TensorMol | Tensorflow Molecules TensorMol

by jparkhill Python Version: 0.1 License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | TensorMol Summary

TensorMol is a Python library typically used in Simulation, Deep Learning applications. TensorMol has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install TensorMol' or download it from GitHub, PyPI.

Kun Yao (kyao@nd.edu), John Herr (jherr1@nd.edu), David Toth (dtoth1@nd.edu), Ryker McIntyre(rmcinty3@nd.edu), Nicolas Casetti, John Parkhill (john.parkhill@gmail.com).

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Quality

Security

License

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Support

TensorMol has a low active ecosystem.

It has 229 star(s) with 74 fork(s). There are 46 watchers for this library.

It had no major release in the last 12 months.

There are 17 open issues and 19 have been closed. On average issues are closed in 18 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of TensorMol is 0.1

Quality

TensorMol has 0 bugs and 0 code smells.

Security

TensorMol has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

TensorMol code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

TensorMol is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

TensorMol releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

TensorMol saves you 22716 person hours of effort in developing the same functionality from scratch.

It has 44485 lines of code, 1559 functions and 103 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed TensorMol and discovered the below as its top functions. This is intended to give you an instant insight into TensorMol implemented functionality, and help decide if they suit your requirements.

Evaluate the model
Bump the population
Run qchemDF on a molecule
Calculate the potential velocity
Build the train set
Verify the shape of the molecule
Loads the TmManager
Loads the set
Prepares the Jacobian
Evaluate test batch
Get a batch of test cases
Gets a test batch
Computes the energy layer
Evaluate a batch
Group atoms
Test the periodic force field
R Compute the Harmonic Spectral spectra
Perform train step of training step
Train the model
Performs training
Generate an ANISyM
Get a batch of test data
Evaluate BPDipole
Builds the train model
Returns a batch of training data
Creates a batch of training data

Get all kandi verified functions for this library.

TensorMol Key Features

No Key Features are available at this moment for TensorMol.

TensorMol Examples and Code Snippets

No Code Snippets are available at this moment for TensorMol.

Community Discussions

Trending Discussions on TensorMol

pip search finds tensorflow, but pip install does not

QUESTION

pip search finds tensorflow, but pip install does not

Asked 2020-Jan-23 at 06:55

I am trying to build a Django app that would use Keras models to make recommendations. Right now I'm trying to use one custom container that would hold both Django and Keras. Here's the Dockerfile I've written.

...

ANSWER

Answered 2019-Jan-02 at 22:56

It looks like tensorflow only publishes wheels (and only up to 3.6), and Alpine linux is not manylinux1-compatible due to its use of musl instead of glibc. Because of this, pip cannot find a suitable installation candidate and fails. Your best options are probably to build from source or change your base image.

Source https://stackoverflow.com/questions/54014076

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install TensorMol

You can install using 'pip install TensorMol' or download it from GitHub, PyPI.
You can use TensorMol like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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