GitHub - ponnhide/patchworklib: Patchwork for matplotlib: A subplot manager for intuitive layouts in matplotlib, seaborn, and plotnine. (original) (raw)

patchworklib

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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Installation

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

News

10122024: version 0.6.5 is released.

10232023: version 0.6.3 is released.

05162023: version 0.6.1 was released.

Change log

#### 12082022: version 0.5.0 was released. - New operators, "+" and "-", were added. - plotnine > v0.10.x is now supported. - Plots generated by object-oriented seaborn interface can now be handled by patchworklib. - Descriptions of each function and class provided in patchworklib was added to this repository. If you want to know how to use patchworklib in detail, please see [API.md](https://github.com/ponnhide/patchworklib/blob/main/API.md). - Updated [patchworklib-examples](https://github.com/ponnhide/patchworklib-examples)

08152022: Version 0.4.7 was released.

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")

08092022: Version 0.4.6 was released.

07202022: Version 0.4.5 was released.

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.

07192022: Version 0.4.3 was released.

04222022: Version 0.4.2 was released.

04182022: Version 0.4.1 was released.

03272022: Version 0.4.0 was released.

02042022: Version 0.3.6 was released.

02042022: Version 0.3.5 was released.

01242022: Version 0.3.3 was released.

01222022: Version 0.3.0 was released.

Patchworklib now supports the function to arrange matplotlib.projections.polar.PolarAxes ojbects.

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

01212022: Version 0.2.1 was released.

01202022: Version 0.2.0 was released.

Patchworklib is now possible to arrange Seabron gridded plots. The "stack" function is added. A few bugs were fixed.

Arranging seaborn gridded plots

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.

"stack" fucntion

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()

01142022: Version 0.1.0 was released.

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("")

01072022: Patchworklib was updated to allow arranging multiple plots generated by plotnine.

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()

Usage

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

Getting started

Example codes

Tutorial ~_Compose multiple seaborn plots_~The follwoing tutorial codes can be executable in tutorial1

1. Importing patchworklib library

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")

2. Creating example plots

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, bboxtoanchor=(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()

3. Arranging and stacking plots

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()

4. Packing plots with label indexing (Advanced method)

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")

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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.