Files
linguist/lib/linguist/samples.rb
2012-09-24 10:12:05 -05:00

99 lines
2.6 KiB
Ruby

require 'yaml'
require 'linguist/md5'
require 'linguist/classifier'
module Linguist
# Model for accessing classifier training data.
module Samples
# Path to samples root directory
ROOT = File.expand_path("../../../samples", __FILE__)
# Path for serialized samples db
PATH = File.expand_path('../samples.json', __FILE__)
# Hash of serialized samples object
if File.exist?(PATH)
DATA = YAML.load_file(PATH)
end
# Public: Iterate over each sample.
#
# &block - Yields Sample to block
#
# Returns nothing.
def self.each(&block)
Dir.entries(ROOT).each do |category|
next if category == '.' || category == '..'
# Skip text and binary for now
# Possibly reconsider this later
next if category == 'Text' || category == 'Binary'
dirname = File.join(ROOT, category)
Dir.entries(dirname).each do |filename|
next if filename == '.' || filename == '..'
if filename == 'filenames'
Dir.entries(File.join(dirname, filename)).each do |subfilename|
next if subfilename == '.' || subfilename == '..'
yield({
:path => File.join(dirname, filename, subfilename),
:language => category,
:filename => subfilename
})
end
else
if File.extname(filename) == ""
raise "#{File.join(dirname, filename)} is missing an extension, maybe it belongs in filenames/ subdir"
end
yield({
:path => File.join(dirname, filename),
:language => category,
:extname => File.extname(filename)
})
end
end
end
nil
end
# Public: Build Classifier from all samples.
#
# Returns trained Classifier.
def self.data
db = {}
db['extnames'] = {}
db['filenames'] = {}
each do |sample|
language_name = sample[:language]
if sample[:extname]
db['extnames'][language_name] ||= []
if !db['extnames'][language_name].include?(sample[:extname])
db['extnames'][language_name] << sample[:extname]
db['extnames'][language_name].sort!
end
end
if sample[:filename]
db['filenames'][language_name] ||= []
db['filenames'][language_name] << sample[:filename]
db['filenames'][language_name].sort!
end
data = File.read(sample[:path])
Classifier.train!(db, language_name, data)
end
db['md5'] = Linguist::MD5.hexdigest(db)
db
end
end
end