DeepLigand

by gifford-lab Python Version: Current License: MIT

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

kandi X-RAY | DeepLigand Summary

DeepLigand is a Python library. DeepLigand has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However DeepLigand build file is not available. You can download it from GitHub.

DeepLigand

Support

Quality

Security

License

Reuse

Support

DeepLigand has a low active ecosystem.

It has 15 star(s) with 6 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 1 have been closed. On average issues are closed in 9 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DeepLigand is current.

Quality

DeepLigand has 0 bugs and 0 code smells.

Security

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

DeepLigand code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DeepLigand is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

DeepLigand releases are not available. You will need to build from source code and install.

DeepLigand has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Encodes sentences from a list of sentences
Encodes a sentence
Return a list of char ids
Convert a word to a numpy array
Embed data into an embedding file
Calculates the length of the feature in pep
Output a hdf5 file
Run an embedding
Load a model
Get basic setup
Restore the optimizer
Splits input file into tokens
Creates a directory
Create a directory
Rename hcc
Train the model
Generator for batches of data
Saves the current checkpoint
Evaluate the model at the given mass
Evaluate the model for a given dataset
Yields batches of data
Forwarding layer
Return basic setup
Convert a list of sentences into a sequence of tensors
Makes mhc mhc
Set up training and validation
Parse command line arguments
Pad seq_type seq_type

Get all kandi verified functions for this library.

DeepLigand Key Features

No Key Features are available at this moment for DeepLigand.

DeepLigand Examples and Code Snippets

No Code Snippets are available at this moment for DeepLigand.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install DeepLigand

With the above prerequisites installed, install and activate a Conda environment with all necessary Python packages by:.
R > 3.3
CUDA 8.0 with cudnn 5.1

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 .

Find more information at: