Module functions 

Auto-generated module

🤖 Generated with SplitRS

Functions

arange

Generate values from start to stop (exclusive) with step step.

detect_npy_dtype

Auto-detect dtype from header and return the NpyDtype.

flat_index

Compute the flat index from multi-dimensional indices (row-major).

linspace

Generate n equally-spaced values from start to stop (inclusive).

logspace

Generate n log-spaced values from 10^start to 10^stop.

matmul

Compute the matrix product C = A * B where A is (m×k) and B is (k×n), both stored as flat row-major f64 slices.

read_npy_f32

Parse a .npy byte buffer and return (shape, f32 data).

read_npy_f64

Parse a .npy byte buffer and return (shape, f64 data).

read_npy_i32

Parse a .npy byte buffer and return (shape, i32 data).

read_npy_i64

Parse a .npy byte buffer and return (shape, i64 data).

read_npy_shape

Auto-detect and return the shape from a .npy byte buffer.

slice_add

Element-wise sum of two equal-length slices.

slice_clip

Clip values to \[lo, hi\].

slice_dot

Dot product of two equal-length slices.

slice_mean

Compute the arithmetic mean of a slice.

slice_min_max

Compute min, max, and their flat indices.

slice_mul

Element-wise product of two equal-length slices.

slice_percentile

Compute the p-th percentile of a slice using linear interpolation.

slice_std

Compute the standard deviation (population, ddof=0).

slice_var

Compute the variance of a slice (population variance, ddof=0).

transpose_2d

Transpose a 2-D row-major matrix stored as a flat Vecf64`.

unravel_index

Compute multi-dimensional indices from a flat index (row-major).

validate_shape

Validate that a shape and data length are consistent.

write_npy_f32

Assemble a complete .npy v1.0 byte sequence for an f32 array.

write_npy_f64

Assemble a complete .npy v1.0 byte sequence for a f64 array.

write_npy_i32

Assemble a complete .npy v1.0 byte sequence for an i32 array.

write_npy_i64

Assemble a complete .npy v1.0 byte sequence for an i64 array.