STY, LINT: resolve numerous style/lint flags

- resolved only simple ones, more severe ones remaining

examples/tutorials/climate_network_cartopy_plotting.py

@@ -176,7 +176,3 @@
 # Plot with cartopy and matplotlib
 cn_plot.generate_plots(file_name="climate_network_measures",
                                  title_on=False, labels_on=True)
-
-
-
-

src/pyunicorn/climate/cartopy_plots.py

@@ -20,24 +20,15 @@
 multivariate data and generating time series surrogates.
 """
 
-import os
-import glob
-# time handling
-# import datetime
-
-import numpy as np
 import matplotlib.pyplot as plt
 
-#  Import Ngl support functions for plotting, map projections etc.
 try:
-    import cartopy
+    import cartopy.crs as ccrs
+    import cartopy.feature as cf
 except ImportError:
     print("climate: Package cartopy could not be loaded. Some functionality "
           "in class MapPlots might not be available!")
 
-import cartopy.crs as ccrs
-import cartopy.feature as cf
-
 #
 #  Define class CartopyPlots
 #
@@ -84,18 +75,18 @@ def __init__(self, grid, title):
 
         # get spatial dims
         self.lon = self.grid.convert_lon_coordinates(self.grid.lon_sequence())
-        # self.lon = self.grid.lon_sequence()
         self.lat = self.grid.lat_sequence()
         self.gridsize_lon = len(self.lon)
         self.gridsize_lat = len(self.lat)
         self.lon_min = self.grid.boundaries()["lon_min"]
         self.lon_max = self.grid.boundaries()["lon_max"]
         self.lat_min = self.grid.boundaries()["lat_min"]
         self.lat_max = self.grid.boundaries()["lat_max"]
-        
+
         # extent of data will also give extent of world map
-        self.data_extent = [self.lon_min, self.lon_max, self.lat_min, self.lat_max]
-
+        self.data_extent = [self.lon_min, self.lon_max,
+                            self.lat_min, self.lat_max]
+
         print("Created plot class.")
 
     def add_dataset(self, title, data):
@@ -126,52 +117,50 @@ def generate_plots(self, file_name, title_on=True, labels_on=True):
             plotted.
         """
 
-        for dataset in self.map_data: 
-            
+        for dataset in self.map_data:
+
             #  Generate figue
             fig = plt.figure()
-            
+
             # create map plot
             ax = plt.axes(projection=self.projection)
-        
+
             # make it a class feature, as to work with it from outside
             # self.ax = ax
-            
+
             # create some standards of plotting that can be adjusted
-            # before calling generate_cartopy_plot    
+            # before calling generate_cartopy_plot
             # adjust size and plot coastlines and borders
             ax.set_extent(self.data_extent, crs=self.crs)
             # ax.set_global()
             ax.add_feature(cf.COASTLINE.with_scale("50m"), lw=0.5)
-            ax.add_feature(cf.BORDERS.with_scale("50m"), lw=0.2)       
-            
+            ax.add_feature(cf.BORDERS.with_scale("50m"), lw=0.2)
+
             # Draw gridlines in degrees over map
             gl = ax.gridlines(crs=self.crs, draw_labels=True,
-                          linewidth=.6, color='gray', alpha=0.5, linestyle='-.')
+                              linewidth=.6, color='gray',
+                              alpha=0.5, linestyle='-.')
             gl.xlabel_style = {"size": 7}
-            gl.ylabel_style = {"size": 7}                
+            gl.ylabel_style = {"size": 7}
             # plot data upon map
-            ax = plt.tricontourf(self.lon, self.lat, dataset["data"], extent = self.data_extent, transform = self.crs)
-
+            ax = plt.tricontourf(self.lon, self.lat, dataset["data"],
+                                 extent=self.data_extent, transform=self.crs)
             ax = plt.colorbar(shrink=0.5)
 
             # plot main title
             if title_on:
                 plt.suptitle(self.title)
-            
+
             # plot subtitles
             if labels_on:
                 plt.title(dataset["title"])
-            
+
             # save figures at current dir
             file_extension = dataset["title"] + ".png"
             file_extension = file_extension.replace(" ", "")
-            
+
             fig.savefig(file_name + "_" + file_extension)
-
-            plt.close()            
-
-        print("Created and saved plots @ current directory.")
-
 
+            plt.close()
 
+        print("Created and saved plots @ current directory.")

src/pyunicorn/climate/climate_network.py

@@ -126,8 +126,8 @@ def __str__(self):
         Local connections filtered out: False
         """
         return (f'ClimateNetwork:\n{GeoNetwork.__str__(self)}\n' +
-        f'Threshold: {self.threshold()}\n' +
-        f'Local connections filtered out: {self.non_local()}')
+                f'Threshold: {self.threshold()}\n' +
+                f'Local connections filtered out: {self.non_local()}')
 
     def clear_cache(self, irreversible=False):
         """
@@ -164,9 +164,8 @@ def _regenerate_network(self):
     #  Load and save ClimateNetwork object
     #
 
-    def save(self, filename_network, filename_grid=None,
-             filename_similarity_measure=None, fileformat=None, *args,
-             **kwds):
+    def save(self, filename_network, filename_grid=None, fileformat=None,
+             filename_similarity_measure=None, *args, **kwds):
         """
         Save the ClimateNetwork object to files.
 
@@ -193,8 +192,6 @@ def save(self, filename_network, filename_grid=None,
             object is to be stored.
         :arg str filename_grid:  The name of the file where the GeoGrid object
             is to be stored (including ending).
-        :arg str filename_similarity_measure:  The name of the file where the
-            similarity measure matrix is to be stored.
         :arg str fileformat: the format of the file (if one wants to override
             the format determined from the filename extension, or the filename
             itself is a stream). ``None`` means auto-detection.  Possible
@@ -205,6 +202,8 @@ def save(self, filename_network, filename_grid=None,
             (DIMACS format), ``"edgelist"``, ``"edges"`` or ``"edge"`` (edge
             list), ``"adjacency"`` (adjacency matrix), ``"pickle"`` (Python
             pickled format), ``"svg"`` (Scalable Vector Graphics).
+        :arg str filename_similarity_measure:  The name of the file where the
+            similarity measure matrix is to be stored.
         """
         #  Store GeoNetwork
         GeoNetwork.save(self, filename_network=filename_network,

src/pyunicorn/climate/coupled_climate_network.py

@@ -146,8 +146,8 @@ def __str__(self):
         """
         Return a string representation of CoupledClimateNetwork object.
         """
-        return f'CoupledClimateNetwork:\n{ClimateNetwork.__str__(self)}\
-        	\nN1: {self.N_1}\nN2: self.N_2'
+        return f'CoupledClimateNetwork:\n{ClimateNetwork.__str__(self)} \
+                \nN1: {self.N_1}\nN2: self.N_2'
 
     #
     #  Define methods for handling the coupled network

src/pyunicorn/climate/eventseries_climatenetwork.py

@@ -112,9 +112,9 @@ def __init__(self, data, method='ES', taumax=np.inf, lag=0.0,
 
         method_types = ['ES', 'ECA', 'ES_pval', 'ECA_pval']
         if method not in method_types:
-            raise IOError(f"Method input must be: {method_types[0]},\
-            		   {method_types[1]},\
-                          {method_types[2]}, or {method_types[3]}!")
+            raise IOError(f"Method input must be:"
+                          f"{method_types[0]}, {method_types[1]},"
+                          f"{method_types[2]}, or {method_types[3]}!")
 
         etypes = ["directed", "symmetric", "antisym", "mean", "max", "min"]
         if symmetrization not in etypes:
@@ -125,7 +125,7 @@ def __init__(self, data, method='ES', taumax=np.inf, lag=0.0,
 
         self.__method = method
         self.__symmetry = symmetrization
-        self.directed = (self.__symmetry == "directed")
+        self.directed = self.__symmetry == "directed"
         self.__es_type = method
         self.__window_type = window_type
         self.__p_value = p_value

src/pyunicorn/climate/map_plots.py

@@ -22,8 +22,6 @@
 
 import os
 import glob
-# time handling
-# import datetime
 
 import numpy as np
 
@@ -203,7 +201,7 @@ def generate_multiple_map_plots(self, map_names, map_scales, title_on=True,
         list of dictionaries. Stores the plots in the file indicated by
         filename in the current directory.
         """
-        for k in range(len(self.map_mult_data)):
+        for k, map_data in enumerate(self.map_mult_data):
             #  Set resources
             resources = self.resources
 
@@ -225,7 +223,7 @@ def generate_multiple_map_plots(self, map_names, map_scales, title_on=True,
             #  Generate map plots
             #
 
-            for dataset in self.map_mult_data[k]:
+            for dataset in map_data:
                 #  Set title
                 if labels_on:
                     resources.lbTitleString = dataset["title"]

src/pyunicorn/climate/rainfall.py

@@ -242,7 +242,7 @@ def calculate_top_events(rainfall, event_threshold):
 
         up_mask = rainfall <= onelist[uplimit-1]
 
-        no_rain_mask = (rainfall != 0)
+        no_rain_mask = rainfall != 0
 
         final_mask = down_mask & up_mask & no_rain_mask
 

src/pyunicorn/climate/tsonis.py

@@ -121,8 +121,9 @@ def __str__(self):
         Local connections filtered out: False
         Use only data points from winter months: False
         """
-        return (f'TsonisClimateNetwork:\n{ClimateNetwork.__str__(self)}\n' +
-        f'Use only data points from winter months: {self.winter_only()}')
+        return (f'TsonisClimateNetwork:\n{ClimateNetwork.__str__(self)}\n'
+                f'Use only data points from winter months: '
+                f'{self.winter_only()}')
 
     #
     #  Methods for testing purposes

src/pyunicorn/core/data.py

@@ -115,10 +115,9 @@ def __str__(self):
         if self.file_name:
             self.print_data_info()
 
-        return ('Data: %i grid points, %i measurements.\n'
-                'Geographical boundaries:\n%s') % (
-                    self.grid.N, self.grid.n_grid_points,
-                    self.grid.print_boundaries())
+        return (f"Data: {self.grid.N} grid points, "
+                f"{self.grid.n_grid_points} measurements.\n"
+                f"Geographical boundaries:\n{self.grid.print_boundaries()}")
 
     def set_silence_level(self, silence_level):
         """
@@ -397,7 +396,7 @@ def print_data_info(self):
             print(name + ":", getattr(f, name))
         print("Variables (size):")
         for name, obj in f.variables.items():
-            print("%s (%i)" % (name, len(obj)))
+            print(f"{name} ({len(obj)})")
         f.close()
 
     def observable(self):
@@ -592,8 +591,7 @@ def rescale(array, var_type):
             array /= scale_factor
             scaled_array = array.astype('uint8')
         else:
-            print("Data type %s variable %s for rescaling array "
-                  "not supported!" % var_type)
+            print(f"Data type {var_type} not supported!")
             scale_factor = 1.
             add_offset = 0.
 

src/pyunicorn/core/geo_grid.py

@@ -88,8 +88,8 @@ def __str__(self):
         """
         Return a string representation of the GeoGrid object.
         """
-        return 'GeoGrid: %i grid points, %i timesteps.' % (
-            self._grid_size['space'], self._grid_size['time'])
+        return (f"GeoGrid: {self._grid_size['space']} grid points, "
+                f"{self._grid_size['time']} timesteps.")
 
     def clear_cache(self):
         """

src/pyunicorn/core/geo_network.py

@@ -1044,9 +1044,9 @@ def boundary(self, nodes, geodesic=True, gap=0.0):
             import stripack  # @UnresolvedImport
             # tries to import stripack.so which must have been compiled with
             # f2py -c -m stripack stripack.f90
-        except ImportError:
-            raise RuntimeError("NOTE: stripack.so not available, boundary() \
-                               won't work.")
+        except ImportError as err:
+            raise RuntimeError("NOTE: stripack.so not available, "
+                               "boundary() won't work.") from err
 
         N = self.N
         nodes_set = set(nodes)
@@ -1174,8 +1174,7 @@ def boundary(self, nodes, geodesic=True, gap=0.0):
                     rep = self.cartesian2latlon((pos1+pos2)/2)
                     mind2 = d2
             latlon_shape.append(self.cartesian2latlon(partial_shape[-1]))
-            for it, _ in enumerate(partial_fullshape):
-                pos1 = partial_fullshape[it]
+            for pos1 in partial_fullshape:
                 latlon_fullshape.append(self.cartesian2latlon(pos1))
 
             boundary.append(partial_boundary)

src/pyunicorn/core/grid.py

@@ -99,8 +99,8 @@ def __str__(self):
         """
         Return a string representation of the Grid object.
         """
-        return 'Grid: %i grid points, %i timesteps.' % (
-            self._grid_size['space'], self._grid_size['time'])
+        return (f"Grid: {self._grid_size['space']} grid points, "
+                f"{self._grid_size['time']} timesteps.")
 
     #
     #  Functions for loading and saving the Grid object
@@ -114,9 +114,8 @@ def save(self, filename):
             (including ending).
         """
         try:
-            f = open(filename, 'wb')
-            pickle.dump(self, f)
-            f.close()
+            with open(filename, 'wb') as f:
+                pickle.dump(self, f)
         except IOError:
             print("An error occurred while saving Grid instance to "
                   f"pickle file {filename}")
@@ -132,10 +131,8 @@ def Load(filename):
         :return: :class:`Grid` instance.
         """
         try:
-            f = open(filename, 'rb')
-            grid = pickle.load(f)
-            f.close()
-
+            with open(filename, 'rb') as f:
+                grid = pickle.load(f)
             return grid
         except IOError:
             print("An error occurred while loading Grid instance from "

src/pyunicorn/core/interacting_networks.py

@@ -24,7 +24,7 @@
 import numpy as np
 from numpy import random
 
-from ._ext.types import to_cy, ADJ, NODE, WEIGHT, DWEIGHT, FIELD, DFIELD
+from ._ext.types import to_cy, ADJ, NODE, DWEIGHT, DFIELD
 from ._ext.numerics import _randomlySetCrossLinks, _randomlyRewireCrossLinks, \
     _cross_transitivity, _nsi_cross_transitivity, _cross_local_clustering, \
     _nsi_cross_local_clustering
@@ -805,8 +805,8 @@ def cross_global_clustering(self, node_list1, node_list2):
             subnetworks.
         """
         #  Get cross local clustering sequences
-        cc = InteractingNetworks.cross_local_clustering(self, node_list1,
-         node_list2)
+        cc = InteractingNetworks.cross_local_clustering(self,
+                                                        node_list1, node_list2)
         return cc.mean()
 
     def cross_global_clustering_sparse(self, node_list1, node_list2):
@@ -995,7 +995,7 @@ def cross_average_path_length(self, node_list1, node_list2,
             subnetworks.
         """
         path_lengths = InteractingNetworks.cross_path_lengths(
-        self, node_list1, node_list2, link_attribute)
+            self, node_list1, node_list2, link_attribute)
 
         return self._calculate_general_average_path_length(
             path_lengths, internal=False)
@@ -1427,8 +1427,9 @@ def cross_closeness(self, node_list1, node_list2, link_attribute=None):
         :rtype: 1D arrays [index]
         :return: the cross closeness sequence.
         """
-        path_lengths = InteractingNetworks.cross_path_lengths(self, node_list1,
-         node_list2, link_attribute)
+        path_lengths = InteractingNetworks.cross_path_lengths(
+            self, node_list1, node_list2, link_attribute)
+
         return self._calculate_general_closeness(path_lengths, internal=False)
 
     def internal_closeness(self, node_list, link_attribute=None):