https://github.com/incognito124/knarrow

Shoot a knarrow to the knee
https://github.com/incognito124/knarrow

elbow knee machine-learning optimization python python3

Last synced: about 1 year ago
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Shoot a knarrow to the knee

• Host: GitHub
• URL: https://github.com/incognito124/knarrow
• Owner: InCogNiTo124
• License: apache-2.0
• Created: 2021-09-20T16:39:14.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2025-02-27T23:35:00.000Z (over 1 year ago)
• Last Synced: 2025-03-27T06:44:56.471Z (over 1 year ago)
• Topics: elbow, knee, machine-learning, optimization, python, python3
• Language: Python
• Homepage: https://knarrow.readthedocs.io/en/latest/
• Size: 179 KB
• Stars: 18
• Watchers: 1
• Forks: 0
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

          
# knarrow

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Shoot a `knarrow` to the knee ;)

_(The lib is better than this pun, I swear.)_

Detect knee points in various scenarios using a plethora of methods

## Usage

Just plug in your values in a `list`, `tuple` or an `np.ndarray` and watch `knarrow` hit the knee:

```pycon

>>> from knarrow import find_knee

>>> find_knee([1, 2, 3, 4, 6])  # use a list

3

>>> find_knee((1, 2, 3, 4, 6))  # or a tuple

3

>>> import numpy as np

>>> y = np.array([1.0, 1.05, 1.15, 1.28, 1.30, 2.5, 3.6, 4.9])

>>> find_knee(y)  # provide just the values

4

>>> x = np.arange(8)

>>> find_knee(x, y)  # or both x and y

4

>>> A = np.vstack((x, y))

>>> A

array([[0.  , 1.  , 2.  , 3.  , 4.  , 5.  , 6.  , 7.  ],

       [1.  , 1.05, 1.15, 1.28, 1.3 , 2.5 , 3.6 , 4.9 ]])

>>> find_knee(A)  # works with x in first row, y in the second

4

>>> A.T

array([[0.  , 1.  ],

       [1.  , 1.05],

       [2.  , 1.15],

       [3.  , 1.28],

       [4.  , 1.3 ],

       [5.  , 2.5 ],

       [6.  , 3.6 ],

       [7.  , 4.9 ]])

>>> find_knee(A.T)  # also works with x in the first column, y in the second column

4

>>> find_knee(x, y, smoothing=0.01)  # for better results use cubic spline smoothing

4

```

### CLI

This library can also come with a handy CLI if you install it with the `cli` extra:

```shell

$ pip install "knarrow[cli]"

$ cat data.txt | knarrow -

 11

$ cat data.txt | knarrow -o value -

 59874.14171519781845532648

$ knarrow --sort -d ',' -o value shuf_delim.txt

shuf_delim.txt 20

```

_(the `-` for stdin is, unfortunately, mandatory)_

Try writing `knarrow --help` for more info.

## Similar projects

While I've come up with most of these methods by myself, I am not the only one. Here is a (non-comprehensive) list of projects I've found that implement a similar functionality and may have been an inspiration for me:

- [mariolpantunes/knee](https://github.com/mariolpantunes/knee)

Note: this project was bootstrapped by [python-blueprint](https://github.com/johnthagen/python-blueprint). Since then, it has been heavily modified, though.