Signal Viewer

Find what went wrong. Prove what is right. Send the answer.
Offline analysis of flight logs, test runs, simulations and parameter sweeps – on your own machine.

⬇ Download for Windows  ·  pip install signalviewer  ·  Documentation  ·  מדריך בעברית

CSV · Parquet · MATLAB .mat · ArduPilot .bin · MAVLink .tlog · PX4 .ulg · ROS 2 .mcap · HDF5 · CAN + .dbc · your own format

Try it in one minute

Install, start it, and pick a card on the welcome screen. Every part of the app has a demo with a known answer – nothing to prepare, nothing leaves your PC.

Card on the welcome screen	What you will see
A drone flight	The flight on the map and in 3D over real terrain, played back in time with its attitude
An ArduPilot flight log	A real .bin log with its automatic health check: vibration, GPS, battery, EKF, motors
The same mission flown twice · Three car runs	Every shared signal ranked by how different it is
A simulation against its flight	The model beside the real flight, aligned in time, judged within a tolerance
Find out what went wrong	A known fault – find which signal changed first, and what led what
A sweep: which settings hold	810 runs of a controller sweep – the 12 settings that hold in every wind and payload, the best one
One gain set, three drones	One set of gains that holds for three different drones – and why the others fail
Smart sweep demo	The next runs chosen for you, round after round, until it converges – about 64× fewer runs than the full grid
A fleet of flights	Ten flights of two copters – the one whose vibration grows, flight after flight

What it does for you

1 · Find what went wrong

Put two cursors around the moment it went wrong and ask What changed? – every signal that left its usual range, in time order, the likeliest cause first, and which one led which. Then name the event (abs(Roll - DesRoll) > 5), find every time it happened, and line them up.

Tutorial: what went wrong, in ten minutes

2 · Judge a run against a golden one

A golden run with a tolerance per signal judges the next recording – pass or fail, the worst moment, the verdict ready for the report. The same check runs in CI.

signalviewer-cli compare golden.csv runs/*.csv --tol-pct 2 --junit results.xml   # exit 1 when one fails
signalviewer-cli check   runs/*.csv --checks checks.json                         # limits, per flight mode

3 · See the flight – on the map, in 3D, as a story

Truth, each navigation solution, each GPS and EKF lane – on an offline map or in 3D over real terrain, compared in position, velocity and attitude. ▶ Story plays the flight as a short film: the camera flies to each moment that matters.

4 · Choose parameters that hold everywhere

A results table with a row per run: which parameter sets hold in every scenario, the best of them, and how the runs spread over each scenario. With several systems, one set for all of them. Then let the app run the loop: it proposes the next runs, starts your program (or hands them to your farm's launcher), reads the results and goes on until the best stops changing.

One parameter set for many systems · The smart-sweep demo · Your farm as the runner

5 · Watch the whole fleet

Point it at the folders of logs. Every flight is checked the same way; ask which flights had errors? or is the vibration growing over the weeks? – and open the one that needs a look.

Tutorial: what the Fleet is for

6 · Send the answer, not a screenshot

One HTML file that opens with the process in brief – the data, what was checked, what it shows and the conclusion – then plots, map and 3D on one time bar with Play. Any browser, no install, no network. PDF and Word too.

Fast on big data – without cutting corners

• A 1.2 GB ArduPilot log opens in seconds; every sample stays available at full resolution, and the display keeps every spike.
• A sweep of a million runs opens with its answer in about 2 s; switching between parameter sets and every run does not work the answer out again.
• Every computation is checked against an independent reference – 29 validation cases, run them yourself with signalviewer-cli validate.

Get started

• Windows: the installer or the portable .zip from the latest release – no administrator rights.
• Linux / macOS: the -portable.7z, or Python 3.9+: pip install signalviewer, then signalviewer.
• From source: git clone, pip install -r requirements.txt, python run.py.

Nothing needs the internet – not the map, not the 3D terrain. No account, no telemetry.

In your scripts

import signalviewer as sv
rec = sv.load("flight.bin")
sv.scene_html(rec, path="flight-3d.html")      # the flight in 3D, one offline page

python -m signalviewer.study loop drones.svstudy.json      # the sweep loop, from a terminal or a scheduler

Command line and Python · Scripting API · Everything it does · CHANGELOG

Where it fits

You mostly…	Also used	What Signal Viewer adds
stream ROS topics live	PlotJuggler, Foxglove	recorded runs compared, pass / fail, live reports
work in MATLAB / Simulink	Simulation Data Inspector	no licence; flight logs and CAN next to the .mat; sweeps of runs
review one flight online	UAV Log Viewer, PX4 Flight Review	offline, many flights side by side, a fleet, your limits in CI

בעברית בקצרה

Signal Viewer – מוצאים מה השתבש, מוכיחים מה תקין, ושולחים את התשובה. הכול על המחשב שלכם, בלי אינטרנט.

• לכל חלק באפליקציה יש הדגמה במסך הפתיחה – טיסה, לוג ArduPilot, השוואה לסימולציה, חקירת תקלה, סריקת פרמטרים, הלולאה החכמה וצי טיסות.
• מה השתבש: שני סמנים סביב הרגע – והאפליקציה מראה מה השתנה ראשון, מה הסיבה הסבירה ומי הוביל את מי.
• סריקות: אילו הגדרות עומדות בכל תרחיש, סט אחד לכמה מערכות, ולולאה שמריצה את הקוד שלכם עד התכנסות.
• דוח: דף HTML חי שנפתח ב"התהליך בקצרה" – הנתונים, מה נבדק, מה מוצג והמסקנה.

התקנה: מ־השחרור האחרון, או pip install signalviewer. מדריך: docs/GUIDE.he.md.

License

MIT – free to use, change and ship, also commercially. Third-party parts keep their own licences: uPlot (MIT), three.js (MIT), the report fonts (SIL OFL), CesiumJS (Apache-2.0), map data from OpenStreetMap (ODbL), Natural Earth and the AWS Terrain Tiles (details).