relative imports again

measprocess/__init__.py

-from measprocess.plotting import plot_locations_osm, plot_street_nodes
+from .plotting import plot_locations_osm, plot_street_nodes
 
-from measprocess.simulation import TCP_on_lines, ShadowFading
+from .simulation import TCP_on_lines, ShadowFading
 
-from measprocess.rtr.fetch import (
+from .rtr.process import (
+    process,
+    interpolate_signal_loc
+)
+
+from .rtr.fetch import (
     rtr_details,
     rtr_overview
 )
 
-from measprocess.nemo.process import (
+from .nemo.process import (
     link_dataframes
 )
 
-from measprocess.geospatial.fetch import (
+from .geospatial.fetch import (
     geoseries_streets,
     geoseries_buildings,
     pull_from_geodatenviewer_list,
     pull_from_geodatenviewer_meas
 )
 
-from measprocess.geospatial.process import (
+from .geospatial.process import (
     project_onto_streets,
     crop_geoseries_by_bounds,
     interpolate_series_at_distance,

measprocess/rtr/__init__.py

+from .process import (
+    process,
+    interpolate_signal_loc
+)

measprocess/rtr/process.py

@@ -70,13 +70,13 @@ def interpolate_signal_loc(path_processed_signal, path_processed_location, path_
     :param path_processed_location: path of location.csv
     :path_processed_final: path of final.csv where the returned dataframe is stored, this is optional, default is None
 
-    :return df_signal_final: pandas dataframe containing all not NaN values from signal.csv, 
+    :return df_signal_final: pandas dataframe containing all not NaN values from signal.csv,
                              including interpolated longitude and latitude for each value
     '''
 
     df_signal = pd.read_csv(path_processed_signal)
     df_loc = pd.read_csv(path_processed_location)
-    
+
     df_signal = df_signal[df_signal['cat_technology']=='4G'] #select only 4G techonology
     df_signal = df_signal[df_signal['lte_rsrp'].notna()] # remove all where lte_rsrp value is missing
 
@@ -117,7 +117,7 @@ def interpolate_signal_loc(path_processed_signal, path_processed_location, path_
         df_signal_selected['y'] = ynew
 
         df_signal_final.append(df_signal_selected)
-    
+
     df_signal_final = pd.concat(df_signal_final, ignore_index=True)
     xy = gpd.GeoDataFrame(geometry=gpd.points_from_xy(df_signal_final.x, df_signal_final.y)).set_crs('EPSG:31287').to_crs('EPSG:4326')
     df_signal_final.drop(['x','y'], axis=1, inplace=True) #remove x and y in epsg:31287
@@ -128,4 +128,4 @@ def interpolate_signal_loc(path_processed_signal, path_processed_location, path_
     if path_processed_final!=None:
         df_signal_final.to_csv(path_processed_final, index=False)
 
-    return df_signal_final
\ No newline at end of file
+    return df_signal_final

setup.py

 import pathlib
 from setuptools import setup
 
+import measprocess as mpc
+
 # The directory containing this file
 HERE = pathlib.Path(__file__).parent