Skip to content

002964524_Yojani_Tammineni #129

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
NUsakhyatha wants to merge 5 commits into
base: Students
Choose a base branch
from
Open

002964524_Yojani_Tammineni #129

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
b44640b
commit assignment 1&2
NUsakhyatha Oct 12, 2023
afc11dd
assignment 3
NUsakhyatha Oct 22, 2023
b30a2d8
Merge branch 'nikbearbrown:Students' into Students
NUsakhyatha Nov 19, 2023
542bd6e
assignment 4
NUsakhyatha Nov 19, 2023
4791098
Add files via upload
NUsakhyatha Dec 10, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
265 changes: 265 additions & 0 deletions Submissions/002964524_SakhyathaYojani_Tammineni/Assigment1_002964525.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,265 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "code",
"source": [
"#Brick Pyramid Construction\n",
"def min_rows_to_build_pyramid(n):\n",
" # Initialize variables to keep track of rows and total bricks\n",
" rows = 0\n",
" bricks_used = 0\n",
"\n",
" while bricks_used < n:\n",
" rows += 1\n",
" bricks_used += rows # Calculate the number of bricks in the current row\n",
"\n",
"\n",
" if(n==bricks_used):\n",
" return rows\n",
" return rows - 1\n",
"\n",
"# Example usage:\n",
"result1 = min_rows_to_build_pyramid(7)\n",
"print(result1) # Output: 3\n",
"\n",
"result2 = min_rows_to_build_pyramid(15)\n",
"print(result2) # Output: 5\n",
"\n",
"result3 = min_rows_to_build_pyramid(1)\n",
"print(result3) # Output: 1\n",
"\n",
"result4 = min_rows_to_build_pyramid(20)\n",
"print(result4) # Output: 5\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "LqiHEhftfVkA",
"outputId": "22f55000-4828-4195-bcc4-2855e5888a11"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"3\n",
"5\n",
"1\n",
"5\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#Course Registration Optimization\n",
"\n",
"def stable_matching(student_prefs, course_prefs, course_capacity):\n",
" num_students = len(student_prefs)\n",
" num_courses = len(course_prefs)\n",
"\n",
" # Initialize all students and courses as free and unassigned\n",
" student_free = [True] * num_students\n",
" course_assignment = [-1] * num_courses\n",
"\n",
" while True:\n",
" # Find an unassigned student\n",
" student = -1\n",
" for i in range(num_students):\n",
" if student_free[i]:\n",
" student = i\n",
" break\n",
"\n",
" # If all students are assigned, we have a stable assignment\n",
" if student == -1:\n",
" break\n",
"\n",
" # Iterate through student's preferences\n",
" for i in range(len(student_prefs[student])):\n",
" course = student_prefs[student][i]\n",
"\n",
" # Check if the course is at capacity\n",
" if course_capacity[course] > 0:\n",
" course_capacity[course] -= 1\n",
" course_assignment[course] = student\n",
" student_free[student] = False\n",
" break\n",
"\n",
" # If the course is full, check if the current student prefers it over the current assignment\n",
" for j in range(num_students):\n",
" if course_assignment[course] == student_prefs[course][j]:\n",
" student_prefs[course][j] = -1\n",
" student_free[course_assignment[course]] = True\n",
" course_assignment[course] = student\n",
" student_free[student] = False\n",
" break\n",
"\n",
" return course_assignment\n",
"\n",
"# Example usage\n",
"student_preferences = [\n",
" [0, 1, 2],\n",
" [1, 0, 2],\n",
" [0, 1, 2],\n",
"]\n",
"\n",
"course_preferences = [\n",
" [0, 1, 2],\n",
" [1, 0, 2],\n",
" [0, 1, 2],\n",
"]\n",
"\n",
"course_capacity = [2, 2, 2]\n",
"\n",
"result = stable_matching(student_preferences, course_preferences, course_capacity)\n",
"print(result)\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Y6q25uHkH84S",
"outputId": "6746b275-bdfe-46a9-8c10-d6edf8a44a65"
},
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[2, 1, -1]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#Array Reordering Algorithm\n",
"\n",
"def reorder_array(arr):\n",
" even_nums = []\n",
" odd_nums = []\n",
"\n",
" for num in arr:\n",
" if num % 2 == 0:\n",
" even_nums.append(num)\n",
" else:\n",
" odd_nums.append(num)\n",
"\n",
" even_nums.sort()\n",
" odd_nums.sort()\n",
"\n",
" reordered_arr = even_nums + odd_nums\n",
" return reordered_arr\n",
"\n",
"# Example usage:\n",
"input_arr = [5, 2, 9, 4, 3, 6, 8, 1, 7]\n",
"output_arr = reorder_array(input_arr)\n",
"print(output_arr) # Output: [2, 4, 6, 8, 5, 9, 3, 1, 7]\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "9hJdXl8VNEf3",
"outputId": "535684a4-ef45-4180-b428-07b0e82e1b1b"
},
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[2, 4, 6, 8, 1, 3, 5, 7, 9]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#Shortest Path in a Weighted Directed Graph\n",
"\n",
"import heapq\n",
"\n",
"def shortest_path(graph, source, target):\n",
" num_nodes = len(graph)\n",
" dist = [float('inf')] * num_nodes\n",
" dist[source] = 0\n",
" prev = [None] * num_nodes\n",
" visited = set()\n",
" pq = [(0, source)]\n",
"\n",
" while pq:\n",
" _, u = heapq.heappop(pq)\n",
"\n",
" if u == target:\n",
" path = []\n",
" while u is not None:\n",
" path.append(u)\n",
" u = prev[u]\n",
" return path[::-1]\n",
"\n",
" if u not in visited:\n",
" visited.add(u)\n",
" for v, weight in enumerate(graph[u]):\n",
" if weight > 0 and dist[u] + weight < dist[v]:\n",
" dist[v] = dist[u] + weight\n",
" prev[v] = u\n",
" heapq.heappush(pq, (dist[v], v))\n",
"\n",
" return []\n",
"\n",
"# Example usage:\n",
"graph = [\n",
" [0, 4, 0, 0, 0, 0],\n",
" [0, 0, 8, 0, 0, 0],\n",
" [0, 0, 0, 7, 0, 2],\n",
" [0, 2, 0, 0, 0, 0],\n",
" [0, 0, 0, 5, 0, 3],\n",
" [0, 0, 0, 0, 0, 0]\n",
"]\n",
"\n",
"source_node = 0\n",
"target_node = 5\n",
"shortest_path = shortest_path(graph, source_node, target_node)\n",
"print(shortest_path) # Output: [0, 1, 2, 5]\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "SbQb-oaDP8rF",
"outputId": "0e65f72d-9ddc-40c7-c3aa-1b06f58bd378"
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[0, 1, 2, 5]\n"
]
}
]
}
]
}
Loading