# 6. pyopus.design — Design automation support¶

Design automation module

Provides functions and classes for computing sensitivity, sizing a design across corners, worst case performance, worst case distance, yield targeting, and Monte Carlo analysis.

pyopus.design.nSamples(y, deltaY, confidence=0.99)[source]

Computes the number of Monte Carlo samples needed for obtaining a yield estimate that is within +-deltaY of y with confidence level given by confidence.

pyopus.design.wcd2yield(beta)[source]

Computes the yield that corresponds to the worst case distance beta.

pyopus.design.yield2wcd(y)[source]

Computes the worst case distance that corresponds to yield y.

pyopus.design.yieldSigma(y, nSamples)[source]

Computes the standard deviation of estimated yield y computed with nSamples Monte Carlo samples.