discriminator-based inference for population genetics
Project description
Dinf is discriminator-based inference for population genetics. It uses a neural network to discriminate between a target dataset and a simulated dataset. Inference is done by finding simulation parameters that produce data closely matching the target dataset. Dinf provides a Python API for creating simulation models, and a CLI for discriminator training and inference.
See the documentation for details. https://racimolab.github.io/dinf/
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file dinf-0.5.0.tar.gz.
File metadata
- Download URL: dinf-0.5.0.tar.gz
- Upload date:
- Size: 353.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0a6d925dcc28bca8cfbd2bf8d3213ddf70646dfff814bd574068e6720e7f455f
|
|
| MD5 |
b6c221d201d04a7788d2d2bbc88f607e
|
|
| BLAKE2b-256 |
735d903805bf6d670056d36537ce5f35a6d87bd1c071881f88747f234d1000bf
|
File details
Details for the file dinf-0.5.0-py3-none-any.whl.
File metadata
- Download URL: dinf-0.5.0-py3-none-any.whl
- Upload date:
- Size: 64.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2431d711c3c4d0bbbfe1c76f66a36dbf1605f72646f80860f1f525de448ad61a
|
|
| MD5 |
7e2c15ae2edb248dc23ea7008367a0b6
|
|
| BLAKE2b-256 |
aed3312685e91c4d5f4b794f722e0e3e2e028e3cce6cdc3c25fe2a7c88000317
|
