Skip to main content

ZMPY3D Tensorflow version

Project description

ZMPY3D_TF

ZMPY3D: accelerating protein structure volume analysis through vectorized 3D Zernike Moments and Python-based GPU Integration

For CPU support only, please refer to the repository:

ZMPY3D supports NumPy (https://github.com/tawssie/ZMPY3D)

For GPU support with TensorFlow and CuPy, please refer to the other two repositories:

ZMPY3D_TF supports Tensorflow (https://github.com/tawssie/ZMPY3D_TF)

ZMPY3D_CP supports CuPy (https://github.com/tawssie/ZMPY3D_CP)

Here presents a Python-based software package, ZMPY3D, to accelerate the moments computation by vectorizing the mathematical formulae, enabling their computation in graphical processing units (GPUs). The package offers popular GPU-supported libraries such as CuPy and TensorFlow along with NumPy implementations, aiming to improve computational efficiency, adaptability, and flexibility in future algorithmic development.

Installation

Prerequisites:

  • ZMPY3D : Python >=3.9.16, NumPy >=1.23.5
  • ZMPY3D_CP: Python >=3.9.16, NumPy, CuPy >=12.2.0
  • ZMPY3D_TF: Python >=3.9.16, NumPy >=1.23.5, Tensorflow >=2.12.0, Tensorflow-Probability >=0.20.1
  1. Open the terminal
  2. Using pip to install the package through PyPI
  3. Run pip install ZMPY3D_TF for the installation

Usage

  • 3D Zernike moments with Tensorflow: Open In Colab
  • Shape similarity with CuPy: Open In Colab
  • Structure superposition with NumPy: Open In Colab
  • Runtime evaluation: Open In Colab

Performances

A voxel cube with dimensions of 100x100x100 was applied to perform 10,000 3D Zernike moment calculations, using 2 different maximum orders 20 and 40. Execution times for different hardware configurations using TensorFlow, CuPy, and NumPy libraries:

NumPy

Order CPU1 CPU2
20 33m20s 14m1s
40 951m40s 338m20s

TensorFlow

Order T4 RX3070Ti V100 L4
20 1m1s 0m36s 0m31s 0m39s
40 24m40s 9m3s 10m54s 11m13s

CuPy

Order T4 RX3070Ti V100 L4
20 4m45s 2m30s 1m42s 2m50s
40 35m20s 19m19s 14m45s 18m40s

Note: m = minutes, s = seconds.

Cache data for order 40

Due to GitHub's file size limitations, follow these steps to download the cache data for order 40 (1.3G) in the ZMPY3D_TF package:

1. Locate Package Folder

  • Open your terminal and execute the following command to find the folder of the ZMPY3D_TF package:
  • python -c "import ZMPY3D_TF; print(ZMPY3D_TF.__file__)"
  • Note the path, which ends with /User/path/ptyhon/site-packages/ZMPY3D_TF/__init__.py.

2. Navigate to Cache Data Folder

  • Go to the cache_data folder at the same level as __init__.py file, i.e., /User/path/ptyhon/site-packages/ZMPY3D_TF/cache_data.

3. Download the Cache File:

Contributing

Feel free to submit pull requests for improvements or bug fixes.


Citation

Lai, J. S., Burley, S. K., & Duarte, J. M. (2024). ZMPY3D: Accelerating protein structure volume analysis through vectorized 3D Zernike moments and Python-based GPU integration. (Submitted)

License

This project is licensed under the GNU General Public License v3.0. You can view the full license here.

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

ZMPY3D_TF-0.0.2.tar.gz (16.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ZMPY3D_TF-0.0.2-py3-none-any.whl (16.3 MB view details)

Uploaded Python 3

File details

Details for the file ZMPY3D_TF-0.0.2.tar.gz.

File metadata

  • Download URL: ZMPY3D_TF-0.0.2.tar.gz
  • Upload date:
  • Size: 16.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.16

File hashes

Hashes for ZMPY3D_TF-0.0.2.tar.gz
Algorithm Hash digest
SHA256 090d4ae929c65d29be1c4deb52892d15426e391d79b8dab51ddb15ecc3b07805
MD5 cd5df273097e2e203d618a18f931da64
BLAKE2b-256 9aa3810abac4a27d8672e41e80e9da5ebc00e80eebe685709a864faeedd6a818

See more details on using hashes here.

File details

Details for the file ZMPY3D_TF-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: ZMPY3D_TF-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 16.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.16

File hashes

Hashes for ZMPY3D_TF-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 6410915c137b9238986f850c423822d999d3d0658efb97822fb0b889c197e94a
MD5 6c529118fe5c1f55094a156e70773a5e
BLAKE2b-256 0c03282ebdf4dbd860975fcd69b68fd34dc3c11605abc9b51176296c3342baba

See more details on using hashes here.

Supported by

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