Global scaling, normalized MAE, saved models and marimo workflow

DECODE_marimo.py

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+import marimo
+
+__generated_with = "0.14.17"
+app = marimo.App(width="medium")
+
+
+@app.cell
+def _():
+    import os
+    import subprocess
+    import sys
+    from pathlib import Path
+    import marimo as mo
+    return Path, mo, os, subprocess, sys
+
+
+@app.cell
+def _(Path, os):
+    ROOT = Path(__file__).resolve().parent
+    SCRIPT = ROOT / "scripts" / "decode_reimplementation.py"
+    OUTPUT = ROOT / "decode_reimplementation_outputs"
+    TRAIN_ENV = os.environ.copy()
+    TRAIN_ENV["DECODE_DISABLE_TENSORFLOW"] = "1"
+    return OUTPUT, SCRIPT, TRAIN_ENV
+
+
+@app.cell
+def _(mo):
+    mode = mo.ui.dropdown(["paper_buildings", "meters"], value="paper_buildings", label="Scope")
+    model_case = mo.ui.dropdown(["baselines", "lstm", "cnn", "tcn", "timesnet"], value="baselines", label="Model case")
+    run = mo.ui.run_button(label="Train full dataset")
+    mo.vstack([mo.md("# DECODE full-data experiments"), mode, model_case, run])
+    return mode, model_case, run
+
+
+@app.cell
+def _(SCRIPT, TRAIN_ENV, mode, model_case, run, subprocess, sys):
+    if run.value:
+        args = [sys.executable, str(SCRIPT), "--mode", mode.value]
+        if model_case.value == "baselines":
+            args += ["--skip-lstm"]
+        else:
+            args += ["--dl-models", model_case.value, "--epochs", "20", "--batch-size", "64"]
+            if model_case.value == "timesnet":
+                args += ["--lookback", "144"]
+        completed = subprocess.run(args, check=True, env=TRAIN_ENV, text=True)
+    else:
+        completed = None
+    completed
+    return
+
+
+@app.cell
+def _(OUTPUT, mo):
+    result_files = sorted(OUTPUT.glob("results_*.csv"))
+    mo.md("## Outputs\n" + "\n".join(f"- `{p}`" for p in result_files))
+    return
+
+
+if __name__ == "__main__":
+    app.run()