Fix minor documentation issues

- Add explanation of columns in returned data frames
- Fix formatting of docstring for proper display on website
- Fix wrong column name in return of compute_individual_voronoi_polygons

Author: schroedtert

pedpy/methods/acceleration_calculator.py

@@ -1,6 +1,6 @@
 """Module containing functions to compute accelerations."""
 
-from typing import Optional, Tuple
+from typing import Optional
 
 import numpy as np
 import numpy.typing as npt
@@ -112,8 +112,8 @@ def compute_individual_acceleration(
 
     Returns:
         DataFrame containing the columns 'id', 'frame', and 'acceleration' in
-        'm/s^2', 'a_x' and 'a_y' with the speed components in x and y direction
-        if :code:`compute_acceleration_components` is True
+        :math:`m/s^2`, 'a_x' and 'a_y' with the acceleration components
+        in x and y direction if :code:`compute_acceleration_components` is True
     """
     df_movement = _compute_individual_movement_acceleration(
         traj_data=traj_data,
@@ -136,7 +136,7 @@ def compute_mean_acceleration_per_frame(
     traj_data: TrajectoryData,
     individual_acceleration: pd.DataFrame,
     measurement_area: MeasurementArea,
-) -> Tuple[pd.DataFrame, pd.DataFrame]:
+) -> pd.DataFrame:
     r"""Compute mean acceleration per frame inside a given measurement area.
 
     Computes the mean acceleration :math:`a_{mean}(t)` inside the measurement
@@ -166,7 +166,8 @@ def compute_mean_acceleration_per_frame(
             acceleration is computed
 
     Returns:
-        DataFrame containing the columns 'frame' and 'acceleration' in 'm/s^2'
+        DataFrame containing the columns 'frame' and 'acceleration' in
+        :math:`m/s^2`
     """
     if len(individual_acceleration.index) < len(traj_data.data.index):
         raise AccelerationError(
@@ -240,7 +241,8 @@ def compute_voronoi_acceleration(
             acceleration should be computed
 
     Returns:
-        DataFrame containing the columns 'frame' and 'acceleration' in 'm/s^2'
+        DataFrame containing the columns 'frame' and 'acceleration' in
+        :math:`m/s^2`
     """
     if len(individual_acceleration.index) < len(
         individual_voronoi_intersection.index

pedpy/methods/density_calculator.py

@@ -113,9 +113,10 @@ def compute_voronoi_density(
     Returns:
         DataFrame containing the columns 'id' and 'density' in :math:`1/m^2`,
         DataFrame containing the columns: 'id', 'frame', 'polygon' which
-        contains the Voronoi polygon of the pedestrian, 'intersection' which
-        contains the intersection area of the Voronoi polygon and the given
-        measurement area.
+        contains the Voronoi polygon of the pedestrian, 'density' in
+        :math:`1/m^2` which contains the individual density of the pedestrian,
+        'intersection' which contains the intersection area of the Voronoi
+        polygon and the given measurement area.
 
     """
     df_intersecting = compute_intersecting_polygons(
@@ -265,7 +266,10 @@ def compute_line_density(
             the species of every pedestrian intersecting the line,
             result from :func:`~speed_calculator.compute_species`
     Returns:
-        Dataframe containing columns 'frame', 'p_sp+1', 'p_sp-1', 'density'
+        Dataframe containing columns 'frame', 'p_sp+1' which contains the
+        density in :math:`1/m^2` for species +1, 'p_sp-1' which contains the
+        density in :math:`1/m^2` for species -1, 'density' which contains the
+        density at the line in :math:`1/m^2`.
     """
     if not is_species_valid(
         species=species,

pedpy/methods/flow_calculator.py

@@ -316,7 +316,10 @@ def compute_line_flow(
             species of every pedestrian intersecting the line,
             result from :func:`~speed_calculator.compute_species`
     Returns:
-        Dataframe containing columns 'frame', 'j_sp+1', 'j_sp-1', 'flow'
+        Dataframe containing columns 'frame', 'j_sp+1' which contains the flow
+        in :math:`1/s` for species +1, 'j_sp-1' which contains the flow
+        in :math:`1/s` for species -1, 'flow' which contains the total flow at
+        the line in :math:`1/s`.
     """
     _validate_inputs(
         individual_voronoi_polygons, measurement_line, individual_speed, species

pedpy/methods/method_utils.py

@@ -483,8 +483,8 @@ def compute_time_distance_line(
         measurement_line (MeasurementLine): line which is crossed
 
     Returns:
-        DataFrame containing 'id', 'frame', 'time' (seconds until
-        crossing),  and 'distance' (meters to measurement line)
+        DataFrame containing 'id', 'frame', 'distance' (meters to measurement
+        line), and 'time' (seconds until crossing)
     """
     df_distance_time = traj_data.data[[ID_COL, FRAME_COL, POINT_COL]].copy(
         deep=True
@@ -575,7 +575,7 @@ def compute_individual_voronoi_polygons(
 
     Returns:
         DataFrame containing the columns 'id', 'frame','polygon' (
-        :class:`shapely.Polygon`), and 'individual_density' in :math:`1/m^2`.
+        :class:`shapely.Polygon`), and 'density' in :math:`1/m^2`.
     """
     dfs = []
 
@@ -1434,11 +1434,10 @@ def is_individual_speed_valid(
         measurement_line (MeasurementLine): measurement line
 
     Returns:
-        DATA_CORRECT if all needed data is provided
-            by the individual speed dataframe,
-        COLUMN_MISSING if there is a column missing,
-        ENTRY_MISSING if there is no matching entry
-            for a frame where polygon and line intersect.
+        DATA_CORRECT if all needed data is provided by the individual speed
+        dataframe, COLUMN_MISSING if there is a column missing, ENTRY_MISSING
+        if there is no matching entry for a frame where polygon and line
+        intersect.
     """
     if not all(
         column in individual_speed.columns

pedpy/methods/profile_calculator.py

@@ -920,8 +920,8 @@ def compute_grid_cell_polygon_intersection_area(
 
     Returns:
         Tuple containing first the grid cell-polygon intersection areas, and
-            second the reordered data by 'frame', which needs to be used in
-            the next steps.
+        second the reordered data by 'frame', which needs to be used in
+        the next steps.
     """
     (
         grid_intersections_area,

pedpy/methods/spatial_analysis.py

@@ -45,10 +45,9 @@ def compute_pair_distribution_function(
 
 
     Returns:
-        Tuple[np.ndarray, np.ndarray]: A tuple of two numpy arrays. The first
-            array contains the bin edges (excluding the first bin edge), and
-            the second array contains the values of the pair-distribution
-            function :math:`g(r)` for each bin.
+        A tuple of two numpy arrays. The first array contains the bin edges
+        (excluding the first bin edge), and the second array contains the values
+        of the pair-distribution function :math:`g(r)` for each bin.
     """
     data_df = traj_data.data
 

pedpy/methods/speed_calculator.py

@@ -560,7 +560,10 @@ def compute_line_speed(
             the species of every pedestrian intersecting the line,
             result from :func:`~speed_calculator.compute_species`
     Returns:
-        Dataframe containing columns 'frame', 's_sp+1', 's_sp-1', 'speed'
+        Dataframe containing columns 'frame', 's_sp+1' which contains the
+        speed in :math:`m/s` for species +1, 's_sp-1' which contains the
+        speed in :math:`m/s` for species -1, 'speed' which contains the
+        density at the line in :math:`1/m^2`.
     """
     _validate_inputs(
         individual_voronoi_polygons, measurement_line, individual_speed, species