def loadJobItemResults(self, paramNameFile=None, bestfit=True, bestfitonly=False, noconverge=False, silent=False): self.result_converge = None self.result_marge = None self.result_likemarge = None self.result_bestfit = self.chainBestfit(paramNameFile) if not bestfitonly: marge_root = self.distRoot if self.getDistExists(): if not noconverge: self.result_converge = ResultObjs.convergeStats(marge_root + '.converge') self.result_marge = ResultObjs.margeStats(marge_root + '.margestats', paramNameFile) self.result_likemarge = ResultObjs.likeStats(marge_root + '.likestats') if self.result_bestfit is not None and bestfit: self.result_marge.addBestFit(self.result_bestfit) elif not silent: print 'missing: ' + marge_root
def R(self): if self.result_converge is None: fname = self.distRoot + '.converge' if not nonEmptyFile(fname): return None self.result_converge = ResultObjs.convergeStats(fname) return float(self.result_converge.worstR())