A Python library for kernels used in analytical chemistry
Project description
ackl
Publication
Analytical chemistry kernel library for spectroscopic profiling data, Food Chemistry Advances, Volume 3, 2023, 100342, ISSN 2772-753X, https://doi.org/10.1016/j.focha.2023.100342.
PyPI (Python Package Index) repository
https://pypi.org/project/ackl/
Reproducible Code-Ocean capsule
https://doi.org/10.24433/CO.4614220.v2
Install (Ubuntu Env Setup)
!apt-get install r-base r-base-dev ffmpeg libsm6 libxext6
!pip install rpy2
!pip install qsi==0.3.9
!pip install ackl==1.0.2
!pip install cla==1.1.4
!pip install opencv-python
# Post-install script
#!/usr/bin/env bash
set -e
Rscript -e 'install.packages("ECoL")'
Compile
python -m build
Use
Kernel Response Patterns
import ackl.metrics
ackl.metrics.linear_response_pattern(20)
Run Kernels on Target Dataset
_, dics, _ = ackl.metrics.classify_with_kernels(X, y,embed_title = False)
Show the result as HTML table and bar charts:
html_str = ackl.metrics.visualize_metric_dicts(dics, plot = True)
display(HTML( html_str ))
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
ackl-2.1.0-py3-none-any.whl
(772.5 kB
view hashes)