# **************************************************************************
# *
# * Authors: Jose Gutierrez Tabuenca (jose.gutierrez@cnb.csic.es)
# * Laura del Cano (laura.cano@cnb.csic.es)
# *
# * Unidad de Bioinformatica of Centro Nacional de Biotecnologia , CSIC
# *
# * 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'
# *
# **************************************************************************
from os.path import exists, basename, join
from pyworkflow.protocol.params import STEPS_PARALLEL, PointerParam, EnumParam
from pyworkflow.utils.path import *
from pwem.protocols import ProtParticlePickingAuto
from pwem import emlib
from xmipp3.base import XmippProtocol
from xmipp3.convert import readSetOfCoordinates
MICS_SAMEASPICKING = 0
MICS_OTHER = 1
[docs]class XmippParticlePickingAutomatic(ProtParticlePickingAuto, XmippProtocol):
"""Protocol to pick particles automatically in a set of
micrographs using previous training """
_label = 'auto-picking (step 2)'
filesToCopy = ['model_training.txt', 'model_svm.txt',
'model_pca_model.stk', 'model_rotpca_model.stk',
'model_particle_avg.xmp', 'config.xmd', 'templates.stk']
def __init__(self, **kwargs):
ProtParticlePickingAuto.__init__(self, **kwargs)
self.stepsExecutionMode = STEPS_PARALLEL
# --------------------------- DEFINE param functions -----------------------
def _defineParams(self, form):
form.addSection(label='Input')
form.addParam('xmippParticlePicking', PointerParam,
label="Xmipp particle picking run",
pointerClass='XmippProtParticlePicking',
#pointerCondition='isFinished',
help='Select the previous xmipp particle picking run.')
form.addParam('micsToPick', EnumParam,
choices=['Same as supervised', 'Other'],
default=0, label='Micrographs to pick',
display=EnumParam.DISPLAY_LIST,
help="Select from which set of micrographs to pick using "
"the training from supervised run."
"If you use Same as supervised, the same set of "
"micrographs used for training the picker will be "
"used at this point. If you select Other, you can "
"select another set of micrograph (normally from "
"the same specimen) and pick them completely "
"automatic using the trained picker.")
form.addParam('inputMicrographs', PointerParam,
pointerClass='SetOfMicrographs',
condition='micsToPick==%d' % MICS_OTHER,
label="Micrographs",
help="Select other set of micrographs to pick using the "
"trained picker.")
self._defineStreamingParams(form)
form.addParallelSection(threads=1, mpi=1)
# --------------------------- INSERT steps functions -----------------------
def _insertInitialSteps(self):
# Get pointer to input micrographs
self.particlePickingRun = self.xmippParticlePicking.get()
copyId = self._insertFunctionStep('copyInputFilesStep')
return [copyId]
# --------------------------- STEPS functions ------------------------------
[docs] def copyInputFilesStep(self):
# Copy training model files to current run
for f in self.filesToCopy:
copyFile(self.particlePickingRun._getExtraPath(f),
self._getExtraPath(f))
def _pickMicrograph(self, mic, *args):
micPath = mic.getFileName()
# Get particle picking boxsize from the previous run
boxSize = self.particlePickingRun.outputCoordinates.getBoxSize()
modelRoot = self._getExtraPath('model')
micName = removeBaseExt(micPath)
proceed = True
if self.micsToPick == MICS_SAMEASPICKING:
basePos = replaceBaseExt(micPath, "pos")
fnPos = self.particlePickingRun._getExtraPath(basePos)
if exists(fnPos):
blocks = emlib.getBlocksInMetaDataFile(fnPos)
copy = True
if 'header' in blocks:
mdheader = emlib.MetaData("header@" + fnPos)
state = mdheader.getValue(emlib.MDL_PICKING_MICROGRAPH_STATE,
mdheader.firstObject())
if state == "Available":
copy = False
if copy:
# Copy manual .pos file of this micrograph
copyFile(fnPos, self._getExtraPath(basename(fnPos)))
proceed = False
if proceed:
args = "-i %s " % micPath
args += "--particleSize %d " % boxSize
args += "--model %s " % modelRoot
args += "--outputRoot %s " % self._getExtraPath(micName)
args += "--mode autoselect --thr %d" % self.numberOfThreads
self.runJob("xmipp_micrograph_automatic_picking", args)
[docs] def readSetOfCoordinates(self, workingDir, coordSet):
readSetOfCoordinates(workingDir, self.getInputMicrographs(), coordSet)
[docs] def readCoordsFromMics(self, workingDir, micList, coordSet):
readSetOfCoordinates(workingDir, micList, coordSet)
# --------------------------- INFO functions -------------------------------
def _validate(self):
validateMsgs = []
if not hasattr(self.xmippParticlePicking.get(),"outputCoordinates"):
validateMsgs.append("You need to generate coordinates for the "
"supervised picking")
srcPaths = [self.xmippParticlePicking.get()._getExtraPath(k)
for k in self.filesToCopy]
# Check that all needed files exist
if missingPaths(*srcPaths):
validateMsgs.append('Input picking run has not been trained, '
'use *Autopick* for at least one micrograph')
# If other set of micrographs is provided they should have same
# sampling rate and acquisition
if self.micsToPick.get() == MICS_OTHER:
inputMics = self.inputMicrographs.get()
manualMics = self.xmippParticlePicking.get().inputMicrographs.get()
# FIXME: manualMics is always None when scheduled...
# it should be fixed in the update step at Scipion scheduler app
if manualMics is not None:
pixsizeInput = inputMics.getSamplingRate()
pixsizeMics = manualMics.getSamplingRate()
acq = manualMics.getAcquisition()
if pixsizeInput != pixsizeMics:
validateMsgs.append('New micrographs should have same sampling '
'rate as the ones already picked.')
if not inputMics.getAcquisition().equalAttributes(acq):
validateMsgs.append('New micrographs should have same '
'acquisition parameters as the ones '
'already picked.')
return validateMsgs
[docs] def getSummary(self, coordSet):
summary = []
summary.append("Previous run: %s" %
self.xmippParticlePicking.get().getNameId())
configfile = join(self._getExtraPath(), 'config.xmd')
existsConfig = exists(configfile)
if existsConfig:
md = emlib.MetaData('properties@' + configfile)
configobj = md.firstObject()
def _get(label):
return md.getValue(label, configobj)
pickingState = _get(emlib.MDL_PICKING_STATE)
particleSize = _get(emlib.MDL_PICKING_PARTICLE_SIZE)
activeMic = _get(emlib.MDL_MICROGRAPH)
isAutopick = pickingState != "Manual"
manualParticlesSize = _get(emlib.MDL_PICKING_MANUALPARTICLES_SIZE)
autoParticlesSize = _get(emlib.MDL_PICKING_AUTOPARTICLES_SIZE)
summary.append("Manual particles picked: %s" % manualParticlesSize)
summary.append("Particle size:%d" %(particleSize))
autopick = "Yes" if isAutopick else "No"
summary.append("Autopick: " + autopick)
if isAutopick:
summary.append("Automatic particles picked: %s"
% autoParticlesSize)
summary.append("Last micrograph: " + activeMic)
return "\n".join(summary)
[docs] def getMethods(self, output):
manualPickName = self.xmippParticlePicking.get().getNameId()
msg = 'Program picked %d particles ' % output.getSize()
msg += 'of size %d ' % output.getBoxSize()
msg += 'using training from %s. ' % manualPickName
msg += 'For more detail see [Abrishami2013]'
return msg
def _citations(self):
return ['Abrishami2013']
# --------------------------- UTILS functions ------------------------------
[docs] def getCoordsDir(self):
return self._getExtraPath()
[docs] def getInputMicrographsPointer(self):
# Get micrographs to pick
if self.micsToPick == MICS_SAMEASPICKING:
inputPicking = self.xmippParticlePicking.get()
return inputPicking.inputMicrographs if inputPicking else None
else:
return self.inputMicrographs
[docs] def getInputMicrographs(self):
""" Return the input micrographs that can be the same of the supervised
picking or other ones selected by the user. (This can be used to pick
a new set of micrographs with the same properties than a previous
trained ones. )
"""
return self.getInputMicrographsPointer().get() if self.getInputMicrographsPointer() else None