new synth examples global

Author: dimitrskpl

effector/models.py

@@ -103,4 +103,99 @@ def jacobian(self, x: np.ndarray) -> np.ndarray:
         y[~ind1 & ~ind2, 0] = 3*np.exp(3*x[~ind1 & ~ind2, 0])
         return y
 
+class ConditionalInteraction4Regions(Base):
+    def __init__(self):
+        """
+        $f(x_1, x_2, x_3) = 
+        \begin{cases} 
+        -x_1^2 + e^{x_3}, & \text{if } x_2 < 0 \text{ and } x_3 < 0 \\
+        x_1^2 + e^{x_3}, & \text{if } x_2 < 0 \text{ and } x_3 \geq 0 \\
+        -x_1^4 + e^{x_3}, & \text{if } x_2 \geq 0 \text{ and } x_3 < 0 \\
+        x_1^4 + e^{x_3}, & \text{if } x_2 \geq 0 \text{ and } x_3 \geq 0
+        \end{cases}
+        """
+        super().__init__(name=self.__class__.__name__)
+
+    def predict(self, x: np.ndarray) -> np.ndarray:
+        """Predict.
+
+        Args:
+            x : Input data, shape (N, 4)
+
+        Returns:
+            Output of the model, shape (N,)
+        """
+        y = np.exp(x[:, 3])
+
+        mask1 = (x[:, 1] < 0) & (x[:, 2] < 0)
+        mask2 = (x[:, 1] < 0) & (x[:, 2] >= 0)
+        mask3 = (x[:, 1] >= 0) & (x[:, 2] < 0)
+        mask4 = (x[:, 1] >= 0) & (x[:, 2] >= 0)
+
+        y[mask1] += -x[mask1, 0] ** 2
+        y[mask2] += x[mask2, 0] ** 2
+        y[mask3] += -x[mask3, 0] ** 4
+        y[mask4] += x[mask4, 0] ** 4
+
+        return y
+
+    def jacobian(self, x: np.ndarray) -> np.ndarray:
+        """Calculate the Jacobian of the model.
+
+        Args:
+            x : Input data, shape (N, 4)
+
+        Returns:
+            Jacobian of the model, shape (N, 4)
+        """
+        y = np.zeros(x.shape)
+
+        y[:, 3] = np.exp(x[:, 3])
+
+        mask1 = (x[:, 1] < 0) & (x[:, 2] < 0)
+        mask2 = (x[:, 1] < 0) & (x[:, 2] >= 0)
+        mask3 = (x[:, 1] >= 0) & (x[:, 2] < 0)
+        mask4 = (x[:, 1] >= 0) & (x[:, 2] >= 0)
+
+        y[mask1, 0] = -2 * x[mask1, 0]
+        y[mask2, 0] = 2 * x[mask2, 0]
+        y[mask3, 0] = -4 * x[mask3, 0] ** 3
+        y[mask4, 0] = 4 * x[mask4, 0] ** 3
+
+        return y
 
+class GeneralInteraction(Base):
+    def __init__(self):
+        """Define a simple model.
+
+        $f(x_1, x_2, x_3) = x_1 x_2^2 + e^{x_3}$
+
+        """
+        super().__init__(name=self.__class__.__name__)
+
+    def predict(self, x: np.ndarray) -> np.ndarray:
+        """Predict.
+
+        Args:
+            x : Input data, shape (N, 3)
+
+        Returns:
+            Output of the model, shape (N,)
+        """
+        y = x[:, 0] * x[:, 1] ** 2 + np.exp(x[:, 2])
+        return y
+
+    def jacobian(self, x: np.ndarray) -> np.ndarray:
+        """Calculate the Jacobian of the model.
+
+        Args:
+            x : Input data, shape (N, 3)
+
+        Returns:
+            Jacobian of the model, shape (N, 3)
+        """
+        y = np.zeros_like(x)
+        y[:, 0] = x[:, 1] ** 2
+        y[:, 1] = 2 * x[:, 0] * x[:, 1]
+        y[:, 2] = np.exp(x[:, 2])
+        return y