Example Python script to implement the Laser Lock Box (plotting)

# pymoku example: Plotting - Laser Lock Box
#
# This example demonstrates how you can configure the laser lock box
# instrument and monitor signals at each oscilloscope probe point.
#
# (c) 2019 Liquid Instruments Pty. Ltd.
# 

from pymoku import Moku
from pymoku.instruments import LaserLockBox

import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
from scipy import signal


def gen_butterworth(corner_frequency):
 """
 Generate coefficients for a second order butterworth low-pass filter.

 Corner frequencies for laser lock box second harmonic filtering should be
 in the range: 1 kHz < corner frequency < 31.25 MHz.
 """
 sample_rate = 31.25e6
 normalised_corner = corner_frequency / (sample_rate / 2)
 b, a = signal.butter(2, normalised_corner, 'low', analog=False)

 coefficient_array = [[1.0, b[0], b[1], b[2], -a[1], -a[2]],
 [1.0, 1.0, 0.0, 0.0, 0.0, 0.0]]
 return coefficient_array


# Use Moku.get_by_serial() or get_by_name() if you don't know the IP
m = Moku.get_by_name('Moku')

try:
 i = m.deploy_or_connect(LaserLockBox)

 # set enables
 i.set_output_enables(1, True)
 i.set_output_enables(2, True)
 i.set_pid_enables(1, True)
 i.set_pid_enables(2, False)
 i.set_channel_pid_enables(1, True)
 i.set_channel_pid_enables(2, True)

 # set local oscillator, auxiliary and scan generators
 i.set_local_oscillator(source='internal', frequency=10e3, phase=0,
 pll_auto_acq=False)
 i.set_aux_sine(amplitude=1.0, frequency=10e3, phase=0, sync_to_lo=False,
 output='out1')
 i.set_scan(frequency=1e3, phase=0, output='out2', amplitude=1.0,
 waveform='triangle')

 # configure PIDs:
 i.set_pid_by_gain(1, g=1, kp=1)
 i.set_pid_by_gain(2, g=1, kp=1)

 # set offsets
 i.set_offsets(position='pid_input', offset=0.1)
 i.set_offsets(position='out1', offset=-0.1)
 i.set_offsets(position='out2', offset=0.2)

 # set allowable output range
 i.set_output_range(1, 0.5, -0.5)
 i.set_output_range(2, 0.5, -0.5)

 # configure second harmonic rejection low pass filter
 coef_array = gen_butterworth(1e4)
 i.set_custom_filter(coef_array)

 # Monitor the error signal and fast pid output signal
 i.set_monitor('A', 'pid_fast')
 i.set_monitor('B', 'pid_slow') # green

 # Trigger on rising edge of the scan signal, 0V threshold level with 0.1V
 # hysteresis
 i.set_trigger('scan', 'rising', level=0, hysteresis=0.1,
 trig_on_scan_rising=True)

 # View +- 2 millisecond, i.e. trigger in the centre
 i.set_timebase(-2e-3, 2e-3)

 # Get initial data frame to set up plotting parameters. This can be done
 # once if we know that the axes aren't going to change (otherwise we'd do
 # this in the loop)
 data = i.get_realtime_data()

 # Set up the plotting parameters
 plt.ion()
 plt.show()
 plt.grid(b=True)
 plt.ylim([-2, 2])
 plt.xlim([data.time[0], data.time[-1]])

 line1, = plt.plot([])
 line2, = plt.plot([])

 # Configure labels for axes
 ax = plt.gca()
 ax.xaxis.set_major_formatter(FuncFormatter(data.get_xaxis_fmt))
 ax.yaxis.set_major_formatter(FuncFormatter(data.get_yaxis_fmt))
 ax.fmt_xdata = data.get_xcoord_fmt
 ax.fmt_ydata = data.get_ycoord_fmt

 # This loops continuously updates the plot with new data
 while True:
 # Get new data
 data = i.get_realtime_data()

 # Update the plot
 line1.set_ydata(data.ch1)
 line2.set_ydata(data.ch2)
 line1.set_xdata(data.time)
 line2.set_xdata(data.time)
 plt.pause(0.001)
finally:
 # Close the connection to the Moku device
 # This ensures network resources and released correctly
 m.close()