chore: import upstream snapshot with attribution

2026-07-13 13:05:14 +08:00
commit 2a547be7fe
7904 changed files with 1000926 additions and 0 deletions
@@ -0,0 +1,91 @@
+#!/usr/bin/env python3
+"""Show several live plots of random walk data using a scrolling fixed window size."""
+
+from __future__ import annotations
+
+import argparse
+import time
+from typing import TYPE_CHECKING
+
+import numpy as np
+
+import rerun as rr  # pip install rerun-sdk
+import rerun.blueprint as rrb
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+
+def random_walk_generator() -> Iterator[float]:
+    value = 0.0
+    while True:
+        value += np.random.normal()
+        yield value
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Plot dashboard stress test")
+    rr.script_add_args(parser)
+
+    parser.add_argument("--num-plots", type=int, default=6, help="How many different plots?")
+    parser.add_argument("--num-series-per-plot", type=int, default=5, help="How many series in each single plot?")
+    parser.add_argument("--freq", type=float, default=100, help="Frequency of logging (applies to all series)")
+    parser.add_argument("--window-size", type=float, default=5.0, help="Size of the window in seconds")
+    parser.add_argument("--duration", type=float, default=60, help="How long to log for in seconds")
+
+    args = parser.parse_args()
+
+    plot_paths = [f"plot_{i}" for i in range(args.num_plots)]
+    series_paths = [f"series_{i}" for i in range(args.num_series_per_plot)]
+
+    rr.script_setup(args, "rerun_example_live_scrolling_plot")
+
+    # Always send the blueprint since it is a function of the data.
+    rr.send_blueprint(
+        rrb.Grid(
+            contents=[
+                rrb.TimeSeriesView(
+                    origin=plot_path,
+                    time_ranges=[
+                        rrb.VisibleTimeRange(
+                            "time",
+                            start=rrb.TimeRangeBoundary.cursor_relative(seconds=-args.window_size),
+                            end=rrb.TimeRangeBoundary.cursor_relative(),
+                        ),
+                    ],
+                    plot_legend=rrb.PlotLegend(visible=False),
+                )
+                for plot_path in plot_paths
+            ],
+        ),
+    )
+
+    # Generate a list of generators for each series in each plot
+    values = [[random_walk_generator() for _ in range(args.num_series_per_plot)] for _ in range(args.num_plots)]
+
+    cur_time = time.time()
+    end_time = cur_time + args.duration
+    time_per_tick = 1.0 / args.freq
+
+    while cur_time < end_time:
+        # Advance time and sleep if necessary
+        cur_time += time_per_tick
+        sleep_for = cur_time - time.time()
+        if sleep_for > 0:
+            time.sleep(sleep_for)
+
+        if sleep_for < -0.1:
+            print(f"Warning: missed logging window by {-sleep_for:.2f} seconds")
+
+        rr.set_time("time", timestamp=cur_time)
+
+        # Output each series based on its generator
+        for plot_idx, plot_path in enumerate(plot_paths):
+            for series_idx, series_path in enumerate(series_paths):
+                rr.log(f"{plot_path}/{series_path}", rr.Scalars(next(values[plot_idx][series_idx])))
+
+    rr.script_teardown(args)
+
+
+if __name__ == "__main__":
+    main()