medpc2excel 4.0.0

export medpc data to excel file and generate user defined variables

medpc2excel

medpc2excel is a Python package for converting single or multiple medpc data files into Excels. medpc2excel can also return a pandas DataFrame for further analysis

Installation

I recommend installing an Anaconda distribution of Python. The current validation target is Python 3.12. Use the package manager pip to install medpc2excel. The current version is 4.0.0

pip install medpc2excel==4.0.0

To install directly from GitHub and bypass PyPI, run:

pip install "git+https://github.com/cyf203/medpc2excel.git"

If you downloaded or installed the latest version of Anaconda or Miniconda, you can create a conda environment in your cmd. To do so:

conda env create --name <envname> --file=environments.yml

If conda has problem to install dependencies, you can also run:

pip install -r requirements.txt

Version updating note

Version 4.0.0 updates the package for Python 3.12, current pandas/openpyxl behavior, and more resilient handling of malformed MED-PC chunks.

Configure *.MPC file

Please include a medpc protocol file (*.MPC) that you used for behavior task. The file name of this MPC file should be the same as that of the medpc data file. The medpc2excel will open the medpc data file and automatically search the used *.MPC file in the same directory. In *.MPC file, please explicitly declare each array as below:

<... your MPC code...>

    DIM C =9999  \ Levertype                     
    DIM D =9999  \ PelHLON                       
    DIM E =9999  \ PelHLOFF   
    
<... your MPC code ...>

Naming and formatting medpc data file

Please make sure medpc data file is a 'file' but not not a '*.txt' file. If so, just remove *.txt at the end Please make sure the data file's name starts with some number. I usually keep a time tag like: '20240904_xxx' But it can also be any number like: '2000_xxx'

Running medpc2excel

The quickest way to start is to open the GUi from a command line terminal in Anaconda cmd prompt:

python -m medpc2excel

After installing the package, you can also launch the GUI directly with:

medpc2excel

You can use the data explorer tab to see the raster of each event.

You also can import this module and use the function called medpc_read as following

from medpc2excel.medpc_read import medpc_read

f = <file path>

ts_df, log = medpc_read(f, override = True, replace = False) # return a timestamp dataframe and a log string

Please download the Example folder to your local disk and run the medpc2excel_example.py to give a try.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.

Dependencies

numpy==2.4.1
pandas==2.3.3
openpyxl==3.1.5
matplotlib==3.10.8
mplcursors==0.7.1
PyQt5==5.15.10