cocopp.algportfolio module documentationcocopp
Algorithm portfolio data set module.
The algorithm portfolio consists in running multiple algorithms in
parallel.
Current limitation: the portfolio data set must come from data sets that
are identical (same number of repetitions on the same instances of the
functions.
**Example:**
.. plot::
:width: 75%
import glob
from pylab import *
import pickle
import cocopp
import cocopp.compall.pprldmany
import cocopp.algportfolio
# Collect and unarchive data
dsets = {}
for alg in ('BIPOP-CMA-ES_hansen_noiseless', 'NEWUOA_ros_noiseless'):
dsets[alg] = cocopp.load(cocopp.bbob(alg))
# Generate the algorithm portfolio
dspf = cocopp.algportfolio.build(dsets)
dsets['Portfolio'] = dspf # store the portfolio in dsets
# plot the run lengths distribution functions
plt.figure()
for algname, ds in dsets.items():
dataset = ds.dictByDimFunc()[10][13] # DataSet dimension 10 on F13
cocopp.compall.pprldmany.plot(dataset, label=algname)
cocopp.compall.pprldmany.beautify()
legend(loc='best') # Display legend
plt.show()
| Class | Usage | Undocumented |
| Class | DataSet | Unit element of algorithm portfolio data set. |
| Function | build | Merge datasets in an algorithm portfolio. |
Merge datasets in an algorithm portfolio.
:param dict dictAlg: dictionary of data sets with algorithm name for
keys, see ``pproc.DataSetList.dictByAlg``
:param seq sortedAlgs: sequence for sorting the entries of
:py:data:`dictAlg`, if not provided,
dictAlg.keys() will be instead
:returns: an instance of :py:class:`DataSetList` with the porfolio
data sets