31 REAL(KIND=8),
DIMENSION(:,:),
ALLOCATABLE,
PUBLIC ::
sig1 32 REAL(KIND=8),
DIMENSION(:,:),
ALLOCATABLE,
PUBLIC ::
sig2 33 REAL(KIND=8),
DIMENSION(:,:),
ALLOCATABLE,
PUBLIC ::
sig1r 35 REAL(KIND=8),
DIMENSION(:,:),
ALLOCATABLE ::
dumb_mat1 36 REAL(KIND=8),
DIMENSION(:,:),
ALLOCATABLE ::
dumb_mat2 37 REAL(KIND=8),
DIMENSION(:,:),
ALLOCATABLE ::
dumb_mat3 38 REAL(KIND=8),
DIMENSION(:,:),
ALLOCATABLE ::
dumb_mat4 48 LOGICAL,
INTENT(OUT) :: mult,Q1fill
49 INTEGER :: AllocStat,info1,info2
54 IF (allocstat /= 0) stop
"*** Not enough memory ! ***" 57 IF (allocstat /= 0) stop
"*** Not enough memory ! ***" 60 IF (allocstat /= 0) stop
"*** Not enough memory ! ***" 63 IF (allocstat /= 0) stop
"*** Not enough memory ! ***" 65 print*,
"Initializing the sigma matrices" 93 REAL(KIND=8),
DIMENSION(0:ndim),
INTENT(IN) :: y
103 IF ((.not.any(isnan(
dumb_mat2))).and.(info.eq.0).and.(.not.any(
dumb_mat2>huge(0.d0))))
THEN integer ndim
Number of variables (dimension of the model)
subroutine, public chol(A, sqA, info)
Routine to perform a Cholesky decomposition.
The MTV tensors used to integrate the MTV model.
subroutine, public init_sigma(mult, Q1fill)
Subroutine to initialize the sigma matices.
subroutine, public sqrtm(A, sqA, info, info_triu, bs)
Routine to compute a real square-root of a matrix.
subroutine, public printmat(A)
subroutine, public ireduce(A, Ared, n, ind, rind)
integer, dimension(:), allocatable ind2
real(kind=8), dimension(:,:), allocatable dumb_mat3
Dummy matrix.
The MTV noise sigma matrices used to integrate the MTV model.
subroutine, public compute_mult_sigma(y)
Routine to actualize the matrix based on the state y of the MTV system.
logical function, public tensor_empty(t)
Test if a rank-3 tensor coolist is empty.
real(kind=8), dimension(:,:), allocatable, public sig1
state-dependent noise matrix
real(kind=8), dimension(:,:), allocatable, public q2
Constant terms for the state-independent noise covariance matrix.
subroutine, public reduce(A, Ared, n, ind, rind)
integer, dimension(:), allocatable rind2
Reduction indices.
real(kind=8), dimension(:,:), allocatable dumb_mat1
Dummy matrix.
real(kind=8), dimension(:,:), allocatable dumb_mat2
Dummy matrix.
subroutine, public sparse_mul3_mat(coolist_ijk, arr_k, res)
Sparse multiplication of a rank-3 tensor coolist with a vector: . Its output is a matrix...
real(kind=8), dimension(:,:), allocatable, public q1
Constant terms for the state-dependent noise covariance matrix.
subroutine, public init_sqrt
type(coolist), dimension(:), allocatable, public utot
Linear terms for the state-dependent noise covariance matrix.
type(coolist4), dimension(:), allocatable, public vtot
Quadratic terms for the state-dependent noise covariance matrix.
The model parameters module.
integer, dimension(:), allocatable rind1
real(kind=8), dimension(:,:), allocatable, public sig2
state-independent noise matrix
subroutine, public cprintmat(A)
logical function, public tensor4_empty(t)
Test if a rank-4 tensor coolist is empty.
integer, dimension(:), allocatable ind1
Utility module with various routine to compute matrix square root.
subroutine, public sparse_mul4_mat(coolist_ijkl, arr_k, arr_l, res)
Sparse multiplication of a tensor with two vectors: .
real(kind=8), dimension(:,:), allocatable dumb_mat4
Dummy matrix.
real(kind=8), dimension(:,:), allocatable, public sig1r
Reduced state-dependent noise matrix.
subroutine, public sqrtm_svd(A, sqA, info, info_triu, bs)
Routine to compute a real square-root of a matrix via a SVD decomposition.