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Fix missing _RP kind suffix on floating-point literals that are not binary-representable. #302

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Fix missing _RP kind suffix on floating-point literals that are not binary-representable. #302

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2 changes: 1 addition & 1 deletion fortran/bobyqa/bobyqb.f90
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Expand Up @@ -330,7 +330,7 @@ subroutine bobyqb(calfun, iprint, maxfun, npt, eta1, eta2, ftarget, gamma1, gamm
! Set QRED to the reduction of the quadratic model when the move D is made from XOPT. QRED
! should be positive. If it is nonpositive due to rounding errors, we will not take this step.
qred = -quadinc(d, xpt, gopt, pq, hq) ! QRED = Q(XOPT) - Q(XOPT + D)
trfail = (.not. qred > 1.0E-6 * rho**2) ! QRED is tiny/negative or NaN.
trfail = (.not. qred > 1.0E-6_RP * rho**2) ! QRED is tiny/negative or NaN.

! When D is short, make a choice between reducing RHO and improving the geometry depending
! on whether or not our work with the current RHO seems complete. RHO is reduced if the
Expand Down
6 changes: 3 additions & 3 deletions fortran/bobyqa/geometry.f90
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Expand Up @@ -491,9 +491,9 @@ function geostep(knew, kopt, bmat, delbar, sl, su, xpt, zmat) result(d)
! How to make this condition adaptive? A naive idea is to replace the thresholds to,
! e.g.,1.0E-2*RHOBEG. However, in a test on 20220517, this adaptation worsened the performance. In
! such a test, RHOBEG must take a value that is quite different from one. We tried RHOBEG = 0.9E-2.
!if (delbar > 1.0E-3) then
!if (delbar > 1.0E-1) then
if (delbar > 1.0E-2) then
!if (delbar > 1.0E-3_RP) then
!if (delbar > 1.0E-1_RP) then
if (delbar > 1.0E-2_RP) then
return
end if
!--------------------------------------------------------------------------------------------------!
Expand Down
4 changes: 2 additions & 2 deletions fortran/bobyqa/rescue.f90
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Expand Up @@ -499,7 +499,7 @@ subroutine rescue(calfun, solver, iprint, maxfun, delta, ftarget, xl, xu, kopt,
! Skipping an XNEW that is close but not identical to XPT(:, KPT) will cause discrepancy
! between [BMAT, ZMAT] and XPT, since the former has been updated, but it is not severe as
! the difference between XNEW and XPT(:, KPT) is tiny.
if (sum(abs(xnew - xpt(:, kpt))) <= 1.0E-2 * delta .or. .not. is_finite(sum(abs(xnew)))) then
if (sum(abs(xnew - xpt(:, kpt))) <= 1.0E-2_RP * delta .or. .not. is_finite(sum(abs(xnew)))) then
cycle
end if
xpt(:, kpt) = xnew
Expand Down Expand Up @@ -747,7 +747,7 @@ subroutine updateh_rsc(knew, beta, vlag_in, bmat, zmat, info)
! Apply Givens rotations to put zeros in the KNEW-th row of ZMAT. After this, ZMAT(KNEW, :) contains
! only one nonzero at ZMAT(KNEW, 1). Entries of ZMAT are treated as 0 if the moduli are quite small.
do j = 2, npt - n - 1_IK
if (abs(zmat(knew, j)) > 1.0E-20 * maxval(abs(zmat))) then ! This threshold is by Powell
if (abs(zmat(knew, j)) > 1.0E-20_RP * maxval(abs(zmat))) then ! This threshold is by Powell
grot = planerot(zmat(knew, [1_IK, j]))
zmat(:, [1_IK, j]) = matprod(zmat(:, [1_IK, j]), transpose(grot))
end if
Expand Down
2 changes: 1 addition & 1 deletion fortran/bobyqa/update.f90
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Expand Up @@ -153,7 +153,7 @@ subroutine updateh(knew, kopt, d, xpt, bmat, zmat, info)
! Apply Givens rotations to put zeros in the KNEW-th row of ZMAT. After this, ZMAT(KNEW, :) contains
! only one nonzero at ZMAT(KNEW, 1). Entries of ZMAT are treated as 0 if the moduli are quite small.
do j = 2, npt - n - 1_IK
if (abs(zmat(knew, j)) > 1.0E-20 * maxval(abs(zmat))) then ! This threshold is by Powell
if (abs(zmat(knew, j)) > 1.0E-20_RP * maxval(abs(zmat))) then ! This threshold is by Powell
grot = planerot(zmat(knew, [1_IK, j]))
zmat(:, [1_IK, j]) = matprod(zmat(:, [1_IK, j]), transpose(grot))
end if
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6 changes: 3 additions & 3 deletions fortran/cobyla/cobylb.f90
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Expand Up @@ -368,7 +368,7 @@ subroutine cobylb(calcfc, iprint, maxfilt, maxfun, amat, bvec, ctol, cweight, et
! Evaluate PREREM, which is the predicted reduction in the merit function.
! In theory, PREREM >= 0 and it is 0 iff CPEN = 0 = PREREF. This may not be true numerically.
prerem = preref + cpen * prerec
trfail = (.not. prerem > 1.0E-6 * min(cpen, ONE) * rho) ! PREREM is tiny/negative or NaN.
trfail = (.not. prerem > 1.0E-6_RP * min(cpen, ONE) * rho) ! PREREM is tiny/negative or NaN.

if (shortd .or. trfail) then
! Reduce DELTA if D is short or D fails to render PREREM > 0. The latter can happen due to
Expand All @@ -387,7 +387,7 @@ subroutine cobylb(calcfc, iprint, maxfilt, maxfun, amat, bvec, ctol, cweight, et
distsq(1:n) = [(sum((x - (sim(:, n + 1) + sim(:, j)))**2), j=1, n)] ! Implied do-loop
!!MATLAB: distsq(1:n) = sum((x - (sim(:,1:n) + sim(:, n+1)))**2, 1) % Implicit expansion
j = int(minloc(distsq, dim=1), kind(j))
if (distsq(j) <= (1.0E-4 * rhoend)**2) then
if (distsq(j) <= (1.0E-4_RP * rhoend)**2) then
f = fval(j)
constr = conmat(:, j)
cstrv = cval(j)
Expand Down Expand Up @@ -582,7 +582,7 @@ subroutine cobylb(calcfc, iprint, maxfilt, maxfun, amat, bvec, ctol, cweight, et
distsq(1:n) = [(sum((x - (sim(:, n + 1) + sim(:, j)))**2), j=1, n)] ! Implied do-loop
!!MATLAB: distsq(1:n) = sum((x - (sim(:,1:n) + sim(:, n+1)))**2, 1) % Implicit expansion
j = int(minloc(distsq, dim=1), kind(j))
if (distsq(j) <= (1.0E-4 * rhoend)**2) then
if (distsq(j) <= (1.0E-4_RP * rhoend)**2) then
f = fval(j)
constr = conmat(:, j)
cstrv = cval(j)
Expand Down
2 changes: 1 addition & 1 deletion fortran/common/powalg.f90
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Expand Up @@ -1272,7 +1272,7 @@ subroutine updateh(knew, kref, d, xpt, idz, bmat, zmat, info)

! Powell's condition in NEWUOA/LINCOA for the IF ... THEN below: IF (ZMAT(KNEW, J) /= 0) THEN
! A possible alternative: IF (ABS(ZMAT(KNEW, J)) > 1.0E-20 * ABS(ZMAT(KNEW, JL))) THEN
if (abs(zmat(knew, j)) > 1.0E-20 * maxval(abs(zmat))) then ! Threshold comes from Powell's BOBYQA
if (abs(zmat(knew, j)) > 1.0E-20_RP * maxval(abs(zmat))) then ! Threshold comes from Powell's BOBYQA
! Multiply a Givens rotation to ZMAT from the right so that ZMAT(KNEW, [JL,J]) becomes [*,0].
grot = planerot(zmat(knew, [jl, j])) !!MATLAB: grot = planerot(zmat(knew, [jl, j])')
zmat(:, [jl, j]) = matprod(zmat(:, [jl, j]), transpose(grot))
Expand Down
4 changes: 2 additions & 2 deletions fortran/common/string.f90
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Expand Up @@ -151,7 +151,7 @@ function real2str_scalar(x, ndgt, nexp) result(s)
if (present(nexp)) then
nexp_loc = nexp
else
nexp_loc = ceiling(log10(real(range(x) + 0.1))) ! Use + 0.1 in case RANGE(X) = 10^k.
nexp_loc = ceiling(log10(real(range(x) + 0.1_RP))) ! Use + 0.1 in case RANGE(X) = 10^k.
end if
nexp_loc = min(nexp_loc, floor(real(MAX_NUM_STR_LEN - 5) / 2.0))

Expand Down Expand Up @@ -254,7 +254,7 @@ function real2str_vector(x, ndgt, nexp, nx) result(s)
if (present(nexp)) then
nexp_loc = nexp
else
nexp_loc = ceiling(log10(real(range(x)) + 0.1)) ! Use + 0.1 in case RANGE(X) = 10^k.
nexp_loc = ceiling(log10(real(range(x)) + 0.1_RP)) ! Use + 0.1 in case RANGE(X) = 10^k.
end if
nexp_loc = min(nexp_loc, floor(real(MAX_NUM_STR_LEN - 5) / 2.0))

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4 changes: 2 additions & 2 deletions fortran/lincoa/lincob.f90
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Expand Up @@ -429,7 +429,7 @@ subroutine lincob(calfun, iprint, maxfilt, maxfun, npt, Aeq, Aineq, amat, beq, b
! Set QRED to the reduction of the quadratic model when the move D is made from XOPT. QRED
! should be positive. If it is nonpositive due to rounding errors, we will not take this step.
qred = -quadinc(d, xpt, gopt, pq, hq) ! QRED = Q(XOPT) - Q(XOPT + D)
trfail = (.not. qred > 1.0E-6 * rho**2) ! QRED is tiny/negative or NaN.
trfail = (.not. qred > 1.0E-6_RP * rho**2) ! QRED is tiny/negative or NaN.

if (shortd .or. trfail) then
! In this case, do nothing but reducing DELTA. Afterward, DELTA < DNORM may occur.
Expand Down Expand Up @@ -534,7 +534,7 @@ subroutine lincob(calfun, iprint, maxfilt, maxfun, npt, Aeq, Aineq, amat, beq, b
! verify a curvature condition that really indicates that recent models are sufficiently
! accurate. Here, however, we are not really sure whether they are accurate or not. Therefore,
! ACCURATE_MOD is not the best name, but we keep it to align with the other solvers.
accurate_mod = all(dnorm_rec <= rho) .or. all(dnorm_rec(2:size(dnorm_rec)) <= 0.2 * rho)
accurate_mod = all(dnorm_rec <= rho) .or. all(dnorm_rec(2:size(dnorm_rec)) <= 0.2_RP * rho)
! Powell's version (note that size(dnorm_rec) = 5 in his implementation):
!accurate_mod = all(dnorm_rec <= HALF * rho) .or. all(dnorm_rec(3:size(dnorm_rec)) <= TENTH * rho)
! CLOSE_ITPSET: Are the interpolation points close to XOPT?
Expand Down
6 changes: 3 additions & 3 deletions fortran/newuoa/newuob.f90
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Expand Up @@ -287,7 +287,7 @@ subroutine newuob(calfun, iprint, maxfun, npt, eta1, eta2, ftarget, gamma1, gamm
! Set QRED to the reduction of the quadratic model when the move D is made from XOPT. QRED
! should be positive. If it is nonpositive due to rounding errors, we will not take this step.
qred = -quadinc(d, xpt, gopt, pq, hq)
trfail = (.not. qred > 1.0E-6 * rho**2) ! QRED is tiny/negative, or NaN.
trfail = (.not. qred > 1.0E-6_RP * rho**2) ! QRED is tiny/negative, or NaN.

if (shortd .or. trfail) then
! In this case, do nothing but reducing DELTA. Afterward, DELTA < DNORM may occur.
Expand All @@ -306,7 +306,7 @@ subroutine newuob(calfun, iprint, maxfun, npt, eta1, eta2, ftarget, gamma1, gamm
distsq = [(sum((x - (xbase + xpt(:, k)))**2, dim=1), k=1, npt)] ! Implied do-loop
!!MATLAB: distsq = sum((x - (xbase + xpt))**2, 1) % Implicit expansion
k = int(minloc(distsq, dim=1), kind(k))
if (distsq(k) <= (1.0E-3 * rhoend)**2) then
if (distsq(k) <= (1.0E-3_RP * rhoend)**2) then
f = fval(k)
else
! Evaluate the objective function at X, taking care of possible Inf/NaN values.
Expand Down Expand Up @@ -553,7 +553,7 @@ subroutine newuob(calfun, iprint, maxfun, npt, eta1, eta2, ftarget, gamma1, gamm
distsq = [(sum((x - (xbase + xpt(:, k)))**2, dim=1), k=1, npt)] ! Implied do-loop
!!MATLAB: distsq = sum((x - (xbase + xpt))**2, 1) % Implicit expansion
k = int(minloc(distsq, dim=1), kind(k))
if (distsq(k) <= (1.0E-3 * rhoend)**2) then
if (distsq(k) <= (1.0E-3_RP * rhoend)**2) then
f = fval(k)
else
! Evaluate the objective function at X, taking care of possible Inf/NaN values.
Expand Down
8 changes: 4 additions & 4 deletions fortran/tests/test_bobyqa.f90
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Expand Up @@ -238,10 +238,10 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)
iprint = int(randn(), kind(iprint))
maxfun = int(1.0E2_RP * rand() * real(n, RP), kind(maxfun))
maxhist = int(TWO * rand() * real(max(10_IK * n, maxfun), RP), kind(maxhist))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
maxhist = -maxhist
end if
if (rand() <= 0.8) then
if (rand() <= 0.8_RP) then
ftarget = -TEN**abs(real(min(range(ftarget), 12), RP) * rand())
elseif (rand() <= 0.5) then ! Note that the value of rand() changes.
ftarget = REALMAX
Expand All @@ -251,9 +251,9 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)

rhobeg = noisy(prob % Delta0)
rhoend = max(1.0E-5_RP, rhobeg * 10.0_RP**(6.0_RP * rand() - 5.0_RP))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
rhoend = rhobeg
elseif (rand() <= 0.1) then ! Note that the value of rand() changes.
elseif (rand() <= 0.1_RP) then ! Note that the value of rand() changes.
rhobeg = ZERO
end if

Expand Down
14 changes: 7 additions & 7 deletions fortran/tests/test_cobyla.f90
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Expand Up @@ -262,21 +262,21 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)
iprint = int(randn(), kind(iprint))
maxfun = int(1.0E2_RP * rand() * real(n, RP), kind(maxfun))
maxhist = int(TWO * rand() * real(max(10_IK * n, maxfun), RP), kind(maxhist))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
maxhist = -maxhist
end if
maxfilt = int(TWO * rand() * real(maxfun, RP), kind(maxfilt))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
maxfilt = 0
end if
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
ctol = randn() * TEN**(-abs(TWO * randn()))
elseif (rand() <= 0.1) then ! Note that the value of rand() changes.
elseif (rand() <= 0.1_RP) then ! Note that the value of rand() changes.
ctol = REALMAX
else
ctol = ZERO
end if
if (rand() <= 0.8) then
if (rand() <= 0.8_RP) then
ftarget = -TEN**abs(real(min(range(ftarget), 12), RP) * rand())
elseif (rand() <= 0.5) then ! Note that the value of rand() changes.
ftarget = REALMAX
Expand All @@ -286,9 +286,9 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)

rhobeg = noisy(prob % Delta0)
rhoend = max(1.0E-5_RP, rhobeg * 10.0_RP**(6.0_RP * rand() - 5.0_RP))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
rhoend = rhobeg
elseif (rand() <= 0.1) then ! Note that the value of rand() changes.
elseif (rand() <= 0.1_RP) then ! Note that the value of rand() changes.
rhobeg = ZERO
end if

Expand Down
14 changes: 7 additions & 7 deletions fortran/tests/test_lincoa.f90
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Expand Up @@ -303,21 +303,21 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)
iprint = int(randn(), kind(iprint))
maxfun = int(1.0E2_RP * rand() * real(n, RP), kind(maxfun))
maxhist = int(TWO * rand() * real(max(10_IK * n, maxfun), RP), kind(maxhist))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
maxhist = -maxhist
end if
maxfilt = int(TWO * rand() * real(maxfun, RP), kind(maxfilt))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
maxfilt = 0
end if
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
ctol = randn() * TEN**(-abs(TWO * randn()))
elseif (rand() <= 0.1) then ! Note that the value of rand() changes.
elseif (rand() <= 0.1_RP) then ! Note that the value of rand() changes.
ctol = REALMAX
else
ctol = ZERO
end if
if (rand() <= 0.8) then
if (rand() <= 0.8_RP) then
ftarget = -TEN**abs(real(min(range(ftarget), 12), RP) * rand())
elseif (rand() <= 0.5) then ! Note that the value of rand() changes.
ftarget = REALMAX
Expand All @@ -327,9 +327,9 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)

rhobeg = noisy(prob % Delta0)
rhoend = max(1.0E-5_RP, rhobeg * 10.0_RP**(6.0_RP * rand() - 5.0_RP))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
rhoend = rhobeg
elseif (rand() <= 0.1) then ! Note that the value of rand() changes.
elseif (rand() <= 0.1_RP) then ! Note that the value of rand() changes.
rhobeg = ZERO
end if

Expand Down
8 changes: 4 additions & 4 deletions fortran/tests/test_newuoa.f90
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Expand Up @@ -215,10 +215,10 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)
iprint = int(randn(), kind(iprint))
maxfun = int(1.0E2_RP * rand() * real(n, RP), kind(maxfun))
maxhist = int(TWO * rand() * real(max(10_IK * n, maxfun), RP), kind(maxhist))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
maxhist = -maxhist
end if
if (rand() <= 0.8) then
if (rand() <= 0.8_RP) then
ftarget = -TEN**abs(real(min(range(ftarget), 12), RP) * rand())
elseif (rand() <= 0.5) then ! Note that the value of rand() changes.
ftarget = REALMAX
Expand All @@ -228,9 +228,9 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)

rhobeg = noisy(prob % Delta0)
rhoend = max(1.0E-5_RP, rhobeg * 10.0_RP**(6.0_RP * rand() - 5.0_RP))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
rhoend = rhobeg
elseif (rand() <= 0.1) then ! Note that the value of rand() changes.
elseif (rand() <= 0.1_RP) then ! Note that the value of rand() changes.
rhobeg = ZERO
end if

Expand Down
8 changes: 4 additions & 4 deletions fortran/tests/test_uobyqa.f90
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Expand Up @@ -199,10 +199,10 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)
iprint = int(randn(), kind(iprint))
maxfun = int(1.0E2_RP * rand() * real(n, RP), kind(maxfun))
maxhist = int(TWO * rand() * real(max(10_IK * n, maxfun), RP), kind(maxhist))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
maxhist = -maxhist
end if
if (rand() <= 0.8) then
if (rand() <= 0.8_RP) then
ftarget = -TEN**abs(real(min(range(ftarget), 12), RP) * rand())
elseif (rand() <= 0.5) then ! Note that the value of rand() changes.
ftarget = REALMAX
Expand All @@ -212,9 +212,9 @@ subroutine test_solver(probs, mindim, maxdim, nrand, randseed, testdim)

rhobeg = noisy(prob % Delta0)
rhoend = max(1.0E-5_RP, rhobeg * 10.0_RP**(6.0_RP * rand() - 5.0_RP))
if (rand() <= 0.1) then
if (rand() <= 0.1_RP) then
rhoend = rhobeg
elseif (rand() <= 0.1) then ! Note that the value of rand() changes.
elseif (rand() <= 0.1_RP) then ! Note that the value of rand() changes.
rhobeg = ZERO
end if

Expand Down
6 changes: 3 additions & 3 deletions fortran/uobyqa/uobyqb.f90
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Expand Up @@ -294,7 +294,7 @@ subroutine uobyqb(calfun, iprint, maxfun, eta1, eta2, ftarget, gamma1, gamma2, r
! Set QRED to the reduction of the quadratic model when the move D is made from XOPT. QRED
! should be positive. If it is nonpositive due to rounding errors, we will not take this step.
qred = -quadinc(pq, d, xpt(:, kopt)) ! QRED = Q(XOPT) - Q(XOPT + D)
trfail = (.not. qred > 1.0E-6 * rho**2) ! QRED is tiny/negative or NaN.
trfail = (.not. qred > 1.0E-6_RP * rho**2) ! QRED is tiny/negative or NaN.

if (shortd .or. trfail) then
! Powell's code does not reduce DELTA as follows. This comes from NEWUOA and works well.
Expand All @@ -310,7 +310,7 @@ subroutine uobyqb(calfun, iprint, maxfun, eta1, eta2, ftarget, gamma1, gamma2, r
distsq = [(sum((x - (xbase + xpt(:, k)))**2, dim=1), k=1, npt)] ! Implied do-loop
!!MATLAB: distsq = sum((x - (xbase + xpt))**2, 1) % Implicit expansion
k = int(minloc(distsq, dim=1), kind(k))
if (distsq(k) <= (1.0E-4 * rhoend)**2) then
if (distsq(k) <= (1.0E-4_RP * rhoend)**2) then
f = fval(k)
else
! Evaluate the objective function at X, taking care of possible Inf/NaN values.
Expand Down Expand Up @@ -474,7 +474,7 @@ subroutine uobyqb(calfun, iprint, maxfun, eta1, eta2, ftarget, gamma1, gamma2, r
distsq = [(sum((x - (xbase + xpt(:, k)))**2, dim=1), k=1, npt)] ! Implied do-loop
!!MATLAB: distsq = sum((x - (xbase + xpt))**2, 1) % Implicit expansion
k = int(minloc(distsq, dim=1), kind(k))
if (distsq(k) <= (1.0E-4 * rhoend)**2) then
if (distsq(k) <= (1.0E-4_RP * rhoend)**2) then
f = fval(k)
else
! Evaluate the objective function at X, taking care of possible Inf/NaN values.
Expand Down