code: def plot_state_histogram(result: trial_result.TrialResult) -> np.ndarray:
      
  
      # pyplot import is deferred because it requires a system dependency
      # (python3-tk) that `python -m pip install cirq` can't handle for the user.
      # This allows cirq to be usable without python3-tk.
      import matplotlib.pyplot as plt
  
      num_qubits = len(result.measurements.keys())
      states = 2**num_qubits
      values = np.zeros(states)
  
      # measurements is a dict of {measurement gate key:
      #                            array(repetitions, boolean result)}
      # Convert this to an array of repetitions, each with an array of booleans.
      # e.g. {q1: array([[True, True]]), q2: array([[False, False]])}
      #      --> array([[True, False], [True, False]])
      measurement_by_result = np.array([
          v.transpose()[0] for k, v in result.measurements.items()]).transpose()
  
      for meas in measurement_by_result:
          # Convert each array of booleans to a string representation.
          # e.g. [True, False] -> [1, 0] -> '10' -> 2
          state_ind = int(''.join([str(x) for x in [int(x) for x in meas]]), 2)
          values[state_ind] += 1
  
      plot_labels = [bin(x)[2:].zfill(num_qubits) for x in range(states)]
      plt.bar(np.arange(states), values, tick_label=plot_labels)
      plt.xlabel('qubit state')
      plt.ylabel('result count')
      plt.show()
  
      return values
docs: Plot the state histogram from a single result with repetitions.
  
      States is a bitstring representation of all the qubit states in a single
      result.
      Currently this function assumes each measurement gate applies to only
      a single qubit.
  
      Args:
          result: The trial results to plot.
  
      Returns:
          The histogram. A list of values plotted on the y-axis.