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Utility and Auxiliary Widgets

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youtube-at-vach edited this page Jul 23, 2026 · 1 revision

Utility and Auxiliary Widgets

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The Utility and Auxiliary widgets in MeasureLab provide essential support functions that extend beyond standard signal analysis. These include tools for signal recording/playback, transmission path verification, system benchmarking, and specialized signal generation.

Recorder / Player

The RecorderPlayer module provides high-performance audio recording and playback with disk-streaming capabilities. It is designed to handle large files without exhausting system memory by utilizing a background writer thread and chunked I/O.

Implementation Details

  • Disk Streaming: Unlike simple buffer-based recorders, this module uses a _writer_thread and a queue.Queue to stream recorded samples to a temporary file on disk src/gui/widgets/recorder_player.py:132-136.
  • Resampling: When loading files with a sample rate different from the AudioEngine, the FileLoadWorker performs polyphase resampling via AudioCalc.resample src/gui/widgets/recorder_player.py:63-66.
  • Safety: The FileLoadWorker validates file sizes before loading to prevent OOM (Out of Memory) errors src/gui/widgets/recorder_player.py:49-53.

Data Flow: Recording

  1. The AudioEngine master callback provides input samples.
  2. RecorderPlayer pushes these samples into the _write_queue.
  3. The background thread pulls from the queue and writes to a soundfile object src/gui/widgets/recorder_player.py:97-109.

Sources: src/gui/widgets/recorder_player.py:39-115, src/gui/widgets/recorder_player.py:116-214

Transmission Analyzer

The Transmission Analyzer is a sophisticated tool for validating digital and analog signal paths using Pseudo-Random Binary Sequences (PRBS). It measures Bit Error Rate (BER), Error Vector Magnitude (EVM), and impulse response.

Core Logic: PRBS and Synchronization

The system uses an LFSR (Linear Feedback Shift Register) to generate standard patterns (PRBS-7 through PRBS-31) src/core/transmission_logic.py:14-58.

Feature Implementation
Initial Sync Sliding Pearson correlation against a reference cycle src/core/transmission_logic.py:146-184.
Jitter Tracking Neighborhood search around the last known offset to track sample slips src/core/transmission_logic.py:187-205.
Digital Mode Bit-by-bit comparison to diagnose bit-perfection and active bit depth src/gui/widgets/transmission_analyzer.py:87-90.
Analog Mode Fractional delay estimation and Equalized EVM to remove linear frequency response errors src/core/transmission_logic.py:240-275.

Entity Mapping: Transmission Logic

graph TD
    subgraph "TransmissionAnalyzer (Module)"
        TA["TransmissionAnalyzer Class"]
        RX["rx_buffer (np.ndarray)"]
        GEN["generator_l/r (PRBSGenerator)"]
    end

    subgraph "Logic Layer (transmission_logic.py)"
        FSD["find_sequence_delay()"]
        TJ["track_jitter()"]
        EIR["extract_impulse_response()"]
        CE["calculate_evm()"]
    end

    TA -->|1. Sync| FSD
    TA -->|2. Track| TJ
    TA -->|3. Deconvolve| EIR
    TA -->|4. Metric| CE
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Sources: src/gui/widgets/transmission_analyzer.py:43-145, src/core/transmission_logic.py:8-205, tests/logic_verification/core/test_transmission.py:26-144

Timecode Monitor (LTC)

The TimecodeMonitor handles Longitudinal Timecode (LTC) encoding and decoding. It supports "Jam Syncing," where the generator can be slaved to an incoming external timecode signal.

  • Encoder: Implements Bi-phase Mark Encoding (BPM). Transitions occur at every bit boundary; a '1' bit adds a transition in the middle src/core/ltc.py:102-157.
  • Decoder: Uses zero-crossing detection and pulse-width discrimination to identify "short" vs "long" pulses, reconstructing the 80-bit LTC frame src/core/ltc.py:160-214.
  • Precision: The encoder uses a global sample accumulator (samples_generated) to prevent drift over long durations src/core/ltc.py:21-23.

Sources: src/gui/widgets/timecode_monitor.py:99-210, src/core/ltc.py:10-157

Sound Quality Analyzer

This module performs offline psychoacoustic analysis based on human hearing models. It calculates metrics that correlate with subjective perception rather than just physical SPL.

Key Metrics

  • Sharpness: Measures high-frequency content in acum units src/gui/widgets/sound_quality_analyzer.py:120-129.
  • Roughness: Analyzes modulation in the 70Hz range to quantify "grating" sounds in asper src/gui/widgets/sound_quality_analyzer.py:131-139.
  • Tonality: Identifies pure tones against a noise floor src/gui/widgets/sound_quality_analyzer.py:141-149.
  • Articulation Index: Estimates speech intelligibility src/gui/widgets/sound_quality_analyzer.py:162-170.

The analysis is performed by AnalysisWorker (a QThread), which resamples audio to a fixed 48kHz internal rate optimized for the psychoacoustic filters src/gui/widgets/sound_quality_analyzer.py:80-88.

Sources: src/gui/widgets/sound_quality_analyzer.py:37-180, docs/widgets/sound_quality_analyzer.md:15-20

Processor Benchmark

The ProcessorBenchmark evaluates the host system's capability to handle real-time DSP at various FFT sizes and sample rates.

  • FFT Performance: Measures the execution time of fft_manager.forward() across sizes from 4096 to 16M samples src/gui/widgets/processor_benchmark.py:195-200.
  • UI Rendering: Benchmarks pyqtgraph update speeds to ensure the display does not lag the audio processing src/gui/widgets/processor_benchmark.py:73-78.
  • Safety Factor: Calculates the maximum sustainable FPS by comparing processing time against the hardware buffer duration src/gui/widgets/processor_benchmark.py:126-132.

Sources: src/gui/widgets/processor_benchmark.py:68-202

Plot Comparer

The PlotComparer serves as a centralized hub for overlaying data from different modules (e.g., comparing a Spectrum Analyzer trace with a Network Analyzer sweep).

Data Integration

It interacts with the ComparisonManager singleton to retrieve ComparisonTrace objects src/gui/widgets/plot_comparer.py:61-62.

graph LR
    subgraph "Modules"
        SA["SpectrumAnalyzer"]
        NA["NetworkAnalyzer"]
    end
    
    subgraph "Data Storage"
        CM["ComparisonManager"]
        CT["ComparisonTrace"]
    end
    
    subgraph "UI"
        PCW["PlotComparerWidget"]
        TW["QTreeWidget (Trace List)"]
    end

    SA -->|get_comparable_data| CM
    NA -->|get_comparable_data| CM
    CM -->|signal: trace_added| PCW
    PCW -->|Populate| TW
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Advanced Plotting Features

  • Dual Y-Axis: Supports simultaneous display of different units (e.g., dB for Magnitude and Degrees for Phase) using a secondary ViewBox src/gui/widgets/plot_comparer.py:174-180.
  • Trace Normalization: Allows applying offset_db or time-shifts to individual traces for alignment src/gui/widgets/plot_comparer.py:66-68.
  • Interactive Readout: A Dash-style cursor provides precise X/Y values for all visible traces src/gui/widgets/plot_comparer.py:185-191.

Sources: src/gui/widgets/plot_comparer.py:59-200, tests/logic_verification/gui/test_plot_comparer.py:35-142

Loopback Finder

A diagnostic utility that detects physical or virtual routing paths between output and input channels.

  • Method: Sequentially outputs a 440Hz test tone on each output channel while monitoring all input channels src/gui/widgets/loopback_finder.py:131-135.
  • Detection: Uses FFT to look for the specific target_bin corresponding to the test frequency src/gui/widgets/loopback_finder.py:146-148.
  • Concurrency: The scan runs in a LoopbackWorker thread to keep the UI responsive during the hardware polling process src/gui/widgets/loopback_finder.py:26-58.

Sources: src/gui/widgets/loopback_finder.py:66-155

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