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{
"cells": [
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"slideshow": {
"slide_type": "skip"
}
},
"outputs": [],
"source": [
"from IPython.display import HTML\n",
"from IPython.display import Image"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Algoritmos de Ordenação\n",
"\n",
"Nessa Aula iremos ver os algoritmos de ordenação Insertionsort, Mergesort e Heapsort.\n",
"\n",
"## InsertionSort - Ordenação por Inserção\n",
"\n",
"1. Nesse algoritmo será eleito o segundo número do vetor para iniciar as comparações.\n",
"2. Os elementos masi à esquerda do número eleito estão sempre ordenados de forma crescente ou decrescente.\n",
"3. Um laço de comparação será executado do segundo elemento ao último.\n",
"4. Essa repetição se realizará na quantidade de vezes igual ao número de elementosd do vetor menos um (n-1)."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"text/html": [
"<iframe width='560' height='315' src='https://www.youtube.com/embed/10G5u4jfZ1I' frameborder='0' allow='autoplay; encrypted-media' allowfullscreen></iframe>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"HTML(\"<iframe width='560' height='315' src='https://www.youtube.com/embed/10G5u4jfZ1I' frameborder='0' allow='autoplay; encrypted-media' allowfullscreen></iframe>\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/ROalU379l3U\" frameborder=\"0\" allow=\"autoplay; encrypted-media\" allowfullscreen></iframe>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"HTML('<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/ROalU379l3U\" frameborder=\"0\" allow=\"autoplay; encrypted-media\" allowfullscreen></iframe>')"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## InsertSort em Python"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Entre com o número de elementos de X: 9\n",
"Digite o 1°: 7\n",
"Digite o 2°: 8\n",
"Digite o 3°: 5\n",
"Digite o 4°: 9\n",
"Digite o 5°: 3\n",
"Digite o 6°: 4\n",
"Digite o 7°: 2\n",
"Digite o 8°: 0\n",
"Digite o 9°: 1\n",
"O vetor de entrada é: \n",
"[7, 8, 5, 9, 3, 4, 2, 0, 1]\n",
"O vetor ordenado é: \n",
"[0, 1, 2, 3, 4, 5, 7, 8, 9]\n"
]
}
],
"source": [
"n = int(input(\"Entre com o número de elementos de X: \"))\n",
"\n",
"#Criando a lista de 5 elementos a partir da entrada do usuário\n",
"X = [int(input(\"Digite o {0}{1}: \".format(i+1, chr(176)))) for i in range(n)]\n",
"print(\"O vetor de entrada é: \")\n",
"print(X)\n",
"#Ordenação de forma crescente, a partir do número de elementos em X\n",
"\n",
"#Laço com a quantidade de elementos do vetor\n",
"for i in range(1, n):\n",
" eleito = X[i]\n",
" j = i - 1\n",
" while j >=0 and X[j] > eleito:\n",
" X[j+1] = X[j]\n",
" j = j - 1\n",
" X[j+1] = eleito\n",
" \n",
"print(\"O vetor ordenado é: \")\n",
"print(X)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Qual a complexidade do algoritmo anterior?\n",
"<br>\n",
"<br>\n",
"\n",
"<b>\n",
"\n",
"for i in range(1, n):\n",
"\n",
" eleito = X[i]\n",
" \n",
" j = i - 1\n",
" \n",
" while j >=0 and X[j] > eleito:\n",
" \n",
" X[j+1] = X[j]\n",
" \n",
" j = j - 1\n",
" \n",
" X[j+1] = eleito\n",
"</b>\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"1. Temos duas estruturas de repetição (for, while);\n",
"2. A primeira estrutura (for) roda n-1 vezes.\n",
"3. A segunda estrutura de repetição (While), roda a princípio n-1 vezes, porém dependendo do vetor de entrada isso pode mudar.\n",
"4. No pior dos caso, cada elemento X[j] é comparado a cada elemento do subvetor X[0..j-1].\n",
"5. Com isso o laço interno será executado j+2 para cada valor de j=0,1,..,n-2, no pior dos casos (Qual o pior dos casos?)\n",
"6. Assim temos a seguinte fórmula:\n",
" - $T(n) = 2+ 3+4+...+n$\n",
" - $T(n) = \\sum_{i=1}^{n}{i} - 1$\n",
" - $T(n) = \\frac{(1+n)n}{2} - 1 $\n",
" - $T(n) = \\frac{(n^{2}+n}{2} - 1 $\n",
" - $T(n) = O(n^{2})$ para $c=2$, $n \\ge 1$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## MergerSort - Algoritmo de ordenação por intercalação\n",
"\n",
"1. O vertor é dividido em vetores com a metade do tamanho original por meio de um procedimento recursivo\n",
"2. Essa divisão ocorre até que o vetor fique com apenas um elemento e estes sejam ordenados e intercalados.\n",
"3. Usaremos a técnica da divisão e conquista, que envolve três passos:\n",
" - Dividir o problema em um certo número de subproblemas.\n",
" - Conquistar os subproblemas solucionando-os recursivamente. Se os tamanhos dos subproblemas são suficientemente pequenos, então solucionar os subproblemas de forma simples\n",
" - Combinar as soluções dos subproblemas na solução do problema original\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"1. No MergeSort, usa-se a técnica de dividir e conquistar da seguinte forma:\n",
" - Dividir: dividir a sequência de n elementos a serem ordenados em duas subsequencias de $n/2$ elementos cada.\n",
" - Conquistar: ordenar as duas subsequências recursivamente utilizando ordenação por intercalação\n",
" - Combinar: intercalar as duas subsequências ordenadas para produziar a solução."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"text/html": [
"<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/Y81hkywOKSo\" frameborder=\"0\" allow=\"autoplay; encrypted-media\" allowfullscreen></iframe>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"HTML('<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/Y81hkywOKSo\" frameborder=\"0\" allow=\"autoplay; encrypted-media\" allowfullscreen></iframe>')"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## MergeSort em Python"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Entre com o número de elementos de X: 5\n",
"Digite o 1°: 5\n",
"Digite o 2°: 4\n",
"Digite o 3°: 3\n",
"Digite o 4°: 2\n",
"Digite o 5°: 1\n",
"O vetor de entrada é: \n",
"[5, 4, 3, 2, 1]\n",
"O vetor ordenado é: \n",
"[1, 2, 3, 4, 5]\n"
]
}
],
"source": [
"def merge(X, inicio, fim):\n",
" if inicio < fim:\n",
" meio = int((inicio + fim) / 2)\n",
" merge(X, inicio, meio)\n",
" merge(X, meio + 1, fim)\n",
" intercalar(X, inicio, meio, fim)\n",
"\n",
" \n",
" \n",
"def intercalar(X, inicio, meio, fim):\n",
" aux = [] \n",
" i, j = inicio, meio + 1\n",
" poslivre = inicio\n",
"\n",
" while poslivre < fim + 1:\n",
" if i > meio:\n",
" aux.append(X[j])\n",
" j += 1\n",
" elif j > fim:\n",
" aux.append(X[i])\n",
" i += 1\n",
" elif X[j] < X[i]:\n",
" aux.append(X[j])\n",
" j += 1\n",
" else:\n",
" aux.append(X[i])\n",
" i += 1\n",
" \n",
" poslivre = poslivre + 1\n",
"\n",
" poslivre = 0\n",
" for i in range(inicio, fim+1):\n",
" X[i] = aux[poslivre]\n",
" poslivre = poslivre + 1\n",
"\n",
" \n",
"\n",
"n = int(input(\"Entre com o número de elementos de X: \"))\n",
"\n",
"#Criando a lista de 5 elementos a partir da entrada do usuário\n",
"X = [int(input(\"Digite o {0}{1}: \".format(i+1, chr(176)))) for i in range(n)]\n",
"print(\"O vetor de entrada é: \")\n",
"print(X)\n",
"merge(X, 0, n-1)\n",
"print(\"O vetor ordenado é: \")\n",
"print(X)\n",
"\n",
"\n",
"\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Complexidade do MergeSort\n",
"\n",
"O Trecho relevante do código é:\n",
"<br>\n",
"<br>\n",
"\n",
"<b>\n",
" if inicio < fim:\n",
" \n",
" meio = int((inicio + fim) / 2)\n",
" \n",
" merge(X, inicio, meio)\n",
" \n",
" merge(X, meio + 1, fim)\n",
" \n",
" intercalar(X, inicio, meio, fim)\n",
"</b>\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"1. Primeiro precisamos saber o tempo do algoritmo intercalar.\n",
"2. Observe que não temos um laço dentro de outro laço nesse novo algoritmo.\n",
"3. Como o intercalar irá fazer a intercalação entre doi vetores de tamanho $m_{1}$ e $m_{2}$, então o tempo é $n = m_{1} + m_{2}$\n",
"4. Note que fazemos a chamada recursiva da função `merge` duas vezes, sendo que em cada chamada passa apenas a metade do vetor, ou seja $n/2$ para cada chamada.\n",
"5. Sabendo então que a função intercalar será executada $n$ vezes, a função que representa esse algorítmo será:\n",
" - $T(n) = T(\\frac{n}{2}) + T(\\frac{n}{2}) + n$\n",
" - $T(n) = 2T(\\frac{n}{2}) + n$\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"#### Notação $\\Theta$ e método master\n",
"\n",
"1. Notação $\\Theta$ é utilizada para limite assintótico firme sobre uma função.\n",
"2. Nesse caso a função $f(n)$ é $\\Theta(g(n))$ se existem constantes positivas $c_{1}$, $c_{2}$ e $n_{0}$ tais que $0 \\le c_{1} g(n) \\le f(n) \\le c_{2}g(n)$, para todo $n \\ge n_{0}$\n",
"3. Exemplo: $f(n) = 1/2n^{2}-3n$, $f(n)$ é $\\Theta(n^2)$, pois c_{1} n^2 \\le f(n) \\le c_{2}n^2$, quando $c_{1} = 1/8$, $c_{2} = 1/2$ e $n_{0}=8$. \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
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},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Image(filename='./imagens/notacaoTeta.png')"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"1. O método master apresenta um teorema para resolver quase todas as recorrências $T(n)$ que possuam a forma $aT(\\frac{n}{b})+f(n)$ para $a,b>1$\n",
"2. Para isso fazemos:\n",
" - Se $f(n) = O(n^{log_{b}{a-\\varepsilon}})$, para alguma constante $\\varepsilon > 0$, então $T(n) = \\Theta(n^{\\log_{b}{a}})$\n",
" - Se $f(n) = \\Theta(n^{\\log_{b}{a}})$ então $T(n) = \\Theta(n^{\\log_{b}{a}}\\log(n))$\n",
" - Se $f(n) = \\Omega(n^{log_{b}{a-\\varepsilon}})$ para alguma constante $\\varepsilon > 0$, se $a f(\\frac{n}{b}) \\le c f(n)$ para alguma constante $c < 1$ e para todo $n$ suficientemente grande, então $T(n) = \\Theta(f(n))$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"1. Para o Algoritmo MergeSort podemos ver que:\n",
" - $T(n) = 2T(\\frac{n}{2}) + n$\n",
" - Assim, $a=2$, $b=2$ e $f(n)=n$\n",
" - Em linhas gerais, podemos ver que $f(n) = \\Theta(n^{\\log_{b}{a}})$\n",
" - Logo: $n = \\Theta(n^{\\log_{2}{1}})$\n",
" - Que leva: $n = \\Theta(n^{1})$\n",
" - Pelo método master, podemos concluir que $T(n) = \\Theta(n\\log(n))$\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Heapsort\n",
"1. Baseado na estrutura HEAP, que nada é que um vetor (X) que pode ser visto como uma árvore binária completa, em que cada nó possui no máximo 2 filhos.\n",
"2. Cada vértice da árvore corresponde a um elemento do vetor.\n",
"3. A árvore é completamente preenchida exceto no último nível.\n",
"4. Cada nível é sempre preenchido da direita para a esquerda.\n",
"5. Num HEAP, para todo vértice i diferente da raiz, a seguinte propriedade dever ser válida: X[Pai(i)] $\\ge$ X[i]"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"1. Dado um índice i do vetor: \n",
" - $Pai(i) = i / 2)$\n",
" - $Filho_{esquerdo}(i) = 2* i$\n",
" - $Filho_{direito}(i) = 2 * i + 1$\n",
"2. Como o HEAP é um vetor, o maior elemento ficará na rais, então o primeiro elemento pode ser trocado com o último, ocupando a posição correta dentro do vetor.\n",
"3. Após feita a troca, desconsidera-se esse último elemento.\n",
"4. Esse processo continua até a árvore permanecer com um único elemento\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"data": {
"text/html": [
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"HTML('<iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/MtQL_ll5KhQ\" frameborder=\"0\" allow=\"autoplay; encrypted-media\" allowfullscreen></iframe>')"
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{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Entre com o número de elementos de X: 5\n",
"Digite o 1°: 5\n",
"Digite o 2°: 2\n",
"Digite o 3°: 3\n",
"Digite o 4°: 1\n",
"Digite o 5°: 6\n",
"O vetor de entrada é: \n",
"[5, 2, 3, 1, 6]\n",
"O vetor ordenado é: \n",
"[1, 2, 3, 5, 6]\n"
]
}
],
"source": [
"def transformar_heap(arr, n, i):\n",
" #Inicializa a Raíz com o maior valor\n",
" largest = i # Initialize largest as root\n",
" # left = 2*i + 1\n",
" l = 2 * i + 1 \n",
" # right = 2*i + 2\n",
" r = 2 * i + 2 \n",
" \n",
" #Verifica se o filho esquerdo da raiz existe e se é a maior raiz\n",
" if l < n and arr[i] < arr[l]:\n",
" largest = l\n",
" \n",
" #Verifica se o filho direito da raiz existe e se ela \n",
" # é maior que a raiz\n",
"\n",
" if r < n and arr[largest] < arr[r]:\n",
" largest = r\n",
" \n",
" #Troca a raíz, se necessário\n",
" if largest != i:\n",
" arr[i],arr[largest] = arr[largest],arr[i] # troca \n",
" # Heapify the root.\n",
" transformar_heap(arr, n, largest)\n",
" \n",
"# Função principal de ordenação do vetor dado\n",
"def heapSort(arr):\n",
" n = len(arr)\n",
" \n",
" # Construídno o maxheap\n",
" for i in range(n, -1, -1):\n",
" transformar_heap(arr, n, i)\n",
" \n",
" # Um por um extraímos os elementos\n",
" for i in range(n-1, 0, -1):\n",
" arr[i], arr[0] = arr[0], arr[i] # troca\n",
" transformar_heap(arr, i, 0)\n",
" \n",
"n = int(input(\"Entre com o número de elementos de X: \"))\n",
"\n",
"#Criando a lista de 5 elementos a partir da entrada do usuário\n",
"X = [int(input(\"Digite o {0}{1}: \".format(i+1, chr(176)))) for i in range(n)]\n",
"print(\"O vetor de entrada é: \")\n",
"print(X)\n",
"\n",
"\n",
"heapSort(X)\n",
"print(\"O vetor ordenado é: \")\n",
"print(X)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
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\n",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Image(filename='./imagens/heapsort.png')"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Complexidade do HeapSort\n",
"\n",
"1. A função `heapSort` faz a chamada do método `transformar_heap` duas vezes, em dois laços distintos.\n",
"2. O `heapSort` chama o `transformar_heap` $n$ vezes.\n",
"3. O método `transformar_heap` é aplicado sempre a um nó da árvore, que representa um elemento do vetor, e afunda esse nó até que a propriedade HEAP seja válida.\n",
"4. O pior caso ocorre quando quando o procedimento é aplicado sobre o primeiro elemento e este deve afundar até alcançar uma folha.\n",
"5. Logo, o número de trocas corresponde à altura da árvore, que é $\\log n$.\n",
"6. Dessa forma, vemos que a complexidade desse algorítmo é $O(n\\log{(n)})$\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Exercícios\n",
"\n",
"1. Execute os algoritmos de ordenação apresentados nessa aula e faça uma comparação de tempo de execução para cada caso, para um vetor de tamanho 10000. Para isso, use também como base o seguinte código em Python:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2.0009677410125732\n",
"[24, 26, 56, 19, 6, 45, 37, 67, 1, 59]\n"
]
}
],
"source": [
"import time\n",
"import random\n",
"t0 = time.time()\n",
"time.sleep(2)\n",
"t1 = time.time()\n",
"deltaT = t1 - t0\n",
"print(deltaT)\n",
"\n",
"meusNumeros = random.sample(range(100), 10)\n",
"print(meusNumeros)"
]
}
],
"metadata": {
"celltoolbar": "Slideshow",
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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