CAMD | based sequential learning software for materials discovery | Machine Learning library

by TRI-AMDD Python Version: 2022.8.24 License: Apache-2.0

X-Ray Key Features Code Snippets(2)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | CAMD Summary

CAMD is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. CAMD has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install CAMD' or download it from GitHub, PyPI.

CAMD provides a flexible software framework for sequential / Bayesian optimization type campaigns for materials discovery. Its key features include:. A more in-depth description of the scientific framework can be found in this recent open-access article, which demonstrates an end-to-end CAMD-based framework for autonomous inorganic materials discovery using cloud-based density functional theory calculations.

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Quality

Security

License

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Support

CAMD has a low active ecosystem.

It has 48 star(s) with 25 fork(s). There are 7 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 7 have been closed. On average issues are closed in 40 days. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of CAMD is 2022.8.24

Quality

CAMD has 0 bugs and 0 code smells.

Security

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

CAMD code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

CAMD is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

CAMD 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, examples and code snippets are available.

It has 4628 lines of code, 260 functions and 47 files.

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

Top functions reviewed by kandi - BETA

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

Estimate hypotheses from candidate data
Fit the committee
Predict mean variance of committee models
Create a campaign factory from a chemsysysys
Load a dataframe into a pandas dataframe
Download a file from S3
Download a MATRIO data file
Calculate the state of each experiment
Analyze VASQP jobs
Analyze seed data
Update the results of the run
Estimate the hypothesis for a given candidate
Runs anALM analysis
Compute the hypothesis for the candidate data
Submit a new workflow
Create an instance from a reserved name
Get the hypotheses for a given candidate
Return new version number
Start new campaign
Calculate phononformation energy from M3Gnet
Update agent pool
Load seed data
Gather seed data from a pickle file
The list of hypo structures in the structure
Update changes md file
Release camd

Get all kandi verified functions for this library.

CAMD Key Features

No Key Features are available at this moment for CAMD.

CAMD Examples and Code Snippets

Computational Autonomy for Materials Discovery (CAMD),Installation,Mac OSX

Python

Lines of Code : 4

License : Permissive (Apache-2.0)

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brew install gcc

pip install numpy
pip install -r requirements.txt
python setup.py develop

Computational Autonomy for Materials Discovery (CAMD),Installation,Linux

Python

Lines of Code : 3

License : Permissive (Apache-2.0)

Copy

pip install numpy
pip install -r requirements.txt
python setup.py develop

Community Discussions

Trending Discussions on CAMD

Difference in behavior between between "normal" build and ExternalProject_Add

C# MySql how to bind stored procedure with dataGridView

Class becomes null when exception is thrown

QUESTION

Difference in behavior between between "normal" build and ExternalProject_Add

Asked 2019-Jun-04 at 10:09

I am trying to build the ceres-solver on linux using CMake's external project feature.

I have a specific version of Eigen that I built and the other dependencies are installed through my packet manager (BLAS, LAPACK and Suitesparse).

If I build Ceres-solver directly from source:

...

ANSWER

Answered 2019-Jun-04 at 10:09

It seems my build folder was corrupted. I just deleted the build folder & the install folder. When I re-run the install, everything worked perfectly.

Source https://stackoverflow.com/questions/56293558

QUESTION

C# MySql how to bind stored procedure with dataGridView

Asked 2017-Oct-24 at 23:58

I have here stored procedure and I don't know how to bind to the datagridview, need help with this?

here mysql code stored procedure:

...

ANSWER

Answered 2017-Oct-24 at 23:35

Try this

Source https://stackoverflow.com/questions/46921454

QUESTION

Class becomes null when exception is thrown

Asked 2017-Mar-03 at 18:26

I'm building a desktop application in WPF and I'm debugging an error that is triggered in a property changed method in code behind for a UserControl.

...

ANSWER

Answered 2017-Mar-03 at 18:26

FrameworkElementAutomationPeer.FromElement returned null, and calling RaiseAutomationEvent on that caused the NullReferenceException.

Source https://stackoverflow.com/questions/42583329

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

Vulnerabilities

No vulnerabilities reported

Install CAMD

CAMD can be installed using pip as pip install camd. If issues are encountered, we recommend following the installation procedures below:. Note that, since qmpy is currently only python 2.7 compatible, CAMD python 3 compatibility depends on a custom fork of qmpy here, which is installed using the setup.py procedure. We recommend using Anaconda python, and creating a fresh conda environment for the install (e. g. conda create -n MY_ENV_NAME).
Datasets for featurized OQMD entries for after-the-fact testing can be downloaded at data.matr.io/3. These are done automatically in the code and stored in the camd/_cache directory.

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: