R: File access to data files written by (or for) NumPy (Numeric...

RcppCNPy-package {RcppCNPy} | R Documentation

## File access to data files written by (or for) NumPy (Numeric Python) modules

### Description

This package provides access to the `cnpy` library by Carl Rogers which provides read and write facilities for files created with (or for) the NumPy extension for Python.

Support is provided to reading and writing of either vectors or matrices of numeric or integer types.

Files with `gzip` compression can be transparently read and written as well.

### Usage

      npyLoad(filename, type="numeric", dotranspose=TRUE)
      npySave(filename, object, mode="w", checkPath=TRUE)
      npyHasIntegerSupport()

### Arguments

`filename` | string with (path and) filename for a `npy` object file. If the string ends with `.gz`, compressed files can be read or written.
`type` | string with type 'numeric' (default) or 'integer'.
`object` | an R object, currently limited to a vector or matrix of either integer or numeric type
`dotranspose` | a boolean variable indicating whether a two-dimensional object should be transposed after reading, default is true
`mode` | a one-character string indicating whether files are appended to ("a") or written ("w", the default). In case of writing `gzip`-ed file, this option is not supported as such files can only be (over-)written, and bot appended.
`checkPath` | a boolean variable indicating whether a path implied in the `filename` argument is to be checked for existing directories, default is true.

### Details

The package uses Rcpp modules to provide R bindings `npyLoad()` and `npySave()` which wrap the `npy_load()` and `npy_save()` functions. Currently, only one- and two-dimensional vectors and matrices are suppported; higher-dimensional arrays could be added.

Integer support requires access to the `long long` type which is available if the package is built using the C++11 standard; this is the default since release 0.2.3 which came out after R 3.1.0 permitted used of C++11 in CRAN packages.

### Author(s)

Dirk Eddelbuettel provided the binding to R (using the Rcpp package).

Carl Rogers wrote the underlying `cnpy` library, which is released under the MIT license.

Maintainer: Dirk Eddelbuettel <edd@debian.org>

### References

Rcpp, in particular the Rcpp modules documentation.

The `cnpy` repository: https://github.com/rogersce/cnpy

### See Also

`Rcpp`

### Examples

    ## Not run:
        library(RcppCNPy)

        ## load NumPy file with floating-point data
        fmat <- npyLoad("fmat.npy")

        ## load NumPy file with integer data
        imat <- npyLoad("imat.npy", "integer")

        ## save floating-point data: matrix and vector
        M <- matrix(0:11, 3, 4, byrow=TRUE) * 1.1
        v <- v <- 0:4 * 1.1
        npySave("fmat.npy", M)
        npySave("fvec.npy", v)

        ## save integer data: matrix and vector
        M <- matrix(0:11, 3, 4, byrow=TRUE)
        v <- v <- 0:4
        npySave("imat.npy", M)
        npySave("ivec.npy", v)

    ## End(Not run)

[Package RcppCNPy version 0.2.10 Index]