Source code for xmipp3.protocols.protocol_preprocess.protocol_add_noise

# **************************************************************************
# *
# * Authors:     Jose Luis Vilas (
# *              Pablo Conesa (
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# * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia , CSIC
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from os.path import basename

from pyworkflow import VERSION_1_1
from pyworkflow.utils import removeExt
from pyworkflow.protocol.params import (PointerParam, EnumParam, FloatParam,

from pwem.protocols import ProtRefine3D
from pwem.objects import Volume
import pwem.emlib.metadata as md

from xmipp3.convert import writeSetOfParticles, xmippToLocation

[docs]class XmippProtAddNoise(ProtRefine3D): """ Given a sets of volumes or particles the protocol adds noise to them The types of noise are Uniform, Student and Gaussian. """ GAUSSIAN_NOISE = 0 STUDENT_NOISE = 1 UNIFORM_NOISE = 2 _lastUpdateVersion = VERSION_1_1 #--------------------------- DEFINE param functions ------------------------ def _defineParams(self, form): form.addParam('noiseType', EnumParam, choices=['Gaussian', 'Student', 'Uniform'], default = 0, label="Noise Type") form.addParam('gaussianStd', FloatParam, default=0.08, condition='noiseType == %d' % self.GAUSSIAN_NOISE, label="Standard Deviation", help='Please, introduce the standard deviation value.' 'Mean value can be changed in advanced mode.') form.addParam('gaussianMean', FloatParam, default=0, expertLevel=LEVEL_ADVANCED, condition='noiseType == %d' % self.GAUSSIAN_NOISE, label="Mean", help='Please, introduce the mean value (default = 0).') form.addParam('studentDf', FloatParam, default=1, condition='noiseType == %d' % self.STUDENT_NOISE, label="Degree of Freedom", help='Please, introduce the Degree of Freedom.' 'Mean value can be changed in advanced mode.') form.addParam('studentStd', FloatParam, default=0.08, condition='noiseType == %d' % self.STUDENT_NOISE, label="Standard Deviation", help='Please, introduce the standard deviation value.' 'Mean value can be changed in advanced mode.') form.addParam('studentMean', FloatParam, default=0, expertLevel=LEVEL_ADVANCED, condition='noiseType == %d' % self.STUDENT_NOISE, label="Mean", help='Please, introduce the mean value (default = 0).') form.addParam('uniformMin', FloatParam, default=0, condition='noiseType == %d' % self.UNIFORM_NOISE, label="Minimum Value", help='Please, introduce the minimum value. (default = 0)') form.addParam('uniformMax', FloatParam, default=1, condition='noiseType == %d' % self.UNIFORM_NOISE, label="Maximum Value", help='Please, introduce the maximum value (default = 1).') form.addParallelSection(threads=1, mpi=1) #--------------------------- INSERT steps functions ------------------------ def _insertAllSteps(self): self.micsFn = self._getPath() # Convert input into xmipp Metadata format convertId = self._insertFunctionStep('convertInputStep') self._insertFunctionStep('addNoiseStep') self._insertFunctionStep('createOutputStep') def _getTypeOfNoise(self): if self.noiseType == self.GAUSSIAN_NOISE: kindNoise = 'gaussian' noiseParams = '%f %f' % (self.gaussianStd, self.gaussianMean) if self.noiseType == self.STUDENT_NOISE: kindNoise = 'student' noiseParams = '%f %f %f' % (self.studentDf, self.studentStd , self.studentMean) if self.noiseType == self.UNIFORM_NOISE: kindNoise = 'uniform' noiseParams = '%f %f' % (self.uniformMin, self.uniformMax) return kindNoise, noiseParams #--------------------------- INFO functions ------------------------------- def _validate(self): validateMsgs = [] if self.input and not self.input.hasValue(): validateMsgs.append('Please provide input volume.') return validateMsgs def _summary(self): summary = [] if (not hasattr(self,'outputVolume')): summary.append("Output volume not ready yet.") else: summary.append("Volume with %s noise has been obtained" % (self.getEnumText("noiseType")) ) # return summary def _methods(self): messages = [] if (hasattr(self,'outputVolume')): messages.append('Noisy volume has been obtained') return messages def _citations(self): return ['Do not apply']
[docs] def getSummary(self): summary = [] summary.append("Particles analyzed:") #summary.append("Particles picked: %d" %coordsSet.getSize()) return "\n"#.join(summary)
[docs]class XmippProtAddNoiseVolumes(XmippProtAddNoise): """ Given a set of volumes, or a volume the protocol will add noise to them The types of noise are Uniform, Student and Gaussian. """ _label = 'add noise volume/s' #--------------------------- DEFINE param functions ------------------------ def _defineParams(self, form): form.addSection(label='Input') form.addParam('input', PointerParam, pointerClass='SetOfVolumes, Volume', label="Input Volume/s", help='Select a volume or Set of volumes.') XmippProtAddNoise._defineParams(self, form)
[docs] def convertInputStep(self): pass
def _getNoisyOutputPath(self, fnvol): fnNoisy = self._getExtraPath(removeExt(basename(fnvol)) + '_Noisy.vol') return fnNoisy def _addNoisetoVolumeStep(self, kindNoise, noiseParams, vol): fnvol = vol.getFileName() fnNoisy = self._getNoisyOutputPath(fnvol) params = " -i %s --type %s %s -o %s" % (fnvol, kindNoise, noiseParams, fnNoisy) self.runJob('xmipp_transform_add_noise', params, numberOfMpi=1)
[docs] def addNoiseStep(self): kindNoise, noiseParams = self._getTypeOfNoise() inputSet = self.input.get() if isinstance(inputSet, Volume): self._addNoisetoVolumeStep(kindNoise, noiseParams, inputSet) else: for vol in self.input.get(): self._addNoisetoVolumeStep(kindNoise, noiseParams, vol)
[docs] def createOutputStep(self): #Output Volume/SetOfVolumes volInput = self.input.get() if self._isSingleVolume(): # Create the output with the same class as # the input, that should be Volume or a subclass # of Volume like VolumeMask fnvol = volInput.getFileName() fnOutVol = self._getNoisyOutputPath(fnvol) volClass = volInput.getClass() vol = volClass() # Create an instance with the same class of input vol.copyInfo(volInput) vol.setFileName(fnOutVol) self._defineOutputs(outputVolume=vol) self._defineSourceRelation(self.input.get(), vol) else: volumes = self._createSetOfVolumes() volumes.copyInfo(volInput) volumes.copyItems(volInput, updateItemCallback=self._updateNoisyPath) self._defineOutputs(outputVol=volumes) self._defineSourceRelation(self.input.get(), volumes)
# self._defineTransformRelation(self.inputVolumes, self.outputVol) def _updateNoisyPath(self, vol, row): fnvol = vol.getFileName() fnOutVol = self._getNoisyOutputPath(fnvol) vol.setFileName(fnOutVol) def _isSingleVolume(self): return isinstance(self.input.get(), Volume)
[docs]class XmippProtAddNoiseParticles(XmippProtAddNoise): """ Given a set of particles, the protocol will add noise to them The types of noise are Uniform, Student and Gaussian. """ _label = 'add noise particles' #--------------------------- DEFINE param functions -------------------- def _defineParams(self, form): form.addSection(label='Input') form.addParam('input', PointerParam, pointerClass='SetOfParticles', label="Input particles", help='Select a set of particles.') XmippProtAddNoise._defineParams(self, form)
[docs] def convertInputStep(self): """ Read the input metadatata. """ # Get the converted input micrographs in Xmipp format inputSet = self.input.get() inputPath = self._getExtraPath('inputSet') fnSet = inputPath+'.xmd' writeSetOfParticles(inputSet, fnSet)
[docs] def addNoiseStep(self): kindNoise, noiseParams = self._getTypeOfNoise() params ='--save_metadata_stack' params += " -i %s --type %s %s -o %s" % (self._getExtraPath('inputSet.xmd'), kindNoise, noiseParams, self.getFileNameNoisyStk()) self.runJob('xmipp_transform_add_noise', params, numberOfMpi=1)
[docs] def createOutputStep(self): #Output Volume/SetOfVolumes particlesSet = self._createSetOfParticles() particlesSet.copyInfo(self.input.get()) inputMd = self._getExtraPath('Noisy.xmd') particlesSet.copyItems(self.input.get(), updateItemCallback=self._updateParticle, itemDataIterator=md.iterRows(inputMd)) self._defineOutputs(outputParticles=particlesSet) self._defineSourceRelation(self.input.get(), particlesSet)
[docs] def getFileNameNoisyStk(self): return self._getExtraPath('Noisy.stk')
def _updateParticle(self, particle, row): #fn = particle.getFileName() # fnOut = self.getFileNameNoisyStk() # particle.setFileName(fnOut) index, filename = xmippToLocation(row.getValue(md.MDL_IMAGE)) particle.setLocation(index, filename)