ensemble_hic/analysis_functions.py
def load_samples(samples_folder, n_replicas, n_samples,
                 dump_interval, burnin, interval=1):
    """Loads full results of a Replica Exchange
    simulation.

    :param samples_folder: directory in which samples are stored
    :type samples_folder: str ending with a slash ("/")

    :param n_replicas: number of replicas
    :type n_replicas: int

    :param n_samples: number of samples
    :type n_samples: int

    :param dump_interval: number of MCMC steps after which samples are written
    :type dump_interval: int

    :param burnin: number of MCMC samples discarded as burnin
    :type burnin: int (multiple of dump_interval)

    :param interval: return only every interval-th sample
    :type interval: int

    :returns: a two-dimensional array of MCMC samples with the first axis being
              the replicas and the second axis the samples for a given replica
    :rtype: :class:`numpy.ndarray`
    """

    samples = []
    for i in xrange(1, n_replicas + 1):
        samples.append(load_sr_samples(samples_folder, i, n_samples, dump_interval,
                                       burnin, interval))
        
    return np.array(samples)
Loads full results of a Replica Exchange
    simulation.

    :param samples_folder: directory in which samples are stored
    :type samples_folder: str ending with a slash ("/")

    :param n_replicas: number of replicas
    :type n_replicas: int

    :param n_samples: number of samples
    :type n_samples: int

    :param dump_interval: number of MCMC steps after which samples are written
    :type dump_interval: int

    :param burnin: number of MCMC samples discarded as burnin
    :type burnin: int (multiple of dump_interval)

    :param interval: return only every interval-th sample
    :type interval: int

    :returns: a two-dimensional array of MCMC samples with the first axis being
              the replicas and the second axis the samples for a given replica
    :rtype: :class:`numpy.ndarray`
    
Loads full results of a Replica Exchange
simulation.
Loads full results of a Replica Exchange simulation .
def load_samples(samples_folder, n_replicas, n_samples,
                 dump_interval, burnin, interval=1):
    samples = []
    for i in xrange(1, n_replicas + 1):
        samples.append(load_sr_samples(samples_folder, i, n_samples, dump_interval,
                                       burnin, interval))
    return np.array(samples)
def load_samples ( samples_folder , n_replicas , n_samples , dump_interval , burnin , interval = 1 ) : samples = [ ] for i in xrange ( 1 , n_replicas + 1 ) : samples . append ( load_sr_samples ( samples_folder , i , n_samples , dump_interval , burnin , interval ) ) return np . array ( samples )
Loads full results of a Replica Exchange
simulation.
Loads full results of a Replica Exchange simulation .
"""Loads full results of a Replica Exchange
    simulation.

    :param samples_folder: directory in which samples are stored
    :type samples_folder: str ending with a slash ("/")

    :param n_replicas: number of replicas
    :type n_replicas: int

    :param n_samples: number of samples
    :type n_samples: int

    :param dump_interval: number of MCMC steps after which samples are written
    :type dump_interval: int

    :param burnin: number of MCMC samples discarded as burnin
    :type burnin: int (multiple of dump_interval)

    :param interval: return only every interval-th sample
    :type interval: int

    :returns: a two-dimensional array of MCMC samples with the first axis being
              the replicas and the second axis the samples for a given replica
    :rtype: :class:`numpy.ndarray`
    """
a two-dimensional array of MCMC samples with the first axis being
the replicas and the second axis the samples for a given replica
a two - dimensional array of MCMC samples with the first axis being the replicas and the second axis the samples for a given replica
:class:`numpy.ndarray`
samples_folder
directory in which samples are stored
directory in which samples are stored
n_replicas
number of replicas
number of replicas
n_samples
number of samples
number of samples
dump_interval
number of MCMC steps after which samples are written
number of MCMC steps after which samples are written
burnin
number of MCMC samples discarded as burnin
number of MCMC samples discarded as burnin
interval
return only every interval-th sample
return only every interval - th sample