Feat/system/show graph (#555)

* - * - * - * • Library: - docs: "Base class" -> "Core class" * • CONVENTIONS: - added section on organization of repo and base vs. core classes * • System - fixed bug in show_graph producing empty image for graphs with just one Mechanism * • System - show_graph(): fixed bug producing empty image for graphs with just one Mechanism added auto-recurrent projections * • System - show_graph(): fixed bug producing empty image for graphs with just one Mechanism added auto-recurrent projections * • System - show_graph(): shows dimensions for Mechanisms and Projections * • System - show_graph(): shows dimensions for Mechanisms and Projections * • System, Process - minor modes to enabling of learning to prevent crash when learning is specified in constructor but no learnable elements are included in Process * • System, Process - minor modes to enabling of learning to prevent crash when learning is specified in constructor but no learnable elements are included in Process
PrincetonUniversity · Nov 30, 2017 · 7b097af · 7b097af
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diff --git a/CONVENTIONS.md b/CONVENTIONS.md
@@ -1,6 +1,62 @@
 
-# PsyNeuLink Coding and Documentation Conventions
-
+# PsyNeuLink Organization, Coding, and Documentation Conventions
+
+## REPOSITORY ORGANIZATION:
+
+### Core:
+Made up of two types of classes:
+- *abstract base classes* (italicized) - cannot be instantiated.
+- **core classes** (bold) - most basic (abstract) level of objects that can be instantiated. 
+
+#### Components
+"Building blocks"
+- *Mechanism*
+    - *ProcessingMechanism*
+        - **TransferMechanism**
+        - **IntegratorMechanism**
+        - **ObjectiveMechanism**
+    - *AdaptiveMechanism*
+        - **LearningMechanism**
+        - **ControlMechanism**
+        - **GatingMechanism**
+- *Projection*
+    - *PathwayProjection*
+        - **MappingProjection**
+    - *ModulatoryProjection*
+        - **LearningProjection**
+        - **ControlProjection**
+        - **GatingProjection**
+- *State*
+    - **InputState**
+    - **ParameterState**
+    - **OutputState**
+    - *ModulatorySignal*
+        - **LearningSignal**
+        - **ControlSignal**
+        - **GatingSignal**
+- *Function*
+    - *TransferFunction*
+    - *CombinationFunction*
+    - *IntegratorFunction*
+    - *DistributionFunction*
+    - *LearningFunction*
+
+#### Composisitons
+Objects that compose building blocks and control their execution.
+- *Composition*
+    - **System**
+    - **Process**
+
+#### Scheduler
+Objects used by Compositions to control the execution of Components and Compositions.
+- **Scheduler**
+- **Condition** 
+
+### Library
+Extensions of Core objects
+- *Components:* classes derived from Core objects
+- *Compositions:*  models
+- *Models:*  published, implemented models
 
 ### NAMING:
 

diff --git a/Scripts/Examples/EVC-Gratton.py b/Scripts/Examples/EVC-Gratton.py
@@ -152,6 +152,7 @@ def test_outcome_function(**kwargs):
 # Show characteristics of system:
 mySystem.show()
 mySystem.controller.show()
+mySystem.show_graph(show_control=pnl.ALL, show_dimensions=pnl.ALL)
 
 # configure EVC components
 mySystem.controller.control_signals[0].intensity_cost_function = pnl.Exponential(rate=0.8046).function

diff --git a/Scripts/Examples/Multilayer-Learning.py b/Scripts/Examples/Multilayer-Learning.py
@@ -104,7 +104,7 @@ def show_target(system):
 )
 
 mySystem.reportOutputPref = True
-mySystem.show_graph(show_learning=pnl.ALL)
+mySystem.show_graph(show_learning=pnl.ALL, show_dimensions=pnl.ALL)
 # mySystem.show_graph()
 
 stim_list = {Input_Layer: [[-1, 30]]}
@@ -119,4 +119,3 @@ def show_target(system):
     termination_processing={pnl.TimeScale.TRIAL: pnl.AfterNCalls(Output_Layer, 1)}
 )
 
-mySystem.show_graph(show_learning=pnl.ALL)
diff --git a/Scripts/Scratch Pad.py b/Scripts/Scratch Pad.py
@@ -716,7 +716,6 @@ def __init__(self, error_value):
 
 #endregion
 
-
 # region TEST MODULATORY SPECS
 # print ("TEST MODULATORY SPECS")
 #
@@ -811,7 +810,6 @@ def __init__(self, error_value):
 
 #endregion
 
-
 #region TEST DOCUMENTATION
 # print ("TEST DOCUMENTATION")
 
@@ -881,6 +879,23 @@ def __init__(self, error_value):
 
 #endregion
 
+#region TEST System Graph with AutoAssociativeMechanism
+print("TEST System Graph with AutoAssociativeMechanism")
+
+a = pnl.DDM(name='MY DDM')
+# a = pnl.RecurrentTransferMechanism(name='Autoassociator')
+p = pnl.Process(pathway=[a],
+                learning=pnl.ENABLED
+                )
+s = pnl.System(processes=[p])
+s.show_graph(show_learning=pnl.ALL,
+             show_dimensions=pnl.ALL
+             )
+
+
+#endregion
+
+
 #region TEST INSTANTATION OF Cyclic and Acyclic Systems @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
 #
 #

diff --git a/docs/source/ControlMechanisms.rst b/docs/source/ControlMechanisms.rst
@@ -1,7 +1,7 @@
 ControlMechanisms
 =================
 
-**Base class**:
+**Core class**:
 
 * `ControlMechanism`
 

diff --git a/docs/source/ControlProjections.rst b/docs/source/ControlProjections.rst
@@ -1,7 +1,7 @@
 Control Projections
 ===================
 
-**Base class**:
+**Core class**:
 
 * `ControlProjection`
 

diff --git a/docs/source/GatingMechanisms.rst b/docs/source/GatingMechanisms.rst
@@ -1,7 +1,7 @@
 GatingMechanisms
 ================
 
-**Base class**:
+**Core class**:
 
 * `GatingMechanism`
 

diff --git a/docs/source/GatingProjections.rst b/docs/source/GatingProjections.rst
@@ -1,7 +1,7 @@
 GatingProjections
 =================
 
-**Base class**:
+**Core class**:
 
 * `GatingProjection`
 

diff --git a/docs/source/IntegratorMechanisms.rst b/docs/source/IntegratorMechanisms.rst
@@ -1,7 +1,7 @@
 IntegratorMechanisms
 ====================
 
-**Base class**:
+**Core class**:
 
 * `IntegratorMechanism`
 

diff --git a/docs/source/LearningMechanisms.rst b/docs/source/LearningMechanisms.rst
@@ -1,7 +1,7 @@
 Learning Mechanisms
 ===================
 
-**Base class**:
+**Core class**:
 
 * `LearningMechanism`
 

diff --git a/docs/source/LearningProjections.rst b/docs/source/LearningProjections.rst
@@ -1,7 +1,7 @@
 Learning Projections
 ====================
 
-**Base class**:
+**Core class**:
 
 * `LearningProjection`
 

diff --git a/docs/source/ObjectiveMechanisms.rst b/docs/source/ObjectiveMechanisms.rst
@@ -1,7 +1,7 @@
 Objective Mechanisms
 ====================
 
-**Base class**:
+**Core class**:
 
 * `ObjectiveMechanism`
 

diff --git a/docs/source/TransferMechanisms.rst b/docs/source/TransferMechanisms.rst
@@ -1,7 +1,7 @@
 Transfer Mechanisms
 ===================
 
-**Base class**:
+**Core class**:
 
 * `TransferMechanism`
 

diff --git a/psyneulink/components/component.py b/psyneulink/components/component.py
@@ -1765,7 +1765,6 @@ def _instantiate_defaults(self,
             #    so that latter are evaluated in context of former
             for param_name, param_value in sorted(default_set.items()):
 
-                # MODIFIED 11/30/16 NEW:
                 # FUNCTION class has changed, so replace rather than update FUNCTION_PARAMS
                 if param_name is FUNCTION:
                     try:
@@ -1778,27 +1777,22 @@ def _instantiate_defaults(self,
                     except UnboundLocalError:
                         pass
                 # FIX: MAY NEED TO ALSO ALLOW assign_default_FUNCTION_PARAMS FOR COMMAND_LINE IN CONTEXT
-                # MODIFIED 11/30/16 END
 
                 if param_name is FUNCTION_PARAMS and not self.assign_default_FUNCTION_PARAMS:
                     continue
 
-                # MODIFIED 11/29/16 NEW:
                 # Don't replace requested entry with default
                 if param_name in request_set:
                     continue
-                # MODIFIED 11/29/16 END
 
                 # Add to request_set any entries it is missing fron the default_set
                 request_set.setdefault(param_name, param_value)
                 # Update any values in a dict
                 if isinstance(param_value, dict):
                     for dict_entry_name, dict_entry_value in param_value.items():
-                        # MODIFIED 11/29/16 NEW:
                         # Don't replace requested entries
                         if dict_entry_name in request_set[param_name]:
                             continue
-                        # MODIFIED 11/29/16 END
                         request_set[param_name].setdefault(dict_entry_name, dict_entry_value)
 
         # VALIDATE PARAMS
@@ -1813,11 +1807,6 @@ def _instantiate_defaults(self,
             #                       any override of _validate_params, which (should not, but) may process params
             #                       before calling super()._validate_params
             for param_name, param_value in request_set.items():
-                # # MODIFIED 11/25/17 OLD:
-                # if isinstance(param_value, tuple):
-                #     param_value = self._get_param_value_from_tuple(param_value)
-                #     request_set[param_name] = param_value
-                # MODIFIED 11/25/17 NEW:
                 if isinstance(param_value, tuple):
                     param_value = self._get_param_value_from_tuple(param_value)
                 elif isinstance(param_value, (str, Component, type)):
@@ -1826,7 +1815,6 @@ def _instantiate_defaults(self,
                 else:
                     continue
                 request_set[param_name] = param_value
-                # MODIFIED 11/25/17 END:
 
             try:
                 self._validate_params(variable=variable,
@@ -1887,11 +1875,7 @@ def _assign_params(self, request_set:tc.optional(dict)=None, context=None):
 
         self._instantiate_defaults(request_set=request_set,
                                    target_set=validated_set,
-                                   # # MODIFIED 4/14/17 OLD:
-                                   # assign_missing=False,
-                                   # MODIFIED 4/14/17 NEW:
-                                   assign_missing=False,
-                                   # MODIFIED 4/14/17 END
+                                    assign_missing=False,
                                    context=context)
 
         self.paramInstanceDefaults.update(validated_set)
@@ -2086,7 +2070,6 @@ def _validate_params(self, request_set, target_set=None, context=None):
                 raise ComponentError("{0} is not a valid parameter for {1}".format(param_name, self.__class__.__name__))
 
             # The value of the param is None in paramClassDefaults: suppress type checking
-            # DOCUMENT:
             # IMPLEMENTATION NOTE: this can be used for params with multiple possible types,
             #                      until type lists are implemented (see below)
             if self.paramClassDefaults[param_name] is None or self.paramClassDefaults[param_name] is NotImplemented:
@@ -2100,18 +2083,14 @@ def _validate_params(self, request_set, target_set=None, context=None):
             # If the value in paramClassDefault is a type, check if param value is an instance of it
             if inspect.isclass(self.paramClassDefaults[param_name]):
                 if isinstance(param_value, self.paramClassDefaults[param_name]):
-                    # MODIFIED 2/14/17 NEW:
                     target_set[param_name] = param_value
-                    # MODIFIED 2/14/17 END
                     continue
                 # If the value is a Function class, allow any instance of Function class
                 from psyneulink.components.functions.function import Function_Base
                 if issubclass(self.paramClassDefaults[param_name], Function_Base):
                     # if isinstance(param_value, (function_type, Function_Base)):  <- would allow function of any kind
                     if isinstance(param_value, Function_Base):
-                        # MODIFIED 2/14/17 NEW:
                         target_set[param_name] = param_value
-                        # MODIFIED 2/14/17 END
                         continue
 
             # If the value in paramClassDefault is an object, check if param value is the corresponding class
@@ -2247,7 +2226,6 @@ def _validate_params(self, request_set, target_set=None, context=None):
                 raise ComponentError("Value of {} param for {} ({}) is not compatible with {}".
                                     format(param_name, self.name, param_value, type_name))
 
-    # MODIFIED 11/25/17 NEW:
     def _get_param_value_for_modulatory_spec(self, param_name, param_value):
         from psyneulink.globals.keywords import MODULATORY_SPEC_KEYWORDS
         if isinstance(param_value, str):
@@ -2273,8 +2251,6 @@ def _get_param_value_for_modulatory_spec(self, param_name, param_value):
             raise ComponentError("PROGRAM ERROR: Could not get default value for {} of {} (to replace spec as {})".
                                  format(param_name, self.name, param_value))
 
-    # MODIFIED 11/25/17 END:
-
     def _get_param_value_from_tuple(self, param_spec):
         """Returns param value (first item) of a (value, projection) tuple;
         """

diff --git a/psyneulink/components/process.py b/psyneulink/components/process.py
@@ -1029,10 +1029,12 @@ def _instantiate_pathway(self, context):
         self._instantiate__deferred_inits(context=context)
 
         if self.learning:
-            self._check_for_target_mechanisms()
-            if self._target_mechs:
-                self._instantiate_target_input(context=context)
-            self._learning_enabled = True
+            if self._check_for_target_mechanisms():
+                if self._target_mechs:
+                    self._instantiate_target_input(context=context)
+                self._learning_enabled = True
+            else:
+                self._learning_enabled = False
         else:
             self._learning_enabled = False
 
@@ -1934,6 +1936,8 @@ def _check_for_target_mechanisms(self):
          Identify TARGET Mechanisms and assign to self.target_mechanisms,
              assign self to each TARGET Mechanism
              and report assignment if verbose
+
+         Returns True of TARGET Mechanisms are found and/or assigned, else False
         """
 
         from psyneulink.components.mechanisms.processing.objectivemechanism import ObjectiveMechanism
@@ -1970,8 +1974,18 @@ def trace_learning_objective_mechanism_projections(mech):
                             if (isinstance(object_item, ObjectiveMechanism) and
                                 object_item._learning_role is TARGET))
 
-        if not target_mechs:
+        if target_mechs:
+
+            # self.target_mechanisms = target_mechs
+            self._target_mechs = target_mechs
+            if self.prefs.verbosePref:
+                print("\'{}\' assigned as TARGET Mechanism(s) for \'{}\'".
+                      format([mech.name for mech in self._target_mechs], self.name))
+            return True
+
 
+        # No target_mechs already specified, so get from learning_mechanism
+        elif self._learning_mechs:
             last_learning_mech  = self._learning_mechs[0]
 
             # Trace projections to first learning ObjectiveMechanism, which is for the last mechanism in the process,
@@ -2005,13 +2019,10 @@ def trace_learning_objective_mechanism_projections(mech):
 
                 raise ProcessError("PROGRAM ERROR: {} has a learning specification ({}) "
                                    "but no TARGET ObjectiveMechanism".format(self.name, self.learning))
+            return True
 
         else:
-            # self.target_mechanisms = target_mechs
-            self._target_mechs = target_mechs
-            if self.prefs.verbosePref:
-                print("\'{}\' assigned as TARGET Mechanism(s) for \'{}\'".
-                      format([mech.name for mech in self._target_mechs], self.name))
+            return False
 
     def _instantiate_target_input(self, context=None):