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.
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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.
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pyopus.design.
wcd2yield
(beta)[source]¶ Computes the yield that corresponds to the worst case distance beta.
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pyopus.design.
yieldSigma
(y, nSamples)[source]¶ Computes the standard deviation of estimated yield y computed with nSamples Monte Carlo samples.
- 6.1.
pyopus.design.sensitivity
— Finite difference sensitivity computation and parameter screening - 6.2.
pyopus.design.wc
— Worst case performance computation - 6.3.
pyopus.design.wcd
— Worst case distance computation - 6.4.
pyopus.design.mc
— Monte Carlo analysis - 6.5.
pyopus.design.cbd
— Sizing across corners - 6.6.
pyopus.design.yt
— Yield targeting (design for yield) - 6.7.
pyopus.design.sqlite
— Support for sqlite database