Add logic to save the result graphs

src/__main__.py

@@ -2,6 +2,7 @@ import os
 from collections.abc import Iterator
 from contextlib import contextmanager
 from dataclasses import dataclass
+from pathlib import Path
 from time import perf_counter
 from typing import cast, final
 
@@ -20,6 +21,8 @@ from sklearn.utils import Bunch
 # Set to -1 to disable downsizing
 DOWNSIZE_MNIST: int = 8000
 
+OUTPUT_DIR = Path.cwd() / "output"
+
 # pyqt6 only bundles Windows & Fusion styles, which means that if you use a
 # different preferred qt style, a warning would be produced. This gets rid
 # of that warning and removes the env-var override.
@@ -111,11 +114,22 @@ def knn_accuracy(data: MLDataset, k_range: range | None = None) -> tuple[object,
     return best_k, acc
 
 
-def plot_2d(x: DataFrame, y: "Series[str]", title: str) -> None:
+def plot_2d(
+    x: DataFrame,
+    y: "Series[str]",
+    title: str,
+    *,
+    show_plot: bool = False,
+    save_plot: Path | None = None,
+) -> None:
     """Show a 2D visualization of the given 2D (dim-reduced) dataset."""
     plt.figure(figsize=(8, 6))
     sns.scatterplot(x=x[:, 0], y=x[:, 1], hue=y, palette="tab10", legend="full", s=15)
     plt.title(title)
+
+    if save_plot:
+        plt.savefig(save_plot)
+    if show_plot:
         plt.show()
 
 
@@ -132,6 +146,8 @@ def timed(start_msg: str, end_msg: str) -> Iterator[None]:
 
 def main() -> None:
     """Program entrypoint."""
+    OUTPUT_DIR.mkdir(exist_ok=True)
+
     with timed("Loading the MNIST dataset", "MNIST dataset loaded"):
         # Working with the entire dataset would be way too computationally expensive
         # (TSNE would take hours, if not more), instead, downsize the dataset and work
@@ -165,8 +181,20 @@ def main() -> None:
     print()
 
     with timed("Showing graphs", "Finished"):
-        plot_2d(mnist_pca.x_train, mnist_pca.y_train, "2D PCA of MNIST")
+        plot_2d(
-        plot_2d(mnist_tsne.x_train, mnist_tsne.y_train, "2D t-SNE of MNIST")
+            mnist_pca.x_train,
+            mnist_pca.y_train,
+            "2D PCA of MNIST",
+            show_plot=True,
+            save_plot=OUTPUT_DIR.joinpath("pca.png"),
+        )
+        plot_2d(
+            mnist_tsne.x_train,
+            mnist_tsne.y_train,
+            "2D t-SNE of MNIST",
+            show_plot=True,
+            save_plot=OUTPUT_DIR.joinpath("tsne.png"),
+        )
 
 
 if __name__ == "__main__":