Pack an Enthought Traits app inside a .exe using py2exe (Canopy Edit)

10 months ago, I published the updated version of my tutorial to pack an Enthought TraitsUI based application inside an .exe Windows Executable file, using a standard Python 2.7 install and the Enthought Tool Suite 4.0 (ETS4.0). In April 2013, Enthought published their latest distribution called “Canopy”. This distribution marks a clear change in the…

New Tutorial Series: Pandas

In the coming months, I’ll prepare some tutorials over an excellent data analysis package called pandas ! To show you the power of pandas, just take a look at this old tutorial, where I exploited the power of itertools to group sparse data into 5 seconds bins. The magic of pandas is that, when you…

Matplotlib & Datetimes – Tutorial 02: Bar Plot

To add some interesting information to the previous tutorial, I’ve downloaded the number of licence plates given for new cars in Belgium for the same time span: 2005 587764 2006 633570 2007 644313 2008 652590 2009 571001 2010 642086 2011 679619 Load them in the same fashion: plates, number = np.loadtxt(‘newplates.txt’,skiprows=1,unpack=True) xdates2 = [datetime.datetime.strptime(str(int(date)),’%Y’) for…

Matplotlib Basemap tutorial 09: Drawing circles

In the previous tutorial, I defined a “shoot” method to compute the landing point of a shoot from one point, to a given azimuth and distance. Using this logic, it’s possible to find the points situated at a given distance from a “centre” point, a circle. The goal: Drawing circles of a given radius around…

Matplotlib Basemap: Tell me what you need !

Dear visitors, I’m always searching new ideas of preparing new tutorials for things doable with Basemap, but I’d like these examples to be as useful as possible, which means : If you have something you would like to appear here, please, use the Comment box below to tell me ! I’ll do my best to…

Matplotlib Basemap tutorial 03 : Masked arrays & Zoom

Here, we will focus on adding a “zoom box” on the top left corner of the plot. But before that, we will mask a part of the earthquakes, in order to have a “cleaner” map ! This is achieved by using the numpy.ma module : import numpy.ma as ma Mlon = ma.masked_outside(lon, 5.6, 7.5) #…

Matplotlib Basemap tutorial 02 : Let’s add some earthquakes !

Now, let’s imagine we have a dataset containing latitude/longitudes of earthquakes, plus their depth and magnitude. Of course, you don’t always have this dataset available, so let’s build a fake one : import numpy as np lon = np.random.random_integers(11,79,1000)/10. lat = np.random.random_integers(491,519,1000)/10. depth = np.random.random_integers(0,300,1000)/10. magnitude = np.random.random_integers(0,100,1000)/10. We create random integer values, and we…

Matplotlib Basemap tutorial 01 : Your first map

# # BaseMap example by geophysique.be # tutorial 01 from mpl_toolkits.basemap import Basemap import matplotlib.pyplot as plt import numpy as np fig = plt.figure(figsize=(11.7,8.3)) #Custom adjust of the subplots plt.subplots_adjust(left=0.05,right=0.95,top=0.90,bottom=0.05,wspace=0.15,hspace=0.05) ax = plt.subplot(111) #Let’s create a basemap around Belgium m = Basemap(resolution=’i’,projection=’merc’, llcrnrlat=49.0,urcrnrlat=52.0,llcrnrlon=1.,urcrnrlon=8.0,lat_ts=51.0) m.drawcountries(linewidth=0.5) m.drawcoastlines(linewidth=0.5) m.drawparallels(np.arange(49.,53.,1.),labels=[1,0,0,0],color=’black’,dashes=[1,0],labelstyle=’+/-‘,linewidth=0.2) # draw parallels m.drawmeridians(np.arange(1.,9.,1.),labels=[0,0,0,1],color=’black’,dashes=[1,0],labelstyle=’+/-‘,linewidth=0.2) # draw meridians plt.show()