# *
# * Authors: Scipion Team
# *
# * 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-users@lists.sourceforge.net'
# *
# **************************************************************************
from enum import Enum
from pwem.protocols import EMProtocol
from pyworkflow import BETA
from pyworkflow.protocol import PointerParam, IntParam, GE, LE
from pyworkflow.utils import Message
from reliontomo.constants import OPTIMISATION_SET_STAR
from reliontomo.objects import relionTomoMetadata, SetOfPseudoSubtomograms
from reliontomo.utils import genOutputPseudoSubtomograms
[docs]class outputObjects(Enum):
outputRelionParticles = relionTomoMetadata
outputVolumes = SetOfPseudoSubtomograms
[docs]class ProtRelionPerParticlePerTiltBase(EMProtocol):
"""Base protocol used for the getting the frame alignment and ctf-refinment"""
_devStatus = BETA
_boxSize4Est = None
# -------------------------- DEFINE param functions -----------------------
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.inParticlesStar = None
def _defineParams(self, form):
form.addSection(label=Message.LABEL_INPUT)
form.addParam('inOptSet', PointerParam,
pointerClass='relionTomoMetadata',
label='Input Relion Tomo Metadata')
form.addParam('recVolume', PointerParam,
pointerClass='AverageSubTomogram',
allowsNull=False,
label='Volume to get the halves')
form.addParam('inRefMask', PointerParam,
pointerClass='VolumeMask',
label="Input reference mask")
@staticmethod
def _insertBoxSizeForEstimationParam(form):
form.addParam('boxSize', IntParam,
label='Box size for estimation (pix)',
default=128,
allowsNull=False,
validators=[GE(32), LE(512)],
help="Box size to be used for the estimation. Note that this can be larger than the box size "
"of the reference map. A sufficiently large box size allows more of the high-frequency "
"signal to be captured that has been delocalized by the CTF.")
# -------------------------- INSERT steps functions -----------------------
def _insertAllSteps(self):
pass
# -------------------------- UTILS functions -----------------------------
# def _initialize(self):
# self._findClosestAdmittedVal()
# self.inTomosStar = self._getExtraPath(IN_TOMOS_STAR)
# createLink(getFileFromDataPrepProt(self, OUT_TOMOS_STAR), self.inTomosStar)
# def convertInputStep(self):
# self.inParticlesStar = self._getExtraPath(IN_PARTICLES_STAR)
# writeSetOfPseudoSubtomograms(self.inPseudoSubtomos.get(), self.inParticlesStar)
[docs] def createOutputStep(self):
# Output pseudosubtomograms --> set of volumes for visualization purposes
outputSet = genOutputPseudoSubtomograms(self)
# Output RelionParticles
relionParticles = relionTomoMetadata(optimSetStar=self._getExtraPath(OPTIMISATION_SET_STAR),
tsSamplingRate=self.inOptSet.get().getTsSamplingRate(),
relionBinning=self.inOptSet.get().getRelionBinning(),
nParticles=outputSet.getSize())
self._defineOutputs(**{outputObjects.outputRelionParticles.name: relionParticles,
outputObjects.outputVolumes.name: outputSet})
# def _findClosestAdmittedVal(self):
# validVals = np.array(BOX_SIZE_VALS)
# # Find index of minimum value
# ind = np.where(validVals == np.amin(validVals - self.boxSize.get()))[0].tolist()[0]
# self._boxSize4Est = BOX_SIZE_VALS[ind]
def _genIOCommand(self):
optSet = self.inOptSet.get()
trajectories = optSet.getTrajectories()
postProcess = optSet.getReferenceFsc()
half1, half2 = self.recVolume.get().getHalfMaps().split(',')
cmd = '--p %s ' % optSet.getParticles()
cmd += '--t %s ' % optSet.getTomograms()
cmd += '--o %s ' % self._getExtraPath()
if trajectories:
cmd += '--mot %s ' % trajectories
cmd += '--ref1 %s ' % half1
cmd += '--ref2 %s ' % half2
cmd += '--mask %s ' % self.inRefMask.get().getFileName()
if postProcess:
cmd += '--fsc %s ' % postProcess
cmd += '--b %i ' % self.boxSize.get()
return cmd