rcppcnpy | Rcpp bindings for NumPy files | Data Manipulation library

by eddelbuettel C++ Version: Current License: GPL-2.0

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kandi X-RAY | rcppcnpy Summary

rcppcnpy is a C++ library typically used in Utilities, Data Manipulation, Numpy applications. rcppcnpy has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

This package uses the cnpy library written by Carl Rogers to provide read and write facilities for files created with (or for) the NumPy extension for Python. Vectors and matrices of numeric types can be read or written to and from files as well as compressed files. Support for integer files is available if the package has been built with -std=c++11 which is the default starting with release 0.2.3 following the release of R 3.1.0, and available on all platforms following the release of R 3.3.0 with the updated 'Rtools'.

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rcppcnpy has a low active ecosystem.

It has 20 star(s) with 14 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 11 have been closed. On average issues are closed in 83 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of rcppcnpy is current.

Quality

rcppcnpy has no bugs reported.

Security

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

License

rcppcnpy is licensed under the GPL-2.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

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

Installation instructions, examples and code snippets are available.

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Community Discussions

Trending Discussions on rcppcnpy

How to read a numpy boolean array in R?

Loop over multidimensional NumPy fileArray in R

Reading numpy ndarrays into R?

QUESTION

How to read a numpy boolean array in R?

Asked 2021-May-28 at 12:08

I tried reading into R a boolean vector stored as a numpy array (.npy) with RcppCNPy package like this:

...

ANSWER

Answered 2021-May-28 at 12:08

EDIT:

The only way I found so far without modifying the numpy array itself is to use the reticulate package in R:

The reticulate package provides a comprehensive set of tools for interoperability between Python and R. The package includes facilities for translation between R and Python objects (for example, between R and Pandas data frames, or between R matrices and NumPy arrays).

Usage would be like this:

Source https://stackoverflow.com/questions/67722484

QUESTION

Loop over multidimensional NumPy fileArray in R

Asked 2019-Dec-18 at 17:20

I´m new to R and have problems to generate a for loop: I have a multidimensional array (NumPy File) in R and would like to automate the request of the part of the array. My array has a shape of (500, 192). I would like to plot a graph for Sample 1, 2 ... until sample 500.

AP has the structure: num [1:500, 1:192] 0.0323 0.0532 0.0135 0.0474 0.2026 ...

AP.shap has the structure: num [1:192] 3.23e-02 4.88e-04 1.39e-03 7.49e-04 5.82e-05 ...

...

ANSWER

Answered 2019-Dec-18 at 17:20

Simply generalize your process into a user-defined method that receives a number as input parameter since this is the only item that changes. Have that parameter slice data for sample and pass into titles and file names. See below where num is used.

Then, call it iteratively with for, while, or lapply which latter can store plot objects to a list for continued use later.

Source https://stackoverflow.com/questions/59395009

QUESTION

Reading numpy ndarrays into R?

Asked 2019-May-14 at 02:21

I've got a numpy ndarray in three dimensions, saved to disk as a .npy file. I want to bring it into R to apply some statistical functions that aren't implemented in python. Is there a convenient way to do so? The RcppCNPy doesn't generalize to 3+ dimensions, at least not yet.

I could always save the array in some different format on the python side, but that'd be less convenient and more error-prone.

Here's some dummy data:

...

ANSWER

Answered 2019-Apr-04 at 17:09

You can try to use reticulate to wrap from R around the existing Python code. This is a little newer, but pretty general supporting many types.

In the RcppCNPy package I have vignette showing how reticulate can do what RcppCNPy does (of course at a cost of potentially slightly more involved installation) so maybe give that a try?

Again, the vignette is here for your perusal.

Source https://stackoverflow.com/questions/55521314

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