From 41f5d07b4e6712d9cc7746a9ac7e3a2ec19c1a4b Mon Sep 17 00:00:00 2001
From: Charlie Vanaret <vanaret@zib.de>
Date: Wed, 11 Dec 2024 19:20:03 +0100
Subject: [PATCH] Removed uno/solvers/BQPD/wdotd.f

---
 uno/solvers/BQPD/wdotd.f | 118 ---------------------------------------
 1 file changed, 118 deletions(-)
 delete mode 100644 uno/solvers/BQPD/wdotd.f

diff --git a/uno/solvers/BQPD/wdotd.f b/uno/solvers/BQPD/wdotd.f
deleted file mode 100644
index e7ab5954..00000000
--- a/uno/solvers/BQPD/wdotd.f
+++ /dev/null
@@ -1,118 +0,0 @@
-C Copyright (c) 2018-2024 Sven Leyffer
-C Licensed under the MIT license. See LICENSE file in the project directory for details.
-
-C     hristen this file wdotd.f
-
-      subroutine wdotd (n, x, ws, lws, result)
-
-c     ==========================================================
-c     Computes result = W.x where W is Hessian and x is a vector for AMPL
-c     Assumes v=0 on entry (OK, if called from gdotx, see QPsolve*.f)
-c     ==========================================================
-
-      implicit none
-
-c     ... declaration of passed parameters
-      integer          n, lws(0:*)
-      double precision x(n), result(n), ws(*)
-
-c     ... declaration of internal variables
-      integer i, j, k, footer_start
-
-c     inertia control for diagonal terms
-      double precision alpha
-      common /kktalphac/ alpha
-
-c     ========================  procedure body  =========================
-
-c     ... form result = W.x from sparse, upper triangular Hessian
-      footer_start = lws(0)
-      do i=1,n
-         do k=lws(footer_start + i - 1), lws(footer_start + i)-1
-            j = lws(k)
-            result(i) = result(i) + ws(k)*x(j)
-            if (j.ne.i) then
-c               off-diagonal term
-               result(j) = result(j) + ws(k)*x(i)
-            else
-c               diagonal term
-               result(i) = result(i) + alpha*x(j)
-            endif
-         enddo
-      enddo
-      return
-      end
-
-c     ******************************************************************
-
-      subroutine gdotx (n, x, ws, lws, result)
-
-      implicit none
-
-c     ... declaration of passed parameters
-      integer n, lws(*)
-      double precision    x(n), result(n), ws(*)
-
-c     ... declaration of internal variables
-      integer i
-
-c     ... storage map for hessian and scale_mode
-      integer         scale_mode, phe
-      common /scalec/ scale_mode, phe
-
-c     ========================  procedure body  =========================
-
-c     ... set result = 0
-      do i=1,n
-         result(i) = 0.D0
-      enddo
-
-c     ... allow for scaling of variables 
-      if ((scale_mode.eq.1).or.(scale_mode.eq.3)) then
-         do i=1,n
-            x(i) = x(i) * ws(i)
-         enddo
-      endif
-
-c     ... form v = W.d from sparse, upper triangular Hessian
-      call Wdotd (n, x, ws(phe+1), lws, result)
-
-c     ... allow for scaling of variables 
-      if ((scale_mode.eq.1).or.(scale_mode.eq.3)) then
-         do i=1,n
-            result(i) = result(i) * ws(i)
-            x(i) = x(i) / ws(i)
-         enddo
-      endif
-
-      return
-      end
-c     ******************************************************************
-      subroutine saipy2(s,a,la,i,y,n)
-      implicit double precision (a-h,o-z)
-      dimension a(*),la(0:*),y(*)
-c     ========================  procedure body  =========================
-c     saxpy with column i of A: y + s*A_{i, :}
-      if(s.eq.0.D0) return
-      j_column_start = la(0) + i
-      do j = la(j_column_start), la(j_column_start+1)-1
-         i_variable = la(j)
-         y(i_variable) = y(i_variable) + s*a(j)
-      enddo
-      return
-      end
-
-c     **************************** E N D *********************************
-      function daiscpr2(n,a,la,i,x,b)
-      implicit double precision (a-h,o-z)
-      dimension a(*),la(0:*),x(*)
-      DOUBLE PRECISION daiscpr2
-c     dot product of x and row i of A
-      daiscpr2 = dble(b)
-      j_column_start = la(0) + i
-      do j = la(j_column_start), la(j_column_start+1)-1
-         i_variable = la(j)
-         daiscpr2 = daiscpr2 + dble(x(i_variable))*dble(a(j))
-      enddo
-      return
-      end