I am not being able to acquire continuos data from NI DAQ using nidaqxm on Python 3.
I already acquired finite data with a similar code, although I can't understand what I need to change to acquire data continuously.
import nidaqmx
from nidaqmx import constants
from nidaqmx import stream_readers
from nidaqmx import stream_writers
import matplotlib.pyplot as plt
#user input Acquisition
Ch00_name = 'A00'
Sens_Ch00 = 100#sensibilidade em mV/g
Ch01_name = 'A01'
Sens_Ch01 = 100#sensibilidade em mV/g
fs_acq = 1651 #sample frequency
t_med = 2 #time to acquire data
with nidaqmx.Task() as task:
task.ai_channels.add_ai_accel_chan(physical_channel="cDAQ9191-1B7B393Mod1/ai0", name_to_assign_to_channel=Ch00_name,
sensitivity=Sens_Ch00, min_val=-5, max_val=5, current_excit_val=0.002)
task.ai_channels.add_ai_accel_chan(physical_channel="cDAQ9191-1B7B393Mod1/ai1", name_to_assign_to_channel=Ch01_name,
sensitivity=Sens_Ch01, min_val=-5, max_val=5, current_excit_val=0.002)
task.timing.cfg_samp_clk_timing(rate=fs_acq, sample_mode= constants.AcquisitionType.CONTINUOUS, samps_per_chan=(t_med * fs_acq),)
reader = stream_readers.AnalogMultiChannelReader(task.in_stream)
writer = stream_writers.AnalogMultiChannelWriter(task.out_stream)
What do I have to change in my code to acquire continuos data?
You need to register a callback function. I am assuming that your box is running and there is some type of status LED flashing to show that the task is running.
import nidaqmx
from nidaqmx import constants
from nidaqmx import stream_readers
from nidaqmx import stream_writers
import matplotlib.pyplot as plt
import numpy as np
#user input Acquisition
Ch00_name = 'A00'
Sens_Ch00 = 100#sensibilidade em mV/g
Ch01_name = 'A01'
Sens_Ch01 = 100#sensibilidade em mV/g
num_channels = 2
fs_acq = 1651 #sample frequency
t_med = 2 #time to acquire data
with nidaqmx.Task() as task:
task.ai_channels.add_ai_accel_chan(physical_channel="cDAQ9191-1B7B393Mod1/ai0", name_to_assign_to_channel=Ch00_name,
sensitivity=Sens_Ch00, min_val=-5, max_val=5, current_excit_val=0.002)
task.ai_channels.add_ai_accel_chan(physical_channel="cDAQ9191-1B7B393Mod1/ai1", name_to_assign_to_channel=Ch01_name,
sensitivity=Sens_Ch01, min_val=-5, max_val=5, current_excit_val=0.002)
task.timing.cfg_samp_clk_timing(rate=fs_acq, sample_mode=constants.AcquisitionType.CONTINUOUS,
samps_per_chan=(t_med * fs_acq),) # you may not need samps_per_chan
# I set an input_buf_size
samples_per_buffer = int(fs_acq // 30) # 30 hz update
# task.in_stream.input_buf_size = samples_per_buffer * 10 # plus some extra space
reader = stream_readers.AnalogMultiChannelReader(task.in_stream)
writer = stream_writers.AnalogMultiChannelWriter(task.out_stream)
def reading_task_callback(task_idx, event_type, num_samples, callback_data=None):
"""After data has been read into the NI buffer this callback is called to read in the data from the buffer.
This callback is for working with the task callback register_every_n_samples_acquired_into_buffer_event.
Args:
task_idx (int): Task handle index value
event_type (nidaqmx.constants.EveryNSamplesEventType): ACQUIRED_INTO_BUFFER
num_samples (int): Number of samples that was read into the buffer.
callback_data (object)[None]: No idea. Documentation says: The callback_data parameter contains the value
you passed in the callback_data parameter of this function.
"""
buffer = np.zeros((num_channels, num_samples), dtype=np.float32)
reader.read_many_sample(buffer, num_samples, timeout=constants.WAIT_INFINITELY)
# Convert the data from channel as a row order to channel as a column
data = buffer.T.astype(np.float32)
# Do something with the data
return 0 # callback must return an integer, otherwise callback throws a wall of errors
task.register_every_n_samples_acquired_into_buffer_event(samples_per_buffer, reading_task_callback)
This is what worked for me. I hope it helps