Skip to content
Back to skills

Magnetometer Calibration

ASecurity

Sensor calibration toolkit with magnetometer calibration using close-form method. Use when calibrating IMU sensors (accelerometer, gyroscope, magnetometer) to compute soft-iron matrix and hard-iron offset for magnetometer correction. Requires sensor fusion with VQF for orientation estimation.

  • 8 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added February 10, 2026
developmentpython

Security analysis

A100/100

Scanned February 12, 2026

npx -y skills add wangyendt/wayne-skills --skill magnetometer-calibration --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Magnetometer Calibration?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Magnetometer Calibration
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/wangyendt-magnetometer-calibration/badge)](https://www.skillsdirectory.com/skills/wangyendt-magnetometer-calibration)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: pywayne-calibration-magnetometer-calibration
description: Sensor calibration toolkit with magnetometer calibration using close-form method. Use when calibrating IMU sensors (accelerometer, gyroscope, magnetometer) to compute soft-iron matrix and hard-iron offset for magnetometer correction. Requires sensor fusion with VQF for orientation estimation.
---

# Pywayne Calibration

`pywayne.calibration.MagnetometerCalibrator` provides magnetometer calibration using sensor data (accelerometer, gyroscope, magnetometer).

## Quick Start

```python
from pywayne.calibration import MagnetometerCalibrator
import numpy as np

# Sensor data: ts (N,), acc (N,3), gyro (N,3), mag (N,3)
calibrator = MagnetometerCalibrator(method='close_form')
Sm, h = calibrator.process(ts, acc, gyro, mag)

# Sm: Soft-iron matrix (3x3)
# h: Hard-iron offset vector (3,)
```

## Input Data Format

Sensor data must be numpy arrays with matching sample counts:

```python
ts   # (N,)     - Timestamps (seconds)
acc  # (N, 3)   - Accelerometer [ax, ay, az]
gyro # (N, 3)   - Gyroscope [gx, gy, gz]
mag  # (N, 3)   - Magnetometer [mx, my, mz]
```

**Data requirements:**
- Sensor data should cover various orientations for effective calibration
- Minimum data points required (exact number depends on calibration stability)
- Arrays must be C-contiguous (auto-converted internally)

## Calibration Parameters

`process()` returns:

| Parameter | Shape | Description |
|-----------|--------|-------------|
| `Sm` | (3, 3) | Soft-iron matrix |
| `h` | (3,) | Hard-iron offset vector |

## Usage in Application

Apply calibration to raw magnetometer readings:

```python
# Calibrated reading
m_calibrated = Sm @ (m_raw - h)
```

## Temporal Calibration

Temporal calibration module exists but is reserved for future expansion. Currently no functionality is implemented.

## Important Notes

- **Dependencies**: Requires `vqf` (VQF quaternion filter) and `qmt` (quaternion math) modules
- **Method**: Currently only supports `close_form` method
- **Orientation**: Uses VQF for sensor fusion and orientation estimation during calibration
- **Output**: Prints calibration parameters during processing

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.