Bokeh MultiSelect plotting in infinite loop, distorting plot - loops

Question

I'm trying to plotting multiple lines into a graph based on a user's "MultiSelect" options. I read in two separate excel files of data and and plot their axis based on the user's request. I'm using Python 3.5 and running on a MAC.
1). As soon as I make a multiselection the figure gets distorted
2). It seems the plot is running in an infinite loop.
3). The plot doses not properly update when user changes selections. It just adds more plots without removing the previous plot.
from os.path import dirname, join
from pandas import *
import numpy as np
import pandas.io.sql as psql
import sqlite3 as sql
import sys, os
from bokeh.plotting import figure
from bokeh.layouts import layout, widgetbox
from bokeh.models import ColumnDataSource, HoverTool, Div
from bokeh.models.widgets import Slider, Select, TextInput, MultiSelect
from bokeh.io import curdoc
import matplotlib.pyplot as plt
files = list()
path = os.getcwd()
for x in os.listdir(path):
if x.endswith(".xlsx"):
if x != 'template.xlsx' :
files.append(x)
axis_map = {
"0% void": "0% void",
"40% void": "40% void",
"70% void": "70% void",
}
files_list = MultiSelect(title="Files", value=["dummy2.xlsx"],
options=open(join(dirname(__file__), 'files.txt')).read().split())
voids = MultiSelect(title="At what void[s]", value=["0% void"], options=sorted(axis_map.keys()))
p = figure(plot_height=600, plot_width=700, title="", toolbar_location=None)
pline = figure(plot_height=600, plot_width=700, title="")
path = os.getcwd()
data_dict = {}
for file in os.listdir(path):
if file.endswith(".xlsx"):
xls = ExcelFile(file)
df = xls.parse(xls.sheet_names[0])
data = df.to_dict()
data_dict[file] = data
# converting dictionary to dataframe
newdict = {(k1, k2):v2 for k1,v1 in data_dict.items() \
for k2,v2 in data_dict[k1].items()}
xxs = DataFrame([newdict[i] for i in sorted(newdict)],
index=MultiIndex.from_tuples([i for i in sorted(newdict.keys())]))
master_data = xxs.transpose()
def select_data():
for vals in files_list.value:
for vox in voids.value:
pline.line(x=master_data[vals]['Burnup'], y= master_data[vals][vox])
pline.circle(x=master_data[vals]['Burnup'], y= master_data[vals][vox])
return
def update():
select_data()
controls = [ files_list, voids]
for control in controls:
control.on_change('value', lambda attr, old, new: update())
sizing_mode = 'fixed' # 'scale_width' also looks nice with this example
inputs = widgetbox(*controls, sizing_mode=sizing_mode)
l = layout([
[inputs, pline],
], sizing_mode=sizing_mode)
update()
curdoc().add_root(l)
curdoc().title = "Calculations"

Answer 1

I am not 100% certain, since the code above is not self-contained and cannot be run and investigated, but there are some issues (as of Bokeh 0.12.4) with adding new components to documents being problematic in some situations. These issues are high on the priority list for the next two point releases.
Are the data sizes reasonable such that you could create all the combinations up front? If so, I would recommend doing that, and then having the multi-select values toggle the visibility on/off appropriately. E.g., here's a similar example using a checkbox:
import numpy as np
from bokeh.io import curdoc
from bokeh.layouts import row
from bokeh.palettes import Viridis3
from bokeh.plotting import figure
from bokeh.models import CheckboxGroup
p = figure()
props = dict(line_width=4, line_alpha=0.7)
x = np.linspace(0, 4 * np.pi, 100)
l0 = p.line(x, np.sin(x), color=Viridis3[0], legend="Line 0", **props)
l1 = p.line(x, 4 * np.cos(x), color=Viridis3[1], legend="Line 1", **props)
l2 = p.line(x, np.tan(x), color=Viridis3[2], legend="Line 2", **props)
checkbox = CheckboxGroup(labels=["Line 0", "Line 1", "Line 2"], active=[0, 1, 2], width=100)
def update(attr, old, new):
l0.visible = 0 in checkbox.active
l1.visible = 1 in checkbox.active
l2.visible = 2 in checkbox.active
checkbox.on_change('active', update)
layout = row(checkbox, p)
curdoc().add_root(layout)
If the data sizes are not such that you can create all the combinations up front, then I would suggest making an issue on the project issue trackerhttps://github.com/bokeh/bokeh/issues) that has a complete, minimal, self-contained, runnable as-is code to reproduce the problem (i.e. generates random or synthetic data but it otherwise identical). This it the number one thing that would help the core devs address the issue more promptly.

Answer 2

#bigreddot Thanks for your response.
I edited the code to now make it self contained.
1). The plot does not reset. The new selected plots over the previous plot.
2). When the user makes multiple selections (ctrl+shift) the plot axis gets distorted and it seems to be running in an infinite loop
from pandas import *
import numpy as np
import sys, os
from bokeh.plotting import figure
from bokeh.layouts import layout, widgetbox
from bokeh.models.widgets import MultiSelect
from bokeh.io import curdoc
from bokeh.plotting import reset_output
import math
axis_map = {
"y1": "y3",
"y2": "y2",
"y3": "y1",
}
x1 = np.linspace(0,20,62)
y1 = [1.26 * math.cos(x) for x in np.linspace(-1,1,62) ]
y2 = [1.26 * math.cos(x) for x in np.linspace(-0.95,.95,62) ]
y3 = [1.26 * math.cos(x) for x in np.linspace(-.9,.90,62) ]
TOOLS = "pan,wheel_zoom,box_zoom,reset,save,hover"
vars = MultiSelect(title="At what void[s]", value=["y1"], options=sorted(axis_map.keys()))
master_data = { 'rate' : x1,
'y1' : y1,
'y2' : y2,
'y3' : y3
}
p = figure(plot_height=600, plot_width=700, title="", toolbar_location=None)
pline = figure(plot_height=600, plot_width=700, title="", tools=TOOLS)
def select_data():
for vox in vars.value:
pline.line(x=master_data['rate'], y= master_data[vox], line_width=2)
pline.circle(x=master_data['rate'], y=master_data[vox], line_width=2)
return
controls = [ vars]
for control in controls:
control.on_change('value', lambda attr, old, new: select_data())
sizing_mode = 'fixed'
inputs = widgetbox(*controls)
l = layout([
[inputs, pline],
])
select_data()
curdoc().add_root(l)
curdoc().title = "Plot"