[1.0.0] Interpolation

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评估

难度
5/5
预计耗时
一周以上
新手友好度
30/100
Issue 类型
重构
描述清晰度
需要澄清
活跃度
冷清
技术栈
python
领域
data, testing

调研方向

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.

由索引模型根据 Issue 内容生成。

描述

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
主要语言
Python
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