def hillclimberMain(data, iterationNumber): '''Calls different functions to perform hillclimber''' colorNumber = 2 # prepare list colorList = [0] * len(data) # color graph randomly for i in range (0, len(colorList) - 1): colorList[i] = random.randint(0, colorNumber) output = check.Checklist(colorList, data) # keep iterating as long as there are still errors while(len(output) != 0): # try to eliminate errors with iteration colorList = hillclimber(iterationNumber, colorNumber, colorList, data) # check if there are still errors output = check.Checklist(colorList, data) # if errors increase color number colorNumber = colorNumber + 1 graph.makeGraph(colorList, data) return colorList
def detalleAnimal(id):
if 'nombre' in session:
print(id + ' IDDDDDDDDDDDDDDDDD')
makeGraph(id)
data = getAnimalDetail(id)
source = "../static/grafica{0}.png".format(id)
return render_template("animalHistoryGraph.html",
details=data,
source=source)
else:
return render_template('login.html')
def systematicApproach(l):
for counter, option in enumerate(narrow_list):
SAresults = search(option)
SAresults = search(option)
SA_id_list = SAresults['IdList']
summary_details(SA_id_list)
remove_supp_authors(m_lastAuthor, m_authorList)
graph.makeGraph(authorDict)
graph.nodeDegree(graph.g)
graph.graphRP(graph.PgenL, graph.RgenL)
graph.graphAnalysis(graph.g, counter)
#graph.writeToCSV(graph.clusterCo, graph.eig_cen, graph.deg_cen, counter)
#graph.inclusiveGraphs(graph.communities, graph.densities)
graph.printGraphingLists(graph.communities, graph.totalNodes,
graph.degreeCentAvg, graph.degreeCentMedian,
graph.betweennessCent, graph.clusterCoAvg)
def main(algorithm, network, isMapType): '''Calls different functions to color a network''' # ----------------------------- Select data type ----------------------------- # load in data if network is 'random': totalConnections, tuplesList = randomconnections.randomConnections(20, 0, 190) data = socialload.loadData(tuplesList) elif isMapType is True: loadin.loadData(network) else: socialload.loadData(network) # ----------------------------- Select algorithm ----------------------------- # color network if algorithm is 'shell': colorList = lowestcolor.shell(data, None) # color islands too for i, a in enumerate(colorList): if a == None: colorList = lowestcolor.shell(data, i) elif algorithm is 'annealing': colorList = annealing.annealingMain(data, 10000) elif algorithm is 'hillclimber': colorList = hillclimber.hillclimberMain(data, 10000) elif algorithm is 'degree': colorList = lowestcolor.degree(data) elif algorithm is 'hybrid': colorList = hybrid.algorithm(data) elif algorithm is 'clockwise': colorList = lowestcolor.clockwise(data, None) # color islands too for i, a in enumerate(colorList): if a == None: colorList = lowestcolor.clockwise(data, i) # check if no errors output = check.Checklist(colorList, data) print output # ----------------------------- Obtain testdata ----------------------------- # Test degree maximum = len(data[lowestcolor.getLongest(data)][1]) # find biggest clique figurelist = figuresearch.buildFigures(data) biggest = figuresearch.findBiggestClique(figurelist) colors = check.checkColors(colorList) # make graph of colored network graph.makeGraph(colorList, data)
from Bio import Entrez
import graph
import utilities
Entrez.email = '*****@*****.**'
Entrez.api_key = 'f513b4e2e1a0b578c9d3dd731e36f19f7f08'
def __init__(self, email):
Entrez.email = '*****@*****.**'
Entrez.api_key = 'f513b4e2e1a0b578c9d3dd731e36f19f7f08'
if __name__ == '__main__':
results = utilities.search('etiology')
id_list = results['IdList']
papers = utilities.fetch_details(id_list)
utilities.summary_details(id_list)
utilities.systematicApproach(utilities.narrow_list)
utilities.remove_supp_authors(utilities.m_lastAuthor,
utilities.m_authorList)
graph.makeGraph(utilities.authorDict)
graph.nodeDegree(graph.g)
graph.graphAnalysis(graph.g)
def makeQueries(filename):
"""creates a graph(list of cities) from the flightdata file
returns a list of cities (each containing a list of flights)"""
f = open(filename, 'r')
queries = []
for q in f.read().replace("\n",
"").replace("]",
"").replace(" ",
"").strip().split("["):
if q != "":
q = q.replace("(", "")
q = q.replace(")", "")
parts = q.split(',')
currQ = flightClasses.Query(parts[0], parts[1], parts[2], parts[3],
parts[4], parts[5], parts[6],
int(parts[7]))
queries.append(currQ)
return queries
#testing file for the project
g = graph.makeGraph(sys.argv[1])
q = makeQueries(sys.argv[2])
for k in q:
x = algorithm.getFlightSolutions(k, g)
ret = str(flightClasses.printSolutions(k, x)) + "\n"
print(ret)
# Pages definition file. Page response handler classes should be defined here.
import tornado.web
import tornado.template
import graph
import flightClasses
import algorithm
g = graph.makeGraph("testFiles/testdata2")
class LandingHandler(tornado.web.RequestHandler):
"""Class which allows users to make requests for flights
Additionally, request responses will be displayed as an element of the
page this class genereates.
"""
def get(self):
loader = tornado.template.Loader("templates/")
self.write(
loader.load("landing.html").generate(cities=sorted(g.getCityNames()), airlines=["None"] + g.getAirlines())
)
class QueryHandler(tornado.web.RequestHandler):
"""Class which handles a request for flights"""
def get(self):
loader = tornado.template.Loader("templates/")
if self.get_argument("origCity") == self.get_argument("desCity"):
self.write(
temp[random.randint(0, size - 1)] = random.randint(0, max_col)
new_len = len(check.Checklist(temp, data))
delta_score = new_len - max_error
a = delta_score / T
print a, delta_score, T
chance = math.exp(-(a))
# print chance
T = T * math.pow(g, i)
evaluate = random.uniform(0, 1)
if chance >= evaluate:
max_error = new_len
CCL = temp
i += 1
return CCL
def algorithm(data, CCL):
CCL = [0] * len(CCL)
for i in range(1, 100):
CCL = anealing(CCL, data, i, len(check.Checklist(CCL, data)))
if len(check.Checklist(CCL, data)) == 0:
break
# chaneColoring(CCL, check.Checklist(CCL, data), i, data)
return CCL
if __name__ == "__main__":
data = socialload.loadData('network1.txt')
CCL = [None] * len(data)
CCL = algorithm(data, CCL)
graph.makeGraph(countryColorList, data)
print("--- %s seconds ---" % (time.time() - start_time))
#Pages definition file. Page response handler classes should be defined here.
import tornado.web
import tornado.template
import graph
import flightClasses
import algorithm
g = graph.makeGraph("testFiles/testdata2")
class LandingHandler(tornado.web.RequestHandler):
"""Class which allows users to make requests for flights
Additionally, request responses will be displayed as an element of the
page this class genereates.
"""
def get(self):
loader = tornado.template.Loader("templates/")
self.write(loader.load("landing.html").generate(
cities=sorted(g.getCityNames()),
airlines=["None"] + g.getAirlines()
))
class QueryHandler(tornado.web.RequestHandler):
"""Class which handles a request for flights"""
def get(self):
loader = tornado.template.Loader("templates/")
if (self.get_argument("origCity") == self.get_argument("desCity")):
self.write(loader.load("errorResponse.html").generate(msg="The origin and destination city you entered are the same"))
else:
def historiaAnimal():
if 'nombre' in session:
makeGraph()
return render_template("animalHistory.html")
else:
return render_template('login.html')
def historiaAnimal():
makeGraph()
return render_template("animalHistory.html")
import sys
def makeQueries(filename):
"""creates a graph(list of cities) from the flightdata file
returns a list of cities (each containing a list of flights)"""
f = open(filename, "r")
queries = []
for q in f.read().replace("\n", "").replace("]", "").replace(" ", "").strip().split("["):
if q != "":
q = q.replace("(", "")
q = q.replace(")", "")
parts = q.split(",")
currQ = flightClasses.Query(
parts[0], parts[1], parts[2], parts[3], parts[4], parts[5], parts[6], int(parts[7])
)
queries.append(currQ)
return queries
# testing file for the project
g = graph.makeGraph(sys.argv[1])
q = makeQueries(sys.argv[2])
for k in q:
x = algorithm.getFlightSolutions(k, g)
ret = str(flightClasses.printSolutions(k, x)) + "\n"
print(ret)