MILESTONE

First working version. Executes test of classification with SVM and plots evaluated result.

main.py

@@ -11,43 +11,52 @@ import matplotlib.pyplot as plt
 import pandas as pd
 
 import slopestabilitytools
+import slopestabilitytools.datamanagement
 import slopestabilityML
 import slostabcreatedata
 
-
 import pygimli as pg
 import pygimli.meshtools as mt
 import pygimli.physics.ert as ert
 
+# Config
+create_new_data = False
+
 # Prepare folder structure for output
 is_success = slopestabilitytools.folder_structure.create_folder_structure()
 
-# Settings
-number_of_tests = 10
-rho_spread_factor = 1.5
-rho_max = 150
-layers_min = 1
-layers_max = 5
-min_depth = 1
-max_depth = 25
+if not create_new_data:
+
+    test_results = slopestabilitytools.datamanagement.import_tests()
+
+else:
 
-# Generate parameters for tests
-tests_horizontal = slopestabilitytools.model_params(number_of_tests,
-                                                    rho_spread_factor, rho_max,
-                                                    layers_min, layers_max,
-                                                    min_depth, max_depth)
+    # TODO Put this part into a function
 
-#  Create models and invert them
-test_results = {}
+    # Settings
+    number_of_tests = 10
+    rho_spread_factor = 1.5
+    rho_max = 150
+    layers_min = 1
+    layers_max = 5
+    min_depth = 1
+    max_depth = 25
 
-for test_name in tests_horizontal.keys():
+    # Generate parameters for tests
+    tests_horizontal = slopestabilitytools.model_params(number_of_tests,
+                                                        rho_spread_factor, rho_max,
+                                                        layers_min, layers_max,
+                                                        min_depth, max_depth)
 
-    test_result_curr = slostabcreatedata.create_data(test_name, tests_horizontal[test_name], max_depth)
-    test_results.update({test_name: test_result_curr})
-    del test_result_curr
+    #  Create models and invert them
+    test_results = {}
 
-    # Plot and save figures
-    slopestabilitytools.plot_and_save(test_name, test_results[test_name], 'Test: '+test_name)
+    for test_name in tests_horizontal.keys():
+        test_result_curr = slostabcreatedata.create_data(test_name, tests_horizontal[test_name], max_depth)
+        test_results.update({test_name: test_result_curr})
+        del test_result_curr
 
+        # Plot and save figures
+        slopestabilitytools.plot_and_save(test_name, test_results[test_name], 'Test: ' + test_name)
 
 svm_accuracy_score, svm_accuracy_labels = slopestabilityML.svm_run(test_results)

slopestabilityML/SVM/svm_run.py

@@ -26,7 +26,7 @@ def svm_run(test_results):
                                      k=math.ceil(test_number * 0.1))
 
     test_training = slopestabilitytools.set_diff(list(test_results.keys()), set(test_prediction))
-
+    print(test_prediction)
     # Create classifier
     clf = svm.SVC(gamma=0.001, C=100, kernel='linear')
 
@@ -35,7 +35,7 @@ def svm_run(test_results):
     for test_name in test_training:
         # Prepare data
         data_set = test_results[test_name]
-        x_train = data_set.drop('Z', 'INM', 'CLASS')
+        x_train = data_set.drop(['Z', 'INM', 'CLASS'], axis='columns')
         y_train = data_set['CLASS']
 
         # Train classifier
@@ -44,8 +44,10 @@ def svm_run(test_results):
     # Predict with classfier
     for test_name_pred in test_prediction:
         # Prepare data
-        data_set_pred = test_prediction[test_name_pred]
-        x_question = data_set_pred.drop('Z', 'INM', 'CLASS')
+
+        data_set_pred = test_results[test_name_pred]
+        print(data_set_pred)
+        x_question = data_set_pred.drop(['Z', 'INM', 'CLASS'], axis='columns')
         y_answer = data_set_pred['CLASS']
 
         y_pred = clf.predict(x_question)

slopestabilityML/plot_results.py

@@ -11,13 +11,15 @@ import matplotlib.pyplot as plt
 
 def plot_results(accuracy_labels, accuracy_score):
 
-    plt.figure()
-    plt.scatter(accuracy_labels, accuracy_score)
-    plt.ylabel('Test name')
-    plt.xlabel('Correct points [%]')
+    fig = plt.figure()
+    ax = plt.subplot(111)
+    ax.scatter(accuracy_labels, accuracy_score)
+    plt.xlabel('Test name')
+    plt.ylabel('Correct points [%]')
     plt.title('SVM classification accuracy')
-    plt.savefig('results/figures/SVM.eps')
-    plt.savefig('results/figures/SVM.pdf')
-    plt.savefig('results/figures/SVM.png')
+    print('plot script is executed')
+    fig.savefig('results/figures/SVM.eps')
+    fig.savefig('results/figures/SVM.pdf')
+    fig.savefig('results/figures/SVM.png')
 
     return

slopestabilitytools/__init__.py

@@ -20,3 +20,7 @@ from .set_diff import set_diff
 from .folder_structure.create_folder_structure import create_folder_structure
 from .folder_structure.create_folder_for_test import create_folder_for_test
 from .folder_structure.check_create_folder import check_create_folder
+
+from .datamanagement.import_tests import import_tests
+from .datamanagement.read_to_pandas import read_to_pandas
+from .datamanagement.test_list import test_list

slopestabilitytools/datamanagement/__init__.py

@@ -8,5 +8,4 @@ Created on
 
 from .test_list import test_list
 from .read_to_pandas import read_to_pandas
-from .write import write
-from .import_tests import import_tests
\ No newline at end of file
+from .import_tests import import_tests

slopestabilitytools/datamanagement/import_tests.py

@@ -6,7 +6,18 @@ Created on 17.01.2021
 @author: Feliks Kiszkurno
 """
 
+import slopestabilitytools.datamanagement.test_list
+import pandas as pd
+
 
 def import_tests():
+    test_results = {}
+    test_names = slopestabilitytools.datamanagement.test_list('.csv')
+    #print('test')
+    #print(test_names)
+
+    for test_name in test_names:
+        test_result_curr = pd.read_csv('results/results/' + test_name + '.csv')
+        test_results.update({test_name: test_result_curr})
 
-    return
+    return test_results

slopestabilitytools/datamanagement/test_list.py

@@ -8,6 +8,8 @@ Created on 17.01.2021
 
 import os
 
+# TODO Add more flexibility in the way, that the path is handled
+
 
 def test_list(extension):
 
@@ -19,7 +21,12 @@ def test_list(extension):
     for file in file_list:
 
         test_names.append(file[:file.find(extension)])
+        print(file[:file.find(extension)])
 
-    test_names = test_names.sort()
+    print('start')
+    print(test_names)
+    print('end')
+    test_names = sorted(test_names)
+    print(test_names)
 
     return test_names

slopestabilitytools/datamanagement/write.py

-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Created on 17.01.2021
-
-@author: Feliks Kiszkurno
-"""
-
-
-def read_to_pandas():
-
-    return

slopestabilitytools/folder_structure/__init__.py

@@ -8,4 +8,4 @@ Created on 15.01.2021
 
 from .create_folder_for_test import create_folder_for_test
 from .create_folder_structure import create_folder_structure
-from .check_create_folder import check_create_folder
\ No newline at end of file
+from .check_create_folder import check_create_folder