Merge branch 'master' into atrutnev/new_tables

.gitignore

@@ -15,4 +15,4 @@ experiments/
 .DS_Store
 .vscode
 logs
-data
+data

report/generate_dimension_histogram.py

@@ -0,0 +1,46 @@
+from argparse import ArgumentParser
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+
+from lkmeans.examples.data.experiment_data import get_experiment_data
+from lkmeans.examples.data.points_generator import generate_mix_distribution
+
+parser = ArgumentParser()
+
+parser.add_argument(
+    '--path',
+    type=Path,
+    default=Path('images'),
+    help='Path to save results'
+)
+
+
+def main():
+    args = parser.parse_args()
+    args.path.mkdir(exist_ok=True)
+
+    dimension = 20
+    n_points = 100
+
+    n_clusters, prob, mu_list, cov_matrices = get_experiment_data(num_clusters=2, dimension=dimension)
+
+    for t in [0.2, 0.4, 0.9]:
+        filename = args.path / f'{n_clusters}_cluster_hist_t_{t}.png'
+        clusters, _, _ = generate_mix_distribution(
+            probability=prob,
+            mu_list=mu_list,
+            cov_matrices=cov_matrices,
+            n_samples=n_points,
+            t=t
+        )
+
+        fig, ax = plt.subplots(figsize=(5, 3))
+        ax.hist(clusters[:, 0], bins=15)
+        ax.grid(True, color='gray', linestyle='--', linewidth=0.5)
+        fig.savefig(str(filename), dpi=300, bbox_inches='tight')
+        plt.close(fig)
+
+
+if __name__ == '__main__':
+    main()

report/plot_minkowski.py

@@ -0,0 +1,79 @@
+from argparse import ArgumentParser
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from lkmeans.clustering.utils import assign_to_cluster
+from lkmeans.distance import DistanceCalculator
+from lkmeans.examples.data.experiment_data import get_experiment_data
+from lkmeans.examples.data.points_generator import generate_mix_distribution
+
+parser = ArgumentParser()
+
+parser.add_argument(
+    '--path',
+    type=Path,
+    default=Path('images'),
+    help='Path to save results'
+)
+
+parser.add_argument(
+    '--p',
+    type=float,
+    default=2,
+    help='Minkowski parameter'
+)
+
+parser.add_argument(
+    '--t',
+    type=float,
+    default=0.,
+    help='T parameter of distribution'
+)
+
+
+# pylint: disable=too-many-locals
+def main():
+    args = parser.parse_args()
+    args.path.mkdir(exist_ok=True)
+    p = int(args.p) if (args.p).is_integer() else args.p
+
+    dimension = 20
+    n_points = 10
+    n_observation = 10000
+
+    distance_calculator = DistanceCalculator(p)
+
+    n_clusters, prob, mu_list, cov_matrices = get_experiment_data(num_clusters=2, dimension=dimension)
+
+    filename = args.path / f'plot_minkowski_function_with_p_{p}.png'
+    samples, _, centroids = generate_mix_distribution(
+        probability=prob,
+        mu_list=mu_list,
+        cov_matrices=cov_matrices,
+        n_samples=n_points,
+        t=0.1
+    )
+
+    dim = 0
+
+    clusters, _ = assign_to_cluster(samples, centroids, n_clusters, p)
+    cluster = np.array(clusters[0])
+    dimension_data = cluster[:,dim]
+
+    points = np.linspace(min(dimension_data), max(dimension_data), n_observation)
+    minkowski_values = distance_calculator.get_pairwise_distance(
+        point_a = dimension_data,
+        points=points,
+    )
+
+    fig, ax = plt.subplots(figsize=(5, 3))
+    ax.scatter(points, minkowski_values)
+    ax.axis('off')
+    fig.savefig(str(filename), dpi=300, bbox_inches='tight')
+    plt.close(fig)
+
+
+if __name__ == '__main__':
+    main()