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require 'json'
require 'yaml'
require 'csv'
#require_relative "../lazar/lib/lazar.rb"
#include OpenTox
class Object
def numeric?
true if Float(self) rescue false
end
end
def euclidean_distance(a, b)
sq = a.zip(b).map{|a,b| (a - b) ** 2}
Math.sqrt(sq.inject(0) {|s,c| s + c})
end
def dot_product(a, b)
products = a.zip(b).map{|a, b| a * b}
products.inject(0) {|s,p| s + p}
end
def magnitude(point)
squares = point.map{|x| x ** 2}
Math.sqrt(squares.inject(0) {|s, c| s + c})
end
def cosine_similarity(a, b)
dot_product(a, b) / (magnitude(a) * magnitude(b))
end
#@endpoint = @data.collect{|r| r[5]}
def neighbors query
end
def csv2json
csv = CSV.read("data/MergedSheets_edit.csv")
csv.collect!{|row| row[0..36].collect{|c| c.numeric? ? c.to_f : c } }.compact
feature_names = [
"ID",
csv[0][1],
csv[0][2],
csv[0][3],
csv[6][4],
"#{csv[0][5]} (#{csv[6][5]} [#{csv[11][5]}])", # endpoint
"#{csv[0][6]} (#{csv[6][6]})", # endpoint
"#{csv[6][7]} [#{csv[11][7]}]",
"#{csv[6][8]} [#{csv[11][8]}]",
"#{csv[6][9]} [#{csv[11][9]}]",
]
(10..10+5*3).step(3) do |i|
feature_names += [
"#{csv[6][i]} [#{csv[11][i]}]",
"#{csv[6][i+1]} #{csv[8][i+1]} [#{csv[11][i+1]}]",
"#{csv[6][i+2]} #{csv[8][i+2]}",
]
end
feature_names += [
"#{csv[6][28]}",
"#{csv[6][29]} #{csv[8][29]}",
"#{csv[6][30]} #{csv[8][30]}",
]
(31..34).each do |i|
feature_names << "#{csv[6][i]} #{csv[8][i]} [#{csv[11][i]}]"
end
(35..36).each do |i|
feature_names << "#{csv[6][i]} #{csv[8][i]} #{csv[10][i]} [#{csv[11][i]}]"
end
data = {}
csv.drop(12).each do |row|
id = row.first
data[id] = {}
row.each_with_index do |col,i|
if i == 0
data[id][:composition] = {}
elsif i < 5
data[id][:composition][feature_names[i]] = col
elsif i < 7
data[id][:tox] ||= {}
data[id][:tox][feature_names[i]] = col
else
data[id][:physchem] ||= {}
data[id][:physchem][feature_names[i]] = col
end
end
end
File.open("data.json","w+"){|f| f.puts data.to_json}
data
end
#puts data.to_yaml
=begin
R.assign "endpoint", endpoint
(0..data[0].size).each do |c|
if data.collect{|r| r[c]}.uniq.size > 1
begin
R.assign "feature", data.collect{|r| r[c]}
R.eval "r <- cor(-log(endpoint),-log(feature),use='complete')"
r = R.eval("r").to_ruby
p "#{c}: #{r}" if r > 0.3 or r < -0.3
rescue
end
end
end
csv[0..13].each do |row|
row.each_with_index do |col,i|
features[i] = features[i].to_s+", "+col.to_s
end
end
puts features.select{|f| f.match(/Mean/)}.to_yaml
#n+=1
#p n,row.first unless row.first.match /^[G|S]/
=end
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