Creates a new zero matrix with dimensions row x columns.

Linalg::Matrix(Float64).new(2, 2) # => [[0.0, 0.0], [0.0, 0.0]]
Linalg::Matrix(Int32).new(2, 3) # => [[0, 0, 0], [0, 0, 0]]

Creates a new matrix filled with vectors of the given elements.

matrix = Linalg::Matrix.new([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
matrix # => [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

An ArgumentError is raised if the elements in the given array have differents sizes.

Creates a new matrix filled with the given elements.

rows = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
vectors = Array(Linalg::Vector(Int32)).new

rows.each { |r| vectors << Linalg::Vector.new(r) }

mat = Linalg::Matrix.new(vectors)
mat # => [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

An ArgumentError is raised if the given vectors have different sizes.

Creates a new identity matrix of the given size.

Linalg::Matrix(Int32).new(1) # => [[1]]
Linalg::Matrix(Int32).new(2) # => [[1, 0], [0, 1]]
Linalg::Matrix(Float64).new(3) # => [[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]

An ArgumentError is raised if the given size is less than 1.

Creates a new empty matrix.

matrix = Linalg::Matrix(Float64).new
matrix # => []

Matrix-vector multiplication

vec = Linalg::Vector.new([2.0, 3.0, 4.0])
mat = Linalg::Matrix.new([[5, 2, 6], [7, 2, 5], [1, 4, 2]])
mat * vec # => [40.0, 40.0, 22.0]

Returns the product of self and other. If self is a m x n matrix and other is a n x p matrix then the product will be a m x p matrix.

mat1 = Linalg::Matrix.new([[2, 1, 4], [-1, 0, 3]])
mat2 = Linalg::Matrix.new([[1, 6], [5, 1], [2, -2]])
product = mat1.product(mat2)
product # => [[15, 5], [5, -12]]

NOTE Same as Linalg::Matrix#product

Scales all the vectors in self by the given scalar and return a new Linalg::Matrix.

mat = Linalg::Matrix.new([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
scaled_mat = mat * 2.0
scaled_mat # => [[2.0, 4.0, 6.0], [8.0, 10.0, 12.0], [14.0, 16.0, 18.0]]

Matrix addition. Adds self and other together and returns a new Linalg::Matrix.

mat1 = Linalg::Matrix.new([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
mat2 = Linalg::Matrix.new([[4, -1, 6], [2, 9, -3], [-4, 5, 1]])

mat3 = mat1 + mat2
mat3 # => [[5.0, 1.0, 9.0], [6.0, 14.0, 3.0], [3.0, 13.0, 10.0]]

Matrix subtraction. Subtracts other from self and returns a new Linalg::Matrix.

mat1 = Linalg::Matrix.new([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
mat2 = Linalg::Matrix.new([[4, -1, 6], [2, 9, -3], [-4, 5, 1]])

mat3 = mat1 - mat2
mat3 # => [[-3.0, 3.0, -3.0], [2.0, -4.0, 9.0], [11.0, 3.0, 8.0]]

Unary operator. Returns the inverted matrix to self.

mat = Linalg::Matrix.new([[-1, 2, -3], [-4, -5, -6], [7, -8, 9]])
-mat # => [[1, -2, 3], [4, 5, 6], [-7, 8, -9]]

Append. Converts the given array into a Linalg::Vector and appends it to self.

mat = Linalg::Matrix(Int32).new
mat << [1, 2, 3]
mat # => [1, 2, 3]

An ArgumentError is raised if the given array doesn't have the same size as the vectors already in the matrix.

Appends the given vector to self.

mat = Linalg::Matrix(Int32).new
mat << Linalg::Vector.new([1, 2, 3])
mat # => [1, 2, 3]

An ArgumentError is raised if the given vector doesn't have the same size as the vectors already in the matrix.

Returns true if each element in self is equal to each corresponding element in other.

Returns the element at the given position (row, col).

mat = Linalg::Matrix.new([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
mat[1, 0] # => 4

Returns the element at the given index.

mat = Linalg::Matrix.new([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
mat[2] # => [7, 8, 9]

Sets the given value at the given position (row, col).

mat = Linalg::Matrix.new([[1, 0, 0], [0, 0, 0], [0, 0, 1]])
mat[1, 1] = 1
mat # => [[1, 0, 0], [0, 1, 0], [0, 0, 1]]

Appends the given column to self.

mat = Linalg::Matrix.new([[1, 2], [4, 5], [7, 8]])
mat.append_column([3, 6, 9])
mat # => [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

Appends the given column to self.

mat = Linalg::Matrix.new([[1, 2], [4, 5], [7, 8]])
mat.append_column([3, 6, 9])
mat # => [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

Returns the number of columns in the matrix.

Iterates over the collection, yielding the elements.

Iterates over the collection, yielding both the elements and their index.

See Enumerable#each_with_index for more details.

Returns true if self is empty, false otherwise.

Returns the column at the given index. Assumes that self is a non-empty Linalg::Matrix with at least 1 column.

mat = Linalg::Matrix.new([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
mat.get_column(1) # => [2, 5, 8]

Return true if self is an identity matrix, otherwise false.

Returns the product of self and other. If self is a m x n matrix and other is a n x p matrix then the product will be a m x p matrix.

mat1 = Linalg::Matrix.new([[2, 1, 4], [-1, 0, 3]])
mat2 = Linalg::Matrix.new([[1, 6], [5, 1], [2, -2]])
product = mat1.product(mat2)
product # => [[15, 5], [5, -12]]

Returns the number of rows in the matrix.

NOTE Same as Linalg::Matrix#size.

Returns the number of elements in the vector.

NOTE Same as Linalg::Matrix#rows.

Appends a short String representation of this object which includes its class name and its object address.

class Person
  def initialize(@name : String, @age : Int32)
  end
end

Person.new("John", 32).to_s # => #<Person:0x10a199f20>

Transposes the rows and columns of self.

mat = Linalg::Matrix.new([[1, 2], [3, 4], [5, 6]])
mat.transpose # => [[1, 3, 5], [2, 4, 6]]
mat # => [[1, 2], [3, 4], [5, 6]]

Returns true if self is a zero matrix, otherwise false.

NOTE An empty matrix is not considered a zero matrix.