test param file

test/pcmdi/region_specs_test.py

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+import os
+
+#
+# OPTIONS ARE SET BY USER IN THIS FILE AS INDICATED BELOW BY:
+#
+#
+
+# RUN IDENTIFICATION
+# DEFINES A SUBDIRECTORY TO METRICS OUTPUT RESULTS SO MULTIPLE CASES CAN
+# BE COMPARED
+case_id = 'installationTest'
+
+# LIST OF MODEL VERSIONS TO BE TESTED - WHICH ARE EXPECTED TO BE PART OF
+# CLIMATOLOGY FILENAME
+model_versions = ['GFDL-ESM2G', ]
+
+# dictionary of keywords for simulation description that you want to save
+# or remap
+simulation_description_mapping = {
+ "Login": "Login",
+ "Center": "Center",
+ "SimTrackingDate": "creation_date"}
+
+# VARIABLES AND OBSERVATIONS TO USE
+vars = ['tos', 'tas']
+
+# MODEL SPECIFC PARAMETERS
+model_tweaks = {
+ # Keys are model accronym or None which applies to all model entries
+ None: {
+ # Variables name mapping
+ "variable_mapping": {"tos": "tos"},
+ },
+ "GFDL-ESM2G": {
+ "variable_mapping": {"tas": "tas_ac"},
+ },
+}
+
+# REGIONS ON WHICH WE WANT TO RUN METRICS (var specific)
+# Here we run glb for both but also terre and ocean for tas (only)
+regions = {"tas": [None, "ocean","Nino34","NAM"], "tos": [None, ]}
+# USER CAN CUSTOMIZE REGIONS
+regions_specs = {"Nino34":
+ {"value":0.,
+ "domain": {'lat1':-5., 'lat2':5., 'lon1':190., 'lon2':240.}},
+ "NAM": { "value":0.,
+ "domain": {'lat1':0., 'lat2':45.,'lon1':210.,'lon2':310.}
+ }
+ }
+
+# Observations to use at the moment "default" or "alternate"
+ref = ['all']
+ext = '.nc'
+
+# INTERPOLATION OPTIONS
+targetGrid = '2.5x2.5' # OPTIONS: '2.5x2.5' or an actual cdms2 grid object
+regrid_tool = 'regrid2' # 'regrid2' # OPTIONS: 'regrid2','esmf'
+# OPTIONS: 'linear','conservative', only if tool is esmf
+regrid_method = 'linear'
+regrid_tool_ocn = 'esmf' # OPTIONS: "regrid2","esmf"
+# OPTIONS: 'linear','conservative', only if tool is esmf
+regrid_method_ocn = 'linear'
+
+# SIMULATION PARAMETERS
+period = '198501-200512'
+realization = 'r1i1p1'
+
+# SAVE INTERPOLATED MODEL CLIMATOLOGIES ?
+save_mod_clims = True # True or False
+
+# DATA LOCATION: MODELS, OBS AND METRICS OUTPUT
+
+# Templates for climatology files
+# TEMPLATE EXAMPLE: tas_GFDL-ESM2G_Amon_historical_r1i1p1_198001-199912-clim.nc
+filename_template = "%(variable)_%(model_version)_%(table)_historical_%(realization)_%(period)-clim.nc"
+# filename template for landsea masks ('sftlf')
+sftlf_filename_template = "sftlf_%(model_version).nc"
+
+pth = os.path.dirname(__file__)
+# ROOT PATH FOR MODELS CLIMATOLOGIES
+mod_data_path = os.path.abspath(os.path.join(pth, "data"))
+# ROOT PATH FOR OBSERVATIONS
+obs_data_path = os.path.abspath(os.path.join(pth, "obs"))
+# Custom obs dictionary file (one we use for tests)
+custom_observations = os.path.abspath(
+ os.path.join(
+ obs_data_path,
+ "obs_info_dictionary.json"))
+# DIRECTORY WHERE TO PUT RESULTS
+metrics_output_path = os.path.join(
+ 'pcmdi_install_test_results',
+ 'metrics_results', "%(case_id)")
+# DIRECTORY WHERE TO PUT INTERPOLATED MODELS' CLIMATOLOGIES
+model_clims_interpolated_output = os.path.join(
+ 'pcmdi_install_test_results',
+ 'interpolated_model_clims')
+# FILENAME FOR INTERPOLATED CLIMATOLOGIES OUTPUT
+filename_output_template = "%(variable)%(level)_%(model_version)_%(table)_" +\
+ "historical_%(realization)_%(period).interpolated.%(regridMethod).%(targetGridName)-clim%(ext)"
+
+# Ok do we have custom metrics?
+# The following allow users to plug in a set of custom metrics
+# Function needs to take in var name, model clim, obs clim
+import pcmdi_metrics # Or whatever your custom metrics package name is
+compute_custom_metrics = pcmdi_metrics.pcmdi.compute_metrics
+# or
+
+
+def mymax(slab, nm):
+ if slab is None:
+ return {"custom_%s_max" % nm:
+ {"Abstract": "Computes Custom Maximum for demo purposes",
+ "Name": "Custom Maximum",
+ "Contact": "[email protected]"},
+ }
+ else:
+ return {"custom_%s_max" % nm: float(slab.max())}
+
+
+def mymin(slab, nm):
+ if slab is None:
+ return {"custom_%s_min" % nm:
+ {"Abstract": "Computes Custom Minimum for demo purposes",
+ "Name": "Custom Minimum",
+ "Contact": "[email protected]"},
+ }
+ else:
+ return {"custom_%s_min" % nm: float(slab.min())}
+
+
+def my_custom(var, dm, do):
+ out = {}
+ if var == "tas":
+ out.update(mymax(dm, "model"))
+ elif var == "tos":
+ out.update(mymin(dm, "ref"))
+ if dm is None and do is None:
+ out["some_custom"] = {
+ "Name": "SomeCustom",
+ "Abstract": "For demo purpose really does nothing",
+ "Contact": "[email protected]",
+ }
+ else:
+ out["some_custom"] = 1.5
+ return out
+compute_custom_metrics = my_custom
+# or for different metrics