recognize _Unsigned attribute and return unsigned integer data (issue #656)

Changelog

@@ -1,5 +1,7 @@
- version 1.2.8a0 (tag XXXX)
-===========================
+ version 1.2.8 (not yet released)
+=================================
+ * recognize _Unsigned attribute used by netcdf-java to designate unsigned
+   integer data stored with a signed integer type in netcdf-3.
  * add Dataset init memory parameter to allow loading a file from memory
 
  version 1.2.7 (tag v1.2.7rel)

netCDF4/_netCDF4.pyx

@@ -1,5 +1,5 @@
 """
-Version 1.2.8a0
+Version 1.2.8
 -------------
 - - - 
 
@@ -936,7 +936,7 @@ except ImportError:
     # python3: zip is already python2's itertools.izip
     pass
 
-__version__ = "1.2.8a0"
+__version__ = "1.2.8"
 
 # Initialize numpy
 import posixpath
@@ -3792,6 +3792,13 @@ rename a `netCDF4.Variable` attribute named `oldname` to `newname`."""
             # length 1.
             if data.ndim != 0: data = numpy.asarray(data[0])
 
+        # if attribute _Unsigned is True, and variable has signed integer
+        # dtype, return view with corresponding unsigned dtype (issue #656)
+        if self.scale:  # only do this if autoscale option is on.
+            is_unsigned = getattr(self, '_Unsigned', False)
+            if is_unsigned and data.dtype.kind == 'i':
+                data = data.view('u%s' % data.dtype.itemsize)
+
         # if auto_scale mode set to True, (through
         # a call to set_auto_scale or set_auto_maskandscale),
         # perform automatic unpacking using scale_factor/add_offset.

setup.py

@@ -467,7 +467,7 @@ def getnetcdfvers(libdirs):
 
 setup(name = "netCDF4",
   cmdclass = cmdclass,
-  version = "1.2.8a0",
+  version = "1.2.8",
   long_description = "netCDF version 4 has many features not found in earlier versions of the library, such as hierarchical groups, zlib compression, multiple unlimited dimensions, and new data types.  It is implemented on top of HDF5.  This module implements most of the new features, and can read and write netCDF files compatible with older versions of the library.  The API is modelled after Scientific.IO.NetCDF, and should be familiar to users of that module.\n\nThis project has a `Subversion repository <http://code.google.com/p/netcdf4-python/source>`_ where you may access the most up-to-date source.",
   author            = "Jeff Whitaker",
   author_email      = "jeffrey.s.whitaker@noaa.gov",

test/tst_Unsigned.py

@@ -0,0 +1,27 @@
+import unittest
+import netCDF4
+from numpy.testing import assert_array_equal
+import numpy as np
+
+class Test_Unsigned(unittest.TestCase):
+    """
+    Test autoconversion to unsigned ints when _Unsigned attribute is True.
+    This attribute is is set by netcdf-java to designate unsigned
+    integer data stored with a signed integer type in netcdf-3.
+    If _Unsigned=True, a view to the data as unsigned integers is returned.
+    set_autoscale can be used to turn this off (default is on)
+    See issue #656 (pull reqeust #658).
+    """
+    def test_unsigned(self):
+        f = netCDF4.Dataset("ubyte.nc3")
+        data = f['ub'][:]
+        assert data.dtype.str[1:] == 'u1'
+        assert_array_equal(data,np.array([0,255],np.uint8))
+        f.set_auto_scale(False)
+        data2 = f['ub'][:]
+        assert data2.dtype.str[1:] == 'i1'
+        assert_array_equal(data2,np.array([0,-1],np.int8))
+        f.close()
+
+if __name__ == '__main__':
+    unittest.main()