def extractDeformations(log, WorkingDir):
MD = MetaData(os.path.join(WorkingDir, "images.xmd"))
deformations = MD.getColumnValues(MDL_NMA)
fnDef = os.path.join(WorkingDir, "extra/deformations.txt")
fhDef = open(fnDef, "w")
for deformation in deformations:
for coef in deformation:
fhDef.write("%f " % coef)
fhDef.write("\n")
fhDef.close()
def computeCutoff(WorkingDir, fnHist, RcPercentage):
MDhist=MetaData(fnHist)
distances=MDhist.getColumnValues(MDL_X)
distanceCount=MDhist.getColumnValues(MDL_COUNT)
# compute total number of distances
Ncounts=0
for count in distanceCount:
Ncounts+=count
# Compute threshold
NcountThreshold=Ncounts*RcPercentage/100.0
Ncounts=0
for i in range(len(distanceCount)):
Ncounts+=distanceCount[i]
if Ncounts>NcountThreshold:
Rc=distances[i]
break
print("Cut-off distance="+str(Rc)+" A")
fhWarning=open(os.path.join(WorkingDir,"warnings.xmd"),'w')
fhWarning.write("Cut-off distance="+str(Rc)+" A\n")
fhWarning.close()
return Rc
def coocurenceMatrix(log,RemainingClasses,WorkingDirStructure,NumVolumes,nI,CorePercentile,CorrThresh):
import numpy
mdRemaining = MetaData(RemainingClasses)
Nimgs=mdRemaining.size()
allNames=mdRemaining.getColumnValues(MDL_IMAGE)
matrixTotal = numpy.zeros([Nimgs,Nimgs])
for n in range(NumVolumes):
fnBase='proposedVolume%05d'%n
fnRoot=os.path.join(WorkingDirStructure,fnBase)
md = MetaData(fnRoot+".xmd")
size = md.size()
num=[]
corr=[]
for objId in md:
name = md.getValue(MDL_IMAGE, objId)
if name in allNames:
num.append(allNames.index(name))
corr.append(md.getValue(MDL_MAXCC, objId))
else:
print "Cannot find ",name
if size!=len(num):
print "Error when processing: ",fnRoot+".xmd"
aaa
matrix = numpy.zeros([Nimgs,Nimgs])
for i in range(size):
for j in range(size):
matrix[num[i],num[j]]=((corr[i]+corr[j])/2)
#numpy.savetxt(os.path.join(WorkingDirStructure,'coocurrenceMatrix_%05d.txt'%n), matrix)
matrixTotal=matrixTotal+matrix
matrixTotal=matrixTotal/NumVolumes
numpy.savetxt(os.path.join(WorkingDirStructure,'coocurrenceMatrix.txt'),matrixTotal)
largestComponent=procCoocurenceMatrix(matrixTotal,CorePercentile,CorrThresh)
md = MetaData()
for idx in largestComponent:
id=md.addObject()
md.setValue(MDL_IMAGE,allNames[idx],id)
md.write(os.path.join(WorkingDirStructure+"_core","imagesCore.xmd"))
if md.size()==0:
print "There are no images in the core"
aaa
def extendCore(log,WorkingDirStructureCore,WorkingDirStructureExtended,NumVolumes,RemainingClasses,ComplementaryClasses,AngularSampling,\
SymmetryGroup,CorrThresh,NumberOfMpi):
from protlib_projmatch import projMatch
fnCore=os.path.join(WorkingDirStructureCore,"imagesCore.xmd")
fnComplementary=os.path.join(WorkingDirStructureExtended,"imagesComplementary.xmd")
runJob(log,"xmipp_metadata_utilities","-i %s --set subtraction %s image image -o %s"%(RemainingClasses,fnCore,fnComplementary))
runJob(log,"xmipp_metadata_utilities","-i %s --operate keep_column image"%fnComplementary)
if ComplementaryClasses!="":
fnAux=os.path.join(WorkingDirStructureExtended,"aux.xmd")
runJob(log,"xmipp_metadata_utilities","-i %s -o %s --operate keep_column image"%(ComplementaryClasses,fnAux))
runJob(log,"xmipp_metadata_utilities", "-i %s --set union %s image image"%(fnComplementary,fnAux))
deleteFile(log,fnAux)
runJob(log,"xmipp_metadata_utilities", "-i %s --set subtraction %s image image"%(fnComplementary,fnCore))
for i in range(NumVolumes):
# Projection matching with the complementary images
fnVolume=os.path.join(WorkingDirStructureCore,"proposedVolume%05d.vol"%i)
fnAngles=os.path.join(WorkingDirStructureExtended,"anglesComplementary%05d.xmd"%i)
projMatch(log,fnVolume,AngularSampling,SymmetryGroup,fnComplementary,WorkingDirStructureExtended,fnAngles,NumberOfMpi)
# Calculate minimum correlation
fnInliers=fnVolume=os.path.join(WorkingDirStructureCore,"proposedVolume%05d.xmd"%i)
md=MetaData(fnInliers)
cc=md.getColumnValues(MDL_MAXCC)
cc.sort()
minCC=min(cc[0],CorrThresh)
# Choose those complementary images whose correlation is larger than the minimum
fnAnglesChosen=os.path.join(WorkingDirStructureExtended,"anglesComplementaryChosen%05d.xmd"%i)
runJob(log,"xmipp_metadata_utilities",'-i %s --query select "maxCC>%f" -o %s'%(fnAngles,minCC,fnAnglesChosen))
fnExtended=os.path.join(WorkingDirStructureExtended,"proposedVolume%05d.xmd"%i)
runJob(log,"xmipp_metadata_utilities",'-i %s --set union %s -o %s'%(fnInliers,fnAnglesChosen,fnExtended))
deleteFile(log,fnAngles)
deleteFile(log,fnAnglesChosen)
fnOutOfCore=os.path.join(WorkingDirStructureExtended,"imagesOutOfCore%05d.xmd"%i)
runJob(log,"xmipp_metadata_utilities",'-i %s --set subtraction %s -o %s'%(RemainingClasses,fnExtended,fnOutOfCore))
runJob(log,"xmipp_metadata_utilities",'-i %s --operate sort'%fnOutOfCore)
runJob(log,"xmipp_metadata_utilities",'-i %s --operate drop_column scale'%fnOutOfCore)
runJob(log,"xmipp_metadata_utilities",'-i %s --operate sort'%fnExtended)
deleteFile(log,os.path.join(WorkingDirStructureExtended,"gallery.stk"))
def validate(self):
errors = []
md = mdFirstRow(self.ImgMd)
if md.containsLabel(MDL_IMAGE):
# If using reference check that have same size as images:
if not self.DoGenerateReferences:
from protlib_xmipp import validateInputSize
mdRef = MetaData(self.RefMd)
references = mdRef.getColumnValues(MDL_IMAGE)
validateInputSize(references, self.ImgMd, errors)
else:
errors.append("Input metadata <%s> doesn't contains image label" % self.ImgMd)
if self.acquisionInfo is None:
errors.append("Acquisition info was not found relative to image location")
if (self.NumberOfThreads > 1 and self.DoMlf):
errors.append("""WARNING: Threads are not implemented for MLF,
set number of threads to 1 and consider to
increment the number of MPI processes """)
return errors