catch up with pre-commit

Author: lee1043

pcmdi_metrics/__init__.py

@@ -1,5 +1,5 @@
 #  put here the import calls to expose whatever we want to the user
-import logging
+import logging  # noqa
 
 LOG_LEVEL = logging.DEBUG
 plog = logging.getLogger("pcmdi_metrics")
@@ -15,7 +15,4 @@
 plog.addHandler(ch)
 plog.setLevel(LOG_LEVEL)
 from . import io  # noqa
-
-# from . import pcmdi  # noqa
-# from . import mean_climate  # noqa
 from .version import __git_sha1__, __git_tag_describe__, __version__  # noqa

pcmdi_metrics/cloud_feedback/lib/cal_CloudRadKernel_xr.py

@@ -10,7 +10,6 @@
 from datetime import date
 
 # IMPORT STUFF:
-import cftime
 import numpy as np
 import xarray as xr
 import xcdat as xc
@@ -371,7 +370,7 @@ def bony_sorting_part2(OKwaps, data, OKland, WTS, binedges):
     # Ensure that the area matrix has zeros rather than masked points
     CNTS = CNTS.where(~np.isnan(CNTS), 0.0)
 
-    if np.allclose(0.5, np.sum(CNTS.values, 1)) == False:
+    if np.allclose(0.5, np.sum(CNTS.values, 1)) is False:
         print(
             "sum of fractional counts over all wapbins does not equal 0.5 (tropical fraction)"
         )
@@ -386,7 +385,7 @@ def bony_sorting_part2(OKwaps, data, OKland, WTS, binedges):
     v2b = (data * WTS).sum(dim=["lat", "lon"]).transpose("time", "tau", "plev")
 
     # if np.allclose(v1.values,v2a.values)==False or np.allclose(v1.values,v2b.values)==False:
-    if np.allclose(v1.values, v2b.values) == False:
+    if np.allclose(v1.values, v2b.values) is False:
         print("Cannot reconstruct tropical average via summing regimes")
 
     return DATA, CNTS  # [time,wapbin]
@@ -603,7 +602,7 @@ def obscuration_terms3(c1, c2):
     L_R_bar = L_R_bar.where(L_R_bar >= 0, 0.0)
     F_bar = F_bar.where(F_bar >= 0, 0.0)
 
-    rep_L_bar = tile_uneven(L_bar, L12)
+    # rep_L_bar = tile_uneven(L_bar, L12)
     rep_L_R_bar = tile_uneven(L_R_bar, L_R12)
     rep_F_bar = tile_uneven(F_bar, F12b)
 
@@ -874,7 +873,7 @@ def klein_metrics(obs_clisccp, gcm_clisccp, LWkern, SWkern, WTS):
     # take only clouds with tau>3.6
     clisccp_bias_CPM = clisccp_bias[:, 2:, :]  # 4 tau bins
     obs_clisccp_CPM = obs_clisccp[:, 2:, :]  # 4 tau bins
-    gcm_clisccp_CPM = gcm_clisccp[:, 2:, :]  # 4 tau bins
+    # gcm_clisccp_CPM = gcm_clisccp[:, 2:, :]  # 4 tau bins
     LWkernel_CPM = LWkern[:, 2:, :]  # 4 tau bins
     SWkernel_CPM = SWkern[:, 2:, :]  # 4 tau bins
     NETkernel_CPM = SWkernel_CPM + LWkernel_CPM

pcmdi_metrics/cloud_feedback/lib/compute_ECS_xr.py

@@ -94,7 +94,7 @@ def get_data(pi, ab):
         print("len(time)<1200...skipping")
         return None
 
-    bdate = pisub.time.dt.year.values
+    # bdate = pisub.time.dt.year.values
     # compute global means:
     GLcntl = pisub.spatial.average(var)
     GLpert = absub.spatial.average(var)

pcmdi_metrics/cloud_feedback/lib/organize_jsons.py

@@ -65,7 +65,7 @@ def organize_err_jsons(new_dict, mo, ripf):
                         old_dict[mo][ripf][region][sfc][sec][name] = new_dict[sec][
                             region
                         ][sfc][name]
-                    except:
+                    except Exception:
                         old_dict[mo][ripf][region][sfc][sec][name] = np.nan
                 # end name loop
             # end section loop:
@@ -85,7 +85,7 @@ def organize_ecs_jsons(new_ecs, mo, ripf):
     ) as url:
         old_dict = json.load(url)
 
-    if new_ecs != None:
+    if new_ecs is not None:
         old_dict["CMIP6"][mo][ripf]["ECS"] = new_ecs
 
     return old_dict  # now updated to include info from input dictionary

pcmdi_metrics/graphics/share/read_json_mean_clim.py

@@ -97,7 +97,7 @@ def extract_unit(var, results_dict_var):
     model_list = sorted(list(results_dict_var["RESULTS"].keys()))
     try:
         units = results_dict_var["RESULTS"][model_list[0]]["units"]
-    except Exception as e:
+    except Exception:
         units = None
     return units
 
@@ -106,7 +106,7 @@ def extract_ref(var, results_dict_var):
     model_list = sorted(list(results_dict_var["RESULTS"].keys()))
     try:
         ref = results_dict_var["RESULTS"][model_list[0]]["default"]["source"]
-    except Exception as e:
+    except Exception:
         ref = None
     return ref
 

pcmdi_metrics/io/region_from_file.py

@@ -1,7 +1,5 @@
 import geopandas as gpd
 import regionmask
-import xarray as xr
-import xcdat
 
 
 def region_from_file(data, rgn_path, attr, feature):

pcmdi_metrics/mean_climate/lib/calculate_climatology.py

@@ -3,7 +3,6 @@
 
 import dask
 import xcdat as xc
-from genutil import StringConstructor
 
 
 def calculate_climatology(

pcmdi_metrics/mean_climate/lib/load_and_regrid.py

@@ -1,4 +1,3 @@
-import cftime
 import numpy as np
 import xcdat as xc
 

pcmdi_metrics/mean_climate/scripts/post_process_merge_jsons.py

@@ -4,7 +4,6 @@
 import glob
 import json
 import os
-import sys
 
 from genutil import StringConstructor
 

pcmdi_metrics/mjo/scripts/parallel_driver.py

@@ -8,7 +8,6 @@
 
 from genutil import StringConstructor
 
-import pcmdi_metrics
 from pcmdi_metrics.mean_climate.lib.pmp_parser import PMPParser
 from pcmdi_metrics.misc.scripts import parallel_submitter
 from pcmdi_metrics.mjo.lib import AddParserArgument

pcmdi_metrics/precip_distribution/precip_distribution_driver.py

@@ -6,7 +6,6 @@
 
 import MV2 as MV
 import xarray as xr
-import xcdat
 from genutil import StringConstructor
 
 from pcmdi_metrics.mean_climate.lib.pmp_parser import PMPParser

pcmdi_metrics/variability_mode/scripts_pcmdi/parallel_driver.py

@@ -8,7 +8,6 @@
 
 from genutil import StringConstructor
 
-import pcmdi_metrics
 from pcmdi_metrics.mean_climate.lib.pmp_parser import PMPParser
 from pcmdi_metrics.misc.scripts import parallel_submitter
 from pcmdi_metrics.variability_mode.lib import (

pcmdi_metrics/variability_mode/variability_modes_driver.py

@@ -60,7 +60,6 @@
 import MV2
 from genutil import StringConstructor
 
-import pcmdi_metrics
 from pcmdi_metrics import resources
 from pcmdi_metrics.mean_climate.lib import pmp_parser
 from pcmdi_metrics.variability_mode.lib import (