Add --blueprint to plot_dashboard_stress

examples/python/blueprint/blueprint.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 import rerun as rr  # pip install rerun-sdk
-from rerun.blueprint import Blueprint, BlueprintPanel, Grid, SelectionPanel, Spatial2DView, TimePanel
+import rerun.blueprint as rrb
 
 
 def main() -> None:
@@ -26,20 +26,20 @@ def main() -> None:
         #
         # If auto_space_views is True, the blueprint will automatically add one of the heuristic
         # space views, which will include the image and both rectangles.
-        blueprint = Blueprint(
-            Grid(
-                Spatial2DView(name="Rect 0", origin="/", contents=["image", "rect/0"]),
-                Spatial2DView(
+        blueprint = rrb.Blueprint(
+            rrb.Grid(
+                rrb.Spatial2DView(name="Rect 0", origin="/", contents=["image", "rect/0"]),
+                rrb.Spatial2DView(
                     name="Rect 1",
                     origin="/",
                     contents=["/**"],
                     defaults=[rr.components.Radius(2)],  # Default all rectangles to have a radius of 2
                     overrides={"rect/0": [rr.components.Radius(1)]},  # Override the radius of rect/0 to be 1
                 ),
             ),
-            BlueprintPanel(state="collapsed"),
-            SelectionPanel(state="collapsed"),
-            TimePanel(state="collapsed"),
+            rrb.BlueprintPanel(state="collapsed"),
+            rrb.SelectionPanel(state="collapsed"),
+            rrb.TimePanel(state="collapsed"),
             auto_space_views=args.auto_space_views,
         )
 
@@ -49,8 +49,14 @@ def main() -> None:
     for i in range(8):
         img[(i * 16) + 4 : (i * 16) + 12, :] = (0, 0, 200)
     rr.log("image", rr.Image(img))
-    rr.log("rect/0", rr.Boxes2D(mins=[16, 16], sizes=[64, 64], labels="Rect0", colors=(255, 0, 0)))
-    rr.log("rect/1", rr.Boxes2D(mins=[48, 48], sizes=[64, 64], labels="Rect1", colors=(0, 255, 0)))
+    rr.log(
+        "rect/0",
+        rr.Boxes2D(mins=[16, 16], sizes=[64, 64], labels="Rect0", colors=(255, 0, 0)),
+    )
+    rr.log(
+        "rect/1",
+        rr.Boxes2D(mins=[48, 48], sizes=[64, 64], labels="Rect1", colors=(0, 255, 0)),
+    )
 
 
 if __name__ == "__main__":

tests/python/plot_dashboard_stress/main.py

@@ -24,23 +24,53 @@
 
 import numpy as np
 import rerun as rr  # pip install rerun-sdk
+import rerun.blueprint as rrb
 
 parser = argparse.ArgumentParser(description="Plot dashboard stress test")
 rr.script_add_args(parser)
 
 parser.add_argument("--num-plots", type=int, default=1, help="How many different plots?")
-parser.add_argument("--num-series-per-plot", type=int, default=1, help="How many series in each single plot?")
-parser.add_argument("--num-points-per-series", type=int, default=100000, help="How many points in each single series?")
-parser.add_argument("--freq", type=float, default=1000, help="Frequency of logging (applies to all series)")
-parser.add_argument("--temporal-batch-size", type=int, default=None, help="Number of rows to include in each log call")
+parser.add_argument(
+    "--num-series-per-plot",
+    type=int,
+    default=1,
+    help="How many series in each single plot?",
+)
+parser.add_argument(
+    "--num-points-per-series",
+    type=int,
+    default=100000,
+    help="How many points in each single series?",
+)
+parser.add_argument(
+    "--freq",
+    type=float,
+    default=1000,
+    help="Frequency of logging (applies to all series)",
+)
+parser.add_argument(
+    "--temporal-batch-size",
+    type=int,
+    default=None,
+    help="Number of rows to include in each log call",
+)
+parser.add_argument(
+    "--blueprint",
+    action="store_true",
+    help="Setup a blueprint for a 5s window",
+)
 
 order = [
     "forwards",
     "backwards",
     "random",
 ]
 parser.add_argument(
-    "--order", type=str, default=order[0], help="What order to log the data in (applies to all series)", choices=order
+    "--order",
+    type=str,
+    default=order[0],
+    help="What order to log the data in (applies to all series)",
+    choices=order,
 )
 
 series_type = [
@@ -68,6 +98,27 @@ def main() -> None:
     plot_paths = [f"plot_{i}" for i in range(0, args.num_plots)]
     series_paths = [f"series_{i}" for i in range(0, args.num_series_per_plot)]
 
+    if args.blueprint:
+        print("logging blueprint!")
+        rr.send_blueprint(
+            rrb.Blueprint(
+                rrb.Grid(*[
+                    rrb.TimeSeriesView(
+                        name=p,
+                        origin=f"/{p}",
+                        time_ranges=rrb.VisibleTimeRange(
+                            "sim_time",
+                            start=rrb.TimeRangeBoundary.cursor_relative(offset=rr.TimeInt(seconds=-2.5)),
+                            end=rrb.TimeRangeBoundary.cursor_relative(offset=rr.TimeInt(seconds=2.5)),
+                        ),
+                    )
+                    for p in plot_paths
+                ]),
+                rrb.BlueprintPanel(state="collapsed"),
+                rrb.SelectionPanel(state="collapsed"),
+            )
+        )
+
     time_per_sim_step = 1.0 / args.freq
     stop_time = args.num_points_per_series * time_per_sim_step
 
@@ -110,7 +161,10 @@ def main() -> None:
         ticks = enumerate(sim_times)
     else:
         offsets = range(0, len(sim_times), args.temporal_batch_size)
-        ticks = zip(offsets, (sim_times[offset : offset + args.temporal_batch_size] for offset in offsets))
+        ticks = zip(
+            offsets,
+            (sim_times[offset : offset + args.temporal_batch_size] for offset in offsets),
+        )
 
     time_batch = None
 
@@ -129,7 +183,11 @@ def main() -> None:
                 else:
                     value_index = slice(index, index + args.temporal_batch_size)
                     value_batch = rr.components.ScalarBatch(values[value_index, plot_idx, series_idx])
-                    rr.log_temporal_batch(f"{plot_path}/{series_path}", times=[time_batch], components=[value_batch])
+                    rr.log_temporal_batch(
+                        f"{plot_path}/{series_path}",
+                        times=[time_batch],
+                        components=[value_batch],
+                    )
 
         # Progress report