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Update svd_matrix.rb #7

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629ac9d
Update svd_matrix.rb
pporter2876 May 8, 2014
53ed4c0
Update svd.c
pporter2876 May 8, 2014
5f479f7
Update svd_matrix.rb
pporter2876 May 8, 2014
f142ac0
Update svd_matrix.rb
pporter2876 May 8, 2014
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2 changes: 1 addition & 1 deletion ext/svd.c
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ VALUE decompose(VALUE module, VALUE matrix_ruby, VALUE m_ruby, VALUE n_ruby) {
/* precondition */
if((m*n) != RARRAY_LEN(matrix_ruby)) {
rb_raise(rb_eRangeError, "Size of the array is not equal to m * n");
return;
return 0;
}

/* convert to u matrix */
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25 changes: 18 additions & 7 deletions lib/svd_matrix.rb
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Expand Up @@ -37,16 +37,27 @@ def inspect
# [ 0, 0, 0, 0 ]
def decompose(reduce_dimensions_to = nil)
input_array = []
@rows.each {|row| input_array += row}
u_array, w_array, v_array = SVD.decompose(input_array, row_size, column_size)
# @rows.each {|row| input_array += row}
c_count = 0
@rows.each do |row|
input_array += row
end
c_count = input_array.length / row_size
puts "input array"
puts input_array.length
puts "row size"
puts row_size
puts "column size"
puts c_count
u_array, w_array, v_array = SVD.decompose(input_array, row_size, c_count)

# recompose U matrix
u = SVDMatrix.new(row_size, reduce_dimensions_to || column_size)
row_size.times {|i| u.set_row(i, u_array.slice!(0, column_size)[0...(reduce_dimensions_to || column_size)])}
u = SVDMatrix.new(row_size, reduce_dimensions_to || c_count)
row_size.times {|i| u.set_row(i, u_array.slice!(0, c_count)[0...(reduce_dimensions_to || c_count)])}

# recompose V matrix
v = SVDMatrix.new(column_size, reduce_dimensions_to || column_size)
column_size.times {|i| v.set_row(i, v_array.slice!(0, column_size)[0...(reduce_dimensions_to || column_size)])}
v = SVDMatrix.new(c_count, reduce_dimensions_to || c_count)
c_count.times {|i| v.set_row(i, v_array.slice!(0, c_count)[0...(reduce_dimensions_to || c_count)])}

# diagonalise W array as a matrix
if reduce_dimensions_to
Expand All @@ -56,7 +67,7 @@ def decompose(reduce_dimensions_to = nil)

[u, w, v]
end

# Reduce the number of dimensions of the data to dimensions.
# Returns a back a recombined matrix (conceptually the original
# matrix dimensionally reduced). For example Latent Semantic
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