# Path: randopt/samplers.py
# class Uniform(Sampler):
#     '''
#     Generates a randomly sampled value from low to high with equal probability.
# 
#     Parameters:
# 
#     * low - (float) minimum value.
#     * high - (float) maximum value.
#     * dtype - (string) data type. Default: float
# 
#     Return type: n/a
# 
#     Example:
# 
#         randopt.Uniform(low=-1.0, high=1.0, dtype='float')
#     '''
#     def __init__(self, low=0.0, high=1.0, dtype='float'):
#         super(Uniform, self).__init__()
#         self.low = low
#         self.high = high
#         self.dtype = dtype
# 
#     def sample(self):
#         res = self.rng.uniform(self.low, self.high)
#         if 'fl' in self.dtype:
#             return res
#         return int(res)
# 
# Path: randopt/experiment/experiment.py
# ATTACHMENT_DIR = '_attachments'
# ATTACHMENT_EXT = '.pk'
# class SummaryList(list):
# class JSONSummary(dict):
# class Experiment(object):
#     def __init__(self, results):
#     def __getitem__(self, key):
#     def __getslice__(self, i, j):
#     def __str__(self):
#     def count(self):
#     def filter(self, fn):
#     def values(self, key='result'):
#     def map(self, fn, key='result'):
#     def min(self, key='result'):
#     def max(self, key='result'):
#     def mean(self, key='result'):
#     def variance(self, key='result'):
#     def std(self, key='result'):
#     def median(self, key='result'):
#     def __init__(self, path):
#     def __getattr__(self, attr):
#     def __str__(self):
#     def _load_attachment(self):
#     def __getstate__(self):
#     def __setstate__(self, state):
#     def __init__(self, name, params={}, directory='randopt_results'):
#     def current(self):
#     def _search(self, fn=leq):
#     def top(self, count, fn=leq):
#     def maximum(self):
#     def minimum(self):
#     def all(self):
#     def list(self):
#     def count(self):
#     def seed(self, seed):
#     def set(self, key, value):
#     def sample(self, key):
#     def sample_all_params(self):
#     def add_result(self, result, data=None, attachment=None):
#     def all_results(self):
#     def save_state(self, path):
#     def set_state(self, path):


import os
import random
    import ujson as json
    import json
    import cPickle as pk
    import pickle as pk
from time import time
from math import log, ceil
from collections import namedtuple
from randopt.samplers import Uniform
from .experiment import Experiment, leq, geq
#!/usr/bin/env python3

try:
except ImportError:
try:
except ImportError:





# Path: randopt/samplers.py
# class Uniform(Sampler):
#     '''
#     Generates a randomly sampled value from low to high with equal probability.
# 
#     Parameters:
# 
#     * low - (float) minimum value.
#     * high - (float) maximum value.
#     * dtype - (string) data type. Default: float
# 
#     Return type: n/a
# 
#     Example:
# 
#         randopt.Uniform(low=-1.0, high=1.0, dtype='float')
#     '''
#     def __init__(self, low=0.0, high=1.0, dtype='float'):
#         super(Uniform, self).__init__()
#         self.low = low
#         self.high = high
#         self.dtype = dtype
# 
#     def sample(self):
#         res = self.rng.uniform(self.low, self.high)
#         if 'fl' in self.dtype:
#             return res
#         return int(res)
# 
# Path: randopt/experiment/experiment.py
# ATTACHMENT_DIR = '_attachments'
# ATTACHMENT_EXT = '.pk'
# class SummaryList(list):
# class JSONSummary(dict):
# class Experiment(object):
#     def __init__(self, results):
#     def __getitem__(self, key):
#     def __getslice__(self, i, j):
#     def __str__(self):
#     def count(self):
#     def filter(self, fn):
#     def values(self, key='result'):
#     def map(self, fn, key='result'):
#     def min(self, key='result'):
#     def max(self, key='result'):
#     def mean(self, key='result'):
#     def variance(self, key='result'):
#     def std(self, key='result'):
#     def median(self, key='result'):
#     def __init__(self, path):
#     def __getattr__(self, attr):
#     def __str__(self):
#     def _load_attachment(self):
#     def __getstate__(self):
#     def __setstate__(self, state):
#     def __init__(self, name, params={}, directory='randopt_results'):
#     def current(self):
#     def _search(self, fn=leq):
#     def top(self, count, fn=leq):
#     def maximum(self):
#     def minimum(self):
#     def all(self):
#     def list(self):
#     def count(self):
#     def seed(self, seed):
#     def set(self, key, value):
#     def sample(self, key):
#     def sample_all_params(self):
#     def add_result(self, result, data=None, attachment=None):
#     def all_results(self):
#     def save_state(self, path):
#     def set_state(self, path):


# Path: randopt/experiment/hyperband.py
import os
import random
    import ujson as json
    import json
    import cPickle as pk
    import pickle as pk
from time import time
from math import log, ceil
from collections import namedtuple
from randopt.samplers import Uniform
from .experiment import Experiment, leq, geq

#!/usr/bin/env python3

try:
except ImportError:
try:
except ImportError:





class HyperBand(Experiment):