[rasterio] numpy arrays in transform.xy, a crs of None, and read(masked=True)

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@omkhpb25 já está trabalhando nisso.

Desde 21/10/2026.

Avaliação

Dificuldade
2/5
Tempo estimado
1-3 horas
Facilidade para iniciantes
45/100
Tipo de issue
Bug
Clareza
Claramente especificada
Status de atividade
Ativa
Stack de tecnologia
numpy, python
Domínio
tooling

Direção de pesquisa

The three problems are in the rasterio stubs bundled in typeshed: rasterio.transform.xy (the rows/cols parameters and return type), DatasetBase.crs, and DatasetReaderBase.read (the return type when masked=True). Reproduce each case with the snippets in the issue, then compare against the current stub signatures. Done means the stubs accept numpy arrays, allow crs to be None, and return a masked array type when masked=True, with the repository's stub tests passing. The issue asks for maintainer approval before a pull request, so confirm that first.

Escrita pelo modelo de indexação a partir do texto da issue.

Descrição

Researched and drafted by Claude (Anthropic's AI model, in Claude Code), which also ran the measurements below; reviewed by @bjlittle before posting.

Type checking geovista against types-rasterio 1.5.2.20261005 turned up three places where the rasterio stubs are narrower than rasterio 1.5.2 at runtime.

  1. rasterio.transform.xy types rows and cols as int | Sequence[int], and its result as tuple[float, float] | tuple[list[float], list[float]]. rasterio takes numpy arrays, and gives arrays back for them:

    import numpy as np
    from rasterio.transform import from_origin, xy
    
    transform = from_origin(10.0, 20.0, 1.0, 1.0)
    rows, cols = np.meshgrid(np.arange(2), np.arange(3), indexing="ij")
    xs, ys = xy(transform, rows.flatten(), cols.flatten())
    type(xs)  # <class 'numpy.ndarray'>
    

    An ndarray is not a Sequence, so a caller passing one needs a cast.

  2. DatasetBase.crs is typed CRS, but a GeoTIFF without a CRS gives None.

  3. DatasetReaderBase.read is typed to return NDArray[Any] whatever masked is, but with masked=True it returns a numpy.ma.MaskedArray, so using its mask doesn't type check.

If any of these would be welcome as a pull request, Claude can prepare one the same way, for @bjlittle to review before it is opened.

🤖 Generated with Claude Code

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