"""
Company structure
=================

This example shows how to use `iplotx` to visualise simple logical relationships, for instance the organisational chart of a company.
"""

import networkx as nx
import matplotlib.pyplot as plt
import iplotx as ipx

g = nx.DiGraph()
g.add_edges_from(
    [
        ("CEO", "Manager 1"),
        ("CEO", "Manager 2"),
        ("CEO", "Manager 3"),
        ("Manager 1", "Employee 1"),
        ("Manager 1", "Employee 2"),
        ("Manager 2", "Employee 3"),
        ("Manager 2", "Employee 4"),
        ("Manager 3", "Employee 4"),
    ]
)
layout = {
    "CEO": [0, 0],
    "Manager 1": [1, -1],
    "Manager 2": [1, 0],
    "Manager 3": [1, 1],
    "Employee 1": [2, -1],
    "Employee 2": [2, -0.5],
    "Employee 3": [2, 0],
    "Employee 4": [2, 0.5],
}
fig, ax = plt.subplots()
ipx.network(
    g,
    layout=layout,
    ax=ax,
    vertex_labels=True,
    style="hollow",
    vertex_marker="r",
    edge_ports=[("e", "w")] * 8,
    edge_curved=True,
    edge_tension=[0.65] * 3 + [0.6] * 5,
    margins=(0.08, 0.05),
)
# Show the layout top to bottom for clarity
ax.invert_yaxis()

# %%
# If you prefer a more squared look, you can use S-style waypoints with per-edge offsets:

fig, ax = plt.subplots()
ipx.network(
    g,
    layout=layout,
    ax=ax,
    vertex_labels=True,
    style="hollow",
    vertex_marker="r",
    edge_ports=[("e", "w")] * 8,
    edge_waypoints="xmidy0,xmidy1",
    edge_offset=[(0, 0)] * 7 + [(0, -6)],
    margins=(0.08, 0.05),
    edge_linestyle=["-"] * 7 + ["--"],
)
ax.invert_yaxis()

# %%
# The `offset` edge style bypasses any layout coordinate system and acts in figure points directly.
# Combining edge offsets with noncartesian layout coordinate systems (e.g. `polar`) can lead to unexpected results.