Skip to main content

Membrane Curvature

Powered by MDAnalysis GitHub Actions Status codecov docs PyPI

MembraneCurvature is an MDAnalysis tool to calculate membrane curvature from Molecular Dynamics simulations.

Interested in becoming a maintainer? We welcome your passion and expertise to help shape and grow this open-source project! Please contact estefania@ojeda-e.com for more details.

Features

With MembraneCurvature you can:

  • Calculate mean and Gaussian curvature from MD simulations.
  • Derive 2D curvature profiles.
  • Live a happier life.

Installation

The main dependency in MembraneCurvature is MDAnalysis. You can find instructions to install the latest stable version of MDAnalysis via conda in the UserGuide.

MembraneCurvature is available via pip:

pip install membrane-curvature

To install from source:

git clone https://github.com/MDAnalysis/membrane-curvature.git
cd membrane-curvature
conda env create -f devtools/conda-envs/environment.yaml
conda activate membrane-curvature
python setup.py install

Some of the examples included in the MembraneCurvature documentation use test cases from MDAnalysisTests. To install the unit tests via conda:

conda install -c conda-forge MDAnalysisTests

or via pip:

pip install --upgrade MDAnalysisTests

Usage

This is a quick example on how to run MembraneCurvature:

import MDAnalysis as mda
from membrane_curvature.base import MembraneCurvature
from MDAnalysis.tests.datafiles import Martini_membrane_gro

universe = mda.Universe(Martini_membrane_gro)

curvature_upper_leaflet = MembraneCurvature(universe,
                                            select='resid 1-225 and name PO4',
                                            n_x_bins=8,
                                            n_y_bins=8,
                                            wrap=True).run()

# extract mean curvature
mean_upper_leaflet = curvature_upper_leaflet.results.z_surface

# extract mean curvature
mean_upper_leaflet = curvature_upper_leaflet.results.mean

# extract Gaussian
gaussian_upper_leaflet = curvature_upper_leaflet.results.gaussian

In this example, we use the PO4 beads in the upper leaflet as reference to derive a surface and calculate its respective mean and Gaussian curvature.

You can find more examples on how to run MembraneCurvature in the Usage page. To plot results from MembraneCurvature please check the Visualization page.

Documentation

To help you get the most out MembraneCurvature, we have documentation available where you can find:

  • The standard API documentation.
  • Quick examples of how to run Membrane Curvature in the Usage page.
  • Detailed explanation of the Algorithm implemented in MembraneCurvature.
  • Examples on how to plot the results obtained from MembraneCurvature in the Visualization page.

License

Source code included in this project is available in the GitHub repository https://github.com/MDAnalysis/membrane-curvature under the GNU Public License v3 , version 3 (see LICENSE).

MembraneCurvature was developed as a Google Summer of Code 2021 project with MDAnalysis and it is linked to a Code of Conduct.

Metadata

Release files for membrane-curvature 1.1.2

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

Source distribution (sdist)

Source distribution for membrane-curvature 1.1.2
File Size Uploaded
membrane_curvature-1.1.2.tar.gz 4.2 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for membrane-curvature 1.1.2
File Interpreter ABI Platform
membrane_curvature-1.1.2-py3-none-any.whl Python 3 none any Details

Total release size: 8.5 MB

Release files / membrane_curvature-1.1.2.tar.gz

Download URL membrane_curvature-1.1.2.tar.gz
Size 4.2 MB
Tags Source
SHA-256 checksum
How to use checksums
6b5775e53a69689d222b373353909bcd2625ef4a1090a1b5c34ca14943d8516b
BLAKE2b-256 checksum
How to use checksums
945389268f2afff180c0b2a7a96f1931aa89062b20b71e94b36a9a35e1246f13
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.13

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.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Apr 25, 2026.

Transparency log

Release files / membrane_curvature-1.1.2-py3-none-any.whl

Download URL membrane_curvature-1.1.2-py3-none-any.whl
Size 4.2 MB
Tags Python 3
SHA-256 checksum
How to use checksums
887d70d73e26f0bcc9c5593b677f949b6fdecade97e49380a0d95b3610b6004f
BLAKE2b-256 checksum
How to use checksums
1980e78523d3b999c83af47bbcdea1c7faa46572c91e530c26c90bd4707992ed
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.13

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.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Apr 25, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

1.1.2 This release

2 release files

1.1.1

2 release files

1.1.0

2 release files

1.0.0

2 release files

0.0.2

2 release files

0.0.1

2 release files

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