New example and tutorial showing how to create a live scrolling plot

docs/content/howto.md

@@ -5,6 +5,7 @@ order: 1
 
 Guides for using Rerun in more advanced ways.
  - [Configure the viewer through code](howto/configure-viewer-through-code.md)
+ - [Create a fixed-window plot](howto/fixed-window-plot.md)
  - [Limit memory usage](howto/limit-ram.md)
  - [Share recordings across multiple processes](howto/shared-recordings.md)
  - [Clear out already logged data](howto/short-lived-entities.md)

docs/content/howto/fixed-window-plot.md

@@ -0,0 +1,62 @@
+---
+title: Create a fixed-window plot
+order: 150
+---
+
+As of Rerun 0.16, the [TimeSeriesView](../reference/types/views/time_series_view.md) now supports direct
+manipulation of the visible time range. This allows you to create a plot that only shows a fixed window of data.
+
+## VisibleTimeRange
+
+To specify the visible time range, you must pass one or more `VisibleTimeRange` objects to the `time_ranges` parameter of the `TimeSeriesView` blueprint type. If your app only uses a single timeline, you can directly pass a single `VisibleTimeRange` object instead of wrapping it in a list.
+
+The `VisibleTimeRange` object takes three parameters:
+- `timeline`: The timeline that the range will apply to. This must match the timeline used to log your data, or if you are only using the rerun-provided timestamps, you can use the strings `"log_time"`, or `"log_tick"`.
+- `start`: The start of the visible time range.
+- `end`: The end of the visible time range.
+
+The `start` and `end` parameters are set using a `TimeRangeBoundary`:
+- To specify an absolute time, you can use the `TimeRangeBoundary.absolute()` method.
+- To specify a cursor-relative time, you can use the `TimeRangeBoundary.cursor_relative()` method.
+- You can also specify `TimeRangeBoundary.infinite()` to indicate that the start or end of the time range should be unbounded.
+
+In order to account for the different types of timeline (temporal or sequence-based), both the
+`TimeRangeBoundary.absolute()` and `TimeRangeBoundary.cursor_relative()` methods can be specified using one of
+the keyword args:
+- `seconds`: Use this if you called `rr.set_time_seconds()` to update the timeline.
+- `nanos`: Use this if you called `rr.set_time_nanos()` to update the timeline.
+- `seq`: Use this if you called `rr.set_time_seq()` to update the timeline.
+
+## Example syntax
+To create a trailing 5 second window plot, you can specify your `TimeSeriesView` like this:
+```python
+rrb.TimeSeriesView(
+    origin="plot_path",
+    time_ranges=rrb.VisibleTimeRange(
+            timeline="time",
+            start=rrb.TimeRangeBoundary.cursor_relative(seconds=-5.0),
+            end=rrb.TimeRangeBoundary.cursor_relative(),
+        )
+)
+```
+
+## Full example
+For a complete working example, you can run the following code:
+
+snippet: tutorials/fixed_window_plot
+
+This should create a plot that only shows the last 5 seconds of data. If you select the view, you should
+see that the time range is configured as expected.
+
+<picture>
+  <img src="https://static.rerun.io/fixed_window_example/f76228dc2e1212c148064c2193cdf75ef14bb2b9/full.png" alt="">
+  <source media="(max-width: 480px)" srcset="https://static.rerun.io/fixed_window_example/f76228dc2e1212c148064c2193cdf75ef14bb2b9/480w.png">
+  <source media="(max-width: 768px)" srcset="https://static.rerun.io/fixed_window_example/f76228dc2e1212c148064c2193cdf75ef14bb2b9/768w.png">
+  <source media="(max-width: 1024px)" srcset="https://static.rerun.io/fixed_window_example/f76228dc2e1212c148064c2193cdf75ef14bb2b9/1024w.png">
+  <source media="(max-width: 1200px)" srcset="https://static.rerun.io/fixed_window_example/f76228dc2e1212c148064c2193cdf75ef14bb2b9/1200w.png">
+</picture>
+
+Alternatively, you can check out a more full-featured example with multiple plot windows [here](https://github.com/rerun-io/rerun/tree/latest/examples/python/live_scrolling_plot?speculative-link).
+
+## Additional notes
+- Any time you log data, it has two timepoints associated with it: "log_time", and "log_tick".

docs/snippets/all/tutorials/fixed_window_plot.py

@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+"""A live plot of a random walk using a scrolling fixed window size."""
+
+from __future__ import annotations
+
+import time
+
+import numpy as np
+import rerun as rr  # pip install rerun-sdk
+import rerun.blueprint as rrb
+
+rr.init("rerun_example_fixed_window_plot", spawn=True)
+
+rr.send_blueprint(
+    rrb.TimeSeriesView(
+        origin="random_walk",
+        time_ranges=rrb.VisibleTimeRange(
+            "time",
+            start=rrb.TimeRangeBoundary.cursor_relative(seconds=-5.0),
+            end=rrb.TimeRangeBoundary.cursor_relative(),
+        ),
+    )
+)
+
+cur_time = time.time()
+value = 0.0
+
+while True:
+    cur_time += 0.01
+    sleep_for = cur_time - time.time()
+    if sleep_for > 0:
+        time.sleep(sleep_for)
+
+    value += np.random.normal()
+
+    rr.set_time_seconds("time", cur_time)
+
+    rr.log("random_walk", rr.Scalar(value))

docs/snippets/snippets.toml

@@ -37,7 +37,11 @@
   "rust",
   "py",
 ]
-
+"tutorials/fixed_window_plot" = [
+  "cpp",  # Not implemented
+  "rust", # Not implemented
+  "py",   # Doesn't terminate
+]
 
 "migration/log_line" = [ # Not a complete example -- just a single log line
   "cpp",

examples/manifest.toml

@@ -131,6 +131,7 @@ examples = [
   "multiprocess_logging",
   "multithreading",
   "plots",
+  "live_scrolling_plot",
   "raw_mesh",
 ]
 

examples/python/live_scrolling_plot/README.md

@@ -0,0 +1,69 @@
+<!--[metadata]
+title = "Live Scrolling Plot"
+tags = ["Plots", "Live"]
+thumbnail = "https://static.rerun.io/live_scrolling_plot_thumbnail/73c6b11bd074af258b8d30092e15361e358d8069/480w.png"
+thumbnail_dimensions = [480, 384]
+-->
+
+Visualize a live stream of several plots, scrolling horizontally to keep a fixed window of data.
+
+<picture>
+  <img src="https://static.rerun.io/live_scrolling_plot/9c9a9b3a4dd1d5e858ba58489f686b5d481cfb2e/full.png" alt="">
+  <source media="(max-width: 480px)" srcset="https://static.rerun.io/live_scrolling_plot/9c9a9b3a4dd1d5e858ba58489f686b5d481cfb2e/480w.png">
+  <source media="(max-width: 768px)" srcset="https://static.rerun.io/live_scrolling_plot/9c9a9b3a4dd1d5e858ba58489f686b5d481cfb2e/768w.png">
+  <source media="(max-width: 1024px)" srcset="https://static.rerun.io/live_scrolling_plot/9c9a9b3a4dd1d5e858ba58489f686b5d481cfb2e/1024w.png">
+  <source media="(max-width: 1200px)" srcset="https://static.rerun.io/live_scrolling_plot/9c9a9b3a4dd1d5e858ba58489f686b5d481cfb2e/1200w.png">
+</picture>
+
+## Used Rerun types
+[`Scalar`](https://www.rerun.io/docs/reference/types/archetypes/scalar)
+
+## Setting up the blueprint
+
+In order to only show a fixed window of data, this example creates a blueprint that uses
+the `time_ranges` parameter of the `TimeSeriesView` blueprint type.
+
+We dynamically create a `TimeSeriesView` for each plot we want to show, so that we can
+set the `time_ranges`. The start of the visible time range is set to the current time
+minus the window size, and the end is set to the current time.
+
+```python
+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
+        ]
+    ),
+)
+
+```
+
+## Run the code
+To run this example, make sure you have the Rerun repository checked out and the latest SDK installed:
+```bash
+# Setup
+pip install --upgrade rerun-sdk  # install the latest Rerun SDK
+git clone [email protected]:rerun-io/rerun.git  # Clone the repository
+cd rerun
+git checkout latest  # Check out the commit matching the latest SDK release
+```
+Install the necessary libraries specified in the requirements file:
+```bash
+pip install -e examples/python/live_scrolling_plot
+```
+
+Then, simply execute the main Python script:
+```bash
+python -m live_scrolling_plot
+```

examples/python/live_scrolling_plot/live_scrolling_plot.py

@@ -0,0 +1,87 @@
+#!/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 Iterator
+
+import numpy as np
+import rerun as rr  # pip install rerun-sdk
+import rerun.blueprint as rrb
+
+
+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(0, args.num_plots)]
+    series_paths = [f"series_{i}" for i in range(0, 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_seconds("time", 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.Scalar(next(values[plot_idx][series_idx])))
+
+    rr.script_teardown(args)
+
+
+if __name__ == "__main__":
+    main()

examples/python/live_scrolling_plot/pyproject.toml

@@ -0,0 +1,12 @@
+[project]
+name = "live_scrolling_plot"
+version = "0.1.0"
+readme = "README.md"
+dependencies = ["numpy", "rerun-sdk"]
+
+[project.scripts]
+live_scrolling_plot = "live_scrolling_plot:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"