wb_command -file-information gives you stats like this:

Map     Minimum     Maximum     Mean   Sample Dev   % Positive   %Negative   
Inf/NaN   Map Name


On Aug 25, 2015, at 6:32 AM, Matthew George Liptrot <[email protected]> 
wrote:

> Hi Stam,
> 
> Yep, workbench opens them fine. If I load in the dconn file, a surface and 
> the greyordinates.dscalar file, then I can see the connectivity maps as I 
> click different parts of the surface. 
> Is there a better way to check if the values are reasonable? E.g. Would the 
> histograms report if NaNs are present?
> 
> Good to hear about the FSL release! I guess though that this is a wb_command 
> bug (or a bug in my use of it! :-)
> 
> Cheers,
> 
> M@
> 
> On 24/8/15 14:40 , "Stamatios Sotiropoulos" 
> <[email protected]> wrote:
> 
> Hi Matthew
> 
> No, they are not meant to be there. Can you open and display the dconn file 
> in workbench?
> 
> FYI, there will be a new FSL release sometime this or the next week. It will 
> have some bug fixes in probtrackx2 and some new features. It may be the case 
> that this problem disappears with the new version. 
> 
> Cheers
> Stam
> 
> 
> 
> On 24 Aug 2015, at 08:24, Matthew George Liptrot <[email protected]> 
> wrote:
> 
>> Hi all,
>> 
>> We’ve been using the HCP DWI data to generate dense connectomes in ‘matrix3’ 
>> format. Following previous advice, we are doing this in multiple stages:
>>      • Generate 3 separate targets (left surface, right surface, subcortical 
>> voxels)
>>      • For each, run probtrackx2 (seed = white matter voxels, target as 
>> above) multiple times using the ‘-rseed’ option (1000 streams per voxel as a 
>> robustness / computational trade-off). 
>>      • The multiple probtrackx2 runs are combined with FSL’s 
>> fdt_matrix_merge. This gives us 3 FSL  .dot files.
>>      • Convert each of the three .dot files to .dconn using <wb_command 
>> -probtrackx-dot-convert>
>>      • Merge the three .dconn files using <wb_command  -cifti-merge-dense> 
>> to obtain the final 92K x 92K dconn matrix.
>> The problem is that we get both NaN’s and zeros in the final, merged dconn 
>> matrix. Presumably we should not have any NaN’s, as the numbers should just 
>> represent count statistics?
>> 
>> We looked into the outputs at different stages, and it seems that the NaN’s 
>> only appear after Step 5.
>> 
>> So our question is: are the NaN’s meant to be there, and if so, what do they 
>> represent? If not, is this a bug or a mistake on our part?
>> 
>> Many thanks for any help!
>> 
>> M@
>> 
> 
> 
> -- 
> Matthew George Liptrot
> 
> Department of Computer Science
> University of Copenhagen
> & 
> Section for Cognitive Systems
> Department of Applied Mathematics and Computer Science
> Technical University of Denmark
> 
> http://about.me/matthewliptrot
> 
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> 


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