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i am developing a GUI application for which there will be multiple dynamic subplots for which i would like to have a cursor integration for which is used "Matplotlib's MultiCursor widget" the code seems to be all good without any errors but the cursor alone is not being displayed on the screen
The below is a small snippet function which iam currently using
import numpy as np
import PySimpleGUI as sg
from matplotlib.backends.backend_tkagg import (FigureCanvasTkAgg,
NavigationToolbar2Tk)
from matplotlib.widgets import Cursor
from matplotlib.widgets import MultiCursor
from matplotlib.gridspec import GridSpec
from matplotlib.figure import Figure
class Toolbar(NavigationToolbar2Tk):
def __init__(self, *args, **kwargs):
super(Toolbar, self).__init__(*args, **kwargs)
def repack(widget, option):
pack_info = widget.pack_info()
pack_info.update(option)
widget.pack(**pack_info)
def draw_figure_w_toolbar(canvas, fig, canvas_toolbar):
if canvas.children:
for child in canvas.winfo_children():
child.destroy()
if canvas_toolbar.children:
for child in canvas_toolbar.winfo_children():
child.destroy()
figure_canvas_agg = FigureCanvasTkAgg(fig, master=canvas)
figure_canvas_agg.draw_idle()
toolbar = Toolbar(figure_canvas_agg, canvas_toolbar)
toolbar.update()
figure_canvas_agg.get_tk_widget().pack(side='right', fill='both', expand=1)
layout=[
[
sg.Frame(
'Controls',
expand_x=True,
layout=[[
sg.Canvas(key='controls_cv')
]])
],
[
sg.Canvas(
key='fig_cv',
size=(1024, 525), #(W,H)
expand_x=True,
expand_y=True,
background_color='black')
],
]
window = sg.Window('Data Visualization Tool',
layout=layout,
location=(0, 0),
resizable=True,
margins=(0, 0),
finalize=True)
fig = Figure()
def get_data_ax(x_data, y_data, y_label, marker_sym=None):
ax = fig.add_subplot()
lines = ax.step(
x_data,
y_data,
marker=marker_sym,
where='post')
return ax, lines
cursor_handle_list = []
axes_handle_list = []
def on_move(event, flag=False, c_flag=False):
global cursor_present_flag, cursor_handle_list, axes_handle_list
if event.dblclick:
def change_cursor_position(handle_obj):
for handles in handle_obj:
handles.set_xdata(float(event.xdata))
if event.inaxes is not None:
ax = event.inaxes
if ax not in axes_handle_list:
cursor_handle = ax.axvline(event.xdata, color ='red', lw = .75, alpha = 0.65, visible=True)
cursor_handle_list.append(cursor_handle)
axes_handle_list.append(ax)
else:
change_cursor_position(cursor_handle_list)
draw_figure_w_toolbar(window['fig_cv'].TKCanvas, fig,
window['controls_cv'].TKCanvas)
window.refresh()
fig.canvas.mpl_connect("button_press_event", on_move)
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2 * np.pi * t)
num_rows = 2
gs = GridSpec(num_rows, 1, hspace=0)
ax0, lines = get_data_ax(t, s, 'test')
ax0.set_subplotspec(gs[0])
fig.add_subplot(ax0)
ax, lines = get_data_ax(t, s, 'test')
ax.set_subplotspec(gs[1])
fig.add_subplot(ax)
ax.get_shared_x_axes().join(ax0, ax)
graph = FigureCanvasTkAgg(fig, master=window['fig_cv'].TKCanvas)
cursor_multi = MultiCursor(graph, [ax,], color='r', lw=2.0, vertOn=True)
graph.draw()
draw_figure_w_toolbar(window['fig_cv'].TKCanvas, fig,
window['controls_cv'].TKCanvas)
while True:
event, values = window.read()
if event in (sg.WIN_CLOSED, 'Exit'):
break
I tried using axvline with matplotlib events but the results were not satisfactory
i saw somewhere that defining the return value of MultiCursor as gloabl should fix the issue but that did not happen in my case
next i tried simple putting plt.var_name as a variable for catching the returned object from MultiCursor but even this did not yeild me any result
Note: The code with mpl_connect and on_move callback with axvline integration were just an workaround i was trying as MultiCursor was not working you can discard that part if not required
It's because you created the MultiCursor widget before you created the FigureCanvasTkAgg for the axes objects. So do like this.
draw_figure_w_toolbar(window['fig_cv'].TKCanvas, ...)
cursor_multi = MultiCursor(None, [ax,], ...)
Also note that the first argument of the MultiCursor() is recommended to be set to None because it is ignored. Also your code contain many problems, such as an unused object graph.
I made a graph viewer GUI program in Python using Tkinter and matplotlib, where I switch between two graphs.
I have three problems I don't know how to fix:
Can't change the radiobutton after I move the slider it stops updating.
Can't change radiobutton after I switch the graph.
I would like to switch between graphs with 1 subplot and 2 subplots, but when I switch to graph with 2 subplots with slider and radiobar I can't move back to first.
I think the problem might be in the way I update the slider and radiobutton
Here is the code:
import matplotlib
import tkinter as Tk
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
import numpy as np
from tkinter import *
from matplotlib.backends.backend_tkagg import (
FigureCanvasTkAgg, NavigationToolbar2Tk)
from matplotlib.backend_bases import key_press_handler
from matplotlib.widgets import Slider, RadioButtons
# Seperated out config of plot to just do it once
def config_plot():
fig, ax = plt.subplots()
ax.set(xlabel='time (s)', ylabel='voltage (mV)',
title='Graph One')
return (fig, ax)
class matplotlibSwitchGraphs:
def __init__(self, master):
self.master = master
self.frame = Frame(self.master)
self.fig, self.ax = config_plot()
self.graphIndex = 0
self.canvas = FigureCanvasTkAgg(self.fig, self.master)
self.config_window()
self.draw_graph_one()
self.frame.pack(expand=YES, fill=BOTH)
def config_window(self):
self.canvas.mpl_connect("key_press_event", self.on_key_press)
toolbar = NavigationToolbar2Tk(self.canvas, self.master)
toolbar.update()
self.canvas.get_tk_widget().pack(side=TOP, fill=BOTH, expand=1)
self.button = Button(self.master, text="Quit", command=self._quit)
self.button.pack(side=BOTTOM)
self.button_switch = Button(self.master, text="Switch Graphs", command=self.switch_graphs)
self.button_switch.pack(side=BOTTOM)
def plot_data(self):
def func3(x, y):
return (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-(x ** 2 + y ** 2))
dx, dy = 0.05, 0.05
x = np.arange(-3.0, 3.0, dx)
y = np.arange(-3.0, 3.0, dy)
X, Y = np.meshgrid(x, y)
self.extent = np.min(x), np.max(x), np.min(y), np.max(y)
self.Z1 = np.add.outer(range(8), range(8)) % 2 # chessboard
self.Z2 = func3(X, Y)
def draw_graph_one(self):
self.plot_data()
self.ax.remove()
self.ax = plt.imshow(self.Z2, cmap=plt.cm.viridis, alpha=.9, interpolation='bilinear',
extent=self.extent)
self.canvas.draw()
def draw_graph_two(self):
self.plot_data()
self.ax.remove()
self.ax = plt.subplot(1, 2, 1)
self.ax = plt.imshow(self.Z1, cmap=plt.cm.gray, interpolation='nearest',
extent=self.extent)
self.ax = plt.subplot(1, 2, 2)
self.a = plt.imshow(self.Z2, cmap=plt.cm.viridis, alpha=.9, interpolation='bilinear',
extent=self.extent)
self.b = plt.imshow(self.Z1, cmap=plt.cm.gray, interpolation='nearest',
extent=self.extent)
self.canvas.draw()
plt.subplots_adjust(left=0.15, bottom=0.15)
slider_ax = plt.axes([0.06, 0.25, 0.0225, 0.5])
alfa_slider = Slider(slider_ax,
label="Transparency",
valmin=0,
valmax=1,
valinit=0,
orientation="vertical"
)
alfa_slider.on_changed(self.update_slider)
rax = plt.axes([0.06, 0.05, 0.15, 0.15])
radio = RadioButtons(rax, ('Reds', 'Greens', 'Blues', 'Oranges', 'Wistia', 'plasma', 'inferno'), active=0)
radio.on_clicked(self.update_radio)
self.canvas.draw()
def update_slider(self,alpha_):
self.b.set_alpha(alpha_)
self.canvas.draw()
def update_radio(self,label_):
self.b.set_cmap(label_)
self.canvas.draw()
def on_key_press(self,event,toolbar):
print("you pressed {}".format(event.key))
key_press_handler(event, self.canvas, toolbar)
def _quit(self):
self.master.quit() # stops mainloop
def switch_graphs(self):
# Need to call the correct draw, whether we're on graph one or two
self.graphIndex = (self.graphIndex + 1) % 2
if self.graphIndex == 0:
self.draw_graph_one()
else:
self.draw_graph_two()
def main():
root = Tk()
matplotlibSwitchGraphs(root)
root.mainloop()
if __name__ == '__main__':
main()
I tried to input update_slider and update_radio function inside of function, but than I cant use self.canvas.draw().
Also .remove() and .cla() doesn't clear the window.
Here is the view of the graphs I would like to switch between:
Answering your last question first, your big issue is that you are trying to use one figure to display two seperate graphs, without understanding how pyplot actually works. It is possible to do so, as I will outline below, but you lose any modifications you make to the graphs when you switch between them. I would recommend reading the working with multiple axes and figures section of the pyplot tutorial. The key takeaway as that in MATLAB and pyplot, all plotting functions are applied to the last figure and axes.
When you call self.draw_graph_two(), the last axes you create are the RadioButtons. Therefore, pyplot has these axes as the current axes. When you then call self.draw_graph_one() for the second time (the first time was when you intialised), it draws the plot on the current figure and current axes, where the RadioButtons are.
To solve this, call plt.clf() as the first line of draw_graph_one and draw_graph_two, before attempting to draw the new graph. This clears the figure, allowing for a new plot to be drawn from scratch (which is what your two draw functions do). This allows you to continuously switch between your two plots, although each time you switch the plot is cleared and any modifications to the plot are lost. You can also remove the self.ax.remove() lines, as they cause errors and are not needed.
For your first two questions, these can be answered by reading the documentation for the RadioButtons and Slider here. You must keep a reference to the widgets for them to remain responsive. So modifying your draw_graph_two to return alfa_slider and radio keeps these widgets responsive. Alternatively, declaring them as instance variables also keeps a reference (self.alfa_slider and self.radio).
So your working graph viewer is:
import matplotlib
import tkinter as tk
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.backends.backend_tkagg import (
FigureCanvasTkAgg, NavigationToolbar2Tk)
from matplotlib.backend_bases import key_press_handler
from matplotlib.widgets import Slider, RadioButtons
# Seperated out config of plot to just do it once
def config_plot():
fig, ax = plt.subplots()
ax.set(xlabel='time (s)', ylabel='voltage (mV)',
title='Graph One')
return (fig, ax)
class matplotlibSwitchGraphs:
def __init__(self, master):
self.master = master
self.frame = tk.Frame(self.master)
self.fig, self.ax = config_plot()
self.graphIndex = 0
self.canvas = FigureCanvasTkAgg(self.fig, self.master)
self.config_window()
self.plot_data()
self.draw_graph_one()
self.frame.pack(expand=True, fill=tk.BOTH)
def config_window(self):
self.canvas.mpl_connect("key_press_event", self.on_key_press)
toolbar = NavigationToolbar2Tk(self.canvas, self.master)
toolbar.update()
self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
self.button = tk.Button(self.master, text="Quit", command=self._quit)
self.button.pack(side=tk.BOTTOM)
self.button_switch = tk.Button(self.master, text="Switch Graphs", command=self.switch_graphs)
self.button_switch.pack(side=tk.BOTTOM)
def plot_data(self):
def func3(x, y):
return (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-(x ** 2 + y ** 2))
dx, dy = 0.05, 0.05
x = np.arange(-3.0, 3.0, dx)
y = np.arange(-3.0, 3.0, dy)
X, Y = np.meshgrid(x, y)
self.extent = np.min(x), np.max(x), np.min(y), np.max(y)
self.Z1 = np.add.outer(range(8), range(8)) % 2 # chessboard
self.Z2 = func3(X, Y)
def draw_graph_one(self):
plt.clf()
self.ax = plt.imshow(self.Z2, cmap=plt.cm.viridis, alpha=.9, interpolation='bilinear',
extent=self.extent)
self.canvas.draw()
def draw_graph_two(self):
plt.clf()
self.ax = plt.subplot(1, 2, 1)
self.ax = plt.imshow(self.Z1, cmap=plt.cm.gray, interpolation='nearest',
extent=self.extent)
self.ax = plt.subplot(1, 2, 2)
self.a = plt.imshow(self.Z2, cmap=plt.cm.viridis, alpha=.9, interpolation='bilinear',
extent=self.extent)
self.b = plt.imshow(self.Z1, cmap=plt.cm.gray, interpolation='nearest',
extent=self.extent)
self.canvas.draw()
plt.subplots_adjust(left=0.15, bottom=0.15)
slider_ax = plt.axes([0.06, 0.25, 0.0225, 0.5])
self.alfa_slider = Slider(slider_ax,
label="Transparency",
valmin=0,
valmax=1,
valinit=0,
orientation="vertical"
)
self.alfa_slider.on_changed(self.update_slider)
rax = plt.axes([0.06, 0.05, 0.15, 0.15])
self.radio = RadioButtons(rax, ('Reds', 'Greens', 'Blues', 'Oranges', 'Wistia', 'plasma', 'inferno'), active=0)
self.radio.on_clicked(self.update_radio)
self.canvas.draw()
def update_slider(self,alpha_):
self.b.set_alpha(1-alpha_)
self.canvas.draw()
def update_radio(self,label_):
self.b.set_cmap(label_)
self.canvas.draw()
def on_key_press(self,event,toolbar):
print("you pressed {}".format(event.key))
key_press_handler(event, self.canvas, toolbar)
def _quit(self):
self.master.quit() # stops mainloop
def switch_graphs(self):
# Need to call the correct draw, whether we're on graph one or two
self.graphIndex = (self.graphIndex + 1) % 2
if self.graphIndex == 0:
self.draw_graph_one()
else:
self.draw_graph_two()
def main():
root = tk.Tk()
matplotlibSwitchGraphs(root)
root.mainloop()
if __name__ == '__main__':
main()
Note I also made some other slight modifications. Don't use from tkinter import *, you had already imported it above and using import * is a bad habit. I reversed the slider so that the transparency makes sense. self.plot_data() is only called once in __init__ as it doesn't change.
I have the following code. The grid is visible without the Button widget. But when the grid is not shown if I add the button. What am I doing wrong?
from matplotlib import pyplot as plot
from matplotlib.widgets import Button
plot.plot([1,2,3], [1,2,3])
ax = plot.axes([0.5, 0.5, 0.05, 0.05])
Button(ax, "A")
plot.grid()
plot.show()
For me you code is working fine! (Except the button is in the middle of the screen)
Maybe you should try the following snippet:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Button
freqs = np.arange(2, 20, 3)
fig, ax = plt.subplots()
plt.subplots_adjust(bottom=0.2)
t = np.arange(0.0, 1.0, 0.001)
s = np.sin(2*np.pi*freqs[0]*t)
l, = plt.plot(t, s, lw=2)
class Index:
ind = 0
def next(self, event):
self.ind += 1
i = self.ind % len(freqs)
ydata = np.sin(2*np.pi*freqs[i]*t)
l.set_ydata(ydata)
plt.draw()
def prev(self, event):
self.ind -= 1
i = self.ind % len(freqs)
ydata = np.sin(2*np.pi*freqs[i]*t)
l.set_ydata(ydata)
plt.draw()
callback = Index()
axprev = plt.axes([0.7, 0.05, 0.1, 0.075])
axnext = plt.axes([0.81, 0.05, 0.1, 0.075])
bnext = Button(axnext, 'Next')
bnext.on_clicked(callback.next)
bprev = Button(axprev, 'Previous')
bprev.on_clicked(callback.prev)
plt.show()
To read more about matplotlib buttons read and see the snippet: https://matplotlib.org/stable/gallery/widgets/buttons.html
Also you might want to rename the button to have a bigger name like "TEST" to avoid problems regarding the size of the label.
The Button() instantiation changes the current axes. So when I call plot.grid() it is operated on Button axes. I changed the order of calling plot.grid() and it worked. I have shown the modified code below.
from matplotlib import pyplot as plot
from matplotlib.widgets import Button
plot.plot([1,2,3], [1,2,3])
# note grid() is called before Button
plot.grid()
ax = plot.axes([0.5, 0.5, 0.05, 0.05])
Button(ax, "A", hovercolor="red")
plot.show()
Hello I am using the RadioButtons widget form matplotlib library, in python.
RadioButtons is updates a plot, after clicking and selecting option. Obviously RadioButtons distinguishes in concordance with a dictionary you define.
I need to pull the "selected, chosen" field to plotted using RadioButtons, because I need to do some post-processing of that selected field.
def funcplot(label):
plotdict = {'TBF': TBF, 'TTR': TTR, 'MTBF': MTBF, 'MTTR': MTTR, 'Avail': Avail}
ydata = plotdict[label]
l.set_ydata(ydata)
plt.draw()
radio.on_clicked(funcplot)
I am trying to pull from here the selected field:
radio = RadioButtons(rax, ('TBF', 'TTR', 'MTBF', 'MTTR', 'Avail'))
Is it there any way to pull out ydata from the defined function?
Looking after your comments I salute everyone of you.-
Second part:
Thanks to the help the first part of the code is resumed as follows:
fig = plt.figure(figsize=(8, 6))
ax = fig.add_subplot(211, facecolor='gainsboro')
ax.set_title('Press left mouse button and drag to test')
l, = ax.plot(Time,TBF,'b-',label = 'TBF')
ax.set_ylabel('Valor')
plt.subplots_adjust(left=0.3)
axcolor = 'lightgoldenrodyellow'
rax = plt.axes([0.05, 0.7, 0.15, 0.15], facecolor=axcolor)
radio = RadioButtons(rax, ('TBF', 'TTR', 'MTBF', 'MTTR', 'Avail'))
plotdict = {'TBF': TBF, 'TTR': TTR, 'MTBF': MTBF, 'MTTR': MTTR, 'Avail': Avail}
def funcplot(label):
l.set_ydata(plotdict[label])
plt.draw()
radio.on_clicked(funcplot)
The selected field is stored as follows
label = radio.value_selected
y = plotdict[label]
What I wanted is to use y as entry for the SpannSelector called and defined as follows:
ax2 = fig.add_subplot(212, facecolor='gainsboro')
line2, = ax2.plot(x,y, 'bs-')
ax2.set_ylabel('Valor')
ax2.set_xlabel('Horas')
def onselect(xmin, xmax):
indmin, indmax = np.searchsorted(x, (xmin, xmax))
indmax = min(len(x) - 1, indmax)
thisx = x[indmin:indmax]
thisy = y[indmin:indmax]
line2.set_data(thisx, thisy)
ax2.set_xlim(thisx[0], thisx[-1])
ax2.set_ylim(thisy.min(), thisy.max())
fig.canvas.draw()
# set useblit True on gtkagg for enhanced performance
span = SpanSelector(ax, onselect, 'horizontal', useblit=True,
rectprops=dict(alpha=0.5, facecolor='red'))
The RadioButton selects the variable y, and the SpannSelector zooms the variable y. But when y changes due to clicks the SpannSelector remains as default
The currently selected label of a RadioButtons widget is stored in RadioButtons.value_selected. Hence you can access it at any point.
plotdict = {'TBF': TBF, 'TTR': TTR, 'MTBF': MTBF, 'MTTR': MTTR, 'Avail': Avail}
currentlabel = [None]
def funcplot(label):
l.set_ydata(plotdict[label])
currentlabel[0] = label
plt.draw()
radio.on_clicked(funcplot)
### later...
plt.plot(plotdict[currentlabel[0]])
I have a line generalisation algorithm and want to add a scroll bar to the plot that will increase the tolerance (i,e make the line more and more generalised). Using matplotlib how would this be possible?
So to sum up, I want to be able to click and drag a slider that will display the increase in the tolerances effect on the line.
Still really struggling with this. I only want one slider on a simple scale from 1-10.
yeah the demo helps, i'm just struggerling to get one slider to work, this is what I have so far,
fig = mp.figure()
ax = fig.add_subplot(111)
fig.subplots_adjust(left=0.25, bottom=0.25)
min0=1
max0=10
tolerance = 0
chain1 = ChainLoader('Wiggle1.txt')
chain = chain1[0]
chain2 = chain.generalise(tolerance)
axcolor = 'lightgoldenrodyellow'
axmin = fig.add_axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
axmax = fig.add_axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)
tolerance = Slider(axmin, 'Min', 1, 10, valinit=min0)
#smax = Slider(axmax, 'Max', 0, 30000, valinit=max0)
def update(val):
tolerance = tolerance.val
#pp.show()
tolerance.on_changed(update)
#smax.on_changed(update)
chain2 = chain.generalise(tolerance)
pp.plotPolylines(chain2)
pp.show()
My problems are how to write the def update section. Any help?
from PointPlotter import PointPlotter
from ChainHandler import ChainLoader
pp=PointPlotter()
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
ax = plt.subplot(111)
plt.subplots_adjust(left=0.25, bottom=0.25)
tolerance = 0
f0 = 0
chain2 = ChainLoader('Wiggle1.txt')
for chain in chain2:
chain2 = chain.generalise(tolerance)
pp.plotPolylines(chain2)
axcolor = 'lightgoldenrodyellow'
axtol = plt.axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
tolerance = Slider(axtol, 'tol', 0.1, 30.0, valinit=f0)
def update(val):
tolerance = tolerance.val
for chain in chain2:
chain2 = chain.generalise(tolerance)
pp.plotPolylines(chain2)
pp.plotPolylines(chain2)
tolerance.on_changed(update)
plt.show()
So close! Its now plotting, but returns "UnboundLocalError: local variable 'tolerance' referenced before assignment" when the scroll bar is used. #tcaswell any help?
You want the slider widget (doc).
Here is the demo from the examples:
http://matplotlib.org/examples/widgets/slider_demo.html
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons
ax = plt.subplot(111)
plt.subplots_adjust(left=0.25, bottom=0.25)
t = np.arange(0.0, 1.0, 0.001)
a0 = 5
f0 = 3
s = a0*np.sin(2*np.pi*f0*t)
l, = plt.plot(t,s, lw=2, color='red')
plt.axis([0, 1, -10, 10])
axcolor = 'lightgoldenrodyellow'
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
axamp = plt.axes([0.25, 0.15, 0.65, 0.03], facecolor=axcolor)
sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0)
samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)
def update(val):
amp = samp.val
freq = sfreq.val
l.set_ydata(amp*np.sin(2*np.pi*freq*t))
plt.draw()
sfreq.on_changed(update)
samp.on_changed(update)
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
sfreq.reset()
samp.reset()
button.on_clicked(reset)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], facecolor=axcolor)
radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
def colorfunc(label):
l.set_color(label)
plt.draw()
radio.on_clicked(colorfunc)
plt.show()
To adapt this to your case:
#smax.on_changed(update)
chain2 = chain.generalise(tol)
pp.plotPolylines(chain2)
def update(val):
tol = tolerance.val # get the value from the slider
chain2 = chain.generalise(tol) # shove that value into your code
ax.cla() # clear the axes
pp.plotPolylines(chain2) # re-plot your new results
# register the call back
tolerance.on_changed(update)
Be careful about re-using variable names (you use tolerance twice, once for a float and once for the Slider and python will happily clobber your old variables with new ones of an entirely different type).
In update I went with the most brute-force approach, clearing the axes and then re-drawing it, in general you want to grab the artists that are returned by plotPolylines and update those with your new data. (If you need help with that step, open a new question with details about your data structure).
The way to understand .on_changed is that when the slider notices it has been changed, it will call the function you passed in (update) with a single argument (val) which is the current value of the slider. Inside that function you can do what ever you want, and it will be executed in full every time the slider is changed.