Vectorious: NDArray

new NDArray(data, optionsopt)

Constructs or copies an NDArray instance.

Parameters

data
options Object <optional>

Properties
- shape Array.<Number> <optional>
- length Number <optional>
- strides Array.<Number> <optional>
- dtype string <optional>

Example

import { NDArray } from 'vectorious';

new NDArray() // => array([], dtype=float64)
new NDArray([]) // => array([], dtype=float64)
new NDArray([1, 2, 3]) // => array([1, 2, 3], dtype=float64)
new NDArray([[1, 2], [3, 4]]) // => array([ [ 1, 2 ], [ 3, 4 ] ], dtype=float64)
new NDArray(new Int32Array([1, 2, 3])) // => array([ 1, 2, 3 ], dtype=int32)
new NDArray([1, 2, 3, 4], {
  shape: [2, 2],
  dtype: 'uint32'
}) // => array([ [ 1, 2 ], [ 3, 4 ] ], dtype=uint32)

Source

core/index.js , line 90

Members

dataTypedArray

Type

TypedArray

Default Value

new Float64Array(0)

Source

core/index.js , line 114

dtypeString

Type

String

Default Value

'float64'

Source

core/index.js , line 121

lengthNumber

Type

Number

Default Value

Source

core/index.js , line 128

shapeArray.<Number>

Type

Array.<Number>

Default Value

Source

core/index.js , line 135

stridesArray.<Number>

Type

Array.<Number>

Default Value

Source

core/index.js , line 142

TNDArray

Short for this.copy().transpose()

Type

NDArray

Source

core/index.js , line 299

wNumber

Gets or sets the value at index 3

Type

Number

Source

core/index.js , line 287

xNumber

Gets or sets the value at index 0

Type

Number

Source

core/index.js , line 251

yNumber

Gets or sets the value at index 1

Type

Number

Source

core/index.js , line 263

zNumber

Gets or sets the value at index 2

Type

Number

Source

core/index.js , line 275

Methods

abs() → {this}

Returns the absolute value of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([-1, -2, -3]).abs() // <=> array([1, 2, 3])

Source

core/abs.js , line 21

acos() → {this}

Returns the arccosine of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([-1, 0, 1]).acos(); // <=> array([3.141592653589793, 1.5707963267948966, 0])

Source

core/acos.js , line 21

acosh(x) → {this}

Returns the hyperbolic arccosine of each element of current array.

Parameters

x NDArray

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).acosh(); // <=> array([0, 1.316957950592041, 1.7627471685409546])

Source

core/acosh.js , line 21

add(x) → {NDArray}

Adds x multiplied by alpha to the current array. Accelerated with BLAS ?axpy.

Parameters

x NDArray

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).add([4, 5, 6]); // <=> array([5, 7, 9])

Source

core/add.js , line 43

angle(x) → {number}

Determines the angle between the current vector and x.

Parameters

x NDArray

Returns

number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).angle([4, 5, 6]); // <=> 0.22572622788897287

Source

core/angle.js , line 21

asin() → {this}

Returns the arcsine of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([-1, 0, 1]).asin() // <=> array([-1.5707963705062866, 0, 1.5707963705062866])

Source

core/asin.js , line 21

asinh() → {this}

Returns the hyperbolic arcsine of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([0, 1, 2]).asinh() // <=> array([0, 0.8813735842704773, 1.4436354637145996])

Source

core/asinh.js , line 21

atan() → {this}

Returns the arctangent of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).atan() // <=> array([0.7853981852531433, 1.1071487665176392, 1.249045729637146])

Source

core/atan.js , line 21

atanh() → {this}

Returns the hyperbolic arctangent of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([0, -0.5]).atanh(); // <=> array([0, -0.5493061542510986])

Source

core/atanh.js , line 21

augment(x) → {this}

Augments x with current matrix.

Parameters

x NDArray

Returns

this

Example

import { array } from 'vectorious/core/array';

array([[1, 2], [3, 4]]).augment(array([[1], [2]])); // <=> array([[1, 2, 1], [3, 4, 2]])

Source

core/augment.js , line 21

binOp(x) → {this}

Perform binary operation f on x in the current array.

Parameters

x NDArray

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).binOp([4, 5, 6], (a, b) => a + b); // => array([[5, 7, 9])

Source

core/binOp.js , line 21

cbrt() → {this}

Returns the cube root of each element of current array.

Returns

this

Example

import { cbrt } from 'vectorious/core/cbrt';

cbrt([1, 8, 27]); // => array([1, 2, 3])

Source

core/cbrt.js , line 21

ceil() → {NDArray}

Returns smallest integer greater than or equal to of each element of current array.

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([0.5, 1.5, 2.5]).ceil(); // <=> array([1, 2, 3])

Source

core/ceil.js , line 21

check()

Asserts if indices i, j, ..., n are within the bounds of current array

Parameters

...indices Array.<Number>

Example

import { array } from 'vectorious/core/array';

array([0.5, 1.5, 2.5]).check(3); // Error: index out of bounds

Throws

index out of bounds
Type Error

Source

core/check.js , line 22

combine(x) → {this}

Combines the current vector with x

Parameters

x NDArray

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).combine([4, 5, 6]); // => array([1, 2, 3, 4, 5, 6])

Source

core/combine.js , line 21

copy() → {NDArray}

Makes a copy of the class and underlying data

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).copy(); // => array([1, 2, 3])

Source

core/copy.js , line 21

cos() → {this}

Returns the cosine of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([0, Math.PI / 2, Math.PI]).cos(); // => array([1, 0, -1])

Source

core/cos.js , line 21

cosh() → {this}

Returns the hyperbolic cosine of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([0, 1, 2]).cosh(); // => array([1, 1.5430806875228882, 3.762195587158203])

Source

core/cosh.js , line 21

cross(x) → {this}

Computes the cross product of the current vector and the vector x This operation can only calculated for vectors with three components. Otherwise it throws an exception.

Parameters

x NDArray

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).cross([4, 5, 6]); // <=> array([-3, 6, -3])

Source

core/cross.js , line 23

det() → {Number}

Gets the determinant of current matrix using LU factorization.

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([[0, 1], [2, 3]]).det(); // => -2

Source

core/det.js , line 19

diagonal() → {this}

Gets the diagonal of current matrix.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).diagonal(); // => array([1, 4])

Source

core/diagonal.js , line 19

dot(x) → {Number}

Performs dot multiplication with x and current array Accelerated with BLAS ?dot.

Parameters

x NDArray

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).dot([4, 5, 6]); // => 32

Source

core/dot.js , line 43

eig() → {Array.<NDArray>}

Gets eigenvalues and eigenvectors of the current matrix using the Jacobi method. Accelerated with LAPACK ?geev.

Returns

Array.<NDArray>

Example

import { array } from 'vectorious/core/array';

array([[1, 0, 0], [0, 2, 0], [0, 0, 3]]).eig(); // => [array([1, 2, 3]), array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])]

Source

core/eig.js , line 45

equals(x, tolerance) → {Boolean}

Checks if current array and x are equal.

Parameters

x NDArray
tolerance Number

Returns

Boolean

Example

import { equals } from 'vectorious/core/equals';

array([1, 2, 3]).equals([1, 2, 3]); // => true

Source

core/equals.js , line 22

equidimensional(x)

Asserts if current array and x have the same shape

Parameters

x NDArray

Deprecated

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).equidimensional([1, 2]); // Error: shapes 3 and 2 do not match

Throws

shapes x and y do not match
Type Error

Source

core/equidimensional.js , line 23

equilateral(x)

Asserts if current array and x have the same length

Parameters

x NDArray

Deprecated

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).equilateral([1, 2]); // Error: lengths 3 and 2 do not match

Throws

lengths x and y do not match
Type Error

Source

core/equilateral.js , line 23

exp() → {this}

Returns e^x of each element of current array, where x is the argument, and e is Euler's constant (2.718…), the base of the natural logarithm.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).exp(); // <=> array([2.7182817459106445, 7.389056205749512, 20.08553695678711])

Source

core/exp.js , line 23

expm1() → {this}

Returns subtracting 1 from exp(x) of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).expm1(); // <=> array([1.7182817459106445, 6.389056205749512, 19.08553695678711])

Source

core/expm1.js , line 21

fill(value) → {this}

Fills the current array with a scalar value

Parameters

value Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).fill(0); // <=> array([0, 0, 0])

Source

core/fill.js , line 21

floor() → {this}

Returns the largest integer less than or equal to a number of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1.5, 2.5, 3.5]).floor(); // <=> array([1, 2, 3])

Source

core/floor.js , line 21

forEach(f)

Equivalent to TypedArray.prototype.forEach.

Parameters

f function

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).forEach(console.log);
// 1 0 [ 1, 2, 3 ]
// 2 1 [ 1, 2, 3 ]
// 3 2 [ 1, 2, 3 ]

Source

core/forEach.js , line 24

fround() → {this}

Returns the nearest single precision float representation of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([-5.05, 5.05]).fround(); // <=> array([-5.050000190734863, 5.050000190734863])

Source

core/fround.js , line 21

gauss() → {NDArray}

Gauss-Jordan elimination (i.e. returns the reduced row echelon form) of the current matrix.

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([[1, 2, 3], [4, 5, 6]]).gauss(); // <=> array([[1, 0, -1], [-0, 1, 2]])

Source

core/gauss.js , line 20

get() → {Number}

Gets the element at i, j, ..., n from current vector.

Parameters

...indices Array.<Number>

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).get(2); // 3

Source

core/get.js , line 20

inv() → {this}

Determines the inverse of current matrix using Gaussian elimination. Accelerated with LAPACK ?getri.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([[2, -1, 0], [-1, 2, -1], [0, -1, 2]]).inv(); // <=> array([[0.75, 0.5, 0.25], [0.5, 1, 0.5], [0.25, 0.5, 0.75]])

Source

core/inv.js , line 45

log() → {this}

Returns the natural logarithm (log_e, also ln) of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).log(); // <=> array([0, 0.6931471824645996, 1.0986123085021973])

Source

core/log.js , line 21

log1p() → {this}

Returns the natural logarithm (log_e, also ln) of 1 + x for each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]); // <=> array([0.6931471824645996, 1.0986123085021973, 1.3862943649291992])

Source

core/log1p.js , line 21

log2() → {this}

Returns the base 2 logarithm of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 4]).log2(); // => array([0, 1, 2])

Source

core/log2.js , line 21

log10() → {this}

Returns the base 10 logarithm of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([10, 100, 1000]).log10(); // <=> array([1, 2, 3])

Source

core/log10.js , line 21

lu() → {Array.<(NDArray|Int32Array)>}

Performs full LU decomposition on current matrix. Accelerated with LAPACK ?getrf.

Returns

Array.<(NDArray|Int32Array)>

Example

import { array } from 'vectorious/core/array';

array([[1, 3, 5], [2, 4, 7], [1, 1, 0]]).lu(); // => [array([[1, 0, 0], [0.5, 1, 0], [0.5, -1, 1]]), array([[2, 4, 7], [0, 1, 1.5], [0, 0, -2]]), Int32Array([2, 2, 3])]

Source

core/lu.js , line 22

lu_factor() → {Array.<(NDArray|Int32Array)>}

Performs LU factorization on current matrix. Accelerated with LAPACK ?getrf.

Returns

Array.<(NDArray|Int32Array)>

Example

import { array } from 'vectorious/core/array';

array([[1, 3, 5], [2, 4, 7], [1, 1, 0]]).lu_factor(); // <=> [array([[2, 4, 7], [0.5, 1, 1.5], [0.5, -1, -2]]), Int32Array([2, 2, 3])]

Source

core/lu_factor.js , line 41

map() → {this}

Equivalent to TypedArray.prototype.map.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).map(value => -value); // => array([-1, -2, -3])

Source

core/map.js , line 20

max() → {Number}

Gets the maximum value (smallest) element of current array. Accelerated with BLAS i?amax.

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).max(); // => 3

Source

core/max.js , line 42

mean() → {Number}

Gets the arithmetic mean of current array.

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).mean(); // => 2

Source

core/mean.js , line 20

min() → {Number}

Gets the minimum value (smallest) element of current array.

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).min(); // 1

Source

core/min.js , line 20

multiply(x) → {NDArray}

Multiplies current matrix with x. Accelerated with BLAS ?gemm.

Parameters

x NDArray

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([[1, 2]]).multiply([[1], [2]]); // <=> array([[5]])

Source

core/multiply.js , line 44

norm() → {Number}

Calculates the norm of current array (also called L2 norm or Euclidean length). Accelerated with BLAS ?nrm2.

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).norm(); // => 3.7416574954986572

Source

core/norm.js , line 42

normalize() → {this}

Normalizes current vector.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).normalize(); // => array([0.26726123690605164, 0.5345224738121033, 0.8017836809158325])

Source

core/normalize.js , line 19

pow(exponent) → {this}

Returns each element of current array to the exponent power, that is, element^exponent.

Parameters

exponent Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).pow(2); // <=> array([1, 4, 9])

Source

core/pow.js , line 22

prod() → {Number}

Product of all elements of current array

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).prod(); // => 6

Source

core/prod.js , line 20

product() → {NDArray}

Hadamard product of current matrix and x

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).product([4, 5, 6]); // <=> array([4, 10, 18])

Source

core/product.js , line 21

project() → {NDArray}

Projects the current vector onto x using the projection formula (y * (x * y / y * y)).

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).project([4, 5, 6]); // <=> array([1.6623376607894897, 2.0779221057891846, 2.49350643157959])

Source

core/project.js , line 20

push(value) → {this}

Pushes a new value into current vector.

Parameters

value Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).push(4); // => array([1, 2, 3, 4])

Source

core/push.js , line 21

rank(tolerance) → {Number}

Finds the rank of current matrix using gaussian elimination.

Parameters

tolerance Number

To Do

Switch to SVD algorithm

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([[1, 1, 1], [2, 2, 2], [3, 3, 3]]).rank(); // => 1

Source

core/rank.js , line 21

reciprocal() → {this}

Gets the element-wise reciprocal of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]); // => array([1, 0.5, 0.3333333432674408])

Source

core/reciprocal.js , line 20

reduce(f, initialValue) → {Number}

Equivalent to TypedArray.prototype.reduce.

Parameters

f function
initialValue Number

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).reduce((a, b) => a + b, 0); // => 6

Source

core/reduce.js , line 22

reshape() → {this}

Reshapes current array

Parameters

...shape Array.<Number>

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3, 4]).reshape(2, 2); // <=> array([[1, 2], [3, 4]])

Source

core/reshape.js , line 21

round() → {this}

Returns the value of each element of current array rounded to the nearest integer.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1.2, 2.8, 3.5]).round(); // <=> array([1, 3, 4])

Source

core/round.js , line 21

row_add(dest, source, scalar) → {this}

Adds a multiple of one row multiplied by scalar to another inside current matrix.

Parameters

dest Number
source Number
scalar Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([[1, 2], [3, 4]]).row_add(1, 0, 2); // <=> array([[1, 2], [5, 8]])

Source

core/row_add.js , line 22

scale(scalar) → {this}

Multiplies all elements of current array with a specified scalar. Accelerated with BLAS ?scal.

Parameters

scalar Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).scale(2); // <=> array([2, 4, 6])

Source

core/scale.js , line 43

set(value) → {this}

Sets the element at i, j, ..., n to value.

Parameters

...indices Array.<Number>
value Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).set(1, 0); // <=> array([1, 0, 3])

Source

core/set.js , line 22

sign() → {this}

Returns the sign of each element of current array, indicating whether it is positive, negative or zero.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).sign(); // <=> array([1, 1, 1])

Source

core/sign.js , line 23

sin() → {this}

Returns the sine of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([0, Math.PI / 2, Math.PI]).sin(); // <=> array([0, 1, 0])

Source

core/sin.js , line 21

sinh() → {this}

Returns the hyperbolic sine of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).sinh(); // <=> array([1.175201177597046, 3.6268603801727295, 10.017874717712402])

Source

core/sinh.js , line 21

slice(begin, end, step) → {this}

Slices the current array along the leading dimension

Parameters

begin Number
end Number
step Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3, 4]).slice(0, 4, 2); // => array([1, 3])

Source

core/slice.js , line 24

solve(x) → {NDArray}

Solves the equation AX = B (where A is current matrix and B is x). Accelerated with LAPACK ?gesv.

Parameters

x NDArray

Returns

NDArray

Example

import { array } from 'vectorious/core/array';

array([[1, 3, 5], [2, 4, 7], [1, 1, 0]]).solve([[1], [3], [5]]); // => array([[3.25], [1.75], [-1.5]])

Source

core/solve.js , line 42

sqrt() → {this}

Returns the positive square root of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 4, 9]); // <=> array([1, 2, 3])

Source

core/sqrt.js , line 21

square()

Asserts if current matrix is square.

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).square(); // Error: matrix is not square

Throws

matrix is not square
Type Error

Source

core/square.js , line 21

subtract() → {this}

Subtracts x from the current array. Accelerated with BLAS ?axpy.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).subtract([1, 1, 1]); // <=> array([0, 1, 2])

Source

core/subtract.js , line 21

sum() → {Number}

Sum of array elements

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).sum(); // => 6

Source

core/sum.js , line 20

swap(i, j) → {this}

Swaps two rows i and j in current matrix

Parameters

i Number
j Number

Returns

this

Example

import { array } from 'vectorious/core/array';

array([[1, 2], [3, 4]]); // <=> array([[3, 4], [1, 2]])

Source

core/swap.js , line 21

tan() → {this}

Returns the tangent of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).tan(); // <=> array([1.5574077367782593, -2.185039758682251, -0.14254654943943024])

Source

core/tan.js , line 21

tanh() → {this}

Returns the hyperbolic tangent of each element of current array.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).tanh(); // <=> array([0.7615941762924194, 0.9640275835990906, 0.9950547814369202])

Source

core/tanh.js , line 21

toArray(index, dim) → {Array}

Converts current vector into a JavaScript array.

Parameters

index Number
dim Number

Returns

Array

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).toArray(); // => [1, 2, 3]

Source

core/toArray.js , line 19

toString() → {String}

Converts current vector into a readable formatted string.

Returns

String

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).toString(); // => '1,2,3'

Source

core/toString.js , line 20

trace() → {Number}

Gets the trace of the matrix (the sum of all diagonal elements).

Returns

Number

Example

import { array } from 'vectorious/core/array';

array([1, 2, 3]).trace(); // => 5

Source

core/trace.js , line 19

transpose() → {this}

Transposes current matrix (mirror across the diagonal).

Returns

this

Example

import { array } from 'vectorious/core/array';

array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]); // <=> array([[1, 4, 7], [2, 5, 8], [3, 6, 9]])

Source

core/transpose.js , line 19

trunc() → {this}

Returns the integer part of each element of current array, removing any fractional digits.

Returns

this

Example

import { array } from 'vectorious/core/array';

array([1.2, 2.8, 3.5]).trunc(); // => array([1, 2, 3])

Source

core/trunc.js , line 23