def convertInputStep(self, micsId, refsId):
self._ih = ImageHandler() # used to convert micrographs
# Match ctf information against the micrographs
self.ctfDict = {}
if self.ctfRelations.get() is not None:
for ctf in self.ctfRelations.get():
self.ctfDict[ctf.getMicrograph().getMicName()] = ctf.clone()
micStar = self._getPath('input_micrographs.star')
writeSetOfMicrographs(self.getInputMicrographs(), micStar,
preprocessImageRow=self._preprocessMicrographRow,
postprocessImageRow=self._postprocessMicrographRow)
writeReferences(self.getInputReferences(), self._getPath('input_references'))
def convertInputStep(self, inputId, avgId, volId):
""" Create the input file in STAR format as expected by Relion.
If the input particles comes from Relion, just link the file.
Params:
particlesId: use this parameters just to force redo of convert if
the input particles are changed.
"""
inputSet = self.inputSet.get()
imgStar = self._getFileName('input_particles')
refStar = self._getFileName('input_refs')
# Pass stack file as None to avoid write the images files
self.info("Converting set from '%s' into '%s'" %
(inputSet.getFileName(), imgStar))
refSet = None
# case refine3D
if self.isInputClasses():
refSet = self.inputSet.get() # 2D or 3D classes
else:
if self.isInputAutoRefine():
em.ImageHandler().convert(self.referenceVolume.get(),
self._getFileName('input_refvol'))
else: # Autopicking case
refSet = self.referenceAverages.get()
self.classDict = {}
if refSet:
self.info("Converting reference from '%s' into %s" %
(refSet.getFileName(), refStar))
# Compute class mapping
classList = [cls.getObjId() for cls in refSet]
classList.sort()
for i, c in enumerate(classList):
self.classDict[c] = i + 1
writeReferences(refSet,
removeExt(refStar),
postprocessImageRow=self._updateClasses)
# Write particles star file
allParticles = self._allParticles(iterate=False)
writeSetOfParticles(allParticles,
imgStar,
self._getPath(),
postprocessImageRow=self._postProcessImageRow)
def convertInputStep(self, micsId, refsId, runType):
# runType is passed as parameter to force a re-execute of this step
# if there is a change in the type
self._ih = ImageHandler() # used to convert micrographs
# Match ctf information against the micrographs
self.ctfDict = {}
if self.ctfRelations.get() is not None:
for ctf in self.ctfRelations.get():
self.ctfDict[ctf.getMicrograph().getMicName()] = ctf.clone()
micStar = self._getPath('input_micrographs.star')
writeSetOfMicrographs(self.getMicrographList(), micStar,
alignType=ALIGN_NONE,
preprocessImageRow=self._preprocessMicrographRow)
if self.useInputReferences():
writeReferences(self.getInputReferences(),
self._getPath('input_references'), useBasename=True)
def convertInputStep(self, micsId, refsId, runType):
# runType is passed as parameter to force a re-execute of this step
# if there is a change in the type
self._ih = ImageHandler() # used to convert micrographs
# Match ctf information against the micrographs
self.ctfDict = {}
if self.ctfRelations.get() is not None:
for ctf in self.ctfRelations.get():
self.ctfDict[ctf.getMicrograph().getMicName()] = ctf.clone()
micStar = self._getPath('input_micrographs.star')
writeSetOfMicrographs(self.getMicrographList(),
micStar,
alignType=ALIGN_NONE,
preprocessImageRow=self._preprocessMicrographRow)
if self.useInputReferences():
writeReferences(self.getInputReferences(),
self._getPath('input_references'),
useBasename=True)