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Home Page: https://knarrow.readthedocs.io/en/latest/
License: Apache License 2.0
Shoot a knarrow to the knee
Home Page: https://knarrow.readthedocs.io/en/latest/
License: Apache License 2.0
There are 4 main types of trends in the data:
a simple infographics which help understand how the knees are numbered:
______________
| 2 ____ 3 |
| / \ |
| | | |
| | | |
| | | |
| \ ____ / |
| 1 4 |
______________
after detection there should be a conversion to a standard knee type (im in favour of 2)
Smooth the input data using smoothing cubic splines
https://data.princeton.edu/eco572/smoothing.pdf page 6 section 2.3
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.github/workflows/build-and-publish.yml
actions/setup-python v5
.github/workflows/lint-and-test.yml
actions/setup-python v5
pyproject.toml
cli/typer ==0.9.0
It would be awesome to write a cicd pipeline to run tests and coverage I've successfully setup at my local computer
The knee is to be defined as the point which is furthest from the y=x line on the y axis
this implies that x's and y's are scaled into a [0, 1] x [0, 1] domain, so such scaling should be performed in the method
also closes this
https://github.com/InCogNiTo124/knarrow/projects/1#card-70433054
mypy complains about a missing decorator typings so I should really spend some time to fix that
Split dataset in two parts, do OLS and measure R2
Consider speeding it up with raw numpy and not function invocations
Add kneedle from https://doi.org/10.1109/ICDCSW.2011.20
It seems no tests touch these lines: https://github.com/InCogNiTo124/knarrow/blob/master/src/knarrow/kneedle.py#L26,L52
this should be improved
By using various internet resources, I'm going to automatize the pypi release process with tbump
workflow:
I dislike pip-tools
and I belive poetry may be a better choice
Python 3.6 dropped
My own analytical method of finding the knee. More details in the future
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