def objectToRow(obj, row, attrDict, extraLabels={}):
""" This function will convert an EMObject into a XmippMdRow.
Params:
obj: the EMObject instance (input)
row: the XmippMdRow instance (output)
attrDict: dictionary with the map between obj attributes(keys) and
row MDLabels in Xmipp (values).
extraLabels: a list with extra labels that could be included
as _xmipp_labelName
"""
if obj.isEnabled():
enabled = True
else:
enabled = False
row.setValue(md.RLN_IMAGE_ENABLED, enabled)
for attr, label in attrDict.iteritems():
if hasattr(obj, attr):
valueType = md.label2Python(label)
row.setValue(label, valueType(getattr(obj, attr).get()))
attrLabels = attrDict.values()
for label in extraLabels:
attrName = '_' + md.label2Str(label)
if label not in attrLabels and hasattr(obj, attrName):
value = obj.getAttributeValue(attrName)
row.setValue(label, value)
def rowToObject(row, obj, attrDict, extraLabels={}):
""" This function will convert from a XmippMdRow to an EMObject.
Params:
row: the XmippMdRow instance (input)
obj: the EMObject instance (output)
attrDict: dictionary with the map between obj attributes(keys) and
row MDLabels in Xmipp (values).
extraLabels: a list with extra labels that could be included
as properties with the label name such as: _rlnSomeThing
"""
obj.setEnabled(row.getValue(md.RLN_IMAGE_ENABLED, 1) > 0)
for attr, label in attrDict.iteritems():
value = row.getValue(label)
if not hasattr(obj, attr):
setattr(obj, attr, ObjectWrap(value))
else:
getattr(obj, attr).set(value)
attrLabels = attrDict.values()
for label in extraLabels:
if label not in attrLabels and row.hasLabel(label):
labelStr = md.label2Str(label)
setattr(obj, '_' + labelStr, row.getValueAsObject(label))
def objectToRow(obj, row, attrDict, extraLabels={}):
""" This function will convert an EMObject into a XmippMdRow.
Params:
obj: the EMObject instance (input)
row: the XmippMdRow instance (output)
attrDict: dictionary with the map between obj attributes(keys) and
row MDLabels in Xmipp (values).
extraLabels: a list with extra labels that could be included
as _xmipp_labelName
"""
if obj.isEnabled():
enabled = True
else:
enabled = False
row.setValue(md.RLN_IMAGE_ENABLED, enabled)
for attr, label in attrDict.iteritems():
if hasattr(obj, attr):
valueType = md.label2Python(label)
row.setValue(label, valueType(getattr(obj, attr).get()))
attrLabels = attrDict.values()
for label in extraLabels:
attrName = '_' + md.label2Str(label)
if label not in attrLabels and hasattr(obj, attrName):
value = obj.getAttributeValue(attrName)
row.setValue(label, value)
def rowToObject(row, obj, attrDict, extraLabels={}):
""" This function will convert from a XmippMdRow to an EMObject.
Params:
row: the XmippMdRow instance (input)
obj: the EMObject instance (output)
attrDict: dictionary with the map between obj attributes(keys) and
row MDLabels in Xmipp (values).
extraLabels: a list with extra labels that could be included
as properties with the label name such as: _rlnSomeThing
"""
obj.setEnabled(row.getValue(md.RLN_IMAGE_ENABLED, 1) > 0)
for attr, label in attrDict.iteritems():
value = row.getValue(label)
if not hasattr(obj, attr):
setattr(obj, attr, ObjectWrap(value))
else:
getattr(obj, attr).set(value)
attrLabels = attrDict.values()
for label in extraLabels:
if label not in attrLabels and row.hasLabel(label):
labelStr = md.label2Str(label)
setattr(obj, '_' + labelStr, row.getValueAsObject(label))
def test_particlesFromStar(self):
""" Read a set of particles from an .star file. """
fnStar = self.getFile('relion_it020_data')
print ">>> Reading star file: ", fnStar
mdAll = md.MetaData(fnStar)
print "labels: ", [md.label2Str(l) for l in mdAll.getActiveLabels()]
print "size: ", mdAll.size()
def setRelionAttributes(obj, objRow, *labels):
""" Set an attribute to obj from a label that is not
basic ones. The new attribute will be named _rlnLabelName
and the datatype will be set correctly.
"""
for label in labels:
setattr(obj, '_%s' % md.label2Str(label),
objRow.getValueAsObject(label))
def _findImagesPath(self, label, warnings=True):
row = md.getFirstRow(self._starFile)
if row is None:
raise Exception("Can not import from an empty metadata: %s" %
self._starFile)
if not row.containsLabel(label):
raise Exception("Label *%s* is missing in metadata: %s" %
(md.label2Str(label), self._starFile))
index, fn = relionToLocation(row.getValue(label))
self._imgPath = findRootFrom(self._starFile, fn)
if warnings and self._imgPath is None:
self.protocol.warning(
"Binary data was not found from metadata: %s" % self._starFile)
if (self._starFile.endswith('_data.star')
and self._getModelFile(self._starFile)):
self._modelStarFile = self._getModelFile(self._starFile)
modelRow = md.getFirstRow(self._modelStarFile)
classDimensionality = modelRow.getValue(
'rlnReferenceDimensionality')
self._optimiserFile = self._starFile.replace(
'_data.star', '_optimiser.star')
if not exists(self._optimiserFile):
raise Exception("Missing required optimiser star file: %s" %
self._optimiserFile)
optimiserRow = md.getFirstRow(self._optimiserFile)
autoRefine = optimiserRow.containsLabel('rlnModelStarFile2')
self.alignType = ALIGN_PROJ
if not autoRefine:
if classDimensionality == 3:
self._classesFunc = self.protocol._createSetOfClasses3D
else:
self._classesFunc = self.protocol._createSetOfClasses2D
self.alignType = ALIGN_2D
else:
self._classesFunc = None
else:
self.alignType = ALIGN_NONE
self._classesFunc = None
self._modelStarFile = None
modelRow = None
# Check if the MetaData contains either MDL_MICROGRAPH_ID
# or MDL_MICROGRAPH, this will be used when imported
# particles to keep track of the particle's micrograph
self._micIdOrName = (row.containsLabel('rlnMicrographName')
or row.containsLabel('rlnMicrographId'))
#init dictionary. It will be used in the preprocessing
self.micDict = {}
return row, modelRow
def _findImagesPath(self, label, warnings=True):
row = md.getFirstRow(self._starFile)
if row is None:
raise Exception("Can not import from an empty metadata: %s" % self._starFile)
if not row.containsLabel(label):
raise Exception("Label *%s* is missing in metadata: %s" % (md.label2Str(label),
self._starFile))
index, fn = relionToLocation(row.getValue(label))
self._imgPath = findRootFrom(self._starFile, fn)
if warnings and self._imgPath is None:
self.protocol.warning("Binary data was not found from metadata: %s" % self._starFile)
if (self._starFile.endswith('_data.star') and
self._getModelFile(self._starFile)):
self._modelStarFile = self._getModelFile(self._starFile)
modelRow = md.getFirstRow(self._modelStarFile)
classDimensionality = modelRow.getValue('rlnReferenceDimensionality')
self._optimiserFile = self._starFile.replace('_data.star', '_optimiser.star')
if not exists(self._optimiserFile):
raise Exception("Missing required optimiser star file: %s" % self._optimiserFile)
optimiserRow = md.getFirstRow(self._optimiserFile)
autoRefine = optimiserRow.containsLabel('rlnModelStarFile2')
self.alignType = ALIGN_PROJ
if not autoRefine:
if classDimensionality == 3:
self._classesFunc = self.protocol._createSetOfClasses3D
else:
self._classesFunc = self.protocol._createSetOfClasses2D
self.alignType = ALIGN_2D
else:
self._classesFunc = None
else:
self.alignType = ALIGN_NONE
self._classesFunc = None
self._modelStarFile = None
modelRow = None
# Check if the MetaData contains either MDL_MICROGRAPH_ID
# or MDL_MICROGRAPH, this will be used when imported
# particles to keep track of the particle's micrograph
self._micIdOrName = (row.containsLabel('rlnMicrographName') or
row.containsLabel('rlnMicrographId'))
#init dictionary. It will be used in the preprocessing
self.micDict = {}
return row, modelRow
def test_particlesFromStar(self):
""" Read a set of particles from an .star file. """
fnStar = self.getFile('relion_it020_data')
print ">>> Reading star file: ", fnStar
mdAll = md.MetaData(fnStar)
goldLabels = ['rlnVoltage', 'rlnDefocusU', 'rlnDefocusV',
'rlnDefocusAngle', 'rlnSphericalAberration',
'rlnAmplitudeContrast', 'rlnImageName', 'rlnImageId',
'rlnCoordinateX', 'rlnCoordinateY', 'rlnMagnificationCorrection',
'rlnNormCorrection', 'rlnMicrographName', 'rlnGroupNumber',
'rlnOriginX', 'rlnOriginY', 'rlnAngleRot', 'rlnAngleTilt',
'rlnAnglePsi', 'rlnClassNumber', 'rlnLogLikeliContribution',
'rlnNrOfSignificantSamples', 'rlnMaxValueProbDistribution']
self.assertEqual(goldLabels, [md.label2Str(l) for l in mdAll.getActiveLabels()])
self.assertEqual(4700, mdAll.size())
def test_particlesFromStar(self):
""" Read a set of particles from an .star file. """
fnStar = self.getFile('relion_it020_data')
print (">>> Reading star file: ", fnStar)
mdAll = md.MetaData(fnStar)
goldLabels = ['rlnVoltage', 'rlnDefocusU', 'rlnDefocusV',
'rlnDefocusAngle', 'rlnSphericalAberration',
'rlnAmplitudeContrast', 'rlnImageName', 'rlnImageId',
'rlnCoordinateX', 'rlnCoordinateY', 'rlnMagnificationCorrection',
'rlnNormCorrection', 'rlnMicrographName', 'rlnGroupNumber',
'rlnOriginX', 'rlnOriginY', 'rlnAngleRot', 'rlnAngleTilt',
'rlnAnglePsi', 'rlnClassNumber', 'rlnLogLikeliContribution',
'rlnNrOfSignificantSamples', 'rlnMaxValueProbDistribution']
self.assertEqual(goldLabels, [md.label2Str(l) for l in mdAll.getActiveLabels()])
self.assertEqual(4700, mdAll.size())
def _findPathAndCtf(self, label, warnings=True):
""" Find the relative path from which the micrographs exists
repect to the metadata location. Also check if it contains
CTF information and their relative root.
"""
row = md.getFirstRow(self._mdFile)
if row is None:
raise Exception("Can not import from an empty metadata: "
"%s" % self._mdFile)
if not row.containsLabel(label):
raise Exception("Label *%s* is missing in metadata: "
"%s" % (md.label2Str(label), self._mdFile))
# take only the filename part after the @
index, fn = xmippToLocation(row.getValue(label))
self._imgPath = findRootFrom(self._mdFile, fn)
if warnings and self._imgPath is None:
self.protocol.warning("Binary data was not found from metadata: "
"%s" % self._mdFile)
if row.containsLabel(md.MDL_CTF_MODEL):
self._ctfPath = findRootFrom(self._mdFile,
row.getValue(md.MDL_CTF_MODEL))
else:
self._ctfPath = None # means no CTF info from micrographs metadata
if row.containsLabel(md.MDL_REF):
self._classFunc = self.protocol._createSetOfClasses2D
elif row.containsLabel(md.MDL_REF3D):
self._classFunc = self.protocol._createSetOfClasses3D
else:
self._classLabel = None
self._classFunc = None
# Check if the MetaData contains either MDL_MICROGRAPH_ID
# or MDL_MICROGRAPH, this will be used when imported
# particles to keep track of the particle's micrograph
self._micIdOrName = (row.containsLabel(md.MDL_MICROGRAPH_ID)
or row.containsLabel(md.MDL_MICROGRAPH))
#init dictionary. It will be used in the preprocessing
self.micDict = {}
return row
def _findPathAndCtf(self, label, warnings=True):
""" Find the relative path from which the micrographs exists
repect to the metadata location. Also check if it contains
CTF information and their relative root.
"""
row = md.getFirstRow(self._mdFile)
if row is None:
raise Exception("Can not import from an empty metadata: "
"%s" % self._mdFile)
if not row.containsLabel(label):
raise Exception("Label *%s* is missing in metadata: "
"%s" % (md.label2Str(label), self._mdFile))
# take only the filename part after the @
index, fn = xmippToLocation(row.getValue(label))
self._imgPath = findRootFrom(self._mdFile, fn)
if warnings and self._imgPath is None:
self.protocol.warning("Binary data was not found from metadata: "
"%s" % self._mdFile)
if row.containsLabel(md.MDL_CTF_MODEL):
self._ctfPath = findRootFrom(self._mdFile,
row.getValue(md.MDL_CTF_MODEL))
else:
self._ctfPath = None # means no CTF info from micrographs metadata
if row.containsLabel(md.MDL_REF):
self._classFunc = self.protocol._createSetOfClasses2D
elif row.containsLabel(md.MDL_REF3D):
self._classFunc = self.protocol._createSetOfClasses3D
else:
self._classLabel = None
self._classFunc = None
# Check if the MetaData contains either MDL_MICROGRAPH_ID
# or MDL_MICROGRAPH, this will be used when imported
# particles to keep track of the particle's micrograph
self._micIdOrName = (row.containsLabel(md.MDL_MICROGRAPH_ID) or
row.containsLabel(md.MDL_MICROGRAPH))
#init dictionary. It will be used in the preprocessing
self.micDict = {}
return row
def createAngDistribution(inputMd, splitLabel, classes):
# List of list of 3 elements containing angleTilt, anglePsi, weight
projectionListDict = {}
def getCloseProjection(angleRot, angleTilt, projectionList):
""" Get an existing projection close to angleRot, angleTilt.
Return None if not found close enough.
"""
for projection in projectionList:
if (abs(projection[0] - angleRot) <= 0.01 and
abs(projection[1] - angleTilt) <= 0.01):
return projection
return None
weight = 1.
for row in md.iterRows(inputMd):
splitValue = row.getValue(splitLabel)
if classes and splitValue not in classes:
continue
angleRot = row.getValue('rlnAngleRot')
angleTilt = row.getValue('rlnAngleTilt')
if splitValue is None:
raise Exception('Label %s not found' % md.label2Str(splitLabel))
if not splitValue in projectionListDict:
projectionListDict[splitValue] = []
projectionList = projectionListDict[splitValue]
projection = getCloseProjection(angleRot, angleTilt, projectionList)
if projection is None:
projectionList.append([angleRot, angleTilt, weight])
else:
projection[2] = projection[2] + weight
return projectionListDict
def particleToRow(part, partItem, **kwargs):
""" Set labels values from Particle to md row. """
partRow = md.Row()
coord = part.getCoordinate()
if coord is not None:
coordinateToRow(coord, partRow, md.RLN_MICROGRAPH_ID, copyId=False)
if part.hasMicId():
partRow.setValue(md.RLN_MICROGRAPH_ID, long(part.getMicId()))
# If the row does not contains the micrgraphs name
# use a fake micrograph name using id to relion
# could at least group for CTF using that
if not partRow.hasLabel(md.RLN_MICROGRAPH_NAME):
partRow.setValue(md.RLN_MICROGRAPH_NAME,
'fake_micrograph_%06d.mrc' % part.getMicId())
if part.hasAttribute('_rlnParticleId'):
partRow.setValue(md.RLN_PARTICLE_ID, long(part._rlnParticleId.get()))
imageToRow(part, partRow, md.RLN_IMAGE_NAME, **kwargs)
for label, value in partRow._labelDict.iteritems():
labelStr = md.label2Str(label)
setattr(partItem, labelStr, value)
def particleToRow(part, partItem, **kwargs):
""" Set labels values from Particle to md row. """
partRow = md.Row()
coord = part.getCoordinate()
if coord is not None:
coordinateToRow(coord, partRow, md.RLN_MICROGRAPH_ID, copyId=False)
if part.hasMicId():
partRow.setValue(md.RLN_MICROGRAPH_ID, long(part.getMicId()))
# If the row does not contains the micrgraphs name
# use a fake micrograph name using id to relion
# could at least group for CTF using that
if not partRow.hasLabel(md.RLN_MICROGRAPH_NAME):
partRow.setValue(md.RLN_MICROGRAPH_NAME,
'fake_micrograph_%06d.mrc' % part.getMicId())
if part.hasAttribute('_rlnParticleId'):
partRow.setValue(md.RLN_PARTICLE_ID, long(part._rlnParticleId.get()))
imageToRow(part, partRow, md.RLN_IMAGE_NAME, **kwargs)
for label, value in partRow._labelDict.iteritems():
labelStr = md.label2Str(label)
setattr(partItem, labelStr, value)
