Equistore was renamed to metatensor

.github/workflows/build-wheels.yml

@@ -67,7 +67,7 @@ jobs:
           CIBW_BUILD_VERBOSITY: 2
           CIBW_MANYLINUX_X86_64_IMAGE: rustc-manylinux2014_x86_64
           CIBW_REPAIR_WHEEL_COMMAND_MACOS: "delocate-wheel --ignore-missing-dependencies --require-archs {delocate_archs} -w {dest_dir} -v {wheel}"
-          CIBW_REPAIR_WHEEL_COMMAND_LINUX: "auditwheel repair --exclude libequistore.so -w {dest_dir} {wheel}"
+          CIBW_REPAIR_WHEEL_COMMAND_LINUX: "auditwheel repair --exclude libmetatensor.so -w {dest_dir} {wheel}"
 
       - uses: actions/upload-artifact@v3
         with:

docs/requirements.txt

@@ -10,7 +10,7 @@ myst-parser     # markdown => rst translation, used in extensions/rascaline_json
 
 # dependencies for the tutorials
 --extra-index-url https://download.pytorch.org/whl/cpu
-equistore[torch] @ https://github.com/lab-cosmo/equistore/archive/ee5ab99.zip
+metatensor[torch] @ https://github.com/lab-cosmo/metatensor/archive/32ad5bb.zip
 torch
 chemfiles
 matplotlib

docs/src/conf.py

@@ -12,7 +12,7 @@
 sys.path.append(os.path.join(ROOT, "docs", "extensions"))
 
 os.environ["RASCALINE_IMPORT_FOR_SPHINX"] = "1"
-os.environ["EQUISTORE_IMPORT_FOR_SPHINX"] = "1"
+os.environ["METATENSOR_IMPORT_FOR_SPHINX"] = "1"
 
 # -- Project information -----------------------------------------------------
 
@@ -45,7 +45,7 @@ def build_cargo_docs():
             "--package",
             "rascaline",
             "--package",
-            "equistore",
+            "metatensor",
             "--no-deps",
         ],
         env=environment,
@@ -137,7 +137,7 @@ def setup(app):
 intersphinx_mapping = {
     "ase": ("https://wiki.fysik.dtu.dk/ase/", None),
     "chemfiles": ("https://chemfiles.org/chemfiles.py/latest/", None),
-    "equistore": ("https://lab-cosmo.github.io/equistore/latest/", None),
+    "metatensor": ("https://lab-cosmo.github.io/metatensor/latest/", None),
     "matplotlib": ("https://matplotlib.org/stable/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
     "skmatter": ("https://scikit-matter.readthedocs.io/en/latest/", None),

docs/src/devdoc/how-to/new-calculator.rst

@@ -55,12 +55,12 @@ system, already implemented or not.
 In this tutorial, our goal is to write a new struct implementing
 `CalculatorBase`_. This implementation will take as input a slice of boxed
 `System`_ trait objects, and using data from those fill up a `TensorMap`_
-(defined in the equistore crate).
+(defined in the metatensor crate).
 
 .. _System: ../reference/rust/rascaline/systems/trait.System.html
 .. _CalculatorBase: ../reference/rust/rascaline/calculators/trait.CalculatorBase.html
 .. _Calculator: ../reference/rust/rascaline/struct.Calculator.html
-.. _TensorMap: ../reference/rust/equistore/tensor/struct.TensorMap.html
+.. _TensorMap: ../reference/rust/metatensor/tensor/struct.TensorMap.html
 
 Implementation
 --------------
@@ -181,8 +181,8 @@ center species and one neighbor species. This key builder requires a ``cutoff``
 (to determine which neighbors it should use) and ``self_pairs`` indicated
 whether atoms should be considered to be their own neighbor or not.
 
-.. _Labels: ../reference/rust/equistore/labels/struct.Labels.html
-.. _LabelsBuilder: ../reference/rust/equistore/labels/struct.LabelsBuilder.html
+.. _Labels: ../reference/rust/metatensor/labels/struct.Labels.html
+.. _LabelsBuilder: ../reference/rust/metatensor/labels/struct.LabelsBuilder.html
 
 .. literalinclude:: ../../../../rascaline/src/tutorials/moments/s2_metadata.rs
    :language: rust
@@ -378,7 +378,7 @@ requested, then we can skip the calculation for this pair. We also use
    :dedent: 4
 
 
-.. _Labels::position: ../reference/rust/equistore/labels/struct.Labels.html#method.position
+.. _Labels::position: ../reference/rust/metatensor/labels/struct.Labels.html#method.position
 
 Now, we can check if the samples are present, and if they are, iterate over the
 requested features, compute the moments for the current pair distance, and

docs/src/explanations/concepts.rst

@@ -65,9 +65,9 @@ Descriptors: data storage for atomistic machine learning
 
 After using a calculator on one or multiple systems, users will get the
 numerical representation of their atomic systems in a ``descriptor`` object.
-Rascaline uses `equistore`_ ``TensorMap`` type when returning descriptors.
+Rascaline uses `metatensor`_ ``TensorMap`` type when returning descriptors.
 
-.. _equistore: https://lab-cosmo.github.io/equistore/latest/
+.. _metatensor: https://lab-cosmo.github.io/metatensor/latest/
 
 A ``TensorMap`` can be seen as a dictionary mapping some keys to a set of data
 blocks. Each block contains both data (and gradients) arrays — i.e.
@@ -80,4 +80,4 @@ representations will have keys for the different equivariance classes
 (``spherical_harmonics_l`` for SO(3) equivariants, *etc.*).
 
 For more information on ``TensorMap`` and what can be done with one, please see
-the `equistore`_ documentation.
+the `metatensor`_ documentation.

docs/src/get-started/installation.rst

@@ -57,8 +57,8 @@ The build and installation can be configures with a few cmake options, using
 | RASCALINE_ENABLE_CHEMFILES           | Enable the usage of chemfiles for reading     | ON             |
 |                                      | structures from files                         |                |
 +--------------------------------------+-----------------------------------------------+----------------+
-| RASCALINE_FETCH_EQUISTORE            | Automatically fetch, build and install        | OFF            |
-|                                      | equistore (a dependency of rascaline)         |                |
+| RASCALINE_FETCH_METATENSOR           | Automatically fetch, build and install        | OFF            |
+|                                      | metatensor (a dependency of rascaline)        |                |
 +--------------------------------------+-----------------------------------------------+----------------+
 
 Using the Rust library
@@ -125,28 +125,28 @@ dependencies:
     python -c "import torch; print(torch.utils.cmake_prefix_path)"
 
 - :ref:`the C++ interface of rascaline <install-c-lib>`, which itself requires
-  the `C++ interface of equistore`_;
-- the `TorchScript interface of equistore`_. We can download and build an
+  the `C++ interface of metatensor`_;
+- the `TorchScript interface of metatensor`_. We can download and build an
   appropriate version of it automatically by setting the cmake option
-  ``-DRASCALINE_TORCH_FETCH_EQUISTORE_TORCH=ON``
+  ``-DRASCALINE_TORCH_FETCH_METATENSOR_TORCH=ON``
 
 If any of these dependencies is not in a standard location, you should specify
 the installation directory when configuring cmake with ``CMAKE_PREFIX_PATH``.
 Other useful configuration options are:
 
-+---------------------------------------+-----------------------------------------------+----------------+
-| Option                                | Description                                   | Default        |
-+=======================================+===============================================+================+
-| CMAKE_BUILD_TYPE                      | Type of build: debug or release               | release        |
-+---------------------------------------+-----------------------------------------------+----------------+
-| CMAKE_INSTALL_PREFIX                  | Prefix in which the library will be installed | ``/usr/local`` |
-+---------------------------------------+-----------------------------------------------+----------------+
-| CMAKE_PREFIX_PATH                     | ``;``-separated list of path where CMake will |                |
-|                                       | search for dependencies.                      |                |
-+---------------------------------------+-----------------------------------------------+----------------+
-| RASCALINE_TORCH_FETCH_EQUISTORE_TORCH | Should CMake automatically download and       | OFF            |
-|                                       | install equistore-torch?                      |                |
-+---------------------------------------+-----------------------------------------------+----------------+
-
-.. _C++ interface of equistore: https://lab-cosmo.github.io/equistore/latest/get-started/installation.html#installing-the-c-and-c-library
-.. _TorchScript interface of equistore: https://lab-cosmo.github.io/equistore/latest/get-started/installation.html#for-usage-from-c
++----------------------------------------+-----------------------------------------------+----------------+
+| Option                                 | Description                                   | Default        |
++========================================+===============================================+================+
+| CMAKE_BUILD_TYPE                       | Type of build: debug or release               | release        |
++----------------------------------------+-----------------------------------------------+----------------+
+| CMAKE_INSTALL_PREFIX                   | Prefix in which the library will be installed | ``/usr/local`` |
++----------------------------------------+-----------------------------------------------+----------------+
+| CMAKE_PREFIX_PATH                      | ``;``-separated list of path where CMake will |                |
+|                                        | search for dependencies.                      |                |
++----------------------------------------+-----------------------------------------------+----------------+
+| RASCALINE_TORCH_FETCH_METATENSOR_TORCH | Should CMake automatically download and       | OFF            |
+|                                        | install metatensor-torch?                     |                |
++----------------------------------------+-----------------------------------------------+----------------+
+
+.. _C++ interface of metatensor: https://lab-cosmo.github.io/metatensor/latest/get-started/installation.html#installing-the-c-and-c-library
+.. _TorchScript interface of metatensor: https://lab-cosmo.github.io/metatensor/latest/get-started/installation.html#for-usage-from-c

docs/src/get-started/rascaline.rst

@@ -10,7 +10,7 @@ There exist several libraries able to compute such structural representations,
 such as `DScribe`_, `QUIP`_, and many more. Rascaline tries to distinguish
 itself by focussing on speed and memory efficiency of the calculations, with the
 explicit goal of running molecular simulations with ML potentials. In
-particular, memory efficiency is achieved by using the `equistore`_ to store the
+particular, memory efficiency is achieved by using the `metatensor`_ to store the
 structural representation. Additionally, rascaline is not limited to a single
 representation but supports several:
 
@@ -21,4 +21,4 @@ representation but supports several:
 
 .. _DScribe: https://singroup.github.io/dscribe/
 .. _QUIP: https://www.libatoms.org
-.. _equistore: https://lab-cosmo.github.io/equistore/
+.. _metatensor: https://lab-cosmo.github.io/metatensor/

pyproject.toml

@@ -26,7 +26,7 @@ classifiers = [
 ]
 
 dependencies = [
-    "equistore-core @ https://github.com/lab-cosmo/equistore/archive/ee5ab99.zip#subdirectory=python/equistore-core",
+    "metatensor-core @ https://github.com/lab-cosmo/metatensor/archive/32ad5bb.zip#subdirectory=python/metatensor-core",
 ]
 
 [project.urls]

python/rascaline-torch/build-backend/backend.py

@@ -13,7 +13,7 @@
     # we are building from a git checkout
 
     # add a random uuid to the file url to prevent pip from using a cached
-    # wheel for equistore-core, and force it to re-build from scratch
+    # wheel for metatensor-core, and force it to re-build from scratch
     uuid = uuid.uuid4()
     RASCALINE_DEP = f"rascaline @ file://{RASCALINE}?{uuid}"
 else:

python/rascaline-torch/pyproject.toml

@@ -38,7 +38,7 @@ requires = [
     "wheel >=0.38",
     "cmake",
     "torch >= 1.11",
-    "equistore-torch @ https://github.com/lab-cosmo/equistore/archive/ee5ab99.zip#subdirectory=python/equistore-torch",
+    "metatensor-torch @ https://github.com/lab-cosmo/metatensor/archive/32ad5bb.zip#subdirectory=python/metatensor-torch",
 ]
 
 # use a custom build backend to add a dependency on the right version of rascaline

python/rascaline-torch/rascaline/torch/_c_lib.py

@@ -3,7 +3,7 @@
 import sys
 from collections import namedtuple
 
-import equistore.torch
+import metatensor.torch
 import torch
 
 import rascaline
@@ -107,9 +107,9 @@ def _check_dll(path):
 
 
 def _load_library():
-    # Load rascaline & equistore-torch shared library in the process first, to ensure
+    # Load rascaline & metatensor-torch shared library in the process first, to ensure
     # the rascaline_torch shared library can find them
-    equistore.torch._c_lib._load_library()
+    metatensor.torch._c_lib._load_library()
 
     rascaline._c_lib._get_library()
 

python/rascaline-torch/rascaline/torch/calculator_base.py

@@ -1,6 +1,6 @@
 from typing import List, Optional, Union
 
-import equistore.torch
+import metatensor.torch
 import torch
 
 from .system import System
@@ -11,13 +11,13 @@
 
 def register_autograd(
     systems: Union[List[System], System],
-    precomputed: equistore.torch.TensorMap,
+    precomputed: metatensor.torch.TensorMap,
     forward_gradients: Optional[List[str]] = None,
-) -> equistore.torch.TensorMap:
+) -> metatensor.torch.TensorMap:
     """
     Register autograd nodes between ``system.positions`` and ``system.cell`` for each of
     the systems and the values in the ``precomputed``
-    :py:class:`equistore.torch.TensorMap`.
+    :py:class:`metatensor.torch.TensorMap`.
 
     This is an advanced function must users should not need to use.
 
@@ -27,7 +27,7 @@ def register_autograd(
     system's cell ``requires_grad``, ``precomputed`` must contain ``"cell"`` gradients.
 
     :param systems: list of system used to compute ``precomputed``
-    :param precomputed: precomputed :py:class:`equistore.torch.TensorMap`
+    :param precomputed: precomputed :py:class:`metatensor.torch.TensorMap`
     :param forward_gradients: which gradients to keep in the output, defaults to None
     """
     if forward_gradients is None:
@@ -87,7 +87,7 @@ def compute(
         systems: Union[System, List[System]],
         gradients: Optional[List[str]] = None,
         use_native_system: bool = True,
-    ) -> equistore.torch.TensorMap:
+    ) -> metatensor.torch.TensorMap:
         """Runs a calculation with this calculator on the given ``systems``.
 
         .. seealso::
@@ -127,7 +127,7 @@ def forward(
         systems: List[System],
         gradients: Optional[List[str]] = None,
         use_native_system: bool = True,
-    ) -> equistore.torch.TensorMap:
+    ) -> metatensor.torch.TensorMap:
         """forward just calls :py:meth:`CalculatorModule.compute`"""
 
         return self.compute(

python/rascaline-torch/rascaline/torch/utils.py

@@ -1,6 +1,6 @@
 import os
 
-import equistore.torch
+import metatensor.torch
 
 import rascaline
 
@@ -13,7 +13,7 @@
     [
         _rascaline_torch_cmake_prefix,
         rascaline.utils.cmake_prefix_path,
-        equistore.torch.utils.cmake_prefix_path,
+        metatensor.torch.utils.cmake_prefix_path,
     ]
 )
 """

python/rascaline-torch/rascaline/torch/utils/power_spectrum.py

@@ -3,7 +3,7 @@
 from typing import List, Optional, Union
 
 import torch
-from equistore.torch import Labels, TensorBlock, TensorMap
+from metatensor.torch import Labels, TensorBlock, TensorMap
 
 import rascaline.utils.power_spectrum
 
@@ -20,7 +20,7 @@
 )
 module = importlib.util.module_from_spec(spec)
 # This module only exposes a handful of things, defined here. Any changes here MUST also
-# be made to the `equistore/operations/_classes.py` file, which is used in non
+# be made to the `metatensor/operations/_classes.py` file, which is used in non
 # TorchScript mode.
 module.__dict__["Labels"] = Labels
 module.__dict__["TensorBlock"] = TensorBlock

python/rascaline-torch/setup.py

@@ -15,7 +15,7 @@
 
 RASCALINE_TORCH = os.path.join(ROOT, "..", "..", "rascaline-torch")
 if not os.path.exists(RASCALINE_TORCH):
-    # we are building from a sdist, which should include equistore-torch
+    # we are building from a sdist, which should include metatensor-torch
     # sources as a tarball
     cxx_sources = os.path.join(ROOT, "rascaline-torch.tar.gz")
 
@@ -38,7 +38,7 @@ class cmake_ext(build_ext):
     """Build the native library using cmake"""
 
     def run(self):
-        import equistore.torch
+        import metatensor.torch
         import torch
 
         import rascaline
@@ -52,7 +52,7 @@ def run(self):
         # Tell CMake where to find rascaline & torch
         cmake_prefix_path = [
             rascaline.utils.cmake_prefix_path,
-            equistore.torch.utils.cmake_prefix_path,
+            metatensor.torch.utils.cmake_prefix_path,
             torch.utils.cmake_prefix_path,
         ]
 
@@ -140,7 +140,7 @@ def run(self):
         sys.exit(
             "Aborting implicit building of eggs. "
             + "Use `pip install .` or `python setup.py bdist_wheel && pip "
-            + "install dist/equistore-*.whl` to install from source."
+            + "install dist/metatensor-*.whl` to install from source."
         )
 
 

python/rascaline/examples/compute-soap.py

@@ -50,7 +50,7 @@
 
 # %%
 #
-# The descriptor is an equistore ``TensorMap``, containing multiple blocks. We
+# The descriptor is a metatensor ``TensorMap``, containing multiple blocks. We
 # can transform it to a single block containing a dense representation, with one
 # sample for each atom-centered environment by using ``keys_to_samples`` and
 # ``keys_to_properties``