# npy-matlab

**Repository Path**: winter_master/npy-matlab

## Basic Information

- **Project Name**: npy-matlab
- **Description**: Experimental code to read/write NumPy .NPY files in MATLAB
- **Primary Language**: Unknown
- **License**: BSD-2-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-23
- **Last Updated**: 2020-12-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

[![Travis](https://api.travis-ci.org/kwikteam/npy-matlab.svg?branch=master "Travis")](https://travis-ci.org/kwikteam/npy-matlab)
# npy-matlab

Code to read and write NumPy's NPY format (`.npy` files) in MATLAB.

This is experimental code and still work in progress. For example, this code:
- Only reads a subset of all possible NPY files, specifically N-D arrays of
  certain data types.
- Only writes little endian, fortran (column-major) ordering
- Only writes with NPY version number 1.0.
- Always outputs a shape according to matlab's convention, e.g. (10, 1)
  rather than (10,).

Feel free to open an issue and/or send a pull request for improving the
state of this project!

For the complete specification of the NPY format, see the [NumPy documentation](https://www.numpy.org/devdocs/reference/generated/numpy.lib.format.html).

## Installation
After downloading npy-matlab as a zip file or via git, just add the
npy-matlab directory to your search path:

```matlab
>> addpath('my-idiosyncratic-path/npy-matlab/npy-matlab')  
>> savepath
```

## Usage example
```matlab
>> a = rand(5,4,3);
>> writeNPY(a, 'a.npy');
>> b = readNPY('a.npy');
>> sum(a(:)==b(:))
ans =

    60
```

## Tests
Roundtrip testing is performed using Travis CI and GNU Octave, see
the `.travis.yml` file and `tests/test_npy_roundtrip.py`.

You can also use two "manual testing scripts":

- See `tests/npy.ipynb` for Python tests.
- See `tests/test_readNPY.m` for MATLAB reading/writing tests.

## Memory mapping npy files
See `examples/exampleMemmap.m` for an example of how to memory map a `.npy` file in MATLAB, which is not trivial when the file uses C-ordering (i.e., row-major order) rather than Fortran-ordering (i.e., column-major ordering). MATLAB's memory mapping only supports Fortran-ordering, but Python's default is C-ordering so `.npy` files created with Python defaults are not straightforward to read in MATLAB.