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Merged
hageboeck merged 3 commits into from
Oct 9, 2019
Merged

Vectorised PDFs #7

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26dddbf
[RF] Vectorized RooChiSquare
Sep 3, 2019
4044556
[RF] EvaluateBatch() now returns empty span in abscence of any batches.
Sep 9, 2019
2fcaf9e
[RF] Vectorized more PDFs.
Sep 11, 2019
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2 changes: 2 additions & 0 deletions roofit/roofit/inc/RooDstD0BG.h
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Expand Up @@ -45,6 +45,8 @@ class RooDstD0BG : public RooAbsPdf {
RooRealProxy C,A,B ;

Double_t evaluate() const;
RooSpan<double> evaluateBatch(std::size_t begin, std::size_t batchSize) const;


private:

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3 changes: 2 additions & 1 deletion roofit/roofit/inc/RooLognormal.h
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Expand Up @@ -38,7 +38,8 @@ class RooLognormal : public RooAbsPdf {
RooRealProxy k ;

Double_t evaluate() const ;

RooSpan<double> evaluateBatch(std::size_t begin, std::size_t batchSize) const;

private:

ClassDef(RooLognormal,1) // log-normal PDF
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4 changes: 3 additions & 1 deletion roofit/roofit/inc/RooNovosibirsk.h
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Expand Up @@ -45,10 +45,12 @@ class RooNovosibirsk : public RooAbsPdf {

protected:
RooRealProxy x;
RooRealProxy width;
RooRealProxy peak;
RooRealProxy width;
RooRealProxy tail;
Double_t evaluate() const;
RooSpan<double> evaluateBatch(std::size_t begin, std::size_t batchSize) const;


private:
ClassDef(RooNovosibirsk,1) // Novosibirsk PDF
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3 changes: 3 additions & 0 deletions roofit/roofit/inc/RooUniform.h
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Expand Up @@ -40,6 +40,9 @@ class RooUniform : public RooAbsPdf {
RooListProxy x ;

Double_t evaluate() const ;
inline RooSpan<double> evaluateBatch(std::size_t, std::size_t ) const {
return {};
}

private:

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5 changes: 3 additions & 2 deletions roofit/roofit/inc/RooVoigtian.h
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Expand Up @@ -47,12 +47,13 @@ class RooVoigtian : public RooAbsPdf {
RooRealProxy sigma ;

Double_t evaluate() const ;
RooSpan<double> evaluateBatch(std::size_t begin, std::size_t batchSize) const;


private:

Double_t _invRootPi;
Bool_t _doFast;
ClassDef(RooVoigtian,1) // Voigtian PDF (Gauss (x) BreitWigner)
ClassDef(RooVoigtian,2) // Voigtian PDF (Gauss (x) BreitWigner)
};

#endif
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33 changes: 16 additions & 17 deletions roofit/roofit/src/RooArgusBG.cxx
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Expand Up @@ -26,7 +26,6 @@ RooArgusBG is a RooAbsPdf implementation describing the ARGUS background shape.
*/

#include "RooArgusBG.h"
#include "RooFit.h"
#include "RooRealVar.h"
#include "RooRealConstant.h"
#include "RooMath.h"
Expand Down Expand Up @@ -91,7 +90,7 @@ Double_t RooArgusBG::evaluate() const {

////////////////////////////////////////////////////////////////////////////////

namespace ArgusBatchEvaluate {
namespace {
//Author: Emmanouil Michalainas, CERN 19 AUGUST 2019

template<class Tm, class Tm0, class Tc, class Tp>
Expand All @@ -113,26 +112,26 @@ void compute( size_t batchSize,

RooSpan<double> RooArgusBG::evaluateBatch(std::size_t begin, std::size_t batchSize) const {
using namespace BatchHelpers;
using namespace ArgusBatchEvaluate;

EvaluateInfo info = getInfo( {&m,&m0,&c,&p}, begin, batchSize );
auto output = _batchData.makeWritableBatchUnInit(begin, info.size);
auto mData = m.getValBatch(begin, info.size);

EvaluateInfo info = getInfo( {&m, &m0, &c, &p}, begin, batchSize );
if (info.nBatches == 0) {
throw std::logic_error("Requested a batch computation, but no batch data available.");
return {};
}
else if (info.nBatches==1 && !mData.empty()) {
compute(info.size, output.data(), mData.data(),
BracketAdapter<double> (m0),
BracketAdapter<double> (c),
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);
auto mData = m.getValBatch(begin, info.size);

if (info.nBatches==1 && !mData.empty()) {
compute(info.size, output.data(), mData.data(),
BracketAdapter<double> (m0),
BracketAdapter<double> (c),
BracketAdapter<double> (p));
}
else {
compute(info.size, output.data(),
BracketAdapterWithMask (m,m.getValBatch(begin,batchSize)),
BracketAdapterWithMask (m0,m0.getValBatch(begin,batchSize)),
BracketAdapterWithMask (c,c.getValBatch(begin,batchSize)),
BracketAdapterWithMask (p,p.getValBatch(begin,batchSize)));
compute(info.size, output.data(),
BracketAdapterWithMask (m,m.getValBatch(begin,info.size)),
BracketAdapterWithMask (m0,m0.getValBatch(begin,info.size)),
BracketAdapterWithMask (c,c.getValBatch(begin,info.size)),
BracketAdapterWithMask (p,p.getValBatch(begin,info.size)));
}
return output;
}
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18 changes: 8 additions & 10 deletions roofit/roofit/src/RooBernstein.cxx
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Expand Up @@ -129,7 +129,7 @@ Double_t RooBernstein::evaluate() const

////////////////////////////////////////////////////////////////////////////////

namespace BernsteinEvaluate {
namespace {
//Author: Emmanouil Michalainas, CERN 16 AUGUST 2019

void compute( size_t batchSize, double xmax, double xmin,
Expand Down Expand Up @@ -192,17 +192,15 @@ void compute( size_t batchSize, double xmax, double xmin,

RooSpan<double> RooBernstein::evaluateBatch(std::size_t begin, std::size_t batchSize) const {
auto xData = _x.getValBatch(begin, batchSize);
batchSize = xData.size();
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);

if (xData.empty()) {
throw std::logic_error("Requested a batch computation, but no batch data available.");
}
else {
const double xmax = _x.max();
const double xmin = _x.min();
BernsteinEvaluate::compute(batchSize, xmax, xmin, output.data(), xData.data(), _coefList);
return {};
}

batchSize = xData.size();
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);
const double xmax = _x.max();
const double xmin = _x.min();
compute(batchSize, xmax, xmin, output.data(), xData.data(), _coefList);
return output;
}

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32 changes: 16 additions & 16 deletions roofit/roofit/src/RooBifurGauss.cxx
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Expand Up @@ -81,7 +81,7 @@ Double_t RooBifurGauss::evaluate() const {

////////////////////////////////////////////////////////////////////////////////

namespace BifurGaussBatchEvaluate {
namespace {
//Author: Emmanouil Michalainas, CERN 20 AUGUST 2019

template<class Tx, class Tm, class Tsl, class Tsr>
Expand All @@ -107,26 +107,26 @@ void compute( size_t batchSize,

RooSpan<double> RooBifurGauss::evaluateBatch(std::size_t begin, std::size_t batchSize) const {
using namespace BatchHelpers;
using namespace BifurGaussBatchEvaluate;

EvaluateInfo info = getInfo( {&x,&mean,&sigmaL,&sigmaR}, begin, batchSize );
auto output = _batchData.makeWritableBatchUnInit(begin, info.size);
auto xData = x.getValBatch(begin, info.size);

EvaluateInfo info = getInfo( {&x, &mean, &sigmaL, &sigmaR}, begin, batchSize );
if (info.nBatches == 0) {
throw std::logic_error("Requested a batch computation, but no batch data available.");
return {};
}
else if (info.nBatches==1 && !xData.empty()) {
compute(info.size, output.data(), xData.data(),
BracketAdapter<double> (mean),
BracketAdapter<double> (sigmaL),
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);
auto xData = x.getValBatch(begin, info.size);

if (info.nBatches==1 && !xData.empty()) {
compute(info.size, output.data(), xData.data(),
BracketAdapter<double> (mean),
BracketAdapter<double> (sigmaL),
BracketAdapter<double> (sigmaR));
}
else {
compute(info.size, output.data(),
BracketAdapterWithMask (x,x.getValBatch(begin,batchSize)),
BracketAdapterWithMask (mean,mean.getValBatch(begin,batchSize)),
BracketAdapterWithMask (sigmaL,sigmaL.getValBatch(begin,batchSize)),
BracketAdapterWithMask (sigmaR,sigmaR.getValBatch(begin,batchSize)));
compute(info.size, output.data(),
BracketAdapterWithMask (x,x.getValBatch(begin,info.size)),
BracketAdapterWithMask (mean,mean.getValBatch(begin,info.size)),
BracketAdapterWithMask (sigmaL,sigmaL.getValBatch(begin,info.size)),
BracketAdapterWithMask (sigmaR,sigmaR.getValBatch(begin,info.size)));
}
return output;
}
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16 changes: 7 additions & 9 deletions roofit/roofit/src/RooBreitWigner.cxx
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Expand Up @@ -68,7 +68,7 @@ Double_t RooBreitWigner::evaluate() const

////////////////////////////////////////////////////////////////////////////////

namespace BreitWignerBatchEvaluate {
namespace {
//Author: Emmanouil Michalainas, CERN 21 August 2019

template<class Tx, class Tmean, class Twidth>
Expand All @@ -85,17 +85,19 @@ void compute( size_t batchSize,

RooSpan<double> RooBreitWigner::evaluateBatch(std::size_t begin, std::size_t batchSize) const {
using namespace BatchHelpers;
using namespace BreitWignerBatchEvaluate;
auto xData = x.getValBatch(begin, batchSize);
auto meanData = mean.getValBatch(begin, batchSize);
auto widthData = width.getValBatch(begin, batchSize);
const bool batchX = !xData.empty();
const bool batchMean = !meanData.empty();
const bool batchWidth = !widthData.empty();

if (!batchX && !batchMean && !batchWidth) {
return {};
}
batchSize = findSize({ xData, meanData, widthData });
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);

const bool batchX = !xData.empty();
const bool batchMean = !meanData.empty();
const bool batchWidth = !widthData.empty();
if (batchX && !batchMean && !batchWidth ) {
compute(batchSize, output.data(), xData, BracketAdapter<double>(mean), BracketAdapter<double>(width));
}
Expand All @@ -117,10 +119,6 @@ RooSpan<double> RooBreitWigner::evaluateBatch(std::size_t begin, std::size_t bat
else if (batchX && batchMean && batchWidth ) {
compute(batchSize, output.data(), xData, meanData, widthData);
}
else{
throw std::logic_error("Requested a batch computation, but no batch data available.");
}

return output;
}

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40 changes: 20 additions & 20 deletions roofit/roofit/src/RooBukinPdf.cxx
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Expand Up @@ -143,7 +143,7 @@ Double_t RooBukinPdf::evaluate() const

////////////////////////////////////////////////////////////////////////////////////////

namespace BukinBatchEvaluate {
namespace {
//Author: Emmanouil Michalainas, CERN 26 JULY 2019

template<class Tx, class TXp, class TSigp, class Txi, class Trho1, class Trho2>
Expand Down Expand Up @@ -192,30 +192,30 @@ void compute( size_t batchSize,

RooSpan<double> RooBukinPdf::evaluateBatch(std::size_t begin, std::size_t batchSize) const {
using namespace BatchHelpers;
using namespace BukinBatchEvaluate;

EvaluateInfo info = getInfo( {&x,&Xp,&sigp,&xi,&rho1,&rho2}, begin, batchSize );
auto output = _batchData.makeWritableBatchUnInit(begin, info.size);
auto xData = x.getValBatch(begin, info.size);

EvaluateInfo info = getInfo( {&x, &Xp, &sigp, &xi, &rho1, &rho2}, begin, batchSize );
if (info.nBatches == 0) {
throw std::logic_error("Requested a batch computation, but no batch data available.");
return {};
}
else if (info.nBatches==1 && !xData.empty()) {
compute(info.size, output.data(), xData.data(),
BracketAdapter<double> (Xp),
BracketAdapter<double> (sigp),
BracketAdapter<double> (xi),
BracketAdapter<double> (rho1),
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);
auto xData = x.getValBatch(begin, info.size);

if (info.nBatches==1 && !xData.empty()) {
compute(info.size, output.data(), xData.data(),
BracketAdapter<double> (Xp),
BracketAdapter<double> (sigp),
BracketAdapter<double> (xi),
BracketAdapter<double> (rho1),
BracketAdapter<double> (rho2));
}
else {
compute(info.size, output.data(),
BracketAdapterWithMask (x,x.getValBatch(begin,batchSize)),
BracketAdapterWithMask (Xp,Xp.getValBatch(begin,batchSize)),
BracketAdapterWithMask (sigp,sigp.getValBatch(begin,batchSize)),
BracketAdapterWithMask (xi,xi.getValBatch(begin,batchSize)),
BracketAdapterWithMask (rho1,rho1.getValBatch(begin,batchSize)),
BracketAdapterWithMask (rho2,rho2.getValBatch(begin,batchSize)));
compute(info.size, output.data(),
BracketAdapterWithMask (x,x.getValBatch(begin,info.size)),
BracketAdapterWithMask (Xp,Xp.getValBatch(begin,info.size)),
BracketAdapterWithMask (sigp,sigp.getValBatch(begin,info.size)),
BracketAdapterWithMask (xi,xi.getValBatch(begin,info.size)),
BracketAdapterWithMask (rho1,rho1.getValBatch(begin,info.size)),
BracketAdapterWithMask (rho2,rho2.getValBatch(begin,info.size)));
}
return output;
}
23 changes: 11 additions & 12 deletions roofit/roofit/src/RooCBShape.cxx
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Expand Up @@ -93,7 +93,7 @@ Double_t RooCBShape::evaluate() const {

////////////////////////////////////////////////////////////////////////////////

namespace CBShapeBatchEvaluate {
namespace {
//Author: Emmanouil Michalainas, CERN 21 August 2019

template<class Tm, class Tm0, class Tsigma, class Talpha, class Tn>
Expand Down Expand Up @@ -121,16 +121,15 @@ void compute( size_t batchSize,

RooSpan<double> RooCBShape::evaluateBatch(std::size_t begin, std::size_t batchSize) const {
using namespace BatchHelpers;
using namespace CBShapeBatchEvaluate;

EvaluateInfo info = getInfo( {&m, &m0, &sigma, &alpha, &n}, begin, batchSize );
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);

auto mData = m.getValBatch(begin, info.size);
if (info.nBatches == 0) {
throw std::logic_error("Requested a batch computation, but no batch data available.");
return {};
}
else if (info.nBatches==1 && !mData.empty()) {
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);
auto mData = m.getValBatch(begin, info.size);

if (info.nBatches==1 && !mData.empty()) {
compute(info.size, output.data(), mData.data(),
BracketAdapter<double> (m0),
BracketAdapter<double> (sigma),
Expand All @@ -139,11 +138,11 @@ RooSpan<double> RooCBShape::evaluateBatch(std::size_t begin, std::size_t batchSi
}
else {
compute(info.size, output.data(),
BracketAdapterWithMask (m,m.getValBatch(begin,batchSize)),
BracketAdapterWithMask (m0,m0.getValBatch(begin,batchSize)),
BracketAdapterWithMask (sigma,sigma.getValBatch(begin,batchSize)),
BracketAdapterWithMask (alpha,alpha.getValBatch(begin,batchSize)),
BracketAdapterWithMask (n,n.getValBatch(begin,batchSize)));
BracketAdapterWithMask (m,m.getValBatch(begin,info.size)),
BracketAdapterWithMask (m0,m0.getValBatch(begin,info.size)),
BracketAdapterWithMask (sigma,sigma.getValBatch(begin,info.size)),
BracketAdapterWithMask (alpha,alpha.getValBatch(begin,info.size)),
BracketAdapterWithMask (n,n.getValBatch(begin,info.size)));
}
return output;
}
Expand Down
18 changes: 8 additions & 10 deletions roofit/roofit/src/RooChebychev.cxx
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Expand Up @@ -183,7 +183,7 @@ Double_t RooChebychev::evaluate() const

////////////////////////////////////////////////////////////////////////////////

namespace ChebychevEvaluate {
namespace {
//Author: Emmanouil Michalainas, CERN 12 AUGUST 2019

void compute( size_t batchSize, double xmax, double xmin,
Expand Down Expand Up @@ -223,17 +223,15 @@ void compute( size_t batchSize, double xmax, double xmin,

RooSpan<double> RooChebychev::evaluateBatch(std::size_t begin, std::size_t batchSize) const {
auto xData = _x.getValBatch(begin, batchSize);
batchSize = xData.size();
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);

if (xData.empty()) {
throw std::logic_error("Requested a batch computation, but no batch data available.");
}
else {
const Double_t xmax = _x.max(_refRangeName?_refRangeName->GetName() : nullptr);
const Double_t xmin = _x.min(_refRangeName?_refRangeName->GetName() : nullptr);
ChebychevEvaluate::compute(batchSize, xmax, xmin, output.data(), xData.data(), _coefList);
return {};
}

batchSize = xData.size();
auto output = _batchData.makeWritableBatchUnInit(begin, batchSize);
const Double_t xmax = _x.max(_refRangeName?_refRangeName->GetName() : nullptr);
const Double_t xmin = _x.min(_refRangeName?_refRangeName->GetName() : nullptr);
compute(batchSize, xmax, xmin, output.data(), xData.data(), _coefList);
return output;
}
////////////////////////////////////////////////////////////////////////////////
Expand Down
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