class_docstr: The state of the ensemble during an MCMC run
  
  For backwards compatibility, this will unpack into ``coords, log_prob,
  (blobs), random_state`` when iterated over (where ``blobs`` will only be
  included if it exists and is not ``None``).
  
  Args:
      coords (ndarray[nwalkers, ndim]): The current positions of the walkers
          in the parameter space.
      log_prob (ndarray[nwalkers, ndim], Optional): Log posterior
          probabilities for the  walkers at positions given by ``coords``.
      blobs (Optional): The metadata “blobs” associated with the current
          position. The value is only returned if lnpostfn returns blobs too.
      random_state (Optional): The current state of the random number
          generator.
code: def __init__(
      self,
      coords,
      log_prob=None,
      blobs=None,
      random_state=None,
      copy=False,
  ):
      dc = deepcopy if copy else lambda x: x
  
      if hasattr(coords, "coords"):
          self.coords = dc(coords.coords)
          self.log_prob = dc(coords.log_prob)
          self.blobs = dc(coords.blobs)
          self.random_state = dc(coords.random_state)
          return
  
      self.coords = dc(np.atleast_2d(coords))
      self.log_prob = dc(log_prob)
      self.blobs = dc(blobs)
      self.random_state = dc(random_state)
  
file_path: emcee/src/emcee/state.py
imports: from copy import deepcopy
  import numpy
label_desc: Use image node_id 1 to create a new State object from inherited base classes: object with example: obj = State(coords, log_prob, blobs, random_state, copy)