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pyHegel

A Python package to control laboratory instruments in a uniform way using a command line interface (ipython). It can communicate with VISA (using PyVISA) which permits GPIB, USB, RS232 and Ethernet control of instruments. But other communication protocols can be used (custom network or serial protocols, manufacturers provided libraries).

Some code needs to be written to use a new instrument, but this makes it more uniform so it can easily be used with more general tools that perform sweeping measurements and time series recording. The general tools also write the results in files in a standard format that includes headers describing the instruments state.

Description

In a laboratory experiment, many devices are interconnected and they need to be operated in a particular sequence. For example, you might do a sweep, changing a voltage applied to a circuit while reading a current somewhere else. Or you might decide to add to the sweep readings on a spectrum analyzer at each point. Or you might decide to record the drifts in some voltage over time.

To performs those operations, you could write a program in Visual Basic, C or more commonly in LabVIEW. You might need many different programs for each situations or a more complex one that handles all the situations you thought of. Well pyHegel is intended to be the later.

However, contrary to LabVIEW (C, C++, etc.), it uses a command line interface (the one provided by IPython: http://ipython.org/), and the generality of the python language itself to provide the flexibility needed to quickly change and adapt to the experiments and the measurements needed.

Interactivity provides a quick exploration of a setup. And advanced functions like sweep and record permit measurements to be taken interactively (with a single line command). But for more advanced uses, or to better repeat measurements, you can write scripts and new functions.

However to allow this power, some code is required for each new device. Many instruments already have some code, but obviously it is still a small fraction of what is available in laboratories around the world. The needed code is not necessarily very large. It depends on the complexity of the instruments, and the number of their features you want to provide control over.

The communications to many instruments can use the standard VISA library using the python bindings of PyVISA (https://pyvisa.readthedocs.org/en/master/). It is not a requirement of pyHegel, but it is needed for most instruments. This allows to communicate with standard instruments using GPIB, USB (usbtmc), LAN(VXI-11) and serial (RS232).

Other interfaces can be used. For instance Zurich Instruments UHFLI does not use VISA but the manufacturer provides the zhinst python package.

For most instruments, pyHegel also tries very hard to allow proper simultaneous access from many running process and threads (using proper VISA locking for example). Therefore you could have a pyHegel process recording the temperature, while another process sweeps and also reads the same temperature, without blocking or reading the wrong values.

Another feature is to allow measurements to be done in parallel. Imagine you perform a sweep and for each points in the sweep, you need to read two instruments and they both take 10s. If you proceed sequentially it would take 20s in total for each points in the sweep. However if you can take both measurements concurently (in parallel) then it only takes 10s. This is allowed in pyHegel in what is known as async mode. The same tricks that are use for that allow instruments that take a long time to respond to a request to be waited on instead of receiving timeouts (or making the timeouts too long which makes error recovery slower).

The locking and waiting is normally non-blocking and keeps the graphical interface updated. If you want it to stop waiting you can press CTRL-C (or quit a sweep by using the abort button, which is cleaner, but requires waiting for the end of the point).

For simple sweeps and time records, figures are plotted as the data is taken. This uses the matplotlib librairies (http://matplotlib.org/) which needs numpy (http://www.numpy.org/).

pyHegel also provides tools/wrappers to read all the data files created, merge pdf files (using pyPDF or PyPDF2), perform non-linear and polynomial fits (using scipy: http://www.scipy.org/), and other conversions.

Requirements

  • Python (tested on 2.7, does not work on 3.x)
  • numpy
  • scipy
  • matplotlib
  • PyVISA (optional: will run without it, but controlling instruments will be impaired)
  • PyPDF2 or pyPdf (optional: needed for pdf merging)
  • pywin32 is needed on windows platforms
  • some other packages depending on the instruments.

An easy way to obtain most of these on windows is to intall the Anaconda Distribution (https://www.anaconda.com/distribution/). That includes python, numpy, scipy and matplotlib. Others like PyVISA and PyPDF2 can be installed can be install from the command line using:

pip install pyVisa
pip install PyPDF2

or using the conda package installer like:

conda install pyserial

Note that pyHegel starts ipython in pylab mode with autocall enabled and with completions in a readlike fashion. You can start your own ipython with those options like this:

ipython --pylab --TerminalInteractiveShell.display_completions=readlinelike --autocall=1

To have an improved windows console, you can install ConsoleZ (https://github.com/cbucher/console). I provide a starting console.xml config file in extra/console.xml. It can be copied to %USERPROFILE%\AppData\Roaming\Console\console.xml then the different tabs can be modified/removed depending on your personal setup. (It presumes anaconda is installed in C:\Anaconda2 or C:\Anaconda3 and that for 3 it the python2 is in C:\Anaconda3\envs\py2)

Installation

Download the distribution to some directory on your computer

git clone https://github.com/lupien/pyHegel.git

You can then use it from there directly by calling the pyHegel.py script at the base of the distributions.

However you can install it either in develop mode

python setup.py develop

which will keep the current directory the active one (so the code can be modified there) but updates python so it finds the module correctly and creates the pyHegel command so you can start a session. Or use a full install

python setup.py install

In case you are doing an install on a secondary version of python on windows, you can prevent the running of the post install script (which adds the shortcuts) by adding the option --no-post

Documentation

There is some old/partially written documentation in the distribution under the manual directory. However most pyHegel commands as well as instruments/devices have inline documentation (use the ipython trick of placing "?" after an object to obtain its documentation).

About

Python command line interface to provide a uniform interface to laboratory instruments.

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LGPL-3.0, GPL-3.0 licenses found

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