> For the complete documentation index, see [llms.txt](https://nataliekung.gitbook.io/ladder_code/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://nataliekung.gitbook.io/ladder_code/twitter-oa/paint-house.md).

# Paint House

There are a row of `n` houses, each house can be painted with one of the three colors: red, blue or green. The cost of painting each house with a certain color is different. You have to paint all the houses such that **no two adjacent houses have the same color,** and you need to cost the least. Return the minimum cost.

The cost of painting each house with a certain color is represented by a `n` x `3` cost matrix. For example, `costs[0][0]` is the cost of painting house `0` with color red; `costs[1][2]` is the cost of painting house `1` with color green, and so on... Find the minimum cost to paint all houses.

#### Example

**Example 1:**

```
Input: [[14,2,11],[11,14,5],[14,3,10]]
Output: 10
Explanation: Paint house 0 into blue, paint house 1 into green, paint house 2 into blue. Minimum cost: 2 + 5 + 3 = 10.
```

**Example 2:**

```
Input: [[1,2,3],[1,4,6]]
Output: 3
```

#### Notice

All costs are positive integers.

分析

从前一栋房子里另外几个颜色选最小

```
class Solution:
    """
    @param costs: n x 3 cost matrix
    @return: An integer, the minimum cost to paint all houses
    """
    def minCost(self, costs):
        # write your code here
        if not costs:
            return  0 
        n = len(costs)
        
        for i in range(1,n):
            costs[i][0] = costs[i][0] + min(costs[i-1][1],costs[i-1][2])
            costs[i][1] = costs[i][1] + min(costs[i-1][0],costs[i-1][2])
            costs[i][2] = costs[i][2] + min(costs[i-1][0],costs[i-1][1])
            
        return min(costs[n-1])

```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://nataliekung.gitbook.io/ladder_code/twitter-oa/paint-house.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.