DiSPy | Utility for applying the distortion symmetry method

by munrojm Python Version: Current License: MIT

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kandi X-RAY | DiSPy Summary

DiSPy is a Python library typically used in Manufacturing, Utilities, Energy, Utilities, Quantum Computing applications. DiSPy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

DiSPy is a utility for applying the distortion symmetry method (DSM) to the calculation of minimum energy pathways using the nudged elastic band (NEB) algorithm. For information on how to run DiSPy, including all relevant and necessary input parameters, see the PDF manual in the "docs" folder. Details on the DSM can be found in Ref. [1-3]. Example calculations can be found in the "examples" folder.

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DiSPy has a low active ecosystem.

It has 17 star(s) with 5 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DiSPy is current.

Quality

DiSPy has no bugs reported.

Security

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

License

DiSPy 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

DiSPy 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.

Top functions reviewed by kandi - BETA

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

Create a symmetry operation from a list of images
Check if two atoms are in the same range
Get symmetry data for a list of images
Standardize a vector
Returns the attributes of a rotation matrix
Determines if a vector is a vector ID
Implements the magic algorithm
Generate perturbation
Compute the diagonal diagonal matrix
Calculate the projection matrix
Generate the atom map
Get the name of the distortion
Returns the ISO number for the symmetry transformation
Convert a symbol to a name
Return the line number for a given SPG number
Print the distortion band
Pretty print a number
Calculate the D - D distortion
Estimate the tmatrix from the input basis
Get the irrep matrix
Get the irrepairs of symmetry operations
Get the Irrep matrix
Get the distortion group

Get all kandi verified functions for this library.

DiSPy Key Features

No Key Features are available at this moment for DiSPy.

DiSPy Examples and Code Snippets

No Code Snippets are available at this moment for DiSPy.

Community Discussions

Trending Discussions on DiSPy

where condition not supporting more than 1 condition

Can the cluster_status callback submit new jobs?

Python multiprocessing subprocesses with ordered printing?

QUESTION

where condition not supporting more than 1 condition

Asked 2019-Apr-29 at 10:43

The below code I want to use more than one condition but it is not supporting it is taking only one condition only p.score<=35 it is only displaying all records but p.score<=50 this condition applicable record is not dispying how can I resolve this issue.

...

ANSWER

Answered 2019-Apr-29 at 07:54

p.Score<=35 && p.Score <=50

Source https://stackoverflow.com/questions/55899062

QUESTION

Can the cluster_status callback submit new jobs?

Asked 2018-Sep-08 at 02:43

I'm developing a dispy script operating on a large number of objects (duh).

There are multiple operations to be performed for each object -- only one of them must happen first, the rest use the first job's results and can be done in any order.

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ANSWER

Answered 2018-Sep-08 at 02:43

Yes, callback can submit new job(s). See, for example, job_scheduler.py, which submits jobs in callback (although cluster_status can also be used for this purpose). From above description, it seems you can use callback instead of cluster_status.

Source https://stackoverflow.com/questions/52228871

QUESTION

Python multiprocessing subprocesses with ordered printing?

Asked 2017-Jun-12 at 01:07

I'm trying to run some Python functions in parallel, which has print commands throughout the function. What I want is to have each subprocess running the same function, to output to the main stdout in a grouped manner. What I mean by that is that I want each subprocess's output to only be printed after it has finished completing its task. If, however, some kind of error occured during this process, I want to still output whatever was done in the subprocess.

A small example:

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ANSWER

Answered 2017-Jun-12 at 01:07

As you've noticed, using a lock in this case would kill multiprocessing because you'd essentially have all the processes wait for a mutex release from the process who currently holds the 'rights' to STDOUT. However, running in parallel and printing in sync with your function/subprocess is logically exclusive.

What you can do instead is to have your main process serve as a 'printer' for your subprocesses in such a way that once your subprocess finishes/errors, then and only then it sends back to your main process what to print. You seem to be perfectly content for printing not to be 'real time' (nor it could, anyway, as previously mentioned) so that approach should serve you just right. So:

Source https://stackoverflow.com/questions/44488645

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

Vulnerabilities

No vulnerabilities reported

Install DiSPy

You can download it from GitHub.
You can use DiSPy 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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