<h1 align='center'>BrainUnit</h1>
<h2 align='center'>Physical units and unit-aware math system for general-purpose brain dynamics modeling</h2>
<p align="center">
<img alt="Header image of brainunit." src="https://raw.githubusercontent.com/chaobrain/saiunit/main/docs/_static/brainunit.png" width=30%>
</p>
<p align="center">
<a href="https://pypi.org/project/brainunit/"><img alt="Supported Python Version" src="https://img.shields.io/pypi/pyversions/brainunit"></a>
<a href="https://github.com/chaobrain/brainunit/blob/main/LICENSE"><img alt="LICENSE" src="https://img.shields.io/badge/License-Apache%202.0-blue.svg"></a>
<a href='https://brainunit.readthedocs.io/en/latest/?badge=latest'>
<img src='https://readthedocs.org/projects/brainunit/badge/?version=latest' alt='Documentation Status' />
</a>
<a href="https://badge.fury.io/py/brainunit"><img alt="PyPI version" src="https://badge.fury.io/py/brainunit.svg"></a>
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</p>
[BrainUnit](https://github.com/chaobrain/brainunit) provides physical units and unit-aware mathematical system in JAX for brain dynamics modeling. It introduces rigoirous physical units into high-performance AI-driven abstract numerical computing.
BrainUnit is initially designed to enable unit-aware computations in brain dynamics modeling (see our [BDP ecosystem](https://ecosystem-for-brain-dynamics.readthedocs.io/)). However, its features and capacities can be applied to general domains in scientific computing and AI4Science. Starting in 2025/02, BrainUnit has been fully integrated into [SAIUnit](https://github.com/chaobrain/saiunit) (the **Unit** system for **S**cientific **AI**).
Functionalities are the same for both ``brainunit`` and ``saiunit``, and their functions and data structures are interoperable, sharing the same set of APIs, and eliminating any potential conflicts. This meas that
```python
import brainunit as u
```
equals to
```python
import saiunit as u
```
For users primarily engaged in general scientific computing, `saiunit` is likely the preferred choice. However, for those focused on brain modeling, we recommend `brainunit`, as it is more closely aligned with our specialized brain dynamics programming ecosystem.
## Documentation
The official documentation of BrainUnit is hosted on Read the Docs: [https://brainunit.readthedocs.io](https://brainunit.readthedocs.io)
## Features
`brainunit` can be seamlessly integrated into every aspect of our [brain dynamics programming ecosystem](https://ecosystem-for-brain-dynamics.readthedocs.io/), such as, the checkpointing of [braintools](https://github.com/chaobrain/braintools), the event-driven operators in [brainevent](https://github.com/chaobrain/brainevent), the state-based JIT compilation in [brainstate](https://github.com/chaobrain/brainstate), online learning rules in [brainscale](https://github.com/chaobrain/brainscale), or event more.
A quick example for this kind of integration:
```python
import braintools
import brainevent.nn
import brainstate
import brainunit as u
class EINet(brainstate.nn.Module):
def __init__(self):
super().__init__()
self.n_exc = 3200
self.n_inh = 800
self.num = self.n_exc + self.n_inh
self.N = brainstate.nn.LIFRef(
self.num, V_rest=-60. * u.mV, V_th=-50. * u.mV, V_reset=-60. * u.mV,
tau=20. * u.ms, tau_ref=5. * u.ms,
V_initializer=brainstate.init.Normal(-55., 2., unit=u.mV)
)
self.E = brainstate.nn.AlignPostProj(
comm=brainevent.nn.FixedProb(self.n_exc, self.num, 0.02, 0.6 * u.mS),
syn=brainstate.nn.Expon.desc(self.num, tau=5. * u.ms),
out=brainstate.nn.COBA.desc(E=0. * u.mV),
post=self.N
)
self.I = brainstate.nn.AlignPostProj(
comm=brainevent.nn.FixedProb(self.n_inh, self.num, 0.02, 6.7 * u.mS),
syn=brainstate.nn.Expon.desc(self.num, tau=10. * u.ms),
out=brainstate.nn.COBA.desc(E=-80. * u.mV),
post=self.N
)
def update(self, t, inp):
with brainstate.environ.context(t=t):
spk = self.N.get_spike() != 0.
self.E(spk[:self.n_exc])
self.I(spk[self.n_exc:])
self.N(inp)
return self.N.get_spike()
def save_checkpoint(self):
braintools.file.msgpack_save('states.msgpack', self.states())
```
## Installation
You can install ``brainunit`` via pip:
```bash
pip install brainunit --upgrade
```
## See also the BDP ecosystem
We are building the [brain dynamics programming (BDP) ecosystem](https://ecosystem-for-brain-dynamics.readthedocs.io/). [brainunit](https://github.com/chaobrain/brainunit) has been deeply integrated into our BDP ecosystem.
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"description": "<h1 align='center'>BrainUnit</h1>\r\n<h2 align='center'>Physical units and unit-aware math system for general-purpose brain dynamics modeling</h2>\r\n\r\n<p align=\"center\">\r\n \t<img alt=\"Header image of brainunit.\" src=\"https://raw.githubusercontent.com/chaobrain/saiunit/main/docs/_static/brainunit.png\" width=30%>\r\n</p> \r\n\r\n\r\n\r\n<p align=\"center\">\r\n\t<a href=\"https://pypi.org/project/brainunit/\"><img alt=\"Supported Python Version\" src=\"https://img.shields.io/pypi/pyversions/brainunit\"></a>\r\n\t<a href=\"https://github.com/chaobrain/brainunit/blob/main/LICENSE\"><img alt=\"LICENSE\" src=\"https://img.shields.io/badge/License-Apache%202.0-blue.svg\"></a>\r\n <a href='https://brainunit.readthedocs.io/en/latest/?badge=latest'>\r\n <img src='https://readthedocs.org/projects/brainunit/badge/?version=latest' alt='Documentation Status' />\r\n </a> \t\r\n <a href=\"https://badge.fury.io/py/brainunit\"><img alt=\"PyPI version\" src=\"https://badge.fury.io/py/brainunit.svg\"></a>\r\n <a href=\"https://pepy.tech/projects/brainunit\"><img src=\"https://static.pepy.tech/badge/brainunit\" alt=\"PyPI Downloads\"></a>\r\n</p>\r\n\r\n\r\n\r\n\r\n[BrainUnit](https://github.com/chaobrain/brainunit) provides physical units and unit-aware mathematical system in JAX for brain dynamics modeling. It introduces rigoirous physical units into high-performance AI-driven abstract numerical computing. \r\n\r\nBrainUnit is initially designed to enable unit-aware computations in brain dynamics modeling (see our [BDP ecosystem](https://ecosystem-for-brain-dynamics.readthedocs.io/)). However, its features and capacities can be applied to general domains in scientific computing and AI4Science. Starting in 2025/02, BrainUnit has been fully integrated into [SAIUnit](https://github.com/chaobrain/saiunit) (the **Unit** system for **S**cientific **AI**). \r\n\r\nFunctionalities are the same for both ``brainunit`` and ``saiunit``, and their functions and data structures are interoperable, sharing the same set of APIs, and eliminating any potential conflicts. This meas that \r\n\r\n```python\r\nimport brainunit as u\r\n```\r\n\r\nequals to \r\n\r\n```python\r\nimport saiunit as u\r\n```\r\n\r\nFor users primarily engaged in general scientific computing, `saiunit` is likely the preferred choice. However, for those focused on brain modeling, we recommend `brainunit`, as it is more closely aligned with our specialized brain dynamics programming ecosystem.\r\n\r\n\r\n\r\n## Documentation\r\n\r\nThe official documentation of BrainUnit is hosted on Read the Docs: [https://brainunit.readthedocs.io](https://brainunit.readthedocs.io)\r\n\r\n\r\n\r\n## Features\r\n\r\n`brainunit` can be seamlessly integrated into every aspect of our [brain dynamics programming ecosystem](https://ecosystem-for-brain-dynamics.readthedocs.io/), such as, the checkpointing of [braintools](https://github.com/chaobrain/braintools), the event-driven operators in [brainevent](https://github.com/chaobrain/brainevent), the state-based JIT compilation in [brainstate](https://github.com/chaobrain/brainstate), online learning rules in [brainscale](https://github.com/chaobrain/brainscale), or event more. \r\n\r\nA quick example for this kind of integration:\r\n\r\n```python\r\n\r\nimport braintools\r\nimport brainevent.nn\r\nimport brainstate\r\nimport brainunit as u\r\n\r\n\r\nclass EINet(brainstate.nn.Module):\r\n def __init__(self):\r\n super().__init__()\r\n self.n_exc = 3200\r\n self.n_inh = 800\r\n self.num = self.n_exc + self.n_inh\r\n self.N = brainstate.nn.LIFRef(\r\n self.num, V_rest=-60. * u.mV, V_th=-50. * u.mV, V_reset=-60. * u.mV,\r\n tau=20. * u.ms, tau_ref=5. * u.ms,\r\n V_initializer=brainstate.init.Normal(-55., 2., unit=u.mV)\r\n )\r\n self.E = brainstate.nn.AlignPostProj(\r\n comm=brainevent.nn.FixedProb(self.n_exc, self.num, 0.02, 0.6 * u.mS),\r\n syn=brainstate.nn.Expon.desc(self.num, tau=5. * u.ms),\r\n out=brainstate.nn.COBA.desc(E=0. * u.mV),\r\n post=self.N\r\n )\r\n self.I = brainstate.nn.AlignPostProj(\r\n comm=brainevent.nn.FixedProb(self.n_inh, self.num, 0.02, 6.7 * u.mS),\r\n syn=brainstate.nn.Expon.desc(self.num, tau=10. * u.ms),\r\n out=brainstate.nn.COBA.desc(E=-80. * u.mV),\r\n post=self.N\r\n )\r\n\r\n def update(self, t, inp):\r\n with brainstate.environ.context(t=t):\r\n spk = self.N.get_spike() != 0.\r\n self.E(spk[:self.n_exc])\r\n self.I(spk[self.n_exc:])\r\n self.N(inp)\r\n return self.N.get_spike()\r\n \r\n def save_checkpoint(self):\r\n braintools.file.msgpack_save('states.msgpack', self.states())\r\n \r\n```\r\n\r\n\r\n\r\n## Installation\r\n\r\nYou can install ``brainunit`` via pip:\r\n\r\n```bash\r\npip install brainunit --upgrade\r\n```\r\n\r\n\r\n\r\n## See also the BDP ecosystem\r\n\r\nWe are building the [brain dynamics programming (BDP) ecosystem](https://ecosystem-for-brain-dynamics.readthedocs.io/). 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