Hide/Show Glyphs - Heavy interaction with widgets

The behaviour that I’m sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I’ve managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it’s possible and I’m not even far off…

So far I tried to hack my way around the issue by

  • updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won’t update the plot because I’m not pushing anything to the notebook

  • Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!

One option is ipython widgets. Good examples live here:

I find the @interact decorator particularly useful. It is demoed in the Interact.ipynb.

There may be some bokeh specific ways to do better but they should give you a nice start.

···

On Tuesday, September 15, 2015 at 11:02:15 AM UTC-4, Lien Michiels wrote:

The behaviour that I’m sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I’ve managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it’s possible and I’m not even far off…

So far I tried to hack my way around the issue by

  • updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won’t update the plot because I’m not pushing anything to the notebook
  • Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!

Hey Tom!

Thanks for your answer. This is what my application currently looks like:

I’m using the on_trait_change attribute of the widgets to update them exactly the way I want to. The capabilities of interact were unfortunately too limited in this case :-). In general they work really well though.

Problem is that when I try to interact with the Bokeh plot I am not sure what to do. Redraw it entirely? But would that have an effect on the cell it is displayed in? How do I delete the plot to replace it with a new one?

I was hoping to be able to simply interact with it, but I haven’t yet figured it out.

After spending a whole day, I thought I might be better of asking you guys ;-).

···

Op dinsdag 15 september 2015 18:43:30 UTC+2 schreef Tom:

One option is ipython widgets. Good examples live here:

https://github.com/jupyter/scipy-advanced-tutorial/tree/master/Part2

I find the @interact decorator particularly useful. It is demoed in the Interact.ipynb.

There may be some bokeh specific ways to do better but they should give you a nice start.

On Tuesday, September 15, 2015 at 11:02:15 AM UTC-4, Lien Michiels wrote:

The behaviour that I’m sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I’ve managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it’s possible and I’m not even far off…

So far I tried to hack my way around the issue by

  • updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won’t update the plot because I’m not pushing anything to the notebook
  • Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!

No immediate solution, but wanted to mention two things.

Have you referenced the example here for interacting using ipython notebooks? http://bokeh.pydata.org/en/latest/docs/user_guide/notebook.html#integrating-ipython-interactors

I believe the solution would be to think of it as you must create an object representing the things you want to toggle on/off, then you would change the attribute associated with them via the column data source. So, you aren’t redrawing the whole thing, you are updating the values in the columns associated with the visual attributes. I think you were on the right track with alpha, you just need to add columns to associate with the alpha for each glyph, then toggle it between 0 and 1 and push the updated data to the notebook.

The other option is just to make it as a standalone app as a static html page using JS callbacks, or to use the server. I imagine that the shiny example would face similar issues.

···

On Tuesday, September 15, 2015 at 11:54:19 AM UTC-5, Lien Michiels wrote:

Hey Tom!

Thanks for your answer. This is what my application currently looks like:

I’m using the on_trait_change attribute of the widgets to update them exactly the way I want to. The capabilities of interact were unfortunately too limited in this case :-). In general they work really well though.

Problem is that when I try to interact with the Bokeh plot I am not sure what to do. Redraw it entirely? But would that have an effect on the cell it is displayed in? How do I delete the plot to replace it with a new one?

I was hoping to be able to simply interact with it, but I haven’t yet figured it out.

After spending a whole day, I thought I might be better of asking you guys ;-).

Op dinsdag 15 september 2015 18:43:30 UTC+2 schreef Tom:

One option is ipython widgets. Good examples live here:

https://github.com/jupyter/scipy-advanced-tutorial/tree/master/Part2

I find the @interact decorator particularly useful. It is demoed in the Interact.ipynb.

There may be some bokeh specific ways to do better but they should give you a nice start.

On Tuesday, September 15, 2015 at 11:02:15 AM UTC-4, Lien Michiels wrote:

The behaviour that I’m sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I’ve managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it’s possible and I’m not even far off…

So far I tried to hack my way around the issue by

  • updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won’t update the plot because I’m not pushing anything to the notebook
  • Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!

Hey Nick,

Thanks for your answer! I’ve been trying to get it to work the way you described, but I experienced two problems with this approach:

ColumnDataSource will only accept arguments of size > 1, while alpha (at least for the line glyph) seems to be a single value.

If I replace it by an array of alphas, it seems to have no effect. The code will run but not do anything.

I guess you could say I’m trying to establish a proof of concept, that these kinds of web apps that usually require either a lot of work on the JS side, or an expensive tool like Shiny can be built using Notebooks and Bokeh, both OpenSource. So that is just not an option in this case ;-).

Do you have any more ideas?

···

Op dinsdag 15 september 2015 19:45:11 UTC+2 schreef Nick Roth:

No immediate solution, but wanted to mention two things.

Have you referenced the example here for interacting using ipython notebooks? http://bokeh.pydata.org/en/latest/docs/user_guide/notebook.html#integrating-ipython-interactors

I believe the solution would be to think of it as you must create an object representing the things you want to toggle on/off, then you would change the attribute associated with them via the column data source. So, you aren’t redrawing the whole thing, you are updating the values in the columns associated with the visual attributes. I think you were on the right track with alpha, you just need to add columns to associate with the alpha for each glyph, then toggle it between 0 and 1 and push the updated data to the notebook.

The other option is just to make it as a standalone app as a static html page using JS callbacks, or to use the server. I imagine that the shiny example would face similar issues.

On Tuesday, September 15, 2015 at 11:54:19 AM UTC-5, Lien Michiels wrote:

Hey Tom!

Thanks for your answer. This is what my application currently looks like:

I’m using the on_trait_change attribute of the widgets to update them exactly the way I want to. The capabilities of interact were unfortunately too limited in this case :-). In general they work really well though.

Problem is that when I try to interact with the Bokeh plot I am not sure what to do. Redraw it entirely? But would that have an effect on the cell it is displayed in? How do I delete the plot to replace it with a new one?

I was hoping to be able to simply interact with it, but I haven’t yet figured it out.

After spending a whole day, I thought I might be better of asking you guys ;-).

Op dinsdag 15 september 2015 18:43:30 UTC+2 schreef Tom:

One option is ipython widgets. Good examples live here:

https://github.com/jupyter/scipy-advanced-tutorial/tree/master/Part2

I find the @interact decorator particularly useful. It is demoed in the Interact.ipynb.

There may be some bokeh specific ways to do better but they should give you a nice start.

On Tuesday, September 15, 2015 at 11:02:15 AM UTC-4, Lien Michiels wrote:

The behaviour that I’m sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I’ve managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it’s possible and I’m not even far off…

So far I tried to hack my way around the issue by

  • updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won’t update the plot because I’m not pushing anything to the notebook
  • Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!

Re: alpha and line glyph

Line and Patch are both fit slightly oddly in the bokeh scheme. In general, glyphs are meant to be "vectorizable" over data. So a "Line" glyph should be a vector of lines, if we were being completely consistent. with all the other glyphs And then a vector of alphas would set one alpha for every line. But this is perhaps not the common case that people want, so this glyph that draws a vector of lines is called "multi_line" in Bokeh. And then we have the "line" glyph, which accepts a vector of *points* but just draws one *line* from a vector of points. But that's the key observation: there's only one line. So there's nothing that more than one alpha could change. Same for patch: multiple points, but only one patch. These two glyphs are definitely a small inconsistency wrt the normal Bokeh glyph properties usage.

It's possible to really tease out these distinctions, but it requires being very careful to separate geometry ("points") from topology ("connections" between points) but that can also make an API very cumbersome, so we live with the small inconsistency.

Bryan

···

On Sep 16, 2015, at 9:05 AM, Lien Michiels <[email protected]> wrote:

Hey Nick,

Thanks for your answer! I've been trying to get it to work the way you described, but I experienced two problems with this approach:

ColumnDataSource will only accept arguments of size > 1, while alpha (at least for the line glyph) seems to be a single value.
If I replace it by an array of alphas, it seems to have no effect. The code will run but not do anything.

I guess you could say I'm trying to establish a proof of concept, that these kinds of web apps that usually require either a lot of work on the JS side, or an expensive tool like Shiny can be built using Notebooks and Bokeh, both OpenSource. So that is just not an option in this case ;-).

Do you have any more ideas?

Op dinsdag 15 september 2015 19:45:11 UTC+2 schreef Nick Roth:
No immediate solution, but wanted to mention two things.

Have you referenced the example here for interacting using ipython notebooks? http://bokeh.pydata.org/en/latest/docs/user_guide/notebook.html#integrating-ipython-interactors
I believe the solution would be to think of it as you must create an object representing the things you want to toggle on/off, then you would change the attribute associated with them via the column data source. So, you aren't redrawing the whole thing, you are updating the values in the columns associated with the visual attributes. I think you were on the right track with alpha, you just need to add columns to associate with the alpha for each glyph, then toggle it between 0 and 1 and push the updated data to the notebook.

The other option is just to make it as a standalone app as a static html page using JS callbacks, or to use the server. I imagine that the shiny example would face similar issues.

On Tuesday, September 15, 2015 at 11:54:19 AM UTC-5, Lien Michiels wrote:
Hey Tom!

Thanks for your answer. This is what my application currently looks like:

I'm using the on_trait_change attribute of the widgets to update them exactly the way I want to. The capabilities of interact were unfortunately too limited in this case :-). In general they work really well though.

Problem is that when I try to interact with the Bokeh plot I am not sure what to do. Redraw it entirely? But would that have an effect on the cell it is displayed in? How do I delete the plot to replace it with a new one?

I was hoping to be able to simply interact with it, but I haven't yet figured it out.

After spending a whole day, I thought I might be better of asking you guys ;-).

Op dinsdag 15 september 2015 18:43:30 UTC+2 schreef Tom:
One option is ipython widgets. Good examples live here:

https://github.com/jupyter/scipy-advanced-tutorial/tree/master/Part2

I find the @interact decorator particularly useful. It is demoed in the Interact.ipynb.

There may be some bokeh specific ways to do better but they should give you a nice start.

On Tuesday, September 15, 2015 at 11:02:15 AM UTC-4, Lien Michiels wrote:
The behaviour that I'm sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I've managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it's possible and I'm not even far off...

So far I tried to hack my way around the issue by
- updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won't update the plot because I'm not pushing anything to the notebook
- Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!

--
You received this message because you are subscribed to the Google Groups "Bokeh Discussion - Public" group.
To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].
To post to this group, send email to [email protected].
To view this discussion on the web visit https://groups.google.com/a/continuum.io/d/msgid/bokeh/603355a1-61b5-4bf7-931c-2175aa9b05fd%40continuum.io.
For more options, visit https://groups.google.com/a/continuum.io/d/optout.

Hey Bryan,

I agree that this is the best possible solution in this case. Another just wouldn’t make much sense given that a line is indeed never more than just “one line”. From what you are saying though, am I right to conclude that for instance on a rectangle glyph it would work? Or on multi-line?

Another thing that I tried was accessing the “visible” property of a basic glyph as such:

p1.select(name=“dens”)[0].glyph.visible=True

But it is not possible to change any of them after rendering.

Is there a way that you know of though, to achieve the kind of behaviour I’m looking for? Hiding/Showing of all kinds of glyphs?

Lien

···

Op woensdag 16 september 2015 16:32:03 UTC+2 schreef Bryan Van de ven:

Re: alpha and line glyph

Line and Patch are both fit slightly oddly in the bokeh scheme. In general, glyphs are meant to be “vectorizable” over data. So a “Line” glyph should be a vector of lines, if we were being completely consistent. with all the other glyphs And then a vector of alphas would set one alpha for every line. But this is perhaps not the common case that people want, so this glyph that draws a vector of lines is called “multi_line” in Bokeh. And then we have the “line” glyph, which accepts a vector of points but just draws one line from a vector of points. But that’s the key observation: there’s only one line. So there’s nothing that more than one alpha could change. Same for patch: multiple points, but only one patch. These two glyphs are definitely a small inconsistency wrt the normal Bokeh glyph properties usage.

It’s possible to really tease out these distinctions, but it requires being very careful to separate geometry (“points”) from topology (“connections” between points) but that can also make an API very cumbersome, so we live with the small inconsistency.

Bryan

On Sep 16, 2015, at 9:05 AM, Lien Michiels [email protected] wrote:

Hey Nick,

Thanks for your answer! I’ve been trying to get it to work the way you described, but I experienced two problems with this approach:

ColumnDataSource will only accept arguments of size > 1, while alpha (at least for the line glyph) seems to be a single value.
If I replace it by an array of alphas, it seems to have no effect. The code will run but not do anything.

I guess you could say I’m trying to establish a proof of concept, that these kinds of web apps that usually require either a lot of work on the JS side, or an expensive tool like Shiny can be built using Notebooks and Bokeh, both OpenSource. So that is just not an option in this case ;-).

Do you have any more ideas?

Op dinsdag 15 september 2015 19:45:11 UTC+2 schreef Nick Roth:

No immediate solution, but wanted to mention two things.

Have you referenced the example here for interacting using ipython notebooks? http://bokeh.pydata.org/en/latest/docs/user_guide/notebook.html#integrating-ipython-interactors

I believe the solution would be to think of it as you must create an object representing the things you want to toggle on/off, then you would change the attribute associated with them via the column data source. So, you aren’t redrawing the whole thing, you are updating the values in the columns associated with the visual attributes. I think you were on the right track with alpha, you just need to add columns to associate with the alpha for each glyph, then toggle it between 0 and 1 and push the updated data to the notebook.

The other option is just to make it as a standalone app as a static html page using JS callbacks, or to use the server. I imagine that the shiny example would face similar issues.

On Tuesday, September 15, 2015 at 11:54:19 AM UTC-5, Lien Michiels wrote:

Hey Tom!

Thanks for your answer. This is what my application currently looks like:

I’m using the on_trait_change attribute of the widgets to update them exactly the way I want to. The capabilities of interact were unfortunately too limited in this case :-). In general they work really well though.

Problem is that when I try to interact with the Bokeh plot I am not sure what to do. Redraw it entirely? But would that have an effect on the cell it is displayed in? How do I delete the plot to replace it with a new one?

I was hoping to be able to simply interact with it, but I haven’t yet figured it out.

After spending a whole day, I thought I might be better of asking you guys ;-).

Op dinsdag 15 september 2015 18:43:30 UTC+2 schreef Tom:

One option is ipython widgets. Good examples live here:

https://github.com/jupyter/scipy-advanced-tutorial/tree/master/Part2

I find the @interact decorator particularly useful. It is demoed in the Interact.ipynb.

There may be some bokeh specific ways to do better but they should give you a nice start.

On Tuesday, September 15, 2015 at 11:02:15 AM UTC-4, Lien Michiels wrote:

The behaviour that I’m sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I’ve managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it’s possible and I’m not even far off…

So far I tried to hack my way around the issue by

  • updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won’t update the plot because I’m not pushing anything to the notebook
  • Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!


You received this message because you are subscribed to the Google Groups “Bokeh Discussion - Public” group.

To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].

To post to this group, send email to [email protected].

To view this discussion on the web visit https://groups.google.com/a/continuum.io/d/msgid/bokeh/603355a1-61b5-4bf7-931c-2175aa9b05fd%40continuum.io.

For more options, visit https://groups.google.com/a/continuum.io/d/optout.

This works:

def on_dens_toggle(name, value):

if value:

w4.visible = True

clear_output()

p1.select(name=“dens”)[0].glyph.line_alpha=0.5

show(p1)

else:

w4.visible = False

clear_output()

p1.select(name=“dens”)[0].glyph.line_alpha=0

show(p1)

Although a little flickery.

···

Op woensdag 16 september 2015 16:50:34 UTC+2 schreef Lien Michiels:

Hey Bryan,

I agree that this is the best possible solution in this case. Another just wouldn’t make much sense given that a line is indeed never more than just “one line”. From what you are saying though, am I right to conclude that for instance on a rectangle glyph it would work? Or on multi-line?

Another thing that I tried was accessing the “visible” property of a basic glyph as such:

p1.select(name=“dens”)[0].glyph.visible=True

But it is not possible to change any of them after rendering.

Is there a way that you know of though, to achieve the kind of behaviour I’m looking for? Hiding/Showing of all kinds of glyphs?

Lien

Op woensdag 16 september 2015 16:32:03 UTC+2 schreef Bryan Van de ven:

Re: alpha and line glyph

Line and Patch are both fit slightly oddly in the bokeh scheme. In general, glyphs are meant to be “vectorizable” over data. So a “Line” glyph should be a vector of lines, if we were being completely consistent. with all the other glyphs And then a vector of alphas would set one alpha for every line. But this is perhaps not the common case that people want, so this glyph that draws a vector of lines is called “multi_line” in Bokeh. And then we have the “line” glyph, which accepts a vector of points but just draws one line from a vector of points. But that’s the key observation: there’s only one line. So there’s nothing that more than one alpha could change. Same for patch: multiple points, but only one patch. These two glyphs are definitely a small inconsistency wrt the normal Bokeh glyph properties usage.

It’s possible to really tease out these distinctions, but it requires being very careful to separate geometry (“points”) from topology (“connections” between points) but that can also make an API very cumbersome, so we live with the small inconsistency.

Bryan

On Sep 16, 2015, at 9:05 AM, Lien Michiels [email protected] wrote:

Hey Nick,

Thanks for your answer! I’ve been trying to get it to work the way you described, but I experienced two problems with this approach:

ColumnDataSource will only accept arguments of size > 1, while alpha (at least for the line glyph) seems to be a single value.
If I replace it by an array of alphas, it seems to have no effect. The code will run but not do anything.

I guess you could say I’m trying to establish a proof of concept, that these kinds of web apps that usually require either a lot of work on the JS side, or an expensive tool like Shiny can be built using Notebooks and Bokeh, both OpenSource. So that is just not an option in this case ;-).

Do you have any more ideas?

Op dinsdag 15 september 2015 19:45:11 UTC+2 schreef Nick Roth:

No immediate solution, but wanted to mention two things.

Have you referenced the example here for interacting using ipython notebooks? http://bokeh.pydata.org/en/latest/docs/user_guide/notebook.html#integrating-ipython-interactors

I believe the solution would be to think of it as you must create an object representing the things you want to toggle on/off, then you would change the attribute associated with them via the column data source. So, you aren’t redrawing the whole thing, you are updating the values in the columns associated with the visual attributes. I think you were on the right track with alpha, you just need to add columns to associate with the alpha for each glyph, then toggle it between 0 and 1 and push the updated data to the notebook.

The other option is just to make it as a standalone app as a static html page using JS callbacks, or to use the server. I imagine that the shiny example would face similar issues.

On Tuesday, September 15, 2015 at 11:54:19 AM UTC-5, Lien Michiels wrote:

Hey Tom!

Thanks for your answer. This is what my application currently looks like:

I’m using the on_trait_change attribute of the widgets to update them exactly the way I want to. The capabilities of interact were unfortunately too limited in this case :-). In general they work really well though.

Problem is that when I try to interact with the Bokeh plot I am not sure what to do. Redraw it entirely? But would that have an effect on the cell it is displayed in? How do I delete the plot to replace it with a new one?

I was hoping to be able to simply interact with it, but I haven’t yet figured it out.

After spending a whole day, I thought I might be better of asking you guys ;-).

Op dinsdag 15 september 2015 18:43:30 UTC+2 schreef Tom:

One option is ipython widgets. Good examples live here:

https://github.com/jupyter/scipy-advanced-tutorial/tree/master/Part2

I find the @interact decorator particularly useful. It is demoed in the Interact.ipynb.

There may be some bokeh specific ways to do better but they should give you a nice start.

On Tuesday, September 15, 2015 at 11:02:15 AM UTC-4, Lien Michiels wrote:

The behaviour that I’m sort of trying to recreate using the Jupyter Notebooks and Bokeh is this: http://shiny.rstudio.com/gallery/faithful.html

So far I’ve managed to update the number of bins and the bandwidth and thus change the plot (ColumnDataSource, hooray!) but I cannot seem to hide/show the density estimate or individual observations.

Essentially I think it’s possible and I’m not even far off…

So far I tried to hack my way around the issue by

  • updating the value of the alpha to 0.0 -> Alpha is not in my ColumnDataSource so whatever I try it obviously won’t update the plot because I’m not pushing anything to the notebook
  • Set all values to None in updating the plot -> Obviously not a good idea

Is there a way to do this? And if not, would it be interesting for you guys to implement this kind of behaviour and is there any way in which I can help?

Loving Bokeh by the way. Kudos to all of you!


You received this message because you are subscribed to the Google Groups “Bokeh Discussion - Public” group.

To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].

To post to this group, send email to [email protected].

To view this discussion on the web visit https://groups.google.com/a/continuum.io/d/msgid/bokeh/603355a1-61b5-4bf7-931c-2175aa9b05fd%40continuum.io.

For more options, visit https://groups.google.com/a/continuum.io/d/optout.