def _updateParticle(self, item, row): item.setClassId(row.getValue(md.RLN_PARTICLE_CLASS)) item.setTransform(rowToAlignment(row, em.ALIGN_PROJ)) item._rlnLogLikeliContribution = em.Float( row.getValue('rlnLogLikeliContribution')) item._rlnMaxValueProbDistribution = em.Float( row.getValue('rlnMaxValueProbDistribution')) item._rlnGroupName = em.String(row.getValue('rlnGroupName'))
def _updateClass(self, item): classId = item.getObjId() classRow = findRow(self.mdClasses, xmipp.MDL_REF2, classId) representative = item.getRepresentative() representative.setTransform(rowToAlignment(classRow, ALIGN_PROJ)) representative.setLocation(xmippToLocation(classRow.getValue(xmipp.MDL_IMAGE))) setXmippAttributes(representative, classRow, xmipp.MDL_ANGLE_ROT) setXmippAttributes(representative, classRow, xmipp.MDL_ANGLE_TILT) setXmippAttributes(representative, classRow, xmipp.MDL_CLASS_COUNT) self.averageSet.append(representative) reprojection = Image() reprojection.setLocation(xmippToLocation(classRow.getValue(xmipp.MDL_IMAGE1))) item.reprojection = reprojection
def _updateParticle(self, item, row): from convert import rowToAlignment, OrderedDict, HEADER_COLUMNS item.setClassId(row[0]) vals = OrderedDict(zip(HEADER_COLUMNS, row[1])) item.setTransform(rowToAlignment(vals, item.getSamplingRate()))
def _createItemMatrix(self, item, rowList): if rowList[1] == 1: item.setTransform( rowToAlignment(rowList[2:], alignType=em.ALIGN_PROJ)) else: setattr(item, "_appendItem", False)
def _updateParticle(self, item, row): item.setClassId(row.getValue(md.MDL_REF)) item.setTransform(rowToAlignment(row, ALIGN_2D))
def _createItemMatrix(self, item, row): from convert import rowToAlignment item.setTransform(rowToAlignment(row, item.getSamplingRate()))
def _createItemMatrix(self, item, rowList): if rowList[1] == 1: item.setTransform(rowToAlignment(rowList[2:], alignType=em.ALIGN_PROJ)) else: setattr(item, "_appendItem", False)
def _createItemMatrix(self, item, rowList): item.setTransform(rowToAlignment(rowList[1:], alignType=em.ALIGN_PROJ))