DTD | reactive atom-diatom collision system

by MMunibas Python Version: Current License: No License

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kandi X-RAY | DTD Summary

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

Construct a distribution-to-distribution (DTD) model for a reactive atom-diatom collision system. Here, we consider a grid-based DTD model for data from Set1 in reference arXiv:2005.14463. python3, TensorFlow and matplotlib. The data folder contains files for 9 sets of reactant and product state distributions from Set1 that were obtained by quasi-classical trajectory simulations. The corresponding sets of temperatures , can be read from the file tinput.dat. Run the code generate_input_and_reference.py located in the folder data_preprocessing to generate the files containing the input and reference values as well as a PDF with the corresponding plots, based on the 9 data sets from the folder data. The folder training already contains a file with input and reference values that were generated using the code generate_input_and_reference.py considering the complete Set1, with and .

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DTD has a low active ecosystem.

It has 3 star(s) with 4 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

DTD has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DTD is current.

Quality

DTD has no bugs reported.

Security

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

License

DTD 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

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

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

Top functions reviewed by kandi - BETA

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

Multi - layer MLP
Creates a neuron layer
tanh
Returns the next batch
Shuffle training data
Compute the inverse diagonal matrix
Calculate the Gauss - Kruskal - Kronecker function
Calculates the sigma value
Evaluate a keras model
Calculate the sigma of a grid
Softplus function
Return the validation data
Return training data

Get all kandi verified functions for this library.

DTD Key Features

No Key Features are available at this moment for DTD.

DTD Examples and Code Snippets

No Code Snippets are available at this moment for DTD.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install DTD

You can download it from GitHub.
You can use DTD 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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