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