Source code for espressomd.cluster_analysis

# Copyright (C) 2010-2019 The ESPResSo project
#
# This file is part of ESPResSo.
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# ESPResSo is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
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# ESPResSo is distributed in the hope that it will be useful,
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from .script_interface import ScriptInterfaceHelper, script_interface_register
from .particle_data import ParticleHandle, ParticleSlice


[docs]@script_interface_register class Cluster(ScriptInterfaceHelper): """Class representing a cluster of particles. Methods ------- particle_ids() Returns list of particle ids in the cluster size() Returns the number of particles in the cluster center_of_mass() Center of mass of the cluster longest_distance() Longest distance between any combination of two particles in the cluster fractal_dimension(dr=None) Estimates the cluster's fractal dimension by fitting the number of particles :math:`n` in spheres of growing radius around the center of mass to :math:`c*r_g^d`, where :math:`r_g` is the radius of gyration of the particles within the sphere, and :math:`d` is the fractal dimension. .. note:: Requires ``GSL`` external feature, enabled with ``-DWITH_GSL=ON``. Parameters ---------- dr: :obj:`float` Minimum increment for the radius of the spheres. Returns ------- :obj:`tuple`: Fractal dimension and mean square residual. """ _so_name = "ClusterAnalysis::Cluster" _so_bind_methods = ("particle_ids", "size", "longest_distance", "radius_of_gyration", "fractal_dimension", "center_of_mass") _so_creation_policy = "LOCAL"
[docs] def particles(self): """ Get particles in the cluster. Returns ------- :class:`espressomd.particle_data.ParticleSlice` """ return ParticleSlice(self.particle_ids())
[docs]@script_interface_register class ClusterStructure(ScriptInterfaceHelper): """Cluster structure of a simulation system, and access to cluster analysis Parameters ---------- pair_criterion: :class:`espressomd.pair_criteria._PairCriterion` Criterion to decide whether two particles are neighbors. """ _so_name = "ClusterAnalysis::ClusterStructure" _so_creation_policy = "LOCAL" def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._clusters = Clusters(self)
[docs] def run_for_all_pairs(self): """ Runs the cluster analysis, considering all pairs of particles in the system """ return self.call_method("run_for_all_pairs")
[docs] def run_for_bonded_particles(self): """ Runs the cluster analysis, considering only pairs of particles connected by a pair-bond. """ return self.call_method("run_for_bonded_particles")
[docs] def clear(self): """ Clears the cluster structure. """ return self.call_method("clear")
[docs] def cluster_ids(self): """ Returns a list of all cluster ids of the clusters in the structure. """ return self.call_method("cluster_ids")
[docs] def cid_for_particle(self, p): """Returns cluster id for the particle. Parameters ---------- p : :obj:`espressomd.particle_data.ParticleHandle` or :obj:`int` containing the particle id Particle. """ if isinstance(p, ParticleHandle): return self.call_method("cid_for_particle", pid=p.id) if isinstance(p, int): return self.call_method("cid_for_particle", pid=p) raise TypeError( "The particle has to be passed as instance of ParticleHandle or as an integer particle id")
@property def clusters(self): """Gives access to the clusters in the cluster structure via an instance of :class:`Clusters`.""" return self._clusters
[docs]class Clusters: """Access to the clusters in the cluster structure. Access is as follows: * number of clusters: ``len(clusters)`` * access a cluster via its id: ``clusters[id]`` * iterate over clusters:: for c in clusters: where ``c`` will be a tuple containing the cluster id and the cluster object. """ def __init__(self, cluster_structure): self.cluster_structure = cluster_structure def __getitem__(self, cluster_id): return self.cluster_structure.call_method("get_cluster", id=cluster_id) def __iter__(self): for cid in self.cluster_structure.cluster_ids(): yield (cid, self.cluster_structure.call_method("get_cluster", id=cid)) def __len__(self): return self.cluster_structure.call_method("n_clusters")