Docs for ‘QGIS testing’. Visit http://docs.qgis.org/2.18 for QGIS 2.18 docs and translations.

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