Dmitry
422cb49b31
- Create Dockerfile and entrypoint script for application setup - Implement pattern loading from Excel and weight caching - Develop core functions for Hopfield and Hamming networks - Add Sinatra web server for user interaction - Create HTML interface for displaying patterns and results - Include necessary gems in Gemfile and lockfile - Add .dockerignore and .gitignore files
79 lines
2.1 KiB
Ruby
79 lines
2.1 KiB
Ruby
require 'sinatra'
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require 'json'
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require_relative 'loader'
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require_relative 'functions'
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require_relative 'hopfield'
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require_relative 'hamming'
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EPS = 0.01
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set :bind, '0.0.0.0'
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set :port, 4567
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set :server, 'webrick'
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disable :protection
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set :host_authorization, { allow_if: ->(_env) { true } }
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PATTERNS = load_patterns('patterns.xlsx')
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PATTERN_VECTORS = PATTERNS.map { |_, m| to_vector(m) }
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PATTERN_NAMES = PATTERNS.keys.map(&:to_s)
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WEIGHTS = load_weights_cache('patterns.xlsx') || begin
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puts 'Обучение модели...'
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w = train_hopfield(PATTERN_VECTORS)
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save_weights_cache(w, 'patterns.xlsx')
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puts 'Веса сохранены в кэш.'
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w
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end
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get '/' do
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@patterns = PATTERNS.transform_values { |m| to_vector(m) }
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erb :index
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end
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post '/recall_steps' do
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content_type :json
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noisy = JSON.parse(request.body.read)['vector'].map(&:to_f)
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# Хопфилд: собираем каждый шаг
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hopfield_steps = [noisy.map { |v| v.to_i }]
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current = noisy.dup
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MAX_HOPFIELD_ITER.times do
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nxt = step_hopfield(WEIGHTS, current)
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hopfield_steps << nxt
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break if vectors_equal?(current, nxt)
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current = nxt
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end
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# Хэмминг: собираем состояния MAXNET
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eps = 0.9 / PATTERN_VECTORS.length
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outputs = hamming_layer(PATTERN_VECTORS, noisy)
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hamming_steps = [outputs.map { |v| v.round(2) }]
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MAX_MAXNET_ITER.times do
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nxt = maxnet_step(outputs, eps)
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hamming_steps << nxt.map { |v| v.round(2) }
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break if nxt.count { |v| v > 0 } <= 1
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outputs = nxt
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end
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winner_idx = outputs.each_with_index.max_by { |v, _| v }[1]
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{
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hopfield_steps: hopfield_steps,
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hamming_steps: hamming_steps,
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pattern_names: PATTERN_NAMES,
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hamming_winner: PATTERN_NAMES[winner_idx]
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}.to_json
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end
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post '/recall' do
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content_type :json
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noisy = JSON.parse(request.body.read)['vector'].map(&:to_f)
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hopfield_result = recall_hopfield(WEIGHTS, noisy)
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hamming_idx = recall_hamming(PATTERN_VECTORS, noisy)
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{
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hopfield: hopfield_result,
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hamming: PATTERN_NAMES[hamming_idx]
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}.to_json
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end
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