plotID 0.3.1

The plotID toolkit supports researchers in tracking and storing relevant data in plots. Plots are labelled with an ID and the corresponding data is stored.

plotID for Python

This is the python plotID project.
plotID is a program connected to Research Data Management (RDM). It has two main functionalities:

1. Tag your plot with an identifier.
2. Export the resulting file to a specified directory along the corresponding research data, the plot is based on. Additionally, the script that created the plot will also be copied to the directory.

Note: To run plotID python version ≥ 3.10 is required.

Installation

Currently there are two options to run plotID. Either install it via pip from the Python Package Index (PyPi) or install plotID from the source code.
Installation is the same for Windows and Unix systems, except for the optional first set of setting up a virtual environment.

1. [Optional] Create a virtual environment and activate it:

pip install venv
mkdir venv
python3 -m venv venv

source venv/bin/activate  # Unix

venv\Scripts\activate.bat # Windows Command Prompt
venv\Scripts\Activate.ps1 # Windows PowerShell

From PyPi with pip

2. Install plotID
   pip install plotid
   If you also want to run the unittests use plotid[test] instead of plotid.

From source

2. Download the source code from Gitlab:
   git clone https://git.rwth-aachen.de/plotid/plotid_python.git
cd plotid_python
3. Install dependencies
   pip install -r requirements.txt
4. Install plotID
   pip install .

Usage

plotID has two main functionalities:

1. Tag your plot with an identifier.
2. Export the resulting file to a specified directory along the corresponding research data, the plot is based on. Additionally, the script that created the plot will also be copied to the directory.

tagplot()

Tag your figure/plot with an ID. It is possible to tag multiple figures at once.
tagplot(figures, plot_engine)
The variable "figures" can be a single figure or a list of multiple figures.
The argument "plot_engine" defines which plot engine was used to create the figures. It also determines which plot engine plotID uses to place the ID on the plot. Currently supported plot engines are:

• matplotlib, which processes figures created by matplotlib.
• image, which processes pictures files with common extensions (jpg, png, etc.).

tagplot returns a PlotIDTransfer object that contains the tagged figures and the corresponding IDs as strings.

Optional parameters can be used to customize the tag process.

• figure_ids: list of str, optional IDs that will be printed on the plot. If empty, IDs will be generated for each plot. If this option is used, an ID for each plot has to be specified. Default: [].
• prefix : str, optional Will be added as prefix to the ID.
• id_method : str, optional id_method for creating the ID. Create an ID by Unix time is referenced as "time", create a random ID with id_method="random". The default is "time".
• location : string, optional Location for ID to be displayed on the plot. Default is "east".
• qrcode : boolean, optional Experimental support for encoding the ID in a QR Code.
• id_on_plot : boolean, optional Print ID on the plot. Default: True.

Example:

FIG1 = plt.figure()  
FIG2 = plt.figure()   
FIGS_AS_LIST = [FIG1, FIG2]  
FIGS_AND_IDS = tagplot(FIGS_AS_LIST, "matplotlib", prefix="XY23_", id_method="random", location="west")

publish()

Save plot, data and measuring script. Modules that are imported in the script which calls plotID are exported to the file "required_imports.txt". These can later be installed via pip with the command pip install -r /path/to/required_imports.txt. It is possible to export multiple figures at once. publish(figs_and_ids, src_datapath, dst_path)

• figs_and_ids must be a PlotIDTransfer object. Therefore, it can be directly passed from tagplot() to publish().
• src_datapath specifies the path to (raw) data that should be published. It can be a string or a list of strings that specifies all files and directories which will be published.
• dst_path is the path to the destination directory, where all the data should be copied/exported to.
• plot_names will be the file names for the exported plots. If you give only one plot name but several figures, plotID will name the exported plots with an appended number, e.g. example_fig1.png, example_fig2.png, ...

Optional parameters can be used to customize the publish process.

• data_storage: str, optional
  Method how the data should be stored. Available options:
  • centralized: The raw data will copied only once. All other plots will reference this data via sym link.
  • individual: The complete raw data will be copied to a folder for every plot, respectively.
• plot_names : str or list of str, optional Name for the exported plot. If not provided, the corresponding IDs will be used. Example: publish(figs_and_ids, "/home/user/Documents/research_data", "/home/user/Documents/exported_data", plot_names=["EnergyOverTime-Plot", "TimeOverEnergy-Plot")

Build

If you want to build plotID yourself, follow these steps:

1. Download the source code from Gitlab:
   git clone https://git.rwth-aachen.de/plotid/plotid_python.git
cd plotid_python
2. [Optional] Create a virtual environment (see Installation).
3. [Optional] Run unittests and coverage:
   python3 tests/runner_tests.py
4. Build the package python3 -m build

Contributing

Contributions to plotID are very welcome. If you encounter any issues with plotID please report them in our issue tracker. Code contributions via merge request are also highly appreciated. Please have a look at CONTRIBUTING first.

To install all optional dependencies use pip install .[test,docs] or pip install plotid[test,docs] respectively.

Documentation

If you have more questions about plotID, please have a look at the documentation.
Also have a look at the examples that are shipped with plotID.

Acknowledgements

This software is being developed at the Chair of Fluid Systems (FST), TU Darmstadt within the project NFDI4Ing.

The authors would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number 442146713.