Metadata-Version: 1.1
Name: wildcat
Version: 0.0.8
Summary: Wildcat Python SDK to Use Annealers
Home-page: https://github.com/mdrft/wildcat_qdk
Author: Shumpei Kobayashi
Author-email: skonb@w-ax.is
License: MIT
Download-URL: https://github.com/mdrft/wildcat_qdk/tarball/0.0.8
Description: class LocalEndpoint(object):
            pass[![Build Status](https://travis-ci.org/skonb/wildcat_qdk.svg?branch=feature%2Ftravis_ci)](https://travis-ci.org/skonb/wildcat_qdk)
        
        Wildcat Python SDK
        ===============================
        
        version number: 0.0.7
        author: Shumpei Kobayashi
        
        Overview
        --------
        
        Wildcat Python SDK to Use Annealers
        
        Installation / Usage
        --------------------
        
        To install use pip:
        
            $ pip install wildcat
        
        
        Or clone the repo:
        
            $ git clone https://github.com/mdrft/wildcat_qdk.git
            $ python setup.py install
            
        Contributing
        ------------
        
        TBD
        
        Example
        -------
        
        To find an optimal arrangement with wildcat remote server:
        ```python
        from wildcat.util.matrix import random_symmetric_matrix
        from wildcat.solver.ising_hamiltonian_solver import IsingHamiltonianSolver
        
             
        Jij = random_symmetric_matrix(size=40)
        solver = IsingHamiltonianSolver(ising_interactions=Jij)
        
        def callback(arrangement):
            e = solver.hamiltonian_energy(arrangement)
            print("Energy: ", e)
            print("Spins: ", arrangement)
        
        solver.solve(callback)
        ```
        
        
        
        To find an optimal arrangement with local annealer, specify LocalEndpoint:
        ```python
        from wildcat.network.local_endpoint import LocalEndpoint
             
        solver.solve(callback, endpoint=LocalEndpoint())
        ```
        
        You can adjust annealing strategy:
        ```python
        from wildcat.network.local_endpoint import LocalEndpoint
        from wildcat.annealer.simulated.simulated_annealer import SimulatedAnnealer
        from wildcat.annealer.simulated.single_spin_flip_strategy import SingleSpinFlipStrategy
        from wildcat.annealer.simulated.temperature_schedule import TemperatureSchedule
        from wildcat.util.matrix import hamiltonian_energy
        
        def update_callback(q):
            print(q)
            print(hamiltonian_energy(q))
            
        schedule = TemperatureSchedule(initial_temperature=10, last_temperature=0.1, scale=0.8)
        strategy = SingleSpinFlipStrategy(repetition=10, update_callback=update_callback)
        annealer = SimulatedAnnealer(schedule=schedule, strategy=strategy)
        local_endpoint = LocalEndpoint(annealer=annealer)
        
        ```
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
