#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Simulation assignment 2024 - 2025

STARTER FILE

"""

import os

import matplotlib.pyplot as plt
import numpy as np
import numpy.linalg as la
import pandas as pd
import scipy.stats as stats
import statsmodels.api as sm
#import varplot as vpl

#plt.style.use("finthabo")

# this imports all functions from the helper file
from helper import data_frame_to_latex_table_file, print_question

#colors = vpl.color_list()

# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------
# Start of Script for Simulation assignment Econometrics
# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------

# -----------------------------------------------------------------------------
# Set the folders for output of graphs and tables
# -----------------------------------------------------------------------------

# for the figures
FIGURE_DIR = "../figures/"
if not os.path.exists(FIGURE_DIR):
    os.makedirs(FIGURE_DIR)
# for the latex document
REPORT_DIR = "../report/"
if not os.path.exists(REPORT_DIR):
    os.makedirs(REPORT_DIR)

# -----------------------------------------------------------------------------
# Here we set the seed for our group to your group number
# -----------------------------------------------------------------------------


# first birthday
bd_1 = 3112
# second birthday
bd_2 = 3112

group_seed = bd_1 * bd_2

# set the seed
np.random.seed(group_seed)

# -----------------------------------------------------------------------------
# set the random number generator and seed
# -----------------------------------------------------------------------------

# setting for output printing
print_line_length = 90
print_line_start = 5

# the number of data sets that we will simulate
num_obs = 2**10

# set the seed and the random number generator for reproducible results
# this ensures that every time you run this code you get exactly the same random numbers.
# changing the seed would change the random numbers.
rng = np.random.default_rng(group_seed)

# the true value of the parameters.
# Known in your role as creator, unknown to the modeller.
beta = np.array([3.0, -4.0, 2.0])

# standard deviation of the error terms
u = rng.normal(0, 3, (num_obs,))

x1 = rng.normal(3, 6, (num_obs,))
x2 = rng.normal(2, 5, (num_obs,))

# y = TODO

# X = TODO

# m = TODO
# results = #TODO