From c41f7f5b16d3b13895523f0ae4b541b45babdcb2 Mon Sep 17 00:00:00 2001 From: SoftwareLiteracy Date: Fri, 27 Oct 2023 15:40:57 -0700 Subject: [PATCH] v1.15.1 SMap Do not use BLAS on Windows --- doc/cppEDM.pdf | Bin 127320 -> 128789 bytes src/API.h | 2 ++ src/Eval.cc | 15 +++++++++++---- src/Parameter.cc | 7 ++++--- src/SMap.cc | 30 +++++++++++++++++++++++++----- src/SMap.h | 5 +++++ 6 files changed, 47 insertions(+), 12 deletions(-) diff --git a/doc/cppEDM.pdf b/doc/cppEDM.pdf index f57204318d6a0ae30c85305028e8e14ff370c972..1cac2a80b40ae812da51497234ed38916db5e6fe 100644 GIT binary patch delta 68009 zcmV)TK(W8r;s=%P2arvF<2DSw=U4b#Ag-vFZNM<#I7xxtwhhoj(NkYQ(Jj!u?B6db zO15Lkn(WSW>>VtO@i>ki6u(atNhzX);^X1pLKLDDvMww@*;G(e4gde}`{Ac=ihsBS zULXEEoNfoGL|GS=z%s?{x8mC?6kvq^1$`8?%mw>`??@nH+-Qb2vA6JywO2eaBXo@@bA5YxenT5Hs0IbYDkCti5YJnEl zJBJ1kwlF->H9^T^knZzL$r491pcoB*@35I^4mA@7adsnrl>tVqapBHbyY3w-P+DYx zthyt#(m3TYH~si7vc`UaWtrpMVxrCG(k?FleY?)!+C*TBVDNk1~tNYPoW~+RV&>pK1((rVe2T>dWE$I6~ 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z!hul+jyPlm5QaT?7yn%}2nrk#hhb8AJskBQ7&P*TFd*zm0KuTqN8$no13fYWVleQ- z9SFhVz=g$OO|S^ekqC!HLJln$AP_7Paqun7A6~L()_PIBpBol2?N>%{Tu9O|3jhR!s4*hP|&#! zIU$ILI&5kXc4V~*!my}A;TxQ-U??T0N0u4kaX!w&2Z z_8jW>zO%K~F)}r8r*FQYJx#SiC9>~ I PredictNonlinear( std::string pathIn = "./data/", bool verbose = true, std::vector validLib = std::vector(), + bool ignoreNan = true, unsigned nThreads = 4 ); DataFrame< double > PredictNonlinear( DataFrame< double > & dataFrameIn, @@ -378,5 +379,6 @@ DataFrame< double > PredictNonlinear( DataFrame< double > & dataFrameIn, bool verbose = true, std::vector validLib = std::vector(), + bool ignoreNan = true, unsigned nThreads = 4 ); #endif diff --git a/src/Eval.cc b/src/Eval.cc index d4c4e26..3d77c79 100644 --- a/src/Eval.cc +++ b/src/Eval.cc @@ -79,7 +79,8 @@ void SMapThread( EDM_Eval::WorkQueue &workQ, std::string target, bool embedded, bool verbose, - std::vector validLib ); + std::vector validLib, + bool ignoreNan ); //---------------------------------------------------------------- // EmbedDimension() : Evaluate Simplex rho vs. dimension E @@ -497,6 +498,7 @@ DataFrame< double > PredictNonlinear( std::string pathIn, bool embedded, bool verbose, std::vector validLib, + bool ignoreNan, unsigned nThreads ) { // Create DataFrame (constructor loads data) @@ -518,6 +520,7 @@ DataFrame< double > PredictNonlinear( std::string pathIn, embedded, verbose, validLib, + ignoreNan, nThreads ); return Theta_rho; } @@ -542,6 +545,7 @@ DataFrame< double > PredictNonlinear( DataFrame< double > & data, bool embedded, bool verbose, std::vector validLib, + bool ignoreNan, unsigned nThreads ) { std::vector ThetaValues( { 0.01, 0.1, 0.3, 0.5, 0.75, 1, @@ -600,7 +604,8 @@ DataFrame< double > PredictNonlinear( DataFrame< double > & data, target, embedded, verbose, - validLib ) ); + validLib, + ignoreNan ) ); } // join threads @@ -647,7 +652,8 @@ void SMapThread( EDM_Eval::WorkQueue &workQ, std::string target, bool embedded, bool verbose, - std::vector validLib ) + std::vector validLib, + bool ignoreNan ) { std::size_t i = std::atomic_fetch_add( &EDM_Eval::smap_count_i, std::size_t(1) ); @@ -679,7 +685,8 @@ void SMapThread( EDM_Eval::WorkQueue &workQ, embedded, false, // const_predict verbose, - validLib ); + validLib, + ignoreNan ); DataFrame< double > predictions = S.predictions; DataFrame< double > coefficients = S.coefficients; diff --git a/src/Parameter.cc b/src/Parameter.cc index 8187497..b33a06b 100644 --- a/src/Parameter.cc +++ b/src/Parameter.cc @@ -102,7 +102,7 @@ Parameters::Parameters( validated ( false ), // Instantiate Version - version( 1, 15, 0, "2023-10-21" ) + version( 1, 15, 1, "2023-10-27" ) { // Constructor code if ( method != Method::None ) { @@ -184,14 +184,15 @@ void Parameters::Validate() { if ( randomLib ) { if ( subSamples < 1 ) { std::string errMsg( "Parameters::Validate(): " - "CCM samples must be > 0.\n" ); + "CCM sample must be > 0.\n" ); throw std::runtime_error( errMsg ); } } // CCM librarySizes if ( not libSizes_str.size() ) { - std::string errMsg( "Parameters::Validate(): CCM libSize empty.\n" ); + std::string errMsg( "Parameters::Validate(): " + "CCM libSizes empty.\n" ); throw std::runtime_error( errMsg ); } diff --git a/src/SMap.cc b/src/SMap.cc index 78f5e5b..36bc769 100644 --- a/src/SMap.cc +++ b/src/SMap.cc @@ -490,6 +490,11 @@ void SMapClass::WriteOutput () { } } +//>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +// Do not use LAPACK on Windog: use scikit-learn LinearRegression +//>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +#if !defined _WIN32 || defined USING_R + //---------------------------------------------------------------- // Singular Value Decomposition : wrapper for Lapack_SVD() //---------------------------------------------------------------- @@ -504,11 +509,11 @@ SVDValues SVD( DataFrame < double > A, double *b = &( B[0] ); - SVDValues SVD_ = Lapack_SVD( A.NRows(), // number of rows - A.NColumns(), // number of columns - a, // A - b, // b - 1.E-9 ); // rcond + SVDValues SVD_ = Lapack_SVD( A.NRows(), // number of rows + A.NColumns(), // number of columns + a, // A + b, // b + 1.E-9 ); // rcond #ifdef DEBUG_ALL std::cout << "SVD------------------------\n"; @@ -657,3 +662,18 @@ SVDValues Lapack_SVD( int m, // rows in matrix return SVD_; } +#else +//----------------------------------------------------------------- +// Singular Value Decomposition : SVD() dummy function: Replaced by +// scikit-learn LinearRegression on Windog. LAPACK is not feasible. +//----------------------------------------------------------------- +SVDValues SVD( DataFrame < double > A, + std::valarray< double > B ) { + if ( A.NRows() == B.size() ) {} // Avoid compiler unused warn + SVDValues SVD_; + return SVD_; +} +#endif +//<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<< +// Do not use LAPACK on Windog: use scikit-learn LinearRegression +//<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<< diff --git a/src/SMap.h b/src/SMap.h index 6a5d948..fe0469a 100644 --- a/src/SMap.h +++ b/src/SMap.h @@ -11,11 +11,16 @@ using Solver = SVDValues (*) ( DataFrame < double >, // Prototype declaration of general functions SVDValues SVD( DataFrame < double > A, std::valarray< double > B ); +//>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +// Do not use LAPACK on Windog: use scikit-learn LinearRegression +//>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +#if !defined _WIN32 || defined USING_R SVDValues Lapack_SVD( int m, // number of rows in matrix int n, // number of columns in matrix double *a, // pointer to top-left corner double *b, double rcond ); +#endif //---------------------------------------------------------------- // SMap class inherits from EDM class and defines