root_numpy | The interface between ROOT and NumPy | File Utils library

by scikit-hep Python Version: 4.8.0 License: BSD-3-Clause

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

kandi X-RAY | root_numpy Summary

root_numpy is a Python library typically used in Utilities, File Utils, Numpy applications. root_numpy 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.

The interface between ROOT and NumPy

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Quality

Security

License

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root_numpy has a low active ecosystem.

It has 130 star(s) with 52 fork(s). There are 20 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 150 have been closed. On average issues are closed in 415 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of root_numpy is 4.8.0

Quality

root_numpy has 0 bugs and 0 code smells.

Security

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

root_numpy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

root_numpy is licensed under the BSD-3-Clause License. This license is Permissive.

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

Reuse

root_numpy releases are available to install and integrate.

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

root_numpy saves you 3397 person hours of effort in developing the same functionality from scratch.

It has 7283 lines of code, 445 functions and 63 files.

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

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root_numpy Key Features

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root_numpy Examples and Code Snippets

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Community Discussions

Trending Discussions on root_numpy

How to get uproot.iterate() output identical to the root_numpy root2array() output with jagged arrays

Accessing a column of a NumPy array of structured arrays

Add a new branch to a TTree in a ROOT file with root_numpy (Python)

QUESTION

How to get uproot.iterate() output identical to the root_numpy root2array() output with jagged arrays

Asked 2020-Mar-14 at 13:12

I know that there is a solution for the similar question: How to get uproot.iterate() output like the root_numpy root2array() output fast But as I understand it is suitable for the flat ROOT TTrees only. I want to have generalized solution for:

fixed-size dimension but nested data like particle momentum (px, py, pz) which are represented in the ROOT TTree as the vector
arbitrary-size dimension data

All my attempts to apply asjagged for it failed. Is it possible to avoid jaggedarray for case (1)?

...

ANSWER

Answered 2020-Mar-14 at 13:12

If the data are fixed-size but stored as vector, then they're treated as though they were not fixed-size. Uproot would always read them as jagged arrays, and therefore the asarray method described in the other question is unavailable.

That said, if you have more knowledge than your file's metadata and are willing to try an unsupported hack, you can force the interpretation of your vector to always have three elements. Here's an example—first, we need a suitable ROOT file:

Source https://stackoverflow.com/questions/60680991

QUESTION

Accessing a column of a NumPy array of structured arrays

Asked 2017-Jul-31 at 22:17

I've been given a multidimensional numpy array, x that looks like this:

...

ANSWER

Answered 2017-Jul-28 at 09:27

not sure how you are doing it,but it seems to work for me straight from the prompt

Source https://stackoverflow.com/questions/45369514

QUESTION

Add a new branch to a TTree in a ROOT file with root_numpy (Python)

Asked 2017-Jun-08 at 14:51

I would like to know how I could add a new branch to one of my TTree in a ROOT file using Python.

...

ANSWER

Answered 2017-Jun-08 at 14:51

Actually I could found out the solution by myself:

I was not using the correct method from numpy, I should have used the array2root instead of the array2tree.

Source https://stackoverflow.com/questions/44002692

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

Vulnerabilities

No vulnerabilities reported

Install root_numpy

You can download it from GitHub.
You can use root_numpy 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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