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Started by user Peter Roels Obtained jenkins_tests/clubb_release_diff_test/Jenkinsfile from git https://github.com/larson-group/clubb.git Running in Durability level: MAX_SURVIVABILITY [Pipeline] Start of Pipeline [Pipeline] node Still waiting to schedule task Waiting for next available executor Running on Jenkins in /home/jenkins/workspace/clubb_release_diff_test [Pipeline] { [Pipeline] stage [Pipeline] { (Declarative: Checkout SCM) [Pipeline] checkout The recommended git tool is: git Cloning the remote Git repository Cloning repository https://github.com/larson-group/clubb.git > git init /home/jenkins/workspace/clubb_release_diff_test # timeout=10 Fetching upstream changes from https://github.com/larson-group/clubb.git > git --version # timeout=10 > git --version # 'git version 1.8.3.1' using GIT_ASKPASS to set credentials THe key used by the system for the tests > git fetch --tags --progress https://github.com/larson-group/clubb.git +refs/heads/*:refs/remotes/origin/* # timeout=10 > git config remote.origin.url https://github.com/larson-group/clubb.git # timeout=10 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10 Avoid second fetch > git rev-parse refs/remotes/origin/master^{commit} # timeout=10 Checking out Revision c1e00c325e5d875ee54d6d6c30cdd8785dd5d6cd (refs/remotes/origin/master) > git config core.sparsecheckout # timeout=10 > git checkout -f c1e00c325e5d875ee54d6d6c30cdd8785dd5d6cd # timeout=10 Commit message: "Reducing the number of calls to Cholesky_factor. This is bit-for-bit for all standalone cases and our coarse res version of cam. larson-group/cam#129" > git rev-list --no-walk 9c1470d3d5919fbbdcb8d50313ff103166b49bf7 # timeout=10 [Pipeline] } [Pipeline] // stage [Pipeline] withEnv [Pipeline] { [Pipeline] stage [Pipeline] { (Checkout Clubb and Clubb_Release) [Pipeline] sh + git clone https://LarsonGroupSysAdmin:repo99sitori@github.com/larson-group/clubb.git Cloning into 'clubb'... + git clone https://LarsonGroupSysAdmin:repo99sitori@github.com/larson-group/clubb_release.git Cloning into 'clubb_release'... [Pipeline] } [Pipeline] // stage [Pipeline] stage [Pipeline] { (Diff) [Pipeline] sh + diff --exclude=.git --exclude=version_clubb_core.txt --exclude=version_silhs.txt -r clubb clubb_release diff '--exclude=.git' '--exclude=version_clubb_core.txt' '--exclude=version_silhs.txt' -r clubb/src/CLUBB_core/setup_clubb_pdf_params.F90 clubb_release/src/CLUBB_core/setup_clubb_pdf_params.F90 371a372,374 > > ice_supersat_frac_1(j,:) = pdf_params(j)%ice_supersat_frac_1 > ice_supersat_frac_2(j,:) = pdf_params(j)%ice_supersat_frac_2 405,410c408 < < do j = 1, ngrdcol < ice_supersat_frac_1(j,:) = pdf_params(j)%ice_supersat_frac_1 < ice_supersat_frac_2(j,:) = pdf_params(j)%ice_supersat_frac_2 < end do < --- > 496c494 < ! call stat_update_var( ihmp2_zt(i), hydrometp2_zt(:,i), stats_zt ) --- > ! call stat_update_var( ihmp2_zt(i), hydrometp2_zt(:,i), stats_zt ) 584c582 < ! call stat_update_var( iprecip_frac, precip_frac, stats_zt ) --- > ! call stat_update_var( iprecip_frac, precip_frac, stats_zt ) 593c591 < ! call stat_update_var( iprecip_frac_1, precip_frac_1, stats_zt ) --- > ! call stat_update_var( iprecip_frac_1, precip_frac_1, stats_zt ) 602c600 < ! call stat_update_var( iprecip_frac_2, precip_frac_2, stats_zt ) --- > ! call stat_update_var( iprecip_frac_2, precip_frac_2, stats_zt ) 611c609 < ! call stat_update_var( iNcnm, Ncnm, stats_zt ) --- > ! call stat_update_var( iNcnm, Ncnm, stats_zt ) 697,712d694 < < do k = 2, nz, 1 < do j = 1, ngrdcol < call calc_cholesky_corr_mtx_approx & < ( pdf_dim, corr_array_1_n(j,:,:,k), & ! intent(in) < corr_cholesky_mtx_1(j,:,:,k), corr_array_1_n(j,:,:,k) ) ! intent(out) < end do < end do < < do k = 2, nz, 1 < do j = 1, ngrdcol < call calc_cholesky_corr_mtx_approx & < ( pdf_dim, corr_array_2_n(j,:,:,k), & ! intent(in) < corr_cholesky_mtx_2(j,:,:,k), corr_array_2_n(j,:,:,k) ) ! intent(out) < end do < end do 715,772c697,710 < < if ( .not. l_interp_prescribed_params .and. l_fix_w_chi_eta_correlations & < .and. .not. l_calc_w_corr ) then < < ! When the flags are set this way, the correlation matrices do not vary with any vertical < ! values, and instead are determined entirely by prescribed values. This results in there < ! being only two unique correlation matrices, one for when the grid box is in cloud < ! and one for when it is not. So instead of setting up correlation matrices for all < ! grid boxes then calculating their Cholesky decomps, we can simply set up two correlation < ! matrices, one for in cloud and one for out cloud, calculate the corresponding < ! Cholesky decompositions, then use the value of rc at each grid box to determine whether < ! we assign the in cloud or out of cloud matrices to that grid box. < call calc_corr_norm_and_cholesky_factor( nz, ngrdcol, pdf_dim, iiPDF_type, & < rc_1, rc_2, & < corr_array_n_cloud, corr_array_n_below, & < corr_array_1_n, corr_array_2_n, & < corr_cholesky_mtx_1, corr_cholesky_mtx_2 ) < < else < < ! The correlation matrices can vary with vertical values. So we need to set the < ! correlation matrices up for each grid box, then find the Cholesky decomp for each < ! grid box individually. This is very computationally expensive. < < call comp_corr_norm( nz, pdf_dim, ngrdcol, wm_zt(:,:), rc_1(:,:), rc_2(:,:), & < cloud_frac_1(:,:), cloud_frac_2(:,:), mixt_frac(:,:), & < precip_frac_1(:,:), precip_frac_2(:,:), & < wpNcnp_zt(:,:), wphydrometp_zt(:,:,:), & < mu_x_1(:,:,:), mu_x_2(:,:,:), & < sigma_x_1(:,:,:), sigma_x_2(:,:,:), & < sigma_x_1_n(:,:,:), sigma_x_2_n(:,:,:), & < corr_array_n_cloud, corr_array_n_below, & < pdf_params, & < iiPDF_type, & < l_calc_w_corr, & < l_fix_w_chi_eta_correlations, & < corr_array_1_n(:,:,:,:), corr_array_2_n(:,:,:,:) ) < < ! Compute choleksy factorization for the correlation matrix of 1st PDF component < do k = 2, nz, 1 < do j = 1, ngrdcol < call Cholesky_factor( pdf_dim, corr_array_1_n(j,:,:,k), & ! In < corr_array_scaling, corr_cholesky_mtx_1(j,:,:,k), & ! Out < l_corr_array_scaling ) ! Out < end do < end do < < ! Compute choleksy factorization for the correlation matrix of 2nd PDF component < do k = 2, nz, 1 < do j = 1, ngrdcol < call Cholesky_factor( pdf_dim, corr_array_2_n(j,:,:,k), & ! In < corr_array_scaling, corr_cholesky_mtx_2(j,:,:,k), & ! Out < l_corr_array_scaling ) ! Out < end do < end do < < end if < --- > > call comp_corr_norm( nz, pdf_dim, ngrdcol, wm_zt(:,:), rc_1(:,:), rc_2(:,:), & > cloud_frac_1(:,:), cloud_frac_2(:,:), mixt_frac(:,:), & > precip_frac_1(:,:), precip_frac_2(:,:), & > wpNcnp_zt(:,:), wphydrometp_zt(:,:,:), & > mu_x_1(:,:,:), mu_x_2(:,:,:), & > sigma_x_1(:,:,:), sigma_x_2(:,:,:), & > sigma_x_1_n(:,:,:), sigma_x_2_n(:,:,:), & > corr_array_n_cloud, corr_array_n_below, & > pdf_params, & > iiPDF_type, & > l_calc_w_corr, & > l_fix_w_chi_eta_correlations, & > corr_array_1_n(:,:,:,:), corr_array_2_n(:,:,:,:) ) 777,781c715,719 < sigma_x_1_n(:,:,:), sigma_x_2_n(:,:,:), & < sigma2_on_mu2_ip_1(:,:,:), sigma2_on_mu2_ip_2(:,:,:), & < corr_array_1_n(:,:,:,:), & < corr_array_2_n(:,:,:,:), & < corr_array_1(:,:,:,:), corr_array_2(:,:,:,:) ) --- > sigma_x_1_n(:,:,:), sigma_x_2_n(:,:,:), & > sigma2_on_mu2_ip_1(:,:,:), sigma2_on_mu2_ip_2(:,:,:), & > corr_array_1_n(:,:,:,:), & > corr_array_2_n(:,:,:,:), & > corr_array_1(:,:,:,:), corr_array_2(:,:,:,:) ) 815a754,793 > if ( l_diagnose_correlations ) then > > do k = 2, nz, 1 > do j = 1, ngrdcol > call calc_cholesky_corr_mtx_approx & > ( pdf_dim, corr_array_1_n(j,:,:,k), & ! intent(in) > corr_cholesky_mtx_1(j,:,:,k), corr_array_1_n(j,:,:,k) ) ! intent(out) > end do > end do > > do k = 2, nz, 1 > do j = 1, ngrdcol > call calc_cholesky_corr_mtx_approx & > ( pdf_dim, corr_array_2_n(j,:,:,k), & ! intent(in) > corr_cholesky_mtx_2(j,:,:,k), corr_array_2_n(j,:,:,k) ) ! intent(out) > end do > end do > > else > > ! Compute choleksy factorization for the correlation matrix (out of > ! cloud) > do k = 2, nz, 1 > do j = 1, ngrdcol > call Cholesky_factor( pdf_dim, corr_array_1_n(j,:,:,k), & ! In > corr_array_scaling, corr_cholesky_mtx_1(j,:,:,k), & ! Out > l_corr_array_scaling ) ! Out > end do > end do > > do k = 2, nz, 1 > do j = 1, ngrdcol > call Cholesky_factor( pdf_dim, corr_array_2_n(j,:,:,k), & ! In > corr_array_scaling, corr_cholesky_mtx_2(j,:,:,k), & ! Out > l_corr_array_scaling ) ! Out > end do > end do > > end if > 1145,1189d1122 < < !============================================================================= < subroutine calc_corr_norm_and_cholesky_factor( nz, ngrdcol, pdf_dim, iiPDF_type, & < rc_1, rc_2, & < corr_array_n_cloud, corr_array_n_below, & < corr_array_1_n, corr_array_2_n, & < corr_cholesky_mtx_1, corr_cholesky_mtx_2 ) < < ! Description: This subroutine computes the correlation arrays and correlation < ! Cholesky matrices of PDF vars for both components. Here, we assume that < ! there are only two unique correlation arrays, which allows us to compute < ! these two unique arrays and their corresponding Cholesky decompositions, < ! then use rc to determine which one to assign to each grid column and < ! vertical level. If the correlation arrays vary based on vertically varying < ! values, then this subroutine is not appropriate. < ! < ! References: < ! https://github.com/larson-group/cam/issues/129#issuecomment-816205563 < !----------------------------------------------------------------------- < < use constants_clubb, only: & < rc_tol, & < zero < < use clubb_precision, only: & < core_rknd ! Variable(s) < < use array_index, only: & < iiPDF_chi, & ! Variable(s) < iiPDF_eta, & < iiPDF_w, & < iiPDF_Ncn < < use model_flags, only: & < iiPDF_ADG1, & ! Variable(s) < iiPDF_ADG2, & < iiPDF_new_hybrid < < use pdf_parameter_module, only: & < pdf_parameter ! Variable(s) < < use matrix_operations, only: & < Cholesky_factor ! Procedure(s) < < implicit none 1191,1324d1123 < ! Input Variables < integer, intent(in) :: & < nz, & ! Number of vertical levels < pdf_dim, & ! Number of variables in the corr/mean/stdev arrays < ngrdcol ! Number of grid columns < < real( kind = core_rknd ), dimension(ngrdcol,nz), intent(in) :: & < rc_1, & ! Mean of r_c (1st PDF component) [kg/kg] < rc_2 ! Mean of r_c (2nd PDF component) [kg/kg] < < real( kind = core_rknd ), dimension(pdf_dim,pdf_dim), intent(in) :: & < corr_array_n_cloud, & ! Prescribed correlation array in cloud [-] < corr_array_n_below ! Prescribed correlation array below cloud [-] < < integer, intent(in) :: & < iiPDF_type ! Selected option for the two-component normal (double < ! Gaussian) PDF type to use for the w, rt, and theta-l (or < ! w, chi, and eta) portion of CLUBB's multivariate, < ! two-component PDF. < < ! Output Variables < real( kind = core_rknd ), dimension(ngrdcol,pdf_dim,pdf_dim,nz), intent(out) :: & < corr_array_1_n, & ! Corr. array (normal space) of PDF vars. (comp. 1) [-] < corr_array_2_n, & ! Corr. array (normal space) of PDF vars. (comp. 2) [-] < corr_cholesky_mtx_1, & ! Transposed corr. cholesky matrix, 1st comp. [-] < corr_cholesky_mtx_2 ! Transposed corr. cholesky matrix, 2nd comp. [-] < < ! Local Variables < real( kind = core_rknd ), dimension(pdf_dim,pdf_dim) :: & < corr_array_cloud, & ! General in cloud corr. matrix < corr_array_below, & ! General out of cloud corr. matrix < corr_cholesky_mtx_cloud, & ! General in cloud Cholesky matrix < corr_cholesky_mtx_below ! General out of cloud Cholesky matrix < < logical :: & < l_corr_array_scaling ! Dummy variable that we need for calling Cholesky_factor < < real( kind = core_rknd ), dimension(pdf_dim) :: & < corr_array_scaling ! Dummy variable that we need for calling Cholesky_factor < < integer :: jvar, j, k ! Indices < < logical, parameter :: & < l_follow_ADG1_PDF_standards = .true. < < !-------------------- Begin Code -------------------- < < ! Initialize correlation arrays with prescribed values < corr_array_cloud(:,:) = corr_array_n_cloud(:,:) < corr_array_below(:,:) = corr_array_n_below(:,:) < < ! The ADG1 PDF fixes the correlation of w and rt and the correlation of < ! w and theta_l to be 0, which means the correlation of w and chi and the < ! correlation of w and eta must also be 0. < if ( ( iiPDF_type == iiPDF_ADG1 .or. iiPDF_type == iiPDF_ADG2 & < .or. iiPDF_type == iiPDF_new_hybrid ) & < .and. l_follow_ADG1_PDF_standards ) then < < corr_array_cloud(iiPDF_w,iiPDF_chi) = zero < corr_array_below(iiPDF_w,iiPDF_chi) = zero < < corr_array_cloud(iiPDF_w,iiPDF_eta) = zero < corr_array_below(iiPDF_w,iiPDF_eta) = zero < < end if < < ! Ncn is an inherently in-cloud property, so replace out of cloud correlation values < ! with in cloud ones. < corr_array_below(iiPDF_Ncn,iiPDF_chi) = corr_array_cloud(iiPDF_Ncn,iiPDF_chi) < corr_array_below(iiPDF_Ncn,iiPDF_eta) = corr_array_cloud(iiPDF_Ncn,iiPDF_eta) < < < ! Estimates the correlation of the natural logarithm of a < ! hydrometeor species and eta using the correlation of chi and eta and the < ! correlation of chi and the natural logarithm of the hydrometeor. This < ! facilitates the Cholesky decomposability of the correlation array that will < ! inevitably be decomposed for SILHS purposes. Without this estimation, we < ! have found that the resulting correlation matrix cannot be decomposed. < do jvar = iiPDF_Ncn+1, pdf_dim < < corr_array_cloud(jvar,iiPDF_eta) = corr_array_cloud(iiPDF_eta,iiPDF_chi) & < * corr_array_cloud(jvar,iiPDF_chi) < < corr_array_below(jvar,iiPDF_eta) = corr_array_below(iiPDF_eta,iiPDF_chi) & < * corr_array_below(jvar,iiPDF_chi) < < end do < < ! Calc in cloud Cholesky < call Cholesky_factor( pdf_dim, corr_array_cloud(:,:), & ! In < corr_array_scaling, corr_cholesky_mtx_cloud(:,:), & ! Out < l_corr_array_scaling ) ! Out < < ! Calc out of cloud Cholesky < call Cholesky_factor( pdf_dim, corr_array_below(:,:), & ! In < corr_array_scaling, corr_cholesky_mtx_below(:,:), & ! Out < l_corr_array_scaling ) ! Out < < ! Use rc_1 to determine which correlation and Cholesky matrices to assign to 1st PDF < do k = 1, nz < do j = 1, ngrdcol < < if ( rc_1(j,k) > rc_tol ) then < ! Assign in cloud matrices to 1st PDF component < corr_array_1_n(j,:,:,k) = corr_array_cloud < corr_cholesky_mtx_1(j,:,:,k) = corr_cholesky_mtx_cloud < else < ! Assign out of cloud matrices to 1st PDF component < corr_array_1_n(j,:,:,k) = corr_array_below < corr_cholesky_mtx_1(j,:,:,k) = corr_cholesky_mtx_below < end if < < end do < end do < < ! Use rc_1 to determine which correlation and Cholesky matrices to assign to 2nd PDF < do k = 1, nz < do j = 1, ngrdcol < < if ( rc_2(j,k) > rc_tol ) then < ! Assign in cloud matrices to 2nd PDF component < corr_array_2_n(j,:,:,k) = corr_array_cloud < corr_cholesky_mtx_2(j,:,:,k) = corr_cholesky_mtx_cloud < else < ! Assign out of cloud matrices to 2nd PDF component < corr_array_2_n(j,:,:,k) = corr_array_below < corr_cholesky_mtx_2(j,:,:,k) = corr_cholesky_mtx_below < end if < < end do < end do < < end subroutine calc_corr_norm_and_cholesky_factor < [Pipeline] } [Pipeline] // stage [Pipeline] stage [Pipeline] { (Declarative: Post Actions) [Pipeline] cleanWs [WS-CLEANUP] Deleting project workspace... [WS-CLEANUP] Deferred wipeout is used... [WS-CLEANUP] done [Pipeline] emailext Sending email to: messnermet@uwm.edu [Pipeline] } [Pipeline] // stage [Pipeline] } [Pipeline] // withEnv [Pipeline] } [Pipeline] // node [Pipeline] End of Pipeline ERROR: script returned exit code 1 Finished: FAILURE