def calculate_area_totals(subject, registrationFolder, ccfSlice, nSliceGroups=1):
slices = sorted(ccfSlice.keys())
sliceGroups = []
for sgInd in range(nSliceGroups):
sliceGroups.append(slices[sgInd::nSliceGroups])
groupSliceCount = []
for sgInd, slices in enumerate(sliceGroups):
allAreaNames = []
allSliceCounts = []
allSliceTotalVoxels = []
for sliceName in slices:
ccfZ = ccfSlice[sliceName]
filenameSVGPost = os.path.join(settings.HISTOLOGY_PATH, subject, registrationFolder, '{}.svg'.format(sliceName))
(scale, translate, affine) = ha.get_svg_transform(filenameSVGPost, sliceSize=[1388, 1040])
filenameCSV = os.path.join(settings.HISTOLOGY_PATH, subject, registrationFolder, '{}.csv'.format(sliceName))
coords = ha.get_coords_from_fiji_csv(filenameCSV, pixelSize=pixelSizes[subject])
newCoords = ha.apply_svg_transform(scale, translate, affine, coords)
structIDs = []
for indCoords in range(np.shape(newCoords)[1]):
x = newCoords[0,indCoords]
y = newCoords[1,indCoords]
thisCoordID = rspAnnotationVolumeRotated[int(x), int(y), ccfZ]
structIDs.append(thisCoordID)
# structIDs = annotationVolume.get_structure_id_many_xy(newCoords, ccfSlice[sliceNum])
# structNames = [annotationVolume.get_structure_from_id(structID) for structID in structIDs]
structDicts = rsp.structure_tree.get_structures_by_id(structIDs)
structNames = [d['name'] for d in structDicts]
structCounts = Counter(structNames)
allSliceCounts.append(structCounts)
totalVoxels = annotationVolume.get_total_voxels_per_area(ccfZ)
totalVoxels = Counter(totalVoxels)
allSliceTotalVoxels.append(totalVoxels)
sliceCountSum = reduce(operator.add, allSliceCounts)
sliceTotalVoxelsSum = reduce(operator.add, allSliceTotalVoxels)
groupSliceCount.append(sliceCountSum)
allAreaNames.extend(sliceCountSum.keys())
#Compress into one dict with lists for each key
uniqueAreaNames = set(allAreaNames)
allAreasResults = {}
for areaName in uniqueAreaNames:
areaCounts = []
for sliceCountSum in groupSliceCount:
areaCounts.append(sliceCountSum.get(areaName, 0))
allAreasResults.update({areaName:areaCounts})
return allAreasResults
from jaratoolbox import histologyanalysis as ha
reload(ha)
CREATE_SVG = 0
# -- Create SVG file with images --
if CREATE_SVG:
filenameAtlas = '/var/tmp/examplesRegistration/atlas.jpg'
filenameSlice = '/var/tmp/examplesRegistration/slice.jpg'
filenameSVG = '/tmp/testfile.svg'
(atlasSize, sliceSize) = ha.save_svg_for_registration(filenameSVG, filenameAtlas, filenameSlice)
sys.exit()
# -- Transform coords --
filenameSVG = '/var/tmp/examplesRegistration/test03.svg'
(scale, translate, affine) = ha.get_svg_transform(filenameSVG)
filenameCSV = '/var/tmp/examplesRegistration/sliceCoords.csv'
coords = ha.get_coords_from_fiji_csv(filenameCSV)
newCoords = ha.apply_svg_transform(scale, translate, affine, coords)
print newCoords.T
filenameAtlas = '/var/tmp/examplesRegistration/atlas.jpg'
atlasIm = mpimg.imread(filenameAtlas)
plt.clf()
plt.imshow(atlasIm,cmap='gray')
plt.plot(newCoords[0,:],newCoords[1,:],'o',mec='r',mfc='none')
plt.axis('image')
plt.show()
'{}tl.jpg'.format(sliceNum))
filenameSVG = os.path.join(HISTOLOGY_DIR, subject, registrationFolder,
'{}_pre.svg'.format(sliceNum))
(atlasSize,
sliceSize) = ha.save_svg_for_registration(filenameSVG, filenameAtlas,
filenameSlice)
#Read coords, apply transform, output counts per area
elif CASE == 1:
annotationVolume = ha.AllenAnnotation()
allSliceCounts = []
for sliceNum in slices:
filenameSVGPost = '/mnt/jarahubdata/jarashare/histology/{}/{}/{}.svg'.format(
subject, registrationFolder, sliceNum)
(scale, translate,
affine) = ha.get_svg_transform(filenameSVGPost,
sliceSize=[1388, 1040])
filenameCSV = '/mnt/jarahubdata/jarashare/histology/{}/{}/{}.csv'.format(
subject, registrationFolder, sliceNum)
coords = ha.get_coords_from_fiji_csv(filenameCSV, pixelSize=4.0048)
newCoords = ha.apply_svg_transform(scale, translate, affine, coords)
structIDs = annotationVolume.get_structure_id_many_xy(
newCoords, ccfSlice[sliceNum])
structNames = [
annotationVolume.get_structure_from_id(structID)
for structID in structIDs
]
structCounts = Counter(structNames)
allSliceCounts.append(structCounts)
resultCounts = counter_values(allSliceCounts)
# -- Create SVG file with images --
if CREATE_SVG:
filenameAtlas = '/var/tmp/examplesRegistration/atlas.jpg'
filenameSlice = '/var/tmp/examplesRegistration/slice.jpg'
filenameSVG = '/tmp/testfile.svg'
(atlasSize,
sliceSize) = ha.save_svg_for_registration(filenameSVG, filenameAtlas,
filenameSlice)
sys.exit()
'''Transform coordinates from CSV cell count file to Allen CCF.'''
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from jaratoolbox import histologyanalysis as ha
filenameSVG = '/mnt/jarahubdata/jarashare/histology/anat038/registrationAC/p1d1.svg'
(scale, translate, affine) = ha.get_svg_transform(filenameSVG,
sliceSize=[1388, 1040])
filenameCSV = '/mnt/jarahubdata/jarashare/histology/anat038/registrationAC/p1d1.csv'
coords = ha.get_coords_from_fiji_csv(filenameCSV, pixelSize=4.0048)
newCoords = ha.apply_svg_transform(scale, translate, affine, coords)
print newCoords.T
filenameAtlas = '/mnt/jarahubdata/atlas/AllenCCF_25/JPEG/allenCCF_Z193.jpg'
atlasIm = mpimg.imread(filenameAtlas)
plt.clf()
plt.imshow(atlasIm, cmap='gray')
plt.plot(newCoords[0, :], newCoords[1, :], 'o', mec='r', mfc=[0, 1, 0], ms=3)
plt.axis('image')
plt.show()