| Name | ssm-simulators JSON |
| Version |
0.8.3
JSON |
| download |
| home_page | None |
| Summary | SSMS is a package collecting simulators and training data generators for a bunch of generative models of interest in the cognitive science / neuroscience and approximate bayesian computation communities |
| upload_time | 2024-12-23 21:57:52 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <=3.12,>=3.10 |
| license | None |
| keywords |
simulators
generative models
cognitive science
neuroscience
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# SSMS (Sequential Sampling Model Simulators)
Python Package which collects simulators for Sequential Sampling Models.
Find the package documentation [here](https://alexanderfengler.github.io/ssm-simulators/).
[](https://github.com/ambv/black)
[](https://opensource.org/licenses/MIT)
### Quick Start
The `ssms` package serves two purposes.
1. Easy access to *fast simulators of sequential sampling models*
2. Support infrastructure to construct training data for various approaches to likelihood / posterior amortization
We provide two minimal examples here to illustrate how to use each of the two capabilities.
#### Install
Let's start with *installing* the `ssms` package.
You can do so by typing,
`pip install ssm-simulators`
in your terminal.
Below you find a basic tutorial on how to use the package.
#### Tutorial
Check the basic tutorial [here](docs/basic_tutorial/basic_tutorial.ipynb).
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