Skip to main content

Boltzmann sampler tuner using convex optimisation.

Project description

## Paganini: Convex optimisation tuner for combinatorial systems

```
Install: python2 setup.py install
Usage: python2 paganini.py input.txt 1e-6
Usage: python2 paganini.py input.txt CVXOPT
Usage: python2 paganini.py input.txt SCS
Usage: python2 paganini.py input.txt ECOS
```

* `input.txt` is the name of the input file
with coefficients of algebraic
specifications
* `1e-6` is a float number corresponding to precision
* `[CVXOPT, SCS, ECOS]` stand for different convex optimization solvers.
ECOS is more preferrable for algebraic systems, SCS for rational.

## Example

Consider a system for marking abstractions in lambda-terms:

```
L = z L^2 + u z L + D
D = z + z D
```

We want to have `40%` of abstractions, so we encode all the variables and
functions into a single vector `[z, u, L, D]` and construct input file
```
2 1
0.4
3
1 1 1 0
1 0 2 0
0 0 0 1
2
1 0 0 0
1 0 0 1


Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

paganini-0.2955977425.tar.gz (4.5 kB view hashes)

Uploaded Source

Built Distribution

paganini-0.2955977425-py3-none-any.whl (5.2 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page