More linting fixes

netatmoqc/apps/clustering/app.py

@@ -210,7 +210,9 @@ def generate_control_card():
                         value=5,
                         step=1,
                         required=True,
-                        style=dict(display="table-cell",),
+                        style=dict(
+                            display="table-cell",
+                        ),
                     ),
                 ],
                 style=dict(display="table-cell"),
@@ -233,7 +235,9 @@ def generate_control_card():
                         min=2,
                         value=5,
                         step=1,
-                        style=dict(display="table-cell",),
+                        style=dict(
+                            display="table-cell",
+                        ),
                     ),
                 ],
                 style=dict(display="table-cell"),
@@ -250,7 +254,9 @@ def generate_control_card():
                         inputMode="numeric",
                         min=0.0,
                         value=10.0,
-                        style=dict(display="table-cell",),
+                        style=dict(
+                            display="table-cell",
+                        ),
                     ),
                 ],
                 style=dict(display="table-cell"),
@@ -391,8 +397,14 @@ def indicator(text, id_value):
         children=[
             html.Div(
                 children=[
-                    html.P(id=id_value, className="indicator_value",),
-                    html.P(text, className="indicator_text",),
+                    html.P(
+                        id=id_value,
+                        className="indicator_value",
+                    ),
+                    html.P(
+                        text,
+                        className="indicator_text",
+                    ),
                 ],
             ),
         ],
@@ -423,7 +435,11 @@ def generate_right_column_elements():
     children = [
         html.Div(
             id="clustering_plot_div",
-            children=[dcc.Graph(id="clustering_plot",)],
+            children=[
+                dcc.Graph(
+                    id="clustering_plot",
+                )
+            ],
         ),
         html.Div(
             id="clustered_data_table_card",
@@ -438,7 +454,9 @@ def generate_right_column_elements():
                     sort_action="native",
                     filter_action="native",
                     # Styling
-                    style_cell=dict(padding="10px",),
+                    style_cell=dict(
+                        padding="10px",
+                    ),
                     style_header=dict(
                         backgroundColor="rgb(2,21,70)",
                         color="white",
@@ -486,7 +504,10 @@ app.layout = html.Div(
             children=[
                 generate_indicators(),
                 html.B("Visualisation of Clusters"),
-                html.Div(id="calculated_dist", children=[],),
+                html.Div(
+                    id="calculated_dist",
+                    children=[],
+                ),
                 html.Hr(),
                 dcc.Loading(
                     # Embed the the right-hand side column inside a dcc.Loading
@@ -674,7 +695,9 @@ def run_clustering_and_make_plot(
     time_start_clustering = time.time()
     logger.info("Running %s...", method)
     df = cluster_netatmo_obs(
-        df=df, config=clustering_config, calc_silhouette_samples=True,
+        df=df,
+        config=clustering_config,
+        calc_silhouette_samples=True,
     )
     df = sort_df_by_cluster_size(df)
     time_end_clustering = time.time()

netatmoqc/apps/scattergeo_timeseries/app.py

@@ -47,7 +47,10 @@ def description_card():
         children=[
             html.H5("NetAtmo Data Explorer"),
             html.H3("NetAtmo Data Explorer Dashboard"),
-            html.Div(id="intro", children="An aid to explore NetAtmo data",),
+            html.Div(
+                id="intro",
+                children="An aid to explore NetAtmo data",
+            ),
         ],
         style={"text-align": "center"},
     )

netatmoqc/clustering.py

@@ -307,7 +307,9 @@ def run_clustering_on_df(
             metric="precomputed",
         ).fit(distance_matrix)
     logger.debug(
-        "      * Done with %s. Elapsed: %.2fs", method, time.time() - tstart,
+        "      * Done with %s. Elapsed: %.2fs",
+        method,
+        time.time() - tstart,
     )
     # Update df with cluster label info. It is important that this is done
     # right before calling filter_outliers, as the filter_outliers function

netatmoqc/config_parser.py

@@ -357,7 +357,9 @@ def parsed_path(path):
 with config_section("general") as section:
     # in/our dirs
     config_metadata.register(
-        "data_rootdir", default=".", astype=parsed_path,
+        "data_rootdir",
+        default=".",
+        astype=parsed_path,
     )
     config_metadata.register(
         "outdir",

netatmoqc/domains.py

@@ -420,7 +420,10 @@ class Domain:
             )
             # (d) Set _grid attr
             return DomainGrid(
-                xaxis=grid_xaxis, yaxis=grid_yaxis, proj=proj, tstep=tstep,
+                xaxis=grid_xaxis,
+                yaxis=grid_yaxis,
+                proj=proj,
+                tstep=tstep,
             )
 
         self._grid = init_grid(ngrid_lonlat, grid_spacing, ezone_ngrid)

netatmoqc/hollow_symmetric_matrix.py

@@ -588,7 +588,9 @@ class HollowSymmetricMatrix(np.lib.mixins.NDArrayOperatorsMixin):
             new_data = self[indices[:, np.newaxis], indices]
 
         return self.__class__(
-            new_data, dtype=self.dtype, optimize_mode=self.optimize_mode,
+            new_data,
+            dtype=self.dtype,
+            optimize_mode=self.optimize_mode,
         )
 
     def convert_to_dense_storage(self):

netatmoqc/load_data.py

@@ -354,7 +354,11 @@ def rm_overlapping_stations(df):
     overlapping_stations = (
         df[["id", "lat", "lon"]]
         .round(6)
-        .groupby(["lat", "lon"], as_index=False, sort=False,)
+        .groupby(
+            ["lat", "lon"],
+            as_index=False,
+            sort=False,
+        )
         .filter(lambda grp: len(grp["id"].unique()) != 1)["id"]
         .unique()
     )
@@ -397,7 +401,11 @@ def remove_duplicates_within_cycle(df, dtg):
         msg += "Keeping only the one closest to the DTG: "
         msg += "%s obs now became %s"
         logger.debug(
-            msg, n_stations_with_duplicates, dtg, orig_nobs, new_nobs,
+            msg,
+            n_stations_with_duplicates,
+            dtg,
+            orig_nobs,
+            new_nobs,
         )
     return df
 

netatmoqc/outlier_removal.py

@@ -182,7 +182,10 @@ def _filter_outliers_iterative(
         # We use "-2" as a "removed by refining methods" flag
         n_removed_old = np.count_nonzero(df[:, -1] == -2)
         df = _filter_outliers_iterative_one_iter(
-            df, max_n_stdev_around_mean, truncate=trunc_perc, weights=weights,
+            df,
+            max_n_stdev_around_mean,
+            truncate=trunc_perc,
+            weights=weights,
         )
         n_removed_new = np.count_nonzero(df[:, -1] == -2)
         n_removed_this_iter = n_removed_new - n_removed_old

netatmoqc/plots.py

@@ -238,8 +238,16 @@ def get_domain_fig(
             traceorder="reversed",
         ),
         geo=dict(
-            lataxis=dict(range=latrange, showgrid=True, dtick=10,),
-            lonaxis=dict(range=lonrange, showgrid=True, dtick=15,),
+            lataxis=dict(
+                range=latrange,
+                showgrid=True,
+                dtick=10,
+            ),
+            lonaxis=dict(
+                range=lonrange,
+                showgrid=True,
+                dtick=15,
+            ),
         ),
     )
 
@@ -436,7 +444,10 @@ def make_clustering_fig(df, domain, **kwargs):
             trace_visible = True
 
         trace = get_obs_scattergeo_trace(
-            cluster_df, trace_name=label, marker=marker, visible=trace_visible,
+            cluster_df,
+            trace_name=label,
+            marker=marker,
+            visible=trace_visible,
         )
         fig.add_trace(trace)
 
@@ -526,7 +537,9 @@ def generate_single_frame(df, dataset_var, frame_duration, frame=None):
         opacity=0.5,
         line=dict(color="black", width=0.25),
         colorbar=dict(
-            titleside="right", ticks="outside", showticksuffix="last",
+            titleside="right",
+            ticks="outside",
+            showticksuffix="last",
         ),
     )
     trace = get_obs_scattergeo_trace(df, marker=marker)
@@ -581,7 +594,10 @@ def init_fig_dict(domain, dataset_var, frame_duration):
                     args=[
                         None,
                         dict(
-                            frame=dict(duration=frame_duration, redraw=True,),
+                            frame=dict(
+                                duration=frame_duration,
+                                redraw=True,
+                            ),
                             fromcurrent=True,
                             transition=dict(
                                 duration=frame_duration / 2,
@@ -615,9 +631,15 @@ def init_fig_dict(domain, dataset_var, frame_duration):
         y=0,
         pad=dict(b=10, t=50),
         currentvalue=dict(
-            font=dict(size=20), prefix="DTG: ", visible=True, xanchor="right",
+            font=dict(size=20),
+            prefix="DTG: ",
+            visible=True,
+            xanchor="right",
+        ),
+        transition=dict(
+            duration=frame_duration / 2,
+            easing="cubic-in-out",
         ),
-        transition=dict(duration=frame_duration / 2, easing="cubic-in-out",),
         steps=[],
     )
 

netatmoqc/save_data.py

@@ -284,7 +284,10 @@ def _input2output_single_dtg(
     logger = get_logger(__name__, loglevel)
 
     logger.debug(
-        "Reading data for %sDTG=%s%s...", logcolor.cyan, dtg, logcolor.reset,
+        "Reading data for %sDTG=%s%s...",
+        logcolor.cyan,
+        dtg,
+        logcolor.reset,
     )
     try:
         # read_netatmo_data_for_dtg will raise DataNotFoundError if
@@ -385,7 +388,9 @@ def netatmoqc_input2output(
         outdir = Path()
 
     logger.info(
-        "%sSaving selected observations...%s", logcolor.cyan, logcolor.reset,
+        "%sSaving selected observations...%s",
+        logcolor.cyan,
+        logcolor.reset,
     )
 
     outdir_csv = None
@@ -393,7 +398,10 @@ def netatmoqc_input2output(
     if save_csv:
         outdir_csv = Path(outdir) / "csv_files"
         logger.info(
-            "%s> CSV outdir:%s %s", logcolor.cyan, logcolor.reset, outdir_csv,
+            "%s> CSV outdir:%s %s",
+            logcolor.cyan,
+            logcolor.reset,
+            outdir_csv,
         )
     if save_obsoul:
         outdir_obsoul = Path(outdir) / "obsoul_files"