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lib/node_modules/@stdlib/blas/gdot/README.md

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@@ -83,7 +83,7 @@ var z = gdot( [], [] );
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## Notes
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- `gdot()` corresponds to the [BLAS][blas] level 1 function [`ddot`][ddot] with the exception that this implementation works with any array type, not just Float64Arrays.
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- For best performance, provide 1-dimensional [`ndarrays`][@stdlib/ndarray/array] whose underlying data type is either `float64` or `float32`.
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- In general, for best performance, especially for large vectors, provide 1-dimensional [`ndarrays`][@stdlib/ndarray/array] whose underlying data type is either `float64` or `float32`.
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</section>
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lib/node_modules/@stdlib/blas/gdot/docs/repl.txt

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{{alias}}( x, y )
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Computes the dot product of two vectors.
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For best performance, provide 1-dimensional ndarrays whose underlying data
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type is either 'float64' or 'float32'.
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In general, for best performance, especially for large vectors, provide
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1-dimensional ndarrays whose underlying data type is either 'float64' or
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'float32'.
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If provided empty vectors, the function returns `0.0`.
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lib/node_modules/@stdlib/blas/gdot/docs/types/index.d.ts

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*
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* ## Notes
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*
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* - For best performance, provide 1-dimensional `ndarrays` whose underlying data type is either `float64` or `float32`.
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* - In general, for best performance, especially for large vectors, provide 1-dimensional `ndarrays` whose underlying data type is either `float64` or `float32`.
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*
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* @param x - first input array
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* @param y - second input array

lib/node_modules/@stdlib/blas/gdot/lib/main.js

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*
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* ## Notes
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*
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* - For best performance, provide 1-dimensional `ndarrays` whose underlying data type is either `float64` or `float32`.
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* - In general, for best performance, especially for large vectors, provide 1-dimensional `ndarrays` whose underlying data type is either `float64` or `float32`.
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*
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* @param {(ArrayLike|VectorLike)} x - first input array
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* @param {(ArrayLike|VectorLike)} y - second input array

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