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Fixes Ordinary Kriging for both SAGA 2.10 and 2.0.8

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This commit is contained in:
gioman 2013-10-17 13:12:24 +01:00
parent 491231e600
commit fecccda364
2 changed files with 22 additions and 22 deletions
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2
python/plugins/processing/saga/description/2.0.8_OrdinaryKriging.txt
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@ -20,6 +20,6 @@ ParameterNumber|NPOINTS_MIN|Min.Number of m_Points|None|None|4
ParameterNumber|NPOINTS_MAX|Max. Number of m_Points|None|None|20
ParameterNumber|USER_CELL_SIZE|Grid Size|0|None|1.0
ParameterBoolean|USER_FIT_EXTENT |Fit Extent|True
Extent USER_X_EXTENT_MIN USER_X_EXTENT_MAX USER_Y_EXTENT_MIN USER_Y_EXTENT_MIN
Extent USER_X_EXTENT_MIN USER_X_EXTENT_MAX USER_Y_EXTENT_MIN USER_Y_EXTENT_MAX
OutputRaster|GRID|Grid
OutputRaster|VARIANCE|Variance

42
python/plugins/processing/saga/description/2.1_OrdinaryKriging.txt
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@ -1,25 +1,25 @@
Ordinary Kriging
geostatistics_kriging
ParameterVector|SHAPES|Points|0|False
ParameterTableField|FIELD|Attribute|SHAPES|-1|False
ParameterBoolean|BVARIANCE |Create Variance Grid|True
ParameterVector|POINTS|Points|0|False
ParameterTableField|ZFIELD|Attribute|POINTS|-1|False
ParameterSelection|TARGET|Target Grid|[0] user defined
ParameterSelection|MODEL|Variogram Model|[0] Spherical Model;[1] Exponential Model;[2] Gaussian Model;[3] Linear Regression;[4] Exponential Regression;[5] Power Function Regression
ParameterSelection|TQUALITY|Type of Quality Measure|[0] standard deviation;[1] variance
ParameterBoolean|LOG |Logarithmic Transformation|True
ParameterBoolean|BLOCK |Block Kriging|True
ParameterNumber|DBLOCK|Block Size|1|None|100
ParameterBoolean|BLOG |Logarithmic Transformation|True
ParameterNumber|NUGGET|Nugget|None|None|0.0
ParameterNumber|SILL|Sill|None|None|10.0
ParameterNumber|RANGE|Range|None|None|100.0
ParameterNumber|LIN_B|Linear Regression|None|None|1.0
ParameterNumber|EXP_B|Exponential Regression|None|None|0.1
ParameterNumber|POW_A|Power Function - A|None|None|1
ParameterNumber|POW_B|Power Function - B|None|None|0.5
ParameterNumber|MAXRADIUS|Maximum Search Radius (map units)|None|None|1000.0
ParameterNumber|NPOINTS_MIN|Min.Number of m_Points|None|None|4
ParameterNumber|NPOINTS_MAX|Max. Number of m_Points|None|None|20
ParameterNumber|USER_CELL_SIZE|Grid Size|0|None|1.0
ParameterBoolean|USER_FIT_EXTENT |Fit Extent|True
Extent USER_X_EXTENT_MIN USER_X_EXTENT_MAX USER_Y_EXTENT_MIN USER_Y_EXTENT_MIN
OutputRaster|GRID|Grid
OutputRaster|VARIANCE|Variance
ParameterNumber|DBLOCK|Block Size|0|None|100
ParameterNumber|VAR_MAXDIST|Maximum Distance|None|None|-1.0
ParameterNumber|VAR_NCLASSES|Lag Distance Classes|1|None|100
ParameterNumber|VAR_NSKIP|Skip|1|None|1
ParameterString|VAR_MODEL|Variogram Model|a + b * x
ParameterSelection|SEARCH_RANGE|Search Range|[0] local;[1] global
ParameterNumber|SEARCH_RADIUS|Maximum Search Distance|0|None|1000
ParameterSelection|SEARCH_POINTS_ALL|Number of Points|[0] maximum number of nearest points;[1] all points within search distance
ParameterNumber|SEARCH_POINTS_MIN|Minimum|1|None|4
ParameterNumber|SEARCH_POINTS_MAX|Maximum|1|None|20
ParameterSelection|SEARCH_DIRECTION|Search Direction|[0] all directions;[1] quadrants
ParameterBoolean|USER_BVARIANCE |Create Quality Grid|True
Extent USER_XMIN USER_XMAX USER_YMIN USER_YMAX
ParameterNumber|USER_SIZE|Cellsize|0|None|1.0
ParameterSelection|USER_FIT|Search Direction|[0] nodes;[1] cells
OutputRaster|USER_GRID|Grid
OutputRaster|USER_VARIANCE|Variance