Skip to main content

# Python contact angle image processing analysis

Project description

Python contact angle image processing analysis

A python script that follows a simple logical progression to reliably measure contact angles from image or video files. While the traditional methods for contact angle analysis typically rely on the user drawing tangent lines to droplets, which is both time consuming and can lead to bias in the analysis results, we attempt to automate this analysis to make the process both more robust and more amenable to high throughput data generation. The logic we use for this process is highlighted below:

Logic flow

Installation

The analysis script can be installed by cloning the repository into your desired working directory or via the following:

$ pip install contactangles

With the pip installation, the main script can be run from the command line by calling analysis; otherwise it must be run from within a Python instance (see Use section below).

Dependencies

The following packages must already be installed in your Python environment to contribute to the development of this project:

  • numpy
  • scipy
  • scikit-image
  • imageio
  • matplotlib
  • setuptools
  • wheel
  • twine
  • pytest
  • pip:
    • imageio-ffmpeg
    • pytest-subtests
    • pytest-cov

Use

Depending on the installation choice, the script can either be run from the command line:

$ analysis path/to/files/of/interest

If you have installed as a developer, you can use the script by calling the main() function from the file analysis.py

Parameter Definitions

The relevant threshold parameters that define where the tangent lines, baseline, and circle will be identified are most easily explained through the image below:

Threshold example image

These parameters can be accessed through the flags --baselineThreshold, --circleThreshold, and --linThreshold respectively. Additional flags can be set and can be shown from the help accessed by

$ analysis --help

Credits

Contact angle measurement automation has also been performed by mvgorcum, which uses a different approach to fitting the tangents, but inspired our work here.

Contribute

Please don't hesitate to submit any issues that you may identify with the approach or the coding. We will try to respond quickly to any questions that may arise. If you would like to contribute to the project, feel free to make any pull requests that will make the solution more robust/efficient/better for your application, and we will do our best to incorporate it in the next release.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

contactangles-0.2.0.dev1.tar.gz (36.0 MB view details)

Uploaded Source

Built Distribution

contactangles-0.2.0.dev1-py3-none-any.whl (25.6 kB view details)

Uploaded Python 3

File details

Details for the file contactangles-0.2.0.dev1.tar.gz.

File metadata

  • Download URL: contactangles-0.2.0.dev1.tar.gz
  • Upload date:
  • Size: 36.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.6

File hashes

Hashes for contactangles-0.2.0.dev1.tar.gz
Algorithm Hash digest
SHA256 747fe9a4ba3f358c2825e2eb2dcbafbcbec19f7ad3d46727ffc3fcc938c85294
MD5 876a2037a6a1a9ef3d2119774812b158
BLAKE2b-256 939ff35ad943fded7c6a77cc089926c8c6ebd472d3a1154befa138a080cf04a3

See more details on using hashes here.

File details

Details for the file contactangles-0.2.0.dev1-py3-none-any.whl.

File metadata

  • Download URL: contactangles-0.2.0.dev1-py3-none-any.whl
  • Upload date:
  • Size: 25.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.6

File hashes

Hashes for contactangles-0.2.0.dev1-py3-none-any.whl
Algorithm Hash digest
SHA256 23087f5ec5aa27c8deafd025fa36640f1c51fa8d969e8e99c974a0915af422d3
MD5 415c7cabef609e69d90a8a7e3ea1b331
BLAKE2b-256 9695330f40d718813e7d744887e694625f06e4c32983728fc0235369674567b4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page