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")

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(str(feat.location.start))
    end = int(str(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")

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")