# pyCirclize: Circular visualization in Python
[](https://pypi.python.org/pypi/pycirclize)
[](https://anaconda.org/conda-forge/pycirclize)
[](https://github.com/moshi4/pyCirclize/actions/workflows/ci.yml)
## Table of contents
- [Overview](#overview)
- [Installation](#installation)
- [API Usage](#api-usage)
- [Code Example](#code-example)
- [Not Implemented Features](#not-implemented-features)
- [Star History](#star-history)
## Overview
pyCirclize is a circular visualization python package implemented based on matplotlib.
This package is developed for the purpose of easily and beautifully plotting circular figure such as Circos Plot and Chord Diagram in Python.
In addition, useful genome and phylogenetic tree visualization methods for the bioinformatics field are also implemented.
pyCirclize was inspired by [circlize](https://github.com/jokergoo/circlize) and [pyCircos](https://github.com/ponnhide/pyCircos).
More detailed documentation is available [here](https://moshi4.github.io/pyCirclize/).
**Fig.1 pyCirclize example plot gallery**
## Installation
`Python 3.8 or later` is required for installation.
**Install PyPI package:**
pip install pycirclize
**Install conda-forge package:**
conda install -c conda-forge pycirclize
## API Usage
API usage is described in each of the following sections in the [document](https://moshi4.github.io/pyCirclize/).
- [Getting Started](https://moshi4.github.io/pyCirclize/getting_started/)
- [Plot API Example](https://moshi4.github.io/pyCirclize/plot_api_example/)
- [Chord Diagram](https://moshi4.github.io/pyCirclize/chord_diagram/)
- [Radar Chart](https://moshi4.github.io/pyCirclize/radar_chart/)
- [Circos Plot (Genomics)](https://moshi4.github.io/pyCirclize/circos_plot/)
- [Phylogenetic Tree](https://moshi4.github.io/pyCirclize/phylogenetic_tree/)
- [Plot Tips](https://moshi4.github.io/pyCirclize/plot_tips/)
## Code Example
### 1. Circos Plot
```python
from pycirclize import Circos
import numpy as np
np.random.seed(0)
# Initialize Circos sectors
sectors = {"A": 10, "B": 15, "C": 12, "D": 20, "E": 15}
circos = Circos(sectors, space=5)
for sector in circos.sectors:
# Plot sector name
sector.text(f"Sector: {sector.name}", r=110, size=15)
# Create x positions & random y values
x = np.arange(sector.start, sector.end) + 0.5
y = np.random.randint(0, 100, len(x))
# Plot lines
track1 = sector.add_track((80, 100), r_pad_ratio=0.1)
track1.xticks_by_interval(interval=1)
track1.axis()
track1.line(x, y)
# Plot points
track2 = sector.add_track((55, 75), r_pad_ratio=0.1)
track2.axis()
track2.scatter(x, y)
# Plot bars
track3 = sector.add_track((30, 50), r_pad_ratio=0.1)
track3.axis()
track3.bar(x, y)
# Plot links
circos.link(("A", 0, 3), ("B", 15, 12))
circos.link(("B", 0, 3), ("C", 7, 11), color="skyblue")
circos.link(("C", 2, 5), ("E", 15, 12), color="chocolate", direction=1)
circos.link(("D", 3, 5), ("D", 18, 15), color="lime", ec="black", lw=0.5, hatch="//", direction=2)
circos.link(("D", 8, 10), ("E", 2, 8), color="violet", ec="red", lw=1.0, ls="dashed")
circos.savefig("example01.png")
```
### 2. Circos Plot (Genomics)
```python
from pycirclize import Circos
from pycirclize.utils import fetch_genbank_by_accid
from pycirclize.parser import Genbank
# Download `NC_002483` E.coli plasmid genbank
gbk_fetch_data = fetch_genbank_by_accid("NC_002483")
gbk = Genbank(gbk_fetch_data)
# Initialize Circos instance with genome size
circos = Circos(sectors={gbk.name: gbk.range_size})
circos.text(f"Escherichia coli K-12 plasmid F\n\n{gbk.name}", size=14)
circos.rect(r_lim=(90, 100), fc="lightgrey", ec="none", alpha=0.5)
sector = circos.sectors[0]
# Plot forward strand CDS
f_cds_track = sector.add_track((95, 100))
f_cds_feats = gbk.extract_features("CDS", target_strand=1)
f_cds_track.genomic_features(f_cds_feats, plotstyle="arrow", fc="salmon", lw=0.5)
# Plot reverse strand CDS
r_cds_track = sector.add_track((90, 95))
r_cds_feats = gbk.extract_features("CDS", target_strand=-1)
r_cds_track.genomic_features(r_cds_feats, plotstyle="arrow", fc="skyblue", lw=0.5)
# Plot 'gene' qualifier label if exists
labels, label_pos_list = [], []
for feat in gbk.extract_features("CDS"):
start = int(feat.location.start)
end = int(feat.location.end)
label_pos = (start + end) / 2
gene_name = feat.qualifiers.get("gene", [None])[0]
if gene_name is not None:
labels.append(gene_name)
label_pos_list.append(label_pos)
f_cds_track.xticks(label_pos_list, labels, label_size=6, label_orientation="vertical")
# Plot xticks (interval = 10 Kb)
r_cds_track.xticks_by_interval(
10000, outer=False, label_formatter=lambda v: f"{v/1000:.1f} Kb"
)
circos.savefig("example02.png")
```
### 3. Chord Diagram
```python
from pycirclize import Circos
import pandas as pd
# Create matrix dataframe (3 x 6)
row_names = ["F1", "F2", "F3"]
col_names = ["T1", "T2", "T3", "T4", "T5", "T6"]
matrix_data = [
[10, 16, 7, 7, 10, 8],
[4, 9, 10, 12, 12, 7],
[17, 13, 7, 4, 20, 4],
]
matrix_df = pd.DataFrame(matrix_data, index=row_names, columns=col_names)
# Initialize Circos from matrix for plotting Chord Diagram
circos = Circos.initialize_from_matrix(
matrix_df,
space=5,
cmap="tab10",
label_kws=dict(size=12),
link_kws=dict(ec="black", lw=0.5, direction=1),
)
circos.savefig("example03.png")
```
### 4. Phylogenetic Tree
```python
from pycirclize import Circos
from pycirclize.utils import load_example_tree_file, ColorCycler
from matplotlib.lines import Line2D
# Initialize Circos from phylogenetic tree
tree_file = load_example_tree_file("large_example.nwk")
circos, tv = Circos.initialize_from_tree(
tree_file,
r_lim=(30, 100),
leaf_label_size=5,
line_kws=dict(color="lightgrey", lw=1.0),
)
# Define group-species dict for tree annotation
# In this example, set minimum species list to specify group's MRCA node
group_name2species_list = dict(
Monotremata=["Tachyglossus_aculeatus", "Ornithorhynchus_anatinus"],
Marsupialia=["Monodelphis_domestica", "Vombatus_ursinus"],
Xenarthra=["Choloepus_didactylus", "Dasypus_novemcinctus"],
Afrotheria=["Trichechus_manatus", "Chrysochloris_asiatica"],
Euarchontes=["Galeopterus_variegatus", "Theropithecus_gelada"],
Glires=["Oryctolagus_cuniculus", "Microtus_oregoni"],
Laurasiatheria=["Talpa_occidentalis", "Mirounga_leonina"],
)
# Set tree line color & label color
ColorCycler.set_cmap("tab10")
group_name2color = {name: ColorCycler() for name in group_name2species_list.keys()}
for group_name, species_list in group_name2species_list.items():
color = group_name2color[group_name]
tv.set_node_line_props(species_list, color=color, apply_label_color=True)
# Plot figure & set legend on center
fig = circos.plotfig()
_ = circos.ax.legend(
handles=[Line2D([], [], label=n, color=c) for n, c in group_name2color.items()],
labelcolor=group_name2color.values(),
fontsize=6,
loc="center",
bbox_to_anchor=(0.5, 0.5),
)
fig.savefig("example04.png")
```
### 5. Radar Chart
```python
from pycirclize import Circos
import pandas as pd
# Create RPG jobs parameter dataframe (3 jobs, 7 parameters)
df = pd.DataFrame(
data=[
[80, 80, 80, 80, 80, 80, 80],
[90, 20, 95, 95, 30, 30, 80],
[60, 90, 20, 20, 100, 90, 50],
],
index=["Hero", "Warrior", "Wizard"],
columns=["HP", "MP", "ATK", "DEF", "SP.ATK", "SP.DEF", "SPD"],
)
# Initialize Circos instance for radar chart plot
circos = Circos.radar_chart(
df,
vmax=100,
marker_size=6,
grid_interval_ratio=0.2,
)
# Plot figure & set legend on upper right
fig = circos.plotfig()
_ = circos.ax.legend(loc="upper right", fontsize=10)
fig.savefig("example05.png")
```
## Not Implemented Features
List of features implemented in other Circos plotting tools but not yet implemented in pyCirclize.
I may implement them when I feel like it.
- Plot histogram
- Plot boxplot
- Plot violin
- Plot curved text
- Adjust overlap label position
## Star History
[](https://star-history.com/#moshi4/pyCirclize&Date)
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"description": "# pyCirclize: Circular visualization in Python\n\n\n\n\n[](https://pypi.python.org/pypi/pycirclize)\n[](https://anaconda.org/conda-forge/pycirclize)\n[](https://github.com/moshi4/pyCirclize/actions/workflows/ci.yml)\n\n## Table of contents\n\n- [Overview](#overview)\n- [Installation](#installation)\n- [API Usage](#api-usage)\n- [Code Example](#code-example)\n- [Not Implemented Features](#not-implemented-features)\n- [Star History](#star-history)\n\n## Overview\n\npyCirclize is a circular visualization python package implemented based on matplotlib.\nThis package is developed for the purpose of easily and beautifully plotting circular figure such as Circos Plot and Chord Diagram in Python.\nIn addition, useful genome and phylogenetic tree visualization methods for the bioinformatics field are also implemented.\npyCirclize was inspired by [circlize](https://github.com/jokergoo/circlize) and [pyCircos](https://github.com/ponnhide/pyCircos).\nMore detailed documentation is available [here](https://moshi4.github.io/pyCirclize/).\n\n \n**Fig.1 pyCirclize example plot gallery**\n\n## Installation\n\n`Python 3.8 or later` is required for installation.\n\n**Install PyPI package:**\n\n pip install pycirclize\n\n**Install conda-forge package:**\n\n conda install -c conda-forge pycirclize\n\n## API Usage\n\nAPI usage is described in each of the following sections in the [document](https://moshi4.github.io/pyCirclize/).\n\n- [Getting Started](https://moshi4.github.io/pyCirclize/getting_started/)\n- [Plot API Example](https://moshi4.github.io/pyCirclize/plot_api_example/)\n- [Chord Diagram](https://moshi4.github.io/pyCirclize/chord_diagram/)\n- [Radar Chart](https://moshi4.github.io/pyCirclize/radar_chart/)\n- [Circos Plot (Genomics)](https://moshi4.github.io/pyCirclize/circos_plot/)\n- [Phylogenetic Tree](https://moshi4.github.io/pyCirclize/phylogenetic_tree/)\n- [Plot Tips](https://moshi4.github.io/pyCirclize/plot_tips/)\n\n## Code Example\n\n### 1. Circos Plot\n\n```python\nfrom pycirclize import Circos\nimport numpy as np\nnp.random.seed(0)\n\n# Initialize Circos sectors\nsectors = {\"A\": 10, \"B\": 15, \"C\": 12, \"D\": 20, \"E\": 15}\ncircos = Circos(sectors, space=5)\n\nfor sector in circos.sectors:\n # Plot sector name\n sector.text(f\"Sector: {sector.name}\", r=110, size=15)\n # Create x positions & random y values\n x = np.arange(sector.start, sector.end) + 0.5\n y = np.random.randint(0, 100, len(x))\n # Plot lines\n track1 = sector.add_track((80, 100), r_pad_ratio=0.1)\n track1.xticks_by_interval(interval=1)\n track1.axis()\n track1.line(x, y)\n # Plot points \n track2 = sector.add_track((55, 75), r_pad_ratio=0.1)\n track2.axis()\n track2.scatter(x, y)\n # Plot bars\n track3 = sector.add_track((30, 50), r_pad_ratio=0.1)\n track3.axis()\n track3.bar(x, y)\n\n# Plot links \ncircos.link((\"A\", 0, 3), (\"B\", 15, 12))\ncircos.link((\"B\", 0, 3), (\"C\", 7, 11), color=\"skyblue\")\ncircos.link((\"C\", 2, 5), (\"E\", 15, 12), color=\"chocolate\", direction=1)\ncircos.link((\"D\", 3, 5), (\"D\", 18, 15), color=\"lime\", ec=\"black\", lw=0.5, hatch=\"//\", direction=2)\ncircos.link((\"D\", 8, 10), (\"E\", 2, 8), color=\"violet\", ec=\"red\", lw=1.0, ls=\"dashed\")\n\ncircos.savefig(\"example01.png\")\n```\n\n \n\n### 2. Circos Plot (Genomics)\n\n```python\nfrom pycirclize import Circos\nfrom pycirclize.utils import fetch_genbank_by_accid\nfrom pycirclize.parser import Genbank\n\n# Download `NC_002483` E.coli plasmid genbank\ngbk_fetch_data = fetch_genbank_by_accid(\"NC_002483\")\ngbk = Genbank(gbk_fetch_data)\n\n# Initialize Circos instance with genome size\ncircos = Circos(sectors={gbk.name: gbk.range_size})\ncircos.text(f\"Escherichia coli K-12 plasmid F\\n\\n{gbk.name}\", size=14)\ncircos.rect(r_lim=(90, 100), fc=\"lightgrey\", ec=\"none\", alpha=0.5)\nsector = circos.sectors[0]\n\n# Plot forward strand CDS\nf_cds_track = sector.add_track((95, 100))\nf_cds_feats = gbk.extract_features(\"CDS\", target_strand=1)\nf_cds_track.genomic_features(f_cds_feats, plotstyle=\"arrow\", fc=\"salmon\", lw=0.5)\n\n# Plot reverse strand CDS\nr_cds_track = sector.add_track((90, 95))\nr_cds_feats = gbk.extract_features(\"CDS\", target_strand=-1)\nr_cds_track.genomic_features(r_cds_feats, plotstyle=\"arrow\", fc=\"skyblue\", lw=0.5)\n\n# Plot 'gene' qualifier label if exists\nlabels, label_pos_list = [], []\nfor feat in gbk.extract_features(\"CDS\"):\n start = int(feat.location.start)\n end = int(feat.location.end)\n label_pos = (start + end) / 2\n gene_name = feat.qualifiers.get(\"gene\", [None])[0]\n if gene_name is not None:\n labels.append(gene_name)\n label_pos_list.append(label_pos)\nf_cds_track.xticks(label_pos_list, labels, label_size=6, label_orientation=\"vertical\")\n\n# Plot xticks (interval = 10 Kb)\nr_cds_track.xticks_by_interval(\n 10000, outer=False, label_formatter=lambda v: f\"{v/1000:.1f} Kb\"\n)\n\ncircos.savefig(\"example02.png\")\n```\n\n \n\n### 3. Chord Diagram\n\n```python\nfrom pycirclize import Circos\nimport pandas as pd\n\n# Create matrix dataframe (3 x 6)\nrow_names = [\"F1\", \"F2\", \"F3\"]\ncol_names = [\"T1\", \"T2\", \"T3\", \"T4\", \"T5\", \"T6\"]\nmatrix_data = [\n [10, 16, 7, 7, 10, 8],\n [4, 9, 10, 12, 12, 7],\n [17, 13, 7, 4, 20, 4],\n]\nmatrix_df = pd.DataFrame(matrix_data, index=row_names, columns=col_names)\n\n# Initialize Circos from matrix for plotting Chord Diagram\ncircos = Circos.initialize_from_matrix(\n matrix_df,\n space=5,\n cmap=\"tab10\",\n label_kws=dict(size=12),\n link_kws=dict(ec=\"black\", lw=0.5, direction=1),\n)\n\ncircos.savefig(\"example03.png\")\n```\n\n \n\n### 4. Phylogenetic Tree\n\n```python\nfrom pycirclize import Circos\nfrom pycirclize.utils import load_example_tree_file, ColorCycler\nfrom matplotlib.lines import Line2D\n\n# Initialize Circos from phylogenetic tree\ntree_file = load_example_tree_file(\"large_example.nwk\")\ncircos, tv = Circos.initialize_from_tree(\n tree_file,\n r_lim=(30, 100),\n leaf_label_size=5,\n line_kws=dict(color=\"lightgrey\", lw=1.0),\n)\n\n# Define group-species dict for tree annotation\n# In this example, set minimum species list to specify group's MRCA node\ngroup_name2species_list = dict(\n Monotremata=[\"Tachyglossus_aculeatus\", \"Ornithorhynchus_anatinus\"],\n Marsupialia=[\"Monodelphis_domestica\", \"Vombatus_ursinus\"],\n Xenarthra=[\"Choloepus_didactylus\", \"Dasypus_novemcinctus\"],\n Afrotheria=[\"Trichechus_manatus\", \"Chrysochloris_asiatica\"],\n Euarchontes=[\"Galeopterus_variegatus\", \"Theropithecus_gelada\"],\n Glires=[\"Oryctolagus_cuniculus\", \"Microtus_oregoni\"],\n Laurasiatheria=[\"Talpa_occidentalis\", \"Mirounga_leonina\"],\n)\n\n# Set tree line color & label color\nColorCycler.set_cmap(\"tab10\")\ngroup_name2color = {name: ColorCycler() for name in group_name2species_list.keys()}\nfor group_name, species_list in group_name2species_list.items():\n color = group_name2color[group_name]\n tv.set_node_line_props(species_list, color=color, apply_label_color=True)\n\n# Plot figure & set legend on center\nfig = circos.plotfig()\n_ = circos.ax.legend(\n handles=[Line2D([], [], label=n, color=c) for n, c in group_name2color.items()],\n labelcolor=group_name2color.values(),\n fontsize=6,\n loc=\"center\",\n bbox_to_anchor=(0.5, 0.5),\n)\nfig.savefig(\"example04.png\")\n```\n\n \n\n### 5. Radar Chart\n\n```python\nfrom pycirclize import Circos\nimport pandas as pd\n\n# Create RPG jobs parameter dataframe (3 jobs, 7 parameters)\ndf = pd.DataFrame(\n data=[\n [80, 80, 80, 80, 80, 80, 80],\n [90, 20, 95, 95, 30, 30, 80],\n [60, 90, 20, 20, 100, 90, 50],\n ],\n index=[\"Hero\", \"Warrior\", \"Wizard\"],\n columns=[\"HP\", \"MP\", \"ATK\", \"DEF\", \"SP.ATK\", \"SP.DEF\", \"SPD\"],\n)\n\n# Initialize Circos instance for radar chart plot\ncircos = Circos.radar_chart(\n df,\n vmax=100,\n marker_size=6,\n grid_interval_ratio=0.2,\n)\n\n# Plot figure & set legend on upper right\nfig = circos.plotfig()\n_ = circos.ax.legend(loc=\"upper right\", fontsize=10)\nfig.savefig(\"example05.png\")\n```\n\n \n\n## Not Implemented Features\n\nList of features implemented in other Circos plotting tools but not yet implemented in pyCirclize.\nI may implement them when I feel like it.\n\n- Plot histogram\n- Plot boxplot\n- Plot violin\n- Plot curved text\n- Adjust overlap label position\n\n## Star History\n\n[](https://star-history.com/#moshi4/pyCirclize&Date)\n",
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