Geostatistics
=============
Directional statistics for single grid
--------------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grid`` [raster]
<put parameter description here>
``Points`` [vector: any]
Optional.
<put parameter description here>
``Direction [Degree]`` [number]
<put parameter description here>
Default: *0.0*
``Tolerance [Degree]`` [number]
<put parameter description here>
Default: *0.0*
``Maximum Distance [Cells]`` [number]
<put parameter description here>
Default: *0*
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *1*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *1.0*
Outputs
.......
``Arithmetic Mean`` [raster]
<put output description here>
``Difference from Arithmetic Mean`` [raster]
<put output description here>
``Minimum`` [raster]
<put output description here>
``Maximum`` [raster]
<put output description here>
``Range`` [raster]
<put output description here>
``Variance`` [raster]
<put output description here>
``Standard Deviation`` [raster]
<put output description here>
``Mean less Standard Deviation`` [raster]
<put output description here>
``Mean plus Standard Deviation`` [raster]
<put output description here>
``Deviation from Arithmetic Mean`` [raster]
<put output description here>
``Percentile`` [raster]
<put output description here>
``Directional Statistics for Points`` [vector]
<put output description here>
Console usage
.............
::
processing.runalg('saga:directionalstatisticsforsinglegrid', grid, points, direction, tolerance, maxdistance, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, mean, difmean, min, max, range, var, stddev, stddevlo, stddevhi, devmean, percent, points_out)
See also
........
Fast representativeness
-----------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Input`` [raster]
<put parameter description here>
``Level of Generalisation`` [number]
<put parameter description here>
Default: *16*
Outputs
.......
``Output`` [raster]
<put output description here>
``Output Lod`` [raster]
<put output description here>
``Output Seeds`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:fastrepresentativeness', input, lod, result, result_lod, seeds)
See also
........
Geographically weighted multiple regression (points/grids)
----------------------------------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Predictors`` [multipleinput: rasters]
<put parameter description here>
``Output of Regression Parameters`` [boolean]
<put parameter description here>
Default: *True*
``Points`` [vector: point]
<put parameter description here>
``Dependent Variable`` [tablefield: any]
<put parameter description here>
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *1*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *1.0*
``Search Range`` [selection]
<put parameter description here>
Options:
* 0 --- [0] search radius (local)
* 1 --- [1] no search radius (global)
Default: *0*
``Search Radius`` [number]
<put parameter description here>
Default: *100*
``Search Mode`` [selection]
<put parameter description here>
Options:
* 0 --- [0] all directions
* 1 --- [1] quadrants
Default: *0*
``Number of Points`` [selection]
<put parameter description here>
Options:
* 0 --- [0] maximum number of observations
* 1 --- [1] all points
Default: *0*
``Maximum Number of Observations`` [number]
<put parameter description here>
Default: *10*
``Minimum Number of Observations`` [number]
<put parameter description here>
Default: *4*
Outputs
.......
``Regression`` [raster]
<put output description here>
``Coefficient of Determination`` [raster]
<put output description here>
``Regression Parameters`` [raster]
<put output description here>
``Residuals`` [vector]
<put output description here>
Console usage
.............
::
processing.runalg('saga:geographicallyweightedmultipleregressionpointsgrids', predictors, parameters, points, dependent, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, range, radius, mode, npoints, maxpoints, minpoints, regression, quality, slopes, residuals)
See also
........
Geographically weighted multiple regression (points)
----------------------------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Points`` [vector: any]
<put parameter description here>
``Dependent Variable`` [tablefield: any]
<put parameter description here>
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *1*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *1.0*
``Search Range`` [selection]
<put parameter description here>
Options:
* 0 --- [0] search radius (local)
* 1 --- [1] no search radius (global)
Default: *0*
``Search Radius`` [number]
<put parameter description here>
Default: *100*
``Search Mode`` [selection]
<put parameter description here>
Options:
* 0 --- [0] all directions
* 1 --- [1] quadrants
Default: *0*
``Number of Points`` [selection]
<put parameter description here>
Options:
* 0 --- [0] maximum number of observations
* 1 --- [1] all points
Default: *0*
``Maximum Number of Observations`` [number]
<put parameter description here>
Default: *10*
``Minimum Number of Observations`` [number]
<put parameter description here>
Default: *4*
Outputs
.......
``Regression`` [vector]
<put output description here>
Console usage
.............
::
processing.runalg('saga:geographicallyweightedmultipleregressionpoints', points, dependent, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, range, radius, mode, npoints, maxpoints, minpoints, regression)
See also
........
Geographically weighted multiple regression
-------------------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Points`` [vector: point]
<put parameter description here>
``Dependent Variable`` [tablefield: any]
<put parameter description here>
``Target Grids`` [selection]
<put parameter description here>
Options:
* 0 --- [0] user defined
Default: *0*
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *1*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *1*
``Search Range`` [selection]
<put parameter description here>
Options:
* 0 --- [0] search radius (local)
* 1 --- [1] no search radius (global)
Default: *0*
``Search Radius`` [number]
<put parameter description here>
Default: *100*
``Search Mode`` [selection]
<put parameter description here>
Options:
* 0 --- [0] all directions
* 1 --- [1] quadrants
Default: *0*
``Number of Points`` [selection]
<put parameter description here>
Options:
* 0 --- [0] maximum number of observations
* 1 --- [1] all points
Default: *0*
``Maximum Number of Observations`` [number]
<put parameter description here>
Default: *10*
``Minimum Number of Observations`` [number]
<put parameter description here>
Default: *4*
``Output extent`` [extent]
<put parameter description here>
Default: *0,1,0,1*
``Cellsize`` [number]
<put parameter description here>
Default: *100.0*
Outputs
.......
``Quality`` [raster]
<put output description here>
``Intercept`` [raster]
<put output description here>
``Quality`` [raster]
<put output description here>
``Intercept`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:geographicallyweightedmultipleregression', points, dependent, target, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, range, radius, mode, npoints, maxpoints, minpoints, output_extent, user_size, user_quality, user_intercept, grid_quality, grid_intercept)
See also
........
Geographically weighted regression (points/grid)
------------------------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Predictor`` [raster]
<put parameter description here>
``Points`` [vector: point]
<put parameter description here>
``Dependent Variable`` [tablefield: any]
<put parameter description here>
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *1*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *1.0*
``Search Range`` [selection]
<put parameter description here>
Options:
* 0 --- [0] search radius (local)
* 1 --- [1] no search radius (global)
Default: *0*
``Search Radius`` [number]
<put parameter description here>
Default: *0*
``Search Mode`` [selection]
<put parameter description here>
Options:
* 0 --- [0] all directions
* 1 --- [1] quadrants
Default: *0*
``Number of Points`` [selection]
<put parameter description here>
Options:
* 0 --- [0] maximum number of observations
* 1 --- [1] all points
Default: *0*
``Maximum Number of Observations`` [number]
<put parameter description here>
Default: *10*
``Minimum Number of Observations`` [number]
<put parameter description here>
Default: *4*
Outputs
.......
``Regression`` [raster]
<put output description here>
``Coefficient of Determination`` [raster]
<put output description here>
``Intercept`` [raster]
<put output description here>
``Slope`` [raster]
<put output description here>
``Residuals`` [vector]
<put output description here>
Console usage
.............
::
processing.runalg('saga:geographicallyweightedregressionpointsgrid', predictor, points, dependent, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, range, radius, mode, npoints, maxpoints, minpoints, regression, quality, intercept, slope, residuals)
See also
........
Geographically weighted regression
----------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Points`` [vector: point]
<put parameter description here>
``Dependent Variable`` [tablefield: any]
<put parameter description here>
``Predictor`` [tablefield: any]
<put parameter description here>
``Target Grids`` [selection]
<put parameter description here>
Options:
* 0 --- [0] user defined
Default: *0*
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *0*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *0.0*
``Search Range`` [selection]
<put parameter description here>
Options:
* 0 --- [0] search radius (local)
* 1 --- [1] no search radius (global)
Default: *0*
``Search Radius`` [number]
<put parameter description here>
Default: *100*
``Search Mode`` [selection]
<put parameter description here>
Options:
* 0 --- [0] all directions
* 1 --- [1] quadrants
Default: *0*
``Number of Points`` [selection]
<put parameter description here>
Options:
* 0 --- [0] maximum number of observations
* 1 --- [1] all points
Default: *0*
``Maximum Number of Observations`` [number]
<put parameter description here>
Default: *10*
``Minimum Number of Observations`` [number]
<put parameter description here>
Default: *4*
``Output extent`` [extent]
<put parameter description here>
Default: *0,1,0,1*
``Cellsize`` [number]
<put parameter description here>
Default: *100.0*
Outputs
.......
``Grid`` [raster]
<put output description here>
``Quality`` [raster]
<put output description here>
``Intercept`` [raster]
<put output description here>
``Slope`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:geographicallyweightedregression', points, dependent, predictor, target, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, range, radius, mode, npoints, maxpoints, minpoints, output_extent, user_size, user_grid, user_quality, user_intercept, user_slope)
See also
........
Global moran's i for grids
--------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grid`` [raster]
<put parameter description here>
``Case of contiguity`` [selection]
<put parameter description here>
Options:
* 0 --- [0] Rook
* 1 --- [1] Queen
Default: *0*
Outputs
.......
``Result`` [table]
<put output description here>
Console usage
.............
::
processing.runalg('saga:globalmoransiforgrids', grid, contiguity, result)
See also
........
Minimum distance analysis
-------------------------
Description
...........
Performs a complete distance analysis of a point layer:
* minimum distance of points
* maximum distance of points
* average distance of all the points
* standard deviation of the distance
* duplicated points
Parameters
..........
``Points`` [vector: point]
Layer to analyze.
Outputs
.......
``Minimum Distance Analysis`` [table]
The resulting table.
Console usage
.............
::
processing.runalg('saga:minimumdistanceanalysis', points, table)
See also
........
Multi-band variation
--------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grids`` [multipleinput: rasters]
<put parameter description here>
``Radius [Cells]`` [number]
<put parameter description here>
Default: *1*
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *1*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *1.0*
Outputs
.......
``Mean Distance`` [raster]
<put output description here>
``Standard Deviation`` [raster]
<put output description here>
``Distance`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:multibandvariation', bands, radius, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, mean, stddev, diff)
See also
........
Multiple regression analysis (grid/grids)
-----------------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Dependent`` [raster]
<put parameter description here>
``Grids`` [multipleinput: rasters]
<put parameter description here>
``Grid Interpolation`` [selection]
<put parameter description here>
Options:
* 0 --- [0] Nearest Neighbor
* 1 --- [1] Bilinear Interpolation
* 2 --- [2] Inverse Distance Interpolation
* 3 --- [3] Bicubic Spline Interpolation
* 4 --- [4] B-Spline Interpolation
Default: *0*
``Include X Coordinate`` [boolean]
<put parameter description here>
Default: *True*
``Include Y Coordinate`` [boolean]
<put parameter description here>
Default: *True*
``Method`` [selection]
<put parameter description here>
Options:
* 0 --- [0] include all
* 1 --- [1] forward
* 2 --- [2] backward
* 3 --- [3] stepwise
Default: *0*
``P in`` [number]
<put parameter description here>
Default: *5*
``P out`` [number]
<put parameter description here>
Default: *5*
Outputs
.......
``Regression`` [raster]
<put output description here>
``Residuals`` [raster]
<put output description here>
``Details: Coefficients`` [table]
<put output description here>
``Details: Model`` [table]
<put output description here>
``Details: Steps`` [table]
<put output description here>
Console usage
.............
::
processing.runalg('saga:multipleregressionanalysisgridgrids', dependent, grids, interpol, coord_x, coord_y, method, p_in, p_out, regression, residuals, info_coeff, info_model, info_steps)
See also
........
Multiple regression analysis (points/grids)
-------------------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grids`` [multipleinput: rasters]
<put parameter description here>
``Shapes`` [vector: any]
<put parameter description here>
``Attribute`` [tablefield: any]
<put parameter description here>
``Grid Interpolation`` [selection]
<put parameter description here>
Options:
* 0 --- [0] Nearest Neighbor
* 1 --- [1] Bilinear Interpolation
* 2 --- [2] Inverse Distance Interpolation
* 3 --- [3] Bicubic Spline Interpolation
* 4 --- [4] B-Spline Interpolation
Default: *0*
``Include X Coordinate`` [boolean]
<put parameter description here>
Default: *True*
``Include Y Coordinate`` [boolean]
<put parameter description here>
Default: *True*
``Method`` [selection]
<put parameter description here>
Options:
* 0 --- [0] include all
* 1 --- [1] forward
* 2 --- [2] backward
* 3 --- [3] stepwise
Default: *0*
``P in`` [number]
<put parameter description here>
Default: *5*
``P out`` [number]
<put parameter description here>
Default: *5*
Outputs
.......
``Details: Coefficients`` [table]
<put output description here>
``Details: Model`` [table]
<put output description here>
``Details: Steps`` [table]
<put output description here>
``Residuals`` [vector]
<put output description here>
``Regression`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:multipleregressionanalysispointsgrids', grids, shapes, attribute, interpol, coord_x, coord_y, method, p_in, p_out, info_coeff, info_model, info_steps, residuals, regression)
See also
........
Polynomial regression
---------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Points`` [vector: any]
<put parameter description here>
``Attribute`` [tablefield: any]
<put parameter description here>
``Polynom`` [selection]
<put parameter description here>
Options:
* 0 --- [0] simple planar surface
* 1 --- [1] bi-linear saddle
* 2 --- [2] quadratic surface
* 3 --- [3] cubic surface
* 4 --- [4] user defined
Default: *0*
``Maximum X Order`` [number]
<put parameter description here>
Default: *4*
``Maximum Y Order`` [number]
<put parameter description here>
Default: *4*
``Maximum Total Order`` [number]
<put parameter description here>
Default: *4*
``Trend Surface`` [selection]
<put parameter description here>
Options:
* 0 --- [0] user defined
Default: *0*
``Output extent`` [extent]
<put parameter description here>
Default: *0,1,0,1*
``Cellsize`` [number]
<put parameter description here>
Default: *100.0*
Outputs
.......
``Residuals`` [vector]
<put output description here>
``Grid`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:polynomialregression', points, attribute, polynom, xorder, yorder, torder, target, output_extent, user_size, residuals, user_grid)
See also
........
Radius of variance (grid)
-------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grid`` [raster]
<put parameter description here>
``Standard Deviation`` [number]
<put parameter description here>
Default: *1.0*
``Maximum Search Radius (cells)`` [number]
<put parameter description here>
Default: *20*
``Type of Output`` [selection]
<put parameter description here>
Options:
* 0 --- [0] Cells
* 1 --- [1] Map Units
Default: *0*
Outputs
.......
``Variance Radius`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:radiusofvariancegrid', input, variance, radius, output, result)
See also
........
Regression analysis
-------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grid`` [raster]
<put parameter description here>
``Shapes`` [vector: any]
<put parameter description here>
``Attribute`` [tablefield: any]
<put parameter description here>
``Grid Interpolation`` [selection]
<put parameter description here>
Options:
* 0 --- [0] Nearest Neighbor
* 1 --- [1] Bilinear Interpolation
* 2 --- [2] Inverse Distance Interpolation
* 3 --- [3] Bicubic Spline Interpolation
* 4 --- [4] B-Spline Interpolation
Default: *0*
``Regression Function`` [selection]
<put parameter description here>
Options:
* 0 --- [0] Y = a + b * X (linear)
* 1 --- [1] Y = a + b / X
* 2 --- [2] Y = a / (b - X)
* 3 --- [3] Y = a * X^b (power)
* 4 --- [4] Y = a e^(b * X) (exponential)
* 5 --- [5] Y = a + b * ln(X) (logarithmic)
Default: *0*
Outputs
.......
``Regression`` [raster]
<put output description here>
``Residuals`` [vector]
<put output description here>
Console usage
.............
::
processing.runalg('saga:regressionanalysis', grid, shapes, attribute, interpol, method, regression, residual)
See also
........
Representativeness
------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grid`` [raster]
<put parameter description here>
``Radius (Cells)`` [number]
<put parameter description here>
Default: *10*
``Exponent`` [number]
<put parameter description here>
Default: *1*
Outputs
.......
``Representativeness`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:representativeness', input, radius, exponent, result)
See also
........
Residual analysis
-----------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grid`` [raster]
<put parameter description here>
``Radius (Cells)`` [number]
<put parameter description here>
Default: *7*
``Distance Weighting`` [selection]
<put parameter description here>
Options:
* 0 --- [0] no distance weighting
* 1 --- [1] inverse distance to a power
* 2 --- [2] exponential
* 3 --- [3] gaussian weighting
Default: *0*
``Inverse Distance Weighting Power`` [number]
<put parameter description here>
Default: *1*
``Inverse Distance Offset`` [boolean]
<put parameter description here>
Default: *True*
``Gaussian and Exponential Weighting Bandwidth`` [number]
<put parameter description here>
Default: *1.0*
Outputs
.......
``Mean Value`` [raster]
<put output description here>
``Difference from Mean Value`` [raster]
<put output description here>
``Standard Deviation`` [raster]
<put output description here>
``Value Range`` [raster]
<put output description here>
``Minimum Value`` [raster]
<put output description here>
``Maximum Value`` [raster]
<put output description here>
``Deviation from Mean Value`` [raster]
<put output description here>
``Percentile`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:residualanalysis', grid, radius, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, mean, diff, stddev, range, min, max, devmean, percent)
See also
........
Spatial point pattern analysis
------------------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Points`` [vector: point]
<put parameter description here>
``Vertex Distance [Degree]`` [number]
<put parameter description here>
Default: *5*
Outputs
.......
``Mean Centre`` [vector]
<put output description here>
``Standard Distance`` [vector]
<put output description here>
``Bounding Box`` [vector]
<put output description here>
Console usage
.............
::
processing.runalg('saga:spatialpointpatternanalysis', points, step, centre, stddist, bbox)
See also
........
Statistics for grids
--------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Grids`` [multipleinput: rasters]
<put parameter description here>
Outputs
.......
``Arithmetic Mean`` [raster]
<put output description here>
``Minimum`` [raster]
<put output description here>
``Maximum`` [raster]
<put output description here>
``Variance`` [raster]
<put output description here>
``Standard Deviation`` [raster]
<put output description here>
``Mean less Standard Deviation`` [raster]
<put output description here>
``Mean plus Standard Deviation`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:statisticsforgrids', grids, mean, min, max, var, stddev, stddevlo, stddevhi)
See also
........
Variogram cloud
---------------
Description
...........
<put algorithm description here>
Parameters
..........
``Points`` [vector: point]
<put parameter description here>
``Attribute`` [tablefield: any]
<put parameter description here>
``Maximum Distance`` [number]
<put parameter description here>
Default: *0.0*
``Skip Number`` [number]
<put parameter description here>
Default: *1*
Outputs
.......
``Variogram Cloud`` [table]
<put output description here>
Console usage
.............
::
processing.runalg('saga:variogramcloud', points, field, distmax, nskip, result)
See also
........
Variogram surface
-----------------
Description
...........
<put algorithm description here>
Parameters
..........
``Points`` [vector: point]
<put parameter description here>
``Attribute`` [tablefield: any]
<put parameter description here>
``Number of Distance Classes`` [number]
<put parameter description here>
Default: *10*
``Skip Number`` [number]
<put parameter description here>
Default: *1*
Outputs
.......
``Number of Pairs`` [raster]
<put output description here>
``Variogram Surface`` [raster]
<put output description here>
``Covariance Surface`` [raster]
<put output description here>
Console usage
.............
::
processing.runalg('saga:variogramsurface', points, field, distcount, nskip, count, variance, covariance)
See also
........
Zonal grid statistics
---------------------
Description
...........
<put algorithm description here>
Parameters
..........
``Zone Grid`` [raster]
<put parameter description here>
``Categorial Grids`` [multipleinput: rasters]
Optional.
<put parameter description here>
``Grids to analyse`` [multipleinput: rasters]
Optional.
<put parameter description here>
``Aspect`` [raster]
Optional.
<put parameter description here>
``Short Field Names`` [boolean]
<put parameter description here>
Default: *True*
Outputs
.......
``Zonal Statistics`` [table]
<put output description here>
Console usage
.............
::
processing.runalg('saga:zonalgridstatistics', zones, catlist, statlist, aspect, shortnames, outtab)
See also
........