Taylor Salo tsalo

## fmriprep_warp.sh
# First, let's define some paths to the fMRIPrep and tedana outputs
fmriprep_dir="/path/to/fmriprep/derivatives/of/subject"
tedana_dir="/path/to/tedana/derivatives"

# Result of denoising the scanner-space multi-echo data with tedana
file_to_warp="${tedana_dir}/sub-01_task-rest_desc-optcomDenoised_bold.nii.gz"

# Name of the standard-space denoised data file to be written out
out_file="${tedana_dir}/sub-01_task-rest_space-MNI152NLin2009cAsym_desc-optcomDenoised_bold.nii.gz"

## profile_nimare.py
"""A small job to profile kernel transformers and meta estimators in NiMARE."""
import logging
import os.path as op
import psutil
from datetime import datetime

import numpy as np
import pandas as pd
from memory_profiler import memory_usage

## collect_fmriprep.py
"""
Collect native-space preprocessed data from fMRIPrep working directory and
copy into fMRIPrep derivatives directory, in BIDS format.

This script has only been tested on fMRIPrep v20.2.1.
It may not work with other versions.

Written by Julio Peraza (@JulioAPeraza)
"""
import argparse

## nimare_atlas_decoding.ipynb

      
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                tsalo
                / nimare_atlas_decoding.ipynb
            
            
              Created
              June 17, 2020 19:44
            
              
                Decoding an atlas with NiMARE v0.0.3
              
          
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## tedana_decision_tree_pseudocode.py
from textwrap import dedent
import logging

LGR = logging.getLogger(__name__)


def list_to_str(lst, joiner='and'):
    if len(lst) == 1:
        return lst[0]
    elif len(lst) == 2:

## assign_intendedfor.py
import json
import bisect
from glob import glob
from os.path import join, splitext
from bids.grabbids import BIDSLayout
from dateutil.parser import parse

# subj_dir *must* have trailing /
subj_dir = '/scratch/tsalo006/dset/sub-01/'
sess = '01'

## nipype_lss.py
from nipype.interfaces.base import Bunch
from nipype.algorithms import modelgen
from copy import deepcopy


def lss(bunch_list):
    """Takes input Bunch list and returns list of Bunch lists with LSS regressors.
    """
    all_infos = []
    other_items = ['durations', 'amplitudes',

## coolCellFuns.m
% Dir results to cell array of file names
AllTextFiles = dir('/home/tsalo/*.txt');
cellArray = struct2cell(AllTextFiles);
cellArray = cellArray(1, :);
[allFilepaths, allFilenames, allSuffixes] = cellfun(@(X) fileparts(X), cellArray, 'UniformOutput', false);


## allFilesExist.m
function log = allFilesExist(cellArray)
log = all(cellfun(@(X) logical(exist(X, 'file')), cellArray));
end

## get_code_dir.py
"""
Get directory of script. Also, get parent directory.
"""
import os.path

code_dir = os.path.dirname(__file__)
par_dir = os.path.abspath(os.path.join(code_dir, os.path.pardir))
	# First, let's define some paths to the fMRIPrep and tedana outputs
	fmriprep_dir="/path/to/fmriprep/derivatives/of/subject"
	tedana_dir="/path/to/tedana/derivatives"

	# Result of denoising the scanner-space multi-echo data with tedana
	file_to_warp="${tedana_dir}/sub-01_task-rest_desc-optcomDenoised_bold.nii.gz"

	# Name of the standard-space denoised data file to be written out
	out_file="${tedana_dir}/sub-01_task-rest_space-MNI152NLin2009cAsym_desc-optcomDenoised_bold.nii.gz"
	"""A small job to profile kernel transformers and meta estimators in NiMARE."""
	import logging
	import os.path as op
	import psutil
	from datetime import datetime

	import numpy as np
	import pandas as pd
	from memory_profiler import memory_usage
	"""
	Collect native-space preprocessed data from fMRIPrep working directory and
	copy into fMRIPrep derivatives directory, in BIDS format.

	This script has only been tested on fMRIPrep v20.2.1.
	It may not work with other versions.

	Written by Julio Peraza (@JulioAPeraza)
	"""
	import argparse
	from textwrap import dedent
	import logging

	LGR = logging.getLogger(__name__)


	def list_to_str(lst, joiner='and'):
	if len(lst) == 1:
	return lst[0]
	elif len(lst) == 2:
	import json
	import bisect
	from glob import glob
	from os.path import join, splitext
	from bids.grabbids import BIDSLayout
	from dateutil.parser import parse

	# subj_dir must have trailing /
	subj_dir = '/scratch/tsalo006/dset/sub-01/'
	sess = '01'
	from nipype.interfaces.base import Bunch
	from nipype.algorithms import modelgen
	from copy import deepcopy


	def lss(bunch_list):
	"""Takes input Bunch list and returns list of Bunch lists with LSS regressors.
	"""
	all_infos = []
	other_items = ['durations', 'amplitudes',
	% Dir results to cell array of file names
	AllTextFiles = dir('/home/tsalo/*.txt');
	cellArray = struct2cell(AllTextFiles);
	cellArray = cellArray(1, :);
	[allFilepaths, allFilenames, allSuffixes] = cellfun(@(X) fileparts(X), cellArray, 'UniformOutput', false);
	function log = allFilesExist(cellArray)
	log = all(cellfun(@(X) logical(exist(X, 'file')), cellArray));
	end
	"""
	Get directory of script. Also, get parent directory.
	"""
	import os.path

	code_dir = os.path.dirname(__file__)
	par_dir = os.path.abspath(os.path.join(code_dir, os.path.pardir))