from paleta.color import Color
from paleta.palette import Palette
from paleta.image import export_palette, extract_convert_palette

# Initializing Colors
red = Color.from_hex("#F00")
green = Color.from_hex("#0F0")
blue = Color.from_hex("#00F")

# Operations on Color
magenta = red + blue
yellow = red + green
cyan = green + blue

print(magenta.rgba)  # Get RGBA value
print(yellow.to_lightness())  # To 0...255 Value
print(cyan.to_hsl())  # Get HSL Value

magenta += 10  # Add 10 across values of RGB
cyan -= (10, 0, 10)  # Subtract 10 across R and B value

twilight_5 = Palette(
    Color.from_hex("fbbbad"),
    Color.from_hex("ee8695"),
    Color.from_hex("4a7a96"),
    Color.from_hex("333f58"),
    Color.from_hex("292831")
)  # Create a Palette Class

tw = Palette.from_lospec("twilight-5")  # Or use the Lospec API

assert (twilight_5.colors == tw.colors)  # They're the same

twilight_5.add(yellow)  # Add yellow to the palette
twilight_5.remove(yellow)  # And Remove it

warm_ochre = Palette.from_lospec("warm-ochre")
the_after = Palette.from_lospec("the-after")

twilight_5.union(warm_ochre)  # Combine Palette Sets
twilight_5.intersection(the_after)  # Or find where they intersect

extract_convert_palette("ref.png", "palette.png", f_out="new_ref.png")  # Map a Palette to an Image
export_palette(warm_ochre, f="warm-ochre.png")  # Export a Created or Imported Palette

from paleta.palette import Palette
from paleta.palette import ConversionPalette
from paleta.metric import euclidean_distance, cosine_distance, cosine_similarity

warm_ochre = Palette.from_lospec("warm-ochre")
the_after = Palette.from_lospec("the-after")

# Will create a Dictionary of how Palette (Warm Ochre) be mapped with Palette (The After)
# Using a Euclidean Distance Function and the Metric of Minimum Distance
cmap = ConversionPalette.map(warm_ochre, the_after, algo=euclidean_distance, metric=min)
print(cmap.to_dict())


# Making your own function works
def some_distance_function() -> float:
    # Map by distance
    return float()


def some_metric_function() -> object:
    # Find Max Value
    return max()


cmap2 = ConversionPalette.map(warm_ochre, the_after, algo=some_distance_function, metric=some_metric_function)
print(cmap2.to_dict())

# Randomize the Mapping
cmap3 = ConversionPalette.random(warm_ochre, the_after)
print(cmap3.to_dict())

from paleta.palette import Palette
from paleta.palette import minimize_by_average, maximize_by_average

warm_ochre = Palette.from_lospec("warm-ochre")
the_after = Palette.from_lospec("the-after")

# Reduce the Palette by Averaging Neighboring Colors
min_warm_ochre = minimize_by_average(warm_ochre)
print(warm_ochre.color_set)
print(minimize_by_average(warm_ochre).color_set)
print(len(min_warm_ochre))

# Increase the Palette by Adding the Averaging of Neighboring Colors
max_the_after = minimize_by_average(the_after)
print(the_after.color_set)
print(minimize_by_average(the_after).color_set)
print(len(max_the_after))