color_continuous_scale incompatible with marginal distributions in density_heatmap

I was trying out the examples from https://plotly.com/python/2D-Histogram/ and wanted to use the density heat map with marginal distribution on x and y but wanted to change the colour map to align with some previous work.
I found when combining the two subsequent examples from the 2D-Histogram page I got an error. If the marginal distribution and color_continuous_scale aren't meant to be used together there should at least be a better error message.
I btw also test other kinds of distributions like box, violin and rug with the same result.

plotly Version: 5.17.0

My code:

import plotly.express as px
df = px.data.tips()

fig = px.density_heatmap(df, x="total_bill", y="tip", nbinsx=20, nbinsy=20, marginal_x="histogram", marginal_y="histogram", color_continuous_scale="Viridis")
fig.show()

Traceback:

ValueError                                Traceback (most recent call last)
[/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/attention_weight_event_viewer.ipynb](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/attention_weight_event_viewer.ipynb) Cell 10 line 4
      [1](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a226865705f475055227d/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/attention_weight_event_viewer.ipynb#Y130sdnNjb2RlLXJlbW90ZQ%3D%3D?line=0) import plotly.express as px
      [2](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a226865705f475055227d/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/attention_weight_event_viewer.ipynb#Y130sdnNjb2RlLXJlbW90ZQ%3D%3D?line=1) df = px.data.tips()
----> [4](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a226865705f475055227d/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/attention_weight_event_viewer.ipynb#Y130sdnNjb2RlLXJlbW90ZQ%3D%3D?line=3) fig = px.density_heatmap(df, x="total_bill", y="tip", nbinsx=20, nbinsy=20, marginal_y="histogram", color_continuous_scale="Viridis")
      [5](vscode-notebook-cell://ssh-remote%2B7b22686f73744e616d65223a226865705f475055227d/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/attention_weight_event_viewer.ipynb#Y130sdnNjb2RlLXJlbW90ZQ%3D%3D?line=4) fig.show()

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/express/_chart_types.py:187](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/express/_chart_types.py:187), in density_heatmap(data_frame, x, y, z, facet_row, facet_col, facet_col_wrap, facet_row_spacing, facet_col_spacing, hover_name, hover_data, animation_frame, animation_group, category_orders, labels, orientation, color_continuous_scale, range_color, color_continuous_midpoint, marginal_x, marginal_y, opacity, log_x, log_y, range_x, range_y, histfunc, histnorm, nbinsx, nbinsy, text_auto, title, template, width, height)
    145 def density_heatmap(
    146     data_frame=None,
    147     x=None,
   (...)
    180     height=None,
    181 ) -> go.Figure:
    182     """
    183     In a density heatmap, rows of `data_frame` are grouped together into
    184     colored rectangular tiles to visualize the 2D distribution of an
    185     aggregate function `histfunc` (e.g. the count or sum) of the value `z`.
    186     """
--> 187     return make_figure(
    188         args=locals(),
    189         constructor=go.Histogram2d,
    190         trace_patch=dict(
    191             histfunc=histfunc,
    192             histnorm=histnorm,
    193             nbinsx=nbinsx,
    194             nbinsy=nbinsy,
    195             xbingroup="x",
    196             ybingroup="y",
    197         ),
    198     )

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/express/_core.py:2256](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/express/_core.py:2256), in make_figure(args, constructor, trace_patch, layout_patch)
   2251         group[var] = 100.0 * group[var] [/](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/) group_sum
   2253 patch, fit_results = make_trace_kwargs(
   2254     args, trace_spec, group, mapping_labels.copy(), sizeref
   2255 )
-> 2256 trace.update(patch)
   2257 if fit_results is not None:
   2258     trendline_rows.append(mapping_labels.copy())

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:5141](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:5141), in BasePlotlyType.update(self, dict1, overwrite, **kwargs)
   5139         BaseFigure._perform_update(self, kwargs, overwrite=overwrite)
   5140 else:
-> 5141     BaseFigure._perform_update(self, dict1, overwrite=overwrite)
   5142     BaseFigure._perform_update(self, kwargs, overwrite=overwrite)
   5144 return self

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:3921](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:3921), in BaseFigure._perform_update(plotly_obj, update_obj, overwrite)
   3915 validator = plotly_obj._get_prop_validator(key)
   3917 if isinstance(validator, CompoundValidator) and isinstance(val, dict):
   3918 
   3919     # Update compound objects recursively
   3920     # plotly_obj[key].update(val)
-> 3921     BaseFigure._perform_update(plotly_obj[key], val)
   3922 elif isinstance(validator, CompoundArrayValidator):
   3923     if plotly_obj[key]:
   3924         # plotly_obj has an existing non-empty array for key
   3925         # In this case we merge val into the existing elements

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:3942](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:3942), in BaseFigure._perform_update(plotly_obj, update_obj, overwrite)
   3939                 plotly_obj[key] = val
   3940         else:
   3941             # Assign non-compound value
-> 3942             plotly_obj[key] = val
   3944 elif isinstance(plotly_obj, tuple):
   3946     if len(update_obj) == 0:
   3947         # Nothing to do

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:4876](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:4876), in BasePlotlyType.__setitem__(self, prop, value)
   4872         self._set_array_prop(prop, value)
   4874     # ### Handle simple property ###
   4875     else:
-> 4876         self._set_prop(prop, value)
   4877 else:
   4878     # Make sure properties dict is initialized
   4879     self._init_props()

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:5220](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:5220), in BasePlotlyType._set_prop(self, prop, val)
   5218         return
   5219     else:
-> 5220         raise err
   5222 # val is None
   5223 # -----------
   5224 if val is None:
   5225     # Check if we should send null update

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:5215](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/plotly/basedatatypes.py:5215), in BasePlotlyType._set_prop(self, prop, val)
   5212 validator = self._get_validator(prop)
   5214 try:
-> 5215     val = validator.validate_coerce(val)
   5216 except ValueError as err:
   5217     if self._skip_invalid:

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/_plotly_utils/basevalidators.py:1374](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/_plotly_utils/basevalidators.py:1374), in ColorValidator.validate_coerce(self, v, should_raise)
   1372     validated_v = self.vc_scalar(v)
   1373     if validated_v is None and should_raise:
-> 1374         self.raise_invalid_val(v)
   1376     v = validated_v
   1378 return v

File [~/miniconda3/envs/icet2/lib/python3.8/site-packages/_plotly_utils/basevalidators.py:287](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a226865705f475055227d.vscode-resource.vscode-cdn.net/groups/icecube/moust/work/IceCubeEncoderTransformer/notebooks/~/miniconda3/envs/icet2/lib/python3.8/site-packages/_plotly_utils/basevalidators.py:287), in BaseValidator.raise_invalid_val(self, v, inds)
    284             for i in inds:
    285                 name += "[" + str(i) + "]"
--> 287         raise ValueError(
    288             """
    289     Invalid value of type {typ} received for the '{name}' property of {pname}
    290         Received value: {v}
    291 
    292 {valid_clr_desc}""".format(
    293                 name=name,
    294                 pname=self.parent_name,
    295                 typ=type_str(v),
    296                 v=repr(v),
    297                 valid_clr_desc=self.description(),
    298             )
    299         )

ValueError: 
    Invalid value of type 'builtins.str' received for the 'color' property of histogram.marker
        Received value: 'V'

    The 'color' property is a color and may be specified as:
      - A hex string (e.g. '#ff0000')
      - An rgb/rgba string (e.g. 'rgb(255,0,0)')
      - An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
      - An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
      - A named CSS color:
            aliceblue, antiquewhite, aqua, aquamarine, azure,
            beige, bisque, black, blanchedalmond, blue,
            blueviolet, brown, burlywood, cadetblue,
            chartreuse, chocolate, coral, cornflowerblue,
            cornsilk, crimson, cyan, darkblue, darkcyan,
            darkgoldenrod, darkgray, darkgrey, darkgreen,
            darkkhaki, darkmagenta, darkolivegreen, darkorange,
            darkorchid, darkred, darksalmon, darkseagreen,
            darkslateblue, darkslategray, darkslategrey,
            darkturquoise, darkviolet, deeppink, deepskyblue,
            dimgray, dimgrey, dodgerblue, firebrick,
            floralwhite, forestgreen, fuchsia, gainsboro,
            ghostwhite, gold, goldenrod, gray, grey, green,
            greenyellow, honeydew, hotpink, indianred, indigo,
            ivory, khaki, lavender, lavenderblush, lawngreen,
            lemonchiffon, lightblue, lightcoral, lightcyan,
            lightgoldenrodyellow, lightgray, lightgrey,
            lightgreen, lightpink, lightsalmon, lightseagreen,
            lightskyblue, lightslategray, lightslategrey,
            lightsteelblue, lightyellow, lime, limegreen,
            linen, magenta, maroon, mediumaquamarine,
            mediumblue, mediumorchid, mediumpurple,
            mediumseagreen, mediumslateblue, mediumspringgreen,
            mediumturquoise, mediumvioletred, midnightblue,
            mintcream, mistyrose, moccasin, navajowhite, navy,
            oldlace, olive, olivedrab, orange, orangered,
            orchid, palegoldenrod, palegreen, paleturquoise,
            palevioletred, papayawhip, peachpuff, peru, pink,
            plum, powderblue, purple, red, rosybrown,
            royalblue, rebeccapurple, saddlebrown, salmon,
            sandybrown, seagreen, seashell, sienna, silver,
            skyblue, slateblue, slategray, slategrey, snow,
            springgreen, steelblue, tan, teal, thistle, tomato,
            turquoise, violet, wheat, white, whitesmoke,
            yellow, yellowgreen
      - A number that will be interpreted as a color
        according to histogram.marker.colorscale
      - A list or array of any of the above

Bắt đầu tại plotly/express/_chart_types.py ở density_heatmap và theo dõi make_figure trong plotly/express/_core.py, sử dụng ví dụ được cung cấp với marginal và color_continuous_scale để tái hiện lỗi. Xác định xem tổ hợp này có nên hoạt động hay tạo ra một lỗi có chủ đích, sau đó xác minh rằng hành vi thu được bao quát các marginal histogram, box, violin và rug đã được báo cáo.