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 0.1.4 - 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;