Devel

.github/actions/install-pnl/action.yml

@@ -18,7 +18,7 @@ runs:
       run: |
         case "$RUNNER_OS" in
           macOS*) brew install graphviz ;;
-          Linux*) sudo apt-get install -y graphviz ;;
+          Linux*) sudo apt-get update && sudo apt-get install -y --no-install-recommends graphviz ;;
           Windows*) choco install --no-progress -y graphviz --version=2.38.0.20190211 ;;
           *) echo "Unsupported OS"; exit 1 ;;
         esac
@@ -42,6 +42,7 @@ runs:
       run: |
         if [ $(python -c 'import struct; print(struct.calcsize("P") * 8)') == 32 ]; then
           sed -i /torch/d requirements.txt
+          sed -i /modeci_mdf/d requirements.txt
           # pywinpty is a transitive dependency and v1.0+ removed support for x86 wheels
           # terminado >= 0.10.0 pulls in pywinpty >= 1.1.0
           [[ ${{ runner.os }} = Windows* ]] && pip install "pywinpty<1" "terminado<0.10"

.github/workflows/pnl-ci-docs.yml

@@ -39,20 +39,24 @@ jobs:
       on_master: ${{ steps.on_master.outputs.on-branch }}
 
     steps:
+    # increased fetch-depth and tag checkout needed as in pnl-ci.yml
     - name: Checkout sources
-      uses: actions/checkout@v2.4.0
+      uses: actions/checkout@v3
       if: ${{ matrix.pnl-version == 'head' }}
       with:
-        fetch-depth: 10
+        fetch-depth: 200
         ref: ${{ github.ref }}
 
     - name: Checkout pull base
-      uses: actions/checkout@v2.4.0
+      uses: actions/checkout@v3
       if: ${{ matrix.pnl-version == 'base' }}
       with:
-        fetch-depth: 10
+        fetch-depth: 200
         ref: ${{ github.base_ref }}
 
+    - name: Checkout tags
+      run: git fetch --tags origin master
+
     - name: Check if on master
       if: ${{ github.event_name == 'push' }}
       id: on_master
@@ -61,7 +65,7 @@ jobs:
         branch: master
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2.3.1
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
         architecture: ${{ matrix.python-architecture }}
@@ -75,7 +79,7 @@ jobs:
         echo ::set-output name=pip_cache_dir::$(python -m pip cache dir)
 
     - name: Wheels cache
-      uses: actions/cache@v2.1.7
+      uses: actions/cache@v3
       with:
         path: ${{ steps.pip_cache.outputs.pip_cache_dir }}/wheels
         key: ${{ runner.os }}-python-${{ matrix.python-version }}-${{ matrix.python-architecture }}-pip-wheels-v2-${{ github.sha }}
@@ -103,7 +107,7 @@ jobs:
       run: git tag -d 'v999.999.999.999'
 
     - name: Upload Documentation
-      uses: actions/upload-artifact@v2.3.1
+      uses: actions/upload-artifact@v3
       with:
         name: Documentation-${{matrix.pnl-version}}-${{ matrix.os }}-${{ matrix.python-version }}-${{ matrix.python-architecture }}
         retention-days: 1
@@ -115,7 +119,7 @@ jobs:
 
     - name: Upload PR number for other workflows
       if: ${{ github.event_name == 'pull_request' }}
-      uses: actions/upload-artifact@v2.3.1
+      uses: actions/upload-artifact@v3
       with:
           name: pr_number
           path: ./pr_number.txt
@@ -142,7 +146,7 @@ jobs:
 
     steps:
     - name: Checkout docs
-      uses: actions/checkout@v2.4.0
+      uses: actions/checkout@v3
       with:
         ref: gh-pages
 

.github/workflows/pnl-ci.yml

@@ -40,13 +40,21 @@ jobs:
             os: macos-latest
 
     steps:
+    # increased fetch-depth and tag checkout needed to get correct
+    # version string from versioneer (must have history to a prior tag);
+    # otherwise install fails due to circular dependency with modeci_mdf
     - name: Checkout sources
-      uses: actions/checkout@v2.4.0
+      uses: actions/checkout@v3
       with:
-        fetch-depth: 10
+        fetch-depth: 200
+
+    # fetch only master to avoid getting unneeded branches with
+    # characters invalid on windows
+    - name: Checkout tags
+      run: git fetch --tags origin master
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2.3.1
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
         architecture: ${{ matrix.python-architecture }}
@@ -60,7 +68,7 @@ jobs:
         echo ::set-output name=pip_cache_dir::$(python -m pip cache dir)
 
     - name: Wheels cache
-      uses: actions/cache@v2.1.7
+      uses: actions/cache@v3
       with:
         path: ${{ steps.pip_cache.outputs.pip_cache_dir }}/wheels
         key: ${{ runner.os }}-python-${{ matrix.python-version }}-${{ matrix.python-architecture }}-pip-wheels-v2-${{ github.sha }}
@@ -85,7 +93,7 @@ jobs:
       run: pytest --junit-xml=tests_out.xml --verbosity=0 -n auto ${{ matrix.extra-args }}
 
     - name: Upload test results
-      uses: actions/upload-artifact@v2.3.1
+      uses: actions/upload-artifact@v3
       with:
         name: test-results-${{ matrix.os }}-${{ matrix.python-version }}-${{ matrix.python-architecture }}-${{ matrix.extra-args }}
         path: tests_out.xml
@@ -111,7 +119,7 @@ jobs:
         python setup.py sdist bdist_wheel
 
     - name: Upload dist packages
-      uses: actions/upload-artifact@v2.3.1
+      uses: actions/upload-artifact@v3
       with:
         name: dist-${{ matrix.os }}-${{ matrix.python-version }}-${{ matrix.python-architecture }}
         path: dist/

.github/workflows/test-release.yml

@@ -18,10 +18,10 @@ jobs:
       wheel: ${{ steps.create_dist.outputs.wheel }}
     steps:
     - name: Checkout sources
-      uses: actions/checkout@v2.4.0
+      uses: actions/checkout@v3
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2.3.1
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
 
@@ -38,7 +38,7 @@ jobs:
         echo ::set-output name=wheel::$(ls *.whl)
 
     - name: Upload Python dist files
-      uses: actions/upload-artifact@v2.3.1
+      uses: actions/upload-artifact@v3
       with:
         name: Python-dist-files
         path: dist/
@@ -84,7 +84,7 @@ jobs:
         path: dist/
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2.3.1
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
 
@@ -113,7 +113,7 @@ jobs:
       run: pip install dist/${{ needs.create-python-dist.outputs.sdist }}[dev]
 
     - name: Get tests from the repository
-      uses: actions/checkout@v2.4.0
+      uses: actions/checkout@v3
 
     - name: Run tests
       shell: bash
@@ -126,7 +126,7 @@ jobs:
         pytest  --junit-xml=tests_out.xml --verbosity=0 -n auto tests
 
     - name: Upload test results
-      uses: actions/upload-artifact@v2.3.1
+      uses: actions/upload-artifact@v3
       with:
         name: test-results-${{ matrix.os }}-${{ matrix.python-version }}
         path: tests_out.xml

.gitignore

@@ -1,9 +1,16 @@
 
 # Created by https://www.gitignore.io/api/osx,python,pycharm
 
+# Ignore JSON files created in tests/json/
+# Maybe these should be generated in tmpdir instead
+tests/json/*.json
+
 # Log files created by SLURM jobs in this directory
 Scripts/Debug/predator_prey_opt/logs/
 
+# Any plots generated from testing DDMs
+Scripts/Debug/ddm/*.png
+
 ### OSX ###
 *.DS_Store
 .AppleDouble

README.rst

@@ -5,6 +5,10 @@
 .. image:: https://mybinder.org/badge.svg
     :target: https://mybinder.org/v2/gh/PrincetonUniversity/PsyNeuLink/master
 
+.. *****************************************************************************************
+.. ****** NOTE:  UPDATES TO THIS PAGE SHOULD ALSO BE MADE TO docs/source.index.rst *********
+.. *****************************************************************************************
+
 
 Welcome to PsyNeuLink
 =====================

Scripts/Debug/Jason_Reward_rate_with_penalty_with_inputs.py

@@ -119,8 +119,8 @@ def get_stroop_model(unit_noise_std=.01, dec_noise_std=.1):
                        function=pnl.DriftDiffusionAnalytical(drift_rate=1,
                                                              threshold =1,
                                                              noise=1,
-                                                             starting_point=0,
-                                                             t0=0.35),
+                                                             starting_value=0,
+                                                             non_decision_time=0.35),
                        output_ports=[pnl.RESPONSE_TIME,
                                      pnl.PROBABILITY_UPPER_THRESHOLD,
                                      pnl.PROBABILITY_LOWER_THRESHOLD]
@@ -204,7 +204,7 @@ def get_stroop_model(unit_noise_std=.01, dec_noise_std=.1):
                                                                   inp_task.input_port,
                                                                   reward.input_port,
                                                                   punish.input_port],
-                                                  state_feature_functions=pnl.AdaptiveIntegrator(rate=0.1),
+                                                  state_feature_function=pnl.AdaptiveIntegrator(rate=0.1),
                                                   objective_mechanism=objective_mech,
                                                   function=pnl.GridSearch(),
                                                   control_signals=[driftrate_control_signal,

Scripts/Debug/Predator-Prey Sebastian REDUCED.py

@@ -62,7 +62,7 @@ def get_new_episode_flag():
 
 ocm = OptimizationControlMechanism(name='EVC',
                                    state_features=[trial_type_input_mech],
-                                   # state_feature_functions=FEATURE_FUNCTION,
+                                   # state_feature_function=FEATURE_FUNCTION,
                                    agent_rep=RegressionCFA(
                                            name='RegressionCFA',
                                            update_weights=BayesGLM(mu_0=0.5, sigma_0=0.1),

Scripts/Debug/Predator-Prey Sebastian.py

@@ -167,7 +167,7 @@ def get_action(variable=[[0,0],[0,0],[0,0]]):
 
 ocm = OptimizationControlMechanism(name='EVC',
                                    state_features=[trial_type_input_mech],
-                                   # state_feature_functions=FEATURE_FUNCTION,
+                                   # state_feature_function=FEATURE_FUNCTION,
                                    agent_rep=RegressionCFA(
                                            name='RegressionCFA',
                                            update_weights=BayesGLM(mu_0=0.5, sigma_0=0.1),

Scripts/Debug/StabilityFlexibility.py

@@ -69,7 +69,7 @@ def computeAccuracy(variable):
 gain = np.asarray([[g]])
 
 DRIFT = 1 # Drift Rate
-STARTING_POINT = 0.0 # Starting Point
+STARTING_VALUE = 0.0 # Starting Point
 THRESHOLD = 0.0475 # Threshold
 NOISE = 0.04 # Noise
 T0 = 0.2 # T0
@@ -123,10 +123,10 @@ def computeAccuracy(variable):
 ddmCombination.set_log_conditions([pnl.RESULT])
 
 decisionMaker = pnl.DDM(function=pnl.DriftDiffusionAnalytical(drift_rate = DRIFT,
-                                                                 starting_point = STARTING_POINT,
+                                                                 starting_value = STARTING_VALUE,
                                                                  threshold = THRESHOLD,
                                                                  noise = NOISE,
-                                                                 t0 = T0),
+                                                                 non_decision_time = T0),
                                                                  output_ports = [pnl.DECISION_VARIABLE, pnl.RESPONSE_TIME,
                                                                                   pnl.PROBABILITY_UPPER_THRESHOLD, pnl.PROBABILITY_LOWER_THRESHOLD],
                                                                  name='DDM')

Scripts/Debug/Umemoto_Feb.py

@@ -13,7 +13,7 @@
 
 
 # EVC params for Umemoto et al
-t0 = 0.2
+non_decision_time = 0.2
 c = 0.19
 thresh = 0.21
 x_0 = 0 # starting point
@@ -59,8 +59,8 @@
        # drift_rate=(0.1170),
         threshold=(thresh),
         noise=(c),
-        starting_point=(x_0),
-        t0=t0
+        starting_value=(x_0),
+        non_decision_time=non_decision_time
     ),name='Decision',
     output_ports=[
         pnl.DECISION_VARIABLE,
@@ -71,7 +71,7 @@
             pnl.VARIABLE: (pnl.OWNER_VALUE, 2),
             pnl.FUNCTION: pnl.Linear(0, slope=1.0, intercept=1)
         }
-    ],) #drift_rate=(1.0),threshold=(0.2645),noise=(0.5),starting_point=(0), t0=0.15
+    ],) #drift_rate=(1.0),threshold=(0.2645),noise=(0.5),non_decision_time=(0), non_decision_time=0.15
 
 Decision.set_log_conditions('InputPort-0')#, log_condition=pnl.PROCESSING)
 
@@ -120,7 +120,7 @@
 
 Umemoto_comp.add_model_based_optimizer(optimizer=pnl.OptimizationControlMechanism(agent_rep=Umemoto_comp,
                                                                                   state_features=[Target_Stim.input_port, Distractor_Stim.input_port, Reward.input_port],
-                                                                                  state_feature_functions=pnl.AdaptiveIntegrator(rate=1.0),
+                                                                                  state_feature_function=pnl.AdaptiveIntegrator(rate=1.0),
                                                                                   objective_mechanism=pnl.ObjectiveMechanism(monitor_for_control=[Reward,
                                                                                                                                                  (Decision.output_ports[pnl.PROBABILITY_UPPER_THRESHOLD], 1, -1)],
                                                                                                                              ),

Scripts/Debug/Umemoto_Feb2.py

@@ -13,7 +13,7 @@
 
 
 # EVC params for Umemoto et al
-t0 = 0.2
+non_decision_time = 0.2
 c = 0.19
 thresh = 0.21
 x_0 = 0 # starting point
@@ -61,8 +61,8 @@
        # drift_rate=(0.1170),
         threshold=(thresh),
         noise=(c),
-        starting_point=(x_0),
-        t0=t0
+        starting_value=(x_0),
+        non_decision_time=non_decision_time
     ),name='Decision',
     output_ports=[
         pnl.DECISION_VARIABLE,
@@ -73,7 +73,7 @@
             pnl.VARIABLE: (pnl.OWNER_VALUE, 2),
             pnl.FUNCTION: pnl.Linear(0, slope=1.0, intercept=1)
         }
-    ],) #drift_rate=(1.0),threshold=(0.2645),noise=(0.5),starting_point=(0), t0=0.15
+    ],) #drift_rate=(1.0),threshold=(0.2645),noise=(0.5),non_decision_time=(0), non_decision_time=0.15
 
 Decision.set_log_conditions('InputPort-0')#, log_condition=pnl.PROCESSING)
 Decision.set_log_conditions('PROBABILITY_UPPER_THRESHOLD')
@@ -132,7 +132,7 @@
         state_features=[Target_Stim.input_port,
                         Distractor_Stim.input_port,
                         Reward.input_port],
-        state_feature_functions=pnl.AdaptiveIntegrator(rate=1.0),
+        state_feature_function=pnl.AdaptiveIntegrator(rate=1.0),
         objective_mechanism=pnl.ObjectiveMechanism(
                 monitor_for_control=[Reward,
                                      (Decision.output_ports[pnl.PROBABILITY_UPPER_THRESHOLD], 1, -1)],