feat(jssp): add basic plotting utility

.envrc

@@ -0,0 +1,2 @@
+source .venv/bin/activate
+unset PS1

.gitignore

@@ -2,3 +2,5 @@
 .env/
 .vscode/
 *local.*
+test-data/
+__pycache__/

src/ectoolkit/jssp.py

@@ -0,0 +1,18 @@
+import polars as pl
+import matplotlib.pyplot as plt
+
+
+def plot_fitness_improvements(data: pl.DataFrame, plot: plt.Axes):
+    data = (
+        data
+        .lazy()
+        .filter(pl.col('event') == 'bestingen')
+        .sort('gen')
+        .collect()
+    )
+
+    print(data)
+    x_data = data.get_column('gen')
+    y_data = data.get_column('fitness')
+
+    plot.plot(x_data, y_data, marker='o', linestyle='--')

src/ectoolkit/main.py

@@ -1,2 +1,38 @@
+def main():
+    import sys
+    import polars as pl
+    import matplotlib.pyplot as plt
+    from pathlib import Path
+    import jssp
+
+    pl.Config.set_tbl_rows(400)
+    pl.Config.set_tbl_cols(10)
+    plt.rcParams['figure.figsize'] = (16, 9)
+
+    assert len(sys.argv) > 1, "Expected path to a data file"
+
+    data_file = Path(sys.argv[1])
+    assert data_file.is_file(), "Pointed file does not exist or is not a regular file"
+
+    problem_name = None
+    if len(sys.argv) > 2:
+        problem_name = sys.argv[2]
+
+    data_df = pl.read_csv(data_file, has_header=False, new_columns=[
+                          "event", "gen", "time", "fitness"]).filter(pl.col('event') != 'diversity').select(pl.exclude('column_5'))
+    print(data_df)
+
+    fig, plot = plt.subplots(nrows=1, ncols=1)
+    jssp.plot_fitness_improvements(data_df, plot)
+    plot.set(
+        title="Najlepszy osobnik w populacji w danej generacji" +
+        f', problem: {problem_name}' if problem_name else "",
+        xlabel="Generacja",
+        ylabel="Wartość funkcji fitness"
+    )
+
+    plt.show()
+
+
 if __name__ == "__main__":
-    print("Hello world")
+    main()