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])
qbo_param = QboParameter()
qbo_param.reference_data_path = os.path.join(
data_prefix, "obs_for_e3sm_diags/time-series/")
qbo_param.test_data_path = os.path.join(
data_prefix, "test_model_data_for_acme_diags/time-series/E3SM_v1/")
qbo_param.test_name = "e3sm_v1"
qbo_param.start_yr = "1990"
qbo_param.end_yr = "1999"
ts_param = AreaMeanTimeSeriesParameter()
ts_param.reference_data_path = os.path.join(data_prefix,
"obs_for_e3sm_diags/time-series/")
ts_param.test_data_path = os.path.join(
data_prefix, "test_model_data_for_acme_diags/time-series/E3SM_v1/")
ts_param.test_name = "e3sm_v1"
ts_param.start_yr = "1990"
ts_param.end_yr = "1999"
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",
]
runner.run_diags([param, enso_param, qbo_param, ts_param])
"/global/cfs/cdirs/e3sm/e3sm_diags/obs_for_e3sm_diags/climatology/")
param.test_data_path = (
"/global/cfs/cdirs/e3sm/e3sm_diags/test_model_data_for_acme_diags/climatology/"
)
# Name of the test model data, used to find the climo files.
param.test_name = "20161118.beta0.FC5COSP.ne30_ne30.edison"
# An optional, shorter name to be used instead of the test_name.
param.short_test_name = "beta0.FC5COSP.ne30"
# What plotsets to run the diags on.
param.sets = ["lat_lon"]
# Name of the folder where the results are stored.
# Change `prefix` to use your directory.
prefix = "/global/cfs/cdirs/e3sm/www/<your directory>/examples"
param.results_dir = os.path.join(prefix, "ex5_model_to_obs")
# Below are more optional arguments.
# 'mpl' is to create matplotlib plots, 'vcs' is for vcs plots.
param.backend = "mpl"
# Title of the difference plots.
param.diff_title = "Model - Obs."
# Save the netcdf files for each of the ref, test, and diff plot.
param.save_netcdf = True
# For running with multiprocessing.
# param.multiprocessing = True
# param.num_workers = 32
runner.sets_to_run = ["lat_lon"]
runner.run_diags([param])
def run_all_sets(html_prefix, d):
param = CoreParameter()
param.reference_data_path = d["obs_climo"]
param.test_data_path = d["test_climo"]
param.test_name = "20161118.beta0.FC5COSP.ne30_ne30.edison"
param.seasons = [
"ANN",
"JJA",
] # Default setting: seasons = ["ANN", "DJF", "MAM", "JJA", "SON"]
param.results_dir = os.path.join(html_prefix, "v2_3_0_all_sets")
param.multiprocessing = True
param.num_workers = 30
# Set specific parameters for new sets
enso_param = EnsoDiagsParameter()
enso_param.reference_data_path = d["obs_ts"]
enso_param.test_data_path = d["test_ts"]
enso_param.test_name = "e3sm_v1"
enso_param.start_yr = "1990"
enso_param.end_yr = "1999"
qbo_param = QboParameter()
qbo_param.reference_data_path = d["obs_ts"]
qbo_param.test_data_path = d["test_ts"]
qbo_param.test_name = "e3sm_v1"
qbo_param.start_yr = "1990"
qbo_param.end_yr = "1999"
ts_param = AreaMeanTimeSeriesParameter()
ts_param.reference_data_path = d["obs_ts"]
ts_param.test_data_path = d["test_ts"]
ts_param.test_name = "e3sm_v1"
ts_param.start_yr = "1990"
ts_param.end_yr = "1999"
dc_param = DiurnalCycleParameter()
dc_param.reference_data_path = d["dc_obs_climo"]
dc_param.test_data_path = d["dc_test_climo"]
dc_param.test_name = "20180215.DECKv1b_H1.ne30_oEC.edison"
dc_param.short_test_name = "DECKv1b_H1.ne30_oEC"
# Plotting diurnal cycle amplitude on different scales. Default is True
dc_param.normalize_test_amp = False
streamflow_param = StreamflowParameter()
streamflow_param.reference_data_path = d["streamflow_obs_ts"]
streamflow_param.test_data_path = d["streamflow_test_ts"]
streamflow_param.test_name = "20180215.DECKv1b_H1.ne30_oEC.edison"
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]
)
return param.results_dir
from e3sm_diags.parameter.zonal_mean_2d_parameter import ZonalMean2dParameter
from e3sm_diags.run import runner
param = CoreParameter()
param.reference_data_path = (
"/global/cfs/cdirs/e3sm/e3sm_diags/obs_for_e3sm_diags/climatology/"
)
param.test_data_path = (
"/global/cfs/cdirs/e3sm/e3sm_diags/test_model_data_for_acme_diags/climatology/"
)
param.test_name = "20161118.beta0.FC5COSP.ne30_ne30.edison"
param.seasons = ["ANN"]
# Name of the folder where the results are stored.
# Change `prefix` to use your directory.
prefix = "/global/cfs/cdirs/e3sm/www/<your directory>/examples"
param.results_dir = os.path.join(prefix, "ex6_zonal_mean_2d_and_lat_lon_demo")
# Uncomment the two lines below to just
# run the diags with T and PRECT.
# param.selectors += ['variables']
# param.variables = ['T', 'PRECT']
# The new changes are below.
zonal_mean_2d_param = ZonalMean2dParameter()
zonal_mean_2d_param.plevs = [10.0, 20.0, 30.0]
runner.sets_to_run = ["zonal_mean_2d", "lat_lon"]
runner.run_diags([param, zonal_mean_2d_param])