Skip to main content

Matplotlib in Django

The official django tutorial is very good, it stops short of displaying
data with matplotlib - which could be very handy for dsp or automated
testing. This is an extension to the tutorial. So first you must do the
official tutorial!
Complete the tutorial (as of writing this up to part 4).

Adding an image to a view

To start with we will take a static image from the hard drive and
display it on the polls index page.
Usually if it really is a static image this would be managed by the
webserver eg apache. For introduction purposes we will get django to
serve the static image. To do this we first need to change the
template.



Change the template


At the moment poll_list.html probably looks something like this:


<h1>Django test app - Polls</h1>
{% if object_list %}

<ul>
{% for object in object_list %}
<li><a href="/polls/{{object.id}}">{{ object.question }}</a></li>

{% endfor %}
</ul>
{% else %}

<p>No polls are available.</p>
{% endif %}

Change it by adding the line anywhere outside of the special "{% template tags %}"



<img src="/polls/staticImage.png" width="500px">


Now if you reload your page - you should see a placeholder
image, or nothing. If you view the source in your browser you should
see the extra line we added. If we try to view just the image, eg going
to [1] we should see a django 404 (page not found error).



Add the url for the static image into the url handler



Now we must add a line in the urls.py file to link the image with a view:
It should end up looking something like the following:


from django.conf.urls.defaults import *
from mysite.polls.models import Poll


info_dict = {
'queryset': Poll.objects.all()
}

urlpatterns = patterns('',
(r'^$', 'django.views.generic.list_detail.object_list',info_dict),
(r'^(?P<object_id>\d+)/$', 'django.views.generic.list_detail.object_detail',info_dict),
url(r'^(?P<object_id>\d+)/results/$', 'django.views.generic.list_detail.object_detail',dict(info_dict,template_name="polls/results.html"),'poll_results'),
(r'^(?P<poll_id>\d+)/vote/$', 'mysite.polls.views.vote'),
(r'^staticImage.png$', 'mysite.polls.views.showStaticImage'),

)

This means we have to make a view called showStaticImage.



Add the view for the static image


Add a function to the views.py file as follows - replace the path with your own


def showStaticImage(request):
""" Simply return a static image as a png """

imagePath = "C:/Documents and Settings/thorneb/My Documents/Fiordland_Lake_Marian.png"
from PIL import Image
Image.init()
i = Image.open(imagePath)

response = HttpResponse(mimetype='image/png')
i.save(response,'PNG')
return response


This point it is worth noting we have imported PIL the python image library - it is not always included by default.

Now if you try reload your poll index page - you should see whatever image you choose.








Adding a dynamic image


Thats all well and good but we want to plot data, dynamically generated based on changing data.
Keeping going with the polls app - lets plot the results automatically - so the results page shows a graph.


  • Add an image tag somewhere in the results template:

    <img src="result.png">


  • Add another url clause:

    (r'^(?P<poll_id>\d+)/results/result.png$', 'mysite.polls.views.plotResults')

  • Add another new view:

def plotResults(request,poll_id):
import matplotlib
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib.dates import DateFormatter
fig = Figure()

ax=fig.add_subplot(1,1,1)
p = get_object_or_404(Poll, pk=poll_id) # Get the poll object from django

x = matplotlib.numpy.arange(1,p.choice_set.count())
choices = p.choice_set.all()

votes = [choice.votes for choice in choices]
names = [choice.choice for choice in choices]


numTests = p.choice_set.count()
ind = matplotlib.numpy.arange(numTests) # the x locations for the groups

cols = ['red','orange','yellow','green','blue','purple','indigo']*10

cols = cols[0:len(ind)]
ax.bar(ind, votes,color=cols)


ax.set_xticks(ind + 0.5)
ax.set_xticklabels(names)


ax.set_xlabel("Choices")
ax.set_ylabel("Votes")

#ax.set_xticklabels(names)

title = u"Dynamically Generated Results Plot for poll: %s" % p.question
ax.set_title(title)


#ax.grid(True)
canvas = FigureCanvas(fig)
response = HttpResponse(content_type='image/png')

canvas.print_png(response)
return response

I may have fabricated these votes :-P


Hmm, sorry for the formating of this post - I'll try get back to it if I can find the original wiki page I made while at Tait.

Links

Official Django Site

Comments

  1. Hmm. Can't seem to get this to print properly (FF3.5 on Ubuntu 8.10)?

    ReplyDelete
  2. THis isn't working,dn't try it.

    ReplyDelete
  3. Thanks for the feedback, it was quite a while ago - I think django has released a few versions since then! I believe the matplotlib site has a recipe for this now.

    ReplyDelete
  4. Even though the full code example may not work, thank you still for the post. I was originally not considering that I would need one view for the html page and another view for the image alone. It works perfectly now that I've separated into two views.

    ReplyDelete
  5. Thanks for your post it was very helpful!

    ReplyDelete
  6. 3 years later and it worked great for me. The Python tutorials have changed a bit but this is my first time using Python and this was still simple enough that some copy and paste, a hack here and there and I'm left with a graph of my voting results. Now I just need to go back through to understand what I actually did. :D

    Thanks!

    ReplyDelete
  7. Thanks for the feedback! If you let me know what you had to hack I'll update this post!

    ReplyDelete

Post a Comment

Popular posts from this blog

Homomorphic encryption using RSA

I recently had cause to briefly look into Homomorphic Encryption, the process of carrying out computations on encrypted data. This technique allows for privacy preserving computation. Fully homomorphic encryption (FHE) allows both addition and multiplication, but is (currently) impractically slow.

Partially homomorphic encryption just has to meet one of these criteria and can be much more efficient.
An unintended, but well-known, malleability in the common RSA algorithm means that the multiplication of ciphertexts is equal to the multiplication of the original messages. So unpadded RSA is a partially homomorphic encryption system.

RSA is beautiful in how simple it is. See wikipedia to see how to generate the public (e, m) and private keys (d, m).

Given a message x it is encrypted with the public keys it to get the ciphertext C(x)with:

C(x)=xemodm
To decrypt a ciphertext

Bluetooth with Python 3.3

Since about version 3.3 Python supports Bluetooth sockets natively. To put this to the test I got hold of an iRacer from sparkfun. To send to New Zealand the cost was $60. The toy has an on-board Bluetooth radio that supports the RFCOMM transport protocol.



The drive protocol is dead easy, you send single byte instructions when a direction or speed change is required. The bytes are broken into two nibbles: 0xXY where X is the direction and Y is the speed. For example the byte 0x16 means forwards at mid-speed. I was surprised to note the car continues carrying out the last given demand!

I let pairing get dealt with by the operating system. The code to create a Car object that is drivable over Bluetooth is very straight forward in pure Python:

importsocketimporttimeclassBluetoothCar:def__init__(self,mac_address="00:12:05:09:98:36"):self.socket=socket.socket(socket.AF_BLUETOOTH,socket.SOCK_STREAM,socket.BTPROTO_RFCOMM)self.socket.connect((mac_address,1))def_write(self,data_byte):…