def call_gengraph(fiber_fn, roi_xml_fn, roi_raw_fn, graphs, graphInvariants, graphsize, run = False):
'''
Run graph building and other related scripts
@param fiber_fn: fiber tract file
@param roi_xml_fn: region of interest xml file
@param roi_raw_fn: region of interest raw file
@param graphs: Dir where biggraphs & smallgraphs are saved
@param graphInvariants: Dir where graph invariants are saved
@param graphsize: the size of the graph 'big' or 'small'
@param run: Whether or not to run processor intensive jobs. Default is - false so nothing is actually run
'''
baseName = getFiberID(fiber_fn) #VERY TEMPORARY
Gfn = os.path.join(graphs, baseName) # partial name
if (run):
if graphsize.lower().startswith("s"):
print("Running Small gengraph ...")
Gfn+="smgr.graphml"
# Note: Some included atlases are present
gengraph.genGraph(fiber_fn, Gfn, roi_xml_fn, roi_raw_fn, bigGraph=False, **settings.ATLASES)
elif graphsize.lower().startswith("b"):
print("\nRunning Big gengraph ...")
Gfn+="bggr.graphml"
gengraph.genGraph(fiber_fn, Gfn, roi_xml_fn, roi_raw_fn, bigGraph=True, **settings.ATLASES)
else:
print '[ERROR]: Graphsize Unkwown' # should never happen
return Gfn
def rungenGraph():
global inputRoi_raw
global inputRoi_xml
global inputFiber_dat
out = "/Users/dmhembere44/Desktop/genGraphOut.mat"
gengraph.genGraph(inputFiber_dat, out)
def process_input_data(derivatives, graph_loc, graphsize, invariants, proj_dir,
to_email):
'''
Extract File name & determine what file corresponds to what for gengraph
@param session: the session dictionary object
'''
"""
if isinstance(session, str) or isinstance(session, unicode):
f = open(session, "rb")
session = pickle.load(f)
f.close()
"""
filesInUploadDir = os.listdir(derivatives)
fiber_fn, data_atlas_fn = checkFileExtGengraph(
filesInUploadDir) # Check & sort files
''' Fully qualify file names '''
fiber_fn = os.path.join(derivatives, fiber_fn)
if not data_atlas_fn:
data_atlas_fn = settings.ATLASES.keys()[0]
else:
data_atlas_fn = os.path.join(derivatives, data_atlas_fn)
print "data_atlas_fn %s ..." % data_atlas_fn
Gfn = os.path.join(graph_loc, getFiberID(fiber_fn)) # partial name
if (graphsize).lower().startswith("s"):
Gfn += "smgr.graphml"
graphsize = False # False is small graph
elif graphsize.lower().startswith("b"):
Gfn += "bggr.graphml"
graphsize = True # True is big graph
else:
print '[ERROR]: Graphsize Unkwown' # should never happen
try:
genGraph(fiber_fn, data_atlas_fn, Gfn, graphsize,
**settings.ATLASES) # FIXME: numfibers = 20000 for tests
except:
msg = "Hello,\n\nYour most recent job failed either because your fiber streamline file or ROI mask was incorrectly formatted."
msg += " Please check both and try again.\n\n"
sendJobFailureEmail(to_email, msg)
return 911
# Run ivariants here
if len(invariants) > 0:
print "Computing invariants {0}".format(invariants)
invariant_fns = run_invariants(invariants, Gfn, graph_loc)
dwnld_loc = get_download_path(proj_dir)
sendJobCompleteEmail(to_email, dwnld_loc)
def process_input_data(derivatives, graph_loc, graphsize, invariants,
proj_dir, to_email):
'''
Extract File name & determine what file corresponds to what for gengraph
@param session: the session dictionary object
'''
"""
if isinstance(session, str) or isinstance(session, unicode):
f = open(session, "rb")
session = pickle.load(f)
f.close()
"""
filesInUploadDir = os.listdir(derivatives)
fiber_fn, data_atlas_fn = checkFileExtGengraph(filesInUploadDir) # Check & sort files
''' Fully qualify file names '''
fiber_fn = os.path.join(derivatives, fiber_fn)
if not data_atlas_fn:
data_atlas_fn = settings.ATLASES.keys()[0]
else:
data_atlas_fn = os.path.join(derivatives, data_atlas_fn)
print "data_atlas_fn %s ..." % data_atlas_fn
Gfn = os.path.join(graph_loc, getFiberID(fiber_fn)) # partial name
if (graphsize).lower().startswith("s"):
Gfn += "smgr.graphml"
graphsize = False # False is small graph
elif graphsize.lower().startswith("b"):
Gfn+="bggr.graphml"
graphsize = True # True is big graph
else: print '[ERROR]: Graphsize Unkwown' # should never happen
try:
genGraph(fiber_fn, data_atlas_fn, Gfn, graphsize, **settings.ATLASES) # FIXME: numfibers = 20000 for tests
except:
msg = "Hello,\n\nYour most recent job failed either because your fiber streamline file or ROI mask was incorrectly formatted."
msg += " Please check both and try again.\n\n"
sendJobFailureEmail(to_email, msg)
return 911
# Run ivariants here
if len(invariants) > 0:
print "Computing invariants {0}".format(invariants)
invariant_fns = run_invariants(invariants, Gfn, graph_loc)
dwnld_loc = get_download_path(proj_dir)
sendJobCompleteEmail(to_email, dwnld_loc)
def processData(fiber_fn,
roi_xml_fn,
roi_raw_fn,
graphs,
graphInvariants,
graphsize,
run=False):
'''
Run graph building and other related scripts
@param fiber_fn: fiber tract file
@param roi_xml_fn: region of interest xml file
@param roi_raw_fn: region of interest raw file
@param graphs: Dir where biggraphs & smallgraphs are saved
@param graphInvariants: Dir where graph invariants are saved
@param graphsize: the size of the graph 'big' or 'small'
@param run: Whether or not to run processor intensive jobs. Default is - false so nothing is actually run
'''
if (run):
import mrcap.svd as svd
import mrcap.lcc as lcc
print "Imported svd and lcc modules..."
baseName = getFiberID(fiber_fn) #VERY TEMPORARY
smGrfn = os.path.join(graphs, (baseName + 'smgr.mat'))
bgGrfn = os.path.join(graphs, (baseName + 'bggr.mat'))
if (run):
if (graphsize == 'small'):
''' Run gengraph SMALL & save output '''
print("Running Small gengraph....")
gengraph.genGraph(fiber_fn,
smGrfn,
roi_xml_fn,
roi_raw_fn,
bigGraph=False)
elif (graphsize == 'big'):
''' Run gengrah BIG & save output '''
print("\nRunning Big gengraph....")
gengraph.genGraph(fiber_fn,
bgGrfn,
roi_xml_fn,
roi_raw_fn,
bigGraph=True)
else:
print '[ERROR]: Graphsize Unkwown' # should never happen
''' Run LCC '''
lccfn = os.path.join(graphInvariants, "LCC", (baseName + 'concomp.npy'))
if (run):
'''Should be big but we'll do small for now'''
if (graphsize == 'big'):
print "Running biggraph Largest connected component..."
lcc.process_single_brain(bgGrfn, lccfn)
if (graphsize == 'small'):
print "Running smallgraph Largest connected component..."
lcc.process_single_brain(smGrfn, lccfn)
''' Run Embed - SVD '''
SVDfn = os.path.join(graphInvariants, "SVD", (baseName + 'embed.npy'))
print("Running SVD....")
if (run):
if (graphsize == 'big'):
print "Running SVD on biggraph"
svd.embed_graph(lccfn, bgGrfn, SVDfn)
if (graphsize == 'small'):
print "Running SVD on smallgraph"
svd.embed_graph(lccfn, smGrfn, SVDfn)
print "Completed generating - graph, lcc & svd"
return [smGrfn, bgGrfn, lccfn, SVDfn]
def processData(fiber_fn, roi_xml_fn, roi_raw_fn,graphs, graphInvariants, graphsize, run = False):
'''
Run graph building and other related scripts
@param fiber_fn: fiber tract file
@param roi_xml_fn: region of interest xml file
@param roi_raw_fn: region of interest raw file
@param graphs: Dir where biggraphs & smallgraphs are saved
@param graphInvariants: Dir where graph invariants are saved
@param graphsize: the size of the graph 'big' or 'small'
@param run: Whether or not to run processor intensive jobs. Default is - false so nothing is actually run
'''
if (run):
import mrcap.svd as svd
import mrcap.lcc as lcc
print "Imported svd and lcc modules..."
baseName = getFiberID(fiber_fn) #VERY TEMPORARY
smGrfn = os.path.join(graphs, (baseName +'smgr.mat'))
bgGrfn = os.path.join(graphs, (baseName +'bggr.mat'))
if (run):
if (graphsize == 'small'):
''' Run gengraph SMALL & save output '''
print("Running Small gengraph....")
gengraph.genGraph(fiber_fn, smGrfn, roi_xml_fn, roi_raw_fn, bigGraph=False)
elif(graphsize == 'big'):
''' Run gengrah BIG & save output '''
print("\nRunning Big gengraph....")
gengraph.genGraph(fiber_fn, bgGrfn, roi_xml_fn, roi_raw_fn, bigGraph=True)
else:
print '[ERROR]: Graphsize Unkwown' # should never happen
''' Run LCC '''
lccfn = os.path.join(graphInvariants,"LCC", (baseName + 'concomp.npy'))
if (run):
'''Should be big but we'll do small for now'''
if (graphsize == 'big'):
print "Running biggraph Largest connected component..."
lcc.process_single_brain(bgGrfn, lccfn)
if (graphsize == 'small'):
print "Running smallgraph Largest connected component..."
lcc.process_single_brain(smGrfn, lccfn)
''' Run Embed - SVD '''
SVDfn = os.path.join(graphInvariants,"SVD" ,(baseName + 'embed.npy'))
print("Running SVD....")
if (run):
if (graphsize == 'big'):
print "Running SVD on biggraph"
svd.embed_graph(lccfn, bgGrfn, SVDfn)
if (graphsize == 'small'):
print "Running SVD on smallgraph"
svd.embed_graph(lccfn, smGrfn, SVDfn)
print "Completed generating - graph, lcc & svd"
return [ smGrfn, bgGrfn, lccfn, SVDfn ]
