https://github.com/simonblanke/the-hyperactive-software-stack
https://github.com/simonblanke/the-hyperactive-software-stack
Last synced: about 13 hours ago
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- Host: GitHub
- URL: https://github.com/simonblanke/the-hyperactive-software-stack
- Owner: SimonBlanke
- License: mit
- Created: 2022-01-14T18:28:19.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-03-23T09:58:11.000Z (about 2 years ago)
- Last Synced: 2025-01-12T19:21:08.670Z (over 1 year ago)
- Language: Python
- Size: 16.6 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
The-Hyperactive-Software-Stack
## Shared data-structures
The hyperactive software stack builds upon some shared data-structures to reliably communicate between packages:
- objective-function
- A function that returns a single score or a tuple of a score and a dictionary. Its only argument is a dictionary in Gradient-Free-Optimizers and a more complex object that behaves like a dictionary in Hyperactive. This argument is often called `opt`, `para` or `access` in examples.
```python
# Hyperactive objective function
def parabola_function(access):
score = -(access["x"] * access["x"] + access["y"] * access["y"])
return score
```
- search-space
- A dictionary with the names of the dimensions as keys and the content of the dimensions as values. In Gradient-Free-Optimizers the values are numpy arrays and Hyperactive they are lists.
```python
# Hyperactive search space
search_space = {
"x": list(np.arange(-10, 10, 0.01)),
"y": list(np.arange(-10, 10, 0.01)),
}
```
- search-data
- The search-data always consists of the score and at least one parameter as columns and has as much rows as iterations performed during the optmization run.
score
x
y
0.756
0.1
0.2
0.823
0.3
0.1
...
...
...
...
...
...
## The official Hyperactive software stack
- [Hyperactive](https://github.com/SimonBlanke/Hyperactive)
- The central library for the Hyperactive software stack.
- [Gradient-Free-Optimizers](https://github.com/SimonBlanke/Gradient-Free-Optimizers)
- The optimization-backend for Hyperactive.
- [Surfaces](https://github.com/SimonBlanke/Surfaces)
- A collection of test-objective-functions.
- [Search Data Explorer](https://github.com/SimonBlanke/search-data-explorer)
- Dashboard to visually analyse saved search-data.
- [Simple Data Collector](https://github.com/SimonBlanke/simple-data-collector)
- Thread safe and atomic data collection into csv-files.