Skip to main content

Python package

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 demo here https://github.com/BhallaLab/moose-examples.

Build

To build pymoose, follow 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.

Metadata

Release files for moose-core 4.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for moose-core 4.1.2
File Actions
moose_core-4.1.2-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details for moose_core-4.1.2-cp313-cp313-win_amd64.whl
moose_core-4.1.2-cp313-cp313-manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ x86-64 Details for moose_core-4.1.2-cp313-cp313-manylinux_2_28_x86_64.whl
moose_core-4.1.2-cp313-cp313-macosx_14_0_arm64.whl CPython 3.13 CPython 3.13 macOS 14.0+ ARM64 Details for moose_core-4.1.2-cp313-cp313-macosx_14_0_arm64.whl
moose_core-4.1.2-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details for moose_core-4.1.2-cp312-cp312-win_amd64.whl
moose_core-4.1.2-cp312-cp312-manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ x86-64 Details for moose_core-4.1.2-cp312-cp312-manylinux_2_28_x86_64.whl
moose_core-4.1.2-cp312-cp312-macosx_14_0_arm64.whl CPython 3.12 CPython 3.12 macOS 14.0+ ARM64 Details for moose_core-4.1.2-cp312-cp312-macosx_14_0_arm64.whl
moose_core-4.1.2-cp311-cp311-win_amd64.whl CPython 3.11 CPython 3.11 Windows x86-64 Details for moose_core-4.1.2-cp311-cp311-win_amd64.whl
moose_core-4.1.2-cp311-cp311-manylinux_2_28_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.28+ x86-64 Details for moose_core-4.1.2-cp311-cp311-manylinux_2_28_x86_64.whl
moose_core-4.1.2-cp311-cp311-macosx_14_0_arm64.whl CPython 3.11 CPython 3.11 macOS 14.0+ ARM64 Details for moose_core-4.1.2-cp311-cp311-macosx_14_0_arm64.whl
moose_core-4.1.2-cp310-cp310-win_amd64.whl CPython 3.10 CPython 3.10 Windows x86-64 Details for moose_core-4.1.2-cp310-cp310-win_amd64.whl
moose_core-4.1.2-cp310-cp310-manylinux_2_28_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.28+ x86-64 Details for moose_core-4.1.2-cp310-cp310-manylinux_2_28_x86_64.whl
moose_core-4.1.2-cp310-cp310-macosx_14_0_arm64.whl CPython 3.10 CPython 3.10 macOS 14.0+ ARM64 Details for moose_core-4.1.2-cp310-cp310-macosx_14_0_arm64.whl
moose_core-4.1.2-cp39-cp39-win_amd64.whl CPython 3.9 CPython 3.9 Windows x86-64 Details for moose_core-4.1.2-cp39-cp39-win_amd64.whl
moose_core-4.1.2-cp39-cp39-manylinux_2_28_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.28+ x86-64 Details for moose_core-4.1.2-cp39-cp39-manylinux_2_28_x86_64.whl
moose_core-4.1.2-cp39-cp39-macosx_14_0_arm64.whl CPython 3.9 CPython 3.9 macOS 14.0+ ARM64 Details for moose_core-4.1.2-cp39-cp39-macosx_14_0_arm64.whl
moose_core-4.1.2-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details for moose_core-4.1.2-cp38-cp38-win_amd64.whl
moose_core-4.1.2-cp38-cp38-manylinux_2_28_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.28+ x86-64 Details for moose_core-4.1.2-cp38-cp38-manylinux_2_28_x86_64.whl

Total release size: 98.9 MB

Release files / moose_core-4.1.2-cp313-cp313-win_amd64.whl

Download URL moose_core-4.1.2-cp313-cp313-win_amd64.whl
Size 3.0 MB
Tags CPython 3.13 Windows x86-64
SHA-256 checksum
How to use checksums
8b3ec1efa483900b683a12e7341ca2c72d94a7797c35437a591346e77bc96a3f
BLAKE2b-256 checksum
How to use checksums
6770fd55da5421f850fe1356452051c85b3a90687af39cc67df1f9d3041c4d84
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp313-cp313-manylinux_2_28_x86_64.whl

Download URL moose_core-4.1.2-cp313-cp313-manylinux_2_28_x86_64.whl
Size 8.7 MB
Tags CPython 3.13 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
90b2bcf1cb4d7c734f53e8723aece4782521bcb3b04ea09f3a1ab347feac07b5
BLAKE2b-256 checksum
How to use checksums
7c7df624b608288f7a6cee755a1f0e46c2727bdcc5dd0c22945bb431e6f3044f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.12

Release files / moose_core-4.1.2-cp313-cp313-macosx_14_0_arm64.whl

Download URL moose_core-4.1.2-cp313-cp313-macosx_14_0_arm64.whl
Size 5.8 MB
Tags CPython 3.13 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
b6e05db9098d3da7ca9263426fdcc58ba1f41bef6e3975fd8c0d0dcc3b28b3cd
BLAKE2b-256 checksum
How to use checksums
6352fe19448bf8a1929712d3d47b023573d316be57b271e283fd070a910ce490
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp312-cp312-win_amd64.whl

Download URL moose_core-4.1.2-cp312-cp312-win_amd64.whl
Size 3.0 MB
Tags CPython 3.12 Windows x86-64
SHA-256 checksum
How to use checksums
10c43e8426562048ddba6cc8d3abf54ec3f0fe0aa1a0ab20587fe6d221acb490
BLAKE2b-256 checksum
How to use checksums
588567fe3bd4a6adcfc343f2babbea08454cad8e04b05710de1e4933a63dfccb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp312-cp312-manylinux_2_28_x86_64.whl

Download URL moose_core-4.1.2-cp312-cp312-manylinux_2_28_x86_64.whl
Size 8.7 MB
Tags CPython 3.12 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
1f9fabaaca8bd749e7ee7facd408db79b0d5da595db5c035019c2d429e46f8a6
BLAKE2b-256 checksum
How to use checksums
9117f3ecdf5756844e64bb5d29318057dbb524ad1eea64cf082868680929be14
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.12

Release files / moose_core-4.1.2-cp312-cp312-macosx_14_0_arm64.whl

Download URL moose_core-4.1.2-cp312-cp312-macosx_14_0_arm64.whl
Size 5.8 MB
Tags CPython 3.12 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
5fad6816503d4da6337b6bdce5bea9a18ebbb2befc2f0e21df7a0159318df102
BLAKE2b-256 checksum
How to use checksums
f1fa9e6b78b16020378c81eb753c9cccff7baeb73b44c70d1bdb8d9fdf4a4bc6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp311-cp311-win_amd64.whl

Download URL moose_core-4.1.2-cp311-cp311-win_amd64.whl
Size 3.0 MB
Tags CPython 3.11 Windows x86-64
SHA-256 checksum
How to use checksums
7e343d4bc3117a8ac7e428019d0efdf6a24196c5663f71b83b16bcb99c51de63
BLAKE2b-256 checksum
How to use checksums
62111d7375b6b8ab915ae73f96c763a4688ae33cf59ed0c3fee49c20b7895a00
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp311-cp311-manylinux_2_28_x86_64.whl

Download URL moose_core-4.1.2-cp311-cp311-manylinux_2_28_x86_64.whl
Size 8.7 MB
Tags CPython 3.11 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
cd69b1de9f9c82f3c6ea61a085455c2c3b0a7d5b6d7c3b0dec34dfb91b957290
BLAKE2b-256 checksum
How to use checksums
3b11c277bfaf1c1b867699b08f0ed649cbccfa03f9203128ab40c1441a4fb061
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.12

Release files / moose_core-4.1.2-cp311-cp311-macosx_14_0_arm64.whl

Download URL moose_core-4.1.2-cp311-cp311-macosx_14_0_arm64.whl
Size 5.8 MB
Tags CPython 3.11 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
2e93c0d15904f07bd033bf344d9c87f63d7edd1e65ce9e4f342095e3f2680b33
BLAKE2b-256 checksum
How to use checksums
922437d794d6364700359d6108ed3ca92babc07ae9b4ed5ddfdae6d11f8659be
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp310-cp310-win_amd64.whl

Download URL moose_core-4.1.2-cp310-cp310-win_amd64.whl
Size 3.0 MB
Tags CPython 3.10 Windows x86-64
SHA-256 checksum
How to use checksums
9e50ae2371a3ae2225a42024e75478b0226296714dee6010282493829c9ad7f3
BLAKE2b-256 checksum
How to use checksums
a332dd65cd318f1bcc707668cf4d458e956062cac2f8a2ca478c4473cde291f6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp310-cp310-manylinux_2_28_x86_64.whl

Download URL moose_core-4.1.2-cp310-cp310-manylinux_2_28_x86_64.whl
Size 8.7 MB
Tags CPython 3.10 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
6927060c940ab0ee592bd91778f4b413c89afb086603651adc4fa6695249307f
BLAKE2b-256 checksum
How to use checksums
0bc67e7c008dc7c6271c3302ce67667dedcd70c3156b6d117701906b24f84feb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.12

Release files / moose_core-4.1.2-cp310-cp310-macosx_14_0_arm64.whl

Download URL moose_core-4.1.2-cp310-cp310-macosx_14_0_arm64.whl
Size 5.7 MB
Tags CPython 3.10 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
95b6dd3e2a7cdbde2b62cbd4bb5462822d14049c10c563ac523b059734d00139
BLAKE2b-256 checksum
How to use checksums
e1ef1b028962b73bd99c7488c606581b37b28a2483be485e44e5b4ae4578bad3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp39-cp39-win_amd64.whl

Download URL moose_core-4.1.2-cp39-cp39-win_amd64.whl
Size 3.0 MB
Tags CPython 3.9 Windows x86-64
SHA-256 checksum
How to use checksums
d2416316b18215d522eef7fea7fa1184d2dbc4ac133ff1260e1a36c5034d0665
BLAKE2b-256 checksum
How to use checksums
0a4c31157b4506c09e4e8f6700e696bf713b32572befdc70646f6b0ef2f261b5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp39-cp39-manylinux_2_28_x86_64.whl

Download URL moose_core-4.1.2-cp39-cp39-manylinux_2_28_x86_64.whl
Size 8.7 MB
Tags CPython 3.9 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
c047499b7c46119bb1fbfaf5d2e966fcec0cd7c358a0c9b301b9f0cf1ac48b97
BLAKE2b-256 checksum
How to use checksums
ef18bdb13d9beca25052b7de4d1851770316b439e4cae2e1239991caeb76e0bd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.12

Release files / moose_core-4.1.2-cp39-cp39-macosx_14_0_arm64.whl

Download URL moose_core-4.1.2-cp39-cp39-macosx_14_0_arm64.whl
Size 5.7 MB
Tags CPython 3.9 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
b8bbd7d60442a3325599eaa4c8e30c23454346a334fba150a8bd208a38a4fd20
BLAKE2b-256 checksum
How to use checksums
97222fd2a640fff0737e1293eabfc3b3f5ccd275da1c991f1b3dac92e2c57d43
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp38-cp38-win_amd64.whl

Download URL moose_core-4.1.2-cp38-cp38-win_amd64.whl
Size 3.0 MB
Tags CPython 3.8 Windows x86-64
SHA-256 checksum
How to use checksums
aba211c87e3c0d412fce0ad5d80e14564e58c126aa7dfaa79e5b6093f5b8a7b2
BLAKE2b-256 checksum
How to use checksums
f24dba639e513700b8bbbd2f288019e6e95871b58bf25ef353fc96764a2f5caa
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.9

Release files / moose_core-4.1.2-cp38-cp38-manylinux_2_28_x86_64.whl

Download URL moose_core-4.1.2-cp38-cp38-manylinux_2_28_x86_64.whl
Size 8.7 MB
Tags CPython 3.8 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
65c124d6588d1d6fe4a49603c924c38c0d34c931e66f7e72d45401a67996b650
BLAKE2b-256 checksum
How to use checksums
e989effc5a9981b193eaeb2ef0ce1a950d7c024580625a900ee0f9e3dc7e2fd5
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.11.12

Security for moose-core 4.1.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

4.1.2 This release

17 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page