import patchworklib as pw
from plotnine import *
from plotnine.data import *

g1  = pw.load_ggplot(ggplot(mtcars) + geom_point(aes("mpg", "disp")),figsize=(4, 2))
g2  = pw.load_ggplot(ggplot(mtcars) + geom_boxplot(aes("gear", "disp", group = "gear")) + theme_classic())
g12 = pw.inset(g1,g2)
g12.savefig()

g12 = pw.inset(g1,g2, loc="lower left", hratio=0.4, wratio=0.2)
g12.savefig("inset_plotnine2.png")

import patchworklib as pw
from plotnine import *
from plotnine.data import *

g1 = pw.load_ggplot(ggplot(mpg, aes(x='cty', color='drv', fill='drv')) +
                    geom_density(aes(y=after_stat('count')), alpha=0.1) +
                    scale_color_discrete(guide=False) +
                    theme(axis_ticks_major_x=element_blank(),
                          axis_text_x =element_blank(),
                          axis_title_x=element_blank(),
                          axis_text_y =element_text(size=12),
                          axis_title_y=element_text(size=14),
                          legend_position="none"),
                    figsize=(4,1))

g2 = pw.load_ggplot(ggplot(mpg, aes(x='hwy', color='drv', fill='drv')) +
                    geom_density(aes(y=after_stat('count')), alpha=0.1) +
                    coord_flip() +
                    theme(axis_ticks_major_y=element_blank(),
                          axis_text_y =element_blank(),
                          axis_title_y=element_blank(),
                          axis_text_x =element_text(size=12),
                          axis_title_x=element_text(size=14)
                         ),
                    figsize=(1,4))

g3 = pw.load_ggplot(ggplot(mpg) +
                    geom_point(aes(x="cty", y="hwy", color="drv")) +
                    scale_color_discrete(guide=False) +
                    theme(axis_text =element_text(size=12),
                          axis_title=element_text(size=14)
                         ),
                    figsize=(4,4))

pw.param["margin"] = 0.2
(g1/(g3|g2)[g3]).savefig() #通过在(g3|g2)中指定g3，g1正好定位在g3上。

当您将 matplotlib.projections.polar.PolarAxes 对象加载为 Brick 类对象时，请使用 'cBrick' 而不是 'Brick'。 现在，您可以使用 pycircos 和 patchworklib 排列多个圆形图。请参阅以下示例代码。 https://colab.research.google.com/drive/1tkn7pxRqh9By5rTFqRbVNDVws-o-ySz9?usp=sharing

排列 Seaborn 网格图

Patchworklib 支持排列基于 axisgrid（FacetGrid、PairGrid 和 JointGrid）生成的多个 Seaborn 图表。 让我们看看以下示例。

import os
import seaborn as sns
import patchworklib as pw
from functools import reduce
pw.overwrite_axisgrid() #使用 pw.load_seagorngrid 时，应执行 'overwrite_axisgrid'。

df = sns.load_dataset("penguins")
g1  = sns.pairplot(df, hue="species")
g1  = pw.load_seaborngrid(g1)
g1.move_legend("upper left", bbox_to_anchor=(0.08,1.01))

planets = sns.load_dataset("planets")
cmap = sns.cubehelix_palette(rot=-.2, as_cmap=True)
g2 = sns.relplot(
    data=planets,
    x="distance", y="orbital_period",
    hue="year", size="mass",
    palette=cmap, sizes=(10, 200),
)
g2.set(xscale="log", yscale="log")
g2.ax.xaxis.grid(True, "minor", linewidth=.25)
g2.ax.yaxis.grid(True, "minor", linewidth=.25)
g2.despine(left=True, bottom=True)
g2 = pw.load_seaborngrid(g2)

penguins = sns.load_dataset("penguins")
g3 = sns.jointplot(
    data=penguins,
    x="bill_length_mm", y="bill_depth_mm", hue="species",
    kind="kde",
)
g3 = pw.load_seaborngrid(g3, labels=["joint","marg_x","marg_y"])
((g2/g3["marg_x"])|g1).savefig()

此外，一些示例代码可在 Google Colaboratory 上执行。

• seaborn grid
• seaborn_ggplot

"stack" 功能

我实现了 stack 功能。此功能允许用户沿指定方向排列多个（两个以上）Brick 或 Bricks 对象，如下所示。

import patchworklib as pw
ax_list = []
for i in range(10):
    ax_list.append(pw.Brick(figsize=(2,2), label="ax{}".format(i)))
stacked_axes = pw.stack(ax_list, operator="|", margin=0.2)
stacked_axes.savefig()

在图表周围添加空白空间

#准备图表数据
import numpy as np 
import matplotlib as mpl
import patchworklib as pw

data1 = 20 * np.random.rand(100,100) - 10
data2 = 20 * np.random.rand(100,100) - 10
cmap = mpl.cm.Reds
norm = mpl.colors.Normalize(vmin=-10, vmax=10)
ax1 = pw.Brick("axx", figsize=(3,3))
ax2 = pw.Brick("axy", figsize=(3,3))
ax1.imshow(data1, interpolation='nearest', cmap=cmap, aspect="auto")
ax2.imshow(data2, interpolation='nearest', cmap=cmap, aspect="auto")

不使用 spacer

ax_cb    = pw.Brick("ax_cb", figsize=(0.1,3))
cb       = mpl.colorbar.ColorbarBase(ax_cb, cmap=cmap, norm=norm)
ax12     = ax1|ax2
heatmap2 = ax12 | ax_cb
heatmap2.savefig()

使用 spacer

ax_cb2   = pw.Brick("ax_cb2", figsize=(0.1,1.5))
cb2      = mpl.colorbar.ColorbarBase(ax_cb2, cmap=cmap, norm=norm)
heatmap2 = ax12 | (pw.spacer(ax_cb2,0.5)/ax_cb2/pw.spacer(ax_cb2,0.5))
heatmap2.savefig()

多个图表的总标题 有时，只需为多个图表设置通用标签和标题。 通过指定 Bricks 类对象的 case 参数，可以处理多个图表的通用 matplotlib 艺术家对象。

ax12.case.set_title("多个图表的总标题", pad=10)
heatmap2 = ax12|(pw.spacer(ax_cb,0.5)/ax_cb/pw.spacer(ax_cb,0.5))
heatmap2.savefig("")

import patchworklib as pw
from plotnine import *
from plotnine.data import *
g1 = pw.load_ggplot(ggplot(mtcars) + geom_point(aes("mpg", "disp")) + theme(figure_size=(2, 3)))
g2 = pw.load_ggplot(ggplot(mtcars) + geom_boxplot(aes("gear", "disp", group = "gear")) + theme(figure_size=(2, 3)))
g12 = g1 | g2
g12.savefig()

g3 = pw.load_ggplot(ggplot(mpg, aes(x='displ', y='hwy')) + geom_point() + geom_smooth(span=.3) + theme(figure_size=(2, 3)))
g4 = pw.load_ggplot(ggplot(mtcars) + geom_bar(aes("carb")) + theme(figure_size=(7, 2)))
g1234 = (g1|g2|g3)/g4
g1234.savefig()