ran flake8

pcmdi_metrics/extremes/lib/plot_extremes.py

@@ -2,15 +2,10 @@
 import json
 import math
 import os
-import sys
 
-import cartopy
 import cartopy.crs as ccrs
-import matplotlib.path as mpath
 import matplotlib.pyplot as plt
-import matplotlib.ticker as mticker
 import numpy as np
-from cartopy.mpl.gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTER
 from cartopy.mpl.ticker import LatitudeFormatter, LongitudeFormatter
 
 from pcmdi_metrics.graphics import TaylorDiagram
@@ -110,7 +105,7 @@ def plot_map_cartopy(
     if proj == "PlateCarree":
         if data_area == "global":
             if gridline:
-                gl = ax.gridlines(alpha=0.5, linestyle="--")
+                ax.gridlines(alpha=0.5, linestyle="--")
             ax.set_xticks([0, 60, 120, 180, 240, 300, 360], crs=ccrs.PlateCarree())
             ax.set_yticks([-90, -60, -30, 0, 30, 60, 90], crs=ccrs.PlateCarree())
             lon_formatter = LongitudeFormatter(zero_direction_label=True)
@@ -119,10 +114,10 @@ def plot_map_cartopy(
             ax.yaxis.set_major_formatter(lat_formatter)
         else:
             if gridline:
-                gl = ax.gridlines(draw_labels=True, alpha=0.5, linestyle="--")
+                ax.gridlines(draw_labels=True, alpha=0.5, linestyle="--")
     elif proj == "Robinson":
         if gridline:
-            gl = ax.gridlines(alpha=0.5, linestyle="--")
+            ax.gridlines(alpha=0.5, linestyle="--")
 
     # Add title
     plt.title(title, pad=15, fontsize=15)

pcmdi_metrics/extremes/lib/region_utilities.py

@@ -5,8 +5,6 @@
 import geopandas as gpd
 import numpy as np
 import regionmask
-import xarray as xr
-import xcdat
 
 
 def check_region_params(shp_path, coords, region_name, col, default):

pcmdi_metrics/extremes/lib/return_value.py

@@ -22,7 +22,7 @@ def compute_rv_from_file(
             "Standard error for return value from stationary fit for single realization"
         )
     else:
-        desc = "Return value from nonstationary GEV fit for single realization"
+        desc1 = "Return value from nonstationary GEV fit for single realization"
         desc2 = "Standard error for return value from nonstationary fit for single realization"
 
     for ncfile in filelist:
@@ -41,7 +41,7 @@ def compute_rv_from_file(
             os.path.basename(rv_file),
             rv_file,
             "return_value",
-            "return value for single realization",
+            desc1,
         )
 
         se_file = outdir + "/" + fname + "_standard_error.nc"
@@ -50,7 +50,7 @@ def compute_rv_from_file(
             os.path.basename(se_file),
             se_file,
             "standard_error",
-            "standard error for return value",
+            desc2,
         )
 
     return meta
@@ -71,7 +71,6 @@ def compute_rv_for_model(
     nreal = len(filelist)
 
     ds = xc.open_dataset(filelist[0])
-    real_list = [os.path.basename(f).split("_")[1] for f in filelist]
     units = ds.ANN.attrs["units"]
 
     print("Return value for multiple realizations")
@@ -274,7 +273,6 @@ def get_dataset_rv(ds, cov_filepath, cov_varname, return_period=20, maxes=True):
     lon = len(ds["lon"])
     time = len(ds["time"])
     dim2 = lat * lon
-    rep_ind = np.ones((time))
 
     if nonstationary:
         return_value = xr.zeros_like(ds)
@@ -302,7 +300,6 @@ def get_dataset_rv(ds, cov_filepath, cov_varname, return_period=20, maxes=True):
         else:
             rv_array = np.ones((dim2)) * np.nan
         se_array = rv_array.copy()
-        success = np.zeros((dim2))
 
         # Turn nans to zeros
         data = np.nan_to_num(data)
@@ -485,7 +482,7 @@ def ll(params):
         A = np.matmul(np.transpose(grad), vcov)
         B = np.matmul(A, grad)
         se = np.sqrt(np.diag(B))
-    except Exception as e:
+    except Exception:
         se = np.ones(np.shape(return_value)) * np.nan
 
     return return_value.squeeze(), se.squeeze()
@@ -528,13 +525,14 @@ def f(x):
                 else:
                     rv = tsorted[count]
                 break
-        except:  # any issues, set to NaN
+        except Exception:  # any issues, set to NaN
             rv = np.nan
             break
         count += 1
     return rv, np.nan
 
 
+"""
 def calc_rv_climex(data, covariate, return_period, nreplicates=1, maxes=True):
     # Use climextRemes to get the return value and standard error
     # This function exists for easy comparison with the pure Python
@@ -578,3 +576,4 @@ def calc_rv_climex(data, covariate, return_period, nreplicates=1, maxes=True):
         return_value = tmp["returnValue"]
         standard_error = tmp["se_returnValue"]
     return return_value, standard_error
+"""

pcmdi_metrics/extremes/lib/utilities.py

@@ -1,16 +1,14 @@
 #!/usr/bin/env python
 import datetime
-import glob
-import json
 import os
 import sys
 
 import cdms2
 import cdutil
 import cftime
 import numpy as np
-import xarray as xr
 import xcdat
+import xarray as xr
 from pcmdi_utils import land_sea_mask
 
 from pcmdi_metrics.io import xcdat_openxml
@@ -114,7 +112,7 @@ def verify_output_path(metrics_output_path, case_id):
         print("Creating metrics output directory", metrics_output_path)
         try:
             os.makedirs(metrics_output_path)
-        except Error as e:
+        except Exception as e:
             print("\nError: Could not create metrics output path", metrics_output_path)
             print(e)
             print("Exiting.")
@@ -140,7 +138,14 @@ def set_up_realizations(realization):
 
 def generate_land_sea_mask(data, debug=False):
     # generate sftlf if not provided.
-    """Commenting out the cdutil version
+    mask = land_sea_mask.generate_land_sea_mask(data, tool="pcmdi", maskname="sftlf")
+    mask = mask * 100.0
+    mask = mask.to_dataset()
+
+    return mask
+
+
+def generate_land_sea_mask_cdutil(data, debug=False):
     latArray = data["lat"]
     lat = cdms2.createAxis(latArray, id="latitude")
     lat.designateLatitude()
@@ -151,24 +156,19 @@ def generate_land_sea_mask(data, debug=False):
     lon.designateLongitude()
     lon.units = "degrees_east"
 
-    t_grid_cdms2 = cdms2.grid.TransientRectGrid(lat, lon, 'yx', 'uniform')
+    t_grid_cdms2 = cdms2.grid.TransientRectGrid(lat, lon, "yx", "uniform")
     sft = cdutil.generateLandSeaMask(t_grid_cdms2)
 
     if debug:
-        print('sft:', sft)
-        print('sft.getAxisList():', sft.getAxisList())
+        print("sft:", sft)
+        print("sft.getAxisList():", sft.getAxisList())
 
     # add sft to target grid dataset
-    t_grid = xr.DataArray(np.array(sft),
-        coords={'lat': latArray,'lon': lonArray},
-        dims=["lat", "lon"]).to_dataset(name="sftlf")
+    t_grid = xr.DataArray(
+        np.array(sft), coords={"lat": latArray, "lon": lonArray}, dims=["lat", "lon"]
+    ).to_dataset(name="sftlf")
     t_grid = t_grid * 100
     if debug:
-        print('t_grid (after sftlf added):', t_grid)
-        t_grid.to_netcdf('target_grid.nc')
-    """
-    mask = land_sea_mask.generate_land_sea_mask(data, tool="pcmdi", maskname="sftlf")
-    mask = mask * 100.0
-    mask = mask.to_dataset()
-
-    return mask
+        print("t_grid (after sftlf added):", t_grid)
+        t_grid.to_netcdf("target_grid.nc")
+    return t_grid