| """Figure for Methodology 3.5: the three chronological splitting schemes. |
| |
| Dates are computed the way the experiments compute them, not typed in: |
| A purged walk-forward (regime ladder, scripts/run_ablation_study.py): |
| the longest contiguous run of 31,234 hours ending 16 Oct 2026, cut into |
| 6 equal blocks; fold k trains on blocks 1..k (last fifth = validation), |
| skips 24 hours, and tests block k+1 |
| B hold-out (deployed regime model, train_vae_transformer_artifacts.py): |
| the same run, first 85% for training, 24 hours purged, last 15% tested |
| C quarterly walk-forward (price range, backtest_improvements.py): each |
| quarter Jan 2023 - Sep 2026 tested by a fit on the two years ending |
| 72 hours before it |
| |
| Usage: |
| python scripts/make_split_diagram.py |
| """ |
| from __future__ import annotations |
|
|
| from pathlib import Path |
|
|
| import matplotlib |
| matplotlib.use("Agg") |
| import matplotlib.dates as mdates |
| import matplotlib.pyplot as plt |
| import pandas as pd |
| from matplotlib.patches import Patch |
|
|
| ROOT = Path(__file__).resolve().parents[1] |
| SURFACE, INK, INK_2, GRID = "#fcfcfb", "#0b0b0b", "#52514e", "#e6e5e1" |
| TRAIN, VALID, TEST, GAP = "#2a78d6", "#a9cbf0", "#eb6834", "#0b0b0b" |
|
|
| END = pd.Timestamp("2026-10-16 23:00") |
| ROWS = 31_234 |
| START = END - pd.Timedelta(hours=ROWS - 1) |
| H = pd.Timedelta(hours=1) |
|
|
|
|
| def bar(ax, y, a, b, color, h=0.62, **kw): |
| if color == GAP: |
| |
| |
| mid = a + (b - a) / 2 |
| a, b = mid - pd.Timedelta(days=9), mid + pd.Timedelta(days=9) |
| h = h * 1.25 |
| ax.barh(y, (b - a) / pd.Timedelta(days=1), left=mdates.date2num(a), height=h, |
| color=color, edgecolor=SURFACE, linewidth=0.6, zorder=3 if color == GAP else 2, **kw) |
|
|
|
|
| def main() -> None: |
| plt.rcParams.update({"font.family": "DejaVu Sans", "text.color": INK}) |
| fig, axes = plt.subplots(3, 1, figsize=(13, 9.6), facecolor=SURFACE, |
| gridspec_kw={"height_ratios": [5, 1.4, 5.6]}) |
| fig.subplots_adjust(left=0.13, right=0.98, top=0.86, bottom=0.07, hspace=0.75) |
| lo, hi = pd.Timestamp("2020-07-01"), pd.Timestamp("2028-03-01") |
|
|
| |
| a = axes[0] |
| edges = [START + (END - START) * k / 6 for k in range(7)] |
| for f in range(5): |
| y = 4 - f |
| tr_end = edges[f + 1] - 24 * H |
| cut = START + (tr_end - START) * 0.8 |
| bar(a, y, START, cut, TRAIN) |
| bar(a, y, cut, tr_end, VALID) |
| bar(a, y, tr_end, edges[f + 1], GAP, h=0.62) |
| bar(a, y, edges[f + 1], edges[f + 2], TEST) |
| a.text(mdates.date2num(edges[f + 2]) + 12, y, f"test {edges[f + 1]:%b %Y} – {edges[f + 2]:%b %Y}", |
| va="center", fontsize=8.5, color=INK_2) |
| a.set_yticks(range(5)) |
| a.set_yticklabels([f"fold {5 - i}" for i in range(5)], fontsize=9) |
| a.set_title("A Purged walk-forward, 5 folds — comparing the 14 regime models", |
| loc="left", fontsize=11.5, fontweight="bold", pad=20) |
| a.text(0, 1.015, "Each model is tested on five different later periods; the training block grows each time. " |
| "Its last fifth (validation) is used for early stopping and the decision cut-off.", |
| transform=a.transAxes, fontsize=8.8, color=INK_2, va="bottom") |
|
|
| |
| b = axes[1] |
| cut = START + (END - START) * 0.85 |
| bar(b, 0, START, cut - 24 * H, TRAIN) |
| bar(b, 0, cut - 24 * H, cut, GAP) |
| bar(b, 0, cut, END, TEST) |
| b.text(mdates.date2num(START) + 20, 0, "train on the first 85%", va="center", fontsize=8.5, color="white") |
| b.text(mdates.date2num(END) + 12, 0, f"test the last 15%\n({cut:%b} – {END:%b %Y}, 4,686 h)", |
| va="center", fontsize=8.5, color=INK_2) |
| b.set_yticks([0]) |
| b.set_yticklabels(["deployed model"], fontsize=9) |
| b.set_ylim(-0.6, 0.6) |
| b.set_title("B Hold-out — the final VAE + Transformer that runs live", loc="left", |
| fontsize=11.5, fontweight="bold", pad=20) |
| b.text(0, 1.04, "One fit on all earlier data, scored once on the most recent period it never saw.", |
| transform=b.transAxes, fontsize=8.8, color=INK_2, va="bottom") |
|
|
| |
| c = axes[2] |
| quarters = pd.date_range("2023-01-01", "2026-07-01", freq="QS") |
| shown = list(quarters[:3]) + [None] + list(quarters[-2:]) |
| labels = [] |
| for i, q in enumerate(shown): |
| y = len(shown) - 1 - i |
| if q is None: |
| c.text(mdates.date2num(pd.Timestamp("2024-09-01")), y, "⋮ one row per quarter, 15 in total ⋮", |
| va="center", ha="center", fontsize=9, color=INK_2) |
| labels.append("") |
| continue |
| q_end = q + pd.offsets.QuarterBegin(1, startingMonth=1) |
| bar(c, y, q - pd.DateOffset(years=2) - 72 * H, q - 72 * H, TRAIN) |
| bar(c, y, q - 72 * H, q, GAP) |
| bar(c, y, q, q_end, TEST) |
| labels.append(f"Q{(q.month - 1) // 3 + 1} {q.year}") |
| c.set_yticks(range(len(shown))) |
| c.set_yticklabels(labels[::-1], fontsize=9) |
| c.set_title("C Quarterly walk-forward — the price range, exactly as it refits live", |
| loc="left", fontsize=11.5, fontweight="bold", pad=20) |
| c.text(0, 1.015, "Every quarter from Jan 2023 to Sep 2026 is forecast by a model fitted on the two years " |
| "before it (≈ 32,700 forecasts per horizon).", |
| transform=c.transAxes, fontsize=8.8, color=INK_2, va="bottom") |
|
|
| for ax in axes: |
| ax.set_facecolor(SURFACE) |
| ax.set_xlim(mdates.date2num(lo), mdates.date2num(hi)) |
| ax.xaxis.set_major_locator(mdates.YearLocator()) |
| ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y")) |
| ax.grid(axis="x", color=GRID, linewidth=0.8) |
| ax.set_axisbelow(True) |
| for s in ("top", "right", "left"): |
| ax.spines[s].set_visible(False) |
| ax.spines["bottom"].set_color(GRID) |
| ax.tick_params(colors=INK_2, labelsize=8.5, length=0) |
|
|
| handles = [Patch(color=TRAIN, label="training (past)"), Patch(color=VALID, label="validation"), |
| Patch(color=GAP, label="gap / purge: 24h (A, B) or 72h (C), drawn wider to be visible"), Patch(color=TEST, label="test (later, unseen)")] |
| fig.legend(handles=handles, loc="upper left", bbox_to_anchor=(0.13, 0.925), ncol=4, frameon=False, fontsize=9) |
| fig.suptitle("Figure 3.2 Three chronological splitting schemes: train on the past, test on the future", |
| x=0.02, ha="left", fontsize=14, fontweight="bold", y=0.975) |
| out = ROOT / "outputs" / "figures" / "fig20_data_splitting.png" |
| fig.savefig(out, dpi=170, facecolor=SURFACE) |
| plt.close(fig) |
| print(f"written: {out.relative_to(ROOT)} (contiguous run {START:%Y-%m-%d} – {END:%Y-%m-%d})") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
