pydho800 0.0.8

Rigol 800 control library (unofficial)

Rigol DHOxxx oscilloscope Python library (unofficial)

Based completely on https://github.com/tspspi/pymso5000/tree/master by tspspi

A simple Python library and utility to control and query data from Rigol DHOxxx oscilloscopes. This library implements the Oscilloscope class from the pylabdevs package which exposes the public interface.

When retrieving sample point data from the scope, the number of points retrieved is set by the scope's memory depth.

The default memory depth of the scope is set to 10k points. This can be changed through the set_memory_depth() function

Alternatively this can be changed by accessing the following menus on the scope:

Click on any channel and click "Acquisition":

Change the memory depth:

Installing

There is a PyPi package that can be installed using

pip install pydho800

Simple example to fetch waveforms:

from pydho800.pydho800 import PYDHO800

with DHO800(address = "10.0.0.123") as dho:
    print(f"Identify: {dho.identify()}")

    dho.set_channel_enable(0, True)
    dho.set_channel_enable(1, True)

    dho.set_run_mode(OscilloscopeRunMode.RUN)
    dho.set_run_mode(OscilloscopeRunMode.STOP)

    data = dho.query_waveform((0, 1))
    print(data)

    import matplotlib.pyplot as plt
    plt.plot(data['x'], data['y0'], label = "Ch1")
    plt.plot(data['x'], data['y1'], label = "Ch2")

    # Note if only one channel were enabled, it would be accessed by:
    # plt.plot(data['x'], data['y'], label = "Ch1")

    plt.show()

Note that numpy usage is optional for this implementation. One can enable numpy support using useNumpy = True in the constructor.

Querying additional statistics

This module allows - via the pylabdevs base class to query additional statistics:

• mean Calculates the mean values and standard deviations
  • A single value for each channels mean at ["means"]["yN_avg"] and a single value for each standard deviation at ["means"]["yN_std"] where N is the channel number
• fft runs Fourier transform on all queried traces
  • The result is stored in ["fft"]["yN"] (complex values) and in ["fft"]["yN_real"] for the real valued Fourier transform. Again N is the channel number
• ifft runs inverse Fourier transform on all queried traces
  • Works as fft but runs the inverse Fourier transform and stores its result in ifft instead of fft
• correlate calculates the correlation between all queried waveform pairs.
  • The result of the correlations are stored in ["correlation"]["yNyM"] for the correlation between channels M and N
• autocorrelate performs calculation of the autocorrelation of each queried channel.
  • The result of the autocorrelation is stored in ["autocorrelation"]["yN"] for channel N

To request calculation of statistics pass the string for the desired statistic or a list of statistics to the stats parameter of query_waveform:

with DHO800(address = "10.0.0.123") as dho:
	data = dho.query_waveform((1,2), stats = [ 'mean', 'fft' ])

Supported methods

More documentation in progress ...

• identify()
• Connection management (when not using with context management):
  • connect()
  • disconnect()
• set_channel_enable(channel, enabled)
• is_channel_enabled(channel)
• set_sweep_mode(mode)
• get_sweep_mode()
• set_trigger_mode(mode)
• get_trigger_mode()
• force_trigger()
• set_timebase_mode(mode)
• get_timebase_mode()
• set_run_mode(mode)
• get_run_mode()
• set_timebase_scale(secondsPerDivision)
• get_timebase_scale()
• set_channel_coupling(channel, couplingMode)
• get_channel_coupling(channel)
• set_channel_probe_ratio(channel, ratio)
• get_channel_probe_ratio(channel)
• set_channel_scale(channel, scale)
• get_channel_scale(channel)
• query_waveform(channel, stats = None)
• off()