b1500_powermeter_rollover

Synchronized Keysight B1500 + Thorlabs power-meter IV sweep with four-algorithm rollover detection.

© Veronica Gao Zhan – May 2026

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Features

Feature	Detail
IV sweep	Point-by-point sourcing via B1500 SMU (IV or VI mode)
Optical power	Real-time Thorlabs PM100D / PM400 readout per point
Rollover detection	4 algorithms: CUSUM (default), EWMA, Rolling Average, Regression (sklearn)
GUI	PyQt5 scrollable control panel + live 2×2 matplotlib canvas
CLI	Full headless operation with argparse
CSV export	Timestamped file per sweep with rollover summary header

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Package Structure

b1500_powermeter_rollover/
├── __init__.py            ← public API re-exports
├── __main__.py            ← python -m b1500_powermeter_rollover
├── config.py              ← SweepConfig, MeasurementPoint, RolloverResult
├── b1500_controller.py    ← thread-safe VISA driver for Keysight B1500
├── powermeter_controller.py ← thread-safe VISA driver for Thorlabs PM100D/PM400
├── rollover_detector.py   ← instrument-agnostic online rollover detector
├── engine.py              ← SynchronizedMeasurementEngine (no GUI dependency)
├── cli.py                 ← build_parser() + run_cli()
├── gui/
│   ├── __init__.py
│   ├── worker.py          ← MeasurementWorker (QThread)
│   └── main_window.py     ← SynchronizedMeasurementGUI (QMainWindow)
├── requirements.txt
└── pyproject.toml

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Installation

# From the B1500/ folder (editable install)
pip install -e ".[all]"

# Or install only the core (no GUI, no ML)
pip install -e .

# Or manually
pip install pyvisa pyvisa-py pyusb numpy PyQt5 matplotlib scikit-learn

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Quick Start

GUI (interactive)

python -m b1500_powermeter_rollover

CLI (headless / automated)

# List connected instruments
python -m b1500_powermeter_rollover --list

# Run an IV sweep with CUSUM rollover detection
python -m b1500_powermeter_rollover \
    --b1500 GPIB0::17::INSTR \
    --pm    USB0::0x1313::0x8078::INSTR \
    --start 0 --stop 2.5 --steps 26 \
    --compliance 0.5 --dwell 0.1 \
    --rollover --method cusum --threshold 90 \
    --output ./results --name MyLaser

Python API

from b1500_powermeter_rollover import (
    SweepConfig,
    B1500Controller,
    ThorlabsPowerMeterController,
    SynchronizedMeasurementEngine,
)

b  = B1500Controller()
pm = ThorlabsPowerMeterController()
b.connect("GPIB0::17::INSTR")
pm.connect("USB0::0x1313::0x8078::INSTR")

cfg = SweepConfig(
    mode="iv", start=0, stop=2.5, steps=26,
    enable_rollover=True, rollover_method="cusum",
)
eng = SynchronizedMeasurementEngine(b, pm, cfg)
eng.on_log = print
data = eng.run()

r = eng.rollover_result
print(f"Peak power {r.peak_power:.4e} W at {r.peak_voltage:.4f} V")

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License

MIT License

Copyright (c) 2026 Veronica Gao Zhan

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Standalone rollover detector (no instruments)

from b1500_powermeter_rollover import SweepConfig, RolloverDetector

cfg = SweepConfig(rollover_method="cusum", rollover_threshold=0.90)
det = RolloverDetector(cfg)

peak = 0.0
for power in my_power_readings:
    peak = max(peak, power)
    triggered, info = det.update(power, peak)
    if triggered:
        print("Rollover detected!", info)
        break

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Detection Algorithms

Method	Latency	Notes
cusum (default)	1–3 pts	Lower-sided CUSUM (Page 1954). Scale-invariant. O(1)/sample
ewma	~window/2	Exponential moving average. Tunable with --alpha
rolling_avg	window pts	Classic windowed mean. Robust to impulse noise
regression	window pts	sklearn LinearRegression (batch) + SGDRegressor (online)

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Acknowledgements

This project was developed using vibe coding — an AI-assisted development workflow powered by GitHub Copilot. The architecture, code structure, and implementation were generated through iterative natural-language prompting and human review.