Changelog¶

All notable changes to metatensor-core are documented here, following the keep a changelog format. This project follows Semantic Versioning.

Unreleased ¶

metatensor-core C++¶

metatensor-core C¶

metatensor-core Python¶

metatensor-core Julia¶

Added¶

the Julia bindings to metatensor-core in the Metatensor.jl package

Version 0.1.6 - 2024-05-03¶

metatensor-core C++¶

Fixed¶

fixed compilation with Rust 1.78 (#605)
fixed compilation on some Windows systems (#575)

Version 0.1.5 - 2024-04-09¶

metatensor-core C++¶

Fixed¶

fixed compilation with cmake 3.29.1 (#573)

metatensor-core Python¶

Changed¶

allow positional arguments in TensorMap.to/TensorBlock.to (#556)

Version 0.1.4 - 2024-03-01¶

Fixed¶

fixed compilation on macOS (#525)
added checks for the size of the new values in Labels.insert (#519)

Version 0.1.3 - 2024-02-12¶

Fixed¶

Fixed the build with Cargo 1.65 (#505)
Pin dependencies for metatensor-core, ensuring reproducibility of the build as new dependencies versions are published (#506)

Version 0.1.2 - 2024-01-26¶

metatensor-core C++¶

Added¶

Offer serialization functionality as free standing functions (i.e. metatensor::io::load) in addition to the existing associated functions (i.e. TensorMap::load) (#453)
Serialization of labels with Labels::save, Labels::load, Labels::save_buffer, Labels::load_buffer and the corresponding free functions. (#455)

Changed¶

TensorMap::save_string_buffer has been replaced with the template version of TensorMap::save_buffer

metatensor-core C¶

Added¶

mts_labels_save, mts_labels_load, mts_labels_save_buffer, and mts_labels_load_buffer to handle serialization of mts_labels_t

metatensor-core Python¶

Added¶

TensorMap.to and TensorBlock.to to change the device, dtype, or backend (numpy or torch) of all arrays stored by metatensor
Labels.device, TensorBlock.device and TensorMap.device; as well as TensorMap.dtype, and TensorBlock.dtype to query the current device and dtype used by the data.
Offer serialization functionality as member functions (i.e. TensorMap.load) in addition to the existing free standing functions (i.e. metatensor.load) (#453)
Serialization of labels with Labels.save, Labels.load, Labels.save_buffer, Labels.load_buffer and the corresponding free functions.

Version 0.1.1 - 2024-01-05¶

Fixed¶

Fixed the build with Cargo 1.75 (#438)
Allowed saving and loading empty TensorMap; i.e. TensorMap where one of the dimensions of the array has 0 elements (#419)

Version 0.1.0 - 2023-10-11¶

metatensor-core C¶

Added¶

Initial implementation of all the core classes of metatensor: mts_labels_t, mts_block_t, mts_tensormap_t, mts_array_t and the corresponding functions;
Serialization for mts_tensormap_t using a format derived from numpy’s npz format

metatensor-core C++¶

Added¶

C++ API for all the C data structures as C++ classes: Labels, TensorBlock, TensorMap;
Wrapper around mts_array_t as an abstract base class DataArrayBase;
Basic implementations of DataArrayBase in SimpleDataArray and EmptyDataArray;
Basic n-dimensional array class NDArray<T>, intended to give a minimal API to use data stored in TensorBlock even if this data does not come from C++ initially;

metatensor-core Python¶

Added¶

Python API for all the C data structures as Python classes: Labels, LabelsEntry, TensorBlock, TensorMap;
Wrapper around mts_array_t as an abstract base class metatensor.data.Array;
Implementation of metatensor.data.Array with numpy.ndarray and torch.Tensor;