# **************************************************************************
# *
# * Authors: Yunior C. Fonseca Reyna (cfonseca@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'
# *
# **************************************************************************
import os
import emtable
from pwem import ALIGN_PROJ
from pwem.protocols import ProtParticles
import pyworkflow.utils as pwutils
from pyworkflow import BETA
from pyworkflow.object import String
from pyworkflow.protocol.params import (PointerParam, FloatParam,
LEVEL_ADVANCED, IntParam, Positive)
from .protocol_base import ProtCryosparcBase
from .. import RELIONCOLUMNS
from ..convert import (defineArgs, convertCs2Star, createItemMatrix,
setCryosparcAttributes)
from ..utils import (addComputeSectionParams, cryosparcValidate, gpusValidate,
enqueueJob, waitForCryosparc, clearIntermediateResults,
copyFiles)
[docs]class ProtCryoSparcLocalCtfRefinement(ProtCryosparcBase, ProtParticles):
"""
Wrapper protocol for the Cryosparc's per-particle Local CTF refinement.
Performs per-particle defocus estimation for each particle in a dataset,
against a given 3D reference structure.
"""
_label = 'local ctf refinement'
_className = "ctf_refine_local"
def _initialize(self):
self._createFilenameTemplates()
def _createFilenameTemplates(self):
""" Centralize how files are called. """
myDict = {
'input_particles': self._getTmpPath('input_particles.star'),
'out_particles': self._getExtraPath('output_particle.star')
}
self._updateFilenamesDict(myDict)
def _defineParams(self, form):
form.addSection(label='Input')
form.addParam('inputParticles', PointerParam,
pointerClass='SetOfParticles',
pointerCondition='hasAlignmentProj',
label="Input particles", important=True,
help='Provide a set of particles for local '
'CTF refinement.')
form.addParam('refVolume', PointerParam, pointerClass='Volume',
important=True,
label="Input volume",
help='Provide a reference volume for local '
'CTF refinement.')
form.addParam('refMask', PointerParam, pointerClass='VolumeMask',
label='Mask to be applied to this map',
important=True,
help="Provide a soft mask. if mask is present, use that, "
"otherwise use mask_refine if present, otherwise "
"fail")
# -----------[Global CTF Refinement]------------------------
form.addSection(label="Local CTF Refinement")
form.addParam('crl_N', FloatParam, default=None,
allowsNull=True,
expertLevel=LEVEL_ADVANCED,
label='Refinement box size (Voxels)',
help='Size of reconstruction/image to use for refinement. '
'Blank means to use the particle box size '
'(upsampling input maps as needed)')
form.addParam('crl_num_plots', IntParam, default=50,
validators=[Positive],
label='Num. groups to plot',
help='Number of exposure groups to make plots for. '
'After this many, stop plotting to save time.')
form.addParam('crl_min_res_A', IntParam, default=20,
validators=[Positive],
label='Minimum Fit Res (A)',
help='The minimum resolution to use during refinement of '
'image aberrations.')
form.addParam('crl_max_res_A', FloatParam, default=None,
label='Maximum Fit Res (A)',
expertLevel=LEVEL_ADVANCED,
allowsNull=True,
help='The maximum resolution to use during refinement of '
'image aberrations. If None, use input half-maps '
'to compute FSC and set max to FSC=0.5')
form.addParam('crl_df_range', IntParam, default=2000,
label='Defocus Search Range (A +/-)',
help='Defocus search range in Angstroms, searching both '
'above and below the input defocus by this amount')
# --------------[Compute settings]---------------------------
form.addSection(label="Compute settings")
addComputeSectionParams(form, allowMultipleGPUs=False)
# --------------------------- INSERT steps functions -----------------------
def _insertAllSteps(self):
self._createFilenameTemplates()
self._defineParamsName()
self._initializeCryosparcProject()
self._insertFunctionStep(self.convertInputStep)
self._insertFunctionStep(self.processStep)
self._insertFunctionStep(self.createOutputStep)
# -------------------------- UTILS functions ------------------------------
def _defineParamsName(self):
""" Define a list with all protocol parameters names"""
self._paramsName = ['crl_N',
'crl_num_plots',
'crl_min_res_A',
'crl_max_res_A',
'crl_df_range',
'compute_use_ssd']
self.lane = str(self.getAttributeValue('compute_lane'))
def _getInputMask(self):
if self.refMask.get() is not None:
return self.refMask.get()
else:
inputProtocolMask = self._getInputPostProcessProtocol().refMask.get()
if inputProtocolMask is not None:
return inputProtocolMask
return None
# --------------------------- STEPS functions ------------------------------
[docs] def processStep(self):
print(pwutils.yellowStr("Local Ctf Refinement started..."), flush=True)
self.doLocalCtfRefinement()
[docs] def createOutputStep(self):
"""
Create the protocol output. Convert cryosparc file to Relion file
"""
self._initializeUtilsVariables()
outputStarFn = self._getFileName('out_particles')
csOutputFolder = os.path.join(self.projectPath, self.projectName.get(),
self.runLocalCtfRefinement.get())
csFileName = "particles.cs"
# Copy the CS output particles to extra folder
copyFiles(csOutputFolder, self._getExtraPath(), files=[csFileName])
csFile = os.path.join(self._getExtraPath(), csFileName)
argsList = [csFile, outputStarFn]
parser = defineArgs()
args = parser.parse_args(argsList)
convertCs2Star(args)
imgSet = self._getInputParticles()
outImgSet = self._createSetOfParticles()
outImgSet.copyInfo(imgSet)
self._fillDataFromIter(outImgSet)
self._defineOutputs(outputParticles=outImgSet)
self._defineTransformRelation(imgSet, outImgSet)
def _fillDataFromIter(self, imgSet):
outImgsFn = 'particles@' + self._getFileName('out_particles')
imgSet.setAlignmentProj()
imgSet.copyItems(self._getInputParticles(),
updateItemCallback=self._createItemMatrix,
itemDataIterator=emtable.Table.iterRows(outImgsFn))
def _createItemMatrix(self, particle, row):
createItemMatrix(particle, row, align=ALIGN_PROJ)
setCryosparcAttributes(particle, row,
RELIONCOLUMNS.rlnRandomSubset.value)
# --------------------------- INFO functions -------------------------------
def _validate(self):
""" Should be overwritten in subclasses to
return summary message for NORMAL EXECUTION.
"""
validateMsgs = cryosparcValidate()
if not validateMsgs:
validateMsgs = gpusValidate(self.getGpuList(), checkSingleGPU=True)
if not validateMsgs:
self._validateDim(self._getInputParticles(),
self._getInputVolume(),
validateMsgs, 'Input particles',
'Input volume')
return validateMsgs
def _summary(self):
summary = []
if not hasattr(self, 'outputParticles'):
summary.append("Output Particles not ready yet.")
else:
summary.append("Input Particles: %s" %
self.getObjectTag('inputParticles'))
summary.append("Reference Mask: %s" %
self.getObjectTag('refMask'))
summary.append("--------------------------------------------------")
summary.append("Output particles %s" %
self.getObjectTag('outputParticles'))
return summary
[docs] def doLocalCtfRefinement(self):
"""
:return:
"""
input_group_connect = {"particles": self.particles.get(),
"volume": self.volume.get(),
"mask": self.mask.get()}
input_result_connect = None
if self._getInputVolume().hasHalfMaps():
input_result_connect = {"volume.0.map_half_A": self.importVolumeHalfA.get(),
"volume.0.map_half_B": self.importVolumeHalfB.get()}
params = {}
for paramName in self._paramsName:
if (paramName != 'crl_max_res_A' and paramName != 'crl_N'):
params[str(paramName)] = str(self.getAttributeValue(paramName))
elif self.crl_max_res_A.get() is not None:
params[str(paramName)] = str(self.getAttributeValue(paramName))
elif self.crl_N.get() is not None:
params[str(paramName)] = str(self.getAttributeValue(paramName))
# Determinate the GPUs to use (in dependence of
# the cryosparc version)
try:
gpusToUse = self.getGpuList()
except Exception:
gpusToUse = False
runLocalCtfRefinementJob = enqueueJob(self._className, self.projectName.get(),
self.workSpaceName.get(),
str(params).replace('\'', '"'),
str(input_group_connect).replace('\'', '"'),
self.lane, gpusToUse,
result_connect=input_result_connect)
self.runLocalCtfRefinement = String(runLocalCtfRefinementJob.get())
self.currenJob.set(runLocalCtfRefinementJob.get())
self._store(self)
waitForCryosparc(self.projectName.get(), self.runLocalCtfRefinement.get(),
"An error occurred in the particles subtraction process. "
"Please, go to cryoSPARC software for more "
"details.")