"""
From numerical values to discrete colors
========================================
"""

# %%
# The :class:`ptvis.color.DiscreteColorConversion` class defines a conversion
# from numerical values to discrete colors. Values in an interval is converted
# into the same color.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = list(range(len(elements)))

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

plotly.io.show(fig)

# %%
# Defining a conversion with colors for evenly spaced levels
# ----------------------------------------------------------

# %%
# Discrete colors are determined by discretizing a color scale. The `colors`
# argument determines colors at evenly spaced levels of the color scale.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = list(range(len(elements)))

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.DiscreteColorConversion(
        colors=["blue", "green", "red"],
    ),
)

plotly.io.show(fig)

# %%
# Defining a conversion with colors at arbitrary levels
# -----------------------------------------------------

# %%
# The levels of the `colors` argument can be changed by the `levels` argument.
# The arugment must be given in ascending order.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = list(range(len(elements)))

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.DiscreteColorConversion(
        colors=["blue", "green", "red"],
        levels=[-1, -0.5, 1],
    ),
)

plotly.io.show(fig)

# %%
# Number of intervals
# -------------------

# %%
# The number of intervals or discrete colors can be changed by the
# `n_intervals` arguments.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = list(range(len(elements)))

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.DiscreteColorConversion(n_intervals=5),
)

plotly.io.show(fig)

# %%
# Clipping
# --------

# %%
# By default, the minimum and maximum values correspond with the lowest and
# highest levels. Values corresponding with the lowest and highest levels can
# be changed by the `value_min` and `value_max` arguments. Values out of range
# are converted into colors of the lowest and highest levels.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = list(range(len(elements)))

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.DiscreteColorConversion(
        colors=["blue", "green", "red"],
        value_min=30,
        value_max=60,
    ),
)

plotly.io.show(fig)

# %%
# Colors for out-of-range values can be changed by the `lower_color` and
# `higher_color` argument.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = list(range(len(elements)))

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.DiscreteColorConversion(
        colors=["blue", "green", "red"],
        value_min=30,
        value_max=60,
        lower_color="black",
        higher_color="white",
    ),
)

plotly.io.show(fig)

# %%
# Closed endpoint of an interval
# ------------------------------

# %%
# A closed endpoint of an interval can be changed by the `closed` argument.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [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.DiscreteColorConversion(
        n_intervals=2,
        closed="high",
    ),
)

plotly.io.show(fig)

# %%
# The `include_boundary` argument controls whether the higher (lower)
# endpoint of the highest (lowest) interval is closed when the `closed`
# argument is ``"low"`` (``"high"``).

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [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.DiscreteColorConversion(
        n_intervals=2,
        closed="high",
        include_boundary=False,
        lower_color="white",
    ),
)

plotly.io.show(fig)

# %%
# Color for NaN
# --------------

# %%
# A color for NaN can be changed by the `na_color` argument.

import plotly
import ptvis.color


elements = list(ptvis.Element)
values = [i if i % 10 else float("nan") for i in range(len(elements))]

fig = plotly.graph_objects.Figure()
ptvis.attach_plain_cells(
    fig,
    elements,
    colors=values,
    color_conversion=ptvis.color.DiscreteColorConversion(
        colors=["blue", "green", "red"],
        na_color="white",
    ),
)

plotly.io.show(fig)