The contents of the Q3 files appear to be:
1. 100307_3T_Structural_preproc.zip
2. 
3. Thu Aug 29 18:30:20 CDT 2013
4. Structural Pipeline v2.0
5. Execution 1
6. 
7. These data were generated and made available by the Human Connectome 
Project...

--Greg

____________________________________________________________________
Greg Burgess, Ph.D.
Staff Scientist, Human Connectome Project
Washington University School of Medicine
Department of Neuroscience
Phone: 314-362-7864
Email: [email protected]

> On Dec 15, 2015, at 10:31 AM, Timothy B. Brown <[email protected]> wrote:
> 
> Hi Matthew,
>  
> Re: Your question 1) below about detected which release data is part of
>  
> I can't really speak to differentiating between Q1 vs. Q2 vs Q3 data, but I 
> can think of a technique that should work and be scriptable for detecting 
> whether a subject's data is from the 500subjects release or the 900subjects 
> release. The technique would be based on the contents of at least 1 release 
> notes file for the subject. 
>  
> If you have downloaded the structurally preprocessed data package for a 
> subject (e.g. 100307_3T_Structural_preproc.zip) and unzipped that package, 
> then you should have a sub-directory below the directory at which you did the 
> unzipping named 100307 and a sub-directory below that named release-notes. In 
> the 100307/release-notes sub-directory, you should find a file named 
> Structural_preproc.txt (the release notes for the Structural_preproc package).
>  
> I think it might be slightly problematic to count on the modification date of 
> that release notes file as an indication of whether the data is part of the 
> 500subjects release or 900subjects release. In my opinion it is too easy for 
> that file modification date to be inadvertently changed or updated. (The tool 
> used to unzip the package may not preserve modification dates; someone might 
> accidentally touch the file and thus change it's modification date; someone 
> may edit the file intending to simply look at it, accidentally add a space, 
> and save the result.)  I think it would be more reliable to differentiate 
> between the 500subjects release and the 900subjects release based on the 
> contents of the release notes file. (I'm supposing that people are unlikely 
> to purposely change the contents of these files and wouldn't be likely to 
> accidentally change the date written in the file or substantially change the 
> contents.)
>  
> For the 500subjects release, the first few lines of the release notes file 
> should look something like the following (without the line numbers):
>       • 100307_3T_Structural_preproc.zip
>       •  
>       • Sat Mar 29 13:21:24 CDT 2014
>       • Structural Pipeline v3.1
>       • Execution 1
>       •  
>       • These data were generated and made available by the Human Connectome 
> Project, ...
> For the 900subjects release, the first few lines of the release notes file 
> should look something like the following (without the line numbers):
>       • 100307_3T_Structural_preproc.zip
>       •  
>       • Mon Nov 30 23:44:34 CST 2015
>       •  
>       • These data were generated and made available by the Human Connectome 
> Project,
> Since all the Structural Preproc packages for the 900subjects release were 
> finalized after 31 Oct 2015, you could read in the 3rd line of the release 
> notes file, parse the date, and check to see if the date is before or after 
> 31 Oct 2015.  If it is before 31 Oct 2015, then the data is from the 
> 500subjects release.  If it's after 31 Oct 2015, then the data is from the 
> 900subjects release.
>  
> If parsing and comparing the dates is cumbersome, you could also simply look 
> at the contents of line 4 in the release notes file. If it starts with 
> "Structural Pipeline" then you're working with 500subjects data. If it is a 
> blank line, then you're working with 900subjects data. (In the 900subjects 
> form of the release notes, the pipeline version numbers come at the end of 
> the release notes file instead of right after the date.)
>  
> If you don't have the structurally preprocessed data for a subject, you could 
> probably extrapolate this technique to use the release notes file for the 
> package(s) you do have.
>  
> Off hand, I don't know what the release notes files look like for Q1, Q2, and 
> Q3, but if you have some of that data, you might be able to extend this 
> method to differentiate between those releases by examining the contents of 
> those release notes files.
>  
> I realize that this isn't a particularly elegant mechanism. Maybe someone 
> else can think of a quicker or more elegant solution (maybe simply based on 
> the presence or absence of a particular file generated by the pipelines.)
>  
> The above technique should allow you to differentiate between releases, but 
> as for your question 2), detecting the version of the image reconstruction 
> algorithm applied, I don't have a good answer for that.
>  
> Hope this is at least somewhat helpful,
>  
>   Tim
>  
> On Tue, Dec 8, 2015, at 04:26, Matthew George Liptrot wrote:
>> Hi,
>>  
>> 1) I understand that some of the processing of HCP data is different for the 
>> different releases (Q1, Q2/3, 500subjects etc).
>> Is there a scriptable way to see which version/release my downloaded data 
>> came from? (I am working on several different HCP releases with various 
>> groups of co-workers and it would be nice if my scripts could check for this 
>> automatically)
>>  
>> 2) I also understand that the image reconstruction method is different for 
>> some releases (From the wiki: “Two versions of the image reconstruction 
>> algorithm applied to dMRI and fMRI data have been used in HCP to date: 
>> version r177 for subjects scanned in Q1 through mid-Q3, version r227 for 
>> subjects scanned mid-Q3 and after. “)
>> Again, is there any scriptable way to check which version was used for data 
>> that is already downloaded? (Same reason as above)
>>  
>> Many thanks,
>>  
>> 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
>>  
>>  
>> _______________________________________________
>> HCP-Users mailing list
>> [email protected]
>> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>> 
> --
> Timothy B. Brown
> Business & Technology Application Analyst III
> Pipeline Developer (Human Connectome Project)
> tbbrown(at)wustl.edu
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