MOOSE is the Multiscale Object-Oriented Simulation Environment. It is designed to simulate neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, circuits, and large networks. MOOSE can operate at many levels of detail, from stochastic chemical computations, to multicompartment single-neuron models, to spiking neuron network models.
MOOSE is multiscale: It can do all these calculations together. For example it handles interactions seamlessly between electrical and chemical signaling. MOOSE is object-oriented. Biological concepts are mapped into classes, and a model is built by creating instances of these classes and connecting them by messages. MOOSE also has classes whose job is to take over difficult computations in a certain domain, and do them fast. There are such solver classes for stochastic and deterministic chemistry, for diffusion, and for multicompartment neuronal models.
MOOSE is a simulation environment, not just a numerical engine: It provides data representations and solvers (of course!), but also a scripting interface with Python, graphical displays with Matplotlib, PyQt, and VPython, and support for many model formats. These include SBML, NeuroML, GENESIS kkit and cell.p formats, HDF5 and NSDF for data writing.
This is the core computational engine of MOOSE
simulator. This repository
contains C++ codebase and python interface called pymoose
. For more
details about MOOSE simulator, visit https://moose.ncbs.res.in .
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials and demo here https://github.com/BhallaLab/moose-examples.
To build pymoose
, follow instructions given in
INSTALLATION.md and for platform specific
information see:
- Linux: UbuntuBuild.md
- MacOSX: AppleM1Build.md
- Windows: WindowsBuild.md
Jhangri
is an Indian sweet
in the shape of a flower. It is made of white-lentil (Vigna mungo)
batter, deep-fried in ornamental shape to form the crunchy, golden
body, which is then soaked in sugar syrup lightly flavoured with
spices.
This release has the following major changes:
- Improved support for reading NeuroML2 models
HHGate2D
: separatexminA
,xminB
, etc. forA
andB
tables replaced by singlexmin
,xmax
,xdivs
,ymin
,ymax
, andydivs
fields for both tables.- Build system switched from cmake to meson
- Native binaries for Windows
- Updated to conform to c/c++-17 standard
- Various bugfixes
MOOSE is released under GPLv3.