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- "peekOfCode": "def heapify(lista, n, i):\n\tlargest = i # Initialize largest as root\n\tl = 2 * i + 1 # left = 2*i + 1\n\tr = 2 * i + 2 # right = 2*i + 2\n\t# See if left child of root exists and is\n\t# greater than root\n\tif l < n and lista[i] < lista[l]:\n\t\tlargest = l\n\t# See if right child of root exists and is\n\t# greater than root",
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- "peekOfCode": "\tlargest = i # Initialize largest as root\n\tl = 2 * i + 1 # left = 2*i + 1\n\tr = 2 * i + 2 # right = 2*i + 2\n\t# See if left child of root exists and is\n\t# greater than root\n\tif l < n and lista[i] < lista[l]:\n\t\tlargest = l\n\t# See if right child of root exists and is\n\t# greater than root\n\tif r < n and lista[largest] < lista[r]:",
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- "peekOfCode": "\tl = 2 * i + 1 # left = 2*i + 1\n\tr = 2 * i + 2 # right = 2*i + 2\n\t# See if left child of root exists and is\n\t# greater than root\n\tif l < n and lista[i] < lista[l]:\n\t\tlargest = l\n\t# See if right child of root exists and is\n\t# greater than root\n\tif r < n and lista[largest] < lista[r]:\n\t\tlargest = r",
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- "peekOfCode": "\tr = 2 * i + 2 # right = 2*i + 2\n\t# See if left child of root exists and is\n\t# greater than root\n\tif l < n and lista[i] < lista[l]:\n\t\tlargest = l\n\t# See if right child of root exists and is\n\t# greater than root\n\tif r < n and lista[largest] < lista[r]:\n\t\tlargest = r\n\t# Change root, if needed",
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- "peekOfCode": "\t\tlargest = l\n\t# See if right child of root exists and is\n\t# greater than root\n\tif r < n and lista[largest] < lista[r]:\n\t\tlargest = r\n\t# Change root, if needed\n\tif largest != i:\n\t\t(lista[i], lista[largest]) = (lista[largest], lista[i]) # swap\n\t\t# Heapify the root.\n\t\theapify(lista, n, largest)",
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- "peekOfCode": "\t\tlargest = r\n\t# Change root, if needed\n\tif largest != i:\n\t\t(lista[i], lista[largest]) = (lista[largest], lista[i]) # swap\n\t\t# Heapify the root.\n\t\theapify(lista, n, largest)",
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- "peekOfCode": "def merge(arr, l, m, r):\n\tn1 = m - l + 1\n\tn2 = r - m\n\t# create temp arrays\n\tL = [0] * (n1)\n\tR = [0] * (n2)\n\t# Copy data to temp arrays L[] and R[]\n\tfor i in range(0, n1):\n\t\tL[i] = arr[l + i]\n\tfor j in range(0, n2):",
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- "peekOfCode": "\tn1 = m - l + 1\n\tn2 = r - m\n\t# create temp arrays\n\tL = [0] * (n1)\n\tR = [0] * (n2)\n\t# Copy data to temp arrays L[] and R[]\n\tfor i in range(0, n1):\n\t\tL[i] = arr[l + i]\n\tfor j in range(0, n2):\n\t\tR[j] = arr[m + 1 + j]",
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- "peekOfCode": "\tn2 = r - m\n\t# create temp arrays\n\tL = [0] * (n1)\n\tR = [0] * (n2)\n\t# Copy data to temp arrays L[] and R[]\n\tfor i in range(0, n1):\n\t\tL[i] = arr[l + i]\n\tfor j in range(0, n2):\n\t\tR[j] = arr[m + 1 + j]\n\t# Merge the temp arrays back into arr[l..r]",
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- "peekOfCode": "\tL = [0] * (n1)\n\tR = [0] * (n2)\n\t# Copy data to temp arrays L[] and R[]\n\tfor i in range(0, n1):\n\t\tL[i] = arr[l + i]\n\tfor j in range(0, n2):\n\t\tR[j] = arr[m + 1 + j]\n\t# Merge the temp arrays back into arr[l..r]\n\ti = 0\t # Initial index of first subarray\n\tj = 0\t # Initial index of second subarray",
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- "peekOfCode": "\tR = [0] * (n2)\n\t# Copy data to temp arrays L[] and R[]\n\tfor i in range(0, n1):\n\t\tL[i] = arr[l + i]\n\tfor j in range(0, n2):\n\t\tR[j] = arr[m + 1 + j]\n\t# Merge the temp arrays back into arr[l..r]\n\ti = 0\t # Initial index of first subarray\n\tj = 0\t # Initial index of second subarray\n\tk = l\t # Initial index of merged subarray",
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- "peekOfCode": "\t\tL[i] = arr[l + i]\n\tfor j in range(0, n2):\n\t\tR[j] = arr[m + 1 + j]\n\t# Merge the temp arrays back into arr[l..r]\n\ti = 0\t # Initial index of first subarray\n\tj = 0\t # Initial index of second subarray\n\tk = l\t # Initial index of merged subarray\n\twhile i < n1 and j < n2:\n\t\tif L[i] <= R[j]:\n\t\t\tarr[k] = L[i]",
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- "peekOfCode": "\t\tR[j] = arr[m + 1 + j]\n\t# Merge the temp arrays back into arr[l..r]\n\ti = 0\t # Initial index of first subarray\n\tj = 0\t # Initial index of second subarray\n\tk = l\t # Initial index of merged subarray\n\twhile i < n1 and j < n2:\n\t\tif L[i] <= R[j]:\n\t\t\tarr[k] = L[i]\n\t\t\ti += 1\n\t\telse:",
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- "peekOfCode": "\ti = 0\t # Initial index of first subarray\n\tj = 0\t # Initial index of second subarray\n\tk = l\t # Initial index of merged subarray\n\twhile i < n1 and j < n2:\n\t\tif L[i] <= R[j]:\n\t\t\tarr[k] = L[i]\n\t\t\ti += 1\n\t\telse:\n\t\t\tarr[k] = R[j]\n\t\t\tj += 1",
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- "peekOfCode": "\tj = 0\t # Initial index of second subarray\n\tk = l\t # Initial index of merged subarray\n\twhile i < n1 and j < n2:\n\t\tif L[i] <= R[j]:\n\t\t\tarr[k] = L[i]\n\t\t\ti += 1\n\t\telse:\n\t\t\tarr[k] = R[j]\n\t\t\tj += 1\n\t\tk += 1",
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- "peekOfCode": "\tk = l\t # Initial index of merged subarray\n\twhile i < n1 and j < n2:\n\t\tif L[i] <= R[j]:\n\t\t\tarr[k] = L[i]\n\t\t\ti += 1\n\t\telse:\n\t\t\tarr[k] = R[j]\n\t\t\tj += 1\n\t\tk += 1\n\t# Copy the remaining elements of L[], if there",
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- "peekOfCode": "\t\t\tarr[k] = L[i]\n\t\t\ti += 1\n\t\telse:\n\t\t\tarr[k] = R[j]\n\t\t\tj += 1\n\t\tk += 1\n\t# Copy the remaining elements of L[], if there\n\t# are any\n\twhile i < n1:\n\t\tarr[k] = L[i]",
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- "peekOfCode": "\t\t\tarr[k] = R[j]\n\t\t\tj += 1\n\t\tk += 1\n\t# Copy the remaining elements of L[], if there\n\t# are any\n\twhile i < n1:\n\t\tarr[k] = L[i]\n\t\ti += 1\n\t\tk += 1\n\t# Copy the remaining elements of R[], if there",
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- "peekOfCode": "\t\tarr[k] = L[i]\n\t\ti += 1\n\t\tk += 1\n\t# Copy the remaining elements of R[], if there\n\t# are any\n\twhile j < n2:\n\t\tarr[k] = R[j]\n\t\tj += 1\n\t\tk += 1\n# l is for left index and r is right index of the",
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- "peekOfCode": "\t\tarr[k] = R[j]\n\t\tj += 1\n\t\tk += 1\n# l is for left index and r is right index of the\n# sub-array of arr to be sorted",
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- "peekOfCode": "def mergeSort(lista, l, r):\n\tif l < r:\n # Same as (l+r)//2, but avoids overflow for\n # large l and h\n\t\tm = l+(r-l)//2\n # Sort first and second halves\n\t\tmergeSort(lista, l, m)\n\t\tmergeSort(lista, m+1, r)\n\t\tmerge(lista, l, m, r)\n''' Luis Andrés López Mañán",
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- "peekOfCode": "def heapSort(lista):\n\t# Se busca el tamaño de la lista\n\tn = len(lista)\n\theap.heapify(lista,n,0)\n\t''' Se crea un heap máximo y el último padre estará en\n\t\tla posición h1, i.e., la mitad del tamaño de la lista.\n\t\tPor lo tanto, ese sería el comienzo. \n\t'''\n\th1 = (n // 2) - 1\n\tfor i in range(h1, -1, -1):",
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- "kind": 5,
|
|
435
|
|
- "importPath": "sorting",
|
|
436
|
|
- "description": "sorting",
|
|
437
|
|
- "peekOfCode": "\t\t\tlista[j] = temp\n\t\tgap = gap // 2 # decreases the gap to continue the loop \n\treturn lista\nmaxValor=1000 \t#define el valor maximo de los elementos de la lista\nlargoLista=1000 #define el largo de las listas a ordenar\nveces=100 \t\t#define las veces que se va a hacer el ordenamiento \nacumulaMerge=0 \t#variable para acumular el tiempo de ejecucion del mergesort\nacumulaHeap=0 \t#variable para acumular el tiempo de ejecucion del heapsort\nacumulaQuick=0 \t#variable para acumular el tiempo de ejecucion del quicksort\nacumulaShell=0 \t#variable para acumular el tiempo de ejecucion del shellsort",
|
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438
|
|
- "detail": "sorting",
|
|
439
|
|
- "documentation": {}
|
|
440
|
|
- },
|
|
441
|
|
- {
|
|
442
|
|
- "label": "\t\tgap",
|
|
443
|
|
- "kind": 5,
|
|
444
|
|
- "importPath": "sorting",
|
|
445
|
|
- "description": "sorting",
|
|
446
|
|
- "peekOfCode": "\t\tgap = gap // 2 # decreases the gap to continue the loop \n\treturn lista\nmaxValor=1000 \t#define el valor maximo de los elementos de la lista\nlargoLista=1000 #define el largo de las listas a ordenar\nveces=100 \t\t#define las veces que se va a hacer el ordenamiento \nacumulaMerge=0 \t#variable para acumular el tiempo de ejecucion del mergesort\nacumulaHeap=0 \t#variable para acumular el tiempo de ejecucion del heapsort\nacumulaQuick=0 \t#variable para acumular el tiempo de ejecucion del quicksort\nacumulaShell=0 \t#variable para acumular el tiempo de ejecucion del shellsort\nfor i in range(veces):",
|
|
447
|
|
- "detail": "sorting",
|
|
448
|
|
- "documentation": {}
|
|
449
|
|
- },
|
|
450
|
|
- {
|
|
451
|
|
- "label": "\tmergelista",
|
|
452
|
|
- "kind": 5,
|
|
453
|
|
- "importPath": "sorting",
|
|
454
|
|
- "description": "sorting",
|
|
455
|
|
- "peekOfCode": "\tmergelista = [randint(0,maxValor) for r in range(largoLista)] #creamos una lista con valores al azar\n\theaplista=list(mergelista)\n\tquicklista=list(mergelista)\n\tsearchlista=list(mergelista)\n\tt1 = time.process_time()\t\t\t\t\t#tomamos el tiempo inicial\n\tmergeSort(mergelista,0,len(mergelista)-1) \t#ejecutamos el algoritmo mergeSort\n\tacumulaMerge+=time.process_time() - t1\t\t#acumulamos el tiempo de ejecucion\n\t# print(mergelista)\t\t\t\t\t\t\t#desplegamos la lista\n\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\theapSort(heaplista)\t\t\t\t\t #ejecutamos el algoritmo heapSort",
|
|
456
|
|
- "detail": "sorting",
|
|
457
|
|
- "documentation": {}
|
|
458
|
|
- },
|
|
459
|
|
- {
|
|
460
|
|
- "label": "\tt1",
|
|
461
|
|
- "kind": 5,
|
|
462
|
|
- "importPath": "sorting",
|
|
463
|
|
- "description": "sorting",
|
|
464
|
|
- "peekOfCode": "\tt1 = time.process_time()\t\t\t\t\t#tomamos el tiempo inicial\n\tmergeSort(mergelista,0,len(mergelista)-1) \t#ejecutamos el algoritmo mergeSort\n\tacumulaMerge+=time.process_time() - t1\t\t#acumulamos el tiempo de ejecucion\n\t# print(mergelista)\t\t\t\t\t\t\t#desplegamos la lista\n\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\theapSort(heaplista)\t\t\t\t\t #ejecutamos el algoritmo heapSort\n\tacumulaHeap+=time.process_time() - t1 \t#acumulamos el tiempo de ejecucion\n\t# print(heaplista)\t\t\t\t\t\t#desplegamos la lista\n\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\tquickresult = quickSort(quicklista)\t\t\t\t\t#ejecutamos el algoritmo quickSort",
|
|
465
|
|
- "detail": "sorting",
|
|
466
|
|
- "documentation": {}
|
|
467
|
|
- },
|
|
468
|
|
- {
|
|
469
|
|
- "label": "\tt1",
|
|
470
|
|
- "kind": 5,
|
|
471
|
|
- "importPath": "sorting",
|
|
472
|
|
- "description": "sorting",
|
|
473
|
|
- "peekOfCode": "\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\theapSort(heaplista)\t\t\t\t\t #ejecutamos el algoritmo heapSort\n\tacumulaHeap+=time.process_time() - t1 \t#acumulamos el tiempo de ejecucion\n\t# print(heaplista)\t\t\t\t\t\t#desplegamos la lista\n\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\tquickresult = quickSort(quicklista)\t\t\t\t\t#ejecutamos el algoritmo quickSort\n\tacumulaQuick+=time.process_time() - t1\t#acumulamos el tiempo de ejecucion\n\t# print(quicklista)\t\t\t\t\t\t#desplegamos la lista\n\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\tshellSort(searchlista)\t\t\t\t\t#ejecutamos el algoritmo shellSort",
|
|
474
|
|
- "detail": "sorting",
|
|
475
|
|
- "documentation": {}
|
|
476
|
|
- },
|
|
477
|
|
- {
|
|
478
|
|
- "label": "\tt1",
|
|
479
|
|
- "kind": 5,
|
|
480
|
|
- "importPath": "sorting",
|
|
481
|
|
- "description": "sorting",
|
|
482
|
|
- "peekOfCode": "\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\tquickresult = quickSort(quicklista)\t\t\t\t\t#ejecutamos el algoritmo quickSort\n\tacumulaQuick+=time.process_time() - t1\t#acumulamos el tiempo de ejecucion\n\t# print(quicklista)\t\t\t\t\t\t#desplegamos la lista\n\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\tshellSort(searchlista)\t\t\t\t\t#ejecutamos el algoritmo shellSort\n\tacumulaShell+=time.process_time() - t1\t#acumulamos el tiempo de ejecucion\n\t# print(searchlista)\t\t\t\t\t\t#desplegamos la lista\n# imprimos los resultados\nprint (\"Promedio de tiempo de ejecucion de \"+ str(veces) +\" listas de largo \" + str(largoLista))",
|
|
483
|
|
- "detail": "sorting",
|
|
484
|
|
- "documentation": {}
|
|
485
|
|
- },
|
|
486
|
|
- {
|
|
487
|
|
- "label": "\tquickresult",
|
|
488
|
|
- "kind": 5,
|
|
489
|
|
- "importPath": "sorting",
|
|
490
|
|
- "description": "sorting",
|
|
491
|
|
- "peekOfCode": "\tquickresult = quickSort(quicklista)\t\t\t\t\t#ejecutamos el algoritmo quickSort\n\tacumulaQuick+=time.process_time() - t1\t#acumulamos el tiempo de ejecucion\n\t# print(quicklista)\t\t\t\t\t\t#desplegamos la lista\n\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\tshellSort(searchlista)\t\t\t\t\t#ejecutamos el algoritmo shellSort\n\tacumulaShell+=time.process_time() - t1\t#acumulamos el tiempo de ejecucion\n\t# print(searchlista)\t\t\t\t\t\t#desplegamos la lista\n# imprimos los resultados\nprint (\"Promedio de tiempo de ejecucion de \"+ str(veces) +\" listas de largo \" + str(largoLista))\nprint (\"MergeSort \" + str(acumulaMerge/veces) + \" segundos\")",
|
|
492
|
|
- "detail": "sorting",
|
|
493
|
|
- "documentation": {}
|
|
494
|
|
- },
|
|
495
|
|
- {
|
|
496
|
|
- "label": "\tt1",
|
|
497
|
|
- "kind": 5,
|
|
498
|
|
- "importPath": "sorting",
|
|
499
|
|
- "description": "sorting",
|
|
500
|
|
- "peekOfCode": "\tt1 = time.process_time()\t\t\t\t#tomamos el tiempo inicial\n\tshellSort(searchlista)\t\t\t\t\t#ejecutamos el algoritmo shellSort\n\tacumulaShell+=time.process_time() - t1\t#acumulamos el tiempo de ejecucion\n\t# print(searchlista)\t\t\t\t\t\t#desplegamos la lista\n# imprimos los resultados\nprint (\"Promedio de tiempo de ejecucion de \"+ str(veces) +\" listas de largo \" + str(largoLista))\nprint (\"MergeSort \" + str(acumulaMerge/veces) + \" segundos\")\nprint (\"HeapSort \" + str(acumulaHeap/veces) + \" segundos\")\nprint (\"QuickSort \" + str(acumulaQuick/veces) + \" segundos\")\nprint (\"ShellSort \" + str(acumulaShell/veces) + \" segundos\")",
|
|
501
|
|
- "detail": "sorting",
|
|
502
|
|
- "documentation": {}
|
|
503
|
|
- }
|
|
504
|
|
-]
|
