pyplotter 0.3.8

A data browser and vizualizer for QCoDes database, csv, npz, s2p and BlueFors logging files.

pyplotter

A data browser and vizualizer for QCoDes database, csv, s2p and BlueFors logging files. The purpose of the plotter is to make data exploration as simple and fast as possible. You should never waste time to plot some raw, do some simple fit, ... and that's why the plotter do it for you.

⚙️ Getting Started

🔗 Requirements

Currently the following packages are required:

• qdarkstyle
• lmfit
• multiprocess
• numpy>=1.17.0
• pandas>=1.0.0
• platformdirs
• pyopengl
• pyqt5
• pyqt5-sip
• pyqtwebengine
• pyqtgraph>=0.12.3
• qcodes>=0.26.0
• scikit-rf
• scipy

Installation

Some users reported various issues with pyqt when using pyplotter in the general conda environment. While the reasons for these various issues aare still unknown, an easy way around it is to dedicate a conda environement to pyplotter. That way seems to keep pyqt happy.

First you create the conda environement

conda create --name pyplotter python=3.11
conda activate pyplotter

Second, install packages with conda

conda install pyqtgraph

Third, install pyplotter

git clone https://github.com/pyplotter/pyplotter
cd pyplotter
pip install -e .

🛠️ Use

The easiest way to launch the program is to search "plotter" in the window search bar and press enter.

Another solution is to open a terminal, type "plotter" and press enter.

Tip

• To open folders, databases, ... : use one click, no double click
• You may create a shortcut which target %windir%\System32\WindowsPowerShell\v1.0\powershell.exe -ExecutionPolicy ByPass -NoExit -Command "& 'C:\Users\****\Anaconda3\shell\condabin\conda-hook.ps1' ; conda activate 'C:\Users\****\Anaconda3'; conda activate python38; plotter"

Main window

Once the software is launched, you access the main window shown below

You can:

• browse in folders
• Open CSV/s2p files
• Open BlueFors log folder
• Open a QCoDeS database

When you select a QCoDeS database, you will display all its information as shown below

You may now click on a run to show its dependent parameters and its station

Extract run

You can directly extract run from the main windows by left clicking on a run

1d plot

To plot your data, check the dependent parameter you want to plot

You can plot as many dependent parameters as you want from the same run, see below

1d plot interactions

Many interactions with your curves are available.

For example the filter interaction. First you select the curve you want to interact with on the "Select curve" group box. Second you select the data you want to use for the interaction and then you click on the interaction you want, here "Savitsky-Golay".

Various model are available for fitting:

2d plot

To plot your data, check the dependent parameter you want to plot

2d ploimage.pngt interactions

Once a 2d plot is launched you can make slices of your data and launched 1d plot linked to your 2d plot. The linked 1d plot has the standard interactivity of a standard 1d plot.

Staring and hiding your run

The plotter allos the user to star or hide a run. To do so simply press "s" and "h" when you have selected a run. A star runs will then appear with a star while a hidden run will no be visible per default but will require the user to click on "Show hidden". This offers an easy way to hide "faulty" run and note "good" run but it doesn't replace a good old labbook.

Find a parameter in QCoDeS metadata

QCoDeS metadata consists of saving everything and while this is nice it makes the recovery of information quite delicate. In order to make this smoother the plotter allows the user to filter the visible metada by typing in the filter text field

Live plot mode

The plotter can also plot data during acquisition by using the livePlot check box. Simply choose a QCoDeS database and click on livePlot and any new run will be displayed as a standard 1d or 2d plot.

Compare data from different run

The plotter offers a way to compare any data already plotted in a 1d plot window. When at least two curves are plotted, an "Add curves" tab will appear allowing user to compare curves from different runs.

⚠️ Known issues

Read data taken by a newer QCoDeS version

QCoDeS ensures backward but not forward compatibility for the data which means that a database taken by a version "i" de QCoDeS can be read by another version "j" of QCoDeS only if "j>i". Otherwise the plotter will most likely have error like the following one:

Traceback (most recent call last):
  File "...\pyplotter\pyplotter\sources\loaddata.py", line 89, in run
    d = self.getParameterData(self.runId, paramsDependent['name'], self.signals.updateProgressBar, self.progressBarKey)
  File "...\pyplotter\pyplotter\sources\qcodesdatabase.py", line 743, in getParameterData
    ds =  load_by_id(run_id=int(runId), conn=conn)
  File "...\Anaconda3\envs\python37\lib\site-packages\qcodes\dataset\data_set.py", line 1228, in load_by_id
    d = DataSet(conn=conn, run_id=run_id)
  File "...\Anaconda3\envs\python37\lib\site-packages\qcodes\dataset\data_set.py", line 295, in __init__
    run_desc = self._get_run_description_from_db()
  File "...\Anaconda3\envs\python37\lib\site-packages\qcodes\dataset\data_set.py", line 559, in _get_run_description_from_db
    return serial.from_json_to_current(desc_str)
  File "...\Anaconda3\envs\python37\lib\site-packages\qcodes\dataset\descriptions\versioning\serialization.py", line 115, in from_json_to_current
    return from_dict_to_current(json.loads(json_str))
  File "...\Anaconda3\envs\python37\lib\site-packages\qcodes\dataset\descriptions\versioning\serialization.py", line 70, in from_dict_to_current
    desc = from_dict_to_native(dct)
  File "...\Anaconda3\envs\python37\lib\site-packages\qcodes\dataset\descriptions\versioning\serialization.py", line 63, in from_dict_to_native
    return run_describers[dct['version']]._from_dict(dct)
KeyError: 2

To solve the issue, just update your QCoDeS verion:

pip install --upgrade qcodes

👷🏼 Authors

• Etienne Dumur -main developer- [e-mail]

🕹️ License

MIT

🙏 Acknowledgments

• plottr, for the inspiration of some interfaces.
• pyqtgraph, for the amazing and fast plotting library.
• bokeh, for their work on the colormap palette reused here.
• qb style, for its color codes of lines.