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A float block read from a .npy file, with the shape it was stored under.

public readonly record struct NpyBlock(ReadOnlyMemory<float> Values, IReadOnlyList<int> Shape)
{
    public float[]? OwnedArray { get; init; }
}

Parameters — Values are the elements in C order, so a matrix reads row by row. Shape has one entry for a vector and two for a matrix. OwnedArray is the array the block owns, or null when it borrows one — set by the reader, never by the caller.

Example — the shape is the file's, not a guess.

using Lodestar.Embeddings.Persistence;

using var buffer = new MemoryStream();
NpyFile.Write(buffer, [1f, 2f, 3f, 4f, 5f, 6f], 2, 3);
buffer.Position = 0;

NpyBlock block = NpyFile.Read(buffer);
string shape = string.Join("x", block.Shape);   // => 2x3
bool adoptable = block.OwnedArray is not null;  // => True

Remarks — Values is ReadOnlyMemory<float> rather than an array because the block is the file's content and not the caller's buffer to grow. .Span reads it without copying; .ToArray() takes a copy when one is wanted.

Shape is what the file declared and what the read was bounded against — the element count is checked before it sizes anything, which is the rule every loader here follows.

OwnedArray is filled by the stream reader and by nobody else. Reading from a Stream or a path allocates an array nothing else holds, and that array is what EmbeddingIndex.FromOwnedBlock may adopt instead of copying the block again — the transfer docs/guides/performance.md puts on the caller. Reading from a ReadOnlyMemory<byte> leaves it null, because those values are borrowed and there is no array to give; so does a block you construct yourself, which is what stops adoption being reached without the method that documents it. docs/guides/performance.md has why the two reads differ.

Applies to — net10.0, netstandard2.0.

See also — NpyFile, NpyFile.Read, the persistence index.