Metadata-Version: 1.1
Name: gdprox
Version: 0.1
Summary: UNKNOWN
Home-page: http://pypi.python.org/pypi/gdprox
Author: Fabian Pedregosa
Author-email: f@bianp.net
License: BSD
Description: gdprox, proximal gradient-descent algorithms
        ============================================
        
        Implements the proximal gradient-descent algorithm for composite objective functions, i.e. functions of the form :code:`f(x) + g(x)`, where f is a smooth function and g is a possibly non-smooth function for which the proximal operator is known. 
        
        The main function in this package is :code:`gdprox.fmin_cgprox`. This function follows a similar interface than the functions in :code:`scipy.optimize`. The definition of this function is:
        
        
        .. code-block:: python
        
        	def fmin_cgprox(f, fprime, g_prox, x0, rtol=1e-6,
        	                maxiter=1000, verbose=0, default_step_size=1.):
        	    """
        	    proximal gradient-descent solver for optimization problems of the form
        
        	                       minimize_x f(x) + g(x)
        
        	    where f is a smooth function and g is a (possibly non-smooth)
        	    function for which the proximal operator is known.
        
        	    Parameters
        	    ----------
        	    f : callable
        	        f(x) returns the value of f at x.
        
        	    f_prime : callable
        	        f_prime(x) returns the gradient of f.
        
        	    g_prox : callable of the form g_prox(x, alpha)
        	        g_prox(x, alpha) returns the proximal operator of g at x
        	        with parameter alpha.
        
        	    x0 : array-like
        	        Initial guess
        
        	    maxiter : int
        	        Maximum number of iterations.
        
        	    verbose : int
        	        Verbosity level, from 0 (no output) to 2 (output on each iteration)
        
        	    default_step_size : float
        	        Starting value for the line-search procedure.
        
        	    Returns
        	    -------
        	    res : OptimizeResult
        	        The optimization result represented as a
        	        ``scipy.optimize.OptimizeResult`` object. Important attributes are:
        	        ``x`` the solution array, ``success`` a Boolean flag indicating if
        	        the optimizer exited successfully and ``message`` which describes
        	        the cause of the termination. See `scipy.optimize.OptimizeResult`
        	        for a description of other attributes.
        	    """
        
        
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
