#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Dataset Overview Figure ======================= A comprehensive visualization of the continuous seismic waveform dataset, contrasting the 2019 Ridgecrest earthquake sequence with a quiet 2021 period. Usage ----- python plot_dataset_overview.py \ --label-json data/label/annotations_for_continuous_hdf5.json \ --waveform-db data/index/waveform_index.sqlite \ --h5-dir data/hdf5 \ --out figures/dataset_overview.pdf Dependencies ------------ numpy, matplotlib, h5py, scipy (optional, for envelope) """ from __future__ import annotations import argparse import json import math import sqlite3 from collections import defaultdict from datetime import datetime, timezone from pathlib import Path from typing import Dict, List, Optional, Tuple import h5py import numpy as np import matplotlib import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec import matplotlib.patches as mpatches import matplotlib.ticker as mticker from matplotlib.lines import Line2D # ────────────────────────────────────────────────────────────────────────────── # Global style # ────────────────────────────────────────────────────────────────────────────── RIDGECREST_COLOR = "#C0392B" # deep red – 2019 Ridgecrest sequence QUIET_COLOR = "#2471A3" # steel blue – 2021 quiet period NET_COLORS = {"CI": "#1F618D", "BK": "#196F3D", "NC": "#B7770D"} NET_LABELS = {"CI": "CI – Southern California", "BK": "BK – Berkeley", "NC": "NC – Northern California"} P_COLOR = "#1A5276" S_COLOR = "#922B21" ACCENT = "#F39C12" FONT_TITLE = dict(fontsize=14, fontweight="bold", color="#1C2833") FONT_LABEL = dict(fontsize=12, color="#2C3E50") FONT_ANNOT = dict(fontsize=10, color="#555555") # ────────────────────────────────────────────────────────────────────────────── # Data helpers # ────────────────────────────────────────────────────────────────────────────── def load_stations(db_path: Path) -> List[Dict]: conn = sqlite3.connect(str(db_path)) rows = conn.execute(""" SELECT station_key, network, station, AVG(latitude) as lat, AVG(longitude) as lon, COUNT(DISTINCT DATE(datetime(start_epoch,'unixepoch'))) as n_days FROM waveform_segments WHERE latitude IS NOT NULL AND ABS(latitude) > 0.1 GROUP BY station_key """).fetchall() conn.close() return [{"key": r[0], "net": r[1], "sta": r[2], "lat": r[3], "lon": r[4], "n_days": r[5]} for r in rows] def load_events(label_json: Path) -> List[Dict]: with open(label_json, encoding="utf-8") as f: data = json.load(f) events = [] for yr in data.get("years", {}).values(): for day_obj in yr.get("days", {}).values(): for ev in day_obj.get("events", {}).values(): evd = ev.get("event", {}) t = evd.get("event_time", "") mag = evd.get("magnitude") if not t or mag is None: continue events.append({ "time": t, "day": t[:10], "mag": float(mag), "lat": evd.get("latitude"), "lon": evd.get("longitude"), "dep": evd.get("depth_km"), "picks": ev.get("counts", {}).get("pick_count", 0), }) return events def load_station_picks(label_json: Path, station_id: str, date_str: str) -> List[Dict]: with open(label_json, encoding="utf-8") as f: data = json.load(f) picks = [] for yr in data.get("years", {}).values(): for day_obj in yr.get("days", {}).values(): for ev in day_obj.get("events", {}).values(): for sid0, sobj in ev.get("stations", {}).items(): for p in sobj.get("picks", []): sid = p.get("station_id") or sid0 t = p.get("time", "") if sid == station_id and t.startswith(date_str): picks.append({"time": t, "phase": p.get("phase", "?"), "status": p.get("status", "")}) return picks def select_best_station_day( label_json: Path, waveform_db: Path, year_prefix: str = "2019", min_picks: int = 50, max_picks: int = 300, preferred_channels: Tuple[str, ...] = ("HHZ", "BHZ", "EHZ", "HNZ"), ) -> Optional[Tuple[str, str, str, int]]: """ Select station-day with the largest number of reference picks and available waveform in the database. Returns ------- (station_id, channel, date_str, n_picks) """ with open(label_json, encoding="utf-8") as f: data = json.load(f) counter = defaultdict(int) for yr in data.get("years", {}).values(): for day_obj in yr.get("days", {}).values(): for ev in day_obj.get("events", {}).values(): for sid0, sobj in ev.get("stations", {}).items(): for p in sobj.get("picks", []): sid = p.get("station_id") or sid0 t = p.get("time", "") if sid and t.startswith(year_prefix): counter[(sid, t[:10])] += 1 if not counter: return None conn = sqlite3.connect(str(waveform_db)) candidates = [ ((sid, date_str), n_picks) for (sid, date_str), n_picks in counter.items() if min_picks <= n_picks <= max_picks ] candidates = sorted(candidates, key=lambda kv: kv[1], reverse=True) for (sid, date_str), n_picks in candidates: for ch in preferred_channels: row = conn.execute(""" SELECT channel FROM waveform_segments WHERE station_id=? AND channel=? AND DATE(datetime(start_epoch,'unixepoch'))=? ORDER BY npts DESC LIMIT 1 """, (sid, ch, date_str)).fetchone() if row is not None: conn.close() return sid, ch, date_str, n_picks conn.close() return None def query_waveform(db_path: Path, station_id: str, channel: str, date_str: str) -> Optional[Dict]: conn = sqlite3.connect(str(db_path)) row = conn.execute(""" SELECT dataset_path, h5_file, npts, sampling_rate, start_epoch, latitude, longitude FROM waveform_segments WHERE station_id=? AND channel=? AND DATE(datetime(start_epoch,'unixepoch'))=? ORDER BY npts DESC LIMIT 1 """, (station_id, channel, date_str)).fetchone() conn.close() if row is None: return None return {"path": row[0], "h5_file": row[1], "npts": row[2], "sr": row[3], "t0": row[4], "lat": row[5], "lon": row[6]} def read_waveform_downsampled(info: Dict, h5_dir: Optional[Path] = None, target_hz: float = 1.0) -> Tuple[np.ndarray, np.ndarray]: """Read waveform and downsample to target_hz via RMS in each window.""" h5_path = info["h5_file"] if h5_dir is not None: h5_path = str(h5_dir / Path(h5_path).name) with h5py.File(h5_path, "r") as h5: raw = h5[info["path"]][:] raw = raw.astype(np.float32) sr = float(info["sr"]) win = max(1, int(sr / target_hz)) n_wins = len(raw) // win data = raw[: n_wins * win].reshape(n_wins, win) # RMS envelope for display envelope = np.sqrt(np.mean(data ** 2, axis=1)) t0 = float(info["t0"]) times = np.arange(n_wins) / target_hz # seconds from midnight return times, envelope def iso_to_epoch(s: str) -> float: s = s.strip() if s.endswith("Z"): s = s[:-1] + "+00:00" dt = datetime.fromisoformat(s) if dt.tzinfo is None: dt = dt.replace(tzinfo=timezone.utc) return dt.timestamp() # ────────────────────────────────────────────────────────────────────────────── # Individual panel drawers # ────────────────────────────────────────────────────────────────────────────── def draw_station_map(ax: plt.Axes, stations: List[Dict], events: List[Dict]) -> None: """Panel A – station map with network colours and Ridgecrest epicentres.""" # Background colour ax.set_facecolor("#EBF5FB") # Plot stations per network for net, color in NET_COLORS.items(): sub = [s for s in stations if s["net"] == net] lons = [s["lon"] for s in sub] lats = [s["lat"] for s in sub] ax.scatter(lons, lats, c=color, s=22, alpha=0.75, linewidths=0, label=f"{net} ({len(sub)} stations)", zorder=3) # Ridgecrest main shocks ridgecrest = [ (35.705, -117.504, "M6.4\n2019-07-04"), (35.770, -117.599, "M7.1\n2019-07-06"), ] for lat, lon, lbl in ridgecrest: ax.scatter(lon, lat, marker="*", c=RIDGECREST_COLOR, s=420, zorder=6, edgecolors="white", linewidths=0.7) ax.annotate(lbl, (lon, lat), xytext=(5, 5), textcoords="offset points", fontsize=9, color=RIDGECREST_COLOR, fontweight="bold", zorder=7) # Mark the two showcase stations showcase = [ ("CI.ADO.--", 34.550, -117.434, "CI.ADO\n(Ridgecrest\ncase)", "left"), ("CI.CSH.--", 33.644, -116.596, "CI.CSH\n(Quiet\ncase)", "right"), ] for sid, lat, lon, lbl, ha in showcase: ax.scatter(lon, lat, marker="^", c=ACCENT, s=120, zorder=5, edgecolors="white", linewidths=0.8) xoff = 6 if ha == "left" else -6 ax.annotate(lbl, (lon, lat), xytext=(xoff, 7), textcoords="offset points", ha=ha, fontsize=9.5, color="#6E2F1A", fontweight="bold", bbox=dict(boxstyle="round,pad=0.2", fc="white", alpha=0.7, lw=0), zorder=7) # Legend entries for epicentres and stations leg_extra = [ Line2D([0], [0], marker="*", color="w", markerfacecolor=RIDGECREST_COLOR, markersize=7, label="Ridgecrest epicentre"), Line2D([0], [0], marker="^", color="w", markerfacecolor=ACCENT, markersize=5, label="Showcase station"), ] handles, labels = ax.get_legend_handles_labels() ax.legend(handles + leg_extra, labels + [h.get_label() for h in leg_extra], fontsize=7, loc="upper left", framealpha=0.88, edgecolor="#AAAAAA", labelspacing=0.3, handlelength=1.2, handletextpad=0.4, borderpad=0.4) # Map extent & labels ax.set_xlim(-124.6, -113.8) ax.set_ylim(32.2, 43.2) ax.set_xlabel("Longitude", **FONT_LABEL) ax.set_ylabel("Latitude", **FONT_LABEL) ax.tick_params(labelsize=10) # Simple graticule ax.xaxis.set_major_locator(mticker.MultipleLocator(2)) ax.yaxis.set_major_locator(mticker.MultipleLocator(2)) ax.grid(True, lw=0.4, color="white", alpha=0.7) # Panel label ax.set_title("A · Seismic Network Coverage", loc="left", **FONT_TITLE, pad=6) # Dataset overview inset (text box) n_ci = sum(1 for s in stations if s["net"] == "CI") n_bk = sum(1 for s in stations if s["net"] == "BK") n_nc = sum(1 for s in stations if s["net"] == "NC") total_picks = sum(e["picks"] for e in events) summary = ( f"Networks: CI·BK·NC\n" f"Stations: {len(stations):,} total\n" f"Days: 14 (7 + 7)\n" f"Events: {len(events):,}\n" f"Total P/S picks: {total_picks:,}" ) ax.text(0.975, 0.97, summary, transform=ax.transAxes, fontsize=8.5, va="top", ha="right", family="monospace", bbox=dict(boxstyle="round,pad=0.6", fc="white", alpha=0.88, ec="#AAAAAA", lw=0.8)) def draw_activity_timeline(ax: plt.Axes, events: List[Dict]) -> None: """Panel B – events & picks per day with broken x-axis feel.""" daily_ev = defaultdict(int) daily_pk = defaultdict(int) for e in events: daily_ev[e["day"]] += 1 daily_pk[e["day"]] += e["picks"] days_2019 = sorted(d for d in daily_ev if d.startswith("2019")) days_2021 = sorted(d for d in daily_ev if d.startswith("2021")) all_days = days_2019 + ["gap"] + days_2021 # X positions with a visual gap pos = {} x = 0 for d in days_2019: pos[d] = x; x += 1 x += 1.2 # gap for d in days_2021: pos[d] = x; x += 1 # Bars: events (left y), picks (right y) ax2 = ax.twinx() bar_w = 0.38 for d in days_2019 + days_2021: col = RIDGECREST_COLOR if d.startswith("2019") else QUIET_COLOR x_ = pos[d] ax.bar(x_ - bar_w/2, max(daily_ev[d], 1), width=bar_w, color=col, alpha=0.90, zorder=3) ax2.bar(x_ + bar_w/2, max(daily_pk[d], 1), width=bar_w, color=col, alpha=0.45, zorder=2) # X tick labels xticks = [pos[d] for d in days_2019 + days_2021] xlbls = [d[5:] for d in days_2019 + days_2021] # MM-DD ax.set_xticks(xticks) ax.set_xticklabels(xlbls, rotation=40, ha="right", fontsize=10) # Log scale on both y-axes ax.set_yscale("log") ax2.set_yscale("log") ax.set_ylim(bottom=0.7) ax2.set_ylim(bottom=0.7) # Gap annotation – place at a fixed log-scale-friendly y gap_x = (pos[days_2019[-1]] + pos[days_2021[0]]) / 2 ax.text(gap_x, 2.5, "╌╌ ~2 yrs ╌╌", ha="center", va="bottom", fontsize=9.5, color="#888888") # Axes styling – use compact 10^n tick labels ax.yaxis.set_major_formatter(mticker.LogFormatterSciNotation(labelOnlyBase=True)) ax2.yaxis.set_major_formatter(mticker.LogFormatterSciNotation(labelOnlyBase=True)) ax.set_ylabel("Events / day", **FONT_LABEL) ax2.set_ylabel("Picks / day", labelpad=0, fontsize=12, color="#666666") ax.tick_params(axis="y", labelsize=10) ax2.tick_params(axis="y", labelsize=10, labelcolor="#888888") ax.set_xlim(-0.7, pos[days_2021[-1]] + 0.7) # Legend handles = [ mpatches.Patch(color=RIDGECREST_COLOR, alpha=0.9, label="Events (2019)"), mpatches.Patch(color=QUIET_COLOR, alpha=0.9, label="Events (2021)"), mpatches.Patch(color=RIDGECREST_COLOR, alpha=0.4, label="Picks (2019)"), mpatches.Patch(color=QUIET_COLOR, alpha=0.4, label="Picks (2021)"), ] ax.legend(handles=handles, fontsize=10, loc="upper left", framealpha=0.85, edgecolor="#AAAAAA", ncol=2, labelspacing=0.4) ax.set_title("B · Daily Seismic Activity", loc="left", **FONT_TITLE, pad=6) ax.spines[["top", "right"]].set_visible(False) ax2.spines[["top", "left"]].set_visible(False) ax.grid(axis="y", lw=0.4, alpha=0.5, zorder=0) box = ax.get_position() dx = 0.02 ax.set_position([box.x0 - dx, box.y0, box.width, box.height]) def draw_magnitude_distribution(ax: plt.Axes, events: List[Dict]) -> None: """Panel C – cumulative magnitude-frequency plot for both periods.""" ev_2019 = sorted([e["mag"] for e in events if e["day"].startswith("2019")]) ev_2021 = sorted([e["mag"] for e in events if e["day"].startswith("2021")]) def cdf(mags): m = np.array(sorted(mags)) n = np.arange(len(m), 0, -1) # cumulative from right return m, n m19, n19 = cdf(ev_2019) m21, n21 = cdf(ev_2021) ax.semilogy(m19, n19, color=RIDGECREST_COLOR, lw=1.8, label=f"2019 (N={len(ev_2019):,})") ax.semilogy(m21, n21, color=QUIET_COLOR, lw=1.8, label=f"2021 (N={len(ev_2021):,})") ax.fill_betweenx(n19, m19, alpha=0.10, color=RIDGECREST_COLOR) ax.fill_betweenx(n21, m21, alpha=0.10, color=QUIET_COLOR) # Mark main shocks for idx, mag, lbl in [(0, 7.1, "M7.1"), (1, 6.4, "M6.4")]: ax.axvline(mag, lw=1.2, ls="--", color=RIDGECREST_COLOR, alpha=0.7) ax.text(mag + 0.07, n19.max() * (idx*2+4)*0.1, lbl, fontsize=9.5, color=RIDGECREST_COLOR, va="top", fontweight="bold") ax.set_xlabel("Magnitude", **FONT_LABEL) ax.set_ylabel("Cumul. # events ≥ M", labelpad=0, **FONT_LABEL) ax.yaxis.set_major_formatter(mticker.LogFormatterSciNotation(labelOnlyBase=True)) ax.tick_params(labelsize=10) ax.legend(fontsize=10, framealpha=0.85, edgecolor="#AAAAAA") ax.set_title("C · Magnitude–Frequency", loc="left", **FONT_TITLE, pad=6) ax.spines[["top", "right"]].set_visible(False) ax.grid(lw=0.4, alpha=0.4) def draw_waveform(ax: plt.Axes, times: np.ndarray, envelope: np.ndarray, picks: List[Dict], t0_epoch: float, date_str: str, station: str, channel: str, period_label: str, color: str) -> None: """Panel D / E – single-day waveform envelope with pick markers.""" # Normalise envelope for display env_norm = envelope / (np.percentile(envelope, 99) + 1e-9) env_norm = np.clip(env_norm, 0, 8) # Shade fill ax.fill_between(times / 3600, env_norm, alpha=0.35, color=color, lw=0) ax.plot(times / 3600, env_norm, lw=0.5, color=color, alpha=0.8) # Pick markers p_times = [p for p in picks if p["phase"] == "P"] s_times = [p for p in picks if p["phase"] == "S"] for group, col, yoff, lbl in [ (p_times, P_COLOR, 0.92, "P"), (s_times, S_COLOR, 0.62, "S"), ]: for p in group: try: t_epoch = iso_to_epoch(p["time"]) t_sec = t_epoch - t0_epoch t_hr = t_sec / 3600 ax.axvline(t_hr, lw=0.7, color=col, alpha=0.65, zorder=4) except Exception: continue if group: ax.text( 0.99, yoff, f"{lbl} ({len(group)})", transform=ax.transAxes, ha="right", va="top", fontsize=10, color=col, fontweight="bold", zorder=20, bbox=dict( boxstyle="round,pad=0.25", facecolor="white", edgecolor="#CCCCCC", linewidth=0.4, alpha=0.85, ), ) # Axes ax.set_xlim(0, 24) ax.set_xticks(range(0, 25, 3)) ax.set_xticklabels([f"{h:02d}:00" for h in range(0, 25, 3)], fontsize=10) ax.set_ylabel("Norm. amplitude", **FONT_LABEL) ax.tick_params(axis="y", labelsize=10) ax.spines[["top", "right"]].set_visible(False) # Title title = (f"{period_label} · {station} {channel} · {date_str}") ax.set_title(title, loc="left", **FONT_TITLE, pad=5) # Annotation box n_picks = len(picks) ax.text( 0.01, 0.97, # 更靠上 f"Reference picks: {n_picks}", transform=ax.transAxes, fontsize=10, color="#333333", va="top", zorder=10, # 🔴 关键：压到最上层 bbox=dict( boxstyle="round,pad=0.35", facecolor="white", # 比 fc 更规范 edgecolor="none", alpha=0.85 # 稍微更实一点 ) ) def draw_stats_banner(ax: plt.Axes, stations: List[Dict], events: List[Dict]) -> None: """Panel F – horizontal key-numbers summary.""" ax.axis("off") n_ev_2019 = sum(1 for e in events if e["day"].startswith("2019")) n_ev_2021 = sum(1 for e in events if e["day"].startswith("2021")) n_pk_2019 = sum(e["picks"] for e in events if e["day"].startswith("2019")) n_pk_2021 = sum(e["picks"] for e in events if e["day"].startswith("2021")) max_mag = max(e["mag"] for e in events) items = [ ("979", "Seismic\nstations", "#1F618D"), ("CI·BK·NC", "Networks", "#196F3D"), ("14 days", "Continuous\ncoverage", "#7D6608"), (f"{n_ev_2019:,}", "2019 sequence\nevents", RIDGECREST_COLOR), (f"{n_pk_2019:,}", "2019 sequence\nP/S picks", RIDGECREST_COLOR), (f"M{max_mag:.1f}", "Largest\nevent", RIDGECREST_COLOR), (f"{n_ev_2021:,}", "2021 quiet\nevents", QUIET_COLOR), (f"{n_pk_2021:,}", "2021 quiet\nP/S picks", QUIET_COLOR), (f"×{n_ev_2019//max(n_ev_2021,1):.0f}", "More events\nin 2019", "#7B241C"), ] ncols = len(items) for i, (val, lbl, col) in enumerate(items): x = (i + 0.5) / ncols ax.text(x, 0.70, val, ha="center", va="center", fontsize=15, fontweight="bold", color=col, transform=ax.transAxes) ax.text(x, 0.18, lbl, ha="center", va="center", fontsize=7.2, color="#555555", linespacing=1.05, transform=ax.transAxes) # Divider lines for i in range(1, ncols): x = i / ncols ax.axvline(x, lw=0.5, color="#CCCCCC", ymin=0.05, ymax=0.95) ax.set_title("F · Dataset Overview and Scale", loc="left", **FONT_TITLE, pad=4) # ────────────────────────────────────────────────────────────────────────────── # Main figure assembly # ────────────────────────────────────────────────────────────────────────────── def build_figure(label_json: Path, waveform_db: Path, h5_dir: Path, out_path: Path) -> None: print("[1/6] Loading stations …") stations = load_stations(waveform_db) print("[2/6] Loading events & picks …") events = load_events(label_json) print("[3/6] Loading waveforms …") best_2019 = select_best_station_day( label_json=label_json, waveform_db=waveform_db, year_prefix="2019", max_picks=500, preferred_channels=("HHZ", "BHZ", "EHZ", "HNZ"), ) if best_2019 is None: print(" [WARN] No valid 2019 station-day found. Fall back to CI.ADO.--") ridge_sid, ridge_ch, ridge_date = "CI.ADO.--", "HHZ", "2019-07-05" else: ridge_sid, ridge_ch, ridge_date, ridge_npicks = best_2019 print( f" Best 2019 station-day: {ridge_sid} {ridge_ch} " f"{ridge_date} with {ridge_npicks} reference picks" ) wf_cfg = [ ("ridgecrest", ridge_sid, ridge_ch, ridge_date, RIDGECREST_COLOR), ("quiet", "CI.CSH.--", "HHZ", "2021-11-14", QUIET_COLOR), ] waveforms = {} picks_wf = {} for label, sid, ch, date_str, col in wf_cfg: info = query_waveform(waveform_db, sid, ch, date_str) if info is None: print(f" [WARN] waveform not found: {sid} {ch} {date_str}") continue print(f" Reading {sid} {ch} {date_str} npts={info['npts']:,} …") t, env = read_waveform_downsampled(info, h5_dir=h5_dir, target_hz=1.0) waveforms[label] = (t, env, info, col, sid, ch, date_str) picks_wf[label] = load_station_picks(label_json, sid, date_str) print(f" {len(picks_wf[label])} picks found for {sid} on {date_str}") # ── Layout ──────────────────────────────────────────────────────────────── print("[4/6] Building figure …") fig = plt.figure(figsize=(12, 8), dpi=150) fig.patch.set_facecolor("white") gs_outer = gridspec.GridSpec( 3, 1, hspace=0.52, #wspace=0.55, height_ratios=[4.2, 1.55, 1.55], left=0.07, right=0.97, top=0.97, bottom=0.13, ) # Row 0: map + timeline + magnitude gs_top = gridspec.GridSpecFromSubplotSpec( 1, 3, subplot_spec=gs_outer[0], width_ratios=[1.35, 1.50, 1.15], wspace=0.30, ) ax_map = fig.add_subplot(gs_top[0]) ax_time = fig.add_subplot(gs_top[1]) ax_mag = fig.add_subplot(gs_top[2]) # Rows 1–2: waveforms ax_wf = {} for row_i, key in enumerate(["ridgecrest", "quiet"]): ax_wf[key] = fig.add_subplot(gs_outer[row_i + 1]) # Stats banner: inset below the quiet waveform panel ax_banner = ax_wf["quiet"].inset_axes([0, -0.92, 1.0, 0.50]) # ── Draw panels ─────────────────────────────────────────────────────────── print("[5/6] Drawing panels …") draw_station_map(ax_map, stations, events) draw_activity_timeline(ax_time, events) draw_magnitude_distribution(ax_mag, events) for label, col, period_lbl in [ ("ridgecrest", RIDGECREST_COLOR, "D · Dense Ridgecrest Aftershock Sequence"), ("quiet", QUIET_COLOR, "E · Quiet Period"), ]: ax = ax_wf[label] if label in waveforms: t, env, info, c, sid, ch, date_str = waveforms[label] draw_waveform( ax, t, env, picks_wf.get(label, []), t0_epoch=info["t0"], date_str=date_str, station=sid, channel=ch, period_label=period_lbl, color=c, ) else: ax.text(0.5, 0.5, "Waveform not available", ha="center", va="center", transform=ax.transAxes, fontsize=9, color="#888888") ax.set_title(period_lbl, loc="left", **FONT_TITLE, pad=5) ax.set_xlabel("Time (UTC)", **FONT_LABEL) draw_stats_banner(ax_banner, stations, events) # ── Title ───────────────────────────────────────────────────────────────── # suptitle removed per user request; panel titles (A–F) are retained. # ── Save ────────────────────────────────────────────────────────────────── print(f"[6/6] Saving → {out_path} …") out_path.parent.mkdir(parents=True, exist_ok=True) fig.savefig(out_path, dpi=200, bbox_inches="tight", facecolor="white") plt.close(fig) print(f"Done. {out_path}") # ────────────────────────────────────────────────────────────────────────────── # CLI # ────────────────────────────────────────────────────────────────────────────── def main() -> None: parser = argparse.ArgumentParser(description="Dataset overview figure.") parser.add_argument("--label-json", type=Path, default=Path("data/label/annotations_for_continuous_hdf5.json")) parser.add_argument("--waveform-db", type=Path, default=Path("data/index/waveform_index.sqlite")) parser.add_argument("--h5-dir", type=Path, default=Path("data/hdf5")) parser.add_argument("--out", type=Path, default=Path("figures/dataset_overview.png")) parser.add_argument("--dpi", type=int, default=200) args = parser.parse_args() build_figure( label_json = args.label_json, waveform_db = args.waveform_db, h5_dir = args.h5_dir, out_path = args.out, ) if __name__ == "__main__": main()