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plotly.graph_objects.FigureWidget does not support NaN or Inf due to JSON limitations #3470
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To get it work, replace np.nan with None:
|
@empet ---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/tmp/ipykernel_129118/530834281.py in <module>
1 z = np.random.uniform(0, 1, size=(10, 10))
2 z[z < 0.5] = None
----> 3 fig = go.FigureWidget(go.Heatmap(z=z))
4 fig.update_layout(template="plotly_white", xaxis_showgrid=False, yaxis_showgrid=False,
5 xaxis_zeroline=False, yaxis_zeroline=False)
~/anaconda3/lib/python3.8/site-packages/plotly/graph_objs/_figurewidget.py in __init__(self, data, layout, frames, skip_invalid, **kwargs)
588 is invalid AND skip_invalid is False
589 """
--> 590 super(FigureWidget, self).__init__(data, layout, frames, skip_invalid, **kwargs)
591
592 def add_bar(
~/anaconda3/lib/python3.8/site-packages/plotly/basewidget.py in __init__(self, data, layout, frames, skip_invalid, **kwargs)
115 # with the `layout` constructor parameter of the `widgets.DOMWidget`
116 # ipywidgets class
--> 117 super(BaseFigureWidget, self).__init__(
118 data=data,
119 layout_plotly=layout,
~/anaconda3/lib/python3.8/site-packages/plotly/basedatatypes.py in __init__(self, data, layout_plotly, frames, skip_invalid, **kwargs)
524 # The _data property is a list of dicts containing the properties
525 # explicitly set by the user for each trace.
--> 526 self._data = [deepcopy(trace._props) for trace in data]
527
528 # ### Create data defaults ###
~/anaconda3/lib/python3.8/site-packages/plotly/basedatatypes.py in __setattr__(self, prop, value)
719 if prop.startswith("_") or hasattr(self, prop):
720 # Let known properties and private properties through
--> 721 super(BaseFigure, self).__setattr__(prop, value)
722 else:
723 # Raise error on unknown public properties
~/anaconda3/lib/python3.8/site-packages/traitlets/traitlets.py in __set__(self, obj, value)
604 raise TraitError('The "%s" trait is read-only.' % self.name)
605 else:
--> 606 self.set(obj, value)
607
608 def _validate(self, obj, value):
~/anaconda3/lib/python3.8/site-packages/traitlets/traitlets.py in set(self, obj, value)
2649 return super().set(obj, [value])
2650 else:
-> 2651 return super().set(obj, value)
2652
2653
~/anaconda3/lib/python3.8/site-packages/traitlets/traitlets.py in set(self, obj, value)
593 # we explicitly compare silent to True just in case the equality
594 # comparison above returns something other than True/False
--> 595 obj._notify_trait(self.name, old_value, new_value)
596
597 def __set__(self, obj, value):
~/anaconda3/lib/python3.8/site-packages/traitlets/traitlets.py in _notify_trait(self, name, old_value, new_value)
1217
1218 def _notify_trait(self, name, old_value, new_value):
-> 1219 self.notify_change(Bunch(
1220 name=name,
1221 old=old_value,
~/anaconda3/lib/python3.8/site-packages/ipywidgets/widgets/widget.py in notify_change(self, change)
603 if name in self.keys and self._should_send_property(name, getattr(self, name)):
604 # Send new state to front-end
--> 605 self.send_state(key=name)
606 super(Widget, self).notify_change(change)
607
~/anaconda3/lib/python3.8/site-packages/ipywidgets/widgets/widget.py in send_state(self, key)
487 state, buffer_paths, buffers = _remove_buffers(state)
488 msg = {'method': 'update', 'state': state, 'buffer_paths': buffer_paths}
--> 489 self._send(msg, buffers=buffers)
490
491
~/anaconda3/lib/python3.8/site-packages/ipywidgets/widgets/widget.py in _send(self, msg, buffers)
735 """Sends a message to the model in the front-end."""
736 if self.comm is not None and self.comm.kernel is not None:
--> 737 self.comm.send(data=msg, buffers=buffers)
738
739 def _repr_keys(self):
~/anaconda3/lib/python3.8/site-packages/ipykernel/comm/comm.py in send(self, data, metadata, buffers)
120 def send(self, data=None, metadata=None, buffers=None):
121 """Send a message to the frontend-side version of this comm"""
--> 122 self._publish_msg('comm_msg',
123 data=data, metadata=metadata, buffers=buffers,
124 )
~/anaconda3/lib/python3.8/site-packages/ipykernel/comm/comm.py in _publish_msg(self, msg_type, data, metadata, buffers, **keys)
64 metadata = {} if metadata is None else metadata
65 content = json_clean(dict(data=data, comm_id=self.comm_id, **keys))
---> 66 self.kernel.session.send(self.kernel.iopub_socket, msg_type,
67 content,
68 metadata=json_clean(metadata),
~/anaconda3/lib/python3.8/site-packages/jupyter_client/session.py in send(self, stream, msg_or_type, content, parent, ident, buffers, track, header, metadata)
828 if self.adapt_version:
829 msg = adapt(msg, self.adapt_version)
--> 830 to_send = self.serialize(msg, ident)
831 to_send.extend(buffers)
832 longest = max([len(s) for s in to_send])
~/anaconda3/lib/python3.8/site-packages/jupyter_client/session.py in serialize(self, msg, ident)
702 content = self.none
703 elif isinstance(content, dict):
--> 704 content = self.pack(content)
705 elif isinstance(content, bytes):
706 # content is already packed, as in a relayed message
~/anaconda3/lib/python3.8/site-packages/jupyter_client/session.py in json_packer(obj)
93
94 def json_packer(obj):
---> 95 return jsonapi.dumps(
96 obj,
97 default=json_default,
~/anaconda3/lib/python3.8/site-packages/zmq/utils/jsonapi.py in dumps(o, **kwargs)
23 Keyword arguments are passed along to :py:func:`json.dumps`.
24 """
---> 25 return json.dumps(o, **kwargs).encode("utf8")
26
27
~/anaconda3/lib/python3.8/json/__init__.py in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
232 if cls is None:
233 cls = JSONEncoder
--> 234 return cls(
235 skipkeys=skipkeys, ensure_ascii=ensure_ascii,
236 check_circular=check_circular, allow_nan=allow_nan, indent=indent,
~/anaconda3/lib/python3.8/json/encoder.py in encode(self, o)
197 # exceptions aren't as detailed. The list call should be roughly
198 # equivalent to the PySequence_Fast that ''.join() would do.
--> 199 chunks = self.iterencode(o, _one_shot=True)
200 if not isinstance(chunks, (list, tuple)):
201 chunks = list(chunks)
~/anaconda3/lib/python3.8/json/encoder.py in iterencode(self, o, _one_shot)
255 self.key_separator, self.item_separator, self.sort_keys,
256 self.skipkeys, _one_shot)
--> 257 return _iterencode(o, 0)
258
259 def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,
ValueError: Out of range float values are not JSON compliant I am using plotly-5.3.1 from the plotly conda channel. EDIT: Maybe I should specify that I am running the notebook on Visual Studio Code |
Ok, I managed to solve the problem with the following workaround: z = np.random.uniform(0, 1, size=(10, 10))
z[z < 0.5] = np.nan
z = np.asarray(z,dtype=object)
z[np.isnan(z.astype(np.float_))] = None
fig = go.FigureWidget(go.Heatmap(z=z))
fig.update_layout(template="plotly_white", xaxis_showgrid=False, yaxis_showgrid=False,
xaxis_zeroline=False, yaxis_zeroline=False) Basically, if you have a numpy array of floats, by default To have a numpy array with If I may, this is a bit inconvenient, as I will have to write some pre-processing functions before creating the plots. Would it be possible to have an internal check/converter in plotly so that numpy arrays can get pre-processed before having them sent to the JSON python package? |
@carlidel this is indeed annoying, and we have some support for automatically handling these values. I wonder if you have a very-recent version of numpy which has new/different representations? Could you tell me which versions of Python, numpy, scipy and/or pandas you have installed please? |
Hello @nicolaskruchten , From my conda list I get, specifically:
Edit: I should highlight that I got this weird behavior with go.FigureWidget only, go.Figure works perfectly. |
Hello everyone.
I'm trying to plot some interactive heatmaps on a Jupyter Notebook using Ipywidgets and FigureWidget.
These heatmaps, by design, will contain some NaN values that needs to be "not plotted" as such. From this point of view, my previous experience of
go.Figure
was perfect.However, when trying to use FigureWidget, I get the
ValueError: Out of range float values are not JSON compliant
, as JSON base standard is not able to serialize Infs or NaNs. Is it possible to avoid this limitation somehow?A minimal example to execute in a notebook:
The full text of the error message from my personal notebook:
Thanks!
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