Changeset 398

Timestamp:

05/29/09 16:57:17 (4 years ago)

Author:

jjr8

Message:

Checkin of unfinished code so that I can rebuild the Arc 9.3 toolbox for testing purposes.

Location:

MGET/Branches/Jason/PythonPackage/src/GeoEco

Files:

• DataManagement/ArcGISRasters.py (modified) (1 diff)
• Statistics/Modeling.py (modified) (14 diffs)

MGET/Branches/Jason/PythonPackage/src/GeoEco/DataManagement/ArcGISRasters.py

@@ -1441 +1441 @@
     description=_(
 u"""Type of rasters to find. If provided, only rasters of this type
-will be found. Please see the documentation for the ArcGIS
-geoprocessor's ListRasters function for more information. At the time
-of this writing, the ArcGIS 9.2 documentation specified that any of
-the following strings would be accepted: All, ADRG, BIL, BIP, BSQ,
-BMP, CADRG, CIB, ERS, GIF, GIS, GRID, STACK, IMG, JPEG, LAN, SID, SDE,
-TIFF, RAW, PNG, NITF."""),
+will be found. At the time of this writing, the ArcGIS 9.3
+documentation specified that any of the following strings would be
+accepted: ALL, BMP, GIF, GRID, IMG, JP2, JPG, PNG, TIFF.
+
+This parameter requires ArcGIS 9.3 or later."""),
     arcGISDisplayName=_(u'Raster type'),
-    arcGISCategory=_(u'Search options'))
+    arcGISCategory=_(u'Search options'),
+    dependencies=[ArcGISDependency(9, 3)])
 
 AddArgumentMetadata(ArcGISRaster.Find, u'basePath',

MGET/Branches/Jason/PythonPackage/src/GeoEco/Statistics/Modeling.py

@@ -103 +103 @@
 
     @classmethod
-    def PredictFromArcGISRasters(cls, inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, coordinateSystem, extent, cellSize, resamplingTechniques=None, ignoreOutOfRangeValues=True, outputErrorRaster=None, outputBinaryResponseRaster=None, cutoff=None, buildPyramids=False, overwriteExisting=False):
+    def PredictFromArcGISRasters(cls, inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, templateRaster=None, resamplingTechniques=None, ignoreOutOfRangeValues=True, outputErrorRaster=None, outputBinaryResponseRaster=None, cutoff=None, buildPyramids=False, overwriteExisting=False):
         cls.__doc__.Obj.ValidateMethodInvocation()
-        _PredictFromArcGISRasters('glm', inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, coordinateSystem, extent, cellSize, resamplingTechniques, ignoreOutOfRangeValues, outputErrorRaster, outputBinaryResponseRaster, cutoff, buildPyramids, overwriteExisting)
+        _PredictFromArcGISRasters('glm', inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, templateRaster, resamplingTechniques, ignoreOutOfRangeValues, outputErrorRaster, outputBinaryResponseRaster, cutoff, buildPyramids, overwriteExisting)
 
 class GAM(object):
@@ -173 +173 @@
 
     @classmethod
-    def PredictFromArcGISRasters(cls, inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, coordinateSystem, extent, cellSize, resamplingTechniques=None, ignoreOutOfRangeValues=True, outputErrorRaster=None, outputBinaryResponseRaster=None, cutoff=None, buildPyramids=False, overwriteExisting=False):
+    def PredictFromArcGISRasters(cls, inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, templateRaster=None, resamplingTechniques=None, ignoreOutOfRangeValues=True, outputErrorRaster=None, outputBinaryResponseRaster=None, cutoff=None, buildPyramids=False, overwriteExisting=False):
         cls.__doc__.Obj.ValidateMethodInvocation()
-        _PredictFromArcGISRasters('gam', inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, coordinateSystem, extent, cellSize, resamplingTechniques, ignoreOutOfRangeValues, outputErrorRaster, outputBinaryResponseRaster, cutoff, buildPyramids, overwriteExisting)
+        _PredictFromArcGISRasters('gam', inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, templateRaster, resamplingTechniques, ignoreOutOfRangeValues, outputErrorRaster, outputBinaryResponseRaster, cutoff, buildPyramids, overwriteExisting)
 
     @classmethod
-    def BayesPredictFromArcGISRasters(cls, inputModelFile, inputPredictorRasters, variableNames, thresholds, outputProbabilityRasters, coordinateSystem, extent, cellSize, resamplingTechniques=None, ignoreOutOfRangeValues=True, samples=1000, chunks=100, buildPyramids=False, overwriteExisting=False):
+    def BayesPredictFromArcGISRasters(cls, inputModelFile, inputPredictorRasters, variableNames, thresholds, outputProbabilityRasters, templateRaster=None, resamplingTechniques=None, ignoreOutOfRangeValues=True, samples=1000, chunks=100, buildPyramids=False, overwriteExisting=False):
         cls.__doc__.Obj.ValidateMethodInvocation()
 
@@ -188 +188 @@
             if raster in inputPredictorRastersLower:
                 Logger.RaiseException(ValueError(_(u'The output raster %(out)s also appears in the list of input predictor rasters. This is not allowed. Please specify a different output raster or remove it from the list of input predictor rasters.') % {u'out': outputProbabilityRasters[i]}))
-
-        from GeoEco.Types import EnvelopeTypeMetadata
-        left, bottom, right, top = EnvelopeTypeMetadata.ParseCoordinatesFromString(extent)
-
-        if right - left <= 0:
-            Logger.RaiseException(ValueError(_(u'The horizontal extent must be greater than zero.')))
-
-        if top - bottom <= 0:
-            Logger.RaiseException(ValueError(_(u'The vertical extent must be greater than zero.')))
-
-        if cellSize <= 0:
-            Logger.RaiseException(ValueError(_(u'The cell size must be greater than zero.')))
 
         # Load the fitted model.
@@ -234 +222 @@
             tempDir = TemporaryDirectory()
 
-            _PreparePredictorRasters(r, gp, tempDir, variableNames, inputPredictorRasters, coordinateSystem, extent, cellSize, resamplingTechniques)
+            _PreparePredictorRasters(r, gp, tempDir, variableNames, inputPredictorRasters, templateRaster, resamplingTechniques)
 
             # Do the prediction. The prediction rasters are
@@ -268 +256 @@
                 tempOutputRaster = os.path.join(tempDir.Path, u'output%i' % i)
                 gp.ASCIIToRaster_Conversion(os.path.join(tempDir.Path, u'temp_output%i.txt' % i), tempOutputRaster, u'FLOAT')
-                gp.DefineProjection_management(tempOutputRaster, coordinateSystem)
+                gp.DefineProjection_management(tempOutputRaster, coordinateSystem)          # TODO: Fix this
                 if buildPyramids:
                     gp.BuildPyramids_Management(tempOutputRaster)
@@ -762 +750 @@
     return dataFrameName, xColumnParam, yColumnParam, zColumnParam, mColumnParam, coordinateSystemParam, familyParam
 
-def _PredictFromArcGISRasters(modelType, inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, coordinateSystem, extent, cellSize, resamplingTechniques, ignoreOutOfRangeValues, outputErrorRaster, outputBinaryResponseRaster, cutoff, buildPyramids, overwriteExisting):
+def _PredictFromArcGISRasters(modelType, inputModelFile, inputPredictorRasters, variableNames, outputResponseRaster, templateRaster, resamplingTechniques, ignoreOutOfRangeValues, outputErrorRaster, outputBinaryResponseRaster, cutoff, buildPyramids, overwriteExisting):
 
     # Perform additional parameter validation.
+
+    gp = GeoprocessorManager.GetWrappedGeoprocessor()
+
+    for raster in inputPredictorRasters:
+        d = gp.Describe(raster)
+        if d.SpatialReference.Name is None or d.SpatialReference.Name.lower() == u'unknown':
+            Logger.RaiseException(ValueError(_(u'The predictor raster %(raster)s does not have a coordinate system defined. Please define the coordinate system for this raster and try again. (Use the ArcGIS Define Projection tool.)') % {u'raster': raster}))
 
     if outputResponseRaster.lower() in map(unicode.lower, inputPredictorRasters):
@@ -772 +767 @@
         Logger.RaiseException(ValueError(_(u'The output standard error raster %(out)s also appears in the list of input predictor rasters. This is not allowed. Please specify a different output standard error raster or remove it from the list of input predictor rasters.') % {u'out': outputResponseRaster}))
 
-    from GeoEco.Types import EnvelopeTypeMetadata
-    left, bottom, right, top = EnvelopeTypeMetadata.ParseCoordinatesFromString(extent)
-
-    if right - left <= 0:
-        Logger.RaiseException(ValueError(_(u'The horizontal extent must be greater than zero.')))
-
-    if top - bottom <= 0:
-        Logger.RaiseException(ValueError(_(u'The vertical extent must be greater than zero.')))
-
-    if cellSize <= 0:
-        Logger.RaiseException(ValueError(_(u'The cell size must be greater than zero.')))
-
     if outputBinaryResponseRaster is not None and cutoff is None:
         Logger.RaiseException(ValueError(_(u'To create a binary response raster, you must also supply a value for the Cutoff parameter.')))
 
+    # Look up the coordinate system, cell size, and extent of the
+    # template raster.
+
+    if templateRaster is None:
+        templateRaster = inputPredictorRasters[0]
+    else:
+        d = gp.Describe(templateRaster)
+        if d.SpatialReference.Name is None or d.SpatialReference.Name.lower() == u'unknown':
+            Logger.RaiseException(ValueError(_(u'The template raster %(raster)s does not have a coordinate system defined. Please define the coordinate system for this raster and try again. (Use the ArcGIS Define Projection tool.)') % {u'raster': templateRaster}))
+
     # Load the fitted model.
 
     r = R.GetInterpreter()
-    gp = GeoprocessorManager.GetWrappedGeoprocessor()
 
     r('load("%s")' % inputModelFile.replace('\\', '\\\\'))
@@ -876 +868 @@
             # First prepare the input rasters for the prediction.
 
-            _PreparePredictorRasters(r, gp, tempDir, variableNames, inputPredictorRasters, coordinateSystem, extent, cellSize, resamplingTechniques)
+            _PreparePredictorRasters(r, gp, tempDir, variableNames, inputPredictorRasters, templateRaster, resamplingTechniques)
 
             # Do the prediction. The prediction rasters are
@@ -953 +945 @@
         r('if (exists("fam20985982305")) rm("fam20985982305", pos=globalenv())')
 
-def _PreparePredictorRasters(r, gp, tempDir, variableNames, inputPredictorRasters, coordinateSystem, extent, cellSize, resamplingTechniques):
+def _PreparePredictorRasters(r, gp, tempDir, variableNames, inputPredictorRasters, templateRaster, resamplingTechniques):
 
     # Build a dictionary that maps predictor variable names in
@@ -1623 +1615 @@
 in the model formula, it will be ignored.
 
-All of the predictor rasters must use the same datum, but they need
-not have the same coordinate system, extent, or cell size. If these
-characteristics differ from those you specify below for the output
-raster, this tool will automatically project and clip them prior to
-performing the prediction.
-
-The predictor rasters must be able to be projected to the output
+All of the predictor rasters must have a coordinate system defined.
+They must all share the same datum. If you also specify the Template
+Raster For Outputs parameter, they must have the datum of the template
+raster. If you do not specify that parameter, the first predictor
+raster will be used as the template raster.
+
+The predictor rasters need not have the same coordinate system,
+extent, or cell size as the template raster. If these characteristics
+differ from the template raster, this tool will automatically project
+and clip the predictor rasters to conform to the template raster. The
+predictor rasters must be able to be projected to the template
 raster's coordinate system without requiring the specification of a
 geographic transformation. An error will be reported if a geographic
@@ -1635 +1631 @@
 predictor rasters manually before providing them to this tool.
 
-By default, the bilinear interpolation resampling technique will be
-used to project the predictor rasters. You can specify different
-resampling techniques using the Resampling Techniques for Predictor
-Rasters parameter. Bilinear interpolation is appropriate for
-continuous variables such as sea surface temperature but not for
-categorical variables such as bottom substrate type. For categorical
-variables, you should specify the nearest neighbor technique."""),
+By default, floating point predictor rasters will be projected using
+bilinear interpolation and integer predictor rasters will be projected
+using nearest neighbor assignment. Bilinear interpolation is
+appropriate for continuous variables such as sea surface temperature,
+while nearest neighbor is appropriate for categorical variables such
+as bottom substrate type. If these defaults are not appropriate for
+your predictors, specify different algorithms using the Resampling
+Techniques for Predictor Rasters parameter."""),
     arcGISDisplayName=_(u'Input predictor rasters'))
 
@@ -1666 +1663 @@
     arcGISDisplayName=_(u'Output response raster'))
 
-AddArgumentMetadata(GLM.PredictFromArcGISRasters, u'coordinateSystem',
-    typeMetadata=CoordinateSystemTypeMetadata(),
-    description=_(
-u"""Coordinate system for the output rasters.
-
-This coordinate system must use the same datum as the input predictor
-rasters but may use a different projection, so long as the input
-rasters can be projected to it without requiring the specification of
-a geographic transformation."""),
-    arcGISDisplayName=_(u'Coordinate system'))
-
-AddArgumentMetadata(GLM.PredictFromArcGISRasters, u'extent',
-    typeMetadata=EnvelopeTypeMetadata(),
-    description=_(
-u"""Extent for the output rasters, in the units of the output rasters'
-coordinate system."""),
-    arcGISDisplayName=_(u'Extent'))
-
-AddArgumentMetadata(GLM.PredictFromArcGISRasters, u'cellSize',
-    typeMetadata=FloatTypeMetadata(minValue=0.0),
-    description=_(
-u"""Cell size for the output rasters, in the units of the output
-rasters' coordinate system.
-
-The selection of the output cell size should be a carefully considered
-decision. If all of the input predictor rasters have the same cell
-size, that size is an obvious choice. If the rasters have different
-cell sizes, the cell size of the coarsest raster (the one with the
-largest cell size) is a common choice. Please consult the scientific
-literature for further advice.
-
-Input predictor rasters that do not have this cell size will be
-automatically projected using the ArcGIS Project Raster geoprocessing
-tool, as described in the documentation for the Input Predictor
-Rasters parameter."""),
-    arcGISDisplayName=_(u'Cell size'))
+AddArgumentMetadata(GLM.PredictFromArcGISRasters, u'templateRaster',
+    typeMetadata=ArcGISRasterTypeMetadata(mustExist=True, mustBeDifferentThanArguments=[u'inputModelFile', u'outputResponseRaster'], canBeNone=True),
+    description=_(
+u"""Template raster that defines the coordinate system, extent, and
+cell size of the output rasters produced by this tool.
+
+If you do not specify a template raster, the first predictor raster
+will be used instead.
+
+All predictor rasters must share the same datum as the template
+raster. The predictor rasters need not have the same coordinate
+system, extent, or cell size as the template raster. If these
+characteristics differ from the template raster, this tool will
+automatically project and clip the predictor rasters to conform to the
+template raster. Please see the documentation for the Input Predictor
+Rasters parameter for more information."""),
+    arcGISDisplayName=_(u'Template raster for outputs'))
 
 AddArgumentMetadata(GLM.PredictFromArcGISRasters, u'resamplingTechniques',
@@ -2042 +2020 @@
 CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'variableNames', GAM.PredictFromArcGISRasters, u'variableNames')
 CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'outputResponseRaster', GAM.PredictFromArcGISRasters, u'outputResponseRaster')
-CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'coordinateSystem', GAM.PredictFromArcGISRasters, u'coordinateSystem')
-CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'extent', GAM.PredictFromArcGISRasters, u'extent')
-CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'cellSize', GAM.PredictFromArcGISRasters, u'cellSize')
+CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'templateRaster', GAM.PredictFromArcGISRasters, u'templateRaster')
 CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'resamplingTechniques', GAM.PredictFromArcGISRasters, u'resamplingTechniques')
 CopyArgumentMetadata(GLM.PredictFromArcGISRasters, u'ignoreOutOfRangeValues', GAM.PredictFromArcGISRasters, u'ignoreOutOfRangeValues')
@@ -2115 +2091 @@
     arcGISDisplayName=_(u'Output probability rasters'))
 
-CopyArgumentMetadata(GAM.PredictFromArcGISRasters, u'coordinateSystem', GAM.BayesPredictFromArcGISRasters, u'coordinateSystem')
-CopyArgumentMetadata(GAM.PredictFromArcGISRasters, u'extent', GAM.BayesPredictFromArcGISRasters, u'extent')
-CopyArgumentMetadata(GAM.PredictFromArcGISRasters, u'cellSize', GAM.BayesPredictFromArcGISRasters, u'cellSize')
+CopyArgumentMetadata(GAM.PredictFromArcGISRasters, u'templateRaster', GAM.BayesPredictFromArcGISRasters, u'templateRaster')
 CopyArgumentMetadata(GAM.PredictFromArcGISRasters, u'resamplingTechniques', GAM.BayesPredictFromArcGISRasters, u'resamplingTechniques')
 CopyArgumentMetadata(GAM.PredictFromArcGISRasters, u'ignoreOutOfRangeValues', GAM.BayesPredictFromArcGISRasters, u'ignoreOutOfRangeValues')