pyCirclize 1.10.1
Circular visualization in Python
Requires Python: >=3.10
Keywords: bioinformatics, chord-diagram, circos, matplotlib, visualization

# pyCirclize: Circular visualization in Python

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## Table of contents

- [Overview](#overview)
- [Installation](#installation)
- [API Usage](#api-usage)
- [Code Example](#code-example)
- [Tooltip Option](#tooltip-option)
- [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/).

![pyCirclize_gallery.png](https://raw.githubusercontent.com/moshi4/pyCirclize/main/docs/images/pyCirclize_gallery.png)  
**Fig.1 pyCirclize example plot gallery**

## Installation

`Python 3.10 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/)
- [Comparative Genomics](https://moshi4.github.io/pyCirclize/comparative_genomics/)
- [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")
```

![example01.png](https://raw.githubusercontent.com/moshi4/pyCirclize/main/docs/images/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
sectors = gbk.get_seqid2size()
space = 0 if len(sectors) == 1 else 2
circos = Circos(sectors, space=space)
circos.text(f"Escherichia coli K-12 plasmid F\n\n{gbk.name}", size=14)

seqid2features = gbk.get_seqid2features(feature_type="CDS")
for sector in circos.sectors:
    # Setup track for features plot
    f_cds_track = sector.add_track((95, 100))
    f_cds_track.axis(fc="lightgrey", ec="none", alpha=0.5)
    r_cds_track = sector.add_track((90, 95))
    r_cds_track.axis(fc="lightgrey", ec="none", alpha=0.5)
    # Plot forward/reverse strand CDS
    features = seqid2features[sector.name]
    for feature in features:
        if feature.location.strand == 1:
            f_cds_track.genomic_features(feature, plotstyle="arrow", fc="salmon", lw=0.5)
        else:
            r_cds_track.genomic_features(feature, plotstyle="arrow", fc="skyblue", lw=0.5)

    # Plot 'gene' qualifier label if exists
    labels, label_pos_list = [], []
    for feature in features:
        start = int(feature.location.start)
        end = int(feature.location.end)
        label_pos = (start + end) / 2
        gene_name = feature.qualifiers.get("gene", [None])[0]
        if gene_name is not None:
            labels.append(gene_name)
            label_pos_list.append(label_pos)
            f_cds_track.annotate(label_pos, gene_name, label_size=6)

    # 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")
```

![example02.png](https://raw.githubusercontent.com/moshi4/pyCirclize/main/docs/images/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 instance for chord diagram plot
circos = Circos.chord_diagram(
    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")
```

![example03.png](https://raw.githubusercontent.com/moshi4/pyCirclize/main/docs/images/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")
```

![example04.png](https://raw.githubusercontent.com/moshi4/pyCirclize/main/docs/images/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")
```

![example05.png](https://raw.githubusercontent.com/moshi4/pyCirclize/main/docs/images/example05.png)  

## Tooltip Option

pyCirclize supports tooltip display in jupyter using [ipympl](https://github.com/matplotlib/ipympl).
To enable tooltip, install pycirclize with ipympl and call `circos.plotfig(tooltip=True)` method.
Tooltip option is tested on jupyter notebooks in VScode and JupyterLab.

```shell
pip install pycirclize[tooltip]
# or
conda install -c conda-forge pycirclize ipympl
```

> [!WARNING]
> Interactive tooltip plots require live python kernel.
> Be aware that tooltips are not permanently enabled in the notebook after plotting.

![pyCirclize_tooltip.gif](https://raw.githubusercontent.com/moshi4/pyCirclize/main/docs/images/pyCirclize_tooltip.gif)  

## Star History

[![Star History Chart](https://api.star-history.com/svg?repos=moshi4/pyCirclize&type=Date)](https://star-history.com/#moshi4/pyCirclize&Date)