Now also masks with .vrt

biota/core.py

@@ -394,16 +394,16 @@ def updateMask(self, filename, buffer_size = 0., classes = [], output = False, s
 
         file_type = filename.split('/')[-1].split('.')[-1]
 
-        assert file_type in ['shp', 'tif', 'tiff'], "Input filename must be a GeoTiff or a shapefile."
+        assert file_type in ['shp', 'tif', 'tiff', 'vrt'], "Input filename must be a GeoTiff, VRT, or a shapefile."
 
         if file_type == 'shp':
 
             # Rasterize the shapefile, optionally with a buffer
             mask = biota.mask.maskShapefile(self, filename, buffer_size = buffer_size)
 
-        if file_type in ['tif', 'tiff']:
+        if file_type in ['tif', 'tiff', 'vrt']:
 
-            assert classes != [], "If adding a GeoTiff file to the mask, you must also specify the class values to add to the mask (e.g. classes = [20, 160, 170, 190, 210])."
+            assert classes != [], "If adding a GeoTiff or VRT file to the mask, you must also specify the class values to add to the mask (e.g. classes = [20, 160, 170, 190, 210])."
 
             # Resample and extract values from shapefile, optionally with a buffer
             mask = biota.mask.maskRaster(self, filename, classes = classes, buffer_size = buffer_size)

biota/mask.py

@@ -164,13 +164,13 @@ def getBBox(shp, field, value):
     return bbox
 
 
-def maskRaster(tile, tif, classes = [], buffer_size = 0.):
+def maskRaster(tile, raster, classes = [], buffer_size = 0.):
     '''
     Extract a mask from a GeoTiff based on specified classes
     
     Args:
         tile: An ALOS tile (biota.LoadTile())
-        tif: A GeoTiff file, with integer values
+        raster: A GeoTiff or VRT file, with integer values
         classes: A list of values to add to be masked
         buffer_size: Optionally specify a buffer to add around maked pixels, in meters.
     
@@ -180,14 +180,14 @@ def maskRaster(tile, tif, classes = [], buffer_size = 0.):
 
     from osgeo import gdal
 
-    assert tif.rstrip('/').split('.')[-1] == 'tif' or tif.rstrip('/').split('.')[-1] == 'tiff', "tif input must be a GeoTiff file."
+    assert raster.rstrip('/').split('.')[-1] == 'tif' or raster.rstrip('/').split('.')[-1] == 'tiff' or raster.rstrip('/').split('.')[-1] == 'vrt', "raster input must be a GeoTiff or VRT file."
 
-    tif = os.path.expanduser(tif)
-    assert os.path.exists(tif), "GeoTiff file %s does not exist in the file system."%tif
+    raster = os.path.expanduser(raster)
+    assert os.path.exists(raster), "GeoTiff file %s does not exist in the file system."%raster
 
     # Open GeoTiff and get metadata
-    ds_source = gdal.Open(tif)
-    proj_source = biota.IO.loadProjection(tif)
+    ds_source = gdal.Open(raster)
+    proj_source = biota.IO.loadProjection(raster)
 
     # Create output file matching ALOS tile
     gdal_driver = gdal.GetDriverByName('MEM')