NACLab · ago109 · May 1, 2026 · Jul 5, 2024 · Jul 6, 2024 · Jul 6, 2024
diff --git a/.github/workflows/python-package-conda.yml b/.github/workflows/python-package-conda.yml
@@ -10,25 +10,19 @@ jobs:
 
     steps:
     - uses: actions/checkout@v4
-    - name: Set up Python 3.10
-      uses: actions/setup-python@v3
+
+    - name: Install Miniconda
+      uses: conda-incubator/setup-miniconda@v2
       with:
-        python-version: '3.10'
-    - name: Add conda to system path
+        auto-update-conda: true
+        python-version: 3.11
+        environment-name: test
+
+    - name: Install dependencies
       run: |
-        # $CONDA is an environment variable pointing to the root of the miniconda directory
-        echo $CONDA/bin >> $GITHUB_PATH
-    - name: Install current library and dependencies
-      run: |
-        pip install -e .
-    # - name: Lint with flake8
-    #   run: |
-    #     conda install flake8
-    #     # stop the build if there are Python syntax errors or undefined names
-    #     flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-    #     # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-    #     flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
-    - name: Test with pytest
+        conda install -n test numpy=1.26 pytest pip
+        conda run -n test pip install -e .
+
+    - name: Run tests
       run: |
-        conda install pytest
-        pytest
+        conda run -n test pytest
diff --git a/AUTHORS b/AUTHORS
@@ -5,12 +5,14 @@
 # The email address is not required for organizations.
 
 Core Team
-Alexander Ororbia <ago@cs.rit.edu>
-William Gebhardt <wdg1351@rit.edu>
-Viet Dung Nguyen <vn1747@rit.edu>
-Ankur Mali <aam35@psu.edu>
+Alexander Ororbia <agocse109@gmail.com>
+William Gebhardt <wdg1351@g.rit.edu>
+Viet Dung Nguyen <vn1747@g.rit.edu>
+Ankur Mali <ankurmali07@gmail.com>
+Faeze Habibi <habibifaeze.66@gmail.com>
 
 Contributors
 Maxbeth2 (Ohas)
 pagrawal-psu
 pulinagrawal
+antonvice
diff --git a/CITATION.cff b/CITATION.cff
@@ -6,10 +6,12 @@ authors:
     orcid: https://orcid.org/0000-0002-2590-1310
   - family-names: Gebhardt
     given-names: William
+    orcid: https://orcid.org/0009-0008-7456-6556
   - family-names: Mali
     given-names: Ankur
+    orcid: https://orcid.org/0000-0001-5813-3584
 title: "ngc-learn"
-version: 1.0.0
+version: 3.0.0
 identifiers:
   - type: doi
     value: 10.5281/zenodo.6605728

diff --git a/README.md b/README.md
@@ -2,19 +2,15 @@
 
 <img src="docs/images/ngc-learn-logo.png" width="300">
 
-<b>ngc-learn</b> is a Python library for building, simulating, and analyzing
-biomimetic systems, neurobiological agents, spiking neuronal networks,
-predictive coding circuitry, and models that learn via biologically-plausible
-forms of credit assignment. This simulation toolkit is built on top of JAX and is
-distributed under the 3-Clause BSD license.
+<b>ngc-learn</b> is a Python library for building, simulating, and analyzing biophysical / neurobiological systems, spiking neuronal networks, predictive coding circuitry, and biomimetic (NeuroAI) agents that learn in a biologically-plausible manner. This simulation toolkit, meant to support computational neuroscience and brain-inspired computing research, is built on top of JAX and is distributed under the 3-Clause BSD license.
 
 It is currently maintained by the
 <a href="https://www.cs.rit.edu/~ago/nac_lab.html">Neural Adaptive Computing (NAC) laboratory</a>.
 
 ## <b>Documentation</b>
 
 Official documentation, including tutorials, can be found
-<a href="https://ngc-learn.readthedocs.io/en/latest/#">here</a>. The model museum repo,
+<a href="https://ngc-learn.readthedocs.io/en/latest/#">here</a>. The model museum repo (ngc-museum),
 which implements several historical models, can be found
 <a href="https://github.com/NACLab/ngc-museum">here</a>.
 
@@ -34,10 +30,10 @@ chosen as one of the <i>Editors' Highlights for Applied Physics and Mathematics<
 
 ngc-learn requires:
 1) Python (>=3.10)
-2) NumPy (>=1.26.0)
+2) NumPy (>=1.22.0)
 3) SciPy (>=1.7.0)
-4) ngcsimlib (>=0.3.b2), (visit official page <a href="https://github.com/NACLab/ngc-sim-lib">here</a>)
-5) JAX (>= 0.4.18) (to enable GPU use, make sure to install one of the CUDA variants)
+4) ngcsimlib (>=3.0.0), (visit official page <a href="https://github.com/NACLab/ngc-sim-lib">here</a>)
+5) JAX (>=0.4.28) (to enable GPU use, make sure to install one of the CUDA variants)
 <!--
 5) scikit-learn (>=1.3.1) if using `ngclearn.utils.density`
 6) matplotlib (>=3.4.3) if using `ngclearn.utils.viz`
@@ -46,7 +42,7 @@ ngc-learn requires:
 -->
 
 ---
-ngc-learn 1.2.beta0 and later require Python 3.10 or newer as well as ngcsimlib >=0.3.b3.
+ngc-learn 3.0.0 and later require Python 3.10 or newer as well as ngcsimlib >=3.0.0.
 ngc-learn's plotting capabilities (routines within `ngclearn.utils.viz`) require
 Matplotlib (>=3.8.0) and imageio (>=2.31.5) and both plotting and density estimation
 tools (routines within ``ngclearn.utils.density``) will require Scikit-learn (>=0.24.2).
@@ -66,7 +62,7 @@ running the above pip command if you want to use the GPU version.
 
 The documentation includes more detailed
 <a href="https://ngc-learn.readthedocs.io/en/latest/installation.html">installation instructions</a>.
-Note that this library was developed on Ubuntu 20.04 and tested on Ubuntu(s) 18.04 and 20.04.
+Note that this library was developed on Ubuntu 20.04/22.04 and tested on Ubuntu(s) 20.04 and 22.04.
 
 If the installation was successful, you should see the following if you test
 it against your Python interpreter, i.e., run the <code>$ python</code> command
@@ -79,7 +75,7 @@ Python 3.11.4 (main, MONTH  DAY YEAR, TIME) [GCC XX.X.X] on linux
 Type "help", "copyright", "credits" or "license" for more information.
 >>> import ngclearn
 >>> ngclearn.__version__
-'1.2b1'
+'3.0.0'
 ```
 
 <i>Note:</i> For access to the previous Tensorflow-2 version of ngc-learn (of
@@ -126,7 +122,7 @@ $ python install -e .
 </pre>
 
 **Version:**<br>
-1.2.1-Beta <!-- -Alpha -->
+3.0.1 <!--1.2.3-Beta--> <!-- -Alpha -->
 
 Author:
 Alexander G. Ororbia II<br>

diff --git a/docs/conf.py b/docs/conf.py
@@ -117,7 +117,7 @@
 html_logo = "images/ngc-learn-logo.png"
 html_theme_options = {
     'logo_only': True,
-    'display_version': True,
+    #'display_version': True,
 }
 
 # def setup(app):

diff --git a/docs/images/museum/ei_rnn/ei_rnn_arch.jpg b/docs/images/museum/ei_rnn/ei_rnn_arch.jpg
diff --git a/docs/images/museum/harmonium/rbm_arch.jpg b/docs/images/museum/harmonium/rbm_arch.jpg
diff --git a/docs/images/museum/harmonium/rbm_recon.jpg b/docs/images/museum/harmonium/rbm_recon.jpg
diff --git a/docs/images/museum/harmonium/receptive_fields.jpg b/docs/images/museum/harmonium/receptive_fields.jpg
diff --git a/docs/images/museum/harmonium/samples_0.jpg b/docs/images/museum/harmonium/samples_0.jpg
diff --git a/docs/images/museum/harmonium/samples_1.jpg b/docs/images/museum/harmonium/samples_1.jpg
diff --git a/docs/images/museum/harmonium/samples_2.jpg b/docs/images/museum/harmonium/samples_2.jpg
diff --git a/docs/images/museum/hgpc/GEC.png b/docs/images/museum/hgpc/GEC.png
diff --git a/docs/images/museum/hgpc/HGPC_inputL.jpg b/docs/images/museum/hgpc/HGPC_inputL.jpg
diff --git a/docs/images/museum/hgpc/Input_layer.png b/docs/images/museum/hgpc/Input_layer.png
diff --git a/docs/images/museum/hgpc/hgpc_model.png b/docs/images/museum/hgpc/hgpc_model.png
diff --git a/docs/images/museum/hgpc/patch_input.png b/docs/images/museum/hgpc/patch_input.png
diff --git a/docs/images/museum/rat_accuracy.jpg b/docs/images/museum/rat_accuracy.jpg
diff --git a/docs/images/museum/rat_rewards.jpg b/docs/images/museum/rat_rewards.jpg
diff --git a/docs/images/museum/ratmaze.png b/docs/images/museum/ratmaze.png
diff --git a/docs/images/museum/real_ratmaze.jpg b/docs/images/museum/real_ratmaze.jpg
diff --git a/docs/images/museum/sindy/C2D.png b/docs/images/museum/sindy/C2D.png
diff --git a/docs/images/museum/sindy/L2D.png b/docs/images/museum/sindy/L2D.png
diff --git a/docs/images/museum/sindy/L3D.png b/docs/images/museum/sindy/L3D.png
diff --git a/docs/images/museum/sindy/LSQ.png b/docs/images/museum/sindy/LSQ.png
diff --git a/docs/images/museum/sindy/Lorenz3D.png b/docs/images/museum/sindy/Lorenz3D.png
diff --git a/docs/images/museum/sindy/Masking.png b/docs/images/museum/sindy/Masking.png
diff --git a/docs/images/museum/sindy/O3D.png b/docs/images/museum/sindy/O3D.png
diff --git a/docs/images/museum/sindy/P1.png b/docs/images/museum/sindy/P1.png
diff --git a/docs/images/museum/sindy/P2.png b/docs/images/museum/sindy/P2.png
diff --git a/docs/images/museum/sindy/SR.png b/docs/images/museum/sindy/SR.png
diff --git a/docs/images/museum/sindy/SRin.png b/docs/images/museum/sindy/SRin.png
diff --git a/docs/images/museum/sindy/STLSQ.png b/docs/images/museum/sindy/STLSQ.png
diff --git a/docs/images/museum/sindy/Theta.png b/docs/images/museum/sindy/Theta.png
diff --git a/docs/images/museum/sindy/Thresholding.png b/docs/images/museum/sindy/Thresholding.png
diff --git a/docs/images/museum/sindy/X_.png b/docs/images/museum/sindy/X_.png
diff --git a/docs/images/museum/sindy/X_dX_.png b/docs/images/museum/sindy/X_dX_.png
diff --git a/docs/images/museum/sindy/Xtheta.png b/docs/images/museum/sindy/Xtheta.png
diff --git a/docs/images/museum/sindy/cubic_2D.png b/docs/images/museum/sindy/cubic_2D.png
diff --git a/docs/images/museum/sindy/dX_.png b/docs/images/museum/sindy/dX_.png
diff --git a/docs/images/museum/sindy/d_xyz.png b/docs/images/museum/sindy/d_xyz.png
diff --git a/docs/images/museum/sindy/dx.png b/docs/images/museum/sindy/dx.png
diff --git a/docs/images/museum/sindy/dy.png b/docs/images/museum/sindy/dy.png
diff --git a/docs/images/museum/sindy/dz.png b/docs/images/museum/sindy/dz.png
diff --git a/docs/images/museum/sindy/flow.png b/docs/images/museum/sindy/flow.png
diff --git a/docs/images/museum/sindy/flow_SR.png b/docs/images/museum/sindy/flow_SR.png
diff --git a/docs/images/museum/sindy/flow_full.jpg b/docs/images/museum/sindy/flow_full.jpg
diff --git a/docs/images/museum/sindy/iterin.png b/docs/images/museum/sindy/iterin.png
diff --git a/docs/images/museum/sindy/linear_2D.png b/docs/images/museum/sindy/linear_2D.png
diff --git a/docs/images/museum/sindy/linear_3D.png b/docs/images/museum/sindy/linear_3D.png
diff --git a/docs/images/museum/sindy/lorenz.png b/docs/images/museum/sindy/lorenz.png
diff --git a/docs/images/museum/sindy/oscillator.png b/docs/images/museum/sindy/oscillator.png
diff --git a/docs/images/museum/sindy/sindy.png b/docs/images/museum/sindy/sindy.png
diff --git a/docs/images/museum/sindy/xdx.png b/docs/images/museum/sindy/xdx.png
diff --git a/docs/images/tutorials/neurocog/GEC.png b/docs/images/tutorials/neurocog/GEC.png
diff --git a/docs/images/tutorials/neurocog/SingleGEC.png b/docs/images/tutorials/neurocog/SingleGEC.png
diff --git a/docs/images/tutorials/neurocog/alphasyn.jpg b/docs/images/tutorials/neurocog/alphasyn.jpg
diff --git a/docs/images/tutorials/neurocog/ei_circuit_dense_exc.jpg b/docs/images/tutorials/neurocog/ei_circuit_dense_exc.jpg
diff --git a/docs/images/tutorials/neurocog/ei_circuit_dynamics.jpg b/docs/images/tutorials/neurocog/ei_circuit_dynamics.jpg
diff --git a/docs/images/tutorials/neurocog/ei_circuit_sparse_inh.jpg b/docs/images/tutorials/neurocog/ei_circuit_sparse_inh.jpg
diff --git a/docs/images/tutorials/neurocog/exp2syn.jpg b/docs/images/tutorials/neurocog/exp2syn.jpg
diff --git a/docs/images/tutorials/neurocog/expsyn.jpg b/docs/images/tutorials/neurocog/expsyn.jpg
diff --git a/docs/images/tutorials/neurocog/gmm_fit.jpg b/docs/images/tutorials/neurocog/gmm_fit.jpg
diff --git a/docs/images/tutorials/neurocog/gmm_samples.jpg b/docs/images/tutorials/neurocog/gmm_samples.jpg
diff --git a/docs/images/tutorials/neurocog/hh_plot.jpg b/docs/images/tutorials/neurocog/hh_plot.jpg
diff --git a/docs/index.rst b/docs/index.rst
@@ -5,10 +5,7 @@
 Welcome to ngc-learn's documentation!
 =====================================
 
-**ngc-learn** is a Python library for building, simulating, and analyzing
-biomimetic computational models, arbitrary predictive processing/coding models,
-and spiking neural networks. This toolkit is built on top of 
-`JAX <https://github.com/google/jax>`_ and is distributed under the 3-Clause BSD license.
+**ngc-learn** is a Python library for building, simulating, and analyzing biomimetic and NeuroAI computational models, arbitrary predictive processing/coding models, spiking neural networks, and general dynamical systems. This toolkit is built on top of `JAX <https://github.com/google/jax>`_ and is distributed under the 3-Clause BSD license.
 
 .. toctree::
    :maxdepth: 1
@@ -23,6 +20,7 @@ and spiking neural networks. This toolkit is built on top of
 
   tutorials/intro
   tutorials/theory
+  tutorials/configuration/index
   tutorials/index
   tutorials/neurocog/index
 
@@ -52,9 +50,10 @@ and spiking neural networks. This toolkit is built on top of
 
 .. toctree::
   :maxdepth: 1
-  :caption: Papers that use NGC-Learn
+  :caption: NGC-Learn Papers & Media
 
   ngclearn_papers
+  ngclearn_talks
 
 Indices and tables
 ==================

diff --git a/docs/installation.md b/docs/installation.md
@@ -1,65 +1,41 @@
 # Installation
 
-**ngc-learn** officially supports Linux on Python 3. It can be run with or
-without a GPU.
+**ngc-learn** officially supports Linux on Python 3. It can be run with or without a GPU.
 
-<i>Setup:</i> <a href="https://github.com/NACLab/ngc-learn">ngc-learn</a>,
-in its entirety (including its supporting utilities),
-requires that you ensure that you have installed the following base dependencies in
-your system. Note that this library was developed and tested on Ubuntu 22.04 (and 18.04).
-Specifically, ngc-learn requires:
+<i>Setup:</i> <a href="https://github.com/NACLab/ngc-learn">NGC-Learn</a>, in its entirety (including its supporting utility sub-packages), requires that you ensure that you have installed the following base dependencies in your system. Note that this library was developed and tested on Ubuntu 22.04 (with much earlier versions on Ubuntu 18.04/20.04). 
+Specifically, NGC-Learn requires:
 * Python (>=3.10)
-* ngcsimlib (>=0.3.b3), (<a href="https://github.com/NACLab/ngc-sim-lib">official page</a>)
-* NumPy (>=1.26.0)
+* ngcsimlib (>=3.0.0), (<a href="https://github.com/NACLab/ngc-sim-lib">official page</a>)
+* NumPy (>=1.22.0)
 * SciPy (>=1.7.0)
-* JAX (>= 0.4.18; and jaxlib>=0.4.18) <!--(tested for cuda 11.8)-->
-* Matplotlib (>=3.4.2), (for `ngclearn.utils.viz`)
-* Scikit-learn (>=1.3.1), (for `ngclearn.utils.patch_utils` and `ngclearn.utils.density`)
+* JAX (>= 0.4.28; and jaxlib>=0.4.28) <!--(tested for cuda 11.8)-->
+* Matplotlib (>=3.8.0), (for `ngclearn.utils.viz`)
+* Scikit-learn (>=1.6.1), (for `ngclearn.utils.patch_utils` and `ngclearn.utils.density`)
 
-Note that the above requirements are taken care of if one installs ngc-learn
-through either `pip`. One can either install the CPU version of ngc-learn (if no JAX is
-pre-installed or only the CPU version of JAX is installed currently) via
+Note that the above requirements are taken care of if one installs NGC-Learn through either `pip`. One can either install the CPU version of NGC-Learn (if no JAX is pre-installed or only the CPU version of JAX is currently installed) via: 
 ```console
 $ pip install ngclearn
 ```
 
-or install the GPU version of ngc-learn by first installing the
-<a href="https://jax.readthedocs.io/en/latest/installation.html">CUDA 11 or 12
-version of JAX</a> before running the above pip command.
+or install the GPU version of NGC-Learn by first installing the <a href="https://jax.readthedocs.io/en/latest/installation.html">CUDA 12 version of JAX</a> before running the above pip command.
 
-Alternatively, one may locally, step-by-step (see below), install and setup
-ngc-learn from source after pulling from the repo.
+Alternatively, one may locally, step-by-step (see below), install and setup NGC-Learn from source after pulling from the repo. 
 
-Note that installing the official pip package without any form of JAX installed
-on your system will default to downloading the CPU version of ngc-learn (see
-below for installing the GPU version).
+Note that installing the official pip package without any form of JAX installed on your system will default to downloading the CPU version of NGC-Learn (see below for installing the GPU version).
 
 ## Install from Source
 
-0. Install ngc-sim-lib first (as an editable install); visit the repo 
-https://github.com/NACLab/ngc-sim-lib for details.
+1. Install NGC-Sim-Lib first (as an editable install); visit the repo https://github.com/NACLab/ngc-sim-lib for details.
 
-1. Clone the ngc-learn repository:
+2. Clone the NGC-Learn repository: 
 ```console
 $ git clone https://github.com/NACLab/ngc-learn.git
 $ cd ngc-learn
 ```
 
-2. (<i>Optional</i>; only for GPU version) Install JAX for either CUDA 11 or 12 , depending
-   on your system setup. Follow the
-   <a href="https://jax.readthedocs.io/en/latest/installation.html">installation instructions</a>
-   on the official JAX page to properly install the CUDA 11 or 12 version.
+3. (<i>Optional</i>; only for GPU version) Install JAX for either CUDA 12 , depending    on your system setup. Follow the    <a href="https://jax.readthedocs.io/en/latest/installation.html">installation instructions</a> on the official JAX page to properly install the CUDA 11 or 12 version.
 
-<!--
-3. (<i>Optional</i>) Install, a pre-package installation step (for only the
-   non-ngclearn dependencies), the base requirements (and a few extras for building
-   the docs) with:
-```console
-$ pip install -r requirements.txt
-```
--->
-
-3. Install the ngc-learn package via:
+4. Install the NGC-Learn package via:
 ```console
 $ pip install .
 ```
@@ -68,22 +44,21 @@ or, to install as an editable install for development, run:
 $ pip install -e .
 ```
 
-If the installation was successful, you should see the following if you test
-it against your Python interpreter, i.e., run the <code>$ python</code> command
-and complete the following sequence of steps as depicted in the screenshot below:<br>
-<!--<img src="images/test_ngclearn_install.png" width="512">-->
+If the installation was successful, you should see the following if you test it against your Python interpreter, i.e., run the <code>$ python</code> command and complete the following sequence of steps as depicted in the screenshot below:<br>
 
 ```console
 Python 3.11.4 (main, MONTH  DAY YEAR, TIME) [GCC XX.X.X] on linux
 Type "help", "copyright", "credits" or "license" for more information.
 >>> import ngclearn
 >>> ngclearn.__version__
-'1.2b1'
+'3.0.1'
 ```
 
+<!--
 <i>Note</i>: If you do not have a JSON configuration file in place (see tutorials
 for details) locally where you call the import to ngc-learn, a warning will pop
 up containing within it "<i>UserWarning: Missing file to preload modules from.</i>";
 this still means that ngc-learn installed successfully but you will need to
 point to a JSON configuration when building projects with ngc-learn.
+-->
 
diff --git a/docs/modeling/input_encoders.md b/docs/modeling/input_encoders.md
@@ -71,3 +71,18 @@ whereas lower intensity values yield later firing times.
   .. automethod:: reset
     :noindex:
 ```
+
+### Phasor Cell
+
+This cell takes a real-valued pattern(s) and transforms it on-the-fly to
+a spike train composed of pulses emitted a regular interval. 
+
+```{eval-rst}
+.. autoclass:: ngclearn.components.PhasorCell
+  :noindex:
+
+  .. automethod:: advance_state
+    :noindex:
+  .. automethod:: reset
+    :noindex:
+```