from scipy import io
import cPickle as pickle
import os.path
import sys
if os.path.exists('/home/onerva/consistency-as-onion'):
sys.path.insert(0,'/home/onerva/consistency-as-onion')
else:
sys.path.insert(0,'/home/onerva/projects/consistency-as-onion')
import functions
import onion_parameters as params
allVoxelTsPath = params.testSubjectFolders[0] + params.ROIVoxelTsFileName
ROIInfoFile = params.ROIInfoFile
allVoxelTs = io.loadmat(allVoxelTsPath)['roi_voxel_data'][0]['roi_voxel_ts'][0]
_,_,voxelCoordinates,ROIMaps = functions.readROICentroids(ROIInfoFile,readVoxels=True,fixCentroids=True)
ROIIndices = []
for ROIMap in ROIMaps:
indices = np.zeros(len(ROIMap),dtype=int)
for i, voxel in enumerate(ROIMap):
indices[i] = np.where((voxelCoordinates == voxel).all(axis=1)==1)[0][0]
ROIIndices.append(indices)
testROIs = ROIIndices[0:20]
spatialConsistencies = functions.calculateSpatialConsistencyInParallel(testROIs,allVoxelTs)
if not visualizeOnly:
subjectFolders = [
'/media/onerva/KINGSTON/test-data/010/',
'/media/onerva/KINGSTON/test-data/011/'
]
nSubjects = len(subjectFolders)
roiInfoFile = '/media/onerva/KINGSTON/test-data/group_roi_mask-30-4mm_with_subcortl_and_cerebellum.mat'
resolution = 4
distanceMatrixPath = params.distanceMatrixPath
radiusRange = np.arange(1, 10, 2)
nRadia = len(radiusRange)
_, _, voxelCoords, _ = functions.readROICentroids(
roiInfoFile, readVoxels=True
) # this returns the coordinates of all voxels belonging to ROIs
nROIs = len(voxelCoords)
correlations = np.zeros((nSubjects, nRadia, nROIs))
allVoxelTs = []
for i, subject in enumerate(
subjectFolders
): # reading the data here and not inside the loop to save time
voxelTsFilePath = subject + params.ROIVoxelTsFileName
allVoxelTs.append(
io.loadmat(voxelTsFilePath)['roi_voxel_data'][0]['roi_voxel_ts']
[0])
for j, radius in enumerate(radiusRange):
"""
import functions
import numpy as np
testDefSphericalROIs = False
testFindROIlessVoxels = False
testFindROIlessNeighbors = False
testUpdateROI = False
testGrowROIs = False
testConstructMultilayer = True
# testing defSphericalROIs
if testDefSphericalROIs:
ROIPath = 'atlases/brainnetome/brainnetome_thr25_4mm_rois.mat'
centroids, _, voxelCoords = functions.readROICentroids(ROIPath,
readVoxels=True)
# testcase 1: ROIs with radius < 1 should contain only ROI centroids
spheres = functions.defineSphericalROIs(centroids, voxelCoords, 0)
sphereMaps = []
for sphereMap in spheres['ROIMaps']:
sphereMaps.append(sphereMap)
sphereMaps = np.array(sphereMaps)
diff = np.sum(np.abs(sphereMaps - centroids))
if diff == 0:
print "defSphericalROIs: testcase 1/3 OK"
# testcase 2: small example space
space = np.zeros((4, 4, 4))
subjects = [params.testSubjectFolders[0]]
originalROIInfoPath = params.originalROIInfoFile
optimizedROIInfoFile = params.optimizedROIInfoFile
allVoxelTsFile = params.ROIVoxelTsFileName
optimizedConsistencySaveName = params.optimizedSpatialConsistencySaveName
originalConsistencySavePath = params.originalSpatialConsistencySavePath
optimizedCorrelationSaveName = params.optimizedCorrelationSaveName
originalCorrelationSavePath = params.originalCorrelationSavePath
figureSavePath = params.spatialConsistencyValidationPath
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
originalCentroids, _, originalVoxelCoordinates, originalROIMaps = functions.readROICentroids(
originalROIInfoPath, readVoxels=True, fixCentroids=True)
centroidIndices = np.zeros(len(originalCentroids), dtype=int)
for i, originalCentroid in enumerate(originalCentroids):
centroidIndices[i] = np.where(
(originalVoxelCoordinates == originalCentroid).all(axis=1) == 1)[0][0]
for i, subject in enumerate(subjects):
optimizedROIInfoPath = subject + optimizedROIInfoFile
allVoxelTsPath = subject + allVoxelTsFile
allVoxelTs = io.loadmat(
allVoxelTsPath)['roi_voxel_data'][0]['roi_voxel_ts'][0]
_, _, _, ROIMaps = functions.readROICentroids(optimizedROIInfoPath,
readVoxels=True)
ROIIndices = []
visualizeOnly = False
consistencySavePath = params.consistencyVsRadiusPath
figureSavePath = '/media/onerva/KINGSTON/test-data/outcome/consistency-vs-radius.pdf'
if not visualizeOnly:
subjectFolders = params.testSubjectFolders
nSubjects = len(subjectFolders)
roiInfoFile = '/media/onerva/KINGSTON/test-data/group_roi_mask-30-4mm_with_subcortl_and_cerebellum.mat'
resolution = 4
distanceMatrixPath = params.distanceMatrixPath
radiusRange = np.arange(1, 20, 2)
nRadia = len(radiusRange)
centroids, _, voxelCoords, _ = functions.readROICentroids(roiInfoFile,
readVoxels=True)
nROIs = len(centroids)
consistencies = np.zeros((nSubjects, nRadia, nROIs))
allVoxelTs = []
for i, subject in enumerate(
subjectFolders
): # reading the data here and not inside the loop to save time
voxelTsFilePath = subject + params.ROIVoxelTsFileName
allVoxelTs.append(
io.loadmat(voxelTsFilePath)['roi_voxel_data'][0]['roi_voxel_ts']
[0])
for j, radius in enumerate(radiusRange):