<put algortithm description here>
Points
[vector: point]Attribute
[tablefield: any]Create Variance Grid
[boolean]<put parameter description here>
Default: True
Target Grid
[selection]<put parameter description here>
Options:
Default: 0
Variogram Model
[selection]<put parameter description here>
Options:
Default: 0
Block Kriging
[boolean]<put parameter description here>
Default: True
Block Size
[number]<put parameter description here>
Default: 100
Logarithmic Transformation
[boolean]<put parameter description here>
Default: True
Nugget
[number]<put parameter description here>
Default: 0.0
Sill
[number]<put parameter description here>
Default: 10.0
Range
[number]<put parameter description here>
Default: 100.0
Linear Regression
[number]<put parameter description here>
Default: 1.0
Exponential Regression
[number]<put parameter description here>
Default: 0.1
Power Function - A
[number]<put parameter description here>
Default: 1
Power Function - B
[number]<put parameter description here>
Default: 0.5
Maximum Search Radius (map units)
[number]<put parameter description here>
Default: 1000.0
Min.Number of m_Points
[number]<put parameter description here>
Default: 4
Max. Number of m_Points
[number]<put parameter description here>
Default: 20
Grid Size
[number]<put parameter description here>
Default: 1.0
Fit Extent
[boolean]<put parameter description here>
Default: True
Output extent
[extent]<put parameter description here>
Default: 0,1,0,1
Grid
[raster]Variance
[raster]processing.runalg('saga:ordinarykriging', shapes, field, bvariance, target, model, block, dblock, blog, nugget, sill, range, lin_b, exp_b, pow_a, pow_b, maxradius, npoints_min, npoints_max, user_cell_size, user_fit_extent, output_extent, grid, variance)