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AppleM1Build.md
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Python package

Repo for testing git workflow

This is a repo for testing workflow using git.

This is another test. This is one more test.

This is the third commit entry.

Testing git repo

Dry Run Testing for moose dev

MOOSE

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 .

Installation

See INSTALL.md for instructions on installation.

Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.

Build

To build pymoose, follow the instructions given in
INSTALL.md
and for platform-specific information, see:

ABOUT VERSION 4.1.0, Jhangri

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:

  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables replaced by single xmin, xmax, xdivs, ymin, ymax, and ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.

LICENSE

MOOSE is released under GPLv3.

About

Moose Project Dev

Resources

Readme
GPL-3.0 license

Contributing

Contributing
Activity

Stars

1 star

Watchers

2 watching

Forks

1 fork
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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diffusion
examples
examples
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hsolve
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python
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shell
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.gitlab-ci.yml
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.pre-commit-config.yaml
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.travis.yml
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AUTHORS
AUTHORS
AppleM1Build.md
AppleM1Build.md
CONTRIBUTING.md
CONTRIBUTING.md
INSTALL.md
INSTALL.md
LICENSE
LICENSE
MANIFEST.in
MANIFEST.in
README.md
README.md
UbuntuBuild.md
UbuntuBuild.md
WSLGuide.md
WSLGuide.md
WindowsBuild.md
WindowsBuild.md
cmake_moose_cpack.cmake
cmake_moose_cpack.cmake
cmake_uninstall.cmake.in
cmake_uninstall.cmake.in
meson.build
meson.build
meson_options.txt
meson_options.txt
pyproject.toml
pyproject.toml
Repository files navigation
Python package
Repo for testing git workflow
This is a repo for testing workflow using git.
This is another test.
This is one more test.
This is the third commit entry.
Testing git repo
Dry Run Testing for moose dev
MOOSE
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 .
Installation
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.
Build
To build pymoose, follow the instructions given in
INSTALL.md

and for platform-specific information, see:
ABOUT VERSION 4.1.0, Jhangri
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:
  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables
replaced by single xmin, xmax, xdivs, ymin, ymax, and
ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.
LICENSE
MOOSE is released under GPLv3.
About
Moose Project Dev
Resources
Readme
GPL-3.0 license
Contributing
Contributing
Activity
Stars
1 star
Watchers
2 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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device
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diffusion
examples
examples
external
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hsolve
hsolve
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intfire
kinetics
kinetics
ksolve
ksolve
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mesh
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python
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randnum
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signeur
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synapse
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.clang-format
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.gitlab-ci.yml
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.pre-commit-config.yaml
.pre-commit-config.yaml
.travis.yml
.travis.yml
AUTHORS
AUTHORS
AppleM1Build.md
AppleM1Build.md
CONTRIBUTING.md
CONTRIBUTING.md
INSTALL.md
INSTALL.md
LICENSE
LICENSE
MANIFEST.in
MANIFEST.in
README.md
README.md
UbuntuBuild.md
UbuntuBuild.md
WSLGuide.md
WSLGuide.md
WindowsBuild.md
WindowsBuild.md
cmake_moose_cpack.cmake
cmake_moose_cpack.cmake
cmake_uninstall.cmake.in
cmake_uninstall.cmake.in
meson.build
meson.build
meson_options.txt
meson_options.txt
pyproject.toml
pyproject.toml
Repository files navigation
Python package
Repo for testing git workflow
This is a repo for testing workflow using git.
This is another test.
This is one more test.
This is the third commit entry.
Testing git repo
Dry Run Testing for moose dev
MOOSE
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 .
Installation
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.
Build
To build pymoose, follow the instructions given in
INSTALL.md

and for platform-specific information, see:
ABOUT VERSION 4.1.0, Jhangri
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:
  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables
replaced by single xmin, xmax, xdivs, ymin, ymax, and
ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.
LICENSE
MOOSE is released under GPLv3.
About
Moose Project Dev
Resources
Readme
GPL-3.0 license
Contributing
Contributing
Activity
Stars
1 star
Watchers
2 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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device
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diffusion
examples
examples
external
external
hsolve
hsolve
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kinetics
ksolve
ksolve
mesh
mesh
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mpi
msg
msg
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pymoose
python
python
randnum
randnum
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scheduling
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shell
signeur
signeur
synapse
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tests
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utility
utility
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.pre-commit-config.yaml
.pre-commit-config.yaml
.travis.yml
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AUTHORS
AUTHORS
AppleM1Build.md
AppleM1Build.md
CONTRIBUTING.md
CONTRIBUTING.md
INSTALL.md
INSTALL.md
LICENSE
LICENSE
MANIFEST.in
MANIFEST.in
README.md
README.md
UbuntuBuild.md
UbuntuBuild.md
WSLGuide.md
WSLGuide.md
WindowsBuild.md
WindowsBuild.md
cmake_moose_cpack.cmake
cmake_moose_cpack.cmake
cmake_uninstall.cmake.in
cmake_uninstall.cmake.in
meson.build
meson.build
meson_options.txt
meson_options.txt
pyproject.toml
pyproject.toml
Repository files navigation
Python package
Repo for testing git workflow
This is a repo for testing workflow using git.
This is another test.
This is one more test.
This is the third commit entry.
Testing git repo
Dry Run Testing for moose dev
MOOSE
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 .
Installation
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.
Build
To build pymoose, follow the instructions given in
INSTALL.md

and for platform-specific information, see:
ABOUT VERSION 4.1.0, Jhangri
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:
  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables
replaced by single xmin, xmax, xdivs, ymin, ymax, and
ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.
LICENSE
MOOSE is released under GPLv3.
About
Moose Project Dev
Resources
Readme
GPL-3.0 license
Contributing
Contributing
Activity
Stars
1 star
Watchers
2 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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devel
devel
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device
diffusion
diffusion
examples
examples
external
external
hsolve
hsolve
intfire
intfire
kinetics
kinetics
ksolve
ksolve
mesh
mesh
mpi
mpi
msg
msg
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pymoose
pymoose
python
python
randnum
randnum
scheduling
scheduling
shell
shell
signeur
signeur
synapse
synapse
tests
tests
utility
utility
.clang-format
.clang-format
.gitignore
.gitignore
.gitlab-ci.yml
.gitlab-ci.yml
.pre-commit-config.yaml
.pre-commit-config.yaml
.travis.yml
.travis.yml
AUTHORS
AUTHORS
AppleM1Build.md
AppleM1Build.md
CONTRIBUTING.md
CONTRIBUTING.md
INSTALL.md
INSTALL.md
LICENSE
LICENSE
MANIFEST.in
MANIFEST.in
README.md
README.md
UbuntuBuild.md
UbuntuBuild.md
WSLGuide.md
WSLGuide.md
WindowsBuild.md
WindowsBuild.md
cmake_moose_cpack.cmake
cmake_moose_cpack.cmake
cmake_uninstall.cmake.in
cmake_uninstall.cmake.in
meson.build
meson.build
meson_options.txt
meson_options.txt
pyproject.toml
pyproject.toml
Repository files navigation
Python package
Repo for testing git workflow
This is a repo for testing workflow using git.
This is another test.
This is one more test.
This is the third commit entry.
Testing git repo
Dry Run Testing for moose dev
MOOSE
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 .
Installation
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.
Build
To build pymoose, follow the instructions given in
INSTALL.md

and for platform-specific information, see:
ABOUT VERSION 4.1.0, Jhangri
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:
  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables
replaced by single xmin, xmax, xdivs, ymin, ymax, and
ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.
LICENSE
MOOSE is released under GPLv3.
About
Moose Project Dev
Resources
Readme
GPL-3.0 license
Contributing
Contributing
Activity
Stars
1 star
Watchers
2 watching
Forks
1 fork
Report repository
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Packages
Contributors
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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examples
examples
external
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AUTHORS
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AppleM1Build.md
AppleM1Build.md
CONTRIBUTING.md
CONTRIBUTING.md
INSTALL.md
INSTALL.md
LICENSE
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MANIFEST.in
MANIFEST.in
README.md
README.md
UbuntuBuild.md
UbuntuBuild.md
WSLGuide.md
WSLGuide.md
WindowsBuild.md
WindowsBuild.md
cmake_moose_cpack.cmake
cmake_moose_cpack.cmake
cmake_uninstall.cmake.in
cmake_uninstall.cmake.in
meson.build
meson.build
meson_options.txt
meson_options.txt
pyproject.toml
pyproject.toml
Repository files navigation
Python package
Repo for testing git workflow
This is a repo for testing workflow using git.
This is another test.
This is one more test.
This is the third commit entry.
Testing git repo
Dry Run Testing for moose dev
MOOSE
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 .
Installation
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.
Build
To build pymoose, follow the instructions given in
INSTALL.md

and for platform-specific information, see:
ABOUT VERSION 4.1.0, Jhangri
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:
  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables
replaced by single xmin, xmax, xdivs, ymin, ymax, and
ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.
LICENSE
MOOSE is released under GPLv3.
About
Moose Project Dev
Resources
Readme
GPL-3.0 license
Contributing
Contributing
Activity
Stars
1 star
Watchers
2 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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.github
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biophysics
builtins
builtins
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cmake
devel
devel
device
device
diffusion
diffusion
examples
examples
external
external
hsolve
hsolve
intfire
intfire
kinetics
kinetics
ksolve
ksolve
mesh
mesh
mpi
mpi
msg
msg
pybind11
pybind11
pymoose
pymoose
python
python
randnum
randnum
scheduling
scheduling
shell
shell
signeur
signeur
synapse
synapse
tests
tests
utility
utility
.clang-format
.clang-format
.gitignore
.gitignore
.gitlab-ci.yml
.gitlab-ci.yml
.pre-commit-config.yaml
.pre-commit-config.yaml
.travis.yml
.travis.yml
AUTHORS
AUTHORS
AppleM1Build.md
AppleM1Build.md
CONTRIBUTING.md
CONTRIBUTING.md
INSTALL.md
INSTALL.md
LICENSE
LICENSE
MANIFEST.in
MANIFEST.in
README.md
README.md
UbuntuBuild.md
UbuntuBuild.md
WSLGuide.md
WSLGuide.md
WindowsBuild.md
WindowsBuild.md
cmake_moose_cpack.cmake
cmake_moose_cpack.cmake
cmake_uninstall.cmake.in
cmake_uninstall.cmake.in
meson.build
meson.build
meson_options.txt
meson_options.txt
pyproject.toml
pyproject.toml
Repository files navigation
Python package
Repo for testing git workflow
This is a repo for testing workflow using git.
This is another test.
This is one more test.
This is the third commit entry.
Testing git repo
Dry Run Testing for moose dev
MOOSE
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 .
Installation
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.
Build
To build pymoose, follow the instructions given in
INSTALL.md

and for platform-specific information, see:
ABOUT VERSION 4.1.0, Jhangri
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:
  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables
replaced by single xmin, xmax, xdivs, ymin, ymax, and
ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.
LICENSE
MOOSE is released under GPLv3.
About
Moose Project Dev
Resources
Readme
GPL-3.0 license
Contributing
Contributing
Activity
Stars
1 star
Watchers
2 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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builtins
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cmake
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device
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examples
examples
external
external
hsolve
hsolve
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kinetics
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ksolve
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msg
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python
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randnum
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signeur
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synapse
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tests
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utility
utility
.clang-format
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.gitlab-ci.yml
.gitlab-ci.yml
.pre-commit-config.yaml
.pre-commit-config.yaml
.travis.yml
.travis.yml
AUTHORS
AUTHORS
AppleM1Build.md
AppleM1Build.md
CONTRIBUTING.md
CONTRIBUTING.md
INSTALL.md
INSTALL.md
LICENSE
LICENSE
MANIFEST.in
MANIFEST.in
README.md
README.md
UbuntuBuild.md
UbuntuBuild.md
WSLGuide.md
WSLGuide.md
WindowsBuild.md
WindowsBuild.md
cmake_moose_cpack.cmake
cmake_moose_cpack.cmake
cmake_uninstall.cmake.in
cmake_uninstall.cmake.in
meson.build
meson.build
meson_options.txt
meson_options.txt
pyproject.toml
pyproject.toml
Repository files navigation
Python package
Repo for testing git workflow
This is a repo for testing workflow using git.
This is another test.
This is one more test.
This is the third commit entry.
Testing git repo
Dry Run Testing for moose dev
MOOSE
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 .
Installation
See INSTALL.md for instructions on installation.
Have a look at examples, tutorials, and demos here:
https://github.com/BhallaLab/moose-examples.
Build
To build pymoose, follow the instructions given in
INSTALL.md

and for platform-specific information, see:
ABOUT VERSION 4.1.0, Jhangri
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:
  1. Improved support for reading NeuroML2 models
  2. HHGate2D: separate xminA, xminB, etc. for A and B tables
replaced by single xmin, xmax, xdivs, ymin, ymax, and
ydivs fields for both tables.
  3. Build system switched from cmake to meson
  4. Native binaries for Windows
  5. Updated to conform to c/c++-17 standard
  6. Various bugfixes.
LICENSE
MOOSE is released under GPLv3.
About
Moose Project Dev
Resources
Readme
GPL-3.0 license
Contributing
Contributing
Activity
Stars
1 star
Watchers
2 watching
Forks
1 fork
Report repository
Releases
Packages
Contributors
Languages