Add Search Algorithm

[UditNayak]

Issue: #1155 - Add Animations for Search Algorithms

Context:

This PR introduces animations for search algorithms, enhancing the user experience by providing a visual understanding of the algorithm's progression.

Changes Introduced:

1. Animation Components:

   • Developed an AnimateProblem class to handle animations for various search algorithms.
   • Implemented methods for generating random lines, calculating straight-line distances, and transposing matrices.

2. Integration with Search Algorithms:

   • Integrated the AnimateProblem class with different search algorithms such as A*, Weighted A*, BFS, DFS, UCS, and Best-First Search.
   • Utilized a dictionary to define the solvers and their corresponding f-value functions.

3. User Interface and Visualization:

   • Created a matplotlib figure for displaying the animations.
   • Added visual indicators for obstacles, explored nodes, the current node, the initial state, and the goal state.

4. Performance Optimizations:

   • Optimized the animation rendering to ensure smooth performance.
   • Minimized potential lag by efficiently handling the exploration and plotting of nodes.

[dmeoli]

Thanks for this, @UditNayak — animated search on a grid is a genuinely nice addition for #1155. A few things to address before it can be merged: (1) It currently crashes on modern matplotlib: ax.scatter(*transpose(...)) raises 'missing x and y' whenever the point set is empty - this happens on the very first step because the root node's solution() is [] (and also if obstacles is empty). Please guard empty sets before scatter. (2) obstacles=random_lines(...) as a default argument is evaluated once at import time and shared across instances - please use obstacles=None and generate them inside init. (3) import heapq is unused (the frontier uses utils.PriorityQueue). (4) straight_line_distance duplicates utils.euclidean_distance - please reuse it. (5) Minor: use triple-quoted docstrings to match the repo style. Once it runs end-to-end on current matplotlib, happy to re-review!