Autodoc test¶
neuropype¶
Parallel processing of MEG/EEG data
neuropype [OPTIONS] COMMAND1 [ARGS]... [COMMAND2 [ARGS]...]...
Options
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-n,--ncpu<ncpu>¶ number of CPUs to use takes effect only for MultiProc and PBS plugins
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-p,--plugin<plugin>¶ plugin to use; use Linear for single-thread computation, MultiProc parallel computation on local machine and PBS to compute on cluster
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-s,--save-path<save_path>¶ path to store results
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-w,--workflow-name<workflow_name>¶ name of destination directory
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--verbose,--no-verbose¶ verbosity level
conn¶
Create spectral connectivity node
neuropype conn [OPTIONS]
Options
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-b,--band<band>¶ frequency band
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-m,--method<method>¶ connectivity measure
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-s,--sfreq<sfreq>¶ data sampling frequency
epoch¶
Epoch raw .fif resting state data
neuropype epoch [OPTIONS]
Options
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-l,--length<length>¶ epoch length
ica¶
Compute ica solution for raw fif file
neuropype ica [OPTIONS]
Options
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-n,--n-components<n_components>¶
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-c,--ecg-ch-name<ecg_ch_name>¶
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-o,--eog-ch-name<eog_ch_name>¶
input¶
Create input node.
Use wildcards to run computations on multiple files; To check yourself it’s a good idea to run ls command first like this:
$ ls .//.fif
$ neuropype input .//.fif
neuropype input [OPTIONS] [FIF_FILES]...
Arguments
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FIF_FILES¶ Optional argument(s)
mse¶
Create multiscale entropy node
Experimental functionality. Available only in mse branch of neuropype_ephy
neuropype mse [OPTIONS]
Options
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-m<m>¶
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-r<r>¶
preproc¶
Create preprocessing node.
Filter and downsample of raw .fif data
neuropype preproc [OPTIONS]
Options
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-l,--l-freq<l_freq>¶
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-h,--h-freq<h_freq>¶
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-d,--ds_freq<ds_freq>¶ downsampling frequency
psd¶
Create power computation node.
Lower and higher frequency bounds for computation can be changed
Takes as input epochs in .fif format
EXAMPLE:
$ neuropype pwr input ~/fif_epochs//-epo.fif
neuropype psd [OPTIONS]
Options
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--fmin<fmin>¶ lower frequency bound; default=0
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--fmax<fmax>¶ higher frequency bound; default=300