henchman.plotting.show¶
-
henchman.plotting.
show
(plot, png=False, static=False, hover=True, width=None, height=None, title=None, x_axis=None, y_axis=None, x_range=None, y_range=None, colors=None, fig=False)[source]¶ Format and show a bokeh plot. This is a wrapper around bokeh show which can add common plot attributes like height, axis labels and whether or not you would like the output as a png. This function also runs the bokeh function
output_notebook()
to start.You can get a full list of options by function with
show_template()
.Parameters: - plot (function) – The plot to show.
- static (bool) – If True, show a static bokeh plot.
- hover (bool) – If True, show the hovertool. Default is True.
- width (int, optional) – Plot width.
- height (int, optional) – Plot height.
- title (str, optional) – The title for the plot.
- x_axis (str, optional) – The x_axis label.
- y_axis (str, optional) – The y_axis label.
- x_range (tuple[int, int], optional) – A min and max x value to plot.
- y_range (tuple[int, int], optional) – A min and max y value to plot.
- colors (list[str], optional) – A list of colors to use for the plot.
- png (bool) – If True, return a png of the plot. Default is False
- fig (bool, advanced) – If True, return a bokeh figure instead of showing the plot. Only use if you want to manipulate the bokeh figure directly.
Example
>>> import henchman.plotting as hplot >>> hplot.show_template() show(plot, static=False, png=False, hover=True, width=None, height=None, title='Temporary title', x_axis='my xaxis name', y_axis='my yaxis name', x_range=(0, 10) or None, y_range=(0, 10) or None, colors=None)
>>> hplot.show(plot, width=500, title='My Plot Title') >>> hplot.show(plot, png=True, static=True)