import urllib
import tarfile
from pylab import *
ion() # may be needed for figures to be shown when executing the script
import bbob_pproc as bb
# Collect and unarchive data (~20MB)
dataurl = 'http://coco.lri.fr/BBOB2009/rawdata/BIPOP-CMA-ES_hansen_noiseless.tar.gz'
filename, headers = urllib.urlretrieve(dataurl)
archivefile = tarfile.open(filename)
archivefile.extractall()
# Display some information
ds = bb.load('BBOB2009rawdata/BIPOP-CMA-ES_hansen_noiseless/bbobexp_f2.info')
print ds
# Collect and unarchive data (3.4MB)
dataurl = 'http://coco.lri.fr/BBOB2009/pythondata/BIPOP-CMA-ES.tar.gz'
filename, headers = urllib.urlretrieve(dataurl)
archivefile = tarfile.open(filename)
archivefile.extractall()
# Load a pickle file
ds = bb.load('BBOB2009pythondata/BIPOP-CMA-ES/ppdata_f002_20.pickle')
# Load a folder
ds = bb.load('BBOB2009rawdata/BIPOP-CMA-ES_hansen_noiseless')
# Load data using a wildcard
import glob
import urllib
import tarfile
from pylab import *
ion() # may be needed for figures to be shown when executing the script
import bbob_pproc as bb
# Collect and unarchive data (~20MB)
dataurl = 'http://coco.gforge.inria.fr/data-archive/2009/BIPOP-CMA-ES_hansen_noiseless.tgz'
filename, headers = urllib.urlretrieve(dataurl)
archivefile = tarfile.open(filename)
archivefile.extractall()
# Display some information
ds = bb.load('BIPOP-CMA-ES/bbobexp_f2.info')
print ds
# Collect and unarchive data (3.4MB)
dataurl = 'http://coco.lri.fr/BBOB2009/pythondata/BIPOP-CMA-ES.tar.gz'
filename, headers = urllib.urlretrieve(dataurl)
archivefile = tarfile.open(filename)
archivefile.extractall()
# Load a pickle file
ds = bb.load('BBOB2009pythondata/BIPOP-CMA-ES/ppdata_f002_20.pickle')
# Load a folder
ds = bb.load('BIPOP-CMA-ES')
# Load data using a wildcard
import glob
picklefile = sys.argv[1]
dashidx = sys.argv.index("--")
algs = sys.argv[2:dashidx]
strats = sys.argv[dashidx + 1 :]
if os.path.exists(picklefile) or os.path.exists(picklefile + ".gz"):
pds = PortfolioDataSets(pickleFile=picklefile)
else:
pds = PortfolioDataSets()
for apath in algs:
print apath
aname = os.path.basename(os.path.normpath(apath))
pds.add_algorithm(aname, bb.load(glob.glob(apath + "/bbobexp_f*.info")))
for spath in strats:
print spath
sname = os.path.basename(os.path.normpath(spath))
pds.add_strategy(sname, bb.load(glob.glob(spath + "/bbobexp_f*.info") + glob.glob(spath + "/*/bbobexp_f*.info")))
# TODO: Make generating these optional?
print "bestalg"
pds.bestalg(None)
print "unifpf"
pds.unifpf()
# TODO: Pickle to tmp file and rename()?
print "Pickling..."
pds.pickle(picklefile)
'''
Generates "pprldistr2009_RLB.pickle.gz" that is used to plot, in the background, the results of the 2009 algorithms
'''
# datapath = "../../data-archive/data/gecco-bbob-1-24/2009/data"
datapaths = ["../../data-archive/data/gecco-bbob-1-24/2009/data", "../../data-archive/data/gecco-bbob-noisy/2009/data"]
savepath = "bbob_pproc/pprldistr2009_hardestRLB.pickle"
# savepath = "bbob_pproc/pprldistr2009_RLB.pickle"
import pickle
import bbob_pproc as bb
import numpy as np
data = {}
for datapath in datapaths:
print "loading data from", datapath
data2009 = bb.load(datapath)
Algs = data2009.dictByAlg()
target_runlengths_in_table = [0.5, 1.2, 3, 10, 50]
targets = bb.pproc.RunlengthBasedTargetValues(target_runlengths_in_table,
force_different_targets_factor = 10 ** -0.2)
for alg in Algs:
curAlg = Algs[alg].dictByFunc()
algname = curAlg[curAlg.keys()[0]][0].algId
if not data.has_key(algname):
data[algname] = {}
for func in curAlg:
data[algname][func] = {}
funcdata = curAlg[func].dictByDim()
for dim in funcdata:
data[algname][func][dim] = [[]]
curtarget = targets((func, dim))[-1]
data[algname][func][dim][0].append(curtarget) # record hardest target
import urllib
import tarfile
from pylab import *
ion() # may be needed for figures to be shown when executing the script
import bbob_pproc as bb
# Collect and unarchive data (~20MB)
dataurl = 'http://coco.gforge.inria.fr/data-archive/2009/BIPOP-CMA-ES_hansen_noiseless.tgz'
filename, headers = urllib.urlretrieve(dataurl)
archivefile = tarfile.open(filename)
archivefile.extractall()
# Display some information
ds = bb.load('BIPOP-CMA-ES/bbobexp_f2.info')
print ds
# Collect and unarchive data (3.4MB)
dataurl = 'http://coco.lri.fr/BBOB2009/pythondata/BIPOP-CMA-ES.tar.gz'
filename, headers = urllib.urlretrieve(dataurl)
archivefile = tarfile.open(filename)
archivefile.extractall()
# Load a pickle file
ds = bb.load('BBOB2009pythondata/BIPOP-CMA-ES/ppdata_f002_20.pickle')
# Load a folder
ds = bb.load('BIPOP-CMA-ES')
# Load data using a wildcard
import glob
picklefile = sys.argv[1]
dashidx = sys.argv.index('--')
algs = sys.argv[2:dashidx]
strats = sys.argv[dashidx+1:]
if os.path.exists(picklefile) or os.path.exists(picklefile + '.gz'):
pds = PortfolioDataSets(pickleFile=picklefile)
else:
pds = PortfolioDataSets()
for apath in algs:
print apath
aname = os.path.basename(os.path.normpath(apath))
pds.add_algorithm(aname, bb.load(glob.glob(apath+'/bbobexp_f*.info')))
for spath in strats:
print spath
sname = os.path.basename(os.path.normpath(spath))
pds.add_strategy(sname, bb.load(glob.glob(spath+'/bbobexp_f*.info') + glob.glob(spath+'/*/bbobexp_f*.info')))
# TODO: Make generating these optional?
print "bestalg"
pds.bestalg(None)
print "unifpf"
pds.unifpf()
# TODO: Pickle to tmp file and rename()?
print "Pickling..."
pds.pickle(picklefile)
