Source code for xmipp3.protocols.protocol_consensus_local_ctf

# coding=utf-8
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# *
# * Authors:     Estrella Fernandez Gimenez (
# *              Carlos Oscar Sanchez Sorzano
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# * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia, CSIC
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import numpy as np

from pyworkflow import VERSION_2_0
from pyworkflow.object import Float
from pyworkflow.protocol.params import MultiPointerParam, PointerParam

from pwem.protocols import ProtAnalysis3D
from pwem import emlib
from pwem.objects import SetOfParticles

from xmipp3.convert import setXmippAttribute

OUTPUTNAME = "outputParticles"

[docs]class XmippProtConsensusLocalCTF(ProtAnalysis3D): """This protocol compares the estimations of local defocus computed by different protocols for a set of particles""" _label = 'consensus local defocus' _lastUpdateVersion = VERSION_2_0 _possibleOutputs = {OUTPUTNAME:SetOfParticles} def __init__(self, **args): ProtAnalysis3D.__init__(self, **args) #--------------------------- DEFINE param functions -------------------------------------------- def _defineParams(self, form): form.addSection(label='Input') form.addParam('inputSet', PointerParam, label="Input particles to assign the consensus defocus", pointerClass='SetOfParticles', help="Particle set of interest to estimate the defocus") form.addParam('inputSets', MultiPointerParam, label="Input defocus estimations", pointerClass='SetOfParticles', help="Sets of particles with different local defocus estimations to compare") #--------------------------- INSERT steps functions -------------------------------------------- def _insertAllSteps(self): self._insertFunctionStep(self.compareDefocus) self._insertFunctionStep(self.createOutputStep) #--------------------------- STEPS functions ---------------------------------------------------
[docs] def compareDefocus(self): """compare with median, mad and correlation matrix the local defocus value for each pixel estimated by different programs (Xmipp, Relion, gCTF, ...)""" allParticlesDefU = {} allParticlesDefV = {} for defsetP in self.inputSets: defset = defsetP.get() for particle in defset: pIDs = [] pDefUs = [] pDefVs = [] pIDs.append(particle.getObjId()) pDefUs.append(particle.getCTF().getDefocusU()) pDefVs.append(particle.getCTF().getDefocusV()) for pId, pDefU, pDefV in zip(pIDs, pDefUs, pDefVs): if not pId in allParticlesDefU.keys(): allParticlesDefU[pId]=[] allParticlesDefV[pId] = [] allParticlesDefU[pId].append(pDefU) allParticlesDefV[pId].append(pDefV) self.defMatrixU = np.full(shape=(len(allParticlesDefU.keys()),len(self.inputSets)),fill_value=np.NaN) self.defMatrixV = np.full(shape=(len(allParticlesDefV.keys()),len(self.inputSets)),fill_value=np.NaN) i=0 self.pMatrixIdx={} for pIdU, pdefiU in allParticlesDefU.items(): self.pMatrixIdx[pIdU]=i for j in enumerate(pdefiU): self.defMatrixU[i,j[0]]=j[1] i+=1 l=0 for pIdV, pdefiV in allParticlesDefV.items(): self.pMatrixIdx[pIdV] = l for k in enumerate(pdefiV): self.defMatrixV[l, k[0]] = k[1] l += 1 self.medianU = np.nanmedian(self.defMatrixU, axis=1) self.medianV = np.nanmedian(self.defMatrixV, axis=1) self.madU = np.empty_like(self.medianU) self.madV = np.empty_like(self.medianV) for l in enumerate(self.medianU): self.madU[l[0]] = np.nanmedian(np.abs(self.defMatrixU[l[0],:] - self.medianU[l[0]])) for m in enumerate(self.medianV): self.madV[m[0]] = np.nanmedian(np.abs(self.defMatrixV[m[0], :] - self.medianV[m[0]])) self.defMatrixU = np.hstack((self.defMatrixU, self.medianU.reshape(len(self.medianU),1))) self.corrMatrixU = np.zeros((self.defMatrixU.shape[0],self.defMatrixU.shape[1])) defMatrixInvalidU = self.corrMatrixU =,rowvar=False) np.savetxt(self._getExtraPath("defocusMatrixU.txt"),self.defMatrixU) np.savetxt(self._getExtraPath("correlationMatrixU.txt"),self.corrMatrixU) self.defMatrixV = np.hstack((self.defMatrixV, self.medianV.reshape(len(self.medianV),1))) self.corrMatrixV = np.zeros((self.defMatrixV.shape[0],self.defMatrixV.shape[1])) defMatrixInvalidV = self.corrMatrixV =,rowvar=False) np.savetxt(self._getExtraPath("defocusMatrixV.txt"),self.defMatrixV) np.savetxt(self._getExtraPath("correlationMatrixV.txt"),self.corrMatrixV)
[docs] def createOutputStep(self): """create as output a setOfParticles with a consensus estimation of local defocus (median) and its median standard deviation (mad)""" imgSet = self.inputSet.get() outputSet = self._createSetOfParticles() outputSet.copyInfo(imgSet) # Loop through input set of for part in imgSet.iterItems(): id = part.getObjId() if id in self.pMatrixIdx: index = self.pMatrixIdx[id] newPart = part.clone() pMedianU = Float(self.medianU[index]) # consensus defocus U pMedianV = Float(self.medianV[index]) # consensus defocus V pMadU = Float(self.madU[index]) # residual consensus defocus U newPart._ctfModel._defocusU.set(pMedianU) newPart._ctfModel._defocusV.set(pMedianV) setXmippAttribute(newPart.getCTF(), emlib.MDL_CTF_DEFOCUS_RESIDUAL, pMadU) outputSet.append(newPart) self._defineOutputs(**{OUTPUTNAME:outputSet}) self._defineSourceRelation(self.inputSet, outputSet)
def _updateItem(self, particle, row): """update each particle in the set with the values computed""" pId = particle.getObjId() setXmippAttribute(particle,emlib.MDL_CTF_DEFOCUSA,self.medianU[self.pMatrixIdx[pId]]) setXmippAttribute(particle,emlib.MDL_CTF_DEFOCUS_RESIDUAL,self.madU[self.pMatrixIdx[pId]]) #--------------------------- INFO functions -------------------------------------------- def _summary(self): summary = [] summary.append("Consensus local defocus and residual computed for %s particles" % self.getObjectTag(OUTPUTNAME)) return summary def _methods(self): methods = [] methods.append("The results obtained when local CTF is estimated by different methods are compared here " "computing the median, MAD and correlation matrix.") return methods