Add print graph strees to img folder

img/.gitignore

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+*
+!.gitignore

src/print_strees.py

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+import os
+import subprocess
+import argparse
+import json
+from stree import Stree
+from graphviz import Source
+from Experiments import Datasets
+from Utils import Files, Folders
+
+
+def parse_arguments():
+    ap = argparse.ArgumentParser()
+    ap.add_argument(
+        "-c",
+        "--color",
+        type=bool,
+        required=False,
+        default=False,
+        help="use colors for the tree",
+    )
+    args = ap.parse_args()
+    return (args.color,)
+
+
+def compute_stree(X, y, random_state):
+    clf = Stree(random_state=random_state)
+    clf.fit(X, y)
+    return clf
+
+
+def load_hyperparams(score_name, model_name):
+    grid_file = os.path.join(
+        Folders.results, Files.grid_output(score_name, model_name)
+    )
+    with open(grid_file) as f:
+        return json.load(f)
+
+
+def hyperparam_filter(hyperparams):
+    res = {}
+    for key, value in hyperparams.items():
+        if key.startswith("base_estimator"):
+            newkey = key.split("__")[1]
+            res[newkey] = value
+    return res
+
+
+def build_title(dataset, accuracy, n_samples, n_features, n_classes, nodes):
+    dataset_chars = f"-{dataset}- f={n_features} s={n_samples} c={n_classes}"
+    return (
+        f'<font point-size="25" color="brown">{dataset_chars}<BR/></font>'
+        f'<font point-size="20" color="red">accuracy: {accuracy:.6f} / '
+        f"{nodes} nodes</font>"
+    )
+
+
+def print_stree(clf, dataset, X, y):
+    output_folder = "img"
+    samples, features = X.shape
+    classes = max(y) + 1
+    accuracy = clf.score(X, y)
+    nodes, _ = clf.nodes_leaves()
+    title = build_title(dataset, accuracy, samples, features, classes, nodes)
+    grp = Source(clf.graph(title))
+    file_name = os.path.join(output_folder, f"stree_{dataset}")
+    grp.render(format="png", filename=f"{file_name}")
+    os.remove(f"{file_name}")
+    print(f"File {file_name}.png generated")
+    cmd_open = "/usr/bin/open"
+    if os.path.isfile(cmd_open) and os.access(cmd_open, os.X_OK):
+        subprocess.run([cmd_open, f"{file_name}.png"])
+
+
+if __name__ == "__main__":
+    (color,) = parse_arguments()
+    hyperparameters = load_hyperparams("accuracy", "ODTE")
+    random_state = 57
+    dt = Datasets()
+    for dataset in dt:
+        X, y = dt.load(dataset)
+        clf = Stree(random_state=random_state)
+        hyperparams_dataset = hyperparam_filter(hyperparameters[dataset][1])
+        clf.set_params(**hyperparams_dataset)
+        clf.fit(X, y)
+        print_stree(clf, dataset, X, y)