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| author | Christoph Helma <helma@in-silico.ch> | 2011-03-09 12:16:07 +0100 |
|---|---|---|
| committer | Christoph Helma <helma@in-silico.ch> | 2011-03-09 12:16:07 +0100 |
| commit | ef5c37ed8cb76b476133d3f7e013059b9bb13fee (patch) | |
| tree | 88c9c23b55796d393c958128b26bc91354902c89 /README.markdown | |
| parent | d1f555bdb0368fc82a2bb379ab7857bae727072a (diff) | |
README fixed
Diffstat (limited to 'README.markdown')
| -rw-r--r-- | README.markdown | 44 |
1 files changed, 21 insertions, 23 deletions
diff --git a/README.markdown b/README.markdown index 8f18598..4254748 100644 --- a/README.markdown +++ b/README.markdown @@ -1,43 +1,41 @@ opentox-ruby ============ -Ruby wrapper for the OpenTox REST API (http://www.opentox.org) +Ruby wrapper for the [OpenTox](http://www.opentox.org) REST API Installation ------------ -opentox-ruby depends on many third party programs and libraries, which makes the setup complicated and error prone. For this reason we recommend to use the installer from (opentox-install)[http://github.com/opentox/opentox-install]. If you want to install manually you can find the necessary steps in the installation scripts. +opentox-ruby depends on many third party programs and libraries, which makes the setup complicated and error prone. For this reason we recommend to use the installer from [opentox-install](http://github.com/opentox/opentox-install). If you want to install manually you can find the necessary steps in the installation scripts. Quickstart ---------- This example shows how to create a lazar model and predict a compound, it assumes that you have access to a working installation of OpenTox services with corresponding settings in $HOME/.opentox/config. Run the following code in irb or from a ruby script: - require 'rubygems' - require 'opentox-ruby' + require 'rubygems' + require 'opentox-ruby' - # Authenticate - subjectid = OpenTox::Authorization.authenticate(USER,PASSWORD) + # Authenticate + subjectid = OpenTox::Authorization.authenticate(USER,PASSWORD) - # Upload a dataset - training_dataset = OpenTox::Dataset.create_from_csv_file(TRAINING_DATASET, subjectid) + # Upload a dataset + training_dataset = OpenTox::Dataset.create_from_csv_file(TRAINING_DATASET, subjectid) - # Create a prediction model - model_uri = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => training_dataset.uri, :subjectid => subjectid}).to_s - lazar = OpenTox::Model::Lazar.find model_uri, subjectid - - # Predict a compound - compound = OpenTox::Compound.from_smiles("c1ccccc1NN") - prediction_uri = lazar.run(:compound_uri => compound.uri, :subjectid => subjectid) - prediction = OpenTox::LazarPrediction.find(prediction_uri, subjectid) - puts prediction.to_yaml + # Create a prediction model + model_uri = OpenTox::Algorithm::Lazar.new.run({:dataset_uri => training_dataset.uri, :subjectid => subjectid}).to_s + lazar = OpenTox::Model::Lazar.find model_uri, subjectid + + # Predict a compound + compound = OpenTox::Compound.from_smiles("c1ccccc1NN") + prediction_uri = lazar.run(:compound_uri => compound.uri, :subjectid => subjectid) + prediction = OpenTox::LazarPrediction.find(prediction_uri, subjectid) + puts prediction.to_yaml -API documentation ------------------ - -http://rdoc.info/gems/opentox-ruby/0.0.2/frames +[API documentation](http://rdoc.info/gems/opentox-ruby/0.0.2/frames) +------------------------------------------------------------------- Copyright --------- +--------- -Copyright (c) 2009-2011 Christoph Helma. See LICENSE for details. +Copyright (c) 2009-2011 Christoph Helma, Martin Guetlein, Micha Rautenberg, Andreas Maunz, David Vorgrimmler, Denis Gebele. See LICENSE for details. |