def connect(args, force=False):
if len([x for x in (args.serial, args.name, args.ip) if x]) != 1:
print("Please specify exactly one of serial, name or IP address of "
"target Moku")
exit(1)
force = force or args.force
if args.serial:
moku = Moku.get_by_serial(args.serial, force=force)
print(moku.get_name())
elif args.name:
moku = Moku.get_by_name(args.name, force=force)
else:
moku = Moku(args.ip, force=force)
return moku
def main():
print("Beginning automated testing sequence")
# Connect to the Moku device by name
moku = Moku.get_by_name('Moku')
try:
# Run Phase 1 - Rise Times
res1, fails1, criteria1 = phase1(moku)
# Run Phase 2 - Line Widths
res2, fails2, criteria2 = phase2(moku)
generate_results_file(moku, res1, fails1, criteria1, res2, fails2,
criteria2)
print("Testing complete")
finally:
moku.close()
from pymoku import Moku, ValueOutOfRangeException
from pymoku.instruments import *
import time, logging
import matplotlib
import matplotlib.pyplot as plt
logging.basicConfig(format='%(asctime)s:%(name)s:%(levelname)s::%(message)s')
logging.getLogger('pymoku').setLevel(logging.DEBUG)
# Use Moku.get_by_serial() or get_by_name() if you don't know the IP
m = Moku.get_by_name("Aqua")
i = m.discover_instrument()
if i is None or i.type != 'signal_generator':
print "No or wrong instrument deployed"
i = SignalGenerator()
m.attach_instrument(i)
else:
print "Attached to existing Signal Generator"
i.set_defaults()
i.synth_sinewave(1, 1.0, 1000000)
i.synth_squarewave(2, 1.0, 2000000, risetime=0.1, falltime=0.1, duty=0.3)
i.commit()
try:
while True:
try:
from scipy import fft
import math
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
# Specify nyquist and cutoff (-3dB) frequencies
nyq_rate = 125e6 / 2**10 / 2.0
cutoff_hz = 1e3
# Calculate FIR kernel using 1000 taps and a chebyshev window with -60dB
# stop-band attenuation
taps = firwin(1000, cutoff_hz / nyq_rate, window='hamming')
# Connect to your Moku by its device name
# Alternatively, use Moku.get_by_serial('#####') or Moku('192.168.###.###')
m = Moku.get_by_name('Moku')
try:
i = m.deploy_or_connect(FIRFilter)
# Configure the Moku:Lab frontend settings
i.set_frontend(1, fiftyr=True, atten=False, ac=False)
i.set_frontend(2, fiftyr=True, atten=False, ac=False)
# Both filter channels are configured with the same FIR kernel. A
# decimation factor of 10 is used to achieve the desired nyquist rate and
# FIR kernel length of 1000.
i.set_filter(1, decimation_factor=10, filter_coefficients=taps)
i.set_filter(2, decimation_factor=10, filter_coefficients=taps)
# Channel 1 has unity input/output gain and acts solely on ADC1.
from pymoku import Moku, MokuException
from pymoku.instruments import *
import pymoku.plotly_support as pmp
import time, logging, traceback
logging.basicConfig(format='%(asctime)s:%(name)s:%(levelname)s::%(message)s')
logging.getLogger('pymoku').setLevel(logging.INFO)
# Use Moku.get_by_serial() or get_by_name() if you don't know the IP
m = Moku.get_by_name('example')
i = m.discover_instrument()
if i is None or i.type != 'oscilloscope':
print "No or wrong instrument deployed"
i = Oscilloscope()
m.attach_instrument(i)
else:
print "Attached to existing Oscilloscope"
linespec = {
'color' : '(rgb(100,0,0),)',
'shape' : 'spline',
'width' : '2'
}
try:
i.set_defaults()
i.set_samplerate(10)
from pymoku import Moku, MokuException
from pymoku.instruments import *
import time, logging, traceback
logging.basicConfig(format='%(asctime)s:%(name)s:%(levelname)s::%(message)s')
logging.getLogger('pymoku').setLevel(logging.DEBUG)
# Use Moku.get_by_serial() or get_by_name() if you don't know the IP
m = Moku.get_by_name('example')
i = m.discover_instrument()
if i is None or i.type != 'oscilloscope':
print "No or wrong instrument deployed"
i = Oscilloscope()
m.attach_instrument(i)
else:
print "Attached to existing Oscilloscope"
try:
i.set_defaults()
i.set_samplerate(1000) #10ksps
i.set_xmode(OSC_ROLL)
i.commit()
if i.datalogger_busy():
i.datalogger_stop()
i.datalogger_start(start=0, duration=10, filetype='net')
while True:
from pymoku import Moku, ValueOutOfRangeException
from pymoku.instruments import *
import time, logging
import matplotlib
import matplotlib.pyplot as plt
logging.basicConfig(format='%(asctime)s:%(name)s:%(levelname)s::%(message)s')
logging.getLogger('pymoku').setLevel(logging.DEBUG)
# Use Moku.get_by_serial() or get_by_name() if you don't know the IP
m = Moku.get_by_name("Aqua")
i = m.discover_instrument()
if i is None or i.type != 'signal_generator':
print "No or wrong instrument deployed"
i = SignalGenerator()
m.attach_instrument(i)
else:
print "Attached to existing Signal Generator"
i.set_defaults()
i.synth_sinewave(1, 1.0, 1000000)
i.synth_squarewave(2, 1.0, 2000000, risetime=0.1, falltime=0.1, duty=0.3)
i.commit()
try:
while True:
try:
from pymoku import Moku, MokuException, NoDataException
from pymoku.instruments import *
import time, logging, traceback
logging.basicConfig(format="%(asctime)s:%(name)s:%(levelname)s::%(message)s")
logging.getLogger("pymoku").setLevel(logging.INFO)
# Use Moku.get_by_serial() or get_by_name() if you don't know the IP
m = Moku.get_by_name("example")
i = Oscilloscope()
m.attach_instrument(i)
try:
i.set_samplerate(10)
i.set_xmode(OSC_ROLL)
i.commit()
time.sleep(1)
i.datalogger_stop()
i.datalogger_start(start=0, duration=100, use_sd=False, ch1=True, ch2=False, filetype="net")
while True:
ch, idx, d = i.datalogger_get_samples(timeout=5)
print("Received samples %d to %d from channel %d" % (idx, idx + len(d) - 1, ch))
except NoDataException as e:
# This will be raised if we try and get samples but the session has finished.
print(e)
except Exception as e:
print(traceback.format_exc())
#
# (c) 2019 Liquid Instruments Pty. Ltd.
#
from pymoku import Moku
from pymoku.instruments import PIDController
def from_dB(dB):
# Helper function that converts from dB to linear scale
return 10**(dB / 20.0)
# Connect to your Moku by its device name
# Alternatively, use Moku.get_by_serial('#####') or Moku('192.168.###.###')
m = Moku.get_by_name("Moku")
try:
i = m.deploy_instrument(PIDController)
# Configure the PID Controller using frequency response characteristics
# P = -10dB
# I Crossover = 100Hz
# D Crossover = 10kHz
# I Saturation = 10dB
# D Saturation = 10dB
# Double-I = OFF
# Note that gains must be converted from dB first
i.set_by_frequency(1,
kp=from_dB(-10),
i_xover=1e2,
