def straightMUa(bundles, revenue, pricePrediction, verbose = False):
if verbose:
print "straightMUa"
expectedPrices = pricePrediction.expectedValue()
return straightMV(bundles, revenue, expectedPrices, verbose)
def straightMU(bundles, revenue, pricePrediction, n_samples, verbose = False):
if verbose:
print "straightMU - Drawing {0} samples.".format(n_samples)
samples = pricePrediction.sample(n_samples = n_samples)
if verbose:
print "Samples:"
print "{0}".format(samples)
expectedPrices = numpy.mean(samples, 0)
if verbose:
print "Expected Price Vector: {0}".format(expectedPrices)
return straightMV( bundles, revenue, expectedPrices, verbose)
def averageMU(bundles, revenue, pricePrediction, nSamples, verbose = False):
if verbose:
print "averageMU - Drawing {0} samples.".format(nSamples)
bundleView = numpy.atleast_2d(bundles)
samples = pricePrediction.sample(n_samples = nSamples)
accum = numpy.zeros(bundleView.shape[1], dtype = 'float')
#accumulate sum of marginal utility
for sample in samples:
accum += straightMV(bundles, revenue, sample, verbose)
#divide by number of samples for average
accum /= nSamples
if verbose:
print "bid = {0}".format(accum)
return accum
