APbase

APbase is an intelligent mapping pipeline for irregular field data, such as yield monitor, soil samples, and sensor grids. Its intelligence comes from the way it handles the workflow automatically: it filters the source data, handles geographic coordinates when needed, builds the target grid, compares interpolation methods, and chooses the one with the lowest validation error. The result is a ready-to-use map without requiring users to choose a mathematical model by hand.

import apbase

result = apbase.Map(resolution=10.0)(x, y, z)

result.method                  # "idw" or "kriging", picked by validation error
result.x, result.y, result.z   # compact map points inside the boundary

Contents

• Installation
• Quickstart
• Production and cloud deployment
• User Guide
• Methodology
• index

What the pipeline handles

• One mapping pipeline. The high-level interface handles filtering, boundary and grid generation, variogram fitting, validation, model selection, and final interpolation in one workflow.
• Automatic model selection. The pipeline compares IDW with ordinary kriging and uses the method with the lower RMSE for the current dataset.
• Efficient numerical work. A fitted variogram is reused for radius selection, cross-validation, and final kriging, avoiding repeated work.
• Ready for services and batch jobs. The pipeline accepts field data and returns compact map results without requiring a web framework, database, desktop GIS, or notebook runtime.
• Works with irregular, noisy points. Invalid rows, global outliers, and local spatial outliers are removed before interpolation runs.
• Useful defaults. When no search radius is provided, IDW and kriging use the range estimated by the fitted variogram.

See Quickstart for a full worked example and Production and cloud deployment for deployment guidance. Use User Guide and Methodology when you need advanced control or want to audit the mathematics behind the automatic choice.