Antonio Cañada Momblant tonicanada

## csvNamedColors.csv

          
            keyword
            RGB hex value

            
              black
              #000000

            
              silver
              #c0c0c0

            
              gray
              #808080

            
              white
              #ffffff

            
              maroon
              #800000

            
              red
              #ff0000

            
              purple
              #800080

            
              fuchsia
              #ff00ff

            
              green
              #008000

## brute_force_test_graph_isomorphism.py
import itertools
import numpy as np


def get_graph_order(adj_matrix):
    if len(adj_matrix) != len(adj_matrix[0]):
        return -1
    else:
        return len(adj_matrix)

## example_of_vertex_permutation_graph.csv

          
            g2_vertex_id
             transormed_to

            
              1
              1

            
              2
              3

            
              3
              5

            
              4
              2

            
              5
              4

## cycle_notation.py
test_case = [3, 5, 2, 4, 7, 8, 1, 6]
expected_result = [[1, 3, 2, 5, 7], [4], [6, 8]]


def first_idx_unseen(seen_array):
    for i in range(len(seen_array)):
        if seen_array[i] == False:
            return i


## generate_automorphisms.py
# Function that receives a matrix adjacency and returns edge set
def edge_set(adj_matrix):
  edge_set = []
  for row in range(len(adj_matrix)):
    for col in range(len(adj_matrix[0])):
      if (list(np.sort([row, col])) not in edge_set):
        if adj_matrix[row][col] == 1:
          edge_set.append(list(np.sort([row, col])))
  return sorted(edge_set)

## example_usage_generate_automorphisms.py
# Bipartite graph K_13
graph_k13 = np.array([
    [0, 0, 0, 1],
    [0, 0, 0, 1],
    [0, 0, 0, 1],
    [1, 1, 1, 0]
])

k13_automorphisms = generate_automorphisms(graph_k13)

## vertex-transitive_edge-transitive_graphs.py
def check_vertex_transitive(adj_matrix):
    vertex_comb = list(itertools.permutations(range(len(adj_matrix)), 2))
    automorphisms_perm = [
        auto["perm_vertex"] for auto in generate_automorphisms(adj_matrix)
    ]
    check = [None] * len(vertex_comb)
    for pair_vertex_idx in range(len(vertex_comb)):
        for auto_idx in range(len(automorphisms_perm)):
            if automorphisms_perm[auto_idx][vertex_comb[pair_vertex_idx][
                    0]] == vertex_comb[pair_vertex_idx][1]:

## UN_Population_2019.csv
Country,Notes,Country code,Type,Parent code,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020
China,9,156,Country/Area,906,554419,569909,582576,593366,603052,612242,621363,630678,640296,650213,660408,670953,682103,694339,708255,724219,742415,762581,784075,805986,827601,848760,869486,889485,908464,926241,942685,957891,972205,986132,1000089,1014022,1027949,1042431,1058172,1075589,1095014,1116095,1137724,1158357,1176884,1192897,1206711,1218817,1230020,1240921,1251636,1261996,1271982,1281515,1290551,1299130,1307352,1315304,1323085,1330776,1338409,1345994,1353569,1361169,1368811,1376498,1384206,1391883,1399454,1406848,1414049,1421022,1427648,1433784,1439324
India,,356,Country/Area,5501,376325,382377,388799,395544,4

## 20220409_understanding_clt_and_ttest.ipynb

      
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## 20220409_understanding_clt_and_ttest_part1.ipynb

      
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	keyword	RGB hex value
	black	#000000
	silver	#c0c0c0
	gray	#808080
	white	#ffffff
	maroon	#800000
	red	#ff0000
	purple	#800080
	fuchsia	#ff00ff
	green	#008000
	import itertools
	import numpy as np


	def get_graph_order(adj_matrix):
	if len(adj_matrix) != len(adj_matrix[0]):
	return -1
	else:
	return len(adj_matrix)
	test_case = [3, 5, 2, 4, 7, 8, 1, 6]
	expected_result = [[1, 3, 2, 5, 7], [4], [6, 8]]


	def first_idx_unseen(seen_array):
	for i in range(len(seen_array)):
	if seen_array[i] == False:
	return i
	# Function that receives a matrix adjacency and returns edge set
	def edge_set(adj_matrix):
	edge_set = []
	for row in range(len(adj_matrix)):
	for col in range(len(adj_matrix[0])):
	if (list(np.sort([row, col])) not in edge_set):
	if adj_matrix[row][col] == 1:
	edge_set.append(list(np.sort([row, col])))
	return sorted(edge_set)
	# Bipartite graph K_13
	graph_k13 = np.array([
	[0, 0, 0, 1],
	[0, 0, 0, 1],
	[0, 0, 0, 1],
	[1, 1, 1, 0]
	])

	k13_automorphisms = generate_automorphisms(graph_k13)
	def check_vertex_transitive(adj_matrix):
	vertex_comb = list(itertools.permutations(range(len(adj_matrix)), 2))
	automorphisms_perm = [
	auto["perm_vertex"] for auto in generate_automorphisms(adj_matrix)
	]
	check = [None] * len(vertex_comb)
	for pair_vertex_idx in range(len(vertex_comb)):
	for auto_idx in range(len(automorphisms_perm)):
	if automorphisms_perm[auto_idx][vertex_comb[pair_vertex_idx][
	0]] == vertex_comb[pair_vertex_idx][1]:
	Country,Notes,Country code,Type,Parent code,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020
	China,9,156,Country/Area,906,554419,569909,582576,593366,603052,612242,621363,630678,640296,650213,660408,670953,682103,694339,708255,724219,742415,762581,784075,805986,827601,848760,869486,889485,908464,926241,942685,957891,972205,986132,1000089,1014022,1027949,1042431,1058172,1075589,1095014,1116095,1137724,1158357,1176884,1192897,1206711,1218817,1230020,1240921,1251636,1261996,1271982,1281515,1290551,1299130,1307352,1315304,1323085,1330776,1338409,1345994,1353569,1361169,1368811,1376498,1384206,1391883,1399454,1406848,1414049,1421022,1427648,1433784,1439324
	India,,356,Country/Area,5501,376325,382377,388799,395544,4