slist = os.listdir('/mnt/data001/MBAProcessingResults/PMD')
for sr in slist:
if sr.startswith('PMD17'):
brain = Brain(name=sr)
brain.save()
numSections = (len(os.listdir('/mnt/data001/MBAProcessingResults/PMD/'+sr))-1)/2
#sampleSectionNum = random.randrange(1,numSections)
errorf.write(' sample section num ' + str(sampleSectionNum) + '\n')
series_n = Series(desc=brain.name + ' Nissl Series', brain_id=brain.id, isRestricted=False, sectionThickness = 20, sectionThicknessUnit = 'mu' ,lab_id=lab_m.id, labelMethod_id = lm_n.id, imageMethod_id = im_b.id, sectioningPlane_id=sp_s.id, numQCSections = numSections)
series_n.save()
series_f = Series(desc=brain.name + ' Flourescent Series', brain_id=brain.id, isRestricted=False, sectionThickness = 20, sectionThicknessUnit = 'mu', lab_id=lab_m.id, labelMethod_id = lm_f.id, imageMethod_id = im_f.id, sectioningPlane_id=sp_s.id, numQCSections = numSections)
series_f.save()
series_ihc = Series(desc=brain.name + ' IHC Series', brain_id=brain.id, isRestricted=False, sectionThickness = 20, sectionThicknessUnit = 'mu' ,lab_id=lab_m.id, labelMethod_id = lm_ihc.id, imageMethod_id = im_b.id, sectioningPlane_id=sp_s.id, numQCSections = numSections)
series_ihc.save()
for l in limslist:
if l.name == sr:
tn = l.tracer
tracer = Tracer(name=tn)
try:
# errorf.write('Match found : ' + sr + ' - ' + tn + '\n')
slist = os.listdir('/mnt/data001/MBAProcessingResults/PMD')
for sr in slist:
if sr.startswith('PMD'):
brain = Brain(name=sr)
brain.save()
numSections = (len(os.listdir('/mnt/data001/MBAProcessingResults/PMD/'+sr))-1)/2
sampleSectionNum = random.randrange(1,numSections)
errorf.write(' sample section num ' + str(sampleSectionNum) + '\n')
series_n = Series(desc=brain.name + ' Nissl Series', brain_id=brain.id, isRestricted=False, sectionThickness = 20, sectionThicknessUnit = 'mu' ,lab_id=lab_m.id, labelMethod_id = lm_n.id, imageMethod_id = im_b.id, sectioningPlane_id=sp_s.id, numQCSections = numSections)
series_n.save()
series_f = Series(desc=brain.name + ' Flourescent Series', brain_id=brain.id, isRestricted=False, sectionThickness = 20, sectionThicknessUnit = 'mu', lab_id=lab_m.id, labelMethod_id = lm_f.id, imageMethod_id = im_f.id, sectioningPlane_id=sp_s.id, numQCSections = numSections)
series_f.save()
series_ihc = Series(desc=brain.name + ' IHC Series', brain_id=brain.id, isRestricted=False, sectionThickness = 20, sectionThicknessUnit = 'mu' ,lab_id=lab_m.id, labelMethod_id = lm_ihc.id, imageMethod_id = im_b.id, sectioningPlane_id=sp_s.id, numQCSections = numSections)
series_ihc.save()
for l in limslist:
if l.name == sr:
tn = l.tracer
tracer = Tracer(name=tn)
try:
# errorf.write('Match found : ' + sr + ' - ' + tn + '\n')
labelBOOLDict = {}
with open('/brainimg/' + brainName + '/ImageLookup.txt') as f:
for line in f:
m = re.match(r"(Section.*)\:\s+(-?\d+.\d+)\s+(N|IHC|F)", line)
section2yDict[m.group(1)] = m.group(2)
section2labelDict[m.group(1)] = m.group(3)
labelBOOLDict[m.group(3)] = 1
idSeries = -1
label2fullDict = {'N':'Nissl', 'IHC':'IHC', 'F':'Fluorescent'}
label2fieldDict = {'N':'Brightfield', 'IHC':'Brightfield', 'F':'Fluorescent'}
for label in ('N', 'IHC', 'F'):
if label in labelBOOLDict:
series = Series(desc = brain.name + ' ' + label2fullDict[label],
brain_id = brain.id, sectionThickness = 20,
lab_id = Laboratory.objects.get(name='Mitra').id,
labelMethod_id = LabelMethod.objects.get(name=label2fullDict[label]).id,
imageMethod_id = ImageMethod.objects.get(name=label2fieldDict[label]).id,
sectioningPlane_id = SectioningPlane.objects.get(desc='Coronal').id)
series.save()
if label == 'IHC' or label == 'F':
idSeries = series.id
mouse = series2limsDict[brainName]
tn = mouse.tracer
try:
tracer = Tracer(name=tn)
tracer.save()
except:
pass
try:
