Inverse Distance Weighting interpolation algorithm.
Each cell receives the weighted average of the whole data set with weights being 1/r² (r being the distance of the current cell to the contributing station) and renormalized (so that the sum of the weights is equal to 1.0). It takes the following arguments:
- SCALE: this is a scaling parameter to smooth the IDW distribution. In effect, this is added to the distance in order to move into the tail of the 1/d distribution (default: 1000m);
- ALPHA: this is an exponent to the 1/d distribution (default: 1);
- Note
- If IDW is applied on wind speed (VW, VW_MAX or VW_DRIFT) or wind direction (DW), the algorithm internally applies the interpolation on the wind speed components individually, if both wind speed and direction are available at the same station.
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| IDWAlgorithm (const std::vector< std::pair< std::string, std::string > > &vecArgs, const std::string &i_algo, const std::string &i_param, TimeSeriesManager &i_tsm) |
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virtual double | getQualityRating (const Date &i_date) |
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virtual void | calculate (const DEMObject &dem, Grid2DObject &grid) |
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| InterpolationAlgorithm (const std::vector< std::pair< std::string, std::string > > &, const std::string &i_algo, const std::string &i_param, TimeSeriesManager &i_tsm) |
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virtual | ~InterpolationAlgorithm () |
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virtual double | getQualityRating (const Date &i_date)=0 |
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virtual void | calculate (const DEMObject &dem, Grid2DObject &grid)=0 |
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std::string | getInfo () const |
| Return an information string about the interpolation process. More...
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