org.saddle.mat

Type members

Classlikes

object MatCols
object MatMath

Matrix mathematical helper routines.

Matrix mathematical helper routines.

Value members

Concrete methods

def diag(v: Vec[Double]): Mat[Double]

Given a vector, create a matrix whose diagonal entries equal the vector, with zeros off-diagonal.

Given a vector, create a matrix whose diagonal entries equal the vector, with zeros off-diagonal.

Value parameters:
v

The vector of source data

def ident(n: Int): Mat[Double]

Create a square identity matrix of dimension n x n

Create a square identity matrix of dimension n x n

Value parameters:
n

The number of rows/columns of the square matrix

def ones(rows: Int, cols: Int): Mat[Double]
def rand(rows: Int, cols: Int): Mat[Double]

Generate a uniform [0,1) random Mat[Double] of a certain size

Generate a uniform [0,1) random Mat[Double] of a certain size

Value parameters:
cols

Number of rows

rows

Number of rows

def randI(rows: Int, cols: Int): Mat[Int]

Generate a uniform random Mat[Int] of a certain size

Generate a uniform random Mat[Int] of a certain size

Value parameters:
cols

Number of rows

rows

Number of rows

def randl(rows: Int, cols: Int): Mat[Long]

Generate a uniform random Mat[Long] of a certain size

Generate a uniform random Mat[Long] of a certain size

Value parameters:
cols

Number of rows

rows

Number of rows

def randn(rows: Int, cols: Int): Mat[Double]

Generate a standard normal random Mat[Double] of a certain size

Generate a standard normal random Mat[Double] of a certain size

Value parameters:
cols

Number of rows

rows

Number of rows

def randn2(rows: Int, cols: Int, mu: Double, sigma: Double): Mat[Double]

Generate a gaussian(mu, sigma) random Mat[Double] of a certain size

Generate a gaussian(mu, sigma) random Mat[Double] of a certain size

Value parameters:
cols

Number of rows

mu

Mean of distribution

rows

Number of rows

sigma

Stdev of distribution

def randp(rows: Int, cols: Int): Mat[Double]

Generate a uniform random (0,1] Mat[Double] of a certain size

Generate a uniform random (0,1] Mat[Double] of a certain size

Value parameters:
cols

Number of rows

rows

Number of rows

def randpi(rows: Int, cols: Int): Mat[Int]

Generate a uniform random positive Mat[Int] of a certain size

Generate a uniform random positive Mat[Int] of a certain size

Value parameters:
cols

Number of rows

rows

Number of rows

def randpl(rows: Int, cols: Int): Mat[Long]

Generate a uniform random positive Mat[Long] of a certain size

Generate a uniform random positive Mat[Long] of a certain size

Value parameters:
cols

Number of rows

rows

Number of rows

def repeat[@specialized(Boolean, Int, Long, Double) T : ScalarTag](v: Array[T], n: Int, asRows: Boolean): Mat[T]

Repeats an array in a particular direction to create a 2D matrix

Repeats an array in a particular direction to create a 2D matrix

Type parameters:
T

type of elements in array

Value parameters:
asRows

if true, returns row-tiling; default is column-tiling

n

number of repetitions

v

array of values to repeat

def zeros(rows: Int, cols: Int): Mat[Double]