Diffusion model for galaxy generation
Project description
Contains 4 generative diffusion models ScoreNet32 and ScoreNet64 for both the HSC and ZTF surveys. These are used to return the gradients of an arbitrary image with respect to a prior distribution of individual artifact free galaxy models. Current functions include ScoreNetXX(image) returns gradients as stated. Data transformatons are now done inside the package.
Project details
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
galaxygrad-0.1.6.tar.gz
(32.0 MB
view details)
Built Distribution
File details
Details for the file galaxygrad-0.1.6.tar.gz
.
File metadata
- Download URL: galaxygrad-0.1.6.tar.gz
- Upload date:
- Size: 32.0 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 54212ab2df4185a2a8723c5d59376a4d51369ef7dbc6bfce43448d76571574c9 |
|
MD5 | 6805d6baecd09c9120cfe809601d2d91 |
|
BLAKE2b-256 | 94aed09b4f6766dbf16cf97035ffa1fb84d16ad57be6a935d4f559e4ff3bbdf6 |
File details
Details for the file galaxygrad-0.1.6-py3-none-any.whl
.
File metadata
- Download URL: galaxygrad-0.1.6-py3-none-any.whl
- Upload date:
- Size: 32.0 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 00fcf670e38f0b48a3f000fbc84cc5964954b665068362804470de00d7ac547e |
|
MD5 | 224893cdb6333d9672b81b8cc017dc3c |
|
BLAKE2b-256 | 03f8f708a015cc3e0b6dde9da289c78594f66335e2c4ba94c84b99e9c4d790b0 |