Fix/ddm/threshold

psyneulink/components/functions/function.py

@@ -5928,8 +5928,10 @@ def function(self,
 
         if np.all(abs(value) < threshold):
             adjusted_value = value + offset
-        else:
+        elif np.all(value >= threshold):
             adjusted_value = np.atleast_2d(threshold)
+        elif np.all(value <= -threshold):
+            adjusted_value = np.atleast_2d(-threshold)
 
         # If this NOT an initialization run, update the old value and time
         # If it IS an initialization run, leave as is

psyneulink/library/mechanisms/processing/integrator/ddm.py

@@ -822,13 +822,19 @@ def plot(self, stimulus=1.0, threshold=10.0):
         """
         Generate a dynamic plot of the DDM integrating over time towards a threshold.
 
-        NOTE: plot is only available `integration mode <DDM_Integration_Mode>` (with the Integrator function).
+        .. note::
+            The plot method is only available when the DriftDiffusionIntegrator function is in use. The plot method does
+            not represent the results of this DDM mechanism in particular, and does not affect the current state of this
+            mechanism's DriftDiffusionIntegrator. The plot method is only meant to visualize a possible path of a DDM
+            mechanism with these function parameters.
 
         Arguments
         ---------
+        stimulus: float: default 1.0
+            specify a stimulus value for the AdaptiveIntegrator function
 
         threshold: float: default 10.0
-             specify the threshold at which the DDM will stop integrating
+            specify the threshold at which the DDM will stop integrating
 
         Returns
         -------
@@ -1002,10 +1008,6 @@ def _execute(self,
         :rtype self.outputState.value: (number)
         """
 
-        # PLACEHOLDER for a time_step_size parameter when time_step_mode/Scheduling is implemented:
-        time_step_size = 1.0
-
-
         # FIX: 2/5/18: PUT CODE HERE FOR input_format = ARRAY/VECTOR, TO SUBTRACT variable[1] from variable[0]
 
         if variable is None or np.isnan(variable):

tests/mechanisms/test_ddm_mechanism.py

@@ -114,6 +114,22 @@ def test_threshold_stops_accumulation(self):
         # time accumulation does not stop
         assert np.allclose(time_points, [1.0, 2.0, 3.0, 4.0, 5.0])
 
+    def test_threshold_stops_accumulation_negative(self):
+        D = DDM(name='DDM',
+                function=DriftDiffusionIntegrator(threshold=5.0))
+        decision_variables = []
+        time_points = []
+        for i in range(5):
+            output = D.execute(-2.0)
+            decision_variables.append(output[0][0][0])
+            time_points.append(output[1][0][0])
+
+        # decision variable accumulation stops
+        assert np.allclose(decision_variables, [-2.0, -4.0, -5.0, -5.0, -5.0])
+
+        # time accumulation does not stop
+        assert np.allclose(time_points, [1.0, 2.0, 3.0, 4.0, 5.0])
+
     # def test_threshold_stops_accumulation_multiple_variables(self):
     #     D = IntegratorMechanism(name='DDM',
     #                             default_variable=[[0,0,0]],