pytest-ification

.gitignore

@@ -32,6 +32,7 @@ pip-log.txt
 .tox
 nosetests.xml
 .cache
+.ropeproject/
 
 # Translations
 *.mo
@@ -51,4 +52,7 @@ doc/_build
 doc/generated
 xarray/version.py
 
+# Sync tools
+Icon*
+
 .ipynb_checkpoints

ci/requirements-py34.yml

@@ -2,9 +2,9 @@ name: test_env
 dependencies:
   - python=3.4
   - bottleneck
-  - pytest
   - flake8
   - pandas
   - pip:
     - coveralls
     - pytest-cov
+    - pytest

xarray/conventions.py

@@ -355,7 +355,7 @@ def ensure_dtype_not_object(var, name=None):
                 fill_value = u''
             else:
                 # insist on using float for numeric values
-                if not np.issubdtype(inferred_dtype, float):
+                if not np.issubdtype(inferred_dtype, np.floating):
                     inferred_dtype = np.dtype(float)
                 fill_value = inferred_dtype.type(np.nan)
 

xarray/core/dataset.py

@@ -1573,7 +1573,8 @@ def relevant_keys(mapping):
             dim_name = dim
             dim_coord = None
 
-        reordered = self.transpose(*(list(indexer_dims) + list(non_indexed_dims)))
+        reordered = self.transpose(
+            *(list(indexer_dims) + list(non_indexed_dims)))
 
         variables = OrderedDict()
 
@@ -3383,7 +3384,8 @@ def rank(self, dim, pct=False, keep_attrs=False):
             Variables that do not depend on `dim` are dropped.
         """
         if dim not in self.dims:
-            raise ValueError('Dataset does not contain the dimension: %s' % dim)
+            raise ValueError(
+                'Dataset does not contain the dimension: %s' % dim)
 
         variables = OrderedDict()
         for name, var in iteritems(self.variables):

xarray/core/dtypes.py

@@ -20,13 +20,15 @@ def maybe_promote(dtype):
     fill_value : Valid missing value for the promoted dtype.
     """
     # N.B. these casting rules should match pandas
-    if np.issubdtype(dtype, float):
+    if np.issubdtype(dtype, np.floating):
         fill_value = np.nan
-    elif np.issubdtype(dtype, int):
-        # convert to floating point so NaN is valid
-        dtype = float
+    elif np.issubdtype(dtype, np.integer):
+        if dtype.itemsize <= 2:
+            dtype = np.float32
+        else:
+            dtype = np.float64
         fill_value = np.nan
-    elif np.issubdtype(dtype, complex):
+    elif np.issubdtype(dtype, np.complexfloating):
         fill_value = np.nan + np.nan * 1j
     elif np.issubdtype(dtype, np.datetime64):
         fill_value = np.datetime64('NaT')

xarray/core/indexing.py

@@ -879,7 +879,7 @@ def __array__(self, dtype=None):
         if isinstance(array, pd.PeriodIndex):
             with suppress(AttributeError):
                 # this might not be public API
-                array = array.asobject
+                array = array.astype('object')
         return np.asarray(array.values, dtype=dtype)
 
     @property

xarray/core/missing.py

@@ -41,6 +41,7 @@ class NumpyInterpolator(BaseInterpolator):
     --------
     numpy.interp
     '''
+
     def __init__(self, xi, yi, method='linear', fill_value=None, **kwargs):
 
         if method != 'linear':
@@ -83,6 +84,7 @@ class ScipyInterpolator(BaseInterpolator):
     --------
     scipy.interpolate.interp1d
     '''
+
     def __init__(self, xi, yi, method=None, fill_value=None,
                  assume_sorted=True, copy=False, bounds_error=False, **kwargs):
         from scipy.interpolate import interp1d
@@ -118,6 +120,7 @@ class SplineInterpolator(BaseInterpolator):
     --------
     scipy.interpolate.UnivariateSpline
     '''
+
     def __init__(self, xi, yi, method='spline', fill_value=None, order=3,
                  **kwargs):
         from scipy.interpolate import UnivariateSpline

xarray/core/utils.py

@@ -542,6 +542,7 @@ class HiddenKeyDict(MutableMapping):
     Acts like a normal dictionary, but hides certain keys.
     '''
     # ``__init__`` method required to create instance from class.
+
     def __init__(self, data, hidden_keys):
         self._data = data
         if type(hidden_keys) not in (list, tuple):

xarray/tests/__init__.py

@@ -8,14 +8,15 @@
 import importlib
 
 import numpy as np
-from numpy.testing import assert_array_equal
+from numpy.testing import assert_array_equal  # noqa: F401
 from xarray.core.duck_array_ops import allclose_or_equiv
 import pytest
 
 from xarray.core import utils
 from xarray.core.pycompat import PY3
 from xarray.core.indexing import ExplicitlyIndexed
-from xarray.testing import assert_equal, assert_identical, assert_allclose
+from xarray.testing import (assert_equal, assert_identical,  # noqa: F401
+                            assert_allclose)
 from xarray.plot.utils import import_seaborn
 
 try:
@@ -109,6 +110,9 @@ def _importorskip(modname, minversion=None):
 
 
 class TestCase(unittest.TestCase):
+    """
+    These functions are all deprecated. Instead, use functions in xr.testing
+    """
     if PY3:
         # Python 3 assertCountEqual is roughly equivalent to Python 2
         # assertItemsEqual
@@ -125,26 +129,10 @@ def assertWarns(self, message):
         assert len(w) > 0
         assert any(message in str(wi.message) for wi in w)
 
-    def assertVariableEqual(self, v1, v2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_equal(v1, v2)
-
-    def assertVariableIdentical(self, v1, v2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_identical(v1, v2)
-
-    def assertVariableAllClose(self, v1, v2, rtol=1e-05, atol=1e-08):
-        __tracebackhide__ = True  # noqa: F841
-        assert_allclose(v1, v2, rtol=rtol, atol=atol)
-
     def assertVariableNotEqual(self, v1, v2):
         __tracebackhide__ = True  # noqa: F841
         assert not v1.equals(v2)
 
-    def assertArrayEqual(self, a1, a2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_array_equal(a1, a2)
-
     def assertEqual(self, a1, a2):
         __tracebackhide__ = True  # noqa: F841
         assert a1 == a2 or (a1 != a1 and a2 != a2)
@@ -153,38 +141,6 @@ def assertAllClose(self, a1, a2, rtol=1e-05, atol=1e-8):
         __tracebackhide__ = True  # noqa: F841
         assert allclose_or_equiv(a1, a2, rtol=rtol, atol=atol)
 
-    def assertDatasetEqual(self, d1, d2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_equal(d1, d2)
-
-    def assertDatasetIdentical(self, d1, d2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_identical(d1, d2)
-
-    def assertDatasetAllClose(self, d1, d2, rtol=1e-05, atol=1e-08,
-                              decode_bytes=True):
-        __tracebackhide__ = True  # noqa: F841
-        assert_allclose(d1, d2, rtol=rtol, atol=atol,
-                        decode_bytes=decode_bytes)
-
-    def assertCoordinatesEqual(self, d1, d2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_equal(d1, d2)
-
-    def assertDataArrayEqual(self, ar1, ar2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_equal(ar1, ar2)
-
-    def assertDataArrayIdentical(self, ar1, ar2):
-        __tracebackhide__ = True  # noqa: F841
-        assert_identical(ar1, ar2)
-
-    def assertDataArrayAllClose(self, ar1, ar2, rtol=1e-05, atol=1e-08,
-                                decode_bytes=True):
-        __tracebackhide__ = True  # noqa: F841
-        assert_allclose(ar1, ar2, rtol=rtol, atol=atol,
-                        decode_bytes=decode_bytes)
-
 
 @contextmanager
 def raises_regex(error, pattern):

xarray/tests/test_accessors.py

@@ -6,7 +6,8 @@
 import numpy as np
 import pandas as pd
 
-from . import TestCase, requires_dask, raises_regex
+from . import (TestCase, requires_dask, raises_regex, assert_equal,
+               assert_array_equal)
 
 
 class TestDatetimeAccessor(TestCase):
@@ -36,10 +37,10 @@ def test_field_access(self):
         hours = xr.DataArray(self.times.hour, name='hour',
                              coords=[self.times, ], dims=['time', ])
 
-        self.assertDataArrayEqual(years, self.data.time.dt.year)
-        self.assertDataArrayEqual(months, self.data.time.dt.month)
-        self.assertDataArrayEqual(days, self.data.time.dt.day)
-        self.assertDataArrayEqual(hours, self.data.time.dt.hour)
+        assert_equal(years, self.data.time.dt.year)
+        assert_equal(months, self.data.time.dt.month)
+        assert_equal(days, self.data.time.dt.day)
+        assert_equal(hours, self.data.time.dt.hour)
 
     def test_not_datetime_type(self):
         nontime_data = self.data.copy()
@@ -75,16 +76,16 @@ def test_dask_field_access(self):
 
         # Double check that outcome chunksize is unchanged
         dask_chunks = dask_times_2d.chunks
-        self.assertEqual(dask_year.data.chunks, dask_chunks)
-        self.assertEqual(dask_month.data.chunks, dask_chunks)
-        self.assertEqual(dask_day.data.chunks, dask_chunks)
-        self.assertEqual(dask_hour.data.chunks, dask_chunks)
+        assert dask_year.data.chunks == dask_chunks
+        assert dask_month.data.chunks == dask_chunks
+        assert dask_day.data.chunks == dask_chunks
+        assert dask_hour.data.chunks == dask_chunks
 
         # Check the actual output from the accessors
-        self.assertDataArrayEqual(years, dask_year.compute())
-        self.assertDataArrayEqual(months, dask_month.compute())
-        self.assertDataArrayEqual(days, dask_day.compute())
-        self.assertDataArrayEqual(hours, dask_hour.compute())
+        assert_equal(years, dask_year.compute())
+        assert_equal(months, dask_month.compute())
+        assert_equal(days, dask_day.compute())
+        assert_equal(hours, dask_hour.compute())
 
     def test_seasons(self):
         dates = pd.date_range(start="2000/01/01", freq="M", periods=12)
@@ -93,4 +94,4 @@ def test_seasons(self):
                    "SON", "SON", "SON", "DJF"]
         seasons = xr.DataArray(seasons)
 
-        self.assertArrayEqual(seasons.values, dates.dt.season.values)
+        assert_array_equal(seasons.values, dates.dt.season.values)