refactor(MNP): extra message when MNP finished

mnp/MNP.py

@@ -19,7 +19,7 @@ from mnp.preparation.aggregate_land_type_map import (
     read_aggregated_map,
 )
 from mnp.preparation.filter_incomplete_cells import filter_incomplete_cells
-from mnp.preparation.io_pathways import verify_user_input, InputPathway, OutputPathway
+from mnp.preparation.io_pathways import InputPathway, OutputPathway, verify_user_input
 from mnp.preparation.read_rasters_from_cover import read_rasters_from_cover
 from mnp.preparation.verify_spatial_data_coverage import verify_spatial_data_coverage
 from mnp.species_models.species_model import (
@@ -27,16 +27,16 @@ from mnp.species_models.species_model import (
     run_species_models,
 )
 from mnp.utils import (
-    log_file_to_cover,
     TEMP_DIR,
-    create_directories,
-    copy_input_file,
-    config_section_to_cover,
-    list_sources_destinations,
     add_dynamics_to_config,
+    config_section_to_cover,
+    copy_input_file,
+    create_directories,
     geo_profile_from_hsi,
-    log_start_completed,
     get_logger,
+    list_sources_destinations,
+    log_file_to_cover,
+    log_start_completed,
 )
 
 DATA_COVERAGE_TIF = "spatial_data_coverage.tif"
@@ -67,9 +67,11 @@ def prepare_input(parameters: MNPParameters, input_pathway: InputPathway) -> (
     Returns
     -------
     land_types:dict
-        The land type map as a dictionary with land type codes as key and arrays as values
+        The land type map as a dictionary with land type codes as key
+        and arrays as values
     environmentals
-        Dictionary with the name of the environmental factor as keys and their corresponding arrays as values
+        Dictionary with the name of the environmental factor as keys
+        and their corresponding arrays as values
     complying_species: set
         which species have all the needed information required for running
     parameters:dict
@@ -95,18 +97,20 @@ def prepare_input(parameters: MNPParameters, input_pathway: InputPathway) -> (
     # Prepare geodata
     land_types, environmentals = None, None
     if not input_pathway.hsi_from_disk:
-        # aggregate land type map if not already done (the task itself checks this) and read from folder
+        # aggregate land type map if not already done (the task itself checks this)
+        # and read from folder
         aggregate_land_type_map(parameters.folders)
         land_types = read_aggregated_map(folders=parameters.folders)
 
-        # Verify spatial overlap of all input in the case of running with environmental variables
+        # Verify spatial overlap of all input in the case of running with
+        # environmental variables
         if input_pathway.has_environmentals:
             environmentals = read_rasters_from_cover(
                 parameters.folders["environmentals"]
             )
 
-            # Check if land types and environmentals have enough overlap (at least 95%) and create spatial mask (=cells
-            # for which there is a value in all rasters)
+            # Check if land types and environmentals have enough overlap (at least 95%)
+            # and create spatial mask (=cells with a value in all rasters)
             verify_spatial_data_coverage(land_types, environmentals, parameters)
 
             # filter environmentals (keep only cells within spatial mask)
@@ -149,9 +153,10 @@ def evaluate_models(
     subselection_evaluation: list[SubselectionEvaluation]
         list with an evaluation object for each species in this run
     parameters:dict
-        databases containing all domain parameters, like species traits and group traits
+        databases containing all domain parameters, eg species traits and group traits
     land_types:dict
-        The land type map as a dictionary with land type codes as key and arrays as values
+        The land type map as a dictionary with land type codes as key and arrays
+        as values
 
     Returns
     -------
@@ -193,9 +198,11 @@ def run_and_evaluate(
     Parameters
     ----------
     land_types:dict
-        The land type map as a dictionary with land type codes as key and arrays as values
+        The land type map as a dictionary with land type codes as key
+        and arrays as values
     environmentals
-        Dictionary with the name of the environmental factor as keys and their corresponding arrays as values
+        Dictionary with the name of the environmental factor as keys and
+        their corresponding arrays as values
     parameters
 
     Returns
@@ -264,7 +271,8 @@ def mnp(config: ConfigParser):
 
     try:
         logger.info(
-            f'Starting MNP run by {os.environ.get("username")} on {os.environ.get("computername")}.'
+            f'Starting MNP run by {os.environ.get("username")} on '
+            '{os.environ.get("computername")}.'
         )
         add_dynamics_to_config(config)
         input_pathway, output_pathway = verify_user_input(config)
@@ -302,4 +310,5 @@ def mnp(config: ConfigParser):
     shutil.rmtree(TEMP_DIR)
 
     print(f"run took {(time.time() - start) / 60:.2f} minutes")
+    print("Thanks for using MNP")
     return subselection_evaluations