Remove wrong file

.gitignore

@@ -5,6 +5,7 @@ utilities/__pycache__/
 # Ignore archive directory
 archive/
 examples/
+test/
 
 # Ignore all pickle files
 *.pkl

src/plain_scripts/settings copy.py

-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-"""
-    This is a template file for settings.py
-    Either duplicate and rename or fill out and rename.
-    More information on the individual meaning and what to consider can be
-    found in the user manual
-"""
-
-import logging
-import json
-import types
-
-def export_variables(logger):
-
-    variables = globals()
-    # Filter out non-serializable objects
-    defined_vars = {}
-    for k, v in variables.items():
-        if not k.startswith('__') and not callable(v) and not isinstance(v, types.ModuleType):
-            try:
-                # Test if the value is JSON serializable
-                json.dumps(v)
-                defined_vars[k] = v
-            except (TypeError, OverflowError):
-                # Skip non-serializable values
-                pass
-    # Convert the dictionary to a JSON string
-    vars_json = json.dumps(defined_vars, indent=4)
-    logger.info("Exported variables: %s", vars_json)
-
-# Mandatory parameters
-days = 2
-approach = 'statistical'
-
-# Steps
-training_dataset = False # Boolean, if training dataset shall be created
-preprocessing = 'no_interpolation' # Defines preprocessing approach: 'cluster', 'interpolation', 'no_interpolation'
-train_from_scratch = True
-train_delete = None
-
-prediction_dataset = False # Boolean, if prediction dataset shall be created
-pred_from_scratch = True
-pred_delete = None
-
-map_generation = True # Boolean, if mapping shall be performed
-
-# General
-
-crs = 'wgs84' # Coordinate reference system, string
-no_value = -999 # No data value, integer, suggestion -999
-random_seed = 42 # Random seed, integer
-resolution = 25 # Resolution in m of the final map, integer, all datasets will be interpolated to this resolution
-path_ml = '/Volumes/LaCie/2nd_Paper/entire_swiss_for_paper/maps/' # Path to where shire framework related parameters/files will be stored
-data_summary_path = None # Path to the data summary file, string, relevant only for training/prediction dataset generation
-key_to_include_path = None # Path to kets_to_include file, string, relevant only for training/prediction dataset generation
-
-# Training dataset generation
-
-size = None # Size of the validation dataset, float number between 0 and 1
-path_train = '/Volumes/LaCie/2nd_Paper/entire_swiss_for_paper/training_datasets/{days}/training_statistical_{days}d.csv' # Path to directory where the training dataset is/shall be stored
-ohe = None # One-hot encoding, bool
-
-path_landslide_database = None # Path to where the landslide database is stored, string 
-ID = 'ID' # Name of the column containing landslide ID, string
-landslide_database_x = 'xcoord' # Name of the column containing longitude values, string
-landslide_database_y = 'ycoord' # Name of the column containing latitude values, string
-
-path_nonls_locations = None # Path to where the non-landslide database is stored, string
-num_nonls = None # Number of non-landslide locations to include in the training dataset, integer
-nonls_database_x = None # Name of the column containing longitude values, string
-nonls_database_y = None  # Name of the column containing longitude values, string
-
-#cluster = False # Use clustering for training dataset generation, bool
-#interpolation = False # Use interpolation for training dataset generation, bool
-
-# Prediction dataset generation
-
-bounding_box = None # Coordinates of the edges of the bounding box of the area of interest, list, [<ymax>, <ymin>, <xmin>, <xmax>]
-path_pred = None # Path to directory where the prediction dataset is/shall be stored
-
-# Map generation
-
-RF_training = True # Train the RF, bool
-RF_prediction = True # Make a prediction using the RF, bool
-
-not_included_pred_data = ['xcoord', 'ycoord']# List of features in the training dataset not to be considered in prediction
-not_included_train_data = [] # List of features in the training dataset not to be considered in model training
-
-num_trees = 100 # Number of trees in the Random Forest, integer
-criterion = 'gini' # Criterion for the Random Forest, string
-depth = 20  # Number of nodes of the RF, integer
-
-model_to_save = '/Volumes/LaCie/2nd_Paper/entire_swiss_for_paper/maps/{approach}/RF_{days}' # Folder name for storage of the RF results, string
-model_to_load = '/Volumes/LaCie/2nd_Paper/entire_swiss_for_paper/maps/{approach}/RF_{days}' # Folder where RF model is stored, string, identical to model_to_save if training and prediction is done at the same time
-model_database_dir = path_ml # Directory where models should be stored
-parallel = True # Boolean, true if prediction data shall be split to predict in parallel
-
-keep_cat_features = False #bool, true if categorical features shall be kept even if some instances in prediction dataset have classes not covered by the prediction dataset
-remove_instances = True # bool, true of instances in prediction dataset shall be removed if they have different classes than the instances in the training dataset
\ No newline at end of file