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matlab-modernize-daq

Port MATLAB Data Acquisition Toolbox code from the discouraged (legacy) session-based interface (daq.createSession, addAnalogInputChannel, startBackground, DataAvailable listeners, queueOutputData, wait) to the recommended DataAcquisition interface (daq("ni"), addinput, start, ScansAvailableFcn, wri…

Install / Use

npx skills add matlab/matlab-agentic-toolkit --skill matlab-modernize-daq

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

93/100

Supported Platforms

Universal

Our assessment of matlab-modernize-daq

matlab-modernize-daq scores 93/100 on our quality scale, 246th of 1,200 Content & Media skills we index (top 21%).

Its SKILL.md is 18 KB long, well organised into 14 sections with 5 code examples: a thorough specification that gives an agent plenty to work with.

With 1,098 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 18 days ago, so matlab-modernize-daq is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

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Frequently asked questions

How do I install matlab-modernize-daq?
Run npx skills add matlab/matlab-agentic-toolkit --skill matlab-modernize-daq. The install tabs above show the steps for each supported agent.
Which AI agents does matlab-modernize-daq work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is matlab-modernize-daq safe to use?
It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is matlab-modernize-daq still maintained?
The repository was last updated 18 days ago, so matlab-modernize-daq is actively maintained.

name: matlab-modernize-daq description: > Port MATLAB Data Acquisition Toolbox code from the discouraged (legacy) session-based interface (daq.createSession, addAnalogInputChannel, startBackground, DataAvailable listeners, queueOutputData, wait) to the recommended DataAcquisition interface (daq("ni"), addinput, start, ScansAvailableFcn, write, preload). Use when migrating legacy DAQ scripts, converting session-API calls, working with DataAcquisition objects, writing multi-feature DAQ scripts that combine triggers, callbacks, continuous acquisition, or analog output. Also use when a user says their DAQ script "used to work" or "errors on R20XX", since modernizing legacy session-API code is a frequent fix for those failures. Trigger keywords: daq, DAQ, NI, session interface, addtrigger, addclock, ScansAvailableFcn, ScansRequiredFcn, daq.createSession, addAnalogInputChannel, startBackground, queueOutputData, DataAvailable, evt.Data, evt.TimeStamps, wait(d), preload, discouraged, legacy, modernize, R2020a. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: author: MathWorks version: "1.0"

Port DAQ Code to the Modern DataAcquisition Interface

Translate legacy session-based Data Acquisition Toolbox code (daq.createSession, addAnalogInputChannel, DataAvailable listeners, startBackground, queueOutputData, wait) to the modern DataAcquisition interface introduced in R2020a (daq("ni"), addinput, ScansAvailableFcn, start, write, preload). Also covers writing new multi-feature DAQ scripts where the modern API patterns are easy to get wrong under cognitive load.

When to Use

  • Porting an existing script that calls daq.createSession, addAnalogInputChannel, addAnalogOutputChannel, addCounterInputChannel, addCounterOutputChannel, or addDigitalChannel.
  • Replacing DataAvailable / DataRequired / ErrorOccurred listeners with ScansAvailableFcn / ScansRequiredFcn / ErrorOccurredFcn.
  • Replacing startBackground / startForeground / s.wait() lifecycle calls.
  • Replacing queueOutputData with preload + write.
  • Writing a new DAQ script that combines two or more of: external triggers, continuous acquisition, callback-driven streaming, analog output with refill, or cross-callback state.
  • Debugging errors like Undefined function 'wait' for input arguments of type 'daq.interfaces.DataAcquisition' or Unrecognized method, property, or field 'Data' for class 'matlabshared.asyncio.buffer.ElementsAvailableInfo'.

When NOT to Use

  • Single-channel foreground acquisition with no trigger and no callbacks (e.g. "acquire 1 s of voltage from ai0 at 10 kHz and plot"). The modern API is straightforward at this scale and this skill would be unnecessary overhead.
  • Picking a DAQ vendor or evaluating non-NI hardware. This skill's evidence base is NI.
  • Signal processing or analysis of already-acquired data (filtering, spectral analysis, etc.). This skill only covers acquiring and generating data through the DataAcquisition interface, not post-processing it.
  • Simulink, App Designer, or real-time-target DAQ workflows.
  • Modernizing matlab.unittest test suites or framework-style test classes (parameterized fixtures, assumeTrue gating, arity-contract tests, helper-class hierarchies). The API substitutions in this skill apply, but the test-harness scaffolding (parent-class stripping, fixture redesign, retiring tests that target removed contracts) is out of scope. Use this skill to translate the API calls inside test bodies, then make the harness-level judgment calls separately.

Workflow

When porting a session-based script or composing a new multi-feature DAQ script, follow this order. Verify after every step — most failure modes in this domain are silent.

  1. Inventory the legacy script (porting only). Identify: device(s), channel types, rate, continuous vs finite, trigger/clock connections, callbacks (DataAvailable/DataRequired/ErrorOccurred), state shared across callbacks, output queueing.

  2. Translate vocabulary. Map every session-API token to its modern counterpart. Consult references/session-to-modern-mapping.md — load it whenever a session-API token appears in the legacy script. Common silent-rename traps: NotifyWhenDataAvailableExceeds → ScansAvailableFcnCount, NumberOfScans/NumScans → implicit (no equivalent argument), ExternalTriggerTimeout → DigitalTriggerTimeout, IsContinuous=true → start(d, "Continuous") argument.

  3. Build the DataAcquisition object. d = daq("ni"), set d.Rate, add channels with addinput/addoutput. Apply per-channel properties via the channel handle returned by addinput/addoutput.

  4. Wire triggers and clocks. Use references/canonical-snippets.md §1 — load it when the script involves addtrigger or addclock. Argument order is (d, type, role, trigSrc, trigDest) — Source is 4th, Destination is 5th. Verify: the returned trigger object's Source and Destination fields show what you intended.

  5. Wire callbacks. Use canonical snippets §2 — load it when the script needs ScansAvailableFcn or ScansRequiredFcn. Inside the callback, always pull data via read(src, src.ScansAvailableFcnCount, "OutputFormat", "Matrix") — the evt argument is matlabshared.asyncio.buffer.ElementsAvailableInfo and exposes only NumElementsAvailable, no Data, no TimeStamps. Strongly recommend wiring d.ErrorOccurredFcn = @(~,evt) fprintf("DAQ error: %s\n", evt.Error.message) — without it, exceptions inside other callbacks are silently swallowed and the run "succeeds" while every fire throws. For strict ports where the legacy script had no ErrorOccurred listener, surface this trade-off to the user instead of silently adding the handler — let them opt in.

  6. Pick a state-sharing pattern (callbacks only). If a callback needs to maintain state across fires (running counters, phase accumulator, latch flags), see references/callback-state-patterns.md — load it any time a callback maintains state. Default: handle-class wrapper or nested function. Avoid src.UserData.X = src.UserData.X + ... field-mutation; it does not persist.

  7. Wire the lifecycle. Use canonical snippets §3 — load it when blocking on completion. There is no wait(d) method on the modern object. For finite acquisitions, prefer start(d, "Duration", seconds(N)) then read or a Running poll. For continuous, set a stop condition inside the callback (if scansRead >= target; stop(src); end) and poll d.Running from the caller.

  8. Run verifyDataAcquisition before live execution. Script: scripts/verifyDataAcquisition.m. Catches the four highest-frequency silent gaps (missing ErrorOccurredFcn, evt.Data in callback source, wait(d) token, UserData.X = UserData.X + ... field mutation) by inspecting the live object and grepping the source file. Run via mcp__matlab__run_matlab_file if available, or copy into the user's project.

  9. Live verification. Run a short version (e.g. 1–2 s instead of the user's full duration). Check that the script reaches start cleanly, that the callback fires at least once, and that no errors print from ErrorOccurredFcn. Use mcp__matlab__run_matlab_file against a saved .m file, not mcp__matlab__evaluate_matlab_code — the eval-string buffer runs in script mode and rejects local/nested function definitions, which Pattern 5 and most callback bodies require.

Key Functions

| Function | Purpose | Toolbox | Available From | |----------|---------|---------|----------------| | daq | Create a DataAcquisition object (d = daq("ni")) | Data Acquisition Toolbox | R2020a | | addinput | Add input channel (analog, counter, or digital) | Data Acquisition Toolbox | R2020a | | addoutput | Add output channel | Data Acquisition Toolbox | R2020a | | addtrigger | Add trigger connection: addtrigger(d, type, role, trigSrc, trigDest) | Data Acquisition Toolbox | R2020a | | addclock | Add clock connection (similar signature) | Data Acquisition Toolbox | R2020a | | read | Foreground acquire OR pull data inside ScansAvailableFcn | Data Acquisition Toolbox | R2020a | | write | Write output samples (also from inside ScansRequiredFcn) | Data Acquisition Toolbox | R2020a | | preload | Load initial output buffer before start(d, "Continuous"). Output channels only. | Data Acquisition Toolbox | R2020a | | start | Begin background acquisition: start(d), start(d, "Continuous"), start(d, "Duration", seconds(N)) | Data Acquisition Toolbox | R2020a | | stop | Stop a running acquisition | Data Acquisition Toolbox | R2020a | | flush | Discard buffered scans before reading | Data Acquisition Toolbox | R2020a | | daqlist | Enumerate available devices (replaces daq.getDevices) | Data Acquisition Toolbox | R2020a | | daqreset | Reset DAQ subsystem (replaces daq.reset) | Data Acquisition Toolbox | R2020a |

Properties on DataAcquisition: Rate, Running, NumScansAcquired, NumScansOutputByHardware, ScansAvailableFcn, ScansAvailableFcnCount, ScansRequiredFcn, ScansRequiredFcnCount, ErrorOccurredFcn, DigitalTriggerTimeout, UserData.

Patterns

The five canonical patterns below appear in full, with verified code, in references/canonical-snippets.md. Inline below is the minimal recall snippet for each — enough to anchor the agent's memory under load. Load the reference for the full, runnable forms.

Pattern 1: Add an external start trigger

trg = addtrigger(d, "Digital", "StartTrigger", "External", "Dev1/PFI0");
trg.Condition = "RisingEdge";
d.DigitalTriggerTimeout = 30;

The 4th argument is the Source ("External" for an external signal). The 5th is the Destination (the device terminal). Reversing them is the most-frequent error in this domain. The trigger condition ("RisingEdge", "FallingEdge") is set on the trigger object returned by addtrigger (trg.Condition), not on the DataAcquisition object. There is no d.DigitalTriggerCondition property — inventing one passes static lint but errors at runtime.

Pattern 2: ScansAvailableFcn body — pull data via read, never evt.Data

d.ScansAvailableFcnCount = round(d.Rate * 0.5);
d.ScansAvailableFcn = @(src, ~) onBlock(src);
d.ErrorOccurredFcn  = @(~, evt) fprintf("DAQ error: %s\n", evt.Error.message);

function onBlock(src)
    [data, t] = read(src, src.ScansAvailableFcnCount, "OutputFormat", "Matrix");
    plot(t, data); drawnow limitrate;
end

The evt argument carries only NumElementsAvailable; it has no Data or TimeStamps. Wiring ErrorOccurredFcn is strongly recommended — without it, callback exceptions are silently swallowed and the run "succeeds" while every fire throws. For strict ports of legacy scripts that did not have an ErrorOccurred listener, ask the user before adding one rather than inserting it silently.

Pattern 3: Block until acquisition completes — there is no wait(d)

start(d, "Duration", seconds(10));
while d.Running
    pause(0.05);
end

wait(d) does not exist on daq.interfaces.DataAcquisition. Poll d.Running, or rely on start(d, "Duration", ...) + a stop condition inside the callback.

Pattern 4: Continuous AO playback with auto-refill

d = daq("ni");
d.Rate = 1000;
addoutput(d, "Dev1", "ao0", "Voltage");
d.ScansRequiredFcnCount = d.Rate;
d.ScansRequiredFcn = @(src, ~) write(src, generateNextBlock());
preload(d, generateNextBlock());
preload(d, generateNextBlock());
start(d, "Continuous");

preload is output-only — calling it on input-only setups errors. Two preloaded blocks before start give the buffer headroom for the first

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars1.1k
CategoryContent
Updated18d ago
Forks134

Languages

MATLAB

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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