Plotting with matplotlib
matplotlib
?le:///home/kaustubh/Temp/matplotlib.html
Plotting with matplotlib
Yogesh Wadadekar
NCRA-TIFR, Pune
thanks to Varun Bhalerao for several slides used here.
Plotting with Python
ppgplot
sm
gnuplot
R
Matlab
Mathematica
IDL
Octave
Matplotlib - the standard plotting library for
Python
Matplotlib has very powerful plotting facilities. So before we start with the details, let us take a look at
() . It is a showcase of the capabilities of
Matplotlib: starting from very simple graphs, to far more complicated ones.
Let's get started!
Matplotlib commands are nearly identical to Matlab commands. So, if you know Matlab, you won't have to
learn much. For basic plotting, it is easiest to use pylab. You can start it from the command line by issuing
the command,
ipython --pylab
Or, if you already have an iPython session open, you can give the command,
%pylab or %pylab inline
Remember in a real program, you would never import a module namespace into a global namespace.
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matplotlib
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In [21]: %pylab inline
Populating the interactive namespace from numpy and matplotlib
WARNING: pylab import has clobbered these variables: ['f']
`%pylab --no-import-all` prevents importing * from pylab and numpy
In [22]: # Generate some test data
x = np.arange(0, 6.28, 0.01)
y = np.sin(x)
Now we plot y versus x
In [23]: plot(x, y)
Out[23]: []
Adding Labels
That was simple: we have plotted y as a function of x. Now let us add labels:
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In [24]: plot(x, y)
plt.xlabel("theta (angle in radians)")
plt.ylabel('sin(theta)')
plt.title("This is my first plot")
Out[24]:
Fancier labels:
In [25]: plot(x, y)
xlab = plt.xlabel(r"$\theta$ (angle in radians)") # note the r before q
uotes
ylab = plt.ylabel(r'sin($\theta$)')
thetitle= plt.title("This is is a nicer plot")
thetitle.set_fontweight('bold')
ylab.set_color('blue')
xlab.set_color('red')
xlab.set_style('italic')
More examples at [ (
/examples/pylab_examples/fonts_demo.html)]
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Axis Range and scale
In [26]: another_x = x+1
plot(another_x,another_x**4)
plt.title('X**4 versus X')
Out[26]:
In [27]: # Let's make it look a bit better
plot(another_x,another_x**4)
plt.title(r'X$^4$ versus X') # The $ signs are for latex inputs
plt.xlim(min(another_x), max(another_x))
plt.yscale('log')
plt.show()
Overplot
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In [28]: plot(x, y)
plot(x, np.cos(x))
Out[28]: []
Styles, symbols and colours
In [29]: plot(x, y)
x_spaced = np.arange(0, 2.0*np.pi, 0.3)
plot(x_spaced, np.sin(x_spaced), marker='o', color='red', linestyle='No
ne')
plot(x_spaced, np.cos(x_spaced), 'b+')
Out[29]: []
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