Source code for pwem.protocols.protocol_2d

# **************************************************************************
# *
# * Authors:     Airen Zaldivar Peraza (azaldivar@cnb.csic.es)
# *
# * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia , CSIC
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"""
Protocol base classes related to 2D processing.
"""
import pyworkflow.protocol.params as params
import pyworkflow.utils as pwutils

import pwem.objects as emobj
from .protocol import EMProtocol


[docs]class Prot2D(EMProtocol): pass
[docs]class ProtAlign2D(Prot2D): """ This class will serve as a base for all protocols that align a set of 2D images. All Align protocols receive as input: A set of particles and will allow the option to generate the aligned particles. """ def _defineParams(self, form): form.addSection(label='Input') form.addParam('inputParticles', params.PointerParam, important=True, label=pwutils.Message.LABEL_INPUT_PART, pointerClass='SetOfParticles') # Hook that should be implemented in subclasses self._defineAlignParams(form) def _defineAlignParams(self, form): """ This method should be implemented by subclasses to add other parameter relatives to the specific align protocol.""" pass
[docs]class ProtCreateMask2D(Prot2D): """ For those protocols who create mask as output. """ pass
[docs]class ProtClassify2D(Prot2D): pass
[docs]class ProtAnalysis2D(Prot2D): pass
# ------------ Some testing protocols -----------------------------------------
[docs]class ProtEvenClassify2D: # ProtClassify2D): """ This is a simple classification protocol for testing purposes. It will iterate over the images and assign each one to a different class. """ def _defineParams(self, form): form.addSection(label='Input') form.addParam('inputParticles', params.PointerParam, important=True, label=pwutils.Message.LABEL_INPUT_PART, pointerClass='SetOfParticles') form.addParam('numberOfClasses', params.IntParam, default=8, label="Number of classes", help="Select into how many classes do you want to classify your images.") def _insertAllSteps(self): self._insertFunctionStep('createOutputStep')
[docs] def createOutputStep(self): """ This single step will do the fullish classification and create the output classes. """ classes = self._createSetOfClasses2D() n = self.numberOfClasses.get() for classNumber in range(1, n+1): classes.append(emobj.Class2D()) for img in self.inputParticles.get(): classNumber = (img.getObjId() % n) + 1 classes[classNumber].append(img) for cls in classes: classes.update(cls) classes.write() self._defineOutputs(outputClasses=classes)