alexgiving · alexgiving · Apr 30, 2023 · Apr 13, 2023 · Apr 13, 2023 · Apr 13, 2023
diff --git a/.DS_Store b/.DS_Store
diff --git a/.github/.pylintrc b/.github/.pylintrc
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
@@ -21,10 +21,13 @@ jobs:
         pip install -r requirements.txt
     - name: Analysing the code with pylint
       run: |
-        export PYTHONPATH=${PYTHONPATH}:.
-        # pylint $(git ls-files '*.py')  --fail-under=9.94
-    - name: Tests
+        export PYTHONPATH=${PYTHONPATH}:$(pwd)
+        pylint $(git ls-files '*.py') --rcfile .github/.pylintrc
+    - name: Test optimizers
       run: |
-        mkdir -p images
-        export PYTHONPATH=${PYTHONPATH}:.
-        pytest lib/*_test.py -v
+        export PYTHONPATH=${PYTHONPATH}:$(pwd)
+        pytest tests -v -m optimizers
+    - name: Test KMeans
+      run: |
+        export PYTHONPATH=${PYTHONPATH}:$(pwd)
+        pytest tests -v -m kmeans
diff --git a/.gitignore b/.gitignore
@@ -1,8 +1,9 @@
 venv
-lib/__pycache__
 notebooks/.ipynb_checkpoints
 .pytest_cache
 images
 cache
+.env
 
 *.png
+*__pycache__
diff --git a/experiments/experiment_1_sigma_1/experiment_1.tex b/experiments/experiment_1_sigma_1/experiment_1.tex
diff --git a/experiments/experiment_2_sigma_1/experiment_1.tex b/experiments/experiment_2_sigma_1/experiment_1.tex
diff --git a/lib/__init__.py b/lib/__init__.py
@@ -0,0 +1,5 @@
+from lib.decomposition import get_tsne_clusters
+from lib.experiment_metrics import get_average_experiment_metrics
+from lib.kmeans import KMeans
+from lib.metric_meter import MetricTable, insert_hline
+from lib.experiment import run_experiment
diff --git a/lib/decomposition.py b/lib/decomposition.py
@@ -1,15 +1,30 @@
-from sklearn.decomposition import PCA
+from typing import Optional
+
+import matplotlib.pyplot as plt
+import numpy as np
 from sklearn.manifold import TSNE
 
 
-def fit_to_2d_tsne(data):
-    """Fit data to 2d."""
-    tsne = TSNE(n_components=2, random_state=0, perplexity=30, n_iter=5000)
-    return tsne.fit_transform(data)
+def get_tsne_clusters(clusters: np.ndarray,
+                      labels: np.ndarray,
+                      centroids: Optional[np.ndarray] = None):
+
+    fig = plt.figure()
+    axe = fig.add_subplot(1, 1, 1)
+    color_map = {0: 'red', 1: 'green', 2: 'blue', 3: 'yellow', 4: 'purple'}
+
+    colors = [color_map[label] for label in labels]
+    tsne = TSNE(n_components=2, random_state=42)
 
+    if not isinstance(centroids, type(None)):
+        concuted = np.concatenate((clusters, np.array(centroids)), axis=0)
+        clusters_tsne = tsne.fit_transform(concuted)
 
-def fit_to_2d_PCA(data):
-    """Fit data to 2d."""
-    pca = PCA(n_components=2)
-    pca.fit(data)
-    return pca.transform(data)
+        axe.scatter(clusters_tsne[:-len(centroids), 0],
+                    clusters_tsne[:-len(centroids), 1], c=colors)
+        axe.scatter(clusters_tsne[-len(centroids):, 0],
+                    clusters_tsne[-len(centroids):, 1], marker='*', s=100, c='black')
+    else:
+        clusters_tsne = tsne.fit_transform(clusters)
+        axe.scatter(clusters_tsne[:, 0], clusters_tsne[:, 1], c=colors)
+    return fig
diff --git a/lib/deprecated.py b/lib/deprecated.py
diff --git a/lib/distance.py b/lib/distance.py
diff --git a/lib/distance_test.py b/lib/distance_test.py