コード例 #1
0
ファイル: loaddata.py プロジェクト: njakimo/webMBArepo
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')
コード例 #2
0
ファイル: loaddata.py プロジェクト: jbohland/webMBArepo
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')
コード例 #3
0
ファイル: LoadMitraBrains.py プロジェクト: njakimo/webMBArepo
	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: