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APbase

Version License: Apache 2.0 Python Kernel: Fortran Parallel: OpenMP CI

APbase Python

APbase is an intelligent mapping pipeline for irregular field data, including yield monitor, soil samples, and sensor grids. It automates the map workflow: filtering source data, handling geographic coordinates when needed, building the target grid, comparing interpolation methods, and selecting a ready-to-use map without requiring users to choose a mathematical model by hand.

Full documentation: https://apbase.io

Install

pip install apbase

Development version:

pip install git+https://github.com/ap-base/apbase-python.git

Quick Use

import numpy as np

import apbase
from apbase import Map

apbase.config["n_threads"] = 4

x = np.ascontiguousarray(x_metric, dtype=np.float64)
y = np.ascontiguousarray(y_metric, dtype=np.float64)
z = np.ascontiguousarray(values, dtype=np.float64)

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

result.method                # "idw" or "kriging"
result.x, result.y, result.z # compact output points

X, Y, Z = result.to_raster() # dense raster, NaN outside the boundary

Functional shortcut:

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

Main API

  • apbase.Map: automated map pipeline.
  • apbase.create_map: one-shot map creation.
  • apbase.config: runtime configuration, including OpenMP thread count.

Advanced modules are available under apbase.filtering, apbase.grid, apbase.variogram, apbase.idw, apbase.kriging, apbase.cokriging, and apbase.cross_validate.

Data Requirements

  • x, y, and z must be one-dimensional arrays.
  • Projected metric coordinates, such as UTM, are used directly.
  • Geographic lon/lat input is converted internally before distance operations; distance settings such as resolution are meters.
  • For best performance, use contiguous float64 arrays.

Performance

  • Native Fortran kernels exposed through F2PY/NumPy.
  • OpenMP parallelism for critical numerical work.
  • Local neighborhoods and neighbor limits instead of full distance matrices.
  • Compact output by default; dense rasters are materialized only with result.to_raster().

Set threads before creating maps:

import apbase

apbase.config["n_threads"] = 4

License

Apache License 2.0. See LICENSE.

Metadata

Release files for apbase 0.1.3

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apbase-0.1.3-cp314-cp314-win_amd64.whl CPython 3.14 CPython 3.14 Windows x86-64 Details
apbase-0.1.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.14 CPython 3.14 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
apbase-0.1.3-cp314-cp314-macosx_15_0_x86_64.whl CPython 3.14 CPython 3.14 macOS 15.0+ x86-64 Details
apbase-0.1.3-cp314-cp314-macosx_14_0_arm64.whl CPython 3.14 CPython 3.14 macOS 14.0+ ARM64 Details
apbase-0.1.3-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
apbase-0.1.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
apbase-0.1.3-cp313-cp313-macosx_15_0_x86_64.whl CPython 3.13 CPython 3.13 macOS 15.0+ x86-64 Details
apbase-0.1.3-cp313-cp313-macosx_14_0_arm64.whl CPython 3.13 CPython 3.13 macOS 14.0+ ARM64 Details
apbase-0.1.3-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
apbase-0.1.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
apbase-0.1.3-cp312-cp312-macosx_15_0_x86_64.whl CPython 3.12 CPython 3.12 macOS 15.0+ x86-64 Details
apbase-0.1.3-cp312-cp312-macosx_14_0_arm64.whl CPython 3.12 CPython 3.12 macOS 14.0+ ARM64 Details

Total release size: 153.6 MB

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