Source code for xmipp3.viewers.viewer_classes3D

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# * Authors:     J.M. De la Rosa Trevin (
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# * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia , CSIC
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This module implement the wrappers aroung Xmipp CL2D protocol
visualization program.
from pyworkflow.gui import IconButton, Icon
from pyworkflow.gui.form import FormWindow
from pyworkflow.viewer import (ProtocolViewer, DESKTOP_TKINTER, WEB_DJANGO)
from pyworkflow.protocol.params import StringParam, LabelParam, IntParam

from xmipp3.protocols.protocol_consensus_classes3D import XmippProtConsensusClasses3D
from pwem.objects import Class3D

import pickle
import matplotlib.pyplot as plt

FILE_OBJECTIVE_FDATA = 'ObjectiveFData.pkl'
FILE_CLUSTERINGS = 'clusterings.pkl'
FILE_ELBOWCLUSTERS = 'elbowclusters.pkl'

[docs]class XmippClasses3DViewer(ProtocolViewer): """ Visualization of results from the consensus classes 3D protocol """ _label = 'viewer classes 3D' _targets = [XmippProtConsensusClasses3D] _environments = [DESKTOP_TKINTER, WEB_DJANGO] def __init__(self, **kwargs): ProtocolViewer.__init__(self, **kwargs) self.nclusters, self.objFValues = self.getObjectiveFData() self._elbowIdx = self.getElbowIndex() self._allClusterings = self.getClusterings()
[docs] def getObjectiveFData(self): loadPath = self.protocol._getExtraPath(FILE_OBJECTIVE_FDATA) with open(loadPath, 'rb') as f: self._ObjFData = pickle.load(f) return self._ObjFData
[docs] def getClusterings(self): loadPath = self.protocol._getExtraPath(FILE_CLUSTERINGS) with open(loadPath, 'rb') as f: self._allClusterings = pickle.load(f) return self._allClusterings
[docs] def getElbowIndex(self): loadPath = self.protocol._getExtraPath(FILE_ELBOWCLUSTERS) with open(loadPath, 'rb') as f: self.elbowIndex = pickle.load(f) return self.elbowIndex
def _defineParams(self, form): form.addSection(label='Visualization') form.addParam('displayObjectiveFunction', LabelParam, label='Visualize Objective Function', help='Open a GUI to visualize the objective function for each number of clusters ') form.addParam('chooseNumberOfClusters', IntParam, default=-1, label='Number of Clusters', help='Choose the final number of clusters in the consensus clustering. Press the eye') #TODO: set an apply button to change the number of clusters instead of using the eye '''command = self._chooseNumberOfClusters() btn = IconButton(self.getWindow(), "Apply", Icon.ACTION_CONTINUE, command=command) btn.config(relief="flat", activebackground=None, compound='left', fg='black', overrelief="raised") btn.bind('<Button-1>') btn.grid(row=2, column=2, sticky='nw')''' def _getVisualizeDict(self): return {'chooseNumberOfClusters': self._chooseNumberOfClusters, 'displayObjectiveFunction': self._visualizeObjectiveFunction} def _visualizeObjectiveFunction(self, e=None): nclusters, ob_values = self.nclusters, self.objFValues elbowIdx = self._elbowIdx plt.plot(nclusters, ob_values) plt.scatter([nclusters[elbowIdx]], [ob_values[elbowIdx]], color='green') plt.xlabel('Number of clusters') plt.ylabel('Objective values') plt.title('Objective values for each number of clusters') def _chooseNumberOfClusters(self, e=None): views=[] nclusters = self.nclusters elbow_nclust = nclusters[self._elbowIdx] nclust = self.chooseNumberOfClusters.get() if nclust == -1: nclust = elbow_nclust elif nclust > max(nclusters): nclust = max(nclusters) scipion_clustering = self.buildSetOfClasses(nclust) self.protocol._defineOutputs(outputClasses=scipion_clustering) for item in self.protocol.inputMultiClasses: self.protocol._defineSourceRelation(item, scipion_clustering) #TODO: esto es un objeto SetOfClasses3D pero no sabemos como lanzar un viewer con el sin tener el protocolo #views.append(ObjectView(self._project, self.protocol.strId())) return views
[docs] def buildSetOfClasses(self, nclust): '''From a list of clusterings, nclust index it and that clustering is converted into a scipion setOfClasses''' clustIdx = self.nclusters.index(nclust) clustering = self._allClusterings[clustIdx] inputParticles = self.protocol.inputMultiClasses[0].get().getImages() outputClasses = self.protocol._createSetOfClasses3D(inputParticles) for classItem in clustering: numOfPart = classItem[0] partIds = classItem[1] setRepId = classItem[2] clsRepId = classItem[3] setRep = self.protocol.inputMultiClasses[setRepId].get() clRep = setRep[clsRepId] newClass = Class3D() # newClass.copyInfo(clRep) newClass.setAcquisition(clRep.getAcquisition()) newClass.setRepresentative(clRep.getRepresentative()) outputClasses.append(newClass) enabledClass = outputClasses[newClass.getObjId()] enabledClass.enableAppend() for itemId in partIds: enabledClass.append(inputParticles[itemId]) outputClasses.update(enabledClass) return outputClasses