A professional-grade visualization toolkit for high-precision time-frequency analysis and enhanced spectrogram generation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install plot
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install plot using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Pywayne Plot?
Pywayne Plot is a specialized technical visualization extension designed for researchers and developers working with complex signal data. By integrating seamlessly with matplotlib, it introduces advanced projections and the highly-coveted parula colormap to ensure scientific accuracy in data representation. As a core utility within Openclaw Skills, it bridges the gap between raw signal processing and actionable visual insights, providing robust handling for logarithmic scales and automated frequency unit conversions.
This skill is particularly valuable for those needing to visualize multi-modal data, ranging from low-frequency physiological signals to high-frequency audio or vibration data. It simplifies the often-complex task of setting up Short-Time Fourier Transforms (STFT) by providing intelligent defaults and helper functions that optimize the trade-off between time and frequency resolution.
Pywayne Plot Use Cases
- Analyzing IMU data from accelerometers and gyroscopes for motion tracking and gait analysis.
- Visualizing physiological signals like heart rate (PPG) and respiration by scaling frequencies directly to bpm.
- Detecting machinery faults through vibration analysis using global normalization to preserve relative intensity.
- High-resolution audio spectrum analysis with zero-padding for smoother visualizations.
- Interactive signal debugging where users can extract instantaneous FFT slices from a spectrogram.
How Pywayne Plot Works
- Register the custom SpecgramAxes projection to enable enhanced matplotlib functionality.
- Utilize get_specgram_params to calculate the optimal window length (NFFT) and overlap based on your specific signal length and sampling rate.
- Pass the raw time-series signal into the enhanced specgram function, specifying the desired normalization and scaling modes.
- Apply frequency scaling factors to automatically convert axis units into human-readable formats like bpm or kHz.
- Render the result using the perceptually uniform parula_map for clear identification of spectral peaks and patterns.
Pywayne Plot Setup
To integrate this tool into your Openclaw Skills workflow, ensure you have the necessary library installed and register the projection at the start of your script:
pip install pywayne
from pywayne.plot import regist_projection
import matplotlib.pyplot as plt
# Essential: Register the projection before creating subplots
regist_projection()
Pywayne Plot Data Schema & Taxonomy
The skill manages signal transformations and produces structured visualization objects. The following table describes the primary data outputs from the enhanced spectrogram tool:
| Output Component | Description | Format |
|---|---|---|
| spec | 2D magnitude or PSD array | NumPy Array (n_freqs, n_times) |
| freqs | Computed frequency axis values | NumPy Array |
| t | Computed time axis values | NumPy Array |
| im | Image object for colorbar and display | Matplotlib AxesImage |
It accepts configuration parameters such as NFFT (window length), Fs (sampling frequency), and freq_scale (scaling factor for units).
Pywayne Plot Advanced Features
- Perceptually uniform parula colormap for accurate visualization that mimics professional scientific software like MATLAB.
- Automated STFT parameter recommendation to help users find the perfect balance between time and frequency resolution.
- Multiple normalization modes including 'global' for intensity preservation and 'local' for frequency content focus.
- Built-in frequency unit scaling for seamless conversion between Hz, bpm, and kHz.
- Support for custom projections (z_norm) that simplify the creation of standardized, high-quality spectral plots within Openclaw Skills.
SKILL.md
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