Feat/log/log levels

psyneulink/components/mechanisms/mechanism.py

@@ -2434,6 +2434,7 @@ def value(self):
     @value.setter
     def value(self, assignment):
         self._value = assignment
+        self.log._log_value(assignment)
 
         # # MODIFIED 1/28/17 NEW: [COPIED FROM State]
         # # Store value in log if specified

psyneulink/components/process.py

@@ -2289,6 +2289,8 @@ def _execute_learning(self, target=None, clock=CentralClock, context=None):
                             # Note: do this rather just calling LearningSignals directly
                             #       since parameter_state.update() handles parsing of LearningProjection-specific params
                             context = context + SEPARATOR_BAR + LEARNING
+                            # FIX: IMPLEMENT EXECUTION+LEARNING CONDITION
+                            # context = context.replace(EXECUTING, LEARNING + ' ')
 
                             # NOTE: This will need to be updated when runtime params are re-enabled
                             # parameter_state.update(params=params, time_scale=TimeScale.TRIAL, context=context)

psyneulink/components/projections/pathway/mappingprojection.py

@@ -658,28 +658,6 @@ def matrix(self, matrix):
 
         self.function_object.matrix = matrix
 
-        # # Log matrix value if specified by owner, sender, or sender's owner
-        #
-        # # Get context
-        # try:
-        #     curr_frame = inspect.currentframe()
-        #     prev_frame = inspect.getouterframes(curr_frame, 2)
-        #     context = inspect.getargvalues(prev_frame[2][0]).locals['context']
-        # except KeyError:
-        #     context = ""
-
-        # # Get logPref
-        # self_log_pref = self.prefs.logPref if self.prefs else None
-        #
-        # # Go through loggers, and if context is consistent with log_pref of logger, record value to logger's log
-        # for log_name, log, log_pref in loggers:
-        #     if (log_pref is LogLevel.ALL_ASSIGNMENTS or
-        #             (INITIALIZING in context and log_pref is LogLevel.INITIALIZATION) or
-        #             (EXECUTING in context and log_pref is LogLevel.EXECUTION) or
-        #             (all(c in context for c in {EXECUTING, kwAssign}) and log_pref is LogLevel.VALUE_ASSIGNMENT)):
-        #         log.entries[self.name] = LogEntry(CurrentTime(), context, matrix)
-
-
     @property
     def _matrix_spec(self):
         """Returns matrix specification in self.paramsCurrent[FUNCTION_PARAMS][MATRIX]

psyneulink/components/projections/projection.py

@@ -403,7 +403,7 @@
 from psyneulink.globals.preferences.preferenceset import PreferenceLevel
 from psyneulink.globals.registry import register_category
 from psyneulink.globals.utilities import ContentAddressableList, iscompatible, is_numeric, is_matrix, type_match
-from psyneulink.globals.log import LogLevel, LogEntry
+from psyneulink.globals.log import LogLevel, LogEntry, _get_log_context
 from psyneulink.scheduling.timescale import CurrentTime
 
 __all__ = [
@@ -965,33 +965,8 @@ def value(self):
 
     @value.setter
     def value(self, assignment):
-
         self._value = assignment
-
-        # STORE value IN log IF SPECIFIED
-
-        # Get context
-        try:
-            curr_frame = inspect.currentframe()
-            prev_frame = inspect.getouterframes(curr_frame, 2)
-            # context = inspect.getargvalues(prev_frame[1][0]).locals['context']
-            context = inspect.getargvalues(prev_frame[2][0]).locals['context']
-        except KeyError:
-            context = ""
-        if not isinstance(context, str):
-            context = ""
-
-        # Get logPref
-        log_pref = self.prefs.logPref if self.prefs else None
-
-        # If context is consistent with log_pref, record value to log
-        if (log_pref is LogLevel.ALL_ASSIGNMENTS or
-                (INITIALIZING in context and log_pref is LogLevel.INITIALIZATION) or
-                (EXECUTING in context and log_pref is LogLevel.EXECUTION) or
-                (all(c in context for c in {EXECUTING, kwAssign}) and log_pref is LogLevel.VALUE_ASSIGNMENT)
-        ):
-            self.log.entries[self.name] = LogEntry(CurrentTime(), context, assignment)
-
+        self.log._log_value(assignment)
 
 @tc.typecheck
 def _is_projection_spec(spec, proj_type:tc.optional(type)=None, include_matrix_spec=True):

psyneulink/components/states/modulatorysignals/controlsignal.py

@@ -1271,6 +1271,8 @@ def value(self):
             # FIX: NEED TO DEAL WITH LOGGING HERE (AS PER @PROPERTY State.value)
             return self._intensity
 
+
     @value.setter
     def value(self, assignment):
         self._value = assignment
+        self.log._log_value(assignment)

psyneulink/components/states/state.py

@@ -741,7 +741,7 @@ def test_multiple_modulatory_projections_with_mech_and_state_name_specs(self):
     PREFS_ARG, PROJECTIONS, PROJECTION_PARAMS, PROJECTION_TYPE, RECEIVER, REFERENCE_VALUE, REFERENCE_VALUE_NAME, \
     SENDER, SIZE, STANDARD_OUTPUT_STATES, STATE, STATE_PARAMS, STATE_TYPE, STATE_VALUE, VALUE, VARIABLE, \
     kwAssign, kwStateComponentCategory, kwStateContext, kwStateName, kwStatePrefs
-from psyneulink.globals.log import LogEntry, LogLevel
+from psyneulink.globals.log import LogEntry, LogLevel, _get_log_context
 from psyneulink.globals.preferences.componentpreferenceset import kpVerbosePref
 from psyneulink.globals.preferences.preferenceset import PreferenceLevel
 from psyneulink.globals.registry import register_category
@@ -2052,28 +2052,7 @@ def value(self, assignment):
         # MODIFIED 7/8/17 END
 
         self._value = assignment
-
-        # STORE value IN log IF SPECIFIED
-
-        # Get context
-        try:
-            curr_frame = inspect.currentframe()
-            prev_frame = inspect.getouterframes(curr_frame, 2)
-            context = inspect.getargvalues(prev_frame[1][0]).locals['context']
-        except KeyError:
-            context = ""
-
-        # Get logPref
-        log_pref = self.prefs.logPref if self.prefs else None
-
-
-        # If context is consistent with log_pref, record value to log
-        if (log_pref is LogLevel.ALL_ASSIGNMENTS or
-                (INITIALIZING in context and log_pref is LogLevel.INITIALIZATION) or
-                ((EXECUTING in context and not LEARNING in context) and log_pref is LogLevel.EXECUTION) or
-                (all(c in context for c in {EXECUTING, kwAssign}) and log_pref is LogLevel.VALUE_ASSIGNMENT)
-        ):
-            self.log.entries[self.name] = LogEntry(CurrentTime(), context, assignment)
+        self.log._log_value(assignment)
 
     @property
     def projections(self):

psyneulink/components/system.py

@@ -442,9 +442,14 @@
 from psyneulink.components.shellclasses import Mechanism, Process_Base, System_Base
 from psyneulink.components.states.inputstate import InputState
 from psyneulink.components.states.state import _parse_state_spec
-from psyneulink.globals.keywords import ALL, COMPONENT_INIT, CONROLLER_PHASE_SPEC, CONTROL, CONTROLLER, CYCLE, EVC_SIMULATION, EXECUTING, EXPONENT, FUNCTION, IDENTITY_MATRIX, INITIALIZED, INITIALIZE_CYCLE, INITIALIZING, INITIAL_VALUES, INTERNAL, LEARNING, LEARNING_SIGNAL, MATRIX, MONITOR_FOR_CONTROL, ORIGIN, PARAMS, PROJECTIONS, SAMPLE, SINGLETON, SYSTEM, SYSTEM_INIT, TARGET, TERMINAL, TIME_SCALE, WEIGHT, kwSeparator, kwSystemComponentCategory
+from psyneulink.globals.keywords import ALL, COMPONENT_INIT, CONROLLER_PHASE_SPEC, CONTROL, CONTROLLER, CYCLE, \
+    EVC_SIMULATION, EXECUTING, EXPONENT, FUNCTION, IDENTITY_MATRIX, INITIALIZED, INITIALIZE_CYCLE, INITIALIZING, \
+    INITIAL_VALUES, INTERNAL, LEARNING, LEARNING_SIGNAL, MATRIX, MONITOR_FOR_CONTROL, ORIGIN, PARAMS, PROJECTIONS, \
+    SAMPLE, SINGLETON, SYSTEM, SYSTEM_INIT, TARGET, TERMINAL, TIME_SCALE, WEIGHT, kwSeparator, \
+    kwSystemComponentCategory, SEPARATOR_BAR
 from psyneulink.globals.preferences.componentpreferenceset import is_pref_set
 from psyneulink.globals.preferences.preferenceset import PreferenceLevel
+from psyneulink.globals.log import Log
 from psyneulink.globals.registry import register_category
 from psyneulink.globals.utilities import AutoNumber, ContentAddressableList, append_type_to_name, convert_to_np_array, iscompatible
 from psyneulink.scheduling.scheduler import Scheduler
@@ -2533,7 +2538,9 @@ def execute(self,
 
         # Don't execute learning for simulation runs
         if not EVC_SIMULATION in context and self.learning:
-            self._execute_learning(clock=clock, context=context + ' ' + LEARNING)
+            self._execute_learning(clock=clock, context=context + SEPARATOR_BAR + LEARNING)
+            # FIX: IMPLEMENT EXECUTION+LEARNING CONDITION
+            # self._execute_learning(clock=clock, context=context.replace(EXECUTING, LEARNING + ' '))
         # endregion
 
 
@@ -3571,6 +3578,8 @@ def __init__(self, owner=None, variable=None, name=None, prefs=None):
         else:
             self.name = owner.name + "_" + name
         self.prefs = prefs
+        self.log = Log(owner=self)
+        self.recording = False
         self.efferents = []
         self.owner = owner
         self.value = variable

psyneulink/globals/environment.py

@@ -1029,4 +1029,4 @@ def _get_object_type(object):
 
 import uuid
 def _get_unique_id():
-    return uuid.uuid4()
+    return uuid.uuid4()

psyneulink/globals/keywords.py

@@ -37,15 +37,17 @@
     'DEFERRED_ASSIGNMENT', 'DEFERRED_DEFAULT_NAME', 'DEFERRED_INITIALIZATION', 'DIFFERENCE', 'DIFFERENCE', 'DIFFUSION',
     'DIST_FUNCTION_TYPE', 'DIST_MEAN', 'DIST_SHAPE', 'DISTANCE_FUNCTION', 'DISTANCE_METRICS', 'DISTRIBUTION_FUNCTION_TYPE',
     'DIVISION', 'DRIFT_DIFFUSION_INTEGRATOR_FUNCTION', 'DRIFT_RATE', 'ENABLE_CONTROLLER', 'ENABLED', 'ENERGY', 'ENTROPY',
-    'ERROR_DERIVATIVE_FUNCTION', 'EUCLIDEAN', 'EVC_MECHANISM', 'EVC_SIMULATION', 'EXAMPLE_FUNCTION_TYPE', 'EXECUTING',
-    'EXPONENT', 'EXPONENTIAL_DIST_FUNCTION', 'EXPONENTIAL_FUNCTION', 'EXPONENTS', 'FHN_INTEGRATOR_FUNCTION', 'FULL',
-    'FULL_CONNECTIVITY_MATRIX', 'FUNCTION', 'FUNCTION_CHECK_ARGS', 'FUNCTION_OUTPUT_TYPE',
+    'ERROR_DERIVATIVE_FUNCTION', 'EUCLIDEAN', 'EVC_MECHANISM', 'EVC_SIMULATION', 'EXAMPLE_FUNCTION_TYPE',
+    'EXECUTING', 'EXECUTION', 'EXPONENT', 'EXPONENTIAL_DIST_FUNCTION', 'EXPONENTIAL_FUNCTION', 'EXPONENTS',
+    'FHN_INTEGRATOR_FUNCTION', 'FINAL', 'FULL', 'FULL_CONNECTIVITY_MATRIX',
+    'FUNCTION', 'FUNCTION_CHECK_ARGS', 'FUNCTION_OUTPUT_TYPE',
     'FUNCTION_OUTPUT_TYPE_CONVERSION', 'FUNCTION_PARAMS', 'GAIN', 'GAMMA_DIST_FUNCTION', 'GATE', 'GATING',
     'GATING_MECHANISM', 'GATING_POLICY', 'GATING_PROJECTION', 'GATING_PROJECTION_PARAMS', 'GATING_PROJECTIONS',
     'GATING_SIGNAL', 'GATING_SIGNAL_SPECS', 'GATING_SIGNALS', 'GILZENRAT_INTEGRATOR_FUNCTION', 'HARD_CLAMP',
     'HEBBIAN_FUNCTION', 'HETERO', 'HIGH', 'HOLLOW_MATRIX', 'IDENTITY_MATRIX', 'INCREMENT', 'INDEX',
     'INIT__EXECUTE__METHOD_ONLY', 'INIT_FULL_EXECUTE_METHOD', 'INIT_FUNCTION_METHOD_ONLY', 'INITIAL_VALUES',
-    'INITIALIZE_CYCLE', 'INITIALIZED', 'INITIALIZER', 'INITIALIZING', 'INPUT_STATE', 'INPUT_STATE_PARAMS', 'INPUT_STATES',
+    'INITIALIZE_CYCLE', 'INITIALIZATION', 'INITIALIZED', 'INITIALIZER', 'INITIALIZING', 'INPUT_STATE',
+    'INPUT_STATE_PARAMS', 'INPUT_STATES',
     'INPUTS_DIM', 'INTEGRATION_TYPE', 'INTEGRATOR_FUNCTION', 'INTEGRATOR_FUNCTION', 'INTEGRATOR_FUNCTION_TYPE',
     'INTEGRATOR_MECHANISM', 'INTERCEPT', 'INTERNAL', 'K_VALUE', 'kpMechanismControlAllocationsLogEntry',
     'kpMechanismExecutedLogEntry', 'kpMechanismInputLogEntry', 'kpMechanismOutputLogEntry', 'kpMechanismTimeScaleLogEntry',
@@ -73,7 +75,7 @@
     'OUTPUT_STATE', 'OUTPUT_STATE_PARAMS', 'OUTPUT_STATES', 'OUTPUT_TYPE', 'OWNER', 'PARAM_CLASS_DEFAULTS',
     'PARAM_INSTANCE_DEFAULTS', 'PARAMETER_STATE', 'PARAMETER_STATE_PARAMS', 'PARAMETER_STATES', 'PARAMS',
     'PARAMS_CURRENT', 'PATHWAY', 'PATHWAY_PROJECTION', 'PEARSON', 'PREDICTION_MECHANISM', 'PREDICTION_MECHANISM_OUTPUT',
-    'PREDICTION_MECHANISM_PARAMS', 'PREDICTION_MECHANISM_TYPE', 'PREFS_ARG', 'PRIMARY', 'PROB', 'PROCESS',
+    'PREDICTION_MECHANISM_PARAMS', 'PREDICTION_MECHANISM_TYPE', 'PREFS_ARG', 'PRIMARY', 'PROB', 'PROCESS', 'PROCESSING',
     'PROCESS_INIT', 'PROCESSES', 'PROCESSES_DIM', 'PROCESSING_MECHANISM', 'PRODUCT', 'PROJECTION',
     'PROJECTION_PARAMS', 'PROJECTION_SENDER', 'PROJECTION_SENDER_VALUE', 'PROJECTION_TYPE', 'PROJECTIONS',
     'QUOTIENT', 'RANDOM_CONNECTIVITY_MATRIX', 'RATE', 'RATIO', 'RECEIVER', 'RECURRENT_TRANSFER_MECHANISM',
@@ -84,8 +86,8 @@
     'STATE_TYPE', 'STATE_VALUE', 'STATES', 'SUBTRACTION', 'SUM', 'SYSTEM', 'SYSTEM_DEFAULT_CONTROLLER',
     'SYSTEM_INIT', 'TARGET', 'TERMINAL', 'THRESHOLD', 'TIME_SCALE', 'TIME_STEP_SIZE', 'TIME_STEPS_DIM',
     'TRANSFER_FUNCTION_TYPE', 'TRANSFER_MECHANISM', 'TRIALS_DIM', 'UNCHANGED', 'UNIFORM_DIST_FUNCTION',
-    'USER_DEFINED_FUNCTION', 'USER_DEFINED_FUNCTION_TYPE', 'USER_PARAMS', 'UTILITY_INTEGRATOR_FUNCTION', 'VALIDATE',
-    'VALUE', 'VALUE_FUNCTION', 'VARIABLE', 'VARIANCE', 'VECTOR',
+    'USER_DEFINED_FUNCTION', 'USER_DEFINED_FUNCTION_TYPE', 'USER_PARAMS', 'UTILITY_INTEGRATOR_FUNCTION',
+    'VALIDATE', 'VALIDATION', 'VALUE', 'VALUE_ASSIGNMENT', 'VALUE_FUNCTION', 'VARIABLE', 'VARIANCE', 'VECTOR',
     'WALD_DIST_FUNCTION', 'WEIGHT', 'WEIGHTS',
 ]
 
@@ -382,6 +384,14 @@ def _is_metric(metric):
 kwContext = 'Context'
 kwValue = 'Value'
 LOG_ENTRIES = 'LOG_ENTRIES'
+INITIALIZATION = 'INITIALIZATION'
+VALIDATION = 'VALIDATION'
+EXECUTION = 'EXECUTION'
+PROCESSING = 'PROCESSING'
+VALUE_ASSIGNMENT = 'VALUE_ASSIGNMENT'
+FINAL = 'FINAL'
+
+
 #endregion
 
 #region -----------------------------------------------  UTILITIES  ----------------------------------------------------
@@ -577,7 +587,7 @@ def _is_metric(metric):
 HARD_CLAMP = "hard_clamp"
 LEARNING = 'LEARNING'
 LEARNING_RATE = "learning_rate"
-CONTROL = 'control'
+CONTROL = 'CONTROL'
 GATING = 'gating'
 kwProjections = "projections"
 kwProcessDefaultProjectionFunction = "Default Projection Function"