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# Do a 10-fold crossvalidation
# # Author: Andreas Maunz, David Vorgrimmler
# # @params: Dataset_name(see dataset_nestle.yaml), pc_type(electronic,cpsa or constitutional ... or nil to disable), prediction_algorithm(local_mlr_prop or local_svm_regression ...)
if ARGV.size != 4
puts "Args: ds_name, pc_type, algo, random_seed"
puts ARGV.size
exit
end
ds_file = "datasets.yaml"
pwd=`pwd`
path = "#{pwd.chop}/../data/#{ds_file}"
if File.exists?(path)
puts "#{ds_file} exists"
else
puts "#{ds_file} does not exist."
exit
end
require 'rubygems'
require 'opentox-ruby'
require 'yaml'
subjectid = nil
ds_name = ARGV[0] # e.g. MOU
pc_type = ARGV[1] # e.g. electronic,cpsa or nil to disable
algo = ARGV[2] # e.g. local_svm_regression, local_mlr_prop
r_seed = ARGV[3] # 1, 2, ..., 10
ds = YAML::load_file("../data/datasets.yaml")
ds_uri = ds[ds_name]["dataset"]
pc_ds_uri = ds[ds_name][pc_type]
algo_params = "prediction_algorithm=#{algo}"
algo_params += ";pc_type=#{pc_type}" unless pc_type == "nil"
algo_params += ";feature_dataset_uri=#{pc_ds_uri}" unless pc_type == "nil"
puts algo_params.to_yaml
prediction_feature = OpenTox::Dataset.find(ds_uri).features.keys.first
# Ready
cv_args = {}
cv_args[:dataset_uri] = ds_uri
cv_args[:prediction_feature] = prediction_feature
cv_args[:algorithm_uri] = "http://toxcreate3.in-silico.ch:80XX/algorithm/lazar"
cv_args[:algorithm_params] = algo_params
cv_args[:stratified] = false
cv_args[:random_seed] = r_seed
puts cv_args.to_yaml
#cv = OpenTox::Crossvalidation.create(cv_args).uri
#puts cv
#cvr = OpenTox::CrossvalidationReport.create( cv , subjectid).uri
#puts cvr
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