Seaborn Complex Heatmap ---在瓦片内绘制圆圈来表示复杂的注释 [英] Seaborn Complex Heatmap---drawing circles within tiles to denote complex annotation
问题描述
我在 python 中有两个数据框.
I have two data-frames in python.
data_A
Name X Y
A 1 0
B 1 1
C 0 0
data_B
Name X Y
A 0 1
B 1 1
C 0 1
我想重叠这些热图，如果它在 data_frame A 中为 1，则图块为紫色(或任何颜色)，但如果在 data_frame B 中为 1，则绘制一个圆圈(最好是第一).
I would like to overlap these heatmaps, where if it is a 1 in data_frame A, then the tile is colored purple (or any color), but if it's a 1 in data_frame B, then a circle is drawn (preferably the first one).
例如，热图将显示 A[,X][1] 紫色，但那些在两个数据框中都为 1 的将是带有点的紫色.C[,Y][3] 只有一个点，而 C[,X][3] 什么都没有.
So for example, the heatmap would show A[,X][1] colored purple, but those with 1 in both data frames would be purple with a dot. C[,Y][3] would have just a dot, while C[,X][3] would have nothing.
我似乎可以用 seaborn 进行遮罩，并用不同的颜色绘制两个热图，但颜色差异不够清晰，用户只能看到一个磁贴只有一个而不是两个.我认为在一个矩阵中用圆圈表示正数会更好.
I can seem to mask, with seaborn, and plot two heatmaps with different colors, but the color differential isn't clear enough that a user can simply see that a tile has only one versus both. I think having a circle to denote a positive in one matrix would be better.
有人知道如何使用 seaborn 将圆圈绘制到热图上吗?
Does anyone have an idea of how to plot circles onto a heatmap using seaborn?
推荐答案
要显示热图，您可以使用 imshow 图.要显示一些点，您可以使用 scatter 图.然后在相同的轴上绘制两者.
To show a heatmap you may use an imshow plot. To show some dots, you may use a scatter plot. Then just plot both in the same axes.
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
dfA = pd.DataFrame([[1,0],[1,1],[0,0]], columns=list("XY"), index=list("ABC"))
dfB = pd.DataFrame([[0,1],[1,1],[0,1]], columns=list("XY"), index=list("ABC"))
assert dfA.shape == dfB.shape
x = np.arange(0,len(dfA.columns))
y = np.arange(0,len(dfB.index))
X,Y=np.meshgrid(x,y)
fig, ax = plt.subplots(figsize=(2.6,3))
ax.invert_yaxis()
ax.imshow(dfA.values, aspect="auto", cmap="Purples")
cond = dfB.values == 1
ax.scatter(X[cond], Y[cond], c="crimson", s=100)
ax.set_xticks(x)
ax.set_yticks(y)
ax.set_xticklabels(dfA.columns)
ax.set_yticklabels(dfA.index)
plt.show()
使用点在同一热图上显示多个数据集的替代方法也可以
Alternatives to using a dot to show several datasets on the same heatmap could also
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