"""
From categories
===============
"""

# %%
# The :class:`ptvis.color.CategoricalColorConversion` class defines a
# conversion from categories to colors.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [str(i % 3) for i in range(len(elements))]

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.CategoricalColorConversion(),
)

plotly.io.show(fig)

# %%
# Defining a conversion explicitly
# --------------------------------

# %%
# The `mapping` argument determines an explicit mapping from categories to
# colors.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [str(i % 3) for i in range(len(elements))]

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.CategoricalColorConversion(
        mapping={"0": "red", "1": "green", "2": "blue"},
    ),
)

plotly.io.show(fig)

# %%
# Colors for categories missing from the mapping
# ----------------------------------------------

# %%
# Categories missing from the `mapping` argument are converted using a preset
# colorway.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [str(i % 3) for i in range(len(elements))]

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.CategoricalColorConversion(
        mapping={"0": "red"},
    ),
)

plotly.io.show(fig)

# %%
# The colorway can be changed by the `missing_colors` argument.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [str(i % 3) for i in range(len(elements))]

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.CategoricalColorConversion(
        mapping={"0": "red"},
        missing_colors=["cyan", "magenta", "yellow"],
    ),
)

plotly.io.show(fig)

# %%
# Color for N/A
# -------------

# %%
# A color for N/A is given by the `na_color` argument.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [str(i % 3) if i % 10 else None for i in range(len(elements))]

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.CategoricalColorConversion(
        mapping={"0": "red", "1": "green", "2": "blue"},
        na_color="white",
    ),
)

plotly.io.show(fig)