"""
Venn Diagram Examples
=====================

This example demonstrates Venn diagram functionality in PubliPlots,
supporting 2-way through 5-way Venn diagrams with customizable colors,
labels, and formatting.
"""

import publiplots as pp
import numpy as np

# %%
# 2-Way Venn Diagram
# ------------------
# Simple 2-way Venn diagram showing set overlaps.

# Create two sets
set1 = set(range(1, 51))    # 1-50
set2 = set(range(30, 81))   # 30-80

# Create 2-way Venn
ax = pp.venn(
    sets=[set1, set2],
    labels=['Set A', 'Set B'],
    colors=pp.color_palette('pastel', n_colors=2),
)
pp.show()

# %%
# 2-Way Venn with Percentage Format
# ----------------------------------
# Show percentages instead of sizes in the labels.

# Create two sets with overlap
np.random.seed(777)
set1 = set(np.random.randint(1, 100, 60))
set2 = set(np.random.randint(40, 140, 60))

# Create 2-way Venn with percentage format.
pp.venn(
    sets=[set1, set2],
    labels=['Dataset A', 'Dataset B'],
    colors=['#75B375', '#E6B375'],
    fmt='{percentage:.1f}%',
    alpha=0.3,
)
pp.show()

# %%
# Vertical 2-Way Venn Diagram
# ---------------------------
# Stack the two circles vertically (first set on top) instead of
# side-by-side. Vertical orientation is supported for 2-way diagrams only.

set1 = set(range(1, 51))    # 1-50
set2 = set(range(30, 81))   # 30-80

pp.venn(
    sets=[set1, set2],
    labels=['Set A', 'Set B'],
    colors=pp.color_palette('pastel', n_colors=2),
    orientation='vertical',
)
pp.show()

# %%
# 3-Way Venn Diagram
# ------------------
# Three-way Venn diagram showing all pairwise and triple overlaps.

# Create three sets
setA = set(range(1, 61))     # 1-60
setB = set(range(40, 101))   # 40-100
setC = set(range(51, 131))   # 51-130

# Create 3-way Venn
ax = pp.venn(
    sets=[setA, setB, setC],
    labels=['Set A', 'Set B', 'Set C'],
    colors=pp.color_palette('pastel', n_colors=3),
)
pp.show()

# %%
# 4-Way Venn Diagram
# ------------------
# Four-way Venn diagram using ellipses to show all possible intersections.

# Create four sets with realistic overlaps
np.random.seed(888)
set1 = set(np.random.randint(1, 120, 70))
set2 = set(np.random.randint(30, 150, 75))
set3 = set(np.random.randint(60, 180, 70))
set4 = set(np.random.randint(1, 100, 65))

# Create 4-way Venn
fig, ax = pp.subplots(axes_size=(80, 80))
pp.venn(
    sets=[set1, set2, set3, set4],
    labels=['Dataset A', 'Dataset B', 'Dataset C', 'Dataset D'],
    colors=pp.color_palette('pastel', n_colors=4),
    ax=ax,
)
pp.show()

# %%
# 5-Way Venn Diagram
# ------------------
# Five-way Venn diagram showing complex overlaps between multiple sets.

# Create five sets with varying overlaps
np.random.seed(999)
set1 = set(np.random.randint(1, 140, 80))
set2 = set(np.random.randint(40, 180, 85))
set3 = set(np.random.randint(80, 200, 75))
set4 = set(np.random.randint(20, 160, 70))
set5 = set(np.random.randint(60, 180, 80))

# Create 5-way Venn
fig, ax = pp.subplots(axes_size=(80, 80))
pp.venn(
    sets=[set1, set2, set3, set4, set5],
    labels=['Group A', 'Group B', 'Group C', 'Group D', 'Group E'],
    colors=pp.color_palette('pastel', n_colors=5),
    ax=ax,
)
pp.show()

# %%
# Custom Styled Venn Diagram
# ---------------------------
# Demonstrate custom colors and styling options.

# Create three sets for gene analysis
genes_control = set(range(1, 100))
genes_treatment1 = set(range(60, 160))
genes_treatment2 = set(range(120, 200))

# Create custom styled Venn
fig, ax = pp.subplots(axes_size=(90, 90))
pp.venn(
    sets=[genes_control, genes_treatment1, genes_treatment2],
    labels=['Control', 'Treatment 1', 'Treatment 2'],
    colors=['#8E8EC1', '#75B375', '#E6B375'],
    alpha=0.4,
    ax=ax,
)
ax.set_title('Differentially Expressed Genes', fontsize=14, fontweight='bold')
pp.show()