An offline deep reinforcement learning library
Project description
optinist ![optinist](https://pypi-camo.freetls.fastly.net/879f6be220237516f7e9e2f3a3843152e8014296/646f63732f5f7374617469632f6f7074696e6973742e706e67)
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
Support Developers
Project details
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Source Distribution
optinist-0.1.1.tar.gz
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