class_docstr: A backend that stores the chain in an HDF5 file using h5py
  
  .. note:: You must install `h5py <http://www.h5py.org/>`_ to use this
      backend.
  
  Args:
      filename (str): The name of the HDF5 file where the chain will be
          saved.
      name (str; optional): The name of the group where the chain will
          be saved.
      read_only (bool; optional): If ``True``, the backend will throw a
          ``RuntimeError`` if the file is opened with write access.
class_docstr_tok: ["A","backend","that","stores","the","chain","in","an","HDF5","file","using","h5py","..","note",":",":","You","must","install","`","h5py","<","http",":","\/\/www.h5py.org\/",">","`","_","to","use","this","backend",".","Args",":","filename","(","str",")",":","The","name","of","the","HDF5","file","where","the","chain","will","be","saved",".","name","(","str",";","optional",")",":","The","name","of","the","group","where","the","chain","will","be","saved",".","read_only","(","bool",";","optional",")",":","If","``","True","``",",","the","backend","will","throw","a","``","RuntimeError","``","if","the","file","is","opened","with","write","access","."]
docstr: Clear the state of the chain and empty the backend
  
  Args:
      nwakers (int): The size of the ensemble
      ndim (int): The number of dimensions
docstr_tok: ["Clear","the","state","of","the","chain","and","empty","the","backend","Args",":","nwakers","(","int",")",":","The","size","of","the","ensemble","ndim","(","int",")",":","The","number","of","dimensions"]
code: def reset(self, nwalkers, ndim):
      """Clear the state of the chain and empty the backend
  
      Args:
          nwakers (int): The size of the ensemble
          ndim (int): The number of dimensions
  
      """
      with self.open("a") as f:
          if self.name in f:
              del f[self.name]
  
          g = f.create_group(self.name)
          g.attrs["version"] = __version__
          g.attrs["nwalkers"] = nwalkers
          g.attrs["ndim"] = ndim
          g.attrs["has_blobs"] = False
          g.attrs["iteration"] = 0
          g.create_dataset(
              "accepted",
              data=np.zeros(nwalkers),
              compression=self.compression,
              compression_opts=self.compression_opts,
          )
          g.create_dataset(
              "chain",
              (0, nwalkers, ndim),
              maxshape=(None, nwalkers, ndim),
              dtype=self.dtype,
              compression=self.compression,
              compression_opts=self.compression_opts,
          )
          g.create_dataset(
              "log_prob",
              (0, nwalkers),
              maxshape=(None, nwalkers),
              dtype=self.dtype,
              compression=self.compression,
              compression_opts=self.compression_opts,
          )
  
imports: from __future__ import division, print_function
  import os
  from tempfile import NamedTemporaryFile
  import numpy
  from ..None import __version__
  from .backend import Backend
label_desc: Use image node_id 4 for calling the HDFBackend obj's underlying member method code with example usage: obj.reset(nwalkers, ndim) without return types