def pollack_boxcox_uncertainty(d, perc):
mean = get_pollack(d)
std = mean * perc
gt_perf = pollack_uncertainty(d, perc)
if std:
return Distribution.DistributionFromBoxCoxGaussian(mean, std, gt_perf._mcpts, lower=0)
else:
return gt_perf
def fabrication_boxcox_uncertainty(d, n):
if n > 0:
func = UncertaintyModel.fabrication()
gt = func(d, n)
tgt_mean = gt.mean
tgt_std = gt.var ** .5
return Distribution.DistributionFromBoxCoxGaussian(tgt_mean, tgt_std, gt._mcpts, lower=0)
else:
return 0
def design_pollack_boxcox_uncertainty(d, p0, perc):
mean = get_pollack(d)
std = mean * perc
gt_perf = design_pollack_uncertainty(d, p0, perc)
if std:
tgt_mean = gt_perf.mean
tgt_std = gt_perf.var ** .5
return Distribution.DistributionFromBoxCoxGaussian(tgt_mean, tgt_std, gt_perf._mcpts, lower=0)
else:
return gt_perf