def loadResults2(fileName) : """ load a list of list of Results objects or a dictionary of a list of Results objects """ res = myio.load(fileName) if type(res) == type({}) : results = {} for key in res : results[key] = [ Results(object) for object in res[key] ] return results elif type(res) == type([]) : return [ [Results(object) for object in listOfResults] for listOfResults in res ]
def extractNumFeatures(resultsFileName) : r = myio.load(resultsFileName) numFeatures = {} if type(r) == type({}) : info = misc.extractAttribute(r, 'foldInfo') for key in info : numFeat = [] for lines in info[key] : for line in lines.split('\n') : if line.find('number of features') == 0 : numFeat.append(float(line.split(':')[1])) numFeatures[key] = numpy.average(numFeat) return numFeatures
def extractNumFeatures(resultsFileName): r = myio.load(resultsFileName) numFeatures = {} if type(r) == type({}): info = misc.extractAttribute(r, 'foldInfo') for key in info: numFeat = [] for lines in info[key]: for line in lines.split('\n'): if line.find('number of features') == 0: numFeat.append(float(line.split(':')[1])) numFeatures[key] = numpy.average(numFeat) return numFeatures
def loadResults(fileName, isNewFormat = True) : """ isNewFormat -- whether the Results were saved under version 0.6.1 or newer """ res = myio.load(fileName) if not isNewFormat : return ClassificationResults([res]) if type(res) == type({}) : results = {} for key in res : results[key] = ClassificationResults(res[key]) return results if type(res[0]) == type([]) : return ResultsList(res) else : return ClassificationResults(res)