optinist 0.1.1

An offline deep reinforcement learning library

optinist

OptiNiSt(Optical Neuroimage Studio) helps researchers try multiple data analysis methods, visualize the results, and construct the data analysis pipelines easily and quickly. OptiNiSt's data-saving format follows NWB standards.

OptiNiSt also supports reproducibility of scientific research, standardization of analysis protocols, and developments of novel analysis tools as plug-in.

Key Features

:beginner: Easy-To-Create Workflow

• zero-knowledge of coding: OptiNiSt allows you to create analysis pipelines easily on the GUI.

:zap: Visualizing analysis results

• quick visualization: OptiNiSt supports you visualize the analysis results by plotly.

:rocket: Managing Workflows

• recording and reproducing: OptiNiSt records and reproduces the workflow pipelines easily.

Installation

Need anaconda or miniconda environment.

conda create -n optinist python=3.8
conda activate optinist

Install from pip.

pip install optinist

launch.

run_optinist

Documentation

https://optinist.readthedocs.io/en/latest/

Using GUI

Workflow

• OptiNiSt allows you to make your analysis pipelines by graph style using nodes and edges on GUI. Parameters for each analysis are easily changeable.

Visualize

• OptiNiSt allows you to visualize the analysis results with one click by plotly. It supports a variety of plotting styles.

Record

• OptiNiSt supports you in recording and reproducing workflow pipelines in an organized manner.

Contributors

Proposers

• Kenji Doya, OIST Neural Computation Unit
• Yukako Yamane, OIST Neural Computation Unit

Main Developers

• Shogo Akiyama
• Yoshifumi Takeshima

Support Developers

• Tatsuya Tanabe
• Yosuke Kaneko
• Syuya Saeki