STEAD subsample 4 CDiffSD

# STEAD Subsample Dataset for CDiffSD Training

## Overview
This dataset is a subsampled version of the STEAD dataset, specifically tailored for training our CDiffSD model (Cold Diffusion for Seismic Denoising). It consists of four CSV files, each saved in a format that requires Python's `pd.read_pickle` method for opening.

## Dataset Files
The dataset includes the following files:

• df_train: Used for both training and validation phases (with validation train split). Contains earthquake ground truth traces.
• df_noise_train: Used for both training and validation phases. Contains noise used to contaminate the traces.
• df_test: Used for the testing phase, structured similarly to df_train.
• df_noise_test: Used for the testing phase, contains noise data for testing.

Each file is structured to support the training and evaluation of seismic denoising models.

## Data Columns
The dataset files contain columns from the original STEAD dataset, with specific focus on the following columns that are critical for our use:

• E_channel: East-West channel data
• N_channel: North-South channel data
• Z_channel: Vertical channel data
• s_arrival_sample: Sample index for S-wave arrival
• p_arrival_sample: Sample index for P-wave arrival
• trace_name: Identifier for the seismic trace

## Usage
To load these files in a Python environment, use the following approach:

```python
import pandas as pd

# Example of loading the training data
df_train = pd.read_pickle('path/to/df_train.csv')
```

Ensure that the path to the file is correctly specified relative to your Python script.

## Requirements
To use this dataset, ensure you have Python installed along with the Pandas library, which can be installed via pip if not already available:

```bash
pip install pandas
```