Waveform timestamps do not have enough precision for high AI Convert Clock rates
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- Dominant language
- Python
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Description
Bug Report
Waveform timestamps are returned from the DAQmx C API in .NET-style 100ns ticks, which is not high enough precision for high AI Convert Clock rates.
Repro or Code Sample
Add print(f"{time_offset:f}") to the updated voltage_acq_int_clk_plot_wfm.py from #940 and acquire Dev1/ai0:3 with a sample rate of 250e3.
Expected Behavior
Each channel has a unique time offset.
Current Behavior
Each channel has a time offset of 0.0.
0.000000
0.000000
0.000000
0.000000
Possible Solution
Fix internal bug AB#3229757
Context
Updating shipping example to plot multiple channels correctly
Your Environment
- Operating system and version: Windows 11
- NI-DAQmx version: 2026 Q2 dev build
nidaqmx-pythonversion: 1.5.0 dev build- Python version: 3.11.7
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the updated voltage_acq_int_clk_plot_wfm.py example from #940 and reproduce the Dev1/ai0:3 acquisition at a 250e3 sample rate, checking the printed time_offset values. Trace how waveform timestamps returned by the DAQmx C API are represented in Python, then use internal bug AB#3229757 as the reported implementation reference. Done means each channel has a unique time offset and the multi-channel plot is correct.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- api, backend
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100