def createOutputStep(self):
imgSet = self.inputParticles.get()
partSet = self._createSetOfParticles()
partSet.copyInfo(imgSet)
outImagesMd = self._getExtraPath('expanded_particles.star')
# remove repeating rlnImageId column
tableName = ''
if Plugin.IS_GT30():
tableName = 'particles'
mdOptics = Table(fileName=outImagesMd, tableName='optics')
mdOut = Table(fileName=outImagesMd, tableName=tableName)
mdOut.removeColumns("rlnImageId")
with open(outImagesMd, "w") as f:
mdOut.writeStar(f, tableName=tableName)
if Plugin.IS_GT30():
mdOptics.writeStar(f, tableName='optics')
reader = convert.createReader()
reader.readSetOfParticles(
outImagesMd, partSet,
alignType=ALIGN_PROJ,
postprocessImageRow=self._postprocessImageRow)
self._defineOutputs(outputParticles=partSet)
self._defineSourceRelation(imgSet, partSet)
def _insertReconstructStep(self):
imgSet = self.inputParticles.get()
params = ' --i %s' % self._getFileName('input_particles')
params += ' --o %s' % self._getFileName('output_volume')
params += ' --sym %s' % self.symmetryGroup.get()
params += ' --angpix %0.5f' % imgSet.getSamplingRate()
params += ' --maxres %0.3f' % self.maxRes.get()
params += ' --pad %0.3f' % self.pad.get()
subset = -1 if self.subset.get() == 0 else self.subset
params += ' --subset %d' % subset
if Plugin.IS_GT30():
params += ' --class %d' % self.classNum.get()
if self.doCTF:
params += ' --ctf'
if self.ctfIntactFirstPeak:
params += ' --ctf_intact_first_peak'
if imgSet.isPhaseFlipped():
params += ' --ctf_phase_flipped'
if self.extraParams.hasValue():
params += " " + self.extraParams.get()
self._insertFunctionStep('reconstructStep', params)
def _defineParamDict(self):
""" Define all parameters to run relion_postprocess"""
# It seems that in Relion3 now the input should be the map
# filename and not the prefix as before
inputFn = self._getFileName('half1')
self.paramDict = {'--i': inputFn,
'--o': self._getExtraPath('postprocess'),
'--angpix': self._getOutputPixelSize(),
# Expert params
'--filter_edge_width': self.filterEdgeWidth.get(),
'--randomize_at_fsc': self.randomizeAtFsc.get(),
'--mask': self._getFileName('mask')
}
mtfFile = self.mtf.get()
if mtfFile:
self.paramDict['--mtf'] = mtfFile
if self.doAutoBfactor:
self.paramDict['--auto_bfac'] = ''
self.paramDict['--autob_lowres'] = self.bfactorLowRes.get()
self.paramDict['--autob_highres'] = self.bfactorHighRes.get()
else:
self.paramDict['--adhoc_bfac'] = self.bfactor.get()
if self.skipFscWeighting:
self.paramDict['--skip_fsc_weighting'] = ''
self.paramDict['--low_pass'] = self.lowRes.get()
if Plugin.IS_GT30() and self.origPixelSize.get() != -1.0:
self.paramDict['--mtf_angpix'] = self.origPixelSize.get()
def _getMdOut(self, it, prefix, ref3d):
randomSet = self._getRandomSet(prefix)
dataStar = self._getDataStar(prefix, it)
tableName = 'particles' if Plugin.IS_GT30() else None
mdOut = []
table = Table(fileName=dataStar, tableName=tableName)
for row in table:
if 0 < randomSet < 3:
if int(row.rlnRandomSubset) == randomSet and int(
row.rlnClassNumber) == ref3d:
mdOut.append(row)
else:
if int(row.rlnClassNumber) == ref3d:
mdOut.append(row)
return mdOut
def test_fromStar(self):
if not Plugin.IS_GT30():
print("Skipping test (required Relion > 3.1)")
return
partsStar = self.ds.getFile("Extract/job018/particles.star")
print("<<< Reading optics groups from file: \n %s\n" % partsStar)
og = OpticsGroups.fromStar(partsStar)
fog = og.first()
# test hasColumn method
for colName in ['rlnMtfFileName', 'rlnOpticsGroupName']:
self.assertTrue(og.hasColumn(colName))
# acq = first.getAcquisition()
self.assertEqual(fog.rlnMtfFileName, 'mtf_k2_200kV.star')
self.assertEqual(fog.rlnOpticsGroupName, 'opticsGroup1')
self.assertEqual(og['opticsGroup1'], fog)
def _defineParams(self, form):
form.addSection(label='Input')
form.addParam('inputParticles', PointerParam,
pointerClass='SetOfParticles',
pointerCondition='hasAlignmentProj',
label="Input particles",
help='Select the input images from the project.')
form.addParam('symmetryGroup', StringParam, default='c1',
label="Symmetry group",
help='See [[Relion Symmetry][http://www2.mrc-lmb.cam.ac.uk/'
'relion/index.php/Conventions_%26_File_formats#Symmetry]] '
'page for a description of the symmetry format '
'accepted by Relion')
form.addParam('maxRes', FloatParam, default=-1,
label="Maximum resolution (A)",
help='Maximum resolution (in Angstrom) to consider \n'
'in Fourier space (default Nyquist).')
form.addParam('pad', FloatParam, default=2,
label="Padding factor")
form.addParam('subset', EnumParam, default=0,
choices=['all', 'half1', 'half2'],
display=EnumParam.DISPLAY_HLIST,
label='Subset to reconstruct',
help='Subset of images to consider.')
if Plugin.IS_GT30():
form.addParam('classNum', IntParam, default=-1,
label='Use only this class',
help='Consider only this class (-1: use all classes)')
form.addParam('extraParams', StringParam, default='',
expertLevel=LEVEL_ADVANCED,
label='Extra parameters: ',
help='Extra parameters to *relion_reconstruct* program. '
'Address to Relion to see full list of options.')
form.addSection('CTF')
form.addParam('doCTF', BooleanParam, default=False,
label='Apply CTF correction?')
form.addParam('ctfIntactFirstPeak', BooleanParam, default=False,
condition='doCTF',
label='Leave CTFs intact until first peak?')
form.addParallelSection(threads=0, mpi=1)
def test_readSetOfParticles(self):
if not Plugin.IS_GT30():
print("Skipping test (required Relion > 3.1)")
return
partsSet = self.__readParticles(
self.ds.getFile("Extract/job018/particles.star"),
extraLabels=['rlnNrOfSignificantSamples'])
partsSet.write()
first = partsSet.getFirstItem()
first.printAll()
self.assertAlmostEqual(first.getSamplingRate(), 1.244531)
self.assertEqual(first.getClassId(), 4)
self.assertTrue(hasattr(first, '_rlnNrOfSignificantSamples'))
fog = OpticsGroups.fromImages(partsSet).first()
self.assertEqual(fog.rlnMtfFileName, 'mtf_k2_200kV.star')
self.assertEqual(fog.rlnOpticsGroupName, 'opticsGroup1')
def test_readSetOfParticlesAfterCtf(self):
if not Plugin.IS_GT30():
print("Skipping test (required Relion > 3.1)")
return
starFile = self.ds.getFile(
"CtfRefine/job023/particles_ctf_refine.star")
partsReader = Table.Reader(starFile, tableName='particles')
firstRow = partsReader.getRow()
partsSet = self.__readParticles(starFile)
first = partsSet.getFirstItem()
ogLabels = ['rlnBeamTiltX', 'rlnBeamTiltY']
extraLabels = ['rlnCtfBfactor', 'rlnCtfScalefactor', 'rlnPhaseShift']
for l in extraLabels:
value = getattr(first, '_%s' % l)
self.assertIsNotNone(value, "Missing label: %s" % l)
self.assertAlmostEqual(getattr(firstRow, l), value)
fog = OpticsGroups.fromImages(partsSet).first()
self.assertTrue(all(hasattr(fog, l) for l in ogLabels))
# Also test writing and preserving extra labels
outputStar = self.getOutputPath('particles.star')
print(">>> Writing to particles star: %s" % outputStar)
starWriter = convert.createWriter()
starWriter.writeSetOfParticles(partsSet, outputStar)
fog = OpticsGroups.fromStar(outputStar).first()
self.assertTrue(all(hasattr(fog, l) for l in ogLabels))
partsReader = Table.Reader(outputStar, tableName='particles')
firstRow = partsReader.getRow()
for l in extraLabels:
value = getattr(first, '_%s' % l)
self.assertIsNotNone(value, "Missing label: %s" % l)
self.assertAlmostEqual(getattr(firstRow, l), value)
def test_string(self):
if not Plugin.IS_GT30():
print("Skipping test (required Relion > 3.1)")
return
og = OpticsGroups.create(rlnMtfFileName='mtf_k2_200kV.star')
fog = og.first()
# acq = first.getAcquisition()
self.assertEqual(fog.rlnMtfFileName, 'mtf_k2_200kV.star')
self.assertEqual(fog.rlnOpticsGroupName, 'opticsGroup1')
self.assertEqual(og['opticsGroup1'], fog)
# try update by id
og.update(1, rlnMtfFileName="new_mtf_k2.star")
# try update by name
og.update('opticsGroup1', rlnImageSize=512)
fog = og.first()
# acq = first.getAcquisition()
self.assertEqual(fog.rlnMtfFileName, 'new_mtf_k2.star')
self.assertEqual(fog.rlnImageSize, 512)
self.assertEqual(fog.rlnOpticsGroupName, 'opticsGroup1')
self.assertEqual(og['opticsGroup1'], fog)
class ProtRelionRefine3D(ProtRefine3D, ProtRelionBase):
""" Protocol to refine a 3D map using Relion.
Relion employs an empirical Bayesian approach to refinement
of (multiple) 3D reconstructions
or 2D class averages in electron cryo-microscopy (cryo-EM). Many
parameters of a statistical model are learned from the data,which
leads to objective and high-quality results.
"""
_label = '3D auto-refine'
IS_CLASSIFY = False
CHANGE_LABELS = ['rlnChangesOptimalOrientations',
'rlnChangesOptimalOffsets',
'rlnOverallAccuracyRotations',
'rlnOverallAccuracyTranslationsAngst' if Plugin.IS_GT30() else 'rlnOverallAccuracyTranslations']
PREFIXES = ['half1_', 'half2_']
def __init__(self, **args):
ProtRelionBase.__init__(self, **args)
def _initialize(self):
""" This function is mean to be called after the
working dir for the protocol have been set.
(maybe after recovery from mapper)
"""
ProtRelionBase._initialize(self)
self.ClassFnTemplate = '%(ref)03d@%(rootDir)s/relion_it%(iter)03d_classes.mrcs'
# -------------------------- INSERT steps functions -----------------------
def _setSamplingArgs(self, args):
""" Set sampling related params"""
args['--auto_local_healpix_order'] = self.localSearchAutoSamplingDeg.get()
if not self.doContinue:
args['--healpix_order'] = self.angularSamplingDeg.get()
args['--offset_range'] = self.offsetSearchRangePix.get()
f = self._getSamplingFactor()
args['--offset_step'] = self.offsetSearchStepPix.get() * f
args['--auto_refine'] = ''
args['--split_random_halves'] = ''
joinHalves = "--low_resol_join_halves"
if joinHalves not in self.extraParams.get():
args['--low_resol_join_halves'] = 40
if self.IS_GT30() and self.useFinerSamplingFaster:
args['--auto_ignore_angles'] = ''
args['--auto_resol_angles'] = ''
# -------------------------- STEPS functions ------------------------------
def createOutputStep(self):
imgSet = self._getInputParticles()
vol = Volume()
vol.setFileName(self._getExtraPath('relion_class001.mrc'))
vol.setSamplingRate(imgSet.getSamplingRate())
half1 = self._getFileName("final_half1_volume", ref3d=1)
half2 = self._getFileName("final_half2_volume", ref3d=1)
vol.setHalfMaps([half1, half2])
outImgSet = self._createSetOfParticles()
outImgSet.copyInfo(imgSet)
self._fillDataFromIter(outImgSet, self._lastIter())
self._defineOutputs(outputVolume=vol)
self._defineSourceRelation(self.inputParticles, vol)
self._defineOutputs(outputParticles=outImgSet)
self._defineTransformRelation(self.inputParticles, outImgSet)
fsc = FSC(objLabel=self.getRunName())
fn = self._getExtraPath("relion_model.star")
table = Table(fileName=fn, tableName='model_class_1')
resolution_inv = table.getColumnValues('rlnResolution')
frc = table.getColumnValues('rlnGoldStandardFsc')
fsc.setData(resolution_inv, frc)
self._defineOutputs(outputFSC=fsc)
self._defineSourceRelation(vol, fsc)
# -------------------------- INFO functions -------------------------------
def _validateNormal(self):
errors = []
if self.IS_3D and self.solventFscMask and not self.referenceMask.get():
errors.append('When using solvent-corrected FSCs, '
'please provide a reference mask.')
return errors
def _validateContinue(self):
errors = []
continueRun = self.continueRun.get()
continueRun._initialize()
lastIter = continueRun._lastIter()
if self.continueIter.get() == 'last':
continueIter = lastIter
else:
continueIter = int(self.continueIter.get())
if continueIter > lastIter:
errors += ["You can continue only from the iteration %01d or less" % lastIter]
return errors
def _summaryNormal(self):
summary = []
if not hasattr(self, 'outputVolume'):
summary.append("Output volume not ready yet.")
it = self._lastIter() or -1
if it >= 1 and it > self._getContinueIter():
table = Table(fileName=self._getFileName('half1_model', iter=it),
tableName='model_general')
row = table[0]
resol = float(row.rlnCurrentResolution)
summary.append("Current resolution: *%0.2f A*" % resol)
else:
table = Table(fileName=self._getFileName('modelFinal'),
tableName='model_general')
row = table[0]
resol = float(row.rlnCurrentResolution)
summary.append("Final resolution: *%0.2f A*" % resol)
return summary
def _summaryContinue(self):
return ["Continue from iteration %01d" % self._getContinueIter()]
# -------------------------- UTILS functions ------------------------------
def _fillDataFromIter(self, imgSet, iteration):
tableName = 'particles@' if self.IS_GT30() else ''
outImgsFn = self._getFileName('data', iter=iteration)
imgSet.setAlignmentProj()
self.reader = convert.createReader(alignType=ALIGN_PROJ,
pixelSize=imgSet.getSamplingRate())
mdIter = Table.iterRows(tableName + outImgsFn, key='rlnImageId')
imgSet.copyItems(self._getInputParticles(), doClone=False,
updateItemCallback=self._updateParticle,
itemDataIterator=mdIter)
def _updateParticle(self, particle, row):
self.reader.setParticleTransform(particle, row)
if getattr(self, '__updatingFirst', True):
self.reader.createExtraLabels(particle, row, PARTICLE_EXTRA_LABELS)
self.__updatingFirst = False
else:
self.reader.setExtraLabels(particle, row)
def IS_GT30(self):
return Plugin.IS_GT30()
class ProtRelionClassify3D(ProtClassify3D, ProtRelionBase):
"""
Protocol to classify 3D using Relion Bayesian approach.
Relion employs an empirical Bayesian approach to refinement of (multiple)
3D reconstructions or 2D class averages in electron cryo-EM. Many
parameters of a statistical model are learned from the data, which
leads to objective and high-quality results.
"""
_label = '3D classification'
CHANGE_LABELS = ['rlnChangesOptimalOrientations',
'rlnChangesOptimalOffsets',
'rlnOverallAccuracyRotations',
'rlnOverallAccuracyTranslationsAngst' if Plugin.IS_GT30() else 'rlnOverallAccuracyTranslations',
'rlnChangesOptimalClasses']
def __init__(self, **args):
ProtRelionBase.__init__(self, **args)
def _initialize(self):
""" This function is mean to be called after the
working dir for the protocol have been set.
(maybe after recovery from mapper)
"""
ProtRelionBase._initialize(self)
# -------------------------- INSERT steps functions -----------------------
def _setSamplingArgs(self, args):
""" Set sampling related params. """
if self.doImageAlignment:
args['--healpix_order'] = self.angularSamplingDeg.get()
args['--offset_range'] = self.offsetSearchRangePix.get()
args['--offset_step'] = self.offsetSearchStepPix.get() * self._getSamplingFactor()
if self.localAngularSearch:
args['--sigma_ang'] = self.localAngularSearchRange.get() / 3.
if relion.Plugin.IS_GT30() and self.allowCoarserSampling:
args['--allow_coarser_sampling'] = ''
else:
args['--skip_align'] = ''
# -------------------------- STEPS functions ------------------------------
def createOutputStep(self):
partSet = self.inputParticles.get()
classes3D = self._createSetOfClasses3D(partSet)
self._fillClassesFromIter(classes3D, self._lastIter())
self._defineOutputs(outputClasses=classes3D)
self._defineSourceRelation(self.inputParticles, classes3D)
# create a SetOfVolumes and define its relations
volumes = self._createSetOfVolumes()
volumes.setSamplingRate(partSet.getSamplingRate())
for class3D in classes3D:
vol = class3D.getRepresentative()
vol.setObjId(class3D.getObjId())
volumes.append(vol)
self._defineOutputs(outputVolumes=volumes)
self._defineSourceRelation(self.inputParticles, volumes)
if not self.doContinue:
self._defineSourceRelation(self.referenceVolume, classes3D)
self._defineSourceRelation(self.referenceVolume, volumes)
# -------------------------- INFO functions -------------------------------
def _validateNormal(self):
errors = []
return errors
def _validateContinue(self):
errors = []
continueRun = self.continueRun.get()
continueRun._initialize()
lastIter = continueRun._lastIter()
if self.continueIter.get() == 'last':
continueIter = lastIter
else:
continueIter = int(self.continueIter.get())
if continueIter > lastIter:
errors += ["You can continue only from the iteration %01d or less" % lastIter]
return errors
def _summaryNormal(self):
summary = []
it = self._lastIter() or -1
if it >= 1:
table = Table(fileName=self._getFileName('model', iter=it),
tableName='model_general')
row = table[0]
resol = float(row.rlnCurrentResolution)
summary.append("Current resolution: *%0.2f A*" % resol)
inputParts = self.inputParticles.get()
sizeStr = 'None' if inputParts is None else inputParts.getSize()
summary.append("Input Particles: *%s*\n"
"Classified into *%d* 3D classes\n"
% (sizeStr, self.numberOfClasses))
return summary
def _summaryContinue(self):
summary = list()
summary.append("Continue from iteration %01d" % self._getContinueIter())
return summary
def _methods(self):
strline = ''
if hasattr(self, 'outputClasses'):
strline += 'We classified %d particles into %d 3D classes using Relion Classify3d. ' %\
(self.inputParticles.get().getSize(), self.numberOfClasses.get())
return [strline]
# -------------------------- UTILS functions ------------------------------
def _fillClassesFromIter(self, clsSet, iteration):
""" Create the SetOfClasses3D from a given iteration. """
classLoader = convert.ClassesLoader(self, ALIGN_PROJ)
classLoader.fillClassesFromIter(clsSet, iteration)
def _plotClassDistribution(self, paramName=None):
labels = ["rlnClassDistribution", "rlnAccuracyRotations"]
if Plugin.IS_GT30():
labels.append("rlnAccuracyTranslationsAngst")
else:
labels.append("rlnAccuracyTranslations")
iterations = range(self.firstIter, self.lastIter + 1)
classInfo = {}
for it in iterations:
modelStar = self.protocol._getFileName('model', iter=it)
table = Table(fileName=modelStar, tableName='model_classes')
for row in table:
i, fn = relionToLocation(row.rlnReferenceImage)
if i == NO_INDEX: # the case for 3D classes
# NOTE: Since there is not an proper ID value in
# the classes metadata, we are assuming that class X
# has a filename *_classXXX.mrc (as it is in Relion)
# and we take the ID from there
index = int(fn[-7:-4])
else:
index = i
if index not in classInfo:
classInfo[index] = {}
for l in labels:
classInfo[index][l] = []
for l in labels:
classInfo[index][l].append(float(getattr(row, l)))
xplotter = RelionPlotter()
xplotter.createSubPlot("Classes distribution over iterations",
"Iterations", "Classes Distribution")
# Empty list for each iteration
iters = [[]] * len(iterations)
l = labels[0]
for index in sorted(classInfo.keys()):
for it, value in enumerate(classInfo[index][l]):
iters[it].append(value)
ax = xplotter.getLastSubPlot()
n = len(iterations)
ind = range(n)
bottomValues = [0] * n
width = 0.45 # the width of the bars: can also be len(x) sequence
def get_cmap(N):
import matplotlib.cm as cmx
import matplotlib.colors as colors
"""Returns a function that maps each index in 0, 1, ... N-1 to a distinct
RGB color."""
color_norm = colors.Normalize(vmin=0, vmax=N) # -1)
scalar_map = cmx.ScalarMappable(norm=color_norm, cmap='hsv')
def map_index_to_rgb_color(ind):
return scalar_map.to_rgba(ind)
return map_index_to_rgb_color
cmap = get_cmap(len(classInfo))
for classId in sorted(classInfo.keys()):
values = classInfo[classId][l]
ax.bar(ind,
values,
width,
label='class %s' % classId,
bottom=bottomValues,
color=cmap(classId))
bottomValues = [a + b for a, b in zip(bottomValues, values)]
ax.get_xaxis().set_ticks([i + 0.25 for i in ind])
ax.get_xaxis().set_ticklabels([str(i) for i in ind])
ax.legend(loc='upper left', fontsize='xx-small')
return [xplotter]
def _defineParams(self, form):
form.addSection(label='Input')
form.addParam('protRefine', params.PointerParam,
pointerClass="ProtRefine3D",
label='Select a previous refinement protocol',
help='Select any previous refinement protocol to get the '
'3D half maps. Note that it is recommended that the '
'refinement protocol uses a gold-standard method.')
form.addParam('solventMask', params.PointerParam,
pointerClass="VolumeMask",
label='Solvent mask',
help="Provide a soft mask where the protein is white "
"(1) and the solvent is black (0). Often, the "
"softer the mask the higher resolution estimates "
"you will get. A soft edge of 5-10 pixels is often "
"a good edge width.")
form.addParam('calibratedPixelSize', params.FloatParam, default=0,
label='Calibrated pixel size (A)',
help="Provide the final, calibrated pixel size in "
"Angstroms. If 0, the input pixel size will be used. "
"This value may be different from the pixel-size "
"used thus far, e.g. when you have recalibrated "
"the pixel size using the fit to a PDB model. "
"The X-axis of the output FSC plot will use this "
"calibrated value.")
form.addSection(label='Sharpening')
group = form.addGroup('MTF')
group.addParam('mtf', params.FileParam,
label='MTF of the detector',
help='User-provided STAR-file with the MTF-curve '
'of the detector. Use the wizard to load one '
'of the predefined ones provided at:\n'
'- [[https://www3.mrc-lmb.cam.ac.uk/relion/index.php/'
'FAQs#Where_can_I_find_MTF_curves_for_typical_detectors.3F]'
'[Relion\'s Wiki FAQs]]\n'
' - [[https://www.gatan.com/techniques/cryo-em#MTF][Gatan\'s website]]\n\n'
'Relion param: *--mtf*')
if Plugin.IS_GT30():
group.addParam('origPixelSize', params.FloatParam,
default=-1.0,
label='Original detector pixel size (A)',
help='This is the original pixel size (in Angstroms)'
' in the raw (non-super-resolution!) micrographs')
form.addParam('doAutoBfactor', params.BooleanParam, default=True,
label='Estimate B-factor automatically?',
help='If set to Yes, then the program will use the '
'automated procedure described by Rosenthal and '
'Henderson (2003, JMB) to estimate an overall '
'B-factor for your map, and sharpen it accordingly.')
line = form.addLine('B-factor resolution (A): ',
condition='doAutoBfactor',
help='There are the frequency (in Angstroms), '
'lowest and highest, that will be included in '
'the linear fit of the Guinier plot as '
'described in Rosenthal and Henderson '
'(2003, JMB).')
line.addParam('bfactorLowRes', params.FloatParam,
default=10.0, label='low')
line.addParam('bfactorHighRes', params.FloatParam,
default=0.0, label='high')
form.addParam('bfactor', params.FloatParam, default=-350,
condition='not doAutoBfactor',
label='Provide B-factor:',
help='User-provided B-factor (in A^2) for map '
'sharpening, e.g. -400. Use negative values for '
'sharpening. Be careful: if you over-sharpen\n'
'your map, you may end up interpreting noise for '
'signal!\n'
'Relion param: *--adhoc_bfac*')
form.addSection(label='Filtering')
form.addParam('skipFscWeighting', params.BooleanParam, default=False,
label='Skip FSC-weighting for sharpening?',
help='If set to No (the default), then the output map '
'will be low-pass filtered according to the '
'mask-corrected, gold-standard FSC-curve. '
'Sometimes, it is also useful to provide an ad-hoc '
'low-pass filter (option below), as due to local '
'resolution variations some parts of the map may '
'be better and other parts may be worse than the '
'overall resolution as measured by the FSC. In '
'such cases, set this option to Yes and provide '
'an ad-hoc filter as described below.')
form.addParam('lowRes', params.FloatParam, default=5,
condition='skipFscWeighting',
label='Ad-hoc low-pass filter (A):',
help='This option allows one to low-pass filter the map '
'at a user-provided frequency (in Angstroms). When '
'using a resolution that is higher than the '
'gold-standard FSC-reported resolution, take care '
'not to interpret noise in the map for signal...')
form.addParam('filterEdgeWidth', params.IntParam, default=2,
expertLevel=params.LEVEL_ADVANCED,
label='Low-pass filter edge width:',
help='Width of the raised cosine on the low-pass filter '
'edge (in resolution shells)\n'
'Relion param: *--filter_edge_width*')
form.addParam('randomizeAtFsc', params.FloatParam, default=0.8,
expertLevel=params.LEVEL_ADVANCED,
label='Randomize phases threshold',
help='Randomize phases from the resolution where FSC '
'drops below this value\n'
'Relion param: *--randomize_at_fsc*')
form.addParallelSection(threads=0, mpi=1)