def fromXML(self, xmlObj):
from lxml.etree import _Element
if xmlObj.__class__ != _Element:
raise Exception('You must provide a valid XML object.')
if xmlObj.tag == "CTFCorrectionJob":
jobDescription = xmlObj
else:
jobDescription = xmlObj.xpath('CTFCorrectionJob')
if len(jobDescription) == 0:
raise Exception("This XML is not a CTFCorrectionJob.")
jobDescription = jobDescription[0]
from pytom.basic.structures import ParticleList, Reference, Mask, SampleInformation
particleList_element = jobDescription.xpath('ParticleList')[0]
pl = ParticleList('.')
pl.fromXML(particleList_element)
self.particleList = pl
self.reference = []
r = jobDescription.xpath('Reference')
for ref_obj in r:
ref = Reference('')
ref.fromXML(ref_obj)
self.reference.append(ref)
m = jobDescription.xpath('Mask')[0]
self.mask = Mask('')
self.mask.fromXML(m)
try:
si = jobDescription.xpath('SampleInformation')[0]
self.sampleInformation = SampleInformation()
self.sampleInformation.fromXML(si)
except:
self._sampleInformation = SampleInformation()
self.ctf_conv_pl = jobDescription.get('CTFConvolutedParticleList')
self.peak_offset = int(jobDescription.get('PeakOffset'))
self.bw_range = [
int(i)
for i in jobDescription.get('BandwidthRange')[1:-1].split(',')
]
self.freq = int(jobDescription.get('Frequency'))
self.destination = jobDescription.get('Destination')
self.max_iter = int(jobDescription.get('MaxIterations'))
self.r_score = jobDescription.get('RScore') == 'True'
self.weighting = jobDescription.get('WeightedAverage') == 'True'
self.bfactor = jobDescription.get('BFactor')
self.sum_ctf_sqr = jobDescription.get('CTFSquared')
raise RuntimeError('Destination directory ' + destination +
' does not exist!')
from pytom.cluster.mcoEXMXStructures import MCOEXMXJob
from pytom.basic.structures import ParticleList, Reference, Mask, Wedge, SampleInformation, PointSymmetry
from pytom.score.score import FLCFScore
from pytom.frontend.serverpages.createMCOEXMXJob import createRunscripts
from pytom.alignment.preprocessing import Preprocessing
p = ParticleList()
p.fromXMLFile(particleList)
m = Mask(mask)
w = Wedge([float(wedge1), float(wedge2)])
pre = Preprocessing(lowestFrequency=float(lowestFrequency),
highestFrequency=float(highestFrequency))
sample = SampleInformation(pixelSize=float(pixelSize),
particleDiameter=float(diameter))
if symmetryN is None or symmetryAxisZ is None or symmetryAxisX is None:
sym = None
else:
sym = PointSymmetry(nfold=int(symmetryN),
z2=float(symmetryAxisZ),
x=float(symmetryAxisX))
job = MCOEXMXJob(particleList=p,numberIterations=numberIterations,\
destinationDirectory=destination,mask=mask,score=FLCFScore(),preprocessing=pre,\
wedgeInfo=w,binning=int(binning),sampleInformation=sample,numberClasses=int(numberClasses),\
endThreshold=float(endThreshold),symmetry = sym,doAlignment = False,frmBandwidth = None)
job.toXMLFile(jobName)
def fromXML(self, xmlObj):
"""
read from xml file
@param xmlObj: xml object
@type xmlObj: L{lxml.etree.Element}
"""
from lxml.etree import _Element
if xmlObj.__class__ != _Element:
raise Exception('You must provide a valid XML object.')
if xmlObj.tag == "FRMJob":
jobDescription = xmlObj
else:
jobDescription = xmlObj.xpath('FRMJob')
if len(jobDescription) == 0:
raise Exception("This XML is not a FRMJob.")
jobDescription = jobDescription[0]
from pytom.basic.structures import ParticleList, Reference, Mask, SampleInformation, MultiSymmetries
pl = ParticleList('.')
particleList_element = jobDescription.xpath('ParticleList')
if len(particleList_element) > 0:
pl.fromXML(particleList_element[0])
else:
list_elements = jobDescription.xpath('ParticleListLocation')
for e in list_elements:
sub_pl = ParticleList()
sub_pl.fromXMLFile(e.get('Path'))
pl += sub_pl
self.particleList = pl
r = jobDescription.xpath('Reference')[0]
self.reference = Reference('')
self.reference.fromXML(r)
m = jobDescription.xpath('Mask')[0]
self.mask = Mask('')
self.mask.fromXML(m)
try:
si = jobDescription.xpath('SampleInformation')[0]
self.sampleInformation = SampleInformation()
self.sampleInformation.fromXML(si)
except:
self.sampleInformation = SampleInformation()
try:
syms = jobDescription.xpath('MultiSymmetries')[0]
self.symmetries = MultiSymmetries()
self.symmetries.fromXML(syms)
except:
self.symmetries = MultiSymmetries()
self.peak_offset = int(jobDescription.get('PeakOffset'))
self.bw_range = [
int(i)
for i in jobDescription.get('BandwidthRange')[1:-1].split(',')
]
self.freq = int(jobDescription.get('Frequency'))
self.destination = jobDescription.get('Destination')
self.max_iter = int(jobDescription.get('MaxIterations'))
self.r_score = jobDescription.get('RScore') == 'True'
self.weighting = jobDescription.get('WeightedAverage') == 'True'
self.bfactor = jobDescription.get('BFactor')
self.binning = int(jobDescription.get('binning'))
if jobDescription.get('AdaptiveResolution'):
adaptive_resolution = jobDescription.get('AdaptiveResolution')
if adaptive_resolution == '+1':
self.adaptive_res = False # always increase by 1
else:
self.adaptive_res = float(adaptive_resolution)
else:
self.adaptive_res = 0.0 # default, if not specified
if jobDescription.get('FSC'):
self.fsc_criterion = float(jobDescription.get('FSC'))
else:
self.fsc_criterion = 0.5 # default value
# for the constraint
try:
from sh_alignment.constrained_frm import AngularConstraint
con = jobDescription.xpath('AngularConstraint')
if len(con) != 0:
ac = AngularConstraint()
c = ac.fromXML(con[0])
self.constraint = c
else:
self.constraint = None
except:
self.constraint = None
class FRMJob(PyTomClass): # i need to rename the class, but for now it works
def __init__(self,
pl=None,
ref=None,
mask=None,
peak_offset=0,
sample_info=None,
bw_range=None,
freq=None,
dest='.',
max_iter=10,
r_score=False,
weighting=False,
bfactor=None,
symmetries=None,
adaptive_res=0.1,
fsc_criterion=0.5,
constraint=None,
binning=1):
"""
initiate FRM job
@param pl: particle list
@type ps: L{pytom.basic.structures.ParticleList}
@param ref: reference density
@type ref: L{pytom.basic.structures.Reference}
@param mask: mask
@type ref: L{pytom.basic.structures.Mask}
@param peak_offset: peak offset in voxel
@type peak_offset: C{int}
@param sample_info: ?? (Default: None)
@type sample_info: ??
@param bw_range: bandwidth range in pixel (2-dim vector)
@type bw_range: C{list}
@param freq: frequency (default: None)
@type: C{int}
@param dest: distination directory (default: '.')
@type: C{str}
@param max_iter: maximum number of iterations
@type max_iter: C{int}
@param r_score: use r_score (??) (default: False)
@type r_score: C{bool}
@param weighting: weighting (default: False)
@type weighting: C{bool}
@param bfactor: B-factor (default: None)
@type bfactor: C{float}?
@param symmetries: symmetry (default: None)
@type L{pytom.basic.structures.Symmetries}
@param adaptive_res: adaptive resolution - add to resolution for filtering
@type adaptive_res: C{float}
@param fsc_criterion: FSC criterion (default: 0.5)
@type fsc_criterion: C{float}
@param constraint: Constraint on orientations (deafult: None)
@type constraint: ??
@param binning: Perform binning (downscale) of subvolumes by factor. Default=1.
@type binning C{float}
"""
self.particleList = pl
self.reference = ref
self.mask = mask
self.peak_offset = peak_offset
self.sampleInformation = sample_info
self.bw_range = bw_range
self.freq = freq
self.destination = dest
self.max_iter = max_iter
self.r_score = r_score
self.weighting = weighting
self.bfactor = bfactor
self.symmetries = symmetries
self.adaptive_res = adaptive_res
self.fsc_criterion = fsc_criterion
self.constraint = constraint
self.binning = binning
def fromXML(self, xmlObj):
"""
read from xml file
@param xmlObj: xml object
@type xmlObj: L{lxml.etree.Element}
"""
from lxml.etree import _Element
if xmlObj.__class__ != _Element:
raise Exception('You must provide a valid XML object.')
if xmlObj.tag == "FRMJob":
jobDescription = xmlObj
else:
jobDescription = xmlObj.xpath('FRMJob')
if len(jobDescription) == 0:
raise Exception("This XML is not a FRMJob.")
jobDescription = jobDescription[0]
from pytom.basic.structures import ParticleList, Reference, Mask, SampleInformation, MultiSymmetries
pl = ParticleList('.')
particleList_element = jobDescription.xpath('ParticleList')
if len(particleList_element) > 0:
pl.fromXML(particleList_element[0])
else:
list_elements = jobDescription.xpath('ParticleListLocation')
for e in list_elements:
sub_pl = ParticleList()
sub_pl.fromXMLFile(e.get('Path'))
pl += sub_pl
self.particleList = pl
r = jobDescription.xpath('Reference')[0]
self.reference = Reference('')
self.reference.fromXML(r)
m = jobDescription.xpath('Mask')[0]
self.mask = Mask('')
self.mask.fromXML(m)
try:
si = jobDescription.xpath('SampleInformation')[0]
self.sampleInformation = SampleInformation()
self.sampleInformation.fromXML(si)
except:
self.sampleInformation = SampleInformation()
try:
syms = jobDescription.xpath('MultiSymmetries')[0]
self.symmetries = MultiSymmetries()
self.symmetries.fromXML(syms)
except:
self.symmetries = MultiSymmetries()
self.peak_offset = int(jobDescription.get('PeakOffset'))
self.bw_range = [
int(i)
for i in jobDescription.get('BandwidthRange')[1:-1].split(',')
]
self.freq = int(jobDescription.get('Frequency'))
self.destination = jobDescription.get('Destination')
self.max_iter = int(jobDescription.get('MaxIterations'))
self.r_score = jobDescription.get('RScore') == 'True'
self.weighting = jobDescription.get('WeightedAverage') == 'True'
self.bfactor = jobDescription.get('BFactor')
self.binning = int(jobDescription.get('binning'))
if jobDescription.get('AdaptiveResolution'):
adaptive_resolution = jobDescription.get('AdaptiveResolution')
if adaptive_resolution == '+1':
self.adaptive_res = False # always increase by 1
else:
self.adaptive_res = float(adaptive_resolution)
else:
self.adaptive_res = 0.0 # default, if not specified
if jobDescription.get('FSC'):
self.fsc_criterion = float(jobDescription.get('FSC'))
else:
self.fsc_criterion = 0.5 # default value
# for the constraint
try:
from sh_alignment.constrained_frm import AngularConstraint
con = jobDescription.xpath('AngularConstraint')
if len(con) != 0:
ac = AngularConstraint()
c = ac.fromXML(con[0])
self.constraint = c
else:
self.constraint = None
except:
self.constraint = None
def toXML(self):
"""
copy to xml structure
@return: xml object for job
@rtype L{lxml.etree.Element}
"""
from lxml import etree
jobElement = etree.Element("FRMJob")
jobElement.append(self.particleList.toXML())
jobElement.append(self.reference.toXML())
jobElement.append(self.mask.toXML())
jobElement.append(self.sampleInformation.toXML())
if self.symmetries is not None:
jobElement.append(self.symmetries.toXML())
jobElement.set("PeakOffset", str(self.peak_offset))
jobElement.set("BandwidthRange", str(self.bw_range))
jobElement.set("Frequency", str(self.freq))
jobElement.set("Destination", self.destination)
jobElement.set("MaxIterations", str(self.max_iter))
jobElement.set("RScore", str(self.r_score))
jobElement.set("WeightedAverage", str(self.weighting))
jobElement.set("BFactor", str(self.bfactor))
jobElement.set("binning", str(self.binning))
if self.adaptive_res is False:
jobElement.set("AdaptiveResolution", '+1')
else:
jobElement.set("AdaptiveResolution", str(self.adaptive_res))
jobElement.set("FSC", str(self.fsc_criterion))
if self.constraint:
jobElement.append(self.constraint.toXML())
return jobElement
def check(self):
from pytom.tools.files import checkDirExists
self.particleList.check()
self.reference.check()
self.mask.check()
if not checkDirExists(self.destination):
raise RuntimeError('Destination path not found! ' +
self.destination)
class FRMJob(PyTomClass): # i need to rename the class, but for now it works
def __init__(self,
pl=None,
ref=None,
mask=None,
peak_offset=0,
sample_info=None,
bw_range=None,
freq=None,
dest='.',
max_iter=10,
r_score=False,
weighting=False,
bfactor=None,
symmetries=None,
adaptive_res=0.1,
fsc_criterion=0.5,
constraint=None):
self.particleList = pl
self.reference = ref
self.mask = mask
self.peak_offset = peak_offset
self.sampleInformation = sample_info
self.bw_range = bw_range
self.freq = freq
self.destination = dest
self.max_iter = max_iter
self.r_score = r_score
self.weighting = weighting
self.bfactor = bfactor
self.symmetries = symmetries
self.adaptive_res = adaptive_res
self.fsc_criterion = fsc_criterion
self.constraint = constraint
def fromXML(self, xmlObj):
from lxml.etree import _Element
if xmlObj.__class__ != _Element:
raise Exception('You must provide a valid XML object.')
if xmlObj.tag == "FRMJob":
jobDescription = xmlObj
else:
jobDescription = xmlObj.xpath('FRMJob')
if len(jobDescription) == 0:
raise Exception("This XML is not a FRMJob.")
jobDescription = jobDescription[0]
from pytom.basic.structures import ParticleList, Reference, Mask, SampleInformation, MultiSymmetries
pl = ParticleList('.')
particleList_element = jobDescription.xpath('ParticleList')
if len(particleList_element) > 0:
pl.fromXML(particleList_element[0])
else:
list_elements = jobDescription.xpath('ParticleListLocation')
for e in list_elements:
sub_pl = ParticleList()
sub_pl.fromXMLFile(e.get('Path'))
pl += sub_pl
self.particleList = pl
r = jobDescription.xpath('Reference')[0]
self.reference = Reference('')
self.reference.fromXML(r)
m = jobDescription.xpath('Mask')[0]
self.mask = Mask('')
self.mask.fromXML(m)
try:
si = jobDescription.xpath('SampleInformation')[0]
self.sampleInformation = SampleInformation()
self.sampleInformation.fromXML(si)
except:
self.sampleInformation = SampleInformation()
try:
syms = jobDescription.xpath('MultiSymmetries')[0]
self.symmetries = MultiSymmetries()
self.symmetries.fromXML(syms)
except:
self.symmetries = MultiSymmetries()
self.peak_offset = int(jobDescription.get('PeakOffset'))
self.bw_range = [
int(i)
for i in jobDescription.get('BandwidthRange')[1:-1].split(',')
]
self.freq = int(jobDescription.get('Frequency'))
self.destination = jobDescription.get('Destination')
self.max_iter = int(jobDescription.get('MaxIterations'))
self.r_score = jobDescription.get('RScore') == 'True'
self.weighting = jobDescription.get('WeightedAverage') == 'True'
self.bfactor = jobDescription.get('BFactor')
if jobDescription.get('AdaptiveResolution'):
adaptive_resolution = jobDescription.get('AdaptiveResolution')
if adaptive_resolution == '+1':
self.adaptive_res = False # always increase by 1
else:
self.adaptive_res = float(adaptive_resolution)
else:
self.adaptive_res = 0.0 # default, if not specified
if jobDescription.get('FSC'):
self.fsc_criterion = float(jobDescription.get('FSC'))
else:
self.fsc_criterion = 0.5 # default value
# for the constraint
try:
from sh_alignment.constrained_frm import AngularConstraint
con = jobDescription.xpath('AngularConstraint')
if len(con) != 0:
ac = AngularConstraint()
c = ac.fromXML(con[0])
self.constraint = c
else:
self.constraint = None
except:
self.constraint = None
def toXML(self):
from lxml import etree
jobElement = etree.Element("FRMJob")
jobElement.append(self.particleList.toXML())
jobElement.append(self.reference.toXML())
jobElement.append(self.mask.toXML())
jobElement.append(self.sampleInformation.toXML())
if self.symmetries is not None:
jobElement.append(self.symmetries.toXML())
jobElement.set("PeakOffset", str(self.peak_offset))
jobElement.set("BandwidthRange", str(self.bw_range))
jobElement.set("Frequency", str(self.freq))
jobElement.set("Destination", self.destination)
jobElement.set("MaxIterations", str(self.max_iter))
jobElement.set("RScore", str(self.r_score))
jobElement.set("WeightedAverage", str(self.weighting))
jobElement.set("BFactor", str(self.bfactor))
if self.adaptive_res is False:
jobElement.set("AdaptiveResolution", '+1')
else:
jobElement.set("AdaptiveResolution", str(self.adaptive_res))
jobElement.set("FSC", str(self.fsc_criterion))
if self.constraint:
jobElement.append(self.constraint.toXML())
return jobElement
def check(self):
from pytom.tools.files import checkDirExists
self.particleList.check()
self.reference.check()
self.mask.check()
if not checkDirExists(self.destination):
raise RuntimeError('Destination path not found! ' +
self.destination)
def interpretRequestParameters(parameters):
"""
interpretRequestParameters
"""
from pytom.basic.structures import ParticleList, SampleInformation, Reference, Mask, Wedge
from pytom.alignment.preprocessing import Preprocessing
from pytom.frontend.serverpages.serverMessages import FileMessage
particleList = ParticleList()
if 'plXML' in parameters:
particleList.fromXMLFile(parameters['plXML'])
elif 'plDIR' in parameters:
particleList = ParticleList(parameters['plDIR'])
particleList.loadDirectory()
else:
raise RuntimeError('ParticleList parameter missing in request!')
sampleInfo = SampleInformation()
if 'pixSize' in parameters:
sampleInfo.setPixelSize(parameters['pixSize'])
else:
raise RuntimeError('Pixelsize parameter missing in request!')
if 'partDia' in parameters:
sampleInfo.setParticleDiameter(parameters['partDia'])
else:
raise RuntimeError('Particle diameter missing in request!')
if 'wa1' in parameters:
wedgeAngle1 = float(parameters['wa1'])
else:
raise RuntimeError('Wedge angle 1 parameter missing in request!')
if 'wa2' in parameters:
wedgeAngle2 = float(parameters['wa2'])
else:
raise RuntimeError('Wedge angle 2 parameter missing in request!')
wedgeInfo = Wedge([wedgeAngle1, wedgeAngle2])
if 'mask' in parameters:
mask = Mask(parameters['mask'])
else:
raise RuntimeError('Mask parameter missing in request!')
if not 'lowestF' in parameters:
raise RuntimeError('Lowest frequency parameter missing in request!')
if not 'highestF' in parameters:
raise RuntimeError('Highest frequency parameter missing in request!')
if not 'filtSm' in parameters:
raise RuntimeError('Filter smooth parameter missing in request!')
preprocessing = Preprocessing(float(parameters['lowestF']),
float(parameters['highestF']),
float(parameters['filtSm']))
score = None
if 'score' in parameters:
if parameters['score'] == 'xcf':
from pytom.score.score import xcfScore as scoreClass
elif parameters['score'] == 'nxcf':
from pytom.score.score import nxcfScore as scoreClass
elif parameters['score'] == 'flcf':
from pytom.score.score import FLCFScore as scoreClass
score = scoreClass()
else:
raise RuntimeError('Score parameter missing in request!')
if 'iter' in parameters:
iterations = int(parameters['iter'])
else:
raise RuntimeError('Number of iterations missing in request!')
if 'binning' in parameters:
binning = int(parameters['binning'])
else:
raise RuntimeError('Scaling parameter missing in request!')
if 'classes' in parameters:
numberClasses = float(parameters['classes'])
else:
raise RuntimeError('Number classes parameter missing in request!')
if 'conv' in parameters:
convergence = float(parameters['conv'])
else:
raise RuntimeError('Convergence parameter missing in request!')
if 'dest' in parameters:
destination = parameters['dest']
else:
raise RuntimeError('Destination parameter missing in request!')
sampleInfo = SampleInformation()
if 'pixSize' in parameters:
sampleInfo.setPixelSize(float(parameters['pixSize']))
else:
raise RuntimeError('Pixelsize parameter missing in request!')
if 'partDia' in parameters:
sampleInfo.setParticleDiameter(float(parameters['partDia']))
else:
raise RuntimeError('Particle diameter missing in request!')
from pytom.cluster.mcoEXMXStructures import MCOEXMXJob
job = MCOEXMXJob(particleList,
iterations,
destination,
mask,
score,
preprocessing,
wedgeInfo,
binning,
sampleInfo,
numberClasses,
convergence,
symmetry=None)
jobXMLFile = ''
if 'jobFile' in parameters:
jobXMLFile = parameters['jobFile']
job.toXMLFile(jobXMLFile)
jobRunFile = jobXMLFile[0:-3]
createRunscripts(jobRunFile + 'sh', jobXMLFile)
return FileMessage('MCOEXMXJob', jobXMLFile, 'created')
def interpretRequestParameters(parameters):
"""
interpretRequestParameters
"""
from pytom.basic.structures import ParticleList, SampleInformation, Reference, Mask, Wedge
from pytom.alignment.preprocessing import Preprocessing
from pytom.frontend.serverpages.serverMessages import FileMessage
particleList = ParticleList('.')
if 'plXML' in parameters:
particleList.fromXMLFile(parameters['plXML'])
elif 'plDIR' in parameters:
particleList = ParticleList(parameters['plDIR'])
particleList.loadDirectory()
else:
raise RuntimeError('ParticleList parameter missing in request!')
sampleInfo = SampleInformation()
if 'pixSize' in parameters:
sampleInfo.setPixelSize(parameters['pixSize'])
else:
raise RuntimeError('Pixelsize parameter missing in request!')
if 'partDia' in parameters:
sampleInfo.setParticleDiameter(parameters['partDia'])
else:
raise RuntimeError('Particle diameter missing in request!')
if 'wa1' in parameters:
wedgeAngle1 = float(parameters['wa1'])
else:
raise RuntimeError('Wedge angle 1 parameter missing in request!')
if 'wa2' in parameters:
wedgeAngle2 = float(parameters['wa2'])
else:
raise RuntimeError('Wedge angle 2 parameter missing in request!')
wedgeInfo = Wedge([wedgeAngle1, wedgeAngle2])
if 'mask' in parameters:
mask = Mask(parameters['mask'])
else:
raise RuntimeError('Mask parameter missing in request!')
if not 'lowestF' in parameters:
raise RuntimeError('Lowest frequency parameter missing in request!')
if not 'highestF' in parameters:
raise RuntimeError('Highest frequency parameter missing in request!')
if not 'filtSm' in parameters:
raise RuntimeError('Filter smooth parameter missing in request!')
preprocessing = Preprocessing(float(parameters['lowestF']),
float(parameters['highestF']),
float(parameters['filtSm']))
score = None
if 'score' in parameters:
if parameters['score'] == 'xcf':
from pytom.score.score import xcfScore as scoreClass
elif parameters['score'] == 'nxcf':
from pytom.score.score import nxcfScore as scoreClass
elif parameters['score'] == 'flcf':
from pytom.score.score import FLCFScore as scoreClass
score = scoreClass()
else:
raise RuntimeError('Score parameter missing in request!')
if 'binning' in parameters:
binning = int(parameters['binning'])
else:
raise RuntimeError('Scaling parameter missing in request!')
if 'classes' in parameters:
numberClasses = float(parameters['classes'])
else:
raise RuntimeError('Number classes parameter missing in request!')
if 'conv' in parameters:
convergence = float(parameters['conv'])
else:
raise RuntimeError('Convergence parameter missing in request!')
if 'dest' in parameters:
destination = parameters['dest']
else:
raise RuntimeError('Destination parameter missing in request!')
sampleInfo = SampleInformation()
if 'pixSize' in parameters:
sampleInfo.setPixelSize(float(parameters['pixSize']))
else:
raise RuntimeError('Pixelsize parameter missing in request!')
if 'partDia' in parameters:
sampleInfo.setParticleDiameter(float(parameters['partDia']))
else:
raise RuntimeError('Particle diameter missing in request!')
temperature = None
if 'temp' in parameters:
temperature = parameters['temp']
if 'stemp' in parameters:
startTemperature = float(parameters['stemp'])
else:
raise RuntimeError(
'Start temperature parameter missing in request!')
if 'astep' in parameters:
annealingStep = float(parameters['astep'])
else:
raise RuntimeError('Annealing step parameter missing in request!')
from pytom.cluster.mcoACStructures import SigmaTemperature
if temperature == 'sigma':
temperature = SigmaTemperature(startTemperature, annealingStep)
else:
raise RuntimeError('Temperature missing in request!')
criterion = None
if 'crit' in parameters:
from pytom.cluster.mcoACStructures import MetropolisCriterion, ThresholdAcceptance
criterion = parameters['crit']
if criterion == 'metropolis':
criterion = MetropolisCriterion()
elif criterion == 'threshold':
criterion = ThresholdAcceptance()
else:
raise RuntimeError('Criterion missing in request!')
if 'refin' in parameters:
localSearchIncrement = float(parameters['refin'])
else:
raise RuntimeError('Number of refinement rounds missing in request!')
from pytom.cluster.mcoACStructures import MCOACJob
job = MCOACJob(particleList,
destination,
mask,
score,
preprocessing,
wedgeInfo,
binning,
sampleInfo,
numberClasses,
temperature,
criterion,
convergence,
localSearchIncrement,
symmetry=None)
jobXMLFile = ''
if 'jobFile' in parameters:
jobXMLFile = parameters['jobFile']
job.toXMLFile(jobXMLFile)
jobRunFile = jobXMLFile[0:-3]
createRunscripts(jobRunFile + 'sh', jobXMLFile)
return FileMessage('MCOACJob', jobXMLFile, 'created')
class CTFCorrectionJob(PyTomClass):
"""For the worker to actually run.
"""
def __init__(self,
pl=None,
ctf_conv_pl=None,
ref=None,
mask=None,
peak_offset=0,
sample_info=None,
bw_range=None,
freq=None,
dest='.',
max_iter=10,
r_score=False,
weighting=False,
bfactor=None,
sum_ctf_sqr=None):
self.particleList = pl
self.ctf_conv_pl = ctf_conv_pl
if ref is None:
self.reference = []
else:
self.reference = ref
self.mask = mask
self.peak_offset = peak_offset
self.sampleInformation = sample_info
self.bw_range = bw_range
self.freq = freq
self.destination = dest
self.max_iter = max_iter
self.r_score = r_score
self.weighting = weighting
self.bfactor = bfactor
self.sum_ctf_sqr = sum_ctf_sqr
def fromXML(self, xmlObj):
from lxml.etree import _Element
if xmlObj.__class__ != _Element:
raise Exception('You must provide a valid XML object.')
if xmlObj.tag == "CTFCorrectionJob":
jobDescription = xmlObj
else:
jobDescription = xmlObj.xpath('CTFCorrectionJob')
if len(jobDescription) == 0:
raise Exception("This XML is not a CTFCorrectionJob.")
jobDescription = jobDescription[0]
from pytom.basic.structures import ParticleList, Reference, Mask, SampleInformation
particleList_element = jobDescription.xpath('ParticleList')[0]
pl = ParticleList('.')
pl.fromXML(particleList_element)
self.particleList = pl
self.reference = []
r = jobDescription.xpath('Reference')
for ref_obj in r:
ref = Reference('')
ref.fromXML(ref_obj)
self.reference.append(ref)
m = jobDescription.xpath('Mask')[0]
self.mask = Mask('')
self.mask.fromXML(m)
try:
si = jobDescription.xpath('SampleInformation')[0]
self.sampleInformation = SampleInformation()
self.sampleInformation.fromXML(si)
except:
self._sampleInformation = SampleInformation()
self.ctf_conv_pl = jobDescription.get('CTFConvolutedParticleList')
self.peak_offset = int(jobDescription.get('PeakOffset'))
self.bw_range = [
int(i)
for i in jobDescription.get('BandwidthRange')[1:-1].split(',')
]
self.freq = int(jobDescription.get('Frequency'))
self.destination = jobDescription.get('Destination')
self.max_iter = int(jobDescription.get('MaxIterations'))
self.r_score = jobDescription.get('RScore') == 'True'
self.weighting = jobDescription.get('WeightedAverage') == 'True'
self.bfactor = jobDescription.get('BFactor')
self.sum_ctf_sqr = jobDescription.get('CTFSquared')
def toXML(self):
from lxml import etree
jobElement = etree.Element("CTFCorrectionJob")
jobElement.append(self.particleList.toXML())
for ref in self.reference:
jobElement.append(ref.toXML())
jobElement.append(self.mask.toXML())
jobElement.append(self.sampleInformation.toXML())
jobElement.set("CTFConvolutedParticleList", self.ctf_conv_pl)
jobElement.set("PeakOffset", str(self.peak_offset))
jobElement.set("BandwidthRange", str(self.bw_range))
jobElement.set("Frequency", str(self.freq))
jobElement.set("Destination", self.destination)
jobElement.set("MaxIterations", str(self.max_iter))
jobElement.set("RScore", str(self.r_score))
jobElement.set("WeightedAverage", str(self.weighting))
jobElement.set("BFactor", str(self.bfactor))
jobElement.set("CTFSquared", str(self.sum_ctf_sqr))
return jobElement
def fromXML(self, xmlObj): # only rewrite this function
from lxml.etree import _Element
if xmlObj.__class__ != _Element:
raise Exception('You must provide a valid XML object.')
if xmlObj.tag == "FRMJob": # the name is not changed here!
jobDescription = xmlObj
else:
jobDescription = xmlObj.xpath('FRMJob')
if len(jobDescription) == 0:
raise Exception("This XML is not a FRMJob.")
jobDescription = jobDescription[0]
from pytom.basic.structures import Reference, Mask, SampleInformation, MultiSymmetries
particleList_element = jobDescription.xpath('ParticleListSet')[0]
pl = ParticleListSet()
pl.fromXML(particleList_element)
self.particleList = pl # here i still use the original name!
self.reference = []
r = jobDescription.xpath('Reference')
for ref_obj in r:
ref = Reference('')
ref.fromXML(ref_obj)
self.reference.append(ref)
m = jobDescription.xpath('Mask')[0]
self.mask = Mask('')
self.mask.fromXML(m)
try:
si = jobDescription.xpath('SampleInformation')[0]
self.sampleInformation = SampleInformation()
self.sampleInformation.fromXML(si)
except:
self.sampleInformation = SampleInformation()
try:
syms = jobDescription.xpath('MultiSymmetries')[0]
self.symmetries = MultiSymmetries()
self.symmetries.fromXML(syms)
except:
self.symmetries = MultiSymmetries()
self.peak_offset = int(jobDescription.get('PeakOffset'))
self.bw_range = [
int(i)
for i in jobDescription.get('BandwidthRange')[1:-1].split(',')
]
self.freq = int(jobDescription.get('Frequency'))
self.destination = jobDescription.get('Destination')
self.max_iter = int(jobDescription.get('MaxIterations'))
self.r_score = jobDescription.get('RScore') == 'True'
self.weighting = jobDescription.get('WeightedAverage') == 'True'
self.bfactor = jobDescription.get('BFactor')
if jobDescription.get('AdaptiveResolution'):
adaptive_resolution = jobDescription.get('AdaptiveResolution')
if adaptive_resolution == '+1':
self.adaptive_res = False # always increase by 1
else:
self.adaptive_res = float(adaptive_resolution)
else:
self.adaptive_res = 0.0 # default, if not specified
if jobDescription.get('FSC'):
self.fsc_criterion = float(jobDescription.get('FSC'))
else:
self.fsc_criterion = 0.5 # default value
def interpretRequestParameters(parameters):
"""
interpretRequestParameters
"""
from pytom.basic.structures import ParticleList, SampleInformation, Reference, Mask, Wedge, PointSymmetry
from pytom.alignment.preprocessing import Preprocessing
from pytom.frontend.serverpages.serverMessages import FileMessage
particleList = ParticleList('.')
if 'plXML' in parameters:
particleList.fromXMLFile(parameters['plXML'])
elif 'plDIR' in parameters:
particleList = ParticleList(parameters['plDIR'])
particleList.loadDirectory()
else:
raise RuntimeError('ParticleList parameter missing in request!')
sampleInfo = SampleInformation()
if 'pixSize' in parameters:
sampleInfo.setPixelSize(parameters['pixSize'])
else:
raise RuntimeError('Pixelsize parameter missing in request!')
if 'partDia' in parameters:
sampleInfo.setParticleDiameter(parameters['partDia'])
else:
raise RuntimeError('Particle diameter missing in request!')
reference = ''
if 'ref' in parameters:
reference = Reference(parameters['ref'])
else:
raise RuntimeError('Reference parameter missing in request!')
if 'mask' in parameters:
mask = Mask(parameters['mask'])
else:
raise RuntimeError('Mask parameter missing in request!')
angles = None
if 'sampling' in parameters:
if parameters['sampling'] == 'GLOBAL':
from pytom.angles.globalSampling import GlobalSampling
if 'angFile' in parameters:
angles = GlobalSampling(parameters['angFile'])
else:
raise RuntimeError('Angle file missing in request!')
else:
from pytom.angles.localSampling import LocalSampling
if 'angStart' in parameters:
startIncrement = int(parameters['angStart'])
else:
raise RuntimeError('Angle start missing in request!')
if 'angShells' in parameters:
shells = int(parameters['angShells'])
else:
raise RuntimeError('Angle shells missing in request!')
if 'angInc' in parameters:
shellIncrement = int(parameters['angInc'])
else:
raise RuntimeError('Angle increment missing in request!')
angles = LocalSampling(shells=shells, increment=startIncrement)
else:
raise RuntimeError('Sampling completely missing in request!')
if not 'lowestF' in parameters:
raise RuntimeError('Lowest frequency parameter missing in request!')
if not 'highestF' in parameters:
raise RuntimeError('Highest frequency parameter missing in request!')
if not 'filtSm' in parameters:
raise RuntimeError('Filter smooth parameter missing in request!')
preprocessing = Preprocessing(float(parameters['lowestF']),
float(parameters['highestF']),
float(parameters['filtSm']))
adaptive = True
if 'adapt' in parameters:
fscCriterion = 0.5
resOffset = 0.1
angleFactor = 0.5
adaptive = parameters['adapt'] == 'ON'
if parameters['adapt'] == 'ON':
if 'adResC' in parameters:
fscCriterion = float(parameters['adResC'])
else:
raise RuntimeError('Resolution criterion missing in request!')
if 'adResOf' in parameters:
resOffset = parameters['adResOf']
else:
raise RuntimeError(
'Resolution offset parameter missing in request!')
if 'angFac' in parameters:
angleFactor = float(parameters['angFac'])
else:
raise RuntimeError(
'Angular factor parameter missing in request!')
else:
raise RuntimeError('Adaptive parameter missing in request!')
score = None
if 'score' in parameters:
if parameters['score'] == 'xcf':
from pytom.score.score import xcfScore as scoreClass
elif parameters['score'] == 'nxcf':
from pytom.score.score import nxcfScore as scoreClass
elif parameters['score'] == 'flcf':
from pytom.score.score import FLCFScore as scoreClass
score = scoreClass()
else:
raise RuntimeError('Score parameter missing in request!')
if 'pkPriRad' in parameters:
radius = float(parameters['pkPriRad'])
else:
raise RuntimeError('Peak distance parameter missing in request!')
if 'pkSmooth' in parameters:
smooth = float(parameters['pkSmooth'])
else:
raise RuntimeError('Peak distance smooth missing in request!')
score.setPeakPrior(radius=radius, smooth=smooth)
if 'iter' in parameters:
iterations = int(parameters['iter'])
else:
raise RuntimeError('Number of iterations missing in request!')
if 'binning' in parameters:
binning = int(parameters['binning'])
else:
raise RuntimeError('Scaling parameter missing in request!')
if 'dest' in parameters:
destination = parameters['dest']
else:
raise RuntimeError('Destination parameter missing in request!')
from pytom.alignment.ExMaxAlignment import ExMaxJob
job = ExMaxJob(particleList, destination, reference, score, angles, mask,
PointSymmetry(1), 1, iterations, preprocessing, -1, binning,
sampleInfo, fscCriterion, adaptive, resOffset, angleFactor)
#print job
jobXMLFile = ''
if 'jobFile' in parameters:
jobXMLFile = parameters['jobFile']
job.toXMLFile(jobXMLFile)
if jobXMLFile[-4:] == '.xml':
jobRunFile = jobXMLFile[0:-4]
else:
jobRunFile = jobXMLFile
createRunscripts(jobRunFile + '.sh', jobXMLFile)
return FileMessage('AlignmentJob', jobXMLFile, 'created')
