Traceback (most recent call last):
  File "/opt/anaconda3/lib/python3.8/site-packages/jupyter_cache/executors/utils.py", line 51, in single_nb_execution
    executenb(
  File "/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 1087, in execute
    return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute()
  File "/opt/anaconda3/lib/python3.8/site-packages/nbclient/util.py", line 74, in wrapped
    return just_run(coro(*args, **kwargs))
  File "/opt/anaconda3/lib/python3.8/site-packages/nbclient/util.py", line 53, in just_run
    return loop.run_until_complete(coro)
  File "/opt/anaconda3/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete
    return future.result()
  File "/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 540, in async_execute
    await self.async_execute_cell(
  File "/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 832, in async_execute_cell
    self._check_raise_for_error(cell, exec_reply)
  File "/opt/anaconda3/lib/python3.8/site-packages/nbclient/client.py", line 740, in _check_raise_for_error
    raise CellExecutionError.from_cell_and_msg(cell, exec_reply['content'])
nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
------------------
 # Filtering
fig, ax = plt.subplots()
plot_inference(filtered_dist, z_hist, ax)
ax.set_ylabel("p(loaded)")
ax.set_title("Filtered")
 

  
------------------

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-17-a3a9c11b46bd> in <module>
      1 # Filtering
      2 fig, ax = plt.subplots()
----> 3 plot_inference(filtered_dist, z_hist, ax)
      4 ax.set_ylabel("p(loaded)")
      5 ax.set_title("Filtered")

<ipython-input-16-9c8ddad3f57c> in plot_inference(inference_values, z_hist, ax, state, map_estimate)
      3     n_samples = len(inference_values)
      4     xspan = np.arange(1, n_samples + 1)
----> 5     spans = find_dishonest_intervals(z_hist)
      6     if map_estimate:
      7         ax.step(xspan, inference_values, where="post")

<ipython-input-15-4606c615e17a> in find_dishonest_intervals(z_hist)
      4     x_init = 0
      5     for t, _ in enumerate(z_hist[:-1]):
----> 6         if z_hist[t + 1] == 0 and z_hist[t] == 1:
      7             x_end = t
      8             spans.append((x_init, x_end))

/opt/anaconda3/lib/python3.8/functools.py in _method(cls_or_self, *args, **keywords)
    397         def _method(cls_or_self, /, *args, **keywords):
    398             keywords = {**self.keywords, **keywords}
--> 399             return self.func(cls_or_self, *self.args, *args, **keywords)
    400         _method.__isabstractmethod__ = self.__isabstractmethod__
    401         _method._partialmethod = self

/opt/anaconda3/lib/python3.8/site-packages/jax/_src/device_array.py in _forward_method(attrname, self, fun, *args)
     39 
     40 def _forward_method(attrname, self, fun, *args):
---> 41   return fun(getattr(self, attrname), *args)
     42 _forward_to_value = partial(_forward_method, "_value")
     43 

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()