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* lib/matrix: alias {row|column}_size to {row|column}_count and use the latter.

Browse source 
[Bug #7369] [ruby-core:49409]

git-svn-id: svn+ssh://ci.ruby-lang.org/ruby/trunk@38300 b2dd03c8-39d4-4d8f-98ff-823fe69b080e
This commit is contained in:
marcandre 2012-12-10 16:53:57 +00:00
parent 4c02cff191
commit 8aac5f48fc
4 changed files with 124 additions and 116 deletions
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56
lib/matrix/lup_decomposition.rb
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@ -19,7 +19,7 @@ class Matrix
include Matrix::ConversionHelper
def l
Matrix.build(@row_size, @col_size) do |i, j|
Matrix.build(@row_count, @column_count) do |i, j|
if (i > j)
@lu[i][j]
elsif (i == j)
@ -33,7 +33,7 @@ class Matrix
# Returns the upper triangular factor +U+
def u
Matrix.build(@col_size, @col_size) do |i, j|
Matrix.build(@column_count, @column_count) do |i, j|
if (i <= j)
@lu[i][j]
else
@ -45,9 +45,9 @@ class Matrix
# Returns the permutation matrix +P+
def p
rows = Array.new(@row_size){Array.new(@col_size, 0)}
rows = Array.new(@row_count){Array.new(@column_count, 0)}
@pivots.each_with_index{|p, i| rows[i][p] = 1}
Matrix.send :new, rows, @col_size
Matrix.send :new, rows, @column_count
end
# Returns +L+, +U+, +P+ in an array
@ -64,7 +64,7 @@ class Matrix
# Returns +true+ if +U+, and hence +A+, is singular.
def singular? ()
@col_size.times do |j|
@column_count.times do |j|
if (@lu[j][j] == 0)
return true
end
@ -76,11 +76,11 @@ class Matrix
# from the factorization.
def det
if (@row_size != @col_size)
if (@row_count != @column_count)
Matrix.Raise Matrix::ErrDimensionMismatch unless square?
end
d = @pivot_sign
@col_size.times do |j|
@column_count.times do |j|
d *= @lu[j][j]
end
d
@ -96,24 +96,24 @@ class Matrix
Matrix.Raise Matrix::ErrNotRegular, "Matrix is singular."
end
if b.is_a? Matrix
if (b.row_size != @row_size)
if (b.row_count != @row_count)
Matrix.Raise Matrix::ErrDimensionMismatch
end
# Copy right hand side with pivoting
nx = b.column_size
nx = b.column_count
m = @pivots.map{|row| b.row(row).to_a}
# Solve L*Y = P*b
@col_size.times do |k|
(k+1).upto(@col_size-1) do |i|
@column_count.times do |k|
(k+1).upto(@column_count-1) do |i|
nx.times do |j|
m[i][j] -= m[k][j]*@lu[i][k]
end
end
end
# Solve U*m = Y
(@col_size-1).downto(0) do |k|
(@column_count-1).downto(0) do |k|
nx.times do |j|
m[k][j] = m[k][j].quo(@lu[k][k])
end
@ -126,7 +126,7 @@ class Matrix
Matrix.send :new, m, nx
else # same algorithm, specialized for simpler case of a vector
b = convert_to_array(b)
if (b.size != @row_size)
if (b.size != @row_count)
Matrix.Raise Matrix::ErrDimensionMismatch
end
@ -134,13 +134,13 @@ class Matrix
m = b.values_at(*@pivots)
# Solve L*Y = P*b
@col_size.times do |k|
(k+1).upto(@col_size-1) do |i|
@column_count.times do |k|
(k+1).upto(@column_count-1) do |i|
m[i] -= m[k]*@lu[i][k]
end
end
# Solve U*m = Y
(@col_size-1).downto(0) do |k|
(@column_count-1).downto(0) do |k|
m[k] = m[k].quo(@lu[k][k])
k.times do |i|
m[i] -= m[k]*@lu[i][k]
@ -154,28 +154,28 @@ class Matrix
raise TypeError, "Expected Matrix but got #{a.class}" unless a.is_a?(Matrix)
# Use a "left-looking", dot-product, Crout/Doolittle algorithm.
@lu = a.to_a
@row_size = a.row_size
@col_size = a.column_size
@pivots = Array.new(@row_size)
@row_size.times do |i|
@row_count = a.row_count
@column_count = a.column_count
@pivots = Array.new(@row_count)
@row_count.times do |i|
@pivots[i] = i
end
@pivot_sign = 1
lu_col_j = Array.new(@row_size)
lu_col_j = Array.new(@row_count)
# Outer loop.
@col_size.times do |j|
@column_count.times do |j|
# Make a copy of the j-th column to localize references.
@row_size.times do |i|
@row_count.times do |i|
lu_col_j[i] = @lu[i][j]
end
# Apply previous transformations.
@row_size.times do |i|
@row_count.times do |i|
lu_row_i = @lu[i]
# Most of the time is spent in the following dot product.
@ -192,13 +192,13 @@ class Matrix
# Find pivot and exchange if necessary.
p = j
(j+1).upto(@row_size-1) do |i|
(j+1).upto(@row_count-1) do |i|
if (lu_col_j[i].abs > lu_col_j[p].abs)
p = i
end
end
if (p != j)
@col_size.times do |k|
@column_count.times do |k|
t = @lu[p][k]; @lu[p][k] = @lu[j][k]; @lu[j][k] = t
end
k = @pivots[p]; @pivots[p] = @pivots[j]; @pivots[j] = k
@ -207,8 +207,8 @@ class Matrix
# Compute multipliers.
if (j < @row_size && @lu[j][j] != 0)
(j+1).upto(@row_size-1) do |i|
if (j < @row_count && @lu[j][j] != 0)
(j+1).upto(@row_count-1) do |i|
@lu[i][j] = @lu[i][j].quo(@lu[j][j])
end
end