Hotfix v1.9.4

.travis.yml

@@ -27,10 +27,10 @@ install:
   - conda update -q conda
   # Useful for debugging any issues with conda
   - conda info -a
-  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION scipy=0.18.1 numpy freetype nose pandas=0.19.2 jupyter ipython=4.2.0 param pyqt=4 matplotlib=1.5.1 xarray
+  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION flake8 scipy=1.0.0 numpy freetype nose pandas=0.22.0 jupyter ipython=4.2.0 param matplotlib=2.1.2 xarray
   - source activate test-environment
-  - conda install -c conda-forge  iris sip=4.18 plotly flexx
-  - conda install -c bokeh datashader dask=0.13 bokeh=0.12.10 selenium
+  - conda install -c conda-forge  iris plotly flexx --quiet
+  - conda install -c bokeh datashader dask=0.16.1 bokeh=0.12.14 selenium
   - if [[ "$TRAVIS_PYTHON_VERSION" == "3.4" ]]; then
       conda install python=3.4.3;
     fi
@@ -68,8 +68,9 @@ before-script:
 script:
   - export HOLOVIEWSRC=`pwd`'/holoviews.rc'
   - echo 'import holoviews as hv;hv.config(style_17=True);hv.config.warn_options_call=True' > holoviews.rc
-  - nosetests --with-doctest --with-coverage --cover-package=holoviews
-  - cd doc/nbpublisher; chmod +x test_notebooks.py; BOKEH_DEV=True ./test_notebooks.py
+  - flake8 --ignore=E,W,F999,F405 holoviews tests
+  - nosetests --with-doctest --with-coverage --cover-package=holoviews -v
+  - cd doc/nbpublisher; chmod +x test_notebooks.py; QT_QPA_PLATFORM='offscreen' BOKEH_DEV=True ./test_notebooks.py
   - chmod +x concat_html.py; ./concat_html.py ../test_data ../test_html
   - cd ../../; mv doc/Tutorials/.coverage ./.coverage.notebooks
   - coverage combine --append

CHANGELOG.md

@@ -1,3 +1,18 @@
+Version 1.9.4
+=============
+
+This release contains a small number of important bug fixes:
+
+-    Compatibility with recent versions of dask and pandas
+     ([\#2329](https://github.com/ioam/holoviews/pull/2329))
+-    Fixed bug referencing columns containing non-alphanumeric characters
+     in bokeh Tables ([\#2336](https://github.com/ioam/holoviews/pull/2336))
+-    Fixed issue in regrid operation
+     ([2337](https://github.com/ioam/holoviews/pull/2337))
+-    Fixed issue when using datetimes with datashader when processing
+     ranges ([\#2344](https://github.com/ioam/holoviews/pull/2344))
+
+
 Version 1.9.3
 =============
 

holoviews/__init__.py

@@ -5,7 +5,7 @@
 import numpy as np # noqa (API import)
 import param
 
-__version__ = param.Version(release=(1,9,3), fpath=__file__,
+__version__ = param.Version(release=(1,9,4), fpath=__file__,
                             commit="$Format:%h$", reponame='holoviews')
 
 from .core import archive, config                        # noqa (API import)

holoviews/core/data/dask.py

@@ -109,7 +109,7 @@ def select_mask(cls, dataset, selection):
             else:
                 masks.append(series == k)
             for mask in masks:
-                if select_mask:
+                if select_mask is not None:
                     select_mask &= mask
                 else:
                     select_mask = mask
@@ -145,7 +145,10 @@ def groupby(cls, columns, dimensions, container_type, group_type, **kwargs):
         if len(group_by) == 1:
             column = columns.data[group_by[0]]
             if column.dtype.name == 'category':
-                indices = ((ind,) for ind in column.cat.categories)
+                try:
+                    indices = ((ind,) for ind in column.cat.categories)
+                except NotImplementedError:
+                    indices = ((ind,) for ind in column.unique().compute())
             else:
                 indices = ((ind,) for ind in column.unique().compute())
         else:

holoviews/core/data/dictionary.py

@@ -214,7 +214,7 @@ def values(cls, dataset, dim, expanded=True, flat=True):
         else:
             if not expanded:
                 return util.unique_array(values)
-            values = np.array(values)
+            values = np.asarray(values)
         return values
 
 

holoviews/core/traversal.py

@@ -72,7 +72,7 @@ def unique_dimkeys(obj, default_dim='Frame'):
                 for d, k in zip(dims, key):
                     dim_keys[d.name] = k
         if dim_keys:
-            keys = [tuple(dim_keys[dim.name] for dim in dimensions)]
+            keys = [tuple(dim_keys.get(dim.name) for dim in dimensions)]
         else:
             keys = []
         return merge_dimensions(dim_groups), keys

holoviews/core/util.py

@@ -180,7 +180,7 @@ def run(self):
             self.counter += 1
             try:
                 self.callback(self.counter)
-            except Exception as e:
+            except Exception:
                 self.stop()
 
             if self.timeout is not None:
@@ -213,7 +213,7 @@ def deephash(obj):
     basestring = basestring
     unicode = unicode
     from itertools import izip
-    generator_types = (izip, xrange, types.GeneratorType)
+    generator_types = (izip, xrange, types.GeneratorType) # noqa
 
 
 
@@ -1555,8 +1555,14 @@ def dt_to_int(value, time_unit='us'):
     """
     Converts a datetime type to an integer with the supplied time unit.
     """
-    if time_unit == 'ns':
-        tscale = 1./np.timedelta64(1, time_unit).tolist()
+    if isinstance(value, np.datetime64):
+        value = np.datetime64(value, 'ns')
+        if time_unit == 'ns':
+            tscale = 1
+        else:
+            tscale = (np.timedelta64(1, time_unit)/np.timedelta64(1, 'ns')) * 1000.
+    elif time_unit == 'ns':
+        tscale = 1000.
     else:
         tscale = 1./np.timedelta64(1, time_unit).tolist().total_seconds()
     if pd and isinstance(value, pd.Timestamp):

holoviews/element/stats.py

@@ -75,7 +75,7 @@ def dframe(self, dimensions=None):
             dimensions = [self.get_dimension(d, strict=True) for d in dimensions
                           if d in dimensions.kdims]
         else:
-            dimensions = dimensions.kdims
+            dimensions = self.kdims
         return self.interface.dframe(self, dimensions)
 
 

holoviews/element/util.py

@@ -241,6 +241,8 @@ def circular_layout(nodes):
     Lay out nodes on a circle and add node index.
     """
     N = len(nodes)
+    if not N:
+        return ([], [], [])
     circ = np.pi/N*np.arange(N)*2
     x = np.cos(circ)
     y = np.sin(circ)
@@ -269,7 +271,6 @@ def connect_edges_pd(graph):
     df = df.sort_values('graph_edge_index').drop(['graph_edge_index'], axis=1)
 
     edge_segments = []
-    N = len(nodes)
     for i, edge in df.iterrows():
         start = edge['src_x'], edge['src_y']
         end = edge['dst_x'], edge['dst_y']

holoviews/operation/datashader.py

@@ -136,8 +136,8 @@ def _get_sampling(self, element, x, y):
             ytype = 'datetime'
         elif not np.isfinite(ystart) and not np.isfinite(yend):
             if element.get_dimension_type(y) in datetime_types:
-                xstart, xend = 0, 10000
-                xtype = 'datetime'
+                ystart, yend = 0, 10000
+                ytype = 'datetime'
             else:
                 ystart, yend = 0, 1
         elif ystart == yend:
@@ -239,7 +239,7 @@ def get_agg_data(cls, obj, category=None):
                 paths = [p.compute() if isinstance(p, dd.DataFrame) else p for p in paths]
                 df = pd.concat(paths)
         else:
-            df = paths[0]
+            df = paths[0] if paths else pd.DataFrame([], columns=[x.name, y.name])
         if category and df[category].dtype.name != 'category':
             df[category] = df[category].astype('category')
 
@@ -338,6 +338,10 @@ def _process(self, element, key=None):
             xarray = xr.DataArray(np.full((height, width), np.NaN, dtype=np.float32),
                                   dims=['y', 'x'], coords={'x': xs, 'y': ys})
             return self.p.element_type(xarray)
+        elif not len(data):
+            xarray = xr.DataArray(np.full((height, width), np.NaN, dtype=np.float32),
+                                  dims=[y.name, x.name], coords={x.name: xs, y.name: ys})
+            return self.p.element_type(xarray)
 
         cvs = ds.Canvas(plot_width=width, plot_height=height,
                         x_range=x_range, y_range=y_range)
@@ -432,7 +436,7 @@ def _get_xarrays(self, element, coords, xtype, ytype):
                 xarr = element.data[vd.name]
                 if 'datetime' in (xtype, ytype):
                     xarr = xarr.copy()
-                if dims != xarr.dims and not irregular:
+                if dims != xarr.dims:
                     xarr = xarr.transpose(*dims)
             else:
                 arr = element.dimension_values(vd, flat=False)
@@ -492,6 +496,7 @@ def _process(self, element, key=None):
                              datatype=['xarray']+element.datatype)
 
 
+
 class shade(Operation):
     """
     shade applies a normalization function followed by colormapping to

holoviews/plotting/bokeh/callbacks.py

@@ -121,7 +121,8 @@ def _init_plot_handles(self):
                 requested[h] = handles[h]
             elif h in self.extra_models:
                 print("Warning %s could not find the %s model. "
-                      "The corresponding stream may not work.")
+                      "The corresponding stream may not work."
+                      % (type(self).__name__, h))
         self.handle_ids.update(self._get_stream_handle_ids(requested))
 
         return requested

holoviews/plotting/bokeh/chart.py

@@ -3,20 +3,19 @@
 import numpy as np
 import param
 from bokeh.models import (CategoricalColorMapper, CustomJS, HoverTool,
-                          FactorRange, Whisker, Band, Range1d, Circle,
-                          VBar, HBar)
+                          FactorRange, Whisker, Range1d, Circle, VBar,
+                          HBar)
 from bokeh.models.tools import BoxSelectTool
 from bokeh.transform import jitter
 
-from ...core import Dataset, OrderedDict
-from ...core.dimension import Dimension
+from ...core import Dataset, OrderedDict, Dimension
 from ...core.util import (max_range, basestring, dimension_sanitizer,
-                          wrap_tuple, unique_iterator)
+                          unique_iterator, wrap_tuple)
 from ...element import Bars
 from ...operation import interpolate_curve
 from ..util import compute_sizes, get_min_distance, dim_axis_label
-from .element import (ElementPlot, ColorbarPlot, LegendPlot, CompositeElementPlot,
-                      line_properties, fill_properties)
+from .element import (ElementPlot, CompositeElementPlot, ColorbarPlot,
+                      LegendPlot, line_properties, fill_properties)
 from .util import expand_batched_style, categorize_array, rgb2hex, mpl_to_bokeh
 
 
@@ -1078,6 +1077,7 @@ def get_data(self, element, ranges, style):
 
             # Compute statistics
             vals = g.dimension_values(g.vdims[0])
+            vals = vals[np.isfinite(vals)]
             if len(vals):
                 qmin, q1, q2, q3, qmax = (np.percentile(vals, q=q) for q in range(0,125,25))
                 iqr = q3 - q1

holoviews/plotting/bokeh/element.py

@@ -1,4 +1,3 @@
-from itertools import groupby
 import warnings
 
 import param
@@ -21,7 +20,7 @@
 from ...core import DynamicMap, CompositeOverlay, Element, Dimension
 from ...core.options import abbreviated_exception, SkipRendering
 from ...core import util
-from ...streams import Stream, Buffer
+from ...streams import Buffer
 from ..plot import GenericElementPlot, GenericOverlayPlot
 from ..util import dynamic_update, process_cmap
 from .plot import BokehPlot, TOOLS

holoviews/plotting/bokeh/plot.py

@@ -7,11 +7,9 @@
 from bokeh.models import (ColumnDataSource, Column, Row, Div)
 from bokeh.models.widgets import Panel, Tabs
 
-from ...core import (OrderedDict, Store, GridMatrix, AdjointLayout,
-                     NdLayout, Empty, GridSpace, HoloMap, Element,
-                     DynamicMap)
+from ...core import (OrderedDict, Store, AdjointLayout, NdLayout,
+                     Empty, GridSpace, HoloMap, Element, DynamicMap)
 from ...core.util import basestring, wrap_tuple, unique_iterator
-from ...element import Histogram
 from ...streams import Stream
 from ..plot import (DimensionedPlot, GenericCompositePlot, GenericLayoutPlot,
                     GenericElementPlot, GenericOverlayPlot)

holoviews/plotting/bokeh/raster.py

@@ -3,8 +3,8 @@
 
 from bokeh.models import HoverTool
 from ...core.util import cartesian_product, is_nan, dimension_sanitizer
+from ...core.options import SkipRendering
 from ...element import Raster
-from ..renderer import SkipRendering
 from .element import ElementPlot, ColorbarPlot, line_properties, fill_properties
 
 

holoviews/plotting/bokeh/tabular.py

@@ -70,9 +70,23 @@ def initialize_plot(self, ranges=None, plot=None, plots=None, source=None):
             source = self._init_datasource(data)
         self.handles['source'] = source
 
+        columns = self._get_columns(element, data)
+        style['reorderable'] = False
+        table = DataTable(source=source, columns=columns, height=self.height,
+                          width=self.width, **style)
+        self.handles['plot'] = table
+        self.handles['glyph_renderer'] = table
+        self._execute_hooks(element)
+        self.drawn = True
+
+        for cb in self.callbacks:
+            cb.initialize()
+
+        return table
+
+    def _get_columns(self, element, data):
         columns = []
-        dims = element.dimensions()
-        for d in dims:
+        for d in element.dimensions():
             col = dimension_sanitizer(d.name)
             kind = data[col].dtype.kind
             if kind == 'i':
@@ -89,21 +103,10 @@ def initialize_plot(self, ranges=None, plot=None, plots=None, source=None):
             else:
                 formatter = StringFormatter()
                 editor = StringEditor()
-            column = TableColumn(field=d.name, title=d.pprint_label,
+            column = TableColumn(field=dimension_sanitizer(d.name), title=d.pprint_label,
                                  editor=editor, formatter=formatter)
             columns.append(column)
-        style['reorderable'] = False
-        table = DataTable(source=source, columns=columns, height=self.height,
-                          width=self.width, **style)
-        self.handles['plot'] = table
-        self.handles['glyph_renderer'] = table
-        self._execute_hooks(element)
-        self.drawn = True
-
-        for cb in self.callbacks:
-            cb.initialize()
-
-        return table
+        return columns
 
 
     def update_frame(self, key, ranges=None, plot=None):

holoviews/plotting/mpl/__init__.py

@@ -26,8 +26,12 @@
 mpl_ge_150 = LooseVersion(mpl.__version__) >= '1.5.0'
 
 if pd:
-    from pandas.tseries import converter
-    converter.register()
+    try:
+        from pandas.plotting import register_matplotlib_converters
+        register_matplotlib_converters()
+    except ImportError:
+        from pandas.tseries import converter
+        converter.register()
 
 
 def set_style(key):

meta.yaml

@@ -1,6 +1,6 @@
 package:
   name: holoviews
-  version: 1.9.3
+  version: 1.9.4
 
 source:
   path: .

setup.py

@@ -35,7 +35,7 @@
 
 setup_args.update(dict(
     name='holoviews',
-    version="1.9.3",
+    version="1.9.4",
     install_requires=install_requires,
     extras_require=extras_require,
     description='Stop plotting your data - annotate your data and let it visualize itself.',

tests/operation/testdatashader.py

@@ -11,7 +11,7 @@
     import datashader as ds
     from holoviews.operation.datashader import (
         aggregate, regrid, ds_version, stack, directly_connect_edges,
-        shade, rasterize
+        shade
     )
 except:
     ds_version = None
@@ -77,6 +77,20 @@ def test_aggregate_curve_datetimes(self):
                          datatype=['xarray'], bounds=bounds, vdims='Count')
         self.assertEqual(img, expected)
 
+    def test_aggregate_curve_datetimes_microsecond_timebase(self):
+        dates = pd.date_range(start="2016-01-01", end="2016-01-03", freq='1D')
+        xstart = np.datetime64('2015-12-31T23:59:59.723518000', 'us')
+        xend = np.datetime64('2016-01-03T00:00:00.276482000', 'us')
+        curve = Curve((dates, [1, 2, 3]))
+        img = aggregate(curve, width=2, height=2, x_range=(xstart, xend), dynamic=False)
+        bounds = (np.datetime64('2015-12-31T23:59:59.585277000'), 1.0,
+                  np.datetime64('2016-01-03T00:00:00.414723000'), 3.0)
+        dates = [np.datetime64('2016-01-01T11:59:59.861759000',),
+                 np.datetime64('2016-01-02T12:00:00.138241000')]
+        expected = Image((dates, [1.5, 2.5], [[1, 0], [0, 2]]),
+                         datatype=['xarray'], bounds=bounds, vdims='Count')
+        self.assertEqual(img, expected)
+
     def test_aggregate_ndoverlay(self):
         ds = Dataset([(0.2, 0.3, 0), (0.4, 0.7, 1), (0, 0.99, 2)], kdims=['x', 'y', 'z'])
         ndoverlay = ds.to(Points, ['x', 'y'], [], 'z').overlay()