Source code for emantomo.protocols.protocol_tomo_extraction

# **************************************************************************
# *
# * Authors:     Adrian Quintana (adrian@eyeseetea.com) [1]
# *
# * [1] EyeSeeTea Ltd, London, UK
# *
# * This program is free software; you can redistribute it and/or modify
# * it under the terms of the GNU General Public License as published by
# * the Free Software Foundation; either version 2 of the License, or
# * (at your option) any later version.
# *
# * This program is distributed in the hope that it will be useful,
# * but WITHOUT ANY WARRANTY; without even the implied warranty of
# * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# * GNU General Public License for more details.
# *
# * You should have received a copy of the GNU General Public License
# * along with this program; if not, write to the Free Software
# * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
# * 02111-1307  USA
# *
# *  All comments concerning this program package may be sent to the
# *  e-mail address 'scipion@cnb.csic.es'
# *
# **************************************************************************


import glob
from os.path import abspath

from pyworkflow import BETA
from pyworkflow import utils as pwutils
import pyworkflow.protocol.params as params
from pyworkflow.utils.path import moveFile, cleanPath, cleanPattern

from pwem.emlib.image import ImageHandler
from pwem.protocols import EMProtocol

from tomo.protocols import ProtTomoBase
from tomo.objects import SetOfSubTomograms, SubTomogram, TomoAcquisition

from emantomo.constants import *

import tomo.constants as const

# Tomogram type constants for particle extraction
SAME_AS_PICKING = 0
OTHER = 1


[docs]class EmanProtTomoExtraction(EMProtocol, ProtTomoBase): """ Extraction for Tomo. Uses EMAN2 e2spt_boxer_old.py.""" _label = 'tomo extraction' _devStatus = BETA OUTPUT_PREFIX = 'outputSetOfSubtomogram' def __init__(self, **kwargs): EMProtocol.__init__(self, **kwargs) # --------------------------- DEFINE param functions ---------------------- def _defineParams(self, form): form.addSection(label='Input') form.addParam('inputCoordinates', params.PointerParam, label="Input Coordinates", important=True, pointerClass='SetOfCoordinates3D', help='Select the SetOfCoordinates3D.') form.addParam('tomoSource', params.EnumParam, choices=['same as picking', 'other'], default=0, display=params.EnumParam.DISPLAY_HLIST, label='Tomogram source', help='By default the subtomograms will be extracted ' 'from the tomogram used in the picking ' 'step ( _same as picking_ option ). \n' 'If you select _other_ option, you must provide ' 'a different tomogram to extract from. \n' '*Note*: In the _other_ case, ensure that provided ' 'tomogram and coordinates are related ') form.addParam('inputTomograms', params.PointerParam, pointerClass='SetOfTomograms', condition='tomoSource != %s' % SAME_AS_PICKING, label='Input tomogram', help='Select the tomogram from which to extract.') form.addParam('boxSize', params.FloatParam, label='Box size', help='The subtomograms are extracted as a cubic box of this size. ' 'The wizard selects same box size as picking') form.addParam('downFactor', params.FloatParam, default=1.0, label='Downsampling factor', help='If 1.0 is used, no downsample is applied. ' 'Non-integer downsample factors are possible. ') form.addSection(label='Preprocess') form.addParam('doInvert', params.BooleanParam, default=False, label='Invert contrast?', help='Invert the contrast if your tomogram is black ' 'over a white background. Xmipp, Spider, Relion ' 'and Eman require white particles over a black ' 'background. Frealign (up to v9.07) requires black ' 'particles over a white background') form.addParam('doNormalize', params.BooleanParam, default=False, label='Normalize subtomogram?', help='Normalization processor applied to subtomograms before extraction.') form.addParam('normproc', params.EnumParam, choices=['normalize', 'normalize.edgemean'], label='Normalize method', condition='doNormalize', default=PROC_NORMALIZE, display=params.EnumParam.DISPLAY_COMBO, help='Use normalize.edgemean if the particles have a clear solvent background ' '(i.e., they are not part of a larger complex or embeded in a membrane)') # Uncomment once migrated to new tomo extraction (e2spt_extract.py) # form.addParallelSection(threads=4, mpi=0) # --------------------------- INSERT steps functions ---------------------- def _insertAllSteps(self): self._insertFunctionStep('writeSetOfCoordinates3D') self._insertFunctionStep('extractParticles') self._insertFunctionStep('convertOutput') self._insertFunctionStep('createOutputStep') # --------------------------- STEPS functions -----------------------------
[docs] def writeSetOfCoordinates3D(self): self.lines = [] self.tomoFiles = [] tomoList = [] for tomo in self.getInputTomograms(): tomoList.append(tomo.clone()) for tomo in tomoList: coordDict = [] self.coordsFileName = self._getExtraPath( pwutils.replaceBaseExt(tomo.getFileName(), 'coords')) with open(self.coordsFileName, "w") as out: coords = self.inputCoordinates.get() for coord3D in coords.iterCoordinates(volume=tomo): if os.path.basename(tomo.getFileName()) == os.path.basename(coord3D.getVolName()): out.write("%d\t%d\t%d\n" % (coord3D.getX(const.BOTTOM_LEFT_CORNER), coord3D.getY(const.BOTTOM_LEFT_CORNER), coord3D.getZ(const.BOTTOM_LEFT_CORNER))) newCoord = coord3D.clone() newCoord.setVolume(coord3D.getVolume()) coordDict.append(newCoord) if coordDict: self.lines.append(coordDict) self.tomoFiles.append(tomo.getFileName()) self.samplingRateTomo = tomo.getSamplingRate()
[docs] def extractParticles(self): samplingRateCoord = self.inputCoordinates.get().getSamplingRate() samplingRateTomo = self.getInputTomograms().getFirstItem().getSamplingRate() for tomo in self.tomoFiles: args = '%s ' % os.path.abspath(tomo) args += "--coords % s --boxsize % d" % (pwutils.replaceBaseExt(tomo, 'coords'), self.boxSize.get()) if self.doInvert: args += ' --invert' if self.doNormalize: args += ' --normproc %s' % self.getEnumText('normproc') self.cshrink = float(samplingRateCoord / samplingRateTomo) if self.cshrink > 1: args += ' --cshrink %d' % self.cshrink # Uncomment once migrated to new tomo extraction (e2spt_extract.py) # args += ' --threads=% d' % self.numberOfThreads.get() program = emantomo.Plugin.getProgram('e2spt_boxer_old.py') self.runJob(program, args, cwd=self._getExtraPath(), numberOfMpi=1, numberOfThreads=1) moveFile(self._getExtraPath(os.path.join('sptboxer_01', 'basename.hdf')), self._getExtraPath(pwutils.replaceBaseExt(tomo, 'hdf'))) cleanPath(self._getExtraPath("sptboxer_01"))
[docs] def convertOutput(self): program = emantomo.Plugin.getProgram('e2proc3d.py') for hdfFile in glob.glob(self._getExtraPath('*.hdf')): args = ' --unstacking' args += ' %s' % abspath(hdfFile) args += ' %s' % abspath(self._getExtraPath(pwutils.replaceBaseExt(hdfFile, 'mrc'))) self.runJob(program, args, cwd=self._getExtraPath(), numberOfMpi=1, numberOfThreads=1) cleanPattern(hdfFile)
[docs] def createOutputStep(self): self.outputSubTomogramsSet = self._createSetOfSubTomograms(self._getOutputSuffix(SetOfSubTomograms)) self.outputSubTomogramsSet.setSamplingRate(self.getInputTomograms().getSamplingRate() / self.downFactor.get()) self.outputSubTomogramsSet.setCoordinates3D(self.inputCoordinates) acquisition = TomoAcquisition() acquisition.setAngleMin(self.getInputTomograms().getFirstItem().getAcquisition().getAngleMin()) acquisition.setAngleMax(self.getInputTomograms().getFirstItem().getAcquisition().getAngleMax()) acquisition.setStep(self.getInputTomograms().getFirstItem().getAcquisition().getStep()) self.outputSubTomogramsSet.setAcquisition(acquisition) for item in self.getInputTomograms().iterItems(): for ind, tomoFile in enumerate(self.tomoFiles): if os.path.basename(tomoFile) == os.path.basename(item.getFileName()): coordSet = self.lines[ind] outputSet = self.readSetOfSubTomograms(tomoFile, self.outputSubTomogramsSet, coordSet, item.getObjId()) self._defineOutputs(outputSetOfSubtomogram=outputSet) self._defineSourceRelation(self.inputCoordinates, outputSet)
# --------------------------- INFO functions -------------------------------- def _methods(self): methodsMsgs = [] if self.getOutputsSize() >= 1: msg = ("A total of %s subtomograms of size %s were extracted" % (str(self.inputCoordinates.get().getSize()), self.boxSize.get())) if self._tomosOther(): msg += (" from another set of tomograms: %s" % self.getObjectTag('inputTomogram')) msg += " using coordinates %s" % self.getObjectTag('inputCoordinates') msg += self.methodsVar.get('') methodsMsgs.append(msg) else: methodsMsgs.append("Set of Subtomograms not ready yet") if self.doInvert: methodsMsgs.append("Inverted contrast on images.") if self.downFactor.get() != 1: methodsMsgs.append("Subtomograms downsample by factor %d." % self.downFactor.get()) if self.doNormalize: methodsMsgs.append("Particles were normalised. Using normalization method %s" % self.getEnumText('normproc')) return methodsMsgs def _summary(self): summary = [] summary.append("Tomogram source: *%s*" % self.getEnumText("tomoSource")) if self.getOutputsSize() >= 1: summary.append("Particle box size: *%s*" % self.boxSize.get()) summary.append("Subtomogram extracted: *%s*" % self.inputCoordinates.get().getSize()) else: summary.append("Output subtomograms not ready yet.") if self.doInvert: summary.append('*Contrast was inverted.*') return summary def _validate(self): errors = [] if self.tomoSource.get() == SAME_AS_PICKING: return errors tomo_from_coords = self.inputCoordinates.get().getPrecedents() tomoFiles = [pwutils.removeBaseExt(file) for file in self.getInputTomograms().getFiles()] coordFiles = [pwutils.removeBaseExt(file) for file in tomo_from_coords.getFiles()] numberMatches = len(set(tomoFiles) & set(coordFiles)) if numberMatches == 0: errors.append("Cannot relate Coordinate Tomograms and New Tomograms. In order to stablish a " "relation, the filename of the corresponding Coordinate Tomograms and New Tomogram " "files must be equal. For example, if a coordinate Coordinate Tomogram file is named Tomo_1.mrc, " "then the New Tomogram file to be associated to it should be named Tomo_1.ext " "(being 'ext' any valid extension - '.mrc', '.em'...).\n") return errors def _warnings(self): warnings = [] if self.tomoSource.get() == SAME_AS_PICKING: return warnings tomo_from_coords = self.inputCoordinates.get().getPrecedents() tomoFiles = [pwutils.removeBaseExt(file) for file in self.getInputTomograms().getFiles()] coordFiles = [pwutils.removeBaseExt(file) for file in tomo_from_coords.getFiles()] numberMatches = len(set(tomoFiles) & set(coordFiles)) if numberMatches < max(len(tomoFiles), len(coordFiles)): warnings.append("Couldn't find a correspondence between all tomogram files. " "Association is performed in terms of the file name of the Coordinate Tomograms and the New Tomograms " "(without the extension). For example, if a Coordinate Tomogram file is named Tomo_1.mrc, then the New Tomogram file " "file to be associated to it should be named Tomo_1.ext (being 'ext' any valid extension " "- '.mrc', '.em'...).\n") mismatches_coords = set(coordFiles).difference(tomoFiles) if mismatches_coords: warnings.append("The following Coordinate Tomogram files will not be associated to any New Tomogram " "(name without extension):") for file in mismatches_coords: warnings.append("\t%s" % file) warnings.append("\n") mismatches_tomos = set(tomoFiles).difference(coordFiles) if mismatches_tomos: warnings.append("The following New Tomogram files will not be associated to any Coordinate Tomogram " "(name without extension):") for file in mismatches_tomos: warnings.append("\t%s" % file) warnings.append("\n") return warnings # --------------------------- UTILS functions ---------------------------------- def _tomosOther(self): """ Return True if other tomograms are used for extract. """ return self.tomoSource == OTHER
[docs] def getInputTomograms(self): """ Return the tomogram associated to the 'SetOfCoordinates3D' or 'Other' tomograms. """ if self.tomoSource.get() == SAME_AS_PICKING: return self.inputCoordinates.get().getPrecedents() else: return self.inputTomograms.get()
[docs] def readSetOfSubTomograms(self, tomoFile, outputSubTomogramsSet, coordSet, volId): outRegex = self._getExtraPath(pwutils.removeBaseExt(tomoFile) + '-*.mrc') subtomoFileList = sorted(glob.glob(outRegex)) ih = ImageHandler() for counter, subtomoFile in enumerate(subtomoFileList): subtomogram = SubTomogram() subtomogram.cleanObjId() subtomogram.setLocation(subtomoFile) dfactor = self.downFactor.get() if dfactor != 1: fnSubtomo = self._getExtraPath("downsampled_subtomo%d.mrc" % counter) ImageHandler.scaleSplines(subtomogram.getLocation()[1]+':mrc', fnSubtomo, dfactor) subtomogram.setVolId(volId) subtomogram.setLocation(fnSubtomo) subtomogram.setCoordinate3D(coordSet[counter]) subtomogram.setTransform(coordSet[counter]._eulerMatrix) subtomogram.setVolName(tomoFile) outputSubTomogramsSet.append(subtomogram) return outputSubTomogramsSet