Resolve "(LearnerND) add iso-surface plot feature"

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46f2d8d4 - add iso_surface_plot to adaptive learnerND

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Now there is :)

Quick demo:

import adaptive
adaptive.notebook_extension()

def f(xyz):
    x, y, z = xyz
    return x**4 + y**4 + z**4 - (x**2+y**2+z**2)**2


learner = adaptive.LearnerND(f, bounds=[(-1,1), (-1,1), (-1,1)])
runner = adaptive.Runner(learner, goal=lambda l:l.npoints>1000)
runner.live_info()

and when it's finished:

from ipywidgets import interact_manual
interact_manual(learner.plot_isosurface, level=(-5.99,-.01,0.01), hull_opacity=(0,1,0.2))

or

learner.plot_isosurface(level=-0.5)

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e52a6325 - fix style issues

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b47cbb40 - fix style issues

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85243d94 - fix style issues

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a2b5aca6 - import plotly only when using it

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63175598 - add iso_surface_plot to adaptive learnerND

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c1c1b872 - improve 'notebook_extension'

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9ed15f76 - improve 'notebook_extension'

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4e0090e6 - add iso_surface_plot to adaptive learnerND
3e660922 - improve 'notebook_extension'

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mentioned in merge request !127 (merged)

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f07282c4 - add iso_surface_plot to adaptive learnerND
f518d872 - improve 'notebook_extension'

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3f611327 - set lighting such that the plots look even better

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i have found why the surface looks so rough/ugly. It has to do with lighting.

With this commit it should look nicer:

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dff5c5d9 - add plotly to environment.yml

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resolved all discussions

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8b0c5472 - also add an isoline feature
260df457 - add ability to plot multiple isolines

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This plotly MR may be relevant: https://github.com/plotly/plotly.js/pull/2752

(but it's work in progress on their side)

It would be great if we could add some example to the documentation.

However, I don't think that the plotly plots will correctly show up ATM.

Related: https://github.com/spatialaudio/nbsphinx/issues/128

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d22cd4a0 - add iso_surface_plot to adaptive learnerND
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7c453813 - add plotly to environment.yml
1810e2bf - also add an isoline feature

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4a3a6254 - also add an isoline feature
f6f2ef27 - add a 3D plot using plotly

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I've learned how to load them correctly, and we should be able to do so via jupyter-sphinx.

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82605cfe - add a Plotly example to the docs

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It already works :)

BTW, we probably shoulnd't show the triangulation edges: these are mainly relevant for debugging, but they obscure the information about the function that's being learned.