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First suggestion for restart #3

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1805cea
First suggestion for restart
p-lauer Jun 6, 2017
bec84f3
Update fscabc.py
p-lauer Jun 6, 2017
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111 changes: 73 additions & 38 deletions spotpy/algorithms/fscabc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,8 +67,27 @@ def __init__(self, spot_setup, dbname=None, dbformat=None, parallel='seq', save_
def mutate(self, r):
x = 4 * r * (1 - r)
return x

def readbreakdata(self, dbname):
import pickle
import pprint
with open(dbname+'.break', 'rb') as csvfile:
work,r,icall,gnrng =pickle.load(csvfile)
pprint.pprint(work)
pprint.pprint(r)
pprint.pprint(icall)
pprint.pprint(gnrg)
return work, r, icall, gnrg

def sample(self, repetitions, eb=48, a=(1 / 10), peps=0.0001, kpow=5, ownlimit=False, limit=24):
def writebreakdata(self,dbname, work, r,icall,gnrg):
import pickle
with open(str(dbname)+'.break', 'wb') as csvfile:
work=work,r,icall,gnrg
pickle.dump(work,csvfile)



def sample(self, repetitions, eb=48, a=(1 / 10), peps=0.0001, kpow=5, ownlimit=False, limit=24,breakpoint=None, backup_every_rep=100):
"""


Expand All @@ -81,13 +100,17 @@ def sample(self, repetitions, eb=48, a=(1 / 10), peps=0.0001, kpow=5, ownlimit=F
a: float
mutation factor
peps: float
convergence criterium
convergence criterion
kpow: float
exponent for power scaling method
ownlimit: boolean
determines if an userdefined limit is set or not
limit: int
sets the limit
sets the limit for scout bee phase
breakpoint: None, 'write', 'read' or 'readandwrite'
None does nothing, 'write' writes a breakpoint for restart as specified in backup_every_rep, 'read' reads a breakpoint file with dbname + '.break', 'readandwrite' does both
backup_every_rep: int
writes a breakpoint after every generation, if more at least the specified number of samples are carried out after writing the last breakpoint
"""
# Initialize the progress bar
starttime = time.time()
Expand All @@ -105,41 +128,50 @@ def sample(self, repetitions, eb=48, a=(1 / 10), peps=0.0001, kpow=5, ownlimit=F
r = 0.25
while r == 0.25 or r == 0.5 or r == 0.75:
r = random.random()
# Initialization
work = []
firstcall = True
# Calculate the objective function
param_generator = (
(rep, self.parameter()['random']) for rep in range(eb))
for rep, randompar, simulations in self.repeat(param_generator):
# Calculate fitness
like = self.objectivefunction(
evaluation=self.evaluation, simulation=simulations)
self.status(rep, like, randompar)
if firstcall == True:
self.initialize_database(randompar, self.parameter()['name'], simulations, like)
firstcall = False
# Save everything in the database
self.datawriter.save(like, randompar, simulations=simulations)
c = 0
p = 0
# (fit_x,x,fit_v,v,limit,normalized fitness)
work.append([like, randompar, like, randompar, c, p])
# Progress bar
acttime = time.time()
# get str showing approximate timeleft to end of simulation in H,
# M, S
timestr = time.strftime("%H:%M:%S", time.gmtime(round(((acttime - starttime) /
(rep + 1)) * (repetitions - (rep + 1)))))
# Refresh progressbar every second
if acttime - intervaltime >= 2:
text = '%i of %i (best like=%g) est. time remaining: %s' % (rep, repetitions,
self.status.objectivefunction, timestr)
print(text)
intervaltime = time.time()
icall = 0
gnrng = 1e100
# and criter_change>pcento:
if breakpoint == None or breakpoint == 'write':
# Initialization
work = []
firstcall = True
# Calculate the objective function
param_generator = (
(rep, self.parameter()['random']) for rep in range(eb))
for rep, randompar, simulations in self.repeat(param_generator):
# Calculate fitness
like = self.objectivefunction(
evaluation=self.evaluation, simulation=simulations)
self.status(rep, like, randompar)
if firstcall == True:
self.initialize_database(randompar, self.parameter()['name'], simulations, like)
firstcall = False
# Save everything in the database
self.datawriter.save(like, randompar, simulations=simulations)
c = 0
p = 0
# (fit_x,x,fit_v,v,limit,normalized fitness)
work.append([like, randompar, like, randompar, c, p])
# Progress bar
acttime = time.time()
# get str showing approximate timeleft to end of simulation in H,
# M, S
timestr = time.strftime("%H:%M:%S", time.gmtime(round(((acttime - starttime) /
(rep + 1)) * (repetitions - (rep + 1)))))
# Refresh progressbar every second
if acttime - intervaltime >= 2:
text = '%i of %i (best like=%g) est. time remaining: %s' % (rep, repetitions,
self.status.objectivefunction, timestr)
print(text)
intervaltime = time.time()
icall = 0
gnrng = 1e100
# and criter_change>pcento:
elif breakpoint == 'read' or breakpoint == 'readandwrite':
datafrombreak=self.readbreakdata(dbname)
r=datafrombreak[1]
work=datafrombreak[0]
icall = datafrombreak[2]
gnrng = datafrombreak[3]
#Here database needs to be reinvoked
#Bee Phases
while icall < repetitions and gnrng > peps:
# Employed bee phase
# Generate new input parameters
Expand Down Expand Up @@ -241,6 +273,9 @@ def sample(self, repetitions, eb=48, a=(1 / 10), peps=0.0001, kpow=5, ownlimit=F
text = '%i of %i (best like=%g) est. time remaining: %s' % (
icall, repetitions, self.status.objectivefunction, timestr)
print(text)
if breakpoint == 'write' or breakpoint == 'readandwrite' and icall >= lastbackup+backup_every_rep:
self.writebreakdata(self.dbname, work,r,icall,gnrng)
lastbackup=icall
if icall >= repetitions:
print('*** OPTIMIZATION SEARCH TERMINATED BECAUSE THE LIMIT')
print('ON THE MAXIMUM NUMBER OF TRIALS ')
Expand Down