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Metatensor
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  • Metatensor’s goals
  • Installation
  • Core classes
    • Overview
    • Python API reference
      • TensorMap
      • TensorBlock
      • Labels
      • Serialization
      • Data arrays
      • Miscellaneous
    • C++ API reference
      • TensorMap
      • Labels
      • TensorBlock
      • Data arrays
      • Miscellaneous
    • C API reference
      • TensorMap
      • Labels
      • TensorBlock
      • Data arrays
      • Miscellaneous
    • Rust API reference
    • Tutorials
      • First steps with metatensor
      • Handling sparsity
      • Managing gradients
    • Changelog
  • Operations
    • Operations and PyTorch
    • API reference
      • Creation operations
        • empty_like()
        • ones_like()
        • zeros_like()
        • random_like()
        • block_from_array()
      • Linear algebra
        • dot()
        • lstsq()
        • solve()
      • Logic function
        • allclose()
        • equal()
        • equal_metadata()
        • is_contiguous()
      • Manipulation operations
        • detach()
        • drop_blocks()
        • filter_blocks()
        • join()
        • make_contiguous()
        • manipulate dimension
        • one_hot()
        • remove_gradients()
        • requires_grad()
        • samples reduction
        • slice()
        • split()
      • Mathematical functions
        • abs()
        • add()
        • divide()
        • multiply()
        • pow()
        • subtract()
      • Set operations
        • unique_metadata()
        • sort()
      • Checks
    • Changelog
  • TorchScript backend
    • API reference
      • TensorMap
      • TensorBlock
      • Labels
      • Serialization
      • TorchScript C++ API reference
        • TensorMap
        • TensorBlock
        • Labels
        • Miscellaneous
    • Changelog
  • Learning utilities
    • API reference
      • Data utilites
      • Neural Network
    • Tutorials
      • Datasets and data loaders
      • Using IndexedDataset
    • Changelog
  • Atomistic applications
    • Overview
    • API reference
      • Systems
      • Models
        • Exporting models
        • Information about models
      • Atomic Simulation Environment (ASE) integration
      • Serialization
      • C++ API reference
        • Systems
        • Models
    • Standard model outputs
      • Energy
      • Features
    • Simulation engines
      • ASE
      • Chemiscope
      • i-PI
      • LAMMPS
      • PLUMED
    • Tutorials
      • Exporting a model
      • Running Molecular Dynamics with ASE
      • Creating models that use neighbor lists
      • Profiling your models
  • Developer documentation
    • Getting started
    • Code organization
    • Version number management
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Chemiscope¶

Official website

How is metatensor supported?

https://chemiscope.org

In the original version

Supported model outputs¶

The features output is supported, and can be used to compute features for multiple structures in chemiscope.explore().

How to install the code¶

The code can be installed with the following command:

pip install chemiscope[metatensor]

How to use the code¶

See the example from https://chemiscope.org/docs/examples/8-explore-with-metatensor.html.

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  • Chemiscope
    • Supported model outputs
    • How to install the code
    • How to use the code