Move M_PI preproc const from EigTJ to EigTJGen (other subclasses need it).

Fix for Win10 Visual Studio of error: faust_EigTJComplex.hpp(130,32): error C2065: 'M_PI': undeclared identifier.

src/algorithm/factorization/faust_EigTJ.h

-#ifndef __EIGTJ__
-#define __EIGTJ__
-
-#include "faust_constant.h"
-#include "faust_MatSparse.h"
-#include "faust_MatDense.h"
-#include "faust_Transform.h"
-#include "faust_EigTJGen.h"
-#include <cfloat>
-#include <vector>
-#include <cmath>
-#ifndef M_PI
-#define M_PI acos(-1)
-#endif
-
-namespace Faust
-{
-
-
-	template<typename FPP, FDevice DEVICE, typename FPP2 = Real<FPP>>
-		class EigTJ : public EigTJGen<FPP, DEVICE, FPP2> {
-			/**
-			 * \class EigTJ
-			 *
-			 * \brief This class implements the EigTJ algorithm.
-			 * This algorithm is based on the classical Jacobi eigenvalues algorithm.
-			 *
-			 * See parent class EigTJGen for documentation about members.
-			 *
-			 *  References:
-			 *
-			 *  [1]   Le Magoarou L., Gribonval R. and Tremblay N., "Approximate fast
-			 *    graph Fourier transforms via multi-layer sparse approximations",
-			 *    submitted to IEEE Transactions on Signal and Information Processing
-			 *    over Networks.
-			 *    <https://hal.inria.fr/hal-01416110>
-			 *
-			 */
-			/** \brief Temporary storage matrix for maximization of L. */
-			MatDense<FPP,DEVICE> C;
-			/** \brief Column vector for the rowwise minimization of C (i.e. maximization of L). */
-			Vect<FPP,DEVICE> C_min_row;
-			protected:
-				/** \brief Rotation angle theta for the current iteration's Givens matrix. */
-				FPP2 theta;
-
-				/** \brief In calc_theta() two values are calculated for theta, this boolean is set to true to always choose theta2 (useful for EigTJParallel). */
-				bool always_theta2;
-
-				/**
-				 * Function pointer to any step of the algorithm (internal purpose only).
-				 */
-				typedef void (EigTJ<FPP,DEVICE,FPP2>::*substep_fun)();
-
-
-			public:
-
-				const static unsigned int ERROR_CALC_PERIOD = 100;
-				/** Algorithm class constructor.
-				 * \param Lap The Laplacian matrix to approximate/diagonalize.
-				 * \param J The number of iterations, Givens rotations factors.
-				 * */
-				EigTJ(MatSparse<FPP,DEVICE>& Lap, int J, unsigned int verbosity = 0, const double stoppingError = 0.0, const bool errIsRel = true, const bool enable_large_Faust = false, const int err_period=100);
-				EigTJ(MatDense<FPP,DEVICE>& Lap, int J, unsigned int verbosity = 0, const double stoppingError = 0.0, const bool errIsRel = true, const bool enable_large_Faust = false, const int err_period=100);
-				/** Destructor */
-				virtual ~EigTJ() {/*delete[] q_candidates; delete L;*/};
-
-				/**
-				 * \brief Algo. main step.
-				 *
-				 * This function calls all step functions of the algorithm in the proper order to execute only one iteration.
-				 *
-				 * External code may call this function instead of compute_facts() in order to debug iterations taken one by one.
-				 */
-				virtual void next_step();
-
-				/**
-				 * \brief Algo. step 2.4
-				 *
-				 * Updates L after Givens factor update for the next iteration.
-				 */
-				virtual void update_L();
-
-			protected:
-				virtual void choose_pivot();
-
-				virtual void max_L();
-
-				void calc_theta();
-
-				virtual void update_fact();
-
-				virtual void update_L(MatDense<FPP,Cpu> &);
-
-				virtual void update_L(MatSparse<FPP,Cpu> &);
-
-				/**
-				 * Computes the first S'*L (only used by update_L() in optimization enabled code).
-				 *
-				 */
-				void update_L_first(Vect<FPP,DEVICE>& L_vec_p, Vect<FPP,DEVICE>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatDense<FPP,DEVICE> & L);
-
-				/**
-				 * Computes L*S (only used by update_L() in optimization enabled code).
-				 * Must be called after update_L_first() to finish the update of L = S'*L*S.
-				 */
-				void update_L_second(Vect<FPP,DEVICE>& L_vec_p, Vect<FPP,DEVICE>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatDense<FPP,DEVICE> & L);
-
-				void update_L_first(Eigen::SparseMatrix<FPP, Eigen::RowMajor> & L_vec_p, Eigen::SparseMatrix<FPP, Eigen::RowMajor>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatSparse<FPP,DEVICE> & L);
-				void update_L_second(Eigen::SparseMatrix<FPP, Eigen::RowMajor> & L_vec_p, Eigen::SparseMatrix<FPP, Eigen::RowMajor>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatSparse<FPP,DEVICE> & L);
-
-			public:
-
-
-				const MatSparse<FPP,DEVICE> get_Dspm(const bool ord=false);
-
-
-
-		};
-
-}
-#include "faust_EigTJ.hpp"
-#endif
+#ifndef __EIGTJ__
+#define __EIGTJ__
+
+#include "faust_constant.h"
+#include "faust_MatSparse.h"
+#include "faust_MatDense.h"
+#include "faust_Transform.h"
+#include "faust_EigTJGen.h"
+#include <cfloat>
+#include <vector>
+
+namespace Faust
+{
+
+
+	template<typename FPP, FDevice DEVICE, typename FPP2 = Real<FPP>>
+		class EigTJ : public EigTJGen<FPP, DEVICE, FPP2> {
+			/**
+			 * \class EigTJ
+			 *
+			 * \brief This class implements the EigTJ algorithm.
+			 * This algorithm is based on the classical Jacobi eigenvalues algorithm.
+			 *
+			 * See parent class EigTJGen for documentation about members.
+			 *
+			 *  References:
+			 *
+			 *  [1]   Le Magoarou L., Gribonval R. and Tremblay N., "Approximate fast
+			 *    graph Fourier transforms via multi-layer sparse approximations",
+			 *    submitted to IEEE Transactions on Signal and Information Processing
+			 *    over Networks.
+			 *    <https://hal.inria.fr/hal-01416110>
+			 *
+			 */
+			/** \brief Temporary storage matrix for maximization of L. */
+			MatDense<FPP,DEVICE> C;
+			/** \brief Column vector for the rowwise minimization of C (i.e. maximization of L). */
+			Vect<FPP,DEVICE> C_min_row;
+			protected:
+				/** \brief Rotation angle theta for the current iteration's Givens matrix. */
+				FPP2 theta;
+
+				/** \brief In calc_theta() two values are calculated for theta, this boolean is set to true to always choose theta2 (useful for EigTJParallel). */
+				bool always_theta2;
+
+				/**
+				 * Function pointer to any step of the algorithm (internal purpose only).
+				 */
+				typedef void (EigTJ<FPP,DEVICE,FPP2>::*substep_fun)();
+
+
+			public:
+
+				const static unsigned int ERROR_CALC_PERIOD = 100;
+				/** Algorithm class constructor.
+				 * \param Lap The Laplacian matrix to approximate/diagonalize.
+				 * \param J The number of iterations, Givens rotations factors.
+				 * */
+				EigTJ(MatSparse<FPP,DEVICE>& Lap, int J, unsigned int verbosity = 0, const double stoppingError = 0.0, const bool errIsRel = true, const bool enable_large_Faust = false, const int err_period=100);
+				EigTJ(MatDense<FPP,DEVICE>& Lap, int J, unsigned int verbosity = 0, const double stoppingError = 0.0, const bool errIsRel = true, const bool enable_large_Faust = false, const int err_period=100);
+				/** Destructor */
+				virtual ~EigTJ() {/*delete[] q_candidates; delete L;*/};
+
+				/**
+				 * \brief Algo. main step.
+				 *
+				 * This function calls all step functions of the algorithm in the proper order to execute only one iteration.
+				 *
+				 * External code may call this function instead of compute_facts() in order to debug iterations taken one by one.
+				 */
+				virtual void next_step();
+
+				/**
+				 * \brief Algo. step 2.4
+				 *
+				 * Updates L after Givens factor update for the next iteration.
+				 */
+				virtual void update_L();
+
+			protected:
+				virtual void choose_pivot();
+
+				virtual void max_L();
+
+				void calc_theta();
+
+				virtual void update_fact();
+
+				virtual void update_L(MatDense<FPP,Cpu> &);
+
+				virtual void update_L(MatSparse<FPP,Cpu> &);
+
+				/**
+				 * Computes the first S'*L (only used by update_L() in optimization enabled code).
+				 *
+				 */
+				void update_L_first(Vect<FPP,DEVICE>& L_vec_p, Vect<FPP,DEVICE>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatDense<FPP,DEVICE> & L);
+
+				/**
+				 * Computes L*S (only used by update_L() in optimization enabled code).
+				 * Must be called after update_L_first() to finish the update of L = S'*L*S.
+				 */
+				void update_L_second(Vect<FPP,DEVICE>& L_vec_p, Vect<FPP,DEVICE>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatDense<FPP,DEVICE> & L);
+
+				void update_L_first(Eigen::SparseMatrix<FPP, Eigen::RowMajor> & L_vec_p, Eigen::SparseMatrix<FPP, Eigen::RowMajor>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatSparse<FPP,DEVICE> & L);
+				void update_L_second(Eigen::SparseMatrix<FPP, Eigen::RowMajor> & L_vec_p, Eigen::SparseMatrix<FPP, Eigen::RowMajor>& L_vec_q, const FPP2& c, const FPP2& s, int p, int q, MatSparse<FPP,DEVICE> & L);
+
+			public:
+
+
+				const MatSparse<FPP,DEVICE> get_Dspm(const bool ord=false);
+
+
+
+		};
+
+}
+#include "faust_EigTJ.hpp"
+#endif