"""
.. _lookup_table_example:

Lookup Tables
~~~~~~~~~~~~~
Demonstrate the usage of a lookup table within PyVista

The :class:`pyvista.LookupTable` can be used to have fine-tuned control over
the mapping between a :class:`pyvista.DataSet`'s scalars and RGBA colors.

"""

from __future__ import annotations

import pyvista as pv
from pyvista import examples

# sphinx_gallery_start_ignore
# big figures of colormaps and widgets show better in static images
PYVISTA_GALLERY_FORCE_STATIC_IN_DOCUMENT = True
# sphinx_gallery_end_ignore

# download an example dataset
bracket = examples.download_fea_bracket().cell_data_to_point_data()
bracket


# %%
# Default Color Map - Lookup Table
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# First, let's plot using the default color map, "viridis". Internally, PyVista
# will automatically create a lookup table to map the scalars (stored here
# within `point_data`) to RGBA colors. This is shown here as a nested attribute
# to the :class:`pyvista.DataSetMapper` and it has a helpful ``repr`` method:

pl = pv.Plotter()
actor = pl.add_mesh(bracket)
actor.mapper.lookup_table


# %%
# Plot the Lookup Table
# ~~~~~~~~~~~~~~~~~~~~~
# You can also plot lookup table to see the mapping between the scalar values
# (here, between 0 and 23.3) and RGBA colors.

pl = pv.Plotter()
actor = pl.add_mesh(bracket)
actor.mapper.lookup_table.plot()


# %%
# Plot the DataSet
# ~~~~~~~~~~~~~~~~
# Let's plot the dataset using the automatically generated lookup table.

pl = pv.Plotter()
pl.add_mesh(bracket)
pl.show()


# %%
# Create a Custom Lookup Table using a Matplotlib Color Map
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Here we create a lookup table with a narrow table range (same as ``clim``)
# and color values above and below the range.

lut = pv.LookupTable(cmap='magma')
lut.scalar_range = (5, 15)
lut.below_range_color = pv.Color('grey', opacity=0.5)
lut.above_range_color = 'r'
lut.plot()


# %%
# Plot the bracket with the custom colormap
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# You can set assign the lookup table when using ``add_mesh`` with ``cmap=``.


pl = pv.Plotter()
actor = pl.add_mesh(bracket, cmap=lut, lighting=False)
pl.show()


# %%
# Create a Custom Lookup Table using VTK's Methods
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# If you want to create a completely unique color map, you can use attributes
# like :attr:`pyvista.LookupTable.hue_range` and
# :attr:`pyvista.LookupTable.value_range` to create your own lookup table.

lut = pv.LookupTable()
lut.value_range = (0.35, 1)  # dark grey to white
lut.hue_range = (0.35, 0.7)  # green to cyna
lut.saturation_range = (0.75, 0.5)  # reduce saturation near the upper end
lut.alpha_range = (0.0, 0.9)
lut.scalar_range = (2, 18)
lut.plot()


# %%
# Plot the bracket with the custom colormap
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Assign this custom color map to the plotter and disable lighting to improve
# the plot.

pl = pv.Plotter()
actor = pl.add_mesh(bracket, cmap=lut, lighting=False)
pl.show()


# %%
# Custom colormap with widgets
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Here we plot the scalars and dynamically change the lookup table through
# widgets. We create several overlapping single slider widgets to simulate a
# double ended slider widget.
#
# This example just controls the alpha channel.


pl = pv.Plotter()
actor = pl.add_mesh(bracket, cmap=lut, lighting=False)
pl.add_text('Alpha Range Demo')


def set_min_alpha(min_value):
    max_value = lut.alpha_range[1]
    if min_value > max_value:
        # force the movement of the maximum value
        max_value = min_value
        pl.slider_widgets[1].GetRepresentation().SetValue(max_value)
    lut.alpha_range = (min_value, max_value)


def set_max_alpha(max_value):
    min_value = lut.alpha_range[0]
    if max_value < min_value:
        # force the movement of the minimum value
        min_value = max_value
        pl.slider_widgets[0].GetRepresentation().SetValue(min_value)

    lut.alpha_range = (min_value, max_value)


# create two overlapping slider bars by hiding the tube of the second
pl.add_slider_widget(
    set_min_alpha,
    (0, 1),
    value=lut.alpha_range[0],
    interaction_event='always',
    title='Alpha Range',
    tube_width=0.003,
)
pl.add_slider_widget(
    set_max_alpha,
    (0, 1),
    value=lut.alpha_range[1],
    interaction_event='always',
    tube_width=0.0,
)

pl.show()


# %%
# Control Several Lookup Table Attributes
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Demonstrate the use of several slider bar widgets with lookup table
# callbacks.

# Create a new lookup table with oranges
lut = pv.LookupTable()
lut.value_range = (0.3, 0.75)
lut.hue_range = (0.0, 0.095)
lut.saturation_range = (0.0, 0.67)
lut.alpha_range = (0.0, 1.0)
lut.scalar_range = (2, 18)

scalars_rng = (bracket.active_scalars.min(), bracket.active_scalars.max())


def make_double_slider(attr, idx):
    """Create a double slider for a given lookup table attribute."""

    def set_min(min_value):
        max_value = getattr(lut, attr)[1]
        if min_value > max_value:
            # force the movement of the maximum value
            max_value = min_value
            pl.slider_widgets[idx * 2 + 1].GetRepresentation().SetValue(max_value)
        setattr(lut, attr, (min_value, max_value))

        if attr == 'scalar_range':
            actor.mapper.scalar_range = getattr(lut, attr)

    def set_max(max_value):
        min_value = getattr(lut, attr)[0]
        if max_value < min_value:
            # force the movement of the minimum value
            min_value = max_value
            pl.slider_widgets[idx * 2].GetRepresentation().SetValue(min_value)
        setattr(lut, attr, (min_value, max_value))

        if attr == 'scalar_range':
            actor.mapper.scalar_range = getattr(lut, attr)

    rng = scalars_rng if attr == 'scalar_range' else (0, 1)

    # create two overlapping slider bars by hiding the tube of the second
    pl.add_slider_widget(
        set_min,
        rng,
        value=getattr(lut, attr)[0],
        interaction_event='always',
        title=' '.join(attr.split('_')).capitalize(),
        tube_width=0.003,
        pointa=(0.6, 0.9 - 0.165 * idx),
        pointb=(0.9, 0.9 - 0.165 * idx),
    )
    pl.add_slider_widget(
        set_max,
        rng,
        value=getattr(lut, attr)[1],
        interaction_event='always',
        tube_width=0.0,
        pointa=(0.6, 0.9 - 0.165 * idx),
        pointb=(0.9, 0.9 - 0.165 * idx),
    )


pl = pv.Plotter()
actor = pl.add_mesh(bracket, cmap=lut, lighting=False)
make_double_slider('alpha_range', 0)
make_double_slider('hue_range', 1)
make_double_slider('value_range', 2)
make_double_slider('saturation_range', 3)
make_double_slider('scalar_range', 4)

pl.camera_position = [(9.021, 5.477, 7.780), (-0.679, 1.349, 0.874), (-0.498, -0.228, 0.836)]
cpos = pl.show(return_cpos=True)
# %%
# .. tags:: plot