Read proprietary file formats from electrochemical test stations.
Use the MPRfile class from BioLogic.py (exported in the main package)
from galvani import BioLogic
import pandas as pd
mpr_file = BioLogic.MPRfile('test.mpr')
df = pd.DataFrame(mpr_file.data)Use the ./galvani/res2sqlite.py script to convert the .res file to a sqlite3 database with the same schema, which can then be interrogated with external tools or directly in Python.
For example, to extract the data into a pandas DataFrame (will need to be installed separately):
import sqlite3
import pandas as pd
from galvani.res2sqlite import convert_arbin_to_sqlite
convert_arbin_to_sqlite("input.res", "output.sqlite")
with sqlite3.connect("output.sqlite") as db:
df = pd.read_sql(sql="select * from Channel_Normal_Table", con=db)This functionality requires MDBTools to be installed on the local system.
The latest galvani releases can be installed from PyPI via
pip install galvaniThe latest development version can be installed with pip directly from GitHub (see note about git-lfs below):
GIT_LFS_SKIP_SMUDGE=1 pip install git+https://github.com/echemdata/galvaniWarning
This project uses Git Large File Storage (LFS) to store its test files,
however the LFS quota provided by GitHub is frequently exceeded.
This means that anyone cloning the repository with LFS installed will get
failures unless they set the GIT_LFS_SKIP_SMUDGE=1 environment variable when
cloning.
The full test data from the last release can always be obtained by
downloading the GitHub release archives (tar or zip), at
https://github.com/echemdata/galvani/releases/latest
If you wish to add test files, please ensure they are as small as possible, and take care that your tests work locally without the need for the LFS files. Ideally, you could commit them to your fork when making a PR, and then they can be converted to LFS files as part of the review.
If you wish to contribute to galvani, please clone the repository and install the testing dependencies:
git clone [email protected]:echemdata/galvani
cd galvani
pip install -e .\[tests\]Code can be contributed back via GitHub pull requests and new features or bugs can be discussed in the issue tracker.