Project Name: Simple_DAQ

Table of Contents

1. Introduction
2. Installation
   • Graphical Interface Guide
   • Command-line Guide
3. Features
4. Usage
   • Quick Start
   • Advanced Usage
   • PicoVNA108
5. FAQ
6. Contributing

Introduction

Simple_DAQ is a Python-based, user-friendly interface tailored for data acquisition from prevalent instruments in the Henriksen lab.

This project draws inspiration from an earlier LabVIEW version of SimpleDAQ.vi that was a staple in the Henriksen lab. The decision to reimagine it stemmed from recurring challenges faced with the LabVIEW iteration: transferring it between PCs often led to failures due to broken dependencies with sub VIs. Additionally, integrating new instrument drivers became a challenge when manufacturers lacked a robustly written one.

Installation

Graphical Interface Guide

1. Download the Simple_DAQ Repository

• Visit the Simple_DAQ GitHub repository.
• Click on the green Code button on the right.
• Choose Download ZIP.
• Once downloaded, extract the ZIP file to a location of your choice.

2. Install Anaconda

Anaconda is a popular distribution of Python that simplifies package management and deployment.

• Download Anaconda for your operating system.
• Follow the installation instructions for your operating system from the Anaconda installation guide.

3. Setting Up a Virtual Environment with Anaconda Navigator

Anaconda Navigator is a GUI tool that comes with the Anaconda distribution.

1. Open Anaconda Navigator from your applications or programs list.
2. Click on Environments on the left sidebar.
3. Click on Create at the bottom.
4. Name it simple_daq_env and choose the Python version you want (e.g., 3.X). Click on the Create button.
5. After the environment is created, make sure it's activated (should be highlighted in green).

4. Setting Up Your IDE and Installing Dependencies

For PyCharm:

1. Open PyCharm and choose Open to load the Simple_DAQ directory you extracted from the ZIP file.
2. Once the project is open, navigate to File > Settings (or Preferences on macOS) > Project: Simple_DAQ > Python Interpreter.
3. Click on the gear icon and choose 'Add'.
4. From the left pane, select 'Conda Environment' and then 'Existing environment'.
5. Select the interpreter from the simple_daq_env environment you created in Anaconda Navigator. The path would typically be in the Anaconda directory under envs/simple_daq_env/bin/python.
6. To automatically install the required packages, navigate to Tools in the top menu and select Sync Python Requirements. This will read the requirements.txt file and install all necessary packages.

For VSCode:

1. Open the Simple_DAQ directory (that you extracted from the ZIP file) in VSCode.
2. Press Ctrl + Shift + P to open the command palette.
3. Type and select "Python: Select Interpreter".
4. Choose the interpreter from the simple_daq_env environment you created in Anaconda Navigator.
5. Open the terminal in VSCode (View > Terminal) and type:

pip install -r requirements.txt

Command-line Guide

1. Clone the Repository

To get started, first clone the Simple_DAQ repository from GitHub:

git clone https://github.com/Henriksen-Lab/Simple_DAQ.git

Navigate to the cloned directory:

cd Simple_DAQ

2. Set Up a Virtual Environment

Using Python's built-in venv:

# Using venv module for Python
python -m venv venv

# Activate the virtual environment
# For Windows
venv\Scripts\activate

# For macOS and Linux
source venv/bin/activate

Using Anaconda (if installed):

conda create --name simple_daq_env python=3.X
conda activate simple_daq_env

Replace 3.X with your desired Python version.

3. Install Dependencies

To install the required packages,

pip install -r requirements.txt

Features

While the Python version maintains the UI style of the original LabVIEW version, it introduces several enhancements to improve user convenience.

• Configuration Management:

  • Save: The Measurement Set-up window captures the current settings as a screenshot and saves it to a designated folder. The file is named [Filename]_Simple_DAQ_config and is saved whenever the Save config or Run buttons are pressed.
  • Load: You can revert to previous settings at any time by using the Load config button. This feature is especially handy for reviewing past measurement configurations or for initiating new measurements with similar settings.

• Real-Time Data Visualization:

  The Realtime plotting window provides live data visualization, allowing you to see measurements as they are being taken.

• Instant Data Backup:

  Within the Realtime plotting panel, a special button allows you to quickly save the visualized data. The saved data is named temp and stored in a designated folder. This function is beneficial for safeguarding against potential data loss, such as accidental file corruption (which might occur if files are being synced to cloud storage while concurrently being modified by the program). It also provides a method to keep a separate copy of continuous data.

Usage

Quick Start

1. Safety First:

   • Before initiating any measurements, ensure you're knowledgeable about the equipment and the measurements you're planning. Ensure connections are correct and that the readings are sensible. Proceeding without this confirmation can lead to wasted time and inaccurate data.

2. Initial Setup:

   • Begin by following the installation instructions provided.
   • In your IDE, execute the Simple_DAQ_beta.py file. Two windows named Specify your measurement below and Realtime plotting will appear.

3. Measurement Specification Window:

   • This window primarily contains three fields: Instrument, File, and Sweep.

4. File Configuration:

   

   • Determine a File name for your data.

   • Specify the Folder path where data should be saved.

   • Determine the order of your files. Input should be an integer. E.g., default data will save as name_me_please.001.

     Note: If a file with the same name and order already exists, the program will automatically increment the order by one to prevent overwriting.

   • Set the File size. Input should be an integer. This represents the number of data points the program will save at once. E.g., an input of 1000 means the data file will be updated after 1000 data points are acquired.

   • Specify the Data interval, using a positive float number. This defines the time gap between successive instrument value queries.

   • Use the My note field to document any relevant information about the device or physical setup. This helps in future data analysis.

5. Instrument Configuration:

   • The far-left block is reserved for VNA-type instruments. Remaining blocks are for instruments that return a single value.

   

   • Assign a Variable name which will represent this in your data set.

   • Fill in the Visa address, verifiable via NI MAX software or Visa_troubleshooting.py.

   • Choose your Instrument_name and Function_selection for specific data recording.

     Note: To avoid VISA communication issues, only one instrument is communicated with at any given time.

6. Sweep Configurations:

   • This panel contains: Main loop, Secondary loop, and PID control.

   • For a single parameter sweep, fill in the Main loop:

     

     • Instrument settings mirror those in the instrument panel.
     • Sweep settings include Start, Stop, Sweep step size, and Delay time.
     • Toggles include:
       • Log scale?: Toggles between linear and ratio sweeps. With this enabled, Sweep step size changes to Ratio between steps. A value greater than 1 is advised.
       • Sweep back?: Returns the sweep to the start point. Additional configurations like Back step and Back delay are available for costumizing, or it keeps to original settings.
     • Click Time estimate to view an estimated duration for the sweep.

   • For a double parameter sweep, use both the Main loop and Secondary loop. The program completes the entire secondary loop for every main loop step.

   • Use PID control for temperature regulation. Options here include IceT noise setup and NV transfer setup.

7. Initiating the Measurement

   Once you click the Run button, your IDE will display a sequence of status updates, which might include:

   Measurement loaded
   Monitor functioning            # Displayed when no sweep is set up.
   Single Sweep Starting          # Displayed for Mainloop sweep configuration.
   Double Sweep Started           # Displayed when both Mainloop and Secondary loop configurations.

   Over time, as the data files are created or updated, you'll notice additional messages like:

   2023.08.16      11:16:36        name_me_please.001
   Data file created.
   2023.08.16      11:26:36        name_me_please.001
   Data file updated.
   2023.08.16      11:36:36        name_me_please.001
   Data file updated.

8. Visualizing Data with the Plot Window

   Select Data:

   • Navigate to data_selector to specify the data category you'd like to visualize. Your options might be:
     • data: Represents data to be saved in files
     • sweep: Refers to internal record for you sweep parameters
     • pid: Indicates the temp log from the PID set up

   Define Axes:

   • Determine which parameters you want on the X1 and Y1 axes for your graph.

   Begin Visualization:

   • Click on Start plotting. A live-updating plot will subsequently appear on the right side of the screen.

Advanced Usage

1. Visa_troubleshooting.py

This tool is particularly useful when you need to test individual instruments or make simultaneous manual adjustments. Its primary purpose is to validate the connection and assess the functionality of a single instrument.

2. Datafile editor.py

When you've captured data on different computers and wish to synchronize their timestamps, this tool comes to the rescue. It efficiently concatenates identically formatted data (with matching axes) found within a folder. By comparing diverse timestamps, it aligns data and then exports the newly consolidated data to the specified folder.

3. Instrument_Drivers

• Instrument_dict.py: This contains the nomenclature and functionalities associated with the drivers.

To Incorporate Additional Instruments or Functions:

1. Start by editing or adding the desired function/driver within the Instrument_Drivers directory.

2. If you're introducing a new driver:

• Import the new driver in Instrument_dict.py

3. Integrating a New Driver or Function:

Whenever you add a new driver or function:

• Update the get_value() and set_value() functions in Instrument_dict.py to accommodate the new additions.

• Make appropriate modifications to the instrument_dict in Instrument_dict.py.

For Instance:

Suppose you've created a new driver, SampleInstrument.py, housing several functions like follows, and you've placed this in the Instrument_Drivers directory.

def SampleInstrument_get_random1(address):
    ...
    return value

def SampleInstrument_get_random2(address):
    ...
    return value

def SampleInstrument_set_random3(address, value):
    ...

def SampleInstrument_set_random4(address, value):
    ...

To integrate this in Instrument_dict.py, proceed as follows:

• Incorporate the new driver by adding:

from SampleInstrument import *

• Enhance the instrument_dict to include the new functions:

instrument_dict['get'].update({SampleInstrument: ['random1', 'random2']})
instrument_dict['set'].update({SampleInstrument: ['random3', 'random4']})

• Embed the new functions into the get_value and set_value procedures:

def get_value(address='', name='', func='', **kwargs):  # Extend this function
    ...
    elif name == 'SampleInstrument':
        if func == 'random1':
            value = SampleInstrument_get_random1(address)
        elif func == 'random2':
            value = SampleInstrument_get_random2(address)

def set_value(value, address='', name='', func='', **kwargs):  # Expand this function
    ...
    elif name == 'SampleInstrument':
        if func == 'random3':
            SampleInstrument_set_random3(address, value)
        elif func == 'random4':
            SampleInstrument_set_random4(address, value)

4. Before pushing your changes to GitHub (and please do so if you add new drivers/functions), ensure that the Visa_troubleshooting.py correctly displays the intended readouts or causes the instrument to behave as desired.

Folder Tree

├── Simple_DAQ_beta.py
├── Visa_troubleshooting.py
├── Datafile editor.py
├── UI_manager
│   ├── DataManager.py
│   └── _ini_.py
├── Customized
│   ├── LYW_plot_universal.py
│   ├── SD_picoVNA_py32bit.py
│   ├── SD_plot
│   │   ├── SD_FigureFormat.py
│   │   ├── SD_Func.py
│   │   ├── SD_LoadData.py
│   │   ├── SD_plot_universal.py
│   │   ├── __pycache__
│   │   └── _ini_.py
│   └── SD_pywin32error.sh
├── requirments.txt
├── README.md
├── LICENSE
├── Instrument_Drivers
│   ├── _ini_.py
│   ├── FileManager.py
│   ├── Instrument_dict.py
│   ├── Agilent_infiniVision.py
│   ├── DC205.py
│   ├── E4405B.py
│   ├── Keysight_U2741A.py
│   ├── PicoVNA108
│   │   ├── PicoVNA108.py
│   │   ├── pywin32-env
│   ├── PicoVNA Python Wrapper(folded)
│   ├── SR124.py
│   ├── SR770.py
│   ├── SR830.py
│   ├── hp34461A.py
│   ├── keithley.py
│   ├── keithley2230G_30_1.py
│   ├── keysightN6700c.py
│   ├── thermometer
│   │   ├── _ini_.py
│   │   ├── RuOx.py
│   │   └── Cernox.py
│   ├── noise_probe_PID.py
│   ├── noise_probe_arduino_control.py
│   ├── Arduino_run_noise_probe
│   │   └── Arduino_run_noise_probe.ino
│   ├── transfer_heater_PID.py
│   ├── transfer_heater_arduino_comm.py
│   ├── Arduino_run_transfer_Heater
│   │   └── Arduino_run_transfer_Heater.ino
│   └── vna_analysis.py
└── older reference(folded)

PicoVNA108

PicoVNA 108 is a peculiar instrument to query because the python warpper the instrument uses bases on pywin32 package and only function in Python 32bit ver, which means you might need to separately install a 32 bit python for the instrument. There are serveral more steps to prepare if you want to install picovna 3 and talk to it through python on a new PC

1. Install the PicoVNA 3 Software

The step is required even if you don't want to use the software built by manufactor, because only after installation, the instrument would be registered in registry and thus to be accessed. You could find the installation package in ~\Instrument_Drivers\PicoVNA_InitialSetup\picovna3_exe_install.exe. After installation, the folder in Document should have content as a example shown in ~\Instrument_Drivers\PicoVNA_InitialSetup\picovna3_exe_install\PicoVNA3_whatItShouldLookLikeAfterInstall. You could run the program to check if the software is correctly installed

2. Run python warpper

For PicoVNA 3 usage, run ~\Instrument_Drivers\PicoVNA_InitialSetup\PICOVNA_pythonWarpper\9B7C3137-F2BB-4D8E-9FDB-450B6D527E5Ex0x1x0.py under Python 32bit environment with pywin32 pre-installed(or use the embeded python 32 bit package at ~\Instrument_Drivers\PicoVNA108\pywin32-env). No error should show up at this step if python installed correctly.

3. Find Picovna in registry(Not necessary if no error pops)

Bring the registry up by press win + R on keyboard and type in regedit in the pop-up window at bottom left. Look for items with format Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Classes\PicoControl3[].PicoVNA_3[] like the following:

Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Classes\PicoControl3.PicoVNA_3 Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Classes\PicoControl3.PicoVNA_3_1 Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Classes\PicoControl3.PicoVNA_3_2 Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Classes\PicoControl3_1.PicoVNA_3_1 Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Classes\PicoControl3_2.PicoVNA_3_2

Now go to the function you call for smith data get_picoVNA_smith (details of the function in ~\Instrument_Drivers\PicoVNA108.py), change the arg picoVNA="PicoControl3.PicoVNA_3". Change "PicoControl3.PicoVNA_3" by testing the conbination of in your registry and see which one gave you response PicoControl3[].PicoVNA_3[]. Usually one of them would work out.

4. If you encounter has no attribute 'CLSIDToClassMap' or other random error at one point

try this one by one if previous not working:

• re-run the program
• restart the equipment
• Run this command in WindowPowerShell as Administrator:

Remove-Item -path $env:LOCALAPPDATA\Temp\gen_py -recurse

FAQ

Problems you may encounter and possible solution:

• Q: What to do if error messages show up with pyvisa.errors.VisaIOError or something similar?
  • A: Check you GPIB/Usb connection and visa addressesa. Make sure you can see the instrument in NI MAX softerware with the same Visa address as your input.

Contributing

Xinyi Du (Shilling) (2021-2024)