Candas2

This is a project inspired on the original Candas library by https://gist.github.com/JulianWgs, a blf file can be handle in a faster way using python data science classical libraries. This project is licensed under the GNU Affero General Public License (AGPL). By adopting this license, we ensure that any modifications or derivatives of this library are made publicly available, and that appropriate credit is given to the original

Installation

pip install candas2

Import module

import candas2

#BLF file loading The CAN file in BLF format is automatically converted into a DataFrame for subsequent processing. The blf filepath should be provided.

blf = Candas(r'C:\Users\Folder\file.blf')

ID Filtering

IDs are filtered to allow for targeted analysis, ensuring only relevant data is processed. id_filter --> str

blf.id_filtering(id_filter)

Time revision between each ID

The time interval between each ID is reviewed to ensure accurate temporal analysis and synchronization.

period_time(int) --> The time period between each ID, measured in milliseconds, is analyzed to ensure precise timing and synchronization in the data.

tolerance(int) --> As with all electronic instruments, a certain level of lag or tolerance is accounted for to ensure accurate data interpretation and analysis. It should be provided in a range from 0 to 100

blf.time_rev(period_time, tolerance)