DatAnalyzer (Python)

Notice: This is a Python version of DatAnalyzer tool. AI Assistant (Cursor) is heavy used in this transformation. Under development.

Tools to load, visualize, and analyse Multi-Electrode Array (MEA) field potential data using Python.

DatAnalyzer provides flexible, customizable semi-autonomous data analysis: good automatic settings to detect most peaks from large datasets, and the ability to refine results (e.g. add or remove peaks) programmatically or via future GUI tools.

Data format: MEA HDF5 (.h5) files. Measurement files must be converted to HDF5 first; for Multichannel Systems devices, use MultiChannel Data Manager.

Features

• Load raw MEA data from Multichannel Systems HDF5 (.h5) files
• MEA layout: read electrode layout and map electrode numbers to data columns
• Peak finding: semi-autonomous peak detection (low/high) with configurable rules (MinPeakValue, MaxBPM, MinPeakDistance)
• BPM update: peak-to-peak distances (ms), BPM per file/electrode, low vs high peak choice per channel
• BPM summary: Amount_of_peaks, BPM_avg, Amplitude_avg, normalizing, peak_distances

Requirements

• Python 3.8+
• numpy, scipy, h5py, pandas, matplotlib

Installation

git clone https://github.com/AnaHill/DatAnalyzer-Python.git
cd DatAnalyzer-Python
pip install -r requirements.txt

Optional, install as a package:

pip install -e .

Project layout

DatAnalyzer-Python/
├── README.md
├── requirements.txt
├── pyproject.toml
├── run_mea_analysis.py       # Example: load → find peaks → BPM summary
├── mea_layouts/
│   └── MEA_64_electrode_layout.txt
└── datanalyzer/
    ├── __init__.py
    ├── models.py
    ├── part1_raw_data_handling/   # HDF5 load, MEA layout
    ├── part2_peak_handling/       # find_peaks_in_loop, rules
    └── part3_data_handling_and_analyses/  # update_Data_BPM, create_BPM_summary

Usage

Command line

python run_mea_analysis.py /path/to/h5/folder --electrodes 21 28 31 51 --max-bpm 40 --min-peak-value 5e-5

From Python

from datanalyzer.part1_raw_data_handling import load_raw_mea_data_to_Data_and_DataInfo
from datanalyzer.part2_peak_handling import find_peaks_in_loop, set_default_filetype_rules_for_peak_finding
from datanalyzer.part3_data_handling_and_analyses import update_Data_BPM, create_BPM_summary

Data, DataInfo = load_raw_mea_data_to_Data_and_DataInfo(
    folder_of_files="/path/to/h5/folder",
    manually_chosen_mea_electrodes=[21, 28, 31, 51],
)
Rule = set_default_filetype_rules_for_peak_finding(frame_rate=float(DataInfo.framerate.flat[0]))
Rule.max_bpm = 40
Rule.min_peak_value = 5e-5
DataInfo.Rule = Rule
Data_BPM = find_peaks_in_loop(Data, DataInfo, Rule_in=Rule, data_multiply=-1)
Data_BPM = update_Data_BPM(DataInfo, Data_BPM, using_high_peaks=-1)
Data_BPM_summary = create_BPM_summary(DataInfo, Data_BPM)

Citations

DatAnalyzer has been developed at Tampere University (TAU) in the Micro- and Nanosystems Research Group (MST). If you find it useful, please consider citing:

• Mäki, A.-J. (2023). Opinion: The correct way to analyze FP signals. Zenodo. https://doi.org/10.5281/zenodo.10205591

License

See LICENSE file in the repository.