Mozaik is intended to improve the efficiency of computational neuroscience projects by relieving users from writing boilerplate code for simulations involving complex heterogenous neural network models, complex stimulation and experimental protocols and subsequent analysis and plotting.
Mozaik integrates the model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualization into a single automated workflow, ensuring that all relevant
meta-data are available to all workflow components. It is based on several widely used tools, including PyNN, Neo and Matplotlib. It offers a declarative way of specifying models and recording configurations, using hierarchically organized configuration files.
To install the stable 0.1 version run:
pip install mozaik
The code repository with the latest developmental version is at https://github.com/antolikjan/mozaik
The Mozaik homepage, with full documentation, is http://neuralensemble.org/mozaik/
Mozaik integrates the model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualization into a single automated workflow, ensuring that all relevant
meta-data are available to all workflow components. It is based on several widely used tools, including PyNN, Neo and Matplotlib. It offers a declarative way of specifying models and recording configurations, using hierarchically organized configuration files.
To install the stable 0.1 version run:
pip install mozaik
The code repository with the latest developmental version is at https://github.com/antolikjan/mozaik
The Mozaik homepage, with full documentation, is http://neuralensemble.org/mozaik/
