 [rand]
3 v= 0.991307: -2.16 -48.86 -24.07 -17.89 15.44 -17.44 [rand]
* 4 v= 0.976106: -5.11 -44.44 -6.96 -1.27 20.97 5.93 [rand]
5 v= 0.988791: 5.93 -42.60 -19.05 -7.77 12.09 29.89 [rand]
6 v= 0.991677: -7.43 -47.48 -13.27 13.91 18.80 16.15 [rand]
7 v= 0.988200: -12.15 -46.68 -11.59 13.66 22.25 -21.35 [rand]
8 v= 0.988120: -11.45 -47.24 -10.31 12.55 23.32 -17.52 [rand]
9 v= 0.986795: -1.69 -46.26 -8.88 -13.85 24.52 20.05 [rand]
10 v= 0.991297: -2.90 -49.54 -22.79 -20.21 11.24 -17.80 [rand]
11 v= 0.993797: -15.10 -35.30 -20.12 -16.27 19.65 -17.26 [rand]
12 v= 0.990894: -3.42 -46.25 -13.68 -11.34 19.21 -15.81 [rand]
13 v= 0.994389: -50.56 -63.57 -22.29 -16.27 -2.18 23.57 [rand]
14 v= 0.988695: 2.85 -46.87 -4.12 -17.36 20.72 5.35 [grid]
15 v= 0.988886: -14.79 -34.92 -23.12 3.68 9.25 -17.55 [rand]
16 v= 0.990190: 2.62 -51.49 -16.63 -15.19 12.13 27.29 [rand]
17 v= 0.994596: -49.30 -60.82 -20.79 -17.12 -0.42 24.90 [rand]
18 v= 0.994776: -18.93 6.56 -0.32 -21.30 -11.10 -13.87 [rand]
19 v= 0.988464: -13.36 -44.08 -7.82 23.35 17.96 -1.44 [rand]
20 v= 0.978718: -6.71 -46.25 -7.47 3.56 20.27 1.16 [rand]
21 v= 0.992096: 1.13 -41.84 -28.11 -13.85 10.51 -24.63 [rand]
22 v= 0.995217: -24.26 -55.96 -10.73 -7.13 -8.08 20.47 [rand]
+ - Coarse startup search net CPU time = 84.2 s
++ Start refinement #1 on 6 coarse parameter sets
+ - param set #1 has cost=0.963532
+ - param set #2 has cost=0.965081
+ - param set #3 has cost=0.982783
+ - param set #4 has cost=0.960553
+ - param set #5 has cost=0.971428
+ - param set #6 has cost=0.970102
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
++ Start refinement #2 on 6 coarse parameter sets
+ - param set #1 has cost=0.962306
+ - param set #2 has cost=0.963406
+ - param set #3 has cost=0.962520
+ - param set #4 has cost=0.962649
+ - param set #5 has cost=0.963123
+ - param set #6 has cost=0.969416
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
++ Start refinement #3 on 6 coarse parameter sets
+ - param set #1 has cost=0.967493
+ - param set #2 has cost=0.967420
+ - param set #3 has cost=0.967458
+ - param set #4 has cost=0.967552
+ - param set #5 has cost=0.967547
+ - param set #6 has cost=0.967652
+ - sorting parameter sets by cost
+ -- scanning for distances from #1
+ - Total coarse refinement net CPU time = 46.8 s; 1664 funcs
++ *** Fine pass begins ***
++ Picking best parameter set out of 7 cases
+ - cost(#1)=0.970313 *
+ - cost(#2)=0.970365
+ - cost(#3)=0.970309 *
+ - cost(#4)=0.970383
+ - cost(#5)=0.970370
+ - cost(#6)=0.970501
+ - cost(#7)=0.991414
+ -num_rtb 99 ==> refine all 7 cases
+ - cost(#1)=0.970227 *
+ - cost(#2)=0.970256
+ - cost(#3)=0.970240
+ - cost(#4)=0.970254
+ - cost(#5)=0.970219 *
+ - cost(#6)=0.970241
+ - cost(#7)=0.989077
+ - case #5 is now the best
+ - Initial cost = 0.970219
+ - Initial fine Parameters = -5.2913 -46.0009 -5.7777 -0.3384 19.4021 5.8925 0.9291 0.9762 0.8599 0.0059 -0.0126 -0.0411
+ - Finalish cost = 0.970214 ; 85 funcs
+ - Final cost = 0.970214 ; 124 funcs
+ Final fine fit Parameters:
x-shift=-5.2684 y-shift=-45.9861 z-shift=-5.7693
z-angle=-0.3214 x-angle=19.4090 y-angle= 5.8738
x-scale= 0.9291 y-scale= 0.9761 z-scale= 0.8600
y/x-shear= 0.0032 z/x-shear=-0.0126 z/y-shear=-0.0410
+ - Fine net CPU time = 61.6 s
++ Computing output image
++ Output dataset ./XYZ_Q-l48r2Mwu3O5DM8j6Q5Ag.nii.gz
++ Wrote -1Dmatrix_save XYZ_Q-l48r2Mwu3O5DM8j6Q5Ag.aff12.1D
++ total CPU time = 218.5 sec Elapsed = 81.9
++ ###########################################################
++ ### Please check results visually for alignment quality ###
++ ###########################################################
++ 3dQwarp: replacing source dataset with CID.0341.anat.uni.strip.mni.2in1_Allin.nii
** FATAL ERROR: Can't open replacement source??
** Program compile date = Jan 30 2014
