Patchworklib is a universal composer of matplotlib-related plots (simple matplotlib plots, Seaborn plots (both axis-level and figure-level), and plotnine plots). This library is inspired by patchwork for ggplot2. Accordingly, as original patchwork, users can easily align matplotlib plots with only "/" and "|" operators. Although a good subplot composer, "subplot_mosaic" is provided from matplotlib formally, I believe the way of patchworklib is more straightforward and more flexible.
Additionally, several third-party libraries based on matplotlib, such as plotnine and seaborn, provide functions to generate beautiful plots with simple python codes, but many of those plots cannot be handled as matplotlib subplots. Therefore, their placement must be adjusted manually. Now, scientists spend their valuable time arranging figures.
Patchworklib provides a solution for the problem. By using patchworklib, any kind of seaborn and plotnine plots can be handled as matplotlib subplots.
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For normal users, we recommended you to install the official release as follows.
pip install patchworklib
If you want to use developmental version, it can be installed using the following single command:
pip install git+https://github.com/ponnhide/patchworklib.git
align_xlabels and align_ylabels, which help users align x/y labels of the given Brick object.equal_spacing was added to the stack function. If this value is True, axes bounding-boxes should be placed with equal spacing between them. Otherwise, depending on the text values of x/y tick labels and x/y labels, they may not always be equally spaced.keep_aspect parameter to hstack and vstack funciton.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() #By specifying g3 in (g3|g2), g1 is positioned exactly on g3.
basefigure parameter was added. You can access the base figure of patchworklib by patchworklib.basefigureload_seaborngrid can accepts a seaborn.clustermap plot. For details, see example code on Google colabpatchworklib.Bricks class to set common label, title, spine and colorbar for Brick objets in the Bricks object.move_legend were fixed. (The move_legend for seaborn grided plot was not working properly.)savefig operation.When you load a matplotlib.projections.polar.PolarAxes object as a Brick class object, please use 'cBrick' instead of 'Brick'.
Now, you can arrange multiple circos plots using pycircos and patchworklib. Please see the following example code.
https://colab.research.google.com/drive/1tkn7pxRqh9By5rTFqRbVNDVws-o-ySz9?usp=sharing
Patchworklib supported the function to arange multiple seborn plots generated based on axisgrid (FacetGrid, PairGrid, and JointGrid). Let's see the follwoing example.
import os
import seaborn as sns
import patchworklib as pw
from functools import reduce
pw.overwrite_axisgrid() #When you use pw.load_seagorngrid, 'overwrite_axisgrid' should be executed.
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()
Also, some example codes are made executable in Google Colaboratory.
I implemented the stack function. This function allows users to arrange multiple (more than two) Brick or Bricks objects along the specified direction as follows.
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()
Add empty spaces around a plot
#preparation of plot data
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")
w/o 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()
w/ 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()
Super titile for multiple plots
Sometimes, all that is needed to have common labels and title for multiple plots.
By specifying case parameter of a Bricks class object, common matplotlib artist ojbects for multiple plots can be handled.
ax12.case.set_title("A global title for multiple plots", 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()
If you want to know how to use patchworklib in detail, please see API.md.
Using patchworklib, you can quickly and freely arrange matplotlib plots with only | and / oparators as follows.
import patchworklib as pw
import seaborn as sns
fmri = sns.load_dataset("fmri")
ax1 = pw.Brick(figsize=(3,2))
sns.lineplot(x="timepoint", y="signal", hue="region", style="event", data=fmri, ax=ax1)
ax1.legend(bbox_to_anchor=(1.05, 1.0), loc='upper left')
ax1.set_title("ax1")
titanic = sns.load_dataset("titanic")
ax2 = pw.Brick(figsize=(1,2))
sns.barplot(x="sex", y="survived", hue="class", data=titanic, ax=ax2)
ax2.move_legend(new_loc='upper left', bbox_to_anchor=(1.05, 1.0))
ax2.set_title("ax2")
ax12 = ax1|ax2
ax12.savefig("ax12.png")
Jupyter Notebook files for all of the example codes are provided in patchworklib-examples and also made executable in Google Colaboratory.
Arrangement of multiple axis-level seaborn plots
Arrangement of multiple Plotnine plots
Arrangement of multiple figure-level seaborn plots
Tutorial ~Compose multiple seaborn plots~ The follwoing tutorial codes can be executable in tutorial1
import patchworklib as pw
fmri = sns.load_dataset("fmri")
ax1 = pw.Brick("ax1", figsize=(4,2))
sns.lineplot(x="timepoint", y="signal", hue="region", style="event", data=fmri, ax=ax1)
ax1.move_legend(new_loc='upper right')
ax1.set_title("ax1")
Creating some example plots using the searborn module. Brick class provided by the patchworklib module is implemented as subclass of matplotlib.axes.Axes. Therefore, Brick class object can be given to the seaborn plot functions that have the ax parameters.
When creating a Brick class object, the label value should be specified, and it should be unique among the Brick class objects generated in the python script (If the label value is not specified, the unique label name is automatically given. By using get_label() method, the value can be confirmed). The figisize parameter can also be specified. However, the value is not very important because the figure size of Brick class objects can be automatically adjusted in arranging the plots. The savefig(filename=str) method returns matplotlib.figure.Figure class object. If filename is given, the figure object can be output to the file.
import seaborn as sns
#Example plot 1 (ref: https://seaborn.pydata.org/examples/errorband_lineplots.html)
fmri = sns.load_dataset("fmri")
ax1 = pw.Brick("ax1", figsize=(4,2))
sns.lineplot(x="timepoint", y="signal", hue="region", style="event", data=fmri, ax=ax1)
ax1.move_legend(new_loc='upper right')
ax1.set_title("ax1")
ax1.savefig()
Brick class provides the movelegend(loc=str, bbox_to_anchor=(float,float)) method. By using this method, legend location can be quickly modified.
#Example plot 2 (ref: https://seaborn.pydata.org/tutorial/categorical.html)
titanic = sns.load_dataset("titanic")
ax2 = pw.Brick("ax2", figsize=(1,2))
sns.barplot(x="sex", y="survived", hue="class", data=titanic, ax=ax2)
ax2.move_legend(new_loc='upper left', bbox_to_anchor=(1.05, 1.0)) #Original method of Blick class
ax2.set_title("ax2")
ax2.savefig()
#Example plot 3 (ref: https://seaborn.pydata.org/examples/histogram_stacked.html)
diamonds = sns.load_dataset("diamonds")
ax3 = pw.Brick("ax3", (5,2))
sns.histplot(diamonds, x="price", hue="cut", multiple="stack",
palette="light:m_r", edgecolor=".3", linewidth=.5, log_scale=True,
ax = ax3)
ax3.set_title("ax3")
ax3.savefig()
#Example plot 4 (ref:https://seaborn.pydata.org/examples/grouped_violinplots.html)
tips = sns.load_dataset("tips")
ax4 = pw.Brick("ax4", (6,2))
sns.violinplot(data=tips, x="day", y="total_bill", hue="smoker",
split=True, inner="quart", linewidth=1,
palette={"Yes": "b", "No": ".85"},
ax=ax4)
ax4.set_title("ax4")
ax4.savefig("../img/ax4.png")
#Example plot 5 (ref:https://seaborn.pydata.org/examples/wide_data_lineplot.html)
rs = np.random.RandomState(365)
values = rs.randn(365, 4).cumsum(axis=0)
dates = pd.date_range("1 1 2016", periods=365, freq="D")
data = pd.DataFrame(values, dates, columns=["A", "B", "C", "D"])
data = data.rolling(7).mean()
ax5 = pw.Brick("ax5", (5,2))
sns.lineplot(data=data, palette="tab10", linewidth=2.5, ax=ax5)
ax5.set_xlabel("date")
ax5.set_ylabel("value")
ax5.set_title("ax5")
ax5.savefig()
The patchworklib module provides two operators " |", "/" that enable designing tidy layout for multiple plots with simple operations. The "|" operator will place the plots beside each other, while the "/" operator will stack them.
#Arrange "ax1," "ax2," and "ax4" horizontally.
ax124 = ax1|ax2|ax4
ax124.savefig("../img/ax124.png")
The object generated by arranging multiple Brick object (Bricks class object) can also be arranged and stacked with other Brick objects. Additionally, It is possible to create more complex layouts by nesting the operations.
ax12435 = ax124/(ax3|ax5)
ax12435.savefig("../img/ax12435.png")
You can quickly test another layout by rearranging them.
ax35214 = (ax3/(ax2|ax1))|(ax5/ax4)
ax35214.savefig()
If you want to adjust the margins between objects, please change the value of .param["margin"].
pw.param["margin"]=0.2 #Default value is 0.5.
ax35214 = (ax3/(ax2|ax1))|(ax5/ax4)
ax35214.savefig("../img/ax35214_v1.1.png")
Also, the aspect ratios of each plot can be freely modifiable.
pw.param["margin"]=0.5
ax1.change_aspectratio((4,2))
ax3.change_aspectratio((4,1))
ax4.change_aspectratio((5,2))
ax35214_v2 = (ax3/(ax2|ax1))|(ax5/ax4)
ax35214_v2.savefig()
By specifying the Brick objects in a Bricks object with their label name, you can adjust the position of another Brick object to be packed.
ax321 = ax3/(ax2|ax1)
ax321.savefig("../img/ax321.png")
ax3214 = ax321["ax1"]|ax4
ax3214.savefig("../img/ax3214.png")
ax35214_v3 = ax3214["ax3"]|ax5
ax35214_v3.savefig("../img/ax35214_v3.png")
The above packing process allows the axes of the objects to be accurately aligned with each other. Actually, in "ax35214" and "ax35214_v2", the bottom axis lines of ax3 and ax5 are not precisely aligned, while in "ax35214_v3", their bottom axis lines are exactly aligned. However, please note that this packing method using label indexing changes aspect ratios of the Brick objects to be packed from the original one to align their axis lines with others.
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patchwork for matplotlib
We found that patchworklib demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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