def _plot_bokeh(self, current_plot, show_legend=True):
import bokeh.models as mdl
import bokeh.plotting as bkh
from bokeh.properties import value
lst = []
row_lst = []
for plotter in self.plots:
cur_plot = bkh.figure(title=plotter.title, plot_width=self.one_figsize[0] * self.BOKEH_RESIZE,
plot_height=self.one_figsize[1] * self.BOKEH_RESIZE)
if plotter.xlim is not None:
cur_plot.x_range = mdl.Range1d(start=plotter.xlim[0], end=plotter.xlim[1])
if plotter.ylim is not None:
cur_plot.y_range = mdl.Range1d(start=plotter.ylim[0], end=plotter.ylim[1])
cur_plot.title_text_font_size = value("{}pt".format(plotter.fontsize))
cur_plot.xaxis.axis_label = plotter.xlabel
cur_plot.yaxis.axis_label = plotter.ylabel
cur_plot.legend.orientation = 'top_right'
cur_plot = plotter._plot_bokeh(cur_plot, show_legend=show_legend)
if len(row_lst) >= self.columns:
lst.append(row_lst)
row_lst = []
row_lst.append(cur_plot)
if len(row_lst) > 0:
lst.append(row_lst)
grid = mdl.GridPlot(children=lst)
return grid
def plot_bokeh(self, xlim=None, ylim=None, title=None, figsize=None,
xlabel=None, ylabel=None, fontsize=None, show_legend=True):
"""
Plot data using bokeh library. Use show() method for bokeh to see result.
:param bool new_plot: create or not new figure
:param xlim: x-axis range
:param ylim: y-axis range
:type xlim: None or tuple(x_min, x_max)
:type ylim: None or tuple(y_min, y_max)
:param title: title
:type title: None or str
:param figsize: figure size
:type figsize: None or tuple(weight, height)
:param xlabel: x-axis name
:type xlabel: None or str
:param ylabel: y-axis name
:type ylabel: None or str
:param fontsize: font size
:type fontsize: None or int
:param bool show_legend: show or not labels for plots
"""
global _COLOR_CYCLE_BOKEH
import bokeh.plotting as bkh
from bokeh.models import Range1d
from bokeh.properties import value
figsize = self.figsize if figsize is None else figsize
xlabel = self.xlabel if xlabel is None else xlabel
ylabel = self.ylabel if ylabel is None else ylabel
title = self.title if title is None else title
xlim = self.xlim if xlim is None else xlim
ylim = self.ylim if ylim is None else ylim
fontsize = self.fontsize if fontsize is None else fontsize
self.fontsize_ = fontsize
self.show_legend_ = show_legend
figsize = (figsize[0] * self.BOKEH_RESIZE, figsize[1] * self.BOKEH_RESIZE)
bkh.output_notebook()
current_plot = bkh.figure(title=title, plot_width=figsize[0], plot_height=figsize[1])
_COLOR_CYCLE_BOKEH = itertools.cycle(COLOR_ARRAY_BOKEH)
if xlim is not None:
current_plot.x_range = Range1d(start=xlim[0], end=xlim[1])
if ylim is not None:
current_plot.y_range = Range1d(start=ylim[0], end=ylim[1])
current_plot.title_text_font_size = value("{}pt".format(fontsize))
current_plot.xaxis.axis_label = xlabel
current_plot.yaxis.axis_label = ylabel
current_plot.legend.orientation = 'top_right'
current_plot = self._plot_bokeh(current_plot, show_legend)
bkh.show(current_plot)
plot_height=300,
min_border=0,
title="Hover and tap discontinuous patches.")
patches_dis_data = pd.DataFrame(
{
'xs': [[0, 49, 49, 0, NAN, 51, 89, 89, 51], [90, 100, 100, 90],
[92, 98, 98, 92]],
'ys': [[0, 0, 80, 80, NAN, 0, 0, 90, 90], [0, 0, 100, 100],
[20, 20, 90, 90]],
'value':
['I am one object split in two', 'I am wheat', 'I am steelblue'],
'fill_color': ['firebrick', 'wheat', 'steelblue']
}, )
plot_patches_dis = Plot(**PLOT_FORMATS)
plot_patches_dis.add_glyph(
ColumnDataSource(patches_dis_data),
Patches(
xs='xs',
ys='ys',
fill_color='fill_color',
line_color=value('wheat'),
))
plot_patches_dis.add_tools(HoverTool(tooltips='@value'))
plot_patches_dis.add_tools(TapTool())
filename = '2376_hover_on_discontinuous_patches.html'
output_file(filename, title='Discontinuous Patches', mode='relative-dev')
save(plot_patches_dis)
view(filename)
from bokeh.models import Plot, Range1d, ColumnDataSource, Patches, HoverTool, TapTool
from bokeh.properties import value
from bokeh.io import save, output_file
PLOT_FORMATS = dict(x_range=Range1d(0,100), y_range=Range1d(0,100), plot_width=500, plot_height=300, min_border=0, title="Hover and tap discontinuous patches.")
patches_dis_data = pd.DataFrame(
{
'xs': [[0, 49, 49, 0, NAN, 51, 89, 89, 51], [90, 100, 100, 90], [92, 98, 98, 92]],
'ys': [[0, 0, 80, 80, NAN, 0, 0, 90, 90], [0, 0, 100, 100], [20, 20, 90, 90]],
'value': ['I am one object split in two', 'I am wheat', 'I am steelblue'],
'fill_color': ['firebrick', 'wheat', 'steelblue']
},
)
plot_patches_dis = Plot(**PLOT_FORMATS)
plot_patches_dis.add_glyph(
ColumnDataSource(patches_dis_data),
Patches(
xs='xs', ys='ys',
fill_color='fill_color',
line_color=value('wheat'),
)
)
plot_patches_dis.add_tools(HoverTool(tooltips='@value'))
plot_patches_dis.add_tools(TapTool())
filename = '2376_hover_on_discontinuous_patches.html'
output_file(filename, title='Discontinuous Patches', mode='relative-dev')
save(plot_patches_dis)
view(filename)
