Streaming

In this example code, data is acquired at 50,000 Samples/s, for two consecutive 0.5 s blocks. On a LabJack U3, two 183 Hz PWM signals are generated on ports FIO4 and FIO5, and streamed into AIN0 and AIN1, repectively.

""" lj_streaming.py

Collects streaming data.

Data is acquired at a user-defined `samplerate` up to 50000 Samples/s on a U3
or a U6, and 100000 Samples/s on a T7. The effective sampling rate per channel
is `samplerate` divided by the number of channels. Data blocks are collected
at a user-defined `readrate` in seconds. Typical values of 0.5 seconds are used
for high sample rates.

Setup:
    In this example code, 2 PWM signals are generated on the following ports:
    FIO4 and FIO5 on a U3
    FIO0 and FIO1 on a U6
    FIO0 and FIO4 on a T7
    which in turn should be connected respectively to ports AIN0 and AIN1.

The LabJack unified methods in this example are:
    set_PWM .......... Sets LabJack configuration for PWM output
    set_dutycycle .... Sets duty cycle of PWM output (-100 to 100)
    set_stream ....... Sets LabJack configuration for data streaming
    get_stream ....... Gets streaming data
    stop_stream ...... Stops data streaming
    close ............ Closes the LabJack device

"""
import time
import numpy as np
from labjack_unified.utils import plot_line
from labjack_unified.devices import LabJackU3, LabJackU6, LabJackT7

# To use a LabJack U6 or a T7, change the device name
# from LabJackU3 below to either LabJackU6 or LabJackT7
lj = LabJackU3()

# Assigning streaming parameters
samplerate = 50000 # Samples/s
readrate = 0.5 # Block size (s)
nblocks = 2 # Number of acquired blocks
portlist = ['AIN0', 'AIN1']
# Creating array with dummy values to enable concatenation
data = np.zeros((1, len(portlist)))

# Setting a PWM output
lj.set_pwm(pwmnum=2, frequency=183)
lj.set_dutycycle(value1=25, value2=50)
# Configuring and starting streaming
lj.set_stream(portlist, scanrate=samplerate, readrate=readrate)
# Waiting for first block to become available
time.sleep(readrate)
# Executing acquisition loop
for i in range(nblocks):
    # Starting computational overhead time watch
    t0 = time.time()
    # Getting one block of data
    dt, datablock, numscans, commbacklog, U3backlog = lj.get_stream()
    # Concatenating new data
    data = np.vstack((data, datablock))
    # Showing statistics
    print('Block :', i+1)
    print('Scans :', numscans)
    print('Comm Backlog : {:0.1f}'.format(commbacklog))
    print('U3 Backlog   : {:0.1f}'.format(U3backlog))
    # Pausing taking into account computation overhead
    thead = time.time()-t0
    time.sleep(readrate-thead)
# Stopping streaming
lj.stop_stream()
# Closing LabJack
lj.close()
del lj

# Removing first row of dummy data
data = data[1::, :]
# Creating time array
t = dt * np.linspace(0, data.shape[0]-1, data.shape[0])
# Setting x and y arrays for plotting
naxes = len(portlist)
x = [t] * naxes
y = [data[:, i] for i in range(naxes)]
# Plotting results
plot_line(x, y, yname=portlist, axes='multi')