import argparse

import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt

parser = argparse.ArgumentParser()
parser.add_argument("-g", "--graph", action="store_true", default=False, help="Plot graph")
parser.add_argument("-s", "--save", default="", help="Graph save location")
args = parser.parse_args()
graph = args.graph
save = args.save

dataset = np.load("clean.npy")
print(f"dataset shape: {dataset.shape}; analyzing column 11 (absence)")
print("\tinteger value")
print("")


def analyze_absence(name: str, col: np.ndarray):
    absence_col = dataset[:, 11]
    tau, p = stats.kendalltau(absence_col, col)
    print(f"ken-tau for {name}: {tau}")
    print(f"p-value for {name}: {p}")

    if p > 0.05:
        print("statistically insignificant\n")
    else:
        print("statistically significant\n")

    return (absence_col, col), tau, p


data_gpa, tau_gpa, p_gpa = analyze_absence("gpa", dataset[:, 2])
data_math, tau_math, p_math = analyze_absence("math", dataset[:, 3])
data_slovak, tau_slovak, p_slovak = analyze_absence("slovak", dataset[:, 4])
data_english, tau_english, p_english = analyze_absence("english", dataset[:, 5])
data = [data_gpa, data_math, data_slovak, data_english]
taus = [tau_gpa, tau_math, tau_slovak, tau_english]
ps = [p_gpa, p_math, p_slovak, p_english]

if not graph:
    exit(0)

grade_names = ["Priemer", "Matematika", "Slovenčina", "Angličtina"]
grade_name_labels = ["Priemer známok", "Známka z matematiky", "Známka zo slovenčiny", "Známka z angličtiny"]

fig, axs = plt.subplots(2, 2)
fig.suptitle("Absencia")
fig.set_size_inches(12, 9)

for j in range(2):
    for k in range(2):
        index = j * 2 + k
        step = 1 if index > 0 else 0.5

        if index == 0:
            axs[j, k].scatter(dataset[:, 11], dataset[:, 2])
            axs[j, k].set_xlabel("Počet vymeškaných hodín")
            axs[j, k].set_ylabel(grade_name_labels[index])
        else:
            current = list([data[index][0][data[index][1] == i + 1] for i in range(5)])  # i wanna kms
            axs[j, k].violinplot(list(filter(lambda x: len(x), current)), showmeans=True)
            axs[j, k].set_xticks(np.arange(1, 6, 1), labels=["1", "2", "3", "4", "5"])
            axs[j, k].set_xlabel(grade_name_labels[index])
            axs[j, k].set_ylabel("Počet vymeškaných hodín")

        axs[j, k].set_title(grade_names[index])

        tau = round(taus[index], 2)
        p = round(ps[index], 4)
        axs[j, k].text(0.01, 0.99, f"Tau τ: {tau:.2f}\np-val: {p:.4f}", ha="left", va="top", transform=axs[j, k].transAxes,
                       fontweight="bold")

        if index:
            by_grade = [data[index][0][data[index][1] == i + 1] for i in range(5)]
            means = list([a.mean() for a in filter(lambda b: len(b), by_grade)])
            for l in range(len(means)):
                mean = round(means[l], 2)
                axs[j, k].text(l + 1.02, mean + 5, f"{mean}")

fig.tight_layout()
if save != "":
    plt.savefig(save)
else:
    plt.show()