MultiPyVu 1.1.0.post1

Control MultiVu using Python

MultiPyVu

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Introduction

MultiPyVu provides the ability to control the temperature, magnetic field, and chamber status of Quantum Design, Inc. products using python. This module includes MultiVuServer, which runs on the same computer as MultiVu, and MultiVuClient, which is used to send commands to the cryostat. MultiVuClient can run (1) locally on the same PC as MultiVu + MultiVuServer, or (2) remotely on another computer that has TCP access to the computer running MultiVuServer.

MultiVuDataFile is a module which allows a python script to save data in a MultiVu-readable .dat format. Any data can be saved using this module, so it is easy to combine temperature and field data along with the output from a researcher's own instrumentation.

The components of MultiPyVu enable access to the set and read the temperature, field, and chamber on the following QD platforms: PPMS, DynaCool, VersaLab, MPMS3, and OptiCool. MultiVuClient can run on a PC, Mac, or Linux, including a RaspberryPi.

Module Requirements

MultiPyVu uses the following modules:

• python version 3.8 or higher
• pywin32 - We recommend using version 300 or higher.
• pandas

For the Python 3 distribution Quantum Design recommends Anaconda (https://www.anaconda.com/products/individual) as it includes most modules needed for this server and other packages useful for scientific computing. This code was built and tested using Python 3.8. If you are not sure which version of Python you are using, from a command prompt type:

python --version

MultiPyVu can be installed using pip via the following command:

pip install MultiPyVu

Included Example Scripts

Several examples have been uploaded to Quantum Design's Pharos database and can be downloaded from there. These examples demonstrate various capabilities of the module, and serve as templates upon which users can add their own code to integrate external hardware operations with the environmental controls of the Quantum Design instrument.

Filename	Description
example_Local.py	A simple script which starts the server, then the client, on the PC running MultiVu. It relays instrument parameters and status to demonstrate communication, serving as a minimum working example useful for testing basic functionality.
example_Remote-Server.py	For remote operation; this script must be running on the on the control PC along with the MultiVu executable.
example_Remote-Client.py	For remote operation; this script runs on a separate PC and relays instrument parameters and status to demonstration communication.
example_Command-Demos.py	Utilizes most functions of the module, setting temperature/field/chamber operations, reading back the values and status of those parameters, and waiting for stability conditions to be met. As-written, it runs in local mode.
example_MVDataFile-VISA.py	Simple example showing how to route environmental parameters and data from external instruments into a single MultiVu-readable .dat file. As-written, it runs in local mode.
whats_my_ip_address.cmd	This batch file script prints out the IP address for the computer, providing an easy way to get the server IP address needed for remote opertation.

Getting Started

Once the MultiPyVu module has been installed, be sure that the MultiVu executable is running on the PC connected to the cryostat before starting the server. For testing purposes, you can use MultiVu in simulation mode on an office computer.

Local Operation It is suggested to run first run the 'Local' example with no changes on the MultiVu PC connected to the instrument- this should verify that the underlying resources required by the module are all present and functioning properly. If this is successful, proceed to the 'example_Command-Demos.py' example for a brief demonstration of the commands used to set and monitor the sample space environmental parameters, as well as the wait command.

Remote Operation After confirming the local example scripts have executed correctly, remote operation can be attempted. First, on the MultiVu PC, run the 'Remote-Server' script, being sure to update the IP address to reflect the IPV4 address of the server PC. To determine this address on a Windows PC, open a command prompt, change the directory to the location of the downloaded example files, and run the following command:

whats_my_ip_address

This executes a small batch file of the same name which returns the IPV4 address needed to facilitate remote operation. Update the existing address in the 'flags' variable of the 'example_Remote-Server.py' script and then run it.

Similarly, on the client PC, update the 'host' variable of the 'example_Remote-Client.py' script with the same server PC IPV4 address and run it. The script will report the present temperature and field value/status a few times to show the connection is functioning.

Next Steps It may sometimes be desirable to combine the sample environment parameters (temperature, field) with readings from a user's own instrumentation into a single .dat file which can be plotted in MultiVu. This functionality, accomplished using the MultiVuDataFile module, is demonstrated using PyVISA to communicate with a VISA-compatible instrument in the 'example_MVDataFile-VISA.py' example. Note that for this routine to execute properly, the correct instrument bus/address and query string need to be updated in the script.

For further information on the detailed operation of the components of the module, see the following sections.

Using MultiVuServer() and MultiVuClient()

To start the server on localhost, open MultiVu, and then, using the example script run_server.py, go to a command prompt and type:

python run_server.py

As mentioned above, if the client and the server are running on the same computer as MultiVu, then one can use example_Local.py as a guide to set up the whole script in one file.

There are a list of useful flags to specify settings. These can be found by typing -h, which brings up help information:

python run_server.py -h

One can specify the PPMS platform, but if MultiVu is running, specifying the platform should not be necessary. For example:

python run_server.py opticool

If the server and client are going to be running on two different computers, the server IP address must be specified using the -ip flag. For example, to specify an IP address of 127.0.0.1

python run_server.py -ip=127.0.0.1

One can also follow example_Remote_Server.py to insert the IP address directly in the script. If they are on the same computer, then the -ip flag can be omitted and server will use 'localhost.'

To write a script which connects to the server from a client machine, put all of the commands to control the cryostat inside a with block:

from MultiPyVu import MultiVuClient as mvc

with mvc.MultiVuClient('127.0.0.1') as client:
    <put scripting commands here>
<do any post-processing once the client has been closed>

If needed, the host and port can be specified as parameters to MultiVuClient().

Alternatively, one can start a connection to the server using:

client = mvc.MultiVuClient(host='127.0.0.1')
client.open()
<put scripting commands here>
client.close_client()
<do any post-processing once the client has been closed>

The client can also end the control scripting commands by closing the server at the same time using

client.close_server()

instead of client.close_client().

If the client and server are being run on the same computer, then one could also write one script to control them both.

from MultiPyVu import MultiVuServer as mvs
from MultiPyVu import MultiVuClient as mvc

with mvs.MultiVuServer() as server:
    with mvc.MultiVuClient() as client:
        <put scripting commands here>
<do any post-processing once the client and server have been closed>

Commands

The commands to set and get the temperature, field, and chamber status are defined here:

Temperature

client.set_temperature(set_point,
                       rate_K_per_min,
                       client.temperature.approach_mode.<enum_option>)

Note that the mode is set using the client.temperature.approach_mode enum. The temperature and status are read back using:

temperature, status = client.get_temperature()

The possible status values can be listed by typing

state_code_dictionary = client.temperature.state_code_dict()

Field

client.set_field(set_point,
                 rate_oe_per_sec,
                 client.field.approach_mode.<enum_option>)

Note that the approach mode is set using the client.field.approach_mode enum. The PPMS magnet can be run driven or persistent, so it has a fourth input which is specified using the client.field.driven_mode enum. For the PPMS flavor:

client.set_field(set_point,
                rate_oe_per_sec,
                client.field.approach_mode.<enum_option>,
                client.field.driven_mode.<enum_option>)

The field and status are read back using:

field, status = client.get_field()

and the possible status values can be found using the client.field.state_code_dict()

Chamber

client.set_chamber(client.chamber.mode.<enum_option>)

And read back using:

chmbr = client.get_chamber()

Wait For When a setting on a cryostat is configured, it will take time to reach the new setpoint. If desired, one can wait for the setting to become stable using the .wait_for(delay, timeout, bitmask) command. A delay will set the time in seconds after the setting is stable; timeout is the seconds until the command will give up; bitmask tells the system which settings need to be stable. This can be set using the client.subsystem enum. Multiple settings can be configured using bitwise or. For example:

client.wait_for(0, 90, client.subsystem.temperature | client.subsystem.field)

Saving to a MultiVu Data File

The MultiVuClient class can be used in conjunction with 3rd party tools in order to expand the capabilities of measurements from a Quantum Design cryostat. One can set up a VISA connection to a voltmeter, for example, and then collect information while controlling the cryostat temperature, field, and chamber status. This data can be collected into a MultiVu data file using MultiVuDataFile.py. First, import this into a script, then instantiate the MultiVuDataFile() class. Then assign the column headers and create the file:

from MultiPyVu import MultiVuDataFile

# configure the MultiVu columns
data = MultiVuDataFile()
data.add_multiple_columns(['Temperature', 'Field', 'Chamber Status'])
data.create_file_and_write_header('myMultiVuFile.dat', 'Special Data')

Data is loaded into the file using .set_value(column_name, value), and then a line of data is written to the file using .write_data() For example:

temperature, status = client.get_temperature()
data.set_value('Temperature', temperature)
data.write_data()

Testing the Server Using Scaffolding

For testing the server, QD has supplied scaffolding for the MultiVu commands to simulate their interactions with the server. This can be helpful for writing scripts on a computer which is not running MultiVu. To use this, start the server in scaffolding mode by using the -s flag. The scaffolding does not need MultiVu running, so it is also necessary to specify the platform. For example, to use scaffolding to test a script which will be used with Dynacool:

python run_mv_server.py Dynacool -s

Troubleshooting

Typical connection issues are due to:

• Firewall. You might need to allow connections on port 5000 (the default port number) in your firewall.
• Port conflict. If port 5000 is in use, a different number can be specified when instantiating MultiVuServer() and MultiVuClient().

server = mvs.MultiVuServer(port=6000)
client = mvc.MultiVuServer(port=6000)

• A log file named QdMultiVu.log shows the traffic between the server and client which can also be useful during troubleshooting.

Contact

Please reach out to [e-mail] with questions or concerns concerning MultiPyVu.