# %% [markdown]
# # Visualization in notebooks

# %% [markdown]
# It is possible to visualize pyddg objects in jupyter notebooks.
# For this we use the python package [k3d](https://k3d-jupyter.org/).

# Objects in this package can be displayed as interactive widgets
# in a jupyter notebook
# or in even in a static html page.

# On the top right of the widgets there is a `k3d` panel that
# allows to take screenshots, show the widget in fullscreen
# or modify objects.

# %%
import ddg
import numpy as np

# %% [markdown]
# ## Converting pyddg objects to drawable objects

# %% [markdown]
# ### Default conversion

# %%
quadric = ddg.geometry.Quadric(np.diag((1, 1, -1, -1)))

# %% [markdown]
# To visualize this quadric as a smooth surface,
# we first need to convert it to an instance of `k3d.objects.Drawable`.

# %%
hyperboloid = ddg.jupyter.convert(quadric)
type(hyperboloid)

# %% [markdown]
# `k3d.objects.Drawable` objects can be previewed direclty
# when outputed from a jupyter cell:

# %%
hyperboloid

# %% [markdown]
# ### Special conversions

# %% [markdown]
# To convert to a `k3d.objects.Drawable` containing only the edges of an object, run:

# %%
hyperboloid_edges = ddg.jupyter.edges(quadric)
hyperboloid_edges

# %% [markdown]
# To get only the points of an object, run:

# %%
hyperboloid_points = ddg.jupyter.vertices(quadric)
hyperboloid_points

# %% [markdown]
# ## Visualizing a 3D scene

# %% [markdown]
# To create a 3D scene from `k3d.objects.Drawable` objects,
# one must add them to a `k3d.plot.Plot`. We provide a utility function
# to render them in a clean and higher quality render setting.
# One can combine objects to create more complex scenes:

# %%
ddg.jupyter.show_3d(hyperboloid, hyperboloid_points, hyperboloid_edges)

# %% [markdown]
# ## Visualizing a 2D scene

# %% [markdown]
# To create a 2D scene, we provide a similar function:

# %%
I = (-1, 0, 1)
conics = [ddg.geometry.Quadric(np.diag((i, j, k))) for i in I for j in I for k in I]
kobjs = [ddg.jupyter.convert(c) for c in conics]
ddg.jupyter.show_2d(*kobjs)

# %% [markdown]
# Compared to 3D scenes, 2D scenes just have flat colors
# and the camera looks from the top by default.

# %% [markdown]
# ## Interactive visualization

# %% [markdown]
# One can make interactive visualizations using widgets,
# like the ones from `ipywigets`.
# Let's make an empty plot for the visualization:

# %%
pencil = ddg.geometry.Pencil(quadric, ddg.geometry.Quadric(np.diag((1, 1, 1, -1))))
plot = ddg.jupyter.show_3d()
plot

# %% [markdown]
# Now let's create a slider widgets and define a callback function
# that places a quadric in the scene for each value of the slider.

# %%
from ipywidgets import FloatSlider, interact


@interact(i=FloatSlider(value=0, min=-2, max=2))
def callback(i):
    global plot
    ddg.jupyter.clear_plot(plot)
    quadric = pencil.quadric(i)
    plot += ddg.jupyter.convert(quadric)


# %% [markdown]
# (The slider will take effect in the jupyter notebook, but not here in the docs.)