Hello,

First of all thanks for this great package.

Today, I got the following error while importing molplotly whereas I previously had no issue: ImportError: cannot import name 'Input' from 'dash'

As my version of dash was a bit old 1.6 I believe, I upgraded it to version 2.3.0 via pip. The import error disappeared but I had another error when trying to run the server "app.run_server(mode='inline', port=8003, height=800)": AttributeError: ('Read-only: can only be set in the Dash constructor or during init_app()', 'requests_pathname_prefix')

I have managed to get around by downgrading dash to version 2.0.0 as recommended here https://stackoverflow.com/questions/70908709/jupyterdash-app-run-server-error-using-jupyter-notebook, but there may be something to look into...

Thanks again

Great idea this package! I however ran into an issue during installation: UnicodeDecodeError: 'charmap' codec can't decode byte 0x8f in position 1822: character maps to <undefined> This is certainly due to unusal characters in the readme, since I could install the package locally by editing the readme file. Cheers!

Is there some reason for the very specific version requirements for the dependencies? For the pip install I would loosen this up unless there are any particular known issues.

Best not to wait too long to start testing. Here's a basic scaffold to get started.

Probably shouldn't be merged as is but y'all can push more commits here to get this in shape.

Hi! I have a small dash app that I use to explore the molecules present in different samples. It is possible to select the samples of interest and then display a plotly scatter plot generated using the structures. I tried to add the molplotly layer on the scatter plot but no molecules are displayed. Any experience on that? Thanks!

Hi there, thanks for providing a great and easy to use tool!

This issue is reproducible with the first example in the documentation:

df_esol['delY'] = df_esol["y_pred"] - df_esol["y_true"]
fig_scatter = px.scatter(df_esol,
                         x="y_true",
                         y="y_pred",
                         color='delY',
                         marker='Minimum Degree', # <- addition
                         title='ESOL Regression (default plotly)',
                         labels={'y_pred': 'Predicted Solubility',
                                 'y_true': 'Measured Solubility',
                                 'delY': 'ΔY'},
                         width=1200,
                         height=800)

# This adds a dashed line for what a perfect model _should_ predict
y = df_esol["y_true"].values
fig_scatter.add_shape(
    type="line", line=dict(dash='dash'),
    x0=y.min(), y0=y.min(),
    x1=y.max(), y1=y.max()
)

fig_scatter.update_layout(title='ESOL Regression (with add_molecules!)')

app_scatter = molplotly.add_molecules(fig=fig_scatter,
                                      df=df_esol,
                                      smiles_col='smiles',
                                      title_col='Compound ID',
                                      color_col='delY' # <- addition
                                      )

# change the arguments here to run the dash app on an external server and/or change the size of the app!
app_scatter.run_server(mode='inline', port=8001, height=1000)

This returns

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
~/anaconda3/envs/ml/lib/python3.7/site-packages/molplotly/main.py in display_hover(
    hoverData={'points': [{'bbox': {'x0': 948.39, 'x1': 950.39, 'y0': 177.7, 'y1': 179.7}, 'curveNumber': 0, 'marker.color': -0.48000000000000004, 'pointIndex': 960, 'pointNumber': 960, 'x': 0.79, 'y': 0.31}]}
)
    111             df_curve = df[df[color_col] ==
    112                           curve_dict[curve_num]].reset_index(drop=True)
--> 113             df_row = df_curve.iloc[num]
        df_row = undefined
        df_curve.iloc = <pandas.core.indexing._iLocIndexer object at 0x7f7e3d16c950>
        num = 960
    114         else:
    115             df_row = df.iloc[num]

~/anaconda3/envs/ml/lib/python3.7/site-packages/pandas/core/indexing.py in __getitem__(
    self=<pandas.core.indexing._iLocIndexer object>,
    key=960
)
    929 
    930             maybe_callable = com.apply_if_callable(key, self.obj)
--> 931             return self._getitem_axis(maybe_callable, axis=axis)
        self._getitem_axis = <bound method _iLocIndexer._getitem_axis of <pandas.core.indexing._iLocIndexer object at 0x7f7e3d490c50>>
        maybe_callable = 960
        axis = 0
    932 
    933     def _is_scalar_access(self, key: tuple):

~/anaconda3/envs/ml/lib/python3.7/site-packages/pandas/core/indexing.py in _getitem_axis(
    self=<pandas.core.indexing._iLocIndexer object>,
    key=960,
    axis=0
)
   1564 
   1565             # validate the location
-> 1566             self._validate_integer(key, axis)
        self._validate_integer = <bound method _iLocIndexer._validate_integer of <pandas.core.indexing._iLocIndexer object at 0x7f7e3d490c50>>
        key = 960
        axis = 0
   1567 
   1568             return self.obj._ixs(key, axis=axis)

~/anaconda3/envs/ml/lib/python3.7/site-packages/pandas/core/indexing.py in _validate_integer(
    self=<pandas.core.indexing._iLocIndexer object>,
    key=960,
    axis=0
)
   1498         len_axis = len(self.obj._get_axis(axis))
   1499         if key >= len_axis or key < -len_axis:
-> 1500             raise IndexError("single positional indexer is out-of-bounds")
        global IndexError = undefined
   1501 
   1502     # -------------------------------------------------------------------

IndexError: single positional indexer is out-of-bounds

Using either only marker or color alone causes no issues with the hoverbox. Also, using Minimum Degree as color_col for add_molecules when both color and symbol are defined gives no issues.

Thanks for the great library, really useful!

You pinned the pandas version to ~=1.4.1 which effectively cuts of users that use python<3.7. See the pandas release notes: https://pandas.pydata.org/docs/whatsnew/v1.4.0.html

Is this intentional? Which novel features from pandas >1.4.0 are strictly necessary to keep the package running? I'll create a PR with a relaxed pandas requirements that works fine for me in a python3.7 env.

I find list of parameters easier to parse in a table than as list. Here's what that would look like. If you think it's an improvement, could consider joining type and default columns to save horizontal space.

After

Before

Implemented support for specifying multiple smiles in the smiles_col argument for molplotly.add_molecules:

• When a single str argument is passed to smiles_col, the function behaves as before.
• When a list is passed, a slider is created under the plot, which allows the user to decide which column to use to render molecules.

Also changed the ports in the example.ipynb to start from 8700 and go up. On my system 8000 and 8001 were reserverd already.

When trying to use molplotly to generate hover structures with a series of scatterplots generated using make_subplots (generated using different columns of a dataframe for the same RDKit molecule row), molplotly.add_molecules returns

ValueError: More than one plotly curve in figure - color_col and/or marker_col needs to be specified.

As these plots are generated using different columns, rather than faceting data in a single column based on values in another, there is no common color or marker column. Is there a way to generate molecular structures for these subplots?

Hello everyone,

My name is Judith and for my PhD studies, I would like to use your beautiful scripts. I get a distance matrix by rmsd between each pose but I don't see how to pass it to a scatter plot of 2 clusters, I tried with pandas but I'm really blocked, I can't select the lines and the columns to generate the scatter plot

Best Regards, Judith

Thanks for the great package!

It would be fantastic if the interactive plots could be exported/saved. I understand that this is non-trvial in plotly, but other libraries like mpl3d also allow to export as interactive HTML or SVG. See here for an exemplary plot. Also TMAP and Faerun support this natively. I think it will be a heavily sought-after feature for real usability of this package.

Possible solutions:

• separate integration building on top of mpl3d (seems overkill, might be the last resort)
• Building upon this gist to export the Dash as HTML: https://gist.github.com/exzhawk/33e5dcfc8859e3b6ff4e5269b1ba0ba4
• Faerun-style solution, see here: https://github.com/reymond-group/faerun-python