jdavidrcamacho

# Install fluent-package v6 LTS: 

sudo apt update  

curl -fsSL https://fluentd.cdn.cncf.io/sh/install-ubuntu-noble-fluent-package6-lts.sh | sudo sh  

# Make sure the service is up and running: 

sudo systemctl enable --now fluentd  

jdavidrcamacho

# 1) Create the group (safe if it already exists)
sudo groupadd -r cmdlog || true

# 2) Make sure the log file exists
sudo touch /var/log/test.log

# 3) Give it group ownership & permissions
sudo chgrp cmdlog /var/log/test.log
sudo chmod 664 /var/log/test.log

jdavidrcamacho

<system>
  log_level info
</system>

# Still tail your test file
<source>
  @type tail
  path /var/log/test.log
  pos_file /var/log/fluentd/test.pos
  tag test_logs

jdavidrcamacho

import matplotlib.pyplot as plt

# Updated timeline data for European civilizations and periods
timelines_europe = {
    # Neolithic Cultures
    "Neolithic Cultures": {"start": -7000, "end": -2500, "color": "lightgreen"},
    "Cardial Culture": {"start": -6000, "end": -5000, "color": "lightblue"},
    "Linear Pottery Culture (LBK)": {
        "start": -5500,
        "end": -4500,

jdavidrcamacho

import matplotlib.pyplot as plt

# Updated timeline data with BCE year representation, including all events
timelines_simple = {
    # Ubaid Period
    "Ubaid Period": {"start": -6500, "end": -3800, "color": "salmon"},
    # Sumerian periods
    "Early Sumerian Settlement": {"start": -4500, "end": -4000, "color": "skyblue"},
    "Uruk Period (Sumerians)": {"start": -4000, "end": -3100, "color": "skyblue"},
    "Early Dynastic Period (Sumerians)": {

jdavidrcamacho

# Global initialisation file for SciTE
# For Linux, place in $prefix/share/scite
# For Windows, place in same directory as SciTE.EXE (or Sc1.EXE)
# Documentation at http://www.scintilla.org/SciTEDoc.html

# Globals

# Window sizes and visibility
if PLAT_WIN
	position.left=0

jdavidrcamacho

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import matplotlib.pylab as plt
from scipy import stats

myclip_a, myclip_b = -2, 2
my_mean, my_std = 0, 0.5
a, b = (myclip_a - my_mean) / my_std, (myclip_b - my_mean) / my_std

plt.hist(stats.norm(0,0.5).rvs(10000), bins = 100)

jdavidrcamacho

import numpy as np
#np.random.seed(101111)
import matplotlib.pyplot as plt
plt.close('all')
from tedi import utils

def SamplingSun(initFile, finalFile, timespan, observationsNumber,
                planet = False, planetParams = [], saveFile = True):
    """ Parameters:
            initFile = cleaned SunAsAStar file

jdavidrcamacho

import numpy as np
import matplotlib.pylab as plt
plt.close('all')

def vanEck(n):
    #starts at 0
    vanEck = np.array([0])
    #first value is 0
    i=vanEck[0]
    while i < n: