semvec/pypi-packages huggingface dataset:
keras-quadopt 0.2.0
Solving quadratic optimization problems with Keras.
License: Apache License 2.0
Requires Python: >=3.7

[![PyPI version](https://badge.fury.io/py/keras-quadopt.svg)](https://badge.fury.io/py/keras-quadopt)
[![PyPi downloads](https://img.shields.io/pypi/dm/keras-quadopt)](https://img.shields.io/pypi/dm/keras-quadopt)
[![DOI](https://zenodo.org/badge/477837694.svg)](https://zenodo.org/badge/latestdoi/477837694)

# keras-quadopt: Solving Constrained Quadratic Optimization Problems with Reverse Automatic Differentation (Keras/TF2)
Solving quadratic optimization problems with resource constraints and upper boundaries using TF2/Keras.

## Usage

```py
import tensorflow as tf
import keras_quadopt as kqp
import time

# goodness scores
good = tf.constant([.51, .53, .55, .57])

# similarity matrices
simi_1 = tf.constant([
    [1, .9, .8, .7],
    [.9, 1, .6, .5],
    [.8, .6, 1, .4],
    [.7, .5, .4, 1],
])

simi_2 = tf.constant([
    [1, .7, .8, .3],
    [.7, 1, .4, .2],
    [.8, .4, 1, .6],
    [.3, .2, .6, 1],
])

# preference parameters
lam = 0.4
beta_1 = 0.25
beta_2 = 0.75

# compute weights
simi = kqp.aggregate_matrices(simi_1, beta_1, simi_2, beta_2)

start = time.time()
wbest, fbest = kqp.get_weights(good, simi, lam)
print(f"elapsed: {time.time() - start}")
```




## Appendix

### Installation
The `keras-quadopt` [git repo](http://github.com/ulf1/keras-quadopt) is available as [PyPi package](https://pypi.org/project/keras-quadopt)

```sh
pip install keras-quadopt
pip install git+ssh://git@github.com/ulf1/keras-quadopt.git
```

### Install a virtual environment

```sh
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt --no-cache-dir
pip install -r requirements-dev.txt --no-cache-dir
```

(If your git repo is stored in a folder with whitespaces, then don't use the subfolder `.venv`. Use an absolute path without whitespaces.)

### Python commands

* Check syntax: `flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')`
* Run Unit Tests: `PYTHONPATH=. pytest`

Publish

```sh
python setup.py sdist 
twine upload -r pypi dist/*
```

### Clean up 

```sh
find . -type f -name "*.pyc" | xargs rm
find . -type d -name "__pycache__" | xargs rm -r
rm -r .pytest_cache
rm -r .venv
```


### Support
Please [open an issue](https://github.com/ulf1/keras-quadopt/issues/new) for support.


### Contributing
Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/ulf1/keras-quadopt/compare/).

### Acknowledgements
The "Evidence" project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - [433249742](https://gepris.dfg.de/gepris/projekt/433249742) (GU 798/27-1; GE 1119/11-1).

### Maintenance
- till 31.Aug.2023 (v0.1.0) the code repository was maintained within the DFG project [433249742](https://gepris.dfg.de/gepris/projekt/433249742)
- since 01.Sep.2023 (v0.2.0) the code repository is maintained by Ulf Hamster.
scipy-quadopt 0.2.0
Wrapper and utility functions to apply scipy's SLSQP algorithm to quadratic optimization problems with resource constraints and upper boundaries.
License: Apache License 2.0
Requires Python: >=3.6

[![PyPI version](https://badge.fury.io/py/scipy-quadopt.svg)](https://badge.fury.io/py/scipy-quadopt)
[![PyPi downloads](https://img.shields.io/pypi/dm/scipy-quadopt)](https://img.shields.io/pypi/dm/scipy-quadopt)
[![DOI](https://zenodo.org/badge/355471428.svg)](https://zenodo.org/badge/latestdoi/355471428)

# scipy-quadopt: Quadratic optimization with constraints and upper boundaries
Wrapper and utility functions to apply scipy's SLSQP algorithm to quadratic optimization problems with resource constraints and upper boundaries.

## Usage

```py
import numpy as np
import scipy_quadopt as sqp

# goodness scores
good = np.array([.51, .53, .55, .57])

# similarity matrices
simi_1 = np.array([
    [1, .9, .8, .7],
    [.9, 1, .6, .5],
    [.8, .6, 1, .4],
    [.7, .5, .4, 1],
])

simi_2 = np.array([
    [1, .7, .8, .3],
    [.7, 1, .4, .2],
    [.8, .4, 1, .6],
    [.3, .2, .6, 1],
])

# preference parameters
lam = 0.4
beta_1 = 0.25
beta_2 = 0.75

# compute weights
simi = sqp.aggregate_matrices(simi_1, beta_1, simi_2, beta_2)
weights, _ = sqp.get_weights(good, simi, lam)
```

## Appendix

### Installation
The `scipy-quadopt` [git repo](http://github.com/ulf1/scipy-quadopt) is available as [PyPi package](https://pypi.org/project/scipy-quadopt)

```
pip install scipy-quadopt
pip install git+ssh://git@github.com/ulf1/scipy-quadopt.git
```

### Install a virtual environment

```
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt --no-cache-dir
pip install -r requirements-dev.txt --no-cache-dir
```

(If your git repo is stored in a folder with whitespaces, then don't use the subfolder `.venv`. Use an absolute path without whitespaces.)

### Python commands

* Jupyter for the examples: `jupyter lab`
* Check syntax: `flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')`
* Run Unit Tests: `PYTHONPATH=. pytest`

Publish

```sh
python setup.py sdist 
twine upload -r pypi dist/*
```

### Clean up 

```
find . -type f -name "*.pyc" | xargs rm
find . -type d -name "__pycache__" | xargs rm -r
rm -r .pytest_cache
rm -r .venv
```


### Support
Please [open an issue](https://github.com/ulf1/scipy-quadopt/issues/new) for support.


### Contributing
Please contribute using [Github Flow](https://guides.github.com/introduction/flow/). Create a branch, add commits, and [open a pull request](https://github.com/ulf1/scipy-quadopt/compare/).


### Acknowledgements
The "Evidence" project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - [433249742](https://gepris.dfg.de/gepris/projekt/433249742) (GU 798/27-1; GE 1119/11-1).

### Maintenance
- till 31.Aug.2023 (v0.1.2) the code repository was maintained within the DFG project [433249742](https://gepris.dfg.de/gepris/projekt/433249742)
- since 01.Sep.2023 (v0.2.0) the code repository is maintained by Ulf Hamster.