Introduction

MeaVis is a python framework intended to define how Measurements have to be run and a programming interface to Visualise resulting datasets.

See more details at ReadTheDocs.io.

Basic example

General configuration of intruments

Let’s assume two basic drivers as follow:

import vxi11


class AgilentB596X(vxi11.Instrument):
    def __init__(self, host):
        super().__init__(host=host)

        self.channel = None
        self.mode = None

    def conf():
        if self.channel and self.mode:
            self.write(":SOUR{}:FUNC:MODE {}".format(self.channel, self.mode))

    def output(self, value):
        self.conf()
        if self.channel:
            self.write(
                ":OUTP{} {}".format(self.channel, "ON" if value else "OFF")
            )

    def set_channel(self, channel):
        self.channel = channel
        self.write(":SOUR{}:FUNC:SHAP DC".format(self.channel))
        self.conf()

    def set_mode(self, mode):
        self.mode = mode
        self.conf()

    def set_value(self, value):
        self.write(":SOUR{}:{} {}".format(self.channel, self.mode, value))


class KeySight344XX(vxi11.Instrument):
    def __init__(self, host):
        super().__init__(host=host)

        self.write("*CLS")
        self.write("*RST")

        self.write("TRIG:SOUR IMM")

        self.write("CALC:FUNC AVER")
        self.write("CALC:STAT ON")

        self.ACorDC = None
        self.mode = None

    def calc_average(self):
        self.write("*CALC:AVER:AVER")
        return float(self.read())

    def conf(self):
        if self.ACorDC and self.mode:
            self.write("CONF:{}:{}".format(self.mode, self.ACorDC))

    def conf_ACorDC(self, ACorDC):
        self.ACorDC = ACorDC
        self.conf()

    def conf_mode(self, mode):
        self.mode = mode
        self.conf()

    def count(self, value):
        self.write("SAMP:COUN {}".format(value))

    def initiate(self):
        self.write("INIT")

    def opc(self):
        self.write("*OPC")

    def set_aperture(self, value):
        self.write("{}:APER {}".format(self.mode, value))

As you see, this driver is very close to a one-to-one correpondance between the SPCI commands and the methods. Of course, methods can be more complexe, however a simplest driver as possible allow more flexiblity.

Then classes specific to MeaVis have to be written to decribe how to use this driver:

• Drivers: Front panel instrument.

• MeaVis classes: How an experimentalist use the front panel.

import drivers

import meavis.tags


@meavis.tags.initialiser("power_source.current_source", mode="CURR")
@meavis.tags.initialiser("power_source.voltage_source", mode="VOLT")
class InitialiserB596X:
    def __init__(self, mode):
        self.mode = mode

    def initialise(self, handler, channel):
        handler_channel = drivers.AgilentB596X(**handler)

        handler_channel.set_channel(channel)
        handler_channel.set_mode(self.mode)
        handler_channel.output(True)

        return handler_channel


@meavis.tags.initialiser("multimeter.ac_current_meter")
@meavis.tags.kwargs(mode="CURR", ACorDC="AC")
@meavis.tags.initialiser("multimeter.ac_volt_meter")
@meavis.tags.kwargs(mode="VOLT", ACorDC="AC")
@meavis.tags.initialiser("multimeter.dc_current_meter")
@meavis.tags.kwargs(mode="CURR", ACorDC="DC")
@meavis.tags.initialiser("multimeter.dc_volt_meter")
@meavis.tags.kwargs(mode="VOLT", ACorDC="DC")
class Initialiser344XX:
    def __init__(self, mode, ACorDC):
        self.ACorDC = ACorDC
        self.mode = mode

    def initialise(self, handler, channel):
        handler_channel = drivers.KeySight344XX(**handler)

        handler_channel.conf_mode(self.mode)
        handler_channel.conf_ACorDC(True)

        return handler_channel


@meavis.tags.parameter("power_source.current_source.current")
@meavis.tags.attributes(unit="A", delay=0.1)
@meavis.tags.parameter("power_source.voltage_source.voltage")
@meavis.tags.attributes(unit="V", delay=0.1)
class SourceValue:
    def __init__(self, data):
        self.data = data

    def apply(self, handler, value):
        handler.set_value(value)


@meavis.tags.parameter("multimeter.~.aperture")
@meavis.tags.attributes(unit="s")
class DMMAperture:
    def __init__(self, data):
        self.data = data

    def apply(self, handler, value):
        handler.set_aperture(value)


@meavis.tags.parameter("multimeter.~.average_count")
class DMMCount:
    def __init__(self, data):
        self.data = data

    def apply(self, handler, value):
        handler.count(value)


@meavis.tags.measurement("multimeter.ac_current_meter|dc_current_meter.current")
@meavis.tags.measurement("multimeter.ac_volt_meter|dc_volt_meter.voltage")
class DMMAverage:
    def trigger(self, handler):
        handler.initiate()

    def wait(self, handler):
        handler.opc()
        handler.calc_average()

The elements mapped after kwargs will be used to initialise the corresponding instrument when required. For exemple, if a source is used as a voltage source, the statement handler = meavis_user.InitialiserB596X(mode="VOLT").intialise(/* */) will be executed.

This file have to be loaded as follow:

meavis.instruments.inject(meavis_user._meavis_instruments)

Note that it cannot be loaded multiple time, otherwise name collisions will happen.

Up to now the configuration is independant of what we want to measure: it only describes how to use instruments, but not how they are connect or what we want to do.

Experiment-specific configuration of intruments

First we describe how instruments are wired and for which purpose with a YAML file:

junction_bias:
  instrument: power_source
  usage: voltage_source
  kwargs:
    addr: 192.168.0.0
  attributes:
    channel: 1
junction_current:
  instrument: multimeter
  usage: dc_current_meter
  kwargs:
    host: 192.168.0.1
  attributes:
    channel: 1
junction_voltage:
  instrument: multimeter
  usage: dc_volt_meter
  kwargs:
    host: 192.168.0.1
  attributes:
    channel: 2

The elements mapped after kwargs will be used to construct the corresponding instrument when required. For exemple, the multimeter to measure the junction voltage is constructed with the statement: handler = meavis_user.ConstructorEthernet(host="192.168.0.1").create() when required. Morevoer the attribute channel: 2 is used for the initialisation handler = meavis_user.InitialiserB596X(/* */).intialise(/* */, channel=2).

This file have to be loaded as follow:

with open("instances.yaml") as file:
    meavis.instruments.register(yaml.safe_load(file))

Note that it cannot be loaded multiple time, otherwise name collisions will happen. After this step, parameters and measurements can be accessed as follow:

meavis.parameters.junction_current.aperture([10e-3])
meavis.parameters.junction_current.average_count([100])

meavis.parameters.junction_voltage.aperture([100e-3])
meavis.parameters.junction_voltage.average_count([10])

Avaibled parameters and measurements are displayed in the log output:

INFO --  Register power_source constructor [90e97748d6ea9cbb434602eb177a91c685701667] {host: 192.168.0.0}.
INFO --  Register voltage_source initialiser {mode: VOLT} for junction_bias.
INFO --  Register voltage as parameter named junction_bias.voltage.
INFO --  Register multimeter constructor [1ca226d3ca09e4167fbbfa3bd218a8323d76e12f] {host: 192.168.0.1}.
INFO --  Register dc_current_meter initialiser {mode: CURR, ACorDC: DC} for junction_current.
INFO --  Register aperture as parameter named junction_current.aperture.
INFO --  Register average_count as parameter named junction_current.average_count.
INFO --  Register current as measurement named junction_current.current.
INFO --  Register dc_volt_meter initialiser {mode: VOLT, ACorDC: DC} for junction_voltage.
INFO --  Register aperture as parameter named junction_voltage.aperture.
INFO --  Register average_count as parameter named junction_voltage.average_count.
INFO --  Register voltage as measurement named junction_voltage.voltage.
INFO --  Add completer group for junction_bias : {junction_bias.voltage}.
INFO --  Add completer group for junction_current : {junction_current.average_count, junction_current.aperture}.
INFO --  Add completer group for junction_voltage : {junction_voltage.aperture, junction_voltage.average_count}.

And finally the measurement can be described and processed as follow:

measurement_loop = meavis.loop.LoopEngine(
    yaml.safe_load(
        """
parameters:
    - junction_bias.voltage
measurements:
    - junction_current.current
    - junction_voltage.voltage
name: iv_dc_4probes
"""
)).create(
    meavis.parameters.junction_bias.voltage(numpy.linspace(-1e-3, 1e-3, 401)),
    meavis.measurements.junction_current.current(),
    meavis.measurements.junction_voltage.voltage(),
)
measurement_loop.trigger(None)
measurement_loop.wait(None)

In the log output, instruments are created and intialised when required:

INFO --  Complete parameters with [junction_current.average_count, junction_current.aperture]
INFO --  Complete parameters with [junction_voltage.aperture, junction_voltage.average_count]
INFO --  Create handler of multimeter.constructor [1ca226d3ca09e4167fbbfa3bd218a8323d76e12f] with {host: 192.168.0.1}.
INFO --  Initialise channel 2 on handler of multimeter.dc_volt_meter.initialiser with {mode: VOLT, ACorDC: DC}.
INFO --  Set junction_voltage.aperture to 0.1 s.
INFO --  Set junction_voltage.average_count to 10.
INFO --  Initialise channel 1 on handler of multimeter.dc_current_meter.initialiser with {mode: CURR, ACorDC: DC}.
INFO --  Set junction_current.aperture to 0.01 s.
INFO --  Set junction_current.average_count to 100.
INFO --  Create handler of power_source.constructor [90e97748d6ea9cbb434602eb177a91c685701667] with {host: 192.168.0.0}.
INFO --  Initialise channel 1 on handler of power_source.voltage_source.initialiser with {mode: VOLT}.
INFO --  Set junction_bias.voltage to -0.001 V.
INFO --  Trigger junction_current.current, waiting for data.
INFO --  Trigger junction_voltage.voltage, waiting for data.
INFO --  Set junction_bias.voltage to -0.000998 V.
INFO --  Trigger junction_current.current, waiting for data.
INFO --  Trigger junction_voltage.voltage, waiting for data.

API

meavis package

Measurement & Visualisation python framework.

Submodules

meavis.completer module

MeaVis parameters completion.

class meavis.completer.CompleterEngine(data)

Bases: object

Define how parameters of a loop has to be completed.

instances_parameters = {}

__init__(data)

Store a data structure as loop pattern.

classmethod clear()

Clear instances set.

classmethod inject_instances(instances)

Inject instances in CompleterEngine maps.

complete(instances=())

Complete a loop pattern.

meavis.instruments module

Main loop functions for running MeaVis measurements.

meavis.instruments.clear(module_name)

Clear injected names by users.

meavis.instruments.inject(instruments)

Inject instruments.

meavis.instruments.register(instances)

Inject instances.

meavis.loop module

Main loop functions for running MeaVis measurements.

class meavis.loop.LoopMeasurement(parameters, measurements)

Bases: object

Define a measurement running a loop.

__init__(parameters, measurements)

Ceate a loop measurement.

trigger(handler)

Nothing to trigger.

wait(handler)

Run the loop.

class meavis.loop.LoopEngine(data)

Bases: object

Define how a loop has to be processed.

items_map = {}

default_map = {'measurements': {'handler': None, 'initialiser': None, 'invasive': False}, 'parameters': {'current': None, 'delay': 0, 'handler': None, 'initialiser': None, 'unit': None}}

__init__(data)

Store a data structure as loop pattern.

classmethod clear()

Clear MeaVis item maps.

classmethod inject_items(*items)

Inject MeaVis items in the LoopEngine.

inject_defaults()

Inject default attributes in LoopEngine maps.

complete()

Complete current data structure.

create(*items, completion=True)

Create a measurement from the pattern.

synchronisers(state_parameters, completion=True)

Synchronise parameters group from the pattern.

meavis.markup module

Read and write MeaVis markup language.

meavis.markup.visit_instruments(meavis_instruments, tag_name, meavis_name)

Visit an instrument hierarchy and return corresponding items.

meavis.measurements module

MeaVis measurements namespace for user-defined injection.

meavis.measurements.inject(cls, name)

Wrap and inject user-defined measurement in this namespace.

meavis.parameters module

MeaVis parameters namespace for user-defined injection.

meavis.parameters.inject(cls, name)

Wrap and inject user-defined parameter in this namespace.

meavis.synchroniser module

Synchronisation of MeaVis parameters.

class meavis.synchroniser.LoopSynchroniser(state_parameters, loop_parameters, synchronisers)

Bases: object

Define a looper to pre-synchronise instruments.

__init__(state_parameters, loop_parameters, synchronisers)

Ceate a loop synchroniser.

pre_synchronise(states)

Run the loop.

meavis.tags module

Class decorators to tag MeaVis classes.

meavis.tags.add_metadata(metadata_name, **kwargs)

Add metadata to a tagged MeaVis class.

meavis.tags.add_item(tag_name, meavis_name, **kwargs)

Tag a MeaVis class.

meavis.tags.attributes(**kwargs)

Add attributes to a tagged MeaVis class.

meavis.tags.kwargs(**kwargs)

Add kwargs to a tagged MeaVis class.

meavis.tags.constructor(meavis_name, **kwargs)

Tag a class as a MeaVis initialiser.

meavis.tags.initialiser(meavis_name, **kwargs)

Tag a class as a MeaVis initialiser.

meavis.tags.measurement(meavis_name, **kwargs)

Tag a class as a MeaVis measurement.

meavis.tags.parameter(meavis_name, **kwargs)

Tag a class as a MeaVis parameter.

meavis.tasks module

MeaVis tasks for threading.

meavis.tasks.setup_and_acquire(meavis_item)

Set meavis_item handler if required.

meavis.tasks.settle(parameter, sample, lock_in, lock_out, delay=True)

Settle a parameter.

meavis.tasks.trigger_wait(measurement, lock_in, lock_out, lock_barrier)

Trigger & wait for a measurement.

ChangeLog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

Unreleased

Added

Change

Deprecated

Removed

Fixed

[0.2.1]

Added

• Basic IV measurement as first example.

• Loop completer for parameters.

• Tags mechanism.

Change

• Mapping inheritance for MeaVis Markup Language – Instrument.

• Constructor and Initialiser tags for MeaVis Markup Language – Instrument.

License

                   GNU LESSER GENERAL PUBLIC LICENSE
                       Version 3, 29 June 2007

 Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
 Everyone is permitted to copy and distribute verbatim copies
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