def _updateParticle(self, item, row):
setXmippAttributes(item, row, md.MDL_ANGLE_ROT, md.MDL_ANGLE_TILT,
md.MDL_ANGLE_PSI, md.MDL_SHIFT_X, md.MDL_SHIFT_Y,
md.MDL_FLIP, md.MDL_SPH_DEFORMATION,
md.MDL_SPH_COEFFICIENTS, md.MDL_SPH_TSNE_COEFF1D,
md.MDL_SPH_TSNE_COEFF2D)
createItemMatrix(item, row, align=ALIGN_PROJ)
def _createItemMatrix(self, particle, row):
row.setValue(emlib.MDL_SHIFT_X,
row.getValue(emlib.MDL_SHIFT_X) * self.scaleFactor)
row.setValue(emlib.MDL_SHIFT_Y,
row.getValue(emlib.MDL_SHIFT_Y) * self.scaleFactor)
setXmippAttributes(particle, row, emlib.MDL_SHIFT_X,
emlib.MDL_SHIFT_Y,
emlib.MDL_ANGLE_ROT, emlib.MDL_ANGLE_TILT,
emlib.MDL_ANGLE_PSI)
createItemMatrix(particle, row, align=ALIGN_PROJ)
def _processRow(self, particle, row):
def __setXmippImage(label):
attr = '_xmipp_' + xmippLib.label2Str(label)
if not hasattr(particle, attr):
img = Image()
setattr(particle, attr, img)
img.setSamplingRate(particle.getSamplingRate())
else:
img = getattr(particle, attr)
img.setLocation(xmippToLocation(row.getValue(label)))
particle.setLocation(xmippToLocation(row.getValue(xmippLib.MDL_IMAGE)))
#__setXmippImage(xmippLib.MDL_IMAGE)
#__setXmippImage(xmippLib.MDL_IMAGE_REF)
setXmippAttributes(particle, row, xmippLib.MDL_IMAGE_ORIGINAL,
xmippLib.MDL_IMAGE_REF)
def _processRow(self, particle, row):
setXmippAttributes(particle, row,
xmippLib.MDL_ZSCORE_RESVAR, xmippLib.MDL_ZSCORE_RESMEAN,
xmippLib.MDL_ZSCORE_RESCOV, xmippLib.MDL_IMAGE_ORIGINAL,
xmippLib.MDL_COST, xmippLib.MDL_CONTINUOUS_GRAY_A,
xmippLib.MDL_CONTINUOUS_GRAY_B, xmippLib.MDL_CONTINUOUS_X,
xmippLib.MDL_CONTINUOUS_Y,
xmippLib.MDL_CORRELATION_IDX, xmippLib.MDL_CORRELATION_MASK,
xmippLib.MDL_CORRELATION_WEIGHT, xmippLib.MDL_IMED)
def __setXmippImage(label):
attr = '_xmipp_' + xmippLib.label2Str(label)
if not hasattr(particle, attr):
img = Image()
setattr(particle, attr, img)
img.setSamplingRate(particle.getSamplingRate())
else:
img = getattr(particle, attr)
img.setLocation(xmippToLocation(row.getValue(label)))
__setXmippImage(xmippLib.MDL_IMAGE)
__setXmippImage(xmippLib.MDL_IMAGE_REF)
__setXmippImage(xmippLib.MDL_IMAGE_RESIDUAL)
__setXmippImage(xmippLib.MDL_IMAGE_COVARIANCE)
def readPartsFromMics(self, micList, outputParts):
""" Read the particles extract for the given list of micrographs
and update the outputParts set with new items.
"""
p = Particle()
for mic in micList:
# We need to make this dict because there is no ID in the .xmd file
coordDict = {}
for coord in self.coordDict[mic.getObjId()]:
pos = self._getPos(coord)
if pos in coordDict:
print(
"WARNING: Ignoring duplicated coordinate: %s, id=%s" %
(coord.getObjId(), pos))
coordDict[pos] = coord
added = set() # Keep track of added coords to avoid duplicates
fnMicXmd = self._getMicXmd(mic)
if exists(fnMicXmd):
for row in md.iterRows(fnMicXmd):
pos = (row.getValue(md.MDL_XCOOR),
row.getValue(md.MDL_YCOOR))
coord = coordDict.get(pos, None)
if coord is not None and coord.getObjId() not in added:
# scale the coordinates according to particles dimension.
coord.scale(self.getBoxScale())
p.copyObjId(coord)
p.setLocation(
xmippToLocation(row.getValue(md.MDL_IMAGE)))
p.setCoordinate(coord)
p.setMicId(mic.getObjId())
p.setCTF(mic.getCTF())
# adding the variance and Gini coeff. value of the mic zone
setXmippAttributes(p, row, md.MDL_SCORE_BY_VAR)
setXmippAttributes(p, row, md.MDL_SCORE_BY_GINI)
if row.containsLabel(md.MDL_ZSCORE_DEEPLEARNING1):
setXmippAttributes(p, row,
md.MDL_ZSCORE_DEEPLEARNING1)
# disabled particles (in metadata) should not add to the
# final set
if row.getValue(md.MDL_ENABLED) > 0:
outputParts.append(p)
added.add(coord.getObjId())
# Release the list of coordinates for this micrograph since it
# will not be longer needed
del self.coordDict[mic.getObjId()]
def _updateClass(self, item):
classId = item.getObjId()
classRow = findRow(self.mdClasses, xmippLib.MDL_REF2, classId)
representative = item.getRepresentative()
representative.setTransform(rowToAlignment(classRow, ALIGN_PROJ))
representative.setLocation(xmippToLocation(classRow.getValue(xmippLib.MDL_IMAGE)))
setXmippAttributes(representative, classRow, xmippLib.MDL_ANGLE_ROT)
setXmippAttributes(representative, classRow, xmippLib.MDL_ANGLE_TILT)
setXmippAttributes(representative, classRow, xmippLib.MDL_CLASS_COUNT)
self.averageSet.append(representative)
reprojection = Image()
reprojection.setLocation(xmippToLocation(classRow.getValue(xmippLib.MDL_IMAGE1)))
item.reprojection = reprojection
def _updateParticle(self, item, row):
setXmippAttributes(item, row, MD.MDL_ZSCORE_DEEPLEARNING1)
if row.getValue(MD.MDL_ENABLED) <= 0:
item._appendItem = False
else:
item._appendItem = True
def _updateParticle(self, item, row):
setXmippAttributes(item, row, md.MDL_ANGLE_ROT, md.MDL_ANGLE_TILT,
md.MDL_ANGLE_PSI, md.MDL_SHIFT_X, md.MDL_SHIFT_Y,
md.MDL_FLIP, md.MDL_NMA, md.MDL_COST)
createItemMatrix(item, row, align=em.ALIGN_PROJ)
def _createItemMatrix(self, particle, row):
setXmippAttributes(particle, row, emlib.MDL_SHIFT_DIFF,
emlib.MDL_ANGLE_DIFF)
def _processRow(self, particle, row):
particle.setLocation(xmippToLocation(row.getValue(xmippLib.MDL_IMAGE)))
if self.model.get() == ITER_TRAIN:
setXmippAttributes(particle, row,
xmippLib.MDL_CORR_DENOISED_PROJECTION)
def _updateParticle(self, item, row):
setXmippAttributes(item, row, md.MDL_SCORE_BY_EMPTINESS)
if row.getValue(md.MDL_ENABLED) <= 0:
item._appendItem = False
else:
item._appendItem = True
