1567.8429false10387910clubb_jax.pytests.auto_llm_generated_pytests.test_KK_Nrm_tendencies0.0040test_auto_mean_drop_mass_constantfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_KK_Nrm_tendencies0.240test_evap_local_mean_formula_and_safe_divfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_KK_Nrm_tendencies0.7130test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_NNL_covar_const_limits3.2930test_const_x3_x1x3_x2x3_limitsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_NNL_covar_const_vs_MM2.7010test_trivar_const_variantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_NNL_covar_const_vs_MM1.0990test_quadrivar_const_variantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_NNL_covar_vs_MM4.4330test_trivar_covar_kernel_and_Ymean_termfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_NNL_covar_vs_MM3.2540test_quadrivar_covar_kernel_and_Ymean_termfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_Nc_Ncn_eqns3.7880test_Ncnm_bit_to_bit_vs_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_Nc_Ncn_eqns11.7580test_forward_vs_numpy_referencefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_T_in_K0.0010test_closed_formfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_T_in_K0.0010test_exact_inversefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_T_in_K0.0010test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_adg1_adg2_responder_params0.9420test_responder_params_matches_referencefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_adg1_adg2_responder_params0.0040test_alpha_x_clip_to_unit_intervalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_adg1_adg2_responder_params0.9090test_responder_params_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_adg2_driver1.9140test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_adg2_driver3.1410test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.1210test_smooth_min_closed_formfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.1290test_smooth_min_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.1410test_smooth_max_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.4190test_compute_Cx_fnc_Richardson_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.4420test_calc_xpwp_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.150test_calc_xpwp_identityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras1.0020test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.2520test_stability_and_Ri_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.0980test_vertical_avg_integral_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras1.5740test_brunt_vaisala_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.2190test_calculate_thlp2_rad_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.1610test_Lscale_width_vert_avg_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_helper_extras0.2180test_wp23_term_splat_lhs_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_xp3_simplified0.6610test_term_rhs_formulasfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_advance_xp3_simplified0.6110test_steady_state_vs_compositionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_binormal_moments0.4480test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_binormal_moments0.5510test_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_binormal_moments0.4760test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial0.0930test_general_partial_closed_form_and_mean_identityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial0.0460test_const_x2_partial_closed_form_and_limitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial0.5080test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial_rr_Nr0.3160test_rr_all_vary_generalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial_rr_Nr0.0010test_rr_x1_const_reuses_mean_const_x1falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial_rr_Nr0.0010test_rr_x2_const_partialfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial_rr_Nr0.0010test_rr_both_const_allfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_covar_partial_rr_Nr0.0010test_Nr_all_vary_swappedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_mean_const0.0950test_const_all_closed_form_and_limitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_mean_const0.0470test_const_x1_closed_form_and_limitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_LL_mean_const0.3630test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_NL_mean_eq2.570test_both_vary_selects_generalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_NL_mean_eq0.0070test_x1_const_selects_const_x1falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_NL_mean_eq0.0060test_x2_const_selects_const_x2falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_NL_mean_eq0.0040test_both_const_selects_const_allfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bivar_NL_mean_eq0.0050test_parab_cyl_overflow_forces_const_x1falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.9310test_planck_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.1990test_newexp_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.7320test_rayle_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad1.4990test_gascon_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad1.7610test_cloudg_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.3970test_comscp_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad2.2610test_two_rt_lw_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad1.3250test_two_rt_sw_vs_fortran_replicafalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.004FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h'def test_gases_ckd_data_parser(): """The gases_ckd_data.h parser builds the correlated-k tables with correct shapes, fully filled (no missing T-coefficient slices), and the right spot-checked values.""" from clubb_jax.src.Radiation.BUGSrad.gases_ckd_data import tables, KG, NUMPS, NUMPIR, NUMTS, NUMTIR > t = tables() ^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:367: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:102: in tables _TABLES = load_tables() ^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:64: in load_tables for stmt in _logical_lines(os.path.normpath(_DATA_H)): ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ path = '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' def _logical_lines(path): """Strip comments + #directives, join `&`-continued lines into logical statements.""" out, buf = [], '' > for raw in open(path): ^^^^^^^^^^ E FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:39: FileNotFoundError4test_gases_ckd_data_parserfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.0FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h'def test_gases_dispatch_vs_fortran_replica(): """The `gases` 18-band dispatch (table indexing + overlap formulas + hk weights) vs a NumPy replica.""" from clubb_jax.src.Radiation.BUGSrad.gases_ckd import gases, pscale from clubb_jax.src.Radiation.BUGSrad.gases_ckd_data import tables, KG, STANPS, STANPIR from clubb_jax.src.Radiation.BUGSrad.bugsrad_physconst import MOLAR_VOLUME as MV, GRAVITY as G, \ MW_H2O as MWh, MW_O3 as MWo, MW_DRY_AIR as MWd > T = tables() ^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:396: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:102: in tables _TABLES = load_tables() ^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:64: in load_tables for stmt in _logical_lines(os.path.normpath(_DATA_H)): ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ path = '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' def _logical_lines(path): """Strip comments + #directives, join `&`-continued lines into logical statements.""" out, buf = [], '' > for raw in open(path): ^^^^^^^^^^ E FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:39: FileNotFoundError4test_gases_dispatch_vs_fortran_replicafalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad1.6360test_gases_ckd_helpers_vs_fortran_replicafalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad4.515FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h'def test_bugs_lwr(): """LW band driver: the no-cloud invariant (all-sky == clear-sky, bit-exact), finiteness, physical flux ranges, and clouds adding downward LW.""" from clubb_jax.src.Radiation.BUGSrad.bugs_lwr import bugs_lwr rng = np.random.default_rng(11) ncol, nlm = 2, 25 pp = np.cumsum(15.0 + 10.0 * rng.random((ncol, nlm + 1)), axis=1) + 1.0 dp = pp[:, 1:] - pp[:, :-1]; ppl = 0.5 * (pp[:, :-1] + pp[:, 1:]) tt = 220.0 + 70.0 * rng.random((ncol, nlm)); ts = 290.0 + 10.0 * rng.random(ncol) rmix = 1e-3 * rng.random((ncol, nlm)); o3mix = 1e-6 * rng.random((ncol, nlm)) cw0 = np.zeros((ncol, nlm)); ci0 = np.zeros((ncol, nlm)) fd, fu, fdcl, fucl = (np.asarray(x) for x in > bugs_lwr(ts, ppl, dp, tt, rmix, cw0, ci0, o3mix, pp, 330.0, 1.6, 0.28)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:533: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ clubb_jax/src/Radiation/BUGSrad/bugs_lwr.py:77: in bugs_lwr tg, hk = gases(ib, ig, dp, tt, rmix, o3mix, umco2, umch4, umn2o, pkd, ip1, ip2, pp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd.py:108: in gases T = tables() ^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:102: in tables _TABLES = load_tables() ^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:64: in load_tables for stmt in _logical_lines(os.path.normpath(_DATA_H)): ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ path = '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' def _logical_lines(path): """Strip comments + #directives, join `&`-continued lines into logical statements.""" out, buf = [], '' > for raw in open(path): ^^^^^^^^^^ E FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:39: FileNotFoundError4test_bugs_lwrfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.905FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h'def test_bugs_swr(): """SW band driver: no-cloud invariant (all-sky==clear-sky bit-exact), the TOA incident solar (fdsw[TOA] = amu0·slr·Σband_solar = amu0·slr·1339.946) validating the accumulation, and finiteness.""" from clubb_jax.src.Radiation.BUGSrad.bugs_swr import bugs_swr rng = np.random.default_rng(12) ncol, nlm = 2, 25 pp = np.cumsum(15.0 + 10.0 * rng.random((ncol, nlm + 1)), axis=1) + 1.0 dp = pp[:, 1:] - pp[:, :-1]; ppl = 0.5 * (pp[:, :-1] + pp[:, 1:]) tt = 230.0 + 60.0 * rng.random((ncol, nlm)); ts = 290.0 * np.ones(ncol) rmix = 1e-3 * rng.random((ncol, nlm)); o3mix = 1e-6 * rng.random((ncol, nlm)) amu0 = np.array([0.5, 0.8]); slr = np.ones(ncol); alb = 0.2 * np.ones(ncol) cw0 = np.zeros((ncol, nlm)); ci0 = np.zeros((ncol, nlm)) out = [np.asarray(x) for x in > bugs_swr(ts, amu0, slr, alb, alb, alb, alb, ppl, dp, tt, rmix, cw0, ci0, o3mix, pp, 330.0, 1.6, 0.28)] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:558: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ clubb_jax/src/Radiation/BUGSrad/bugs_swr.py:65: in bugs_swr tg, hk = gases(ib, ig, dp, ttem, rmix, o3mix, umco2, umch4, umn2o, pkd, ip1, ip2, pp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd.py:108: in gases T = tables() ^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:102: in tables _TABLES = load_tables() ^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:64: in load_tables for stmt in _logical_lines(os.path.normpath(_DATA_H)): ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ path = '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' def _logical_lines(path): """Strip comments + #directives, join `&`-continued lines into logical statements.""" out, buf = [], '' > for raw in open(path): ^^^^^^^^^^ E FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:39: FileNotFoundError4test_bugs_swrfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad4.584FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h'def test_bugs_rad(): """Main orchestration: LW heating conserves (telescoping flux divergence), night columns get zero SW heating, the no-cloud invariant (all-sky heating == clear-sky), and physical heating rates.""" from clubb_jax.src.Radiation.BUGSrad.bugs_rad import bugs_rad from clubb_jax.src.Radiation.BUGSrad.bugsrad_physconst import GRAVITY, CP_DRY_AIR rng = np.random.default_rng(13) ncol, nlm = 2, 30 pl2 = np.cumsum(15.0 + 10.0 * rng.random((ncol, nlm + 1)), axis=1) + 1.0 dpl = pl2[:, 1:] - pl2[:, :-1]; ppl = 0.5 * (pl2[:, :-1] + pl2[:, 1:]) tl = 220.0 + 70.0 * rng.random((ncol, nlm)); ts = 290.0 * np.ones(ncol) ql = 1e-3 * rng.random((ncol, nlm)); o3 = 1e-6 * rng.random((ncol, nlm)) # specific humidity, ozone amu0 = np.array([0.5, 0.005]); slr = np.ones(ncol); alb = 0.2 * np.ones(ncol) # col 0 day, col 1 night qcwl = np.where(rng.random((ncol, nlm)) > 0.6, 1e-4, 0.0) # cloud-water mixing ratio [kg/kg] qcil = np.zeros((ncol, nlm)); acld = np.where(qcwl > 0, 1.0, 0.0) # cloud ice, cloud fraction > r = bugs_rad(pl2, ppl, dpl, tl, ql, qcwl, qcil, o3, ts, amu0, slr, alb, alb, alb, alb, acld, s0=1367.0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:582: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ clubb_jax/src/Radiation/BUGSrad/bugs_rad.py:62: in bugs_rad fdlw, fulw, fdlwcl, fulwcl = bugs_lwr(ts, ppl, dpl, tl, rmix, cwrho, cirho, o3mix, pl2, clubb_jax/src/Radiation/BUGSrad/bugs_lwr.py:77: in bugs_lwr tg, hk = gases(ib, ig, dp, tt, rmix, o3mix, umco2, umch4, umn2o, pkd, ip1, ip2, pp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd.py:108: in gases T = tables() ^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:102: in tables _TABLES = load_tables() ^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:64: in load_tables for stmt in _logical_lines(os.path.normpath(_DATA_H)): ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ path = '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' def _logical_lines(path): """Strip comments + #directives, join `&`-continued lines into logical statements.""" out, buf = [], '' > for raw in open(path): ^^^^^^^^^^ E FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:39: FileNotFoundError4test_bugs_radfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad1.755FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_bugsrad_driver(): """CLUBB↔BUGSrad interface: std-atmosphere loads (50 levels), determine_extended_atmos_bounds gives sane bounds for a gabls3-like grid (model top 5 km, radiation_top 30 km), and compute_bugsrad_radiation produces a strictly-increasing radiation-grid pressure, finite CLUBB-grid heating, and zero SW at night.""" import numpy as np from clubb_jax.src.Input_fields.sounding import load_extended_std_atm from clubb_jax.src.Radiation.bugsrad_driver import ( determine_extended_atmos_bounds, build_rad_grid_setup, compute_bugsrad_radiation) ext = load_extended_std_atm() assert ext['alt'].shape == (50,) and ext['alt'][0] == 1000.0 and ext['alt'][-1] == 50000.0 nzm, dz, ncol = 51, 100.0, 2 zm = np.arange(nzm) * dz # 0..5000 m zm_spacing = np.full(nzm - 1, dz) p_zm = 1013e2 * np.exp(-zm / 8000.0) # Pa, hydrostatic (top ≈ 542 mb) rad_top = 30000.0 bottom, top, rsize, linbuf = determine_extended_atmos_bounds(zm, zm_spacing, p_zm, rad_top, ext) assert rsize >= 1 and linbuf >= 0 and top >= bottom, "degenerate extension bounds" assert ext['alt'][bottom - 1] >= 5000.0 and ext['alt'][top - 1] <= 30000.0, "bounds outside [5,30] km" setup = build_rad_grid_setup(zm, zm_spacing, p_zm, rad_top, ext) assert setup['buffer'] == linbuf + rsize # synthetic state on the nzt grid nzt = nzm - 1; rng = np.random.default_rng(7) zt = 0.5 * (zm[1:] + zm[:-1]) T = np.tile(288.0 - 6.5e-3 * zt, (ncol, 1)) p_zt = np.tile(1013e2 * np.exp(-zt / 8000.0), (ncol, 1)) exner = (p_zt / 1.0e5) ** (287.0 / 1004.0) rho = np.tile(p_zm / (287.0 * (288.0 - 6.5e-3 * zm)), (ncol, 1)) rtm = 5e-3 * np.ones((ncol, nzt)); rcm = np.zeros((ncol, nzt)); rcm[:, 5:8] = 1e-4 cf = np.where(rcm > 0, 1.0, 0.0); rim = np.zeros_like(rcm); rsm = np.zeros_like(rcm); isf = np.zeros_like(rcm) amu0 = np.array([0.5, 0.0]); slr = np.ones(ncol); alb = 0.23 * np.ones(ncol) p_zm2 = np.tile(p_zm, (ncol, 1)) > res = compute_bugsrad_radiation(setup, T, rcm, rtm, rsm, rim, cf, isf, p_zt, p_zm2, rho, exner, amu0, slr, alb, alb, alb, alb, sol_const=1321.0) clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:628: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ clubb_jax/src/Radiation/bugsrad_driver.py:143: in compute_bugsrad_radiation out = fn(playerinmb, p_rad, diff_pres, T_rad, q_rad, rcmic_rad, rcil_rad, o3_rad, clubb_jax/src/Radiation/BUGSrad/bugs_rad.py:62: in bugs_rad fdlw, fulw, fdlwcl, fulwcl = bugs_lwr(ts, ppl, dpl, tl, rmix, cwrho, cirho, o3mix, pl2, clubb_jax/src/Radiation/BUGSrad/bugs_lwr.py:77: in bugs_lwr tg, hk = gases(ib, ig, dp, tt, rmix, o3mix, umco2, umch4, umn2o, pkd, ip1, ip2, pp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd.py:108: in gases T = tables() ^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:102: in tables _TABLES = load_tables() ^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:64: in load_tables for stmt in _logical_lines(os.path.normpath(_DATA_H)): ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ path = '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' def _logical_lines(path): """Strip comments + #directives, join `&`-continued lines into logical statements.""" out, buf = [], '' > for raw in open(path): ^^^^^^^^^^ E FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:39: FileNotFoundError4test_bugsrad_driverfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad0.119TypeError: Error interpreting argument to <function advance_clubb_radiation at 0x741183fbac00> as an abstract array. The problematic value is of type <class 'str'> and was passed to the function at path args[0]['cfg']['rad_scheme']. This typically means that a jit-wrapped function was called with a non-array argument, and this argument was not marked as static using the static_argnums or static_argnames parameters of jax.jit. -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_bugsrad_radiation_dispatch(): """End-to-end wiring: advance_clubb_radiation(rad_scheme='bugsrad') builds the grid setup, maps a gabls3-like CLUBB state through bugs_rad, and writes a finite K/s heating rate into state['radht'] (shape (1,nzt)).""" import numpy as np from clubb_jax.src.CLUBB_core.grid_class import setup_grid from clubb_jax.src.Radiation.radiation_module import advance_clubb_radiation gr = setup_grid(ngrdcol=1, deltaz=100.0, zm_init=0.0, zm_top=5000.0) nzt, nzm = gr.nzt, gr.nzm zt = np.asarray(gr.zt)[0] p_zt = (1013e2 * np.exp(-zt / 8000.0))[None, :] exner = (p_zt / 1.0e5) ** (287.0 / 1004.67) thlm = np.full((1, nzt), 295.0); rtm = np.full((1, nzt), 5e-3) rcm = np.zeros((1, nzt)); rcm[:, 5:9] = 2e-4 cloud_frac = np.where(rcm > 0, 1.0, 0.0) rho_zm = (np.asarray(p_zt) / (287.0 * 290.0)) rho_zm = np.concatenate([rho_zm, rho_zm[:, -1:]], axis=1) # pad to nzm cfg = dict(rad_scheme="bugsrad", radiation_top=30000.0, sol_const=1321.0, slr=1.0, alvdr=0.23, alvdf=0.23, alndr=0.23, alndf=0.23, l_fix_cos_solar_zen=True, cos_solar_zen_values=[0.5]) state = dict(cfg=cfg, gr=gr, ngrdcol=1, nzt=nzt, nzm=nzm, stats_writer=None, rad_scheme="bugsrad", p_in_Pa=p_zt, exner=exner, thlm=thlm, rtm=rtm, rcm=rcm, cloud_frac=cloud_frac, ice_supersat_frac=np.zeros((1, nzt)), rho_zm=rho_zm, radht=np.zeros((1, nzt))) > advance_clubb_radiation(state, time_current=43200.0) # local noon-ish ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: Error interpreting argument to <function advance_clubb_radiation at 0x741183fbac00> as an abstract array. The problematic value is of type <class 'str'> and was passed to the function at path args[0]['cfg']['rad_scheme']. E This typically means that a jit-wrapped function was called with a non-array argument, and this argument was not marked as static using the static_argnums or static_argnames parameters of jax.jit. E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:661: TypeError4test_bugsrad_radiation_dispatchfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_bugsrad5.849FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_bugs_rad_differentiable(): """The BUGSrad radiative transfer is DIFFERENTIABLE (a stated project goal): jax.grad of a radiative loss (TOA outgoing LW + total SW heating) w.r.t. temperature and cloud water is finite AND nonzero (the radiation responds to its physical inputs). cloudg is now fully float64 (REFACTOR A3).""" import jax, jax.numpy as jnp from clubb_jax.src.Radiation.BUGSrad.bugs_rad import bugs_rad rng = np.random.default_rng(1); ncol, nlm = 1, 40 pl2 = jnp.asarray(np.cumsum(15.0 + 10.0 * rng.random((ncol, nlm + 1)), axis=1) + 1.0) dpl = pl2[:, 1:] - pl2[:, :-1]; ppl = 0.5 * (pl2[:, :-1] + pl2[:, 1:]) tl0 = jnp.asarray(220.0 + 70.0 * rng.random((ncol, nlm))); ts = jnp.asarray(290.0 * np.ones(ncol)) ql = jnp.asarray(1e-3 * rng.random((ncol, nlm))); o3 = jnp.asarray(1e-6 * rng.random((ncol, nlm))) qcwl0 = jnp.asarray(np.where(rng.random((ncol, nlm)) > 0.5, 1e-4, 0.0)); qcil = jnp.zeros((ncol, nlm)) acld = jnp.asarray(np.where(np.asarray(qcwl0) > 0, 1.0, 0.0)) amu0 = jnp.asarray([0.5]); slr = jnp.ones(ncol); alb = jnp.asarray(0.2 * np.ones(ncol)) def loss(tl, qcwl): r = bugs_rad(pl2, ppl, dpl, tl, ql, qcwl, qcil, o3, ts, amu0, slr, alb, alb, alb, alb, acld, s0=1367.0) return jnp.sum(r['fulw'][:, 0]) + jnp.sum(r['asl']) > g_t, g_q = jax.grad(loss, argnums=(0, 1))(tl0, qcwl0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:691: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ clubb_jax/pytests/auto_llm_generated_pytests/test_bugsrad.py:688: in loss r = bugs_rad(pl2, ppl, dpl, tl, ql, qcwl, qcil, o3, ts, amu0, slr, alb, alb, alb, alb, acld, s0=1367.0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/bugs_rad.py:62: in bugs_rad fdlw, fulw, fdlwcl, fulwcl = bugs_lwr(ts, ppl, dpl, tl, rmix, cwrho, cirho, o3mix, pl2, clubb_jax/src/Radiation/BUGSrad/bugs_lwr.py:77: in bugs_lwr tg, hk = gases(ib, ig, dp, tt, rmix, o3mix, umco2, umch4, umn2o, pkd, ip1, ip2, pp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd.py:108: in gases T = tables() ^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:102: in tables _TABLES = load_tables() ^^^^^^^^^^^^^ clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:64: in load_tables for stmt in _logical_lines(os.path.normpath(_DATA_H)): ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ path = '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' def _logical_lines(path): """Strip comments + #directives, join `&`-continued lines into logical statements.""" out, buf = [], '' > for raw in open(path): ^^^^^^^^^^ E FileNotFoundError: [Errno 2] No such file or directory: '/home/jenkins/workspace/clubb_jax/clubb_release/src/Radiation/BUGSrad/gases_ckd_data.h' E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/src/Radiation/BUGSrad/gases_ckd_data.py:39: FileNotFoundError4test_bugs_rad_differentiablefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_corrs_binormal0.9210test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_corrs_binormal1.1080test_round_tripfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_corrs_binormal0.0050test_boundfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_corrs_binormal0.6650test_smooth_corr_quotient_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_corrs_binormal1.4680test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm2.150test_both_precip_preserves_mean_and_variancefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm0.0130test_rico_params_non_emergencyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm0.0280test_root_sign_selectionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm0.0140test_emergency_preserves_meanfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm0.0270test_single_component_branchesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm2.0530test_no_precip_and_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm1.8510test_compute_mean_stdev_columnsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm0.3030test_norm_transform_matches_L2NfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_comp_mu_sigma_hm3.5070test_orchestration_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_corr_norm_cholesky2.5210test_reconstruction_and_structurefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_corr_norm_cholesky0.0520test_adjustments_and_selectionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_corr_norm_cholesky3.5030test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_corr_w_hm_n0.3740test_round_tripfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_corr_w_hm_n0.3380test_branches_vs_numpyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_corr_w_hm_n0.0010test_clampfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_corr_w_hm_n0.7570test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_ice_cloud_frac_component2.330test_below_freezing_closed_form_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_ice_cloud_frac_component0.0050test_above_freezing_returns_cf_liqfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_ice_cloud_frac_component0.0040test_truncation_limitsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_ice_cloud_frac_component0.7040test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_liquid_cloud_frac_component3.2020test_closed_form_and_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_liquid_cloud_frac_component0.0030test_truncation_limitsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_liquid_cloud_frac_component1.0180test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_roots0.2970test_cube_rootfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_roots0.5590test_quadraticfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_roots0.850test_cubicfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_roots1.3360test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_calc_roots1.144AssertionError: f2py cubic sorted-real mismatch 6.73e-01 assert np.float64(0.6732766293498132) < 1e-08def test_f2py_oracle(): try: import clubb_f2py fn = clubb_f2py.f2py_cubic_solve except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py cubic_solve oracle: SKIP ({type(e).__name__})") # Cases incl. a NEGATIVE-R cubic ([-1.5,0,1.5,-0.75]) where the Cardano args R±sqrt(D) are negative real — # this is the case that exposed the principal-vs-real cube-root branch bug (iter 71). cases = [(1.0, -6.0, 11.0, -6.0), (1.0, -4.0, 5.0, -2.0), (1.0, 0.0, 0.0, -1.0), (-2.0, 0.0, 3.0, 1.5), (-1.5, 0.0, 1.5, -0.75), (1.0, 0.0, -7.0, 6.0)] a = np.array([x[0] for x in cases]); b = np.array([x[1] for x in cases]) c = np.array([x[2] for x in cases]); d = np.array([x[3] for x in cases]) f = np.asarray(fn(a, b, c, d)) # (2, n, 3): [real, imag] ref = f[0] + 1j * f[1] got = np.asarray(cubic_solve(*[jnp.asarray(v) for v in (a, b, c, d)])) # gfortran's complex **(1/3) branch cut orders the conjugate pair / real root differently than this port # for D>0; both return the same correct root SET, so compare the sorted real parts (what the consumers use). err = np.max(np.abs(np.sort(np.real(got), axis=-1) - np.sort(np.real(ref), axis=-1))) # ~1e-9 near the [1,-4,5,-2] double root (1,1,2) is Cardano's intrinsic ill-conditioning, shared by both # implementations; the residual check below is the strict correctness guard. > assert err < 1e-8, f"f2py cubic sorted-real mismatch {err:.2e}" E AssertionError: f2py cubic sorted-real mismatch 6.73e-01 E assert np.float64(0.6732766293498132) < 1e-08 clubb_jax/pytests/auto_llm_generated_pytests/test_calc_roots.py:117: AssertionError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_calc_wp3_on_wp20.203ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[1.00000000e-07 1.02987828e+00 1.10726481e+00 1.12355285e+00 1.00000000e-07 1.89830554e+00 2.02300436e+00 9.89957370e-01 1.00000000e-07 3.69004827e-01 1.55282523e-01 2.55058902e+00 1.00000000e-07 2.93630481e+00 2.48102638e+00 2.35565436e+00 1.00000000e-07 6.22397055e-01 2.54961191e+00 1.29754119e+00 1.00000000e-07 3.66934968e-01 5.59090322e-01 1.49185401e+00 1.00000000e-07 1.61961763e+00 3.20729548e-01 2.59857162e+00 1.00000000e-07 1.31902931e+00 1.76058974e+00] [1.00000000e-07 1.25422069e+00 2.66090478e+00 1.36246169e+00 1.00000000e-07 2.91147041e+00 8.28021811e-01 2.68438108e+00 1.00000000e-07 9.36191848e-01 2.64387945e+00 1.96583695e-01 1.00000000e-07 2.48332008e+00 2.68415505e+00 1.79365827e-01 1.00000000e-07 2.32548333e+00 1.31060658e+00 1.60389446e-02 1.00000000e-07 2.39932904e+00 2.92087746e+00 4.52077322e-01 1.00000000e-07 2.52409764e+00 2.75518190e-01 8.22884278e-01 1.00000000e-07 1.25508666e+00 1.62824751e+00]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_f2py_oracle(): try: clubb_f2py, jgr, ng, nzm = _setup_f2py_grid() except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_wp3_on_wp2 oracle: SKIP ({type(e).__name__})") nzt = nzm - 1 zm2zt = lambda a: np.asarray(clubb_f2py.f2py_zm2zt_2d(nzt, a)) zt2zm = lambda a: np.asarray(clubb_f2py.f2py_zt2zm_2d(nzm, a)) rng = np.random.default_rng(6) wm = wz = 0.0 for _ in range(15): wp2 = rng.uniform(1e-4, 3.0, (ng, nzm)) wp3 = rng.uniform(-5.0, 5.0, (ng, nzt)) # occasionally force the clip to fire (tiny wp2 → |ratio| > 1000) if _ % 3 == 0: wp2[:, ::4] = 1e-7 > jm, jz = calc_wp3_on_wp2(jnp.asarray(wp2), jnp.asarray(wp3), jgr) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[1.00000000e-07 1.02987828e+00 1.10726481e+00 1.12355285e+00 E 1.00000000e-07 1.89830554e+00 2.02300436e+00 9.89957370e-01 E 1.00000000e-07 3.69004827e-01 1.55282523e-01 2.55058902e+00 E 1.00000000e-07 2.93630481e+00 2.48102638e+00 2.35565436e+00 E 1.00000000e-07 6.22397055e-01 2.54961191e+00 1.29754119e+00 E 1.00000000e-07 3.66934968e-01 5.59090322e-01 1.49185401e+00 E 1.00000000e-07 1.61961763e+00 3.20729548e-01 2.59857162e+00 E 1.00000000e-07 1.31902931e+00 1.76058974e+00] E [1.00000000e-07 1.25422069e+00 2.66090478e+00 1.36246169e+00 E 1.00000000e-07 2.91147041e+00 8.28021811e-01 2.68438108e+00 E 1.00000000e-07 9.36191848e-01 2.64387945e+00 1.96583695e-01 E 1.00000000e-07 2.48332008e+00 2.68415505e+00 1.79365827e-01 E 1.00000000e-07 2.32548333e+00 1.31060658e+00 1.60389446e-02 E 1.00000000e-07 2.39932904e+00 2.92087746e+00 4.52077322e-01 E 1.00000000e-07 2.52409764e+00 2.75518190e-01 8.22884278e-01 E 1.00000000e-07 1.25508666e+00 1.62824751e+00]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_calc_wp3_on_wp2.py:72: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_wp4_pdf0.3040test_closed_formfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_wp4_pdf3.9230test_monte_carlo_central_momentfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_wp4_pdf0.2680test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_wpxpyp_pdf0.3360test_closed_formfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_wpxpyp_pdf2.4460test_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_wpxpyp_pdf0.3030test_grad_finitefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_calc_xprcp_component0.001TypeError: calc_xprcp_component() missing 1 required positional argument: 'iiPDF_type'def test_six_covariance_formulas(): k = _KW > wprcp, wp2rcp, rtprcp, thlprcp, uprcp, vprcp = (float(x) for x in calc_xprcp_component(**k)) ^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: calc_xprcp_component() missing 1 required positional argument: 'iiPDF_type' clubb_jax/pytests/auto_llm_generated_pytests/test_calc_xprcp_component.py:42: TypeError4test_six_covariance_formulasfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_calc_xprcp_component0.0TypeError: calc_xprcp_component() missing 1 required positional argument: 'iiPDF_type'def test_cthl_zero_safe(): k = dict(_KW); k['cthl_i'] = 0.0; k['cloud_frac_i'] = 0.0 # rsatl=0 limit, masked by cloud_frac=0 > out = [float(x) for x in calc_xprcp_component(**k)] ^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: calc_xprcp_component() missing 1 required positional argument: 'iiPDF_type' clubb_jax/pytests/auto_llm_generated_pytests/test_calc_xprcp_component.py:66: TypeError4test_cthl_zero_safefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_calc_xprcp_component0.004TypeError: calc_xprcp_component() missing 1 required positional argument: 'iiPDF_type' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_grad_finite(): k = dict(_KW) > g = jax.grad(lambda rc: calc_xprcp_component(**{**k, 'rc_i': rc})[2])(k['rc_i']) # d(rtprcp)/d(rc_i) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_calc_xprcp_component.py:73: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ rc = GradTracer(primal=5e-05, typeof(tangent)=f64[]) > g = jax.grad(lambda rc: calc_xprcp_component(**{**k, 'rc_i': rc})[2])(k['rc_i']) # d(rtprcp)/d(rc_i) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: calc_xprcp_component() missing 1 required positional argument: 'iiPDF_type' E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_calc_xprcp_component.py:73: TypeError4test_grad_finitefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_xpthvp_terms0.7830test_assembly_and_regridfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calc_xpthvp_terms1.3820test_grad_finitefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_calculate_thvm0.002ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[283.85710608 294.97833587 298.04495073 280.86067025 284.43778254 307.84633069 282.11261728 283.89321848] [308.4498536 298.65650778 291.06979371 295.34170065 299.88528858 288.25926447 284.13904219 303.64118784]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calculate_thvm oracle: SKIP ({type(e).__name__})") worst = 0.0 for seed in (11, 22, 33): thlm, rtm, rcm, exner, thv_ds_zt = _inputs(seed) ref = np.asarray(clubb_f2py.f2py_calculate_thvm(thlm, rtm, rcm, exner, thv_ds_zt)) > got = np.asarray(calculate_thvm(thlm, rtm, rcm, exner, thv_ds_zt)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[283.85710608 294.97833587 298.04495073 280.86067025 284.43778254 E 307.84633069 282.11261728 283.89321848] E [308.4498536 298.65650778 291.06979371 295.34170065 299.88528858 E 288.25926447 284.13904219 303.64118784]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_calculate_thvm.py:55: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_calculate_thvm0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[304.15008771 304.23822369 295.45976683 288.5740414 281.61792107 291.50106642 292.25419616 281.35825582] [281.46273132 309.97528345 299.57107335 287.03530605 293.04842657 309.2255858 306.93032824 305.32693113]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_closed_form(): thlm, rtm, rcm, exner, thv_ds_zt = _inputs(5) > got = np.asarray(calculate_thvm(thlm, rtm, rcm, exner, thv_ds_zt)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[304.15008771 304.23822369 295.45976683 288.5740414 281.61792107 E 291.50106642 292.25419616 281.35825582] E [281.46273132 309.97528345 299.57107335 287.03530605 293.04842657 E 309.2255858 306.93032824 305.32693113]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_calculate_thvm.py:63: ValueError4test_closed_formfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_calculate_thvm0.071ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[298.752864 306.91641403 303.27057071 286.7562157 289.00498855 306.20660336 280.15795914 304.63685255] [303.91208286 294.03804859 289.0909728 288.35276836 287.64608763 293.35228918 295.13644777 296.60492056]]. The error was: TypeError: unhashable type: 'numpy.ndarray' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): thlm, rtm, rcm, exner, thv_ds_zt = _inputs(7) def loss(rcm_v): return jnp.sum(calculate_thvm(thlm, rtm, rcm_v, exner, thv_ds_zt) ** 2) > g = np.asarray(jax.grad(loss)(jnp.asarray(rcm))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_calculate_thvm.py:76: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ rcm_v = GradTracer(primal=[[1.17940255e-05 1.92402144e-04 6.92032121e-04 2.00606724e-04 3.69536311e-04 3.73424205e-06 8.3004....09790810e-04 8.47150246e-04 6.39717167e-04 7.41770947e-04 9.14956051e-05 5.41143821e-04]], typeof(tangent)=f64[2,8]) def loss(rcm_v): > return jnp.sum(calculate_thvm(thlm, rtm, rcm_v, exner, thv_ds_zt) ** 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[298.752864 306.91641403 303.27057071 286.7562157 289.00498855 E 306.20660336 280.15795914 304.63685255] E [303.91208286 294.03804859 289.0909728 288.35276836 287.64608763 E 293.35228918 295.13644777 296.60492056]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_calculate_thvm.py:75: ValueError4test_differentiablefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_calculate_w_responder_params1.515AssertionError: calculate_w_params f2py mismatch 7.31e+00 assert np.float64(7.308563841211619) < 1e-12def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calculate_w/responder_params oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(13) worst_w = worst_r = 0.0 for _ in range(4): sh = (NG, NZ) wm = rng.uniform(-1, 1, sh); wp2 = rng.uniform(0.05, 2, sh) Skw = rng.uniform(-2, 2, sh) F_w = rng.uniform(0.05, 0.95, sh); zeta_w = rng.uniform(0.0, 3.0, sh) fw = clubb_f2py.f2py_calculate_w_params(wm, wp2, Skw, F_w, zeta_w) gw = calculate_w_params(wm, wp2, Skw, F_w, zeta_w) for fi, gi in zip(fw, gw): worst_w = max(worst_w, np.max(np.abs(np.asarray(gi) - np.asarray(fi)))) # Responder: use the setter's mixt_frac, a nonzero covariance, and a responder variable. mixt_frac = np.asarray(fw[4]) xm = rng.uniform(285, 305, sh); xp2 = rng.uniform(0.05, 1, sh) Skx = rng.uniform(-2, 2, sh); wpxp = rng.uniform(-0.5, 0.5, sh) fr = clubb_f2py.f2py_calculate_responder_params(xm, xp2, Skx, wpxp, wp2, F_w, mixt_frac) gr = calculate_responder_params(xm, xp2, Skx, wpxp, wp2, F_w, mixt_frac) for fi, gi in zip(fr, gr): worst_r = max(worst_r, np.max(np.abs(np.asarray(gi) - np.asarray(fi)))) > assert worst_w < 1e-12, f"calculate_w_params f2py mismatch {worst_w:.2e}" E AssertionError: calculate_w_params f2py mismatch 7.31e+00 E assert np.float64(7.308563841211619) < 1e-12 clubb_jax/pytests/auto_llm_generated_pytests/test_calculate_w_responder_params.py:60: AssertionError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_calculate_w_responder_params0.0040test_responder_zero_cov_gaussianfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calculate_w_responder_params2.0030test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calendar0.5730test_jdn_anchors_and_roundtripfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calendar0.7610test_compute_current_date_api_matches_referencefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calendar0.5260test_gregorian2julian_dayfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_calendar0.2970test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cholesky_corr_mtx_approx5.6030test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cholesky_corr_mtx_approx0.0420test_reconstructionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cholesky_corr_mtx_approx3.1430test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cholesky_factor3.3850test_reconstructionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cholesky_factor0.8590test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cholesky_factor1.5190test_non_pd_fallbackfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cholesky_factor2.1340test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_clip_covar0.190test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_clip_covar0.390test_clip_covars_denom_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_clip_covar0.0020test_realizabilityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_clip_covar0.4740test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_clip_skewness0.206ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[-1.09037342e+01 1.01028979e-01 -1.87254490e+01 3.02883406e-01 5.86407281e-01 2.27365704e+00 -1.35075253e+01 5.65041352e-01 -4.80154497e+00 -1.29496344e-02 -6.40626569e+00 2.08277752e+00 9.16194160e-01 3.75137369e+00 -1.93030128e+01 -2.97701648e+00 -1.84998448e+01 -4.74273551e+00 -7.58656305e-02 -8.53612174e+00 4.55882694e+00 -5.24979872e-01 8.25667341e-03 2.69321299e-01 7.17671160e+00 1.44870802e+00 -6.75406478e+00 -1.50397145e+01 1.94439847e+00 -9.62630972e-01 4.50866980e+00 2.52388646e-01 -4.96706389e+00 4.94164953e+00 -2.19590136e+00 -8.75542652e+00 -3.37330799e+00] [-2.16745622e+00 6.30271798e+00 1.62730784e+00 8.52814015e+00 4.06005116e+00 -2.15736186e+00 -3.15265138e+00 1.89074950e-02 1.51065893e+00 -7.28524120e-01 2.16375278e+00 1.31793907e+01 -1.80028112e+00 7.23342637e+00 7.27825508e-02 1.00696651e+00 2.38759728e+00 -5.13366391e-01 -2.79264621e+00 4.40369482e+00 4.67499096e+00 1.44736479e+01 -1.95571243e+00 2.22153529e+00 1.14729853e+01 -1.70729923e+01 3.44050497e+00 -3.47531936e+00 1.45604642e+01 -5.47048677e-01 5.44986212e+00 -1.00011428e+01 1.41238389e+00 1.90486796e+00 7.16131038e-01 6.57402152e+00 7.59694400e+00]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py clip_skewness oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape nzt = nzm - 1 clubb_api.init_err_info(ng) cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) rng = np.random.default_rng(4) zt = np.asarray(jgr.zt) sfc_elevation = np.zeros(ng) skw_max = np.full(ng, _SKW_MAX) wp2_zt = rng.uniform(0.05, 2.0, (ng, nzt)) # wp3 large enough at many levels to trigger the skewness clip. wp3 = rng.uniform(-8.0, 8.0, (ng, nzt)) * wp2_zt ** 1.5 worst = 0.0 for l_smth in (True, False): ref = np.asarray(clubb_f2py.f2py_clip_skewness( 60.0, sfc_elevation, skw_max, np.asfortranarray(wp2_zt), l_smth, np.asfortranarray(wp3.copy()))) > got = np.asarray(clip_skewness_core(wp3, wp2_zt, zt, sfc_elevation, skw_max, l_smth)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[-1.09037342e+01 1.01028979e-01 -1.87254490e+01 3.02883406e-01 E 5.86407281e-01 2.27365704e+00 -1.35075253e+01 5.65041352e-01 E -4.80154497e+00 -1.29496344e-02 -6.40626569e+00 2.08277752e+00 E 9.16194160e-01 3.75137369e+00 -1.93030128e+01 -2.97701648e+00 E -1.84998448e+01 -4.74273551e+00 -7.58656305e-02 -8.53612174e+00 E 4.55882694e+00 -5.24979872e-01 8.25667341e-03 2.69321299e-01 E 7.17671160e+00 1.44870802e+00 -6.75406478e+00 -1.50397145e+01 E 1.94439847e+00 -9.62630972e-01 4.50866980e+00 2.52388646e-01 E -4.96706389e+00 4.94164953e+00 -2.19590136e+00 -8.75542652e+00 E -3.37330799e+00] E [-2.16745622e+00 6.30271798e+00 1.62730784e+00 8.52814015e+00 E 4.06005116e+00 -2.15736186e+00 -3.15265138e+00 1.89074950e-02 E 1.51065893e+00 -7.28524120e-01 2.16375278e+00 1.31793907e+01 E -1.80028112e+00 7.23342637e+00 7.27825508e-02 1.00696651e+00 E 2.38759728e+00 -5.13366391e-01 -2.79264621e+00 4.40369482e+00 E 4.67499096e+00 1.44736479e+01 -1.95571243e+00 2.22153529e+00 E 1.14729853e+01 -1.70729923e+01 3.44050497e+00 -3.47531936e+00 E 1.45604642e+01 -5.47048677e-01 5.44986212e+00 -1.00011428e+01 E 1.41238389e+00 1.90486796e+00 7.16131038e-01 6.57402152e+00 E 7.59694400e+00]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_clip_skewness.py:68: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_clip_skewness0.003ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ -1.94911252 0.27473437 -3.45876419 0.85180364 -8.28394316 6.69079985 8.5064924 4.89674194 8.80066671 -1.35903604 0.31690971 11.07791434 0.23805576 -0.36552982 -0.83274419 0.99023125 -0.46216295 2.53957869 17.49653128 -3.3559234 10.74841935 -0.89442824 -2.03271238 3.96819695 9.7030458 -5.73831843 1.21133062 -3.70044391 -1.10993906 -2.88643504 -8.29687983 2.58204724 -2.90504615 7.37709286 -0.5910096 -7.15586172 3.78341072] [ 3.68774519 -12.17739732 5.17247798 -3.524426 2.89044913 -0.55534366 18.31825707 1.72347778 14.36255816 0.32761269 -0.33911837 -7.58645624 5.33973779 0.22518609 7.65726885 10.1196649 -19.96406763 -1.07922932 0.38416512 -14.92742176 0.20759829 3.50293677 -2.19470786 2.57844755 -5.73842907 10.98618018 9.39537493 7.84646377 -1.28579295 -0.85993353 -6.2092601 15.46902334 15.96274788 1.81991143 4.96885912 -10.08636937 6.06079618]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_skewness_limit(): jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzt = jgr.zm.shape[1] - 1 zt = np.asarray(jgr.zt) rng = np.random.default_rng(6) wp2_zt = rng.uniform(0.1, 2.0, (_NG, nzt)) wp3 = rng.uniform(-8.0, 8.0, (_NG, nzt)) * wp2_zt ** 1.5 > got = np.asarray(clip_skewness_core(wp3, wp2_zt, zt, np.zeros(_NG), np.full(_NG, _SKW_MAX), True)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ -1.94911252 0.27473437 -3.45876419 0.85180364 -8.28394316 E 6.69079985 8.5064924 4.89674194 8.80066671 -1.35903604 E 0.31690971 11.07791434 0.23805576 -0.36552982 -0.83274419 E 0.99023125 -0.46216295 2.53957869 17.49653128 -3.3559234 E 10.74841935 -0.89442824 -2.03271238 3.96819695 9.7030458 E -5.73831843 1.21133062 -3.70044391 -1.10993906 -2.88643504 E -8.29687983 2.58204724 -2.90504615 7.37709286 -0.5910096 E -7.15586172 3.78341072] E [ 3.68774519 -12.17739732 5.17247798 -3.524426 2.89044913 E -0.55534366 18.31825707 1.72347778 14.36255816 0.32761269 E -0.33911837 -7.58645624 5.33973779 0.22518609 7.65726885 E 10.1196649 -19.96406763 -1.07922932 0.38416512 -14.92742176 E 0.20759829 3.50293677 -2.19470786 2.57844755 -5.73842907 E 10.98618018 9.39537493 7.84646377 -1.28579295 -0.85993353 E -6.2092601 15.46902334 15.96274788 1.81991143 4.96885912 E -10.08636937 6.06079618]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_clip_skewness.py:83: ValueError4test_skewness_limitfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_clip_skewness0.073ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jax._src.interpreters.ad.LinearizeTracer'>, GradTracer(primal=[[-2.38387866 -2.01508857 3.14225741 -4.08084058 1.00100526 2.28560527 -3.12098927 -4.44853373 -2.25030632 1.57433015 0.62265663 -3.49937737 -0.67369209 1.69297299 -0.77215327 1.33184399 4.67435952 1.83064822 -1.08375167 -3.1274743 -1.54039334 0.11065974 3.9120941 2.75563942 -1.81853399 4.24216897 -0.29090115 1.93758842 -3.92792692 -3.95456442 -2.98092552 3.84449674 1.79811461 3.49236324 1.44436269 -0.93457602 0.16578194]], typeof(tangent)=f64[1,37]). The error was: TypeError: unhashable type: 'LinearizeTracer' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): jgr = setup_grid(ngrdcol=1, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzt = jgr.zm.shape[1] - 1 zt = np.asarray(jgr.zt)[:1] wp2_zt = np.random.default_rng(1).uniform(0.1, 2.0, (1, nzt)) def loss(wp3): return jnp.sum(clip_skewness_core(wp3, wp2_zt, zt, np.zeros(1), np.full(1, _SKW_MAX), True) ** 2) > g = np.asarray(jax.grad(loss)(jnp.asarray(np.random.default_rng(2).uniform(-5, 5, (1, nzt))))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_clip_skewness.py:98: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ wp3 = GradTracer(primal=[[-2.38387866 -2.01508857 3.14225741 -4.08084058 1.00100526 2.28560527 -3.12098927 -4.44853373 ...2 -2.98092552 3.84449674 1.79811461 3.49236324 1.44436269 -0.93457602 0.16578194]], typeof(tangent)=f64[1,37]) def loss(wp3): > return jnp.sum(clip_skewness_core(wp3, wp2_zt, zt, np.zeros(1), np.full(1, _SKW_MAX), True) ** 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jax._src.interpreters.ad.LinearizeTracer'>, GradTracer(primal=[[-2.38387866 -2.01508857 3.14225741 -4.08084058 1.00100526 2.28560527 E -3.12098927 -4.44853373 -2.25030632 1.57433015 0.62265663 -3.49937737 E -0.67369209 1.69297299 -0.77215327 1.33184399 4.67435952 1.83064822 E -1.08375167 -3.1274743 -1.54039334 0.11065974 3.9120941 2.75563942 E -1.81853399 4.24216897 -0.29090115 1.93758842 -3.92792692 -3.95456442 E -2.98092552 3.84449674 1.79811461 3.49236324 1.44436269 -0.93457602 E 0.16578194]], typeof(tangent)=f64[1,37]). The error was: E TypeError: unhashable type: 'LinearizeTracer' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_clip_skewness.py:97: ValueError4test_differentiablefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_clip_variance0.185TypeError: clip_variance() missing 6 required positional arguments: 'gr', 'solve_type', 'dt', 'threshold_lo', 'stats', and 'xp2'def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py clip_variance oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape clubb_api.init_err_info(ng) cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) rng = np.random.default_rng(4) # xp2 with many sub-threshold (incl. negative) values to exercise the floor. xp2 = rng.uniform(-0.5, 2.0, (ng, nzm)) threshold_lo = np.full((ng, nzm), 1e-3) ref = np.asarray(clubb_f2py.f2py_clip_variance(CLIP_RTP2, 60.0, threshold_lo, np.asfortranarray(xp2.copy()))) > got = np.asarray(clip_variance(xp2, threshold_lo)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: clip_variance() missing 6 required positional arguments: 'gr', 'solve_type', 'dt', 'threshold_lo', 'stats', and 'xp2' clubb_jax/pytests/auto_llm_generated_pytests/test_clip_variance.py:60: TypeError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_clip_variance0.0TypeError: clip_variance() missing 6 required positional arguments: 'gr', 'solve_type', 'dt', 'threshold_lo', 'stats', and 'xp2'def test_floor_and_boundary(): nzm = 9 xp2 = np.array([[-0.1, 0.5, 1e-4, 2.0, 0.0, 1.0, -0.2, 0.3, 5.0]]) thr = np.full((1, nzm), 1e-3) > got = np.asarray(clip_variance(xp2, thr)) ^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: clip_variance() missing 6 required positional arguments: 'gr', 'solve_type', 'dt', 'threshold_lo', 'stats', and 'xp2' clubb_jax/pytests/auto_llm_generated_pytests/test_clip_variance.py:70: TypeError4test_floor_and_boundaryfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_clip_variance0.069TypeError: clip_variance() missing 6 required positional arguments: 'gr', 'solve_type', 'dt', 'threshold_lo', 'stats', and 'xp2' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): xp2 = jnp.asarray(np.random.default_rng(1).uniform(-0.5, 2.0, (2, 8))) thr = jnp.full((2, 8), 1e-3) > g = np.asarray(jax.grad(lambda x: jnp.sum(clip_variance(x, thr) ** 2))(xp2)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_clip_variance.py:81: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ x = GradTracer(primal=[[ 0.77955406 1.87615924 -0.13960097 1.87162362 0.27957863 0.55831612 1.56925648 0.52299784]...8422 -0.43110222 1.38378277 0.84535828 0.32432929 1.47107176 0.25798707 0.63374472]], typeof(tangent)=f64[2,8]) > g = np.asarray(jax.grad(lambda x: jnp.sum(clip_variance(x, thr) ** 2))(xp2)) ^^^^^^^^^^^^^^^^^^^^^ E TypeError: clip_variance() missing 6 required positional arguments: 'gr', 'solve_type', 'dt', 'threshold_lo', 'stats', and 'xp2' E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_clip_variance.py:81: TypeError4test_differentiablefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_clip_variance0.017ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[-0.06664883 0.00070224 -0.06749149 -0.01956801 -0.01127056 -0.06010935 -0.05533605 -0.06197961 -0.08909073 -0.05114552] [-0.07538208 -0.07377118 -0.08115738 -0.08022582 -0.01698958 -0.05685561 -0.07389611 -0.03972791 -0.03836423 -0.03402048]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_clip_rcm_f2py(): """clip_rcm (clip_explicit.F90:clip_rcm — ensure rcm <= rtm, clipping to max(zero_threshold, rtm-eps)) vs the Fortran oracle. Previously untested. SKIPs if clubb_f2py is unbuilt. (iter 415)""" try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py clip_rcm oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(8) worst = 0.0 for _ in range(20): ng, nzt = 2, 10 rcm = rng.uniform(-0.1, 2e-3, (ng, nzt)); rtm = rng.uniform(0.0, 2e-3, (ng, nzt)) > cj = np.asarray(clip_rcm(jnp.asarray(rcm), jnp.asarray(rtm))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[-0.06664883 0.00070224 -0.06749149 -0.01956801 -0.01127056 -0.06010935 E -0.05533605 -0.06197961 -0.08909073 -0.05114552] E [-0.07538208 -0.07377118 -0.08115738 -0.08022582 -0.01698958 -0.05685561 E -0.07389611 -0.03972791 -0.03836423 -0.03402048]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_clip_variance.py:100: ValueError4test_clip_rcm_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_correlate17.3090test_vs_literal_loopfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_correlate0.0270test_random_limit_bounds_monotonicfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_correlate0.0150test_edge_branchesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_correlate0.290test_cloudfit_vs_literal_loopfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_correlate1.1790test_cloudfit_reconstruction_invariantfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_correlate1.4110test_differentiable_corefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_drop_sed2.4010test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_feedback_sfclyr2.3020test_vs_literalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_feedback_sfclyr0.9350test_physical_invariantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cloud_feedback_sfclyr1.2130test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cobra_sfclyr1.3280test_cobra_assigns_co2_heat_and_moisture_scalar_fluxesfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_coefs_semiimpl0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_coefs_wp2xp_semiimpl oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(4) worst = 0.0 n_red = 0 for trial in range(20): wp2 = rng.uniform(0.05, 2.0, (NG, NZ)); xp2 = rng.uniform(0.05, 2.0, (NG, NZ)) sgn = np.sign(rng.uniform(-1, 1, (NG, NZ))); sgn[sgn == 0] = 1.0 mf = rng.uniform(0.1, 0.9, (NG, NZ)); F_w = rng.uniform(0.05, 1.0, (NG, NZ)); F_x = rng.uniform(0.05, 1.0, (NG, NZ)) cw1 = rng.uniform(0.1, 2.0, (NG, NZ)); cw2 = rng.uniform(0.1, 2.0, (NG, NZ)) cx1 = rng.uniform(0.1, 2.0, (NG, NZ)); cx2 = rng.uniform(0.1, 2.0, (NG, NZ)) if trial % 4 == 0: # reduced branch (zero sigma products) cw1 = np.zeros((NG, NZ)); cw2 = np.zeros((NG, NZ)); n_red += 1 > fc, ft = clubb_f2py.f2py_calc_coefs_wp2xp_semiimpl(wp2, xp2, sgn, mf, F_w, F_x, cw1, cw2, cx1, cx2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_coefs_semiimpl.py:51: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_coefs_semiimpl0.706AssertionError: calc_coefs_wpxp2_semiimpl f2py mismatch 2.32e+01 assert np.float64(23.21359948303605) < 1e-11def test_wpxp2_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_coefs_wpxp2_semiimpl oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(5) worst = 0.0; n_zero = 0 for trial in range(20): wp2 = rng.uniform(0.05, 2.0, (NG, NZ)); wpxp = rng.uniform(-1, 1, (NG, NZ)) mf = rng.uniform(0.1, 0.9, (NG, NZ)); F_w = rng.uniform(0.05, 1.0, (NG, NZ)) cx1 = rng.uniform(0.1, 2.0, (NG, NZ)); cx2 = rng.uniform(0.1, 2.0, (NG, NZ)) if trial % 4 == 0: F_w = np.zeros((NG, NZ)); n_zero += 1 # F_w=0 -> 0,0 branch fc, ft = clubb_f2py.f2py_calc_coefs_wpxp2_semiimpl(wp2, wpxp, mf, F_w, cx1, cx2) gc, gt = calc_coefs_wpxp2_semiimpl(wp2, wpxp, mf, F_w, cx1, cx2) worst = max(worst, np.max(np.abs(np.asarray(gc) - np.asarray(fc))), np.max(np.abs(np.asarray(gt) - np.asarray(ft)))) > assert worst < 1e-11, f"calc_coefs_wpxp2_semiimpl f2py mismatch {worst:.2e}" E AssertionError: calc_coefs_wpxp2_semiimpl f2py mismatch 2.32e+01 E assert np.float64(23.21359948303605) < 1e-11 clubb_jax/pytests/auto_llm_generated_pytests/test_coefs_semiimpl.py:79: AssertionError4test_wpxp2_f2pyfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_coefs_semiimpl0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_wpxpyp_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_coefs_wpxpyp_semiimpl oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(6) worst = 0.0; n_red = 0 for trial in range(20): sh = (NG, NZ) wp2 = rng.uniform(0.05, 2.0, sh); xp2 = rng.uniform(0.05, 2.0, sh); yp2 = rng.uniform(0.05, 2.0, sh) wpxp = rng.uniform(-1, 1, sh); wpyp = rng.uniform(-1, 1, sh) sx = np.sign(wpxp); sx[sx == 0] = 1.0; sy = np.sign(wpyp); sy[sy == 0] = 1.0 mf = rng.uniform(0.1, 0.9, sh); F_w = rng.uniform(0.05, 1.0, sh); F_x = rng.uniform(0.05, 1.0, sh); F_y = rng.uniform(0.05, 1.0, sh) cw1 = rng.uniform(0.1, 2, sh); cw2 = rng.uniform(0.1, 2, sh) cx1 = rng.uniform(0.1, 2, sh); cx2 = rng.uniform(0.1, 2, sh) cy1 = rng.uniform(0.1, 2, sh); cy2 = rng.uniform(0.1, 2, sh) if trial % 4 == 0: cx1 = np.zeros(sh); cx2 = np.zeros(sh); n_red += 1 # reduced branch args = (wp2, xp2, yp2, wpxp, wpyp, sx, sy, mf, F_w, F_x, F_y, cw1, cw2, cx1, cx2, cy1, cy2) > fc, ft = clubb_f2py.f2py_calc_coefs_wpxpyp_semiimpl(*args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_coefs_semiimpl.py:105: ValueError4test_wpxpyp_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_coefs_semiimpl2.1970test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_comp_corr_norm1.8870test_structurefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_comp_corr_norm0.040test_assembly_rulesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_comp_corr_norm0.0360test_adg_zeros_w_corrfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_comp_corr_norm0.030test_no_w_corr_uses_prescribedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_comp_corr_norm2.2220test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_corr_ip0.1390test_x_hmfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_corr_ip0.0010test_hmx_hmyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_corr_ip0.0010test_w_hm_both_branchesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_corr_ip0.2730test_eta_product_and_gradfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_corr_ip0.0450test_w_xfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_corr_ip0.0620test_chi_etafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_precip_frac_specify1.2610test_conservation_general_branch_no_clipfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_precip_frac_specify0.0070test_conservation_upsilon_one_branchfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_precip_frac_specify0.0150test_validity_bounds_broad_sweepfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_precip_frac_specify1.9350test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_component_precip_frac_specify1.7540test_minimum_precipitation_fraction_does_not_lose_pdf_componentfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_gamma_skw0.002ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 2.65833663 0.06796532 2.85746223 -2.51498386 0.64413499 -0.74108049 1.81140724 -1.9528331 2.22981165] [ 0.2636484 2.41329048 -0.13707886 -0.41702233 1.73368031 2.904918 -0.78164524 2.81359722 2.57415833]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py compute_gamma_skw oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(4) skw_zm = rng.uniform(-3, 3, (NG, NZM)) skw_zt = rng.uniform(-3, 3, (NG, NZT)) worst = 0.0 configs = [(True, _params(0.32, 0.08, 1.2)), # varying (False, _params(0.32, 0.08, 1.2)), # constant (True, _params(0.25, 0.25, 1.0))] # degenerate coefs -> constant gamma_coef for l_gamma, params in configs: f_zm, f_zt = clubb_f2py.f2py_compute_gamma_skw(l_gamma, skw_zm, params, skw_zt) > g_zm = np.asarray(compute_gamma_Skw(skw_zm, params, l_gamma)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 2.65833663 0.06796532 2.85746223 -2.51498386 0.64413499 -0.74108049 E 1.81140724 -1.9528331 2.22981165] E [ 0.2636484 2.41329048 -0.13707886 -0.41702233 1.73368031 2.904918 E -0.78164524 2.81359722 2.57415833]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_compute_gamma_skw.py:62: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_gamma_skw0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 0. 1. -2.]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_closed_form(): gc, gb, gcf = 0.32, 0.08, 1.2 params = _params(gc, gb, gcf)[:1] # single column to match skw's ngrdcol=1 skw = np.array([[0.0, 1.0, -2.0]]) > got = np.asarray(compute_gamma_Skw(skw, params, True)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 0. 1. -2.]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_compute_gamma_skw.py:73: ValueError4test_closed_formfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_gamma_skw0.061ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jax._src.interpreters.ad.LinearizeTracer'>, GradTracer(primal=[[ 0.07092975 2.70278218 -2.13504232 2.69189668 -1.12901129 -0.46004131 1.96621556 -0.54480518 0.29756213] [-2.83464532 1.52107865 0.22885988 -1.0216097 1.73057222 -1.18083102 -0.27901266 -2.19574982 -0.58132208]], typeof(tangent)=f64[2,9]). The error was: TypeError: unhashable type: 'LinearizeTracer' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): params = _params(0.32, 0.08, 1.2) def loss(skw): return jnp.sum(compute_gamma_Skw(skw, params, True) ** 2) > g = np.asarray(jax.grad(loss)(jnp.asarray(np.random.default_rng(1).uniform(-3, 3, (NG, NZM))))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_compute_gamma_skw.py:85: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ skw = GradTracer(primal=[[ 0.07092975 2.70278218 -2.13504232 2.69189668 -1.12901129 -0.46004131 1.96621556 -0.54480518 ...7865 0.22885988 -1.0216097 1.73057222 -1.18083102 -0.27901266 -2.19574982 -0.58132208]], typeof(tangent)=f64[2,9]) def loss(skw): > return jnp.sum(compute_gamma_Skw(skw, params, True) ** 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jax._src.interpreters.ad.LinearizeTracer'>, GradTracer(primal=[[ 0.07092975 2.70278218 -2.13504232 2.69189668 -1.12901129 -0.46004131 E 1.96621556 -0.54480518 0.29756213] E [-2.83464532 1.52107865 0.22885988 -1.0216097 1.73057222 -1.18083102 E -0.27901266 -2.19574982 -0.58132208]], typeof(tangent)=f64[2,9]). The error was: E TypeError: unhashable type: 'LinearizeTracer' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_compute_gamma_skw.py:84: ValueError4test_differentiablefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_compute_rtp2_from_chi0.6270test_compute_rtp2_from_chi_vs_referencefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_compute_rtp2_from_chi1.9640test_compute_rtp2_from_chi_gradfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_sigma_sqd_w0.19ValueError: clubb_f2py.clubb_f2py.f2py_compute_sigma_sqd_w: failed to create array from the 2nd argument `wp2` -- 0-th dimension must be fixed to 1 but got 2def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py compute_sigma_sqd_w oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape nzt = nzm - 1 clubb_api.init_err_info(ng) cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) f = _fields(nzm, 5) order = ('gamma_Skw_fnc', 'wp2', 'thlp2', 'rtp2', 'up2', 'vp2', 'wpthlp', 'wprtp', 'upwp', 'vpwp') worst = 0.0 for l_pred in (False, True): > ref = np.asarray(clubb_f2py.f2py_compute_sigma_sqd_w( nzt, *[np.asfortranarray(f[k]) for k in order], l_pred)) E ValueError: clubb_f2py.clubb_f2py.f2py_compute_sigma_sqd_w: failed to create array from the 2nd argument `wp2` -- 0-th dimension must be fixed to 1 but got 2 clubb_jax/pytests/auto_llm_generated_pytests/test_compute_sigma_sqd_w.py:70: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_sigma_sqd_w0.003ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.28752864 0.36916414 0.33270571 0.16756216 0.19004989 0.36206603 0.10157959 0.34636853 0.33912083 0.24038049 0.19090973 0.18352768 0.17646088 0.23352289 0.25136448 0.26604921 0.39865009 0.33779858 0.28665377 0.39668804 0.16459261 0.14806361 0.28376188 0.1131826 0.11070408 0.25446665 0.23986181 0.37515033 0.28876788 0.25423529 0.24906203] [0.17425448 0.10353821 0.15772064 0.30760964 0.16018202 0.21086089 0.10112027 0.34901432 0.14633832 0.18027979 0.36409965 0.25293724 0.35414507 0.29191515 0.32253128 0.12744868 0.26234315 0.25233167 0.36140181 0.20837922 0.27945522 0.11777549 0.21628954 0.1969109 0.14505992 0.34490143 0.21383385 0.39362437 0.27699751 0.28151688 0.29139897]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_bounds(): jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = jgr.zm.shape[1] f = _fields(nzm, 7) order = ('gamma_Skw_fnc', 'wp2', 'thlp2', 'rtp2', 'up2', 'vp2', 'wpthlp', 'wprtp', 'upwp', 'vpwp') > s = np.asarray(compute_sigma_sqd_w(*[f[k] for k in order], True, jgr)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.28752864 0.36916414 0.33270571 0.16756216 0.19004989 0.36206603 E 0.10157959 0.34636853 0.33912083 0.24038049 0.19090973 0.18352768 E 0.17646088 0.23352289 0.25136448 0.26604921 0.39865009 0.33779858 E 0.28665377 0.39668804 0.16459261 0.14806361 0.28376188 0.1131826 E 0.11070408 0.25446665 0.23986181 0.37515033 0.28876788 0.25423529 E 0.24906203] E [0.17425448 0.10353821 0.15772064 0.30760964 0.16018202 0.21086089 E 0.10112027 0.34901432 0.14633832 0.18027979 0.36409965 0.25293724 E 0.35414507 0.29191515 0.32253128 0.12744868 0.26234315 0.25233167 E 0.36140181 0.20837922 0.27945522 0.11777549 0.21628954 0.1969109 E 0.14505992 0.34490143 0.21383385 0.39362437 0.27699751 0.28151688 E 0.29139897]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_compute_sigma_sqd_w.py:83: ValueError4test_boundsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_sigma_sqd_w0.054ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.36107476 0.18604516 0.28094445 0.33326022 0.31482239 0.37461404 0.35811809 0.37547129 0.10797632 0.2311744 0.2454833 0.11954626 0.10168782 0.34918643 0.39499067 0.33538296 0.19468105 0.31160011 0.18975432 0.32222454 0.18392417 0.33477727 0.39632222 0.39587156 0.36485877 0.37384302 0.31246207 0.26634906 0.37697146 0.12691923 0.21103946]]. The error was: TypeError: unhashable type: 'numpy.ndarray' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): jgr = setup_grid(ngrdcol=1, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = jgr.zm.shape[1] global _NG saved = _NG; _NG = 1 try: f = _fields(nzm, 9) order = ('gamma_Skw_fnc', 'wp2', 'thlp2', 'rtp2', 'up2', 'vp2', 'wpthlp', 'wprtp', 'upwp', 'vpwp') def loss(wpthlp): ff = dict(f); ff['wpthlp'] = wpthlp return jnp.sum(compute_sigma_sqd_w(*[ff[k] for k in order], True, jgr) ** 2) > g = np.asarray(jax.grad(loss)(jnp.asarray(f['wpthlp']))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_compute_sigma_sqd_w.py:101: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ wpthlp = GradTracer(primal=[[-0.0823953 0.06430779 0.26990302 0.20396877 -0.08204958 0.4383344 0.48180162 0.35123097 -...6 0.18814697 -0.09385239 -0.33021589 0.30629132 -0.41984701 0.24821026 -0.19028652]], typeof(tangent)=f64[1,31]) def loss(wpthlp): ff = dict(f); ff['wpthlp'] = wpthlp > return jnp.sum(compute_sigma_sqd_w(*[ff[k] for k in order], True, jgr) ** 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.36107476 0.18604516 0.28094445 0.33326022 0.31482239 0.37461404 E 0.35811809 0.37547129 0.10797632 0.2311744 0.2454833 0.11954626 E 0.10168782 0.34918643 0.39499067 0.33538296 0.19468105 0.31160011 E 0.18975432 0.32222454 0.18392417 0.33477727 0.39632222 0.39587156 E 0.36485877 0.37384302 0.31246207 0.26634906 0.37697146 0.12691923 E 0.21103946]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_compute_sigma_sqd_w.py:100: ValueError4test_differentiablefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_uv_tndcy0.058ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [9.64799869e-05 1.16111763e-04]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_matches_f90_sign_convention(): rng = np.random.default_rng(543) fcor, ug, vg, um, vm, um_f, vm_f = _inputs(rng) > um_t, vm_t = compute_uv_tndcy(jnp.asarray(fcor), jnp.asarray(ug), jnp.asarray(vg), jnp.asarray(um), jnp.asarray(vm), jnp.asarray(um_f), jnp.asarray(vm_f)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [9.64799869e-05 1.16111763e-04]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_compute_uv_tndcy.py:50: ValueError4test_matches_f90_sign_conventionfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_uv_tndcy0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [0.00011251 0.00013972]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_geostrophic_balance(): """With wind == geostrophic wind and zero forcing, the Coriolis+geostrophic tendency must vanish exactly.""" rng = np.random.default_rng(7) fcor = rng.uniform(0.5e-4, 1.5e-4, (_NG,)) ug = rng.uniform(-10.0, 10.0, (_NG, _NZT)); vg = rng.uniform(-10.0, 10.0, (_NG, _NZT)) zero = np.zeros((_NG, _NZT)) > um_t, vm_t = compute_uv_tndcy(jnp.asarray(fcor), jnp.asarray(ug), jnp.asarray(vg), jnp.asarray(ug), jnp.asarray(vg), jnp.asarray(zero), jnp.asarray(zero)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [0.00011251 0.00013972]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_compute_uv_tndcy.py:68: ValueError4test_geostrophic_balancefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_compute_uv_tndcy0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [0.0001006 0.00010651]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_forcing_additive_and_grad(): rng = np.random.default_rng(99) fcor, ug, vg, um, vm, um_f, vm_f = _inputs(rng) # Forcing enters additively: tndcy(forcing) − tndcy(0) == forcing. > a_um, a_vm = compute_uv_tndcy(jnp.asarray(fcor), jnp.asarray(ug), jnp.asarray(vg), jnp.asarray(um), jnp.asarray(vm), jnp.asarray(um_f), jnp.asarray(vm_f)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [0.0001006 0.00010651]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_compute_uv_tndcy.py:79: ValueError4test_forcing_additive_and_gradfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_compute_xp30.7840test_f2py_oracle_adg1falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_config_flags_complete0.390test_config_flags_cover_all_fortran_configurable_flagsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_config_flags_complete0.0220test_default_values_match_fortranfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_constants0.0110test_public_constant_inventory_matches_fortran_sourcefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_constants1.7370test_legacy_constants_aggregate_does_not_returnfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_constants0.0010test_constants_match_fortran_sourcefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_corr_varnce0.0040test_default_table_storagefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_corr_varnce0.0010test_set_corr_arrays_to_defaultfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_corr_varnce0.00test_kk_prescribed_correlationsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_corr_varnce0.00test_def_corr_idxfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_corr_varnce0.00test_get_corr_var_indexfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_corr_varnce0.0120test_kk_hm_metadatafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cos_solar_zen0.7630test_boundsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_cos_solar_zen8.2690test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_covar_KK_mixt_frac_linearity2.4770test_exact_mixt_frac_linearityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_covar_KK_mixt_frac_linearity0.5460test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_denorm_transform_corr1.750test_structure_and_normal_pairsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_denorm_transform_corr0.0560test_transform_entriesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_denorm_transform_corr2.9370test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diagnose_correlations0.2530test_helpersfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diagnose_correlations6.0960test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diagnose_correlations2.6030test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diagnose_correlations0.0010test_corr_array_assertion_checksfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_diagnose_upxp0.196TypeError: diagnose_upxp() missing 3 required positional arguments: 'C6x_Skw_fnc', 'tau_C6_zm', and 'C7_Skw_fnc'def test_f2py_oracle(): try: clubb_f2py, jgr, ng, nzm = _setup_f2py_grid() except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py diagnose_upxp oracle: SKIP ({type(e).__name__})") nzt = nzm - 1 ddzt = lambda a: np.asarray(clubb_f2py.f2py_ddzt_2d(nzm, a)) # zt-field → zm-field, bit-shadowed rng = np.random.default_rng(8) worst = 0.0 for _ in range(12): ypwp = rng.uniform(-0.5, 0.5, (ng, nzm)) xm = rng.uniform(280.0, 320.0, (ng, nzt)) # e.g. thlm (zt) wpxp = rng.uniform(-0.5, 0.5, (ng, nzm)) ym = rng.uniform(-15.0, 15.0, (ng, nzt)) # e.g. um (zt) C6x = rng.uniform(2.0, 6.0, (ng, nzm)) tau = rng.uniform(100.0, 900.0, (ng, nzm)) C7 = rng.uniform(0.3, 0.8, (ng, nzm)) > j = np.asarray(diagnose_upxp(jnp.asarray(ypwp), jnp.asarray(xm), jnp.asarray(wpxp), jnp.asarray(ym), jnp.asarray(C6x), jnp.asarray(tau), jnp.asarray(C7), jgr)) E TypeError: diagnose_upxp() missing 3 required positional arguments: 'C6x_Skw_fnc', 'tau_C6_zm', and 'C7_Skw_fnc' clubb_jax/pytests/auto_llm_generated_pytests/test_diagnose_upxp.py:72: TypeError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_diagnostic_cache1.2690test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability2.7920test_saturation_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability1.6460test_solver_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability1.1440test_penta_solver_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability0.820test_fill_holes_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability0.40test_pdf_cloud_frac_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability0.2160test_composabilityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability1.8750test_brunt_vaisala_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability11.8520test_kk_microphysics_drivers_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability10.7740test_kk_autoconversion_driver_array_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability2.6220test_adg1_w_closure_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability2.5320test_adg1_full_pdf_driver_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability11.0220test_mixing_length_forward_differentiablefalsePASSED5clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability5.620test_mixing_length_reverse_differentiabletruemixing_length reverse-mode gradients currently contain NaNs; forward-mode JVP remains coveredSKIPPED0clubb_jax.pytests.auto_llm_generated_pytests.test_differentiability12.0660test_kk_covar_driver_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.3870test_diffusion_zt_lhs_shapefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.3860test_diffusion_zt_lhs_boundary_zerosfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.5990test_diffusion_zt_lhs_conservationfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.2190test_diffusion_zt_lhs_valuesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.2890test_diffusion_zt_lhs_main_diag_identityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.0990test_diffusion_zm_lhs_shapefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.0920test_diffusion_zm_lhs_boundary_zerosfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.1690test_diffusion_zm_lhs_conservationfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.1480test_diffusion_zm_lhs_valuesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.1830test_diffusion_zm_lhs_main_diag_identityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.1640test_term_dp1_lhs_shapefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.0840test_term_dp1_lhs_boundary_zerosfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.090test_term_dp1_lhs_interior_valuesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.1380test_term_dp1_lhs_multi_colfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.180test_xp2_xpyp_lhs_shapefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.1380test_xp2_xpyp_lhs_boundary_conditionsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.1540test_xp2_xpyp_lhs_interior_formulafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_diffusion0.4480test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_driver_error_checks0.5710test_driver_error_checks_follow_debug_level[-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_driver_error_checks0.0070test_driver_error_checks_follow_debug_level[0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_driver_error_checks0.0060test_driver_error_checks_follow_debug_level[1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_driver_error_checks0.0060test_driver_error_checks_follow_debug_level[2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_error_code0.0010test_negative_debug_level_disables_level_zero_checksfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff1.8880test_at_threshold_is_identity_in_both_ad_modes[0.0-fill_holes_global]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff1.4830test_at_threshold_is_identity_in_both_ad_modes[0.0-fill_holes_sliding_window]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.7410test_at_threshold_is_identity_in_both_ad_modes[0.125-fill_holes_global]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.7780test_at_threshold_is_identity_in_both_ad_modes[0.125-fill_holes_sliding_window]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.530test_zero_windows_preserve_mass_and_its_derivatives[False-1-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff1.1460test_zero_windows_preserve_mass_and_its_derivatives[False-1-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.6550test_zero_windows_preserve_mass_and_its_derivatives[False--1-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.8680test_zero_windows_preserve_mass_and_its_derivatives[False--1-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.5490test_zero_windows_preserve_mass_and_its_derivatives[True-1-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.7180test_zero_windows_preserve_mass_and_its_derivatives[True-1-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.3960test_zero_windows_preserve_mass_and_its_derivatives[True--1-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.8390test_zero_windows_preserve_mass_and_its_derivatives[True--1-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.840test_active_fill_derivatives_match_finite_differences[1.0-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.8260test_active_fill_derivatives_match_finite_differences[1.0-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.390test_active_fill_derivatives_match_finite_differences[-1.0-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.7830test_active_fill_derivatives_match_finite_differences[-1.0-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.2320test_known_conservative_forward_answer[fill_holes_global]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff0.1780test_known_conservative_forward_answer[fill_holes_sliding_window]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_autodiff1.4290test_horizontal_tke_fill_inactive_division_and_active_derivativesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_global0.2290test_mass_conservation_and_no_holesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_global0.5150test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_mean0.2410test_mean_fill_raises_dry_top_and_conserves_massfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_mean0.2490test_mean_fill_noop_when_all_above_thresholdfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_mean0.2290test_thlm_fill_is_noopfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_mean0.4660test_fill_holes_vertical_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_mean0.1750test_fill_holes_wp2_from_horz_tke_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_sliding_window0.2950test_conservation_and_no_holesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_sliding_window0.0010test_no_holes_is_noopfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_fill_holes_sliding_window0.7980test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_forcing_port_structure0.0380test_complete_forcing_modules_keep_source_routine_inventory_and_orderfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_forcing_port_structure0.0120test_prescribe_forcings_keeps_supported_source_argument_orderfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_forcing_port_structure0.0120test_forcing_driver_keeps_explicit_call_and_result_orderfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_forcing_port_structure0.0040test_input_reader_keeps_source_routine_inventory_and_orderfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_forcing_port_structure0.0010test_file_functions_keeps_source_routine_inventory_and_orderfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_forcing_port_structure0.0320test_device_physics_does_not_import_numpy_or_raw_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_forcing_port_structure0.0730test_removed_duplicate_forcing_helpers_do_not_returnfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gabls3_night_stability0.1630test_gm1_gh1_unstable_regimefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gabls3_night_stability0.1230test_fm1_fh1_formulafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gabls3_night_stability0.2560test_landflx_stable_default_real_boundariesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gabls3_night_stability0.0010test_gh1_called_domainfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gabls3_night_stability0.1870test_psi_h_stablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gfdl_activation0.0010test_disabled_activation_interfaces_cannot_simulate[aer_act_clubb_quadrature_Gauss]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gfdl_activation0.00test_disabled_activation_interfaces_cannot_simulate[erff]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gfdl_activation0.00test_disabled_activation_interfaces_cannot_simulate[Loading]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_gfdl_activation0.00test_disabled_activation_interfaces_cannot_simulate[get_unit]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_grid_operators1.5650test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_grid_operators1.0970test_stretched_grid_operatorsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_grid_operators0.0310test_grid_type3_construction_matches_fortranfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_grid_operators0.00test_descending_grid_rejectedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_grid_operators0.1040test_setup_grid_is_sole_grid_constructorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_grid_operators2.1260test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_grid_operators0.0030test_grid_construction_matches_fortranfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydromet_pdf_parameter0.1590test_hydromet_pdf_params_zerofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydromet_pdf_parameter0.0430test_precip_fracs_init_and_zerofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrometeor_mixed_moments5.0270test_driver_vs_literal_loopfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrometeor_mixed_moments4.1060test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrometeor_mixed_moments0.0130test_compute_mean_binormal_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrometp2_zt0.450test_matches_f90_formulafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrometp2_zt0.0020test_safe_division_and_in_cloud_limitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrometp2_zt0.3450test_grad_finitefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrostatic6.1250test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_hydrostatic4.220test_f2py_oracle_stretchedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_ice_dfsn0.270test_thlm2T_in_K_vs_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_ice_dfsn2.7340test_ice_dfsn_vs_numpyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_ice_dfsn0.3440test_branches_and_couplingfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_ice_dfsn0.1290test_over_depletion_capfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_ice_dfsn2.8410test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_ice_dfsn2.5440test_columns_use_their_own_grid_spacing_eager_and_jitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_index_mapping0.0010test_warm_rain_only_pdffalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_index_mapping0.00test_absent_species_guardfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_index_mapping0.00test_full_speciesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_index_mapping0.0010test_sclr_idx_fields_mirror_fortran_typefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation0.00test_lin_interp_identityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation2.9210test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation0.8250test_monotonicityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation0.6210test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation0.00test_linear_interp_factorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation0.1930test_zlinterpfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation0.6260test_zlinterp_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation34.4560test_lin_interp_between_gridsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation7.9480test_plinterpfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_interpolation0.5950test_plinterp_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_inverse_hydrostatic0.780test_vs_literalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_inverse_hydrostatic1.2510test_roundtrip_with_forwardfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_inverse_hydrostatic0.6580test_constant_thvm_analyticfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_inverse_hydrostatic2.8810test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0060test_scm_main_passes_opaque_options_to_case_launch[False-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_main_passes_opaque_options_to_case_launch[False-]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_main_passes_opaque_options_to_case_launch[False-gpu,xla_prealloc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_main_passes_opaque_options_to_case_launch[False-FUTURE,option=some value]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_main_passes_opaque_options_to_case_launch[True-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_main_passes_opaque_options_to_case_launch[True-]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_main_passes_opaque_options_to_case_launch[True-gpu,xla_prealloc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_main_passes_opaque_options_to_case_launch[True-FUTURE,option=some value]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[cpu]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[gpu,xla_prealloc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[FUTURE,option=some value]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[gpu,unknown]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[literal;$NOT_EXPANDED]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_runner_forwards_value_verbatim_without_interpreting_it[gpu\n,typo]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0870test_bad_options_are_rejected_by_wrapper_before_setup[]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0710test_bad_options_are_rejected_by_wrapper_before_setup[tpu]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0710test_bad_options_are_rejected_by_wrapper_before_setup[gpu,]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0850test_bad_options_are_rejected_by_wrapper_before_setup[gpu,typo]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0990test_bad_options_are_rejected_by_wrapper_before_setup[cpu,xla_prealloc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0850test_bad_options_are_rejected_by_wrapper_before_setup[gpu,xla_prealloc,xla_prealloc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0890test_bad_options_are_rejected_by_wrapper_before_setup[gpu,,xla_prealloc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0750test_bad_options_are_rejected_by_wrapper_before_setup[gpu\n,typo]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0890test_wrapper_rejects_conflicting_or_duplicate_settings[options0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0860test_wrapper_rejects_conflicting_or_duplicate_settings[options1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0670test_wrapper_rejects_conflicting_or_duplicate_settings[options2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0680test_wrapper_rejects_preallocation_on_cpufalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_gpu_profile_resolves_to_the_host_native_backend[Darwin-metal]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_gpu_profile_resolves_to_the_host_native_backend[Linux-cuda13]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0030test_discovery_without_target_venv_uses_old_host_python[cpu-0.11.0-host_version0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0030test_discovery_without_target_venv_uses_old_host_python[cpu-0.11.0-host_version1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0020test_discovery_without_target_venv_uses_old_host_python[metal-0.4.34-host_version0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0020test_discovery_without_target_venv_uses_old_host_python[metal-0.4.34-host_version1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_discovery_plans_packages_for_target_but_executes_on_hostfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_unsuitable_setup_python_does_not_block_discoveryfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0030test_scm_rejects_duplicate_or_conflicting_implementations[options0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_rejects_duplicate_or_conflicting_implementations[options1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_rejects_duplicate_or_conflicting_implementations[options2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_scm_rejects_duplicate_or_conflicting_implementations[options3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.1490test_comparison_help_does_not_prepare_environmentfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0020test_environment_setup_uses_launcher_paths_and_restarts_once[None-cpu]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0020test_environment_setup_uses_launcher_paths_and_restarts_once[None-cuda13]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_environment_setup_uses_launcher_paths_and_restarts_once[None-metal]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0020test_environment_setup_uses_launcher_paths_and_restarts_once[custom-runtime-cpu]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0020test_environment_setup_uses_launcher_paths_and_restarts_once[custom-runtime-cuda13]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0020test_environment_setup_uses_launcher_paths_and_restarts_once[custom-runtime-metal]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jax_cli_options0.0010test_environment_setup_failure_stops_before_restartfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile1.0760test_derived_type_pytree_metadata_is_staticfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.3540test_xp2_xpyp_single_lhs_valid_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.2670test_term_tp_rhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0850test_term_dp1_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0440test_term_dp1_rhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0810test_term_pr1_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0990test_term_pr2_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.2870test_xp2_xpyp_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.6970test_xp2_xpyp_solve_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.020test_stats_finalize_xp2_xpyp_terms_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1650test_xp2_xpyp_uv_rhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1610test_xp2_xpyp_rhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.3360test_calc_xp2_xpyp_ta_terms_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.020test_pos_definite_variances_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.5020test_solve_xp2_xpyp_with_single_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.8320test_solve_xp2_xpyp_with_multiple_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.9860test_advance_xp2_xpyp_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.080test_calc_ddzt_umvm_sqd_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1090test_calc_wp3_on_wp2_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0710test_calc_stability_correction_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.2350test_calc_brunt_vaisala_freq_sqd_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.060test_calc_Ri_zm_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0950test_compute_Cx_fnc_Richardson_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1330test_Lscale_width_vert_avg_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.140test_wp23_term_splat_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0550test_smooth_min_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0610test_smooth_max_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0790test_smooth_heaviside_peskin_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0690test_calc_xpwp_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1230test_calculate_thlp2_rad_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0940test_clip_covar_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0960test_clip_skewness_core_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0660test_clip_rcm_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1310test_diffusion_zt_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1150test_diffusion_zm_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1530test_fill_holes_global_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.2050test_fill_holes_sliding_window_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.3240test_fill_holes_vertical_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1290test_fill_holes_wp2_from_horz_tke_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.2210test_term_ma_zt_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.080test_term_ma_zm_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.3630test_penta_lu_solve_single_rhs_multiple_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.4170test_penta_lu_solve_multiple_rhs_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.5170test_tridiag_lu_solve_single_rhs_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1690test_tridiag_lu_solve_single_rhs_multiple_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1860test_tridiag_lu_solve_multiple_rhs_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.2050test_xpyp_term_ta_pdf_lhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0960test_xpyp_term_ta_pdf_lhs_godunov_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.1410test_xpyp_term_ta_pdf_rhs_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_jit_compile0.0820test_xpyp_term_ta_pdf_rhs_godunov_compilesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion1.5310test_bivar_general_vs_quadraturefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion0.2870test_bivar_const_variants_vs_quadraturefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion4.4250test_kk_auto_mean_composes_and_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion0.0840test_accretion_bivar_vs_quadraturefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion0.0750test_kk_accr_mean_composes_and_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion0.1480test_trivar_general_vs_quadraturefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion0.8790test_kk_evap_mean_composes_and_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion0.0350test_bivar_LL_vs_quadraturefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_autoconversion0.3030test_kk_mvr_mean_composes_and_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_covariance_batch12.1780test_driver_matches_unbatched_integrals[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_covariance_batch12.6480test_driver_matches_unbatched_integrals[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_covariance_batch2.1580test_driver_has_one_special_function_callfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_covariance_batch23.520test_nested_jit_gradient_matches_unbatched_finite_differencefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_local_means0.4010test_formulas_and_branchesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_local_means0.8330test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_upscaled_variances0.5130test_closed_formfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_upscaled_variances0.3690test_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_kk_upscaled_variances1.0750test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_lba_sfclyr0.7140test_vs_literalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_lba_sfclyr0.0010test_diurnal_structurefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_lba_sfclyr0.9570test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_limits_f_x_responder0.0660test_sort_rootsfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_limits_f_x_responder0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_limits_f_x_responder oracle: SKIP ({type(e).__name__})") worst = 0.0 for seed in (11, 22, 33): mf, Skx, sgn = _inputs(seed) mp = np.full((NG, NZ), MAX_POS); mn = np.full((NG, NZ), MAX_NEG) > f_min, f_max = clubb_f2py.f2py_calc_limits_f_x_responder(mf, Skx, sgn, mp, mn) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_limits_f_x_responder.py:61: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_limits_f_x_responder2.2590test_boundsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_limits_f_x_responder3.940test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_liq_water_path0.1410test_liq_water_pathfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_luhar_3d_driver0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py luhar_3d_pdf_driver oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(11) order = ('wm', 'rtm', 'thlm', 'wp2', 'rtp2', 'thlp2', 'Skw', 'Skrt', 'Skthl', 'wprtp', 'wpthlp') worst = 0.0 for _ in range(4): a = _inputs(rng) > f = clubb_f2py.f2py_luhar_3d_pdf_driver(*[a[k] for k in order]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_luhar_3d_driver.py:52: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_luhar_3d_driver7.2560test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_luhar_params0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_luhar_params oracle: SKIP ({type(e).__name__})") worst = 0.0 n_const = 0 for seed in (11, 22, 33): Skx, wpxp, xp2 = _inputs(seed) if seed == 33: # force some constant-x points xp2[:, :2] = 1e-8; n_const += 1 > f = clubb_f2py.f2py_calc_luhar_params(Skx, wpxp, xp2, _X_TOL_SQD) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_luhar_params.py:56: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_luhar_params2.0190test_invariantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_luhar_params1.6230test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_ly93_pdf0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_params_ly93 oracle: SKIP ({type(e).__name__})") worst = 0.0 for seed in (11, 22, 33): xm, xp2, Skx, mf = _inputs(seed) > f = clubb_f2py.f2py_calc_params_ly93(xm, xp2, Skx, mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_ly93_pdf.py:53: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_ly93_pdf1.0170test_moment_reconstructionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_ly93_pdf0.3590test_mixt_frac_rootfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_ly93_pdf0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_driver_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py ly93_driver oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(8) worst = 0.0 for _ in range(5): wm = rng.uniform(-1, 1, (NG, NZ)); rtm = rng.uniform(0, 0.02, (NG, NZ)); thlm = rng.uniform(285, 305, (NG, NZ)) wp2 = rng.uniform(0.05, 2.0, (NG, NZ)); rtp2 = rng.uniform(1e-8, 1e-6, (NG, NZ)); thlp2 = rng.uniform(0.01, 1.0, (NG, NZ)) # Skewness spanning both the 0.75 branch (|Sk|<=0.84) and the iterative branch. Skw = rng.uniform(-3, 3, (NG, NZ)); Skrt = rng.uniform(-1, 1, (NG, NZ)); Skthl = rng.uniform(-2, 2, (NG, NZ)) > f = clubb_f2py.f2py_ly93_driver(wm, rtm, thlm, wp2, rtp2, thlp2, Skw, Skrt, Skthl) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_ly93_pdf.py:109: ValueError4test_driver_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_ly93_pdf1.3880test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_max_cubic_root2.8430test_root_property_and_maxfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_max_cubic_root0.010test_fallbacksfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_max_cubic_root4.1210test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mean_adv0.3790test_f2py_oraclefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_mean_vert_vel_up_down0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.2 0.2 0.2 0.2 0.2 0.2]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_interior_truncated_means_vs_mc(): wi, sig = 0.2, 0.5 # |wi| < 3σ (else branch), wm=0 so not too_weak var = sig ** 2 > mwd, mwu = calc_mean_w_up_down_component(_col(wi), _col(var), _col(0.0)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.2 0.2 0.2 0.2 0.2 0.2]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_mean_vert_vel_up_down.py:43: ValueError4test_interior_truncated_means_vs_mcfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_mean_vert_vel_up_down0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.1 0.1 0.1 0.1 0.1 0.1]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_branches_and_boundary(): sig = 0.3; var = sig ** 2 # too_weak: |wi|+3σ <= wm -> (0,0) > mwd, mwu = calc_mean_w_up_down_component(_col(0.1), _col(var), _col(5.0)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.1 0.1 0.1 0.1 0.1 0.1]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_mean_vert_vel_up_down.py:63: ValueError4test_branches_and_boundaryfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_mean_vert_vel_up_down0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.2 0.2 0.2 0.2 0.2 0.2]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_combine(): # NB calc_mean_w_up_down_component returns numpy (a flux-limiter RANGE diagnostic, off the grad path) — no grad test. var1, var2 = 0.25, 0.16 > mwd1, mwu1 = calc_mean_w_up_down_component(_col(0.2), _col(var1), _col(0.0)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.2 0.2 0.2 0.2 0.2 0.2]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_mean_vert_vel_up_down.py:80: ValueError4test_combinefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.0620test_namelist_cannot_override_enumerationsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths1.7290test_failed_solve_preserves_statistics[False-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.9840test_failed_solve_preserves_statistics[False-3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.1330test_failed_solve_preserves_statistics[True-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.1840test_failed_solve_preserves_statistics[True-3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths4.1010test_failed_cloud_number_solve_skips_clipping_and_final_stats[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths1.0440test_failed_cloud_number_solve_skips_clipping_and_final_stats[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.0970test_fatal_host_dump_emits_fields_in_source_orderfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths1.210test_pdf_fatal_skips_mixed_moments_and_statistics[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.5460test_pdf_fatal_skips_mixed_moments_and_statistics[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths1.3570test_failed_hydrometeor_transport_does_not_advance_cloud_number[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.950test_failed_hydrometeor_transport_does_not_advance_cloud_number[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths41.7880test_morrison_debug_output_is_live_in_jitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths1.4130test_silhs_fatal_skips_clipping_and_statistics[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_error_paths0.6780test_silhs_fatal_skips_clipping_and_statistics[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_host_errors0.3160test_fatal_column_respects_source_host_debug_guard[-1-prep]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_host_errors0.0040test_fatal_column_respects_source_host_debug_guard[-1-tendencies]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_host_errors0.0020test_fatal_column_respects_source_host_debug_guard[-1-transport]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_host_errors0.0480test_fatal_column_respects_source_host_debug_guard[0-prep]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_host_errors0.0040test_fatal_column_respects_source_host_debug_guard[0-tendencies]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_host_errors0.0040test_fatal_column_respects_source_host_debug_guard[0-transport]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0450test_species_lifecycle[none-False-False-0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0380test_species_lifecycle[khairoutdinov_kogan-False-False-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0370test_species_lifecycle[morrison-False-False-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0370test_species_lifecycle[morrison-True-False-6]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0390test_species_lifecycle[morrison-True-True-8]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0410test_disabled_dependencies_rejected[config0-SILHS]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0380test_disabled_dependencies_rejected[config1-Unsupported]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0380test_disabled_dependencies_rejected[config2-Unsupported]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0380test_disabled_dependencies_rejected[config3-GFDL]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0350test_disabled_dependencies_rejected[config4-sedimentation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0360test_disabled_dependencies_rejected[config5-l_predict_Nc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0370test_disabled_dependencies_rejected[config6-l_morr_xp2_mc]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration98.2520test_morrison_species_interface_eager_and_jit[2-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration92.530test_morrison_species_interface_eager_and_jit[6-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration91.1120test_morrison_species_interface_eager_and_jit[8-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.4090test_previous_tendencies_feed_next_core_stepfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration2.9720test_cloud_sedimentation_closed_boundaries_conserve_column[1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration3.0790test_cloud_sedimentation_closed_boundaries_conserve_column[3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration1.0290test_kk_adjustment_limits_depletion_and_conserves_waterfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration2.0270test_scheme_startup_returns_zero_tendencies_before_startfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration4.2530test_hydrometeor_transport_surface_loss_and_column_independence[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration4.1860test_hydrometeor_transport_surface_loss_and_column_independence[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.4610test_parameter_override_does_not_reuse_previous_jit_constantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration4.6840test_predicted_cloud_number_transport_and_clipping[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration4.5640test_predicted_cloud_number_transport_and_clipping[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration3.6270test_local_kk_direct_statistics_and_core_contract[1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration4.2430test_local_kk_direct_statistics_and_core_contract[3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration2.3620test_morrison_silhs_feedback_boundary_and_velocity_statistics[False-interactive]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration2.4130test_morrison_silhs_feedback_boundary_and_velocity_statistics[False-non-interactive]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.8510test_morrison_silhs_feedback_boundary_and_velocity_statistics[True-interactive]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.8550test_morrison_silhs_feedback_boundary_and_velocity_statistics[True-non-interactive]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.1120test_silhs_prescribed_probabilities_and_flags_reset_between_cases[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.10test_silhs_prescribed_probabilities_and_flags_reset_between_cases[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.060test_deterministic_silhs_rejects_independent_random_draws[l_lh_importance_sampling]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.0630test_deterministic_silhs_rejects_independent_random_draws[l_random_k_lh_start]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.2970test_initialization_appends_source_configuration_and_correlations[0.0-0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration2.5860test_initialization_appends_source_configuration_and_correlations[0.0-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.2860test_initialization_appends_source_configuration_and_correlations[0.25-0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_integration0.3920test_initialization_appends_source_configuration_and_correlations[0.25-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0020test_interface_file_inventoryfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0150test_source_inventory_order_and_argument_order[KK_microphys_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0210test_source_inventory_order_and_argument_order[advance_microphys_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0010test_source_inventory_order_and_argument_order[cloud_sed_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0020test_source_inventory_order_and_argument_order[coamps_microphys_driver_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0030test_source_inventory_order_and_argument_order[estimate_scm_microphys_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0010test_source_inventory_order_and_argument_order[gfdl_activation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0020test_source_inventory_order_and_argument_order[ice_dfsn_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0010test_source_inventory_order_and_argument_order[lh_microphys_driver_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0030test_source_inventory_order_and_argument_order[microphys_driver]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0050test_source_inventory_order_and_argument_order[microphys_init_cleanup]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0070test_source_inventory_order_and_argument_order[mixed_moment_PDF_integrals]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0110test_source_inventory_order_and_argument_order[morrison_microphys_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0010test_source_inventory_order_and_argument_order[parameters_microphys]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0040test_source_inventory_order_and_argument_order[pdf_hydromet_microphys_wrapper]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0030test_source_inventory_order_and_argument_order[silhs_category_variance_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0070test_returned_state_order[morrison_microphys_module-morrison_microphys_driver-expected0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0030test_returned_state_order[microphys_driver-calc_microphys_scheme_tendcies-expected1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0060test_returned_state_order[microphys_init_cleanup-init_microphys-expected2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0010test_driver_critical_order_and_no_obsolete_stepsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0020test_runtime_interface_has_no_fortran_fallbackfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0060test_scheme_statistics_inventory_and_order[KK_microphys_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0050test_scheme_statistics_inventory_and_order[morrison_microphys_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0160test_updated_shared_hydrometeor_interfaces[fill_holes-fill_holes_driver_api]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0090test_updated_shared_hydrometeor_interfaces[stats_clubb_utilities-stats_accumulate_hydromet_api]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_microphysics_port_structure0.0120test_fatal_dump_uses_actual_model_timefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mirror_lower_triangular0.7690test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mirror_lower_triangular0.2310test_invariantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mirror_lower_triangular0.7040test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals3.2420test_univar_N_closed_form_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals3.3950test_univar_L_closed_form_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals8.1390test_bivar_NL_closed_form_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals0.0550test_comp_eq_branch_selectionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals9.0460test_xp_a_hmpb_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals2.7270test_xphmp_covar_branches_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals2.4180test_hmxphmyp_covar_branches_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mixed_moment_pdf_integrals1.060test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_mixing_length0.001ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()def test_set_Lscale_max_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py set_Lscale_max oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(1) worst = 0.0 for l_impl in (0, 1): for _ in range(10): dx = rng.uniform(100.0, 5e5, 3); dy = rng.uniform(100.0, 5e5, 3) > j = np.asarray(set_Lscale_max(l_impl, dx, dy, 3)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_mixing_length.py:59: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ngrdcol = 0 l_implemented = array([255959.63018766, 475236.80179334, 72165.39039854]) host_dx = array([474329.85862391, 155984.54286004, 211720.89184139]) host_dy = 3 def set_Lscale_max( ngrdcol: int, l_implemented: bool, host_dx, host_dy, ): """Set the maximum allowable value of Lscale. Description: This subroutine sets the value of Lscale_max, which is the maximum allowable value of Lscale. For standard CLUBB, it is set to a very large value so that Lscale will not be limited. However, when CLUBB is running as part of a host model, the value of Lscale_max is dependent on the size of the host model's horizontal grid spacing. The smaller the host model's horizontal grid spacing, the smaller the value of Lscale_max. When Lscale is limited to a small value, the value of time-scale Tau is reduced, which in turn produces greater damping on CLUBB's turbulent parameters. This is the desired effect on turbulent parameters for a host model with small horizontal grid spacing, for small areas usually contain much less variation in meteorological quantities than large areas. References: None """ # Determine the maximum allowable value for Lscale (in meters). > if l_implemented: ^^^^^^^^^^^^^ E ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() clubb_jax/src/CLUBB_core/mixing_length.py:370: ValueError4test_set_Lscale_max_f2pyfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_mixing_length0.223TypeError: calc_Lscale_directly() missing 11 required positional arguments: 'rtpthlp_zt', 'pdf_params', 'em', 'thv_ds_zt', 'Lscale_max', 'lmin', 'clubb_params', 'saturation_formula', 'l_Lscale_plume_centered', 'stats', and 'err_info'def test_calc_Lscale_directly_f2py(): try: clubb_f2py, jgr, ng, nzm = _setup_f2py_grid() except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_Lscale_directly oracle: SKIP ({type(e).__name__})") nzt = nzm - 1 worst_rel = 0.0 for s in range(6): rng = np.random.default_rng(s) thlm = np.sort(rng.uniform(290.0, 330.0, (ng, nzt)), axis=1); exner = rng.uniform(0.8, 1.0, (ng, nzt)) rtm = rng.uniform(2e-3, 1.4e-2, (ng, nzt)); thvm = thlm * (1.0 + 0.6 * rtm) em = rng.uniform(1e-2, 1.0, (ng, nzm)); p = np.sort(rng.uniform(6e4, 1e5, (ng, nzt)), axis=1)[:, ::-1].copy() thv_ds = thvm.copy(); Lmax = np.full(ng, 1e5); lmin = 20.0 npar = max(imu, 100); cp = np.zeros((ng, npar)); cp[:, imu] = rng.uniform(0.4, 1.0, ng); mu = cp[:, imu] > jr = calc_Lscale_directly(jnp.asarray(thvm), jnp.asarray(thlm), jnp.asarray(rtm), jnp.asarray(em), jnp.asarray(Lmax), jnp.asarray(p), jnp.asarray(exner), jnp.asarray(thv_ds), jnp.asarray(cp), lmin, SATURATION_FLATAU, False, jgr) E TypeError: calc_Lscale_directly() missing 11 required positional arguments: 'rtpthlp_zt', 'pdf_params', 'em', 'thv_ds_zt', 'Lscale_max', 'lmin', 'clubb_params', 'saturation_formula', 'l_Lscale_plume_centered', 'stats', and 'err_info' clubb_jax/pytests/auto_llm_generated_pytests/test_mixing_length.py:97: TypeError4test_calc_Lscale_directly_f2pyfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_mixing_length0.019TypeError: diagnose_Lscale_from_tau() missing 4 required positional arguments: 'l_smooth_Heaviside_tau_wpxp', 'brunt_vaisala_freq_sqd_smth', 'Ri_zm', and 'err_info'def test_diagnose_Lscale_from_tau_f2py(): """diagnose_Lscale_from_tau (the l_diag_Lscale_from_tau path — the tau-based mixing-length / dissipation-time diagnostics) vs the Fortran oracle. This routine is GATED OFF in every validated case (no case_setup sets l_diag_Lscale_from_tau), so it is otherwise UN-exercised — this is its only validation. The JAX returns the Fortran's 19 outputs (invrs_tau_* / tau_* / Lscale[/up/down]) plus 2 extra diagnostics appended; the first 19 are compared by name-order. SKIPs if clubb_f2py / clubb_python are unbuilt. (iter 418)""" try: clubb_f2py, jgr, ng, nzm = _setup_f2py_grid() except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py diagnose_Lscale_from_tau oracle: SKIP ({type(e).__name__})") nzt = nzm - 1 cp = np.asarray(init_clubb_params(ng, filename=_TUNABLE_PARAMS)) # realistic defaults (well-conditioned tau) worst = 0.0 for s in range(4): rng = np.random.default_rng(s) upwp = rng.uniform(-0.1, 0.1, ng); vpwp = rng.uniform(-0.1, 0.1, ng) ddzt = rng.uniform(0.0, 1e-3, (ng, nzm)); isf = rng.uniform(0.0, 0.3, (ng, nzt)) em = rng.uniform(1e-2, 1.0, (ng, nzm)); sqem = np.sqrt(rng.uniform(1e-2, 1.0, (ng, nzt))) sfce = np.zeros(ng); Lmax = np.full(ng, 1e5) Ri = rng.uniform(-1.0, 5.0, (ng, nzm)); bvs = rng.uniform(-1e-3, 1e-2, (ng, nzm)) > jr = diagnose_Lscale_from_tau(jnp.asarray(upwp), jnp.asarray(vpwp), jnp.asarray(ddzt), jnp.asarray(isf), jnp.asarray(em), jnp.asarray(sqem), 0.01, 900.0, jnp.asarray(sfce), jnp.asarray(Lmax), jnp.asarray(cp), jnp.asarray(Ri), jnp.asarray(bvs), False, False, jgr) E TypeError: diagnose_Lscale_from_tau() missing 4 required positional arguments: 'l_smooth_Heaviside_tau_wpxp', 'brunt_vaisala_freq_sqd_smth', 'Ri_zm', and 'err_info' clubb_jax/pytests/auto_llm_generated_pytests/test_mixing_length.py:133: TypeError4test_diagnose_Lscale_from_tau_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_mono_flux_limiter2.3270test_bit_exactfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mono_flux_limiter2.2270test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mono_flux_limiter0.150test_full_limiter_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mono_flux_limiter0.5630test_calc_turb_adv_range_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_morrison_special1.5140test_derf1_vs_scipyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_morrison_special3.0580test_derf1_identitiesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mpace_b_lba_tndcy1.4570test_mpace_b_vs_literalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mpace_b_lba_tndcy0.1380test_mpace_b_physicalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mpace_b_lba_tndcy0.1250test_lba_tndcy_zerofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_mpace_b_lba_tndcy1.2440test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_new_pdf0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_coef_wp4_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_coef_wp4_implicit oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(3) worst = 0.0 for _ in range(20): mf = rng.uniform(0.1, 0.9, (NG, NZ)) F = rng.uniform(0.0, 1.0, (NG, NZ)) c1 = rng.uniform(0.0, 2.0, (NG, NZ)) c2 = rng.uniform(0.0, 2.0, (NG, NZ)) > ref = np.asarray(clubb_f2py.f2py_calc_coef_wp4_implicit(mf, F, c1, c2)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_new_pdf.py:51: ValueError4test_coef_wp4_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_pdf1.3960test_mixture_fractionfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_new_pdf0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_coef_wpxp2_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_coef_wpxp2_implicit oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(8) worst = 0.0 n_branchB = 0 for trial in range(30): mf = rng.uniform(0.1, 0.9, (NG, NZ)) F_w = rng.uniform(0.05, 1.0, (NG, NZ)); F_x = rng.uniform(0.05, 1.0, (NG, NZ)) wp2 = rng.uniform(0.1, 2.0, (NG, NZ)); xp2 = rng.uniform(0.1, 2.0, (NG, NZ)) wpxp = rng.uniform(-1.0, 1.0, (NG, NZ)); sgn = np.sign(wpxp); sgn[sgn == 0] = 1.0 cw1 = rng.uniform(0.1, 2.0, (NG, NZ)); cw2 = rng.uniform(0.1, 2.0, (NG, NZ)) cx1 = rng.uniform(0.1, 2.0, (NG, NZ)); cx2 = rng.uniform(0.1, 2.0, (NG, NZ)) if trial % 3 == 0: # trigger the reduced branch (zero sigma products) cw1 = np.zeros((NG, NZ)); cw2 = np.zeros((NG, NZ)); n_branchB += 1 > ref = np.asarray(clubb_f2py.f2py_calc_coef_wpxp2_implicit( wp2, xp2, wpxp, sgn, mf, F_w, F_x, cw1, cw2, cx1, cx2)) E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_new_pdf.py:107: ValueError4test_coef_wpxp2_f2pyfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_new_pdf0.604AssertionError: calc_coef_wp2xp_implicit f2py mismatch 4.09e+00 assert np.float64(4.086323442882921) < 1e-11def test_coef_wp2xp_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_coef_wp2xp_implicit oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(9) worst = 0.0 n_zero = 0 for trial in range(20): mf = rng.uniform(0.1, 0.9, (NG, NZ)) F = rng.uniform(0.05, 1.0, (NG, NZ)) wp2 = rng.uniform(0.05, 2.0, (NG, NZ)) c1 = rng.uniform(0.0, 2.0, (NG, NZ)); c2 = rng.uniform(0.0, 2.0, (NG, NZ)) if trial % 4 == 0: # exercise the F_w = 0 -> 0 branch F = np.zeros((NG, NZ)); n_zero += 1 ref = np.asarray(clubb_f2py.f2py_calc_coef_wp2xp_implicit(wp2, mf, F, c1, c2)) got = np.asarray(calc_coef_wp2xp_implicit(wp2, mf, F, c1, c2)) worst = max(worst, np.max(np.abs(got - ref))) > assert worst < 1e-11, f"calc_coef_wp2xp_implicit f2py mismatch {worst:.2e}" E AssertionError: calc_coef_wp2xp_implicit f2py mismatch 4.09e+00 E assert np.float64(4.086323442882921) < 1e-11 clubb_jax/pytests/auto_llm_generated_pytests/test_new_pdf.py:136: AssertionError4test_coef_wp2xp_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_pdf0.6360test_new_hybrid_aliasesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_pdf2.3170test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf0.5310test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf0.8510test_closed_form_and_swapfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf1.3010test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf0.8720test_setter_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf0.4420test_setter_mean_reconstructionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf1.5120test_setter_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf0.5630test_responderfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_driver_f2py(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py tsdadg_pdf_driver oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(13) worst = 0.0 ng, nz = 2, 8 for _ in range(4): wm = rng.uniform(-1, 1, (ng, nz)); rtm = rng.uniform(0, 0.02, (ng, nz)); thlm = rng.uniform(285, 305, (ng, nz)) wp2 = rng.uniform(0.05, 2, (ng, nz)); rtp2 = rng.uniform(1e-8, 1e-6, (ng, nz)); thlp2 = rng.uniform(0.01, 1, (ng, nz)) # Skewness with varying magnitudes so each of w/rt/thl is the setter at some points. Skw = rng.uniform(-3, 3, (ng, nz)); Skrt = rng.uniform(-3, 3, (ng, nz)); Skthl = rng.uniform(-3, 3, (ng, nz)) wprtp = rng.uniform(-1, 1, (ng, nz)); wpthlp = rng.uniform(-1, 1, (ng, nz)) > f = clubb_f2py.f2py_tsdadg_pdf_driver(wm, rtm, thlm, wp2, rtp2, thlp2, Skw, Skrt, Skthl, wprtp, wpthlp) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_new_tsdadg_pdf.py:173: ValueError4test_driver_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_new_tsdadg_pdf3.9720test_driver_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_no_dead_functions6.4920test_no_dead_functionsfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_no_dead_functions8.432AssertionError: Dead (never-referenced) module-level private helpers found — remove them, or if intentional add to _ALLOW in this test: clubb_jax/src/CLUBB_core/tracer_numpy.py: _asarray clubb_jax/src/CLUBB_core/tracer_numpy.py: _safe_sqrt assert not ['clubb_jax/src/CLUBB_core/tracer_numpy.py: _asarray', 'clubb_jax/src/CLUBB_core/tracer_numpy.py: _safe_sqrt']def test_no_dead_private_helpers(): dead = _dead_private_helpers() > assert not dead, ( "Dead (never-referenced) module-level private helpers found — remove them, or if intentional add to " "_ALLOW in this test:\n " + "\n ".join(sorted(dead))) E AssertionError: Dead (never-referenced) module-level private helpers found — remove them, or if intentional add to _ALLOW in this test: E clubb_jax/src/CLUBB_core/tracer_numpy.py: _asarray E clubb_jax/src/CLUBB_core/tracer_numpy.py: _safe_sqrt E assert not ['clubb_jax/src/CLUBB_core/tracer_numpy.py: _asarray', 'clubb_jax/src/CLUBB_core/tracer_numpy.py: _safe_sqrt'] clubb_jax/pytests/auto_llm_generated_pytests/test_no_dead_functions.py:117: AssertionError4test_no_dead_private_helpersfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_no_dead_imports2.29AssertionError: Dead (never-loaded) imports found — remove them, or if intentional (re-export / API-mirror / noqa) add to _ALLOW in this test: Microphys/advance_microphys_module.py: Cp SILHS/latin_hypercube_driver_module.py: define_importance_categories SILHS/silhs_api_module.py: silhs_config_flags_type SILHS/silhs_api_module.py: set_default_silhs_config_flags_api SILHS/silhs_api_module.py: initialize_silhs_config_flags_type_api SILHS/silhs_api_module.py: print_silhs_config_flags_api SILHS/silhs_api_module.py: latin_hypercube_2D_output_api SILHS/silhs_api_module.py: stats_accumulate_lh_api SILHS/silhs_api_module.py: est_kessler_microphys_api SILHS/silhs_api_module.py: lh_microphys_var_covar_driver_api assert not ['Microphys/advance_microphys_module.py: Cp', 'SILHS/latin_hypercube_driver_module.py: define_importance_categories', 'SILHS/silhs_api_module.py: silhs_config_flags_type', 'SILHS/silhs_api_module.py: set_default_silhs_config_flags_api', 'SILHS/silhs_api_module.py: initialize_silhs_config_flags_type_api', 'SILHS/silhs_api_module.py: print_silhs_config_flags_api', ...]def test_no_dead_imports(): assert os.path.isdir(_SRC), f"Required JAX source directory is missing: {_SRC}" offenders = [] for f in sorted(glob.glob(os.path.join(_SRC, "**", "*.py"), recursive=True)): base = os.path.basename(f) if base.startswith("__"): continue for name in _dead_imports(f): if (base, name) in _ALLOW: continue offenders.append(f"{f.split('/src/')[-1]}: {name}") > assert not offenders, ( "Dead (never-loaded) imports found — remove them, or if intentional (re-export / API-mirror / noqa) " "add to _ALLOW in this test:\n " + "\n ".join(offenders)) E AssertionError: Dead (never-loaded) imports found — remove them, or if intentional (re-export / API-mirror / noqa) add to _ALLOW in this test: E Microphys/advance_microphys_module.py: Cp E SILHS/latin_hypercube_driver_module.py: define_importance_categories E SILHS/silhs_api_module.py: silhs_config_flags_type E SILHS/silhs_api_module.py: set_default_silhs_config_flags_api E SILHS/silhs_api_module.py: initialize_silhs_config_flags_type_api E SILHS/silhs_api_module.py: print_silhs_config_flags_api E SILHS/silhs_api_module.py: latin_hypercube_2D_output_api E SILHS/silhs_api_module.py: stats_accumulate_lh_api E SILHS/silhs_api_module.py: est_kessler_microphys_api E SILHS/silhs_api_module.py: lh_microphys_var_covar_driver_api E assert not ['Microphys/advance_microphys_module.py: Cp', 'SILHS/latin_hypercube_driver_module.py: define_importance_categories', 'SILHS/silhs_api_module.py: silhs_config_flags_type', 'SILHS/silhs_api_module.py: set_default_silhs_config_flags_api', 'SILHS/silhs_api_module.py: initialize_silhs_config_flags_type_api', 'SILHS/silhs_api_module.py: print_silhs_config_flags_api', ...] clubb_jax/pytests/auto_llm_generated_pytests/test_no_dead_imports.py:57: AssertionError4test_no_dead_importsfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_no_dead_imports1.2840test_src_has_no_fortran_runtime_importfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_nov110.2150test_nov11_adjustment_is_jittable_and_preserves_dtypefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_numerical_check_setters0.0010test_check_negativefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_numerical_check_setters0.00test_check_nanfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_numerics_autodiff0.7150test_clipped_root_values_and_both_derivatives[float32]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_numerics_autodiff0.5450test_clipped_root_values_and_both_derivatives[float64]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_numerics_autodiff0.3620test_pdf_helpers_share_boundary_conventionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_param_names0.0010test_index_constant_self_consistencyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_param_names0.0010test_param_names_match_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_param_names0.0090test_parameter_hard_bounds_match_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_param_names0.1310test_parameter_validation_rejects_hard_bound_and_equalityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_param_names0.0270test_param_values_match_fortranfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_param_names0.1390test_calc_derived_params_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_binormal_moments0.4390test_closed_formfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_binormal_moments7.2350test_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_binormal_moments0.3760test_grad_finitefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm1.534AssertionError: base case mu_x2=1.0: rel 9.80e-08 (got 0.9937902373283141, Phi 0.9937903346742238) assert 9.795417240540295e-08 < 1e-09def test_base_case_probability_mass(): """a=b=0 → Phi(mu_x2/sigma_x2), independent of alpha/beta/the other moments.""" for mu_x2, sigma_x2 in ((0.3, 0.5), (-0.2, 0.8), (1.0, 0.4), (0.0, 1.0)): got = float(trivar_NNL_MM( mu_x1=0.5, mu_x2=mu_x2, mu_x3_n=-0.4, sigma_x1=0.6, sigma_x2=sigma_x2, sigma_x3_n=0.5, rho_x1x2=0.3, rho_x1x3_n=0.2, rho_x2x3_n=-0.1, x1_mean=0.4, x2_alpha_x3_beta_mean=1.3, alpha_exp=1.5, beta_exp=0.5, a_exp=0, b_exp=0)) ref = _phi(mu_x2 / sigma_x2) rel = abs(got - ref) / (abs(ref) + 1e-30) > assert rel < 1e-9, f"base case mu_x2={mu_x2}: rel {rel:.2e} (got {got}, Phi {ref})" E AssertionError: base case mu_x2=1.0: rel 9.80e-08 (got 0.9937902373283141, Phi 0.9937903346742238) E assert 9.795417240540295e-08 < 1e-09 clubb_jax/pytests/auto_llm_generated_pytests/test_pdf_integrals_all_mm.py:48: AssertionError4test_base_case_probability_massfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm38.5140test_general_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm13.3780test_const_x1_limit_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm11.9990test_const_x2_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm3.5420test_const_x1x2_limit_and_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm0.2230test_quadrivar_base_and_psumfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm21.2340test_quadrivar_general_complex_mcfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm30.9630test_quadrivar_const_x1falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm29.1120test_quadrivar_const_x2falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm6.5330test_quadrivar_const_x1x2falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_integrals_all_mm3.0760test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_moment_integrals0.7470test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_moment_integrals1.6440test_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_moment_integrals0.7020test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_params_init0.0950test_pdf_parameter_initfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_params_init0.0520test_implicit_coefs_terms_initfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_params_pack_roundtrip0.4110test_pack_unpack_api_roundtripfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_params_pack_roundtrip0.0010test_pdf_parameter_fields_mirror_fortran_typefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_params_pack_roundtrip0.0010test_implicit_coefs_terms_fields_mirror_fortran_typefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_utilities0.3380test_mean_stdev_L2N_bit_to_bitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_utilities1.210test_corr_NL2NN_vs_montecarlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_utilities0.9430test_corr_LL2NN_vs_montecarlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_utilities0.2850test_corr_clip_and_zero_sigmafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_utilities1.6910test_corr_NN2NL_NN2LL_calc_corr_chi_x_bit_to_bitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pdf_utilities4.4810test_corr_chi_eta_rt_thl_roundtripfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_faithful6.6440test_eager_jax_matches_fortran_replica_exactlyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_faithful0.2070test_jit_jax_matches_fortran_replica_to_fma_boundfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_solver0.4670test_shapefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_solver0.260test_diagonalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_solver0.3510test_known_5x5falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_solver0.2640test_full_penta_vs_numpy_single_colfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_solver0.2830test_multi_col_vs_numpyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_penta_solver0.2430test_vs_fortran_single_rhsfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_pos_definite0.122ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'clubb_jax.src.CLUBB_core.grid_class.Grid'>, Grid(nzm=31, nzt=30, ngrdcol=2, zm=Array([[ 0., 40., 80., 120., 160., 200., 240., 280., 320., 360., 400., 440., 480., 520., 560., 600., 640., 680., 720., 760., 800., 840., 880., 920., 960., 1000., 1040., 1080., 1120., 1160., 1200.], [ 0., 40., 80., 120., 160., 200., 240., 280., 320., 360., 400., 440., 480., 520., 560., 600., 640., 680., 720., 760., 800., 840., 880., 920., 960., 1000., 1040., 1080., 1120., 1160., 1200.]], dtype=float64), zt=Array([[ 20., 60., 100., 140., 180., 220., 260., 300., 340., 380., 420., 460., 500., 540., 580., 620., 660., 700., 740., 780., 820., 860., 900., 940., 980., 1020., 1060., 1100., 1140., 1180.], [ 20., 60., 100., 140., 180., 220., 260., 300., 340., 380., 420., 460., 500., 540., 580., 620., 660., 700., 740., 780., 820., 860., 900., 940., 980., 1020., 1060., 1100., 1140., 1180.]], dtype=float64), dzm=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.], [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.]], dtype=float64), dzt=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.], [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.]], dtype=float64), invrs_dzm=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025], [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025]], dtype=float64), invrs_dzt=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025], [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025]], dtype=float64), weights_zt2zm=Array([[[-0.5, 1.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 1.5, -0.5]], [[-0.5, 1.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 1.5, -0.5]]], dtype=float64), weights_zm2zt=Array([[[0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5]], [[0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5]]], dtype=float64), k_lb_zm=0, k_ub_zm=30, k_lb_zt=0, k_ub_zt=29, grid_dir_indx=1, grid_dir=1.0). The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_conservation(): jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) field_np1, flux_np1, field_n = _make_inputs(jgr) > field_adj, flux_lim, field_pd, flux_pd = pos_definite_adj(jgr, _DT, field_np1, flux_np1, field_n) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'clubb_jax.src.CLUBB_core.grid_class.Grid'>, Grid(nzm=31, nzt=30, ngrdcol=2, zm=Array([[ 0., 40., 80., 120., 160., 200., 240., 280., 320., E 360., 400., 440., 480., 520., 560., 600., 640., 680., E 720., 760., 800., 840., 880., 920., 960., 1000., 1040., E 1080., 1120., 1160., 1200.], E [ 0., 40., 80., 120., 160., 200., 240., 280., 320., E 360., 400., 440., 480., 520., 560., 600., 640., 680., E 720., 760., 800., 840., 880., 920., 960., 1000., 1040., E 1080., 1120., 1160., 1200.]], dtype=float64), zt=Array([[ 20., 60., 100., 140., 180., 220., 260., 300., 340., E 380., 420., 460., 500., 540., 580., 620., 660., 700., E 740., 780., 820., 860., 900., 940., 980., 1020., 1060., E 1100., 1140., 1180.], E [ 20., 60., 100., 140., 180., 220., 260., 300., 340., E 380., 420., 460., 500., 540., 580., 620., 660., 700., E 740., 780., 820., 860., 900., 940., 980., 1020., 1060., E 1100., 1140., 1180.]], dtype=float64), dzm=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40.], E [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40.]], dtype=float64), dzt=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40.], E [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40.]], dtype=float64), invrs_dzm=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025], E [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025]], dtype=float64), invrs_dzt=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025], E [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025]], dtype=float64), weights_zt2zm=Array([[[-0.5, 1.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 1.5, -0.5]], E E [[-0.5, 1.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 1.5, -0.5]]], dtype=float64), weights_zm2zt=Array([[[0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5]], E E [[0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5]]], dtype=float64), k_lb_zm=0, k_ub_zm=30, k_lb_zt=0, k_ub_zt=29, grid_dir_indx=1, grid_dir=1.0). The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_pos_definite.py:55: ValueError4test_conservationfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_pos_definite0.084ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'clubb_jax.src.CLUBB_core.grid_class.Grid'>, Grid(nzm=31, nzt=30, ngrdcol=2, zm=Array([[ 0., 40., 80., 120., 160., 200., 240., 280., 320., 360., 400., 440., 480., 520., 560., 600., 640., 680., 720., 760., 800., 840., 880., 920., 960., 1000., 1040., 1080., 1120., 1160., 1200.], [ 0., 40., 80., 120., 160., 200., 240., 280., 320., 360., 400., 440., 480., 520., 560., 600., 640., 680., 720., 760., 800., 840., 880., 920., 960., 1000., 1040., 1080., 1120., 1160., 1200.]], dtype=float64), zt=Array([[ 20., 60., 100., 140., 180., 220., 260., 300., 340., 380., 420., 460., 500., 540., 580., 620., 660., 700., 740., 780., 820., 860., 900., 940., 980., 1020., 1060., 1100., 1140., 1180.], [ 20., 60., 100., 140., 180., 220., 260., 300., 340., 380., 420., 460., 500., 540., 580., 620., 660., 700., 740., 780., 820., 860., 900., 940., 980., 1020., 1060., 1100., 1140., 1180.]], dtype=float64), dzm=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.], [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.]], dtype=float64), dzt=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.], [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.]], dtype=float64), invrs_dzm=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025], [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025]], dtype=float64), invrs_dzt=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025], [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025]], dtype=float64), weights_zt2zm=Array([[[-0.5, 1.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 1.5, -0.5]], [[-0.5, 1.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 1.5, -0.5]]], dtype=float64), weights_zm2zt=Array([[[0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5]], [[0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5]]], dtype=float64), k_lb_zm=0, k_ub_zm=30, k_lb_zt=0, k_ub_zt=29, grid_dir_indx=1, grid_dir=1.0). The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py pos_definite oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape nzt = nzm - 1 clubb_api.init_err_info(ng) cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) # Set the f2py stored_grid to EXACTLY the JAX grid's heights (grid_type=2 = explicit heights). clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) field_np1, flux_np1, field_n = _make_inputs(jgr) f_field, f_flux, f_field_pd, f_flux_pd = clubb_f2py.f2py_pos_definite_adj( _DT, field_np1.copy(), flux_np1.copy(), field_n.copy()) > j_field, j_flux, j_field_pd, j_flux_pd = pos_definite_adj(jgr, _DT, field_np1, flux_np1, field_n) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'clubb_jax.src.CLUBB_core.grid_class.Grid'>, Grid(nzm=31, nzt=30, ngrdcol=2, zm=Array([[ 0., 40., 80., 120., 160., 200., 240., 280., 320., E 360., 400., 440., 480., 520., 560., 600., 640., 680., E 720., 760., 800., 840., 880., 920., 960., 1000., 1040., E 1080., 1120., 1160., 1200.], E [ 0., 40., 80., 120., 160., 200., 240., 280., 320., E 360., 400., 440., 480., 520., 560., 600., 640., 680., E 720., 760., 800., 840., 880., 920., 960., 1000., 1040., E 1080., 1120., 1160., 1200.]], dtype=float64), zt=Array([[ 20., 60., 100., 140., 180., 220., 260., 300., 340., E 380., 420., 460., 500., 540., 580., 620., 660., 700., E 740., 780., 820., 860., 900., 940., 980., 1020., 1060., E 1100., 1140., 1180.], E [ 20., 60., 100., 140., 180., 220., 260., 300., 340., E 380., 420., 460., 500., 540., 580., 620., 660., 700., E 740., 780., 820., 860., 900., 940., 980., 1020., 1060., E 1100., 1140., 1180.]], dtype=float64), dzm=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40.], E [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40.]], dtype=float64), dzt=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40.], E [40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40.]], dtype=float64), invrs_dzm=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025], E [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025]], dtype=float64), invrs_dzt=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025], E [0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025]], dtype=float64), weights_zt2zm=Array([[[-0.5, 1.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 1.5, -0.5]], E E [[-0.5, 1.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 1.5, -0.5]]], dtype=float64), weights_zm2zt=Array([[[0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5]], E E [[0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5]]], dtype=float64), k_lb_zm=0, k_ub_zm=30, k_lb_zt=0, k_ub_zt=29, grid_dir_indx=1, grid_dir=1.0). The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_pos_definite.py:91: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_pos_definite0.077ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'clubb_jax.src.CLUBB_core.grid_class.Grid'>, Grid(nzm=31, nzt=30, ngrdcol=1, zm=Array([[ 0., 40., 80., 120., 160., 200., 240., 280., 320., 360., 400., 440., 480., 520., 560., 600., 640., 680., 720., 760., 800., 840., 880., 920., 960., 1000., 1040., 1080., 1120., 1160., 1200.]], dtype=float64), zt=Array([[ 20., 60., 100., 140., 180., 220., 260., 300., 340., 380., 420., 460., 500., 540., 580., 620., 660., 700., 740., 780., 820., 860., 900., 940., 980., 1020., 1060., 1100., 1140., 1180.]], dtype=float64), dzm=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.]], dtype=float64), dzt=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40.]], dtype=float64), invrs_dzm=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025]], dtype=float64), invrs_dzt=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025]], dtype=float64), weights_zt2zm=Array([[[-0.5, 1.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 0.5, 0.5], [ 1.5, -0.5]]], dtype=float64), weights_zm2zt=Array([[[0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5], [0.5, 0.5]]], dtype=float64), k_lb_zm=0, k_ub_zm=30, k_lb_zt=0, k_ub_zt=29, grid_dir_indx=1, grid_dir=1.0). The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): jgr = setup_grid(ngrdcol=1, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = jgr.zm.shape[1]; nzt = nzm - 1 flux = jnp.asarray(np.random.default_rng(1).standard_normal((1, nzm)) * 1e-3) field_n = jnp.asarray(np.abs(np.random.default_rng(2).standard_normal((1, nzt))) * 1e-2) def loss(field_np1): out, _, _, _ = pos_definite_adj(jgr, _DT, field_np1, flux, field_n) return jnp.sum(out ** 2) > g = np.asarray(jax.grad(loss)(field_n)) # field_np1 = field_n (no negatives) baseline ^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_pos_definite.py:110: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ field_np1 = GradTracer(primal=[[0.00189053 0.00522748 0.00413064 0.02441467 0.01799707 0.01144166 0.00325423 0.00773807 0.002812...0.00330571 0.00410504 0.01010758 0.00783181 0.02056703 0.01638443 0.01729411 0.01504831]], typeof(tangent)=f64[1,30]) def loss(field_np1): > out, _, _, _ = pos_definite_adj(jgr, _DT, field_np1, flux, field_n) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'clubb_jax.src.CLUBB_core.grid_class.Grid'>, Grid(nzm=31, nzt=30, ngrdcol=1, zm=Array([[ 0., 40., 80., 120., 160., 200., 240., 280., 320., E 360., 400., 440., 480., 520., 560., 600., 640., 680., E 720., 760., 800., 840., 880., 920., 960., 1000., 1040., E 1080., 1120., 1160., 1200.]], dtype=float64), zt=Array([[ 20., 60., 100., 140., 180., 220., 260., 300., 340., E 380., 420., 460., 500., 540., 580., 620., 660., 700., E 740., 780., 820., 860., 900., 940., 980., 1020., 1060., E 1100., 1140., 1180.]], dtype=float64), dzm=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40.]], dtype=float64), dzt=Array([[40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., E 40., 40., 40., 40.]], dtype=float64), invrs_dzm=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025]], dtype=float64), invrs_dzt=Array([[0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, E 0.025, 0.025, 0.025]], dtype=float64), weights_zt2zm=Array([[[-0.5, 1.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 0.5, 0.5], E [ 1.5, -0.5]]], dtype=float64), weights_zm2zt=Array([[[0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5], E [0.5, 0.5]]], dtype=float64), k_lb_zm=0, k_ub_zm=30, k_lb_zt=0, k_ub_zt=29, grid_dir_indx=1, grid_dir=1.0). The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_pos_definite.py:108: ValueError4test_differentiablefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_precip_fraction2.5040test_precip_frac_assert_checkfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pressure_coord_forcing0.3680test_pressure_coordinate_interpfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pressure_coord_forcing0.1840test_height_coordinate_interp_is_independent_of_pressurefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pressure_coord_forcing0.990test_apply_temperature_forcing_converts_to_thlmfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pressure_coord_forcing0.5310test_unknown_forcing_name_is_rejectedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pressure_sounding_z2.1080test_real_cgils_soundingfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pressure_sounding_z1.5760test_temperature_branch_independentfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_pressure_sounding_z1.4310test_hydrostatic_roundtripfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_pvertinterp0.178TypeError: pvertinterp() missing 3 required positional arguments: 'p_mid', 'p_out', and 'input_var'def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py pvertinterp oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape nzt = nzm - 1 clubb_api.init_err_info(ng) cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) rng = np.random.default_rng(4) p_mid = np.asfortranarray(_p_profile(nzt)) input_var = np.asfortranarray(rng.standard_normal((ng, nzt))) worst = 0.0 # An interior pressure, plus targets outside both ends (exercise the clamp branches). for p_out in (95000.0, 88000.0, 101000.0, 80000.0): ref = np.asarray(clubb_f2py.f2py_pvertinterp(p_mid.copy(), float(p_out), input_var.copy())) > got = np.asarray(pvertinterp(p_mid, p_out, input_var)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: pvertinterp() missing 3 required positional arguments: 'p_mid', 'p_out', and 'input_var' clubb_jax/pytests/auto_llm_generated_pytests/test_pvertinterp.py:67: TypeError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_pvertinterp0.001TypeError: pvertinterp() missing 3 required positional arguments: 'p_mid', 'p_out', and 'input_var'def test_pressure_weighted_identity(): nzt = 10 p_mid = np.tile(np.linspace(100000.0, 80000.0, nzt)[::-1][None, :], (1, 1)).copy() # p_mid descending in k: index 0 = 100000, index nzt-1 = 80000. p_mid = np.linspace(100000.0, 80000.0, nzt)[None, :] input_var = np.random.default_rng(2).standard_normal((1, nzt)) p_out = 91234.0 > got = float(np.asarray(pvertinterp(p_mid, p_out, input_var))[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: pvertinterp() missing 3 required positional arguments: 'p_mid', 'p_out', and 'input_var' clubb_jax/pytests/auto_llm_generated_pytests/test_pvertinterp.py:80: TypeError4test_pressure_weighted_identityfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_pvertinterp0.02TypeError: pvertinterp() missing 3 required positional arguments: 'p_mid', 'p_out', and 'input_var' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): nzt = 12 p_mid = jnp.asarray(np.linspace(100000.0, 80000.0, nzt)[None, :]) def loss(v): return jnp.sum(pvertinterp(p_mid, 90000.0, v) ** 2) > g = np.asarray(jax.grad(loss)(jnp.asarray(np.random.default_rng(1).standard_normal((1, nzt))))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_pvertinterp.py:95: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ v = GradTracer(primal=[[ 0.34558419 0.82161814 0.33043708 -1.30315723 0.90535587 0.44637457 -0.53695324 0.5811181 0.3645724 0.2941325 0.02842224 0.54671299]], typeof(tangent)=f64[1,12]) def loss(v): > return jnp.sum(pvertinterp(p_mid, 90000.0, v) ** 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: pvertinterp() missing 3 required positional arguments: 'p_mid', 'p_out', and 'input_var' E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_pvertinterp.py:94: TypeError4test_differentiablefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_quadrivar_NNLL_covar_eq_swap2.4720test_base_all_varyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_quadrivar_NNLL_covar_eq_swap0.0310test_c3_const_x3_NONswapfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_quadrivar_NNLL_covar_eq_swap0.0310test_c4_const_x3_SWAPPEDfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_quadrivar_NNLL_covar_eq_swap0.0240test_c1c2c4_cst_x1x2x3_SWAPPEDfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_quadrivar_NNLL_covar_eq_swap0.0270test_all_constfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_quadrivar_covar_const_limits3.990test_const_x3_x3x4_and_allfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_rad_extended_atmosphere1.8990test_real_cgils_extended_atmospherefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_rad_extended_atmosphere0.0010test_theta_branch_exner_conversionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module5.1660test_radiation_schedule_can_toggle_between_calls[lba]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module4.6890test_radiation_schedule_preserves_outputs_and_stats[arm-False-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.1670test_radiation_schedule_preserves_outputs_and_stats[arm-False-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module1.1450test_radiation_schedule_preserves_outputs_and_stats[arm-True-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.1460test_radiation_schedule_preserves_outputs_and_stats[arm-True-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.3060test_soil_updates_use_incoming_fluxes_on_every_step[False-arm]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.1430test_soil_updates_use_incoming_fluxes_on_every_step[True-arm]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module5.0090test_radiation_schedule_preserves_outputs_and_stats[bomex-False-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.7860test_radiation_schedule_preserves_outputs_and_stats[bomex-False-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module1.1680test_radiation_schedule_preserves_outputs_and_stats[bomex-True-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.1640test_radiation_schedule_preserves_outputs_and_stats[bomex-True-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module4.3240test_radiation_schedule_preserves_outputs_and_stats[lba-False-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module3.5510test_radiation_schedule_preserves_outputs_and_stats[lba-False-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module1.290test_radiation_schedule_preserves_outputs_and_stats[lba-True-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.3040test_radiation_schedule_preserves_outputs_and_stats[lba-True-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module5.3770test_radiation_schedule_preserves_outputs_and_stats[dycoms2_rf01-False-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module24.3860test_radiation_schedule_preserves_outputs_and_stats[dycoms2_rf01-False-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module1.5180test_radiation_schedule_preserves_outputs_and_stats[dycoms2_rf01-True-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_module0.3650test_radiation_schedule_preserves_outputs_and_stats[dycoms2_rf01-True-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_port_structure0.0060test_supported_routine_inventory_and_order_match_fortran_modulesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_port_structure0.00test_jax_only_helpers_and_boundaries_are_explicitly_documentedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_port_structure0.0040test_functional_returns_follow_fortran_inout_and_out_orderfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_port_structure0.0010test_retained_parameter_order_matches_the_supported_source_surfacefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_port_structure0.00test_active_driver_uses_only_the_canonical_radiation_modulefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_port_structure0.00test_compiled_radiation_modules_have_no_tracer_compatibility_pathfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_radiation_port_structure0.00test_conceptual_fortran_comments_are_preserved_verbatimfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_rcm_sat_adj11.1620test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_rcm_sat_adj0.120test_self_consistencyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_rcm_sat_adj0.4670test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_read_surface_var_for_bc4.1460test_interpolated_surface_values_match_column_referencefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_module5.3260test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_module1.280test_remapping_matrix_identity_and_conservationfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_module1.2430test_calc_mass_analyticfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_module2.5220test_matvec_and_gradfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_module4.1640test_remap_vals_to_target_two_gridsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_ppm8.7020test_f2py_same_grid_identityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_ppm6.5140test_mass_conservation_refinedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_remapping_ppm13.2190test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_responder_params0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_responder_params oracle: SKIP ({type(e).__name__})") worst = 0.0 n_zero = 0 for seed in (11, 22, 33): xm, xp2, Skx, sgn, F_x, mf = _inputs(seed) if seed == 33: F_x[:, :2] = 0.0; n_zero += 1 # exercise the F_x=0 single-Gaussian branch > f = clubb_f2py.f2py_calc_responder_params(xm, xp2, Skx, sgn, F_x, mf) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_responder_params.py:59: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_responder_params0.7980test_moment_reconstructionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_responder_params1.2320test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_routine_placement0.2530test_routines_live_in_their_fortran_home_filefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_routine_placement0.2220test_documented_renames_are_all_livefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_cuda13_rejects_an_old_driverfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.00test_cuda13_accepts_a_three_component_new_driver_versionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.00test_cuda13_rejects_an_old_compute_capabilityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.00test_gpu_query_retries_without_compute_capabilityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0120test_gpu_report_labels_expected_device_without_claiming_backend_readyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.00test_numeric_visible_device_resolves_to_its_nvidia_smi_uuidfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0020test_missing_environment_requires_setup_but_remains_selectablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_human_output_labels_planned_versionsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.2610test_gpu_preflight_fails_before_creating_an_environmentfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8390test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[False-None-False-false-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8430test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[False-None-False-false-FASTEST_FIRST]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8730test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[False-true-False-true-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.9130test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[False-true-False-true-FASTEST_FIRST]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8760test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[False-false-True-true-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8360test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[False-false-True-true-FASTEST_FIRST]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.890test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[True-None-False-false-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8110test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[True-None-False-false-FASTEST_FIRST]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8170test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[True-true-False-true-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.8160test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[True-true-False-true-FASTEST_FIRST]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.9260test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[True-false-True-true-None]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.90test_gpu_wrapper_resolves_physical_index_even_when_pci_order_differs[True-false-True-true-FASTEST_FIRST]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_invalid_selection_is_rejected[]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_invalid_selection_is_rejected[-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_invalid_selection_is_rejected[9]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_invalid_selection_is_rejected[GPU-missing]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_invalid_selection_is_rejected[GPU-test]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_invalid_selection_is_rejected[0,0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_invalid_selection_is_rejected[1,,0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_explicit_selection_preserves_order_and_expands_unique_prefixfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0040test_preflight_checks_exposed_gpus_only[0-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0030test_preflight_checks_exposed_gpus_only[1-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0030test_preflight_checks_exposed_gpus_only[1,0-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0020test_preflight_checks_exposed_gpus_only[-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0020test_fastest_first_without_selector_does_not_guess_defaultfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.00test_truncated_nvidia_row_returns_unavailablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0010test_metal_query_accepts_gpu_family_capabilityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_runtime_info0.0020test_metal_runtime_uses_plugin_requirementsfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_saturation1.285AssertionError: unsupported saturation_formula=2 should raise ValueErrordef test_dispatcher_matches_leaves(): """sat_vapor_press_liq routes bit-exactly to the leaf chosen by saturation_formula.""" T = jnp.linspace(220.0, 310.0, 64) for formula, leaf in ((SATURATION_FLATAU, sat_vapor_press_liq_flatau), (SATURATION_BOLTON, sat_vapor_press_liq_bolton)): d = float(jnp.max(jnp.abs(sat_vapor_press_liq(T, formula) - leaf(T)))) assert d == 0.0, f"formula {formula}: dispatcher != leaf ({d})" # The documented not-target formulas (saturation.py: gfdl/lookup) must raise — pin the SPECIFIC # constants_clubb codes (gfdl=2, lookup=4), not just a generic out-of-range value, so a future change # that silently routes them somewhere is caught (mirrors saturation.F90's gfdl/lookup leaves being unported). from clubb_jax.src.CLUBB_core.model_flags import saturation_gfdl, saturation_lookup for bad in (saturation_gfdl, saturation_lookup, 999): try: sat_vapor_press_liq(T, bad) except ValueError: pass else: > raise AssertionError(f"unsupported saturation_formula={bad} should raise ValueError") E AssertionError: unsupported saturation_formula=2 should raise ValueError clubb_jax/pytests/auto_llm_generated_pytests/test_saturation.py:54: AssertionError4test_dispatcher_matches_leavesfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_saturation1.1640test_svp_reference_valuesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_saturation2.9880test_sat_mixrat_liq_consistency_and_gradfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_saturation0.8030test_sat_mixrat_f2pyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_saturation0.0020test_saturation_formula_enum_valuesfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_set_sfc_value_of_flux_profiles0.09AttributeError: 'bool' object has no attribute 'k_lb_zm'def test_against_transcription(): gr = setup_grid(ngrdcol=2, deltaz=40.0, zm_init=0.0, zm_top=400.0, grid_type=1) ng, nzm = gr.zm.shape k_lb = int(gr.k_lb_zm) rng = np.random.default_rng(7) combos = [ dict(l_host=False, l_lin=False, sclr_dim=0, edsclr_dim=0), dict(l_host=False, l_lin=True, sclr_dim=2, edsclr_dim=3), dict(l_host=True, l_lin=False, sclr_dim=2, edsclr_dim=3), dict(l_host=True, l_lin=True, sclr_dim=0, edsclr_dim=0), dict(l_host=False, l_lin=False, sclr_dim=1, edsclr_dim=0), ] worst = 0.0 for c in combos: sclr_dim, edsclr_dim = c["sclr_dim"], c["edsclr_dim"] # random nonzero interior profiles (so interior preservation is actually exercised) prof = dict( wpthlp=rng.standard_normal((ng, nzm)), wprtp=rng.standard_normal((ng, nzm)), upwp=rng.standard_normal((ng, nzm)), vpwp=rng.standard_normal((ng, nzm)), upwp_pert=rng.standard_normal((ng, nzm)), vpwp_pert=rng.standard_normal((ng, nzm)), wpsclrp=rng.standard_normal((ng, nzm, sclr_dim)), wpedsclrp=rng.standard_normal((ng, nzm, max(edsclr_dim, 1))), ) sfc = dict( wpthlp=rng.standard_normal(ng), wprtp=rng.standard_normal(ng), upwp=rng.standard_normal(ng), vpwp=rng.standard_normal(ng), upwp_pert=rng.standard_normal(ng), vpwp_pert=rng.standard_normal(ng), wpsclrp=rng.standard_normal((ng, sclr_dim)), wpedsclrp=rng.standard_normal((ng, edsclr_dim)), ) ref = _ref(k_lb, ng, nzm, sclr_dim, edsclr_dim, c["l_host"], c["l_lin"], sfc, prof) > jout = set_sfc_value_of_flux_profiles( sclr_dim, edsclr_dim, gr, c["l_host"], c["l_lin"], sfc["wpthlp"], sfc["wprtp"], sfc["upwp"], sfc["vpwp"], sfc["upwp_pert"], sfc["vpwp_pert"], sfc["wpsclrp"], sfc["wpedsclrp"], prof["wpthlp"], prof["wprtp"], prof["upwp"], prof["vpwp"], prof["upwp_pert"], prof["vpwp_pert"], prof["wpsclrp"], prof["wpedsclrp"], ng, nzm) clubb_jax/pytests/auto_llm_generated_pytests/test_set_sfc_value_of_flux_profiles.py:84: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ nzm = 0, ngrdcol = 0 sclr_dim = Grid(nzm=11, nzt=10, ngrdcol=2, zm=Array([[ 0., 40., 80., 120., 160., 200., 240., 280., 320., 360., 400.], [...0.5], [0.5, 0.5]]], dtype=float64), k_lb_zm=0, k_ub_zm=10, k_lb_zt=0, k_ub_zt=9, grid_dir_indx=1, grid_dir=1.0) edsclr_dim = False, gr = False l_host_applies_sfc_fluxes = array([-0.37526684, -0.29992172]) l_linearize_pbl_winds = array([-1.37857468, -0.80684593]) wpthlp_sfc = array([ 1.65405755, -0.67123322]) wprtp_sfc = array([-1.05409379, 0.33732633]) upwp_sfc = array([ 1.4072722, -1.4540243]) vpwp_sfc = array([-0.20852185, -0.63205255]) upwp_sfc_pert = array([], shape=(2, 0), dtype=float64) vpwp_sfc_pert = array([], shape=(2, 0), dtype=float64) wpsclrp_sfc = array([[ 1.23015336e-03, 2.98745538e-01, -2.74137855e-01, -8.90591839e-01, -4.54670785e-01, -9.91646555e-01, ...-1.34421455e+00, -4.57615761e-01, -1.90122274e+00, -1.28953774e+00, -1.84173504e+00, -2.35091131e-01]]) wpedsclrp_sfc = array([[-1.26744648, 0.27126436, 0.15675109, -0.18693094, -2.51675971, -0.5386929 , -0.04850095, 0.11330899....0325217 , 0.88438987, -0.58360043, -0.11170195, 0.11046414, 0.06378177, -1.22505583, 0.07614023]]) wpthlp = array([[ 1.35882342, -1.54714468, 0.85938269, 0.11935403, -0.64147039, 2.00041655, 0.76225971, -1.1992889 ....43852259, -0.67566225, 0.20313861, -0.46330758, 0.12726841, -1.18719453, -0.5793016 , -0.19619597]]) wprtp = array([[ 0.89876387, 1.14522201, -1.32352779, -0.79464237, 0.64690342, -1.99241978, -0.46316986, -0.09728693....42802494, -0.30368039, 0.35258907, -0.12077045, -0.19728423, -1.11406714, -0.01152147, -0.44358122]]) upwp = array([[ 1.16612778, 0.6530885 , -0.02414361, 0.66838102, -0.33986955, 1.05212636, -0.00539956, 0.58338235....1640528 , 2.24475663, -0.83172318, -0.62394359, 0.20540395, 0.49301329, -0.17640607, -0.20593033]]) vpwp = array([[ 0.70246296, 0.51990764, -1.03367583, -0.07918132, 0.03528685, -1.05448462, 0.2598391 , -0.85795648....13140747, 0.3628398 , -2.12856704, 0.84660852, -1.74609648, 0.7567385 , -0.84549703, 0.77899108]]) upwp_pert = array([], shape=(2, 11, 0), dtype=float64) vpwp_pert = array([[[ 0.13095121], [-1.53683494], [ 1.24914875], [ 1.44170716], [-0.06580491], ...], [ 0.0133246 ], [-0.69440353], [-0.32668526], [-0.56023105], [ 0.0079591 ]]]) wpsclrp = 2, wpedsclrp = 11 def set_sfc_value_of_flux_profiles( nzm, ngrdcol, sclr_dim, edsclr_dim, gr, l_host_applies_sfc_fluxes, l_linearize_pbl_winds, wpthlp_sfc, wprtp_sfc, upwp_sfc, vpwp_sfc, upwp_sfc_pert, vpwp_sfc_pert, wpsclrp_sfc, wpedsclrp_sfc, wpthlp, wprtp, upwp, vpwp, upwp_pert, vpwp_pert, wpsclrp, wpedsclrp, ): """Set or clear the surface values of turbulent flux profiles depending on whether the host model applies surface fluxes outside CLUBB. References: None """ > k_lb = gr.k_lb_zm ^^^^^^^^^^ E AttributeError: 'bool' object has no attribute 'k_lb_zm' clubb_jax/src/CLUBB_core/advance_clubb_core_module.py:1005: AttributeError4test_against_transcriptionfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_setter_var_params0.001ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_setter_var_params oracle: SKIP ({type(e).__name__})") worst = 0.0 for seed in (11, 22, 33): xm, xp2, Skx, sgn, F_x, zeta = _inputs(seed) > f = clubb_f2py.f2py_calc_setter_var_params(xm, xp2, Skx, sgn, F_x, zeta) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_setter_var_params.py:53: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_setter_var_params0.9670test_moment_reconstructionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_setter_var_params2.2550test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_sfc_flux0.2570test_conversions_and_bulk_fluxesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_sfc_flux0.110test_ubar_and_momentumfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_sfc_flux0.2780test_ht_mostr_flux_interpfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_sfc_flux0.3040test_set_scalar_surface_fluxes_updates_surface_arrays_onlyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_sfc_flux0.2060test_shared_surface_flux_path_jits_and_stays_on_devicefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_sfc_varnce0.219ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [-0.04767757 -0.04030177]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_f2py_oracle(): try: clubb_f2py, jgr, ng, nzm = _setup_f2py_grid() except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py calc_sfc_varnce oracle: SKIP ({type(e).__name__})") nzt = nzm - 1 zm_sfc = np.asarray(jgr.zm)[:, 0]; sfce = np.zeros(ng) rng = np.random.default_rng(2) worst = 0.0 for _ in range(20): upwp = rng.uniform(-0.1, 0.1, ng); vpwp = rng.uniform(-0.1, 0.1, ng) wpthlp = rng.uniform(-0.1, 0.1, (ng, nzm)); wprtp = rng.uniform(-1e-4, 1e-4, ng) splat = rng.uniform(0.0, 1e-3, (ng, nzm)); tau = rng.uniform(100.0, 1000.0, (ng, nzm)) T0 = 300.0; up2c = np.full(ng, 2.0); ac = np.full(ng, 1.8) wp2 = rng.uniform(1e-2, 1, (ng, nzm)); up2 = rng.uniform(1e-2, 1, (ng, nzm)); vp2 = rng.uniform(1e-2, 1, (ng, nzm)) thlp2 = rng.uniform(1e-3, 1, (ng, nzm)); rtp2 = rng.uniform(1e-7, 1e-5, (ng, nzm)) rtpthlp = rng.uniform(-1e-3, 1e-3, (ng, nzm)) > jr = calc_sfc_varnce(jnp.asarray(upwp), jnp.asarray(vpwp), jnp.asarray(wpthlp), jnp.asarray(wprtp), jnp.asarray(splat), jnp.asarray(tau), T0, jnp.asarray(up2c), jnp.asarray(ac), jnp.asarray(wp2), jnp.asarray(up2), jnp.asarray(vp2), jnp.asarray(thlp2), jnp.asarray(rtp2), jnp.asarray(rtpthlp), jnp.asarray(zm_sfc), jnp.asarray(sfce)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [-0.04767757 -0.04030177]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_sfc_varnce.py:67: ValueError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.2510test_impossible_weight_transfer_reports_fatal_status[-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.0010test_impossible_weight_transfer_reports_fatal_status[0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.0010test_impossible_weight_transfer_reports_fatal_status[2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.5510test_weight_limiter_error_reaches_importance_driverfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.4560test_kessler_invalid_fraction_is_local_to_column[-0.125-mixture]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.0980test_kessler_invalid_fraction_is_local_to_column[-0.125-cloud1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.0970test_kessler_invalid_fraction_is_local_to_column[-0.125-cloud2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.0930test_kessler_invalid_fraction_is_local_to_column[1.125-mixture]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.0920test_kessler_invalid_fraction_is_local_to_column[1.125-cloud1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.110test_kessler_invalid_fraction_is_local_to_column[1.125-cloud2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_diagnostics0.4670test_kessler_empty_sample_reports_source_stopfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_driver1.1350test_subtimestep_statistics_preserve_previous_window_and_count_oncefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_fortran_oracle1.0870test_inverse_normal_matches_source_literal_precisionfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0010test_silhs_inventory_excludes_mt95falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0030test_silhs_source_routine_and_argument_order[est_kessler_microphys_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0020test_silhs_source_routine_and_argument_order[generate_uniform_sample_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0010test_silhs_source_routine_and_argument_order[latin_hypercube_arrays]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.010test_silhs_source_routine_and_argument_order[latin_hypercube_driver_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0010test_silhs_source_routine_and_argument_order[lh_microphys_var_covar_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0010test_silhs_source_routine_and_argument_order[math_utilities]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0010test_silhs_source_routine_and_argument_order[parameters_silhs]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0010test_silhs_source_routine_and_argument_order[silhs_api_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0080test_silhs_source_routine_and_argument_order[silhs_importance_sample_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_port_structure0.0030test_silhs_source_routine_and_argument_order[transform_to_pdf_module]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling2.9580test_stratification_reproducibility_and_sequence_reusefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.2910test_deterministic_strata_cycle_and_sequence_reuse[1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.2930test_deterministic_strata_cycle_and_sequence_reuse[3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.3630test_deterministic_overlap_pool_is_independent_of_seedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling2.7440test_category_probabilities_weights_and_empty_clusters[fractions0-False-eight_cluster_allocation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling1.6430test_category_probabilities_weights_and_empty_clusters[fractions0-False-four_cluster_no_precip]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling1.5380test_category_probabilities_weights_and_empty_clusters[fractions0-False-two_cluster_cp_nocp]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.3270test_category_probabilities_weights_and_empty_clusters[fractions0-True-eight_cluster_allocation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.1160test_category_probabilities_weights_and_empty_clusters[fractions0-True-four_cluster_no_precip]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.1170test_category_probabilities_weights_and_empty_clusters[fractions0-True-two_cluster_cp_nocp]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0150test_category_probabilities_weights_and_empty_clusters[fractions1-False-eight_cluster_allocation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.010test_category_probabilities_weights_and_empty_clusters[fractions1-False-four_cluster_no_precip]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0080test_category_probabilities_weights_and_empty_clusters[fractions1-False-two_cluster_cp_nocp]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0140test_category_probabilities_weights_and_empty_clusters[fractions1-True-eight_cluster_allocation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.010test_category_probabilities_weights_and_empty_clusters[fractions1-True-four_cluster_no_precip]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.010test_category_probabilities_weights_and_empty_clusters[fractions1-True-two_cluster_cp_nocp]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0140test_category_probabilities_weights_and_empty_clusters[fractions2-False-eight_cluster_allocation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0090test_category_probabilities_weights_and_empty_clusters[fractions2-False-four_cluster_no_precip]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0070test_category_probabilities_weights_and_empty_clusters[fractions2-False-two_cluster_cp_nocp]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0140test_category_probabilities_weights_and_empty_clusters[fractions2-True-eight_cluster_allocation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.010test_category_probabilities_weights_and_empty_clusters[fractions2-True-four_cluster_no_precip]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.010test_category_probabilities_weights_and_empty_clusters[fractions2-True-two_cluster_cp_nocp]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling1.1520test_importance_samples_membership_and_weighted_estimate[False-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.5970test_importance_samples_membership_and_weighted_estimate[False-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.4540test_importance_samples_membership_and_weighted_estimate[False-3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.6930test_importance_samples_membership_and_weighted_estimate[True-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.5980test_importance_samples_membership_and_weighted_estimate[True-2]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.5730test_importance_samples_membership_and_weighted_estimate[True-3]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling2.1770test_inverse_normal_and_cholesky_referencefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.2490test_vertical_overlap_matches_scalar_recurrence_and_maximum_overlapfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.4390test_microphysical_variance_sources_include_optional_dt_terms[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.1940test_microphysical_variance_sources_include_optional_dt_terms[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.1760test_category_rms_uses_weighted_second_moment_and_real_probabilityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling2.7570test_uniform_driver_options_and_shared_permutation_state[False-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling1.050test_uniform_driver_options_and_shared_permutation_state[False-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.5390test_uniform_driver_options_and_shared_permutation_state[True-False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0660test_uniform_driver_options_and_shared_permutation_state[True-True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0010test_old_cloud_weighted_sample_count_check_precedes_dispatch[False]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.0010test_old_cloud_weighted_sample_count_check_precedes_dispatch[True]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.1740test_invalid_category_draw_is_reported_in_jitfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.6870test_random_starting_level_bounds_and_no_cloud_fallback[1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_sampling0.3930test_random_starting_level_bounds_and_no_cloud_fallback[-1]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_surface_schemes0.8060test_mpace_b_sfclyrfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_surface_schemes1.0120test_arm_97_sfclyrfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_surface_schemes0.850test_twp_ice_equals_cloud_feedbackfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_surface_schemes0.0990test_arm_3year_arm_0003_equal_arm_97falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_silhs_surface_schemes0.9350test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_simple_rad0.6440test_simple_rad_cleanfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_simple_rad0.2480test_simple_rad_above_cloudfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_simple_rad0.1720test_simple_rad_bomexfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_simple_rad_lba0.5980test_table_loadfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_simple_rad_lba0.380test_time_interp_vs_literalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_simple_rad_lba0.5550test_full_radht_vs_literalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_simple_rad_lba0.5680test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_skx_func0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[1.88611221 1.02265511 1.95248741 0.16167205 1.21471166 0.75297317] [1.60380241 0.34905563 1.74327055 1.0878828 1.80443016 0.95430705]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_f2py_oracle(): try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py Skx_func oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(4) params = _params() worst = 0.0 for _ in range(10): xp2 = rng.uniform(0.0, 2.0, (NG, NZ)) xp3 = rng.uniform(-1.0, 1.0, (NG, NZ)) ref = np.asarray(clubb_f2py.f2py_skx_func(xp2, xp3, _X_TOL, params)) > got = np.asarray(Skx_func(xp2, xp3, _X_TOL, params)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[1.88611221 1.02265511 1.95248741 0.16167205 1.21471166 0.75297317] E [1.60380241 0.34905563 1.74327055 1.0878828 1.80443016 0.95430705]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_skx_func.py:59: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_skx_func0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.5 1. ]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_closed_form(): params = _params() xp2 = np.array([[0.5, 1.0]]); xp3 = np.array([[0.2, -0.3]]) > got = np.asarray(Skx_func(xp2, xp3, _X_TOL, params)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[0.5 1. ]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_skx_func.py:68: ValueError4test_closed_formfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_skx_func0.054ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[1.07246109 1.90588102 0.37390326 1.90243395 0.69247976 0.90432025] [1.67263493 0.87747836 1.14422801 0.15236232 1.53167491 1.1224723 ]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): params = _params() xp2 = jnp.asarray(np.random.default_rng(1).uniform(0.1, 2.0, (NG, NZ))) def loss(xp3): return jnp.sum(Skx_func(xp2, xp3, _X_TOL, params) ** 2) > g = np.asarray(jax.grad(loss)(jnp.asarray(np.random.default_rng(2).uniform(-1, 1, (NG, NZ))))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ clubb_jax/pytests/auto_llm_generated_pytests/test_skx_func.py:83: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ xp3 = GradTracer(primal=[[-0.47677573 -0.40301771 0.62845148 -0.81616812 0.20020105 0.45712105] [-0.62419785 -0.88970675 -0.45006126 0.31486603 0.12453133 -0.69987547]], typeof(tangent)=f64[2,6]) def loss(xp3): > return jnp.sum(Skx_func(xp2, xp3, _X_TOL, params) ** 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[1.07246109 1.90588102 0.37390326 1.90243395 0.69247976 0.90432025] E [1.67263493 0.87747836 1.14422801 0.15236232 1.53167491 1.1224723 ]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_skx_func.py:82: ValueError4test_differentiablefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_skx_func0.028ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[-1.43032719 -1.20905314 1.88535444 -2.44850435 0.60060316 1.37136316] [-1.87259356 -2.66912024 -1.35018379 0.94459809 0.37359398 -2.09962642]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_LG_2005_ansatz_f2py(): """LG_2005_ansatz (Skx_module.F90 — the Larson-Golaz 2005 skewness ansatz: Skx from Skw/wpxp/wp2/xp2/sigma_sqd_w/ beta) and its <x'^3> wrapper xp3_LG_2005_ansatz vs the f2py oracle. Both previously untested. The ansatz's clip carries a ~1e-11 relative FP difference; checked with a relative tolerance. (iter 422)""" try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py LG_2005_ansatz oracle: SKIP ({type(e).__name__})") from clubb_jax.src.CLUBB_core.Skx_module import LG_2005_ansatz, xp3_LG_2005_ansatz from clubb_jax.src.CLUBB_core.parameter_indices import ibeta params = _params(); params[:, ibeta - 1] = 2.0 # f2py xp3 extracts beta from clubb_params; JAX takes it explicitly beta = np.ascontiguousarray(params[:, ibeta - 1]) rng = np.random.default_rng(2) w_lg = w_xp3 = 0.0 for _ in range(30): Skw = rng.uniform(-3, 3, (NG, NZ)); wpxp = rng.uniform(-1, 1, (NG, NZ)) wp2 = rng.uniform(1e-2, 2, (NG, NZ)); xp2 = rng.uniform(1e-4, 1, (NG, NZ)); ssw = rng.uniform(0, 0.6, (NG, NZ)) > jl = np.asarray(LG_2005_ansatz(jnp.asarray(Skw), jnp.asarray(wpxp), jnp.asarray(wp2), jnp.asarray(xp2), jnp.asarray(ssw), jnp.asarray(beta)[:, None], _X_TOL)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[-1.43032719 -1.20905314 1.88535444 -2.44850435 0.60060316 1.37136316] E [-1.87259356 -2.66912024 -1.35018379 0.94459809 0.37359398 -2.09962642]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_skx_func.py:107: ValueError4test_LG_2005_ansatz_f2pyfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_smooth_heaviside0.01ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 1.59500198e+00 4.07791901e-02 1.71447734e+00 -1.50899031e+00 3.86480995e-01 -4.44648296e-01 1.08684435e+00 -1.17169986e+00 1.33788699e+00 1.58189043e-01 1.44797429e+00 -8.22473142e-02 -2.50213400e-01 1.04020818e+00 1.74295080e+00 -4.68987146e-01 1.68815833e+00 1.54449500e+00 -1.16030669e+00 3.91865821e-01] [ 7.37513084e-01 1.59409324e+00 5.96366701e-01 -1.31977528e+00 -7.67664437e-03 -2.29685978e-02 8.14281655e-04 1.65089623e+00 -5.40225361e-01 -9.94423872e-01 7.95132080e-02 5.08215326e-01 1.58078539e+00 2.95256882e-01 -8.35799795e-01 1.54718890e+00 -2.97889754e-02 6.32883114e-01 -8.62599223e-02 -1.01887190e+00]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_f2py_is_truncated_constants(): """The f2py oracle == the truncated-constant closed form (1e-16); the full-pi JAX differs only by the documented constant-precision improvement (~1e-10).""" try: import clubb_f2py except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py smooth_heaviside oracle: SKIP ({type(e).__name__})") rng = np.random.default_rng(4) worst_trunc = 0.0 worst_jax = 0.0 for smth_range in (0.6, 1.0, 0.25): x = rng.uniform(-3 * smth_range, 3 * smth_range, (2, 20)) ref = np.asarray(clubb_f2py.f2py_smooth_heaviside_peskin(np.asfortranarray(x), smth_range)) worst_trunc = max(worst_trunc, np.max(np.abs(_trunc_ref(x, smth_range) - ref))) > worst_jax = max(worst_jax, np.max(np.abs(np.asarray(smooth_heaviside_peskin(x, smth_range)) - ref))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 1.59500198e+00 4.07791901e-02 1.71447734e+00 -1.50899031e+00 E 3.86480995e-01 -4.44648296e-01 1.08684435e+00 -1.17169986e+00 E 1.33788699e+00 1.58189043e-01 1.44797429e+00 -8.22473142e-02 E -2.50213400e-01 1.04020818e+00 1.74295080e+00 -4.68987146e-01 E 1.68815833e+00 1.54449500e+00 -1.16030669e+00 3.91865821e-01] E [ 7.37513084e-01 1.59409324e+00 5.96366701e-01 -1.31977528e+00 E -7.67664437e-03 -2.29685978e-02 8.14281655e-04 1.65089623e+00 E -5.40225361e-01 -9.94423872e-01 7.95132080e-02 5.08215326e-01 E 1.58078539e+00 2.95256882e-01 -8.35799795e-01 1.54718890e+00 E -2.97889754e-02 6.32883114e-01 -8.62599223e-02 -1.01887190e+00]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_smooth_heaviside.py:61: ValueError4test_f2py_is_truncated_constantsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_smooth_heaviside0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [-0.9 -0.855 -0.81 -0.765 -0.72 -0.675 -0.63 -0.585 -0.54 -0.495 -0.45 -0.405 -0.36 -0.315 -0.27 -0.225 -0.18 -0.135 -0.09 -0.045 0. 0.045 0.09 0.135 0.18 0.225 0.27 0.315 0.36 0.405 0.45 0.495 0.54 0.585 0.63 0.675 0.72 0.765 0.81 0.855 0.9 ]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_full_pi_closed_form_and_endpoints(): r = 0.6 x = np.linspace(-1.5 * r, 1.5 * r, 41) > got = np.asarray(smooth_heaviside_peskin(x, r)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [-0.9 -0.855 -0.81 -0.765 -0.72 -0.675 -0.63 -0.585 -0.54 -0.495 E -0.45 -0.405 -0.36 -0.315 -0.27 -0.225 -0.18 -0.135 -0.09 -0.045 E 0. 0.045 0.09 0.135 0.18 0.225 0.27 0.315 0.36 0.405 E 0.45 0.495 0.54 0.585 0.63 0.675 0.72 0.765 0.81 0.855 E 0.9 ]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_smooth_heaviside.py:72: ValueError4test_full_pi_closed_form_and_endpointsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_smooth_heaviside0.065ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jax._src.interpreters.ad.LinearizeTracer'>, GradTracer(primal=[-0.5 -0.4 -0.3 -0.2 -0.1 0. 0.1 0.2 0.3 0.4 0.5], typeof(tangent)=f64[11]). The error was: TypeError: unhashable type: 'LinearizeTracer' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_differentiable(): r = 0.6 > g = np.asarray(jax.grad(lambda x: jnp.sum(smooth_heaviside_peskin(x, r) ** 2))( jnp.asarray(np.linspace(-0.5, 0.5, 11)))) clubb_jax/pytests/auto_llm_generated_pytests/test_smooth_heaviside.py:84: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ x = GradTracer(primal=[-0.5 -0.4 -0.3 -0.2 -0.1 0. 0.1 0.2 0.3 0.4 0.5], typeof(tangent)=f64[11]) > g = np.asarray(jax.grad(lambda x: jnp.sum(smooth_heaviside_peskin(x, r) ** 2))( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ jnp.asarray(np.linspace(-0.5, 0.5, 11)))) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jax._src.interpreters.ad.LinearizeTracer'>, GradTracer(primal=[-0.5 -0.4 -0.3 -0.2 -0.1 0. 0.1 0.2 0.3 0.4 0.5], typeof(tangent)=f64[11]). The error was: E TypeError: unhashable type: 'LinearizeTracer' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_smooth_heaviside.py:84: ValueError4test_differentiablefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_soil_vegetation0.2390test_soil_veg_vs_fortran_replicafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_soil_vegetation0.4220test_soil_veg_init_and_integrationfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_soil_vegetation0.7690test_soil_veg_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_solver0.3750test_solver_shapefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_solver0.2080test_solver_diagonalfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_solver0.1730test_solver_known_3x3falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_solver0.2020test_solver_vs_numpy_single_colfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_solver0.2840test_solver_vs_numpy_multi_colfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_solver0.2620test_solver_residualfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_solver0.2070test_solver_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_spec_hum_to_mixing_ratio0.0010test_conversionsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_splatting_autodiff0.8110test_clipped_frequency_has_zero_forward_and_reverse_derivatives[-0.0004-0.0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_splatting_autodiff0.3570test_clipped_frequency_has_zero_forward_and_reverse_derivatives[-0.0004-0.25]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_splatting_autodiff0.3810test_clipped_frequency_has_zero_forward_and_reverse_derivatives[0.0-0.0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_splatting_autodiff0.420test_clipped_frequency_has_zero_forward_and_reverse_derivatives[0.0-0.25]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_splatting_autodiff5.4870test_mixed_columns_preserve_values_and_coefficient_sensitivity[0.0]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_splatting_autodiff0.5050test_mixed_columns_preserve_values_and_coefficient_sensitivity[0.25]falsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_sponge_damp_xp230.182ValueError: too many axes: 2 (effrank=2), expected rank=1def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py sponge_damp_xp2/xp3 oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape nzt = nzm - 1 clubb_api.init_err_info(ng) cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) zm = np.asarray(jgr.zm); zt = np.asarray(jgr.zt) rng = np.random.default_rng(4) xp2 = rng.uniform(0.01, 2.0, (ng, nzm)); xp3 = rng.uniform(-1, 1, (ng, nzt)) tau_zm = np.full((ng, nzm), _TAU); tau_zt = np.full((ng, nzt), _TAU) xtol_col = np.full(ng, _XTOLSQ); depth_col = np.full(ng, _DEPTH) # f2py wants rank-1 (ngrdcol) xtol_j = xtol_col[:, None]; depth_j = depth_col[:, None] # JAX broadcasts (ng,1) > f2 = np.asarray(clubb_f2py.f2py_sponge_damp_xp2(_DT, zm, xp2, xtol_col, tau_zm, depth_col)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_sponge_damp_xp23.py:67: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_sponge_damp_xp230.324ValueError: too many axes: 2 (effrank=2), expected rank=1def test_sponge_damp_xm_f2py(): """sponge_damp_xm (sponge_layer_damping.F90) — implicit nudge of the mean xm toward xm_ref in the top sponge. The JAX relies on tau=inf below the sponge (from initialize_tau_sponge_damp) for the no-op rather than a geometric gate, so build that tau profile and pass it to both sides; this also exercises initialize_tau_sponge_damp (no own f2py wrapper). SKIPs if clubb_f2py/clubb_python are unbuilt. (iter 439)""" try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py sponge_damp_xm oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape; nzt = nzm - 1 clubb_api.init_err_info(ng); cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) zt = np.asarray(jgr.zt); zm = np.asarray(jgr.zm); zm_top = float(jgr.zm[0, -1]) tau_min, tau_max, depth_frac = 120.0, 1800.0, 0.25 tau = np.zeros((ng, nzt)) for i in range(ng): tau[i], sld = initialize_tau_sponge_damp(zt[i], _DT, zm_top, tau_min, tau_max, depth_frac) sld = depth_frac * zm_top rng = np.random.default_rng(2) worst = 0.0; damped = False for _ in range(10): xm = rng.uniform(280.0, 320.0, (ng, nzt)); xm_ref = rng.uniform(280.0, 320.0, (ng, nzt)) j = np.asarray(sponge_damp_xm(jnp.asarray(xm), jnp.asarray(xm_ref), zt, zm_top, jnp.asarray(tau), sld, _DT)) > f = np.asarray(clubb_f2py.f2py_sponge_damp_xm(_DT, zt, zm, xm_ref, xm, tau, np.full(ng, sld))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: too many axes: 2 (effrank=2), expected rank=1 clubb_jax/pytests/auto_llm_generated_pytests/test_sponge_damp_xp23.py:110: ValueError4test_sponge_damp_xm_f2pyfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_sponge_damp_xp230.6930test_below_sponge_noopfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_sponge_damp_xp231.1940test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_spurious_source0.3110test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_spurious_source0.1540test_conservation_identityfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_spurious_source0.590test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_standalone_jax40.6150test_active_driver_runs_without_clubb_python[neutral]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_standalone_jax40.3370test_active_driver_runs_without_clubb_python[arm]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_output_time0.0010test_stats_timestamp_uses_end_of_current_model_stepfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_output_time0.00test_inlined_driver_helpers_stay_absentfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_output_time0.00test_driver_uses_canonical_microphysics_interfacesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0050test_registry_expansion_matches_source_familiesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0010test_registry_errors_are_not_silently_skipped[entry(1) = "profile | zt"-expected name | grid | units | long_name]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0010test_registry_errors_are_not_silently_skipped[entry(1) = "profile | bad_grid | K | Profile"-Invalid stats grid]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0010test_registry_errors_are_not_silently_skipped[entry(1) = "profile | zt | K | Profile-Malformed stats registry entry]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0010test_registry_errors_are_not_silently_skipped[entry(1) = " | zt | K | Profile"-name and grid must be non-empty]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0010test_single_quoted_registry_entry_is_supportedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0010test_sampling_uses_open_closed_absolute_time_windowfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer2.3840test_rank_and_selector_dispatch_updates_pointwise_countsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.1340test_budget_sequence_and_l_count_samplefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.1210test_jitted_banks_preserve_column_and_level_selectorsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0060test_jax_layout_reuses_cached_slot_mapsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0060test_rank_one_column_selector_is_bounds_checkedfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.3380test_direct_banks_accumulate_across_sampled_and_unsampled_stepsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0260test_netcdf_record_uses_end_step_timefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0110test_oversampling_is_reported_at_the_host_output_boundaryfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0010test_config_metadata_data_and_source_grid_contractfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0160test_netcdf_metadata_matches_fortran_schemafalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0020test_radiation_registry_entries_require_radiation_gridsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0320test_multiple_runtime_batches_fill_one_output_filefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer4.1480test_output_remapping_preserves_values_on_identical_gridsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_stats_writer0.0350test_silhs_sample_fields_share_the_stats_recordfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_sunray_sw0.4950test_jit_multicolfalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_sunray_sw0.316TypeError: clubb_f2py.f2py_sunray_sw() missing required argument 'zm' (pos 5)def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py sunray_sw oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape; nzt = nzm - 1 clubb_api.init_err_info(ng); cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) # Pin the parameters_radiation constants the f2py wrapper reads (fs_values/cos_solar_zen are fixed dim(20)). z20 = np.zeros(20) clubb_f2py.f2py_set_simplified_radiation_params(0.0, 0.0, 0.0, _RADIUS, _ALVDR, _GC, _OMEGA, False, True, True, 1, z20.copy(), z20.copy(), z20.copy()) dzt = np.asarray(jgr.dzt); zm = np.asarray(jgr.zm); zt = np.asarray(jgr.zt) rng = np.random.default_rng(0) worst = 0.0 for _ in range(15): rcm = rng.uniform(0.0, 1e-3, (ng, nzt)); rho = rng.uniform(0.5, 1.2, (ng, nzt)) fs0 = float(rng.uniform(100.0, 400.0)); amu0 = float(rng.uniform(0.3, 0.9)) j = np.asarray(sunray_sw(ng, nzt, rcm, rho, amu0, dzt, zm, zt, _RADIUS, _ALVDR, _GC, fs0, _OMEGA, True)) > f = np.asarray(clubb_f2py.f2py_sunray_sw(fs0, amu0, rho, rcm)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: clubb_f2py.f2py_sunray_sw() missing required argument 'zm' (pos 5) clubb_jax/pytests/auto_llm_generated_pytests/test_sunray_sw.py:81: TypeError4test_f2py_oraclefalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_time_select0.8430test_interior_triples_match_fortranfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_time_select0.1920test_interpolation_equivalent_everywherefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_time_select0.0570test_endpoints_and_out_of_rangefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_transform_pdf_chi_eta_component0.4970test_deterministic_coefficientsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_transform_pdf_chi_eta_component3.4110test_variance_combination_monte_carlofalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_transform_pdf_chi_eta_component0.8030test_corr_quotient_and_gradfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_transform_pdf_chi_eta_component0.820test_zero_component_variances_have_finite_derivativesfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq2.1620test_all_varyfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq0.0110test_all_constfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq0.010test_x1x2_constfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq0.010test_x1x3_const_uses_swapped_x1x2falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq0.0160test_x2x3_constfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq0.0120test_x1_constfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq0.010test_x2_constfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NLL_mean_eq0.0090test_x3_const_uses_swapped_x2falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq2.030test_all_vary_basefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq0.0150test_c3_const_x3falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq0.0120test_c2_const_x2falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq0.0140test_c1_const_x1falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq0.0170test_c2c3_const_x2x3falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq0.0160test_c1c3_const_x1x3falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq0.0140test_c1c2_const_x1x2falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_trivar_NNL_covar_eq0.0130test_all_const_maps_to_x2x3falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.0010test_baseline_and_supported_radiation_schemes_passfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.0010test_unsupported_active_driver_features_fail_loud[cfg0-overrides0-microphys_scheme]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg1-overrides1-l_gfdl_activation]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg2-overrides2-rad_scheme]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg3-overrides3-l_calc_thlp2_rad]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg4-overrides4-Sponge damping]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg5-overrides5-lh_microphys_type]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg6-overrides6-l_silhs_rad]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg7-overrides7-l_restart]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg8-overrides8-l_input_fields]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg9-overrides9-l_test_grid_generalization]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_unsupported_active_driver_features_fail_loud[cfg10-overrides10-grid_adapt_in_time_method]falsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.0450test_invalid_solar_date_uses_the_source_calendar_failurefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_unsupported_config_guards0.00test_supported_microphysics_and_cloud_sedimentation_pass_initial_gatefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_update_xp2_mc2.5190test_transcription_and_interpfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_update_xp2_mc0.0880test_invariantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_update_xp2_mc4.3510test_differentiablefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_validation_checks0.0010test_assert_corr_symmetric_behaviorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_validation_checks0.0010test_assert_corr_symmetric_f2py_nocrashfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_validation_checks0.00test_sfc_varnce_check_behaviorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_validation_checks0.00test_length_check_behaviorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_validation_checks0.1180test_pdf_closure_check_behaviorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_validation_checks0.0010test_rad_check_behaviorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_validation_checks0.0010test_invalid_model_arrays_behaviorfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_w_up_in_cloud1.0870test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_w_up_in_cloud0.8960test_invariantsfalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_w_up_in_cloud1.7770test_differentiablefalsePASSED1clubb_jax.pytests.auto_llm_generated_pytests.test_windm_edsclrm_lhs0.129ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[-0.68638201 1.52409004 -0.46602778 -0.33872706 -0.39151396 -0.01255222 1.15885653 -1.76984869] [ 1.21548704 -1.55817849 1.00056251 1.14582832 1.29674442 0.99859823 0.33629566 0.54250523]] [[-0.79632431 0.18724632 1.6983095 -0.9961909 -0.79230888 0.06051654 -0.09212711 -0.80942598] [-0.64738986 -1.10715655 0.88700408 -0.95046203 1.54918098 0.34532349 1.14856963 0.50961795]] [[-1.62273185 1.52964745 0.3761664 -0.50771604 1.57947835 0.55469002 -1.1577175 1.79986478] [-0.58395162 1.71350815 0.29173991 0.22391714 0.24590882 1.01796553 -1.33532669 0.60011474]]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_lhs_matches_f90_assembly(): gr = setup_grid(_NG, _DZ, _DZ, _DZ * (_NZT + 1)) rng = np.random.default_rng(544) dt = 60.0 lhs_diff, lhs_ma_zt, invrs_rho_ds_zt, rho_ds_zm, u_star_sqd, wind_speed, invrs_dzt = _inputs(rng, gr) > got = np.asarray(windm_edsclrm_lhs(jnp.asarray(lhs_diff), jnp.asarray(lhs_ma_zt), dt, jnp.asarray(invrs_rho_ds_zt), jnp.asarray(rho_ds_zm), jnp.asarray(u_star_sqd), jnp.asarray(wind_speed), gr, 0, 0)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[-0.68638201 1.52409004 -0.46602778 -0.33872706 -0.39151396 E -0.01255222 1.15885653 -1.76984869] E [ 1.21548704 -1.55817849 1.00056251 1.14582832 1.29674442 E 0.99859823 0.33629566 0.54250523]] E E [[-0.79632431 0.18724632 1.6983095 -0.9961909 -0.79230888 E 0.06051654 -0.09212711 -0.80942598] E [-0.64738986 -1.10715655 0.88700408 -0.95046203 1.54918098 E 0.34532349 1.14856963 0.50961795]] E E [[-1.62273185 1.52964745 0.3761664 -0.50771604 1.57947835 E 0.55469002 -1.1577175 1.79986478] E [-0.58395162 1.71350815 0.29173991 0.22391714 0.24590882 E 1.01796553 -1.33532669 0.60011474]]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_windm_edsclrm_lhs.py:62: ValueError4test_lhs_matches_f90_assemblyfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_windm_edsclrm_lhs0.002ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[-1.48571919 -0.00288855 0.40599343 -1.88524397 -1.40829566 1.71284409 -1.7183177 -1.4809042 ] [ 1.79331381 0.48753437 -0.52402751 0.04556009 0.65137181 -0.89876474 -1.44812771 1.15215838]] [[ 0.68144234 0.04952925 1.26694574 0.19630108 1.92365456 -1.18196215 0.21492145 -0.06550121] [-0.58690058 0.36638122 -1.05879507 1.20881074 1.46933421 -1.48496132 -0.13170717 -0.89142043]] [[-1.66753201 1.58377723 -0.28020523 -1.4092348 0.69344943 -1.19113589 1.60572431 -1.13140697] [-1.86770125 -1.19692418 -0.6170085 -0.12436735 1.62453736 0.78944435 -0.64271736 -1.93249114]]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_surface_term_localized_and_cn_scaling(): gr = setup_grid(_NG, _DZ, _DZ, _DZ * (_NZT + 1)) rng = np.random.default_rng(11) dt = 60.0 lhs_diff, lhs_ma_zt, invrs_rho_ds_zt, rho_ds_zm, u_star_sqd, wind_speed, invrs_dzt = _inputs(rng, gr) args = (jnp.asarray(lhs_diff), jnp.asarray(lhs_ma_zt), dt, jnp.asarray(invrs_rho_ds_zt), jnp.asarray(rho_ds_zm), jnp.asarray(u_star_sqd), jnp.asarray(wind_speed), gr, 0, 0) > base = np.asarray(windm_edsclrm_lhs(*args)) ^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[-1.48571919 -0.00288855 0.40599343 -1.88524397 -1.40829566 E 1.71284409 -1.7183177 -1.4809042 ] E [ 1.79331381 0.48753437 -0.52402751 0.04556009 0.65137181 E -0.89876474 -1.44812771 1.15215838]] E E [[ 0.68144234 0.04952925 1.26694574 0.19630108 1.92365456 E -1.18196215 0.21492145 -0.06550121] E [-0.58690058 0.36638122 -1.05879507 1.20881074 1.46933421 E -1.48496132 -0.13170717 -0.89142043]] E E [[-1.66753201 1.58377723 -0.28020523 -1.4092348 0.69344943 E -1.19113589 1.60572431 -1.13140697] E [-1.86770125 -1.19692418 -0.6170085 -0.12436735 1.62453736 E 0.78944435 -0.64271736 -1.93249114]]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_windm_edsclrm_lhs.py:78: ValueError4test_surface_term_localized_and_cn_scalingfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_windm_edsclrm_rhs0.068ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[-1.19147169 1.26627236 0.60924776 1.90165371 1.76880206 -1.69827121 -0.92372881 -1.84510251] [-1.14636946 -1.9315875 1.87317936 0.73583607 -1.52520287 -1.8679437 1.12926853 -1.06671348]] [[-0.09825562 -0.5705109 1.92056741 1.32182048 -1.32470799 0.08165562 -0.31340509 -0.70146373] [-1.7908162 -1.28913637 -1.6800432 -1.77181536 -0.53644832 1.14905894 -1.8667776 -0.13233778]] [[ 0.14219461 -1.08009536 1.72982352 -0.97913112 0.7923364 -1.25352379 0.53728725 1.57109789] [-0.81325559 -0.03744118 0.21188722 -1.27103021 1.8465853 0.3065091 1.68759379 -0.69125656]]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_rhs_is_cn_explicit_half(): rng = np.random.default_rng(545) dt = 60.0 lhs_diff, xm, xm_tndcy = _inputs(rng) > got = np.asarray(windm_edsclrm_rhs(jnp.asarray(lhs_diff), jnp.asarray(xm), jnp.asarray(xm_tndcy), dt)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[-1.19147169 1.26627236 0.60924776 1.90165371 1.76880206 E -1.69827121 -0.92372881 -1.84510251] E [-1.14636946 -1.9315875 1.87317936 0.73583607 -1.52520287 E -1.8679437 1.12926853 -1.06671348]] E E [[-0.09825562 -0.5705109 1.92056741 1.32182048 -1.32470799 E 0.08165562 -0.31340509 -0.70146373] E [-1.7908162 -1.28913637 -1.6800432 -1.77181536 -0.53644832 E 1.14905894 -1.8667776 -0.13233778]] E E [[ 0.14219461 -1.08009536 1.72982352 -0.97913112 0.7923364 E -1.25352379 0.53728725 1.57109789] E [-0.81325559 -0.03744118 0.21188722 -1.27103021 1.8465853 E 0.3065091 1.68759379 -0.69125656]]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_windm_edsclrm_rhs.py:63: ValueError4test_rhs_is_cn_explicit_halffalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_windm_edsclrm_rhs0.002ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0.]] [[0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0.]] [[0. 0. 0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0. 0. 0.]]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_no_diffusion_is_pure_time_plus_tendency(): rng = np.random.default_rng(3) dt = 30.0 _, xm, xm_tndcy = _inputs(rng) zero = np.zeros((3, _NG, _NZT)) > got = np.asarray(windm_edsclrm_rhs(jnp.asarray(zero), jnp.asarray(xm), jnp.asarray(xm_tndcy), dt)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[0. 0. 0. 0. 0. 0. 0. 0.] E [0. 0. 0. 0. 0. 0. 0. 0.]] E E [[0. 0. 0. 0. 0. 0. 0. 0.] E [0. 0. 0. 0. 0. 0. 0. 0.]] E E [[0. 0. 0. 0. 0. 0. 0. 0.] E [0. 0. 0. 0. 0. 0. 0. 0.]]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_windm_edsclrm_rhs.py:75: ValueError4test_no_diffusion_is_pure_time_plus_tendencyfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_windm_edsclrm_rhs0.008ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[ 0.0241227 0.26036653 0.04766384 1.88874549 0.45961257 0.27313399 -0.85285311 0.21804581] [-0.1299059 0.44023203 1.72176999 -1.01645847 -0.76224665 -0.4356814 -0.91891307 -0.5999402 ]] [[ 1.74491876 -0.48846314 1.09859684 -1.83773104 -0.80537762 0.81036459 -0.19098952 1.55943156] [-0.25959987 0.49423918 0.34151886 0.39652698 0.62274262 0.04512793 -1.22528099 -1.72413047]] [[-0.99181723 -1.61922865 -1.54748253 -0.87765667 0.37006541 -0.62710989 1.11139693 1.86154185] [-0.67263996 -1.05486348 0.75132523 0.2906633 1.07822862 0.46766295 -0.88192609 1.64442527]]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' -------------------- For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these.def test_grad_finite(): rng = np.random.default_rng(99) lhs_diff, xm, xm_tndcy = _inputs(rng) > g = jax.grad(lambda x: jnp.sum( windm_edsclrm_rhs(jnp.asarray(lhs_diff), x, jnp.asarray(xm_tndcy), 60.0) ** 2))(jnp.asarray(xm)) clubb_jax/pytests/auto_llm_generated_pytests/test_windm_edsclrm_rhs.py:84: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ x = GradTracer(primal=[[ 1.75047507 5.23945262 4.13699238 6.47505955 6.05774148 -2.15270662 -11.08977628 -0.3...8.53077714 6.76829763 3.72878118 4.93639771 -6.76548646 -10.19207165 -5.57322864]], typeof(tangent)=f64[2,8]) g = jax.grad(lambda x: jnp.sum( > windm_edsclrm_rhs(jnp.asarray(lhs_diff), x, jnp.asarray(xm_tndcy), 60.0) ** 2))(jnp.asarray(xm)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[[ 0.0241227 0.26036653 0.04766384 1.88874549 0.45961257 E 0.27313399 -0.85285311 0.21804581] E [-0.1299059 0.44023203 1.72176999 -1.01645847 -0.76224665 E -0.4356814 -0.91891307 -0.5999402 ]] E E [[ 1.74491876 -0.48846314 1.09859684 -1.83773104 -0.80537762 E 0.81036459 -0.19098952 1.55943156] E [-0.25959987 0.49423918 0.34151886 0.39652698 0.62274262 E 0.04512793 -1.22528099 -1.72413047]] E E [[-0.99181723 -1.61922865 -1.54748253 -0.87765667 0.37006541 E -0.62710989 1.11139693 1.86154185] E [-0.67263996 -1.05486348 0.75132523 0.2906633 1.07822862 E 0.46766295 -0.88192609 1.64442527]]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' E E -------------------- E For simplicity, JAX has removed its internal frames from the traceback of the following exception. Set JAX_TRACEBACK_FILTERING=off to include these. clubb_jax/pytests/auto_llm_generated_pytests/test_windm_edsclrm_rhs.py:85: ValueError4test_grad_finitefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_lhs_terms0.111TypeError: wp2_term_dp1_lhs() missing 3 required positional arguments: 'gr', 'C1_Skw_fnc', and 'invrs_tau1m'def test_scalar_lhs_terms(): gr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = gr.zm.shape[1]; nzt = nzm - 1 rng = np.random.default_rng(41) C1 = rng.uniform(0.5, 2.0, (_NG, nzm)); itau1 = rng.uniform(1e-3, 1e-2, (_NG, nzm)) C4 = rng.uniform(3.0, 6.0, _NG); itau4 = rng.uniform(1e-3, 1e-2, (_NG, nzm)) C8 = rng.uniform(3.0, 6.0, _NG); C8b = rng.uniform(0.1, 0.5, _NG) itau3 = rng.uniform(1e-3, 1e-2, (_NG, nzt)); Skw = rng.uniform(-3.0, 3.0, (_NG, nzt)) > jd = np.asarray(wp2_term_dp1_lhs(jnp.asarray(C1), jnp.asarray(itau1))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: wp2_term_dp1_lhs() missing 3 required positional arguments: 'gr', 'C1_Skw_fnc', and 'invrs_tau1m' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_lhs_terms.py:47: TypeError4test_scalar_lhs_termsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_lhs_terms0.002TypeError: wp2_term_ta_lhs() missing 3 required positional arguments: 'gr', 'rho_ds_zt', and 'invrs_rho_ds_zm'def test_wp2_term_ta_lhs(): gr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = gr.zm.shape[1]; nzt = nzm - 1 invrs_dzm = np.asarray(gr.invrs_dzm) rng = np.random.default_rng(42) invrs_rho_ds_zm = rng.uniform(0.8, 2.0, (_NG, nzm)) rho_ds_zt = rng.uniform(0.5, 1.2, (_NG, nzt)) > j = np.asarray(wp2_term_ta_lhs(jnp.asarray(invrs_rho_ds_zm), jnp.asarray(rho_ds_zt), gr)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: wp2_term_ta_lhs() missing 3 required positional arguments: 'gr', 'rho_ds_zt', and 'invrs_rho_ds_zm' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_lhs_terms.py:68: TypeError4test_wp2_term_ta_lhsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_lhs_terms0.02TypeError: wp3_term_tp_lhs() missing 3 required positional arguments: 'wp2', 'rho_ds_zm', and 'invrs_rho_ds_zt'def test_wp3_term_tp_lhs(): """wp3_term_tp_lhs — 2-band turbulent-production LHS (F90:4885). Band 0 = coeff of wp2[k+1], band 1 = wp2[k].""" gr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = gr.zm.shape[1]; nzt = nzm - 1 invrs_dzt = np.asarray(gr.invrs_dzt) rng = np.random.default_rng(43) coef = rng.uniform(0.5, 2.0, _NG) wp2 = rng.uniform(1e-3, 2.0, (_NG, nzm)); rho_zm = rng.uniform(0.5, 1.2, (_NG, nzm)) inv_rho_zt = rng.uniform(0.8, 2.0, (_NG, nzt)) > j = np.asarray(wp3_term_tp_lhs(jnp.asarray(coef), jnp.asarray(wp2), jnp.asarray(rho_zm), jnp.asarray(inv_rho_zt), gr)) E TypeError: wp3_term_tp_lhs() missing 3 required positional arguments: 'wp2', 'rho_ds_zm', and 'invrs_rho_ds_zt' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_lhs_terms.py:88: TypeError4test_wp3_term_tp_lhsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_lhs_terms0.002TypeError: wp3_terms_ac_pr2_lhs() missing 3 required positional arguments: 'gr', 'C11_Skw_fnc', and 'wm_zm'def test_ac_pr2_lhs(): """wp3_terms_ac_pr2_lhs (F90:5011) and wp2_terms_ac_pr2_lhs (F90:3511) — accumulation+pr2 LHS via d(wm)/dz.""" gr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = gr.zm.shape[1]; nzt = nzm - 1 idzt = np.asarray(gr.invrs_dzt); idzm = np.asarray(gr.invrs_dzm) rng = np.random.default_rng(44) C11 = rng.uniform(0.3, 0.8, (_NG, nzt)); wm_zm = rng.uniform(-0.1, 0.1, (_NG, nzm)) C_uu_shr = rng.uniform(0.1, 0.5, _NG); wm_zt = rng.uniform(-0.1, 0.1, (_NG, nzt)) > j3 = np.asarray(wp3_terms_ac_pr2_lhs(jnp.asarray(C11), jnp.asarray(wm_zm), gr)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: wp3_terms_ac_pr2_lhs() missing 3 required positional arguments: 'gr', 'C11_Skw_fnc', and 'wm_zm' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_lhs_terms.py:108: TypeError4test_ac_pr2_lhsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_terms0.1TypeError: wp2_terms_bp_pr2_rhs() missing 3 required positional arguments: 'C_uu_buoy', 'thv_ds_zm', and 'wpthvp'def test_wp2_bp_pr2_dp1_pr1(): gr, nzm = _grid() rng = np.random.default_rng(31) C_uu_buoy = rng.uniform(0.1, 0.6, _NG) thv = rng.uniform(290.0, 320.0, (_NG, nzm)); wpthvp = rng.uniform(-0.05, 0.2, (_NG, nzm)) C1 = rng.uniform(0.5, 2.0, (_NG, nzm)); itau1 = rng.uniform(1e-3, 1e-2, (_NG, nzm)) up2 = rng.uniform(1e-3, 2.0, (_NG, nzm)); vp2 = rng.uniform(1e-3, 2.0, (_NG, nzm)) C4 = rng.uniform(3.0, 6.0, _NG); itau4 = rng.uniform(1e-3, 1e-2, (_NG, nzm)) > jb = np.asarray(wp2_terms_bp_pr2_rhs(jnp.asarray(C_uu_buoy), jnp.asarray(thv), jnp.asarray(wpthvp))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: wp2_terms_bp_pr2_rhs() missing 3 required positional arguments: 'C_uu_buoy', 'thv_ds_zm', and 'wpthvp' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_terms.py:57: TypeError4test_wp2_bp_pr2_dp1_pr1falseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_terms0.002TypeError: wp2_term_pr3_rhs() missing 3 required positional arguments: 'um', 'vpwp', and 'vm'def test_wp2_pr3(): gr, nzm = _grid() nzt = nzm - 1 invrs_dzm = np.asarray(gr.invrs_dzm) rng = np.random.default_rng(32) C_uu_shr = rng.uniform(0.1, 0.5, _NG); C_uu_buoy = rng.uniform(0.1, 0.5, _NG) thv = rng.uniform(290.0, 320.0, (_NG, nzm)); wpthvp = rng.uniform(-0.05, 0.2, (_NG, nzm)) upwp = rng.uniform(-0.5, 0.5, (_NG, nzm)); vpwp = rng.uniform(-0.5, 0.5, (_NG, nzm)) um = rng.uniform(-15.0, 15.0, (_NG, nzt)); vm = rng.uniform(-15.0, 15.0, (_NG, nzt)) > j = np.asarray(wp2_term_pr3_rhs(jnp.asarray(C_uu_shr), jnp.asarray(C_uu_buoy), jnp.asarray(thv), jnp.asarray(wpthvp), jnp.asarray(upwp), jnp.asarray(um), jnp.asarray(vpwp), jnp.asarray(vm), gr)) E TypeError: wp2_term_pr3_rhs() missing 3 required positional arguments: 'um', 'vpwp', and 'vm' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_terms.py:79: TypeError4test_wp2_pr3falseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_terms0.002TypeError: wp3_terms_bp1_pr2_rhs() missing 3 required positional arguments: 'C11_Skw_fnc', 'thv_ds_zt', and 'wp2thvp'def test_wp3_bp1_pr2_pr1(): gr, nzm = _grid() nzt = nzm - 1 rng = np.random.default_rng(33) C11 = rng.uniform(0.3, 0.8, (_NG, nzt)); thv_zt = rng.uniform(290.0, 320.0, (_NG, nzt)) wp2thvp = rng.uniform(-0.1, 0.3, (_NG, nzt)) C8 = rng.uniform(3.0, 6.0, _NG); C8b = rng.uniform(0.1, 0.5, _NG) itau3 = rng.uniform(1e-3, 1e-2, (_NG, nzt)); Skw = rng.uniform(-3.0, 3.0, (_NG, nzt)) wp3 = rng.standard_normal((_NG, nzt)) > jb = np.asarray(wp3_terms_bp1_pr2_rhs(jnp.asarray(C11), jnp.asarray(thv_zt), jnp.asarray(wp2thvp))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: wp3_terms_bp1_pr2_rhs() missing 3 required positional arguments: 'C11_Skw_fnc', 'thv_ds_zt', and 'wp2thvp' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_terms.py:104: TypeError4test_wp3_bp1_pr2_pr1falseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_wp2_wp3_terms0.003TypeError: wp2_term_pr_dfsn_rhs() missing 3 required positional arguments: 'wpup2', 'wpvp2', and 'wp3'def test_pr_dfsn_turb(): """The pressure-diffusion / pressure-turbulence RHS builders (deferred from iter 494, F90-verified iter 503): wp2_term_pr_dfsn_rhs (F90:4229) C·invrs_rho_ds_zm·invrs_dzm·Δ(rho_ds_zt·(wpup2+wpvp2+wp3)); lower BC = first interior wp3_term_pr_turb_rhs (F90:5452) −C·invrs_rho_ds_zt·invrs_dzt·Δ(rho_ds_zm·wp2·em) [TKE branch] wp3_term_pr_dfsn_rhs (F90:5564) C·invrs_rho_ds_zt·invrs_dzt·Δ(rho_ds_zm·net), net=(wp2up2+wp2vp2+wp4)−wp2·(up2+vp2+wp2) """ gr = _grid()[0]; nzm = gr.zm.shape[1]; nzt = nzm - 1 idzm = np.asarray(gr.invrs_dzm); idzt = np.asarray(gr.invrs_dzt) rng = np.random.default_rng(34) # wp2_term_pr_dfsn_rhs Cw2 = rng.uniform(0.1, 0.5, _NG); rho_zt = rng.uniform(0.5, 1.2, (_NG, nzt)); irho_zm = rng.uniform(0.8, 2.0, (_NG, nzm)) wpup2 = rng.standard_normal((_NG, nzt)); wpvp2 = rng.standard_normal((_NG, nzt)); wp3 = rng.standard_normal((_NG, nzt)) > j2 = np.asarray(wp2_term_pr_dfsn_rhs(jnp.asarray(Cw2), jnp.asarray(rho_zt), jnp.asarray(irho_zm), jnp.asarray(wpup2), jnp.asarray(wpvp2), jnp.asarray(wp3), gr)) E TypeError: wp2_term_pr_dfsn_rhs() missing 3 required positional arguments: 'wpup2', 'wpvp2', and 'wp3' clubb_jax/pytests/auto_llm_generated_pytests/test_wp2_wp3_terms.py:128: TypeError4test_pr_dfsn_turbfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xm_correction_wpxp_cl0.06TypeError: xm_correction_wpxp_cl() missing 5 required positional arguments: 'dt', 'wpxp_chnge', 'invrs_dzt', 'stats', and 'xm'def test_xm_correction_wpxp_cl_matches_reference(): rng = np.random.default_rng(0) ng, nzt = 3, 12 nzm = nzt + 1 xm = rng.normal(size=(ng, nzt)) invrs_dzt = rng.uniform(0.5, 2.0, size=(ng, nzt)) dt = 60.0 wpxp_chnge = rng.normal(size=(ng, nzm)) * 1e-3 # col 0: clipping fired wpxp_chnge[1] = 0.0 # col 1: no clipping → no-op wpxp_chnge[2] = 0.5 * eps # col 2: sub-eps → gated off (no-op) > got = np.asarray(xm_correction_wpxp_cl( jnp.asarray(xm), jnp.asarray(wpxp_chnge), jnp.asarray(invrs_dzt), dt)) E TypeError: xm_correction_wpxp_cl() missing 5 required positional arguments: 'dt', 'wpxp_chnge', 'invrs_dzt', 'stats', and 'xm' clubb_jax/pytests/auto_llm_generated_pytests/test_xm_correction_wpxp_cl.py:54: TypeError4test_xm_correction_wpxp_cl_matches_referencefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xm_correction_wpxp_cl0.079TypeError: xm_correction_wpxp_cl() missing 5 required positional arguments: 'dt', 'wpxp_chnge', 'invrs_dzt', 'stats', and 'xm'def test_xm_correction_wpxp_cl_all_zero_is_noop(): rng = np.random.default_rng(1) ng, nzt = 2, 8 xm = rng.normal(size=(ng, nzt)) invrs_dzt = rng.uniform(0.5, 2.0, size=(ng, nzt)) > got = np.asarray(xm_correction_wpxp_cl( jnp.asarray(xm), jnp.zeros((ng, nzt + 1)), jnp.asarray(invrs_dzt), 60.0)) E TypeError: xm_correction_wpxp_cl() missing 5 required positional arguments: 'dt', 'wpxp_chnge', 'invrs_dzt', 'stats', and 'xm' clubb_jax/pytests/auto_llm_generated_pytests/test_xm_correction_wpxp_cl.py:71: TypeError4test_xm_correction_wpxp_cl_all_zero_is_noopfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xm_wpxp_terms0.1TypeError: xm_term_ta_lhs() missing 3 required positional arguments: 'gr', 'rho_ds_zm', and 'invrs_rho_ds_zt'def test_xm_term_ta_lhs(): gr, nzm, nzt = _grid() idzt = np.asarray(gr.invrs_dzt) rng = np.random.default_rng(51) inv_rho_zt = rng.uniform(0.8, 2.0, (_NG, nzt)); rho_zm = rng.uniform(0.5, 1.2, (_NG, nzm)) > j = np.asarray(xm_term_ta_lhs(jnp.asarray(inv_rho_zt), jnp.asarray(rho_zm), gr)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: xm_term_ta_lhs() missing 3 required positional arguments: 'gr', 'rho_ds_zm', and 'invrs_rho_ds_zt' clubb_jax/pytests/auto_llm_generated_pytests/test_xm_wpxp_terms.py:50: TypeError4test_xm_term_ta_lhsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xm_wpxp_terms0.002TypeError: wpxp_term_tp_lhs() missing 2 required positional arguments: 'gr' and 'wp2'def test_wpxp_term_tp_lhs(): gr, nzm, nzt = _grid() idzm = np.asarray(gr.invrs_dzm) rng = np.random.default_rng(52) wp2 = rng.uniform(1e-3, 2.0, (_NG, nzm)) > j = np.asarray(wpxp_term_tp_lhs(jnp.asarray(wp2), gr)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: wpxp_term_tp_lhs() missing 2 required positional arguments: 'gr' and 'wp2' clubb_jax/pytests/auto_llm_generated_pytests/test_xm_wpxp_terms.py:64: TypeError4test_wpxp_term_tp_lhsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xm_wpxp_terms0.002TypeError: wpxp_terms_ac_pr2_lhs() missing 4 required positional arguments: 'gr', 'C7_Skw_fnc', 'wm_zt', and 'invrs_dzm'def test_wpxp_ac_pr1_bp(): gr, nzm, nzt = _grid() idzm = np.asarray(gr.invrs_dzm) rng = np.random.default_rng(53) C7 = rng.uniform(0.3, 0.8, (_NG, nzm)); wm_zt = rng.uniform(-0.1, 0.1, (_NG, nzt)) C6 = rng.uniform(2.0, 5.0, (_NG, nzm)); itau6 = rng.uniform(1e-3, 1e-2, (_NG, nzm)) thv = rng.uniform(290.0, 320.0, (_NG, nzm)); xpthvp = rng.uniform(-0.1, 0.3, (_NG, nzm)) > jac = np.asarray(wpxp_terms_ac_pr2_lhs(jnp.asarray(C7), jnp.asarray(wm_zt), gr)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E TypeError: wpxp_terms_ac_pr2_lhs() missing 4 required positional arguments: 'gr', 'C7_Skw_fnc', 'wm_zt', and 'invrs_dzm' clubb_jax/pytests/auto_llm_generated_pytests/test_xm_wpxp_terms.py:81: TypeError4test_wpxp_ac_pr1_bpfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xp2_xpyp_terms0.087ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[ 0.35877341 1.51067731 -1.78633124 1.68661351 -0.04731721 -0.79997858 -0.80295672 -1.08281652 -0.22364536 0.83388418 0.58406373 0.63828602 -1.69480839 -1.57096212 1.55380317 0.96888537 2.183214 1.20981583 -1.02439134 1.28527245 0.62839426 0.21482493 -0.81987332 0.00278022 -0.1469987 0.89253511 0.12449694 1.58474591 -0.77448575 0.47110256] [ 0.49884238 -0.86433854 -1.18126605 1.0135795 0.51744047 -0.16250519 0.3943674 -0.67534403 0.2383482 -0.60512669 0.18878847 0.98608946 -0.33963025 0.84977381 -1.03419934 -0.28849077 -1.3647426 -0.10058609 0.07865408 -0.19726266 -0.26767572 1.34019469 1.42379284 -1.215631 1.17411449 -1.72306961 -0.73447925 -0.1734456 0.1110606 -1.04741668]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_term_tp_rhs(): gr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = gr.zm.shape[1]; nzt = nzm - 1 invrs_dzm = np.asarray(gr.invrs_dzm) rng = np.random.default_rng(21) xam = rng.standard_normal((_NG, nzt)); xbm = rng.standard_normal((_NG, nzt)) wpxap = rng.standard_normal((_NG, nzm)); wpxbp = rng.standard_normal((_NG, nzm)) > j = np.asarray(term_tp_rhs(jnp.asarray(xam), jnp.asarray(xbm), jnp.asarray(wpxap), jnp.asarray(wpxbp), jnp.asarray(invrs_dzm))) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[ 0.35877341 1.51067731 -1.78633124 1.68661351 -0.04731721 -0.79997858 E -0.80295672 -1.08281652 -0.22364536 0.83388418 0.58406373 0.63828602 E -1.69480839 -1.57096212 1.55380317 0.96888537 2.183214 1.20981583 E -1.02439134 1.28527245 0.62839426 0.21482493 -0.81987332 0.00278022 E -0.1469987 0.89253511 0.12449694 1.58474591 -0.77448575 0.47110256] E [ 0.49884238 -0.86433854 -1.18126605 1.0135795 0.51744047 -0.16250519 E 0.3943674 -0.67534403 0.2383482 -0.60512669 0.18878847 0.98608946 E -0.33963025 0.84977381 -1.03419934 -0.28849077 -1.3647426 -0.10058609 E 0.07865408 -0.19726266 -0.26767572 1.34019469 1.42379284 -1.215631 E 1.17411449 -1.72306961 -0.73447925 -0.1734456 0.1110606 -1.04741668]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_xp2_xpyp_terms.py:44: ValueError4test_term_tp_rhsfalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xp2_xpyp_terms0.029ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[4.09904075] [3.59788614]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_term_pr1(): nzm = 11 rng = np.random.default_rng(22) C4 = rng.uniform(3.0, 6.0, (_NG, 1)); C14 = rng.uniform(0.5, 2.0, (_NG, 1)) xbp2 = rng.uniform(1e-3, 2.0, (_NG, nzm)); wp2 = rng.uniform(1e-3, 2.0, (_NG, nzm)) itau4 = rng.uniform(1e-3, 1e-2, (_NG, nzm)); itau14 = rng.uniform(1e-3, 1e-2, (_NG, nzm)) > j = np.asarray(term_pr1(jnp.asarray(C4), jnp.asarray(C14), jnp.asarray(xbp2), jnp.asarray(wp2), jnp.asarray(itau4), jnp.asarray(itau14), w_tol_sqd)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[4.09904075] E [3.59788614]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_xp2_xpyp_terms.py:60: ValueError4test_term_pr1falseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xp2_xpyp_terms0.003ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[0.37757323] [0.35658329]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_term_pr2(): gr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) nzm = gr.zm.shape[1]; nzt = nzm - 1 invrs_dzm = np.asarray(gr.invrs_dzm) rng = np.random.default_rng(23) C_uu_shr = rng.uniform(0.1, 0.5, (_NG, 1)); C_uu_buoy = rng.uniform(0.1, 0.5, (_NG, 1)) thv = rng.uniform(290.0, 320.0, (_NG, nzm)); wpthvp = rng.uniform(-0.05, 0.2, (_NG, nzm)) upwp = rng.uniform(-0.5, 0.5, (_NG, nzm)); vpwp = rng.uniform(-0.5, 0.5, (_NG, nzm)) um = rng.uniform(-15.0, 15.0, (_NG, nzt)); vm = rng.uniform(-15.0, 15.0, (_NG, nzt)) > j = np.asarray(term_pr2(jnp.asarray(C_uu_shr), jnp.asarray(C_uu_buoy), jnp.asarray(thv), jnp.asarray(wpthvp), jnp.asarray(upwp), jnp.asarray(vpwp), jnp.asarray(um), jnp.asarray(vm), gr)) E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[0.37757323] E [0.35658329]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_xp2_xpyp_terms.py:80: ValueError4test_term_pr2falseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xp2_xpyp_terms0.001ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[0.72751079 0.8698369 1.19200186 1.06215956 1.17200376 1.18240589 1.76082141 0.26421788 1.51070301 1.6586978 1.45310413] [0.87885865 1.89161217 0.15880336 1.62558594 1.24389239 0.17813984 0.73155888 0.81871803 0.43448612 1.32094161 0.9345577 ]]. The error was: TypeError: unhashable type: 'jaxlib._jax.ArrayImpl'def test_term_dp1(): """term_dp1_lhs (F90:5729) main-diagonal +(Cn/tau) [interior, BC 0]; term_dp1_rhs (F90:5809) explicit +(Cn/tau)·threshold [ALL levels incl. boundaries]. The DP1 dissipation terms missed by iter 492.""" nzm = 11 rng = np.random.default_rng(24) Cn = rng.uniform(0.1, 2.0, (_NG, nzm)); itau = rng.uniform(1e-3, 1e-2, (_NG, nzm)); thr = 1e-8 > jl = np.asarray(term_dp1_lhs(jnp.asarray(Cn), jnp.asarray(itau))) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'jaxlib._jax.ArrayImpl'>, [[0.72751079 0.8698369 1.19200186 1.06215956 1.17200376 1.18240589 E 1.76082141 0.26421788 1.51070301 1.6586978 1.45310413] E [0.87885865 1.89161217 0.15880336 1.62558594 1.24389239 0.17813984 E 0.73155888 0.81871803 0.43448612 1.32094161 0.9345577 ]]. The error was: E TypeError: unhashable type: 'jaxlib._jax.ArrayImpl' clubb_jax/pytests/auto_llm_generated_pytests/test_xp2_xpyp_terms.py:104: ValueError4test_term_dp1falseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xpyp_term_ta_godunov0.192ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 0.50038187 1.5888552 1.10274276 -1.09917124 -0.79933486 1.49421378 -1.97893878 1.28491367 1.18827772 -0.12826019 -0.78787029 -0.88629755 -0.98052165 -0.21969478 0.01819304 0.21398941 1.98200113 1.17064768 0.48871692 1.95584059 -1.13876521 -1.35915186 0.45015842 -1.82423197 -1.85727888 0.05955528 -0.1351759 1.66867109 0.51690502 0.05647059] [-0.01250626 -1.00994031 -1.9528239 -1.23039142 0.76812848 -1.1975731 -0.52185476 -1.98506303 1.32019092 -1.38215568 -0.92960278 1.52132862 0.03916324 1.38860099 0.55886867 0.96708379 -1.63401758 0.16457529 0.03108895 1.48535751 -0.55494376 0.39273627 -1.76299343 -0.4494728 -0.70785461 -1.39920108 1.26535242 -0.48221531 1.91499154 0.35996677]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_f2py_oracle(): try: import clubb_f2py from clubb_python import clubb_api from clubb_python.derived_types.err_info import ErrInfo except ModuleNotFoundError as e: if (e.name or "").split(".")[0] not in {"clubb_f2py", "clubb_python", "netCDF4"}: raise pytest.skip(f" f2py xpyp_term_ta_*_godunov oracle: SKIP ({type(e).__name__})") jgr = setup_grid(ngrdcol=_NG, deltaz=_DZ, zm_init=0.0, zm_top=_ZTOP, grid_type=1) ng, nzm = jgr.zm.shape nzt = nzm - 1 clubb_api.init_err_info(ng) cf = clubb_api.get_default_config_flags(); clubb_api.init_config_flags(cf) clubb_api.setup_grid(nzmax=nzm, ngrdcol=ng, sfc_elevation=np.zeros(ng), l_implemented=False, l_ascending_grid=True, grid_type=2, deltaz=np.full(ng, _DZ), zm_init=np.zeros(ng), zm_top=np.full(ng, float(jgr.zm[0, -1])), momentum_heights=np.asfortranarray(np.asarray(jgr.zm)), thermodynamic_heights=np.asfortranarray(np.asarray(jgr.zt)), err_info=ErrInfo(ngrdcol=ng)) # Pull the EXACT stored grid so the JAX side uses identical invrs_dzm / grid_dir. g = clubb_f2py.get_grid(ng, nzm, nzt) invrs_dzm = np.asarray(g[4]); grid_dir = float(g[13]) shim = _GridShim(invrs_dzm=jnp.asarray(invrs_dzm)) rng = np.random.default_rng(7) worst = 0.0 for _ in range(3): coef = rng.uniform(-2, 2, (ng, nzt)) # zt-level implicit coef (sign drives upwind split) irho = rng.uniform(0.5, 1.5, (ng, nzm)) rho_zm = rng.uniform(0.5, 1.2, (ng, nzm)) term_zm = rng.uniform(-1, 1, (ng, nzm)) sgn = np.sign(rng.uniform(-1, 1, (ng, nzt))) # ±1 turbulent-velocity sign f_lhs = np.asarray(clubb_f2py.f2py_xpyp_term_ta_pdf_lhs_godunov(coef, irho, rho_zm)) > j_lhs = np.asarray(xpyp_term_ta_pdf_lhs_godunov(coef, irho, rho_zm, shim, grid_dir)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[ 0.50038187 1.5888552 1.10274276 -1.09917124 -0.79933486 1.49421378 E -1.97893878 1.28491367 1.18827772 -0.12826019 -0.78787029 -0.88629755 E -0.98052165 -0.21969478 0.01819304 0.21398941 1.98200113 1.17064768 E 0.48871692 1.95584059 -1.13876521 -1.35915186 0.45015842 -1.82423197 E -1.85727888 0.05955528 -0.1351759 1.66867109 0.51690502 0.05647059] E [-0.01250626 -1.00994031 -1.9528239 -1.23039142 0.76812848 -1.1975731 E -0.52185476 -1.98506303 1.32019092 -1.38215568 -0.92960278 1.52132862 E 0.03916324 1.38860099 0.55886867 0.96708379 -1.63401758 0.16457529 E 0.03108895 1.48535751 -0.55494376 0.39273627 -1.76299343 -0.4494728 E -0.70785461 -1.39920108 1.26535242 -0.48221531 1.91499154 0.35996677]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_xpyp_term_ta_godunov.py:73: ValueError4test_f2py_oraclefalseFAILED1clubb_jax.pytests.auto_llm_generated_pytests.test_xpyp_term_ta_godunov0.052ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[-0.95355146 -0.80603543 1.25690296 -1.63233623 0.4004021 0.91424211 -1.24839571 -1.77941349 -0.90012253] [ 0.62973206 0.24906265 -1.39975095 -0.26947684 0.67718919 -0.30886131 0.5327376 1.86974381 0.73225929]]. The error was: TypeError: unhashable type: 'numpy.ndarray'def test_boundaries_and_grad(): ng, nzm, nzt = 2, 10, 9 jgr = setup_grid(ngrdcol=ng, deltaz=_DZ, zm_init=0.0, zm_top=(nzm - 1) * _DZ, grid_type=1) rng = np.random.default_rng(2) coef = rng.uniform(-2, 2, (ng, nzt)); irho = rng.uniform(0.5, 1.5, (ng, nzm)) rho_zm = rng.uniform(0.5, 1.2, (ng, nzm)); term_zm = rng.uniform(-1, 1, (ng, nzm)) sgn = np.sign(rng.uniform(-1, 1, (ng, nzt))) > lhs = np.asarray(xpyp_term_ta_pdf_lhs_godunov(coef, irho, rho_zm, jgr, jgr.grid_dir)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ E ValueError: Non-hashable static arguments are not supported. An error occurred while trying to hash an object of type <class 'numpy.ndarray'>, [[-0.95355146 -0.80603543 1.25690296 -1.63233623 0.4004021 0.91424211 E -1.24839571 -1.77941349 -0.90012253] E [ 0.62973206 0.24906265 -1.39975095 -0.26947684 0.67718919 -0.30886131 E 0.5327376 1.86974381 0.73225929]]. The error was: E TypeError: unhashable type: 'numpy.ndarray' clubb_jax/pytests/auto_llm_generated_pytests/test_xpyp_term_ta_godunov.py:88: ValueError4test_boundaries_and_gradfalseFAILED0clubb_jax.pytests.auto_llm_generated_pytests.test_xpyp_term_ta_pdf0.5440test_f2py_oraclefalsePASSED0clubb_jax.pytests.auto_llm_generated_pytests.test_xpyp_term_ta_pdf0.6680test_differentiablefalsePASSED1567.8429Declarative: Post Actions56pytest572026-10-05T04:22:54.196230-05:001auto_llm_generated_pytests/test_close_luhar_pdf.py0.0Module process exited 139 before writing its pytest report; see the console.Module process exited 139 before writing its pytest report; see the console.4pytest_module_processfalseFAILED0.0Declarative: Post Actions56auto_llm_generated_pytests_test_close_luhar_pdf.py571auto_llm_generated_pytests/test_new_hybrid_pdf_main.py0.0Module process exited 2 before writing its pytest report; see the console.Module process exited 2 before writing its pytest report; see the console.4pytest_module_processfalseFAILED0.0Declarative: Post Actions56auto_llm_generated_pytests_test_new_hybrid_pdf_main.py571auto_llm_generated_pytests/test_new_pdf_main.py0.0Module process exited 2 before writing its pytest report; see the console.Module process exited 2 before writing its pytest report; see the console.4pytest_module_processfalseFAILED0.0Declarative: Post Actions56auto_llm_generated_pytests_test_new_pdf_main.py57