liquidinstruments/moku-examples
Apr 2025 – Oct 2025
3 Months active
Languages Used
PythonJupyter Notebook
Technical Skills
Data AnalysisEmbedded SystemsPython ProgrammingSignal ProcessingFilter DesignFrequency Response Analysis
dylan-perez
PROFILE
Dylan-perez
Dylan developed three end-to-end measurement and analysis workflows for the liquidinstruments/moku-examples repository, focusing on embedded systems and signal processing challenges. He built a Python-based Dual Frequency Resonance Tracker example to automate FIR filter center frequency tracking, enabling reproducible validation and streamlined prototyping. Dylan also delivered multi-instrument examples for configuring FIR Filter Box instruments and running concurrent Frequency Response Analysis, using Python and Jupyter Notebook to demonstrate practical filter design and performance evaluation. Additionally, he implemented an oscilloscope waveform averaging demo, showcasing real-time data acquisition and visualization. His work provided practical, user-facing scripts that improved onboarding and experimental reproducibility.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
3
Lines of code
1,143
Activity Months3
Your Network
23 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered an end-to-end Oscilloscope Waveform Averaging Demo in liquidinstruments/moku-examples, showcasing an automated Python workflow for configuring the oscilloscope, acquiring data, and computing/displaying a rolling average in real-time. The feature provides a practical blueprint for users to implement signal averaging and enhances the Moku platform’s data-analysis capabilities.
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered an end-to-end Oscilloscope Waveform Averaging Demo in liquidinstruments/moku-examples, showcasing an automated Python workflow for configuring the oscilloscope, acquiring data, and computing/displaying a rolling average in real-time. The feature provides a practical blueprint for users to implement signal averaging and enhances the Moku platform’s data-analysis capabilities.
October 2025
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for liquidinstruments/moku-examples: Delivered FIR Filter Box Instrument Usage and FRA Analysis Examples with multi-instrument support. Added end-to-end examples for configuring the FIR Filter Box instrument on Moku devices, including setup of filter shapes (lowpass, highpass, bandpass, bandstop) and configuring the Frequency Response Analyzer to analyze performance. Implemented a multi-instrument workflow to run FIR filtering and FRA concurrently, enabling streamlined experiments and performance evaluation. This work is anchored by the commit: 2ec2a3d086b18cd8dfd384e8507396bc396a616c.
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for liquidinstruments/moku-examples: Delivered FIR Filter Box Instrument Usage and FRA Analysis Examples with multi-instrument support. Added end-to-end examples for configuring the FIR Filter Box instrument on Moku devices, including setup of filter shapes (lowpass, highpass, bandpass, bandstop) and configuring the Frequency Response Analyzer to analyze performance. Implemented a multi-instrument workflow to run FIR filtering and FRA concurrently, enabling streamlined experiments and performance evaluation. This work is anchored by the commit: 2ec2a3d086b18cd8dfd384e8507396bc396a616c.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary focused on delivering a Python-based DFRT (Dual Frequency Resonance Tracker) example for automating FIR center frequency tracking in the liquidinstruments/moku-examples repository. The work enabled end-to-end measurement workflows, including setup, data logging, plotting, and error calculation to validate DFRT accuracy. This contributes to faster prototyping, improved validation, and a reusable reference for customers and contributors.
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary focused on delivering a Python-based DFRT (Dual Frequency Resonance Tracker) example for automating FIR center frequency tracking in the liquidinstruments/moku-examples repository. The work enabled end-to-end measurement workflows, including setup, data logging, plotting, and error calculation to validate DFRT accuracy. This contributes to faster prototyping, improved validation, and a reusable reference for customers and contributors.
April 2025
Activity
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture80.0%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data AcquisitionData AnalysisData VisualizationEmbedded SystemsFilter DesignFrequency Response AnalysisPython APIPython API IntegrationPython ProgrammingSignal Processing
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