Added normalization, normalized classes, AdaBoost, KNN.

slopestabilitytools/def_classes.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on 26.03.2021
+
+@author: Feliks Kiszkurno
+"""
+
+import numpy as np
+
+
+def def_classes(class_num):
+
+    class_spacing = 1 / class_num
+    ids = np.linspace(0, class_num - 1, class_num)
+    class_start = np.linspace(0, 1 - class_spacing, class_num)
+    class_end = np.linspace(class_spacing, 1, class_num)
+    classes_def = np.vstack((ids, class_start, class_end))
+
+    return classes_def.T
\ No newline at end of file

slopestabilitytools/normalize.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on 15.03.2021
+
+@author: Feliks Kiszkurno
+"""
+
+import numpy as np
+
+
+def normalize(array):
+    array_max = 0
+    array = np.array(array)
+    if array.ndim == 1:
+        array_max = np.max(array)
+
+    elif array.ndim == 2:
+        array_max = np.amax(array)
+
+    else:
+        print('ERROR: incorrect dimensionality of the input array')
+        exit()
+
+    array_norm = array / array_max
+
+    return array_norm
+

slopestabilitytools/plot_and_save.py

@@ -78,8 +78,8 @@ def plot_and_save(test_name, test_result, plot_title, rho_max, rho_min):
 
     fig.tight_layout()
     fig.savefig(Path('results/figures/eps/{}_in_inv_diff.eps'.format(test_name)), bbox_inches="tight")
-    fig.savefig(Path('results/figures/png/{}_in_inv_diff.png'.format(test_name)), bbox_inches="tight")
-    fig.savefig(Path('results/figures/pdf/{}_in_inv_diff.pdf'.format(test_name)), bbox_inches="tight")
+    #fig.savefig(Path('results/figures/png/{}_in_inv_diff.png'.format(test_name)), bbox_inches="tight")
+    #fig.savefig(Path('results/figures/pdf/{}_in_inv_diff.pdf'.format(test_name)), bbox_inches="tight")
 
     # Plot coverage
     cb_cov = []
@@ -97,7 +97,7 @@ def plot_and_save(test_name, test_result, plot_title, rho_max, rho_min):
 
     fig_cov.tight_layout()
     fig_cov.savefig(Path('results/figures/eps/{}_cov.eps'.format(test_name)), bbox_inches="tight")
-    fig_cov.savefig(Path('results/figures/png/{}_cov.png'.format(test_name)), bbox_inches="tight")
-    fig_cov.savefig(Path('results/figures/pdf/{}_cov.pdf'.format(test_name)), bbox_inches="tight")
+    #fig_cov.savefig(Path('results/figures/png/{}_cov.png'.format(test_name)), bbox_inches="tight")
+    #fig_cov.savefig(Path('results/figures/pdf/{}_cov.pdf'.format(test_name)), bbox_inches="tight")
 
     return

slopestabilitytools/save_plot.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on 25.03.2021
+
+@author: Feliks Kiszkurno
+"""
+
+def save_plot(figure_handler, test_name, figure_name):
+    figure_handler.savefig('results/figures/png/' + test_name + '_1_geometry'+'.png', bbox_inches="tight")
+
+    # fig_geometry.savefig('results/figures/pdf/' + test_name + '_1_geometry.pdf', bbox_inches="tight")
+    # fig_geometry.savefig('results/figures/eps/' + test_name + '_1_geometry.eps', bbox_inches="tight")
+

slostabcreatedata/create_data.py

@@ -18,8 +18,10 @@ import slopestabilitytools
 
 
 def create_data(test_name, test_config, max_depth):
-    world_boundary_v = [-20 * max_depth, 0]  # [NW edge] relatively to the middle
-    world_boundary_h = [20 * max_depth, -5 * max_depth]  # [SE edge]
+    from main import settings
+
+    world_boundary_v = [-9 * max_depth, 0]  # [NW edge] relatively to the middle
+    world_boundary_h = [9 * max_depth, -9 * max_depth]  # [SE edge]
     # world_boundary_v = [-500, 0]  # [right, left border] relatively to the middle
     # world_boundary_h = [500, -100]  # [top, bottom border]
 
@@ -38,11 +40,12 @@ def create_data(test_name, test_config, max_depth):
     ax_geometry = slopestabilitytools.set_labels(ax_geometry)
     ax_geometry.set_title('1 Geometry of the model')
     fig_geometry.tight_layout()
-    fig_geometry.savefig('results/figures/png/'+test_name+'_1_geometry.png', bbox_inches="tight")
-    fig_geometry.savefig('results/figures/pdf/' + test_name + '_1_geometry.pdf', bbox_inches="tight")
-    fig_geometry.savefig('results/figures/eps/' + test_name + '_1_geometry.eps', bbox_inches="tight")
+    fig_geometry.savefig('results/figures/png/' + test_name + '_1_geometry.png', bbox_inches="tight")
+    #fig_geometry.savefig('results/figures/pdf/' + test_name + '_1_geometry.pdf', bbox_inches="tight")
+    #fig_geometry.savefig('results/figures/eps/' + test_name + '_1_geometry.eps', bbox_inches="tight")
 
-    measurement_scheme = ert.createERTData(elecs=np.linspace(start=-8*max_depth, stop=8*max_depth, num=8*max_depth+1),
+    measurement_scheme = ert.createERTData(
+        elecs=np.linspace(start=-8 * max_depth, stop=8 * max_depth, num=8 * max_depth + 1),
         schemeName='dd')
 
     for electrode in measurement_scheme.sensors():
@@ -59,8 +62,8 @@ def create_data(test_name, test_config, max_depth):
     ax_model.set_title('2 Mesh and resistivity distribution')
     fig_model.tight_layout()
     fig_model.savefig('results/figures/png/' + test_name + '_2_meshdist.png', bbox_inches="tight")
-    fig_model.savefig('results/figures/pdf/' + test_name + '_2_meshdist.pdf', bbox_inches="tight")
-    fig_model.savefig('results/figures/eps/' + test_name + '_2_meshdist.eps', bbox_inches="tight")
+    #fig_model.savefig('results/figures/pdf/' + test_name + '_2_meshdist.pdf', bbox_inches="tight")
+    #fig_model.savefig('results/figures/eps/' + test_name + '_2_meshdist.eps', bbox_inches="tight")
 
     input_model = pg.solver.parseMapToCellArray(resistivity_map, mesh)  # rename to input_mesh
 
@@ -75,16 +78,17 @@ def create_data(test_name, test_config, max_depth):
 
     # RUN INVERSION #
     k0 = pg.physics.ert.createGeometricFactors(data)
-    model_inverted = ert_manager.invert(data=data, lam=20, paraDX=0.25, paraMaxCellSize=2, paraDepth=2*max_depth,
+    model_inverted = ert_manager.invert(data=data, lam=20, paraDX=0.25, paraMaxCellSize=2, paraDepth=2 * max_depth,
                                         quality=34, zPower=0.4)
 
     result_full = ert_manager.inv.model
-    #result_array = pg.utils.interperc(result_full, 5)
-    #result_lim = result_full.array()
-    #result_lim[np.where(result_array > max(resistivity_map[1]))] = float("NaN")
-    #result_lim[np.where(result_array < min(resistivity_map[1]))] = float("NaN") # min(resistivity_map[1])
-    #result_array = result_lim
+    # result_array = pg.utils.interperc(result_full, 5)
+    # result_lim = result_full.array()
+    # result_lim[np.where(result_array > max(resistivity_map[1]))] = float("NaN")
+    # result_lim[np.where(result_array < min(resistivity_map[1]))] = float("NaN") # min(resistivity_map[1])
+    # result_array = result_lim
     result_array = result_full.array()
+    result_array_norm = slopestabilitytools.normalize(result_array)
 
     fig_result, ax_result = plt.subplots(1)
     pg.show(ert_manager.paraDomain, result_full, label=pg.unit('res'), showMesh=True, ax=ax_result)
@@ -92,12 +96,13 @@ def create_data(test_name, test_config, max_depth):
     ax_result.set_title('3 Result')
     fig_result.tight_layout()
     fig_result.savefig('results/figures/png/' + test_name + '_3_result.png', bbox_inches="tight")
-    fig_result.savefig('results/figures/pdf/' + test_name + '_3_result.pdf', bbox_inches="tight")
-    fig_result.savefig('results/figures/eps/' + test_name + '_3_result.eps', bbox_inches="tight")
+    #fig_result.savefig('results/figures/pdf/' + test_name + '_3_result.pdf', bbox_inches="tight")
+    #fig_result.savefig('results/figures/eps/' + test_name + '_3_result.eps', bbox_inches="tight")
 
     input_model2 = pg.interpolate(srcMesh=mesh, inVec=input_model, destPos=ert_manager.paraDomain.cellCenters())
 
     input_model2_array = input_model2.array()
+    input_model2_array_norm = slopestabilitytools.normalize(input_model2_array)
 
     fig_input, ax_input = plt.subplots(1)
     pg.show(ert_manager.paraDomain, input_model2, label=pg.unit('res'), showMesh=True, ax=ax_input)
@@ -105,8 +110,10 @@ def create_data(test_name, test_config, max_depth):
     ax_input.set_title('4 Model on inv mesh')
     fig_input.tight_layout()
     fig_input.savefig('results/figures/png/' + test_name + '_4_modelinv.png', bbox_inches="tight")
-    fig_input.savefig('results/figures/pdf/' + test_name + '_4_modelinv.pdf', bbox_inches="tight")
-    fig_input.savefig('results/figures/eps/' + test_name + '_4_modelinv.eps', bbox_inches="tight")
+    #fig_input.savefig('results/figures/pdf/' + test_name + '_4_modelinv.pdf', bbox_inches="tight")
+    #fig_input.savefig('results/figures/eps/' + test_name + '_4_modelinv.eps', bbox_inches="tight")
+
+    #if not settings['norm_class']:
 
         # Create classes labels
     classes = []
@@ -115,6 +122,7 @@ def create_data(test_name, test_config, max_depth):
         resistivity_values.append(pair[1])
     # print(resistivity_values)
 
+    # TODO: This has to be rewritten for more complicated cases
     for value in input_model2:
         # print(value)
         res_diff = np.abs(value * np.ones_like(resistivity_values) - resistivity_values)
@@ -123,13 +131,17 @@ def create_data(test_name, test_config, max_depth):
         # print(res_index)
         classes.append(res_index)
 
+    #elif settings['norm_class']:
+
+    classesn = slopestabilitytools.assign_classes(input_model2_array_norm)
+
     # Create sensitivity values
     jac = ert_manager.fop.jacobian()  #
     # Normalization only for visualization!
 
     # Coverage = cumulative sensitivity = all measurements
     cov = ert_manager.coverage()
-    #pg.show(ert_manager.paraDomain, cov, label="Logarithm of cumulative sensitivity")
+    # pg.show(ert_manager.paraDomain, cov, label="Logarithm of cumulative sensitivity")
 
     rho_arr = []
     for entry in resistivity_map:
@@ -138,16 +150,22 @@ def create_data(test_name, test_config, max_depth):
     rho_max = np.max(rho_arr)
     rho_min = np.min(rho_arr)
 
+    # TODO: this assumes only two resistivities, extend it to consider more
     result_array[np.where(result_array < rho_min)] = rho_min
     result_array[np.where(result_array > rho_max)] = rho_max
 
+    result_array_norm = slopestabilitytools.normalize(result_array)
+
     experiment_results = pd.DataFrame(data={'X': ert_manager.paraDomain.cellCenters().array()[:, 0],
                                             'Y': ert_manager.paraDomain.cellCenters().array()[:, 1],
                                             'Z': ert_manager.paraDomain.cellCenters().array()[:, 2],
                                             'INM': input_model2_array,
+                                            'INMN': input_model2_array_norm,
                                             'RES': result_array,
+                                            'RESN': result_array_norm,
                                             'SEN': cov,
-                                            'CLASS': classes})
+                                            'CLASS': classes,
+                                            'CLASSN': classesn})
 
     # experiment_results.to_csv('results/results/'+test_name+'.csv')
 
@@ -155,6 +173,4 @@ def create_data(test_name, test_config, max_depth):
 
     experiment_results.to_csv('results/results/' + test_name + '.csv')
 
-
-
     return experiment_results, rho_max, rho_min