Missing points

[AhmedThahir]

Why are points missing?
From the watching the gif linked from your research paper, I thought that it would resample once again when I zoom in.

Code for the data

from plotly_resampler import FigureResampler
x = np.arange(10_000)
noisy_sin = (3 + np.sin(x / 200) + np.random.randn(len(x)) / 10) * x / 1_000

Before Zooming

Not Resampled

Resampled

After Zooming

Not Resampled

Resampled

[jonasvdd]

@AhmedThahir As you've closed this issue I suppose you found in the readme/docs that the "show" method returns a static figure whereas the "show_dash" method (for the FigureResampler) enables this interactive resampling

[AhmedThahir]

What's the difference between

• using show_dash with FigureResampler
• using show with FigureWidgetResampler

[jonasvdd]

Hi @AhmedThahir,

I agree this is somewhat confusing, I think this can be best summarized with:

• show always returns a static figure view i.e., no dynamic aggregation will be performed
• To have dynamic aggregation:
  • with FigureResampler, you need to call show_dash -> which spawns a dash-web app, and the dynamic aggregation is realized with dash callback
  • with FigureWidgetResampler, you need to use IPython.display, which uses widget-events to realize dynamic aggregation.

Did you find our docs confusing? If so, where would you like to get more of this information? Together we can further improve this toolkit 😄

[AhmedThahir]

Ah got it now.

Regarding the documentation, I believe it's pretty good. Only that this particular concept that you just clarified wasn't very clear.

If you could add this to an FAQ section or something, it'd be great.

[jvdd]

Great suggestion about the FAQ, I'm very keen on adding this. What do you think @jonasvdd?

[jonasvdd]

Agree, we can add an FAQ tab to the docs, but would create a separate PR for that!

[jonasvdd]

@AhmedThahir,

Now there is an FAQ section in our docs. (https://predict-idlab.github.io/plotly-resampler/FAQ.html
This issue is documented there aswell!