scDiffEq: modeling single-cell dynamics using neural differential equations.
Project description
An analysis framework for modeling dynamical single-cell data with neural differential equations, most notably stochastic differential equations allow us to build generative models of single-cell dynamics.
Install the development package:
git clone https://github.com/mvinyard/sc-neural-diffeqs.git; cd ./sc-neural-diffeqs;
pip install -e .
Main API
import scdiffeq as sdq
from neural_diffeqs import NeuralSDE
model = sdq.models.scDiffEq(
adata, func=NeuralSDE(state_size=50, mu_hidden=[400, 400], sigma_hidden=[400, 400])
)
model.fit()
Built on:
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
scdiffeq-0.0.55.tar.gz
(100.5 kB
view details)
Built Distribution
scdiffeq-0.0.55-py3-none-any.whl
(162.1 kB
view details)
File details
Details for the file scdiffeq-0.0.55.tar.gz
.
File metadata
- Download URL: scdiffeq-0.0.55.tar.gz
- Upload date:
- Size: 100.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.12.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 39864ff42781c9cb0974668e004f8444389eea1bcd74d0ec4090a224edab149f |
|
MD5 | 07cf67623c2472ba08cf4e302c6b4983 |
|
BLAKE2b-256 | 9078915c8d72b048d26637d66b1672f78e3f1d37ca4acd6aff57b331365f5451 |
File details
Details for the file scdiffeq-0.0.55-py3-none-any.whl
.
File metadata
- Download URL: scdiffeq-0.0.55-py3-none-any.whl
- Upload date:
- Size: 162.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.12.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 315a3d5a7f44c6346ed9ec708dece7dc81a38712dfc2f99efe5100d42dfe4239 |
|
MD5 | daeae28e73f21c4810393d9db41761f5 |
|
BLAKE2b-256 | 34138d02215923ea21fafd4f9d5f1f851bcac220af88c9ffef6d7276b20e97ae |