Require only numpy 1.7 for the benefit of readthedocs

doc/conf.py

@@ -22,6 +22,11 @@
     print "numpy: %s, %s" % (numpy.__version__, numpy.__file__)
 except ImportError:
     print "no numpy"
+try:
+    import scipy
+    print "scipy: %s, %s" % (scipy.__version__, scipy.__file__)
+except ImportError:
+    print "no scipy"
 try:
     import pandas
     print "pandas: %s, %s" % (pandas.__version__, pandas.__file__)
@@ -68,7 +73,7 @@ def __getattr__(cls, name):
         else:
             return Mock()
 
-MOCK_MODULES = ['netCDF4', 'scipy', 'scipy.io']
+MOCK_MODULES = ['netCDF4']
 
 for mod_name in MOCK_MODULES:
     sys.modules[mod_name] = Mock()

doc/requirements.txt

@@ -1,8 +1,9 @@
 # only the dependencies required to build xray's docs
 # all others (netCDF4, scipy) are mocked out in conf.py
-numpy==1.8.1
+numpy>=1.7
 ipython==2.0.0
 pandas==0.13.1
-six
 python-dateutil
+scipy
+six
 matplotlib

doc/tutorial.rst

@@ -391,6 +391,17 @@ skip missing values, but we expect to switch to NA skipping versions (like
 pandas) in the future. For now, you can do NA skipping aggregate by passing
 NA aware numpy functions to the :py:attr:`~xray.DataArray.reduce` method:
 
+.. ipython:: python
+    :suppress:
+
+    # monkey patch numpy with nanmean from scipy.stats so the docs can build
+    # even with numpy 1.7 (np.nanmean first appears in numpy 1.8).
+    # this is to work around an unfortunate limitation of readthedocs/pip which
+    # stops us from upgrading both numpy and pandas.
+
+    from scipy import stats
+    np.nanmean = stats.nanmean
+
 .. ipython:: python
 
     foo.reduce(np.nanmean, 'time')

setup.py

@@ -153,8 +153,8 @@ def write_version_py(filename=None):
       classifiers=CLASSIFIERS,
       description=DESCRIPTION,
       long_description=LONG_DESCRIPTION,
-      install_requires=['numpy >= 1.8', 'pandas >= 0.13.1'],
-      tests_require=['mock >= 1.0.1', 'nose >= 1.0'],
+      install_requires=['numpy >= 1.7', 'pandas >= 0.13.1'],
+      tests_require=['nose >= 1.0'],
       url=URL,
       test_suite='nose.collector',
       packages=['xray', 'xray.backends'])