# Send Pywayne Plot to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "plot", "name": "Pywayne Plot", "source": "tencent", "type": "skill", "category": "AI 智能", "sourceUrl": "https://clawhub.ai/wangyendt/plot", "canonicalUrl": "https://clawhub.ai/wangyendt/plot", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/plot", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=plot", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "SKILL.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T16:55:25.780Z", "expiresAt": "2026-05-07T16:55:25.780Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null }, "scope": "source", "summary": "Source download looks usable.", "detail": "Yavira can redirect you to the upstream package for this source.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/plot" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/plot", "downloadUrl": "https://openagent3.xyz/downloads/plot", "agentUrl": "https://openagent3.xyz/skills/plot/agent", "manifestUrl": "https://openagent3.xyz/skills/plot/agent.json", "briefUrl": "https://openagent3.xyz/skills/plot/agent.md" } } ``` ## Documentation ### Pywayne Plot Enhanced spectrogram visualization tools for professional time-frequency analysis. ### Quick Start import matplotlib.pyplot as plt from pywayne.plot import regist_projection, parula_map import numpy as np # Register custom projection regist_projection() # Create spectrogram fig, ax = plt.subplots(subplot_kw={'projection': 'z_norm'}) spec, freqs, t, im = ax.specgram( x=signal_data, Fs=100, NFFT=128, noverlap=96, cmap=parula_map, scale='dB' ) ax.set_ylabel('Frequency (Hz)') plt.colorbar(im, label='Magnitude (dB)') plt.show() ### regist_projection Register the custom SpecgramAxes projection. Must be called before using the enhanced specgram functionality. from pywayne.plot import regist_projection regist_projection() ### SpecgramAxes.specgram Enhanced spectrogram with advanced features. Key Parameters: ParameterDescriptionDefaultNFFTFFT window length (points)256FsSampling frequency (Hz)2noverlapOverlap points between windows128cmapColormap (use parula_map)-mode'psd', 'magnitude', 'angle', 'phase''psd'scale'dB' or 'linear''dB'normalize'global', 'local', 'none''global'freq_scaleFrequency scaling factor1.0FcCenter frequency offset (Hz)0 Returns: spec - 2D spectrogram array (n_freqs, n_times) freqs - Frequency axis array t - Time axis array im - matplotlib image object (for colorbar) ### get_specgram_params Auto-recommend STFT parameters based on signal characteristics. from pywayne.plot import get_specgram_params params = get_specgram_params( signal_length=10000, sampling_rate=100, time_resolution=0.1 # or freq_resolution=0.5 ) # Returns: NFFT, noverlap, actual_freq_res, actual_time_res, n_segments ### parula_map MATLAB-style perceptually uniform colormap for scientific visualization. from pywayne.plot import parula_map plt.imshow(data, cmap=parula_map) ### IMU Signal Analysis fs = 100 # Sampling rate win_time, step_time = 1, 0.1 fig, ax = plt.subplots(subplot_kw={'projection': 'z_norm'}) spec, freqs, t, im = ax.specgram( x=acc_data, Fs=fs, NFFT=int(win_time * fs), noverlap=int((win_time - step_time) * fs), scale='dB', cmap=parula_map ) ax.set_ylabel('Frequency (Hz)') ax.set_ylim(0, 30) ### Physiological Signals (PPG - Heart Rate) # Convert Hz to bpm for heart rate visualization fig, ax = plt.subplots(subplot_kw={'projection': 'z_norm'}) spec, freqs, t, im = ax.specgram( x=ppg_signal, Fs=100, NFFT=400, noverlap=300, freq_scale=60, # Hz -> bpm scale='dB' ) ax.set_ylabel('Heart Rate (bpm)') ax.set_ylim(40, 180) ### Vibration Analysis with Global Normalization fig, ax = plt.subplots(subplot_kw={'projection': 'z_norm'}) spec, freqs, t, im = ax.specgram( x=vibration_data, Fs=1000, NFFT=1024, noverlap=512, scale='linear', normalize='global' ) plt.colorbar(im, label='Normalized Magnitude') ### High-Resolution Analysis with Zero-Padding fig, ax = plt.subplots(subplot_kw={'projection': 'z_norm'}) spec, freqs, t, im = ax.specgram( x=signal, Fs=100, NFFT=100, pad_to=512, # Zero-pad for smoother spectrum noverlap=80, scale='dB' ) ### Scale Modes ModeDescriptionUse CasedBLogarithmic (10log10 for PSD, 20log10 for magnitude)Large dynamic range signalslinearLinear amplitudeDirect amplitude comparison ### Normalization Modes (only for scale='linear') ModeDescriptionUse CaseglobalZ/max(Z), preserves relative intensityCompare intensity across timelocalPer-column normalization to [0,1]Focus on frequency content over timenoneNo normalizationRaw spectrogram values ### Frequency Scaling freq_scaleUnitUse Case1.0HzDefault, most signals60bpmHeart rate, respiration rate0.001kHzAudio signals Example: freq_scale=60 converts 2 Hz → 120 bpm ### Resolution Guidelines Frequency resolution: Δf = Fs / NFFT Time resolution: Δt = (NFFT - noverlap) / Fs Trade-off: Cannot simultaneously achieve high frequency and time resolution Use get_specgram_params() to auto-calculate optimal parameters. ### Interactive Analysis spec, freqs, t, im = ax.specgram(...) def on_click(event): if event.xdata and event.inaxes == ax: time_idx = np.argmin(np.abs(t - event.xdata)) plt.figure() plt.plot(freqs, spec[:, time_idx]) plt.title(f'FFT at t={event.xdata:.2f}s') plt.show() fig.canvas.mpl_connect('button_press_event', on_click) ### Application Areas IMU data: Accelerometer and gyroscope analysis Physiological signals: PPG (heart rate), ECG, respiration Vibration analysis: Machinery fault diagnosis Audio processing: Speech and audio spectrum analysis ### Notes Always call regist_projection() before using projection='z_norm' parula_map is recommended for best perceptual uniformity dB mode automatically handles log(0) issues For better FFT efficiency, set NFFT to power of 2 ## Trust - Source: tencent - Verification: Indexed source record - Publisher: wangyendt - Version: 0.1.0 ## Source health - Status: healthy - Source download looks usable. - Yavira can redirect you to the upstream package for this source. - Health scope: source - Reason: direct_download_ok - Checked at: 2026-04-30T16:55:25.780Z - Expires at: 2026-05-07T16:55:25.780Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/plot) - [Send to Agent page](https://openagent3.xyz/skills/plot/agent) - [JSON manifest](https://openagent3.xyz/skills/plot/agent.json) - [Markdown brief](https://openagent3.xyz/skills/plot/agent.md) - [Download page](https://openagent3.xyz/downloads/plot)