style fix for pre-commit test

lee1043 · lee1043 · commit e6345a1a9276 · 2023-11-06T21:31:54.000-08:00
diff --git a/pcmdi_metrics/mean_climate/lib/compute_metrics.py b/pcmdi_metrics/mean_climate/lib/compute_metrics.py
@@ -35,23 +35,23 @@ def compute_metrics(Var, dm, do, debug=False):
 
     # unify time and time bounds between observation and model
     if debug:
-        print('before time and time bounds unifying')
-        print('dm.time: ', dm['time'])
-        print('do.time: ', do['time'])
+        print("before time and time bounds unifying")
+        print("dm.time: ", dm["time"])
+        print("do.time: ", do["time"])
 
     """
     # Below is temporary...
     dm['time'] = do['time']
     dm[dm.time.encoding['bounds']] = do[do.time.attrs['bounds']]
     """
-    
+
     if debug:
-        print('after time and time bounds unifying')
-        print('dm.time: ', dm['time'])
-        print('do.time: ', do['time'])
-        
-        dm.to_netcdf('dm.nc')
-        do.to_netcdf('do.nc')
+        print("after time and time bounds unifying")
+        print("dm.time: ", dm["time"])
+        print("do.time: ", do["time"])
+
+        dm.to_netcdf("dm.nc")
+        do.to_netcdf("do.nc")
 
     metrics_dictionary = OrderedDict()
 
@@ -65,15 +65,15 @@ def compute_metrics(Var, dm, do, debug=False):
 
     print("compute_metrics, rms_xyt")
     rms_xyt = pcmdi_metrics.mean_climate.lib.rms_xyt(dm, do, var)
-    print('compute_metrics, rms_xyt:', rms_xyt)
+    print("compute_metrics, rms_xyt:", rms_xyt)
 
     print("compute_metrics, stdObs_xyt")
     stdObs_xyt = pcmdi_metrics.mean_climate.lib.std_xyt(do, var)
-    print('compute_metrics, stdObs_xyt:', stdObs_xyt)
+    print("compute_metrics, stdObs_xyt:", stdObs_xyt)
 
     print("compute_metrics, std_xyt")
     std_xyt = pcmdi_metrics.mean_climate.lib.std_xyt(dm, var)
-    print('compute_metrics, std_xyt:', std_xyt)
+    print("compute_metrics, std_xyt:", std_xyt)
 
     # CALCULATE ANNUAL MEANS
     print("compute_metrics-CALCULATE ANNUAL MEANS")
@@ -82,23 +82,23 @@ def compute_metrics(Var, dm, do, debug=False):
     # CALCULATE ANNUAL MEAN BIAS
     print("compute_metrics-CALCULATE ANNUAL MEAN BIAS")
     bias_xy = pcmdi_metrics.mean_climate.lib.bias_xy(dm_am, do_am, var)
-    print('compute_metrics-CALCULATE ANNUAL MEAN BIAS, bias_xy:', bias_xy)
+    print("compute_metrics-CALCULATE ANNUAL MEAN BIAS, bias_xy:", bias_xy)
 
     # CALCULATE MEAN ABSOLUTE ERROR
     print("compute_metrics-CALCULATE MSE")
     mae_xy = pcmdi_metrics.mean_climate.lib.meanabs_xy(dm_am, do_am, var)
-    print('compute_metrics-CALCULATE MSE, mae_xy:', mae_xy)
+    print("compute_metrics-CALCULATE MSE, mae_xy:", mae_xy)
 
     # CALCULATE ANNUAL MEAN RMS (centered and uncentered)
     print("compute_metrics-CALCULATE MEAN RMS")
     rms_xy = pcmdi_metrics.mean_climate.lib.rms_xy(dm_am, do_am, var)
     rmsc_xy = pcmdi_metrics.mean_climate.lib.rmsc_xy(dm_am, do_am, var)
-    print('compute_metrics-CALCULATE MEAN RMS: rms_xy, rmsc_xy: ', rms_xy, rmsc_xy)
+    print("compute_metrics-CALCULATE MEAN RMS: rms_xy, rmsc_xy: ", rms_xy, rmsc_xy)
 
     # CALCULATE ANNUAL MEAN CORRELATION
     print("compute_metrics-CALCULATE MEAN CORR")
     cor_xy = pcmdi_metrics.mean_climate.lib.cor_xy(dm_am, do_am, var)
-    print('compute_metrics-CALCULATE MEAN CORR: cor_xy:', cor_xy)
+    print("compute_metrics-CALCULATE MEAN CORR: cor_xy:", cor_xy)
 
     # CALCULATE ANNUAL OBS and MOD STD
     print("compute_metrics-CALCULATE ANNUAL OBS AND MOD STD")
@@ -166,9 +166,7 @@ def compute_metrics(Var, dm, do, debug=False):
     metrics_dictionary["std_xy"]["ann"] = format(std_xy, sig_digits)
     metrics_dictionary["std-obs_xyt"]["ann"] = format(stdObs_xyt, sig_digits)
     metrics_dictionary["std_xyt"]["ann"] = format(std_xyt, sig_digits)
-    metrics_dictionary["std-obs_xy_devzm"]["ann"] = format(
-        stdObs_xy_devzm, sig_digits
-    )
+    metrics_dictionary["std-obs_xy_devzm"]["ann"] = format(stdObs_xy_devzm, sig_digits)
     metrics_dictionary["std_xy_devzm"]["ann"] = format(std_xy_devzm, sig_digits)
     metrics_dictionary["rms_xyt"]["ann"] = format(rms_xyt, sig_digits)
     metrics_dictionary["rms_xy"]["ann"] = format(rms_xy, sig_digits)
diff --git a/pcmdi_metrics/mean_climate/lib/load_and_regrid.py b/pcmdi_metrics/mean_climate/lib/load_and_regrid.py
@@ -34,16 +34,15 @@ def load_and_regrid(
 
     # load data
     ds = xcdat_open(
-        data_path, 
-        data_var=varname_in_file, 
-        decode_times=decode_times)  # NOTE: decode_times=False will be removed once obs4MIP written using xcdat
-    
+        data_path, data_var=varname_in_file, decode_times=decode_times
+    )  # NOTE: decode_times=False will be removed once obs4MIP written using xcdat
+
     # SET CONDITIONAL ON INPUT VARIABLE
     if varname == "pr":
-        print('Adjust units for pr')
+        print("Adjust units for pr")
         if ds[varname_in_file].units == "kg m-2 s-1":
             ds[varname_in_file] = ds[varname_in_file] * 86400
-            print('pr units adjusted to [mm d-1] from [kg m-2 s-1] by 86400 multiplied')
+            print("pr units adjusted to [mm d-1] from [kg m-2 s-1] by 86400 multiplied")
 
     """
     # calendar quality check
@@ -64,20 +63,22 @@ def load_and_regrid(
             ds.time.attrs["calendar"] = 'standard'
             print('[WARNING]: calendar info not found for time axis. ds.time.attrs["calendar"] is adjusted to standard')
     """
-    
+
     # time bound check #1 -- add proper time bound info if cdms-generated annual cycle is loaded
-    if isinstance(ds.time.values[0], np.float64):  # and "units" not in list(ds.time.attrs.keys()):
-        ds.time.attrs['units'] = "days since 0001-01-01"
+    if isinstance(
+        ds.time.values[0], np.float64
+    ):  # and "units" not in list(ds.time.attrs.keys()):
+        ds.time.attrs["units"] = "days since 0001-01-01"
         ds = xc.decode_time(ds)
         if debug:
-            print('decode_time done')
-            
+            print("decode_time done")
+
     # time bound check #2 -- add time bounds itself it it is missing
-    if 'bounds' in list(ds.time.attrs.keys()):
-        time_bnds_key = ds.time.attrs['bounds']
+    if "bounds" in list(ds.time.attrs.keys()):
+        time_bnds_key = ds.time.attrs["bounds"]
         if time_bnds_key not in list(ds.keys()):
-            ds = ds.bounds.add_missing_bounds(['T'])
-            print('[WARNING]: bounds.add_missing_bounds conducted for T axis')
+            ds = ds.bounds.add_missing_bounds(["T"])
+            print("[WARNING]: bounds.add_missing_bounds conducted for T axis")
 
     # level - extract a specific level if needed
     if level is not None:
@@ -143,15 +144,14 @@ def load_and_regrid(
 
     ds_regridded[varname] = ds_regridded[varname].assign_attrs({"units": units})
 
-    ds_regridded[varname] = ds_regridded[varname].assign_attrs({'units': units})
-    
+    ds_regridded[varname] = ds_regridded[varname].assign_attrs({"units": units})
+
     # time bound check #3 -- preserve time bnds in regridded dataset
-    if 'bounds' in list(ds_regridded.time.attrs.keys()):
-        time_bnds_key = ds_regridded.time.attrs['bounds']
+    if "bounds" in list(ds_regridded.time.attrs.keys()):
+        time_bnds_key = ds_regridded.time.attrs["bounds"]
         if time_bnds_key not in list(ds_regridded.keys()):
-            ds_regridded = ds_regridded.bounds.add_missing_bounds(['T'])
-            print('[WARNING]: bounds.add_missing_bounds conducted for T axis')
-        
+            ds_regridded = ds_regridded.bounds.add_missing_bounds(["T"])
+            print("[WARNING]: bounds.add_missing_bounds conducted for T axis")
 
     if debug:
         print("ds_regridded:", ds_regridded)
diff --git a/pcmdi_metrics/mean_climate/lib/mean_climate_metrics_to_json.py b/pcmdi_metrics/mean_climate/lib/mean_climate_metrics_to_json.py
@@ -24,12 +24,21 @@ def mean_climate_metrics_to_json(
             if m == model:
                 ref_list = list(json_dict["RESULTS"][m].keys())
                 if debug:
-                    print('debug:: mean_climate_metrics_to_json:: m, ref_list: ', m, ref_list)
-                if 'units' in ref_list:
-                    ref_list.remove('units')
+                    print(
+                        "debug:: mean_climate_metrics_to_json:: m, ref_list: ",
+                        m,
+                        ref_list,
+                    )
+                if "units" in ref_list:
+                    ref_list.remove("units")
                 for ref in ref_list:
                     if debug:
-                        print('debug:: mean_climate_metrics_to_json:: m, ref, json_dict["RESULTS"][m][ref]: ', m, ref, json_dict["RESULTS"][m][ref])
+                        print(
+                            'debug:: mean_climate_metrics_to_json:: m, ref, json_dict["RESULTS"][m][ref]: ',
+                            m,
+                            ref,
+                            json_dict["RESULTS"][m][ref],
+                        )
                     runs_in_model_dict = list(json_dict["RESULTS"][m][ref].keys())
                     for r in runs_in_model_dict:
                         if (r != run) and (run is not None):
diff --git a/pcmdi_metrics/mean_climate/mean_climate_driver.py b/pcmdi_metrics/mean_climate/mean_climate_driver.py
@@ -233,32 +233,36 @@
     # ----------------
     if "all" in reference_data_set:
         reference_data_set = [
-            x for x in list(obs_dict[varname].keys()) if (x == "default" or "alternate" in x)]
+            x
+            for x in list(obs_dict[varname].keys())
+            if (x == "default" or "alternate" in x)
+        ]
         print("reference_data_set (all): ", reference_data_set)
 
     for ref in reference_data_set:
-        print('ref:', ref)
-        
+        print("ref:", ref)
+
         # identify data to load (annual cycle (AC) data is loading in)
         ref_dataset_name = obs_dict[varname][ref]
         ref_data_full_path = os.path.join(
-            reference_data_path,
-            obs_dict[varname][ref_dataset_name]["template"])
-        print('ref_data_full_path:', ref_data_full_path)
-        
+            reference_data_path, obs_dict[varname][ref_dataset_name]["template"]
+        )
+        print("ref_data_full_path:", ref_data_full_path)
+
         # load data and regrid
         ds_ref = load_and_regrid(
-            data_path=ref_data_full_path, 
-            varname=varname, 
-            level=level, 
-            t_grid=t_grid, 
-            # decode_times=False, 
-            decode_times=True, 
-            regrid_tool=regrid_tool, 
-            debug=debug)
+            data_path=ref_data_full_path,
+            varname=varname,
+            level=level,
+            t_grid=t_grid,
+            # decode_times=False,
+            decode_times=True,
+            regrid_tool=regrid_tool,
+            debug=debug,
+        )
 
         ds_ref_dict = OrderedDict()
-        
+
         # for record in output json
         result_dict["References"][ref] = obs_dict[varname][ref_dataset_name]
 
@@ -421,7 +425,7 @@
                                     )
 
                             # compute metrics
-                            
+
                             print("compute metrics start")
                             result_dict["RESULTS"][model][ref][run][
                                 region
@@ -469,11 +473,7 @@
         # write collective JSON --- all models / all obs / single variable
         json_filename = "_".join([var, target_grid, regrid_tool, "metrics", case_id])
         mean_climate_metrics_to_json(
-            metrics_output_path,
-            json_filename,
-            result_dict,
-            cmec_flag=cmec,
-            debug=debug
+            metrics_output_path, json_filename, result_dict, cmec_flag=cmec, debug=debug
         )
 
-print("pmp mean clim driver completed")
+print("pmp mean clim driver completed")
