利用matplotlib颜色图进行颜色循环

wydwbb8l  于 2022-12-13  发布在  其他
关注(0)|答案(4)|浏览(222)

如果我通过以下方式创建颜色:

import numpy as np
from matplotlib import pyplot as plt

n = 6
color = plt.cm.coolwarm(np.linspace(0.1,0.9,n))
color

color是一个numpy数组:

array([[ 0.34832334,  0.46571115,  0.88834616,  1.        ],
       [ 0.56518158,  0.69943844,  0.99663507,  1.        ],
       [ 0.77737753,  0.84092121,  0.9461493 ,  1.        ],
       [ 0.93577377,  0.8122367 ,  0.74715647,  1.        ],
       [ 0.96049006,  0.61627642,  0.4954666 ,  1.        ],
       [ 0.83936494,  0.32185622,  0.26492398,  1.        ]])

但是,如果我将RGB值(没有alpha值1)作为元组插入到.mplstyle文件(map(tuple,color[:,0:-1]))中,则会出现类似以下的错误:

in file "/home/moritz/.config/matplotlib/stylelib/ggplot.mplstyle"
    Key axes.color_cycle: [(0.34832334141176474 does not look like a color arg
  (val, error_details, msg))

知道为什么吗?

vom3gejh

vom3gejh1#

对于Matplotlib 2.2,使用cycler模块即可完成此操作,无需转换为十六进制值。

import cycler

n = 100
color = pyplot.cm.viridis(np.linspace(0, 1,n))
mpl.rcParams['axes.prop_cycle'] = cycler.cycler('color', color)
baubqpgj

baubqpgj2#

“连续”色彩Map表

如果你想从一个“连续的”色彩Map表(比如默认的viridisMap表)中循环N颜色,the solution by @Gerges可以很好地工作。

import matplotlib.pyplot as plt

N = 6
plt.rcParams["axes.prop_cycle"] = plt.cycler("color", plt.cm.viridis(np.linspace(0,1,N)))

fig, ax = plt.subplots()
for i in range(N):
    ax.plot([0,1], [i, 2*i])

plt.show()

“离散”色彩Map表

Matplotlib提供了一些“离散”的色彩Map表,它们包含少量的不同颜色,用于定性视觉效果,如tab10色彩Map表。要循环使用此类色彩Map表,解决方案可能是不使用N,而只是将Map表的所有颜色都移植到循环器。

import matplotlib.pyplot as plt

plt.rcParams["axes.prop_cycle"] = plt.cycler("color", plt.cm.tab20c.colors)

fig, ax = plt.subplots()
for i in range(15):
    ax.plot([0,1], [i, 2*i])

plt.show()

请注意,只有ListedColormaps具有.colors属性,因此这只适用于那些色彩Map,但不适用于jetMap。

合并溶液

下面是一个通用函数,它将色彩Map表作为输入,并输出相应的循环器。我最初在matplotlib问题中提出了这个解决方案。

from matplotlib.pyplot import cycler
import numpy as np
from matplotlib.colors import LinearSegmentedColormap, ListedColormap
import matplotlib.cm

def get_cycle(cmap, N=None, use_index="auto"):
    if isinstance(cmap, str):
        if use_index == "auto":
            if cmap in ['Pastel1', 'Pastel2', 'Paired', 'Accent',
                        'Dark2', 'Set1', 'Set2', 'Set3',
                        'tab10', 'tab20', 'tab20b', 'tab20c']:
                use_index=True
            else:
                use_index=False
        cmap = matplotlib.cm.get_cmap(cmap)
    if not N:
        N = cmap.N
    if use_index=="auto":
        if cmap.N > 100:
            use_index=False
        elif isinstance(cmap, LinearSegmentedColormap):
            use_index=False
        elif isinstance(cmap, ListedColormap):
            use_index=True
    if use_index:
        ind = np.arange(int(N)) % cmap.N
        return cycler("color",cmap(ind))
    else:
        colors = cmap(np.linspace(0,1,N))
        return cycler("color",colors)

“连续”情况下的用法:

import matplotlib.pyplot as plt
N = 6
plt.rcParams["axes.prop_cycle"] = get_cycle("viridis", N)

fig, ax = plt.subplots()
for i in range(N):
    ax.plot([0,1], [i, 2*i])

plt.show()

“离散”情况下的用法

import matplotlib.pyplot as plt

plt.rcParams["axes.prop_cycle"] = get_cycle("tab20c")

fig, ax = plt.subplots()
for i in range(15):
    ax.plot([0,1], [i, 2*i])

plt.show()
cvxl0en2

cvxl0en23#

**2021年4月编辑:**自matplotlib 2.2.0起,键axes.color_cycle已被弃用(源代码:API更改).新方法是使用set_prop_cyclesource: matplotlib.axes.Axes.set_prop_cycle API

实际上,详细信息在matplotlibrc中:它需要一个字符串rep(十六进制或字母或单词,而不是元组)。

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

fig, ax1 = plt.subplots(1,1)

ys = np.random.random((5, 6))
ax1.plot(range(5), ys)
ax1.set_title('Default color cycle')
plt.show()

# From the sample matplotlibrc:
#axes.color_cycle    : b, g, r, c, m, y, k  # color cycle for plot lines
                                            # as list of string colorspecs:
                                            # single letter, long name, or
                                            # web-style hex

# setting color cycle after calling plt.subplots doesn't "take"
# try some hex values as **string** colorspecs
mpl.rcParams['axes.color_cycle'] = ['#129845','#271254', '#FA4411', '#098765', '#000009']

fig, ax2 = plt.subplots(1,1)
ax2.plot(range(5), ys)
ax2.set_title('New color cycle')

n = 6
color = plt.cm.coolwarm(np.linspace(0.1,0.9,n)) # This returns RGBA; convert:
hexcolor = map(lambda rgb:'#%02x%02x%02x' % (rgb[0]*255,rgb[1]*255,rgb[2]*255),
               tuple(color[:,0:-1]))

mpl.rcParams['axes.color_cycle'] = hexcolor

fig, ax3 = plt.subplots(1,1)
ax3.plot(range(5), ys)
ax3.set_title('Color cycle from colormap')

plt.show()

第一次

kgsdhlau

kgsdhlau4#

如果要局部定义某些内容,可以在出图前添加:

fig, ax4 = plt.subplots(1,1)
ax4.set_prop_cycle(color=plt.cm.plasma(np.linspace(0, 1, n))
ax4.plot(range(5), ys)
ax4.set_title('Color cycle from colormap (local)')

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