diff --git a/src/math.f90 b/src/math.f90 index 207a27e78..3303f3b4c 100644 --- a/src/math.f90 +++ b/src/math.f90 @@ -961,39 +961,36 @@ pure function math_3333toVoigt66(m3333) end function math_3333toVoigt66 - !-------------------------------------------------------------------------------------------------- -!> @brief draw a random sample from Gauss variable +!> @brief Draw a sample from a normal distribution. +!> @details https://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform +!> https://masuday.github.io/fortran_tutorial/random.html !-------------------------------------------------------------------------------------------------- -real(pReal) function math_sampleGaussVar(mu, sigma, width) +impure elemental subroutine math_normal(x,mu,sigma) - real(pReal), intent(in) :: mu, & !< mean - sigma !< standard deviation - real(pReal), intent(in), optional :: width !< cut off as multiples of standard deviation + real(pReal), intent(out) :: x + real(pReal), intent(in), optional :: mu, sigma + + real(pReal) :: sigma_, mu_ + real(pReal), dimension(2) :: rnd - real(pReal), dimension(2) :: rnd ! random numbers - real(pReal) :: scatter, & ! normalized scatter around mean - width_ - - if (abs(sigma) < tol_math_check) then - math_sampleGaussVar = mu + + if (present(mu)) then + mu_ = mu else - if (present(width)) then - width_ = width - else - width_ = 3.0_pReal ! use +-3*sigma as default scatter - endif + mu_ = 0.0_pReal + end if - do - call random_number(rnd) - scatter = width_ * (2.0_pReal * rnd(1) - 1.0_pReal) - if (rnd(2) <= exp(-0.5_pReal * scatter**2)) exit ! test if scattered value is drawn - enddo + if (present(sigma)) then + sigma_ = sigma + else + sigma_ = 1.0_pReal + end if - math_sampleGaussVar = scatter * sigma - endif + call random_number(rnd) + x = mu_ + sigma_ * sqrt(-2.0_pReal*log(1.0_pReal-rnd(1)))*cos(2.0_pReal*PI*(1.0_pReal - rnd(2))) -end function math_sampleGaussVar +end subroutine math_normal !-------------------------------------------------------------------------------------------------- diff --git a/src/phase_mechanical_plastic_nonlocal.f90 b/src/phase_mechanical_plastic_nonlocal.f90 index c762039d4..bf0dc3b19 100644 --- a/src/phase_mechanical_plastic_nonlocal.f90 +++ b/src/phase_mechanical_plastic_nonlocal.f90 @@ -1592,21 +1592,15 @@ subroutine stateInit(ini,phase,Nentries) stt%rhoSglMobile(s,e) = densityBinning end do else ! homogeneous distribution with noise - do e = 1, Nentries - do f = 1,size(ini%N_sl,1) - from = 1 + sum(ini%N_sl(1:f-1)) - upto = sum(ini%N_sl(1:f)) - do s = from,upto - noise = [math_sampleGaussVar(0.0_pReal, ini%sigma_rho_u), & - math_sampleGaussVar(0.0_pReal, ini%sigma_rho_u)] - stt%rho_sgl_mob_edg_pos(s,e) = ini%rho_u_ed_pos_0(f) + noise(1) - stt%rho_sgl_mob_edg_neg(s,e) = ini%rho_u_ed_neg_0(f) + noise(1) - stt%rho_sgl_mob_scr_pos(s,e) = ini%rho_u_sc_pos_0(f) + noise(2) - stt%rho_sgl_mob_scr_neg(s,e) = ini%rho_u_sc_neg_0(f) + noise(2) - end do - stt%rho_dip_edg(from:upto,e) = ini%rho_d_ed_0(f) - stt%rho_dip_scr(from:upto,e) = ini%rho_d_sc_0(f) - end do + do f = 1,size(ini%N_sl,1) + from = 1 + sum(ini%N_sl(1:f-1)) + upto = sum(ini%N_sl(1:f)) + call math_normal(stt%rho_sgl_mob_edg_pos(from:upto,:),ini%rho_u_ed_pos_0(f),ini%sigma_rho_u) + call math_normal(stt%rho_sgl_mob_edg_neg(from:upto,:),ini%rho_u_ed_neg_0(f),ini%sigma_rho_u) + call math_normal(stt%rho_sgl_mob_scr_pos(from:upto,:),ini%rho_u_sc_pos_0(f),ini%sigma_rho_u) + call math_normal(stt%rho_sgl_mob_scr_neg(from:upto,:),ini%rho_u_sc_neg_0(f),ini%sigma_rho_u) + stt%rho_dip_edg(from:upto,:) = ini%rho_d_ed_0(f) + stt%rho_dip_scr(from:upto,:) = ini%rho_d_sc_0(f) end do end if