import os
from acme_diags.parameter.core_parameter import CoreParameter
from acme_diags.run import runner


param = CoreParameter()


# 'mpl' and 'vcs' are for matplotlib or vcs plots respectively.
#run_type= 'model_vs_obs'



multiprocessing = True
num_workers= 32

# Name of folder where all results will be stored.



param.reference_data_path = '/global/cfs/cdirs/e3sm/acme_diags/obs_for_e3sm_diags/climatology/'
#param.test_data_path = '/global/cfs/cdirs/e3sm/shpundk/E3SMv2_alpha5_59/wP3_v4_tuned/eam-h0/eam-rgr/'
#param.test_data_path = '/global/cscratch1/sd/beydoun/SPA_runs_from_LC/SPA_only_mp_fixed_units/climo/rgr'
#param.test_data_path = '/global/cscratch1/sd/beydoun/default.default.spa_tests_with_PA_and_meyers_new_branch.ne30pg2_r0125_oRRS18to6v3/run/climo/rgr'
param.test_data_path = '/global/cscratch1/sd/beydoun/default.default.run_with_SPA_latest_branch_full_tuned.ne30pg2_r0125_oRRS18to6v3/run/climo/rgr'
param.test_name = 'default.default.run_with_SPA_latest_branch_full_tuned.ne30pg2_r0125_oRRS18to6v3'
param.short_test_name = 'spa_tuned_ne30pg2_F2010'
#param.reference_name='E3SM_alpha5_59_v2candidate.F2010SC5-CMIP6_wMG2.ne30pg2_r05_oECv3.compy'
#param.short_reference_name = 'v2 (MG2)'
#param.diff_title = 'v2+P3 - v2'

param.seasons = ["ANN","DJF","JJA","MAM","SON"]

param.run_type = 'model_vs_obs'
param.backend = 'mpl'


#prefix = '/global/cfs/cdirs/e3sm/www/terai/E3SMv2_P3v4_tuned/'
prefix = '/global/cfs/cdirs/e3sm/www/beydoun'
param.results_dir = os.path.join(prefix, 'spa_tuned_ne30pg2_F2010_vs_obs')
#prefix = '/var/www/acme/acme-diags/zhang40/tests/'
#param.results_dir = os.path.join(prefix, 'lat_lon_demo')
param.multiprocessing = True
param.num_workers = 32
#use below to run all core sets of diags:
#runner.sets_to_run = ['lat_lon','zonal_mean_xy', 'zonal_mean_2d', 'polar', 'cosp_histogram', 'meridional_mean_2d']
runner.sets_to_run = ['lat_lon','zonal_mean_xy', 'zonal_mean_2d', 'polar', 'meridional_mean_2d']
#runner.sets_to_run = ['lat_lon']
runner.run_diags([param])