Improved Path and Bounds datetime handling (#3662)

holoviews/core/data/multipath.py

@@ -323,7 +323,7 @@ def split(cls, dataset, start, end, datatype, **kwargs):
                 obj = ds.dframe(**kwargs)
             elif datatype == 'columns':
                 if ds.interface.datatype == 'dictionary':
-                    obj = dict(d)
+                    obj = dict(ds.data)
                 else:
                     obj = ds.columns(**kwargs)
             else:

holoviews/core/util.py

@@ -868,6 +868,18 @@ def isfinite(val):
     return np.isfinite(val)
 
 
+def isdatetime(value):
+    """
+    Whether the array or scalar is recognized datetime type.
+    """
+    if isinstance(value, np.ndarray):
+        return (value.dtype.kind == "M" or
+                (value.dtype.kind == "O" and len(value) and
+                 isinstance(value[0], datetime_types)))
+    else:
+        return isinstance(value, datetime_types)
+
+
 def find_minmax(lims, olims):
     """
     Takes (a1, a2) and (b1, b2) as input and returns

holoviews/element/path.py

@@ -11,7 +11,7 @@
 from ..core import Element2D, Dataset
 from ..core.data import MultiInterface
 from ..core.dimension import Dimension, asdim
-from ..core.util import config, disable_constant, isscalar
+from ..core.util import OrderedDict, config, disable_constant, isscalar
 from .geom import Geometry
 
 
@@ -476,7 +476,7 @@ class Bounds(BaseShape):
     used to compute the corresponding lbrt tuple.
     """
 
-    lbrt = param.NumericTuple(default=(-0.5, -0.5, 0.5, 0.5), doc="""
+    lbrt = param.Tuple(default=(-0.5, -0.5, 0.5, 0.5), doc="""
           The (left, bottom, right, top) coordinates of the bounding box.""")
 
     group = param.String(default='Bounds', constant=True, doc="The assigned group name.")
@@ -489,4 +489,6 @@ def __init__(self, lbrt, **params):
 
         super(Bounds, self).__init__(lbrt=lbrt, **params)
         (l,b,r,t) = self.lbrt
-        self.data = [np.array([(l, b), (l, t), (r, t), (r, b),(l, b)])]
+        xdim, ydim = self.kdims
+        self.data = [OrderedDict([(xdim.name, np.array([l, l, r, r, l])),
+                                  (ydim.name, np.array([b, t, t, b, b]))])]

holoviews/operation/element.py

@@ -13,7 +13,8 @@
                     HoloMap, Dataset, Element, Collator, Dimension)
 from ..core.data import ArrayInterface, DictInterface, default_datatype
 from ..core.util import (group_sanitizer, label_sanitizer, pd,
-                         basestring, datetime_types, isfinite, dt_to_int)
+                         basestring, datetime_types, isfinite, dt_to_int,
+                         isdatetime)
 from ..element.chart import Histogram, Scatter
 from ..element.raster import Image, RGB
 from ..element.path import Contours, Polygons
@@ -586,7 +587,7 @@ def _process(self, element, key=None):
         bins = None if self.p.bins is None else np.asarray(self.p.bins)
         steps = self.p.num_bins + 1
         start, end = hist_range
-        if data.dtype.kind == 'M' or (data.dtype.kind == 'O' and isinstance(data[0], datetime_types)):
+        if isdatetime(data):
             start, end = dt_to_int(start, 'ns'), dt_to_int(end, 'ns')
             datetimes = True
             data = data.astype('datetime64[ns]').astype('int64')
@@ -769,8 +770,7 @@ def _process_layer(self, element, key=None):
         if self.p.interpolation not in INTERPOLATE_FUNCS:
             return element
         x = element.dimension_values(0)
-        dtype = x.dtype
-        is_datetime = dtype.kind == 'M' or isinstance(x[0], datetime_types)
+        is_datetime = isdatetime(x)
         if is_datetime:
             dt_type = 'datetime64[ns]'
             x = x.astype(dt_type).astype('int64')

holoviews/plotting/bokeh/tabular.py

@@ -11,7 +11,7 @@
 from ...core import Dataset, Dimension
 from ...element import ItemTable
 from ...streams import Buffer
-from ...core.util import dimension_sanitizer, datetime_types
+from ...core.util import dimension_sanitizer, isdatetime
 from ..plot import GenericElementPlot
 from .plot import BokehPlot
 
@@ -99,7 +99,7 @@ def _get_columns(self, element, data):
             elif kind == 'f':
                 formatter = NumberFormatter(format='0,0.0[00000]')
                 editor = NumberEditor()
-            elif kind == 'M' or (kind == 'O' and len(data[col]) and type(data[col][0]) in datetime_types):
+            elif isdatetime(data[col]):
                 dimtype = element.get_dimension_type(col)
                 dformat = Dimension.type_formatters.get(dimtype, '%Y-%m-%d %H:%M:%S')
                 formatter = DateFormatter(format=dformat)

holoviews/plotting/mpl/chart.py

@@ -15,7 +15,7 @@
 from ...core.util import (
     OrderedDict, match_spec, unique_iterator, basestring, max_range,
     isfinite, datetime_types, dt_to_int, dt64_to_dt, search_indices,
-    unique_array, isscalar
+    unique_array, isscalar, isdatetime
 )
 from ...element import Raster, HeatMap
 from ...operation import interpolate_curve
@@ -82,7 +82,7 @@ def get_data(self, element, ranges, style):
         xs = element.dimension_values(0)
         ys = element.dimension_values(1)
         dims = element.dimensions()
-        if xs.dtype.kind == 'M' or (len(xs) and isinstance(xs[0], datetime_types)):
+        if isdatetime(xs):
             dimtype = element.get_dimension_type(0)
             dt_format = Dimension.type_formatters.get(dimtype, '%Y-%m-%d %H:%M:%S')
             dims[0] = dims[0](value_format=DateFormatter(dt_format))
@@ -91,7 +91,7 @@ def get_data(self, element, ranges, style):
 
     def init_artists(self, ax, plot_args, plot_kwargs):
         xs, ys = plot_args
-        if xs.dtype.kind == 'M' or (len(xs) and isinstance(xs[0], datetime_types)):
+        if isdatetime(xs):
             artist = ax.plot_date(xs, ys, '-', **plot_kwargs)[0]
         else:
             artist = ax.plot(xs, ys, **plot_kwargs)[0]
@@ -333,8 +333,8 @@ def initialize_plot(self, ranges=None):
 
         # Get plot ranges and values
         dims = hist.dimensions()[:2]
-        edges, hvals, widths, lims, isdatetime = self._process_hist(hist)
-        if isdatetime and not dims[0].value_format:
+        edges, hvals, widths, lims, is_datetime = self._process_hist(hist)
+        if is_datetime and not dims[0].value_format:
             dt_format = Dimension.type_formatters[np.datetime64]
             dims[0] = dims[0](value_format=DateFormatter(dt_format))
 
@@ -381,14 +381,13 @@ def _process_hist(self, hist):
         hist_vals = np.array(values)
         xlim = hist.range(0)
         ylim = hist.range(1)
-        isdatetime = False
-        if edges.dtype.kind == 'M' or isinstance(edges[0], datetime_types):
+        is_datetime = isdatetime(edges)
+        if is_datetime:
             edges = np.array([dt64_to_dt(e) if isinstance(e, np.datetime64) else e for e in edges])
             edges = date2num(edges)
             xlim = tuple(dt_to_int(v, 'D') for v in xlim)
-            isdatetime = True
         widths = np.diff(edges)
-        return edges[:-1], hist_vals, widths, xlim+ylim, isdatetime
+        return edges[:-1], hist_vals, widths, xlim+ylim, is_datetime
 
 
     def _compute_ticks(self, element, edges, widths, lims):

holoviews/plotting/mpl/path.py

@@ -3,9 +3,11 @@
 import param
 import numpy as np
 
+from matplotlib.dates import date2num, DateFormatter
 from matplotlib.collections import PatchCollection, LineCollection
 
 from ...core import util
+from ...core.dimension import Dimension
 from ...core.options import abbreviated_exception
 from ...element import Polygons
 from .element import ColorbarPlot
@@ -32,28 +34,42 @@ def get_data(self, element, ranges, style):
             style = self._apply_transforms(element, ranges, style)
 
         cdim = element.get_dimension(self.color_index)
-        if cdim: cidx = element.get_dimension_index(cdim)
         style_mapping = any(True for v in style.values() if isinstance(v, np.ndarray))
-        if not (cdim or style_mapping):
-            paths = element.split(datatype='array', dimensions=element.kdims)
-            if self.invert_axes:
-                paths = [p[:, ::-1] for p in paths]
-            return (paths,), style, {}
-        paths, cvals = [], []
-        for path in element.split(datatype='array'):
-            length = len(path)
+        dims = element.kdims
+        xdim, ydim = dims
+        generic_dt_format = Dimension.type_formatters[np.datetime64]
+        paths, cvals, dims = [], [], {}
+        for path in element.split(datatype='columns'):
+            xarr, yarr = path[xdim.name], path[ydim.name]
+            if util.isdatetime(xarr):
+                dt_format = Dimension.type_formatters.get(type(xarr[0]), generic_dt_format)
+                xarr = date2num(xarr)
+                dims[0] = xdim(value_format=DateFormatter(dt_format))
+            if util.isdatetime(yarr):
+                dt_format = Dimension.type_formatters.get(type(yarr[0]), generic_dt_format)
+                yarr = date2num(yarr)
+                dims[1] = ydim(value_format=DateFormatter(dt_format))
+            arr = np.column_stack([xarr, yarr])
+            if not (cdim or style_mapping):
+                paths.append(arr)
+                continue
+            length = len(xarr)
             for (s1, s2) in zip(range(length-1), range(1, length+1)):
                 if cdim:
-                    cvals.append(path[s1, cidx])
-                paths.append(path[s1:s2+1, :2])
+                    cvals.append(path[cdim.name])
+                paths.append(arr[s1:s2+1])
+        if self.invert_axes:
+            paths = [p[::-1] for p in paths]
+        if not (cdim or style_mapping):
+            return (paths,), style, {'dimensions': dims}
         if cdim:
             self._norm_kwargs(element, ranges, style, cdim)
             style['array'] = np.array(cvals)
         if 'c' in style:
             style['array'] = style.pop('c')
         if 'vmin' in style:
             style['clim'] = style.pop('vmin', None), style.pop('vmax', None)
-        return (paths,), style, {}
+        return (paths,), style, {'dimensions': dims}
 
     def init_artists(self, ax, plot_args, plot_kwargs):
         line_segments = LineCollection(*plot_args, **plot_kwargs)