我有一个 Python 模块，它提供调色板和处理它们的实用程序。调色板对象只是从list十六进制字符串中指定的颜色列表继承而来。调色板对象具有扩展自身以提供所需颜色的能力。想象一个包含许多不同数据集的图形：可以要求调色板将其具有的颜色数量扩展到为每个图形数据集提供唯一颜色所需的程度。它通过简单地取相邻颜色的平均值并插入这个新的平均颜色来做到这一点。
该extend_palette功能有效，但它没有统一扩展调色板。例如，调色板可能如下所示：
将其扩展到 15 种颜色仍然可用：
将其扩展到 30 种颜色会使扩展算法的问题变得明显；仅在颜色列表的一端添加新颜色：
应该如何改变模块的功能extend_palette，使扩展的新颜色在调色板中分布更均匀？
代码如下（extend_palette为了方便实验，特别关注该功能和其他代码）：
def clamp(x):
return max(0, min(x, 255))
def RGB_to_HEX(RGB_tuple):
# This function returns a HEX string given an RGB tuple.
r = RGB_tuple[0]
g = RGB_tuple[1]
b = RGB_tuple[2]
return "#{0:02x}{1:02x}{2:02x}".format(clamp(r), clamp(g), clamp(b))
def HEX_to_RGB(HEX_string):
# This function returns an RGB tuple given a HEX string.
HEX = HEX_string.lstrip("#")
HEX_length = len(HEX)
return tuple(
int(HEX[i:i + HEX_length // 3], 16) for i in range(
0,
HEX_length,
HEX_length // 3
)
)
def mean_color(colors_in_HEX):
# This function returns a HEX string that represents the mean color of a
# list of colors represented by HEX strings.
colors_in_RGB = []
for color_in_HEX in colors_in_HEX:
colors_in_RGB.append(HEX_to_RGB(color_in_HEX))
sum_r = 0
sum_g = 0
sum_b = 0
for color_in_RGB in colors_in_RGB:
sum_r += color_in_RGB[0]
sum_g += color_in_RGB[1]
sum_b += color_in_RGB[2]
mean_r = sum_r / len(colors_in_RGB)
mean_g = sum_g / len(colors_in_RGB)
mean_b = sum_b / len(colors_in_RGB)
return RGB_to_HEX((mean_r, mean_g, mean_b))
class Palette(list):
def __init__(
self,
name = None, # string name
description = None, # string description
colors = None, # list of colors
*args
):
super(Palette, self).__init__(*args)
self._name = name
self._description = description
self.extend(colors)
def name(
self
):
return self._name
def set_name(
self,
name = None
):
self._name = name
def description(
self
):
return self._description
def set_description(
self,
description = None
):
self._description = description
def extend_palette(
self,
minimum_number_of_colors_needed = 15
):
colors = extend_palette(
colors = self,
minimum_number_of_colors_needed = minimum_number_of_colors_needed
)
self = colors
def save_image_of_palette(
self,
filename = "palette.png"
):
save_image_of_palette(
colors = self,
filename = filename
)
def extend_palette(
colors = None, # list of HEX string colors
minimum_number_of_colors_needed = 15
):
while len(colors) < minimum_number_of_colors_needed:
for index in range(1, len(colors), 2):
colors.insert(index, mean_color([colors[index - 1], colors[index]]))
return colors
def save_image_of_palette(
colors = None, # list of HEX string colors
filename = "palette.png"
):
import numpy
import Image
scale_x = 200
scale_y = 124
data = numpy.zeros((1, len(colors), 3), dtype = numpy.uint8)
index = -1
for color in colors:
index += 1
color_RGB = HEX_to_RGB(color)
data[0, index] = [color_RGB[0], color_RGB[1], color_RGB[2]]
data = numpy.repeat(data, scale_x, axis=0)
data = numpy.repeat(data, scale_y, axis=1)
image = Image.fromarray(data)
image.save(filename)
# Define color palettes.
palettes = []
palettes.append(Palette(
name = "palette1",
description = "primary colors for white background",
colors = [
"#fc0000",
"#ffae3a",
"#00ac00",
"#6665ec",
"#a9a9a9",
]
))
palettes.append(Palette(
name = "palette2",
description = "ATLAS clarity",
colors = [
"#FEFEFE",
"#AACCFF",
"#649800",
"#9A33CC",
"#EE2200",
]
))
def save_images_of_palettes():
for index, palette in enumerate(palettes):
save_image_of_palette(
colors = palette,
filename = "palette_{index}.png".format(index = index + 1)
)
def access_palette(
name = "palette1"
):
for palette in palettes:
if palette.name() == name:
return palette
return None
