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Home > Data > Data Visualization > Interactive Applications using Matplotlib
Interactive Applications using Matplotlib
Interactive Applications using Matplotlib

Interactive Applications using Matplotlib:

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Interactive Applications using Matplotlib

Chapter 2. Using Events and Callbacks

 

Wait time is the worst

I can hardly sit

No one has the time

Someone is always late

 
 --The Strokes, Call Me Back (2011)

The callback system in Matplotlib is central to its interactivity. Unless you are working with the interactive plotting mode on, execution of the script stops when plt.show() is called. Without the ability to execute any additional code, the only way to program interactivity is to register actions to be taken upon some event such as a button click, mouse cursor motion, or key press. Matplotlib's callback system has a base set of events and many callbacks that we have already discussed, such as the default keymap discussed in the previous chapter and the ability to pan a plot. Furthermore, it is possible to add new kinds of events, giving the developer full access to Matplotlib's cross-platform callback system.

Making the connection

The callback system is figure-oriented. Any GUI action that can trigger a callback can only happen to whichever figure window is currently in focus. There are no global actions that can trigger callbacks across multiple figures. The callback function will get an Event object that contains pertinent information about the fired event. In the following example, we will hook up two events to a figure: a keyboard button press and a mouse button press. There are two callback functions, each printing out some of the available pieces of information for their respective events:

Code: chp2/basic_mpl_connect.py 

from __future__ import print_function 
import matplotlib.pyplot as plt 

def process_key(event): 
    print("Key:", event.key) 
def process_button(event): 
    print("Button:", event.x, event.y, event.xdata, event.ydata, event.button) 

fig, ax = plt.subplots(1, 1) 
fig.canvas.mpl_connect('key_press_event', process_key) 
fig.canvas.mpl_connect...

The big event

What is the purpose of interactive plotting? Why is it important for Matplotlib to provide this feature? It is important because you want to interact with your data. What you plot in the figure is a visual representation of your data, and giving it interactivity brings that data an extra step closer to the real world by providing your users the means to interact with that data in a more physically intuitive manner. It is all about data exploration.

So far, for our project, we have only developed the means to display our storm and radar data. While we could simply use these viewers and then manually edit the associated shapefile, it would not be practical. We should be able to provide users the means to interrogate their data. To do this, we will use pick_event to add the ability to select and deselect some tracks. As a simple example, we will make a track thicker when it is selected and make it thinner when it is deselected (or simply, selected again). Let's build upon...

Breaking up is the easiest thing to do

Try the previous radar example again. This time, go forward a few frames and then zoom in with the zoom tool. Now go back a frame.

Go ahead, I'll wait.

Surprised? Remember that Matplotlib has its own built-in keymap. In the default keymap, the left arrow means to go back to a previous view. When we zoomed in and then pressed the left arrow key, not only did we go back a frame via our callback, but we also went back to the original view prior to zooming via Matplotlib's default keymap. The default keymap is a very important and useful feature for providing basic interactivity for most users. However, when developing your own application using Matplotlib, you might want to disable Matplotlib's keymap entirely. The following example shows how to do that while demonstrating the next important feature of the callback system: disconnecting a callback. In this example, you can now press any non-system key or combination of keys without ever triggering...

Keymapping

We can see that our application is going to grow in complexity very soon add we continue to add features. Our current manner of keymapping is probably not going to be easily maintainable as the number of actions increase. Let's take a moment to implement something better. The most essential feature of a keymap is to tie a predefined action to an arbitrary key or key combination. This seems like the perfect job for a dictionary. Furthermore, as the keymap grows, it will become important to be able to display the keymap in a helpful manner to your users. Each key/action pair will need to come with a description that can later be displayed on demand. Also, keeping in mind that our ControlSys class is likely to grow in complexity soon, let's implement this keymap feature as a separate class that ControlSys will inherit. The code is as follows:

Source: chp2/stormcell_anim_with_keymap.py 

class KeymapControl:
    def __init__(self, fig):
        self.fig = fig
        # Deactivate...

Picking

We demonstrated pick events earlier, showing how to select a storm track, changing its thickness, but we haven't incorporated picking into our current design yet. Much in the same vein as the KeymapControl class, let's create a PickControl class that will keep a list of pick functions (pickers) and manage their connection to the callback system for us:

Source: chp2/select_stormcells.py 

class PickControl:
    def __init__(self, fig):
        self.fig = fig
        self._pickers = []
        self._pickcids = []

    def connect_picks(self):
        for i, picker in enumerate(self._pickers):
            if self._pickcids[i] is None:
                cid = self.fig.canvas.mpl_connect('pick_event', picker)
                self._pickcids[i] = cid

    def disconnect_picks(self):
        for i, cid in enumerate(self._pickcids):
            if cid is not None:
                self.fig.canvas.mpl_disconnect(cid)
                self._pickcids[i] = None

    def add_pick_action...

Making the connection

The callback system is figure-oriented. Any GUI action that can trigger a callback can only happen to whichever figure window is currently in focus. There are no global actions that can trigger callbacks across multiple figures. The callback function will get an Event object that contains pertinent information about the fired event. In the following example, we will hook up two events to a figure: a keyboard button press and a mouse button press. There are two callback functions, each printing out some of the available pieces of information for their respective events:

Code: chp2/basic_mpl_connect.py 

from __future__ import print_function 
import matplotlib.pyplot as plt 

def process_key(event): 
    print("Key:", event.key) 
def process_button(event): 
    print("Button:", event.x, event.y, event.xdata, event.ydata, event.button) 

fig, ax = plt.subplots(1, 1) 
fig.canvas.mpl_connect('key_press_event', process_key) 
fig.canvas.mpl_connect('button_press_event', process_button...

The big event

What is the purpose of interactive plotting? Why is it important for Matplotlib to provide this feature? It is important because you want to interact with your data. What you plot in the figure is a visual representation of your data, and giving it interactivity brings that data an extra step closer to the real world by providing your users the means to interact with that data in a more physically intuitive manner. It is all about data exploration.

So far, for our project, we have only developed the means to display our storm and radar data. While we could simply use these viewers and then manually edit the associated shapefile, it would not be practical. We should be able to provide users the means to interrogate their data. To do this, we will use pick_event to add the ability to select and deselect some tracks. As a simple example, we will make a track thicker when it is selected and make it thinner when it is deselected (or simply, selected again). Let's build upon the track...

Breaking up is the easiest thing to do

Try the previous radar example again. This time, go forward a few frames and then zoom in with the zoom tool. Now go back a frame.

Go ahead, I'll wait.

Surprised? Remember that Matplotlib has its own built-in keymap. In the default keymap, the left arrow means to go back to a previous view. When we zoomed in and then pressed the left arrow key, not only did we go back a frame via our callback, but we also went back to the original view prior to zooming via Matplotlib's default keymap. The default keymap is a very important and useful feature for providing basic interactivity for most users. However, when developing your own application using Matplotlib, you might want to disable Matplotlib's keymap entirely. The following example shows how to do that while demonstrating the next important feature of the callback system: disconnecting a callback. In this example, you can now press any non-system key or combination of keys without ever triggering a built...

Keymapping

We can see that our application is going to grow in complexity very soon add we continue to add features. Our current manner of keymapping is probably not going to be easily maintainable as the number of actions increase. Let's take a moment to implement something better. The most essential feature of a keymap is to tie a predefined action to an arbitrary key or key combination. This seems like the perfect job for a dictionary. Furthermore, as the keymap grows, it will become important to be able to display the keymap in a helpful manner to your users. Each key/action pair will need to come with a description that can later be displayed on demand. Also, keeping in mind that our ControlSys class is likely to grow in complexity soon, let's implement this keymap feature as a separate class that ControlSys will inherit. The code is as follows:

Source: chp2/stormcell_anim_with_keymap.py 

class KeymapControl:
    def __init__(self, fig):
        self.fig = fig
        # Deactivate the...
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Description

This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.

Who is this book for?

This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.
Estimated delivery fee Deliver to Philippines

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Publication date : Mar 24, 2015
Length: 174 pages
Edition : 1st
Language : English
ISBN-13 : 9781783988846
Category :
Data
Languages :
Python
Concepts :
Data Visualization
Tools :
Matplotlib

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Product Details

Publication date : Mar 24, 2015
Length: 174 pages
Edition : 1st
Language : English
ISBN-13 : 9781783988846
Category :
Data
Languages :
Python
Concepts :
Data Visualization
Tools :
Matplotlib

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Mastering Matplotlib
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Interactive Applications using Matplotlib
Interactive Applications using Matplotlib
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Table of Contents

6 Chapters
1. Introducing Interactive Plotting Chevron down icon Chevron up icon
1. Introducing Interactive Plotting
Installing Matplotlib
Show() your work
Interactive navigation
Interactive plotting
Scripted plotting
Getting help
From front to backend
The Matplotlib figure-artist hierarchy
Summary
2. Using Events and Callbacks Chevron down icon Chevron up icon
2. Using Events and Callbacks
Making the connection
The big event
Breaking up is the easiest thing to do
Keymapping
Picking
Data editing
User events
Editor events
Summary
3. Animations Chevron down icon Chevron up icon
3. Animations
A short history
The fastest draw in the west
The animation module
Advanced animations
Saving animations
Summary
4. Widgets Chevron down icon Chevron up icon
4. Widgets
Built-in widgets
Third-party tools
Summary
5. Embedding Matplotlib Chevron down icon Chevron up icon
5. Embedding Matplotlib
The revelation
Through a glass, darkly
Bars, menus, and sliders – four ways
Matplotlib in your app
Summary
Index Chevron down icon Chevron up icon
Index

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Full star icon Full star icon Full star icon Half star icon Empty star icon 3.3
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Sanjay Mishra Dec 30, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
If you need to quickly produce graphs and charts and explore data, this is the book for you.You could possibly get the same information from user manuals, blog posts and such like given enough time, but this book makes it easy to grasp the information and be quickly productive.
Amazon Verified review Amazon
Juan Nunez-Iglesias Apr 03, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I highly recommend Ben's book. I fumbled around for a long time with minor interactive matplotlib features. Then I read his book and it completely clarified my mental model of mpl interactivity and, indeed, of GUIs in general.Here's an excerpt that describes my story quite well:"""Indeed, given that the primary audience for Matplotlib is scientific programmers for whom GUIs are, at best, an afterthought, Matplotlib provides a gradual curve to create full-fledged GUI applications. For simple GUI tasks, one can go quite far with Matplotlib without ever having to adopt a GUI platform. And, as we will see in the next chapter, taking those final steps into a GUI application would not require getting rid of any existing code."""If you're a scientist looking to add a bit of interactivity to your data, or to move from a purely command-line interface to providing some graphical interactivity and control, this is a fantastic book to start with. Even if you end up using some newer frameworks such as Bokeh, the ideas in this book about GUI loops and callbacks will be useful forever.
Amazon Verified review Amazon
Dr. Andrew G. Meigs Feb 04, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good book, but a bit short. Nice tidbits throughout.
Amazon Verified review Amazon
Phu ta Feb 18, 2016
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
I think the overall content is okay, good for beginners who want to learned to develop interactive Python app. Keep in mind that specifically builds up a weather application in Matplotlib. So depend on your interest, it may or may not be helpful.
Amazon Verified review Amazon
Philip H Sep 15, 2018
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
A few pages on plotting; the rest of the book is junk. I would ask for my money back if I could!
Amazon Verified review Amazon

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How do I know my custom duty charges? Chevron down icon Chevron up icon

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

  • If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
  • Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.
How can I cancel my order? Chevron down icon Chevron up icon

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy? Chevron down icon Chevron up icon

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

  1. If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
  2. Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
  3. You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
  4. Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
  5. If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
  6. Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged? Chevron down icon Chevron up icon

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use? Chevron down icon Chevron up icon

You can pay with the following card types:

  1. Visa Debit
  2. Visa Credit
  3. MasterCard
  4. PayPal
What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela