release 0.1.2

.github/workflows/pypi-publish.yml

@@ -0,0 +1,39 @@
+# This workflow will upload a Python Package using Twine when a release is created
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python#publishing-to-package-registries
+
+# This workflow uses actions that are not certified by GitHub.
+# They are provided by a third-party and are governed by
+# separate terms of service, privacy policy, and support
+# documentation.
+
+name: Upload Python Package
+
+on:
+  release:
+    types: [published]
+
+permissions:
+  contents: read
+
+jobs:
+  deploy:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python
+      uses: actions/setup-python@v3
+      with:
+        python-version: '3.x'
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install build
+    - name: Build package
+      run: python -m build
+    - name: Publish package
+      uses: pypa/gh-action-pypi-publish@27b31702a0e7fc50959f5ad993c78deac1bdfc29
+      with:
+        user: __token__
+        password: ${{ secrets.PYPI_API_TOKEN }}

README.md

@@ -17,18 +17,25 @@ AdaptiveResonanceLib includes implementations for the following ART models:
     - Fuzzy ART
     - Quadratic Neuron ART
     - Dual Vigilance ART
+    - Gram ART
+- #### Metric Informed 
+    - CVI ART  
+    - iCVI Fuzzy ART  
 - #### Topological
     - Topo ART
 - #### Classification
     - Simple ARTMAP
-
 - #### Regression
     - ARTMAP
+    - Fusion ART
 - #### Hierarchical
     - DeepARTMAP
     - SMART
-- #### Data Fusion and Reinforcement Learning
+- #### Data Fusion
     - Fusion ART
+- #### Reinforcement Learning
+    - FALCON
+
 - #### Biclustering
     - Biclustering ARTMAP
 

artlib/__init__.py

@@ -1,6 +1,7 @@
 from artlib.common.BaseART import BaseART
 from artlib.common.BaseARTMAP import BaseARTMAP
-from artlib.common.utils import normalize, compliment_code
+from artlib.common.utils import normalize, compliment_code, de_compliment_code, de_normalize
+from artlib.common.VAT import VAT
 
 from artlib.elementary.ART1 import ART1
 from artlib.elementary.ART2 import ART2A
@@ -12,13 +13,18 @@
 from artlib.elementary.HypersphereART import HypersphereART
 from artlib.elementary.QuadraticNeuronART import QuadraticNeuronART
 
+from artlib.cvi.iCVIFuzzyArt import iCVIFuzzyART
+from artlib.cvi.CVIART import CVIART
+
 from artlib.supervised.ARTMAP import ARTMAP, SimpleARTMAP
 
 from artlib.hierarchical.SMART import SMART
 from artlib.hierarchical.DeepARTMAP import DeepARTMAP
 
 from artlib.fusion.FusionART import FusionART
 
+from artlib.reinforcement.FALCON import FALCON, TD_FALCON
+
 from artlib.biclustering.BARTMAP import BARTMAP
 
 from artlib.topological.TopoART import TopoART
@@ -44,4 +50,6 @@
     "SMART",
     "FusionART",
     "BARTMAP",
+    "iCVIFuzzyART",
+    "CVIART"
 ]

artlib/biclustering/BARTMAP.py

@@ -298,7 +298,6 @@ def fit(self, X: np.ndarray, max_iter=1):
 
         for _ in range(max_iter):
             for k in range(n):
-                print(k, self.module_a.n_clusters)
                 self.module_a.pre_step_fit(X)
                 c_a = self.step_fit(X_a, k)
                 self.module_a.labels_[k] = c_a