Merge dev into main

pygem/bin/postproc/postproc_distribute_ice.py

@@ -76,8 +76,7 @@ def pygem_to_oggm(pygem_simpath, oggm_diag=None, debug=False):
     area_m2(time, dis_along_flowline): float64
     thickness_m (time, dis_along_flowline): float64
     """
-    yr0, yr1 = pygem_simpath.split('_')[-3:-1]
-    pygem_ds = xr.open_dataset(pygem_simpath).sel(year=slice(yr0, yr1))
+    pygem_ds = xr.open_dataset(pygem_simpath)
     time = pygem_ds.coords['year'].values.flatten().astype(float)
     distance_along_flowline = pygem_ds['bin_distance'].values.flatten().astype(float)
     area = pygem_ds['bin_area_annual'].values[0].astype(float).T

pygem/bin/run/run_calibration.py

@@ -3061,7 +3061,7 @@ def run_objective(
 
         else:
             # LOG FAILURE
-            fail_fp = pygem_prms['root'] + '/Outputcal_fail/' + glacier_str.split('.')[0].zfill(2) + '/'
+            fail_fp = pygem_prms['root'] + '/Output/cal_fail/' + glacier_str.split('.')[0].zfill(2) + '/'
             if not os.path.exists(fail_fp):
                 os.makedirs(fail_fp, exist_ok=True)
             txt_fn_fail = glacier_str + '-cal_fail.txt'

pygem/bin/run/run_simulation.py

@@ -50,6 +50,7 @@
 from pygem.glacierdynamics import MassRedistributionCurveModel
 from pygem.massbalance import PyGEMMassBalance
 from pygem.oggm_compat import (
+    get_spinup_flowlines,
     single_flowline_glacier_directory,
     single_flowline_glacier_directory_with_calving,
 )
@@ -661,7 +662,8 @@ def run(list_packed_vars):
                         modelprms_fp = (
                             pygem_prms['root'] + '/Output/calibration/' + glacier_str.split('.')[0].zfill(2) + '/'
                         ) + modelprms_fn
-
+                    elif os.path.isdir(modelprms_fp):
+                        modelprms_fp = modelprms_fp + '/' + glacier_str + '-modelprms_dict.json'
                     assert os.path.exists(modelprms_fp), 'Calibrated parameters do not exist.'
                     with open(modelprms_fp, 'r') as f:
                         modelprms_dict = json.load(f)
@@ -804,11 +806,16 @@ def run(list_packed_vars):
                     # spinup
                     if args.spinup:
                         try:
-                            # see if model_flowlines from spinup exist
-                            nfls = gdir.read_pickle(
-                                'model_flowlines',
-                                filesuffix=f'_dynamic_spinup_pygem_mb_{args.sim_startyear}',
-                            )
+                            if f'model_flowlines_dynamic_spinup_pygem_mb_{args.sim_startyear}.pkl' in os.listdir(
+                                gdir.dir
+                            ):
+                                # see if model_flowlines from spinup exist
+                                nfls = gdir.read_pickle(
+                                    'model_flowlines',
+                                    filesuffix=f'_dynamic_spinup_pygem_mb_{args.sim_startyear}',
+                                )
+                            else:
+                                nfls = get_spinup_flowlines(gdir, y0=args.sim_startyear)
                         except:
                             raise
                         glen_a = gdir.get_diagnostics()['inversion_glen_a']

pygem/setup/config.yaml

@@ -159,7 +159,7 @@ calib:
     # Chain options
     mcmc_step: 0.5                                # mcmc step size (in terms of standard deviation)
     n_chains: 1                                   # number of chains (min 1, max 3)
-    mcmc_sample_no: 20000                         # number of steps (10000 was found to be sufficient in HMA)
+    mcmc_sample_no: 10000                         # number of steps (10000 was found to be sufficient in HMA)
     mcmc_burn_pct: 2                              # percentage of steps to burn-in (0 records all steps in chain)
     thin_interval: 10                             # thin interval if need to reduce file size (best to leave at 1 if space allows)
     # Degree-day factor of snow distribution options