... | ... | @@ -11,20 +11,26 @@ Running your job locally is easy. There a few restrictions with local jobs such |
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* No pipeline/job based parallelism
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# Before you run
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Since this tutorial doesn't really provide a useful output and is more designed to just show you how to make a pipeline it doesn't really matter what data you use so long as it works.
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Since this tutorial doesn't really provide a useful output and is more designed to just show you how to make a pipeline it doesn't really matter what data you use so long as it works. If you have data formatted for EEGLAB you may go ahead and try it, otherwise you may use these test files:
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You may use these test files
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Practice Data Files
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There are 10 practice data files that can be downloaded from the following owncloud link if you wish to practice before you obtain your own data:
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[:cloud: OwnCloud at Westgrid](https://owncloud.westgrid.ca/index.php/s/0Rf5ekmbsEJLW6c)
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Select two or more sets of files from the link and place the corresponding .set and .fdt in your `data/1_init` directory.
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For our pipeline, our input data has to end in `_init.set`. This is due to the way we discover the correct input files for each stage using string swap.
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1. Open `File > Batch > Run History Template Batch`
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2. Click Load context config and select `config/contextconfig_local.cfg`
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3. Click History file and select s01-s04 from `scripts/`
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4. Click `Load batch config > Batch configuration file` and select `c01-c04 from `config/`
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4. Click `Load batch config > Batch configuration file` and select c01-c04 from `config/`
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5. Click Data file or ESS Capsule
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6. Select a data file
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6. Select a data file ending in `.set`
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7. From the main Run History Template Batch interface click `Ok` in the bottom right. The pipeline should commence.
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You will see output in the main Matlab Command Window
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![Screenshot_2017-08-11_14-08-21](/uploads/84d59e1e9268420a2e92b3c970b0cabe/Screenshot_2017-08-11_14-08-21.png)
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If the pipeline was successful you will see a `[batch_dfn]_fin.set`. If you'd like you can view the ICA data using [vised_marks](https://git.sharcnet.ca/bucanl_eeglab_extensions/vised_marks) or by using `Plot > Component activations (scroll)` in EEGLAB.
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*Updated/Verified by Brad Kennedy on 2017-08-11*
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