[1.0.0] Interpolation

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#2,947 opened on Jun 4, 2026 0 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty: 5/5
Estimated time: Over a week
Newbie friendliness: 30/100

Issue type: Refactor
Clarity: Needs clarification
Activity status: Quiet
Tech stack: python
Domain: data, testing

Research direction

Start with the README feature matrix and the code under xrspatial/interpolate/. Review the dark-corner decisions in #2930, then run /deep-sweep xrspatial/interpolate and inspect the linked kriging and idw issues. Done means no CRITICAL or HIGH findings remain, required coverage and examples are added, and the checklist is cleared.

Written by the indexing model from the issue text.

Description

1.0.0-tracking area:stats

1.0.0 readiness: Interpolation

Area: Stats Functions: idw, kriging, spline
Source: xrspatial/interpolate/

Scope

Public surface frozen against the README feature matrix
Dark-corner decisions resolved (see #2930)

Sweep clearance, no CRITICAL or HIGH (accuracy and security first)

Accuracy /deep-sweep xrspatial/interpolate
Security
Performance
API consistency

Last swept: none yet

Examples

Notebook example
(optional) standalone script

Linked bug issues

#2915 (High) kriging(): nugget lands on the kriging-matrix diagonal (should be gamma(0)=0)
#2916 (Low) Style: fix flake8 E128 and isort drift in interpolate/_kriging.py
#2917 (Low) kriging() raises an opaque numpy error for a single input point
#2919 (Medium) idw(): GPU backends (cupy, dask+cupy) have no test coverage
#2920 (Medium) kriging() crashes on single-point input with "zero-size array to reduction maximum"
#2921 (Medium) Test coverage gaps in interpolate/_kriging.py (backend, params, edge cases)
#2923 (High) kriging() memory guard raises spurious MemoryError on dask-backed templates

Dominant language: Python
Stars: 972
Forks: 92
Avg merge: 2d 12h
Merged PRs (30d): 7

Contributor guide

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First steps

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