import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
from random import shuffle, seed

# LM
model_size = {
    "T5\textsubscript{SMALL}": [60, "T5"],
    "T5\textsubscript{BASE}": [200, "T5"],
    "T5\textsubscript{LARGE}": [770, "T5"],
    "T5\textsubscript{XL}": [3000, "T5"],
    "T5\textsubscript{XXL}": [11000, "T5"],
    "Flan-T5\textsubscript{SMALL}": [60, "Flan-T5"],
    "Flan-T5\textsubscript{BASE}": [200, "Flan-T5"],
    "Flan-T5\textsubscript{LARGE}": [770, "Flan-T5"],
    "Flan-T5\textsubscript{XL}": [3000, "Flan-T5"],
    "Flan-T5\textsubscript{XXL}": [11000, "Flan-T5"],
    "OPT\textsubscript{125M}": [125, "OPT"],
    "OPT\textsubscript{350M}": [350, "OPT"],
    "OPT\textsubscript{1.3B}": [1300, "OPT"],
    "OPT\textsubscript{2.7B}": [2700, "OPT"],
    "OPT\textsubscript{6.7B}": [6700, "OPT"],
    "OPT\textsubscript{13B}": [13000, "OPT"],
    "OPT\textsubscript{30B}": [30000, "OPT"],
    "OPT\textsubscript{66B}": [66000, "OPT"],
    "OPT-IML\textsubscript{1.3B}": [1300, "OPT-IML"],
    "OPT-IML\textsubscript{30B}": [30000, "OPT-IML"],
}
lm_list = ['T5', 'Flan-T5', 'OPT', 'OPT-IML']

# Oracle
df_oracle = pd.read_csv("results/oracle.csv", index_col=0)

# Plot
os.makedirs('figures/main', exist_ok=True)
plt.rcParams.update({'font.size': 16})  # must set in top


def main(target_relation: str = "average", prompt_type: str = "lc"):
    df = pd.read_csv(f"results/lm_{prompt_type}/lm.csv")
    df.index = df.pop("model")
    df = (df * 100).round(1)
    df = df[[i in model_size for i in df.index]]
    df["size"] = [model_size[i][0] * 1000000 for i in df.index]
    df["lm"] = [model_size[i][1] for i in df.index]

    df_target = df[[target_relation, "size", "lm"]]
    out = df_target.pivot_table(index='size', columns='lm', aggfunc='mean')
    out.columns = [i[1] for i in out.columns]
    out = out.reset_index()
    out = out[['size'] + lm_list]

    styles = ['o-', '^--', 'X:', "P:"]
    seed(1)
    colors = list(mpl.colormaps['tab20b'].colors)
    shuffle(colors)

    ax = None
    for n, c in enumerate(lm_list):
        tmp = out[['size', c]].dropna().reset_index()
        ax = tmp.plot.line(y=c, x='size', xlabel='Model Size', ylabel="Correlation", ax=ax, color=colors[n],
                           style=styles[n], label=c, logx=True, grid=True)

    # ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
    plt.tight_layout()
    plt.savefig(f"figures/main/{prompt_type}.{target_relation.replace(' ', '_').replace('/', '-')}.landscape.png", bbox_inches="tight", dpi=600)


if __name__ == '__main__':
    for p in ['lc', 'qa']:
        main('average', p)
        main("competitor/rival of", p)
        main("friend/ally of", p)
        main("influenced by", p)
        main("known for", p)
        main("similar to", p)