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import os
import fitz  # PyMuPDF
from PIL import Image
import pytesseract
import ollama
import shutil
import sys


folder = "~/Test"

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import numpy as np
from pyscenarios.sobol import sobol
import matplotlib.pyplot as plt


def example_func(x):
    """
    Result of integrate this function
    is approximately 0.63661977.

cperales

import multiprocessing as mp
from time import perf_counter
import matplotlib.pyplot as plt


def counting_time(cpu, amount):
    start = perf_counter()
    list_amount = [amount] * cpu
    with mp.Pool(cpu) as p:
        p.map(f, list_amount)

cperales

import multiprocessing as mp


def f(huge_amount):
    count = 0
    for i in range(huge_amount):
        if i % 2:
            count += 1
        else:
            count -= 1

cperales

import os
import pandas as pd
from scipy.stats import wilcoxon, ranksums, mannwhitneyu
import numpy as np


def wilcoxon_csv(csv_name):
    # Load the csv as DataFrame
    df = pd.read_csv(csv_name, delimiter=';', index_col='Dataset')
    # The name of the csv file is the name of the metric

cperales

import os
import pandas as pd
from sklearn import preprocessing


def load_data(folder,
              dataset,
              n_targ=None,
              header=None,
              sep='\s+'):

cperales

sudo apt-get update -y && sudo apt-get upgrade -y && sudo apt-get dist-upgrade -y && sudo apt autoremove -y

cperales

## This classifier compares the average of the shortest distances of the
# samples from target 1 with the average of the distnces of the samples 
# from target 2

from numpy.linalg import norm
from numpy import percentile

def average_shortest_distances(train_set,sample,per=20):
	"""
	"""

cperales

# Código para volver a descargar tweets que están mal parseados (pero poseemos su ID)
# Sería conveniente tener dos claves API, porque es normal que durante el proceso ocurra el error "rate limit"
# De ahí la necesidad de tantos try/except

infile = codecs.open('twitter.json', 'r', encoding='utf-8')
outfile = codecs.open('tweets_completos.json', 'w', encoding='utf-8')
errores = codecs.open('id_tweets_no_recuperados.txt', 'w', encoding='utf-8')

recuperados = 0
perdidos = 0

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# -*- coding: utf-8 -*-

from bson import json_util as json
import codecs
import datetime
import sys

# Introduces por linea de comandos "python dict_to_json.py file.json"
# Pensado para tweets en diccionario de un arhcivo a un JSON