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# encoding: utf-8 # frozen_string_literal: false # # = matrix.rb # # An implementation of Matrix and Vector classes. # # See classes Matrix and Vector for documentation. # # Current Maintainer:: Marc-André Lafortune # Original Author:: Keiju ISHITSUKA # Original Documentation:: Gavin Sinclair (sourced from <i>Ruby in a Nutshell</i> (Matsumoto, O'Reilly)) ## require "e2mmap.rb" module ExceptionForMatrix # :nodoc: extend Exception2MessageMapper def_e2message(TypeError, "wrong argument type %s (expected %s)") def_e2message(ArgumentError, "Wrong # of arguments(%d for %d)") def_exception("ErrDimensionMismatch", "\#{self.name} dimension mismatch") def_exception("ErrNotRegular", "Not Regular Matrix") def_exception("ErrOperationNotDefined", "Operation(%s) can\\'t be defined: %s op %s") def_exception("ErrOperationNotImplemented", "Sorry, Operation(%s) not implemented: %s op %s") end # # The +Matrix+ class represents a mathematical matrix. It provides methods for creating # matrices, operating on them arithmetically and algebraically, # and determining their mathematical properties such as trace, rank, inverse, determinant, # or eigensystem. # class Matrix include Enumerable include ExceptionForMatrix autoload :EigenvalueDecomposition, "matrix/eigenvalue_decomposition" autoload :LUPDecomposition, "matrix/lup_decomposition" # instance creations private_class_method :new attr_reader :rows protected :rows # # Creates a matrix where each argument is a row. # Matrix[ [25, 93], [-1, 66] ] # => 25 93 # -1 66 # def Matrix.[](*rows) rows(rows, false) end # # Creates a matrix where +rows+ is an array of arrays, each of which is a row # of the matrix. If the optional argument +copy+ is false, use the given # arrays as the internal structure of the matrix without copying. # Matrix.rows([[25, 93], [-1, 66]]) # => 25 93 # -1 66 # def Matrix.rows(rows, copy = true) rows = convert_to_array(rows, copy) rows.map! do |row| convert_to_array(row, copy) end size = (rows[0] || []).size rows.each do |row| raise ErrDimensionMismatch, "row size differs (#{row.size} should be #{size})" unless row.size == size end new rows, size end # # Creates a matrix using +columns+ as an array of column vectors. # Matrix.columns([[25, 93], [-1, 66]]) # => 25 -1 # 93 66 # def Matrix.columns(columns) rows(columns, false).transpose end # # Creates a matrix of size +row_count+ x +column_count+. # It fills the values by calling the given block, # passing the current row and column. # Returns an enumerator if no block is given. # # m = Matrix.build(2, 4) {|row, col| col - row } # => Matrix[[0, 1, 2, 3], [-1, 0, 1, 2]] # m = Matrix.build(3) { rand } # => a 3x3 matrix with random elements # def Matrix.build(row_count, column_count = row_count) row_count = CoercionHelper.coerce_to_int(row_count) column_count = CoercionHelper.coerce_to_int(column_count) raise ArgumentError if row_count < 0 || column_count < 0 return to_enum :build, row_count, column_count unless block_given? rows = Array.new(row_count) do |i| Array.new(column_count) do |j| yield i, j end end new rows, column_count end # # Creates a matrix where the diagonal elements are composed of +values+. # Matrix.diagonal(9, 5, -3) # => 9 0 0 # 0 5 0 # 0 0 -3 # def Matrix.diagonal(*values) size = values.size return Matrix.empty if size == 0 rows = Array.new(size) {|j| row = Array.new(size, 0) row[j] = values[j] row } new rows end # # Creates an +n+ by +n+ diagonal matrix where each diagonal element is # +value+. # Matrix.scalar(2, 5) # => 5 0 # 0 5 # def Matrix.scalar(n, value) diagonal(*Array.new(n, value)) end # # Creates an +n+ by +n+ identity matrix. # Matrix.identity(2) # => 1 0 # 0 1 # def Matrix.identity(n) scalar(n, 1) end class << Matrix alias unit identity alias I identity end # # Creates a zero matrix. # Matrix.zero(2) # => 0 0 # 0 0 # def Matrix.zero(row_count, column_count = row_count) rows = Array.new(row_count){Array.new(column_count, 0)} new rows, column_count end # # Creates a single-row matrix where the values of that row are as given in # +row+. # Matrix.row_vector([4,5,6]) # => 4 5 6 # def Matrix.row_vector(row) row = convert_to_array(row) new [row] end # # Creates a single-column matrix where the values of that column are as given # in +column+. # Matrix.column_vector([4,5,6]) # => 4 # 5 # 6 # def Matrix.column_vector(column) column = convert_to_array(column) new [column].transpose, 1 end # # Creates a empty matrix of +row_count+ x +column_count+. # At least one of +row_count+ or +column_count+ must be 0. # # m = Matrix.empty(2, 0) # m == Matrix[ [], [] ] # => true # n = Matrix.empty(0, 3) # n == Matrix.columns([ [], [], [] ]) # => true # m * n # => Matrix[[0, 0, 0], [0, 0, 0]] # def Matrix.empty(row_count = 0, column_count = 0) raise ArgumentError, "One size must be 0" if column_count != 0 && row_count != 0 raise ArgumentError, "Negative size" if column_count < 0 || row_count < 0 new([[]]*row_count, column_count) end # # Create a matrix by stacking matrices vertically # # x = Matrix[[1, 2], [3, 4]] # y = Matrix[[5, 6], [7, 8]] # Matrix.vstack(x, y) # => Matrix[[1, 2], [3, 4], [5, 6], [7, 8]] # def Matrix.vstack(x, *matrices) x = CoercionHelper.coerce_to_matrix(x) result = x.send(:rows).map(&:dup) matrices.each do |m| m = CoercionHelper.coerce_to_matrix(m) if m.column_count != x.column_count raise ErrDimensionMismatch, "The given matrices must have #{x.column_count} columns, but one has #{m.column_count}" end result.concat(m.send(:rows)) end new result, x.column_count end # # Create a matrix by stacking matrices horizontally # # x = Matrix[[1, 2], [3, 4]] # y = Matrix[[5, 6], [7, 8]] # Matrix.hstack(x, y) # => Matrix[[1, 2, 5, 6], [3, 4, 7, 8]] # def Matrix.hstack(x, *matrices) x = CoercionHelper.coerce_to_matrix(x) result = x.send(:rows).map(&:dup) total_column_count = x.column_count matrices.each do |m| m = CoercionHelper.coerce_to_matrix(m) if m.row_count != x.row_count raise ErrDimensionMismatch, "The given matrices must have #{x.row_count} rows, but one has #{m.row_count}" end result.each_with_index do |row, i| row.concat m.send(:rows)[i] end total_column_count += m.column_count end new result, total_column_count end # # Create a matrix by combining matrices entrywise, using the given block # # x = Matrix[[6, 6], [4, 4]] # y = Matrix[[1, 2], [3, 4]] # Matrix.combine(x, y) {|a, b| a - b} # => Matrix[[5, 4], [1, 0]] # def Matrix.combine(*matrices) return to_enum(__method__, *matrices) unless block_given? return Matrix.empty if matrices.empty? matrices.map!(&CoercionHelper.method(:coerce_to_matrix)) x = matrices.first matrices.each do |m| Matrix.Raise ErrDimensionMismatch unless x.row_count == m.row_count && x.column_count == m.column_count end rows = Array.new(x.row_count) do |i| Array.new(x.column_count) do |j| yield matrices.map{|m| m[i,j]} end end new rows, x.column_count end def combine(*matrices, &block) Matrix.combine(self, *matrices, &block) end # # Matrix.new is private; use Matrix.rows, columns, [], etc... to create. # def initialize(rows, column_count = rows[0].size) # No checking is done at this point. rows must be an Array of Arrays. # column_count must be the size of the first row, if there is one, # otherwise it *must* be specified and can be any integer >= 0 @rows = rows @column_count = column_count end def new_matrix(rows, column_count = rows[0].size) # :nodoc: self.class.send(:new, rows, column_count) # bypass privacy of Matrix.new end private :new_matrix # # Returns element (+i+,+j+) of the matrix. That is: row +i+, column +j+. # def [](i, j) @rows.fetch(i){return nil}[j] end alias element [] alias component [] def []=(i, j, v) @rows[i][j] = v end alias set_element []= alias set_component []= private :[]=, :set_element, :set_component # # Returns the number of rows. # def row_count @rows.size end alias_method :row_size, :row_count # # Returns the number of columns. # attr_reader :column_count alias_method :column_size, :column_count # # Returns row vector number +i+ of the matrix as a Vector (starting at 0 like # an array). When a block is given, the elements of that vector are iterated. # def row(i, &block) # :yield: e if block_given? @rows.fetch(i){return self}.each(&block) self else Vector.elements(@rows.fetch(i){return nil}) end end # # Returns column vector number +j+ of the matrix as a Vector (starting at 0 # like an array). When a block is given, the elements of that vector are # iterated. # def column(j) # :yield: e if block_given? return self if j >= column_count || j < -column_count row_count.times do |i| yield @rows[i][j] end self else return nil if j >= column_count || j < -column_count col = Array.new(row_count) {|i| @rows[i][j] } Vector.elements(col, false) end end # # Returns a matrix that is the result of iteration of the given block over all # elements of the matrix. # Matrix[ [1,2], [3,4] ].collect { |e| e**2 } # => 1 4 # 9 16 # def collect(&block) # :yield: e return to_enum(:collect) unless block_given? rows = @rows.collect{|row| row.collect(&block)} new_matrix rows, column_count end alias map collect # # Yields all elements of the matrix, starting with those of the first row, # or returns an Enumerator if no block given. # Elements can be restricted by passing an argument: # * :all (default): yields all elements # * :diagonal: yields only elements on the diagonal # * :off_diagonal: yields all elements except on the diagonal # * :lower: yields only elements on or below the diagonal # * :strict_lower: yields only elements below the diagonal # * :strict_upper: yields only elements above the diagonal # * :upper: yields only elements on or above the diagonal # # Matrix[ [1,2], [3,4] ].each { |e| puts e } # # => prints the numbers 1 to 4 # Matrix[ [1,2], [3,4] ].each(:strict_lower).to_a # => [3] # def each(which = :all) # :yield: e return to_enum :each, which unless block_given? last = column_count - 1 case which when :all block = Proc.new @rows.each do |row| row.each(&block) end when :diagonal @rows.each_with_index do |row, row_index| yield row.fetch(row_index){return self} end when :off_diagonal @rows.each_with_index do |row, row_index| column_count.times do |col_index| yield row[col_index] unless row_index == col_index end end when :lower @rows.each_with_index do |row, row_index| 0.upto([row_index, last].min) do |col_index| yield row[col_index] end end when :strict_lower @rows.each_with_index do |row, row_index| [row_index, column_count].min.times do |col_index| yield row[col_index] end end when :strict_upper @rows.each_with_index do |row, row_index| (row_index+1).upto(last) do |col_index| yield row[col_index] end end when :upper @rows.each_with_index do |row, row_index| row_index.upto(last) do |col_index| yield row[col_index] end end else raise ArgumentError, "expected #{which.inspect} to be one of :all, :diagonal, :off_diagonal, :lower, :strict_lower, :strict_upper or :upper" end self end # # Same as #each, but the row index and column index in addition to the element # # Matrix[ [1,2], [3,4] ].each_with_index do |e, row, col| # puts "#{e} at #{row}, #{col}" # end # # => Prints: # # 1 at 0, 0 # # 2 at 0, 1 # # 3 at 1, 0 # # 4 at 1, 1 # def each_with_index(which = :all) # :yield: e, row, column return to_enum :each_with_index, which unless block_given? last = column_count - 1 case which when :all @rows.each_with_index do |row, row_index| row.each_with_index do |e, col_index| yield e, row_index, col_index end end when :diagonal @rows.each_with_index do |row, row_index| yield row.fetch(row_index){return self}, row_index, row_index end when :off_diagonal @rows.each_with_index do |row, row_index| column_count.times do |col_index| yield row[col_index], row_index, col_index unless row_index == col_index end end when :lower @rows.each_with_index do |row, row_index| 0.upto([row_index, last].min) do |col_index| yield row[col_index], row_index, col_index end end when :strict_lower @rows.each_with_index do |row, row_index| [row_index, column_count].min.times do |col_index| yield row[col_index], row_index, col_index end end when :strict_upper @rows.each_with_index do |row, row_index| (row_index+1).upto(last) do |col_index| yield row[col_index], row_index, col_index end end when :upper @rows.each_with_index do |row, row_index| row_index.upto(last) do |col_index| yield row[col_index], row_index, col_index end end else raise ArgumentError, "expected #{which.inspect} to be one of :all, :diagonal, :off_diagonal, :lower, :strict_lower, :strict_upper or :upper" end self end SELECTORS = {all: true, diagonal: true, off_diagonal: true, lower: true, strict_lower: true, strict_upper: true, upper: true}.freeze # # :call-seq: # index(value, selector = :all) -> [row, column] # index(selector = :all){ block } -> [row, column] # index(selector = :all) -> an_enumerator # # The index method is specialized to return the index as [row, column] # It also accepts an optional +selector+ argument, see #each for details. # # Matrix[ [1,2], [3,4] ].index(&:even?) # => [0, 1] # Matrix[ [1,1], [1,1] ].index(1, :strict_lower) # => [1, 0] # def index(*args) raise ArgumentError, "wrong number of arguments(#{args.size} for 0-2)" if args.size > 2 which = (args.size == 2 || SELECTORS.include?(args.last)) ? args.pop : :all return to_enum :find_index, which, *args unless block_given? || args.size == 1 if args.size == 1 value = args.first each_with_index(which) do |e, row_index, col_index| return row_index, col_index if e == value end else each_with_index(which) do |e, row_index, col_index| return row_index, col_index if yield e end end nil end alias_method :find_index, :index # # Returns a section of the matrix. The parameters are either: # * start_row, nrows, start_col, ncols; OR # * row_range, col_range # # Matrix.diagonal(9, 5, -3).minor(0..1, 0..2) # => 9 0 0 # 0 5 0 # # Like Array#[], negative indices count backward from the end of the # row or column (-1 is the last element). Returns nil if the starting # row or column is greater than row_count or column_count respectively. # def minor(*param) case param.size when 2 row_range, col_range = param from_row = row_range.first from_row += row_count if from_row < 0 to_row = row_range.end to_row += row_count if to_row < 0 to_row += 1 unless row_range.exclude_end? size_row = to_row - from_row from_col = col_range.first from_col += column_count if from_col < 0 to_col = col_range.end to_col += column_count if to_col < 0 to_col += 1 unless col_range.exclude_end? size_col = to_col - from_col when 4 from_row, size_row, from_col, size_col = param return nil if size_row < 0 || size_col < 0 from_row += row_count if from_row < 0 from_col += column_count if from_col < 0 else raise ArgumentError, param.inspect end return nil if from_row > row_count || from_col > column_count || from_row < 0 || from_col < 0 rows = @rows[from_row, size_row].collect{|row| row[from_col, size_col] } new_matrix rows, [column_count - from_col, size_col].min end # # Returns the submatrix obtained by deleting the specified row and column. # # Matrix.diagonal(9, 5, -3, 4).first_minor(1, 2) # => 9 0 0 # 0 0 0 # 0 0 4 # def first_minor(row, column) raise RuntimeError, "first_minor of empty matrix is not defined" if empty? unless 0 <= row && row < row_count raise ArgumentError, "invalid row (#{row.inspect} for 0..#{row_count - 1})" end unless 0 <= column && column < column_count raise ArgumentError, "invalid column (#{column.inspect} for 0..#{column_count - 1})" end arrays = to_a arrays.delete_at(row) arrays.each do |array| array.delete_at(column) end new_matrix arrays, column_count - 1 end # # Returns the (row, column) cofactor which is obtained by multiplying # the first minor by (-1)**(row + column). # # Matrix.diagonal(9, 5, -3, 4).cofactor(1, 1) # => -108 # def cofactor(row, column) raise RuntimeError, "cofactor of empty matrix is not defined" if empty? Matrix.Raise ErrDimensionMismatch unless square? det_of_minor = first_minor(row, column).determinant det_of_minor * (-1) ** (row + column) end # # Returns the adjugate of the matrix. # # Matrix[ [7,6],[3,9] ].adjugate # => 9 -6 # -3 7 # def adjugate Matrix.Raise ErrDimensionMismatch unless square? Matrix.build(row_count, column_count) do |row, column| cofactor(column, row) end end # # Returns the Laplace expansion along given row or column. # # Matrix[[7,6], [3,9]].laplace_expansion(column: 1) # => 45 # # Matrix[[Vector[1, 0], Vector[0, 1]], [2, 3]].laplace_expansion(row: 0) # => Vector[3, -2] # # def laplace_expansion(row: nil, column: nil) num = row || column if !num || (row && column) raise ArgumentError, "exactly one the row or column arguments must be specified" end Matrix.Raise ErrDimensionMismatch unless square? raise RuntimeError, "laplace_expansion of empty matrix is not defined" if empty? unless 0 <= num && num < row_count raise ArgumentError, "invalid num (#{num.inspect} for 0..#{row_count - 1})" end send(row ? :row : :column, num).map.with_index { |e, k| e * cofactor(*(row ? [num, k] : [k,num])) }.inject(:+) end alias_method :cofactor_expansion, :laplace_expansion #-- # TESTING -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Returns +true+ if this is a diagonal matrix. # Raises an error if matrix is not square. # def diagonal? Matrix.Raise ErrDimensionMismatch unless square? each(:off_diagonal).all?(&:zero?) end # # Returns +true+ if this is an empty matrix, i.e. if the number of rows # or the number of columns is 0. # def empty? column_count == 0 || row_count == 0 end # # Returns +true+ if this is an hermitian matrix. # Raises an error if matrix is not square. # def hermitian? Matrix.Raise ErrDimensionMismatch unless square? each_with_index(:upper).all? do |e, row, col| e == rows[col][row].conj end end # # Returns +true+ if this is a lower triangular matrix. # def lower_triangular? each(:strict_upper).all?(&:zero?) end # # Returns +true+ if this is a normal matrix. # Raises an error if matrix is not square. # def normal? Matrix.Raise ErrDimensionMismatch unless square? rows.each_with_index do |row_i, i| rows.each_with_index do |row_j, j| s = 0 rows.each_with_index do |row_k, k| s += row_i[k] * row_j[k].conj - row_k[i].conj * row_k[j] end return false unless s == 0 end end true end # # Returns +true+ if this is an orthogonal matrix # Raises an error if matrix is not square. # def orthogonal? Matrix.Raise ErrDimensionMismatch unless square? rows.each_with_index do |row, i| column_count.times do |j| s = 0 row_count.times do |k| s += row[k] * rows[k][j] end return false unless s == (i == j ? 1 : 0) end end true end # # Returns +true+ if this is a permutation matrix # Raises an error if matrix is not square. # def permutation? Matrix.Raise ErrDimensionMismatch unless square? cols = Array.new(column_count) rows.each_with_index do |row, i| found = false row.each_with_index do |e, j| if e == 1 return false if found || cols[j] found = cols[j] = true elsif e != 0 return false end end return false unless found end true end # # Returns +true+ if all entries of the matrix are real. # def real? all?(&:real?) end # # Returns +true+ if this is a regular (i.e. non-singular) matrix. # def regular? not singular? end # # Returns +true+ if this is a singular matrix. # def singular? determinant == 0 end # # Returns +true+ if this is a square matrix. # def square? column_count == row_count end # # Returns +true+ if this is a symmetric matrix. # Raises an error if matrix is not square. # def symmetric? Matrix.Raise ErrDimensionMismatch unless square? each_with_index(:strict_upper) do |e, row, col| return false if e != rows[col][row] end true end # # Returns +true+ if this is a unitary matrix # Raises an error if matrix is not square. # def unitary? Matrix.Raise ErrDimensionMismatch unless square? rows.each_with_index do |row, i| column_count.times do |j| s = 0 row_count.times do |k| s += row[k].conj * rows[k][j] end return false unless s == (i == j ? 1 : 0) end end true end # # Returns +true+ if this is an upper triangular matrix. # def upper_triangular? each(:strict_lower).all?(&:zero?) end # # Returns +true+ if this is a matrix with only zero elements # def zero? all?(&:zero?) end #-- # OBJECT METHODS -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Returns +true+ if and only if the two matrices contain equal elements. # def ==(other) return false unless Matrix === other && column_count == other.column_count # necessary for empty matrices rows == other.rows end def eql?(other) return false unless Matrix === other && column_count == other.column_count # necessary for empty matrices rows.eql? other.rows end # # Returns a clone of the matrix, so that the contents of each do not reference # identical objects. # There should be no good reason to do this since Matrices are immutable. # def clone new_matrix @rows.map(&:dup), column_count end # # Returns a hash-code for the matrix. # def hash @rows.hash end #-- # ARITHMETIC -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Matrix multiplication. # Matrix[[2,4], [6,8]] * Matrix.identity(2) # => 2 4 # 6 8 # def *(m) # m is matrix or vector or number case(m) when Numeric rows = @rows.collect {|row| row.collect {|e| e * m } } return new_matrix rows, column_count when Vector m = self.class.column_vector(m) r = self * m return r.column(0) when Matrix Matrix.Raise ErrDimensionMismatch if column_count != m.row_count rows = Array.new(row_count) {|i| Array.new(m.column_count) {|j| (0 ... column_count).inject(0) do |vij, k| vij + self[i, k] * m[k, j] end } } return new_matrix rows, m.column_count else return apply_through_coercion(m, __method__) end end # # Matrix addition. # Matrix.scalar(2,5) + Matrix[[1,0], [-4,7]] # => 6 0 # -4 12 # def +(m) case m when Numeric Matrix.Raise ErrOperationNotDefined, "+", self.class, m.class when Vector m = self.class.column_vector(m) when Matrix else return apply_through_coercion(m, __method__) end Matrix.Raise ErrDimensionMismatch unless row_count == m.row_count && column_count == m.column_count rows = Array.new(row_count) {|i| Array.new(column_count) {|j| self[i, j] + m[i, j] } } new_matrix rows, column_count end # # Matrix subtraction. # Matrix[[1,5], [4,2]] - Matrix[[9,3], [-4,1]] # => -8 2 # 8 1 # def -(m) case m when Numeric Matrix.Raise ErrOperationNotDefined, "-", self.class, m.class when Vector m = self.class.column_vector(m) when Matrix else return apply_through_coercion(m, __method__) end Matrix.Raise ErrDimensionMismatch unless row_count == m.row_count && column_count == m.column_count rows = Array.new(row_count) {|i| Array.new(column_count) {|j| self[i, j] - m[i, j] } } new_matrix rows, column_count end # # Matrix division (multiplication by the inverse). # Matrix[[7,6], [3,9]] / Matrix[[2,9], [3,1]] # => -7 1 # -3 -6 # def /(other) case other when Numeric rows = @rows.collect {|row| row.collect {|e| e / other } } return new_matrix rows, column_count when Matrix return self * other.inverse else return apply_through_coercion(other, __method__) end end # # Hadamard product # Matrix[[1,2], [3,4]].hadamard_product(Matrix[[1,2], [3,2]]) # => 1 4 # 9 8 # def hadamard_product(m) combine(m){|a, b| a * b} end alias_method :entrywise_product, :hadamard_product # # Returns the inverse of the matrix. # Matrix[[-1, -1], [0, -1]].inverse # => -1 1 # 0 -1 # def inverse Matrix.Raise ErrDimensionMismatch unless square? self.class.I(row_count).send(:inverse_from, self) end alias inv inverse def inverse_from(src) # :nodoc: last = row_count - 1 a = src.to_a 0.upto(last) do |k| i = k akk = a[k][k].abs (k+1).upto(last) do |j| v = a[j][k].abs if v > akk i = j akk = v end end Matrix.Raise ErrNotRegular if akk == 0 if i != k a[i], a[k] = a[k], a[i] @rows[i], @rows[k] = @rows[k], @rows[i] end akk = a[k][k] 0.upto(last) do |ii| next if ii == k q = a[ii][k].quo(akk) a[ii][k] = 0 (k + 1).upto(last) do |j| a[ii][j] -= a[k][j] * q end 0.upto(last) do |j| @rows[ii][j] -= @rows[k][j] * q end end (k+1).upto(last) do |j| a[k][j] = a[k][j].quo(akk) end 0.upto(last) do |j| @rows[k][j] = @rows[k][j].quo(akk) end end self end private :inverse_from # # Matrix exponentiation. # Equivalent to multiplying the matrix by itself N times. # Non integer exponents will be handled by diagonalizing the matrix. # # Matrix[[7,6], [3,9]] ** 2 # => 67 96 # 48 99 # def **(other) case other when Integer x = self if other <= 0 x = self.inverse return self.class.identity(self.column_count) if other == 0 other = -other end z = nil loop do z = z ? z * x : x if other[0] == 1 return z if (other >>= 1).zero? x *= x end when Numeric v, d, v_inv = eigensystem v * self.class.diagonal(*d.each(:diagonal).map{|e| e ** other}) * v_inv else Matrix.Raise ErrOperationNotDefined, "**", self.class, other.class end end def +@ self end def -@ collect {|e| -e } end #-- # MATRIX FUNCTIONS -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Returns the determinant of the matrix. # # Beware that using Float values can yield erroneous results # because of their lack of precision. # Consider using exact types like Rational or BigDecimal instead. # # Matrix[[7,6], [3,9]].determinant # => 45 # def determinant Matrix.Raise ErrDimensionMismatch unless square? m = @rows case row_count # Up to 4x4, give result using Laplacian expansion by minors. # This will typically be faster, as well as giving good results # in case of Floats when 0 +1 when 1 + m[0][0] when 2 + m[0][0] * m[1][1] - m[0][1] * m[1][0] when 3 m0, m1, m2 = m + m0[0] * m1[1] * m2[2] - m0[0] * m1[2] * m2[1] \ - m0[1] * m1[0] * m2[2] + m0[1] * m1[2] * m2[0] \ + m0[2] * m1[0] * m2[1] - m0[2] * m1[1] * m2[0] when 4 m0, m1, m2, m3 = m + m0[0] * m1[1] * m2[2] * m3[3] - m0[0] * m1[1] * m2[3] * m3[2] \ - m0[0] * m1[2] * m2[1] * m3[3] + m0[0] * m1[2] * m2[3] * m3[1] \ + m0[0] * m1[3] * m2[1] * m3[2] - m0[0] * m1[3] * m2[2] * m3[1] \ - m0[1] * m1[0] * m2[2] * m3[3] + m0[1] * m1[0] * m2[3] * m3[2] \ + m0[1] * m1[2] * m2[0] * m3[3] - m0[1] * m1[2] * m2[3] * m3[0] \ - m0[1] * m1[3] * m2[0] * m3[2] + m0[1] * m1[3] * m2[2] * m3[0] \ + m0[2] * m1[0] * m2[1] * m3[3] - m0[2] * m1[0] * m2[3] * m3[1] \ - m0[2] * m1[1] * m2[0] * m3[3] + m0[2] * m1[1] * m2[3] * m3[0] \ + m0[2] * m1[3] * m2[0] * m3[1] - m0[2] * m1[3] * m2[1] * m3[0] \ - m0[3] * m1[0] * m2[1] * m3[2] + m0[3] * m1[0] * m2[2] * m3[1] \ + m0[3] * m1[1] * m2[0] * m3[2] - m0[3] * m1[1] * m2[2] * m3[0] \ - m0[3] * m1[2] * m2[0] * m3[1] + m0[3] * m1[2] * m2[1] * m3[0] else # For bigger matrices, use an efficient and general algorithm. # Currently, we use the Gauss-Bareiss algorithm determinant_bareiss end end alias_method :det, :determinant # # Private. Use Matrix#determinant # # Returns the determinant of the matrix, using # Bareiss' multistep integer-preserving gaussian elimination. # It has the same computational cost order O(n^3) as standard Gaussian elimination. # Intermediate results are fraction free and of lower complexity. # A matrix of Integers will have thus intermediate results that are also Integers, # with smaller bignums (if any), while a matrix of Float will usually have # intermediate results with better precision. # def determinant_bareiss size = row_count last = size - 1 a = to_a no_pivot = Proc.new{ return 0 } sign = +1 pivot = 1 size.times do |k| previous_pivot = pivot if (pivot = a[k][k]) == 0 switch = (k+1 ... size).find(no_pivot) {|row| a[row][k] != 0 } a[switch], a[k] = a[k], a[switch] pivot = a[k][k] sign = -sign end (k+1).upto(last) do |i| ai = a[i] (k+1).upto(last) do |j| ai[j] = (pivot * ai[j] - ai[k] * a[k][j]) / previous_pivot end end end sign * pivot end private :determinant_bareiss # # deprecated; use Matrix#determinant # def determinant_e warn "Matrix#determinant_e is deprecated; use #determinant", uplevel: 1 determinant end alias det_e determinant_e # # Returns a new matrix resulting by stacking horizontally # the receiver with the given matrices # # x = Matrix[[1, 2], [3, 4]] # y = Matrix[[5, 6], [7, 8]] # x.hstack(y) # => Matrix[[1, 2, 5, 6], [3, 4, 7, 8]] # def hstack(*matrices) self.class.hstack(self, *matrices) end # # Returns the rank of the matrix. # Beware that using Float values can yield erroneous results # because of their lack of precision. # Consider using exact types like Rational or BigDecimal instead. # # Matrix[[7,6], [3,9]].rank # => 2 # def rank # We currently use Bareiss' multistep integer-preserving gaussian elimination # (see comments on determinant) a = to_a last_column = column_count - 1 last_row = row_count - 1 pivot_row = 0 previous_pivot = 1 0.upto(last_column) do |k| switch_row = (pivot_row .. last_row).find {|row| a[row][k] != 0 } if switch_row a[switch_row], a[pivot_row] = a[pivot_row], a[switch_row] unless pivot_row == switch_row pivot = a[pivot_row][k] (pivot_row+1).upto(last_row) do |i| ai = a[i] (k+1).upto(last_column) do |j| ai[j] = (pivot * ai[j] - ai[k] * a[pivot_row][j]) / previous_pivot end end pivot_row += 1 previous_pivot = pivot end end pivot_row end # # deprecated; use Matrix#rank # def rank_e warn "Matrix#rank_e is deprecated; use #rank", uplevel: 1 rank end # Returns a matrix with entries rounded to the given precision # (see Float#round) # def round(ndigits=0) map{|e| e.round(ndigits)} end # # Returns the trace (sum of diagonal elements) of the matrix. # Matrix[[7,6], [3,9]].trace # => 16 # def trace Matrix.Raise ErrDimensionMismatch unless square? (0...column_count).inject(0) do |tr, i| tr + @rows[i][i] end end alias tr trace # # Returns the transpose of the matrix. # Matrix[[1,2], [3,4], [5,6]] # => 1 2 # 3 4 # 5 6 # Matrix[[1,2], [3,4], [5,6]].transpose # => 1 3 5 # 2 4 6 # def transpose return self.class.empty(column_count, 0) if row_count.zero? new_matrix @rows.transpose, row_count end alias t transpose # # Returns a new matrix resulting by stacking vertically # the receiver with the given matrices # # x = Matrix[[1, 2], [3, 4]] # y = Matrix[[5, 6], [7, 8]] # x.vstack(y) # => Matrix[[1, 2], [3, 4], [5, 6], [7, 8]] # def vstack(*matrices) self.class.vstack(self, *matrices) end #-- # DECOMPOSITIONS -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= #++ # # Returns the Eigensystem of the matrix; see +EigenvalueDecomposition+. # m = Matrix[[1, 2], [3, 4]] # v, d, v_inv = m.eigensystem # d.diagonal? # => true # v.inv == v_inv # => true # (v * d * v_inv).round(5) == m # => true # def eigensystem EigenvalueDecomposition.new(self) end alias eigen eigensystem # # Returns the LUP decomposition of the matrix; see +LUPDecomposition+. # a = Matrix[[1, 2], [3, 4]] # l, u, p = a.lup # l.lower_triangular? # => true # u.upper_triangular? # => true # p.permutation? # => true # l * u == p * a # => true # a.lup.solve([2, 5]) # => Vector[(1/1), (1/2)] # def lup LUPDecomposition.new(self) end alias lup_decomposition lup #-- # COMPLEX ARITHMETIC -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= #++ # # Returns the conjugate of the matrix. # Matrix[[Complex(1,2), Complex(0,1), 0], [1, 2, 3]] # => 1+2i i 0 # 1 2 3 # Matrix[[Complex(1,2), Complex(0,1), 0], [1, 2, 3]].conjugate # => 1-2i -i 0 # 1 2 3 # def conjugate collect(&:conjugate) end alias conj conjugate # # Returns the imaginary part of the matrix. # Matrix[[Complex(1,2), Complex(0,1), 0], [1, 2, 3]] # => 1+2i i 0 # 1 2 3 # Matrix[[Complex(1,2), Complex(0,1), 0], [1, 2, 3]].imaginary # => 2i i 0 # 0 0 0 # def imaginary collect(&:imaginary) end alias imag imaginary # # Returns the real part of the matrix. # Matrix[[Complex(1,2), Complex(0,1), 0], [1, 2, 3]] # => 1+2i i 0 # 1 2 3 # Matrix[[Complex(1,2), Complex(0,1), 0], [1, 2, 3]].real # => 1 0 0 # 1 2 3 # def real collect(&:real) end # # Returns an array containing matrices corresponding to the real and imaginary # parts of the matrix # # m.rect == [m.real, m.imag] # ==> true for all matrices m # def rect [real, imag] end alias rectangular rect #-- # CONVERTING -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # The coerce method provides support for Ruby type coercion. # This coercion mechanism is used by Ruby to handle mixed-type # numeric operations: it is intended to find a compatible common # type between the two operands of the operator. # See also Numeric#coerce. # def coerce(other) case other when Numeric return Scalar.new(other), self else raise TypeError, "#{self.class} can't be coerced into #{other.class}" end end # # Returns an array of the row vectors of the matrix. See Vector. # def row_vectors Array.new(row_count) {|i| row(i) } end # # Returns an array of the column vectors of the matrix. See Vector. # def column_vectors Array.new(column_count) {|i| column(i) } end # # Explicit conversion to a Matrix. Returns self # def to_matrix self end # # Returns an array of arrays that describe the rows of the matrix. # def to_a @rows.collect(&:dup) end def elements_to_f warn "Matrix#elements_to_f is deprecated, use map(&:to_f)", uplevel: 1 map(&:to_f) end def elements_to_i warn "Matrix#elements_to_i is deprecated, use map(&:to_i)", uplevel: 1 map(&:to_i) end def elements_to_r warn "Matrix#elements_to_r is deprecated, use map(&:to_r)", uplevel: 1 map(&:to_r) end #-- # PRINTING -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Overrides Object#to_s # def to_s if empty? "#{self.class}.empty(#{row_count}, #{column_count})" else "#{self.class}[" + @rows.collect{|row| "[" + row.collect{|e| e.to_s}.join(", ") + "]" }.join(", ")+"]" end end # # Overrides Object#inspect # def inspect if empty? "#{self.class}.empty(#{row_count}, #{column_count})" else "#{self.class}#{@rows.inspect}" end end # Private helper modules module ConversionHelper # :nodoc: # # Converts the obj to an Array. If copy is set to true # a copy of obj will be made if necessary. # def convert_to_array(obj, copy = false) # :nodoc: case obj when Array copy ? obj.dup : obj when Vector obj.to_a else begin converted = obj.to_ary rescue Exception => e raise TypeError, "can't convert #{obj.class} into an Array (#{e.message})" end raise TypeError, "#{obj.class}#to_ary should return an Array" unless converted.is_a? Array converted end end private :convert_to_array end extend ConversionHelper module CoercionHelper # :nodoc: # # Applies the operator +oper+ with argument +obj+ # through coercion of +obj+ # def apply_through_coercion(obj, oper) coercion = obj.coerce(self) raise TypeError unless coercion.is_a?(Array) && coercion.length == 2 coercion[0].public_send(oper, coercion[1]) rescue raise TypeError, "#{obj.inspect} can't be coerced into #{self.class}" end private :apply_through_coercion # # Helper method to coerce a value into a specific class. # Raises a TypeError if the coercion fails or the returned value # is not of the right class. # (from Rubinius) # def self.coerce_to(obj, cls, meth) # :nodoc: return obj if obj.kind_of?(cls) raise TypeError, "Expected a #{cls} but got a #{obj.class}" unless obj.respond_to? meth begin ret = obj.__send__(meth) rescue Exception => e raise TypeError, "Coercion error: #{obj.inspect}.#{meth} => #{cls} failed:\n" \ "(#{e.message})" end raise TypeError, "Coercion error: obj.#{meth} did NOT return a #{cls} (was #{ret.class})" unless ret.kind_of? cls ret end def self.coerce_to_int(obj) coerce_to(obj, Integer, :to_int) end def self.coerce_to_matrix(obj) coerce_to(obj, Matrix, :to_matrix) end end include CoercionHelper # Private CLASS class Scalar < Numeric # :nodoc: include ExceptionForMatrix include CoercionHelper def initialize(value) @value = value end # ARITHMETIC def +(other) case other when Numeric Scalar.new(@value + other) when Vector, Matrix Scalar.Raise ErrOperationNotDefined, "+", @value.class, other.class else apply_through_coercion(other, __method__) end end def -(other) case other when Numeric Scalar.new(@value - other) when Vector, Matrix Scalar.Raise ErrOperationNotDefined, "-", @value.class, other.class else apply_through_coercion(other, __method__) end end def *(other) case other when Numeric Scalar.new(@value * other) when Vector, Matrix other.collect{|e| @value * e} else apply_through_coercion(other, __method__) end end def /(other) case other when Numeric Scalar.new(@value / other) when Vector Scalar.Raise ErrOperationNotDefined, "/", @value.class, other.class when Matrix self * other.inverse else apply_through_coercion(other, __method__) end end def **(other) case other when Numeric Scalar.new(@value ** other) when Vector Scalar.Raise ErrOperationNotDefined, "**", @value.class, other.class when Matrix #other.powered_by(self) Scalar.Raise ErrOperationNotImplemented, "**", @value.class, other.class else apply_through_coercion(other, __method__) end end end end # # The +Vector+ class represents a mathematical vector, which is useful in its own right, and # also constitutes a row or column of a Matrix. # # == Method Catalogue # # To create a Vector: # * Vector.[](*array) # * Vector.elements(array, copy = true) # * Vector.basis(size: n, index: k) # * Vector.zero(n) # # To access elements: # * #[](i) # # To enumerate the elements: # * #each2(v) # * #collect2(v) # # Properties of vectors: # * #angle_with(v) # * Vector.independent?(*vs) # * #independent?(*vs) # * #zero? # # Vector arithmetic: # * #*(x) "is matrix or number" # * #+(v) # * #-(v) # * #/(v) # * #+@ # * #-@ # # Vector functions: # * #inner_product(v), dot(v) # * #cross_product(v), cross(v) # * #collect # * #magnitude # * #map # * #map2(v) # * #norm # * #normalize # * #r # * #round # * #size # # Conversion to other data types: # * #covector # * #to_a # * #coerce(other) # # String representations: # * #to_s # * #inspect # class Vector include ExceptionForMatrix include Enumerable include Matrix::CoercionHelper extend Matrix::ConversionHelper #INSTANCE CREATION private_class_method :new attr_reader :elements protected :elements # # Creates a Vector from a list of elements. # Vector[7, 4, ...] # def Vector.[](*array) new convert_to_array(array, false) end # # Creates a vector from an Array. The optional second argument specifies # whether the array itself or a copy is used internally. # def Vector.elements(array, copy = true) new convert_to_array(array, copy) end # # Returns a standard basis +n+-vector, where k is the index. # # Vector.basis(size:, index:) # => Vector[0, 1, 0] # def Vector.basis(size:, index:) raise ArgumentError, "invalid size (#{size} for 1..)" if size < 1 raise ArgumentError, "invalid index (#{index} for 0...#{size})" unless 0 <= index && index < size array = Array.new(size, 0) array[index] = 1 new convert_to_array(array, false) end # # Return a zero vector. # # Vector.zero(3) => Vector[0, 0, 0] # def Vector.zero(size) raise ArgumentError, "invalid size (#{size} for 0..)" if size < 0 array = Array.new(size, 0) new convert_to_array(array, false) end # # Vector.new is private; use Vector[] or Vector.elements to create. # def initialize(array) # No checking is done at this point. @elements = array end # ACCESSING # # Returns element number +i+ (starting at zero) of the vector. # def [](i) @elements[i] end alias element [] alias component [] def []=(i, v) @elements[i]= v end alias set_element []= alias set_component []= private :[]=, :set_element, :set_component # Returns a vector with entries rounded to the given precision # (see Float#round) # def round(ndigits=0) map{|e| e.round(ndigits)} end # # Returns the number of elements in the vector. # def size @elements.size end #-- # ENUMERATIONS -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Iterate over the elements of this vector # def each(&block) return to_enum(:each) unless block_given? @elements.each(&block) self end # # Iterate over the elements of this vector and +v+ in conjunction. # def each2(v) # :yield: e1, e2 raise TypeError, "Integer is not like Vector" if v.kind_of?(Integer) Vector.Raise ErrDimensionMismatch if size != v.size return to_enum(:each2, v) unless block_given? size.times do |i| yield @elements[i], v[i] end self end # # Collects (as in Enumerable#collect) over the elements of this vector and +v+ # in conjunction. # def collect2(v) # :yield: e1, e2 raise TypeError, "Integer is not like Vector" if v.kind_of?(Integer) Vector.Raise ErrDimensionMismatch if size != v.size return to_enum(:collect2, v) unless block_given? Array.new(size) do |i| yield @elements[i], v[i] end end #-- # PROPERTIES -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Returns +true+ iff all of vectors are linearly independent. # # Vector.independent?(Vector[1,0], Vector[0,1]) # => true # # Vector.independent?(Vector[1,2], Vector[2,4]) # => false # def Vector.independent?(*vs) vs.each do |v| raise TypeError, "expected Vector, got #{v.class}" unless v.is_a?(Vector) Vector.Raise ErrDimensionMismatch unless v.size == vs.first.size end return false if vs.count > vs.first.size Matrix[*vs].rank.eql?(vs.count) end # # Returns +true+ iff all of vectors are linearly independent. # # Vector[1,0].independent?(Vector[0,1]) # => true # # Vector[1,2].independent?(Vector[2,4]) # => false # def independent?(*vs) self.class.independent?(self, *vs) end # # Returns +true+ iff all elements are zero. # def zero? all?(&:zero?) end #-- # COMPARING -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Returns +true+ iff the two vectors have the same elements in the same order. # def ==(other) return false unless Vector === other @elements == other.elements end def eql?(other) return false unless Vector === other @elements.eql? other.elements end # # Returns a copy of the vector. # def clone self.class.elements(@elements) end # # Returns a hash-code for the vector. # def hash @elements.hash end #-- # ARITHMETIC -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Multiplies the vector by +x+, where +x+ is a number or a matrix. # def *(x) case x when Numeric els = @elements.collect{|e| e * x} self.class.elements(els, false) when Matrix Matrix.column_vector(self) * x when Vector Vector.Raise ErrOperationNotDefined, "*", self.class, x.class else apply_through_coercion(x, __method__) end end # # Vector addition. # def +(v) case v when Vector Vector.Raise ErrDimensionMismatch if size != v.size els = collect2(v) {|v1, v2| v1 + v2 } self.class.elements(els, false) when Matrix Matrix.column_vector(self) + v else apply_through_coercion(v, __method__) end end # # Vector subtraction. # def -(v) case v when Vector Vector.Raise ErrDimensionMismatch if size != v.size els = collect2(v) {|v1, v2| v1 - v2 } self.class.elements(els, false) when Matrix Matrix.column_vector(self) - v else apply_through_coercion(v, __method__) end end # # Vector division. # def /(x) case x when Numeric els = @elements.collect{|e| e / x} self.class.elements(els, false) when Matrix, Vector Vector.Raise ErrOperationNotDefined, "/", self.class, x.class else apply_through_coercion(x, __method__) end end def +@ self end def -@ collect {|e| -e } end #-- # VECTOR FUNCTIONS -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Returns the inner product of this vector with the other. # Vector[4,7].inner_product Vector[10,1] => 47 # def inner_product(v) Vector.Raise ErrDimensionMismatch if size != v.size p = 0 each2(v) {|v1, v2| p += v1 * v2.conj } p end alias_method :dot, :inner_product # # Returns the cross product of this vector with the others. # Vector[1, 0, 0].cross_product Vector[0, 1, 0] => Vector[0, 0, 1] # # It is generalized to other dimensions to return a vector perpendicular # to the arguments. # Vector[1, 2].cross_product # => Vector[-2, 1] # Vector[1, 0, 0, 0].cross_product( # Vector[0, 1, 0, 0], # Vector[0, 0, 1, 0] # ) #=> Vector[0, 0, 0, 1] # def cross_product(*vs) raise ErrOperationNotDefined, "cross product is not defined on vectors of dimension #{size}" unless size >= 2 raise ArgumentError, "wrong number of arguments (#{vs.size} for #{size - 2})" unless vs.size == size - 2 vs.each do |v| raise TypeError, "expected Vector, got #{v.class}" unless v.is_a? Vector Vector.Raise ErrDimensionMismatch unless v.size == size end case size when 2 Vector[-@elements[1], @elements[0]] when 3 v = vs[0] Vector[ v[2]*@elements[1] - v[1]*@elements[2], v[0]*@elements[2] - v[2]*@elements[0], v[1]*@elements[0] - v[0]*@elements[1] ] else rows = self, *vs, Array.new(size) {|i| Vector.basis(size: size, index: i) } Matrix.rows(rows).laplace_expansion(row: size - 1) end end alias_method :cross, :cross_product # # Like Array#collect. # def collect(&block) # :yield: e return to_enum(:collect) unless block_given? els = @elements.collect(&block) self.class.elements(els, false) end alias map collect # # Returns the modulus (Pythagorean distance) of the vector. # Vector[5,8,2].r => 9.643650761 # def magnitude Math.sqrt(@elements.inject(0) {|v, e| v + e.abs2}) end alias r magnitude alias norm magnitude # # Like Vector#collect2, but returns a Vector instead of an Array. # def map2(v, &block) # :yield: e1, e2 return to_enum(:map2, v) unless block_given? els = collect2(v, &block) self.class.elements(els, false) end class ZeroVectorError < StandardError end # # Returns a new vector with the same direction but with norm 1. # v = Vector[5,8,2].normalize # # => Vector[0.5184758473652127, 0.8295613557843402, 0.20739033894608505] # v.norm => 1.0 # def normalize n = magnitude raise ZeroVectorError, "Zero vectors can not be normalized" if n == 0 self / n end # # Returns an angle with another vector. Result is within the [0...Math::PI]. # Vector[1,0].angle_with(Vector[0,1]) # # => Math::PI / 2 # def angle_with(v) raise TypeError, "Expected a Vector, got a #{v.class}" unless v.is_a?(Vector) Vector.Raise ErrDimensionMismatch if size != v.size prod = magnitude * v.magnitude raise ZeroVectorError, "Can't get angle of zero vector" if prod == 0 Math.acos( inner_product(v) / prod ) end #-- # CONVERTING #++ # # Creates a single-row matrix from this vector. # def covector Matrix.row_vector(self) end # # Returns the elements of the vector in an array. # def to_a @elements.dup end # # Return a single-column matrix from this vector # def to_matrix Matrix.column_vector(self) end def elements_to_f warn "Vector#elements_to_f is deprecated", uplevel: 1 map(&:to_f) end def elements_to_i warn "Vector#elements_to_i is deprecated", uplevel: 1 map(&:to_i) end def elements_to_r warn "Vector#elements_to_r is deprecated", uplevel: 1 map(&:to_r) end # # The coerce method provides support for Ruby type coercion. # This coercion mechanism is used by Ruby to handle mixed-type # numeric operations: it is intended to find a compatible common # type between the two operands of the operator. # See also Numeric#coerce. # def coerce(other) case other when Numeric return Matrix::Scalar.new(other), self else raise TypeError, "#{self.class} can't be coerced into #{other.class}" end end #-- # PRINTING -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- #++ # # Overrides Object#to_s # def to_s "Vector[" + @elements.join(", ") + "]" end # # Overrides Object#inspect # def inspect "Vector" + @elements.inspect end end