Asked in: Flipkart
import math
import os
import random
import re
// ... rest of solution available after purchase
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To approach this problem, it’s important to carefully analyze the structure of the input data, the properties of the graph, and the requirements for valid sequences. Here's a detailed breakdown of how to think about the problem step-by-step.
1. Understand the structure and properties of the graph:
- The input describes a network of houses connected by roads, forming a tree.
- Since the graph is a tree, there are no cycles, and exactly one unique shortest path exists between any two nodes.
- Each edge has a binary value: either 0 or 1.
- There are house_nodes nodes and house_nodes - 1 edges, confirming the tree property.
2. Understand the problem statement clearly:
- You need to count sequences of length k of houses h[1], h[2], ..., h[k].
- The condition for a sequence to be counted is that for every consecutive pair (h[i], h[i+1]) in the sequence, the shortest path between these two houses contains at least one edge with value 1.
- Equivalently, for the entire route from h[1] to h[2] to ... to h[k], each segment’s path must have at least one '1' edge.
- Note that the paths are unique due to the tree structure.
3. Key challenges:
- The problem asks for sequences of length k, not just pairs or paths. The count of such sequences could be huge.
- Checking the path between every pair for presence of at least one '1' edge could be expensive if done naively.
- Efficiently determining whether a path contains an edge with value 1 is crucial.
4. Core observations about the tree and edges:
- Edges with value 0 and edges with value 1 split the tree’s connectivity into different components.
- If we consider the subgraph formed only by edges with value 0, it breaks the tree into multiple connected components (forests).
- Within such a 0-edge connected component, any path between two nodes will only contain edges of value 0.
- Hence, the presence of a '1' edge in the path depends on whether the start and end nodes are in the same 0-edge component or not.
5. Restate the problem using components:
- If two nodes are in the same 0-edge connected component, their path contains no '1' edges.
- If two nodes lie in different 0-edge components, their path must cross at least one '1' edge (since the tree connects components through edges valued 1).
- Therefore, a path contains a '1' edge if and only if its endpoints belong to different 0-edge connected components.
6. Simplify the problem using this insight:
- Construct connected components considering only edges valued 0.
- Label each node by the component it belongs to.
- A pair of nodes in the same component → path contains only 0 edges (no '1' edge).
- A pair of nodes in different components → path contains at least one '1' edge.
7. Apply this to sequences of length k:
- For a sequence (h[1], h[2], ..., h[k]) to be valid, every consecutive pair must be from different 0-edge components.
- Thus, no two consecutive nodes can belong to the same component.
- We are essentially counting sequences of length k from nodes such that consecutive nodes belong to different 0-edge components.
8. Model the problem as a sequence constraint:
- Each node belongs to a component.
- The sequence consists of nodes, with the rule that consecutive nodes are not in the same component.
- Counting sequences that satisfy this constraint is a combinatorial problem.
9. Further approach to counting sequences:
- Determine the size (number of nodes) of each 0-edge component.
- The nodes can be grouped by components.
- Since nodes in the same component cannot be adjacent in the sequence, the sequence must alternate between nodes from different components.
- The problem becomes counting sequences of length k formed by picking nodes such that no two adjacent picks come from the same group.
10. High-level method to count:
- If we consider the components as "colors," the sequence is a k-length sequence of nodes colored with components, with the constraint that no two adjacent colors are the same.
- However, within each component, multiple nodes exist, so for each position where the component is chosen, we can choose any node from that component.
11. Calculate total valid sequences:
- First, find the number of ways to assign component labels to each position of the sequence such that no two adjacent are the same.
- Then, for each position, multiply by the size of the chosen component (number of nodes available to choose from).
- Summing over all such valid component sequences gives the total count of sequences.
12. Potential optimizations:
- If the number of components is small, use dynamic programming to count the number of ways to form sequences of length k with no two adjacent identical components.
- For each component at position i, the number of choices is the size of that component.
- DP state could be: current position and last chosen component.
- Transitions: for position i, choose any component different from the last one.
13. Edge cases and constraints:
- If k = 1, any single node sequence is valid because no edges need to be traversed, but since the condition involves paths between consecutive nodes, single-length sequences trivially satisfy it.
- If the tree has only one component with all edges 0, no paths contain edges valued 1, so no valid sequences of length greater than 1 exist.
- Large k or large number of components may require modulo operations and careful optimization.
14. Summary:
- Use the property of the tree and edge values to partition the nodes into 0-edge connected components.
- Transform the problem into counting sequences of nodes with constraints on their component memberships.
- Use combinatorial dynamic programming to count sequences with no consecutive nodes from the same component, factoring in component sizes.
- This leverages the uniqueness of paths in trees and the binary edge values to convert a potentially complex path problem into a combinatorial counting problem over components.
By following this reasoning, you can transform the problem into a manageable one, use graph algorithms to find components, and dynamic programming or combinatorics to count valid sequences efficiently.
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