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(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")

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")

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")

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")