def loadLabels(self, fname):
"""
Load the labels file, which may be in JSON or CSV format
The csv file should have the following format
index,parent_index,data1,data1,dataN\n
The first line should be a header line. Suggested separators: | or ,
Header must include at least the name of the area. So we can get, e.g.
'name': 'Entorhinal area, lateral part, layer 2'
The JSON should be the raw JSON from the ARA website
Returns the labels as a tree structure that can be indexed by ID
"""
if fname.lower().endswith('.csv'):
colSep = self.guessFileSep(fname)
return tree.importData(fname, colSep=colSep, headerLine=True)
if fname.lower().endswith('.json'):
(flattened, colNames) = ara_json.importData(fname)
return tree.importData(flattened.split('\n'),
colSep='|',
headerLine=colNames)
quiet = args.q
if fname is None:
print "Please supply a file name to convert. e.g.:\nexportedGoggleTree2LasagnaLines.py -f myFile.csv\n"
sys.exit(0)
#Get the data out of the tree
if os.path.exists(fname) == False:
print 'Can not find ' + fname
sys.exit(0)
dataTree = importData(fname,headerLine=['id','parent','z','x','y'])
#Get the unique segments of each tree
paths=[]
for thisSegment in dataTree.findSegments():
paths.append(thisSegment)
def dataFromPath(tree,path):
"""
Get the data from the tree given a path.
"""
x=[]
y=[]
z=[]
for thisNode in path:
quiet = args.q
if fname is None:
print("Please supply a file name to convert. e.g.:\nexportedGoggleTree2LasagnaLines.py -f myFile.csv\n")
sys.exit(0)
#Get the data out of the tree
if os.path.exists(fname) == False:
print('Can not find ' + fname)
sys.exit(0)
dataTree = importData(fname,headerLine=['id','parent','z','x','y'])
#Get the unique segments of each tree
paths=[]
for thisSegment in dataTree.findSegments():
paths.append(thisSegment)
def dataFromPath(tree,path):
"""
Get the data from the tree given a path.
"""
x=[]
y=[]
z=[]
for thisNode in path:
def showLoadDialog(self,fname=None):
"""
This slot brings up the load dialog and retrieves the file name.
NOTE:
If a filename is provided then this is loaded and no dialog is brought up.
If the file name is valid, it loads the base stack using the load method.
"""
verbose = False
if fname is None or not fname:
fname = self.lasagna.showFileLoadDialog(fileFilter="Text Files (*.txt *.csv)")
if fname is None or not fname:
return
if os.path.isfile(fname):
with open(str(fname),'r') as fid:
#import the tree
if verbose:
print "tree_reader_plugin.showLoadDialog - importing %s" % fname
dataTree = importData(fname,headerLine=['id','parent','z','x','y'],verbose=verbose)
if not dataTree:
print "No data loaded from %s" % fname
return
#We now have an array of unique paths (segments)
paths=[]
for thisSegment in dataTree.findSegments():
paths.append(thisSegment)
ii=0
asList=[] #list of list data (one item per node)
for thisPath in paths:
data = self.dataFromPath(dataTree,thisPath)
for jj in range(len(data[0])):
tmp = [ii,data[0][jj],data[1][jj],data[2][jj]]
tmp = [float(x) for x in tmp] #convert to floats
asList.append(tmp)
ii += 1
# add nans between lineseries
data=[]
lastLineSeries=None
n=0
for ii in range(len(asList)):
if len(asList[ii])==0:
continue
thisLine = asList[ii]
if lastLineSeries is None:
lastLineSeries=thisLine[0]
if lastLineSeries != thisLine[0]:
n+=1
data.append([np.nan, np.nan, np.nan])
lastLineSeries=thisLine[0]
data.append(thisLine[1:])
if verbose:
print "Divided tree into %d segments" % n
#print data
objName=fname.split(os.path.sep)[-1]
self.lasagna.addIngredient(objectName=objName,
kind=self.kind,
data=np.asarray(data),
fname=fname,
)
self.lasagna.returnIngredientByName(objName).addToPlots() #Add item to all three 2D plots
self.lasagna.initialiseAxes()
else:
self.lasagna.statusBar.showMessage("Unable to find " + str(fname))
atlas_id=obj[u'atlas_id'],
acronym=obj[u'acronym'],
name=obj[u'name'],
color=obj[u'color_hex_triplet'])
for child in obj.get('children', []):
flattened = tree_flatten(child, flattened=flattened)
return flattened
#----------------------------------------------------------------------------
if __name__ == '__main__':
if len(sys.argv) > 1:
fname = sys.argv[1]
(flattened, colNames) = importData(fname)
returnTree = True
#Optionally run flattened structure through tree
if returnTree:
import tree
tree.importData(flattened.split('\n'),
colSep='|',
displayTree=True,
headerLine=colNames)
else:
print flattened