def get_neighborhood(center,result,start,end,step,typ,p,conf,alpha):
for c in conf:
if c in typ.keys():
if typ[c] == "exp":
# New range of values for the conf c
r = int((end[c] - start[c])*alpha)
# So that it doesn't go below the already set low limit
start[c] = utils.roundMultiple(max(math.log(center[c],2)-round(r/2),start[c]),step[c])
end[c] = utils.roundMultiple(min(math.log(center[c],2)+round(r/2),end[c]),step[c])
else:
r = int((end[c] - start[c])*alpha)
start[c] = utils.roundMultiple(max(center[c]-round(r/2),start[c]),step[c])
end[c] = utils.roundMultiple(min(center[c]+round(r/2),end[c]),step[c])
return start,end
def generate_LHS(result,start,end,step,typ,relations,p,conf,size):
lhm = lhs(len(conf),samples=size)
lhs_space = list(dict())
for i in range(0,len(lhm)):
sample = lhm[i]
j =0
print sample
#print typ
for c in conf:
if c in typ.keys():
if typ[c] == "boolean":
# FIXME: This shouldn't be a random choice
result[c] = random.choice([True,False])
else:
result[c] = pow(2,int(start[c] + (end[c] - start[c])*sample[j]))
else:
result[c] = utils.roundMultiple(int(start[c] + (end[c] - start[c])*sample[j]), step[c])
if c in relations:
for e in relations[c]:
result[e] = pow(2,int(math.ceil(math.log(result[c],2))))
if result[c]*1.1>result[e]:
result[e] = pow(2,int(math.ceil(math.log(result[c],2)))+1)
j +=1
lhs_space.append(dict(result))
return lhs_space
def put_limits(value, start, end, step):
if value < start:
return start
elif value > end:
return end
else:
return utils.roundMultiple(value, step)
def generate_initial(result, start, end, step, typ, relations, p, conf):
cores = int(core_count.get())
threads = np.random.dirichlet([1000, 1000, 1000, 1000, 1000], 1)
k = 0
print conf
for c in conf:
if c in typ.keys():
if typ[c] == "boolean":
# FIXME: This shouldn't be a random choice
result[c] = False
else:
result[c] = pow(2, int(start[c]))
else:
if "component.spout" in c or "topology.acker" in c:
result[c] = result["topology.workers"]
elif "component" in c:
#Max so that it never gets below the min of one executor per bolt per worker
result[c] = max(
result["topology.workers"],
roundDownMultiple(
(cores - 1 - 3 * int(result["topology.workers"])) *
threads[0][k], result["topology.workers"]))
k += 1
else:
result[c] = utils.roundMultiple(int(start[c]), step[c])
if c in relations:
for e in relations[c]:
result[e] = pow(2, int(math.ceil(math.log(result[c], 2))))
if result[c] * 1.1 > result[e]:
result[e] = pow(2,
int(math.ceil(math.log(result[c], 2))) + 1)
print result
return result
def get_pbest(design_space, numbers, conf, metric_values, start, end, step,
typ, relations):
vals = dict(list())
y = dict(list())
config = dict()
for c in conf:
vals[c] = list()
y[c] = list()
if c not in typ.keys():
count = 0
for i in numbers:
vals[c].append(design_space[i][c])
y[c].append(metric_values[count])
count += 1
elif typ[c] == "exp":
count = 0
for i in numbers:
vals[c].append(design_space[i][c])
y[c].append(metric_values[count])
count += 1
for c in conf:
if c not in typ.keys():
z = numpy.polyfit(vals[c], y[c], 2)
f = numpy.poly1d(z)
bounds = [start[c], end[c]]
crit_points = bounds + [
x for x in f.deriv().r
if x.imag == 0 and bounds[0] < x.real < bounds[1]
]
crit_vals = [f(x) for x in crit_points]
minimum = min(crit_vals)
config[c] = utils.roundMultiple(
crit_points[crit_vals.index(minimum)], step[c])
elif typ[c] == "exp":
z = numpy.polyfit(vals[c], y[c], 2)
f = numpy.poly1d(z)
bounds = [start[c], end[c]]
crit_points = bounds + [
x for x in f.deriv().r
if x.imag == 0 and bounds[0] < x.real < bounds[1]
]
crit_vals = [f(x) for x in crit_points]
minimum = min(crit_vals)
config[c] = pow(2, int(crit_points[crit_vals.index(minimum)]))
if c in relations:
for e in relations[c]:
config[e] = pow(2, int(math.ceil(math.log(config[c], 2))))
if config[c] * 1.1 > config[e]:
config[e] = pow(2,
int(math.ceil(math.log(config[c], 2))) + 1)
return config