matplotlib：将图例颜色与patchCollection colou匹配

Question

我用（简化）以下代码在图像上覆盖补丁：

import matplotlib.pyplot as plt
from scipy.misc import imread
from matplotlib.collections import PatchCollection
from matplotlib.patches import Circle, Arrow
import numpy as np

def plotFeatures( patches, colours, legends, str_title, colour_scale ):

    fig = plt.figure(); ax = plt.gca()

    p = PatchCollection(patches, cmap=plt.get_cmap('Spectral_r'), alpha=0.9)
    p.set_array(np.array(colours))
    ax.add_collection(p)
    p.set_clim(colour_scale)
    fig.colorbar(p, ax=ax, fraction=0.015)
    plt.xlabel(str_title)
    plt.legend(handles=patches, labels=legends, bbox_to_anchor=(0., 1.02, 1., .2), mode='expand', ncol=3, loc="lower left")
    # ax.set_xticks([]); ax.set_yticks([])
    ax.set_xlim([0,100])
    ax.set_ylim([0,100])


if __name__ == '__main__':

    my_cmap = plt.get_cmap('Spectral_r')

    # simplified data structure for example
    allweights = [  {'name': 'Feature 1', 'mean': 2.1, 'x': 60, 'y':30},
                    {'name': 'Feature 2', 'mean': 3.0, 'x': 10, 'y':40},
                    {'name': 'Feature 3', 'mean': 2.5, 'x': 30, 'y':20} ]

    KPD_patchList  = []
    KPD_colourList = []
    KPD_legendList = []

    for w in allweights:
        KPD_patchList.append( Circle( (w['x'], w['y']), w['mean'] + 5 ) )
        KPD_colourList.append( w['mean'] )
        KPD_legendList.append( '{:s} ({:.2f})'.format( w['name'], w['mean']) )

    plotFeatures( KPD_patchList, KPD_colourList, KPD_legendList, 'myFeatures', [0, 3] )

    plt.show()

结果是：

然而，图例中的补丁没有正确的颜色。在

我的问题是我设置了补丁的颜色，但是plt.图例（）不接受手柄的补丁集合，我必须给它提供不包含颜色数据的补丁。在

当我调用Cricle时，我尝试直接用facecolor=my_cmap(w['mean']将颜色数据添加到面片中，如下所示：

^{pr2}$

但是，颜色的比例并不像图中那样均匀：

Answer 1

我认为你的第二次尝试是正确的，除了你的数据没有被正确地规范化。 当您试图从colormap获取颜色值时，需要提供一个范围为[0-1]的值。为了使事情更简单，我经常使用matplotlib.cm.ScalarMappable（link to documentation）来自动处理这个转换。在

为了解决您的问题，我修改了plotFeatures()函数，如下所示：

def plotFeatures( patches, colours, legends, str_title, colour_scale ):

    fig = plt.figure(); ax = plt.gca()

    p = PatchCollection(patches, cmap=plt.get_cmap('Spectral_r'), alpha=0.9)
    p.set_array(np.array(colours))
    ax.add_collection(p)
    p.set_clim(colour_scale)
    fig.colorbar(p, ax=ax, fraction=0.015)
    plt.xlabel(str_title)

    # generate legend
    # create a `ScalarMappable` object with the colormap used, and the right scaling
    cm = matplotlib.cm.ScalarMappable(cmap=p.get_cmap())
    cm.set_clim(colour_scale)
    # create a list of Patches for the legend
    l = [Circle((None,None), facecolor=cm.to_rgba(mean_value)) for mean_value in colours]
    # add legend to plot
    plt.legend(handles=l, labels=legends, bbox_to_anchor=(0., 1.02, 1., .2), mode='expand', ncol=3, loc="lower left")


    # ax.set_xticks([]); ax.set_yticks([])
    ax.set_xlim([0,100])
    ax.set_ylim([0,100])