Giter Site home page Giter Site logo

stdlib-js / ndarray-base-broadcast-shapes Goto Github PK

View Code? Open in Web Editor NEW
1.0 3.0 0.0 449 KB

Broadcast array shapes to a single shape.

Home Page: https://github.com/stdlib-js/stdlib

License: Apache License 2.0

Makefile 46.68% JavaScript 33.76% C 19.55%
nodejs javascript stdlib node node-js types base ndarray broadcast broadcasting multidimensional array utilities utility utils util

ndarray-base-broadcast-shapes's Introduction

About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

broadcastShapes

NPM version Build Status Coverage Status

Broadcast array shapes to a single shape.

Installation

npm install @stdlib/ndarray-base-broadcast-shapes

Alternatively,

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

Usage

var broadcastShapes = require( '@stdlib/ndarray-base-broadcast-shapes' );

broadcastShapes( shapes )

Broadcasts array shapes to a single shape.

var sh1 = [ 8, 1, 6, 1 ];
var sh2 = [ 7, 1, 5 ];

var sh = broadcastShapes( [ sh1, sh2 ] );
// returns [ 8, 7, 6, 5 ]

Notes

  • When operating on two arrays, the function compares their shapes element-wise, beginning with the trailing (i.e., rightmost) dimension. The following are examples of compatible shapes and their corresponding broadcasted shape:

    A      (4d array):  8 x 1 x 6 x 1
    B      (3d array):      7 x 1 x 5
    ---------------------------------
    Result (4d array):  8 x 7 x 6 x 5
    
    A      (2d array):  5 x 4
    B      (1d array):      1
    -------------------------
    Result (2d array):  5 x 4
    
    A      (2d array):  5 x 4
    B      (1d array):      4
    -------------------------
    Result (2d array):  5 x 4
    
    A      (3d array):  15 x 3 x 5
    B      (3d array):  15 x 1 x 5
    ------------------------------
    Result (3d array):  15 x 3 x 5
    
    A      (3d array):  15 x 3 x 5
    B      (2d array):       3 x 5
    ------------------------------
    Result (3d array):  15 x 3 x 5
    
    A      (3d array):  15 x 3 x 5
    B      (2d array):       3 x 1
    ------------------------------
    Result (3d array):  15 x 3 x 5
    
    A      (5d array):  8 x 1 x 1 x 6 x 1
    B      (4d array):      1 x 7 x 1 x 5
    C      (5d array):  8 x 4 x 1 x 6 x 5
    -------------------------------------
    Result (5d array):  8 x 4 x 7 x 6 x 5
    
    A      (5d array):  8 x 1 x 1 x 6 x 1
    B      (1d array):                  0
    -------------------------------------
    Result (5d array):  8 x 1 x 1 x 6 x 0
    
    A      (5d array):  8 x 0 x 1 x 6 x 1
    B      (2d array):              6 x 5
    -------------------------------------
    Result (5d array):  8 x 0 x 1 x 6 x 5
    
    A      (5d array):  8 x 1 x 1 x 6 x 1
    B      (5d array):  8 x 0 x 1 x 6 x 1
    -------------------------------------
    Result (5d array):  8 x 0 x 1 x 6 x 1
    
    A      (3d array):  3 x 2 x 1
    B      (0d array):
    -----------------------------
    Result (3d array):  3 x 2 x 1
    
    A      (0d array):
    B      (3d array):  3 x 2 x 1
    -----------------------------
    Result (3d array):  3 x 2 x 1
    

    As demonstrated above, arrays are not required to have the same number of dimensions in order to be broadcast compatible. Array shapes with fewer dimensions are implicitly prepended with singleton dimensions (i.e., dimensions equal to 1). Accordingly, the following example

    A      (2d array):  5 x 4
    B      (1d array):      4
    -------------------------
    Result (2d array):  5 x 4
    

    is equivalent to

    A      (2d array):  5 x 4
    B      (2d array):  1 x 4
    -------------------------
    Result (2d array):  5 x 4
    

    Similarly, a zero-dimensional array is expanded (by prepending singleton dimensions) from

    A      (3d array):  3 x 2 x 1
    B      (0d array):
    -----------------------------
    Result (3d array):  3 x 2 x 1
    

    to

    A      (3d array):  3 x 2 x 1
    B      (3d array):  1 x 1 x 1
    -----------------------------
    Result (3d array):  3 x 2 x 1
    

    Stated otherwise, every array has implicit leading dimensions of size 1. During broadcasting, a 3 x 4 matrix is the same as a 3 x 4 x 1 x 1 x 1 multidimensional array.

  • Two respective dimensions in two shape arrays are compatible if

    1. the dimensions are equal.
    2. one dimension is 1.

    The two aforementioned rules apply to empty arrays or arrays that have a dimension of size 0. For unequal dimensions, the size of the dimension which is not 1 determines the size of the output shape dimension.

    Accordingly, dimensions of size 0 must be paired with a dimension of size 0 or 1. In such cases, by the rules above, the size of the corresponding output shape dimension is 0.

  • The function returns null if provided incompatible shapes (i.e., shapes which cannot be broadcast with one another).

    var sh1 = [ 3, 2 ];
    var sh2 = [ 2, 3 ];
    
    var sh = broadcastShapes( [ sh1, sh2 ] );
    // returns null

    The following are examples of array shapes which are not compatible and do not broadcast:

    A      (1d array):  3
    B      (1d array):  4                   # dimension does not match
    
    A      (2d array):      2 x 1
    B      (3d array):  8 x 4 x 3           # second dimension does not match
    
    A      (3d array):  15 x 3 x 5
    B      (2d array):  15 x 3              # singleton dimensions can only be prepended, not appended
    
    A      (5d array):  8 x 8 x 1 x 6 x 1
    B      (5d array):  8 x 0 x 1 x 6 x 1   # second dimension does not match
    

Examples

var lpad = require( '@stdlib/string-left-pad' );
var broadcastShapes = require( '@stdlib/ndarray-base-broadcast-shapes' );

var shapes;
var out;
var sh;
var i;
var j;

function shape2string( shape ) {
    return lpad( shape.join( ' x ' ), 20, ' ' );
}

shapes = [
    [ [ 1, 2 ], [ 2 ] ],
    [ [ 1, 1 ], [ 3, 4 ] ],
    [ [ 6, 7 ], [ 5, 6, 1 ], [ 7 ], [ 5, 1, 7 ] ],
    [ [ 1, 3 ], [ 3, 1 ] ],
    [ [ 1 ], [ 3 ] ],
    [ [ 2 ], [ 3, 2 ] ],
    [ [ 2, 3 ], [ 2, 3 ], [ 2, 3 ], [ 2, 3 ] ],
    [ [ 1, 2 ], [ 1, 2 ] ]
];

for ( i = 0; i < shapes.length; i++ ) {
    sh = shapes[ i ];
    for ( j = 0; j < sh.length; j++ ) {
        console.log( shape2string( sh[ j ] ) );
    }
    console.log( lpad( '', 20, '-' ) );

    out = broadcastShapes( sh );
    console.log( shape2string( out )+'\n' );
}

C APIs

Usage

#include "stdlib/ndarray/base/broadcast_shapes.h"

stdlib_ndarray_broadcast_shapes( M, **shapes, *ndims, *out )

Broadcasts array shapes to a single shape.

#include "stdlib/ndarray/base/broadcast_shapes.h"
#include <stdint.h>

int64_t N1 = 4;
int64_t sh1[] = { 8, 1, 6, 1 };

int64_t N2 = 3;
int64_t sh2[] = { 7, 1, 5 };

int64_t ndims[] = { N1, N2 };
int64_t *shapes[] = { sh1, sh2 };

int64_t out[] = { 0, 0, 0, 0 };
int8_t status = stdlib_ndarray_broadcast_shapes( 2, shapes, ndims, out );
if ( status != 0 ) {
    // Handle error...
}

The function accepts the following arguments:

  • M: [in] int64_t number of shape arrays.
  • shapes: [in] int64_t** array of shape arrays (dimensions).
  • ndims: [in] int64_t* number of dimensions for each respective shape array.
  • out: [out] int64_t* output shape array.
int8_t stdlib_ndarray_broadcast_shapes( int64_t M, int64_t *shapes[], int64_t ndims[], int64_t *out );

If successful, the function returns 0; otherwise, the function returns -1 (e.g., due to incompatible shapes).

Notes

  • Even if the function is unsuccessful, the function may still overwrite elements in the output array before returning. In other words, do not assume that providing incompatible shapes is a no-op with regard to the output array.

Examples

#include "stdlib/ndarray/base/broadcast_shapes.h"
#include <stdint.h>
#include <stdio.h>
#include <inttypes.h>

int main( void ) {
    int64_t N1 = 4;
    int64_t sh1[] = { 8, 1, 6, 1 };

    int64_t N2 = 3;
    int64_t sh2[] = { 7, 1, 5 };

    int64_t ndims[] = { N1, N2 };
    int64_t *shapes[] = { sh1, sh2 };

    int64_t out[] = { 0, 0, 0, 0 };
    int8_t status = stdlib_ndarray_broadcast_shapes( 2, shapes, ndims, out );
    if ( status != 0 ) {
        printf( "incompatible shapes\n" );
        return 1;
    }
    int64_t i;
    printf( "shape = ( " );
    for ( i = 0; i < N1; i++ ) {
        printf( "%"PRId64"", out[ i ] );
        if ( i < N1-1 ) {
            printf( ", " );
        }
    }
    printf( " )\n" );
    return 0;
}

Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2023. The Stdlib Authors.

ndarray-base-broadcast-shapes's People

Contributors

stdlib-bot avatar

Stargazers

 avatar

Watchers

 avatar  avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.