コード例 #1
0
ファイル: gengraph.py プロジェクト: amondal2/MR-connectome
def genGraph(infname, outfname, roixmlname = None, roirawname = None, bigGraph = False , numfibers=0): # Edit
  """
  infname - file name of _fiber.dat file
  outfname - Dir+fileName of output .mat file 
  roixmlname - file name of _roi.xml file
  roirawname - file name of _roi.raw file
  bigGraph - boolean True or False on whether to process a bigraph=True or smallgraph=False
  numfibers - the number of fibers
  """
  
  """Generate a sparse graph from an MRI studio file and write it as a Matlab file"""
  
  # Disa Edit - Determine size of graph to be processed i.e pick a fibergraph module to import
  if bigGraph:
    from fibergraph import FiberGraph
  else:
    from fibergraph_sm import FiberGraph 

  # Disa Edit - if these filenames are undefined then,
  # assume that there are ROI files in ../roi
  
  if not(roixmlname and roirawname):
    [ inpathname, inbasename ] = os.path.split ( infname )
    inbasename = str(inbasename).rpartition ( "_" )[0]
    roifp = os.path.normpath ( inpathname + '/../roi/' + inbasename )
    roixmlname = roifp + '_roi.xml'
    roirawname = roifp + '_roi.raw'
  
#  # Assume that there are mask files in ../mask
#  maskfp = os.path.normpath ( inpathname + '/../mask/' + inbasename )
#  maskxmlname = maskfp + '_mask.xml'
#  maskrawname = maskfp + '_mask.raw'

  # Get the ROIs
  
  try:
    roix = roi.ROIXML( roixmlname ) # Create object of type ROIXML
    rois = roi.ROIData ( roirawname, roix.getShape() )
  except:
    print "ROI files not found at: ", roixmlname, roirawname
    sys.exit (-1)

  # Get the mask
#  try:
#    maskx = mask.MaskXML( maskxmlname )
#    masks = mask.MaskData ( maskrawname, maskx.getShape() )
#  except:
#    print "Mask files not found at: ", maskxmlname, maskrawname
#    sys.exit (-1)

  # Create fiber reader
  reader = FiberReader( infname )

  # Create the graph object
  # get dims from reader
# fbrgraph = FiberGraph ( reader.shape, rois, masks )
  fbrgraph = FiberGraph ( reader.shape, rois, None )

  print "Parsing MRI studio file {0}".format ( infname )

  # Print the high-level fiber information
  print(reader)

  count = 0
  
  # iterate over all fibers
  for fiber in reader:
    count += 1
    # add the contribution of this fiber to the 
    fbrgraph.add(fiber)
    if numfibers > 0 and count >= numfibers:
      break
    if count % 10000 == 0:
      print ("Processed {0} fibers".format(count) )

  print "Deleting the reader"
  
  del reader

  print "Completing the graph"
  # Done adding edges
  fbrgraph.complete()

  print "Saving matlab file"
  # Save a version of this graph to file
  fbrgraph.saveToMatlab ( "fibergraph", outfname )

  # Load a version of this graph from  
#  fbrgraph.loadFromMatlab ( "fibergraph", outfname )

  del fbrgraph
  return
コード例 #2
0
def genGraph(infname,
             outfname,
             roixmlname=None,
             roirawname=None,
             bigGraph=False,
             numfibers=0):  # Edit
    """
  infname - file name of _fiber.dat file
  outfname - Dir+fileName of output .mat file 
  roixmlname - file name of _roi.xml file
  roirawname - file name of _roi.raw file
  bigGraph - boolean True or False on whether to process a bigraph=True or smallgraph=False
  numfibers - the number of fibers
  """
    """Generate a sparse graph from an MRI studio file and write it as a Matlab file"""

    # Disa Edit - Determine size of graph to be processed i.e pick a fibergraph module to import
    if bigGraph:
        from fibergraph import FiberGraph
    else:
        from fibergraph_sm import FiberGraph

    # Disa Edit - if these filenames are undefined then,
    # assume that there are ROI files in ../roi

    if not (roixmlname and roirawname):
        [inpathname, inbasename] = os.path.split(infname)
        inbasename = str(inbasename).rpartition("_")[0]
        roifp = os.path.normpath(inpathname + '/../roi/' + inbasename)
        roixmlname = roifp + '_roi.xml'
        roirawname = roifp + '_roi.raw'

#  # Assume that there are mask files in ../mask
#  maskfp = os.path.normpath ( inpathname + '/../mask/' + inbasename )
#  maskxmlname = maskfp + '_mask.xml'
#  maskrawname = maskfp + '_mask.raw'

# Get the ROIs

    try:
        roix = roi.ROIXML(roixmlname)  # Create object of type ROIXML
        rois = roi.ROIData(roirawname, roix.getShape())
    except:
        print "ROI files not found at: ", roixmlname, roirawname
        sys.exit(-1)

    # Get the mask


#  try:
#    maskx = mask.MaskXML( maskxmlname )
#    masks = mask.MaskData ( maskrawname, maskx.getShape() )
#  except:
#    print "Mask files not found at: ", maskxmlname, maskrawname
#    sys.exit (-1)

# Create fiber reader
    reader = FiberReader(infname)

    # Create the graph object
    # get dims from reader
    # fbrgraph = FiberGraph ( reader.shape, rois, masks )
    fbrgraph = FiberGraph(reader.shape, rois, None)

    print "Parsing MRI studio file {0}".format(infname)

    # Print the high-level fiber information
    print(reader)

    count = 0

    # iterate over all fibers
    for fiber in reader:
        count += 1
        # add the contribution of this fiber to the
        fbrgraph.add(fiber)
        if numfibers > 0 and count >= numfibers:
            break
        if count % 10000 == 0:
            print("Processed {0} fibers".format(count))

    print "Deleting the reader"

    del reader

    print "Completing the graph"
    # Done adding edges
    fbrgraph.complete()

    print "Saving matlab file"
    # Save a version of this graph to file
    fbrgraph.saveToMatlab("fibergraph", outfname)

    # Load a version of this graph from
    #  fbrgraph.loadFromMatlab ( "fibergraph", outfname )

    del fbrgraph
    return
コード例 #3
0
ファイル: gengraph.py プロジェクト: RanjitK/MR-connectome
def genGraph( infname, outfname, numfibers=0 ):
  """Generate a sparse graph from an MRI studio file and write it as a Matlab file"""

  # Assume that there are ROI files in ../roi
  [ inpathname, inbasename ] = os.path.split ( infname )
  inbasename = str(inbasename).rpartition ( "_" )[0]
  roifp = os.path.normpath ( inpathname + '/../roi/' + inbasename )
  roixmlname = roifp + '_roi.xml'
  roirawname = roifp + '_roi.raw'

#  # Assume that there are mask files in ../mask
#  maskfp = os.path.normpath ( inpathname + '/../mask/' + inbasename )
#  maskxmlname = maskfp + '_mask.xml'
#  maskrawname = maskfp + '_mask.raw'


  # Get the ROIs
  try:
    roix = roi.ROIXML( roixmlname )
    rois = roi.ROIData ( roirawname, roix.getShape() )
  except:
    print "ROI files not found at: ", roixmlname, roirawname
    sys.exit (-1)

  # Get the mask
#  try:
#    maskx = mask.MaskXML( maskxmlname )
#    masks = mask.MaskData ( maskrawname, maskx.getShape() )
#  except:
#    print "Mask files not found at: ", maskxmlname, maskrawname
#    sys.exit (-1)

  # Create fiber reader
  reader = FiberReader( infname )

  # Create the graph object
  # get dims from reader
#  fbrgraph = FiberGraph ( reader.shape, rois, masks )
  fbrgraph = FiberGraph ( reader.shape, rois, None )

  print "Parsing MRI studio file {0}".format ( infname )

  # Print the high-level fiber information
  print(reader)

  count = 0

  # iterate over all fibers
  for fiber in reader:
    count += 1
    # add the contribution of this fiber to the 
    fbrgraph.add(fiber)
    if numfibers > 0 and count >= numfibers:
      break
    if count % 10000 == 0:
      print ("Processed {0} fibers".format(count) )

  print "Deleting the reader"

  del reader

  print "Completing the graph"
  # Done adding edges
  fbrgraph.complete()

  print "Saving matlab file"
  # Save a version of this graph to file
  fbrgraph.saveToMatlab ( "fibergraph", outfname )

  # Load a version of this graph from  
#  fbrgraph.loadFromMatlab ( "fibergraph", outfname )

  del fbrgraph
  
  return