Pandas 0.24 compatibility and CI fixes (#3433)

.appveyor.yml

@@ -0,0 +1,34 @@
+environment:
+  matrix:
+    - PY: "2.7"
+      CONDA: "C:\\Miniconda-x64"
+    - PY: "3.6"
+      CONDA: "C:\\Miniconda36-x64"
+
+matrix:
+  allow_failures:
+    - PY: "2.7"
+    - PY: "3.6"
+
+init:
+  - cmd: set PATH=%CONDA%;%CONDA%\Scripts;%CONDA%\Library\bin;%PATH%
+  - cmd: echo %path%
+
+install:
+  - "conda config --set always_yes yes"
+  - "conda update -q conda"
+  - "conda info -a"
+  - "conda create -n holoviews python=%PY%"
+  - "conda env update -n holoviews -f environment.yml"
+  - "activate holoviews"
+  - "python setup.py develop"
+
+build: false
+
+before_test:
+  - cmd: for /f %%i in ('python -c "import matplotlib; print(matplotlib.matplotlib_fname())"') do set matplotlibrc=%%i
+  - cmd: 'echo backend : Agg > %matplotlibrc%'
+
+test_script:
+  - "flake8 --ignore=E,W,F999,F405 holoviews"
+  - "nosetests --with-doctest --with-coverage --cover-package=holoviews"

.travis.yml

@@ -9,9 +9,6 @@ python:
 notifications:
   email:
     on_failure: change # [always|never|change] default: always
-  flowdock:
-    secure: d32tzqLnUIJge2QyAMtseJWf0yRb3LenW77xzEGVUD+abzlTtoCBbQBIRaWjJn3V78wd3ogLinplnMnu46tsQi7Q2XWiKaxrWq2ZPVfVCbV88whFiYMmmwnj6DNJjl3CxfGQXgui/VyPg9fyaDp5TyZfNZa/gEdedkn1J5kIF3g=
-
 
 install:
   - SITE_PACKAGES=`pip --version | cut -d ' ' -f 4`
@@ -25,13 +22,13 @@ install:
   - hash -r
   - conda config --set always_yes yes --set changeps1 no
   - conda update -q conda
+
   # Useful for debugging any issues with conda
-  - conda info -a
-  - conda create -q -n holoviews python=$TRAVIS_PYTHON_VERSION
+  - conda create -n holoviews -q python=$TRAVIS_PYTHON_VERSION
   - travis_wait conda env update -n holoviews -q -f environment.yml
   - source activate holoviews
   - python setup.py develop
-  - conda env export
+  - conda info -a; conda list; conda env export
   - if [ "$TRAVIS_PULL_REQUEST" == 'false' ]; then
       echo "Attempting to find any associated pull request";
       CURRENT_BUILD=$(curl -s -X GET "https://api.travis-ci.org/repos/ioam/holoviews/builds?number=$TRAVIS_BUILD_NUMBER");
@@ -55,10 +52,8 @@ install:
     fi
   - cd ../..
 
-before-script:
-  - "echo 'backend : Agg' > $HOME/.matplotlib/matplotlibrc"
-
 script:
+  - export MPLBACKEND="Agg"
   - export HOLOVIEWSRC=`pwd`'/holoviews.rc'
   - echo 'import holoviews as hv;hv.config(style_17=True);hv.config.warn_options_call=True' > holoviews.rc
   - flake8 --ignore=E,W,F999,F405 holoviews

environment.yml

@@ -1,31 +1,35 @@
 name: holoviews
 
+channels:
+  - conda-forge
+
 dependencies:
-  - numpy<1.16.0
+  - defaults::numpy
+  - defaults::scipy
+  - defaults::matplotlib
   - notebook
-  - matplotlib=2.1.2
-  - pillow=5.2.0
-  - pandas=0.23.4
-  - scipy
-  - xarray=0.10.9
   - networkx
+  - selenium
+  - cyordereddict
+  - phantomjs
+  - ffmpeg
+  - pillow=5.3.0
+  - pandas=0.24.0
+  - xarray=0.11.0
   - ipython=5.4.1
   - jsonschema=2.6.0
-  - cyordereddict
   - nbconvert=5.3.1
-  - pyviz::param=1.8.0
+  - netcdf4=1.3.1
+  - flexx=0.4.1
+  - plotly=3.4
+  - bokeh=1.0.4
+  - pyviz::param=1.8.1
   - pyviz::pyviz_comms=0.7.0
   - pyviz::datashader
-  - conda-forge::netcdf4=1.3.1
-  - conda-forge::ffmpeg
-  - conda-forge::flexx=0.4.1
-  - conda-forge::plotly=3.4
-  - bokeh::bokeh=1.0.0
-  - bokeh::selenium
   # Testing requirements
   - flake8
   - nose
   - path.py
-  - conda-forge::deepdiff
-  - conda-forge::awscli
-  - conda-forge::coveralls
+  - deepdiff
+  - awscli
+  - coveralls

holoviews/core/util.py

@@ -74,24 +74,33 @@ def __cmp__(self, other):
 
 try:
     import pandas as pd
-    pandas_version = LooseVersion(pd.__version__)
-    if pandas_version > '0.20.0':
-        from pandas.core.dtypes.dtypes import DatetimeTZDtypeType
-        from pandas.core.dtypes.generic import ABCSeries, ABCIndexClass
-    else:
-        from pandas.types.dtypes import DatetimeTZDtypeType
-        from pandas.types.dtypes.generic import ABCSeries, ABCIndexClass
-    pandas_datetime_types = (pd.Timestamp, DatetimeTZDtypeType, pd.Period)
-    pandas_timedelta_types = (pd.Timedelta,)
-    datetime_types = datetime_types + pandas_datetime_types
-    timedelta_types = timedelta_types + pandas_timedelta_types
-    arraylike_types = arraylike_types + (ABCSeries, ABCIndexClass)
-    if pandas_version > '0.23.0':
-        from pandas.core.dtypes.generic import ABCExtensionArray
-        arraylike_types = arraylike_types + (ABCExtensionArray,)
 except ImportError:
     pd = None
 
+if pd:
+    try:
+        pandas_version = LooseVersion(pd.__version__)
+        if pandas_version >= '0.24.0':
+            from pandas.core.dtypes.dtypes import DatetimeTZDtype as DatetimeTZDtypeType
+            from pandas.core.dtypes.generic import ABCSeries, ABCIndexClass
+        elif pandas_version > '0.20.0':
+            from pandas.core.dtypes.dtypes import DatetimeTZDtypeType
+            from pandas.core.dtypes.generic import ABCSeries, ABCIndexClass
+        else:
+            from pandas.types.dtypes import DatetimeTZDtypeType
+            from pandas.types.dtypes.generic import ABCSeries, ABCIndexClass
+        pandas_datetime_types = (pd.Timestamp, DatetimeTZDtypeType, pd.Period)
+        pandas_timedelta_types = (pd.Timedelta,)
+        datetime_types = datetime_types + pandas_datetime_types
+        timedelta_types = timedelta_types + pandas_timedelta_types
+        arraylike_types = arraylike_types + (ABCSeries, ABCIndexClass)
+        if pandas_version > '0.23.0':
+            from pandas.core.dtypes.generic import ABCExtensionArray
+            arraylike_types = arraylike_types + (ABCExtensionArray,)
+    except Exception as e:
+        param.main.warning('pandas could not register all extension types '
+                           'imports failed with the following error: %s' % e)
+
 try:
     import cftime
     cftime_types = (cftime.datetime,)

holoviews/element/comparison.py

@@ -109,8 +109,7 @@ def register(cls):
         cls.equality_type_funcs[list] =         cls.compare_lists
         cls.equality_type_funcs[tuple] =        cls.compare_tuples
 
-
-        #Dictionary comparisons
+        # Dictionary comparisons
         cls.equality_type_funcs[dict] =         cls.compare_dictionaries
         cls.equality_type_funcs[OrderedDict] =  cls.compare_dictionaries
 
@@ -262,11 +261,6 @@ def compare_arrays(cls, arr1, arr2, msg='Arrays'):
             except AssertionError as e:
                 raise cls.failureException(msg + str(e)[11:])
 
-    @classmethod
-    def compare_dataframe(cls, df1, df2, msg='DataFrames'):
-        if not df1.equals(df2):
-            raise cls.failureException('%s are not equal' % msg)
-
     @classmethod
     def bounds_check(cls, el1, el2, msg=None):
         lbrt1 = el1.bounds.lbrt()
@@ -672,12 +666,9 @@ def compare_tables(cls, el1, el2, msg='Table'):
     #========#
 
     @classmethod
-    def compare_dframe(cls, el1, el2, msg='DFrame'):
-        cls.compare_dimensioned(el1, el2)
+    def compare_dataframe(cls, df1, df2, msg='DFrame'):
         from pandas.util.testing import assert_frame_equal
         try:
-            df1 = el1.data.reset_index(drop=True)
-            df2 = el2.data.reset_index(drop=True)
             assert_frame_equal(df1, df2)
         except AssertionError as e:
             raise cls.failureException(msg+': '+str(e))

holoviews/plotting/mpl/element.py

@@ -308,56 +308,63 @@ def _set_axis_limits(self, axis, view, subplots, ranges):
         Compute extents for current view and apply as axis limits
         """
         # Extents
-        scalex, scaley = True, True
         extents = self.get_extents(view, ranges)
-        if extents and not self.overlaid:
-            coords = [coord if np.isreal(coord) or isinstance(coord, np.datetime64) else np.NaN for coord in extents]
-            coords = [date2num(util.dt64_to_dt(c)) if isinstance(c, np.datetime64) else c
-                      for c in coords]
-            valid_lim = lambda c: util.isnumeric(c) and not np.isnan(c)
-            if self.projection == '3d' or len(extents) == 6:
-                l, b, zmin, r, t, zmax = coords
-                if self.invert_zaxis or any(p.invert_zaxis for p in subplots):
-                    zmin, zmax = zmax, zmin
-                if zmin != zmax:
-                    if valid_lim(zmin):
-                        axis.set_zlim(bottom=zmin)
-                    if valid_lim(zmax):
-                        axis.set_zlim(top=zmax)
-            else:
-                l, b, r, t = coords
-
-            if self.invert_axes:
-                l, b, r, t = b, l, t, r
-
-            if self.invert_xaxis or any(p.invert_xaxis for p in subplots):
-                r, l = l, r
-
-            if isinstance(l, util.cftime_types) or l != r:
-                lims = {}
-                if valid_lim(l):
-                    lims['left'] = l
-                    scalex = False
-                if valid_lim(r):
-                    lims['right'] = r
-                    scalex = False
-                if lims:
-                    axis.set_xlim(**lims)
-            if self.invert_yaxis or any(p.invert_yaxis for p in subplots):
-                t, b = b, t
-            if isinstance(b, util.cftime_types) or b != t:
-                lims = {}
-                if valid_lim(b):
-                    lims['bottom'] = b
-                    scaley = False
-                if valid_lim(t):
-                    lims['top'] = t
-                    scaley = False
-                if lims:
-                    axis.set_ylim(**lims)
+        if not extents or self.overlaid:
+            axis.autoscale_view(scalex=True, scaley=True)
+            return
+
+        valid_lim = lambda c: util.isnumeric(c) and not np.isnan(c)
+        coords = [coord if np.isreal(coord) or isinstance(coord, np.datetime64) else np.NaN for coord in extents]
+        coords = [date2num(util.dt64_to_dt(c)) if isinstance(c, np.datetime64) else c
+                  for c in coords]
+        if self.projection == '3d' or len(extents) == 6:
+            l, b, zmin, r, t, zmax = coords
+            if self.invert_zaxis or any(p.invert_zaxis for p in subplots):
+                zmin, zmax = zmax, zmin
+            if zmin != zmax:
+                if valid_lim(zmin):
+                    axis.set_zlim(bottom=zmin)
+                if valid_lim(zmax):
+                    axis.set_zlim(top=zmax)
+        else:
+            l, b, r, t = coords
+
+        if self.invert_axes:
+            l, b, r, t = b, l, t, r
+
+        invertx = self.invert_xaxis or any(p.invert_xaxis for p in subplots)
+        xlim, scalex = self._compute_limits(l, r, self.logx, invertx, 'left', 'right')
+        inverty = self.invert_yaxis or any(p.invert_yaxis for p in subplots)
+        ylim, scaley =  self._compute_limits(b, t, self.logy, inverty, 'bottom', 'top')
+        if xlim:
+            axis.set_xlim(**xlim)
+        if ylim:
+            axis.set_ylim(**ylim)
         axis.autoscale_view(scalex=scalex, scaley=scaley)
 
 
+    def _compute_limits(self, low, high, log, invert, low_key, high_key):
+        scale = True
+        lims = {}
+        valid_lim = lambda c: util.isnumeric(c) and not np.isnan(c)
+        if not isinstance(low, util.datetime_types) and log and (low is None or low <= 0):
+            low = 0.01 if high < 0.01 else 10**(np.log10(high)-2)
+            self.param.warning(
+                "Logarithmic axis range encountered value less "
+                "than or equal to zero, please supply explicit "
+                "lower-bound to override default of %.3f." % low)
+        if invert:
+            high, low = low, high
+        if isinstance(low, util.cftime_types) or low != high:
+            if valid_lim(low):
+                lims[low_key] = low
+                scale = False
+            if valid_lim(high):
+                lims[high_key] = high
+                scale = False
+        return lims, scale
+
+
     def _set_axis_position(self, axes, axis, option):
         """
         Set the position and visibility of the xaxis or yaxis by

holoviews/tests/core/data/base.py

@@ -386,11 +386,12 @@ def test_dataset_get_array_by_dimension(self):
 
     def test_dataset_get_dframe(self):
         df = self.dataset_hm.dframe()
-        self.assertEqual(df, pd.DataFrame({'x': self.xs, 'y': self.y_ints}))
+        self.assertEqual(df.x.values, self.xs)
+        self.assertEqual(df.y.values, self.y_ints)
 
     def test_dataset_get_dframe_by_dimension(self):
         df = self.dataset_hm.dframe(['x'])
-        self.assertEqual(df, pd.DataFrame({'x': self.xs}))
+        self.assertEqual(df, pd.DataFrame({'x': self.xs}, dtype=df.dtypes[0]))
 
 
 

holoviews/tests/core/data/testgridinterface.py

@@ -432,6 +432,11 @@ def test_dataset_groupby_drop_dims_dynamic_with_vdim(self):
             partial = ds.to(Dataset, kdims=['Val'], vdims=['Val2'], groupby='y', dynamic=True)
             self.assertEqual(partial[19]['Val'], array[:, -1, :].T.flatten().compute())
 
+    def test_dataset_get_dframe(self):
+        df = self.dataset_hm.dframe()
+        self.assertEqual(df.x.values, self.xs)
+        self.assertEqual(df.y.values, self.y_ints.compute())
+
 
 
 class Image_GridInterfaceTests(Image_ImageInterfaceTests):

holoviews/tests/core/data/testxarrayinterface.py

@@ -188,7 +188,8 @@ def test_datetime_bins_range(self):
         array = np.random.rand(10, 10)
         ds = QuadMesh((xs, ys, array))
         self.assertEqual(ds.interface.datatype, 'xarray')
-        expected = (dt.datetime(2017, 12, 31, 12, 0), dt.datetime(2018, 1, 10, 12, 0))
+        expected = (np.datetime64(dt.datetime(2017, 12, 31, 12, 0)),
+                    np.datetime64(dt.datetime(2018, 1, 10, 12, 0)))
         self.assertEqual(ds.range('x'), expected)
 
     def test_datetime64_bins_range(self):

holoviews/tests/core/testdynamic.py

@@ -775,14 +775,13 @@ def callback(x): return Curve([1,2,3])
         # Add stream subscriber mocking plot
         xval.add_subscriber(lambda **kwargs: dmap[()])
 
-        dmap.periodic(0.0001, 1000, param_fn=lambda i: {'x':i}, block=False)
-        self.assertNotEqual(xval.x, 1000)
-        for i in range(1000):
-            time.sleep(0.01)
-            if dmap.periodic.instance.completed:
-                break
+        self.assertNotEqual(xval.x, 100)
+        dmap.periodic(0.0001, 100, param_fn=lambda i: {'x': i}, block=False)
+        time.sleep(2)
+        if not dmap.periodic.instance.completed:
+            raise RuntimeError('Periodic callback timed out.')
         dmap.periodic.stop()
-        self.assertEqual(xval.x, 1000)
+        self.assertEqual(xval.x, 100)
 
     def test_periodic_param_fn_blocking_period(self):
         def callback(x):

holoviews/tests/element/teststatselements.py

@@ -86,12 +86,12 @@ def test_bivariate_array_range_vdims(self):
 
     def test_distribution_array_kdim_type(self):
         dist = Distribution(np.array([0, 1, 2]))
-        self.assertEqual(dist.get_dimension_type(0), np.int64)
+        self.assertTrue(np.issubdtype(dist.get_dimension_type(0), np.int_))
 
     def test_bivariate_array_kdim_type(self):
         dist = Bivariate(np.array([[0, 1], [1, 2], [2, 3]]))
-        self.assertEqual(dist.get_dimension_type(0), np.int64)
-        self.assertEqual(dist.get_dimension_type(1), np.int64)
+        self.assertTrue(np.issubdtype(dist.get_dimension_type(0), np.int_))
+        self.assertTrue(np.issubdtype(dist.get_dimension_type(1), np.int_))
 
     def test_distribution_array_vdim_type(self):
         dist = Distribution(np.array([0, 1, 2]))