` `
<put algorithm description here>
Grid
[raster]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:
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
Arithmetic Mean
[raster]Difference from Arithmetic Mean
[raster]Minimum
[raster]Maximum
[raster]Range
[raster]Variance
[raster]Standard Deviation
[raster]Mean less Standard Deviation
[raster]Mean plus Standard Deviation
[raster]Deviation from Arithmetic Mean
[raster]Percentile
[raster]Directional Statistics for Points
[vector]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)
<put algorithm description here>
Input
[raster]Level of Generalisation
[number]<put parameter description here>
Default: 16
Output
[raster]Output Lod
[raster]Output Seeds
[raster]processing.runalg('saga:fastrepresentativeness', input, lod, result, result_lod, seeds)
<put algorithm description here>
Predictors
[multipleinput: rasters]Output of Regression Parameters
[boolean]<put parameter description here>
Default: True
Points
[vector: point]Dependent Variable
[tablefield: any]Distance Weighting
[selection]<put parameter description here>
Options:
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:
Default: 0
Search Radius
[number]<put parameter description here>
Default: 100
Search Mode
[selection]<put parameter description here>
Options:
Default: 0
Number of Points
[selection]<put parameter description here>
Options:
Default: 0
Maximum Number of Observations
[number]<put parameter description here>
Default: 10
Minimum Number of Observations
[number]<put parameter description here>
Default: 4
Regression
[raster]Coefficient of Determination
[raster]Regression Parameters
[raster]Residuals
[vector]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)
<put algorithm description here>
Points
[vector: any]Dependent Variable
[tablefield: any]Distance Weighting
[selection]<put parameter description here>
Options:
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:
Default: 0
Search Radius
[number]<put parameter description here>
Default: 100
Search Mode
[selection]<put parameter description here>
Options:
Default: 0
Number of Points
[selection]<put parameter description here>
Options:
Default: 0
Maximum Number of Observations
[number]<put parameter description here>
Default: 10
Minimum Number of Observations
[number]<put parameter description here>
Default: 4
Regression
[vector]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)
<put algorithm description here>
Points
[vector: point]Dependent Variable
[tablefield: any]Target Grids
[selection]<put parameter description here>
Options:
Default: 0
Distance Weighting
[selection]<put parameter description here>
Options:
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:
Default: 0
Search Radius
[number]<put parameter description here>
Default: 100
Search Mode
[selection]<put parameter description here>
Options:
Default: 0
Number of Points
[selection]<put parameter description here>
Options:
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
Quality
[raster]Intercept
[raster]Quality
[raster]Intercept
[raster]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)
<put algorithm description here>
Predictor
[raster]Points
[vector: point]Dependent Variable
[tablefield: any]Distance Weighting
[selection]<put parameter description here>
Options:
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:
Default: 0
Search Radius
[number]<put parameter description here>
Default: 0
Search Mode
[selection]<put parameter description here>
Options:
Default: 0
Number of Points
[selection]<put parameter description here>
Options:
Default: 0
Maximum Number of Observations
[number]<put parameter description here>
Default: 10
Minimum Number of Observations
[number]<put parameter description here>
Default: 4
Regression
[raster]Coefficient of Determination
[raster]Intercept
[raster]Slope
[raster]Residuals
[vector]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)
<put algorithm description here>
Points
[vector: point]Dependent Variable
[tablefield: any]Predictor
[tablefield: any]Target Grids
[selection]<put parameter description here>
Options:
Default: 0
Distance Weighting
[selection]<put parameter description here>
Options:
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:
Default: 0
Search Radius
[number]<put parameter description here>
Default: 100
Search Mode
[selection]<put parameter description here>
Options:
Default: 0
Number of Points
[selection]<put parameter description here>
Options:
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
Grid
[raster]Quality
[raster]Intercept
[raster]Slope
[raster]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)
<put algorithm description here>
Grid
[raster]Case of contiguity
[selection]<put parameter description here>
Options:
Default: 0
Result
[table]processing.runalg('saga:globalmoransiforgrids', grid, contiguity, result)
Performs a complete distance analysis of a point layer:
Points
[vector: point]Minimum Distance Analysis
[table]processing.runalg('saga:minimumdistanceanalysis', points, table)
<put algorithm description here>
Grids
[multipleinput: rasters]Radius [Cells]
[number]<put parameter description here>
Default: 1
Distance Weighting
[selection]<put parameter description here>
Options:
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
Mean Distance
[raster]Standard Deviation
[raster]Distance
[raster]processing.runalg('saga:multibandvariation', bands, radius, distance_weighting_weighting, distance_weighting_idw_power, distance_weighting_idw_offset, distance_weighting_bandwidth, mean, stddev, diff)
<put algorithm description here>
Dependent
[raster]Grids
[multipleinput: rasters]Grid Interpolation
[selection]<put parameter description here>
Options:
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:
Default: 0
P in
[number]<put parameter description here>
Default: 5
P out
[number]<put parameter description here>
Default: 5
Regression
[raster]Residuals
[raster]Details: Coefficients
[table]Details: Model
[table]Details: Steps
[table]processing.runalg('saga:multipleregressionanalysisgridgrids', dependent, grids, interpol, coord_x, coord_y, method, p_in, p_out, regression, residuals, info_coeff, info_model, info_steps)
<put algorithm description here>
Grids
[multipleinput: rasters]Shapes
[vector: any]Attribute
[tablefield: any]Grid Interpolation
[selection]<put parameter description here>
Options:
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:
Default: 0
P in
[number]<put parameter description here>
Default: 5
P out
[number]<put parameter description here>
Default: 5
Details: Coefficients
[table]Details: Model
[table]Details: Steps
[table]Residuals
[vector]Regression
[raster]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)
<put algorithm description here>
Points
[vector: any]Attribute
[tablefield: any]Polynom
[selection]<put parameter description here>
Options:
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:
Default: 0
Output extent
[extent]<put parameter description here>
Default: 0,1,0,1
Cellsize
[number]<put parameter description here>
Default: 100.0
Residuals
[vector]Grid
[raster]processing.runalg('saga:polynomialregression', points, attribute, polynom, xorder, yorder, torder, target, output_extent, user_size, residuals, user_grid)
<put algorithm description here>
Grid
[raster]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:
Default: 0
Variance Radius
[raster]processing.runalg('saga:radiusofvariancegrid', input, variance, radius, output, result)
<put algorithm description here>
Grid
[raster]Shapes
[vector: any]Attribute
[tablefield: any]Grid Interpolation
[selection]<put parameter description here>
Options:
Default: 0
Regression Function
[selection]<put parameter description here>
Options:
Default: 0
Regression
[raster]Residuals
[vector]processing.runalg('saga:regressionanalysis', grid, shapes, attribute, interpol, method, regression, residual)
<put algorithm description here>
Grid
[raster]Radius (Cells)
[number]<put parameter description here>
Default: 10
Exponent
[number]<put parameter description here>
Default: 1
Representativeness
[raster]processing.runalg('saga:representativeness', input, radius, exponent, result)
<put algorithm description here>
Grid
[raster]Radius (Cells)
[number]<put parameter description here>
Default: 7
Distance Weighting
[selection]<put parameter description here>
Options:
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
Mean Value
[raster]Difference from Mean Value
[raster]Standard Deviation
[raster]Value Range
[raster]Minimum Value
[raster]Maximum Value
[raster]Deviation from Mean Value
[raster]Percentile
[raster]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)
<put algorithm description here>
Points
[vector: point]Vertex Distance [Degree]
[number]<put parameter description here>
Default: 5
Mean Centre
[vector]Standard Distance
[vector]Bounding Box
[vector]processing.runalg('saga:spatialpointpatternanalysis', points, step, centre, stddist, bbox)
<put algorithm description here>
Grids
[multipleinput: rasters]Arithmetic Mean
[raster]Minimum
[raster]Maximum
[raster]Variance
[raster]Standard Deviation
[raster]Mean less Standard Deviation
[raster]Mean plus Standard Deviation
[raster]processing.runalg('saga:statisticsforgrids', grids, mean, min, max, var, stddev, stddevlo, stddevhi)
<put algorithm description here>
Points
[vector: point]Attribute
[tablefield: any]Maximum Distance
[number]<put parameter description here>
Default: 0.0
Skip Number
[number]<put parameter description here>
Default: 1
Variogram Cloud
[table]processing.runalg('saga:variogramcloud', points, field, distmax, nskip, result)
<put algorithm description here>
Points
[vector: point]Attribute
[tablefield: any]Number of Distance Classes
[number]<put parameter description here>
Default: 10
Skip Number
[number]<put parameter description here>
Default: 1
Number of Pairs
[raster]Variogram Surface
[raster]Covariance Surface
[raster]processing.runalg('saga:variogramsurface', points, field, distcount, nskip, count, variance, covariance)
<put algorithm description here>
Zone Grid
[raster]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
Zonal Statistics
[table]processing.runalg('saga:zonalgridstatistics', zones, catlist, statlist, aspect, shortnames, outtab)