Adding one more 1-dimensional function.

docs/api/opytimark.markers.one_dimensional.rst

@@ -1,6 +1,10 @@
 opytimark.markers.one_dimensional
 ==================================
 
+.. autoapiclass:: opytimark.markers.one_dimensional.Forrester
+   :members:
+   :show-inheritance:
+
 .. autoapiclass:: opytimark.markers.one_dimensional.GramacyLee
    :members:
    :show-inheritance:

opytimark/markers/one_dimensional.py

@@ -5,6 +5,56 @@
 from opytimark.core import Benchmark
 
 
+class Forrester(Benchmark):
+    """Forrester class implements the Forrester's benchmarking function.
+
+    .. math:: f(x) = (6x - 2)^2 sin(12x - 4)
+
+    Domain:
+        The function is commonly evaluated using :math:`x \in [0, 1]`.
+
+    Global Minima:
+        :math:`f(x^*) \\approx -5.9932767166446155 \mid x^* \\approx (0.75)`.
+
+    """
+
+    def __init__(self, name='Forrester', dims=1, continuous=True, convex=False,
+                 differentiable=True, multimodal=True, separable=True):
+        """Initialization method.
+
+        Args:
+            name (str): Name of the function.
+            dims (int): Number of allowed dimensions.
+            continuous (bool): Whether the function is continuous.
+            convex (bool): Whether the function is convex.
+            differentiable (bool): Whether the function is differentiable.
+            multimodal (bool): Whether the function is multimodal.
+            separable (bool): Whether the function is separable.
+
+        """
+
+        # Override its parent class
+        super(Forrester, self).__init__(name, dims, continuous,
+                                        convex, differentiable, multimodal, separable)
+
+    @d.check_dimension
+    def __call__(self, x):
+        """This method returns the function's output when the class is called.
+
+        Args:
+            x (np.array): An input array for calculating the function's output.
+
+        Returns:
+            The benchmarking function output `f(x)`.
+
+        """
+
+        # Calculating the Forrester's function
+        f = (6 * x[0] - 2) ** 2 * np.sin(12 * x[0] - 4)
+
+        return f
+
+
 class GramacyLee(Benchmark):
     """GramacyLee class implements the Gramacy & Lee's benchmarking function.
 
@@ -18,7 +68,7 @@ class GramacyLee(Benchmark):
 
     """
 
-    def __init__(self, name='GramacyLee', dims=-1, continuous=True, convex=False,
+    def __init__(self, name='GramacyLee', dims=1, continuous=True, convex=False,
                  differentiable=True, multimodal=False, separable=True):
         """Initialization method.
 
@@ -52,4 +102,4 @@ def __call__(self, x):
         # Calculating the Gramacy & Lee's function
         f = np.sin(10 * np.pi * x[0]) / (2 * x[0] + c.EPSILON) + ((x[0] - 1) ** 4)
 
-        return np.sum(f)
+        return f

tests/opytimark/markers/test_one_dimensional.py

@@ -4,6 +4,16 @@
 from opytimark.markers import one_dimensional
 
 
+def test_forrester():
+    f = one_dimensional.Forrester()
+
+    x = np.array([0.75])
+
+    y = f(x)
+
+    assert y == -5.9932767166446155
+
+
 def test_gramacy_lee():
     f = one_dimensional.GramacyLee()