identation fixes

Author: mxaviersmp

pymove/utils/distances.py

@@ -112,8 +112,9 @@ def euclidean_distance_in_meters(
     >>> from pymove.utils.distances import euclidean_distance_in_meters
     >>> lat_fortaleza, lon_fortaleza = [-3.71839 ,-38.5434]
     >>> lat_quixada, lon_quixada = [-4.979224744401671, -39.056434302570665]
-    >>> euclidean_distance_in_meters(lat_fortaleza, lon_fortaleza,
-     lat_quixada, lon_quixada)
+    >>> euclidean_distance_in_meters(
+    >>>    lat_fortaleza, lon_fortaleza, lat_quixada, lon_quixada
+    >>> )
     151907.9670136588
     """
     y1 = utils.conversions.lat_to_y_spherical(lat=lat1)
@@ -157,17 +158,17 @@ def nearest_points(
     -------
     >>> from pymove.utils.distances import nearest_points
     >>> df_a
-                  lat          lon	           datetime	  id
-        0   39.984198   116.319322   2008-10-23 05:53:06   1
-        1   39.984224   116.319402   2008-10-23 05:53:11   1
+             lat          lon               datetime    id
+    0   39.984198   116.319322   2008-10-23 05:53:06     1
+    1   39.984224   116.319402   2008-10-23 05:53:11     1
     >>> df_b
-                  lat          lon              datetime  id
-        0   39.984211	116.319389   2008-10-23 05:53:16   1
-        1	39.984217	116.319422   2008-10-23 05:53:21   1
+              lat          lon              datetime    id
+    0   39.984211   116.319389   2008-10-23 05:53:16     1
+    1   39.984217   116.319422   2008-10-23 05:53:21     1
     >>> nearest_points(df_a,df_b)
-                  lat          lon              datetime   id
-        0	39.984211	116.319389   2008-10-23 05:53:16   1
-        1	39.984211	116.319389   2008-10-23 05:53:16   1
+              lat          lon              datetime    id
+    0   39.984211   116.319389   2008-10-23 05:53:16     1
+    1   39.984211   116.319389   2008-10-23 05:53:16     1
     """
     result = pd.DataFrame(columns=traj1.columns)
 
@@ -196,8 +197,7 @@ def medp(
     """
     Returns the Mean Euclidian Distance Predictive between two trajectories.
 
-    Considers only the spatial
-    dimension for the similarity measure.
+    Considers only the spatial dimension for the similarity measure.
 
     Parameters
     ----------
@@ -221,11 +221,11 @@ def medp(
     -------
     >>> from pymove.utils.distances import medp
     >>> traj_1
-                 lat          lon              datetime   id
-        0   39.98471   116.319865   2008-10-23 05:53:23   1
+                lat          lon           datetime     id
+    0   39.98471   116.319865   2008-10-23 05:53:23      1
     >>> traj_2
-                  lat        lon             datetime    id
-        0   39.984674   116.31981   2008-10-23 05:53:28  1
+                lat        lon             datetime     id
+    0   39.984674   116.31981   2008-10-23 05:53:28      1
     >>> medp(traj_1, traj_2)
     6.573431370981577e-05
     """
@@ -278,11 +278,11 @@ def medt(
     -------
     >>> from pymove.utils.distances import medt
     >>> traj_1
-                 lat          lon              datetime  id
-        0   39.98471   116.319865   2008-10-23 05:53:23   1
+             lat          lon              datetime  id
+    0   39.98471   116.319865   2008-10-23 05:53:23   1
     >>> traj_2
-                  lat         lon              datetime  id
-        0   39.984674   116.31981   2008-10-23 05:53:28   1
+              lat         lon              datetime  id
+    0   39.984674   116.31981   2008-10-23 05:53:28   1
     >>> medt(traj_1, traj_2)
     6.592419887747872e-05
     """