# 3-sigma target yield
yt=YieldTargeting(
designParams, statParams, opParams,
heads, analyses, measures, variables=variables,
beta=3.0, wcSpecs=wcList,
# Comment out to use default initial point (lo+hi)/2
# initial=atDesign,
initialNominalDesign=True,
# Norms for measures with zero goal
norms={ 'area': 100e-12, 'vgs_drv': 1e-3, 'vds_drv':1e-3 },
tradeoffs=1e-6, # Tradeoff optimization weight, can be overridden in *CbdOptions
stopWhenAllSatisfied=True,
# Initial nominal optimization
initialCbdOptions={
'debug': 1, 'method': 'global', 'stepTol': 1e-5,
},
# Main optimization
cbdOptions={
'debug': 1, 'method': 'global', 'stepTol': 1e-5,
}, wcOptions={ 'debug': 0 },
debug=2, spawnerLevel=1
)
atDesign, agg, wc, anCount = yt()
print(formatParameters(atDesign))
print(wc.formatResults())
print(agg.formatResults())
print(anCount)
# Finalize cOS parallel environment
cOS.finalize()
'area': 100e-12,
'vgs_drv': 1e-3,
'vds_drv': 1e-3
},
tradeoffs=
1e-6, # Tradeoff optimization weight, can be overridden in *CbdOptions
stopWhenAllSatisfied=True,
# Initial nominal optimization
initialCbdOptions={
'debug': 1,
'method': 'local',
'stepTol': 1e-5,
},
# Main optimization
cbdOptions={
'debug': 1,
'method': 'local',
'stepTol': 1e-5,
},
wcOptions={'debug': 0},
debug=2,
spawnerLevel=1)
atDesign, agg, wc, anCount = yt()
print(formatParameters(atDesign))
print(wc.formatResults())
print(agg.formatResults())
print(anCount)
# Finalize cOS parallel environment
cOS.finalize()