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| from __future__ import annotations | |
| from pathlib import Path | |
| import matplotlib | |
| import numpy as np | |
| matplotlib.use("Agg") | |
| import matplotlib.pyplot as plt | |
| FIG_SIZE_IN = 4.2 | |
| MAX_ENERGY_SUBPLOTS = 6 | |
| AXIS_LABEL_FONT_SIZE = 8 | |
| TICK_LABEL_FONT_SIZE = 8 | |
| INPLOT_LABEL_FONT_SIZE = 10 | |
| def _to_hourly_zone(values: np.ndarray) -> np.ndarray: | |
| arr = np.asarray(values) | |
| if arr.ndim != 2: | |
| raise ValueError(f"Expected 2D energy matrix, got shape={arr.shape}") | |
| if arr.shape[0] == 8760: | |
| return np.asarray(arr, dtype=float) | |
| if arr.shape[1] == 8760: | |
| return np.asarray(arr.T, dtype=float) | |
| raise ValueError(f"Neither axis is 8760 for energy matrix: shape={arr.shape}") | |
| def _decode_zone_names(columns_arr: np.ndarray | None, zone_count: int) -> list[str]: | |
| if columns_arr is None: | |
| return [f"zone_{i}" for i in range(zone_count)] | |
| cols = np.asarray(columns_arr).reshape(-1) | |
| names = [str(c, "utf-8") if isinstance(c, (bytes, np.bytes_)) else str(c) for c in cols] | |
| if len(names) < zone_count: | |
| names.extend([f"zone_{i}" for i in range(len(names), zone_count)]) | |
| return names[:zone_count] | |
| def _time_window(hourly_zone: np.ndarray, start_hour: int, window_hours: int) -> tuple[np.ndarray, int, int]: | |
| total = int(hourly_zone.shape[0]) | |
| if total < 1: | |
| raise ValueError("No hourly energy records found") | |
| start_idx = max(0, min(total - 1, int(start_hour) - 1)) | |
| window = max(1, int(window_hours)) | |
| end_idx = min(total, start_idx + window) | |
| if end_idx <= start_idx: | |
| raise ValueError(f"Invalid energy window: start={start_hour}, hours={window_hours}") | |
| return hourly_zone[start_idx:end_idx, :], start_idx + 1, end_idx | |
| def _major_ticks(length: int) -> list[int]: | |
| if length <= 8: | |
| return list(range(1, length + 1)) | |
| tick_count = 6 | |
| ticks = np.linspace(1, length, num=tick_count, dtype=int) | |
| uniq = sorted(set(int(t) for t in ticks)) | |
| if uniq[-1] != length: | |
| uniq.append(length) | |
| return uniq | |
| def visualize_energy( | |
| energy_npz: str | Path, | |
| output_png: str | Path, | |
| *, | |
| max_zones: int | None = None, | |
| zone_index: int | None = None, | |
| start_hour: int = 1, | |
| window_hours: int = 24, | |
| dpi: int = 220, | |
| ) -> Path: | |
| """Plot energy curves in compressed square layout with shared x-axis for a selected time window.""" | |
| energy_npz = Path(energy_npz) | |
| output_png = Path(output_png) | |
| with np.load(energy_npz, allow_pickle=True) as data: | |
| if "values" not in data: | |
| keys = ", ".join(sorted(data.files)) | |
| raise KeyError(f"Missing key 'values' in {energy_npz}; keys=[{keys}]") | |
| values = np.asarray(data["values"], dtype=float) | |
| columns = np.asarray(data["columns"], dtype=object) if "columns" in data else None | |
| hourly_zone = _to_hourly_zone(values) | |
| window, window_start, window_end = _time_window(hourly_zone, start_hour=start_hour, window_hours=window_hours) | |
| zone_count = window.shape[1] | |
| if zone_count < 1: | |
| raise ValueError(f"No zones found in {energy_npz}") | |
| names = _decode_zone_names(columns, zone_count) | |
| zone_indices = list(range(zone_count)) | |
| if zone_index is not None: | |
| zi = int(zone_index) | |
| if zi < 0 or zi >= zone_count: | |
| raise ValueError(f"zone_index out of range: {zi}, valid=[0, {zone_count - 1}]") | |
| zone_indices = [zi] | |
| elif max_zones is not None and max_zones > 0: | |
| zone_indices = zone_indices[: max_zones] | |
| if len(zone_indices) < 1: | |
| raise ValueError("No zones selected for plotting") | |
| plotted_zone_indices = zone_indices[:MAX_ENERGY_SUBPLOTS] | |
| omitted_count = len(zone_indices) - len(plotted_zone_indices) | |
| cmap = plt.get_cmap("tab20") | |
| x = np.arange(1, window.shape[0] + 1, dtype=int) | |
| major_ticks = _major_ticks(window.shape[0]) | |
| row_count = len(plotted_zone_indices) | |
| fig, axes = plt.subplots( | |
| row_count, | |
| 1, | |
| figsize=(FIG_SIZE_IN, FIG_SIZE_IN), | |
| sharex=True, | |
| gridspec_kw={"hspace": 0.0}, | |
| ) | |
| if row_count == 1: | |
| axes = [axes] | |
| for row_idx, zone_idx in enumerate(plotted_zone_indices): | |
| ax = axes[row_idx] | |
| color = cmap(row_idx % 20) | |
| ax.plot(x, window[:, zone_idx], color=color, linewidth=0.9, alpha=0.9) | |
| ax.set_ylabel("") | |
| ax.text( | |
| 0.02, | |
| 0.86, | |
| names[zone_idx], | |
| transform=ax.transAxes, | |
| ha="left", | |
| va="top", | |
| rotation=0, | |
| fontsize=INPLOT_LABEL_FONT_SIZE, | |
| bbox={"facecolor": "white", "alpha": 0.65, "edgecolor": "none", "pad": 1.5}, | |
| ) | |
| ax.set_xticks(major_ticks) | |
| ax.grid(axis="y", alpha=0.25, linewidth=0.5) | |
| ax.grid(axis="x", alpha=0.22, linewidth=0.45) | |
| ax.tick_params(axis="both", which="both", labelsize=TICK_LABEL_FONT_SIZE) | |
| if row_idx < row_count - 1: | |
| ax.tick_params(axis="x", which="both", labelbottom=False) | |
| if omitted_count > 0: | |
| axes[-1].text( | |
| 0.98, | |
| 0.86, | |
| f"... (+{omitted_count})", | |
| transform=axes[-1].transAxes, | |
| ha="right", | |
| va="top", | |
| fontsize=INPLOT_LABEL_FONT_SIZE, | |
| bbox={"facecolor": "white", "alpha": 0.65, "edgecolor": "none", "pad": 1.5}, | |
| ) | |
| axes[-1].set_xlabel(f"hour index in window ({window_start}-{window_end})", fontsize=AXIS_LABEL_FONT_SIZE) | |
| axes[-1].set_xlim(1, window.shape[0] + 0.5) | |
| axes[-1].set_xticks(major_ticks) | |
| axes[-1].set_xticklabels([str(t) for t in major_ticks], fontsize=TICK_LABEL_FONT_SIZE) | |
| fig.subplots_adjust(left=0.18, right=0.94, bottom=0.14, top=0.98, hspace=0.0) | |
| output_png.parent.mkdir(parents=True, exist_ok=True) | |
| fig.savefig(output_png, dpi=dpi) | |
| plt.close(fig) | |
| return output_png | |