seismic-waveform-processing

# Seismic Waveform Processing ## Usage ### 1. MCP Server Definition ```python import asyncio import json from mcp.client.streamable_http import streamablehttp_client from mcp import ClientSession class SeismicClient: """SeisOBS-Tool MCP Client""" def __init__(self, server_url: str, api_key: str): self.server_url = server_url self.api_key = api_key self.session = None async def connect(self): """Establish connection and initialize session""" try: self.transport = streamablehttp_client( url=self.server_url, headers={"SCP-HUB-API-KEY": self.api_key} ) self.read, self.write, self.get_session_id = await self.transport.__aenter__() self.session_ctx = ClientSession(self.read, self.write) self.session = await self.session_ctx.__aenter__() await self.session.initialize() return True except Exception as e: print(f"✗ connect failure: {e}") return False async def disconnect(self): """Disconnect from server""" try: if self.session: await self.session_ctx.__aexit__(None, None, None) if hasattr(self, 'transport'): await self.transport.__aexit__(None, None, None) except Exception as e: print(f"✗ disconnect error: {e}") def parse_result(self, result): """Parse MCP tool call result""" try: if hasattr(result, 'content') and result.content: content = result.content[0] if hasattr(content, 'text'): return json.loads(content.text) return str(result) except Exception as e: return {"error": f"parse error: {e}", "raw": str(result)} ``` ### 2. Seismic Waveform Processing Workflow This workflow processes seismic waveform data from MinISEED or SAC files. **Workflow Steps:** 1. **Read Waveform Data** - Load seismic data from file 2. **Extract Metadata** - Retrieve station and instrument information 3. **Visualize Waveform** - Generate time-series plot **Implementation:** ```python ## Initialize client client = SeismicClient( "https://scp.intern-ai.org.cn/api/v1/mcp/33/SeisOBS-Tool", "<your-api-key>" ) if not await client.connect(): print("connection failed") exit() ## Input: Path to seismic data file (URL or local path) data_path = "https://example.com/seismic_data.mseed" channel_idx = 0 # Channel index to process ## Step 1: Read waveform data result = await client.session.call_tool( "read_mseed_file", arguments={ "data_path": data_path, "channel_idx": channel_idx } ) waveform_data = client.parse_result(result) print(f"Waveform data shape: {len(waveform_data['st'])} samples") ## Step 2: Extract metadata result = await client.session.call_tool( "read_mseed_file_stats", arguments={ "data_path": data_path, "channel_idx": channel_idx, "outfile": None } ) metadata = client.parse_result(result) print(f"Station: {metadata.get('station', 'N/A')}") print(f"Sampling rate: {metadata.get('sampling_rate', 'N/A')} Hz") ## Step 3: Visualize waveform result = await client.session.call_tool( "plot_single_waveform", arguments={ "data_path": data_path, "channel_idx": channel_idx, "outfile": None, "starttime": None, "endtime": None } ) plot_result = client.parse_result(result) print(f"Waveform plot saved to: {plot_result['st']}") await client.disconnect() ``` ### Tool Descriptions **SeisOBS-Tool Server:** - `read_mseed_file`: Read waveform data from MinISEED file - Args: - `data_path` (str): Path or URL to MinISEED file - `channel_idx` (int): Channel index to read - Returns: Waveform time series data - `read_mseed_file_stats`: Extract metadata from MinISEED file - Args: - `data_path` (str): Path or URL to MinISEED file - `channel_idx` (int): Channel index - `outfile` (str, optional): Output file path - Returns: Station metadata and instrument information - `plot_single_waveform`: Generate waveform plot - Args: - `data_path` (str): Path or URL to MinISEED file - `channel_idx` (int): Channel index - `outfile` (str, optional): Output image path - `starttime` (str, optional): Plot start time - `endtime` (str, optional): Plot end time - Returns: Path to generated plot image ### Input/Output **Input:** - `data_path`: Path or URL to seismic data file (MinISEED or SAC format) - `channel_idx`: Index of the channel to process (0-based) - `starttime`/`endtime`: Optional time window for plotting **Output:** - Waveform data array - Metadata including station, sampling rate, start time - Visualization image (PNG format) ### Use Cases - Earthquake signal analysis - Seismic station quality control - Waveform data preprocessing - P-wave and S-wave identification - Ground motion visualization ### Performance Notes - **File formats**: MinISEED (.mseed), SAC (.sac) - **Execution time**: <5 seconds for typical earthquake recordings - **Data size**: Handles files up to 100 MB efficiently