Updated apps

examples/gallery/apps/bokeh/game_of_life.py

@@ -1,6 +1,7 @@
 import numpy as np
 import holoviews as hv
 
+from holoviews import opts
 from holoviews.streams import Tap, Counter
 from scipy.signal import convolve2d
 
@@ -56,26 +57,23 @@ def step(X):
     return (nbrs_count == 3) | (X & (nbrs_count == 2))
 
 def update(pattern, counter, x, y):
-    if counter:
-        img.data = step(img.data)
     if x and y:
         pattern = np.array(shapes[pattern])
         r, c = pattern.shape
         y, x = img.sheet2matrixidx(x,y)
         img.data[y:y+r,x:x+c] = pattern[::-1]
+    else:
+        img.data = step(img.data)
     return hv.Image(img)
 
 title = 'Game of Life - Tap to place pattern, Doubletap to clear'
-opts =  {
-    'style': {'cmap': 'gray', 'toolbar': False, },
-    'plot' : {'height': 400, 'width': 800, 'title': '{label}',
-              'xaxis': None, 'yaxis': None}
-}
+img_opts = opts.Image(cmap='gray', toolbar=None, height=400, width=800,
+                      title=title, xaxis=None, yaxis=None)
 img = hv.Image(np.zeros((100, 200), dtype=np.uint8))
 counter, tap = Counter(transient=True), Tap(transient=True)
 pattern_dim = hv.Dimension('Pattern', values=sorted(shapes.keys()))
 dmap = hv.DynamicMap(update, kdims=[pattern_dim], streams=[counter, tap])
 
-doc = renderer.server_doc(dmap.redim.range(z=(0, 1)).opts(**opts))
+doc = renderer.server_doc(dmap.redim.range(z=(0, 1)).opts(img_opts))
 dmap.periodic(0.05, None)
 doc.title = 'Game of Life'

examples/gallery/apps/bokeh/gapminder.py

@@ -11,7 +11,9 @@
 from bokeh.layouts import layout
 from bokeh.models import Slider, Button
 from bokeh.sampledata import gapminder
-from holoviews.plotting.bokeh import BokehRenderer
+from holoviews import dim, opts
+
+renderer = hv.renderer('bokeh')
 
 # Declare dataset
 panel = pd.Panel({'Fertility': gapminder.fertility,
@@ -41,13 +43,13 @@
                            for yr in gapminder_ds.keys()})
 
 # Define options
-opts = {'plot': dict(width=1000, height=600,tools=['hover'], size_index='Population',
-                     color_index='Group', size_fn=np.sqrt, title="{label}"),
-       'style': dict(cmap='Set1', size=0.3, line_color='black', alpha=0.6)}
-text_opts = {'style': dict(text_font_size='52pt', text_color='lightgray')}
-
 # Combine Points and Text
-hvgapminder = (gapminder_ds({'Points': opts}) * text({'Text': text_opts})).relabel('Gapminder Demo')
+hvgapminder = (gapminder_ds * text).opts(
+    opts.Points(alpha=0.6, color='Group', cmap='Set1', line_color='black', 
+                size=np.sqrt(dim('Population'))*0.005, width=1000, height=600,
+                tools=['hover'], title='Gapminder Demo'),
+    opts.Text(text_font_size='52pt', text_color='lightgray'))
+
 
 # Define custom widgets
 def animate_update():
@@ -80,7 +82,8 @@ def animate():
 
 # Get HoloViews plot and attach document
 doc = curdoc()
-hvplot = BokehRenderer.get_plot(hvgapminder, doc)
+hvplot = renderer.get_plot(hvgapminder, doc)
+hvplot.update((1964,))
 
 # Make a bokeh layout and add it as the Document root
 plot = layout([[hvplot.state], [slider, button]], sizing_mode='fixed')

examples/gallery/apps/bokeh/mandelbrot.py

@@ -7,11 +7,12 @@
 import numpy as np
 import holoviews as hv
 
-from holoviews import Options
-from holoviews.plotting.bokeh import BokehRenderer
+from holoviews import opts
 from holoviews.streams import RangeXY
 from numba import jit
 
+renderer = hv.renderer('bokeh')
+
 @jit
 def mandel(x, y, max_iters):
     """
@@ -59,17 +60,11 @@ def get_fractal(x_range, y_range):
 dmap = hv.DynamicMap(get_fractal, label='Manderbrot Explorer',
                      streams=[range_stream]).hist(log=True)
 
-# Define styling options
-options = hv.Store.options('bokeh')
-options.Image = {
-    'style': Options(cmap='fire'),
-    'plot' : Options(logz=True, height=600, width=600,
-                     xaxis=None, yaxis=None)
-}
-options.Histogram = {
-    'norm': Options(framewise=True),
-    'plot': Options(logy=True, width=200)
-}
+# Apply options
+dmap.opts(
+    opts.Histogram(framewise=True, logy=True, width=200),
+    opts.Image(cmap='fire', logz=True, height=600, width=600,
+               xaxis=None, yaxis=None))
 
-doc = BokehRenderer.server_doc(dmap)
+doc = renderer.server_doc(dmap)
 doc.title = 'Mandelbrot Explorer'

examples/gallery/apps/bokeh/nytaxi_hover.py

@@ -2,12 +2,13 @@
 Bokeh app example using datashader for rasterizing a large dataset and
 geoviews for reprojecting coordinate systems.
 
-This example requires the 1.7GB nyc_taxi.csv dataset which you can
-obtain by following the instructions for 'nyc_taxi' at:
+This example requires the 1.7GB nyc_taxi_wide.parquet dataset which
+you can obtain by downloading the file from AWS:
 
-  https://github.com/bokeh/datashader/blob/master/examples/README.md
+  https://s3.amazonaws.com/datashader-data/nyc_taxi_wide.parq
 
-Once this CSV is placed in a data/ subfolder, you can run this app with:
+Once this parquet is placed in a data/ subfolder, you can run this app
+with:
 
   bokeh serve --show nytaxi_hover.py
 
@@ -16,18 +17,23 @@
 import holoviews as hv
 import dask.dataframe as dd
 
+from holoviews import opts
 from holoviews.operation.datashader import aggregate
 
-hv.extension('bokeh')
+renderer = hv.renderer('bokeh')
 
 # Set plot and style options
-hv.util.opts('Image [width=800 height=400 shared_axes=False logz=True xaxis=None yaxis=None] {+axiswise} ')
-hv.util.opts("HLine VLine (color='white' line_width=1) Layout [shared_axes=False] ")
-hv.util.opts("Curve [xaxis=None yaxis=None show_grid=False, show_frame=False] (color='orangered') {+framewise}")
-
-# Read the CSV file
-df = dd.read_parquet('/Users/philippjfr/development/pyviz/data/nyc_taxi_50k.parq')
-df = df.persist()
+opts.defaults(
+    opts.Curve(xaxis=None, yaxis=None, show_grid=False, show_frame=False,
+               color='orangered', framewise=True, width=100),
+    opts.Image(width=800, height=400, shared_axes=False, logz=True,
+               xaxis=None, yaxis=None, axiswise=True),
+    opts.HLine(color='white', line_width=1),
+    opts.Layout(shared_axes=False),
+    opts.VLine(color='white', line_width=1))
+
+# Read the parquet file
+df = dd.read_parquet('./data/nyc_taxi_wide.parq').persist()
 
 # Declare points
 points = hv.Points(df, kdims=['pickup_x', 'pickup_y'], vdims=[])
@@ -42,8 +48,8 @@
 sampled = hv.util.Dynamic(agg, operation=lambda obj, x: obj.sample(pickup_x=x),
                           streams=[pointerx], link_inputs=False)
 
-hvobj = ((agg * hline * vline) << sampled.opts(plot={'Curve': dict(width=100)}))
+hvobj = ((agg * hline * vline) << sampled)
 
 # Obtain Bokeh document and set the title
-doc = hv.renderer('bokeh').server_doc(hvobj)
+doc = renderer.server_doc(hvobj)
 doc.title = 'NYC Taxi Crosshair'

examples/gallery/apps/bokeh/streaming_psutil.py

@@ -3,8 +3,9 @@
 import psutil
 import pandas as pd
 import holoviews as hv
+from holoviews import dim, opts
 
-hv.extension('bokeh')
+renderer = hv.renderer('bokeh')
 
 # Define functions to get memory and CPU usage
 def get_mem_data():
@@ -48,15 +49,12 @@ def cb():
 cpu_dmap = hv.DynamicMap(cpu_box, streams=[cpu_stream])
 mem_dmap = hv.DynamicMap(mem_stack, streams=[mem_stream])
 
-cpu_opts = {'plot': dict(width=500, height=400, color_index='CPU'),
-        'style': dict(box_fill_color=hv.Cycle('Category20'))}
-mem_opts = dict(height=400, width=400)
-
-plot = (cpu_dmap.redim.range(Utilization=(0, 100)).opts(**cpu_opts) +
-        mem_dmap.redim.range(Usage=(0, 100)).opts(plot=mem_opts))
-
+plot = (cpu_dmap + mem_dmap).opts(
+    opts.Area(height=400, width=400, ylim=(0, 100)),
+    opts.BoxWhisker(box_fill_color=dim('CPU').str(), cmap='Category20',
+                    width=500, height=400, ylim=(0, 100)))
 
 # Render plot and attach periodic callback
 
-doc = hv.renderer('bokeh').server_doc(plot)
+doc = renderer.server_doc(plot)
 doc.add_periodic_callback(cb, 0.05)

examples/user_guide/Plots_and_Renderers.ipynb

@@ -125,7 +125,7 @@
     "    # The handles contain common plot objects\n",
     "    plot.handles\n",
     "\n",
-    "curve = curve.options(hooks=[hook])"
+    "curve = curve.opts(hooks=[hook])"
    ]
   },
   {