Merge pull request #66 from keflavich/issue66

check_endian code in _get_filled_data is buggy

.travis.yml

@@ -16,6 +16,7 @@ env:
         - ASTROPY_VERSION=stable
         - CONDA_INSTALL='conda install -c astropy-ci-extras --yes'
         - PIP_INSTALL='pip install'
+        - BOTTLENECK=no
     matrix:
         - SETUP_CMD='egg_info'
 
@@ -34,7 +35,7 @@ matrix:
         # Try Astropy development version
         - python: 2.7
           env: ASTROPY_VERSION=development SETUP_CMD='test'
-        - python: 3.3
+        - python: 3.4
           env: ASTROPY_VERSION=development SETUP_CMD='test'
 
         # Try all python versions with the latest numpy
@@ -59,6 +60,12 @@ matrix:
         - python: 2.7
           env: NUMPY_VERSION=1.5 SETUP_CMD='test'
 
+        # Test with bottleneck
+        - python: 2.7
+          env: ASTROPY_VERSION=stable SETUP_CMD='test' bottleneck=yes NUMPY_VERSION=1.8
+        - python: 3.4
+          env: ASTROPY_VERSION=stable SETUP_CMD='test' bottleneck=yes NUMPY_VERSION=1.8
+
 before_install:
 
     # Use utf8 encoding. Should be default, but this is insurance against
@@ -90,6 +97,10 @@ install:
     # YT
     - if [[ $SETUP_CMD != egg_info ]] && [[ $TRAVIS_PYTHON_VERSION == 2.7 ]] && [[ $NUMPY_VERSION == 1.8 ]]; then $CONDA_INSTALL numpy=$NUMPY_VERSION yt; fi
 
+    # Bottleneck
+    # asmeurer currently (8/26/2014) supports numpy 1.8
+    - if [[ $SETUP_CMD != egg_info ]] && [[ $BOTTLENECK == yes ]] && [[ $NUMPY_VERSION == 1.8 ]]; then $CONDA_INSTALL --channel https://conda.binstar.org/asmeurer bottleneck; fi
+
     # OPTIONAL DEPENDENCIES
     # Here you can add any dependencies your package may have. You can use
     # conda for packages available through conda, or pip for any other

spectral_cube/spectral_cube.py

@@ -613,7 +613,9 @@ def median(self, axis=None, **kwargs):
                                                 projection=True,
                                                 check_endian=True, **kwargs)
         except ImportError:
-            return self.apply_function(np.median, axis=axis, **kwargs)
+            result = self.apply_function(np.median, axis=axis, **kwargs)
+
+        return result
 
     def percentile(self, q, axis=None, **kwargs):
         """

spectral_cube/tests/test_spectral_cube.py

@@ -22,6 +22,12 @@
     yt_version = StrictVersion('0.0.0')
     ytOK = False
 
+try:
+    import bottleneck
+    bottleneckOK = True
+except ImportError:
+    bottleneckOK = False
+
 
 def cube_and_raw(filename):
     p = path(filename)
@@ -475,3 +481,37 @@ def test_ds9region():
 
     #region = 'circle(2,2,2)'
     #subcube = cube.subcube_from_ds9region(region)
+
+@pytest.mark.skipif(not bottleneckOK, reason='Bottleneck could not be imported')
+def test_endians():
+    """
+    Test that the endianness checking returns something in Native form
+    (this is only needed for non-numpy functions that worry about the
+    endianness of their data)
+
+    WARNING: Because the endianness is machine-dependent, this may fail on
+    different architectures!  This is because numpy automatically converts
+    little-endian to native in the dtype parameter; I need a workaround for
+    this.
+    """
+    big = np.array([[[1],[2]]], dtype='>f4')
+    lil = np.array([[[1],[2]]], dtype='<f4')
+    mywcs = WCS(naxis=3)
+    mywcs.wcs.ctype[0] = 'RA'
+    mywcs.wcs.ctype[1] = 'DEC'
+    mywcs.wcs.ctype[2] = 'VELO'
+
+    bigcube = SpectralCube(data=big, wcs=mywcs)
+    xbig = bigcube._get_filled_data(check_endian=True)
+
+    lilcube = SpectralCube(data=lil, wcs=mywcs)
+    xlil = lilcube._get_filled_data(check_endian=True)
+
+    assert xbig.dtype.byteorder == '='
+    assert xlil.dtype.byteorder == '='
+
+    xbig = bigcube._get_filled_data(check_endian=False)
+    xlil = lilcube._get_filled_data(check_endian=False)
+
+    assert xbig.dtype.byteorder == '>'
+    assert xlil.dtype.byteorder == '='