New version

.gitignore

@@ -1,6 +1,6 @@
 # Pycharm
 .idea/
-
+tut_upcode.md
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

README.md

@@ -43,6 +43,7 @@ print(func2d._bird__(solution))
 
 ### Documentation 
 ```code 
+0. A Literature Survey of Benchmark Functions For Global Optimization Problems (2013)
 1. http://benchmarkfcns.xyz/fcns
 2. https://en.wikipedia.org/wiki/Test_functions_for_optimization
 3. https://www.cs.unm.edu/~neal.holts/dga/benchmarkFunction/

opfunu/benchmark1d.py

@@ -0,0 +1,29 @@
+#!/usr/bin/env python                                                                                   #
+# ------------------------------------------------------------------------------------------------------#
+# Created by "Thieu Nguyen" at 02:52, 07/12/2019                                                        #
+#                                                                                                       #
+#       Email:      [email protected]                                                           #
+#       Homepage:   https://www.researchgate.net/profile/Thieu_Nguyen6                                  #
+#       Github:     https://github.com/thieunguyen5991                                                  #
+#-------------------------------------------------------------------------------------------------------#
+
+
+import numpy as np
+
+class Functions:
+    """
+        This class of functions is belongs to 1-dimensional space
+    """
+
+    def _gramacy_lee__(self, solution=None):
+        """
+        Class: uni-modal, non-convex, continuous
+        Global: 1 global minimum fx = −0.869011134989500, atx 0.548563444114526
+        Link: http://benchmarkfcns.xyz/benchmarkfcns/gramacyleefcn.html
+
+        @param solution: A numpy array include 1 items like: [0.5], limited range: [-0.5, 2.5]
+
+        """
+        n = len(solution)
+        assert (n == 1, 'Gramacy and Lee function is only defined on a 1D space.')
+        return np.sin(10*np.pi*solution) / (2*solution) + (solution-1)**4

opfunu/benchmark3d.py

@@ -0,0 +1,28 @@
+#!/usr/bin/env python                                                                                   #
+# ------------------------------------------------------------------------------------------------------#
+# Created by "Thieu Nguyen" at 02:52, 07/12/2019                                                        #
+#                                                                                                       #
+#       Email:      [email protected]                                                           #
+#       Homepage:   https://www.researchgate.net/profile/Thieu_Nguyen6                                  #
+#       Github:     https://github.com/thieunguyen5991                                                  #
+#-------------------------------------------------------------------------------------------------------#
+
+
+import numpy as np
+
+class Functions:
+    """
+        This class of functions is belongs to 3-dimensional space
+    """
+
+    def _wolfe__(self, solution=None):
+        """
+        Class: multi-modal, non-convex, continuous, differentiable, non-separable
+        Global: 1 global minimum fx = 0, [0, 0, 0]
+        Link: http://benchmarkfcns.xyz/benchmarkfcns/wolfefcn.html
+
+        @param solution: A numpy array include 3 items like: [0.2, 0.22, 0.5], limited range: [0, 2]
+        """
+        n = len(solution)
+        assert (n == 3, 'Wolfe function is only defined on a 3D space.')
+        return 4/3 * (solution[0]**2 + solution[1]**2 - solution[0]*solution[1])**0.75 + solution[2]

setup.py

@@ -7,12 +7,12 @@ def readme():
 
 setup(
     name="opfunu",
-    version="0.2.0",
-    description="A python package for Optimization Functions in Numpy.",
+    version="0.2.1",
+    description="A python (Numpy) package for Un-constrained Optimization Functions",
     long_description=readme(),
     long_description_content_type="text/markdown",
     url="https://github.com/thieunguyen5991/opfunu",
-    download_url="https://github.com/thieunguyen5991/opfunu/archive/v.0.2.0.zip",
+    download_url="https://github.com/thieunguyen5991/opfunu/archive/v.0.2.1.zip",
     author="Thieu Nguyen",
     author_email="[email protected]",
     license="Apache License, Version 2.0",