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 --wheel
python -m pyc_wheel x.whl [optional]
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 ))
1 maintainer
Metadata
1 maintainer
Release files for ackl 2.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ackl-2.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Release files / ackl-2.2.2-py3-none-any.whl
| Download URL | ackl-2.2.2-py3-none-any.whl |
|---|---|
| Size | 751.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6af522ef2d12183fa1b037f0a56d1c6127901e4929e3df4491cc4f3b18e41414
|
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BLAKE2b-256 checksum How to use checksums |
0ee781eb166c353c0ab8c31bf8878433e3a674d1b48af252c084dc5f9b6a0b77
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.5
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Security for ackl 2.2.2
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