setting it up

.vscode/extensions.json

@@ -0,0 +1,5 @@
+{
+    "recommendations": [
+        "magicstack.magicpython"
+    ]
+}

.vscode/launch.json

@@ -0,0 +1,19 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+    
+        
+
+        {
+            "name": "Python: Current File",
+            "type": "python",
+            "request": "launch",
+            "program": "${file}",
+            "console": "integratedTerminal",
+            "cwd": "${fileDirname}"
+        }
+    ]
+}

.vscode/settings.json

@@ -0,0 +1,9 @@
+{
+    "python.pythonPath": "/usr/bin/python3.8",
+    "python.testing.pytestArgs": [
+        "Sample codes"
+    ],
+    "python.testing.unittestEnabled": false,
+    "python.testing.nosetestsEnabled": false,
+    "python.testing.pytestEnabled": true
+}

SourceCode/AlgorithmAnalyser.py

@@ -20,6 +20,8 @@ from scipy import signal, misc, ndimage
 
 
 
+
+
 def measure(heuristicpath, heuristic_name, funcpath, funcname, objs, args, scale, connection):
     '''
     This function runs each optimization process of the heuristic with one test function
@@ -126,8 +128,8 @@ def representfunc(funcpath):
             # Valleys and Bassins
             
             # Alternative filter used for calculating derivatives
-            derfilt = array([1.0, -2, 1.0], dtype=float32)
-            alpha = signal.sepfir2d(ck, derfilt, [1]) + signal.sepfir2d(ck, [1], derfilt)
+            #derfilt = array([1.0, -2, 1.0], dtype=float32)
+            #alpha = signal.sepfir2d(ck, derfilt, [1]) + signal.sepfir2d(ck, [1], derfilt)
             
             # Currently used filter for Valley detection
             hor = array([[0,1,1],[-1,0,1], [-1,-1,0]])
@@ -169,16 +171,16 @@ def representfunc(funcpath):
             # Noisyness: use the previously generated DOE and calculate a noisyness factor; average of derivative
             
             # Displaying the plots for development purposes
-            img1 = plt.figure()
-            ax2 = img1.add_subplot(111)
-            ax2.imshow(alpha)
+            #img1 = plt.figure()
+            #ax2 = img1.add_subplot(111)
+            #ax2.imshow(alpha)
             
             img2 = plt.figure()
             ax3 = img2.add_subplot(111)
             ax3.imshow(beta)
             
             plt.show()
-            
+            print("should be plotted")
             
             # Writing the calculated representation into the test function file
             # results['Represented'] = True
@@ -242,7 +244,9 @@ if __name__ == '__main__':
     args = {"high": 200, "low": -200, "t": 1000, "p": 0.95}
     scale = 1
         
-    doe (heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args, scale)
+    #doe (heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args, scale)
     
-    #representfunc("/home/remi/Documents/MDAF-GitLAB/SourceCode/TestFunctions/Bukin6.py")
+    representfunc("TestFunctions/Bukin6.py")
 
+
+# %%

SourceCode/TestFunctions/Bukin6.py

@@ -59,6 +59,30 @@ def main(args):
 	
 	#_# dimmensions: 2.0
 	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
 	#_# dimmensions: 2.0
 	#_# Valleys: True
 	'''

SourceCode/TestFunctions/Bukin6.py.old

@@ -0,0 +1,86 @@
+from math import sqrt, fabs
+
+
+def main(args):
+    '''
+    #_# dimmensions: 2
+    
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	
+	#_# dimmensions: 2.0
+	#_# Valleys: True
+	'''
+    return 100*sqrt(fabs(args[1]-0.01*args[0]**2))+0.01*fabs(args[0]+10)