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Fix typo and move down dependencies table
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README.md

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@@ -24,19 +24,6 @@ The Python bindings for `xtensor` are based on the [pybind11](https://github.com
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conda install -c conda-forge xtensor-python
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```
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### Dependences on `xtensor` and `pybind11`
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`xtensor-python` depends on the `xtensor` and `pybind11` libraries
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| `xtensor-python` | `xtensor` | `pybind11` |
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|-------------------|------------|-------------|
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| master | ^0.9.0 | ^2.1.0 |
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| 0.10.x | ^0.9.0 | ^2.1.0 |
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| 0.9.x | ^0.8.1 | ^2.1.0 |
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| 0.8.x | ^0.8.1 | ^2.1.0 |
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These dependencies are automatically resolved when using the conda package manager.
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## Usage
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xtensor-python offers two container types wrapping numpy arrays inplace to provide an xtensor semantics
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- On the other hand ``pytensor`` has a compile time number of dimensions, specified with a template parameter. Shapes of ``pytensor`` instances are stack allocated, making ``pytensor`` a significantly
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faster expression than ``pyarray``.
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### Example 1: Use an algorithm of the C++ library on a numpy array inplace.
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### Example 1: Use an algorithm of the C++ standard library on a numpy array inplace.
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**C++ code**
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#include "xtensor/xmath.hpp" // xtensor import for the C++ universal functions
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#include "xtensor-python/pyarray.hpp" // Numpy bindings
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double sum_of_sines(xt::pyarray<double> &m)
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double sum_of_sines(xt::pyarray<double>& m)
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{
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auto sines = xt::sin(m); // sines does not actually hold any value, which are only computed upon access
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return std::accumulate(sines.begin(), sines.end(), 0.0);
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from the `docs` subdirectory.
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## Dependencies on `xtensor` and `pybind11`
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`xtensor-python` depends on the `xtensor` and `pybind11` libraries
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| `xtensor-python` | `xtensor` | `pybind11` |
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|-------------------|------------|-------------|
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| master | ^0.9.0 | ^2.1.0 |
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| 0.10.x | ^0.9.0 | ^2.1.0 |
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| 0.9.x | ^0.8.1 | ^2.1.0 |
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| 0.8.x | ^0.8.1 | ^2.1.0 |
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These dependencies are automatically resolved when using the conda package manager.
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## License
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We use a shared copyright model that enables all contributors to maintain the

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