"""Reproduction of AI-Evolution Figure 3C (stacked architecture origins).

Anonymised reproduction of arXiv:2604.10571 Figure 3C as a *stacked area
chart* (the paper renders the same data as a stacked bar; the area form
emphasises the temporal succession of domain niches).

All counts are inline transcribed from the published figure. No external
data files, APIs, or checkpoints are read.
"""

import numpy as np
import matplotlib.pyplot as plt

plt.rcParams.update({
    "font.family": "sans-serif",
    "font.size": 10,
    "axes.linewidth": 0.8,
})

YEARS = np.array([2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020,
                  2021, 2022, 2023, 2024])

CV         = np.array([1, 1, 4, 7, 5, 10, 2, 3, 9, 12, 6, 5, 1])
NLP        = np.array([0, 0, 3, 1, 0,  1, 1, 4, 4,  2, 2, 4, 3])
AUDIO      = np.array([0, 0, 0, 0, 1,  1, 1, 1, 0,  0, 2, 0, 0])
MULTIMODAL = np.array([0, 0, 0, 0, 0,  0, 1, 0, 0,  3, 0, 1, 0])
RL         = np.array([0, 0, 0, 0, 1,  1, 1, 1, 0,  1, 1, 1, 0])
GRAPH      = np.array([0, 1, 0, 0, 1,  2, 0, 0, 0,  0, 0, 0, 0])

stacks = np.vstack([CV, NLP, AUDIO, MULTIMODAL, RL, GRAPH])
labels = ["CV", "NLP", "Audio", "Multimodal", "RL", "Graph"]
colors = ["#3a83b8", "#509a52", "#e07a3a", "#9b56b8", "#3aa9a3", "#f0c54a"]

fig, ax = plt.subplots(figsize=(7.2, 5.4))
ax.stackplot(YEARS, stacks, labels=labels, colors=colors,
             alpha=0.92, edgecolor="white", linewidth=0.8)

ax.set_xlim(YEARS.min(), YEARS.max())
ax.set_ylim(0, 20)
ax.set_xticks(np.arange(2012, 2025, 2))
ax.set_xticklabels([str(y) for y in np.arange(2012, 2025, 2)])
ax.set_xlabel("Year", fontsize=11)
ax.set_ylabel("New architectures", fontsize=11)
ax.set_title("C  Adaptive radiation into domain niches",
             fontsize=12, fontweight="bold", loc="left", pad=10)
ax.grid(True, axis="y", linestyle=":", color="#bbb", alpha=0.6, linewidth=0.6)

for s in ["top", "right"]:
    ax.spines[s].set_visible(False)
ax.spines["left"].set_color("#444")
ax.spines["bottom"].set_color("#444")
ax.tick_params(axis="both", labelsize=9.5, color="#444")

leg = ax.legend(loc="upper left", ncol=2, frameon=True, fontsize=9,
                edgecolor="#888", framealpha=0.95)
leg.get_frame().set_linewidth(0.6)

plt.tight_layout()
plt.savefig("aievol_diversification_repro.png", dpi=200, bbox_inches="tight")
print("saved aievol_diversification_repro.png")