// OpenSTA, Static Timing Analyzer // Copyright (c) 2025, Parallax Software, Inc. // // This program is free software: you can redistribute it and/or modify // it under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with this program. If not, see . // // The origin of this software must not be misrepresented; you must not // claim that you wrote the original software. // // Altered source versions must be plainly marked as such, and must not be // misrepresented as being the original software. // // This notice may not be removed or altered from any source distribution. #include "DelaySkewNormal.hh" #include // sqrt #include "Error.hh" #include "Fuzzy.hh" #include "Units.hh" #include "StaState.hh" #include "Variables.hh" namespace sta { float DelayOpsSkewNormal::stdDev2(const Delay &delay, const EarlyLate *) const { return delay.stdDev2(); } float DelayOpsSkewNormal::asFloat(const Delay &delay, const EarlyLate *early_late, const StaState *sta) const { // LVF: mean + mean_shift + sigma * sigma_factor with skewness consideration. float quantile = sta->variables()->pocvQuantile(); if (early_late == EarlyLate::early()) return delay.mean() + delay.meanShift() - delay.stdDev() * (quantile + delay.skewness() * (square(quantile)-1.0) / 6.0); else // (early_late == EarlyLate::late()) return delay.mean() + delay.meanShift() + delay.stdDev() * (quantile + delay.skewness() * (square(quantile)-1.0) / 6.0); } double DelayOpsSkewNormal::asFloat(const DelayDbl &delay, const EarlyLate *early_late, const StaState *sta) const { // LVF: mean + mean_shift + sigma * sigma_factor with skewness consideration. double quantile = sta->variables()->pocvQuantile(); if (early_late == EarlyLate::early()) return delay.mean() + delay.meanShift() - delay.stdDev() * (quantile + delay.skewness() * (square(quantile)-1.0) / 6.0); else // (early_late == EarlyLate::late()) return delay.mean() + delay.meanShift() + delay.stdDev() * (quantile + delay.skewness() * (square(quantile)-1.0) / 6.0); } bool DelayOpsSkewNormal::isZero(const Delay &delay) const { return fuzzyZero(delay.mean()) && fuzzyZero(delay.meanShift()) && fuzzyZero(delay.stdDev2()) && fuzzyZero(delay.skewness()); } bool DelayOpsSkewNormal::isInf(const Delay &delay) const { return fuzzyInf(delay.mean()); } bool DelayOpsSkewNormal::equal(const Delay &delay1, const Delay &delay2, const StaState *) const { return fuzzyEqual(delay1.mean(), delay2.mean()) && fuzzyEqual(delay1.meanShift(), delay2.meanShift()) && fuzzyEqual(delay1.stdDev2(), delay2.stdDev2()) && fuzzyEqual(delay1.skewness(), delay2.skewness()); } bool DelayOpsSkewNormal::less(const Delay &delay1, const Delay &delay2, const StaState *sta) const { return fuzzyLess(delayAsFloat(delay1, EarlyLate::early(), sta), delayAsFloat(delay2, EarlyLate::early(), sta)); } bool DelayOpsSkewNormal::less(const DelayDbl &delay1, const DelayDbl &delay2, const StaState *sta) const { return fuzzyLess(delayAsFloat(delay1, EarlyLate::early(), sta), delayAsFloat(delay2, EarlyLate::early(), sta)); } bool DelayOpsSkewNormal::lessEqual(const Delay &delay1, const Delay &delay2, const StaState *sta) const { return fuzzyLessEqual(delayAsFloat(delay1, EarlyLate::early(), sta), delayAsFloat(delay2, EarlyLate::early(), sta)); } bool DelayOpsSkewNormal::greater(const Delay &delay1, const Delay &delay2, const StaState *sta) const { return fuzzyGreater(delayAsFloat(delay1, EarlyLate::late(), sta), delayAsFloat(delay2, EarlyLate::late(), sta)); } bool DelayOpsSkewNormal::greaterEqual(const Delay &delay1, const Delay &delay2, const StaState *sta) const { return fuzzyGreaterEqual(delayAsFloat(delay1, EarlyLate::late(), sta), delayAsFloat(delay2, EarlyLate::late(), sta)); } Delay DelayOpsSkewNormal::sum(const Delay &delay1, const Delay &delay2) const { return Delay(delay1.mean() + delay2.mean(), delay1.meanShift() + delay2.meanShift(), delay1.stdDev2() + delay2.stdDev2(), skewnessSum(delay1, delay2)); } float DelayOpsSkewNormal::skewnessSum(const Delay &delay1, const Delay &delay2) const { return skewnessSum(delay1.stdDev(), delay1.skewness(), delay2.stdDev(), delay2.skewness()); } // Helper function to compute combined skewness from std dev and skewness values. double DelayOpsSkewNormal::skewnessSum(double std_dev1, double skewness1, double std_dev2, double skewness2) const { double std_dev_sum = square(std_dev1) + square(std_dev2); if (std_dev_sum == 0.0) return 0.0; else { // Un-normalize the skews so they are third moments so they can be added. double skew = (skewness1 * cube(std_dev1) + skewness2 * cube(std_dev2)) // std_dev_sum^(3/2) / (std_dev_sum * std::sqrt(std_dev_sum)); return skew; } } Delay DelayOpsSkewNormal::sum(const Delay &delay1, float delay2) const { return Delay(delay1.mean() + delay2, delay1.meanShift(), delay1.stdDev2(), delay1.skewness()); } Delay DelayOpsSkewNormal::diff(const Delay &delay1, const Delay &delay2) const { return Delay(delay1.mean() - delay2.mean(), delay1.meanShift() - delay2.meanShift(), delay1.stdDev2() + delay2.stdDev2(), skewnessSum(delay1, delay2)); } Delay DelayOpsSkewNormal::diff(const Delay &delay1, float delay2) const { return Delay(delay1.mean() - delay2, delay1.meanShift(), delay1.stdDev2(), delay1.skewness()); } Delay DelayOpsSkewNormal::diff(float delay1, const Delay &delay2) const { return Delay(delay1 - delay2.mean(), delay2.meanShift(), delay2.stdDev2(), delay2.skewness()); } void DelayOpsSkewNormal::incr(Delay &delay1, const Delay &delay2) const { delay1.setValues(delay1.mean() + delay2.mean(), delay1.meanShift() + delay2.meanShift(), delay1.stdDev2() + delay2.stdDev2(), skewnessSum(delay1, delay2)); } void DelayOpsSkewNormal::incr(DelayDbl &delay1, const Delay &delay2) const { delay1.setValues(delay1.mean() + delay2.mean(), delay1.meanShift() + delay2.meanShift(), delay1.stdDev2() + delay2.stdDev2(), skewnessSum(delay1.stdDev(), delay1.skewness())); } void DelayOpsSkewNormal::decr(Delay &delay1, const Delay &delay2) const { delay1.setValues(delay1.mean() - delay2.mean(), delay1.meanShift() + delay2.meanShift(), delay1.stdDev2() + delay2.stdDev2(), skewnessSum(delay1, delay2)); } void DelayOpsSkewNormal::decr(DelayDbl &delay1, const Delay &delay2) const { delay1.setValues(delay1.mean() - delay2.mean(), delay1.meanShift() + delay2.meanShift(), delay1.stdDev2() + delay2.stdDev2(), skewnessSum(delay1.stdDev(), delay1.skewness())); } Delay DelayOpsSkewNormal::product(const Delay &delay1, float delay2) const { return Delay(delay1.mean() * delay2, delay1.meanShift() * delay2, delay1.stdDev2() * square(delay2), delay1.skewness() * cube(delay2)); } Delay DelayOpsSkewNormal::div(float delay1, const Delay &delay2) const { return Delay(delay1 / delay2.mean()); } const char * DelayOpsSkewNormal::asStringVariance(const Delay &delay, int digits, const StaState *sta) const { const Unit *unit = sta->units()->timeUnit(); return stringPrintTmp("%s[%s,%s,%s]", unit->asString(delay.mean(), digits), unit->asString(delay.meanShift(), digits), unit->asString(delay.stdDev(), digits), sta->units()->scalarUnit()->asString(delay.skewness(), digits)); } } // namespace