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Experimental Data Processing

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'Experimental Data Processing - Process experimental data: absolute error,

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  • Added September 11, 2026
datapythonapi

Works with

  • cli
  • api
  • mcp

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A100/100

Scanned September 11, 2026

npx -y skills add InternScience/DrClaw --skill experimental_data_processing --agent claude-code

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SKILL.md
---
name: experimental_data_processing
description: 'Experimental Data Processing - Process experimental data: absolute error,
  mean square, max value, scientific notation formatting. Use this skill for experimental
  physics tasks involving calculate absolute error calculate mean square calculate
  max value format scientific notation convert to scientific notation. Combines 5
  tools from 1 SCP server(s).'
i18n:
  zh:
    description: 实验数据处理:绝对误差、均方、。
---

# Experimental Data Processing

**Discipline**: Experimental Physics | **Tools Used**: 5 | **Servers**: 1

## Description

Process experimental data: absolute error, mean square, max value, scientific notation formatting.

## Tools Used

- **`calculate_absolute_error`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`calculate_mean_square`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`calculate_max_value`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`format_scientific_notation`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`convert_to_scientific_notation`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`

## Workflow

1. Calculate absolute errors
2. Compute mean square
3. Find maximum
4. Format in scientific notation
5. Summarize results

## Test Case

### Input
```json
{
    "measurements": [
        9.78,
        9.81,
        9.83,
        9.79,
        9.8
    ],
    "true_value": 9.81
}
```

### Expected Steps
1. Calculate absolute errors
2. Compute mean square
3. Find maximum
4. Format in scientific notation
5. Summarize results

## Usage Example

> **Note:** Replace `<YOUR_SCP_HUB_API_KEY>` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn).

```python
import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "server-26": "https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis"
}

async def connect(url, transport_type):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})
    read, write, _ = await transport.__aenter__()
    ctx = ClientSession(read, write)
    session = await ctx.__aenter__()
    await session.initialize()
    return session, ctx, transport

def parse(result):
    try:
        if hasattr(result, 'content') and result.content:
            c = result.content[0]
            if hasattr(c, 'text'):
                try: return json.loads(c.text)
                except: return c.text
        return str(result)
    except: return str(result)

async def main():
    # Connect to required servers
    sessions = {}
    sessions["server-26"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis", "streamable-http")

    # Execute workflow steps
    # Step 1: Calculate absolute errors
    result_1 = await sessions["server-26"].call_tool("calculate_absolute_error", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

    # Step 2: Compute mean square
    result_2 = await sessions["server-26"].call_tool("calculate_mean_square", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

    # Step 3: Find maximum
    result_3 = await sessions["server-26"].call_tool("calculate_max_value", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

    # Step 4: Format in scientific notation
    result_4 = await sessions["server-26"].call_tool("format_scientific_notation", arguments={})
    data_4 = parse(result_4)
    print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")

    # Step 5: Summarize results
    result_5 = await sessions["server-26"].call_tool("convert_to_scientific_notation", arguments={})
    data_5 = parse(result_5)
    print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")

    # Cleanup
    print("Workflow complete!")

if __name__ == "__main__":
    asyncio.run(main())
```

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