def main():
print("Shorest Job First...")
# Sorting the dictionary in terms of each jobs length
# drive function reads in input from file and turns it into dictionary
for v in sorted(drive(), key=lambda x: x[1][1]):
print("Running task = {} {} {} for {} units.\n".format(
v[0], v[1][0], v[1][1], v[1][1]))
def main():
print("Scheduling priority round robin...\n")
a = [] # slice list
for v in sorted(drive(), key=lambda x: x[1][0]):
slice = v[1][1]
a.append(slice) # add time to list
#sort dic dictionary by priority
dic = sorted(drive(), key=lambda x: x[1][0])
# pass list, dictionary and indicator to robin function
# indicator tells the function if it is its first time being passed into the
#robin function
# 0 indicates its first time
robin(a, dic, 0)
while sum(a) != 0:
# 1 indicates its not thie first time its been passed to robin
robin(a, dic, 1)
def step():
x, y, theta = io.getPosition()
robot.slimeX.append(x)
robot.slimeY.append(y)
# the following lines compute the robot's current position and angle
currentPoint = util.Point(x,y).add(robot.initialLocation)
currentAngle = util.fixAnglePlusMinusPi(theta)
fv, rv = driver.drive(robot.path, currentPoint, currentAngle)
io.setForward(fv)
io.setRotational(rv)
def on_step():
x, y, theta = io.get_position(cheat=True)
robot.slime_x.append(x)
robot.slime_y.append(y)
checkoff.update(globals())
# the following lines compute the robot's current position and angle
current_point = util.Point(x,y).add(robot.initial_location)
current_angle = theta
forward_v, rotational_v = drive(robot.path, current_point, current_angle)
io.set_forward(forward_v)
io.set_rotational(rotational_v)
def floodResult():
if request.method == 'POST':
if len(request.form['DATE']) == 0:
return redirect(url_for('floodHome'))
else:
user_date = request.form['DATE']
river = request.form['SEL']
results_dict = driver.drive(river, user_date)
print("-----------", type(results_dict), "----------")
Table = []
for key, value in results_dict.items():
Table.append(value)
return render_template('flood_result.html', result=Table)
else:
return redirect(url_for('floodHome'))
def predict():
user_date = request.form['Date']
river = request.form['River']
print(river, user_date)
results_dict, classification_metrics, data, fut = driver.drive(
river, user_date)
if fut is 0:
data["Date"] = data["Date"].astype(str)
results_dict["Data"] = data.to_dict()
results_dict["Classification Report"] = classification_metrics
response = app.response_class(response=json.dumps(results_dict),
mimetype='application/json')
return response
def test_e2e():
opts = {
'PLAYERS': [(10, 0), (0, 1), (0, 2)],
'N_CONNECTIONS': 3,
'TIME_TO_SIM': 2,
'MEAN_PROP_TIME': 0.1,
'STD_PROP_TIME': 0.001,
'SEED': 20,
'GRAPH': False
}
os.system('./run_server.sh &')
time.sleep(5) # allow the server to boot up
sol = driver.drive(opts)
correctHashes = player.Player.correctHashes
for i in sol.players:
assert len(i.blockchain) > 0
for j in range(len(i.blockchain)):
assert i.blockchain[j] == correctHashes[j]
def floodResult():
if request.method == 'POST':
if len(request.form['DATE']) == 0:
return redirect(url_for('floodHome'))
else:
user_date = request.form['DATE']
river = request.form['SEL']
# print("##3#######",user_date,"#####",river,"#############")
# print(type(user_date))
# print(type(river))
results_dict = driver.drive(river, user_date)
# results_dict={'Mse':0.5,
# 'discharge':1400}
print("-----------", type(results_dict), "----------")
Table = []
for key, value in results_dict.items():
# temp = []
# temp.extend([key,value]) #Note that this will change depending on the structure of your dictionary
Table.append(value)
return render_template('flood_result.html', result=Table)
else:
return redirect(url_for('floodHome'))
def floodResult():
if request.method == 'POST':
# pdb.set_trace()
if len(request.form['DATE']) == 0:
flash("Please Enter Data!!")
return redirect(url_for('floodHome'))
else:
user_date = request.form['DATE']
river = request.form['SEL']
results_dict = driver.drive(river, user_date)
# results_dict={'Mse':0.5,
# 'discharge':1400}
print("-----------", type(results_dict), "----------")
Table = []
key: object
for key, value in results_dict.items():
#df = pd.DataFrame.from_dict(data)
#temp = []
#temp.extend([key, value])
Table.append(value)
return render_template('flood_result.html', result=Table)
else:
return redirect(url_for('floodHome'))
def main(argv):
volume = DetectorVolume(1000.0, 1000.0)
wirePitches = [5.0, 5.0, 5.0]
angles = driver.generateAngles(len(wirePitches))
numbersOfBlobs = [3]
alphas = [0.01]
numberOfIterations = 100
for numberOfBlobs in numbersOfBlobs:
for alpha in alphas:
c1 = root.TCanvas("RecoRateCanvas", "RecoRateCanvas", 200, 10, 700,
500)
correctFractions = root.TH1F("correctFractions",
("Correct Identification Fraction"),
100, -0.1, 1.1)
fakeFractions = root.TH1F("fakeFractions",
("Fake Identification Fraction"), 100,
-0.1, 1.1)
for i in range(numberOfIterations):
blobs, cells, channelList, geometryMatrix, recoWireMatrix, recoCellMatrix, trueCellMatrix = driver.drive(
volume, wirePitches, angles, numberOfBlobs, alpha)
recoCells = list(
map(lambda x: not math.isclose(x, 0, rel_tol=1e-5),
recoCellMatrix))
trueCells = list(
map(lambda x: not math.isclose(x, 0, rel_tol=1e-5),
trueCellMatrix))
correctID = sum(
bool(x[0]) and bool(x[1])
for x in zip(trueCells, recoCells))
fakeID = sum(not bool(x[0]) and bool(x[1])
for x in zip(trueCells, recoCells))
correctFraction = correctID / len(blobs)
fakeFraction = fakeID / len(blobs)
correctFractions.Fill(correctFraction)
fakeFractions.Fill(fakeFraction)
correctFractions.SetTitle("")
correctFractions.GetYaxis().SetTitleSize(0.04)
correctFractions.GetYaxis().SetTitleOffset(1.2)
correctFractions.GetYaxis().SetLabelSize(0.04)
correctFractions.GetXaxis().SetTitleSize(0.04)
correctFractions.GetXaxis().SetTitleOffset(1)
correctFractions.GetXaxis().SetLabelSize(0.04)
correctFractions.SetLineWidth(2)
fakeFractions.SetLineWidth(2)
# correctFractions.SetLineStyle(2)
fakeFractions.SetLineStyle(2)
correctFractions.SetLineColor(root.kBlue)
fakeFractions.SetLineColor(root.kRed)
root.gStyle.SetOptStat(0)
correctFractions.Draw("HIST")
fakeFractions.Draw("HIST SAMES")
root.gApplication.Run()
--nconnections=<ncons> number of connections per person in the network [default: 3]
--timetosim=<timetosim> virtual time in seconds to simulate the system for [default: 10]
--meanproptime=<meanproptime> mean propagation time of messages (latency) [default: 1]
--stdproptime=<stdproptime> std deviation of the propagation time of messages [default: 0.1]
--seed=<seed> random seed [default: 42]
-g generate graph animation
--help show this
"""
import random
import grpc
from docopt import docopt
import driver
import player
import solver
if __name__ == "__main__":
args = docopt(__doc__)
opts = {
"PLAYERS": eval(args["--players"]),
"N_CONNECTIONS": int(args["--nconnections"]),
"TIME_TO_SIM": int(args["--timetosim"]),
"MEAN_PROP_TIME": float(args["--meanproptime"]),
"STD_PROP_TIME": float(args["--stdproptime"]),
"SEED": int(args["--seed"]),
"GRAPH": bool(args["-g"]),
}
driver.drive(opts)
def main():
print("Scheduling priority...\n")
for v in sorted(drive(), key=lambda x: x[1][0]):
print("Running task = {} {} {} for {} units.\n".format(
v[0], v[1][0], v[1][1], v[1][1]))
s.listen(10)
# total number of stops
while True:
# continue to prompt until correct stop number has been entered
while True:
conn, addr = s.accept()
buffer = conn.recv(64)
stopNumber = int(buffer)
conn.close()
if stopNumber > 0 and stopNumber < STOP_COUNT:
break
else:
print "Invalid stop number, please try again..."
# wait until cups have been placed
detector.setup()
# drive to stop
driver.drive(stopNumber)
# wait until cups have been picked up
detector.dropoff()
# return home
driver.drive(STOP_COUNT - stopNumber)
# message
print "Arrived back home!!"
#a = os.path.join("India")
count = 0
for i in range(len(username)):
count += 1
#print(count)
a = open(os.path.join(sys.argv[1],str(username[i]).replace(':','-').replace('?','-').replace('|','-').replace('/','-').replace("\\","-")+'.txt'),'w',encoding = 'utf-8')
#if len(text[i]) > 1:
#print(username[i])
for j in range(0,len(text[i])):
#text[i][j].replace('[',' ').replace(']',' ').replace('<')
new_str = re.sub('[^a-zA-Z0-9\n\.]', ' ', text[i][j])
text[i][j] = new_str
lda_model=gensim.models.LdaModel.load('lda.model')
id2word={}
f = open("file.pkl","rb")
id2word=pickle.load(f)
pp=getTopicForQuery(new_str,lda_model,id2word)
a.write(new_str)
a.write('\n-------------------||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||---------------------------\n')
#print(pp)
mat[i]=pp
a.close()
#print(users[2])
#for i in range(len(username)):
# print(mat[i])
drive(mat)
def efficiencyPurityGraph(volume, wirePitches, angles, numberOfBlobs, alphas,
numberOfIterations):
efficiency = array('f', len(alphas) * [0.])
purity = array('f', len(alphas) * [0.])
eventNo = 0
for pointNo, alpha in enumerate(alphas):
correctSum = 0
fakeSum = 0
for i in range(numberOfIterations):
blobs, cells, channelList, geometryMatrix, recoWireMatrix, recoCellMatrix, trueCellMatrix = driver.drive(
volume, wirePitches, angles, numberOfBlobs, alpha)
if (eventNo % 1000 == 0) or (eventNo == 0):
print("Processed ", eventNo, "/",
len(alphas) * numberOfIterations, " events")
eventNo += 1
recoCells = list(
map(lambda x: not math.isclose(x, 0, rel_tol=1e-5),
recoCellMatrix))
trueCells = list(
map(lambda x: not math.isclose(x, 0, rel_tol=1e-5),
trueCellMatrix))
correctID = sum(
bool(x[0]) and bool(x[1]) for x in zip(trueCells, recoCells))
fakeID = sum(not bool(x[0]) and bool(x[1])
for x in zip(trueCells, recoCells))
correctSum += correctID / len(blobs)
fakeSum += fakeID / len(blobs)
efficiency[pointNo] = correctSum / numberOfIterations
purity[pointNo] = 1 - fakeSum / numberOfIterations
g = root.TGraph(len(alphas), efficiency, purity)
return g
--players=<players> list of tuples e.g. "[(# of players, player type), ...]"; player type 0 = honest node, 1 = failure stop, 2 = fuzz test, 3 = byzantine fault [default: [(10, 0)]]
--nconnections=<ncons> number of connections per person in the network [default: 3]
--timetosim=<timetosim> virtual time in seconds to simulate the system for [default: 10]
--meanproptime=<meanproptime> mean propagation time of messages (latency) [default: 1]
--stdproptime=<stdproptime> std deviation of the propagation time of messages [default: 0.1]
--seed=<seed> random seed [default: 42]
-g generate graph animation
--help show this
"""
import random
import grpc
from docopt import docopt
import driver
import player
import solver
if __name__=="__main__":
args = docopt(__doc__)
opts = {"PLAYERS": eval(args["--players"]),
"N_CONNECTIONS": int(args["--nconnections"]),
"TIME_TO_SIM": int(args["--timetosim"]),
"MEAN_PROP_TIME": float(args["--meanproptime"]),
"STD_PROP_TIME": float(args["--stdproptime"]),
"SEED": int(args["--seed"]),
"GRAPH": bool(args["-g"]),
}
driver.drive(opts)
def main():
print("First Come First Served...")
# calling drive function to read the input and turn it into a dictionary
for v in drive():
print("Running task = {} {} {} for {} units\n".format(
v[0], v[1][0], v[1][1], v[1][1]))