Making things faster

colorcet/plotting.py

@@ -22,34 +22,52 @@ def swatch(name, cmap=None, bounds=None, array=array, **kwargs):
     plot = hv.Image(array, bounds=bounds, group=title)
     backends = hv.Store.loaded_backends()
     if 'bokeh' in backends:
-        plot.opts(opts.Image(backend='bokeh', width=900, height=100, toolbar='above',
+        width = kwargs.pop('width', 900)
+        height = kwargs.pop('height', 100)
+        plot.opts(opts.Image(backend='bokeh', width=width, height=height, toolbar='above',
                              default_tools=['xwheel_zoom', 'xpan', 'save', 'reset'],
                              cmap=cmap or palette[name]))
     if 'matplotlib' in backends:
-        plot.opts(opts.Image(backend='matplotlib', aspect=15, fig_size=350,
+        aspect = kwargs.pop('aspect', 15)
+        fig_size = kwargs.pop('fig_size', 350)
+        plot.opts(opts.Image(backend='matplotlib', aspect=aspect, fig_size=fig_size,
                              cmap=cmap or cm[name]))
     return plot.opts(opts.Image(xaxis=None, yaxis=None), opts.Image(**kwargs))
 
-def swatches(*args, group=None, not_group=None, only_aliased=False, cols=1, **kwargs):
+def swatches(*args, group=None, not_group=None, only_aliased=False, cols=None, **kwargs):
     """Show swatches for given names or names in group"""
     args = args or all_original_names(group=group, not_group=not_group,
                                       only_aliased=only_aliased)
-    plot = hv.Layout([
-      swatch(arg, **kwargs) if isinstance(arg, str) else
-      swatch(*arg, **kwargs) for
-      arg in args]).cols(cols)
+    if not cols:
+        cols = 3 if len(args) >= 3 else 1
 
     backends = hv.Store.loaded_backends()
+    if 'matplotlib' in backends:
+        if 'aspect' not in kwargs:
+            kwargs['aspect'] = 12 // cols
+        if 'fig_size' not in kwargs:
+            kwargs['fig_size'] = 500 // cols
+    if 'bokeh' in backends:
+        if 'height' not in kwargs:
+            kwargs['height'] = 100
+        if 'width' not in kwargs:
+            kwargs['width'] = (9 * kwargs['height']) // 3
+
+    plot = hv.Layout([
+        swatch(arg, **kwargs) if isinstance(arg, str) else
+        swatch(*arg, **kwargs) for
+        arg in args]).cols(cols)
+
     if 'matplotlib' in backends:
         plot.opts(opts.Layout(backend='matplotlib', sublabel_format=None,
-                              fig_size=kwargs.get('fig_size', 350)))
+                              fig_size=kwargs.get('fig_size', 150)))
     return plot
 
+sine = sineramp()
+
 def sine_comb(name, cmap=None, **kwargs):
     """Show sine_comb using matplotlib or bokeh via holoviews"""
     title = name if cmap else get_aliases(name)
-
-    sine = sineramp()
     plot = hv.Image(sine, group=title)
 
     backends = hv.Store.loaded_backends()
@@ -67,9 +85,9 @@ def sine_combs(*args, group=None, not_group=None, only_aliased=False, cols=1, **
     args = args or all_original_names(group=group, not_group=not_group,
                                       only_aliased=only_aliased)
     plot = hv.Layout([
-      sine_comb(arg, **kwargs) if isinstance(arg, str) else
-      sine_comb(*arg, **kwargs) for
-      arg in args]).cols(cols)
+        sine_comb(arg, **kwargs) if isinstance(arg, str) else
+        sine_comb(*arg, **kwargs) for
+        arg in args]).cols(cols)
 
     backends = hv.Store.loaded_backends()
     if 'matplotlib' in backends:

examples/assets/write_named.py

@@ -13,7 +13,7 @@
 
 diverging_col = pn.Column('#Diverging', sine_combs(*diverging_n, width=400, height=150).opts(toolbar=None))
 linear_col = pn.Column('#Linear', sine_combs(*linear_n, width=400, height=150).opts(toolbar=None))
-cat_col = pn.Column('#Categorical', swatches(*cat_n, width=400, height=150).opts(toolbar=None))
+cat_col = pn.Column('#Categorical', swatches(*cat_n, width=400, height=150, cols=1).opts(toolbar=None))
 misc_col = pn.Column('#Misc', sine_combs(*misc_n, width=400, height=150).opts(toolbar=None))
 
 all_named = pn.Row(

examples/user_guide/Continuous.ipynb

@@ -40,9 +40,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "plot_kwargs = dict(cols=3, aspect=4, fig_size=150)\n",
-    "\n",
-    "swatches(only_aliased=True, not_group='glasbey', **plot_kwargs)"
+    "swatches(only_aliased=True, not_group='glasbey')"
    ]
   },
   {
@@ -66,7 +64,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "swatches(group=\"linear\", **plot_kwargs)"
+    "swatches(group=\"linear\")"
    ]
   },
   {
@@ -82,7 +80,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "swatches(group='diverging', **plot_kwargs)"
+    "swatches(group='diverging')"
    ]
   },
   {
@@ -98,7 +96,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "swatches(group='nopic', **plot_kwargs)"
+    "swatches(group='nopic')"
    ]
   },
   {
@@ -119,7 +117,7 @@
    "outputs": [],
    "source": [
     "misc = [name for name in cc.all_original_names() if \"cyclic\" in name or \"isoluminant\" in name or \"rainbow\" in name]\n",
-    "swatches(*misc, **plot_kwargs)"
+    "swatches(*misc)"
    ]
   },
   {

examples/user_guide/index.ipynb

@@ -64,7 +64,7 @@
    "source": [
     "from colorcet.plotting import swatch, swatches\n",
     "import holoviews as hv\n",
-    "hv.extension('bokeh')"
+    "hv.extension('matplotlib')"
    ]
   },
   {