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//
// GENERATED FILE
//
use super::*;
use crate::SpiceContext;
use f2rust_std::*;
/// Matrix transpose times vector, general dimension
///
/// Multiply the transpose of a matrix and a vector of
/// arbitrary size.
///
/// # Brief I/O
///
/// ```text
/// VARIABLE I/O DESCRIPTION
/// -------- --- --------------------------------------------------
/// M1 I Left-hand matrix whose transpose is to be
/// multiplied.
/// V2 I Right-hand vector to be multiplied.
/// NC1 I Column dimension of M1 and length of VOUT.
/// NR1R2 I Row dimension of M1 and length of V2.
/// VOUT O Product vector M1**T * V2.
/// ```
///
/// # Detailed Input
///
/// ```text
/// M1 is a double precision matrix of arbitrary size whose
/// transpose forms the left-hand matrix of the
/// multiplication.
///
/// V2 is a double precision vector on the right of the
/// multiplication.
///
/// NC1 is the column dimension of M1 and length of VOUT.
///
/// NR1R2 is the row dimension of M1 and length of V2.
/// ```
///
/// # Detailed Output
///
/// ```text
/// VOUT is the double precision vector which results from
/// the expression
///
/// T
/// VOUT = (M1) x V2
///
/// where the T denotes the transpose of M1.
///
/// VOUT must NOT overwrite either M1 or V2.
/// ```
///
/// # Exceptions
///
/// ```text
/// Error free.
/// ```
///
/// # Particulars
///
/// ```text
/// The code reflects precisely the following mathematical expression
///
/// For each value of the subscript I from 1 to NC1,
///
/// VOUT(I) = Summation from K=1 to NR1R2 of ( M1(K,I) * V2(K) )
///
/// Note that the reversal of the K and I subscripts in the left-hand
/// matrix M1 is what makes VOUT the product of the TRANSPOSE of M1
/// and not simply of M1 itself.
///
/// Since this subroutine operates on matrices of arbitrary size, it
/// is not feasible to buffer intermediate results. Thus, VOUT
/// should NOT overwrite either M1 or V2.
/// ```
///
/// # Examples
///
/// ```text
/// The numerical results shown for this example may differ across
/// platforms. The results depend on the SPICE kernels used as
/// input, the compiler and supporting libraries, and the machine
/// specific arithmetic implementation.
///
/// 1) Given a 3x2 matrix and a 3-vector, multiply the transpose of
/// the matrix by the vector.
///
///
/// Example code begins here.
///
///
/// PROGRAM MTXVG_EX1
/// IMPLICIT NONE
///
/// C
/// C Local variables.
/// C
/// DOUBLE PRECISION M ( 3, 2 )
/// DOUBLE PRECISION VIN ( 3 )
/// DOUBLE PRECISION VOUT ( 2 )
///
/// INTEGER I
/// INTEGER J
///
/// C
/// C Define M and VIN.
/// C
/// DATA M / 1.0D0, 1.0D0, 1.0D0,
/// . 2.0D0, 3.0D0, 4.0D0 /
///
/// DATA VIN / 1.0D0, 2.0D0, 3.0D0 /
///
/// C
/// C Multiply the transpose of M by VIN.
/// C
/// CALL MTXVG ( M, VIN, 2, 3, VOUT )
///
/// WRITE(*,'(A)') 'Transpose of M times VIN:'
/// WRITE(*,'(2F10.3)') VOUT
///
/// END
///
///
/// When this program was executed on a Mac/Intel/gfortran/64-bit
/// platform, the output was:
///
///
/// Transpose of M times VIN:
/// 6.000 20.000
/// ```
///
/// # Restrictions
///
/// ```text
/// 1) The user is responsible for checking the magnitudes of the
/// elements of M1 and V2 so that a floating point overflow does
/// not occur.
///
/// 2) VOUT not overwrite M1 or V2 or else the intermediate
/// will affect the final result.
/// ```
///
/// # Author and Institution
///
/// ```text
/// J. Diaz del Rio (ODC Space)
/// W.M. Owen (JPL)
/// W.L. Taber (JPL)
/// ```
///
/// # Version
///
/// ```text
/// - SPICELIB Version 1.1.0, 04-JUL-2021 (JDR)
///
/// Added IMPLICIT NONE statement.
///
/// Edited the header to comply with NAIF standard.
/// Added complete code example based on the existing example.
///
/// - SPICELIB Version 1.0.1, 10-MAR-1992 (WLT)
///
/// Comment section for permuted index source lines was added
/// following the header.
///
/// - SPICELIB Version 1.0.0, 31-JAN-1990 (WMO)
/// ```
pub fn mtxvg(m1: &[f64], v2: &[f64], nc1: i32, nr1r2: i32, vout: &mut [f64]) {
MTXVG(m1, v2, nc1, nr1r2, vout);
}
//$Procedure MTXVG ( Matrix transpose times vector, general dimension )
pub fn MTXVG(M1: &[f64], V2: &[f64], NC1: i32, NR1R2: i32, VOUT: &mut [f64]) {
let M1 = DummyArray2D::new(M1, 1..=NR1R2, 1..=NC1);
let V2 = DummyArray::new(V2, 1..=NR1R2);
let mut VOUT = DummyArrayMut::new(VOUT, 1..=NC1);
let mut SUM: f64 = 0.0;
//
// Local variables
//
//
// Perform the matrix-vector multiplication
//
for I in 1..=NC1 {
SUM = 0.0;
for K in 1..=NR1R2 {
SUM = (SUM + (M1[[K, I]] * V2[K]));
}
VOUT[I] = SUM;
}
}