Source code for pwem.protocols.protocol_alignment_assign

# **************************************************************************
# *
# * Authors:     J.M. De la Rosa Trevin (jmdelarosa@cnb.csic.es)
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# * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia , CSIC
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import pyworkflow.protocol.params as params
from pyworkflow.object import Integer

from .protocol_2d import ProtAlign2D


[docs]class ProtAlignmentAssign(ProtAlign2D): """ Assign a the alignment calculated for a set of particles to another set. This protocol will take into account the differences of pixel size (A/pix) between the two sets and multiply by the right factor the shifts. The particles with the alignment can also be a subset of the other images """ _label = 'assign alignment' def _defineParams(self, form): form.addSection(label='Input') form.addParam('inputParticles', params.PointerParam, pointerClass='SetOfParticles', label='Input particles', help='Select the particles that you want to update the new alignment.') form.addParam('inputAlignment', params.PointerParam, pointerClass='SetOfParticles', label="Input alignments", help='Select the particles with alignment to be apply to the other particles.') form.addParam('assignRandomSubsets', params.BooleanParam, default=True, expertLevel=params.LEVEL_ADVANCED, label="Assign random subsets?", help="If yes, the random subset information from the " "assignment input will be transferred to the output " "particles.") form.addParallelSection(threads=0, mpi=0) # --------------------------- INSERT steps functions -------------------------- def _insertAllSteps(self): """for each ctf insert the steps to compare it """ self._insertFunctionStep('createOutputStep') def _updateItem(self, item, row): """ Implement this function to do some update actions over each single item that will be stored in the output Set. """ # Add alignment info from corresponding item on inputAlignment inputAlignment = self.inputAlignment.get() scale = inputAlignment.getSamplingRate()/self.inputParticles.get().getSamplingRate() alignedParticle = inputAlignment[item.getObjId()] # If alignment is found for this particle set the alignment info # on the output particle, if not do not write that item if alignedParticle is not None: alignment = alignedParticle.getTransform() # If shifts Applied before at extraction coordinate time if item.hasCoordinate() and hasattr(item.getCoordinate(), "xFrac"): coord = item.getCoordinate() alignedParticle = inputAlignment[item.getObjId()] alignment.invert() alignment.setShifts(-coord.xFrac.get(), -coord.yFrac.get(), 0) alignment.invert() else: alignment.scaleShifts(scale) item.setTransform(alignment) if self.assignRandomSubsets: subset = \ alignedParticle.getAttributeValue('_rlnRandomSubset', None) if subset is not None: item._rlnRandomSubset = Integer(subset) else: item._appendItem = False
[docs] def createOutputStep(self): inputParticles = self.inputParticles.get() inputAlignment = self.inputAlignment.get() outputParticles = self._createSetOfParticles() outputParticles.copyInfo(inputParticles) outputParticles.setAlignment(inputAlignment.getAlignment()) outputParticles.copyItems(inputParticles, updateItemCallback=self._updateItem) self._defineOutputs(outputParticles=outputParticles) self._defineSourceRelation(self.inputParticles, outputParticles) self._defineSourceRelation(self.inputAlignment, outputParticles)
def _summary(self): summary = [] if not hasattr(self, 'outputParticles'): summary.append("Output particles not ready yet.") else: scale = self.inputAlignment.get().getSamplingRate()/self.inputParticles.get().getSamplingRate() summary.append("Assigned alignment to %s particles from a total of %s." % ( self.outputParticles.getSize(), self.inputParticles.get().getSize())) if scale != 1: summary.append("Applied scale of %s." % scale) return summary def _methods(self): methods = [] if not hasattr(self, 'outputParticles'): methods.append("Output particles not ready yet.") else: scale = self.inputAlignment.get().getSamplingRate()/self.inputParticles.get().getSamplingRate() methods.append("We assigned alignment to %s particles from %s and produced %s." % (self.outputParticles.getSize(), self.getObjectTag('inputParticles'), self.getObjectTag('outputParticles'))) if scale != 1: methods.append("Applied scale factor of %s." % scale) return methods def _validate(self): """ The function of this hook is to add some validation before the protocol is launched to be executed. It should return a list of errors. If the list is empty the protocol can be executed. """ # check that input set of aligned particles do have 2D alignment errors = [] inputAlignmentSet = self.inputAlignment.get() if not inputAlignmentSet.hasAlignment(): errors.append("Input alignment set should contains some kind of alignment (2D, 3D or Projection).") else: # Just for consistency, check that the particles really contains Transform object first = inputAlignmentSet.getFirstItem() alignment = first.getTransform() if alignment is None: errors.append('Inconsistency detected in *Input alignment* !!!') errors.append('It has alignment: _%s_, but the alignment is missing!!!' % inputAlignmentSet.getAlignment()) # Add some errors if input is not valid return errors