Generative-Molecules | DIRECT capstone project : Molecules Design Using Deep

by chennnnnyize Python Version: Current License: No License

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kandi X-RAY | Generative-Molecules Summary

Generative-Molecules is a Python library typically used in Institutions, Learning, Education applications. Generative-Molecules has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

This is the repo for DIRECT capstone project: Molecules Design Using Deep Generative Models. Group Members: Xiaoxiao Jia, Jiaxu Qin and Yize Chen. Advisors: Baosen Zhang and Alex K.-Y. Jen.

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Support

Generative-Molecules has a low active ecosystem.

It has 23 star(s) with 11 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 2 have been closed. On average issues are closed in 15 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Generative-Molecules is current.

Quality

Generative-Molecules has no bugs reported.

Security

Generative-Molecules has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Generative-Molecules does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Generative-Molecules releases are not available. You will need to build from source code and install.

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

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

Top functions reviewed by kandi - BETA

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

Train the generator
Run the pipeline
Create batches from samples
Yield batches of data
Load the training set
Return a list of char_dict
Pad a string by n characters
Build a vocabulary from a smiles
Visualize the latitude
Argument parser
Run autoencoder
Predict the PCE metric for a given list of smiles
Load the metrics
Generates the decoder for the model
Calculate the bandgap for a set of smiles
Calculate melting point
Interpolate from source to destination
Generate a batch variance
Estimate Lipinski
Evaluate the model
Vectorize data
Calculate the score of a structure in a molecule
Train a neural network
Define a metric
Set the training program
Create the model

Get all kandi verified functions for this library.

Generative-Molecules Key Features

No Key Features are available at this moment for Generative-Molecules.

Generative-Molecules Examples and Code Snippets

No Code Snippets are available at this moment for Generative-Molecules.

Community Discussions

No Community Discussions are available at this moment for Generative-Molecules.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install Generative-Molecules

You can download it from GitHub.
You can use Generative-Molecules 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.