Metadata-Version: 1.1
Name: genrp
Version: 0.0.1.dev1
Summary: UNKNOWN
Home-page: https://github.com/dfm/genrp
Author: Daniel Foreman-Mackey
Author-email: foreman.mackey@gmail.com
License: MIT
Description: Python and C++ implementation of the generalized Rybicki Press algorithm
        for solving matrices of the form::
        
            K_{ij} = sum_p a_p exp(-b_p |t_i - t_j|)
        
        The method was developed by `Sivaram Ambikasaran
        <https://github.com/sivaramambikasaran>`_ and you must cite `his paper
        <http://arxiv.org/abs/1409.7852>`_ if you use this code in your work.
        
        This interface allows complex bs and the parameters are specified as
        log-amplitudes, log-Q-factors, and frequencies. A frequency can be set to
        ``None`` if it is meant to be non-periodic.
        
        A simple benchmark shows that this scales as O(N):
        
        .. code-block:: python
        
            import time
            import numpy as np
            import matplotlib.pyplot as pl
        
            from ess import GRPSolver
        
            solver = GRPSolver(
                np.log([10.0, 5.0]),  # log-amplitudes
                np.log([0.1, 10.0]),  # log-Q-factors
                [None, 50.0],         # frequencies
            )
        
            N = 2**np.arange(5, 20)
            times = np.empty((len(N), 3))
        
            t = np.random.rand(np.max(N))
            yerr = np.random.uniform(0.1, 0.2, len(t))
            b = np.random.randn(len(t))
        
            for i, n in enumerate(N):
                strt = time.time()
                solver.compute(t[:n], yerr[:n])
                times[i, 0] = time.time() - strt
        
                strt = time.time()
                solver.log_determinant
                times[i, 1] = time.time() - strt
        
                strt = time.time()
                solver.apply_inverse(b[:n])
                times[i, 2] = time.time() - strt
        
        .. image:: https://raw.github.com/dfm/ess/master/python/demo.png
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
