Compute Euclidean distances between two input vectors.
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#include <distances.hpp>
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| template<typename Output_ , typename DataX_ , typename DataY_ , typename Dim_ > |
| static Output_ | raw_distance (const DataX_ *x, const DataY_ *y, Dim_ num_dimensions) |
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| template<typename Output_ > |
| static Output_ | normalize (Output_ raw) |
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| template<typename Output_ > |
| static Output_ | denormalize (Output_ norm) |
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Compute Euclidean distances between two input vectors.
◆ denormalize()
template<typename Output_ >
| static Output_ knncolle::EuclideanDistance::denormalize |
( |
Output_ |
norm | ) |
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inlinestatic |
- Template Parameters
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| Output_ | Floating point type for the output distance. |
- Parameters
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- Returns
- Squared Euclidean distance.
◆ normalize()
template<typename Output_ >
| static Output_ knncolle::EuclideanDistance::normalize |
( |
Output_ |
raw | ) |
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inlinestatic |
- Template Parameters
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| Output_ | Floating point type for the output distance. |
- Parameters
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| raw | Squared Euclidean distance. |
- Returns
- Euclidean distance.
◆ raw_distance()
template<typename Output_ , typename DataX_ , typename DataY_ , typename Dim_ >
| static Output_ knncolle::EuclideanDistance::raw_distance |
( |
const DataX_ * |
x, |
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const DataY_ * |
y, |
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Dim_ |
num_dimensions |
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) |
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|
inlinestatic |
- Parameters
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| x | Pointer to the array containing the first vector. |
| y | Pointer to the array containing the second vector. |
| num_dimensions | Length of both vectors. |
- Template Parameters
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| Output_ | Floating point type for the output distance. |
| DataX_ | Floating point type for the first data vector. |
| DataY_ | Floating point type for the second data vector. |
| Dim_ | Integer type for the vector length. |
- Returns
- The squared Euclidean distance between
x and y.
The documentation for this struct was generated from the following file:
