Question

这个链接有R代码来复制ggplot的颜色：Plotting family of functions with qplot without duplicating data

我已经开始在python中复制代码 - 但结果不对......

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import math
import colorsys

# function to return a list of hex colour strings
def colorMaker(n=12, start=15.0/360.0, saturation=1.0, valight=0.65) :
    listOfColours = []
    for i in range(n) :
        hue = math.modf(float(i)/float(n) + start)[0]
        #(r,g,b) = colorsys.hsv_to_rgb(hue, saturation, valight)
        (r,g,b) = colorsys.hls_to_rgb(hue, valight, saturation)
        listOfColours.append( '#%02x%02x%02x' % (int(r*255), int(g*255), int(b*255)) )
    return listOfColours

# made up data
x = np.array(range(20))
d = {}
d['y1'] = pd.Series(x, index=x)
d['y2'] = pd.Series(1.5*x + 1, index=x)
d['y3'] = pd.Series(2*x + 2, index=x)
df = pd.DataFrame(d)

# plot example
plt.figure(num=1, figsize=(10,5), dpi=100) # set default image size
colours = colorMaker(n=3)
df.plot(linewidth=2.0, color=colours)
fig = plt.gcf()
fig.savefig('test.png')

结果......

enter image description here

Answer 1

你应该检查mpltools一个非常简洁的matplotlib扩展。有一个ggplot样式见here。例如。（来自链接）： enter image description here

Answer 2

关于在matplotlib之上构建库的统一努力已经有相当多的talk lately，以更直接的方式创建美学上令人愉悦的情节。目前，有几种选择。不幸的是，生态系统严重分散。

除了雅各布提到的mpltools之外，我想指出这三个：

Python-ggplot：http://www.github.com/yhat/ggplot;和
Seaborn：http://www.github.com/mwaskom/seaborn;
prettyplotlib：http://www.github.com/olgabot/prettyplotlib

如果您已经熟悉R的ggplot2，那么您应该对python-ggplot感到非常满意，我衷心鼓励您为此做出贡献。就个人而言，我认为我不会理解那种绘制API的风格（这是对我自己的批评，而不是ggplot）。最后，我粗略地看了Seaborn和prettyplotlib让我相信它们更像是mpltools，因为它们提供了基于matplotlib构建的便利功能。

从事物的声音来看，熊猫社区至少正在努力增加沙棘和ggplot。我个人很兴奋。值得一提的是，所有的努力都是建立在 - 而不是替换 - matplotlib之上。我想大多数人（包括自我）非常感谢MPL开发人员在过去十年中创建的强大而通用的框架。

Answer 3

仔细观察gg代码 - 看起来我有两个问题。第一个是分母应该是n + 1，而不是n。第二个问题是我需要一个色调 - 色度 - 亮度转换工具;而不是我一直在采取的色调 - 亮度 - 饱和度方法。不幸的是，我不知道python中的hcl_to_rgb工具;所以有人写了。

我的解决方案（下面）解决了这两个问题。在我看来，我认为它复制了ggplot2的颜色。

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import math
import collections

def hcl_to_rgb(hue=0, chroma=0, luma=0) :
    # Notes:
    #   coded from http://en.wikipedia.org/wiki/HSL_and_HSV#From_luma.2Fchroma.2Fhue
    #   with insights from gem.c in MagickCore 6.7.8
    #   http://www.imagemagick.org/api/MagickCore/gem_8c_source.html
    # Assume:
    #   h, c, l all in range 0 .. 1 (cylindrical coordinates)
    # Returns a tuple:
    #   r, g, b all in the range 0 .. 1 (cubic cartesian coordinates)

    # sanity checks
    hue = math.modf(float(hue))[0]
    if hue < 0 or hue >= 1 :
        raise ValueError('hue is a value greater than or equal to 0 and less than 1')
    chroma = float(chroma)
    if chroma < 0 or chroma > 1 :
        raise ValueError('chroma is a value between 0 and 1')
    luma = float(luma)
    if luma < 0 or luma > 1 :
        raise ValueError('luma is a value between 0 and 1')

    # do the conversion
    _h = hue * 6.0
    x = chroma * ( 1 - abs((_h % 2) - 1) )

    c = chroma
    if   0 <= _h and _h < 1 :
        r, g, b = (c, x, 0.0)
    elif 1 <= _h and _h < 2 :
        r, g, b = (x, c, 0.0)
    elif 2 <= _h and _h < 3 :
        r, g, b = (0.0, c, x)
    elif 3 <= _h and _h < 4 :
        r, g, b = (0.0, x, c)
    elif 4 <= _h and _h < 5 :
        r, g, b = (x, 0.0, c)
    elif 5 <= _h and _h <= 6 :
        r, g, b = (c, 0.0, x)
    else :
        r, g, b = (0.0, 0.0, 0.0)

    m = luma - (0.298839*r + 0.586811*g + 0.114350*b)
    z = 1.0
    if m < 0.0 :
        z = luma/(luma-m)
        m = 0.0
    elif m + c > 1.0 :
        z = (1.0-luma)/(m+c-luma)
        m = 1.0 - z * c
    (r, g, b) = (z*r+m, z*g+m, z*b+m)

    # clipping ...
    (r, g, b) = (min(r, 1.0), min(g, 1.0), min(b, 1.0))
    (r, g, b) = (max(r, 0.0), max(g, 0.0), max(b, 0.0))
    return (r, g, b)

def ggColorSlice(n=12, hue=(0.004,1.00399), chroma=0.8, luma=0.6, skipHue=True) :
    # Assume:
    #   n: integer >= 1
    #   hue[from, to]: all floats - red = 0; green = 0.33333 (or -0.66667) ; blue = 0.66667 (or -0.33333)
    #   chroma[from, to]: floats all in range 0 .. 1
    #   luma[from, to]: floats all in range 0 .. 1
    # Returns a list of #rgb colour strings:

    # convert stand alone values to ranges
    if not isinstance(hue, collections.Iterable):
        hue = (hue, hue)
    if not isinstance(chroma, collections.Iterable):
        chroma = (chroma, chroma)
    if not isinstance(luma, collections.Iterable):
        luma = (luma, luma)

    # convert ints to floats
    hue = [float(hue[y]) for y in (0, 1)]
    chroma = [float(chroma[y]) for y in (0, 1)]
    luma = [float(luma[y]) for y in (0, 1)]

    # some sanity checks
    n = int(n)
    if n < 1 or n > 360 :
        raise ValueError('n is a value between 1 and 360')
    if any([chroma[y] < 0.0 or chroma[y] > 1.0 for y in (0, 1)]) :
        raise ValueError('chroma is a value between 0 and 1')
    if any([luma[y] < 0.0 or luma[y] > 1.0 for y in (0, 1)]) :
        raise ValueError('luma is a value between 0 and 1')

    # generate a list of hex colour strings
    x = n + 1 if n % 2 else n
    if n > 1 :
        lDiff = (luma[1] - luma[0]) / float(n - 1.0)
        cDiff = (chroma[1] - chroma[0]) / float(n - 1.0)
        if skipHue :
            hDiff = (hue[1] - hue[0]) / float(x)
        else :
            hDiff = (hue[1] - hue[0]) / float(x - 1.0)
    else:
        hDiff = 0.0
        lDiff = 0.0
        cDiff = 0.0

    listOfColours = []
    for i in range(n) :
        c = chroma[0] + i * cDiff
        l = luma[0] + i * lDiff
        h = math.modf(hue[0] + i * hDiff)[0]
        h = h + 1 if h < 0.0 else h
        (h, c, l) = (min(h, 0.99999999999), min(c, 1.0), min(l, 1.0))
        (h, c, l) = (max(h, 0.0), max(c, 0.0), max(l, 0.0))
        (r, g, b) = hcl_to_rgb(h, c, l)
        listOfColours.append( '#%02x%02x%02x' % (int(r*255), int(g*255), int(b*255)) )
    return listOfColours

for i in range(1, 20) :
    # made up data
    x = np.array(range(20))
    d = {}
    for j in range(1, i+1) :
        y = x * (1.0 + j/10.0) + j/10.0
        d['y'+'%03.0d' % j] = pd.Series(data=y , index=x)
    df = pd.DataFrame(d)

    # plot example
    plt.figure(num=1, figsize=(10,5), dpi=100) # set default image size
    colours = ggColorSlice(n=i)
    if len(colours) == 1:
        colours = colours[0] # kludge
    df.plot(linewidth=4.0, color=colours)
    fig = plt.gcf()
    f = 'test-'+str(i)+'.png'
    print f
    plt.title(f)
    fig.savefig(f)
    plt.close()

enter image description here

Answer 4

你想要沿着HUSL颜色空间的色调维度均匀地采样，为此有一个很好的轻量级Python package。这就是seaborn中使用的。

在python中复制R / ggplot2颜色

4 个答案: