如何对齐第二轴中心的热图y-滴答

Question

我有这样一个数据框架：

l1 = ['A','A','A','A','A','A','A','A','A','A','B','B','B','B','B','B','B','B','B','B']
l2 = ['Name-1','Name-2','Name-3','Name-4','Name-5','Name-6','Name-7','Name-8','Name-9','Name-10','Name-11','Name-12','Name-13','Name-14','Name-15','Name-16','Name-17','Name-18','Name-19','Name-20']
v1 = [1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,0,0,0,1,1]
v2 = [0,0,0,1,1,1,0,0,1,1,0,0,0,1,1,1,0,0,1,1]
v3 = [1,0,1,1,1,0,0,0,0,0,1,0,1,1,1,0,0,0,0,0]
v4 = [0,0,0,0,1,1,1,0,0,1,0,0,0,0,1,1,1,0,0,1]
v5 = [1,0,1,0,1,0,1,0,1,1,1,0,1,0,1,0,1,0,1,1]
v6 = [1,1,0,0,1,1,0,1,0,1,1,1,0,0,1,1,0,1,0,1]
v7 = [0,0,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,0,1]
v8 = [0,1,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,0,1,1]
v9 = [1,1,0,1,1,1,0,0,0,1,1,1,0,1,1,1,0,0,0,1]
v10 =[1,1,1,0,0,0,1,1,0,1,1,1,1,0,0,0,1,1,0,1]
d = {'variable': l1, 'value': l2,'ID1': v1,'ID2': v2,'ID3': v3,'ID4': v4,'ID5': v5,'ID6': v6,'ID7': v7,'ID8': v8,'ID9': v9,'ID10': v10} 
df = pd.DataFrame(d)
df = df.set_index(['variable','value'])

sum_list = df.sum(axis=0)

我在左边和右边创建了一个带有Y字号标签的热图。看起来是这样的：

sns.set(rc={'figure.figsize': (10,10),'xtick.labelsize': 12,'ytick.labelsize': 12, 'axes.labelcolor': 'black',
           'ytick.left': True, 'ytick.right': True,'axes.grid': False,})
heat_map = sns.heatmap(df.reset_index(level='variable', col_level=0,drop=True),square=False,yticklabels=True,xticklabels=False,cmap=['#FFFFFF','#ff0303'],vmin=0,vmax=1,cbar=False,linewidths=1,linecolor='black', annot_kws={"fontsize":3})
heat_map.set_yticklabels(labels=heat_map.get_yticklabels(),weight='bold',color='black')
heat_map.set(xlabel=None,ylabel=None)
sec_axis=heat_map.twinx()
sec_axis.set_yticks(heat_map.get_yticks())
sec_axis.set_yticklabels(df.sum(axis=1).values[::-1], weight='bold', color='black', fontsize=12) ## Add tick labels which will be the sum
sec_axis.grid(False)

通过添加第二个y-滴答标签(右侧)，我沿着四个边的边消失了，右边的边在中间不对齐。我想：

1. Display热图和边缘visible
2. Center-align在二次y-axis

上的细胞

我的热图是这样的：

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Answer 1

您可以使用tiwnx()添加第二轴。使用df.sum(axis=1).values[::-1]获取每行值的和，以便将和按正确的顺序设置，然后使用set_yticklabels()显示相同的值。将以下代码添加到现有代码中。

sec_axis=heat_map.twinx() ##sec_axis in the secondary axis (y axis on right)
sec_axis.set_yticks(heat_map.get_yticks()) ## Use same ticks as the primary axis
sec_axis.set_yticklabels(df.sum(axis=1).values[::-1], weight='bold', color='black', fontsize=12) ## Add tick labels which will be the sum
sec_axis.grid(False) ## Remove any grid lines for secondary axis if present

新REQ

我已经更新了代码以调整二级y-滴答。看起来边缘线在你最初的情节或请求中没有出现。不管怎么说，也添加了代码。

使用

• 来调整y-ticks，使用get_ylim()并对其进行调整，使其调整为主要的y-滴答，并使用set_major_locator()来设置次要的y-滴答，但这似乎没有显示。用轴线和轴线代替。

l1 = ['A','A','A','A','A','A','A','A','A','A','B','B','B','B','B','B','B','B','B','B']
l2 = ['Name-1','Name-2','Name-3','Name-4','Name-5','Name-6','Name-7','Name-8','Name-9','Name-10','Name-11','Name-12','Name-13','Name-14','Name-15','Name-16','Name-17','Name-18','Name-19','Name-20']
v1 = [1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,0,0,0,1,1]
v2 = [0,0,0,1,1,1,0,0,1,1,0,0,0,1,1,1,0,0,1,1]
v3 = [1,0,1,1,1,0,0,0,0,0,1,0,1,1,1,0,0,0,0,0]
v4 = [0,0,0,0,1,1,1,0,0,1,0,0,0,0,1,1,1,0,0,1]
v5 = [1,0,1,0,1,0,1,0,1,1,1,0,1,0,1,0,1,0,1,1]
v6 = [1,1,0,0,1,1,0,1,0,1,1,1,0,0,1,1,0,1,0,1]
v7 = [0,0,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,0,1]
v8 = [0,1,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,0,1,1]
v9 = [1,1,0,1,1,1,0,0,0,1,1,1,0,1,1,1,0,0,0,1]
v10 =[1,1,1,0,0,0,1,1,0,1,1,1,1,0,0,0,1,1,0,1]
d = {'variable': l1, 'value': l2,'ID1': v1,'ID2': v2,'ID3': v3,'ID4': v4,'ID5': v5,'ID6': v6,'ID7': v7,'ID8': v8,'ID9': v9,'ID10': v10} 
df = pd.DataFrame(d)
df = df.set_index(['variable','value'])
sum_list = df.sum(axis=0)
sns.set(rc={'figure.figsize': (10,10),'xtick.labelsize': 12, 'ytick.labelsize': 12, 'axes.labelcolor': 'black', 'ytick.left': True, 'ytick.right': True})

heat_map = sns.heatmap(df.reset_index(level='variable', col_level=0, drop=True),square=False,yticklabels=True, xticklabels=False,cmap=['#FFFFFF','#ff0303'], vmin=0,vmax=1,cbar=False,linewidths=1, linecolor='black', annot_kws={"fontsize":3})
heat_map.set_yticklabels(labels=heat_map.get_yticklabels(),weight='bold',color='black')

sec_axis=heat_map.twinx()

import matplotlib.ticker
l = heat_map.get_ylim()
l2 = sec_axis.get_ylim()
f = lambda x : l2[0]+(x-l[0])/(l[1]-l[0])*(l2[1]-l2[0])
ticks = f(heat_map.get_yticks())
sec_axis.yaxis.set_major_locator(matplotlib.ticker.FixedLocator(ticks))

sec_axis.set_yticklabels(df.sum(axis=1).values, ha="center", weight='bold', color='black', fontsize=12, va="center")
sec_axis.grid(False)

heat_map.axhline(y = 0, color = 'k', linewidth = 5)
heat_map.axhline(y = 20, color = 'k', linewidth = 5)
heat_map.axvline(x = 0, color = 'k', linewidth = 5)
heat_map.axvline(x = 20, color = 'k', linewidth = 5)

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