Inverse Distance Weighting interpolation with splitted N/E/S/W slopes and flats.
This is designed around the data produced by the Snowpack model: each station produces virtual slopes (38°) for each of the main 4 aspects. This algorithm interpolates each N/E/S/W group of stations separately (IDW with elevation lapse rate) and then recombines them with weights that depend on the cell's slope and aspect. 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);
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| const std::string | algo |
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| std::vector< double > | getData (const Date &i_date, const std::string &i_param) |
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| size_t | getData (const Date &i_date, const std::string &i_param, std::vector< double > &o_vecData, std::vector< StationData > &o_vecMeta) |
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| TimeSeriesManager & | tsmanager |
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| Date | date |
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| std::vector< MeteoData > | vecMeteo |
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| std::vector< double > | vecData |
| | store the measurement for the given parameter
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| std::vector< StationData > | vecMeta |
| | store the station data for the given parameter
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| std::ostringstream | info |
| | to store some extra information about the interplation process
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| const std::string | param |
| | the parameter that we will interpolate
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| size_t | nrOfMeasurments |
| | Number of stations that have been used, so this can be reported to the user.
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