seaborn clustermap：subplots_adjust 取消颜色条重定位

Question

我正在尝试使用 seaborn 制作带有侧面颜色条的热图。但是，在我的实际应用案例中，我有很长的列名要轮换。这需要使用plt.subplots_adjust，否则标签不适合图像：

plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
plt.subplots_adjust(bottom=0.5)

使用以下最小示例，我发现最后一条命令正在取消彩条重定位：

#!/usr/bin/env python3

import seaborn as sns
import matplotlib.pyplot as plt

iris = sns.load_dataset("iris")
species = iris.pop("species")
# Make long column names
iris.columns = ["________".join(label.split("_")) for label in iris.columns]


g = sns.clustermap(iris, col_cluster=False, yticklabels=False)
# Relocate colour bar on the side
g.cax.set_position([.15, .2, .03, .45])
plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
plt.savefig("/tmp/unadjusted.png")

plt.cla()

g = sns.clustermap(iris, col_cluster=False, yticklabels=False)
g.cax.set_position([.15, .2, .03, .45])
plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
# Adjust to have the column labels not cut out
plt.subplots_adjust(bottom=0.5)
plt.savefig("/tmp/adjusted.png")

这会产生以下图像：

没有plt.subplots_adjust：

与plt.subplots_adjust:

为什么会这样？

这是一个错误吗？

我可以做些什么来让颜色条出现在我想要的位置并且仍然确保我的旋转颜色标签不会被剪切？

Answer 1

根据@ImportanceOfBeingErnest 的建议，我尝试在移动彩条之前进行调整。这导致了以下图像：

由于我其实不想要树状图，而只想要聚类，所以使用树状图框放置彩条可以获得更令人满意的结果：

#!/usr/bin/env python3

import seaborn as sns
import matplotlib.pyplot as plt

iris = sns.load_dataset("iris")
species = iris.pop("species")
# Make long column names
iris.columns = ["________".join(label.split("_")) for label in iris.columns]

g = sns.clustermap(iris, col_cluster=False, yticklabels=False)
plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
# Adjust to have the column labels not cut out
plt.subplots_adjust(bottom=0.5)
g.cax.set_position([.15, .2, .03, .45])
plt.savefig("/tmp/adjusted_before.png")

plt.cla()

g = sns.clustermap(iris, col_cluster=False, yticklabels=False)
plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
# Adjust to have the column labels not cut out
plt.subplots_adjust(bottom=0.5)
# Remove the dendrogram (https://stackoverflow.com/a/42418968/1878788)
g.ax_row_dendrogram.set_visible(False)
# Use the dendrogram box to reposition the colour bar
dendro_box = g.ax_row_dendrogram.get_position()
dendro_box.x0 = (dendro_box.x0 + 2 * dendro_box.x1) / 3
g.cax.set_position(dendro_box)
# Move the ticks to the left (https://stackoverflow.com/a/36939552/1878788)
g.cax.yaxis.set_ticks_position("left")
# If we add a label to the colour bar
# (cbar_kws={"label" : "the_label"} in clustermap arguments)
# we also need to move the label
# g.cax.yaxis.set_label_position("left")
plt.savefig("/tmp/adjusted_before_using_row_dendrogram_box.png")

这会生成以下图像：

---

编辑：plt.tight_layout 也会出现同样的问题。

进一步开发我的热图，我想添加带有图例的行颜色（使用this answer 中提出的方法）。在我的实际应用案例中，图例占用了足够的水平空间以从图像中切出。

我想使用plt.tight_layout 来调整图像。这再次干扰了彩条重定位（甚至无法解决剪切图例问题...），如下面的示例所示。

#!/usr/bin/env python3

import seaborn as sns
import matplotlib.pyplot as plt

iris = sns.load_dataset("iris")
species = iris.pop("species")
# Make long column names
iris.columns = ["________".join(label.split("_")) for label in iris.columns]


# Associating colours with species
species_list = species.unique()
label_colours = dict(zip(species_list, sns.color_palette("colorblind", len(species_list))))
row_colours = species.map(label_colours)

g = sns.clustermap(iris, col_cluster=False, yticklabels=False, row_colors=row_colours, cbar_kws={"label" : "measure"})
# Adding row colour legend
# https://stackoverflow.com/a/27992943/1878788
for (label, colour) in label_colours.items():
    # Make long label
    g.ax_col_dendrogram.bar(0, 0, color=colour, label="Iris___________________{}".format(label))
g.ax_col_dendrogram.legend(loc="center", ncol=3)
# Rotating column labels
plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
# Adjust to have the column labels not cut out
plt.subplots_adjust(bottom=0.5)
# Remove the dendrogram (https://stackoverflow.com/a/42418968/1878788)
g.ax_row_dendrogram.set_visible(False)
# Use the dendrogram box to reposition the colour bar
dendro_box = g.ax_row_dendrogram.get_position()
dendro_box.x0 = (dendro_box.x0 + 2 * dendro_box.x1) / 3
g.cax.set_position(dendro_box)
# Move the ticks and labels to the left (https://stackoverflow.com/a/36939552/1878788)
g.cax.yaxis.set_ticks_position("left")
g.cax.yaxis.set_label_position("left")
plt.savefig("/tmp/with_row_colour_lengend.png")

plt.cla()

g = sns.clustermap(iris, col_cluster=False, yticklabels=False, row_colors=row_colours, cbar_kws={"label" : "measure"})
# Adding row colour legend
# https://stackoverflow.com/a/27992943/1878788
for (label, colour) in label_colours.items():
    # Make long label
    g.ax_col_dendrogram.bar(0, 0, color=colour, label="Iris___________________{}".format(label))
g.ax_col_dendrogram.legend(loc="center", ncol=3)
# Rotating column labels
plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
# Adjust to have the column labels not cut out
plt.subplots_adjust(bottom=0.5)
# Remove the dendrogram (https://stackoverflow.com/a/42418968/1878788)
g.ax_row_dendrogram.set_visible(False)
# Use the dendrogram box to reposition the colour bar
dendro_box = g.ax_row_dendrogram.get_position()
dendro_box.x0 = (dendro_box.x0 + 2 * dendro_box.x1) / 3
g.cax.set_position(dendro_box)
# Move the ticks and labels to the left (https://stackoverflow.com/a/36939552/1878788)
g.cax.yaxis.set_ticks_position("left")
g.cax.yaxis.set_label_position("left")
plt.tight_layout()
plt.savefig("/tmp/tight_after.png")

plt.cla()

g = sns.clustermap(iris, col_cluster=False, yticklabels=False, row_colors=row_colours, cbar_kws={"label" : "measure"})
# Adding row colour legend
# https://stackoverflow.com/a/27992943/1878788
for (label, colour) in label_colours.items():
    # Make long label
    g.ax_col_dendrogram.bar(0, 0, color=colour, label="Iris___________________{}".format(label))
g.ax_col_dendrogram.legend(loc="center", ncol=3)
plt.tight_layout()
# Rotating column labels
plt.setp(g.ax_heatmap.get_xticklabels(), rotation=90)
# Adjust to have the column labels not cut out
plt.subplots_adjust(bottom=0.5)
# Remove the dendrogram (https://stackoverflow.com/a/42418968/1878788)
g.ax_row_dendrogram.set_visible(False)
# Use the dendrogram box to reposition the colour bar
dendro_box = g.ax_row_dendrogram.get_position()
dendro_box.x0 = (dendro_box.x0 + 2 * dendro_box.x1) / 3
g.cax.set_position(dendro_box)
# Move the ticks and labels to the left (https://stackoverflow.com/a/36939552/1878788)
g.cax.yaxis.set_ticks_position("left")
g.cax.yaxis.set_label_position("left")
plt.savefig("/tmp/tight_before.png")

结果如下图：

没有plt.tight_layout，最右边的标签被剪掉（物种应该是“virginica”）：

重定位彩条后调用plt.tight_layout：

在重新定位彩条之前调用plt.tight_layout：