Metadata-Version: 2.1
Name: knarrow
Version: 0.6.1
Summary: Shoot a knarrow to the knee
Home-page: https://github.com/InCogNiTo124/knarrow
Author: Marijan Smetko
Author-email: msmetko@msmetko.xyz
License: Apache License 2.0
Keywords: python
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Utilities
Classifier: Typing :: Typed
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# 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 also comes with a handy CLI:
```shell
$ cat data.txt | knarrow
stdin 11
$ cat data.txt | knarrow -o value
stdin 59874.14171519781845532648
$ knarrow --sort -d ',' -o value shuf_delim.txt
shuf_delim.txt 20
```

## 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 funcionality 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)
