def OptimizeChromosome(self, chromosome):
chromosomeQuality = dict()
for gene in chromosome:
chromosomeQuality[gene] = self.CalculateCachedLinkQuality(gene)
return sorted(chromosomeQuality, key=chromosomeQuality.get, reverse = True)
def Plot(self):
raise NotImplemented
def Display(self):
raise NotImplemented
gsa = GSA()
sc = Scrapper(str(input("Enter search query: ")), 20)
urls = set(sc.getLinks())
urlDict = dict()
for index, url in enumerate(urls):
urlDict[index] = url
gsa.genes = urlDict.keys()
for key, value in urlDict.iteritems():
features = sc.getFeatures(value)
gsa.bounceRate[key] = features[0]
gsa.pageView[key] = features[1]
gsa.time[key] = features[2]
gsa.searchVisit[key] = features[3]
gsa.linkIn[key] = features[4]
gsa.bounceRate = gsa.NormalizeFeature(gsa.bounceRate)
chromosomeQuality[gene] = self.CalculateCachedLinkQuality(gene)
return sorted(chromosomeQuality,
key=chromosomeQuality.get,
reverse=True)
def Plot(self):
raise NotImplemented
def Display(self):
raise NotImplemented
gsa = GSA()
sc = Scrapper(str(input("Enter search query: ")), 20)
urls = set(sc.getLinks())
urlDict = dict()
for index, url in enumerate(urls):
urlDict[index] = url
gsa.genes = urlDict.keys()
for key, value in urlDict.iteritems():
features = sc.getFeatures(value)
gsa.bounceRate[key] = features[0]
gsa.pageView[key] = features[1]
gsa.time[key] = features[2]
gsa.searchVisit[key] = features[3]
gsa.linkIn[key] = features[4]
gsa.bounceRate = gsa.NormalizeFeature(gsa.bounceRate)
gsa.pageView = gsa.NormalizeFeature(gsa.pageView)
