在seaborn FacetGrid热图图中获取传奇

我们怎样才能获得seaborn FacetGrid热图的传说？该.add_legend()方法对我不起作用.

使用上一个问题中的代码:

import pandas as pd
import numpy as np
import itertools
import seaborn as sns

print("seaborn version {}".format(sns.__version__))
# R expand.grid() function in Python
# /sf/ask/17360801/
def expandgrid(*itrs):
   product = list(itertools.product(*itrs))
   return {'Var{}'.format(i+1):[x[i] for x in product] for i in range(len(itrs))}

methods=['method 1', 'method2', 'method 3', 'method 4']
times = range(0,100,10)
data = pd.DataFrame(expandgrid(methods, times, times))
data.columns = ['method', 'dtsi','rtsi']
data['nw_score'] = np.random.sample(data.shape[0])

def facet(data,color):
    data = data.pivot(index="dtsi", columns='rtsi', values='nw_score')
    g = sns.heatmap(data, cmap='Blues', cbar=False)

with sns.plotting_context(font_scale=5.5):
    g = sns.FacetGrid(data, col="method", col_wrap=2, size=3, aspect=1)
    g = g.map_dataframe(facet)
    g.add_legend()
    g.set_titles(col_template="{col_name}", fontweight='bold', fontsize=18)

你想要的(在matplotlib术语中)是一个颜色条,而不是一个图例.在matplotlib中,前者用于连续数据,而后者用于分类数据.Colorbar支持不是内置的FacetGrid,但是扩展示例代码以添加颜色条并不困难:

import pandas as pd
import numpy as np
import itertools
import seaborn as sns

methods=['method 1', 'method2', 'method 3', 'method 4']
times = range(0, 100, 10)
data = pd.DataFrame(list(itertools.product(methods, times, times)))
data.columns = ['method', 'dtsi','rtsi']
data['nw_score'] = np.random.sample(data.shape[0])

def facet_heatmap(data, color, **kws):
    data = data.pivot(index="dtsi", columns='rtsi', values='nw_score')
    sns.heatmap(data, cmap='Blues', **kws)  # <-- Pass kwargs to heatmap

with sns.plotting_context(font_scale=5.5):
    g = sns.FacetGrid(data, col="method", col_wrap=2, size=3, aspect=1)

cbar_ax = g.fig.add_axes([.92, .3, .02, .4])  # <-- Create a colorbar axes

g = g.map_dataframe(facet_heatmap,
                    cbar_ax=cbar_ax,
                    vmin=0, vmax=1)  # <-- Specify the colorbar axes and limits

g.set_titles(col_template="{col_name}", fontweight='bold', fontsize=18)
g.fig.subplots_adjust(right=.9)  # <-- Add space so the colorbar doesn't overlap the plot

我已经指出了我所做的更改以及它们作为内联注释的基本原理.