├── .github └── workflows │ └── build.yml ├── .gitignore ├── CHANGELOG.md ├── Gemfile ├── LICENSE.txt ├── README.md ├── Rakefile ├── lib ├── libmf.rb └── libmf │ ├── ffi.rb │ ├── matrix.rb │ ├── model.rb │ └── version.rb ├── libmf.gemspec ├── test ├── model_test.rb └── test_helper.rb └── vendor ├── COPYRIGHT └── demo ├── real_matrix.te.txt └── real_matrix.tr.txt /.github/workflows/build.yml: -------------------------------------------------------------------------------- 1 | name: build 2 | on: [push, pull_request] 3 | jobs: 4 | build: 5 | strategy: 6 | fail-fast: false 7 | matrix: 8 | os: [ubuntu-latest, macos-latest, windows-latest] 9 | runs-on: ${{ matrix.os }} 10 | steps: 11 | - uses: actions/checkout@v4 12 | - uses: ruby/setup-ruby@v1 13 | with: 14 | ruby-version: 3.4 15 | bundler-cache: true 16 | - run: bundle exec rake vendor:platform 17 | - run: bundle exec rake test 18 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | /.bundle/ 2 | /.yardoc 3 | /_yardoc/ 4 | /coverage/ 5 | /doc/ 6 | /pkg/ 7 | /spec/reports/ 8 | /tmp/ 9 | *.lock 10 | *.so 11 | *.dylib 12 | *.dll 13 | -------------------------------------------------------------------------------- /CHANGELOG.md: -------------------------------------------------------------------------------- 1 | ## 0.4.0 (2024-10-22) 2 | 3 | - Dropped support for Ruby < 3.1 4 | 5 | ## 0.3.0 (2022-08-07) 6 | 7 | - Added metrics 8 | - Prefer `save` over `save_model` 9 | - Prefer `load` over `load_model` 10 | - Dropped support for Ruby < 2.7 11 | 12 | ## 0.2.6 (2021-12-02) 13 | 14 | - Improved ARM detection 15 | 16 | ## 0.2.5 (2021-10-18) 17 | 18 | - Added named loss functions 19 | - Added `Matrix` class 20 | - Improved error checking for `fit`, `cv`, `save_model`, and `load_model` 21 | 22 | ## 0.2.4 (2021-08-05) 23 | 24 | - Fixed memory leak 25 | 26 | ## 0.2.3 (2021-03-14) 27 | 28 | - Added ARM shared library for Linux 29 | 30 | ## 0.2.2 (2021-02-04) 31 | 32 | - Reduced allocations 33 | - Improved ARM detection 34 | 35 | ## 0.2.1 (2020-12-28) 36 | 37 | - Added ARM shared library for Mac 38 | 39 | ## 0.2.0 (2020-03-26) 40 | 41 | - Changed to BSD 3-Clause license to match LIBMF 42 | - Added support for reading data directly from files 43 | - Added `format: :numo` option to `p_factors` and `q_factors` 44 | - Improved performance of loading data by 5x 45 | 46 | ## 0.1.3 (2019-11-07) 47 | 48 | - Made parameter names more Ruby-like 49 | - No need to set `do_nmf` with generalized KL-divergence 50 | 51 | ## 0.1.2 (2019-11-06) 52 | 53 | - Fixed bug in `p_factors` and `q_factors` methods 54 | 55 | ## 0.1.1 (2019-11-05) 56 | 57 | - Fixed errors on Linux and Windows 58 | 59 | ## 0.1.0 (2019-11-04) 60 | 61 | - First release 62 | -------------------------------------------------------------------------------- /Gemfile: -------------------------------------------------------------------------------- 1 | source "https://rubygems.org" 2 | 3 | gemspec 4 | 5 | gem "rake" 6 | gem "minitest", ">= 5" 7 | gem "benchmark-ips" 8 | gem "numo-narray", platform: [:mri, :x64_mingw] 9 | -------------------------------------------------------------------------------- /LICENSE.txt: -------------------------------------------------------------------------------- 1 | BSD 3-Clause License 2 | 3 | Copyright (c) 2014-2015 The LIBMF Project. 4 | Copyright (c) 2019-2024 Andrew Kane. 5 | All rights reserved. 6 | 7 | Redistribution and use in source and binary forms, with or without 8 | modification, are permitted provided that the following conditions 9 | are met: 10 | 11 | 1. Redistributions of source code must retain the above copyright 12 | notice, this list of conditions and the following disclaimer. 13 | 14 | 2. Redistributions in binary form must reproduce the above copyright 15 | notice, this list of conditions and the following disclaimer in the 16 | documentation and/or other materials provided with the distribution. 17 | 18 | 3. Neither name of copyright holders nor the names of its contributors 19 | may be used to endorse or promote products derived from this software 20 | without specific prior written permission. 21 | 22 | 23 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 24 | ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 25 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR 26 | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR 27 | CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, 28 | EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, 29 | PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 30 | PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 31 | LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 32 | NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 33 | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 34 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # LIBMF Ruby 2 | 3 | [LIBMF](https://github.com/cjlin1/libmf) - large-scale sparse matrix factorization - for Ruby 4 | 5 | Check out [Disco](https://github.com/ankane/disco) for higher-level collaborative filtering 6 | 7 | [![Build Status](https://github.com/ankane/libmf-ruby/actions/workflows/build.yml/badge.svg)](https://github.com/ankane/libmf-ruby/actions) 8 | 9 | ## Installation 10 | 11 | Add this line to your application’s Gemfile: 12 | 13 | ```ruby 14 | gem "libmf" 15 | ``` 16 | 17 | ## Getting Started 18 | 19 | Prep your data in the format `row_index, column_index, value` 20 | 21 | ```ruby 22 | data = Libmf::Matrix.new 23 | data.push(0, 0, 5.0) 24 | data.push(0, 2, 3.5) 25 | data.push(1, 1, 4.0) 26 | ``` 27 | 28 | Create a model 29 | 30 | ```ruby 31 | model = Libmf::Model.new 32 | model.fit(data) 33 | ``` 34 | 35 | Make predictions 36 | 37 | ```ruby 38 | model.predict(row_index, column_index) 39 | ``` 40 | 41 | Get the latent factors (these approximate the training matrix) 42 | 43 | ```ruby 44 | model.p_factors 45 | model.q_factors 46 | ``` 47 | 48 | Get the bias (average of all elements in the training matrix) 49 | 50 | ```ruby 51 | model.bias 52 | ``` 53 | 54 | Save the model to a file 55 | 56 | ```ruby 57 | model.save("model.txt") 58 | ``` 59 | 60 | Load the model from a file 61 | 62 | ```ruby 63 | model = Libmf::Model.load("model.txt") 64 | ``` 65 | 66 | Pass a validation set 67 | 68 | ```ruby 69 | model.fit(data, eval_set: eval_set) 70 | ``` 71 | 72 | ## Cross-Validation 73 | 74 | Perform cross-validation 75 | 76 | ```ruby 77 | model.cv(data) 78 | ``` 79 | 80 | Specify the number of folds 81 | 82 | ```ruby 83 | model.cv(data, folds: 5) 84 | ``` 85 | 86 | ## Parameters 87 | 88 | Pass parameters - default values below 89 | 90 | ```ruby 91 | Libmf::Model.new( 92 | loss: :real_l2, # loss function 93 | factors: 8, # number of latent factors 94 | threads: 12, # number of threads used 95 | bins: 25, # number of bins 96 | iterations: 20, # number of iterations 97 | lambda_p1: 0, # coefficient of L1-norm regularization on P 98 | lambda_p2: 0.1, # coefficient of L2-norm regularization on P 99 | lambda_q1: 0, # coefficient of L1-norm regularization on Q 100 | lambda_q2: 0.1, # coefficient of L2-norm regularization on Q 101 | learning_rate: 0.1, # learning rate 102 | alpha: 1, # importance of negative entries 103 | c: 0.0001, # desired value of negative entries 104 | nmf: false, # perform non-negative MF (NMF) 105 | quiet: false # no outputs to stdout 106 | ) 107 | ``` 108 | 109 | ### Loss Functions 110 | 111 | For real-valued matrix factorization 112 | 113 | - `:real_l2` - squared error (L2-norm) 114 | - `:real_l1` - absolute error (L1-norm) 115 | - `:real_kl` - generalized KL-divergence 116 | 117 | For binary matrix factorization 118 | 119 | - `:binary_log` - logarithmic error 120 | - `:binary_l2` - squared hinge loss 121 | - `:binary_l1` - hinge loss 122 | 123 | For one-class matrix factorization 124 | 125 | - `:one_class_row` - row-oriented pair-wise logarithmic loss 126 | - `:one_class_col` - column-oriented pair-wise logarithmic loss 127 | - `:one_class_l2` - squared error (L2-norm) 128 | 129 | ## Metrics 130 | 131 | Calculate RMSE (for real-valued MF) 132 | 133 | ```ruby 134 | model.rmse(data) 135 | ``` 136 | 137 | Calculate MAE (for real-valued MF) 138 | 139 | ```ruby 140 | model.mae(data) 141 | ``` 142 | 143 | Calculate generalized KL-divergence (for non-negative real-valued MF) 144 | 145 | ```ruby 146 | model.gkl(data) 147 | ``` 148 | 149 | Calculate logarithmic loss (for binary MF) 150 | 151 | ```ruby 152 | model.logloss(data) 153 | ``` 154 | 155 | Calculate accuracy (for binary MF) 156 | 157 | ```ruby 158 | model.accuracy(data) 159 | ``` 160 | 161 | Calculate MPR (for one-class MF) 162 | 163 | ```ruby 164 | model.mpr(data, transpose) 165 | ``` 166 | 167 | Calculate AUC (for one-class MF) 168 | 169 | ```ruby 170 | model.auc(data, transpose) 171 | ``` 172 | 173 | ## Example 174 | 175 | Download the [MovieLens 100K dataset](https://grouplens.org/datasets/movielens/100k/) and use: 176 | 177 | ```ruby 178 | require "csv" 179 | 180 | train_set = Libmf::Matrix.new 181 | valid_set = Libmf::Matrix.new 182 | 183 | CSV.foreach("u.data", col_sep: "\t").with_index do |row, i| 184 | data = i < 80000 ? train_set : valid_set 185 | data.push(row[0].to_i, row[1].to_i, row[2].to_f) 186 | end 187 | 188 | model = Libmf::Model.new(factors: 20) 189 | model.fit(train_set, eval_set: valid_set) 190 | 191 | puts model.rmse(valid_set) 192 | ``` 193 | 194 | ## Performance 195 | 196 | For performance, read data directly from files 197 | 198 | ```ruby 199 | model.fit("train.txt", eval_set: "validate.txt") 200 | model.cv("train.txt") 201 | ``` 202 | 203 | Data should be in the format `row_index column_index value`: 204 | 205 | ```txt 206 | 0 0 5.0 207 | 0 2 3.5 208 | 1 1 4.0 209 | ``` 210 | 211 | ## Numo 212 | 213 | Get latent factors as Numo arrays 214 | 215 | ```ruby 216 | model.p_factors(format: :numo) 217 | model.q_factors(format: :numo) 218 | ``` 219 | 220 | ## Resources 221 | 222 | - [LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems](https://www.csie.ntu.edu.tw/~cjlin/papers/libmf/libmf_open_source.pdf) 223 | 224 | ## History 225 | 226 | View the [changelog](https://github.com/ankane/libmf-ruby/blob/master/CHANGELOG.md) 227 | 228 | ## Contributing 229 | 230 | Everyone is encouraged to help improve this project. Here are a few ways you can help: 231 | 232 | - [Report bugs](https://github.com/ankane/libmf-ruby/issues) 233 | - Fix bugs and [submit pull requests](https://github.com/ankane/libmf-ruby/pulls) 234 | - Write, clarify, or fix documentation 235 | - Suggest or add new features 236 | 237 | To get started with development: 238 | 239 | ```sh 240 | git clone https://github.com/ankane/libmf-ruby.git 241 | cd libmf-ruby 242 | bundle install 243 | bundle exec rake vendor:all 244 | bundle exec rake test 245 | ``` 246 | -------------------------------------------------------------------------------- /Rakefile: -------------------------------------------------------------------------------- 1 | require "bundler/gem_tasks" 2 | require "rake/testtask" 3 | 4 | task default: :test 5 | Rake::TestTask.new do |t| 6 | t.libs << "test" 7 | t.pattern = "test/**/*_test.rb" 8 | end 9 | 10 | def download_file(file, sha256) 11 | require "open-uri" 12 | 13 | url = "https://github.com/ankane/ml-builds/releases/download/libmf-master-2/#{file}" 14 | puts "Downloading #{file}..." 15 | contents = URI.parse(url).read 16 | 17 | computed_sha256 = Digest::SHA256.hexdigest(contents) 18 | raise "Bad hash: #{computed_sha256}" if computed_sha256 != sha256 19 | 20 | dest = "vendor/#{file}" 21 | File.binwrite(dest, contents) 22 | puts "Saved #{dest}" 23 | end 24 | 25 | namespace :vendor do 26 | task :linux do 27 | download_file("libmf.so", "5a22ec277a14ab8e3b8efacfec7fe57e5ac4192ea60e233d7e6db38db755a67e") 28 | download_file("libmf.arm64.so", "223ef5d1213b883c8cb8623bf07bf45167cd48585a5f2b59618cea034c72ad61") 29 | end 30 | 31 | task :mac do 32 | download_file("libmf.dylib", "6e3451feeded62a2e761647aef7c2a0e7dbeeee83ce8d4ab06586f5820f7ebf9") 33 | download_file("libmf.arm64.dylib", "063c1dc39a6fda12ea2616d518fa319b8ab58faa65b174f176861cf8f8eaae0d") 34 | end 35 | 36 | task :windows do 37 | download_file("mf.dll", "8b0e53ab50ca3e2b365424652107db382dff47a26220c092b89729f9c3b8d7e7") 38 | end 39 | 40 | task all: [:linux, :mac, :windows] 41 | 42 | task :platform do 43 | if Gem.win_platform? 44 | Rake::Task["vendor:windows"].invoke 45 | elsif RbConfig::CONFIG["host_os"] =~ /darwin/i 46 | Rake::Task["vendor:mac"].invoke 47 | else 48 | Rake::Task["vendor:linux"].invoke 49 | end 50 | end 51 | end 52 | 53 | task :benchmark do 54 | require "benchmark/ips" 55 | require "libmf" 56 | 57 | data = [] 58 | File.foreach("vendor/demo/real_matrix.tr.txt") do |line| 59 | row = line.chomp.split(" ") 60 | data << [row[0].to_i, row[1].to_i, row[2].to_f] 61 | end 62 | model = Libmf::Model.new(quiet: true) 63 | 64 | Benchmark.ips do |x| 65 | x.report("fit") { model.fit(data) } 66 | end 67 | end 68 | -------------------------------------------------------------------------------- /lib/libmf.rb: -------------------------------------------------------------------------------- 1 | # dependencies 2 | require "ffi" 3 | 4 | # modules 5 | require_relative "libmf/matrix" 6 | require_relative "libmf/model" 7 | require_relative "libmf/version" 8 | 9 | module Libmf 10 | class Error < StandardError; end 11 | 12 | class << self 13 | attr_accessor :ffi_lib 14 | end 15 | lib_name = 16 | if Gem.win_platform? 17 | "mf.dll" 18 | elsif RbConfig::CONFIG["host_os"] =~ /darwin/i 19 | if RbConfig::CONFIG["host_cpu"] =~ /arm|aarch64/i 20 | "libmf.arm64.dylib" 21 | else 22 | "libmf.dylib" 23 | end 24 | else 25 | if RbConfig::CONFIG["host_cpu"] =~ /arm|aarch64/i 26 | "libmf.arm64.so" 27 | else 28 | "libmf.so" 29 | end 30 | end 31 | vendor_lib = File.expand_path("../vendor/#{lib_name}", __dir__) 32 | self.ffi_lib = [vendor_lib] 33 | 34 | # friendlier error message 35 | autoload :FFI, "libmf/ffi" 36 | end 37 | -------------------------------------------------------------------------------- /lib/libmf/ffi.rb: -------------------------------------------------------------------------------- 1 | module Libmf 2 | module FFI 3 | extend ::FFI::Library 4 | 5 | ffi_lib Libmf.ffi_lib 6 | 7 | class Node < ::FFI::Struct 8 | layout :u, :int, 9 | :v, :int, 10 | :r, :float 11 | end 12 | 13 | class Problem < ::FFI::Struct 14 | layout :m, :int, 15 | :n, :int, 16 | :nnz, :long_long, 17 | :r, :pointer 18 | end 19 | 20 | class Parameter < ::FFI::Struct 21 | layout :fun, :int, 22 | :k, :int, 23 | :nr_threads, :int, 24 | :nr_bins, :int, 25 | :nr_iters, :int, 26 | :lambda_p1, :float, 27 | :lambda_p2, :float, 28 | :lambda_q1, :float, 29 | :lambda_q2, :float, 30 | :eta, :float, 31 | :alpha, :float, 32 | :c, :float, 33 | :do_nmf, :bool, 34 | :quiet, :bool, 35 | :copy_data, :bool 36 | end 37 | 38 | class Model < ::FFI::Struct 39 | layout :fun, :int, 40 | :m, :int, 41 | :n, :int, 42 | :k, :int, 43 | :b, :float, 44 | :p, :pointer, 45 | :q, :pointer 46 | 47 | def self.release(pointer) 48 | unless pointer.null? 49 | ref = ::FFI::MemoryPointer.new(:pointer).write_pointer(pointer) 50 | FFI.mf_destroy_model(ref) 51 | end 52 | end 53 | end 54 | 55 | attach_function :mf_get_default_param, [], Parameter.by_value 56 | attach_function :mf_read_problem, [:string], Problem.by_value 57 | attach_function :mf_save_model, [Model.by_ref, :string], :int 58 | attach_function :mf_load_model, [:string], Model.auto_ptr 59 | attach_function :mf_destroy_model, [:pointer], :void 60 | attach_function :mf_train, [Problem.by_ref, Parameter.by_value], Model.auto_ptr 61 | attach_function :mf_train_with_validation, [Problem.by_ref, Problem.by_ref, Parameter.by_value], Model.auto_ptr 62 | attach_function :mf_cross_validation, [Problem.by_ref, :int, Parameter.by_value], :double 63 | attach_function :mf_predict, [Model.by_ref, :int, :int], :float 64 | attach_function :calc_rmse, [Problem.by_ref, Model.by_ref], :double 65 | attach_function :calc_mae, [Problem.by_ref, Model.by_ref], :double 66 | attach_function :calc_gkl, [Problem.by_ref, Model.by_ref], :double 67 | attach_function :calc_logloss, [Problem.by_ref, Model.by_ref], :double 68 | attach_function :calc_accuracy, [Problem.by_ref, Model.by_ref], :double 69 | attach_function :calc_mpr, [Problem.by_ref, Model.by_ref, :bool], :double 70 | attach_function :calc_auc, [Problem.by_ref, Model.by_ref, :bool], :double 71 | end 72 | end 73 | -------------------------------------------------------------------------------- /lib/libmf/matrix.rb: -------------------------------------------------------------------------------- 1 | module Libmf 2 | class Matrix 3 | attr_reader :data 4 | 5 | def initialize 6 | @data = [] 7 | end 8 | 9 | def push(row_index, column_index, value) 10 | @data << [row_index, column_index, value] 11 | end 12 | end 13 | end 14 | -------------------------------------------------------------------------------- /lib/libmf/model.rb: -------------------------------------------------------------------------------- 1 | module Libmf 2 | class Model 3 | def initialize(**options) 4 | @options = options 5 | end 6 | 7 | def fit(data, eval_set: nil) 8 | train_set = create_problem(data) 9 | 10 | @model = 11 | if eval_set 12 | eval_set = create_problem(eval_set) 13 | FFI.mf_train_with_validation(train_set, eval_set, param) 14 | else 15 | FFI.mf_train(train_set, param) 16 | end 17 | raise Error, "fit failed" if @model.null? 18 | 19 | nil 20 | end 21 | 22 | def predict(row, column) 23 | FFI.mf_predict(model, row, column) 24 | end 25 | 26 | def cv(data, folds: 5) 27 | problem = create_problem(data) 28 | # TODO update fork to differentiate between bad parameters and zero error 29 | res = FFI.mf_cross_validation(problem, folds, param) 30 | raise Error, "cv failed" if res == 0 31 | res 32 | end 33 | 34 | def save_model(path) 35 | status = FFI.mf_save_model(model, path) 36 | raise Error, "Cannot save model" if status != 0 37 | end 38 | alias_method :save, :save_model 39 | 40 | def self.load(path) 41 | model = Model.new 42 | model.load_model(path) 43 | model 44 | end 45 | 46 | def load_model(path) 47 | @model = FFI.mf_load_model(path) 48 | raise Error, "Cannot open model" if @model.null? 49 | end 50 | 51 | def rows 52 | model[:m] 53 | end 54 | 55 | def columns 56 | model[:n] 57 | end 58 | 59 | def factors 60 | model[:k] 61 | end 62 | 63 | def bias 64 | model[:b] 65 | end 66 | 67 | def p_factors(format: nil) 68 | _factors(model[:p], rows, format) 69 | end 70 | 71 | def q_factors(format: nil) 72 | _factors(model[:q], columns, format) 73 | end 74 | 75 | def rmse(data) 76 | FFI.calc_rmse(create_problem(data), model) 77 | end 78 | 79 | def mae(data) 80 | FFI.calc_mae(create_problem(data), model) 81 | end 82 | 83 | def gkl(data) 84 | FFI.calc_gkl(create_problem(data), model) 85 | end 86 | 87 | def logloss(data) 88 | FFI.calc_logloss(create_problem(data), model) 89 | end 90 | 91 | def accuracy(data) 92 | FFI.calc_accuracy(create_problem(data), model) 93 | end 94 | 95 | def mpr(data, transpose) 96 | FFI.calc_mpr(create_problem(data), model, transpose) 97 | end 98 | 99 | def auc(data, transpose) 100 | FFI.calc_auc(create_problem(data), model, transpose) 101 | end 102 | 103 | private 104 | 105 | def _factors(ptr, n, format) 106 | case format 107 | when :numo 108 | Numo::SFloat.from_string(ptr.read_bytes(n * factors * 4)).reshape(n, factors) 109 | when nil 110 | ptr.read_array_of_float(n * factors).each_slice(factors).to_a 111 | else 112 | raise ArgumentError, "Invalid format" 113 | end 114 | end 115 | 116 | def model 117 | raise Error, "Not fit" unless @model 118 | @model 119 | end 120 | 121 | def param 122 | param = FFI.mf_get_default_param 123 | options = @options.dup 124 | 125 | if options[:loss].is_a?(Symbol) 126 | loss_map = { 127 | real_l2: 0, 128 | real_l1: 1, 129 | real_kl: 2, 130 | binary_log: 5, 131 | binary_l2: 6, 132 | binary_l1: 7, 133 | one_class_row: 10, 134 | one_class_col: 11, 135 | one_class_l2: 12 136 | } 137 | options[:loss] = loss_map[options[:loss]] || (raise ArgumentError, "Unknown loss") 138 | end 139 | 140 | # silence insufficient blocks warning with default params 141 | options[:bins] ||= 25 unless options[:nr_bins] 142 | options[:copy_data] = false unless options.key?(:copy_data) 143 | options_map = { 144 | loss: :fun, 145 | factors: :k, 146 | threads: :nr_threads, 147 | bins: :nr_bins, 148 | iterations: :nr_iters, 149 | learning_rate: :eta, 150 | nmf: :do_nmf 151 | } 152 | options.each do |k, v| 153 | k = options_map[k] if options_map[k] 154 | param[k] = v 155 | end 156 | # do_nmf must be true for generalized KL-divergence 157 | param[:do_nmf] = true if param[:fun] == 2 158 | param 159 | end 160 | 161 | def create_problem(data) 162 | if data.is_a?(String) 163 | # need to expand path so it's absolute 164 | return FFI.mf_read_problem(File.expand_path(data)) 165 | end 166 | 167 | if data.is_a?(Matrix) 168 | data = data.data 169 | end 170 | 171 | raise Error, "No data" if data.empty? 172 | 173 | # TODO do in C for better performance 174 | # can use FIX2INT() and RFLOAT_VALUE() instead of pack 175 | # and write directly to C string 176 | buffer = String.new 177 | pack_format = "iif" 178 | data.each do |row| 179 | row.pack(pack_format, buffer: buffer) 180 | end 181 | 182 | r = ::FFI::MemoryPointer.new(FFI::Node, data.size) 183 | r.write_bytes(buffer) 184 | 185 | # double check size is what we expect 186 | # FFI will throw an error above if too long 187 | raise Error, "Bad buffer size" if r.size != buffer.bytesize 188 | 189 | m = data.max_by { |r| r[0] }[0] + 1 190 | n = data.max_by { |r| r[1] }[1] + 1 191 | 192 | prob = FFI::Problem.new 193 | prob[:m] = m 194 | prob[:n] = n 195 | prob[:nnz] = data.size 196 | prob[:r] = r 197 | prob 198 | end 199 | end 200 | end 201 | -------------------------------------------------------------------------------- /lib/libmf/version.rb: -------------------------------------------------------------------------------- 1 | module Libmf 2 | VERSION = "0.4.0" 3 | end 4 | -------------------------------------------------------------------------------- /libmf.gemspec: -------------------------------------------------------------------------------- 1 | require_relative "lib/libmf/version" 2 | 3 | Gem::Specification.new do |spec| 4 | spec.name = "libmf" 5 | spec.version = Libmf::VERSION 6 | spec.summary = "Large-scale sparse matrix factorization for Ruby" 7 | spec.homepage = "https://github.com/ankane/libmf-ruby" 8 | spec.license = "BSD-3-Clause" 9 | 10 | spec.author = "Andrew Kane" 11 | spec.email = "andrew@ankane.org" 12 | 13 | spec.files = Dir["*.{md,txt}", "{lib,vendor}/**/*"] 14 | spec.require_path = "lib" 15 | 16 | spec.required_ruby_version = ">= 3.1" 17 | 18 | spec.add_dependency "ffi" 19 | end 20 | -------------------------------------------------------------------------------- /test/model_test.rb: -------------------------------------------------------------------------------- 1 | require_relative "test_helper" 2 | 3 | class ModelTest < Minitest::Test 4 | def test_works 5 | data = read_file("real_matrix.tr.txt") 6 | 7 | model = Libmf::Model.new(quiet: true) 8 | model.fit(data) 9 | 10 | assert_equal 2309, model.rows 11 | assert_equal 1368, model.columns 12 | assert_equal 8, model.factors 13 | assert model.bias 14 | assert_equal model.rows, model.p_factors.size 15 | assert_equal model.factors, model.p_factors.first.size 16 | assert_equal model.columns, model.q_factors.size 17 | assert_equal model.factors, model.q_factors.first.size 18 | 19 | pred = model.predict(1, 1) 20 | tempfile = Tempfile.new("libmf") 21 | model.save(tempfile.path) 22 | model = Libmf::Model.load(tempfile.path) 23 | assert_equal pred, model.predict(1, 1) 24 | 25 | lines = File.readlines(tempfile.path) 26 | p10 = lines.find { |l| l.start_with?("p10 ") }[5..-1].split(" ").map(&:to_f) 27 | p10.zip(model.p_factors[10]).each do |a, b| 28 | assert_in_delta a, b 29 | end 30 | q10 = lines.find { |l| l.start_with?("q10 ") }[5..-1].split(" ").map(&:to_f) 31 | q10.zip(model.q_factors[10]).each do |a, b| 32 | assert_in_delta a, b 33 | end 34 | 35 | assert_equal 2309, model.rows 36 | assert_equal 1368, model.columns 37 | assert_equal 8, model.factors 38 | assert model.bias 39 | assert_equal model.rows, model.p_factors.size 40 | assert_equal model.factors, model.p_factors.first.size 41 | assert_equal model.columns, model.q_factors.size 42 | assert_equal model.factors, model.q_factors.first.size 43 | end 44 | 45 | def test_eval_set 46 | train_set = read_file("real_matrix.tr.txt") 47 | eval_set = read_file("real_matrix.te.txt") 48 | 49 | model = Libmf::Model.new(quiet: true) 50 | model.fit(train_set, eval_set: eval_set) 51 | assert model.rmse(eval_set) 52 | end 53 | 54 | def test_path 55 | model = Libmf::Model.new(quiet: true) 56 | model.fit(file_path("real_matrix.tr.txt")) 57 | assert_equal 2309, model.rows 58 | end 59 | 60 | def test_path_eval_set 61 | model = Libmf::Model.new(quiet: true) 62 | model.fit(file_path("real_matrix.tr.txt"), eval_set: file_path("real_matrix.te.txt")) 63 | assert_equal 2309, model.rows 64 | end 65 | 66 | def test_cv 67 | data = read_file("real_matrix.tr.txt") 68 | model = Libmf::Model.new(quiet: true) 69 | assert model.cv(data) 70 | end 71 | 72 | def test_loss_real_kl 73 | data = read_file("real_matrix.tr.txt") 74 | 75 | model = Libmf::Model.new(quiet: true, loss: :real_kl) 76 | model.fit(data) 77 | end 78 | 79 | def test_loss_unknown 80 | data = read_file("real_matrix.tr.txt") 81 | 82 | model = Libmf::Model.new(quiet: true, loss: :unknown) 83 | error = assert_raises ArgumentError do 84 | model.fit(data) 85 | end 86 | assert_equal "Unknown loss", error.message 87 | end 88 | 89 | def test_not_fit 90 | model = Libmf::Model.new 91 | error = assert_raises Libmf::Error do 92 | model.bias 93 | end 94 | assert_equal "Not fit", error.message 95 | end 96 | 97 | def test_no_data 98 | model = Libmf::Model.new 99 | error = assert_raises Libmf::Error do 100 | model.fit([]) 101 | end 102 | assert_equal "No data", error.message 103 | end 104 | 105 | def test_save_missing 106 | data = read_file("real_matrix.tr.txt") 107 | model = Libmf::Model.new(quiet: true) 108 | model.fit(data) 109 | error = assert_raises Libmf::Error do 110 | model.save("missing/model.txt") 111 | end 112 | assert_equal "Cannot save model", error.message 113 | end 114 | 115 | def test_load_missing 116 | error = assert_raises Libmf::Error do 117 | Libmf::Model.load("missing.txt") 118 | end 119 | assert_equal "Cannot open model", error.message 120 | end 121 | 122 | def test_fit_bad_param 123 | data = read_file("real_matrix.tr.txt") 124 | model = Libmf::Model.new(quiet: true, factors: 0) 125 | error = assert_raises Libmf::Error do 126 | model.fit(data) 127 | end 128 | assert_equal "fit failed", error.message 129 | end 130 | 131 | def test_cv_bad_param 132 | data = read_file("real_matrix.tr.txt") 133 | model = Libmf::Model.new(quiet: true, factors: 0) 134 | error = assert_raises Libmf::Error do 135 | model.cv(data) 136 | end 137 | assert_equal "cv failed", error.message 138 | end 139 | 140 | def test_numo 141 | skip if ["jruby", "truffleruby"].include?(RUBY_ENGINE) 142 | 143 | data = read_file("real_matrix.tr.txt") 144 | 145 | model = Libmf::Model.new(quiet: true) 146 | model.fit(data) 147 | 148 | assert_equal [model.rows, model.factors], model.p_factors(format: :numo).shape 149 | assert_equal [model.columns, model.factors], model.q_factors(format: :numo).shape 150 | 151 | # unknown format 152 | error = assert_raises(ArgumentError) do 153 | model.p_factors(format: :bad) 154 | end 155 | assert_equal "Invalid format", error.message 156 | end 157 | 158 | def test_matrix 159 | data = Libmf::Matrix.new 160 | read_file("real_matrix.tr.txt").each do |row| 161 | data.push(*row) 162 | end 163 | 164 | model = Libmf::Model.new(quiet: true) 165 | model.fit(data) 166 | 167 | assert_equal 2309, model.rows 168 | assert_equal 1368, model.columns 169 | end 170 | 171 | private 172 | 173 | def file_path(filename) 174 | "vendor/demo/#{filename}" 175 | end 176 | 177 | FILES = {} 178 | 179 | def read_file(filename) 180 | FILES[filename] ||= begin 181 | data = [] 182 | File.foreach(file_path(filename)) do |line| 183 | row = line.chomp.split(" ") 184 | data << [row[0].to_i, row[1].to_i, row[2].to_f].freeze 185 | end 186 | data.freeze 187 | end 188 | end 189 | end 190 | -------------------------------------------------------------------------------- /test/test_helper.rb: -------------------------------------------------------------------------------- 1 | require "bundler/setup" 2 | Bundler.require(:default) 3 | require "minitest/autorun" 4 | require "minitest/pride" 5 | 6 | class Minitest::Test 7 | def setup 8 | if stress? 9 | # autoload before GC.stress 10 | Libmf::FFI.name 11 | read_file("real_matrix.te.txt") 12 | read_file("real_matrix.tr.txt") 13 | GC.stress = true 14 | end 15 | end 16 | 17 | def teardown 18 | GC.stress = false if stress? 19 | end 20 | 21 | def stress? 22 | ENV["STRESS"] 23 | end 24 | end 25 | -------------------------------------------------------------------------------- /vendor/COPYRIGHT: -------------------------------------------------------------------------------- 1 | 2 | Copyright (c) 2014-2015 The LIBMF Project. 3 | All rights reserved. 4 | 5 | Redistribution and use in source and binary forms, with or without 6 | modification, are permitted provided that the following conditions 7 | are met: 8 | 9 | 1. Redistributions of source code must retain the above copyright 10 | notice, this list of conditions and the following disclaimer. 11 | 12 | 2. Redistributions in binary form must reproduce the above copyright 13 | notice, this list of conditions and the following disclaimer in the 14 | documentation and/or other materials provided with the distribution. 15 | 16 | 3. Neither name of copyright holders nor the names of its contributors 17 | may be used to endorse or promote products derived from this software 18 | without specific prior written permission. 19 | 20 | 21 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 22 | ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 23 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR 24 | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR 25 | CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, 26 | EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, 27 | PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 28 | PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 29 | LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 30 | NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 31 | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 32 | -------------------------------------------------------------------------------- /vendor/demo/real_matrix.te.txt: -------------------------------------------------------------------------------- 1 | 1040 128 3.5 2 | 967 1 2.1 3 | 392 17 4.1 4 | 406 6 3.1 5 | 1333 20 5.1 6 | 2168 45 4.0 7 | 923 26 4.5 8 | 2004 13 4.0 9 | 92 155 4.0 10 | 2019 45 3.0 11 | 1737 1 4.0 12 | 414 187 3.0 13 | 233 6 3.1 14 | 1026 61 1.1 15 | 1253 836 2.6 16 | 1270 41 4.0 17 | 2148 45 4.0 18 | 1200 1227 2.1 19 | 1523 175 3.0 20 | 1820 147 5.1 21 | 899 777 3.0 22 | 1284 81 3.6 23 | 77 7 4.0 24 | 1082 836 4.1 25 | 587 9 4.0 26 | 785 7 5.1 27 | 181 45 4.0 28 | 1185 128 5.0 29 | 2004 17 4.1 30 | 1617 7 3.1 31 | 1839 72 4.1 32 | 1527 20 5.1 33 | 241 100 2.0 34 | 645 17 4.0 35 | 295 43 2.0 36 | 1616 17 3.0 37 | 1995 45 3.0 38 | 2200 27 3.1 39 | 1896 1 5.1 40 | 332 27 4.0 41 | 734 1 4.1 42 | 1696 25 4.0 43 | 1202 7 4.0 44 | 1567 2 4.0 45 | 319 1 4.1 46 | 505 42 3.1 47 | 156 43 4.6 48 | 570 65 3.1 49 | 1722 5 3.1 50 | 947 25 4.1 51 | 1357 555 3.1 52 | 889 41 3.1 53 | 1809 43 2.1 54 | 899 95 4.1 55 | 465 5 4.1 56 | 193 990 5.0 57 | 825 3 5.0 58 | 1284 25 3.1 59 | 1724 42 2.1 60 | 1946 3 3.0 61 | 1092 155 3.6 62 | 253 1 5.1 63 | 92 27 4.1 64 | 2003 5 4.0 65 | 1642 8 4.0 66 | 550 45 3.5 67 | 1853 35 3.0 68 | 667 5 4.1 69 | 1736 11 3.0 70 | 1856 803 4.6 71 | 1860 803 3.6 72 | 312 1 4.5 73 | 1080 108 3.1 74 | 1857 2 3.6 75 | 691 25 4.1 76 | 474 7 3.1 77 | 795 27 4.1 78 | 380 26 5.0 79 | 1452 1 3.0 80 | 2248 1 3.1 81 | 165 4 4.1 82 | 1910 45 4.0 83 | 42 43 5.0 84 | 60 777 4.1 85 | 1312 27 4.0 86 | 887 1 4.0 87 | 2060 7 3.0 88 | 2307 43 3.0 89 | 1374 183 3.5 90 | 2220 63 4.1 91 | 1869 1 4.5 92 | 1252 26 5.0 93 | 2114 5 4.1 94 | 75 42 3.0 95 | 1069 76 4.1 96 | 298 26 3.5 97 | 1172 6 3.0 98 | 426 43 3.0 99 | 1874 29 3.0 100 | 221 50 4.0 101 | 907 1 5.0 102 | 924 84 2.0 103 | 380 86 4.0 104 | 408 100 4.0 105 | 2234 24 3.1 106 | 70 41 4.1 107 | 587 17 3.0 108 | 1951 836 5.0 109 | 780 25 3.1 110 | 1970 1258 4.0 111 | 749 1105 2.5 112 | 2301 39 3.0 113 | 16 35 4.0 114 | 1565 84 2.1 115 | 44 5 5.1 116 | 624 6 4.1 117 | 48 5 3.1 118 | 1475 6 1.1 119 | 1022 128 4.5 120 | 2236 63 2.0 121 | 350 26 5.0 122 | 696 8 3.5 123 | 2173 84 3.0 124 | 1069 64 4.1 125 | 18 83 4.1 126 | 1558 1 5.0 127 | 1422 25 5.0 128 | 1188 84 4.1 129 | 2107 3 3.5 130 | 332 565 3.5 131 | 2271 46 4.0 132 | 2178 45 2.0 133 | 748 7 2.6 134 | 2279 7 5.1 135 | 455 35 2.6 136 | 1225 3 5.1 137 | 1304 35 4.1 138 | 493 118 3.0 139 | 1831 32 3.1 140 | 2233 23 4.1 141 | 2015 1 3.6 142 | 1052 35 3.5 143 | 801 139 4.0 144 | 241 116 2.6 145 | 1627 26 4.6 146 | 1431 45 5.0 147 | 654 35 5.1 148 | 2166 7 3.0 149 | 604 84 3.0 150 | 1196 143 4.5 151 | 236 17 3.0 152 | 1528 43 1.6 153 | 339 42 4.0 154 | 440 45 2.1 155 | 962 49 4.1 156 | 1506 1 3.0 157 | 940 61 4.1 158 | 637 45 3.5 159 | 612 23 3.1 160 | 524 43 4.1 161 | 2236 18 4.1 162 | 2298 8 3.1 163 | 634 1 5.1 164 | 1466 3 5.1 165 | 265 45 4.0 166 | 1970 77 2.6 167 | 400 128 3.0 168 | 899 143 3.1 169 | 1691 45 4.1 170 | 60 1063 4.1 171 | 2062 45 4.1 172 | 2133 9 2.0 173 | 2121 1 3.1 174 | 1662 128 5.1 175 | 1844 58 5.1 176 | 547 35 3.1 177 | 687 11 2.1 178 | 2064 3 3.0 179 | 2172 6 4.5 180 | 1302 65 5.1 181 | 1722 27 3.6 182 | 637 131 3.6 183 | 1522 3 5.0 184 | 2173 166 3.0 185 | 1317 1 4.5 186 | 551 117 5.0 187 | 696 35 4.0 188 | 1736 8 5.0 189 | 9 131 1.6 190 | 200 3 4.0 191 | 1499 45 4.1 192 | 881 80 3.0 193 | 1690 7 5.0 194 | 964 26 3.6 195 | 877 84 3.5 196 | 706 4 3.1 197 | 649 8 4.1 198 | 942 84 3.1 199 | 178 1 5.1 200 | 379 7 4.0 201 | 1860 2 4.5 202 | 317 8 3.6 203 | 2039 45 3.0 204 | 1340 1 5.0 205 | 493 97 1.0 206 | 1198 7 3.0 207 | 194 13 3.5 208 | 1514 84 3.6 209 | 2052 45 3.1 210 | 2258 8 3.1 211 | 1061 135 2.5 212 | 750 66 2.0 213 | 722 84 3.5 214 | 1890 80 2.0 215 | 1857 3 4.0 216 | 1592 1 3.5 217 | 1894 60 3.0 218 | 2058 45 4.5 219 | 1369 20 5.1 220 | 450 7 2.0 221 | 940 18 5.0 222 | 278 6 3.0 223 | 749 145 3.1 224 | 763 7 4.1 225 | 1181 84 4.1 226 | 1616 84 3.0 227 | 474 6 5.1 228 | 634 1227 2.0 229 | 746 3 3.1 230 | 540 7 5.1 231 | 1380 45 1.6 232 | 278 15 3.0 233 | 2285 1 1.6 234 | 461 35 3.0 235 | 2053 2 5.1 236 | 1662 43 3.6 237 | 667 25 4.0 238 | 285 3 3.0 239 | 1778 1 5.0 240 | 1241 1 5.0 241 | 18 45 4.1 242 | 1440 7 4.0 243 | 1069 23 5.1 244 | 904 66 4.1 245 | 1518 84 4.1 246 | 1688 3 3.6 247 | 1523 191 3.0 248 | 1215 1272 4.0 249 | 1212 7 3.1 250 | 1960 84 4.0 251 | 1778 84 2.5 252 | 1865 23 5.1 253 | 1858 30 3.1 254 | 1986 3 3.0 255 | 1230 1 5.1 256 | 1572 84 3.1 257 | 2052 3 3.0 258 | 1252 49 1.0 259 | 1791 1 5.0 260 | 2222 5 3.0 261 | 1609 27 4.0 262 | 1968 803 4.0 263 | 2068 3 0.6 264 | 1300 26 3.6 265 | 2091 20 4.0 266 | 1236 26 4.1 267 | 1359 45 4.0 268 | 1026 1 5.1 269 | 2077 1 5.1 270 | 659 35 5.1 271 | 1543 68 4.1 272 | 518 4 3.5 273 | 749 44 4.6 274 | 1573 803 3.6 275 | 1431 42 5.0 276 | 1026 26 5.1 277 | 1272 7 5.0 278 | 1906 3 1.0 279 | 615 35 2.0 280 | 370 84 4.0 281 | 1447 1 4.0 282 | 543 65 3.0 283 | 827 91 5.0 284 | 433 64 4.0 285 | 1719 43 5.0 286 | 36 26 4.0 287 | 1297 1 4.1 288 | 1864 22 4.0 289 | 801 9 4.0 290 | 1463 22 4.1 291 | 1615 3 5.0 292 | 114 26 4.0 293 | 1660 44 5.0 294 | 2005 45 4.0 295 | 2265 95 4.0 296 | 2080 116 2.1 297 | 1602 7 3.1 298 | 1226 7 3.1 299 | 1813 84 4.0 300 | 1763 43 3.5 301 | 518 178 4.1 302 | 1860 135 1.5 303 | 1814 63 2.1 304 | 317 26 4.6 305 | 14 43 4.0 306 | 549 7 3.6 307 | 1430 35 2.0 308 | 1523 146 3.0 309 | 2104 128 5.0 310 | 1431 24 2.1 311 | 367 5 3.0 312 | 1649 100 2.1 313 | 1474 20 3.0 314 | 2285 8 3.1 315 | 554 2 3.1 316 | 1186 35 5.0 317 | 281 65 3.1 318 | 554 8 2.0 319 | 517 1 2.0 320 | 519 7 4.1 321 | 1910 7 3.1 322 | 424 8 3.1 323 | 506 23 4.1 324 | 1963 128 4.6 325 | 1332 7 5.1 326 | 1474 81 3.1 327 | 1864 25 3.1 328 | 2168 2 4.0 329 | 2099 3 4.0 330 | 323 175 0.6 331 | 1860 155 2.5 332 | 1970 64 3.5 333 | 2178 42 3.1 334 | 1523 6 2.5 335 | 168 4 4.0 336 | 1437 25 3.0 337 | 60 134 2.0 338 | 1232 41 4.1 339 | 956 3 3.0 340 | 2044 6 4.0 341 | 2178 58 4.0 342 | 1430 66 4.0 343 | 1437 1 4.0 344 | 116 3 3.1 345 | 2084 45 3.0 346 | 188 1 4.1 347 | 904 45 4.0 348 | 1244 45 4.6 349 | 256 17 5.1 350 | 278 49 5.1 351 | 1689 803 3.5 352 | 163 128 4.5 353 | 43 64 2.1 354 | 1749 128 4.5 355 | 1917 1 5.1 356 | 1688 146 4.1 357 | 1019 68 4.1 358 | 820 7 3.0 359 | 1357 58 3.1 360 | 2200 17 4.0 361 | 900 5 4.6 362 | 2244 13 4.0 363 | 1569 990 2.1 364 | 2200 100 2.1 365 | 2258 45 2.0 366 | 1454 35 3.0 367 | 194 909 4.1 368 | 781 1 4.0 369 | 1523 68 3.5 370 | 2147 3 4.1 371 | 2140 3 3.1 372 | 2133 33 3.0 373 | 2070 2 4.6 374 | 1232 23 1.1 375 | 942 63 3.1 376 | 1645 1148 3.0 377 | 1291 45 5.0 378 | 592 62 5.0 379 | 702 45 3.6 380 | 1696 26 4.0 381 | 33 1 4.6 382 | 899 6 3.1 383 | 157 117 4.0 384 | 1548 26 4.1 385 | 1523 836 3.1 386 | 612 24 2.1 387 | 1805 61 3.6 388 | 865 803 5.1 389 | 2248 8 3.0 390 | 865 836 4.5 391 | 1428 1 4.0 392 | 1597 27 4.6 393 | 935 42 3.1 394 | 1071 75 3.1 395 | 1991 144 3.6 396 | 221 45 3.1 397 | 1530 11 3.1 398 | 891 23 4.0 399 | 387 1 3.0 400 | 1445 100 4.5 401 | 75 23 3.0 402 | 312 45 3.5 403 | 836 7 3.5 404 | 1977 166 3.6 405 | 1864 66 4.0 406 | 697 35 1.1 407 | 1226 8 4.1 408 | 464 27 4.0 409 | 1860 178 4.1 410 | 637 75 4.5 411 | 1867 84 3.5 412 | 458 3 3.1 413 | 635 27 4.1 414 | 1131 25 5.0 415 | 506 8 3.5 416 | 2070 1 4.5 417 | 1252 1 5.1 418 | 319 128 4.1 419 | 1530 72 4.1 420 | 429 45 3.5 421 | 1524 29 3.1 422 | 696 95 4.0 423 | 1627 1 5.1 424 | 2034 26 5.0 425 | 555 128 4.6 426 | 616 7 3.0 427 | 642 35 3.1 428 | 2258 3 2.1 429 | 942 35 4.0 430 | 928 20 4.1 431 | 1860 43 5.0 432 | 1977 27 4.6 433 | 1236 3 4.0 434 | 1232 58 3.0 435 | 864 43 4.0 436 | 759 1 3.1 437 | 1689 35 4.1 438 | 1990 25 5.0 439 | 1603 7 3.0 440 | 190 129 1.5 441 | 1689 909 2.1 442 | 1970 1227 3.5 443 | 899 35 3.1 444 | 91 35 3.1 445 | 1264 777 1.5 446 | 1785 84 3.0 447 | 1160 20 5.1 448 | 1857 6 4.0 449 | 1214 129 4.0 450 | 260 26 4.1 451 | 39 6 3.1 452 | 42 45 4.0 453 | 945 26 3.1 454 | 1440 17 3.1 455 | 1389 35 3.5 456 | 1536 8 4.0 457 | 433 39 3.1 458 | 518 3 4.0 459 | 929 1 3.0 460 | 319 1233 2.5 461 | 60 45 4.1 462 | 1545 5 4.1 463 | 958 45 3.1 464 | 827 20 3.0 465 | 899 990 3.0 466 | 1523 100 2.0 467 | 846 35 4.1 468 | 799 45 4.6 469 | 1306 5 5.0 470 | 1422 45 3.0 471 | 750 26 4.1 472 | 590 777 3.1 473 | 427 31 4.0 474 | 2044 73 3.5 475 | 1525 49 5.1 476 | 498 1 5.1 477 | 2264 164 0.5 478 | 2279 5 4.1 479 | 1655 22 2.0 480 | 1461 6 5.0 481 | 1461 8 3.0 482 | 893 128 5.1 483 | 190 1 3.6 484 | 1523 95 3.1 485 | 611 35 5.1 486 | 1738 1272 5.1 487 | 904 5 4.1 488 | 1860 80 4.6 489 | 82 84 4.1 490 | 1689 4 1.1 491 | 2052 42 2.6 492 | 1781 84 4.1 493 | 875 26 4.0 494 | 2200 104 3.0 495 | 816 8 5.0 496 | 1042 30 3.1 497 | 696 3 3.1 498 | 60 909 2.6 499 | 819 7 4.0 500 | 706 6 2.1 501 | 437 84 4.0 502 | 60 745 3.1 503 | 1830 7 2.1 504 | 839 1 5.0 505 | 1359 74 4.1 506 | 1813 9 3.1 507 | 260 43 3.0 508 | 2111 25 4.1 509 | 147 26 4.0 510 | 260 35 4.0 511 | 812 2 3.5 512 | 2115 166 4.0 513 | 2168 5 2.0 514 | 2039 26 3.0 515 | 935 23 3.0 516 | 1722 17 2.0 517 | 881 84 5.0 518 | 838 27 3.0 519 | 1430 17 4.0 520 | 1689 73 1.0 521 | 260 4 3.1 522 | 222 1 5.1 523 | 834 58 5.1 524 | 687 35 4.1 525 | 1010 5 4.1 526 | 1052 84 4.0 527 | 1755 5 4.1 528 | 221 7 4.1 529 | 295 39 1.1 530 | 600 178 5.0 531 | 289 43 3.1 532 | 1340 17 3.1 533 | 122 2 3.1 534 | 2173 191 1.6 535 | 2115 1 5.1 536 | 1754 31 4.0 537 | 405 27 5.1 538 | 586 128 4.1 539 | 1672 191 3.1 540 | 168 9 4.1 541 | 1758 20 5.1 542 | 1528 836 4.5 543 | 1069 13 3.0 544 | 1802 7 4.1 545 | 1035 6 5.0 546 | 175 26 4.0 547 | 1530 45 5.1 548 | 669 5 5.1 549 | 2136 7 3.1 550 | 886 1 4.1 551 | 1896 45 4.6 552 | 2041 45 4.1 553 | 2206 7 4.1 554 | 1963 155 4.5 555 | 1829 45 5.0 556 | 1466 7 5.1 557 | 1386 55 4.6 558 | 1206 26 4.0 559 | 1236 836 4.0 560 | 557 20 4.0 561 | 899 43 2.0 562 | 1827 7 4.0 563 | 1897 26 3.0 564 | 1755 45 4.6 565 | 1685 157 3.1 566 | 25 8 4.0 567 | 1865 31 3.6 568 | 1027 35 4.5 569 | 1582 1 3.6 570 | 152 6 3.0 571 | 788 84 2.5 572 | 1430 81 2.1 573 | 899 803 3.6 574 | 1665 1272 4.1 575 | 593 1 4.6 576 | 328 3 4.0 577 | 706 11 4.1 578 | 1847 4 5.1 579 | 2070 84 4.0 580 | 287 45 3.0 581 | 954 84 1.1 582 | 1335 83 2.6 583 | 1065 41 5.0 584 | 650 909 0.6 585 | 468 131 4.0 586 | 1616 69 1.0 587 | 1022 1227 4.1 588 | 749 5 3.5 589 | 1654 181 3.5 590 | 1523 74 3.0 591 | 1160 43 1.0 592 | 1791 68 5.1 593 | 1357 5 2.6 594 | 193 777 4.0 595 | 241 6 2.0 596 | 1304 26 4.0 597 | 520 8 4.1 598 | 1970 84 3.0 599 | 1239 5 3.0 600 | 1737 6 3.0 601 | 470 166 3.5 602 | 259 45 4.1 603 | 2277 3 4.1 604 | 1567 46 1.0 605 | 1792 23 1.0 606 | 476 23 3.0 607 | 1688 178 4.1 608 | 741 35 4.0 609 | 1348 1 4.5 610 | 1823 45 2.0 611 | 1455 68 4.0 612 | 2293 41 4.1 613 | 845 4 3.0 614 | 1501 63 5.1 615 | 1381 37 3.0 616 | 175 84 3.0 617 | 600 26 5.1 618 | 706 3 3.1 619 | 351 84 4.1 620 | 1069 4 4.1 621 | 1236 74 3.5 622 | 942 3 3.6 623 | 904 125 4.1 624 | 1054 146 4.1 625 | 2139 84 3.1 626 | 1441 29 4.1 627 | 1734 49 4.0 628 | 241 23 4.0 629 | 765 8 5.1 630 | 1900 45 4.6 631 | 296 136 4.1 632 | 14 46 1.0 633 | 493 19 4.0 634 | 1022 83 2.1 635 | 476 35 3.0 636 | 75 1272 3.0 637 | 999 26 2.1 638 | 2016 84 1.5 639 | 728 25 4.5 640 | 1607 26 4.1 641 | 1489 64 3.1 642 | 60 178 2.6 643 | 2173 136 2.5 644 | 1089 11 4.0 645 | 1725 1 4.1 646 | 1252 7 3.1 647 | 1791 45 4.0 648 | 414 27 4.6 649 | 1262 26 5.1 650 | 1450 20 3.0 651 | 2286 1 3.1 652 | 1995 27 4.1 653 | 463 17 5.0 654 | 1614 84 5.1 655 | 757 1 5.1 656 | 557 25 5.0 657 | 1461 30 4.1 658 | 330 7 3.0 659 | 271 45 3.1 660 | 750 87 2.0 661 | 534 3 5.0 662 | 805 7 3.0 663 | 93 1 4.0 664 | 1404 3 4.0 665 | 2174 68 4.0 666 | 1049 44 4.0 667 | 2173 134 1.5 668 | 383 84 4.0 669 | 461 836 4.6 670 | 92 39 3.1 671 | 560 131 1.6 672 | 195 66 5.0 673 | 2070 1227 4.5 674 | 1781 1 3.5 675 | 1979 6 4.0 676 | 1431 1227 4.0 677 | 969 1 4.1 678 | 1957 1 5.1 679 | 899 146 3.0 680 | 748 43 4.0 681 | 713 5 5.0 682 | 1307 26 4.1 683 | 993 131 3.0 684 | 520 25 4.0 685 | 506 75 3.0 686 | 84 58 4.0 687 | 1304 7 2.0 688 | 1530 39 3.0 689 | 1865 1 4.5 690 | 928 27 3.1 691 | 1106 6 3.0 692 | 1860 112 3.0 693 | 1613 1 5.0 694 | 1357 565 2.1 695 | 91 8 2.1 696 | 1782 1 4.1 697 | 1810 20 3.1 698 | 2058 7 0.6 699 | 567 3 4.0 700 | 750 43 3.0 701 | 637 26 5.0 702 | 1860 143 3.0 703 | 749 131 2.6 704 | 695 93 1.1 705 | 53 26 3.1 706 | 1915 45 4.1 707 | 1225 42 4.1 708 | 1111 1 4.5 709 | 1638 8 3.1 710 | 1339 26 4.0 711 | 1206 128 5.1 712 | 1849 75 4.1 713 | 21 25 5.0 714 | 1431 1224 4.1 715 | 1537 8 2.0 716 | 1022 1063 3.0 717 | 1311 5 2.0 718 | 502 26 3.1 719 | 73 6 3.1 720 | 1069 35 3.1 721 | 1523 3 3.6 722 | 1743 7 4.0 723 | 278 5 4.0 724 | 1656 45 2.6 725 | 587 84 2.0 726 | 1069 20 4.6 727 | 1691 58 4.1 728 | 1245 84 5.1 729 | 1431 27 4.0 730 | 993 128 4.1 731 | 568 26 5.1 732 | 971 6 3.0 733 | 370 7 3.0 734 | 250 7 3.1 735 | 1821 6 3.0 736 | 2267 45 4.1 737 | 1413 8 3.1 738 | 2276 68 5.1 739 | 2270 1 5.0 740 | 520 1 3.0 741 | 767 66 3.0 742 | 317 84 3.0 743 | 789 1 5.1 744 | 2248 69 4.1 745 | 524 25 4.6 746 | 132 6 3.0 747 | 1374 7 2.6 748 | 1400 7 3.1 749 | 591 43 4.1 750 | 60 61 3.0 751 | 2087 143 4.6 752 | 1421 24 4.1 753 | 587 39 4.1 754 | 982 13 3.1 755 | 1411 42 5.1 756 | 1983 45 4.1 757 | 1660 166 2.5 758 | 617 5 4.1 759 | 1735 5 3.0 760 | 1090 17 4.1 761 | 1259 1 4.0 762 | 1762 43 4.1 763 | 1564 7 3.1 764 | 1869 26 5.0 765 | 1691 1 4.0 766 | 1140 25 4.5 767 | 2013 23 4.1 768 | 597 1 3.0 769 | 2199 990 2.1 770 | 2267 58 4.1 771 | 592 49 1.1 772 | 2194 25 2.0 773 | 1456 58 5.0 774 | 1422 803 3.5 775 | 859 178 4.0 776 | 736 29 5.0 777 | 599 131 4.0 778 | 1631 27 4.1 779 | 1200 131 2.5 780 | 1090 128 4.0 781 | 545 7 3.1 782 | 822 1 4.6 783 | 1317 6 2.5 784 | 1794 43 4.0 785 | 1731 9 1.0 786 | 1185 26 5.0 787 | 465 22 5.0 788 | 1221 8 4.0 789 | 1783 1 4.0 790 | 433 5 4.0 791 | 465 6 3.0 792 | 1317 43 2.5 793 | 1445 188 3.0 794 | 438 84 3.0 795 | -------------------------------------------------------------------------------- /vendor/demo/real_matrix.tr.txt: -------------------------------------------------------------------------------- 1 | 61 7 4.0 2 | 1647 128 3.6 3 | 1850 5 4.6 4 | 1382 53 2.1 5 | 1124 84 5.1 6 | 1810 46 1.0 7 | 1076 1 3.0 8 | 1566 17 3.0 9 | 1374 45 3.5 10 | 1295 25 4.0 11 | 762 39 2.0 12 | 1864 7 3.1 13 | 1528 26 4.6 14 | 755 1 5.0 15 | 1970 990 3.6 16 | 2261 1 4.1 17 | 1069 46 2.1 18 | 912 7 3.1 19 | 1997 84 4.0 20 | 1416 1 3.0 21 | 1374 191 3.6 22 | 611 22 5.1 23 | 744 1 5.0 24 | 1964 1 1.0 25 | 110 1 4.0 26 | 1640 7 4.1 27 | 92 42 3.6 28 | 2267 95 3.0 29 | 1042 72 4.0 30 | 1983 84 2.1 31 | 1295 17 4.0 32 | 1530 9 3.0 33 | 2029 42 3.1 34 | 2174 58 4.1 35 | 1017 26 3.1 36 | 687 27 4.1 37 | 1689 662 4.1 38 | 942 8 1.5 39 | 126 35 5.0 40 | 1607 42 3.1 41 | 686 26 4.0 42 | 2200 2 4.0 43 | 175 12 3.6 44 | 942 7 2.6 45 | 37 7 4.0 46 | 1262 7 2.1 47 | 1860 100 4.1 48 | 1771 61 4.0 49 | 1179 7 4.1 50 | 1718 1 4.0 51 | 1958 7 5.0 52 | 1435 45 3.0 53 | 1514 45 4.6 54 | 1239 17 4.0 55 | 1771 191 1.0 56 | 518 97 2.6 57 | 1054 191 2.0 58 | 261 43 4.1 59 | 1995 26 4.1 60 | 1829 1 5.0 61 | 2141 42 1.1 62 | 2133 26 4.1 63 | 1827 39 2.1 64 | 762 53 3.1 65 | 846 1 4.1 66 | 728 5 3.5 67 | 133 7 4.1 68 | 2115 26 5.1 69 | 692 8 3.1 70 | 837 3 4.1 71 | 1523 4 3.0 72 | 642 1 5.0 73 | 977 1 1.0 74 | 1052 20 4.0 75 | 493 89 5.0 76 | 487 84 4.1 77 | 850 7 3.1 78 | 1864 131 3.0 79 | 494 3 5.0 80 | 1609 66 3.0 81 | 45 45 3.0 82 | 637 42 2.6 83 | 1523 777 2.0 84 | 1493 45 3.1 85 | 1576 43 1.5 86 | 743 127 2.5 87 | 1245 69 5.1 88 | 1948 63 3.1 89 | 1453 6 4.0 90 | 1548 45 4.0 91 | 1640 45 4.6 92 | 1827 79 4.1 93 | 1071 26 4.0 94 | 25 7 4.0 95 | 1381 7 3.0 96 | 1231 1 4.0 97 | 1160 26 4.0 98 | 26 6 4.1 99 | 1998 68 5.1 100 | 1267 7 3.0 101 | 60 110 3.0 102 | 42 5 2.6 103 | 1178 100 4.1 104 | 1052 45 3.1 105 | 2052 155 3.0 106 | 2293 20 4.1 107 | 339 7 4.1 108 | 750 7 1.1 109 | 1100 188 2.1 110 | 1978 1 0.5 111 | 302 72 2.0 112 | 586 100 0.6 113 | 201 42 3.1 114 | 1100 1 4.0 115 | 2006 22 3.1 116 | 1528 84 1.1 117 | 779 1 3.0 118 | 1258 1 4.5 119 | 1638 7 3.1 120 | 1196 181 1.1 121 | 1544 7 4.0 122 | 1462 45 4.1 123 | 1069 131 2.6 124 | 1650 45 5.0 125 | 436 7 3.1 126 | 902 35 4.0 127 | 2167 13 3.1 128 | 1301 1 4.6 129 | 952 1 5.0 130 | 310 41 3.5 131 | 801 61 4.5 132 | 478 29 3.1 133 | 1966 25 2.0 134 | 1909 43 5.0 135 | 2231 5 3.0 136 | 1523 97 2.6 137 | 2049 5 5.0 138 | 2010 131 3.5 139 | 749 1009 4.0 140 | 231 3 3.0 141 | 1647 108 2.6 142 | 2013 104 3.0 143 | 1881 35 4.0 144 | 1805 26 3.6 145 | 1991 1227 4.1 146 | 92 4 3.5 147 | 1359 26 5.1 148 | 493 22 4.0 149 | 195 95 4.5 150 | 1179 1 3.0 151 | 1084 8 3.1 152 | 1567 11 3.1 153 | 1297 42 1.1 154 | 942 42 2.1 155 | 749 27 4.1 156 | 881 23 4.0 157 | 910 162 5.1 158 | 699 8 3.0 159 | 2136 6 3.1 160 | 2275 128 4.6 161 | 1305 24 3.0 162 | 1493 26 3.0 163 | 2139 45 4.0 164 | 311 1224 1.1 165 | 269 5 4.1 166 | 296 95 4.0 167 | 361 8 4.0 168 | 1364 1 4.1 169 | 1593 128 4.5 170 | 208 35 4.0 171 | 152 69 0.6 172 | 1583 7 4.0 173 | 1723 64 5.0 174 | 1253 43 2.0 175 | 1181 82 4.0 176 | 1544 3 3.0 177 | 1143 1227 4.1 178 | 1903 1 4.1 179 | 687 39 5.1 180 | 37 6 4.0 181 | 960 1 4.1 182 | 547 17 3.1 183 | 570 5 2.1 184 | 767 20 4.1 185 | 442 26 5.1 186 | 2039 35 3.1 187 | 1850 1227 4.6 188 | 1879 25 3.1 189 | 1597 42 3.6 190 | 904 146 3.1 191 | 1430 31 2.1 192 | 1724 22 5.1 193 | 160 1 3.0 194 | 706 10 2.1 195 | 190 84 3.0 196 | 942 45 3.1 197 | 2155 128 5.0 198 | 1472 3 3.0 199 | 1430 29 3.1 200 | 1516 112 2.5 201 | 993 43 3.6 202 | 1850 178 4.1 203 | 1848 26 4.1 204 | 1046 72 4.0 205 | 1047 43 2.0 206 | 1140 166 2.6 207 | 1382 7 1.0 208 | 1752 1 4.1 209 | 2156 104 3.1 210 | 1873 63 5.0 211 | 1090 1272 3.0 212 | 1019 26 5.1 213 | 2176 41 3.1 214 | 1252 39 2.0 215 | 518 9 3.0 216 | 706 7 3.0 217 | 701 5 3.1 218 | 58 1 4.1 219 | 1284 1 3.0 220 | 1464 84 4.1 221 | 587 20 4.0 222 | 538 45 5.0 223 | 953 17 5.0 224 | 985 7 2.1 225 | 218 836 4.0 226 | 1931 76 2.1 227 | 1092 131 4.0 228 | 1530 13 3.0 229 | 611 3 4.5 230 | 1544 43 3.0 231 | 375 27 5.1 232 | 1800 45 4.0 233 | 750 8 3.0 234 | 1191 6 3.0 235 | 1570 35 4.0 236 | 1647 68 4.1 237 | 1217 43 4.0 238 | 2152 58 4.0 239 | 1561 1 2.1 240 | 1405 1 4.6 241 | 1252 8 3.0 242 | 2142 39 4.0 243 | 965 1 4.1 244 | 1595 5 5.1 245 | 1059 7 1.1 246 | 143 84 3.6 247 | 469 45 3.1 248 | 44 1 4.1 249 | 1855 26 4.0 250 | 749 8 3.1 251 | 697 1 2.0 252 | 1804 25 4.1 253 | 1357 139 2.5 254 | 1459 26 4.0 255 | 298 133 3.0 256 | 1152 1 4.0 257 | 1010 7 3.0 258 | 1556 6 4.1 259 | 942 145 3.0 260 | 1010 6 3.0 261 | 593 45 4.0 262 | 2120 6 3.1 263 | 1981 7 4.0 264 | 904 23 3.0 265 | 2209 128 1.0 266 | 661 26 5.1 267 | 1236 8 3.1 268 | 1748 1 3.0 269 | 2038 20 3.0 270 | 468 132 4.1 271 | 1082 803 3.5 272 | 32 43 3.1 273 | 2188 7 3.1 274 | 2133 8 4.0 275 | 2167 9 5.0 276 | 2062 84 3.1 277 | 2146 33 4.0 278 | 509 7 2.0 279 | 1523 1233 2.0 280 | 1467 43 5.1 281 | 1841 100 3.1 282 | 190 7 2.1 283 | 16 113 4.0 284 | 1386 190 5.0 285 | 2273 49 5.1 286 | 617 43 1.1 287 | 2117 25 5.1 288 | 192 5 5.1 289 | 1573 128 4.5 290 | 2200 1 5.0 291 | 766 68 3.1 292 | 979 7 3.0 293 | 1597 8 3.0 294 | 223 1 5.0 295 | 490 1 5.1 296 | 2179 1 4.5 297 | 2168 7 4.0 298 | 1017 178 3.5 299 | 962 74 4.0 300 | 16 8 4.1 301 | 632 23 4.1 302 | 10 11 3.1 303 | 984 51 4.1 304 | 60 131 2.1 305 | 1347 117 3.1 306 | 1371 131 3.6 307 | 2244 43 5.1 308 | 393 1 5.0 309 | 2009 100 4.1 310 | 263 72 4.0 311 | 624 7 3.1 312 | 1641 7 3.1 313 | 1430 27 5.1 314 | 650 128 5.0 315 | 527 20 4.1 316 | 311 1 4.1 317 | 2114 7 1.5 318 | 1371 909 1.5 319 | 1891 41 5.0 320 | 459 143 5.0 321 | 1741 5 3.0 322 | 2159 7 2.5 323 | 2005 990 3.1 324 | 2010 84 4.6 325 | 2139 9 4.0 326 | 1860 24 1.0 327 | 1588 990 4.1 328 | 2143 84 2.0 329 | 1737 43 4.0 330 | 1093 44 5.1 331 | 1607 69 2.6 332 | 2176 49 4.0 333 | 646 128 5.0 334 | 845 45 4.0 335 | 1178 84 4.0 336 | 1915 35 3.0 337 | 493 95 5.1 338 | 1774 845 1.1 339 | 1232 47 3.0 340 | 1028 1 3.1 341 | 268 128 4.5 342 | 1359 68 4.1 343 | 319 1063 3.6 344 | 1609 20 3.1 345 | 119 66 3.1 346 | 2258 2 4.0 347 | 723 43 3.5 348 | 992 7 3.0 349 | 801 20 5.0 350 | 240 1 4.0 351 | 194 45 4.1 352 | 424 7 5.0 353 | 2220 84 5.1 354 | 1101 1 4.6 355 | 940 2 3.1 356 | 587 11 3.1 357 | 278 26 4.0 358 | 2015 128 5.1 359 | 806 1 2.1 360 | 264 26 5.1 361 | 1198 1 5.1 362 | 52 909 4.1 363 | 1069 777 1.5 364 | 1319 131 3.6 365 | 27 15 4.1 366 | 1380 3 3.5 367 | 289 7 4.1 368 | 2200 22 2.0 369 | 412 84 4.1 370 | 2015 41 3.6 371 | 2173 116 1.0 372 | 1371 8 3.6 373 | 323 168 3.6 374 | 9 80 3.6 375 | 1430 5 4.0 376 | 1185 35 5.1 377 | 470 1 3.0 378 | 520 9 3.0 379 | 1497 836 3.1 380 | 1357 43 2.5 381 | 818 84 5.0 382 | 41 42 4.0 383 | 2003 95 3.0 384 | 2113 23 5.1 385 | 899 75 3.0 386 | 43 45 3.1 387 | 2301 100 2.1 388 | 982 4 2.0 389 | 801 35 3.0 390 | 264 1 4.1 391 | 1823 46 2.0 392 | 547 4 3.1 393 | 1989 131 5.1 394 | 1066 8 5.1 395 | 60 4 3.0 396 | 241 8 2.0 397 | 180 26 3.5 398 | 542 23 3.1 399 | 1991 128 5.1 400 | 1688 84 4.1 401 | 1724 25 5.0 402 | 1675 75 1.1 403 | 217 131 3.5 404 | 296 45 3.5 405 | 42 26 4.1 406 | 1573 45 2.0 407 | 542 20 5.1 408 | 1228 84 4.1 409 | 1739 1 5.0 410 | 1431 188 4.1 411 | 228 6 1.0 412 | 1307 68 4.0 413 | 1956 35 2.5 414 | 519 6 3.1 415 | 2035 1 2.1 416 | 367 26 5.0 417 | 493 18 4.0 418 | 1353 1 3.0 419 | 1491 27 2.1 420 | 461 181 3.0 421 | 92 3 2.6 422 | 2299 3 3.1 423 | 1226 6 5.0 424 | 1135 2 4.1 425 | 1841 45 3.0 426 | 554 9 3.0 427 | 971 5 4.0 428 | 2210 6 3.1 429 | 1069 17 4.0 430 | 1499 68 4.5 431 | 1416 11 5.1 432 | 118 26 4.0 433 | 908 84 4.0 434 | 1252 21 3.1 435 | 2124 35 4.1 436 | 1860 1009 4.1 437 | 425 26 3.0 438 | 1795 6 3.1 439 | 468 43 5.1 440 | 2300 20 4.6 441 | 122 3 4.1 442 | 414 45 4.0 443 | 1980 20 3.0 444 | 1566 1 3.0 445 | 1178 139 4.0 446 | 1860 25 4.5 447 | 2142 30 2.1 448 | 1236 13 3.6 449 | 190 26 4.1 450 | 612 1 4.0 451 | 1027 6 3.1 452 | 2244 42 3.0 453 | 1599 3 4.1 454 | 1284 43 3.1 455 | 1792 25 4.1 456 | 58 1227 4.6 457 | 1386 26 4.6 458 | 1186 26 5.0 459 | 658 40 4.5 460 | 2133 45 4.1 461 | 461 55 5.0 462 | 543 84 3.0 463 | 695 37 1.1 464 | 1846 43 4.0 465 | 106 1 4.1 466 | 2142 35 4.0 467 | 922 7 3.0 468 | 857 5 3.1 469 | 1709 7 3.0 470 | 48 128 5.0 471 | 1191 7 3.0 472 | 2164 17 2.6 473 | 520 43 3.0 474 | 1068 27 5.1 475 | 1422 58 3.6 476 | 57 1227 4.6 477 | 455 76 1.5 478 | 1114 20 4.1 479 | 1893 6 5.0 480 | 1754 100 5.0 481 | 819 1 4.0 482 | 312 5 4.1 483 | 1934 49 3.6 484 | 1020 128 4.0 485 | 570 46 2.0 486 | 1431 3 3.1 487 | 1912 84 3.6 488 | 695 53 5.0 489 | 1178 93 5.0 490 | 767 41 4.0 491 | 1853 27 5.1 492 | 2062 69 1.1 493 | 10 31 3.0 494 | 2072 1 5.0 495 | 14 25 4.0 496 | 2070 128 5.1 497 | 1027 131 2.0 498 | 802 3 3.0 499 | 2233 27 4.0 500 | 750 75 3.0 501 | 560 1227 4.5 502 | 503 803 3.1 503 | 1140 45 4.0 504 | 1098 803 3.0 505 | 2113 45 4.1 506 | 493 45 3.0 507 | 1715 128 4.1 508 | 157 80 3.0 509 | 1422 128 4.5 510 | 611 83 3.0 511 | 658 178 2.6 512 | 1864 45 4.0 513 | 935 8 3.1 514 | 157 23 4.6 515 | 1430 7 1.0 516 | 1581 5 3.0 517 | 1662 45 3.5 518 | 587 73 3.1 519 | 1052 7 4.0 520 | 194 131 2.1 521 | 106 6 5.1 522 | 130 35 4.0 523 | 938 1 3.5 524 | 1922 1 4.0 525 | 1359 11 4.0 526 | 727 7 5.1 527 | 1392 20 4.0 528 | 2014 1 3.0 529 | 612 25 5.1 530 | 904 89 4.0 531 | 75 45 3.1 532 | 1064 6 5.1 533 | 1864 61 2.0 534 | 2080 3 2.6 535 | 829 27 4.0 536 | 73 7 4.0 537 | 1990 45 3.0 538 | 1080 6 4.0 539 | 1640 714 4.6 540 | 2061 84 3.5 541 | 1445 25 3.0 542 | 61 39 4.1 543 | 945 178 3.6 544 | 1377 75 3.0 545 | 1898 1 4.0 546 | 771 131 3.0 547 | 221 17 5.1 548 | 137 1 3.0 549 | 1048 7 4.0 550 | 514 1 5.1 551 | 238 3 4.1 552 | 635 23 4.0 553 | 565 6 2.0 554 | 261 1 4.1 555 | 231 42 5.1 556 | 1742 7 3.1 557 | 152 84 3.1 558 | 1970 170 1.6 559 | 1273 1 4.0 560 | 743 3 4.5 561 | 993 26 4.5 562 | 1960 35 4.0 563 | 127 43 3.1 564 | 1431 162 5.0 565 | 91 11 3.0 566 | 2233 5 3.1 567 | 1498 84 3.1 568 | 820 17 4.1 569 | 1567 3 3.0 570 | 958 41 5.0 571 | 1645 44 4.6 572 | 1864 1105 3.5 573 | 592 136 1.1 574 | 930 155 5.1 575 | 1239 35 3.1 576 | 37 10 1.1 577 | 2301 7 3.0 578 | 617 27 5.1 579 | 1956 128 3.0 580 | 1560 5 3.1 581 | 702 26 5.0 582 | 973 7 4.1 583 | 637 35 3.0 584 | 671 3 3.0 585 | 146 84 3.5 586 | 2028 131 2.6 587 | 1566 23 2.1 588 | 560 990 2.5 589 | 1162 3 5.1 590 | 822 131 3.6 591 | 750 1 4.1 592 | 1231 1063 5.0 593 | 2241 79 3.0 594 | 1140 1 4.1 595 | 1241 26 4.1 596 | 180 27 4.1 597 | 150 45 3.6 598 | 1544 68 4.0 599 | 1225 22 4.0 600 | 404 68 4.5 601 | 2282 17 3.5 602 | 687 45 2.0 603 | 1995 128 3.6 604 | 1674 26 5.0 605 | 169 5 3.6 606 | 1567 8 3.1 607 | 493 42 3.0 608 | 815 96 5.1 609 | 1099 8 3.1 610 | 1623 1 4.6 611 | 1931 17 4.1 612 | 1586 1272 3.5 613 | 82 35 4.0 614 | 2267 181 5.0 615 | 502 44 5.0 616 | 1578 69 3.0 617 | 166 8 3.0 618 | 2080 45 4.1 619 | 1252 34 3.1 620 | 1335 72 5.1 621 | 2082 7 3.0 622 | 465 51 2.1 623 | 1719 45 5.1 624 | 1631 23 5.0 625 | 661 1 5.1 626 | 1348 68 5.1 627 | 1118 4 4.1 628 | 570 17 2.0 629 | 92 35 3.5 630 | 1706 1 5.0 631 | 2163 23 4.1 632 | 953 7 4.1 633 | 570 131 3.1 634 | 586 35 2.6 635 | 1551 7 3.0 636 | 696 49 5.1 637 | 1827 3 4.0 638 | 1090 35 3.1 639 | 280 45 4.1 640 | 1231 128 5.0 641 | 535 1 5.0 642 | 540 6 1.0 643 | 42 131 3.0 644 | 468 69 2.5 645 | 1860 129 3.0 646 | 1740 3 3.0 647 | 832 27 2.0 648 | 1400 1 4.0 649 | 1015 24 2.0 650 | 2060 25 5.1 651 | 1407 1 3.0 652 | 1515 1272 3.5 653 | 1040 5 2.5 654 | 822 95 4.5 655 | 1346 1227 4.1 656 | 1357 6 2.5 657 | 1205 30 3.1 658 | 1613 6 5.1 659 | 1304 58 4.0 660 | 1149 35 2.5 661 | 406 27 5.1 662 | 1691 84 3.0 663 | 1374 26 3.0 664 | 1983 43 3.6 665 | 493 46 2.0 666 | 2287 95 4.0 667 | 493 84 3.1 668 | 1253 1 4.6 669 | 547 84 4.0 670 | 60 20 3.0 671 | 1959 6 3.0 672 | 1162 7 5.1 673 | 904 131 2.1 674 | 968 45 3.6 675 | 355 84 1.0 676 | 231 43 4.1 677 | 590 84 4.1 678 | 1566 26 5.0 679 | 468 74 3.0 680 | 296 128 4.6 681 | 1912 27 4.0 682 | 838 20 5.0 683 | 1379 2 4.1 684 | 195 990 4.6 685 | 1320 23 1.1 686 | 92 8 2.5 687 | 570 84 2.0 688 | 838 11 3.0 689 | 247 3 5.1 690 | 1591 7 4.1 691 | 1860 147 2.5 692 | 1161 45 3.5 693 | 1489 8 3.1 694 | 543 85 2.1 695 | 1734 26 4.1 696 | 904 22 3.0 697 | 538 116 0.5 698 | 1931 11 4.0 699 | 553 42 1.0 700 | 687 34 3.1 701 | 1674 80 2.1 702 | 1324 1063 3.6 703 | 231 17 5.1 704 | 900 1 3.5 705 | 1688 45 4.1 706 | 2052 31 3.1 707 | 83 43 4.0 708 | 274 1 4.0 709 | 43 84 4.1 710 | 1430 75 4.0 711 | 1956 95 4.1 712 | 1284 58 5.0 713 | 1586 128 4.6 714 | 1719 27 5.1 715 | 279 1 5.1 716 | 150 1 4.1 717 | 1311 44 4.0 718 | 788 35 4.0 719 | 1407 3 4.0 720 | 1991 1148 4.1 721 | 1357 803 4.1 722 | 1671 128 1.1 723 | 1548 21 3.0 724 | 1633 1 5.0 725 | 455 43 3.6 726 | 361 7 3.0 727 | 2161 7 4.0 728 | 2285 84 1.6 729 | 2267 562 2.5 730 | 513 178 3.6 731 | 637 836 4.0 732 | 468 100 3.0 733 | 1022 836 3.5 734 | 982 1 5.0 735 | 2259 6 4.0 736 | 769 43 2.0 737 | 1649 1105 3.0 738 | 1573 1 5.0 739 | 1662 26 4.1 740 | 934 1 5.1 741 | 863 17 4.1 742 | 2213 84 4.6 743 | 92 117 4.1 744 | 803 128 4.6 745 | 1548 178 3.0 746 | 1371 1 4.5 747 | 1538 27 4.0 748 | 404 166 4.6 749 | 620 1 3.0 750 | 1597 3 4.1 751 | 928 41 4.0 752 | 1225 26 2.0 753 | 2288 4 4.1 754 | 1544 39 3.1 755 | 132 116 1.5 756 | 925 1 5.1 757 | 1827 84 4.0 758 | 570 7 3.1 759 | 2003 27 3.0 760 | 906 30 4.0 761 | 2174 41 5.0 762 | 1237 45 5.1 763 | 2068 26 3.6 764 | 1868 86 5.0 765 | 2042 149 4.6 766 | 661 45 4.5 767 | 1617 6 3.1 768 | 1347 72 2.6 769 | 1252 43 5.0 770 | 958 43 3.0 771 | 1426 5 3.1 772 | 2052 26 4.0 773 | 1724 45 2.1 774 | 942 146 3.1 775 | 1066 3 5.0 776 | 1042 45 4.1 777 | 733 191 2.5 778 | 1312 129 4.1 779 | 728 147 3.6 780 | 2189 3 3.0 781 | 1712 3 3.1 782 | 680 7 3.1 783 | 1523 75 2.6 784 | 1516 26 4.1 785 | 1300 131 2.0 786 | 2013 49 5.1 787 | 1339 45 4.0 788 | 1017 7 3.1 789 | 1534 35 2.6 790 | 570 49 3.0 791 | 1531 6 4.0 792 | 2102 11 4.0 793 | 674 6 5.0 794 | 2227 1 5.1 795 | 1232 49 2.1 796 | 330 10 3.1 797 | 871 43 4.0 798 | 1864 23 3.0 799 | 1359 23 3.0 800 | 1824 75 3.1 801 | 830 49 4.1 802 | 2156 45 5.1 803 | 961 74 2.0 804 | 2005 27 4.1 805 | 686 46 1.1 806 | 1319 35 3.0 807 | 1603 6 5.0 808 | 2126 10 1.0 809 | 2142 42 4.0 810 | 1069 143 5.0 811 | 1556 1 5.0 812 | 2248 35 4.0 813 | 1523 13 2.1 814 | 1961 7 3.0 815 | 719 7 5.1 816 | 1375 128 0.6 817 | 428 1 5.0 818 | 196 1 2.1 819 | 1682 1 3.6 820 | 1256 7 5.1 821 | 2173 46 1.0 822 | 340 8 4.0 823 | 1865 29 3.5 824 | 296 23 2.1 825 | 1567 42 2.0 826 | 2173 24 2.5 827 | 1026 39 3.0 828 | 1143 1258 4.5 829 | 1829 1272 3.6 830 | 964 139 3.1 831 | 210 1 3.1 832 | 1317 894 3.6 833 | 1481 84 2.0 834 | 49 43 3.0 835 | 96 8 3.0 836 | 762 9 4.1 837 | 893 45 3.6 838 | 60 1272 4.0 839 | 1809 35 3.1 840 | 1025 5 3.1 841 | 468 31 4.0 842 | 1544 22 4.0 843 | 1556 7 3.0 844 | 1245 845 4.5 845 | 1689 3 3.1 846 | 1440 3 3.0 847 | 1585 5 5.1 848 | 179 3 3.1 849 | 499 20 5.1 850 | 381 7 3.0 851 | 661 20 4.5 852 | 1608 43 1.5 853 | 362 5 5.1 854 | 440 43 3.0 855 | 722 26 4.0 856 | 1626 27 5.1 857 | 1931 61 3.0 858 | 2028 1 5.0 859 | 1357 23 3.0 860 | 2080 26 4.5 861 | 218 1 3.6 862 | 455 131 3.5 863 | 1150 27 4.1 864 | 91 34 4.0 865 | 1543 116 2.1 866 | 1758 7 4.1 867 | 406 23 5.1 868 | 1279 43 3.1 869 | 899 11 2.1 870 | 1670 7 1.0 871 | 1460 5 4.1 872 | 989 1258 4.5 873 | 982 5 4.0 874 | 75 845 2.5 875 | 295 35 2.0 876 | 1071 35 3.0 877 | 2173 69 3.0 878 | 1318 63 4.0 879 | 1284 6 0.6 880 | 1307 27 4.1 881 | 1046 68 5.1 882 | 1022 1148 2.5 883 | 587 8 4.1 884 | 1455 45 4.0 885 | 1245 45 5.1 886 | 750 27 4.0 887 | 1239 43 4.1 888 | 150 990 2.5 889 | 1647 166 3.5 890 | 1864 146 4.0 891 | 2215 7 3.1 892 | 1856 58 4.0 893 | 1790 7 3.1 894 | 1671 1063 4.1 895 | 1316 8 3.1 896 | 1913 26 4.0 897 | 1576 80 1.5 898 | 1206 1 4.0 899 | 1042 20 5.1 900 | 1170 8 3.1 901 | 610 35 4.0 902 | 1662 84 2.5 903 | 823 7 3.1 904 | 397 45 4.1 905 | 276 7 3.0 906 | 967 6 5.1 907 | 1568 5 4.1 908 | 1397 43 2.6 909 | 1298 17 3.0 910 | 1696 45 3.1 911 | 2210 3 1.1 912 | 1758 26 3.1 913 | 1821 1 3.0 914 | 2179 5 4.1 915 | 1069 25 4.1 916 | 779 7 3.0 917 | 2168 35 2.1 918 | 1607 45 3.5 919 | 123 35 3.0 920 | 1850 2 3.1 921 | 359 6 4.1 922 | 1035 7 2.1 923 | 900 26 4.1 924 | 820 1 4.0 925 | 1421 27 5.0 926 | 643 6 3.6 927 | 2282 178 3.5 928 | 570 43 2.0 929 | 208 45 4.1 930 | 1876 181 3.6 931 | 2008 1 5.1 932 | 1618 74 4.1 933 | 1090 1 4.1 934 | 1698 7 5.1 935 | 1273 3 4.6 936 | 958 30 2.1 937 | 750 74 3.1 938 | 1608 7 4.6 939 | 1552 31 3.0 940 | 801 27 4.1 941 | 1286 63 3.0 942 | 1638 6 3.1 943 | 1717 8 3.1 944 | 550 17 3.0 945 | 296 84 1.0 946 | 1697 191 3.6 947 | 1020 45 3.6 948 | 1441 31 5.0 949 | 742 43 2.1 950 | 859 1 4.6 951 | 1523 5 2.0 952 | 1338 116 1.0 953 | 1027 8 3.0 954 | 2101 6 4.1 955 | 75 116 2.0 956 | 15 128 4.6 957 | 1527 5 4.0 958 | 613 6 4.0 959 | 2167 8 4.0 960 | 260 37 1.0 961 | 892 7 3.1 962 | 1585 7 3.1 963 | 1031 1 3.6 964 | 912 5 4.0 965 | 2030 3 3.0 966 | 1648 23 4.0 967 | 84 1 4.0 968 | 868 1 3.0 969 | 335 3 3.5 970 | 125 1 4.0 971 | 495 27 3.1 972 | 749 3 2.5 973 | 1573 26 4.1 974 | 1991 143 4.0 975 | 801 7 4.0 976 | 2142 24 2.1 977 | 489 6 3.0 978 | 1026 84 5.0 979 | 1310 26 5.1 980 | 634 990 0.5 981 | 1565 1 5.1 982 | 637 7 3.5 983 | 388 1 4.5 984 | 1752 7 4.1 985 | 91 3 1.1 986 | 2013 15 1.0 987 | 1634 8 4.1 988 | 562 7 2.0 989 | 1020 1 4.6 990 | 12 1 4.1 991 | 1205 3 3.1 992 | 233 5 5.1 993 | 2232 35 3.0 994 | 1621 68 4.0 995 | 2004 35 4.1 996 | 62 80 3.1 997 | 2265 6 1.6 998 | 1273 26 4.0 999 | 2267 44 3.6 1000 | 18 11 3.0 1001 | 1551 8 3.1 1002 | 1983 13 2.1 1003 | 1649 1 4.0 1004 | 621 1 4.0 1005 | 60 84 3.1 1006 | 1859 990 4.0 1007 | 464 41 5.0 1008 | 937 7 3.1 1009 | 2244 46 2.1 1010 | 319 134 1.6 1011 | 2161 17 4.0 1012 | 1474 45 3.1 1013 | 2062 26 5.0 1014 | 1528 128 4.5 1015 | 871 5 5.0 1016 | 1431 175 4.1 1017 | 2195 3 3.1 1018 | 1249 1 5.1 1019 | 1608 23 4.0 1020 | 1909 7 4.0 1021 | 748 26 2.5 1022 | 1116 66 4.1 1023 | 208 1 4.1 1024 | 85 8 3.1 1025 | 788 1 5.1 1026 | 1864 128 3.1 1027 | 1647 134 2.0 1028 | 1056 45 3.6 1029 | 1181 1148 3.5 1030 | 2142 86 4.1 1031 | 2143 1 5.0 1032 | 532 13 3.1 1033 | 247 17 3.0 1034 | 60 714 3.6 1035 | 157 39 3.6 1036 | 998 139 5.1 1037 | 634 1224 2.6 1038 | 1956 20 3.0 1039 | 1784 1 4.1 1040 | 2188 8 3.0 1041 | 1851 1 4.6 1042 | 2209 84 2.0 1043 | 645 3 4.1 1044 | 538 128 5.1 1045 | 1970 26 5.1 1046 | 80 17 4.5 1047 | 1237 39 2.6 1048 | 1864 6 2.6 1049 | 694 1 3.1 1050 | 1624 75 3.1 1051 | 1992 5 1.1 1052 | 650 990 3.0 1053 | 542 11 4.0 1054 | 850 45 3.1 1055 | 555 26 4.0 1056 | 908 128 4.0 1057 | 912 13 3.0 1058 | 1693 3 3.0 1059 | 1559 27 1.5 1060 | 740 7 5.0 1061 | 2279 6 5.0 1062 | 1106 5 2.0 1063 | 722 131 2.5 1064 | 638 45 5.1 1065 | 1567 39 3.1 1066 | 1860 84 2.1 1067 | 1567 5 5.1 1068 | 696 5 5.0 1069 | 121 7 3.0 1070 | 1640 1105 3.5 1071 | 817 1 5.0 1072 | 495 8 3.1 1073 | 1846 35 5.1 1074 | 527 45 4.1 1075 | 1728 7 3.0 1076 | 165 5 3.0 1077 | 2052 178 3.5 1078 | 634 1105 2.5 1079 | 1567 80 4.0 1080 | 1563 55 3.0 1081 | 611 1063 5.0 1082 | 76 26 4.6 1083 | 2303 8 3.1 1084 | 1718 7 3.1 1085 | 70 26 5.0 1086 | 168 2 3.1 1087 | 1931 26 3.1 1088 | 406 7 3.1 1089 | 1474 139 3.5 1090 | 1654 25 5.1 1091 | 960 45 2.6 1092 | 518 26 3.0 1093 | 96 6 3.0 1094 | 411 84 4.6 1095 | 1336 3 3.0 1096 | 2288 3 4.1 1097 | 1627 80 4.1 1098 | 1502 3 4.1 1099 | 2104 1 4.5 1100 | 1334 3 1.1 1101 | 1608 31 4.1 1102 | 912 11 3.1 1103 | 2233 3 3.1 1104 | 904 84 3.0 1105 | 2235 80 5.1 1106 | 1040 45 3.0 1107 | 1656 128 3.6 1108 | 700 1 4.5 1109 | 2171 45 4.5 1110 | 1947 25 5.1 1111 | 2142 45 5.1 1112 | 2091 43 2.0 1113 | 1734 72 3.0 1114 | 173 95 4.0 1115 | 380 166 3.5 1116 | 891 27 4.1 1117 | 1860 11 3.5 1118 | 75 95 2.6 1119 | 2052 25 3.6 1120 | 118 25 5.0 1121 | 422 1 4.1 1122 | 1114 41 5.1 1123 | 1379 14 3.0 1124 | 1238 43 5.1 1125 | 127 26 2.1 1126 | 904 155 4.1 1127 | 417 185 4.0 1128 | 279 7 5.1 1129 | 1879 21 5.0 1130 | 1328 5 3.1 1131 | 1527 95 4.0 1132 | 1957 45 1.1 1133 | 559 1 5.0 1134 | 1069 5 4.1 1135 | 666 1 4.1 1136 | 759 35 4.1 1137 | 329 7 4.0 1138 | 2107 45 3.5 1139 | 302 26 3.1 1140 | 1386 1 4.0 1141 | 340 5 4.1 1142 | 424 11 5.0 1143 | 617 26 3.0 1144 | 1592 128 3.5 1145 | 379 6 3.1 1146 | 2301 45 4.0 1147 | 1243 63 4.1 1148 | 2230 41 5.1 1149 | 585 1 4.1 1150 | 1829 43 4.1 1151 | 2087 1 3.0 1152 | 500 1 5.0 1153 | 1860 131 3.5 1154 | 1647 3 3.6 1155 | 1856 128 5.1 1156 | 749 191 2.1 1157 | 570 79 2.1 1158 | 2133 35 2.1 1159 | 242 3 3.1 1160 | 1160 74 2.0 1161 | 830 45 3.6 1162 | 2068 1 4.1 1163 | 1115 836 3.6 1164 | 2053 178 3.1 1165 | 513 45 4.5 1166 | 2052 39 3.1 1167 | 1983 116 2.1 1168 | 2035 6 4.1 1169 | 1406 20 3.5 1170 | 1572 1 3.0 1171 | 175 5 4.0 1172 | 323 60 4.0 1173 | 1683 87 3.0 1174 | 1425 1 1.0 1175 | 805 5 3.1 1176 | 263 45 3.1 1177 | 303 25 4.5 1178 | 2107 155 4.0 1179 | 1722 803 4.1 1180 | 570 125 3.6 1181 | 1863 173 5.1 1182 | 1333 26 5.0 1183 | 904 74 3.1 1184 | 601 26 4.1 1185 | 1566 5 3.1 1186 | 1763 7 4.1 1187 | 517 45 3.0 1188 | 1810 65 3.1 1189 | 93 26 5.0 1190 | 2043 23 4.1 1191 | 1226 3 4.0 1192 | 4 43 3.1 1193 | 1440 6 4.1 1194 | 953 23 3.0 1195 | 75 63 3.1 1196 | 834 49 4.1 1197 | 90 59 3.1 1198 | 1963 1 5.0 1199 | 1335 139 4.0 1200 | 2008 10 3.0 1201 | 1683 95 4.1 1202 | 1680 1 5.0 1203 | 1114 83 3.0 1204 | 2103 7 3.1 1205 | 1524 4 4.0 1206 | 1528 1 4.5 1207 | 19 7 3.1 1208 | 1567 19 4.0 1209 | 1231 104 4.0 1210 | 2040 93 1.1 1211 | 2192 49 5.1 1212 | 2173 1176 3.1 1213 | 676 7 3.1 1214 | 1357 25 3.5 1215 | 1759 5 3.0 1216 | 1560 7 3.0 1217 | 1972 5 4.0 1218 | 1042 26 4.1 1219 | 1855 41 5.1 1220 | 1485 44 3.0 1221 | 2167 1 5.1 1222 | 1797 1 5.1 1223 | 357 45 4.1 1224 | 1312 178 3.5 1225 | 1357 7 2.0 1226 | 91 31 4.1 1227 | 1052 129 4.6 1228 | 190 155 0.5 1229 | 1860 104 3.1 1230 | 1265 116 4.0 1231 | 531 6 3.1 1232 | 1405 181 4.6 1233 | 1225 80 4.0 1234 | 1273 128 4.6 1235 | 1264 64 4.1 1236 | 602 30 4.0 1237 | 1660 5 4.0 1238 | 1863 1148 4.6 1239 | 984 122 1.1 1240 | 52 1 4.0 1241 | 1890 139 3.5 1242 | 433 7 4.0 1243 | 1275 1 5.0 1244 | 2068 45 3.1 1245 | 2199 845 3.0 1246 | 1597 17 3.0 1247 | 122 17 3.1 1248 | 1173 26 3.5 1249 | 596 49 4.1 1250 | 908 35 3.1 1251 | 118 43 5.0 1252 | 1284 24 3.0 1253 | 908 58 4.6 1254 | 115 7 4.0 1255 | 2129 43 4.0 1256 | 611 62 3.1 1257 | 1997 178 3.0 1258 | 222 25 3.1 1259 | 130 1 3.6 1260 | 520 20 5.1 1261 | 854 45 2.0 1262 | 2106 84 3.0 1263 | 1317 803 5.0 1264 | 1567 35 3.0 1265 | 1114 84 4.0 1266 | 1043 7 3.1 1267 | 484 6 3.5 1268 | 1809 26 5.1 1269 | 1521 178 4.5 1270 | 1236 87 3.0 1271 | 1374 20 4.5 1272 | 10 45 4.0 1273 | 949 1 5.1 1274 | 706 24 2.1 1275 | 2178 84 3.0 1276 | 1638 1 3.0 1277 | 1463 26 5.0 1278 | 1236 94 3.1 1279 | 169 45 2.1 1280 | 1523 57 2.0 1281 | 2080 131 2.0 1282 | 1508 45 4.5 1283 | 1266 6 3.1 1284 | 1104 45 3.0 1285 | 1470 7 4.0 1286 | 1117 80 5.0 1287 | 2080 6 3.6 1288 | 468 45 4.0 1289 | 774 11 3.0 1290 | 363 58 5.1 1291 | 1809 27 2.0 1292 | 1766 8 3.0 1293 | 60 104 3.1 1294 | 1771 1 4.0 1295 | 1858 3 5.1 1296 | 38 120 4.0 1297 | 42 1227 2.6 1298 | 221 6 3.0 1299 | 1346 35 4.0 1300 | 1722 836 3.5 1301 | 1195 7 3.1 1302 | 1860 95 4.0 1303 | 33 26 4.6 1304 | 617 24 1.0 1305 | 440 35 2.1 1306 | 1623 128 4.6 1307 | 1760 7 4.1 1308 | 157 43 3.0 1309 | 75 6 3.6 1310 | 749 45 2.5 1311 | 141 25 5.1 1312 | 436 1 4.0 1313 | 969 4 4.1 1314 | 942 803 3.5 1315 | 2084 84 3.0 1316 | 1802 6 5.0 1317 | 691 27 4.0 1318 | 1548 104 4.5 1319 | 1942 26 4.5 1320 | 2067 26 3.1 1321 | 1569 20 4.6 1322 | 1892 66 5.1 1323 | 1248 8 3.0 1324 | 1116 45 3.1 1325 | 1304 45 4.0 1326 | 830 95 3.5 1327 | 1770 66 4.1 1328 | 1196 5 4.5 1329 | 2168 44 4.1 1330 | 648 3 4.1 1331 | 1754 84 5.0 1332 | 1502 27 4.1 1333 | 1612 1105 4.6 1334 | 479 1 5.1 1335 | 388 836 4.1 1336 | 2056 6 3.1 1337 | 240 25 4.5 1338 | 1864 39 3.0 1339 | 2008 4 4.1 1340 | 1826 4 3.0 1341 | 1538 3 4.0 1342 | 2052 63 3.0 1343 | 823 8 4.1 1344 | 2126 34 4.6 1345 | 1491 43 3.1 1346 | 339 66 4.0 1347 | 1572 26 4.0 1348 | 945 84 3.1 1349 | 714 128 4.1 1350 | 1047 35 4.1 1351 | 506 45 3.6 1352 | 596 117 4.0 1353 | 971 63 2.1 1354 | 1307 66 3.0 1355 | 1571 45 4.1 1356 | 1289 41 4.0 1357 | 1042 73 4.0 1358 | 969 5 5.1 1359 | 2099 1 3.1 1360 | 1052 181 4.0 1361 | 319 1148 3.1 1362 | 506 5 4.1 1363 | 152 116 0.5 1364 | 871 75 2.0 1365 | 1386 128 5.1 1366 | 278 41 4.1 1367 | 1253 128 4.5 1368 | 1404 2 4.0 1369 | 1143 1176 3.6 1370 | 277 6 3.1 1371 | 2080 84 4.0 1372 | 945 69 1.0 1373 | 1327 4 3.0 1374 | 1168 45 4.1 1375 | 1515 3 3.0 1376 | 2058 6 4.1 1377 | 1892 68 5.1 1378 | 806 5 2.1 1379 | 1991 1272 4.0 1380 | 750 51 3.1 1381 | 2030 26 5.1 1382 | 718 1 4.0 1383 | 1970 909 3.5 1384 | 933 1 3.1 1385 | 1690 6 4.1 1386 | 1450 84 4.1 1387 | 943 26 2.0 1388 | 1008 7 3.0 1389 | 1939 5 3.0 1390 | 489 1 4.0 1391 | 1778 777 4.1 1392 | 254 27 5.0 1393 | 10 8 4.0 1394 | 256 42 3.0 1395 | 935 35 2.0 1396 | 2132 3 3.0 1397 | 2178 26 4.0 1398 | 2244 45 5.1 1399 | 950 7 3.0 1400 | 981 7 4.0 1401 | 75 68 5.1 1402 | 1647 191 1.6 1403 | 1923 80 4.1 1404 | 2308 1 3.1 1405 | 517 75 1.0 1406 | 1419 1 5.0 1407 | 2173 35 3.6 1408 | 518 45 2.5 1409 | 335 27 4.0 1410 | 904 42 2.0 1411 | 1166 7 2.5 1412 | 1338 84 2.6 1413 | 1708 6 5.1 1414 | 2258 30 2.0 1415 | 518 8 2.1 1416 | 90 82 4.0 1417 | 264 2 3.0 1418 | 899 565 3.6 1419 | 781 84 1.6 1420 | 1548 2 4.5 1421 | 753 1 5.1 1422 | 1070 31 3.5 1423 | 1294 26 5.1 1424 | 187 6 4.1 1425 | 1095 3 3.1 1426 | 1160 5 3.1 1427 | 69 1 3.0 1428 | 465 24 1.1 1429 | 1243 84 4.1 1430 | 1979 7 4.0 1431 | 1912 35 4.0 1432 | 2275 35 4.0 1433 | 2258 29 3.0 1434 | 1800 26 3.5 1435 | 891 6 3.1 1436 | 1775 1 3.0 1437 | 1264 836 5.0 1438 | 1791 26 5.0 1439 | 2010 1094 4.1 1440 | 2108 45 4.0 1441 | 1087 178 3.0 1442 | 1178 136 3.1 1443 | 285 6 3.0 1444 | 592 127 4.0 1445 | 1374 128 3.1 1446 | 1280 7 3.0 1447 | 1867 7 4.0 1448 | 1279 35 3.1 1449 | 2142 51 4.0 1450 | 682 7 5.0 1451 | 388 84 4.1 1452 | 1193 31 3.1 1453 | 2102 3 4.1 1454 | 854 35 1.5 1455 | 2080 894 3.5 1456 | 1052 143 4.6 1457 | 42 13 4.1 1458 | 1523 9 2.5 1459 | 1970 5 3.6 1460 | 1609 68 4.0 1461 | 1691 25 5.0 1462 | 2124 1 4.0 1463 | 1892 26 4.0 1464 | 1570 128 4.0 1465 | 1136 84 5.0 1466 | 425 7 3.1 1467 | 891 7 3.0 1468 | 750 45 2.0 1469 | 1752 6 3.0 1470 | 604 7 3.6 1471 | 2283 18 4.1 1472 | 1036 26 4.1 1473 | 1374 43 4.0 1474 | 617 29 2.0 1475 | 2033 990 4.1 1476 | 1515 131 2.5 1477 | 1323 41 4.0 1478 | 1213 1 1.1 1479 | 1049 43 3.1 1480 | 679 1 4.0 1481 | 1857 26 5.0 1482 | 1335 80 4.0 1483 | 1348 66 4.5 1484 | 1902 1 5.1 1485 | 617 42 1.1 1486 | 2264 6 2.0 1487 | 1991 909 4.0 1488 | 307 68 4.0 1489 | 433 9 3.0 1490 | 1202 1 3.1 1491 | 151 68 5.1 1492 | 2091 7 2.5 1493 | 262 116 4.1 1494 | 881 26 2.0 1495 | 1846 1 4.1 1496 | 1116 43 3.0 1497 | 974 84 4.0 1498 | 2183 5 4.0 1499 | 157 45 4.6 1500 | 1970 129 4.6 1501 | 1178 23 5.1 1502 | 1809 75 2.0 1503 | 1856 5 3.1 1504 | 1569 27 4.6 1505 | 1490 1 4.1 1506 | 484 131 4.0 1507 | 1865 87 3.6 1508 | 1864 8 4.0 1509 | 1888 5 2.0 1510 | 1431 5 4.5 1511 | 550 35 2.5 1512 | 1480 63 5.1 1513 | 1537 30 3.1 1514 | 806 6 3.1 1515 | 1568 1 4.0 1516 | 1908 1 4.1 1517 | 1336 100 3.1 1518 | 2052 9 3.0 1519 | 37 4 4.0 1520 | 281 64 4.1 1521 | 1508 69 3.0 1522 | 1300 128 5.0 1523 | 1148 23 5.0 1524 | 2052 43 3.0 1525 | 1656 1 4.6 1526 | 734 26 4.6 1527 | 1601 5 4.1 1528 | 596 43 4.0 1529 | 340 7 3.0 1530 | 2155 1 4.1 1531 | 908 80 3.0 1532 | 353 35 4.6 1533 | 776 22 1.0 1534 | 1820 1 5.1 1535 | 1743 6 4.0 1536 | 489 7 3.0 1537 | 194 990 4.0 1538 | 2299 7 2.0 1539 | 1640 1224 4.6 1540 | 323 24 0.6 1541 | 2282 3 4.0 1542 | 1069 27 5.0 1543 | 193 45 4.0 1544 | 804 45 4.0 1545 | 1069 117 4.0 1546 | 213 26 3.0 1547 | 2253 7 4.1 1548 | 1253 26 4.1 1549 | 1435 128 4.1 1550 | 2171 8 4.0 1551 | 1523 87 1.1 1552 | 463 128 5.1 1553 | 696 6 3.1 1554 | 2244 20 3.0 1555 | 2080 803 3.6 1556 | 1861 84 2.0 1557 | 1523 80 3.1 1558 | 1433 91 3.0 1559 | 2268 84 4.0 1560 | 557 27 5.1 1561 | 1776 41 5.0 1562 | 15 26 3.6 1563 | 1357 91 2.6 1564 | 942 116 1.0 1565 | 893 131 3.0 1566 | 1860 125 3.1 1567 | 43 31 3.0 1568 | 1391 26 4.0 1569 | 612 17 4.1 1570 | 788 1148 4.6 1571 | 178 3 2.1 1572 | 1865 164 4.0 1573 | 1763 45 4.0 1574 | 1149 84 3.1 1575 | 2057 1 5.1 1576 | 2209 100 1.1 1577 | 1431 95 4.5 1578 | 10 27 4.1 1579 | 1970 7 3.0 1580 | 42 7 4.0 1581 | 703 8 3.1 1582 | 590 1105 3.1 1583 | 2087 149 2.5 1584 | 468 7 4.0 1585 | 44 6 4.1 1586 | 2045 1 3.5 1587 | 1470 26 4.1 1588 | 1857 7 4.0 1589 | 1065 20 3.1 1590 | 2120 5 3.0 1591 | 1228 55 3.0 1592 | 1983 5 3.5 1593 | 448 8 3.1 1594 | 1593 803 4.6 1595 | 1069 836 4.6 1596 | 951 84 3.0 1597 | 1019 1 4.0 1598 | 2200 37 1.1 1599 | 2013 80 4.1 1600 | 2296 17 4.1 1601 | 1818 43 3.1 1602 | 287 20 3.0 1603 | 1827 69 2.1 1604 | 957 181 4.1 1605 | 156 143 5.1 1606 | 16 9 5.1 1607 | 1810 26 4.1 1608 | 1657 45 3.0 1609 | 1966 35 3.0 1610 | 38 84 3.6 1611 | 518 7 2.1 1612 | 1159 74 2.0 1613 | 968 35 3.6 1614 | 1722 181 3.6 1615 | 2133 27 4.0 1616 | 908 45 3.5 1617 | 2230 84 4.0 1618 | 1890 49 5.0 1619 | 587 1 4.0 1620 | 1769 37 1.1 1621 | 1462 84 3.1 1622 | 2200 5 4.1 1623 | 317 42 3.1 1624 | 1689 26 4.0 1625 | 1864 95 4.1 1626 | 43 69 3.1 1627 | 222 6 4.0 1628 | 949 7 3.1 1629 | 2091 45 3.0 1630 | 2005 162 3.0 1631 | 1566 74 3.0 1632 | 1885 40 1.1 1633 | 369 35 5.1 1634 | 1864 93 3.6 1635 | 805 8 3.0 1636 | 946 7 3.1 1637 | 1781 6 0.6 1638 | 1069 26 4.5 1639 | 1592 7 3.6 1640 | 493 116 1.1 1641 | 1852 5 5.0 1642 | 147 1 2.0 1643 | 786 7 5.0 1644 | 1347 128 5.1 1645 | 581 17 1.0 1646 | 739 26 3.0 1647 | 1252 31 3.1 1648 | 2293 23 4.1 1649 | 453 6 3.1 1650 | 805 6 3.1 1651 | 1067 66 3.0 1652 | 1337 29 3.0 1653 | 2173 17 2.5 1654 | 1860 39 4.0 1655 | 405 25 4.1 1656 | 1618 29 2.0 1657 | 1995 1 4.0 1658 | 2190 45 3.6 1659 | 1307 8 3.1 1660 | 1769 35 4.1 1661 | 1440 29 3.0 1662 | 1571 135 3.5 1663 | 1737 31 3.1 1664 | 1312 128 3.6 1665 | 2176 27 3.0 1666 | 1592 26 4.1 1667 | 2062 27 4.0 1668 | 1451 5 5.0 1669 | 403 7 3.0 1670 | 1196 128 4.0 1671 | 1232 60 5.0 1672 | 624 1 4.1 1673 | 1893 42 3.0 1674 | 1934 25 4.0 1675 | 1916 6 3.1 1676 | 1480 72 5.0 1677 | 2168 27 4.1 1678 | 1159 51 2.0 1679 | 1660 42 2.1 1680 | 700 26 4.5 1681 | 1649 128 5.1 1682 | 221 35 3.1 1683 | 1679 45 2.6 1684 | 1576 58 4.5 1685 | 1065 21 5.0 1686 | 2161 35 2.1 1687 | 978 1009 4.5 1688 | 2226 84 4.1 1689 | 2276 1 3.1 1690 | 1071 39 3.0 1691 | 153 45 4.1 1692 | 168 63 3.1 1693 | 1860 26 5.1 1694 | 455 125 4.0 1695 | 1864 110 2.5 1696 | 721 27 2.0 1697 | 1304 74 4.1 1698 | 2071 7 3.0 1699 | 1313 155 4.1 1700 | 912 26 5.1 1701 | 1431 7 3.1 1702 | 1618 45 5.1 1703 | 1214 1 3.0 1704 | 1523 127 2.1 1705 | 2016 7 3.6 1706 | 9 104 4.6 1707 | 2110 45 3.0 1708 | 1178 803 5.1 1709 | 2173 836 2.5 1710 | 648 30 4.0 1711 | 231 35 4.0 1712 | 268 1 4.0 1713 | 1339 1 4.0 1714 | 1783 7 1.1 1715 | 912 17 3.0 1716 | 1422 84 3.6 1717 | 1431 23 4.1 1718 | 878 26 2.6 1719 | 15 8 3.6 1720 | 1225 19 5.1 1721 | 152 26 3.5 1722 | 2091 24 3.1 1723 | 355 11 3.0 1724 | 1052 5 4.1 1725 | 1627 45 5.0 1726 | 1522 7 4.1 1727 | 905 43 1.1 1728 | 1950 148 3.0 1729 | 401 1 3.1 1730 | 1836 8 4.1 1731 | 1711 1 4.1 1732 | 404 45 2.0 1733 | 947 22 3.1 1734 | 1126 35 2.0 1735 | 1193 1 4.1 1736 | 961 22 4.0 1737 | 596 84 3.0 1738 | 601 25 4.1 1739 | 60 80 3.1 1740 | 2200 45 3.1 1741 | 488 42 4.1 1742 | 1521 26 4.0 1743 | 1791 35 4.0 1744 | 1052 178 4.1 1745 | 1152 7 5.1 1746 | 43 43 4.1 1747 | 1916 7 4.1 1748 | 1020 7 1.5 1749 | 617 20 4.0 1750 | 1647 39 1.5 1751 | 1843 45 3.5 1752 | 566 1 2.6 1753 | 1966 9 4.1 1754 | 1504 131 1.0 1755 | 1775 25 3.0 1756 | 458 7 1.6 1757 | 1755 35 4.6 1758 | 1359 46 3.0 1759 | 1074 7 5.0 1760 | 1118 43 1.0 1761 | 204 17 3.0 1762 | 2052 1 4.0 1763 | 1805 166 3.1 1764 | 39 178 4.1 1765 | 2052 6 3.6 1766 | 37 1 4.0 1767 | 592 162 4.6 1768 | 1481 8 1.5 1769 | 942 66 2.0 1770 | 1156 3 4.0 1771 | 359 41 4.6 1772 | 14 26 4.1 1773 | 192 25 2.1 1774 | 1036 1 5.1 1775 | 1850 836 4.1 1776 | 2121 84 5.0 1777 | 1860 35 4.6 1778 | 2190 84 3.6 1779 | 601 41 3.1 1780 | 1582 128 4.6 1781 | 1067 61 4.1 1782 | 1196 13 1.6 1783 | 1462 35 4.0 1784 | 1696 1 4.1 1785 | 1647 558 2.5 1786 | 1570 84 3.1 1787 | 2013 89 3.0 1788 | 908 5 4.1 1789 | 66 1 4.1 1790 | 476 84 3.1 1791 | 1231 25 4.5 1792 | 1125 7 4.0 1793 | 1966 43 2.1 1794 | 494 7 3.0 1795 | 1425 43 1.0 1796 | 2104 35 4.0 1797 | 702 84 4.1 1798 | 157 84 3.1 1799 | 1763 131 4.0 1800 | 91 60 3.0 1801 | 308 5 3.6 1802 | 2168 23 4.0 1803 | 1809 5 3.1 1804 | 1026 45 5.0 1805 | 1860 145 3.0 1806 | 2173 132 2.0 1807 | 1396 550 3.6 1808 | 1808 2 1.0 1809 | 1649 178 4.1 1810 | 1781 26 4.1 1811 | 296 191 2.6 1812 | 232 7 4.1 1813 | 834 43 3.1 1814 | 445 3 5.1 1815 | 1685 84 4.1 1816 | 2178 2 4.0 1817 | 157 5 4.6 1818 | 637 43 4.1 1819 | 1007 7 3.1 1820 | 1208 1 3.0 1821 | 1860 146 2.1 1822 | 1647 183 4.1 1823 | 1254 5 5.1 1824 | 1430 64 2.0 1825 | 218 990 2.5 1826 | 289 26 4.1 1827 | 591 7 3.1 1828 | 323 108 3.5 1829 | 1284 26 5.1 1830 | 401 7 3.1 1831 | 292 49 3.0 1832 | 1123 25 4.0 1833 | 517 7 2.0 1834 | 947 84 5.1 1835 | 222 3 5.0 1836 | 1826 6 4.0 1837 | 2052 7 3.1 1838 | 1755 3 4.0 1839 | 50 13 2.1 1840 | 1142 84 5.1 1841 | 1523 1063 3.0 1842 | 77 5 4.1 1843 | 468 66 4.0 1844 | 1860 64 4.6 1845 | 218 178 4.0 1846 | 750 42 4.0 1847 | 241 39 3.0 1848 | 1465 8 4.1 1849 | 465 43 1.0 1850 | 19 5 5.1 1851 | 871 58 5.0 1852 | 2124 26 3.0 1853 | 2258 1 5.1 1854 | 899 169 3.6 1855 | 845 7 2.1 1856 | 28 1 5.0 1857 | 1992 6 5.0 1858 | 1203 43 5.1 1859 | 1827 23 5.1 1860 | 991 1 3.0 1861 | 194 1105 3.0 1862 | 1656 13 1.5 1863 | 1111 26 4.0 1864 | 1610 5 3.0 1865 | 1688 836 4.6 1866 | 1278 27 5.1 1867 | 277 45 5.0 1868 | 88 128 5.1 1869 | 2282 1227 4.6 1870 | 2230 45 3.5 1871 | 801 117 2.1 1872 | 2030 35 4.1 1873 | 1115 8 3.6 1874 | 518 116 0.5 1875 | 676 8 3.1 1876 | 18 803 3.5 1877 | 2282 84 3.1 1878 | 1386 44 3.5 1879 | 1544 25 3.1 1880 | 1544 34 4.0 1881 | 19 25 5.1 1882 | 1864 9 3.1 1883 | 1178 68 5.1 1884 | 1279 1 3.6 1885 | 1527 45 3.5 1886 | 1964 43 2.0 1887 | 131 7 3.1 1888 | 2195 8 5.0 1889 | 1421 60 4.0 1890 | 1864 1 4.0 1891 | 1911 1 5.1 1892 | 1730 84 4.1 1893 | 1284 5 3.5 1894 | 1027 26 5.0 1895 | 1865 178 5.0 1896 | 610 13 1.0 1897 | 180 5 5.1 1898 | 1108 26 1.1 1899 | 2188 6 3.0 1900 | 313 48 1.0 1901 | 611 69 4.0 1902 | 1328 6 2.1 1903 | 1931 7 3.0 1904 | 2232 24 4.1 1905 | 72 43 4.0 1906 | 2039 7 3.1 1907 | 1865 53 3.6 1908 | 756 6 3.5 1909 | 1497 803 3.5 1910 | 1878 6 3.0 1911 | 10 5 3.0 1912 | 1036 128 5.1 1913 | 940 3 5.1 1914 | 2057 3 5.1 1915 | 801 8 3.0 1916 | 1523 34 2.1 1917 | 1775 45 3.1 1918 | 48 93 1.1 1919 | 19 26 3.0 1920 | 959 8 3.1 1921 | 1027 1176 3.0 1922 | 237 25 4.6 1923 | 2042 139 4.6 1924 | 2072 7 1.0 1925 | 935 49 2.0 1926 | 1897 20 3.0 1927 | 722 990 3.0 1928 | 2192 2 4.0 1929 | 404 43 1.6 1930 | 586 175 2.1 1931 | 1300 17 3.0 1932 | 2015 44 4.0 1933 | 719 5 3.1 1934 | 2198 7 5.1 1935 | 2283 45 3.5 1936 | 2030 42 3.1 1937 | 1194 1 4.1 1938 | 1372 45 2.0 1939 | 1523 83 2.5 1940 | 543 63 1.0 1941 | 1722 894 3.1 1942 | 2167 34 5.1 1943 | 2301 909 4.1 1944 | 1983 29 2.1 1945 | 2139 7 4.0 1946 | 1688 35 4.0 1947 | 1691 74 3.1 1948 | 280 128 5.0 1949 | 1176 3 3.1 1950 | 2148 7 2.6 1951 | 2300 1063 4.5 1952 | 433 25 5.0 1953 | 1178 5 4.1 1954 | 1431 1034 4.6 1955 | 1882 6 4.0 1956 | 2087 7 2.5 1957 | 1489 20 5.1 1958 | 650 84 3.5 1959 | 899 1272 3.5 1960 | 60 836 3.6 1961 | 2110 110 0.6 1962 | 942 1272 3.5 1963 | 845 19 4.1 1964 | 1567 26 5.1 1965 | 414 180 3.0 1966 | 2161 45 4.0 1967 | 1275 8 3.0 1968 | 2130 128 4.5 1969 | 92 24 3.6 1970 | 1300 84 4.0 1971 | 904 26 3.6 1972 | 832 44 3.6 1973 | 602 2 2.0 1974 | 1094 43 4.1 1975 | 792 84 4.1 1976 | 2142 8 5.1 1977 | 2200 80 3.0 1978 | 2236 6 4.0 1979 | 977 7 4.1 1980 | 895 35 3.1 1981 | 1060 27 3.1 1982 | 1519 35 3.0 1983 | 42 166 4.0 1984 | 2129 7 3.1 1985 | 1140 191 3.0 1986 | 947 3 4.0 1987 | 1332 1 5.0 1988 | 2258 11 3.0 1989 | 772 1 4.0 1990 | 468 87 4.0 1991 | 1868 61 1.0 1992 | 1860 190 4.0 1993 | 408 27 3.5 1994 | 669 1 2.1 1995 | 695 33 5.0 1996 | 1963 45 1.6 1997 | 899 26 4.1 1998 | 51 128 4.5 1999 | 1496 1 3.1 2000 | 1743 5 4.0 2001 | 317 5 3.6 2002 | 1847 1 5.1 2003 | 367 4 2.1 2004 | 1265 1 3.5 2005 | 312 84 3.6 2006 | 1416 7 2.0 2007 | 122 8 4.0 2008 | 1255 3 4.1 2009 | 1071 11 4.0 2010 | 2142 72 5.1 2011 | 742 3 3.0 2012 | 847 84 5.1 2013 | 550 1 4.0 2014 | 980 8 4.0 2015 | 465 23 3.0 2016 | 157 27 4.5 2017 | 1312 45 3.1 2018 | 812 84 3.1 2019 | 686 35 3.0 2020 | 1018 1 5.1 2021 | 2114 45 4.6 2022 | 75 162 4.1 2023 | 833 29 5.1 2024 | 1365 1 4.0 2025 | 1379 4 4.1 2026 | 1430 3 2.1 2027 | 566 128 3.1 2028 | 1688 131 3.6 2029 | 1990 26 4.1 2030 | 280 1 3.6 2031 | 324 45 3.6 2032 | 1656 84 4.6 2033 | 1388 27 4.0 2034 | 1427 26 3.1 2035 | 835 1 5.0 2036 | 736 17 4.0 2037 | 463 45 4.1 2038 | 1431 803 4.1 2039 | 1196 26 4.1 2040 | 2052 20 4.0 2041 | 1383 84 3.0 2042 | 379 1 5.0 2043 | 2237 43 4.1 2044 | 613 7 3.1 2045 | 16 1 5.0 2046 | 2126 31 3.0 2047 | 1960 26 4.0 2048 | 600 116 0.5 2049 | 778 17 3.0 2050 | 834 42 2.0 2051 | 753 7 3.0 2052 | 1812 31 3.1 2053 | 1386 84 3.1 2054 | 463 26 4.0 2055 | 2030 17 4.0 2056 | 1810 3 3.1 2057 | 2121 83 3.1 2058 | 1593 836 5.0 2059 | 2010 128 5.0 2060 | 1523 8 2.5 2061 | 91 12 2.1 2062 | 1236 106 1.0 2063 | 1409 95 3.5 2064 | 1660 25 4.5 2065 | 1897 8 3.0 2066 | 1462 26 4.0 2067 | 577 3 4.0 2068 | 285 8 3.1 2069 | 2052 5 2.5 2070 | 2120 7 3.1 2071 | 1881 39 4.0 2072 | 1623 6 4.1 2073 | 2010 1 5.1 2074 | 2053 35 1.0 2075 | 8 24 3.0 2076 | 1140 7 3.0 2077 | 520 45 4.1 2078 | 970 43 4.1 2079 | 359 5 5.0 2080 | 1523 178 3.0 2081 | 1191 5 4.1 2082 | 1909 6 4.0 2083 | 2041 35 4.1 2084 | 820 4 3.0 2085 | 1474 11 4.1 2086 | 615 84 4.0 2087 | 2083 116 0.6 2088 | 1294 84 5.1 2089 | 1430 1 4.0 2090 | 881 5 4.1 2091 | 1530 7 3.1 2092 | 1127 5 2.6 2093 | 1608 26 4.0 2094 | 2211 61 4.0 2095 | 1956 100 3.0 2096 | 1915 7 0.5 2097 | 1160 6 5.1 2098 | 355 45 3.0 2099 | 1810 7 2.1 2100 | 194 1272 4.6 2101 | 1089 35 3.0 2102 | 2033 45 4.1 2103 | 1042 8 4.1 2104 | 1262 5 4.1 2105 | 2308 6 4.0 2106 | 1860 6 4.0 2107 | 806 3 1.1 2108 | 1307 20 4.0 2109 | 60 1227 3.6 2110 | 1805 45 4.0 2111 | 1860 42 2.0 2112 | 1434 24 3.1 2113 | 2189 17 2.0 2114 | 306 128 4.0 2115 | 461 1 4.1 2116 | 1679 1105 3.1 2117 | 1938 1 4.6 2118 | 2200 83 2.1 2119 | 947 8 2.0 2120 | 750 24 2.1 2121 | 1357 35 3.0 2122 | 43 26 3.0 2123 | 893 41 5.1 2124 | 1379 5 3.0 2125 | 1357 27 3.1 2126 | 1160 8 3.1 2127 | 1689 45 3.6 2128 | 750 35 3.0 2129 | 406 25 4.1 2130 | 1576 181 4.6 2131 | 1523 69 2.1 2132 | 551 84 4.1 2133 | 1126 1 4.5 2134 | 2258 31 2.1 2135 | 1660 65 5.0 2136 | 527 43 5.0 2137 | 157 134 1.5 2138 | 1814 68 4.0 2139 | 1696 7 3.6 2140 | 2135 1 4.0 2141 | 1880 45 5.0 2142 | 1654 43 1.5 2143 | 319 803 3.1 2144 | 881 43 1.1 2145 | 1016 26 5.1 2146 | 1857 84 4.1 2147 | 1371 26 3.1 2148 | 1530 68 5.0 2149 | 1640 84 4.6 2150 | 845 9 4.1 2151 | 2188 5 1.0 2152 | 2142 61 4.0 2153 | 2142 11 4.1 2154 | 1452 133 3.0 2155 | 888 46 3.0 2156 | 175 17 3.0 2157 | 1319 836 3.1 2158 | 1537 29 3.0 2159 | 2004 7 4.1 2160 | 587 35 4.1 2161 | 1095 5 3.0 2162 | 1523 1176 2.6 2163 | 1730 31 3.0 2164 | 50 43 5.0 2165 | 1638 23 3.0 2166 | 899 72 3.6 2167 | 1281 27 2.0 2168 | 2023 45 5.0 2169 | 993 110 3.5 2170 | 849 1 3.0 2171 | 604 35 3.6 2172 | 493 4 4.0 2173 | 1548 35 3.0 2174 | 1455 26 4.0 2175 | 318 7 5.1 2176 | 509 26 2.0 2177 | 871 69 2.1 2178 | 2231 49 5.0 2179 | 879 1 4.1 2180 | 1264 128 4.6 2181 | 587 41 5.1 2182 | 722 1063 4.1 2183 | 402 7 3.0 2184 | 1319 26 4.0 2185 | 1548 5 5.1 2186 | 222 8 3.1 2187 | 1749 1 4.5 2188 | 126 1 4.0 2189 | 1645 146 3.0 2190 | 1867 1 3.5 2191 | 1218 3 4.1 2192 | 2104 84 3.0 2193 | 2200 13 1.1 2194 | 92 66 3.0 2195 | 501 3 3.0 2196 | 691 5 4.0 2197 | 1991 166 4.1 2198 | 60 8 3.0 2199 | 1803 45 4.0 2200 | 739 1 4.0 2201 | 1304 43 4.1 2202 | 1895 1 2.0 2203 | 2052 8 3.6 2204 | 442 42 3.1 2205 | 573 84 3.0 2206 | 1120 5 4.0 2207 | 1857 166 4.1 2208 | 517 26 3.1 2209 | 1160 45 3.1 2210 | 1245 39 3.6 2211 | 1014 1 1.0 2212 | 566 45 1.0 2213 | 1859 5 4.5 2214 | 2276 44 4.0 2215 | 947 15 3.1 2216 | 924 166 3.6 2217 | 1335 26 5.0 2218 | 1381 26 2.0 2219 | 2074 1 3.5 2220 | 1702 180 4.6 2221 | 1739 25 5.1 2222 | 2052 2 3.6 2223 | 213 42 2.0 2224 | 2289 84 3.6 2225 | 1335 23 4.1 2226 | 690 3 4.1 2227 | 2030 116 1.0 2228 | 1806 64 3.1 2229 | 1570 45 3.5 2230 | 524 80 1.0 2231 | 1516 1 4.5 2232 | 1752 17 4.0 2233 | 550 26 4.6 2234 | 493 75 2.0 2235 | 1307 45 3.0 2236 | 1040 1 3.6 2237 | 1940 35 4.0 2238 | 1597 61 3.0 2239 | 10 43 4.0 2240 | 1452 83 2.5 2241 | 1860 75 3.6 2242 | 722 128 4.5 2243 | 1357 44 3.6 2244 | 92 146 3.1 2245 | 968 26 4.1 2246 | 940 7 4.1 2247 | 1647 100 1.1 2248 | 1087 84 4.0 2249 | 1181 135 4.0 2250 | 592 164 5.1 2251 | 1236 17 4.1 2252 | 1717 39 3.0 2253 | 1862 7 3.5 2254 | 1857 5 4.1 2255 | 1940 26 5.1 2256 | 1247 3 4.1 2257 | 2182 1034 4.0 2258 | 1463 25 5.1 2259 | 1864 173 4.0 2260 | 2083 131 2.5 2261 | 2306 3 3.0 2262 | 468 84 2.5 2263 | 1567 61 4.0 2264 | 1357 128 4.1 2265 | 881 7 3.0 2266 | 1091 45 4.0 2267 | 402 6 5.0 2268 | 1914 7 3.1 2269 | 1157 1 5.1 2270 | 146 45 3.5 2271 | 239 8 3.1 2272 | 1099 1 3.1 2273 | 1089 43 2.0 2274 | 563 118 3.1 2275 | 634 131 4.6 2276 | 838 3 4.1 2277 | 992 1 4.1 2278 | 854 1105 3.5 2279 | 743 84 3.5 2280 | 634 909 3.1 2281 | 1196 35 3.6 2282 | 463 1 5.1 2283 | 838 12 3.1 2284 | 2200 7 4.1 2285 | 2114 26 3.6 2286 | 1864 43 2.1 2287 | 518 76 2.6 2288 | 403 20 4.0 2289 | 1651 23 3.1 2290 | 285 7 3.1 2291 | 587 68 4.1 2292 | 458 5 3.1 2293 | 1279 803 3.6 2294 | 70 43 2.0 2295 | 42 100 2.1 2296 | 792 35 4.0 2297 | 2295 131 1.5 2298 | 1892 75 5.0 2299 | 1751 66 4.1 2300 | 2121 7 4.0 2301 | 370 26 4.0 2302 | 9 1 4.5 2303 | 949 6 3.1 2304 | 2024 1 4.0 2305 | 1159 66 2.1 2306 | 2170 6 2.1 2307 | 924 35 2.1 2308 | 151 41 5.0 2309 | 1770 7 5.0 2310 | 719 6 5.1 2311 | 1596 7 3.1 2312 | 404 95 4.0 2313 | 213 43 5.1 2314 | 323 86 3.0 2315 | 111 803 5.1 2316 | 1792 45 2.0 2317 | 1660 26 4.0 2318 | 824 25 2.0 2319 | 750 61 2.0 2320 | 1239 39 3.1 2321 | 244 35 4.0 2322 | 1920 7 5.1 2323 | 222 5 3.1 2324 | 1586 1227 3.6 2325 | 602 29 3.0 2326 | 560 1 3.5 2327 | 1027 836 1.6 2328 | 363 43 3.6 2329 | 520 7 4.1 2330 | 53 7 1.1 2331 | 2232 26 4.1 2332 | 438 35 4.5 2333 | 2262 7 4.1 2334 | 1178 41 5.1 2335 | 795 26 4.0 2336 | 1494 43 2.1 2337 | 1159 26 3.1 2338 | 1061 43 3.0 2339 | 1986 1 4.0 2340 | 25 3 5.0 2341 | 2080 175 3.6 2342 | 1200 17 2.5 2343 | 517 66 4.0 2344 | 43 35 2.1 2345 | 1252 42 4.1 2346 | 1357 84 3.6 2347 | 2133 84 2.0 2348 | 493 3 3.0 2349 | 60 990 3.1 2350 | 690 17 5.0 2351 | 590 131 3.0 2352 | 2100 7 4.0 2353 | 1699 26 3.0 2354 | 2052 4 3.0 2355 | 537 3 4.5 2356 | 706 26 3.1 2357 | 601 49 2.1 2358 | 1297 45 2.0 2359 | 2119 3 5.0 2360 | 1157 5 5.0 2361 | 323 100 3.5 2362 | 1864 104 3.1 2363 | 643 43 4.0 2364 | 885 3 1.6 2365 | 1042 7 5.0 2366 | 570 26 2.1 2367 | 762 11 5.0 2368 | 1590 3 4.0 2369 | 1695 8 4.1 2370 | 1150 5 4.0 2371 | 1158 25 5.0 2372 | 37 8 3.1 2373 | 191 168 3.5 2374 | 822 35 4.1 2375 | 1915 43 2.1 2376 | 92 116 2.0 2377 | 1891 27 5.0 2378 | 330 6 3.0 2379 | 1968 45 4.0 2380 | 1543 662 3.5 2381 | 684 1 4.0 2382 | 926 7 4.1 2383 | 1621 26 4.1 2384 | 1691 26 5.0 2385 | 2010 3 4.6 2386 | 1231 84 4.0 2387 | 1430 6 1.0 2388 | 1548 84 3.0 2389 | 1436 7 3.0 2390 | 1178 20 4.1 2391 | 838 10 3.1 2392 | 1445 7 4.5 2393 | 978 1 3.5 2394 | 876 45 5.0 2395 | 1493 128 4.1 2396 | 145 1 5.1 2397 | 194 777 4.0 2398 | 1523 26 4.0 2399 | 1900 26 4.5 2400 | 194 5 3.1 2401 | 788 1233 3.0 2402 | 2267 49 4.0 2403 | 357 69 1.1 2404 | 1912 1 3.5 2405 | 2081 5 4.1 2406 | 465 44 4.0 2407 | 1489 1 4.0 2408 | 1567 74 4.0 2409 | 364 7 3.0 2410 | 1471 25 4.1 2411 | 2256 128 4.1 2412 | 2278 1 5.1 2413 | 455 7 3.5 2414 | 1519 26 5.0 2415 | 281 63 1.0 2416 | 1233 3 3.0 2417 | 493 26 5.0 2418 | 1067 43 1.0 2419 | 1688 803 3.6 2420 | 1805 84 4.1 2421 | 1752 26 4.1 2422 | 1200 1224 3.1 2423 | 1690 4 3.1 2424 | 1319 45 2.6 2425 | 1810 5 2.0 2426 | 327 1 3.0 2427 | 560 45 3.0 2428 | 799 128 4.0 2429 | 1136 45 5.1 2430 | 2283 5 4.6 2431 | 2112 7 5.1 2432 | 447 100 2.1 2433 | 611 1224 4.6 2434 | 1524 11 4.1 2435 | 11 45 5.1 2436 | 784 1 4.0 2437 | 1831 3 3.1 2438 | 503 128 5.0 2439 | 958 23 2.0 2440 | 1245 155 0.6 2441 | 1236 990 4.0 2442 | 368 3 5.1 2443 | 1101 45 3.1 2444 | 604 45 5.0 2445 | 514 7 5.0 2446 | 1524 7 3.1 2447 | 1671 7 2.0 2448 | 1889 6 3.1 2449 | 619 2 3.1 2450 | 750 84 3.0 2451 | 1792 7 5.0 2452 | 1115 7 2.5 2453 | 1731 27 4.1 2454 | 2276 95 5.0 2455 | 1567 13 4.1 2456 | 1722 45 3.0 2457 | 493 25 4.1 2458 | 1474 8 4.0 2459 | 2293 72 4.1 2460 | 1860 65 5.0 2461 | 754 84 2.5 2462 | 127 45 3.1 2463 | 1764 1 5.1 2464 | 231 9 4.1 2465 | 942 61 3.1 2466 | 1688 43 3.0 2467 | 691 17 3.0 2468 | 611 84 5.0 2469 | 1431 61 4.0 2470 | 1809 7 3.0 2471 | 2232 81 3.1 2472 | 2178 27 5.0 2473 | 1505 27 4.0 2474 | 1357 588 3.0 2475 | 412 131 4.0 2476 | 440 1 3.1 2477 | 2089 26 3.1 2478 | 1131 45 5.1 2479 | 425 43 4.1 2480 | 1951 128 5.0 2481 | 1324 1 3.6 2482 | 468 75 1.1 2483 | 2046 31 1.1 2484 | 893 9 3.1 2485 | 984 42 2.0 2486 | 1440 2 4.1 2487 | 1715 26 2.1 2488 | 1245 34 4.5 2489 | 168 35 4.1 2490 | 2037 63 4.1 2491 | 458 84 2.6 2492 | 2261 8 3.1 2493 | 1460 8 3.0 2494 | 650 45 3.1 2495 | 1346 26 4.6 2496 | 1225 24 2.1 2497 | 194 803 3.6 2498 | 1381 169 3.5 2499 | 1622 8 5.0 2500 | 731 29 3.0 2501 | 2037 3 4.0 2502 | 1178 27 4.1 2503 | 1737 116 2.0 2504 | 2115 66 4.1 2505 | 1853 45 5.1 2506 | 2004 4 2.1 2507 | 767 45 3.1 2508 | 1648 3 3.1 2509 | 1262 40 5.0 2510 | 518 84 1.0 2511 | 2045 25 4.6 2512 | 305 7 4.1 2513 | 1386 181 4.6 2514 | 1302 18 3.1 2515 | 1696 128 4.5 2516 | 1968 26 3.1 2517 | 1316 6 5.0 2518 | 1236 120 3.5 2519 | 1318 5 4.0 2520 | 380 43 4.0 2521 | 1299 1 5.1 2522 | 650 131 2.5 2523 | 1252 69 3.1 2524 | 1918 20 3.0 2525 | 231 4 4.1 2526 | 904 44 4.5 2527 | 1586 1 4.1 2528 | 693 7 5.1 2529 | 1236 20 4.1 2530 | 935 7 3.0 2531 | 1089 25 3.1 2532 | 523 1 3.0 2533 | 1379 13 2.1 2534 | 1427 45 2.0 2535 | 532 1 4.1 2536 | 1359 20 5.1 2537 | 465 25 3.1 2538 | 1384 1 4.0 2539 | 1436 6 5.0 2540 | 60 46 1.1 2541 | 1905 132 3.1 2542 | 92 6 4.0 2543 | 2126 22 3.6 2544 | 168 17 3.1 2545 | 1419 7 5.0 2546 | 175 7 4.1 2547 | 1821 7 5.1 2548 | 1724 23 4.1 2549 | 611 65 3.0 2550 | 1159 23 3.1 2551 | 169 58 4.6 2552 | 875 45 4.1 2553 | 2127 1 5.1 2554 | 2265 104 1.1 2555 | 813 155 3.6 2556 | 1142 155 3.0 2557 | 2053 128 3.6 2558 | 1702 162 3.6 2559 | 323 68 3.5 2560 | 435 27 4.0 2561 | 1335 5 5.0 2562 | 2042 45 4.1 2563 | 750 86 3.1 2564 | 1634 3 2.1 2565 | 899 80 3.1 2566 | 1060 20 3.1 2567 | 1461 29 3.0 2568 | 1938 45 4.1 2569 | 612 7 1.1 2570 | 430 1 5.1 2571 | 1178 49 4.0 2572 | 1426 1 4.1 2573 | 2091 5 4.1 2574 | 1346 1 4.5 2575 | 970 68 4.0 2576 | 1510 35 5.0 2577 | 2278 26 5.1 2578 | 696 26 4.0 2579 | 147 45 3.1 2580 | 2234 41 4.0 2581 | 400 84 3.6 2582 | 834 26 4.1 2583 | 244 61 4.0 2584 | 1641 20 3.1 2585 | 1617 1 5.0 2586 | 1674 1 5.1 2587 | 1090 26 4.1 2588 | 736 1 5.0 2589 | 329 43 4.0 2590 | 231 12 3.1 2591 | 749 41 4.1 2592 | 523 1272 3.0 2593 | 1864 83 3.0 2594 | 742 45 3.0 2595 | 1605 3 4.1 2596 | 1470 1 4.0 2597 | 1433 108 2.0 2598 | 14 116 1.0 2599 | 891 20 4.0 2600 | 610 11 3.0 2601 | 1775 61 3.1 2602 | 1140 1105 3.0 2603 | 667 3 2.1 2604 | 231 1 5.0 2605 | 1252 65 4.1 2606 | 247 8 3.1 2607 | 658 95 4.1 2608 | 60 166 3.0 2609 | 292 65 5.1 2610 | 1771 43 4.0 2611 | 935 13 1.0 2612 | 2234 117 5.1 2613 | 664 63 1.1 2614 | 2142 27 4.0 2615 | 1245 909 4.0 2616 | 2258 42 2.0 2617 | 2218 8 4.1 2618 | 565 155 3.0 2619 | 2072 3 5.0 2620 | 1386 803 4.5 2621 | 951 35 3.1 2622 | 773 155 5.1 2623 | 1039 156 4.0 2624 | 2145 3 4.1 2625 | 233 7 3.0 2626 | 187 7 5.0 2627 | 1523 45 3.0 2628 | 329 45 5.1 2629 | 1267 5 3.1 2630 | 1897 17 3.1 2631 | 2167 7 4.1 2632 | 1654 26 5.1 2633 | 1295 22 5.1 2634 | 1462 990 3.5 2635 | 1382 3 1.0 2636 | 2200 60 4.1 2637 | 1805 178 4.0 2638 | 2041 1 4.1 2639 | 274 7 3.1 2640 | 1757 64 5.1 2641 | 671 8 3.1 2642 | 1597 131 3.1 2643 | 260 84 4.6 2644 | 600 7 2.5 2645 | 912 4 4.0 2646 | 1647 41 4.0 2647 | 1897 6 4.0 2648 | 2170 26 5.1 2649 | 972 8 4.1 2650 | 1225 5 5.1 2651 | 1567 69 2.1 2652 | 414 689 3.1 2653 | 18 84 3.1 2654 | 1785 80 4.0 2655 | 433 35 4.0 2656 | 91 45 5.1 2657 | 165 7 3.1 2658 | 909 1 3.1 2659 | 1298 76 1.0 2660 | 1494 61 4.1 2661 | 1970 116 1.1 2662 | 1273 35 3.5 2663 | 1695 7 3.0 2664 | 1374 41 3.0 2665 | 175 3 4.0 2666 | 750 73 1.0 2667 | 260 45 4.0 2668 | 323 139 3.0 2669 | 1536 1 5.0 2670 | 1609 41 4.0 2671 | 1118 36 1.0 2672 | 2131 45 5.1 2673 | 654 45 5.1 2674 | 899 45 3.1 2675 | 1352 1 4.0 2676 | 514 6 4.0 2677 | 1695 1 4.1 2678 | 2200 31 2.0 2679 | 1724 26 4.0 2680 | 1488 17 3.1 2681 | 1528 25 5.0 2682 | 2114 166 3.6 2683 | 1275 4 2.1 2684 | 2052 11 3.1 2685 | 899 58 3.5 2686 | 1565 128 4.6 2687 | 156 1 5.1 2688 | 1833 31 4.0 2689 | 1523 1224 2.5 2690 | 1719 1272 5.0 2691 | 2283 8 4.1 2692 | 2101 3 2.0 2693 | 586 185 2.1 2694 | 241 84 3.5 2695 | 406 20 4.1 2696 | 422 128 4.1 2697 | 2301 34 2.0 2698 | 1965 45 4.5 2699 | 1649 155 4.0 2700 | 1543 27 4.6 2701 | 463 43 3.1 2702 | 817 7 4.1 2703 | 1849 26 5.0 2704 | 935 81 4.1 2705 | 1647 5 4.5 2706 | 1867 45 4.0 2707 | 1048 5 1.0 2708 | 1860 7 3.1 2709 | 11 26 5.1 2710 | 71 7 3.0 2711 | 433 45 2.1 2712 | 1142 128 3.1 2713 | 98 128 4.6 2714 | 1722 32 2.5 2715 | 1300 5 4.0 2716 | 1052 17 4.1 2717 | 1236 131 4.0 2718 | 78 113 3.0 2719 | 587 7 3.1 2720 | 598 1 3.1 2721 | 2200 11 2.0 2722 | 637 155 2.5 2723 | 1106 3 3.0 2724 | 1073 128 4.5 2725 | 1983 7 3.6 2726 | 1523 11 3.0 2727 | 615 24 1.0 2728 | 1239 7 2.0 2729 | 2139 61 2.1 2730 | 517 43 2.0 2731 | 1665 26 4.1 2732 | 494 5 4.1 2733 | 690 26 5.0 2734 | 445 30 3.1 2735 | 21 77 3.1 2736 | 2017 45 3.6 2737 | 891 8 4.1 2738 | 2262 17 4.1 2739 | 1456 61 4.0 2740 | 1183 93 4.0 2741 | 1022 803 4.0 2742 | 1949 7 5.0 2743 | 1236 84 4.1 2744 | 190 146 3.1 2745 | 2114 58 3.6 2746 | 1022 45 3.5 2747 | 403 6 3.1 2748 | 2279 3 5.0 2749 | 1335 87 2.0 2750 | 1737 7 3.1 2751 | 2190 17 3.0 2752 | 1702 46 4.1 2753 | 1915 990 3.5 2754 | 1319 1272 3.5 2755 | 1860 22 5.1 2756 | 834 61 3.1 2757 | 1225 44 5.1 2758 | 149 1 4.5 2759 | 2001 8 4.0 2760 | 1860 69 3.6 2761 | 2142 43 2.1 2762 | 1379 16 4.1 2763 | 1426 45 3.5 2764 | 1805 23 1.1 2765 | 1466 1 5.1 2766 | 2142 3 4.1 2767 | 2049 7 5.1 2768 | 1544 35 4.0 2769 | 60 168 3.1 2770 | 2037 8 2.0 2771 | 1860 134 3.6 2772 | 1241 35 3.1 2773 | 1220 3 3.1 2774 | 241 5 2.1 2775 | 1544 45 4.1 2776 | 1267 43 3.0 2777 | 389 7 3.1 2778 | 1592 143 4.1 2779 | 1007 1 3.1 2780 | 1530 26 5.0 2781 | 147 20 4.0 2782 | 942 1176 2.5 2783 | 43 11 3.1 2784 | 2173 96 0.6 2785 | 16 39 4.1 2786 | 1012 116 5.0 2787 | 838 7 1.1 2788 | 538 37 0.5 2789 | 1350 1 4.1 2790 | 84 26 4.1 2791 | 1832 44 5.1 2792 | 910 3 3.6 2793 | 1178 836 5.1 2794 | 433 26 4.1 2795 | 2208 26 4.5 2796 | 1209 3 4.1 2797 | 288 7 4.1 2798 | 1864 777 3.6 2799 | 1599 1 5.0 2800 | 1753 3 4.1 2801 | 822 990 4.1 2802 | 1167 7 5.1 2803 | 215 26 4.1 2804 | 2234 114 4.1 2805 | 190 45 3.1 2806 | 726 31 4.1 2807 | 1401 6 3.1 2808 | 323 135 2.1 2809 | 1441 6 3.1 2810 | 1340 836 4.6 2811 | 1656 565 3.0 2812 | 541 836 4.1 2813 | 1853 43 4.1 2814 | 993 153 2.5 2815 | 590 146 3.1 2816 | 615 42 3.1 2817 | 151 1 3.0 2818 | 947 35 4.0 2819 | 1245 777 2.0 2820 | 428 7 3.0 2821 | 2142 34 4.1 2822 | 1534 1 1.5 2823 | 369 1 1.0 2824 | 1225 17 3.0 2825 | 1338 129 2.5 2826 | 1741 6 3.0 2827 | 1862 84 4.1 2828 | 2016 58 4.6 2829 | 1915 84 3.0 2830 | 1923 45 2.1 2831 | 1950 128 5.1 2832 | 1017 84 3.5 2833 | 1195 6 3.1 2834 | 1805 8 3.5 2835 | 1431 170 4.0 2836 | 1054 26 2.5 2837 | 822 3 3.6 2838 | 75 8 4.0 2839 | 2301 146 3.6 2840 | 1523 35 3.5 2841 | 509 25 3.1 2842 | 604 3 4.0 2843 | 1061 162 4.1 2844 | 1523 25 4.0 2845 | 2013 45 5.1 2846 | 662 3 3.6 2847 | 714 178 3.1 2848 | 1431 35 4.0 2849 | 1455 27 4.0 2850 | 1689 5 5.1 2851 | 1178 117 4.0 2852 | 1252 6 3.1 2853 | 339 74 4.1 2854 | 1749 84 4.1 2855 | 240 3 3.5 2856 | 1178 3 4.0 2857 | 1042 39 4.0 2858 | 245 72 5.0 2859 | 2070 1148 4.1 2860 | 1481 35 3.6 2861 | 1022 2 4.0 2862 | 921 17 4.1 2863 | 1534 143 5.1 2864 | 686 75 1.0 2865 | 687 8 4.0 2866 | 1115 84 2.0 2867 | 989 1 5.0 2868 | 485 1 3.1 2869 | 1755 146 4.0 2870 | 892 6 3.0 2871 | 1160 35 5.1 2872 | 1449 23 4.1 2873 | 611 4 5.1 2874 | 904 49 5.0 2875 | 1769 45 5.0 2876 | 175 45 4.0 2877 | 2045 128 4.6 2878 | 1049 26 5.1 2879 | 2262 131 3.1 2880 | 1445 84 5.1 2881 | 87 1 3.1 2882 | 162 7 3.0 2883 | 2103 6 4.1 2884 | 2148 26 3.6 2885 | 42 803 4.5 2886 | 825 1 4.1 2887 | 1440 4 2.0 2888 | 1970 131 2.6 2889 | 1755 26 4.6 2890 | 1026 42 5.0 2891 | 791 8 4.0 2892 | 671 9 3.0 2893 | 970 26 4.0 2894 | 1215 836 4.6 2895 | 1430 61 4.1 2896 | 1864 191 0.6 2897 | 494 6 4.1 2898 | 84 45 3.1 2899 | 1615 8 3.0 2900 | 1156 7 4.1 2901 | 958 26 3.0 2902 | 1931 43 4.0 2903 | 1493 131 2.6 2904 | 518 42 1.5 2905 | 42 46 3.1 2906 | 834 47 4.1 2907 | 332 1 2.1 2908 | 2276 26 4.1 2909 | 1262 45 4.0 2910 | 1395 1 4.0 2911 | 749 95 4.0 2912 | 1143 1224 3.6 2913 | 80 84 3.5 2914 | 1960 75 3.0 2915 | 1892 25 4.0 2916 | 1195 5 4.0 2917 | 1734 5 4.1 2918 | 1220 84 4.5 2919 | 864 1 3.0 2920 | 1645 26 4.5 2921 | 1252 4 4.1 2922 | 1543 139 4.0 2923 | 473 66 4.1 2924 | 1696 80 1.6 2925 | 1863 100 4.0 2926 | 1570 7 2.5 2927 | 1267 26 5.0 2928 | 832 1 4.5 2929 | 893 143 3.6 2930 | 2059 1 5.1 2931 | 1431 1105 4.5 2932 | 1252 35 3.0 2933 | 1002 1 5.1 2934 | 1894 7 4.1 2935 | 149 166 5.1 2936 | 940 5 4.1 2937 | 2168 8 3.5 2938 | 1071 45 1.0 2939 | 1089 39 2.0 2940 | 1934 181 3.1 2941 | 940 6 3.1 2942 | 1381 1 2.5 2943 | 362 1 5.0 2944 | 1582 1091 3.0 2945 | 1615 6 5.1 2946 | 2005 68 4.0 2947 | 2030 61 4.0 2948 | 126 25 3.0 2949 | 171 25 4.0 2950 | 1111 43 4.0 2951 | 684 26 3.0 2952 | 343 128 4.0 2953 | 939 25 4.0 2954 | 524 26 4.6 2955 | 67 1 5.0 2956 | 1344 1 3.1 2957 | 822 129 3.0 2958 | 1481 803 3.0 2959 | 1827 9 4.1 2960 | 75 58 4.1 2961 | 1597 26 4.6 2962 | 1501 13 3.1 2963 | 1612 909 4.5 2964 | 1662 1 5.1 2965 | 335 803 3.6 2966 | 1781 7 0.6 2967 | 241 29 1.5 2968 | 1956 1 4.5 2969 | 1737 13 3.0 2970 | 980 1 5.1 2971 | 474 3 5.0 2972 | 1567 17 4.1 2973 | 554 7 5.1 2974 | 1766 7 3.1 2975 | 816 3 5.0 2976 | 1284 45 2.5 2977 | 1758 45 3.0 2978 | 1348 73 1.0 2979 | 377 3 4.1 2980 | 1696 43 4.0 2981 | 1592 43 3.0 2982 | 687 66 5.0 2983 | 2211 1 5.1 2984 | 231 13 2.0 2985 | 1737 9 3.0 2986 | 1723 41 5.0 2987 | 1910 43 2.1 2988 | 947 31 3.0 2989 | 2098 1 5.1 2990 | 2173 777 2.5 2991 | 1847 5 3.0 2992 | 1926 7 4.1 2993 | 999 1 4.0 2994 | 1310 84 4.0 2995 | 1864 894 1.0 2996 | 618 58 4.1 2997 | 1874 26 4.1 2998 | 1453 3 4.0 2999 | 1603 1 5.0 3000 | 1181 27 4.0 3001 | 1890 7 4.0 3002 | 1976 2 5.0 3003 | 2126 1 4.1 3004 | 968 1 5.0 3005 | 2162 3 3.5 3006 | 478 8 3.1 3007 | 1973 128 3.0 3008 | 132 35 3.1 3009 | 1523 1 4.0 3010 | 827 45 4.1 3011 | 1656 35 4.1 3012 | 1717 35 5.1 3013 | 1310 43 3.0 3014 | 1445 73 1.1 3015 | 194 7 4.6 3016 | 2234 7 2.1 3017 | 566 25 3.0 3018 | 218 25 4.0 3019 | 1798 15 4.1 3020 | 132 100 1.6 3021 | 702 35 4.6 3022 | 687 20 5.0 3023 | 37 5 5.1 3024 | 465 49 4.1 3025 | 60 803 3.5 3026 | 195 1 4.1 3027 | 487 1 4.0 3028 | 1501 7 4.1 3029 | 355 19 1.0 3030 | 1810 31 2.1 3031 | 231 45 5.0 3032 | 2010 45 4.1 3033 | 1655 65 2.0 3034 | 82 131 3.0 3035 | 714 45 5.0 3036 | 2239 1 4.0 3037 | 1232 1 3.1 3038 | 2031 42 2.1 3039 | 1970 45 3.1 3040 | 388 26 4.1 3041 | 1515 5 4.6 3042 | 99 1 5.1 3043 | 88 990 3.6 3044 | 1335 49 4.0 3045 | 468 23 5.1 3046 | 1019 25 3.1 3047 | 1891 5 4.0 3048 | 1906 1 0.6 3049 | 231 61 5.1 3050 | 1846 26 3.0 3051 | 92 43 4.0 3052 | 1894 45 4.0 3053 | 861 1 3.1 3054 | 402 1 4.0 3055 | 1788 26 3.1 3056 | 1942 42 3.1 3057 | 1291 43 5.0 3058 | 1027 45 4.0 3059 | 1865 116 3.5 3060 | 1042 61 5.1 3061 | 788 1105 3.5 3062 | 1830 1 4.1 3063 | 691 11 2.1 3064 | 856 74 3.0 3065 | 2267 26 4.6 3066 | 1737 84 4.1 3067 | 1928 25 4.1 3068 | 1810 6 3.0 3069 | 1659 84 4.0 3070 | 993 7 3.5 3071 | 194 35 3.6 3072 | 42 990 3.5 3073 | 91 39 2.0 3074 | 2052 166 3.6 3075 | 170 43 4.5 3076 | 1890 79 4.1 3077 | 168 11 3.0 3078 | 495 26 3.0 3079 | 1523 84 3.0 3080 | 127 1 4.1 3081 | 1372 84 3.0 3082 | 1730 100 5.1 3083 | 570 104 4.0 3084 | 854 131 1.0 3085 | 2190 127 2.1 3086 | 255 11 5.0 3087 | 1274 1 3.0 3088 | 899 104 3.5 3089 | 2180 20 3.0 3090 | 1317 83 3.0 3091 | 799 26 3.6 3092 | 940 45 1.0 3093 | 340 6 3.1 3094 | 581 1 3.1 3095 | 1574 1 4.1 3096 | 537 1 5.1 3097 | 1310 1 4.1 3098 | 191 20 4.1 3099 | 908 68 4.6 3100 | 1052 27 4.1 3101 | 1826 5 3.0 3102 | 542 7 3.0 3103 | 1382 8 3.1 3104 | 1674 75 4.0 3105 | 1409 35 3.6 3106 | 1412 8 2.1 3107 | 1874 11 5.1 3108 | 1865 127 3.0 3109 | 575 7 4.1 3110 | 2217 3 4.1 3111 | 942 1367 2.6 3112 | 1225 27 5.1 3113 | 788 777 4.0 3114 | 59 7 5.1 3115 | 1236 80 4.1 3116 | 1069 149 3.1 3117 | 2030 91 3.1 3118 | 1857 45 4.1 3119 | 653 5 2.6 3120 | 92 7 3.1 3121 | 1116 11 3.1 3122 | 1232 45 2.0 3123 | 263 26 4.0 3124 | 1752 23 4.1 3125 | 1597 24 4.0 3126 | 834 66 3.0 3127 | 1606 4 3.1 3128 | 1463 1 5.1 3129 | 1382 6 2.1 3130 | 15 803 4.0 3131 | 1317 45 5.1 3132 | 686 25 5.1 3133 | 1973 1 4.1 3134 | 435 26 3.1 3135 | 92 45 3.6 3136 | 935 5 2.0 3137 | 1858 23 3.1 3138 | 1160 49 1.0 3139 | 1647 20 3.5 3140 | 1459 1 5.0 3141 | 1956 84 4.1 3142 | 1829 1148 5.1 3143 | 2200 25 4.1 3144 | 332 69 3.0 3145 | 552 17 1.0 3146 | 868 7 3.0 3147 | 14 45 4.1 3148 | 1390 35 3.0 3149 | 871 19 3.0 3150 | 1259 55 4.0 3151 | 323 81 3.6 3152 | 609 1 3.1 3153 | 1515 990 3.5 3154 | 2278 35 4.1 3155 | 2267 1 4.1 3156 | 1755 84 3.5 3157 | 1108 45 4.0 3158 | 2126 6 3.5 3159 | 188 35 5.1 3160 | 1523 39 2.5 3161 | 1548 80 2.1 3162 | 1332 8 3.1 3163 | 1289 5 4.1 3164 | 1530 41 4.0 3165 | 781 128 4.0 3166 | 1536 5 4.0 3167 | 1481 1224 2.5 3168 | 1527 139 4.6 3169 | 1769 6 3.6 3170 | 2303 3 4.1 3171 | 1338 45 4.1 3172 | 2111 5 4.1 3173 | 1241 45 4.0 3174 | 1499 1 3.6 3175 | 60 143 3.0 3176 | 2071 1 5.0 3177 | 1239 26 4.1 3178 | 1379 6 4.0 3179 | 1399 1 5.1 3180 | 1810 60 2.0 3181 | 2037 23 4.1 3182 | 1181 127 3.0 3183 | 449 1 4.0 3184 | 1060 25 5.1 3185 | 470 25 4.1 3186 | 1703 26 4.0 3187 | 1090 1227 4.6 3188 | 1688 5 4.6 3189 | 1717 45 3.0 3190 | 1945 1 4.0 3191 | 332 45 4.0 3192 | 935 76 2.0 3193 | 231 31 3.0 3194 | 984 75 4.0 3195 | 65 3 4.0 3196 | 1986 7 3.0 3197 | 2108 26 4.6 3198 | 296 27 4.1 3199 | 1038 46 4.5 3200 | 9 74 4.0 3201 | 1616 3 4.0 3202 | 586 3 0.6 3203 | 1864 11 3.0 3204 | 2221 131 3.0 3205 | 1956 42 3.1 3206 | 1951 37 0.5 3207 | 1593 155 2.5 3208 | 1279 45 1.6 3209 | 106 7 3.1 3210 | 517 41 5.1 3211 | 1649 191 1.6 3212 | 458 45 2.5 3213 | 877 26 4.1 3214 | 1653 1 5.0 3215 | 429 26 4.1 3216 | 1056 26 4.1 3217 | 1430 39 2.0 3218 | 1185 84 3.1 3219 | 91 17 1.1 3220 | 1827 8 3.0 3221 | 822 128 5.0 3222 | 60 112 2.1 3223 | 180 35 1.0 3224 | 1653 777 2.1 3225 | 861 7 2.0 3226 | 1757 84 0.5 3227 | 1760 22 5.1 3228 | 1734 20 4.1 3229 | 893 80 3.1 3230 | 601 5 4.1 3231 | 241 131 1.0 3232 | 687 26 5.1 3233 | 618 128 5.0 3234 | 1755 74 4.0 3235 | 2069 3 4.0 3236 | 612 61 3.0 3237 | 714 37 2.5 3238 | 1950 17 0.6 3239 | 1956 5 4.5 3240 | 1034 1 5.1 3241 | 246 6 4.0 3242 | 2135 45 4.6 3243 | 1824 84 2.6 3244 | 2205 26 2.5 3245 | 2133 7 3.0 3246 | 2209 26 4.6 3247 | 18 95 4.0 3248 | 355 43 2.1 3249 | 619 3 4.0 3250 | 2209 191 1.5 3251 | 805 1 3.0 3252 | 1106 7 3.1 3253 | 280 31 3.1 3254 | 1912 990 1.0 3255 | 2069 5 1.0 3256 | 1236 42 3.0 3257 | 2028 1148 4.6 3258 | 931 2 3.1 3259 | 1864 35 3.0 3260 | 825 23 3.1 3261 | 1196 25 4.1 3262 | 380 80 4.0 3263 | 30 1 4.1 3264 | 1232 20 4.1 3265 | 2278 49 1.0 3266 | 298 1 3.6 3267 | 1033 1 5.0 3268 | 132 45 4.0 3269 | 691 26 3.0 3270 | 468 11 4.0 3271 | 1158 45 3.1 3272 | 958 7 4.0 3273 | 573 5 4.0 3274 | 175 83 3.1 3275 | 2013 5 4.0 3276 | 1481 26 4.0 3277 | 296 6 3.0 3278 | 706 20 4.0 3279 | 1763 84 3.1 3280 | 361 1 3.0 3281 | 956 45 4.0 3282 | 1894 69 3.0 3283 | 1688 42 3.0 3284 | 1017 3 3.6 3285 | 2052 131 3.1 3286 | 1215 26 5.1 3287 | 1644 41 5.0 3288 | 1203 41 4.1 3289 | 493 61 3.0 3290 | 1860 4 4.5 3291 | 1792 43 5.1 3292 | 1432 1 5.1 3293 | 1647 25 4.6 3294 | 1549 5 3.1 3295 | 18 8 3.1 3296 | 1820 43 3.0 3297 | 1177 84 3.1 3298 | 714 687 3.0 3299 | 2192 22 5.1 3300 | 618 26 5.1 3301 | 859 3 3.0 3302 | 277 8 5.1 3303 | 1688 7 3.6 3304 | 2116 1 4.6 3305 | 112 1 4.5 3306 | 167 1 2.5 3307 | 554 3 4.0 3308 | 1450 68 4.0 3309 | 888 8 3.1 3310 | 757 7 2.0 3311 | 2102 1 4.1 3312 | 1178 550 4.5 3313 | 958 35 4.1 3314 | 2261 7 4.0 3315 | 1323 23 5.1 3316 | 750 5 5.1 3317 | 1736 39 3.0 3318 | 113 72 4.1 3319 | 854 20 2.5 3320 | 373 1 4.6 3321 | 1379 3 4.1 3322 | 590 1224 2.5 3323 | 1757 69 3.5 3324 | 629 1105 3.5 3325 | 1387 84 3.5 3326 | 801 84 3.6 3327 | 380 61 3.0 3328 | 829 23 4.1 3329 | 1890 84 4.0 3330 | 813 84 3.0 3331 | 850 27 4.6 3332 | 945 131 2.0 3333 | 1960 41 3.1 3334 | 1052 43 2.5 3335 | 899 66 4.1 3336 | 603 135 5.0 3337 | 45 127 0.6 3338 | 2080 35 4.1 3339 | 788 1272 3.0 3340 | 2267 169 3.5 3341 | 1310 66 5.1 3342 | 2013 72 5.1 3343 | 968 39 2.1 3344 | 317 7 3.1 3345 | 1848 8 3.1 3346 | 2173 45 3.6 3347 | 543 80 2.0 3348 | 1026 43 1.1 3349 | 1634 5 2.0 3350 | 1792 26 3.0 3351 | 435 45 4.1 3352 | 2176 28 4.0 3353 | 1847 7 2.1 3354 | 193 84 2.5 3355 | 1320 43 2.1 3356 | 1236 69 3.6 3357 | 592 86 4.6 3358 | 241 35 3.0 3359 | 1265 2 4.0 3360 | 1649 131 2.5 3361 | 1864 990 3.5 3362 | 1993 45 3.0 3363 | 1497 84 4.5 3364 | 2187 17 3.0 3365 | 2053 45 4.0 3366 | 1446 7 3.0 3367 | 1991 26 4.0 3368 | 163 1 4.0 3369 | 168 31 3.1 3370 | 1567 7 4.0 3371 | 1688 25 4.6 3372 | 168 84 3.1 3373 | 2163 84 4.1 3374 | 1246 1 4.0 3375 | 1108 35 4.0 3376 | 1350 84 2.1 3377 | 1567 43 4.0 3378 | 1728 5 3.0 3379 | 2178 5 3.0 3380 | 2052 27 4.1 3381 | 603 84 5.0 3382 | 1880 7 5.0 3383 | 366 845 2.0 3384 | 2200 35 4.0 3385 | 2013 64 4.1 3386 | 195 26 3.1 3387 | 260 34 4.0 3388 | 80 1 4.0 3389 | 473 26 3.0 3390 | 722 1227 4.0 3391 | 728 181 4.6 3392 | 1189 1 3.0 3393 | 1689 131 2.6 3394 | 1516 45 4.1 3395 | 10 23 5.0 3396 | 1656 191 3.5 3397 | 984 80 5.0 3398 | 42 44 5.1 3399 | 795 25 4.5 3400 | 97 3 4.0 3401 | 2133 23 4.1 3402 | 2275 1 3.1 3403 | 1278 3 3.1 3404 | 42 128 4.6 3405 | 802 29 4.1 3406 | 260 20 5.0 3407 | 2039 11 4.1 3408 | 575 3 3.0 3409 | 1371 45 3.6 3410 | 2052 72 3.0 3411 | 2232 17 3.0 3412 | 850 84 3.6 3413 | 1336 42 4.1 3414 | 1382 35 3.1 3415 | 1178 150 3.5 3416 | 1140 43 2.5 3417 | 708 27 4.0 3418 | 1950 1272 2.6 3419 | 1160 69 2.0 3420 | 990 5 4.0 3421 | 175 75 5.0 3422 | 525 3 3.1 3423 | 750 69 1.1 3424 | 455 4 3.5 3425 | 35 139 5.1 3426 | 1185 45 3.6 3427 | 750 44 4.0 3428 | 146 26 4.6 3429 | 601 58 3.0 3430 | 553 35 3.1 3431 | 2236 5 3.1 3432 | 596 109 3.1 3433 | 1734 25 4.1 3434 | 136 45 5.0 3435 | 1264 1 4.1 3436 | 2291 35 3.0 3437 | 1319 1224 3.5 3438 | 324 26 4.0 3439 | 2251 17 3.1 3440 | 1108 1 3.5 3441 | 1379 7 4.1 3442 | 1970 128 3.5 3443 | 1054 84 4.5 3444 | 1846 8 3.1 3445 | 1746 84 3.6 3446 | 1641 3 5.1 3447 | 1521 45 5.1 3448 | 2173 5 2.6 3449 | 611 63 5.1 3450 | 912 3 3.0 3451 | 2139 35 5.0 3452 | 92 127 2.6 3453 | 1388 5 4.0 3454 | 587 34 3.0 3455 | 935 24 2.1 3456 | 465 42 2.1 3457 | 859 84 3.6 3458 | 205 66 4.1 3459 | 1735 1 5.1 3460 | 1523 76 0.5 3461 | 1189 7 3.0 3462 | 388 45 3.0 3463 | 389 45 3.0 3464 | 1054 131 3.6 3465 | 218 1009 4.5 3466 | 1293 6 3.5 3467 | 1083 1 4.5 3468 | 233 8 3.0 3469 | 1413 45 3.6 3470 | 404 26 3.6 3471 | 359 7 4.1 3472 | 1324 128 3.0 3473 | 1347 26 4.0 3474 | 1158 5 2.0 3475 | 1853 7 5.0 3476 | 1737 80 3.0 3477 | 1687 128 5.1 3478 | 1703 1 4.1 3479 | 982 7 4.0 3480 | 2125 7 4.1 3481 | 1760 32 4.0 3482 | 1372 5 4.5 3483 | 2091 27 4.0 3484 | 1431 26 5.1 3485 | 1537 5 2.1 3486 | 820 5 4.1 3487 | 2232 43 3.1 3488 | 2234 139 3.5 3489 | 1597 7 4.0 3490 | 2278 17 4.0 3491 | 2137 5 3.6 3492 | 1193 27 4.0 3493 | 68 84 4.0 3494 | 1205 17 3.1 3495 | 2139 26 5.0 3496 | 500 7 3.0 3497 | 814 6 3.1 3498 | 1430 12 3.0 3499 | 218 7 2.6 3500 | 2277 6 3.0 3501 | 317 116 1.0 3502 | 586 186 1.0 3503 | 1688 1 4.6 3504 | 1851 128 5.1 3505 | 1548 49 4.1 3506 | 2190 131 3.1 3507 | 2083 146 3.6 3508 | 1906 84 2.1 3509 | 1324 26 3.0 3510 | 2044 43 4.5 3511 | 66 5 4.0 3512 | 142 1 5.0 3513 | 1239 45 4.1 3514 | 256 35 4.1 3515 | 2173 178 4.0 3516 | 1136 35 4.6 3517 | 552 84 3.0 3518 | 218 894 3.5 3519 | 1252 13 1.0 3520 | 38 7 5.1 3521 | 455 15 3.6 3522 | 140 31 3.0 3523 | 1252 25 4.0 3524 | 1346 45 3.0 3525 | 881 45 1.0 3526 | 1864 1009 3.1 3527 | 76 1 4.6 3528 | 2034 43 5.1 3529 | 986 3 2.1 3530 | 1178 162 4.1 3531 | 918 665 3.6 3532 | 1400 6 3.1 3533 | 282 6 4.1 3534 | 1890 44 5.1 3535 | 456 7 5.1 3536 | 1510 1 5.0 3537 | 1291 7 4.1 3538 | 1252 81 4.0 3539 | 2186 8 3.0 3540 | 2301 22 4.1 3541 | 2152 27 5.0 3542 | 2200 42 3.0 3543 | 1560 17 4.0 3544 | 1114 49 4.0 3545 | 2045 5 4.1 3546 | 518 43 4.0 3547 | 728 102 3.1 3548 | 721 8 3.1 3549 | 1957 43 2.0 3550 | 1221 1 5.0 3551 | 997 7 3.0 3552 | 1523 43 2.6 3553 | 834 45 2.1 3554 | 2111 1 4.1 3555 | 2262 84 4.1 3556 | 1602 1 5.0 3557 | 942 112 2.0 3558 | 1950 25 3.5 3559 | 1647 155 1.0 3560 | 276 45 4.1 3561 | 2104 45 2.6 3562 | 526 6 1.0 3563 | 1090 45 3.6 3564 | 1353 5 4.1 3565 | 37 13 3.1 3566 | 2058 35 3.6 3567 | 1151 58 4.1 3568 | 1530 8 2.0 3569 | 35 84 4.1 3570 | 278 27 4.0 3571 | 1990 20 5.0 3572 | 1523 147 2.6 3573 | 1775 26 5.0 3574 | 1860 72 4.6 3575 | 1685 191 3.5 3576 | 92 11 3.5 3577 | 648 27 5.1 3578 | 1049 25 4.0 3579 | 1264 1009 3.6 3580 | 1007 6 5.0 3581 | 241 3 1.6 3582 | 926 3 4.1 3583 | 1359 6 4.0 3584 | 1591 1 3.1 3585 | 1734 45 3.1 3586 | 1374 44 3.0 3587 | 1736 9 3.0 3588 | 1143 35 3.6 3589 | 1294 1 3.0 3590 | 2016 1 5.0 3591 | 388 131 1.6 3592 | 464 60 5.1 3593 | 1800 836 5.0 3594 | 464 44 5.0 3595 | 77 1 3.1 3596 | 1385 26 5.0 3597 | 1357 136 2.5 3598 | 1915 131 1.5 3599 | 1742 5 4.1 3600 | 1860 62 2.5 3601 | 1597 25 5.0 3602 | 1231 35 5.0 3603 | 1864 65 2.0 3604 | 876 1 4.0 3605 | 1576 25 1.0 3606 | 1089 7 3.0 3607 | 191 185 3.5 3608 | 18 26 4.0 3609 | 1770 45 4.1 3610 | 1439 1 3.0 3611 | 1194 84 4.0 3612 | 722 1 4.1 3613 | 2126 39 4.6 3614 | 2062 7 4.0 3615 | 373 128 4.6 3616 | 478 11 3.0 3617 | 1688 26 4.0 3618 | 776 1 4.6 3619 | 244 1 4.1 3620 | 2148 1 4.5 3621 | 15 84 4.1 3622 | 42 25 5.0 3623 | 438 175 4.6 3624 | 56 3 4.1 3625 | 586 129 3.5 3626 | 1471 1 3.5 3627 | 767 72 3.1 3628 | 1950 1063 3.5 3629 | 1465 6 3.0 3630 | 947 95 5.1 3631 | 144 6 3.0 3632 | 570 108 2.1 3633 | 1691 125 4.1 3634 | 1544 40 3.1 3635 | 1523 37 0.5 3636 | 2142 9 4.1 3637 | 1872 1 4.0 3638 | 2215 5 4.0 3639 | 2200 26 5.0 3640 | 1294 45 4.0 3641 | 2209 990 3.0 3642 | 806 7 5.0 3643 | 1445 134 4.0 3644 | 412 1 4.6 3645 | 1409 1227 3.0 3646 | 1758 69 3.1 3647 | 1515 45 3.6 3648 | 1737 131 3.1 3649 | 2042 27 4.1 3650 | 824 15 2.0 3651 | 1445 1 5.1 3652 | 298 25 4.6 3653 | 43 9 3.0 3654 | 543 1 4.0 3655 | 1607 5 4.0 3656 | 256 39 4.0 3657 | 828 26 4.1 3658 | 343 803 4.0 3659 | 1760 20 3.1 3660 | 168 7 2.1 3661 | 1875 26 2.0 3662 | 1534 131 0.6 3663 | 641 1 4.0 3664 | 917 6 3.6 3665 | 1523 155 3.0 3666 | 899 128 3.5 3667 | 877 836 4.1 3668 | 265 84 5.0 3669 | 1212 1 4.0 3670 | 1298 61 5.0 3671 | 458 35 3.1 3672 | 78 84 3.0 3673 | 1523 17 3.0 3674 | 792 13 3.6 3675 | 2126 35 4.6 3676 | 109 3 4.0 3677 | 1231 178 4.0 3678 | 919 5 4.0 3679 | 465 26 3.0 3680 | 905 76 2.0 3681 | 241 83 0.6 3682 | 1168 127 1.0 3683 | 1860 836 3.5 3684 | 1159 1 3.1 3685 | 2282 129 3.6 3686 | 1892 22 5.0 3687 | 2033 7 3.0 3688 | 205 61 5.0 3689 | 1054 777 4.5 3690 | 1319 128 3.5 3691 | 1689 6 3.0 3692 | 569 45 2.1 3693 | 493 2 4.0 3694 | 451 39 2.1 3695 | 36 25 5.0 3696 | 376 8 3.1 3697 | 1059 1 5.1 3698 | 1864 49 3.1 3699 | 605 95 4.0 3700 | 1567 45 4.1 3701 | 75 139 2.6 3702 | 1277 5 3.1 3703 | 919 26 5.1 3704 | 1118 13 3.0 3705 | 899 1009 4.0 3706 | 38 131 2.6 3707 | 1442 37 1.1 3708 | 220 3 3.0 3709 | 296 35 2.6 3710 | 2019 3 4.0 3711 | 1442 39 4.1 3712 | 1894 46 1.0 3713 | 997 8 3.1 3714 | 813 836 3.6 3715 | 2035 8 4.0 3716 | 1456 27 3.1 3717 | 1655 26 4.0 3718 | 93 35 4.0 3719 | 1435 43 3.6 3720 | 60 7 3.1 3721 | 2259 35 3.0 3722 | 738 83 4.0 3723 | 908 1 4.1 3724 | 861 8 3.1 3725 | 801 143 3.1 3726 | 1253 1148 3.0 3727 | 2139 1 5.1 3728 | 2174 26 5.1 3729 | 1462 131 3.6 3730 | 2276 7 3.0 3731 | 579 23 5.1 3732 | 287 1 5.1 3733 | 1794 26 4.0 3734 | 92 131 2.1 3735 | 958 5 5.0 3736 | 1864 26 3.1 3737 | 253 3 5.0 3738 | 2176 20 1.1 3739 | 1576 169 3.0 3740 | 343 836 4.0 3741 | 107 11 4.0 3742 | 463 84 4.6 3743 | 682 1 4.0 3744 | 750 58 5.0 3745 | 1331 1 4.1 3746 | 2232 45 3.0 3747 | 1746 35 3.1 3748 | 733 45 4.6 3749 | 569 84 2.1 3750 | 1093 27 3.0 3751 | 1295 8 3.1 3752 | 343 3 4.0 3753 | 241 45 1.5 3754 | 2234 45 5.0 3755 | 2028 128 5.1 3756 | 643 7 3.0 3757 | 1276 1063 4.0 3758 | 278 25 5.1 3759 | 668 68 5.1 3760 | 1771 7 3.5 3761 | 260 7 3.1 3762 | 2052 84 3.6 3763 | 2041 43 4.1 3764 | 213 45 2.0 3765 | 2200 49 4.1 3766 | 1371 132 2.0 3767 | 562 1 5.0 3768 | 2030 7 1.1 3769 | 1827 43 3.0 3770 | 845 35 3.1 3771 | 1252 22 4.0 3772 | 2190 143 4.0 3773 | 670 26 1.1 3774 | 2236 11 1.0 3775 | 218 128 3.0 3776 | 1944 26 3.6 3777 | 603 162 5.1 3778 | 824 45 3.0 3779 | 1774 128 5.1 3780 | 1168 3 3.1 3781 | 406 26 3.0 3782 | 736 3 5.0 3783 | 813 100 3.0 3784 | 296 178 2.6 3785 | 1944 8 3.5 3786 | 206 17 4.0 3787 | 1858 25 4.0 3788 | 1275 7 5.0 3789 | 1008 1 3.0 3790 | 91 43 3.0 3791 | 52 1195 2.5 3792 | 1013 5 3.0 3793 | 978 803 4.0 3794 | 132 1 3.1 3795 | 1902 128 4.5 3796 | 359 42 0.6 3797 | 241 44 2.5 3798 | 1939 84 4.6 3799 | 1805 803 3.5 3800 | 43 17 3.1 3801 | 1928 3 2.1 3802 | 1317 155 3.1 3803 | 21 68 4.1 3804 | 380 555 4.5 3805 | 543 72 2.0 3806 | 152 2 4.1 3807 | 317 803 4.0 3808 | 648 5 4.0 3809 | 2087 13 2.5 3810 | 144 1 4.0 3811 | 2161 1 4.0 3812 | 679 181 5.0 3813 | 43 39 2.0 3814 | 445 1 4.0 3815 | 493 43 5.0 3816 | 484 8 4.1 3817 | 685 87 3.6 3818 | 319 1272 2.0 3819 | 171 7 3.0 3820 | 1710 45 4.1 3821 | 1956 43 3.1 3822 | 1538 5 3.1 3823 | 1855 91 3.0 3824 | 1042 17 4.0 3825 | 822 26 5.1 3826 | 888 7 2.0 3827 | 1523 131 2.0 3828 | 1772 5 4.1 3829 | 1712 8 4.0 3830 | 1199 59 2.0 3831 | 1688 990 3.0 3832 | 1752 9 3.0 3833 | 92 15 3.6 3834 | 1441 7 3.1 3835 | 414 6 5.1 3836 | 196 84 4.0 3837 | 353 894 0.5 3838 | 2152 35 4.1 3839 | 1371 7 4.1 3840 | 91 42 3.0 3841 | 940 69 3.1 3842 | 433 1 5.1 3843 | 1592 3 1.6 3844 | 1431 69 3.0 3845 | 1472 26 4.0 3846 | 1118 61 2.0 3847 | 1236 25 4.5 3848 | 2174 27 3.0 3849 | 2264 45 4.6 3850 | 2030 131 4.1 3851 | 2232 7 4.1 3852 | 2262 31 2.6 3853 | 1454 1 4.0 3854 | 538 170 3.0 3855 | 1236 7 3.1 3856 | 468 1 3.1 3857 | 1597 35 3.6 3858 | 355 39 3.0 3859 | 672 20 4.6 3860 | 1659 26 4.6 3861 | 2232 42 4.0 3862 | 1266 58 4.5 3863 | 696 45 4.5 3864 | 543 53 1.0 3865 | 1949 6 3.1 3866 | 2037 45 4.0 3867 | 16 17 4.0 3868 | 60 149 3.6 3869 | 1864 51 3.1 3870 | 1951 803 5.1 3871 | 319 26 4.5 3872 | 1026 35 4.1 3873 | 1394 5 4.5 3874 | 1357 665 3.6 3875 | 317 35 4.0 3876 | 62 49 5.1 3877 | 293 1 3.1 3878 | 984 7 5.0 3879 | 1700 803 4.1 3880 | 687 9 3.0 3881 | 1245 7 0.6 3882 | 750 11 3.0 3883 | 984 23 4.0 3884 | 904 43 3.1 3885 | 42 17 4.0 3886 | 1864 34 3.1 3887 | 1178 75 3.1 3888 | 1317 8 3.1 3889 | 962 26 5.1 3890 | 1495 7 4.1 3891 | 799 1 5.1 3892 | 380 45 3.1 3893 | 1966 7 4.0 3894 | 1358 128 4.5 3895 | 2032 6 4.6 3896 | 1431 990 4.6 3897 | 1757 31 2.5 3898 | 92 84 3.0 3899 | 1315 84 3.0 3900 | 1348 20 4.6 3901 | 1879 7 3.0 3902 | 1252 45 4.1 3903 | 2001 3 4.0 3904 | 2032 45 4.1 3905 | 1069 181 4.5 3906 | 1357 45 3.1 3907 | 422 1227 3.5 3908 | 1264 69 1.0 3909 | 422 84 3.6 3910 | 1051 45 4.1 3911 | 998 45 3.1 3912 | 2004 1 5.0 3913 | 877 128 5.0 3914 | 1544 5 3.1 3915 | 60 1224 3.0 3916 | 194 1 5.0 3917 | 2104 990 1.0 3918 | 1314 68 3.5 3919 | 750 9 3.0 3920 | 1497 128 5.0 3921 | 778 3 5.0 3922 | 2200 111 1.1 3923 | 1567 75 3.0 3924 | 2168 3 3.0 3925 | 714 845 2.6 3926 | 674 1 5.0 3927 | 1868 84 4.0 3928 | 1656 131 3.6 3929 | 1523 31 3.0 3930 | 251 3 5.1 3931 | 1430 23 3.0 3932 | 2133 11 3.1 3933 | 2108 1 5.0 3934 | 340 4 3.0 3935 | 608 1 3.0 3936 | 1225 79 5.1 3937 | 1357 24 3.1 3938 | 2168 84 3.1 3939 | 1651 7 3.1 3940 | 691 20 3.0 3941 | 762 35 5.1 3942 | 1425 7 3.1 3943 | 1800 1 2.5 3944 | 920 23 4.1 3945 | 748 20 1.1 3946 | 776 26 5.1 3947 | 571 84 4.0 3948 | 1523 803 3.1 3949 | 353 1 5.1 3950 | 570 93 3.1 3951 | 92 128 4.1 3952 | 761 5 4.1 3953 | 604 26 4.6 3954 | 1100 803 3.6 3955 | 1545 7 3.0 3956 | 1346 803 3.5 3957 | 493 49 5.0 3958 | 2006 63 3.0 3959 | 1564 1 4.0 3960 | 465 45 4.1 3961 | 1681 42 1.0 3962 | 2232 73 3.1 3963 | 317 39 2.5 3964 | 2233 21 3.1 3965 | 1323 8 3.0 3966 | 1324 5 4.1 3967 | 856 68 5.1 3968 | 2108 84 5.0 3969 | 1515 1 4.6 3970 | 278 44 5.0 3971 | 1090 42 4.0 3972 | 788 1227 3.6 3973 | 1565 25 5.0 3974 | 1608 6 4.6 3975 | 478 3 2.1 3976 | 1324 155 3.6 3977 | 650 1 5.1 3978 | 383 1 4.5 3979 | 1157 7 3.1 3980 | 1879 46 2.0 3981 | 1357 82 2.6 3982 | 1031 45 4.1 3983 | 1347 27 4.0 3984 | 1992 17 5.0 3985 | 1931 45 4.1 3986 | 1568 7 4.1 3987 | 1737 26 4.0 3988 | 728 18 4.6 3989 | 1644 49 4.1 3990 | 1565 26 4.6 3991 | 2045 43 3.6 3992 | 1108 7 4.6 3993 | 1860 181 4.6 3994 | 623 45 4.6 3995 | 2293 44 3.0 3996 | 1481 131 1.0 3997 | 779 6 4.1 3998 | 1647 149 3.0 3999 | 734 45 4.1 4000 | 570 128 5.1 4001 | 1860 5 4.1 4002 | 1274 7 3.0 4003 | 88 1 5.0 4004 | 1459 25 3.1 4005 | 1771 45 4.0 4006 | 592 69 2.1 4007 | 362 7 4.1 4008 | 799 84 3.6 4009 | 1287 84 4.1 4010 | 1950 84 1.1 4011 | 587 26 5.0 4012 | 707 7 5.1 4013 | 250 1 3.1 4014 | 1655 5 4.0 4015 | 1026 8 2.0 4016 | 92 25 5.1 4017 | 1846 24 3.1 4018 | 958 25 3.0 4019 | 1703 45 3.5 4020 | 458 8 2.5 4021 | 2010 990 3.6 4022 | 893 26 4.0 4023 | 1161 84 3.1 4024 | 1338 26 4.6 4025 | 1284 128 4.5 4026 | 217 84 4.0 4027 | 541 26 4.0 4028 | 289 42 3.1 4029 | 507 6 3.0 4030 | 935 3 2.0 4031 | 2230 122 0.6 4032 | 458 26 3.5 4033 | 1717 26 4.0 4034 | 900 128 4.6 4035 | 1664 61 3.0 4036 | 1613 7 3.0 4037 | 1026 69 1.1 4038 | 433 84 3.6 4039 | 1860 77 2.5 4040 | 771 155 4.0 4041 | 1810 41 3.1 4042 | 53 45 4.0 4043 | 442 45 4.0 4044 | 1026 66 3.1 4045 | 1319 43 3.0 4046 | 924 26 1.1 4047 | 2215 84 3.6 4048 | 999 22 3.1 4049 | 1548 19 4.1 4050 | 2091 164 4.5 4051 | 220 8 3.0 4052 | 487 43 3.1 4053 | 1455 77 3.1 4054 | 749 803 4.0 4055 | 1731 5 5.0 4056 | 1295 5 5.1 4057 | 1409 26 5.1 4058 | 2070 26 4.5 4059 | 1860 1227 5.1 4060 | 1805 43 2.6 4061 | 1047 45 5.1 4062 | 1069 43 2.1 4063 | 381 5 3.0 4064 | 658 1 4.0 4065 | 1827 61 4.0 4066 | 1238 26 3.1 4067 | 893 11 3.1 4068 | 1382 30 1.1 4069 | 1948 3 5.1 4070 | 2052 68 3.5 4071 | 1090 84 3.5 4072 | 218 104 4.6 4073 | 389 5 4.0 4074 | 803 1 4.0 4075 | 2211 2 4.0 4076 | 1401 7 2.0 4077 | 712 550 5.1 4078 | 1890 23 4.0 4079 | 1037 8 3.0 4080 | 226 43 1.0 4081 | 493 17 5.1 4082 | 1552 7 5.0 4083 | 428 9 4.0 4084 | 311 1227 4.1 4085 | 157 136 3.0 4086 | 227 6 5.1 4087 | 1452 116 2.6 4088 | 625 1 5.0 4089 | 1647 836 3.5 4090 | 1666 1 4.1 4091 | 2233 2 4.1 4092 | 904 9 2.0 4093 | 91 61 2.1 4094 | 294 43 4.1 4095 | 1608 8 4.1 4096 | 2056 5 4.1 4097 | 1404 8 3.0 4098 | 1882 1 4.1 4099 | 2127 20 3.1 4100 | 493 74 4.1 4101 | 1835 1 4.1 4102 | 18 3 3.1 4103 | 2032 5 1.5 4104 | 91 7 4.0 4105 | 1430 49 2.1 4106 | 92 1 4.1 4107 | 60 75 3.0 4108 | 1846 34 4.1 4109 | 543 83 1.0 4110 | 1656 26 3.6 4111 | 1742 6 5.1 4112 | 296 7 3.5 4113 | 1970 42 3.0 4114 | 2028 35 4.5 4115 | 1435 191 2.0 4116 | 1232 26 2.1 4117 | 132 84 3.1 4118 | 1956 26 4.0 4119 | 2180 43 3.0 4120 | 601 27 4.0 4121 | 1382 5 5.1 4122 | 510 4 1.1 4123 | 1770 20 4.1 4124 | 1310 45 4.0 4125 | 1610 6 3.1 4126 | 1864 63 3.1 4127 | 1588 84 4.0 4128 | 296 8 4.0 4129 | 942 6 0.5 4130 | 1089 45 2.1 4131 | 246 8 3.0 4132 | 252 7 4.0 4133 | 1228 21 4.0 4134 | 187 5 5.0 4135 | 1758 11 3.0 4136 | 355 26 4.1 4137 | 649 3 3.0 4138 | 1100 178 4.6 4139 | 1949 3 3.1 4140 | 83 42 1.1 4141 | 495 3 3.0 4142 | 2173 1258 4.1 4143 | 971 18 4.0 4144 | 1858 5 4.0 4145 | 461 128 2.6 4146 | 1196 45 4.1 4147 | 2133 30 3.0 4148 | 1737 127 3.1 4149 | 1143 1105 4.6 4150 | 1194 43 2.6 4151 | 928 26 4.0 4152 | 1042 27 5.1 4153 | 612 45 2.1 4154 | 721 6 3.1 4155 | 590 35 5.0 4156 | 1850 1148 5.0 4157 | 1441 3 3.1 4158 | 998 27 4.6 4159 | 1566 35 3.0 4160 | 544 3 3.0 4161 | 298 43 3.0 4162 | 1523 2 3.1 4163 | 609 7 3.0 4164 | 1682 26 4.1 4165 | 2133 74 3.0 4166 | 511 6 4.1 4167 | 715 6 4.1 4168 | 1660 18 3.5 4169 | 1731 3 4.0 4170 | 157 100 3.6 4171 | 1717 11 3.0 4172 | 553 17 4.1 4173 | 1252 17 4.0 4174 | 1319 803 2.6 4175 | 241 46 1.6 4176 | 551 23 5.1 4177 | 1647 43 1.6 4178 | 928 23 4.1 4179 | 2142 23 5.1 4180 | 194 3 4.6 4181 | 748 25 1.6 4182 | 1864 555 3.5 4183 | 600 45 4.1 4184 | 287 26 4.1 4185 | 1942 128 4.6 4186 | 1950 100 2.0 4187 | 788 990 4.0 4188 | 2091 25 5.1 4189 | 2117 5 4.0 4190 | 1401 5 3.1 4191 | 2114 43 4.6 4192 | 158 100 0.5 4193 | 714 46 3.0 4194 | 1214 155 4.1 4195 | 657 26 1.1 4196 | 1324 25 4.1 4197 | 2275 26 4.6 4198 | 554 11 4.0 4199 | 1236 5 4.5 4200 | 1303 5 3.1 4201 | 766 990 2.1 4202 | 4 45 3.6 4203 | 2167 43 5.1 4204 | 940 23 4.1 4205 | 403 5 4.1 4206 | 573 43 1.0 4207 | 1435 26 3.6 4208 | 1771 46 1.6 4209 | 60 2 3.0 4210 | 10 49 3.1 4211 | 587 45 3.0 4212 | 1681 58 3.1 4213 | 1279 7 1.1 4214 | 958 27 5.0 4215 | 762 7 3.1 4216 | 1540 49 5.1 4217 | 1221 6 5.0 4218 | 194 84 2.0 4219 | 1970 1224 3.5 4220 | 1284 84 3.1 4221 | 871 7 4.0 4222 | 222 29 3.0 4223 | 1140 26 4.6 4224 | 1234 84 0.6 4225 | 650 26 5.1 4226 | 1066 17 4.0 4227 | 157 7 3.0 4228 | 169 169 5.1 4229 | 1316 7 4.1 4230 | 323 120 0.6 4231 | 524 181 3.6 4232 | 950 5 4.0 4233 | 222 27 5.1 4234 | 455 17 4.1 4235 | 2232 11 3.1 4236 | 2030 45 3.1 4237 | 1565 58 4.5 4238 | 912 25 4.1 4239 | 1160 30 5.1 4240 | 339 45 5.1 4241 | 1178 128 4.5 4242 | 1163 3 5.1 4243 | 1538 7 3.1 4244 | 965 7 4.0 4245 | 323 181 0.6 4246 | 1575 42 4.1 4247 | 75 27 3.5 4248 | 1913 5 5.0 4249 | 1864 3 2.5 4250 | 1181 144 4.1 4251 | 60 11 2.0 4252 | 2100 5 4.1 4253 | 560 35 3.5 4254 | 469 1 5.1 4255 | 707 1 3.0 4256 | 1421 23 5.0 4257 | 1026 22 3.0 4258 | 152 1 2.1 4259 | 2146 22 2.0 4260 | 579 45 3.1 4261 | 60 42 3.6 4262 | 2144 1 1.0 4263 | 1981 43 4.1 4264 | 1534 49 4.6 4265 | 2008 6 3.1 4266 | 1357 9 3.1 4267 | 1814 49 5.0 4268 | 618 1 4.0 4269 | 667 43 4.0 4270 | 60 22 3.6 4271 | 1548 128 4.5 4272 | 2247 1 4.1 4273 | 818 100 3.6 4274 | 1737 45 4.0 4275 | 231 8 3.1 4276 | 1853 5 4.0 4277 | 749 26 3.1 4278 | 1966 11 4.0 4279 | 1393 1 3.1 4280 | 1279 84 2.0 4281 | 1236 45 4.0 4282 | 527 23 3.1 4283 | 667 1 3.5 4284 | 1610 8 3.0 4285 | 560 836 3.6 4286 | 393 6 3.1 4287 | 942 131 1.1 4288 | 750 3 3.0 4289 | 241 1 3.0 4290 | 1504 155 4.0 4291 | 1743 1 4.0 4292 | 14 131 4.1 4293 | 742 26 5.1 4294 | 1702 45 5.0 4295 | 171 39 4.0 4296 | 1570 104 4.5 4297 | 1114 5 4.1 4298 | 1116 5 4.1 4299 | 557 26 3.1 4300 | 1431 84 4.0 4301 | 1364 26 5.1 4302 | 335 144 4.1 4303 | 167 84 4.5 4304 | 915 26 3.6 4305 | 359 95 4.6 4306 | 82 45 4.1 4307 | 1039 803 4.6 4308 | 1128 8 3.0 4309 | 2069 7 3.1 4310 | 35 45 4.6 4311 | 2173 909 1.6 4312 | 648 7 4.0 4313 | 935 26 5.0 4314 | 231 24 5.0 4315 | 310 25 4.1 4316 | 1280 43 4.1 4317 | 440 26 4.1 4318 | 984 11 1.1 4319 | 1391 45 4.1 4320 | 1312 191 1.1 4321 | 91 26 2.0 4322 | 157 1 4.0 4323 | 506 113 3.5 4324 | 213 15 3.0 4325 | 1363 45 3.5 4326 | 30 8 5.1 4327 | 83 25 4.1 4328 | 1921 95 3.0 4329 | 317 1 4.0 4330 | 433 34 3.0 4331 | 1981 45 3.0 4332 | 2008 7 4.0 4333 | 1609 72 5.1 4334 | 2283 42 4.1 4335 | 1298 25 5.1 4336 | 1395 35 3.0 4337 | 2035 7 4.1 4338 | 194 43 5.1 4339 | 101 7 4.0 4340 | 1910 1 4.0 4341 | 590 63 3.1 4342 | 2034 45 5.0 4343 | 400 1 4.1 4344 | 1827 75 3.0 4345 | 571 25 5.1 4346 | 1430 77 1.1 4347 | 857 6 3.0 4348 | 2052 35 3.0 4349 | 42 6 2.5 4350 | 42 1272 3.1 4351 | 1668 49 5.1 4352 | 66 7 3.1 4353 | 2302 84 3.1 4354 | 1827 45 3.0 4355 | 1194 803 4.0 4356 | 2142 66 5.1 4357 | 796 1 4.0 4358 | 1860 166 3.0 4359 | 2142 68 5.0 4360 | 353 1227 4.5 4361 | 233 3 4.1 4362 | 637 5 5.1 4363 | 586 17 2.1 4364 | 2085 5 4.1 4365 | 221 11 4.1 4366 | 1647 26 4.5 4367 | 749 43 2.0 4368 | 2052 95 4.0 4369 | 1042 43 5.0 4370 | 175 43 3.0 4371 | 1592 45 3.0 4372 | 2071 45 5.1 4373 | 256 13 2.0 4374 | 2142 7 5.0 4375 | 855 8 3.1 4376 | 363 1148 5.1 4377 | 962 51 4.1 4378 | 523 128 3.1 4379 | 1346 84 3.6 4380 | 612 81 2.1 4381 | 1225 4 4.1 4382 | 1232 27 2.1 4383 | 1836 20 5.1 4384 | 195 84 5.0 4385 | 610 76 1.0 4386 | 1572 45 2.6 4387 | 1608 45 4.5 4388 | 586 7 5.1 4389 | 1844 166 5.1 4390 | 83 26 4.0 4391 | 1472 8 3.0 4392 | 60 1 4.0 4393 | 579 49 5.1 4394 | 1047 1 5.1 4395 | 506 3 2.5 4396 | 43 34 3.0 4397 | 10 33 4.1 4398 | 586 181 2.6 4399 | 2002 7 3.1 4400 | 1481 128 4.6 4401 | 753 6 5.1 4402 | 1159 45 2.0 4403 | 296 26 4.6 4404 | 2273 41 5.0 4405 | 80 35 3.1 4406 | 405 23 3.0 4407 | 949 3 5.1 4408 | 1688 74 3.6 4409 | 1810 43 3.1 4410 | 2173 97 2.6 4411 | 241 2 2.5 4412 | 1196 131 1.6 4413 | 429 7 3.6 4414 | 942 166 2.0 4415 | 287 35 3.0 4416 | 1540 68 4.0 4417 | 1696 6 2.1 4418 | 2052 41 4.0 4419 | 1178 109 4.0 4420 | 2234 43 5.0 4421 | 1239 3 3.0 4422 | 1737 2 4.0 4423 | 92 5 3.5 4424 | 43 8 2.1 4425 | 231 34 3.0 4426 | 2266 5 4.0 4427 | 380 9 4.1 4428 | 1236 11 4.0 4429 | 801 11 3.5 4430 | 600 25 4.6 4431 | 175 46 1.1 4432 | 60 34 3.1 4433 | 1724 8 3.0 4434 | 1142 26 4.0 4435 | 1397 1 3.0 4436 | 1778 26 4.0 4437 | 1689 836 2.1 4438 | 18 173 4.1 4439 | 2296 37 1.1 4440 | 1606 6 3.0 4441 | 281 55 4.0 4442 | 1160 46 2.1 4443 | 1931 13 3.1 4444 | 617 7 3.0 4445 | 2030 13 2.1 4446 | 1841 1 4.0 4447 | 40 35 4.0 4448 | 2155 26 4.6 4449 | 1864 5 2.1 4450 | 1093 25 5.1 4451 | 2293 27 5.0 4452 | 899 149 3.6 4453 | 455 129 3.5 4454 | 2010 35 5.1 4455 | 1647 44 4.1 4456 | 1039 836 3.6 4457 | 450 8 3.0 4458 | 1904 1272 5.1 4459 | 1496 7 3.1 4460 | 1154 5 4.1 4461 | 2013 125 3.1 4462 | 1481 1105 3.0 4463 | 1357 26 3.5 4464 | 333 128 4.0 4465 | 1991 45 3.0 4466 | 83 45 2.0 4467 | 611 6 5.0 4468 | 1791 20 4.1 4469 | 1689 128 4.1 4470 | 296 138 2.6 4471 | 1409 1 3.5 4472 | 1065 35 5.1 4473 | 2228 20 2.0 4474 | 487 35 3.1 4475 | 2016 803 5.1 4476 | 1056 5 4.5 4477 | 2017 100 1.0 4478 | 953 29 3.1 4479 | 504 26 5.0 4480 | 702 128 5.0 4481 | 1323 49 5.1 4482 | 256 26 4.1 4483 | 1357 131 2.0 4484 | 1627 43 5.1 4485 | 1089 131 3.1 4486 | 1760 49 5.0 4487 | 1729 2 3.6 4488 | 331 128 5.1 4489 | 2021 1 5.0 4490 | 1225 95 4.6 4491 | 45 74 3.0 4492 | 1915 26 3.5 4493 | 2236 65 4.0 4494 | 123 1 4.1 4495 | 687 7 4.1 4496 | 2173 146 3.1 4497 | 1118 48 1.1 4498 | 550 143 3.0 4499 | 2045 45 3.5 4500 | 665 7 4.1 4501 | 435 43 4.0 4502 | 904 79 4.1 4503 | 213 35 3.0 4504 | 1440 5 4.1 4505 | 357 39 3.0 4506 | 1544 11 4.1 4507 | 2030 43 4.1 4508 | 788 128 4.5 4509 | 1374 49 3.6 4510 | 1648 13 3.1 4511 | 1857 43 4.1 4512 | 1737 69 3.0 4513 | 1463 35 3.0 4514 | 1184 26 3.1 4515 | 1700 128 4.6 4516 | 1537 7 3.0 4517 | 1042 9 4.0 4518 | 60 26 4.0 4519 | 1821 8 3.0 4520 | 1043 1 4.0 4521 | 2300 116 3.6 4522 | 1715 45 3.6 4523 | 993 990 4.1 4524 | 1606 7 3.1 4525 | 1616 2 3.0 4526 | 60 35 3.6 4527 | 2121 3 5.1 4528 | 2293 66 4.0 4529 | 1654 128 4.0 4530 | 2262 8 2.5 4531 | 183 45 4.0 4532 | 13 3 3.5 4533 | 1827 12 1.1 4534 | 543 55 2.0 4535 | 1536 7 3.1 4536 | 529 84 5.1 4537 | 42 35 2.5 4538 | 2037 5 4.1 4539 | 637 128 5.0 4540 | 602 21 5.1 4541 | 993 1 4.0 4542 | 1464 128 4.0 4543 | 1523 116 0.6 4544 | 180 84 1.5 4545 | 1026 81 4.0 4546 | 2013 3 2.1 4547 | 1399 8 4.1 4548 | 1771 909 3.1 4549 | 665 1 5.1 4550 | 280 26 4.0 4551 | 2133 20 4.1 4552 | 404 91 2.6 4553 | 838 23 3.0 4554 | 1272 6 5.1 4555 | 1225 35 2.0 4556 | 1257 27 4.0 4557 | 706 17 3.1 4558 | 750 50 2.0 4559 | 1176 6 3.1 4560 | 1210 6 4.1 4561 | 924 178 3.5 4562 | 1940 21 4.0 4563 | 1555 45 5.0 4564 | 1131 84 4.1 4565 | 1864 84 4.1 4566 | 93 17 5.1 4567 | 1587 5 4.0 4568 | 801 76 1.0 4569 | 2268 1 4.1 4570 | 357 7 4.1 4571 | 1252 80 5.1 4572 | 1548 25 3.1 4573 | 1027 84 4.1 4574 | 1523 909 3.5 4575 | 1879 43 3.1 4576 | 529 45 5.1 4577 | 946 1 3.0 4578 | 42 4 3.6 4579 | 1544 6 4.0 4580 | 697 69 3.0 4581 | 281 29 2.1 4582 | 1120 1 5.0 4583 | 1140 665 3.6 4584 | 600 82 4.6 4585 | 1200 45 3.1 4586 | 1689 84 3.6 4587 | 1357 39 2.5 4588 | 1335 45 3.1 4589 | 2015 803 4.1 4590 | 942 26 5.1 4591 | 1860 128 4.0 4592 | 571 1 3.0 4593 | 1863 1272 2.6 4594 | 644 8 4.1 4595 | 370 45 3.5 4596 | 947 74 4.1 4597 | 942 155 2.1 4598 | 328 5 2.1 4599 | 1359 7 4.0 4600 | 1597 45 4.6 4601 | 571 89 5.1 4602 | 899 836 4.1 4603 | 355 5 2.1 4604 | 493 1 5.0 4605 | 984 45 4.1 4606 | 1319 7 1.5 4607 | 587 72 4.1 4608 | 886 6 3.1 4609 | 2244 7 1.0 4610 | 148 8 3.0 4611 | 1401 1 3.1 4612 | 2106 1 4.0 4613 | 2167 35 5.1 4614 | 612 43 1.0 4615 | 601 1 4.0 4616 | 2236 25 1.0 4617 | 241 11 3.6 4618 | 241 95 4.1 4619 | 1391 7 3.0 4620 | 947 97 2.0 4621 | 1371 42 2.0 4622 | 575 6 4.1 4623 | 1099 7 3.0 4624 | 506 68 4.1 4625 | 1363 26 3.5 4626 | 617 45 1.1 4627 | 993 836 4.1 4628 | 80 3 4.0 4629 | 1827 114 5.1 4630 | 14 7 2.0 4631 | 194 146 3.6 4632 | 905 13 4.0 4633 | 947 75 2.0 4634 | 2283 25 4.5 4635 | 2229 1 3.1 4636 | 435 84 3.1 4637 | 857 7 3.0 4638 | 1875 7 3.0 4639 | 639 3 4.1 4640 | 984 73 4.1 4641 | 1389 128 4.1 4642 | 899 74 4.0 4643 | 1549 3 3.0 4644 | 2253 20 5.0 4645 | 795 72 3.0 4646 | 1069 45 3.0 4647 | 2013 25 5.1 4648 | 1827 29 1.0 4649 | 231 26 4.1 4650 | 560 143 2.5 4651 | 1621 1 4.0 4652 | 206 3 4.1 4653 | 231 7 5.0 4654 | 1253 1176 4.1 4655 | 788 1224 3.0 4656 | 1185 1 4.6 4657 | 1162 6 5.1 4658 | 2265 49 2.0 4659 | 289 45 4.0 4660 | 1826 3 3.1 4661 | 1509 122 0.5 4662 | 592 95 4.0 4663 | 151 5 5.1 4664 | 1983 55 4.1 4665 | 1379 1 3.1 4666 | 2013 35 3.1 4667 | 600 35 4.1 4668 | 1523 565 2.6 4669 | 1544 26 5.0 4670 | 1523 128 3.5 4671 | 317 45 5.0 4672 | 213 19 3.1 4673 | 1523 157 1.6 4674 | 1295 27 5.0 4675 | 1627 95 4.0 4676 | 10 84 2.1 4677 | 2240 27 4.0 4678 | 2209 155 3.5 4679 | 1678 1 5.0 4680 | 2033 43 4.6 4681 | 1143 42 2.6 4682 | 1758 41 4.0 4683 | 1647 45 3.6 4684 | 2173 990 1.0 4685 | 2114 128 4.0 4686 | 55 45 4.6 4687 | 1523 7 3.0 4688 | 1691 31 3.0 4689 | 336 1 4.0 4690 | 888 73 2.1 4691 | 217 45 4.0 4692 | 2232 13 4.1 4693 | 1846 20 4.1 4694 | 370 128 3.6 4695 | 1515 84 3.0 4696 | 1752 5 5.1 4697 | 246 7 4.0 4698 | 1582 1272 5.1 4699 | 1225 181 5.0 4700 | 1912 803 3.5 4701 | 2234 20 3.0 4702 | 2083 84 4.0 4703 | 766 27 4.6 4704 | 605 128 4.5 4705 | 2283 95 4.0 4706 | 1247 22 3.1 4707 | 370 5 4.1 4708 | 636 22 3.1 4709 | 947 45 3.0 4710 | 788 131 3.6 4711 | 1737 3 3.1 4712 | 433 11 3.1 4713 | 942 134 0.5 4714 | 1159 25 2.1 4715 | 833 1 5.1 4716 | 950 1 5.0 4717 | 493 7 3.1 4718 | 1319 5 3.0 4719 | 1328 1 5.0 4720 | 875 5 5.0 4721 | 1610 7 3.0 4722 | 1422 1 4.1 4723 | 687 1 4.1 4724 | 1686 8 3.0 4725 | 241 31 2.5 4726 | 1827 74 3.0 4727 | 1231 26 5.0 4728 | 801 132 3.0 4729 | 1968 128 4.0 4730 | 13 1 5.1 4731 | 1572 1063 2.6 4732 | 42 20 3.5 4733 | 1064 8 4.1 4734 | 1990 43 2.1 4735 | 1567 30 3.0 4736 | 1162 5 5.0 4737 | 565 181 2.0 4738 | 1931 72 3.1 4739 | 30 6 4.1 4740 | 18 75 3.0 4741 | 1993 26 5.1 4742 | 369 25 5.1 4743 | 493 5 5.1 4744 | 2083 45 4.5 4745 | 1101 26 4.1 4746 | 2121 35 5.1 4747 | 256 61 5.0 4748 | 1998 128 5.0 4749 | 1430 63 3.0 4750 | 1064 7 5.0 4751 | 2139 2 5.1 4752 | 2234 1 5.0 4753 | 175 74 4.0 4754 | 1775 7 3.1 4755 | 241 74 2.1 4756 | 1766 6 3.0 4757 | 523 26 4.0 4758 | 1354 100 1.1 4759 | 365 1 4.0 4760 | 1737 5 4.1 4761 | 1160 23 5.0 4762 | 2271 1 5.0 4763 | 1530 69 4.0 4764 | 1178 44 5.0 4765 | 1973 35 4.6 4766 | 461 26 5.1 4767 | 1956 45 3.1 4768 | 1441 8 3.0 4769 | 882 1 3.0 4770 | 1279 128 4.1 4771 | 901 128 4.5 4772 | 1991 1 4.1 4773 | 1715 1 5.1 4774 | 838 5 3.1 4775 | 1369 1 5.0 4776 | 2185 29 3.1 4777 | 1722 1 3.1 4778 | 1239 11 3.0 4779 | 1031 26 4.1 4780 | 60 1009 3.6 4781 | 2142 20 4.1 4782 | 1185 7 4.5 4783 | 1674 42 2.1 4784 | 2163 45 4.0 4785 | 2236 35 2.0 4786 | 1538 15 4.0 4787 | 517 5 5.1 4788 | 43 7 4.0 4789 | 580 7 3.0 4790 | 382 128 4.1 4791 | 506 74 3.5 4792 | 1799 6 1.0 4793 | 609 3 3.1 4794 | 1627 84 4.0 4795 | 1645 1 4.0 4796 | 543 64 3.1 4797 | 1347 74 2.6 4798 | 1879 63 3.1 4799 | 60 25 3.5 4800 | 1228 44 4.0 4801 | 1291 26 5.1 4802 | 1398 7 3.1 4803 | 928 68 4.0 4804 | 1544 42 2.1 4805 | 1406 27 4.1 4806 | 1665 1 5.1 4807 | 72 7 3.1 4808 | 415 26 4.0 4809 | 1863 1063 4.0 4810 | 854 26 3.0 4811 | 359 43 4.0 4812 | 30 7 3.1 4813 | 1313 1 4.0 4814 | 510 42 3.1 4815 | 60 128 4.5 4816 | 88 131 2.0 4817 | 2265 155 3.6 4818 | 1234 1 4.6 4819 | 1864 24 1.0 4820 | 1357 1 3.6 4821 | 2052 128 3.0 4822 | 1658 6 3.1 4823 | 1220 45 4.5 4824 | 740 1 5.0 4825 | 998 836 4.1 4826 | 2066 41 4.1 4827 | 1116 39 3.0 4828 | 908 26 4.0 4829 | 617 41 4.1 4830 | 216 39 2.0 4831 | 1534 45 3.1 4832 | 1900 1 3.0 4833 | 924 1 4.1 4834 | 1579 6 3.1 4835 | 1465 3 5.0 4836 | 1827 35 3.0 4837 | 1297 2 5.1 4838 | 42 11 3.1 4839 | 1069 128 5.1 4840 | 323 42 0.6 4841 | 1010 8 3.0 4842 | 319 1227 2.5 4843 | 1951 122 0.5 4844 | 2117 26 5.0 4845 | 1115 45 3.0 4846 | 634 1233 4.1 4847 | 154 128 4.5 4848 | 2023 26 5.1 4849 | 1970 803 3.6 4850 | 2083 128 4.1 4851 | 1691 49 4.0 4852 | 1900 128 5.1 4853 | 520 66 5.1 4854 | 126 27 4.0 4855 | 175 9 3.1 4856 | 1019 19 5.0 4857 | 1950 155 3.6 4858 | 893 1 4.5 4859 | 1347 49 4.6 4860 | 15 44 4.0 4861 | 1505 5 3.6 4862 | 5 1 4.0 4863 | 2138 1 5.1 4864 | 1906 803 5.1 4865 | 275 7 4.1 4866 | 1942 1 4.0 4867 | 2020 3 4.0 4868 | 214 63 1.1 4869 | 1734 23 3.1 4870 | 2142 4 5.1 4871 | 1487 43 4.0 4872 | 1666 25 5.1 4873 | 1889 7 3.1 4874 | 1724 66 5.1 4875 | 2141 31 3.0 4876 | 1647 121 3.1 4877 | 1431 909 3.6 4878 | 1523 42 3.1 4879 | 1959 7 1.0 4880 | 191 27 2.5 4881 | 2258 6 3.0 4882 | 1250 1 4.1 4883 | 1026 24 2.0 4884 | 1743 8 5.0 4885 | 904 3 2.0 4886 | 1645 1224 2.0 4887 | 831 7 4.5 4888 | 1783 6 3.0 4889 | 799 35 5.0 4890 | 1440 11 3.0 4891 | 733 1 4.0 4892 | 2107 178 3.5 4893 | 2276 3 3.1 4894 | 1970 166 3.0 4895 | 1287 1105 4.5 4896 | 723 128 4.0 4897 | 878 1 4.1 4898 | 186 20 5.1 4899 | 742 66 2.0 4900 | 899 1227 4.0 4901 | 1834 1 4.0 4902 | 368 7 5.0 4903 | 1623 84 3.6 4904 | 264 31 3.0 4905 | 812 1 4.0 4906 | 676 13 3.1 4907 | 968 131 3.6 4908 | 1108 6 3.6 4909 | 75 20 3.5 4910 | 1104 1 4.0 4911 | 518 35 2.1 4912 | 92 104 3.5 4913 | 296 9 2.1 4914 | 1997 75 3.1 4915 | 329 20 4.1 4916 | 388 35 4.1 4917 | 400 26 3.5 4918 | 968 128 4.0 4919 | 464 68 5.0 4920 | 1252 11 2.1 4921 | 1407 6 3.0 4922 | 908 143 3.5 4923 | 888 74 2.1 4924 | 60 53 2.0 4925 | 780 43 3.1 4926 | 1544 72 4.0 4927 | 893 178 5.1 4928 | 1605 5 4.0 4929 | 560 166 4.6 4930 | 1968 7 3.5 4931 | 1731 45 5.1 4932 | 60 43 3.6 4933 | 468 35 4.0 4934 | 1193 17 3.0 4935 | 1931 35 3.1 4936 | 46 23 2.1 4937 | 60 9 3.5 4938 | 1350 45 5.1 4939 | 332 100 4.0 4940 | 1467 46 4.0 4941 | 60 1105 3.6 4942 | 1372 35 3.0 4943 | 150 26 4.0 4944 | 1000 8 2.1 4945 | 1553 7 4.0 4946 | 2296 5 3.0 4947 | 1300 45 4.5 4948 | 1649 84 3.1 4949 | 1749 35 4.1 4950 | 671 7 4.1 4951 | 1295 26 5.0 4952 | 194 26 4.1 4953 | 1573 84 2.0 4954 | 2230 178 4.0 4955 | 1481 45 3.0 4956 | 303 6 4.1 4957 | 1575 26 5.1 4958 | 1158 26 4.0 4959 | 999 24 4.0 4960 | 1379 8 4.1 4961 | 1739 128 4.1 4962 | 1220 27 4.5 4963 | 984 111 3.0 4964 | 2139 42 3.1 4965 | 1937 128 4.1 4966 | 443 33 2.0 4967 | 1827 66 5.1 4968 | 945 1 2.6 4969 | 1143 45 4.1 4970 | 2171 6 2.0 4971 | 1810 35 4.1 4972 | 1359 5 5.1 4973 | 1809 58 4.1 4974 | 1215 143 3.0 4975 | 1432 26 5.0 4976 | 596 5 4.1 4977 | 832 135 0.6 4978 | 298 7 3.6 4979 | 226 45 3.0 4980 | 781 26 4.0 4981 | 1864 20 2.0 4982 | 2234 128 4.6 4983 | 60 129 2.1 4984 | 351 45 4.0 4985 | 1734 117 3.0 4986 | 749 836 4.0 4987 | 1516 43 5.0 4988 | 716 63 4.1 4989 | 2056 7 3.0 4990 | 942 1105 3.6 4991 | 75 127 3.1 4992 | 1641 27 3.1 4993 | 2045 181 4.0 4994 | 1176 7 4.1 4995 | 2301 31 2.0 4996 | 1359 49 2.1 4997 | 547 43 3.0 4998 | 1820 45 3.6 4999 | 513 25 5.1 5000 | 92 20 3.5 5001 | --------------------------------------------------------------------------------