config_sge.py

# emacs =  -*- mode =  python; py-indent-offset =  4; indent-tabs-mode =  nil -*-
# vi =  set ft=python sts=4 ts=4 sw=4 et = 

"""
1. Distributed Processing Settings
    a) runOnGrid : options True/False or 0/1. Run On SGE Cluster/Grid
    b) qsubArgs : For use only when runOnGrid = True.

       -q QUEUE.q : The queue of nodes to use on the cluster/grid,
                    default is set to the queue of all nodes on the cluster(all.q).

    
       -pe A-B : Can Use with -q option. Specify the range of the number of slots to use on each node.
                   A is the lower bound on the range and B is the higher bound on the number of slots available

    c) num_cores: Use only when runOnGrid = False( or 0).
                  Specify the number of cores on a multiprocessor environment.
"""
runOnGrid = True
qsubArgs = '-q all.q'
numSubjectsAtOnce = 12
numCoresPerSubject = 1

"""
2. Directory Setup
"""

"""
    a) Nipype Specifications
"""

"""
        Nipype Cache/Working/Debug Directory
        Nipype will dump Temporary outputs and workflow engine specific outputs to this directory. 
        Each User must set it. 
        It is recommended to delete this directory once the pipeline completes execution.

"""
workingDirectory = '/home2/ssikka/nki_nyu_pipeline/working_dir/'

"""
        Crash Log Directory
"""
crashLogDirectory = '/home2/data/Projects/Pipelines_testing/Dickstein_working_dir/CrashLog'

"""
    b) Data Specifications
"""

"""
        Subject Data Directory and List
        For Ex:
            If your data directory is 
            /data/projects/ADHD200/usable/0010001
            /data/projects/ADHD200/usable/0010002
        subjectDirectory : '/data/projects/ADHD200/usable'
        subjectList(Optional): Full path to the file that contains subject numbers, one per line.
        exclusionSubjectList(Optional) : File containing subjects which should be left unprocessed.
        For Ex: subjectList : '/data/projects/ADHD200/docs/subjects.txt'

        $ cat subjects.txt
            0010001
            0010002
        $ cat 

        Note: When subjectList is set to None, all the subjects in the subject directory, except the ones in
              exclusionSubjectList are processed

"""
subjectDirectory = '/home2/data/Projects/Pipelines_testing/Dickstein/subjects'
subjectList = '/home2/data/Projects/Pipelines_testing/Dickstein/settings/subject_list.txt'
exclusionSubjectList = None

"""
        Anatomical File Name and Location within Subject Directory
        Note: anatomicalFileName substituted into anatomicalFilePath 
              Subject Number or subject names and anatomical file name automatically
              substitute 1st %s and Last %s. This is done by the pipeline datasource. 
        The user needs to set the directory structure

        For Ex:
           /data/projects/ADHD200/
                        0010001/anat_1/mprage.nii.gz
                        0010001/anat_2/mprage.nii.gz
                        0010002/anat_1/mprage.nii.gz
                        0010002/anat_2/mprage.nii.gz
    
        set
        anatomicalFileName = 'mprage'
        
        anatomicalFilePath = '%s/*/%s.nii.gz'

        /sam/wave0/
                    sub3114/
                            session_1/anat_1/mprage.nii.gz
                            session_1/anat_2/mprage.nii.gz

                    sub3115/  
                            session_1/anat_1/mprage.nii.gz
        
        anatomicalFileName = 'mprage'
        
        anatomicalFilePath = '%s/*/*/%s.nii.gz'

"""
anatTemplate = '%s/anat/%s.nii.gz'
anatTemplateList = ['subject', 'mprage']
anatSessionFile = '/home2/data/Projects/Pipelines_testing/Dickstein/settings/anat_session_list.txt'

"""
        anatLogFile: In case of multiple anatomical scans per subject.
                     Specify the name of the log file which indicates which single anatomical scan to process.

                    anatLogFilePath: Specify the location of the log file relative to the subject directory location.
                    The pipeline substitutes 1st %s with the subject number/name and the 2nd %s is the name of the log file. 
                    The User needs to specify only the structure as per his analysis. 


        Ex: /sam/wave1/sub8000/
                        anat_1/mprage.nii.gz
                        anat_2/mprage.nii.gz
                        logs/log.txt
        anatLogFile = 'log.txt'
        anatLogFilePath = '%s/*/%s'
    
"""
anatLogFile = 'log.txt' #Don't need this, for IPN use only. -Yang
anatLogFilePath = '%s/*/*/%s'



"""
        Functional File Name and Location within Subject Directory
        Note: functionalFileName substituted into functionalDirectorySetup template
"""
funcTemplate = '%s/%s/%s.nii.gz'
funcTemplateList = ['subject','session','rest']
funcSessionFile = '/home2/data/Projects/Pipelines_testing/Dickstein/settings/func_session_list.txt' # show an exmple somewhere... -Yang


"""
        Output Target Directory 
"""
sinkDirectory = '/home2/ssikka/nki_nyu_pipeline/results'


"""
    c) Miscellaneous Specifications
"""


"""
        Set FSL Directory (For Purposes of Template Selection)
"""
FSLDIR = '/usr/share/fsl/4.1/' # this should be something automatically set up, On Sharad's todo list. -Yang


"""
        Tissue Priors Directory
"""
priorDirectory = '/home2/data/Projects/Pipelines_testing/NKI_NYU_Nipype/tissuepriors' ## ask Sharad, should this be hard coded? No?

"""
3. Optional Header and Timeseries Overrides
    nVols: Number of volumes in functional timeseries (defaults to image header specification)
    TR = time of repetition (defaults to image header specification)
    startIdx : starting time point(defaults to 0)
"""
startIdx = 0
stopIdx = 255
nVols = stopIdx - startIdx + 1 # ask Sharad no edits needed for this line, better not put it together with the ones need editing...
TR = 2                # This value can be retrieve from nii data, better have a cross checking...


"""
4. Image Processing Specs
    NOTE: Specification of multiple parameters for any step indicates
          execution of a unique processing path for each parameter from 
          current step onward (e.g., fwhm = [4.5, 6]
          will produce two unique output directories, one for 4.5 spatial smoothing and one for 6mm)
"""



"""
    a) MNI Template Resolution Specification For Registration
"""
standardResolution = '2mm'
MNI = 'MNI152'
# ask Sharad are there other options for standard image, and better "change MNI to standard".

"""
    b) Spatial Filter
        Lowpass 3D Gaussian Filter Kernel Specification in mm [FSL: fslmaths]
        note: Set to [] or 0 to skip spatial filtering
            recommended values are 1.5 or 2 folds of voxel size, e.g. for 3x3x3 mm voxel, use fwhm= [6]
"""
fwhm = [6]

"""
    c) Set various thresholds for cerebral spinal fluid , white matter
    and gray matter mask generation during segmentation
"""
cerebralSpinalFluidThreshold = [0.4]
whiteMatterThreshold = [0.66]
grayMatterThreshold = [0.2]

"""
    d) Scrub data prior to derivate generation: In accord with Power et al. (2012)
       Default value True/False or a list of True/False(if need both at the same time)
"""
scrubData = [False, True]
scrubbingThreshold = [0.5]
"""
    e) Nuisance Signal Correction
"""

"""
            Select Desired Approach:
                - Global mean signal (glb)
                - Compcor:                    A component based noise correction method (CompCor)
                                           for BOLD and perfusion based fMRI
                                           Yashar Behzadia, Khaled Restoma, Joy Liaua, Thomas T. Liua, , 
                                           Science Direct: Received 18 December 2006. Revised 23 April                                                2007.
                                           Accepted 25 April 2007.
                                           Available online 3 May 2007. #ask Sharad: same citation??
                - White Matter    (WM)
                - CSF regression (CSF)
                - GRAY Matter    (GM)
                - First principal component (fpc):
                                           Extracts the  principal components found in white matter and
                                           cerebral spinal fluid.  Algorithm based on:
                                           Y. Behzadi, K. Restom, J. Liau, and T. T. Liu,
                                           component based noise correction
                                           method (CompCor) for BOLD and perfusion based fMRI.,
                                           NeuroImage, vol. 37, no. 1, pp. 90-101, Aug. 2007.
                - Motion 

"""
# Corrections for [glb, Compcor, WM, CSF, GM, FPC, Motion]
Corrections = [
                [0, 2, 3, 6],
]


"""
    f) For Compcor Use Only: Number of components to regress # usally 5 or 6.
"""
nComponents = [5]


"""
    g) For Median Angle Correction Only: Target Angle (degrees)
       Corrects the input file to a specified target angle in degrees.
       Algorithm based on:
       H. He and T. T. Liu, A geometric view of global signal confounds
       in resting-state functional MRI, NeuroImage, Sep. 2011.
"""
targetAngleDeg = [90]


"""
    h) Temporal Filtering
       Temporal Filter Specification in Hz performed after Nuisance Signal Correction
       Note: Set to [] or 0 to skip high- or low-pass filter
"""
"""
        nuisanceHighPassFilter: Turn HighPassFilter ON(value : True/1), OFF(value : False/0)
        nuisanceLowPassFilter:  Turn LowPassFilter ON(value : True/1), OFF(value : False/0)
"""
nuisanceBandpassFreq =[(0.01, 0.1)]

"""
5. Derivative Specification
"""


"""
    a) Select Derivates:
        ALFF/fALFF, SCA, vmhc, reho,
        Unit (e.g., parcellation unit, mask) Time Series Extraction, Voxel TimeSeries Extraction, Vertices Extraction

        -ALFF/fALFF :
              ALFF >> Zang, Y.F., He, Y., Zhu, C.Z., Cao, Q.J., Sui, M.Q., Liang, M., Tian, L.X., Jiang, T.Z., Wang, Y.F., 2007.
                        Altered baseline brain activity in children with ADHD
                      revealed by resting state functional MRI. Brain Dev
              fALFF >> Zou, Q.H., Zhu, C.Z., Yang, Y., Zuo, X.N., Long, X.Y., Cao, Q.J., Wang, Y.F., Zang, Y.F., 2008.
                       An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for
                       resting state fMRI

        -SCA(seed based correlation analysis):
                                       Biswal et al., (1995). doi:10.1002/mrm.1910340409

        -VMHC:
                                       Zuo, et al., (2010). doi:10.1523/JNEUROSCI.2612-10.2010

        -REHO:                           Regional homogeneity approach to fMRI data analysis, Zang 2004 NeuroImage.

        -Unit TimeSeries Extraction (tsE)
        -Vertices Extraction 
        -FSL Group Analysis (GA): http://www.fmrib.ox.ac.uk/fsl/feat5/detail.html#higher
"""
#derivatives = [f/ALFF, SCA, VMHC, ReHo, tsE, VerticesE, GA  ] 
derivatives = [True, True, True, False, False, False, False]


"""
    b) ALFF/fALFF Options
"""

"""
            For ALFF/fALFF only
                Notes: 1) This derivative is allergic to scrubbed data and thus will never use them.
                          2) You need to specify both highPassFreqALFF and lowPassFreqALFF if you intend
                            to use this derivative. The Default values are set below.
"""
highPassFreqALFF = [0.01]
lowPassFreqALFF = [0.1]



"""
    c) Seed-Based Correlation Analysis Options
"""

"""
        For SCA use only
        seedFile : specify full path to the seed list file.
    
        Each line of the seedFile contains full path to a seed.

"""
seedFile = '/home2/data/Projects/Pipelines_testing/Dickstein/settings/seed_list.txt' # yang
correlationSpace = 'mni'

"""
    d) Timeseries Extraction Options
"""

"""
            For Unit Timeseries Extraction Only
            Note: Definitions Directory should contain one subdirectory for each set of units
                    to be generated (e.g., Harvard-Oxford Atlas, AAL, Craddock, Dosenbach-160);
"""
unitDefinitionsDirectory = '/home2/ssikka/nki_nyu_pipeline/tsdata'

# Output type: .csv, numPy
unitTSOutputs = [True, True]

"""
            For Voxel Timeseries Extraction Only
            Note: Definitions Directory should contain one subdirectory for each
                    mask/mask set to be used to select voxels to be output; one output file / mask 
"""
voxelMasksDirectory = '/home2/ssikka/nki_nyu_pipeline/tsdata' #ask sharad, what is this??


# Output type: .csv, numPy
voxelTSOutputs = [True, True]

"""
            For Vertices Timeseries Extraction Only
"""
# Output type: .csv, numPy
verticesTSOutputs = [False]
runSurfaceRegistraion = False
reconSubjectsDirectory = '/home2/data/Projects/Pipelines_testing/Dickstein_CPAC_output/recon_subjects'


"""
    e) FSL Group Analysis
        Notes: 
            - Separate group analysis conducted for each derivative
            - Not applicable to time series extraction derivatives
"""
"""
        List of one or more derivatives on which the group anlaysis is be run
        As a default, some of derivatives which are generated from the pipleine have
        been specified
"""
derivativeFile = '/Users/ranjeet.khanuja/Documents/workspace/GroupAnalysis/devriverFile_list.txt'

"""
        Specify Model List File that contains one or more models to be executed per derivate
"""
modelsFile = '/Users/ranjeet.khanuja/Documents/workspace/GroupAnalysis/model_list.txt'
"""
         Templates for Group Analysis
         Design Files
         .con -> list of contrasts requested.
         .fts -> list of F-tests requested.
         .mat -> the actual values in the design matrix

         model_name in the template_list will be fetch from  modesList above
"""
matTemplateList = ['model_name']
conTemplateList = ['model_name']
ftsTemplateList = ['model_name']
grpTemplateList = ['model_name']

mat = '/Users/ranjeet.khanuja/Desktop/data2/models/%s.mat'
con = '/Users/ranjeet.khanuja/Desktop/data2/models/%s.con'
fts = '/Users/ranjeet.khanuja/Desktop/data2/models/%s.fts'
grp = '/Users/ranjeet.khanuja/Desktop/data2/models/%s.grp'

"""
        Derivative Template
        derivative in the template_list will be fetched from the derivative file
        defined above
"""
dervTemplate = sinkDirectory + '/*/%s.nii.gz'
dervTemplateList = ['derivative']

zThreshold = 2.3
pThreshold = 0.05
fTest = True