wehub-resource-sync
70 lines
2.8 KiB
Markdown
70 lines
2.8 KiB
Markdown
<!--[metadata]
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title = "IMU signals"
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tags = ["Plots"]
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description = "Log multi dimensional signals under a single entity."
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thumbnail = "https://static.rerun.io/imu_signals/64f773d238a0456a0f233abeea7e521cfb871b67/480w.jpg"
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thumbnail_dimensions = [480, 480]
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channel = "main"
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include_in_manifest = true
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build_args = ["--seconds=10"]
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-->
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This example demonstrates how to log multi dimensional signals with the Rerun SDK, using the [TUM VI Benchmark](https://cvg.cit.tum.de/data/datasets/visual-inertial-dataset).
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<picture>
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<img src="https://static.rerun.io/imu_signals/1184ab6e2df3275b8b7a574d7f0e42b1aed8343a/full.png" alt="">
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<source media="(max-width: 480px)" srcset="https://static.rerun.io/imu_signals/1184ab6e2df3275b8b7a574d7f0e42b1aed8343a/480w.png">
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<source media="(max-width: 768px)" srcset="https://static.rerun.io/imu_signals/1184ab6e2df3275b8b7a574d7f0e42b1aed8343a/768w.png">
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<source media="(max-width: 1024px)" srcset="https://static.rerun.io/imu_signals/1184ab6e2df3275b8b7a574d7f0e42b1aed8343a/1024w.png">
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<source media="(max-width: 1200px)" srcset="https://static.rerun.io/imu_signals/1184ab6e2df3275b8b7a574d7f0e42b1aed8343a/1200w.png">
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</picture>
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## Background
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This example shows how to log multi-dimensional signals efficiently using the [`rr.send_columns()`](https://ref.rerun.io/docs/python/0.22.1/common/columnar_api/#rerun.send_columns) API.
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The API automatically selects the right partition sizes, making it simple to log scalar signals like this:
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```py
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# Load IMU data from CSV into a dataframe
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imu_data = pd.read_csv(
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cwd / DATASET_NAME / "dso/imu.txt",
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sep=" ",
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header=0,
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names=["timestamp", "gyro.x", "gyro.y", "gyro.z", "accel.x", "accel.y", "accel.z"],
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comment="#",
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)
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times = rr.TimeColumn("timestamp", timestamp=imu_data["timestamp"])
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# Extract gyroscope data (x, y, z axes) and log it to a single entity.
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gyro = imu_data[["gyro.x", "gyro.y", "gyro.z"]]
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rr.send_columns("/gyroscope", indexes=[times], columns=rr.Scalars.columns(scalars=gyro))
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# Extract accelerometer data (x, y, z axes) and log it to a single entity.
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accel = imu_data[["accel.x", "accel.y", "accel.z"]]
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rr.send_columns("/accelerometer", indexes=[times], columns=rr.Scalars.columns(scalars=accel))
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```
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## Running
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Install the example package:
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```bash
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pip install -e examples/python/imu_signals
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```
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To experiment with the provided example, simply execute the main Python script:
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```bash
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python -m imu_signals
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```
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## Attribution
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This example uses a scene from the **TUM VI Benchmark dataset**, originally provided by [Technical University of Munich (TUM)](https://cvg.cit.tum.de/data/datasets/visual-inertial-dataset).
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The dataset is licensed under **Creative Commons Attribution 4.0 (CC BY 4.0)**.
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- Original dataset: [TUM VI Benchmark](https://cvg.cit.tum.de/data/datasets/visual-inertial-dataset)
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- License details: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
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