import os
from acme_diags.run import runner
from acme_diags.parameter.core_parameter import CoreParameter
from acme_diags.parameter.area_mean_time_series_parameter import AreaMeanTimeSeriesParameter
from acme_diags.parameter.enso_diags_parameter import EnsoDiagsParameter
from acme_diags.parameter.qbo_parameter import QboParameter
from acme_diags.parameter.diurnal_cycle_parameter import DiurnalCycleParameter
from acme_diags.parameter.streamflow_parameter import StreamflowParameter


#Define data paths for obs
input_prefix ='/global/cfs/cdirs/e3sm/acme_diags'
obs_climo = '/global/cfs/cdirs/e3sm/acme_diags/obs_for_e3sm_diags/climatology'
obs_ts = '/global/cfs/cdirs/e3sm/acme_diags/obs_for_e3sm_diags/time-series'

#Define data paths for test model
test_prefix = '/global/cfs/cdirs/e3sm/zhang40/postprocessing_for_e3sm_diags'
case = '20180215.DECKv1b_H1.ne30_oEC.edison'
casename = case.split('.')[1]+'.'+case.split('.')[2]

climo_path = os.path.join(test_prefix, 'climo/'+case+'/1980-2014/rgr')
ts_path = os.path.join(test_prefix, 'monthly_ts/'+case+'/1980-2014/rgr')
dc_climo_path = os.path.join(test_prefix, 'diurnal_climo/'+case+'/1980-2014/rgr')

#Define parameters for core sets: 'lat_lon','zonal_mean_xy', 'zonal_mean_2d', 'polar', 'cosp_histogram', 'meridional_mean_2d' 
param = CoreParameter()
param.reference_data_path = obs_climo
param.test_data_path = climo_path
param.test_name = case
param.test_short_name = casename

#Define results path. 
prefix = '/global/cfs/cdirs/e3sm/www/zhang40/tutorials/'
param.results_dir = os.path.join(prefix, 'run_v230_allsets_knl')

param.multiprocessing = True
param.num_workers = 30
param.seasons = ['ANN', 'JJA']

#Additional parameters:
#Short version of test model name being printed as plot titles
#param.short_test_name = 'beta0.FC5COSP.ne30'
#Specify run_type. Defualt is 'model_vs_obs'
#param.run_type = 'model_vs_model'
#Specify title of the 3rd panel plot. Defualt is 'Model - Observation'
#param.diff_title = 'Difference'
#Save subplots as pdf files.
#param.output_format_subplot = ['pdf']
#Save netcdf files being plotted.
#param.save_netcdf = True


#Set specific parameters for new sets
qbo_param = QboParameter()
qbo_param.reference_data_path = obs_ts
qbo_param.test_data_path = ts_path
qbo_param.test_name = casename
qbo_param.start_yr = '1980'
qbo_param.end_yr = '2014'


dc_param = DiurnalCycleParameter()
dc_param.reference_data_path = obs_climo
dc_param.test_data_path = dc_climo_path
dc_param.test_name = case
dc_param.short_test_name = casename
#Plotting diurnal cycle amplitude on different scales. Default is True
dc_param.normalize_test_amp = False              

enso_param = EnsoDiagsParameter()
enso_param.reference_data_path = obs_ts
enso_param.test_data_path = ts_path
enso_param.test_name = casename
enso_param.start_yr = '1980'
enso_param.end_yr = '2014'

ts_param = AreaMeanTimeSeriesParameter()
ts_param.reference_data_path = obs_ts
ts_param.test_data_path = ts_path 
ts_param.test_name = casename
ts_param.start_yr = '1980'
ts_param.end_yr = '2014'

streamflow_param = StreamflowParameter()
streamflow_param.reference_data_path = obs_ts
streamflow_param.test_data_path = ts_path 
streamflow_param.test_start_yr = '1980'
streamflow_param.test_end_yr = '2014'
# Streamflow gauge station data range from year 1986 to 1995
streamflow_param.ref_start_yr = '1986'
streamflow_param.ref_end_yr = '1995'
#
runner.sets_to_run = ['lat_lon','zonal_mean_xy', 'zonal_mean_2d', 'polar', 'cosp_histogram', 'meridional_mean_2d','enso_diags', 'qbo','area_mean_time_series','diurnal_cycle','streamflow']
runner.run_diags([param, enso_param, qbo_param, ts_param,dc_param,streamflow_param])