Send from C++

In this section we'll log and visualize our first non-trivial dataset, putting many of Rerun's core concepts and features to use.

In a few lines of code, we'll go from a blank sheet to something you don't see every day: an animated, interactive, DNA-shaped abacus:

This guide aims to go wide instead of deep. There are links to other doc pages where you can learn more about specific topics.

At any time, you can checkout the complete code listing for this tutorial here to better keep track of the overall picture. To build the example from the repository, run:

cd examples/cpp/dna
cmake -B build
cmake --build build -j

And then to run it on Linux/Mac:

./build/example_dna

and Windows respectively:

build\Debug\example_dna.exe

Prerequisites prerequisites

You should have already installed the viewer.

We assume you have a working C++ toolchain and are using CMake to build your project. For this example we will let Rerun download build Apache Arrow's C++ library itself. To learn more about how Rerun's CMake script can be configured, see CMake Setup in Detail in the C++ reference documentation.

Setting up your CMakeLists.txt setting-up-your-cmakeliststxt

A minimal CMakeLists.txt for this example looks like this:

cmake_minimum_required(VERSION 3.16...3.27)
project(example_dna LANGUAGES CXX)

add_executable(example_dna main.cpp)

# Download the rerun_sdk
include(FetchContent)
FetchContent_Declare(rerun_sdk URL
    https://github.com/rerun-io/rerun/releases/latest/download/rerun_cpp_sdk.zip)
FetchContent_MakeAvailable(rerun_sdk)

# Rerun requires at least C++17, but it should be compatible with newer versions.
set_property(TARGET example_dna PROPERTY CXX_STANDARD 17)

# Link against rerun_sdk.
target_link_libraries(example_dna PRIVATE rerun_sdk)

Includes includes

To use Rerun all you need to include is rerun.hpp, however for this example we will pull in a few extra headers.

Starting our main.cpp:

#include <rerun.hpp>
#include <rerun/demo_utils.hpp>

#include <algorithm> // std::generate
#include <random>
#include <vector>

using namespace rerun::demo;
using namespace std::chrono_literals;

static constexpr size_t NUM_POINTS = 100;

Initializing the SDK initializing-the-sdk

To get going we want to create a RecordingStream, which is the main interface for sending data to Rerun. When creating the RecordingStream we also need to specify the name of the application we're working on by setting it's ApplicationId.

We then use the stream to spawn a new Rerun Viewer via spawn.

Add our initial main to main.cpp:

int main() {
    auto rec = rerun::RecordingStream("rerun_example_dna_abacus");
    rec.spawn().exit_on_failure();
}

Among other things, a stable ApplicationId will make it so the Rerun Viewer retains its UI state across runs for this specific dataset, which will make our lives much easier as we iterate.

Check out the reference to learn more about how Rerun deals with applications and recordings.

Testing our app testing-our-app

Even though we haven't logged any data yet this is a good time to verify everything is working.

cmake -B build
cmake --build build -j
./build/example_dna

When everything finishes compiling, an empty Rerun Viewer should be spawned:

Logging our first points logging-our-first-points

Now let's add some data to the viewer.

The core structure of our DNA looking shape can easily be described using two point clouds shaped like spirals. Add the following to your main function:

std::vector<rerun::Position3D> points1, points2;
std::vector<rerun::Color> colors1, colors2;
color_spiral(NUM_POINTS, 2.0f, 0.02f, 0.0f, 0.1f, points1, colors1);
color_spiral(NUM_POINTS, 2.0f, 0.02f, TAU * 0.5f, 0.1f, points2, colors2);

rec.log(
    "dna/structure/left",
    rerun::Points3D(points1).with_colors(colors1).with_radii({0.08f})
);
rec.log(
    "dna/structure/right",
    rerun::Points3D(points2).with_colors(colors2).with_radii({0.08f})
);

Re-compile and run your program again:

cmake --build build -j
./build/example_dna

and now you should now see this scene in the viewer:

This is a good time to make yourself familiar with the viewer: try interacting with the scene and exploring the different menus. Checkout the Viewer Walkthrough and viewer reference for a complete tour of the viewer's capabilities.

Under the hood under-the-hood

This tiny snippet of code actually holds much more than meets the eye…

Archetypes archetypes

The easiest way to log geometric primitives is the use the RecordingStream::log method with one of the built-in archetype class, such as Points3D. Archetypes take care of building batches of components that are recognized and correctly displayed by the Rerun viewer.

Components components

Under the hood, the Rerun C++ SDK logs individual components like positions, colors, and radii. Archetypes are just one high-level, convenient way of building such collections of components. For advanced use cases, it's possible to add custom components to archetypes, or even log entirely custom sets of components, bypassing archetypes altogether. For more information on how the Rerun data model works, refer to our section on Entities and Components.

Notably, the RecordingStream::log method will handle any data type that implements the AsComponents<T> trait, making it easy to add your own data. For more information on how to supply your own components see Use custom data.

Entities & hierarchies entities--hierarchies

Note the two strings we're passing in: "dna/structure/left" and "dna/structure/right".

These are entity paths, which uniquely identify each entity in our scene. Every entity is made up of a path and one or more components. Entity paths typically form a hierarchy which plays an important role in how data is visualized and transformed (as we shall soon see).

Batches batches

One final observation: notice how we're logging a whole batch of points and colors all at once here. Batches of data are first-class citizens in Rerun and come with all sorts of performance benefits and dedicated features. You're looking at one of these dedicated features right now in fact: notice how we're only logging a single radius for all these points, yet somehow it applies to all of them. We call this clamping.

A lot is happening in these two simple function calls. Good news is: once you've digested all of the above, logging any other entity will simply be more of the same. In fact, let's go ahead and log everything else in the scene now.

Adding the missing pieces adding-the-missing-pieces

We can represent the scaffolding using a batch of 3D line segments:

std::vector<rerun::LineStrip3D> lines;
for (size_t i = 0; i < points1.size(); ++i) {
    lines.emplace_back(rerun::LineStrip3D({points1[i].xyz, points2[i].xyz}));
}

rec.log(
    "dna/structure/scaffolding",
    rerun::LineStrips3D(lines).with_colors(rerun::Color(128, 128, 128))
);

Which only leaves the beads:

std::default_random_engine gen;
std::uniform_real_distribution<float> dist(0.0f, 1.0f);
std::vector<float> offsets(NUM_POINTS);
std::generate(offsets.begin(), offsets.end(), [&] { return dist(gen); });

std::vector<rerun::Position3D> beads_positions(lines.size());
std::vector<rerun::Color> beads_colors(lines.size());

for (size_t i = 0; i < lines.size(); ++i) {
    float offset = offsets[i];
    auto c = static_cast<uint8_t>(bounce_lerp(80.0f, 230.0f, offset * 2.0f));

    beads_positions[i] = rerun::Position3D(
        bounce_lerp(lines[i].points[0].x(), lines[i].points[1].x(), offset),
        bounce_lerp(lines[i].points[0].y(), lines[i].points[1].y(), offset),
        bounce_lerp(lines[i].points[0].z(), lines[i].points[1].z(), offset)
    );
    beads_colors[i] = rerun::Color(c, c, c);
}

rec.log(
    "dna/structure/scaffolding/beads",
    rerun::Points3D(beads_positions).with_colors(beads_colors).with_radii({0.06f})
);

Once again, although we are getting fancier and fancier with our iterator mappings, there is nothing new here: it's all about populating archetypes and feeding them to the Rerun API.

Animating the beads animating-the-beads

Introducing time introducing-time

Up until this point, we've completely set aside one of the core concepts of Rerun: Time and Timelines.

Even so, if you look at your Timeline View right now, you'll notice that Rerun has kept track of time on your behalf anyway by memorizing when each log call occurred.

Unfortunately, the logging time isn't particularly helpful to us in this case: we can't have our beads animate depending on the logging time, else they would move at different speeds depending on the performance of the logging process! For that, we need to introduce our own custom timeline that uses a deterministic clock which we control.

Rerun has rich support for time: whether you want concurrent or disjoint timelines, out-of-order insertions or even data that lives outside the timeline(s). You will find a lot of flexibility in there.

Let's add our custom timeline.

Replace the section that logs the beads with a loop that logs the beads at different timestamps:

for (int t = 0; t < 400; t++) {
    auto time = std::chrono::duration<float>(t) * 0.01f;

    rec.set_time("stable_time");

    for (size_t i = 0; i < lines.size(); ++i) {
        float time_offset = time.count() + offsets[i];
        auto c = static_cast<uint8_t>(bounce_lerp(80.0f, 230.0f, time_offset * 2.0f));

        beads_positions[i] = rerun::Position3D(
            bounce_lerp(lines[i].points[0].x(), lines[i].points[1].x(), time_offset),
            bounce_lerp(lines[i].points[0].y(), lines[i].points[1].y(), time_offset),
            bounce_lerp(lines[i].points[0].z(), lines[i].points[1].z(), time_offset)
        );
        beads_colors[i] = rerun::Color(c, c, c);
    }

    rec.log(
        "dna/structure/scaffolding/beads",
        rerun::Points3D(beads_positions).with_colors(beads_colors).with_radii({0.06f})
    );
}

First we use RecordingStream::set_time_seconds to declare our own custom Timeline and set the current timestamp. You can add as many timelines and timestamps as you want when logging data.

⚠️ If you run this code as is, the result will be.. surprising: the beads are animating as expected, but everything we've logged until that point is gone! ⚠️

Enter…

Latest-at semantics latestat-semantics

That's because the Rerun Viewer has switched to displaying your custom timeline by default, but the original data was only logged to the default timeline (called log_time). To fix this, go back to the top of your main and initialize your timeline before logging the initial structure:

rec.set_time_seconds("stable_time", 0.0f);

rec.log(
    "dna/structure/left",
    rerun::Points3D(points1).with_colors(colors1).with_radii({0.08f})
);
rec.log(
    "dna/structure/right",
    rerun::Points3D(points2).with_colors(colors2).with_radii({0.08f})
);

This fix actually introduces yet another very important concept in Rerun: "latest-at" semantics. Notice how entities "dna/structure/left" & "dna/structure/right" have only ever been logged at time zero, and yet they are still visible when querying times far beyond that point.

Rerun always reasons in terms of "latest" data: for a given entity, it retrieves all of its most recent components at a given time.

Transforming space transforming-space

There's only one thing left: our original scene had the abacus rotate along its principal axis.

As was the case with time, (hierarchical) space transformations are first class-citizens in Rerun. Now it's just a matter of combining the two: we need to log the transform of the scaffolding at each timestamp.

Either expand the previous loop to include logging transforms or simply add a second loop like this:

for (int t = 0; t < 400; t++) {
    float time = static_cast<float>(t) * 0.01f;

    rec.log(
        "dna/structure",
        rerun::archetypes::Transform3D(rerun::RotationAxisAngle(
            {0.0f, 0.0f, 1.0f},
            rerun::Angle::radians(time.count() / 4.0f * TAU)
        ))
    );
}

Voila!

Other ways of logging & visualizing data other-ways-of-logging--visualizing-data

Saving & loading to/from RRD files saving--loading-tofrom-rrd-files

Sometimes, sending the data over the network is not an option. Maybe you'd like to share the data, attach it to a bug report, etc.

Rerun has you covered:

• Use RecordingStream::save to stream all logging data to disk.
• Visualize it via rerun path/to/recording.rrd

You can also save a recording (or a portion of it) as you're visualizing it, directly from the viewer.

⚠️ RRD files are not yet stable across different versions! ⚠️

Closing closing

This closes our whirlwind tour of Rerun. We've barely scratched the surface of what's possible, but this should have hopefully given you plenty pointers to start experimenting.

As a next step, browse through our example gallery for some more realistic example use-cases, or browse the Types section for more simple examples of how to use the main data types.