IMU signals

Python source

This example demonstrates how to log multi dimensional signals with the Rerun SDK, using the TUM VI Benchmark.

Background background

This example shows how to log multi-dimensional signals efficiently using the rr.send_columns() API.

The API automatically selects the right partition sizes, making it simple to log scalar signals like this:

# Load IMU data from CSV into a dataframe
imu_data = pd.read_csv(
    cwd / DATASET_NAME / "dso/imu.txt",
    sep=" ",
    header=0,
    names=["timestamp", "gyro.x", "gyro.y", "gyro.z", "accel.x", "accel.y", "accel.z"],
    comment="#",
)

times = rr.IndexColumn("timestamp", datetime=imu_data["timestamp"])

# Extract gyroscope data (x, y, z axes) and log it to a single entity.
gyro = imu_data[["gyro.x", "gyro.y", "gyro.z"]]
rr.send_columns("/gyroscope", indexes=[times], columns=rr.Scalar.columns(scalar=gyro))

# Extract accelerometer data (x, y, z axes) and log it to a single entity.
accel = imu_data[["accel.x", "accel.y", "accel.z"]]
rr.send_columns("/accelerometer", indexes=[times], columns=rr.Scalar.columns(scalar=accel))

Running running

Install the example package:

pip install -e examples/python/imu_signals

To experiment with the provided example, simply execute the main Python script:

python -m imu_signals