예제 #1
0
 def trainTest(self,testSplit,**kw):
     idLab = self.idLab
     spDir = self.getSplitDirName(testSplit)
     makedir(spDir)
     idLabRec = idLab.getRecords()
     spIdLab = idLabRec.copy()
     spIdLab["split"] = 1
     spIdLab["split"][idLabRec["split"]==testSplit] = 2
     spIdLabFile = pjoin(spDir,"idlab.pkl")
     saveIdLabelRecords(records=spIdLab,fileName=spIdLabFile)
     spClOpt = copy(self.clOpt)
     spClOpt.labels = [spIdLabFile]
     spClOpt.predFile = pjoin(spDir,"pred.pkl")
     spClOpt.perfFile = pjoin(spDir,"perf.pkl")
     spClOpt.mode = "trainScatter"
     spClOpt.runMode = self.opt.runMode
     spClOpt.cwd = spDir
     spOptFile = self.getSplitOptFileName(testSplit)
     spApp = ClassifierApp(opt=spClOpt)
     spClOpt = spApp.getOpt() #get the missing options filled with defaults
     #that just saves a copy for us - App will create its own when it 
     #submits a batch job (unique and slightly modified)
     dumpObj(spClOpt,spOptFile)
     kw = kw.copy()
     jobs = spApp.run(**kw)
     spClOpt.mode = "test"
     spApp = ClassifierApp(opt=spClOpt)
     kw["depend"] = jobs
     jobs = spApp.run(**kw)
     return jobs
예제 #2
0
파일: DirStore.py 프로젝트: andreyto/mgtaxa
    def run(self, **kw):
        from MGT.ClassifierApp import ClassifierApp

        opt = self.opt
        opt.cwd = self.path  # in case we moved it after __init__()
        jobs = []
        opt.mode = "trainScatter"
        app = ClassifierApp(opt=opt)
        opt = app.getOpt()  # get the missing options filled with defaults
        # we need to clean up the models directory otherwise we run a danger
        # of picking up old models that are not trained in this session
        rmrf(self.getFilePath(opt.modelRoot))
        return app.run(**kw)
예제 #3
0
파일: DirStore.py 프로젝트: andreyto/mgtaxa
    def run(self, **kw):
        from MGT.ClassifierApp import ClassifierApp

        opt = self.opt
        opt.cwd = self.path  # in case we moved it after __init__()
        opt.predFile = pjoin(opt.cwd, "pred.pkl")
        jobs = []
        opt.mode = "predict"
        app = ClassifierApp(opt=opt)
        opt = app.getOpt()  # get the missing options filled with defaults
        jobs = app.run(**kw)
        self.save()
        return jobs
예제 #4
0
파일: DirStore.py 프로젝트: andreyto/mgtaxa
    def run(self, **kw):
        from MGT.ClassifierApp import ClassifierApp

        opt = self.opt
        opt.cwd = self.path  # in case we moved it after __init__()
        opt.predFile = pjoin(opt.cwd, "pred.pkl")
        opt.perfFile = pjoin(opt.cwd, "perf.pkl")
        jobs = []
        opt.mode = "trainScatter"
        app = ClassifierApp(opt=opt)
        opt = app.getOpt()  # get the missing options filled with defaults
        # we need to clean up the models directory otherwise we run a danger
        # of picking up old models that are not trained in this session
        rmrf(self.getFilePath(opt.modelRoot))
        jobs = app.run(**kw)
        opt.mode = "test"
        app = ClassifierApp(opt=opt)
        opt = app.getOpt()  # get the missing options filled with defaults
        self.save()
        kw = kw.copy()
        kw["depend"] = jobs
        jobs = app.run(**kw)
        return jobs