wjm41 / molplotly Goto Github PK

Thanks for the great package!

I am interested in integrating a scatterplot with the 3D structures of my molecules in an existing Dash app. What would be the best way to do this (if it's even possible), considering that the add_molecules() function already returns a Dash app?

Thanks for your help! :)

Edit: My bad, didn't saw issue #15 !

Hi there,

With this code, I am seeing the interactive plot appear twice:

# generate a scatter plot
fig = px.scatter(plot_df, x="umap1", y="umap2", width=600, height=600)

# add molecules to the plotly graph - returns a Dash app
app = molplotly.add_molecules(fig=fig,
                            df=plot_df,
                            smiles_col='smiles'
                            )

# run Dash app inline in notebook (or in an external server)
app.run_server(mode='inline', port=8701, height=650)

Also, when I re-rerun this cell in Jupyter Lab, I get this error:

/Users/kwaneu/sw/miniconda/miniconda3/envs/python/lib/python3.11/site-packages/dash/dash.py:516: UserWarning:

JupyterDash is deprecated, use Dash instead.
See https://dash.plotly.com/dash-in-jupyter for more details.

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[49], line 11
      5 app = molplotly.add_molecules(fig=fig,
      6                             df=plot_df,
      7                             smiles_col='smiles'
      8                             )
     10 # run Dash app inline in notebook (or in an external server)
---> 11 app.run_server(mode='inline', port=8701, height=650) # height should be height+50

File ~/sw/miniconda/miniconda3/envs/python/lib/python3.11/site-packages/jupyter_dash/jupyter_app.py:222, in JupyterDash.run_server(self, mode, width, height, inline_exceptions, **kwargs)
    220 old_server = self._server_threads.get((host, port))
    221 if old_server:
--> 222     old_server.kill()
    223     old_server.join()
    224     del self._server_threads[(host, port)]

File ~/sw/miniconda/miniconda3/envs/python/lib/python3.11/site-packages/jupyter_dash/_stoppable_thread.py:16, in StoppableThread.kill(self)
     13 def kill(self):
     14     thread_id = self.get_id()
     15     res = ctypes.pythonapi.PyThreadState_SetAsyncExc(
---> 16         ctypes.c_long(thread_id), ctypes.py_object(SystemExit)
     17     )
     18     if res == 0:
     19         raise ValueError(f"Invalid thread id: {thread_id}")

TypeError: 'NoneType' object cannot be interpreted as an integer

Thanks!

The most recent addition which support reaction smiles visualizations have not been deployed to pypi

Hi,

Thanks for sharing this, it's great!

Is there a way to display mols in a stacked bar plot? The stacked bars use separate columns for the y-axis, not a shared facet column.

Or are there any examples where it's used on more than one trace per plot (like add_trace with plotly go)?

Attached some plotly code and a test set if that helps!

Thanks,

fig=px.bar(
    data_frame = df,
    x = "Identifier",
    y = ['Conc1',''Conc2','Conc3'],
    barmode = 'stack'

Test Data.csv

Hi,

This may be an error specific to my device (running MacOS Monterey 12.6.3), but Dash currently seems to raise an error when trying to use this package. As a minimal working example, I created a fresh environment using Mambaforge (tested both with Python 3.8 and Python 3.11) and copied the install commands & sample notebook from the package's Readme. When running the notebook as-is, the tooltips would simply not pop up, but after removing mode='inline' and viewing the graph through my browser, the browser showed me a "Callback error" each time I hovered over a datapoint (see attached screenshot). Additionally, it provided the error "Invalid prop for this component" upon loading.

The error seems to be fixed (at least in python 3.11) by replacing df_row[title_col].astype(str) in line 333 of molplotly.main with str(df_row[title_col]) (for some reason, .astype(str) seems to work with numeric dtypes but not with strings as the item returned by df_row[title_col] is the string itself). After making this change, the single "Invalid prop..." error remains, but the tooltip seems to work as intended without throwing the "Callback error"s.

The exact error messages were as follows:

Invalid prop for this component
-------------------------------
Property "value" was used with component ID:
  "smiles-menu"
in one of the Input items of a callback.
This ID is assigned to a dash_core_components.Store component
in the layout, which does not support this property.
This ID was used in the callback(s) for Output(s):
  graph-tooltip.show, graph-tooltip.bbox, graph-tooltip.children

Callback error updating ..graph-tooltip.show...graph-tooltip.bbox...graph-tooltip.children..
--------------------------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
AttributeError: 'str' object has no attribute 'astype'

It would be great to make the image background transparent allowing what’s behind it to show through.

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

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.

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

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

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.

Hey,

Fantastic functionality. Apologies I am trying very hard but cannot figure out how to integrate this with an existing dash app.

Also, at the moment, I am just interested in displaying the plot in addition to showing the complete input table with other features associated with structure. Anyways we can show a table below the figure, such as pca, interactively, when we hover on a dot and show the structure in addition to other metadata or features?

Thanks so much,
JL

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!

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!

Not sure if this is on my end, but when installing using pip install molplotly, I could not import without running into the following issues:

ImportError: cannot import name 'json' from itsdangerous
Fixed by running pip install --force-reinstall itsdangerous==2.0.1

ImportError: cannot import name 'BaseResponse' from 'werkzeug.wrappers
Fixed by running pip install --force-reinstall werkzeug==2.0.3

Not sure if this is just an environment problem, or whether the project should be updated to use the newer releases of these packages. 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.

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?