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Algorithm Animations

Animora provides educational algorithm visualizations (animora.algorithms) driven by real execution logic and explicit OperationTrace recordings.

1. Supported Algorithms

  • Binary Search: binary_search(arr, target) — $O(\log N)$ interval comparison tracing.
  • Sorting Algorithms (Visually Distinguishable):
  • bubble_sort(arr) — Adjacent pair compares & swaps.
  • selection_sort(arr) — Minimum prefix scanning & swaps.
  • insertion_sort(arr) — Key selection & backward shifting.
  • merge_sort(arr) — Subarray divide-and-conquer and merge buffer writes.
  • quick_sort(arr) — Pivot partitioning and recursive sub-ranges.
  • Graph Traversals: bfs(graph, start) and dfs(graph, start).
  • Shortest Path & Pathfinding: dijkstra(graph, start, target) and a_star(graph, start, goal, heuristic).
  • Dynamic Programming: fibonacci_dp(n, table).
  • Backtracking: n_queens(n, table).

2. Usage Example: Sorting an Array

from animora.core import Scene
from animora.datastructures import Array
from animora.algorithms import quick_sort
from animora.theme import ModernDark, use_theme


class SortingScene(Scene):
    def construct(self) -> None:
        with use_theme(ModernDark):
            arr = Array([45, 12, 89, 33, 7, 56])
            self.play(arr.animate_create())
            self.play(*quick_sort(arr))

3. The Algorithm Trace API (animora.algorithms.trace)

Animora separates algorithmic execution from rendering through the Algorithm Trace API. Bundled algorithms log operations into an AlgorithmTrace, which you can query, inspect, serialize, or transform into custom animations.

Inspecting Traces

from animora.algorithms import quick_sort
from animora.algorithms.trace import OperationType

# Run algorithm and collect the recorded trace:
# quick_sort returns an AlgorithmTrace (which also unpacks animations into scene.play)
trace = quick_sort(arr)

# 1. Filter operations by type:
swaps = trace.filter(OperationType.SWAP)
compares = trace.filter(OperationType.COMPARE)

# 2. Count specific operations:
total_swaps = trace.count(OperationType.SWAP)
print(f"Total swaps performed: {total_swaps}")

# 3. Retrieve targets involved in a specific step:
targets = trace.targets_for(OperationType.SWAP)

# 4. Generate structured summary or export to dict:
summary = trace.summary()
trace_data = trace.to_dict()