Changeset 835
- Timestamp:
- 09/14/11 15:58:18 (21 months ago)
- Location:
- MGET/Branches/Jason/PythonPackage/src/GeoEco
- Files:
-
- 4 modified
-
DataProducts/UMaineOMG.py (modified) (2 diffs)
-
Datasets/ArcGIS.py (modified) (5 diffs)
-
SpatialAnalysis/Lines.py (modified) (1 diff)
-
Statistics/PredictLMForArcGISRasters.r (modified) (1 diff)
Legend:
- Unmodified
- Added
- Removed
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MGET/Branches/Jason/PythonPackage/src/GeoEco/DataProducts/UMaineOMG.py
r808 r835 2085 2085 * temp - Potential temperature, in degrees C. 2086 2086 2087 * u - Northward sea water velocity, in m/s.2088 2089 * v - Eastward sea water velocity, in m/s.2087 * u - Eastward sea water velocity, in m/s. 2088 2089 * v - Northward sea water velocity, in m/s. 2090 2090 2091 2091 * zz1 - Biomass concentration of microzooplankton, in nitrogen units, … … 2402 2402 * temp - Potential temperature, in degrees C. 2403 2403 2404 * u - Northward sea water velocity, in m/s.2405 2406 * v - Eastward sea water velocity, in m/s.2404 * u - Eastward sea water velocity, in m/s. 2405 2406 * v - Northward sea water velocity, in m/s. 2407 2407 2408 2408 * zz1 - Biomass concentration of microzooplankton, in nitrogen units, -
MGET/Branches/Jason/PythonPackage/src/GeoEco/Datasets/ArcGIS.py
r808 r835 483 483 d = gp.Describe(workspace) 484 484 if d.DataType.lower() == u'workspace' or d.DataType.lower() == u'folder' and (os.path.basename(workspace) != 'info' or not os.path.exists(os.path.join(path, workspace, 'arc.dir'))): 485 workspace = os.path.basename(workspace) 485 486 contents.append(workspace) 486 487 self._TreeDataTypeCache[os.path.join(path, workspace)] = d.DataType … … 493 494 d = gp.Describe(dataset) 494 495 if issubclass(self._DatasetType, ArcGISRaster) and d.DataType.lower() == u'rastercatalog' or issubclass(self._DatasetType, ArcGISTable) and d.DataType.lower() == u'featuredataset': 496 dataset = os.path.basename(dataset) 495 497 contents.append(dataset) 496 498 self._TreeDataTypeCache[os.path.join(path, dataset)] = d.DataType … … 525 527 raster = enum.Next() 526 528 while isinstance(raster, basestring) and len(raster) > 0: 527 contents.append( raster)529 contents.append(os.path.basename(raster)) 528 530 raster = enum.Next() 529 531 … … 538 540 featureClass = enum.Next() 539 541 while isinstance(featureClass, basestring) and len(featureClass) > 0: 540 contents.append( featureClass)542 contents.append(os.path.basename(featureClass)) 541 543 featureClass = enum.Next() 542 544 … … 545 547 table = enum.Next() 546 548 while isinstance(table, basestring) and len(table) > 0: 547 contents.append( table)549 contents.append(os.path.basename(table)) 548 550 table = enum.Next() 549 551 -
MGET/Branches/Jason/PythonPackage/src/GeoEco/SpatialAnalysis/Lines.py
r775 r835 58 58 raise ValueError(_(u'The X components grid has a different cell size than the Y components grid. Please provide grids that have the same cell size.')) 59 59 60 if abs(xGrid.CenterCoords['x', 0] - yGrid.CenterCoords['x', 0]) / xGrid.CoordIncrements[0] > 0.001 or abs(xGrid.CenterCoords['y', 0] - yGrid.CenterCoords['y', 0]) / xGrid.CoordIncrements[1] > 0.001:61 raise ValueError(_(u'The X components grid has a different extent than the Y components grid. Please provide grids that have the same extent.'))60 ## if abs(xGrid.CenterCoords['x', 0] - yGrid.CenterCoords['x', 0]) / xGrid.CoordIncrements[0] > 0.001 or abs(xGrid.CenterCoords['y', 0] - yGrid.CenterCoords['y', 0]) / xGrid.CoordIncrements[1] > 0.001: 61 ## raise ValueError(_(u'The X components grid has a different extent than the Y components grid. Please provide grids that have the same extent.')) 62 62 63 63 if xGrid.NoDataValue != yGrid.NoDataValue: -
MGET/Branches/Jason/PythonPackage/src/GeoEco/Statistics/PredictLMForArcGISRasters.r
r830 r835 28 28 for (predictor in labels(rastersForPredictors)) 29 29 { 30 minFittedPredictorValues[[predictor]] <- min( model$data[[predictor]], na.rm=TRUE)31 maxFittedPredictorValues[[predictor]] <- max( model$data[[predictor]], na.rm=TRUE)30 minFittedPredictorValues[[predictor]] <- min(c(model$data[[predictor]]), na.rm=TRUE) 31 maxFittedPredictorValues[[predictor]] <- max(c(model$data[[predictor]]), na.rm=TRUE) 32 32 } 33 33
