Metadata-Version: 1.1
Name: randopt
Version: 0.0.1
Summary: Random Search Optimization
Home-page: UNKNOWN
Author: Cyrus Jia, Noel Trivedi, Seb Arnold
Author-email: smr.arnold@gmail.com
License: License :: OSI Approved :: Apache Software License
Description: # rand_opt
        Random search optimization and experiment logging. Support async, fancy visualization, distributed execution. 
        
        ## Example
        Here's a short example on how to use `randopt`.
        
        ```python
        #!/usr/bin/env python
        
        import randopt as ro
        
        def loss(x):
            return x**2
        
        if __name__ == '__main__':
        
            e = ro.Experiment('myexp', {
                    # 'alpha': ro.Normal(low=-1.0, high=1.0, dtype='float'),
                    'alpha': ro.Gaussian(mean=0.0, std=1.0, dtype='float'),
                    # 'alpha': ro.Choice([0.01, 0.05, 0.1, 0.5, 0.7, 0.9], sampler=ro.Uniform()),
                })
        
            # Seeding will make all of your searches reproducible. (Usually not wanted) 
            # e.seed(1234)
        
            # Randomly sampling parameters
            for i in xrange(100):
                alpha = e.sample_alpha()
                res = loss(e.alpha)
                print 'Result: ', res
                e.add_result(res)
        
            # Manually setting parameters
            e.alpha = 0.00001
            res = loss(e.alpha)
            e.add_result(res)
        
            # Search over all experiments results, including ones from previous runs
            opt = e.minimum()
            print 'Best result: ', opt.value, ' with params: ', opt.params
        ```
        
        ## TODO
        
        Check each python file or grep `TODO:` for a complete list of todos. Here's an overview.
        
        * Unit Tests
        * Documentation
        * HTML Vizualization from JSON files
        * Implement more samplers
        * Bayesian optimizaiton on previously ran experiments ?
        
Platform: UNKNOWN
Classifier: Tools
