Examples Gallery

This section provides complete, working examples that demonstrate geo-sampling capabilities. All examples include real data outputs that you can download and examine.

🚀 Getting Started

🐍 Python API Examples

Complete Python workflows with actual Delhi road data. Includes 1,220 road segments and 1,000-sample outputs.

Features: Basic extraction, sampling, visualization Data: Delhi, India road network Output: Sample plots and CSV files

Python API Examples

💻 Command Line Usage

Master the geo-sampling CLI with working examples and real command outputs.

Features: All CLI commands with examples Data: Multiple regions and countries Output: Command logs and sample files

Command Line Interface (CLI) Examples

🎯 Advanced Sampling

Sophisticated sampling strategies with Singapore road network examples.

Features: Random, stratified, filtered sampling Data: Singapore Central region (470 segments) Output: Comparison plots and multiple samples

Advanced Sampling Strategies

📁 Download Outputs

All example outputs are available for download. Browse CSV files, plots, and sample data.

Includes: Sample datasets, visualizations, CLI logs Format: CSV, PNG, TXT files Size: Ready-to-use examples

Download Examples

📊 Live Data Examples

All examples use real OpenStreetMap data and generate actual outputs that are included with the package:

Delhi Basic Workflow

• Input: NCT of Delhi administrative boundary

• Output: 1,220 total road segments → 1,000 random sample

• Files: delhi_all_roads.csv, delhi_sampled_roads.csv

Singapore Advanced Sampling

• Input: Singapore Central region

• Output: Multiple sampling strategies (random, stratified, filtered)

• Files: singapore_*.csv with comparison plots

CLI Command Examples

• Input: Various countries and regions

• Output: Command logs and sample outputs

• Files: commands_log.txt

🔍 Code + Data Philosophy

Each example provides:

1. 🔧 Working code - Copy-paste ready scripts

2. 📈 Real outputs - Actual CSV files and plots you can examine

3. ⚡ Both interfaces - Python API and CLI equivalents

4. 📋 Documentation - Step-by-step explanations

Quick Navigation

By Interface:

• Python API Examples - For programmatic usage

• CLI Examples - For command-line workflows

By Complexity:

• Basic Workflow - Start here

• Advanced Sampling - Multiple strategies

• Custom Integration - Research workflows

💡 Tips for Using Examples

Running Examples Locally

# Clone the repository to get example files
git clone https://github.com/geosensing/geo-sampling.git
cd geo-sampling

# Install with example dependencies
pip install -e .

# Run the basic workflow example
python examples/01_basic_workflow.py

# Try CLI examples
python examples/03_cli_usage.py

Adapting for Your Research

1. Change the region: Replace country/region names with your study area

2. Adjust sample size: Modify sample_size parameters for your needs

3. Filter road types: Use road_types parameter to focus on specific infrastructure

4. Set random seed: Use seed parameter for reproducible research

Understanding Output Files

• *_all_roads.csv: Complete road network for the region

• *_sample.csv: Random/stratified sample of road segments

• *_plot.png: Visualization of sampled road segments

• Metadata: Each example includes sampling methodology details

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Ready to dive in? Start with Python API Examples or jump to CLI Usage!