Handling numpy values explicitly as nodata values.

GDAL only wants python ints/floats, not numpy ints/floats. RE:natcap#396

src/pygeoprocessing/geoprocessing.py

@@ -4239,6 +4239,12 @@ def numpy_array_to_raster(
             "Origin and pixel size must both be defined or both be None")
     new_band = new_raster.GetRasterBand(1)
     if target_nodata is not None:
+        if numpy.issubdtype(type(target_nodata), numpy.floating):
+            target_nodata = float(target_nodata)
+        elif numpy.issubdtype(type(target_nodata), numpy.integer):
+            target_nodata = int(target_nodata)
+        # Explicitly leaving off an else clause in case there's an edge case we
+        # don't know about.  If so, we should wait for GDAL to raise an error.
         new_band.SetNoDataValue(target_nodata)
     new_band.WriteArray(base_array)
     new_band = None

tests/test_geoprocessing.py

@@ -309,8 +309,8 @@ def test_reclassify_raster_reclass_max_nodata(self):
         test_value = 0.5
         pixel_matrix[:] = test_value
         nodata = numpy.finfo(numpy.float32).max - 1
-        pixel_matrix[0,0] = nodata
-        pixel_matrix[5,7] = nodata
+        pixel_matrix[0, 0] = nodata
+        pixel_matrix[5, 7] = nodata
         raster_path = os.path.join(self.workspace_dir, 'raster.tif')
         target_path = os.path.join(self.workspace_dir, 'target.tif')
         _array_to_raster(