CLN: black format

docs/conf.py

@@ -150,7 +150,15 @@ def setup(app):
 # default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
 # 'searchbox.html']``.
 #
-html_sidebars = {"**": ["about.html", "navigation.html", "relations.html", "searchbox.html", "donate.html",]}
+html_sidebars = {
+    "**": [
+        "about.html",
+        "navigation.html",
+        "relations.html",
+        "searchbox.html",
+        "donate.html",
+    ]
+}
 
 # only defined in 'Alabaster' html_theme
 # html_theme_options = {

tests/analysis/test_transport_mode_identification.py

@@ -10,7 +10,7 @@
 
 class TestTransportModeIdentification:
     def test_check_empty_dataframe(self):
-        """Assert that the method does not work for empty DataFrames 
+        """Assert that the method does not work for empty DataFrames
         (but that the rest works fine, e.g., method signature).
         """
         tpls_file = os.path.join("tests", "data", "triplegs_transport_mode_identification.csv")
@@ -20,7 +20,7 @@ def test_check_empty_dataframe(self):
             empty_frame.as_triplegs.predict_transport_mode(method="simple-coarse")
 
     def test_simple_coarse_identification_no_crs(self):
-        """Assert that the simple-coarse transport mode identification throws the correct 
+        """Assert that the simple-coarse transport mode identification throws the correct
         warning and and yields the correct results for WGS84.
         """
         tpls_file = os.path.join("tests", "data", "triplegs_transport_mode_identification.csv")

tests/visualization/test_locations.py

@@ -57,4 +57,4 @@ def test_parameter(self, test_data):
         # plot only location
         locs.as_locations.plot(out_filename=tmp_file, plot_osm=True)
         assert os.path.exists(tmp_file)
-        os.remove(tmp_file)
+        os.remove(tmp_file)

tests/visualization/test_positionfixes.py

@@ -17,4 +17,4 @@ def test_positionfixes_plot(self):
         pfs = ti.read_positionfixes_csv(pfs_file, sep=";", index_col="id", crs="EPSG:4326")
         pfs.as_positionfixes.plot(out_filename=tmp_file, plot_osm=False)
         assert os.path.exists(tmp_file)
-        os.remove(tmp_file)
+        os.remove(tmp_file)

tests/visualization/test_staypoints.py

@@ -43,4 +43,4 @@ def test_parameter(self, test_data):
         # with osm
         stps.as_staypoints.plot(out_filename="staypoints_plot", plot_osm=True)
         assert os.path.exists("staypoints_plot.png")
-        os.remove("staypoints_plot.png")
+        os.remove("staypoints_plot.png")

tests/visualization/test_triplegs.py

@@ -49,4 +49,4 @@ def test_parameter(self, test_data):
         # test plot_osm
         tpls.as_triplegs.plot(out_filename=tmp_file, plot_osm=True)
         assert os.path.exists(tmp_file)
-        os.remove(tmp_file)
+        os.remove(tmp_file)

trackintel/analysis/tracking_quality.py

@@ -16,7 +16,7 @@ def temporal_tracking_quality(source, granularity="all"):
     granularity : {"all", "day", "week", "weekday", "hour"}
         The level of which the tracking quality is calculated. The default "all" returns
         the overall tracking quality; "day" the tracking quality by days; "week" the quality
-        by weeks; "weekday" the quality by day of the week (e.g, Mondays, Tuesdays, etc.) and 
+        by weeks; "weekday" the quality by day of the week (e.g, Mondays, Tuesdays, etc.) and
         "hour" the quality by hours.
 
     Returns
@@ -28,11 +28,11 @@ def temporal_tracking_quality(source, granularity="all"):
     -----
     Requires at least the following columns:
     ``['user_id', 'started_at', 'finished_at']``
-    which means the function supports trackintel ``staypoints``, ``triplegs``, ``trips`` and ``tours`` 
+    which means the function supports trackintel ``staypoints``, ``triplegs``, ``trips`` and ``tours``
     datamodels and their combinations (e.g., staypoints and triplegs sequence).
-    
+
     The temporal tracking quality is the ratio of tracking time and the total time extent. It is
-    calculated and returned per-user in the defined ``granularity``. The possible time extents of 
+    calculated and returned per-user in the defined ``granularity``. The possible time extents of
     the different granularities are different:
 
     - ``all`` considers the time between the latest "finished_at" and the earliest "started_at";

trackintel/geogr/distances.py

@@ -15,46 +15,46 @@
 def calculate_distance_matrix(X, Y=None, dist_metric="haversine", n_jobs=0, **kwds):
     """
     Calculate a distance matrix based on a specific distance metric.
-    
+
     If only X is given, the pair-wise distances between all elements in X are calculated. If X and Y are given, the
     distances between all combinations of X and Y are calculated. Distances between elements of X and X, and distances
     between elements of Y and Y are not calculated.
 
     Parameters
     ----------
     X : GeoDataFrame (as trackintel staypoints or triplegs)
-        
+
     Y : GeoDataFrame (as trackintel staypoints or triplegs), optional
-        
+
     dist_metric: {'haversine', 'euclidean', 'dtw', 'frechet'}
-        The distance metric to be used for calculating the matrix. 
-        
-        For staypoints, common choice is 'haversine' or 'euclidean'. This function wraps around 
-        the ``pairwise_distance`` function from scikit-learn if only `X` is given and wraps around the 
-        ``scipy.spatial.distance.cdist`` function if X and Y are given. 
+        The distance metric to be used for calculating the matrix.
+
+        For staypoints, common choice is 'haversine' or 'euclidean'. This function wraps around
+        the ``pairwise_distance`` function from scikit-learn if only `X` is given and wraps around the
+        ``scipy.spatial.distance.cdist`` function if X and Y are given.
         Therefore the following metrics are also accepted:
-        
+
         via ``scikit-learn``: `[‘cityblock’, ‘cosine’, ‘euclidean’, ‘l1’, ‘l2’, ‘manhattan’]`
-        
+
         via ``scipy.spatial.distance``: `[‘braycurtis’, ‘canberra’, ‘chebyshev’, ‘correlation’, ‘dice’, ‘hamming’, ‘jaccard’,
         ‘kulsinski’, ‘mahalanobis’, ‘minkowski’, ‘rogerstanimoto’, ‘russellrao’, ‘seuclidean’, ‘sokalmichener’,
         ‘sokalsneath’, ‘sqeuclidean’, ‘yule’]`
-        
-        For triplegs, common choice is 'dtw' or 'frechet'. This function uses the implementation 
+
+        For triplegs, common choice is 'dtw' or 'frechet'. This function uses the implementation
         from similaritymeasures.
-        
+
     n_jobs: int
-        Number of cores to use: 'dtw', 'frechet' and all distance metrics from `pairwise_distance` (only available 
+        Number of cores to use: 'dtw', 'frechet' and all distance metrics from `pairwise_distance` (only available
         if only X is given) are parallelized.
-         
-    **kwds: 
+
+    **kwds:
         optional keywords passed to the distance functions.
 
     Returns
     -------
     D: np.array
         matrix of shape (len(X), len(X)) or of shape (len(X), len(Y)) if Y is provided.
-        
+
     """
     geom_type = X.geometry.iat[0].geom_type
     if Y is None:
@@ -171,7 +171,7 @@ def meters_to_decimal_degrees(meters, latitude):
         The meters to convert to degrees.
 
     latitude : float
-        As the conversion is dependent (approximatively) on the latitude where 
+        As the conversion is dependent (approximatively) on the latitude where
         the conversion happens, this needs to be specified. Use 0 for the equator.
 
     Returns

trackintel/geogr/point_distances.py

@@ -4,7 +4,7 @@
 def haversine_dist(lon_1, lat_1, lon_2, lat_2, r=6371000):
     """
     Compute the great circle or haversine distance between two coordinates in WGS84.
-    
+
     Serialized version of the haversine distance.
 
     Parameters

trackintel/io/dataset_reader.py

@@ -32,7 +32,7 @@ def read_geolife(geolife_path):
     -------
     gdf: GeoDataFrame (as trackintel positionfixes)
         Contains all loaded geolife positionfixes
-        
+
     labels: dict
         Dictionary with the available (optional) mode labels.
 
@@ -171,16 +171,16 @@ def geolife_add_modes_to_triplegs(
     ----------
     tpls_in : GeoDataFrame (as trackintel triplegs)
         Geolife triplegs.
-        
+
     labels : dictionary
         Geolife labels as provided by the trackintel `read_geolife` function.
-        
+
     ratio_threshold : float, default 0.5
         How much a label needs to overlap a tripleg to assign a the to this tripleg.
-        
+
     max_triplegs : int, default 20
         Number of neighbors that are considered in the search for matching triplegs.
-        
+
     max_duration_tripleg : float, default 7 * 24 * 60 * 60 (seconds)
         Used for a primary filter. All triplegs that are further away in time than 'max_duration_tripleg' from a
         label won't be considered for matching.
@@ -260,10 +260,10 @@ def _calc_overlap_for_candidates(candidates, tpls_this, labels_this, ratio_thres
 
     tpls_this : GeoDataFrame (as trackintel triplegs)
         triplegs of a single user
-        
+
     labels_this : DataFrame
         labels of a single user
-        
+
     ratio_threshold : float, optional
         How much a label needs to overlap a tripleg to assign a the to this tripleg.