Bokeh colorbars #861
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@@ -7,6 +7,14 @@ | |
| from bokeh.models.tickers import Ticker, BasicTicker, FixedTicker | ||
| from bokeh.models.widgets import Panel, Tabs | ||
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| from bokeh.models.mappers import LinearColorMapper | ||
| try: | ||
| from bokeh.models import ColorBar | ||
| from bokeh.models.mappers import LogColorMapper | ||
| except ImportError: | ||
| LogColorMapper, ColorBar = None, None | ||
| from bokeh.models import LogTicker, BasicTicker | ||
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| try: | ||
| from bokeh import mpl | ||
| except ImportError: | ||
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@@ -22,7 +30,8 @@ | |
| from ..util import dynamic_update | ||
| from .callbacks import Callbacks | ||
| from .plot import BokehPlot | ||
| from .util import (mpl_to_bokeh, convert_datetime, update_plot, | ||
| bokeh_version, mplcmap_to_palette) | ||
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| if bokeh_version >= '0.12': | ||
| from bokeh.models import FuncTickFormatter | ||
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@@ -104,6 +113,13 @@ class ElementPlot(BokehPlot, GenericElementPlot): | |
| tools = param.List(default=[], doc=""" | ||
| A list of plugin tools to use on the plot.""") | ||
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| toolbar = param.ObjectSelector(default='right', | ||
| objects=["above", "below", | ||
| "left", "right", None], | ||
| doc=""" | ||
| The toolbar location, must be one of 'above', 'below', | ||
| 'left', 'right', None.""") | ||
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There was a problem hiding this comment. I assume There was a problem hiding this comment. It's just a convenient way to disable the toolbar altogether. I could either disable it, or warn There was a problem hiding this comment. I think being able to disable the toolbar without issuing warnings could be convenient so I am happy to leave it as it is. |
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| xaxis = param.ObjectSelector(default='bottom', | ||
| objects=['top', 'bottom', 'bare', 'top-bare', | ||
| 'bottom-bare', None], doc=""" | ||
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@@ -268,7 +284,6 @@ def _init_plot(self, key, element, plots, ranges=None): | |
| axis_types, labels, plot_ranges = self._axes_props(plots, subplots, element, ranges) | ||
| xlabel, ylabel, _ = labels | ||
| x_axis_type, y_axis_type = axis_types | ||
| properties = dict(plot_ranges) | ||
| properties['x_axis_label'] = xlabel if 'x' in self.show_labels else ' ' | ||
| properties['y_axis_label'] = ylabel if 'y' in self.show_labels else ' ' | ||
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@@ -278,10 +293,15 @@ def _init_plot(self, key, element, plots, ranges=None): | |
| else: | ||
| title = '' | ||
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| if self.toolbar: | ||
| tools = self._init_tools(element) | ||
| properties['tools'] = tools | ||
| properties['toolbar_location'] = self.toolbar | ||
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| properties['webgl'] = Store.renderers[self.renderer.backend].webgl | ||
| return bokeh.plotting.Figure(x_axis_type=x_axis_type, | ||
| y_axis_type=y_axis_type, title=title, | ||
| **properties) | ||
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| def _plot_properties(self, key, plot, element): | ||
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@@ -618,6 +638,138 @@ def framewise(self): | |
| for frame in current_frames) | ||
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| class ColorbarPlot(ElementPlot): | ||
| """ | ||
| ColorbarPlot provides methods to create colormappers and colorbar | ||
| models which can be added to a glyph. Additionally it provides | ||
| parameters to control the position and other styling options of | ||
| the colorbar. The default colorbar_position options are defined | ||
| by the colorbar_specs, but may be overridden by the colorbar_opts. | ||
| """ | ||
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| colorbar_specs = {'right': {'pos': 'right', | ||
| 'opts': {'location': (0, 0)}}, | ||
| 'left': {'pos': 'left', | ||
| 'opts':{'location':(0, 0)}}, | ||
| 'bottom': {'pos': 'below', | ||
| 'opts': {'location': (0, 0), | ||
| 'orientation':'horizontal'}}, | ||
| 'top': {'pos': 'above', | ||
| 'opts': {'location':(0, 0), | ||
| 'orientation':'horizontal'}}, | ||
| 'top_right': {'pos': 'center', | ||
| 'opts': {'location': 'top_right'}}, | ||
| 'top_left': {'pos': 'center', | ||
| 'opts': {'location': 'top_left'}}, | ||
| 'bottom_left': {'pos': 'center', | ||
| 'opts': {'location': 'bottom_left', | ||
| 'orientation': 'horizontal'}}, | ||
| 'bottom_right': {'pos': 'center', | ||
| 'opts': {'location': 'bottom_right', | ||
| 'orientation': 'horizontal'}}} | ||
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| colorbar = param.Boolean(default=False, doc=""" | ||
| Whether to display a colorbar.""") | ||
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| colorbar_position = param.ObjectSelector(objects=list(colorbar_specs), | ||
| default="right", doc=""" | ||
| Allows selecting between a number of predefined colorbar position | ||
| options. The predefined options may be customized in the | ||
| colorbar_specs class attribute.""") | ||
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| colorbar_opts = param.Dict(default={}, doc=""" | ||
| Allows setting specific styling options for the colorbar overriding | ||
| the options defined in the colorbar_specs class attribute. Includes | ||
| location, orientation, height, width, scale_alpha, title, title_props, | ||
| margin, padding, background_fill_color and more.""") | ||
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| logz = param.Boolean(default=False, doc=""" | ||
| Whether to apply log scaling to the z-axis.""") | ||
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| _update_handles = ['color_mapper', 'source', 'glyph'] | ||
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| def _draw_colorbar(self, plot, color_mapper): | ||
| if LogColorMapper and isinstance(color_mapper, LogColorMapper): | ||
| ticker = LogTicker() | ||
| else: | ||
| ticker = BasicTicker() | ||
| cbar_opts = dict(self.colorbar_specs[self.colorbar_position]) | ||
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| # Check if there is a colorbar in the same position | ||
| pos = cbar_opts['pos'] | ||
| if any(isinstance(model, ColorBar) for model in getattr(plot, pos, [])): | ||
| return | ||
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| opts = dict(cbar_opts['opts'], bar_line_color='black', | ||
| label_standoff=8, major_tick_line_color='black') | ||
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There was a problem hiding this comment. I wouldn't necessarily make these parameters but maybe they could be specified as a dictionary in the class attributes. Alternatively, you could just make them into the default for There was a problem hiding this comment. When you add them to the There was a problem hiding this comment. A class attribute would be good in that case. |
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| color_bar = ColorBar(color_mapper=color_mapper, ticker=ticker, | ||
| **dict(opts, **self.colorbar_opts)) | ||
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| plot.add_layout(color_bar, pos) | ||
| self.handles['colorbar'] = color_bar | ||
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| def _get_colormapper(self, dim, element, ranges, style): | ||
| low, high = ranges.get(dim.name) | ||
| palette = mplcmap_to_palette(style.pop('cmap', 'viridis')) | ||
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There was a problem hiding this comment. Not sure I am happy about hard coding 'viridis' as a default, especially as it is a matplotlib colormap (unless bokeh now has viridis?). There was a problem hiding this comment. Matplotlib has hardcoded defaults, which is viridis now and bokeh does have viridis now as well. There was a problem hiding this comment. Personally, I like that viridis is perceptually uniform, but I don't actually like it overall, because it has no intuitive ordering. Hot is clearly ordered in a way that people can appreciate at first glance, as are cool colormaps (black->blue->white), but viridis just has to be memorized. In that sense it's as bad as jet (but only that sense). There was a problem hiding this comment. Plus that would be a (very slight) change to the current defaults. Probably few people besides me could tell the difference, though. There was a problem hiding this comment. And we would have to come up with a name for it! :-) Definitely good suggestions though and something we should consider doing for 1.7. There was a problem hiding this comment. Mpl's hot definitely has regions where it plateaus and conveys little information about changes in value:
It looks good to me up until it turns yellow, then it's got a huge yellow stretch with little change as intensity varies. It wouldn't be hard to do a better job, and I'd be happy to do that. There was a problem hiding this comment. Looks like mpl's hot came from matlab originally? http://ab-initio.mit.edu/wiki/index.php/Color_tables_in_h5topng There was a problem hiding this comment.
Mpl has hot, afmhot, and gist_heat, so ours could be hhot. :-) |
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| colormapper = LogColorMapper if self.logz else LinearColorMapper | ||
| cmapper = colormapper(palette, low=low, high=high) | ||
| if 'color_mapper' not in self.handles: | ||
| self.handles['color_mapper'] = cmapper | ||
| return cmapper | ||
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There was a problem hiding this comment. I can see the logic of returning There was a problem hiding this comment. Yes, there's some annoyances I have with this, ideally the handles would be set elsewhere but since it is now called from get_data, which is the main method the user has to implement and is duplicated everywhere I didn't want to move it out. The other thing is only the first colormapper that's created is actually used while the rest are simply used to update the existing colormapper. I'll leave it up to you if you think I should find a cleaner solution otherwise I'll make sure to leave a comment. |
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| def _init_glyph(self, plot, mapping, properties): | ||
| """ | ||
| Returns a Bokeh glyph object and optionally creates a colorbar. | ||
| """ | ||
| ret = super(ColorbarPlot, self)._init_glyph(plot, mapping, properties) | ||
| if self.colorbar and 'color_mapper' in self.handles: | ||
| self._draw_colorbar(plot, self.handles['color_mapper']) | ||
| return ret | ||
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| def _update_glyph(self, glyph, properties, mapping): | ||
| allowed_properties = glyph.properties() | ||
| cmappers = [v.get('transform') for v in mapping.values() | ||
| if isinstance(v, dict)] | ||
| cmappers.append(properties.pop('color_mapper', None)) | ||
| for cm in cmappers: | ||
| if cm: | ||
| self.handles['color_mapper'].low = cm.low | ||
| self.handles['color_mapper'].high = cm.high | ||
| merged = dict(properties, **mapping) | ||
| glyph.set(**{k: v for k, v in merged.items() | ||
| if k in allowed_properties}) | ||
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| class LegendPlot(ElementPlot): | ||
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| legend_position = param.ObjectSelector(objects=["top_right", | ||
| "top_left", | ||
| "bottom_left", | ||
| "bottom_right", | ||
| 'right', 'left', | ||
| 'top', 'bottom'], | ||
| default="top_right", | ||
| doc=""" | ||
| Allows selecting between a number of predefined legend position | ||
| options. The predefined options may be customized in the | ||
| legend_specs class attribute.""") | ||
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| legend_cols = param.Integer(default=False, doc=""" | ||
| Whether to lay out the legend as columns.""") | ||
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| legend_specs = {'right': dict(pos='right', loc=(5, -40)), | ||
| 'left': dict(pos='left', loc=(0, -40)), | ||
| 'top': dict(pos='above', loc=(120, 5)), | ||
| 'bottom': dict(pos='below', loc=(60, 0))} | ||
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| class BokehMPLWrapper(ElementPlot): | ||
| """ | ||
| Wraps an existing HoloViews matplotlib plot and converts | ||
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@@ -710,22 +862,8 @@ def update_frame(self, key, ranges=None, element=None): | |
| self.handles['plot'] = self._render_plot(element) | ||
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| class OverlayPlot(GenericOverlayPlot, LegendPlot): | ||
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| tabs = param.Boolean(default=False, doc=""" | ||
| Whether to display overlaid plots in separate panes""") | ||
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@@ -734,11 +872,6 @@ class OverlayPlot(GenericOverlayPlot, ElementPlot): | |
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| _update_handles = ['source'] | ||
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| def _process_legend(self): | ||
| plot = self.handles['plot'] | ||
| if not self.show_legend or len(plot.legend) == 0: | ||
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Looks much cleaner!