Optimation v2.2
A flexible framework for variable weighting, quantum-inspired logic, and simplified modeling.
Features
- Variable Weighting
- Exponential/Quantum Logic
- Modeling: Variables, Objectives, Minimization
Example
from optimation import Variable, Model, Objective, minimize
x = Variable("x", 10)
y = Variable("y", 20)
def total(vars): return sum(v.value for v in vars)
model = Model()
model.add_variable(x)
model.add_variable(y)
model.add_objective(Objective(total))
print(minimize(model))
Release files for optimation 2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| optimation-2.2.tar.gz | 2.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| optimation-2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.0 kB
Release files / optimation-2.2.tar.gz
| Download URL | optimation-2.2.tar.gz |
|---|---|
| Size | 2.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.1.0 CPython/3.12.5
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Release files / optimation-2.2-py3-none-any.whl
| Download URL | optimation-2.2-py3-none-any.whl |
|---|---|
| Size | 3.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.12.5
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