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Create a synchronization example for TDMS logging (#874)
* try workaround * doing * creaate cont_ai_ci_tdms_sync.py * remove generated tdms file * changelod & remove excessive comment * set tdms file path * solve comment * solve comments * resolve comment * resolve comment * resolve comment * resolve mypy * resolve comment
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CHANGELOG.md

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@@ -30,7 +30,7 @@ All notable changes to this project will be documented in this file.
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* [Full changelog: 1.3.0...1.4.0](https://github.com/ni/nidaqmx-python/compare/1.3.0...1.4.0)
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* ### Resolved Issues
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* ...
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* [820: Create a synchronization example for TDMS logging](https://github.com/ni/nidaqmx-python/issues/820)
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* ### Major Changes
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* Removed support for Python 3.9.
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"""Example of logging multiple synchronized tasks to a single TDMS file using a queue.
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This example demonstrates how to:
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1. Synchronize multiple DAQmx tasks using a shared clock
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2. Use a producer-consumer pattern with a queue
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3. Log data from multiple tasks to a single TDMS file
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"""
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import os
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import queue
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import threading
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import time
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from collections.abc import Sequence
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from concurrent.futures import ThreadPoolExecutor
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from pathlib import Path
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import numpy as np
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from nitypes.waveform import AnalogWaveform
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from nptdms import ChannelObject, GroupObject, RootObject, TdmsFile, TdmsWriter
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import nidaqmx
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from nidaqmx.constants import (
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AcquisitionType,
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Edge,
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)
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from nidaqmx.stream_readers import AnalogMultiChannelReader, CounterReader
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os.environ["NIDAQMX_ENABLE_WAVEFORM_SUPPORT"] = "1"
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# Configuration
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SAMPLE_RATE = 1000
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SAMPLES_PER_CHANNEL = 1000
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TIMEOUT = 10.0
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# Note: This example currently assumes all tasks run on a single synchronized device.
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# To make this example work across multiple devices, share the sample clock
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# between devices using the PXI trigger bus or a PFI line.
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DEVICE_NAME = "Dev1"
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TaskData = tuple[
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Sequence[AnalogWaveform[np.float64]], # Analog input: sequence of waveforms
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AnalogWaveform[np.float64], # Counter input: waveform
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]
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data_queue: queue.Queue[TaskData | None] = queue.Queue(maxsize=10)
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def producer(
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tasks: Sequence[nidaqmx.Task],
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data_queue: queue.Queue[TaskData | None],
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stop_event: threading.Event,
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) -> None:
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"""Producer function that reads data from DAQmx tasks and puts it in the queue."""
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# The queue holds a tuple with task data:
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# (
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# Sequence[AnalogWaveform], # Element 0: AI data - sequence of waveform objects
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# AnalogWaveform, # Element 1: Counter data - single waveform object
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# )
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ai_reader = AnalogMultiChannelReader(tasks[0].in_stream)
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counter_reader = CounterReader(tasks[1].in_stream)
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num_ai_channels = len(tasks[0].ai_channels.all)
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try:
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while not stop_event.is_set():
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ai_waveforms = [
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AnalogWaveform(sample_count=SAMPLES_PER_CHANNEL) for _ in range(num_ai_channels)
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]
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counter_waveform = AnalogWaveform(sample_count=SAMPLES_PER_CHANNEL)
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ai_reader.read_waveforms(
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ai_waveforms, number_of_samples_per_channel=SAMPLES_PER_CHANNEL, timeout=TIMEOUT
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)
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counter_reader.read_many_sample_double(
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counter_waveform.raw_data,
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number_of_samples_per_channel=SAMPLES_PER_CHANNEL,
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timeout=TIMEOUT,
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)
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counter_waveform.timing = ai_waveforms[0].timing
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counter_waveform.channel_name = tasks[1].channel_names[0]
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data_queue.put((ai_waveforms, counter_waveform))
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except Exception as e:
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print(f"Error in producer: {e}")
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stop_event.set()
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finally:
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data_queue.put(None)
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def consumer(
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data_queue: queue.Queue[TaskData | None],
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tdms_path: str,
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group_names: Sequence[str],
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channel_names: Sequence[Sequence[str]],
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stop_event: threading.Event,
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) -> None:
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"""Consumer function that writes data from the queue to a TDMS file."""
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with TdmsWriter(tdms_path) as tdms_writer:
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while not stop_event.is_set():
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try:
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data = data_queue.get(timeout=TIMEOUT)
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except queue.Empty:
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continue
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if data is None:
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break
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ai_waveforms, counter_waveform = data
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sample_rate = 1.0 / ai_waveforms[0].timing.sample_interval.total_seconds()
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root_object = RootObject(
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properties={"Creation Time": time.strftime("%Y-%m-%d %H:%M:%S")}
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)
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objects_to_write = [root_object]
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ai_group = GroupObject("AI_Task", properties={"Sample Rate": sample_rate})
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objects_to_write.append(ai_group)
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for chan_idx, waveform in enumerate(ai_waveforms):
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channel = ChannelObject(
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"AI_Task",
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f"Channel{chan_idx + 1:02d}",
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waveform.raw_data,
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properties={
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"Sample Rate": sample_rate,
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"wf_increment": waveform.timing.sample_interval.total_seconds(),
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"wf_samples": len(waveform.raw_data),
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"wf_start_offset": 0.0,
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"wf_start_time": waveform.timing.to_datetime().start_time.strftime(
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"%Y-%m-%d %H:%M:%S"
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),
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},
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)
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objects_to_write.append(channel)
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ci_group = GroupObject("CI_Task", properties={"Sample Rate": sample_rate})
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objects_to_write.append(ci_group)
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channel = ChannelObject(
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"CI_Task",
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"Counter0",
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counter_waveform.raw_data,
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properties={
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"Sample Rate": sample_rate,
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"wf_increment": counter_waveform.timing.sample_interval.total_seconds(),
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"wf_samples": len(counter_waveform.raw_data),
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"wf_start_offset": 0.0,
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"wf_start_time": counter_waveform.timing.to_datetime().start_time.strftime(
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"%Y-%m-%d %H:%M:%S"
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),
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},
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)
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objects_to_write.append(channel)
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# Write all objects to TDMS file
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tdms_writer.write_segment(objects_to_write)
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def main():
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"""Run the synchronized data acquisition and logging example.
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Creates multiple synchronized DAQmx tasks:
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- A counter output task for the sample clock
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- An analog input task reading from two voltage channels
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- A counter input task counting edges
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Data is acquired continuously until user presses Enter, then saved to a TDMS file
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using a producer-consumer pattern with a queue for thread-safe data transfer.
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"""
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data_queue: queue.Queue[TaskData | None] = queue.Queue(maxsize=10)
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stop_event = threading.Event()
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ai_task = nidaqmx.Task()
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ci_task = nidaqmx.Task()
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script_dir = Path(__file__).resolve().parent
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tdms_filepath = script_dir / "multi_task_data.tdms"
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try:
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ai_task.ai_channels.add_ai_voltage_chan(f"{DEVICE_NAME}/ai0", "Channel01")
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ai_task.ai_channels.add_ai_voltage_chan(f"{DEVICE_NAME}/ai1", "Channel02")
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ai_task.timing.cfg_samp_clk_timing(
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SAMPLE_RATE, sample_mode=AcquisitionType.CONTINUOUS, samps_per_chan=SAMPLES_PER_CHANNEL
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)
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ci_chan = ci_task.ci_channels.add_ci_count_edges_chan(
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f"{DEVICE_NAME}/ctr0", "Counter0", edge=Edge.RISING, initial_count=0
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)
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ci_chan.ci_count_edges_term = f"{DEVICE_NAME}/PFI0"
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ci_task.timing.cfg_samp_clk_timing(
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SAMPLE_RATE,
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f"/{DEVICE_NAME}/ai/SampleClock",
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sample_mode=AcquisitionType.CONTINUOUS,
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samps_per_chan=SAMPLES_PER_CHANNEL,
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)
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# Start the Analog task last since the Counter task is using its clock
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ci_task.start()
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ai_task.start()
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with ThreadPoolExecutor(max_workers=2) as executor:
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producer_future = executor.submit(producer, [ai_task, ci_task], data_queue, stop_event)
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consumer_future = executor.submit(
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consumer,
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data_queue,
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str(tdms_filepath),
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["AI_Task", "CI_Task"],
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[["Channel01", "Channel02"], ["Counter0"]],
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stop_event,
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)
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print("Acquiring and logging data. Press Enter to stop...")
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input()
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stop_event.set()
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producer_future.result()
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consumer_future.result()
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finally:
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for task in [ai_task, ci_task]:
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if task:
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task.stop()
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task.close()
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print("\nAcquisition complete. Data saved to multi_task_data.tdms")
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if os.path.exists("multi_task_data.tdms_index"):
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os.remove("multi_task_data.tdms_index")
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with TdmsFile.open(tdms_filepath) as tdms_file:
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for group in tdms_file.groups():
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print("Group:", group.name)
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for channel in group.channels():
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data = channel[:]
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print(f"\nFirst 10 samples from {group.name}/{channel.name}:")
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print(data[:10])
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if __name__ == "__main__":
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main()

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