NITRC Seed-based d Mapping (SDM, formerly Signed Differential Mapping) Forum: sdm-help-list

RE: SDM can't find my txt file despite the correct spelling

psyhelen — Wed, 31 Jul 2024 9:56:11 GMT

Problem solved, please try different combinations of naming (e.g., removing the prefix or suffix of the file, and change the filename to a completely different one and see if it works).
 
Originally posted by psyhelen:
<blockquote>
Hi there,
No, the problem remains outstanding. Do you have any luck resolving this error?
 
 
Originally posted by Xinyun Lin:
<blockquote>
Hello, I'm having the same problem, have you solved this issue please? Can you tell me what to do with it?
 
Originally posted by psyhelen:
<blockquote>
Dear Developers of SDM,
I hope all is well. I am encountering an issues during the preprocessing stage as SDM could not find the txt file under the working directory.
 
The file that could not be traced was called 'Fang.spm_mni.txt'. However, as indicated in the photo attachment, the file with the exact name is actually in the working directory.
 
I have also attached the execution log below, could you please provide me with some suggestions regards how to solve this issue? I have tried to change the file names several times, but the txt file remained undetectable by the software. Thank you in advance for your time and assistance.
 
Kind regards,
Helen 
--- Execution Log ---
$ C:/Users/Psychology/Documents/PsyToolbox/SDM/bin/windows64/sdm_parse.exe pp gray matter, 1, 20, gray matter, 2
Home dir C:\Users\Psychology\sdm.conf
Load atlas C:\Users\Psychology\Documents\PsyToolbox\SDM\bin\windows64\..\..\/share/atlas_aal_cts_2mm.nii.gz
length 902629 sdm1_lengt 902629
aAnalyzing coordinates
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WARNING: File 'Fang.nii.gz', 'Fang.spm_mni.txt', 'Fang.fsl_mni.txt', 'Fang.other_mni.txt', 'Fang.spm_brett.txt', 'Fang.fsl_brett.txt', 'Fang.other_tal.txt' or 'Fang.no_peaks.txt' not found.
The program will close as this problem could cause fatal errors.
 
 
</blockquote>
 
</blockquote>
 
</blockquote>

RE: FWE getting null distributions step - stuck?

Jessica Hazelton — Mon, 29 Jul 2024 17:41:02 GMT

Hi all,
I am running FWE corrections for my meta-analyses, however, it seems to get stuck (or take a long time) on the getting null distributions step:<img src="data:image/png;base64,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" width="608" height="501">
Does this step usually take a long time to run (I am only using 1 thread) or has the process terminated due to some other error? It has been like this for about 1 hour.
There are currently no errors in the executive log which shows this:
%98% Estimated remaining time(s): 1 (ETA 2024-07-29 13:42:17)
oLoading imputations
 
Thanks

RE: problem with meta-regression

Xinyun Lin — Sat, 27 Jul 2024 9:49:40 GMT

Hello, is your problem solved? I had a similar problem when I did a linear regression analysis with SDM version 6.23. I've attached a screenshot of the execution log, I don't understand what the problem is? Can you generously share what went wrong? Thanks in advance!

RE: SDM-PSI is not operational.

xiaomeng fan — Wed, 17 Jul 2024 4:27:40 GMT

Dear yu wang,
i meet the same question with you.Have you solved your problem?If possible,could you share it with me?

RE: SDM can't find my txt file despite the correct spelling

psyhelen — Thu, 11 Jul 2024 5:58:33 GMT

Hi there,
No, the problem remains outstanding. Do you have any luck resolving this error?
 
 
Originally posted by Xinyun Lin:
<blockquote>
Hello, I'm having the same problem, have you solved this issue please? Can you tell me what to do with it?
 
Originally posted by psyhelen:
<blockquote>
Dear Developers of SDM,
I hope all is well. I am encountering an issues during the preprocessing stage as SDM could not find the txt file under the working directory.
 
The file that could not be traced was called 'Fang.spm_mni.txt'. However, as indicated in the photo attachment, the file with the exact name is actually in the working directory.
 
I have also attached the execution log below, could you please provide me with some suggestions regards how to solve this issue? I have tried to change the file names several times, but the txt file remained undetectable by the software. Thank you in advance for your time and assistance.
 
Kind regards,
Helen 
--- Execution Log ---
$ C:/Users/Psychology/Documents/PsyToolbox/SDM/bin/windows64/sdm_parse.exe pp gray matter, 1, 20, gray matter, 2
Home dir C:\Users\Psychology\sdm.conf
Load atlas C:\Users\Psychology\Documents\PsyToolbox\SDM\bin\windows64\..\..\/share/atlas_aal_cts_2mm.nii.gz
length 902629 sdm1_lengt 902629
aAnalyzing coordinates
.
 
.
.
 
.
 
.
 
.
 
.
 
.
 
.
 
 
 
WARNING: File 'Fang.nii.gz', 'Fang.spm_mni.txt', 'Fang.fsl_mni.txt', 'Fang.other_mni.txt', 'Fang.spm_brett.txt', 'Fang.fsl_brett.txt', 'Fang.other_tal.txt' or 'Fang.no_peaks.txt' not found.
The program will close as this problem could cause fatal errors.
 
 
</blockquote>
 
</blockquote>

RE: Error in preprocessing

Xinyun Lin — Tue, 02 Jul 2024 16:49:00 GMT

Hello, may I ask if the file name can not have a space, where is the file name with a space? Because I encountered a similar problem, I hope you can share the way to solve it, thanks. 
Originally posted by giuseppe zito:
<blockquote>Dear developers, I just read your paper on this new meta-analytical method, and I would like to use it for a met-analysis I'm planning to run. I was going through the tutorial, and I stopped already at the pre-processing for the following error: $ D:/SCI Meta-analysis/SdmPsiGui-win64-v6.22/bin/windows64\/sdm_parse.exe pp gray matter, 1, 20, gray matter, 2 $ D:/SCI Meta-analysis/SdmPsiGui-win64-v6.22/bin/windows64\/sdm_parse.exe pp gray matter, 1, 20, gray matter, 2 $ D:/SCI Meta-analysis/SdmPsiGui-win64-v6.22/bin/windows64\/sdm_parse.exe pp cerebrospinal fluid, 1, 20, cerebrospinal fluid, 2 $ D:/SCI Meta-analysis/SdmPsiGui-win64-v6.22/bin/windows64\/sdm_parse.exe pp white matter, 1, 20, white matter, 2 My feeling is that there is a problem in the folder navigation (there is a \ and a / together), but I don't know how to change it, because the path in the Tool/Preferences/Core binaries is set automatically after I navigate the folder. Of note, I am running SDM on Windows 10. Any help would be appreciated. Thank you very much Giuseppe Zito</blockquote>

RE: Error on launch Preprocessing

Xinyun Lin — Tue, 02 Jul 2024 16:32:21 GMT

Hello, is your problem solved? Because I encountered a similar problem, I hope you can share the way to solve it, thanks.
Originally posted by Mekha Thomas:
<blockquote>[i]Originally posted by Anton Albajes-Eizagirre:[/i][quote]Dear Fangyoumutu, It appears that SDM can't find any map/file for study Menka. Can you please double check the C:/Program Files/SDM Meta Analysis/tutorial directory to assert that there is a file for the menka study? If problem persists, could you please send us a copy of the tutorial directory to see if we can reproduce the problem? Best, Anton[/quote][color=#000000]Dear Mr.Anton,[/color] [color=#000000]I was conducting a Coordinate based meta-analysis of networks ,I have only coordinate files for each study but no maps. I have saved my files as "MF1.spm_mni.txt and MF2.spm_mni.txt" and the sdm table for them as "MF1 and MF2" respectively, all in the same working directory as well (D:/Mekha/SDM).[/color] After launching preprocessing ,I got the following warning  'Launched: sdm pp gray matter, 1, 20, gray matter, 2 Analyzing coordinates'; [b][color=#000000]"WARNING: File 'MF1.nii.gz', 'MF1.spm_mni.txt', 'MF1.fsl_mni.txt', 'MF1.other_mni.txt', 'MF1.spm_brett.txt', 'MF1.fsl_brett.txt', 'MF1.other_tal.txt' or 'MF1.no_peaks.txt' not found."[/color][/b] Could you please help me understand and resolve the same ,as I have left the analysis overnight to run as well but it showed no progress ,please let me know what can be done further. A reply at the earliest will be deeply appreciated as this work is a part of my thesis which is to be submitted this month. Thanks and regards, Mekha</blockquote>

RE: meta-analysis on seed-based fMRI

Xinyun Lin — Tue, 02 Jul 2024 16:24:08 GMT

Hello, can you please explain why the SDM software cannot perform seed-based meta-analysis? Because I've seen this type of article before, I'm a little confused now. 
Originally posted by Lydia Fortea:
<blockquote>
Dear maad, 
 
I'm afraif the SDM software doesn't allow seed-based fMRI meta-analysis
 
Best,
Lydia 
</blockquote>

RE: SDM can't find my txt file despite the correct spelling

Xinyun Lin — Tue, 02 Jul 2024 15:31:09 GMT

Hello, I'm having the same problem, have you solved this issue please? Can you tell me what to do with it?
 
Originally posted by psyhelen:
<blockquote>
Dear Developers of SDM,
I hope all is well. I am encountering an issues during the preprocessing stage as SDM could not find the txt file under the working directory.
 
The file that could not be traced was called 'Fang.spm_mni.txt'. However, as indicated in the photo attachment, the file with the exact name is actually in the working directory.
 
I have also attached the execution log below, could you please provide me with some suggestions regards how to solve this issue? I have tried to change the file names several times, but the txt file remained undetectable by the software. Thank you in advance for your time and assistance.
 
Kind regards,
Helen 
--- Execution Log ---
$ C:/Users/Psychology/Documents/PsyToolbox/SDM/bin/windows64/sdm_parse.exe pp gray matter, 1, 20, gray matter, 2
Home dir C:\Users\Psychology\sdm.conf
Load atlas C:\Users\Psychology\Documents\PsyToolbox\SDM\bin\windows64\..\..\/share/atlas_aal_cts_2mm.nii.gz
length 902629 sdm1_lengt 902629
aAnalyzing coordinates
.
 
.
.
 
.
 
.
 
.
 
.
 
.
 
.
 
 
 
WARNING: File 'Fang.nii.gz', 'Fang.spm_mni.txt', 'Fang.fsl_mni.txt', 'Fang.other_mni.txt', 'Fang.spm_brett.txt', 'Fang.fsl_brett.txt', 'Fang.other_tal.txt' or 'Fang.no_peaks.txt' not found.
The program will close as this problem could cause fatal errors.
 
 
</blockquote>

RE: FWE correction: Error message halfway through analysis

Xu Jinglei — Sat, 29 Jun 2024 6:04:37 GMT

Originally posted by Lydia Fortea:
<blockquote>Hello Emily,  Could you tell me how many subjects has the study with the smallest sample size? Kind regards,  Lydia</blockquote>
Dear Lydia
I encountered a "terminate called after throwing an instance of 'std::bad_alloc' what(): bad_alloc" error while running the FWE. I suspect this is due to insufficient memory. I have a total of over fifty .txt files and am performing 1000 permutations. Approximately how much memory would be required to run this?
Best regards,
Leibby Xu