Python 自定义注释 Seaborn 热图
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Custom Annotation Seaborn Heatmap
提问by Tgsmith61591
I'm using Seaborn in Python to create a Heatmap. I'm able to annotate the cells with the values passed in, but I'd like to add annotations that signify what the cell means. For example, instead of merely seeing 0.000000, I'd like to see the corresponding label, for instance "Foo," or 0.000000 (Foo).
我在 Python 中使用 Seaborn 来创建热图。我可以用传入的值注释单元格，但我想添加表示单元格含义的注释。例如，0.000000我希望看到相应的标签，而不是仅仅看到，例如“Foo”或0.000000 (Foo)。
The Seaborn documentationfor the heatmap function is a bit cryptic with the parameter that I believe is the key here:
热图函数的Seaborn 文档有点神秘，我认为参数是这里的关键：
annot_kws : dict of key, value mappings, optional
Keyword arguments for ax.text when annot is True.
I tried setting annot_kwsto a dictionary of the aliases to the values, i.e., {'Foo' : -0.231049060187, 'Bar' : 0.000000}, etc., but I'm getting an AttributeError.
我尝试设置annot_kws为值的别名字典，即{'Foo' : -0.231049060187, 'Bar' : 0.000000}，等，但我收到一个 AttributeError。
Here is my code (I've manually created the data array here for reproducability):
这是我的代码（为了可重复性，我在这里手动创建了数据数组）：
data = np.array([[0.000000,0.000000],[-0.231049,0.000000],[-0.231049,0.000000]])
axs = sns.heatmap(data, vmin=-0.231049, vmax=0, annot=True, fmt='f', linewidths=0.25)
Here is the (working) output when I don't use the annot_kwsparameter:
这是我不使用annot_kws参数时的（工作）输出：
And here the stack trace for when I doinclude the annot_kwsparam:
在这里，当我在堆栈跟踪做包括annot_kwsPARAM：
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-57-38f91f1bb4b8> in <module>()
12
13
---> 14 axs = sns.heatmap(data, vmin=min(uv), vmax=max(uv), annot=True, annot_kws=kws, linewidths=0.25)
15 concepts
/opt/anaconda/2.3.0/lib/python2.7/site-packages/seaborn/matrix.pyc in heatmap(data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, linewidths, linecolor, cbar, cbar_kws, cbar_ax, square, ax, xticklabels, yticklabels, mask, **kwargs)
272 if square:
273 ax.set_aspect("equal")
--> 274 plotter.plot(ax, cbar_ax, kwargs)
275 return ax
276
/opt/anaconda/2.3.0/lib/python2.7/site-packages/seaborn/matrix.pyc in plot(self, ax, cax, kws)
170 # Annotate the cells with the formatted values
171 if self.annot:
--> 172 self._annotate_heatmap(ax, mesh)
173
174 # Possibly add a colorbar
/opt/anaconda/2.3.0/lib/python2.7/site-packages/seaborn/matrix.pyc in _annotate_heatmap(self, ax, mesh)
138 val = ("{:" + self.fmt + "}").format(val)
139 ax.text(x, y, val, color=text_color,
--> 140 ha="center", va="center", **self.annot_kws)
141
142 def plot(self, ax, cax, kws):
/opt/anaconda/2.3.0/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in text(self, x, y, s, fontdict, withdash, **kwargs)
590 if fontdict is not None:
591 t.update(fontdict)
--> 592 t.update(kwargs)
593 self.texts.append(t)
594 t._remove_method = lambda h: self.texts.remove(h)
/opt/anaconda/2.3.0/lib/python2.7/site-packages/matplotlib/artist.pyc in update(self, props)
755 func = getattr(self, 'set_' + k, None)
756 if func is None or not six.callable(func):
--> 757 raise AttributeError('Unknown property %s' % k)
758 func(v)
759 changed = True
AttributeError: Unknown property tokenized
Finally, kws, the attribute I'm passing in the line in the stack trace, is the dictionary and it would look basically like this:
最后，kws我在堆栈跟踪的行中传递的属性是字典，它基本上如下所示：
kws = {'Foo': -0.231049060187, 'Bar': 0.0}
Hope everything makes sense, and I'd appreciate any help anyone can give.
希望一切都有意义，我很感激任何人可以提供的任何帮助。
采纳答案by ojy
This feature has just been added in the recent version of Seaborn 0.7.1.
此功能刚刚添加到最新版本的 Seaborn 0.7.1 中。
From Seaborn update history:
The annot parameter of heatmap() now accepts a rectangular dataset in addition to a boolean value. If a dataset is passed, its values will be used for the annotations, while the main dataset will be used for the heatmap cell colors
除了布尔值之外，heatmap() 的 annot 参数现在还接受矩形数据集。如果传递了数据集，则其值将用于注释，而主数据集将用于热图单元格颜色
Here is an example
这是一个例子
data = np.array([[0.000000,0.000000],[-0.231049,0.000000],[-0.231049,0.000000]])
labels = np.array([['A','B'],['C','D'],['E','F']])
fig, ax = plt.subplots()
ax = sns.heatmap(data, annot = labels, fmt = '')
Note, fmt = '' is necessary if you are using non-numeric labels, since the default value is fmt='.2g' which makes sense only for numeric values and would lead to an error for text labels.
请注意，如果您使用非数字标签，则 fmt = '' 是必需的，因为默认值是 fmt='.2g' 这仅对数字值有意义并且会导致文本标签错误。
回答by Sergey Bushmanov
aanot_kwsin Seaborn serves a different purpose, namely, it provides access to howannotations are displayed, rather than whatis displayed
aanot_kws在Seaborn用于不同的用途，即，它提供了访问如何被显示的注释，而不是什么显示
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
fig, ax = plt.subplots(1,2)
ata = np.array([[0.000000,0.000000],[-0.231049,0.000000],[-0.231049,0.000000]])
sns.heatmap(data, vmin=-0.231049, vmax=0, annot=True, fmt='f', annot_kws={"size": 15}, ax=ax[0])
sns.heatmap(data, vmin=-0.231049, vmax=0, annot=True, fmt='f', annot_kws={"size": 10}, ax=ax[1]);
回答by Sergey Bushmanov
I don't believe this is possible in the current version. If you are up to a hack-y workaround, you could do the following ...
我不相信在当前版本中这是可能的。如果您采用 hack-y 解决方法，则可以执行以下操作...
# Create the 1st heatmap without labels
sns.heatmap(data=df1, annot=False,)
# create the second heatmap, which contains the labels,
# turn the annotation on,
# and make it transparent
sns.heatmap(data=df2, annot=True, alpha=0.0)
Note that you may have a problem with the coloring of your text labels. Here, I created a custom cmapto have all labels uniformly black.
请注意，您的文本标签的颜色可能有问题。在这里，我创建了一个自定义cmap，使所有标签都统一为黑色。
