.. code:: python

    # this ipython magic command imports pylab and allows the plots to reside within the notebook
    %pylab inline


.. parsed-literal::

    Populating the interactive namespace from numpy and matplotlib


The following examples are based on Florian Lhuillier's lecture on
Matlab which can be found online:

http://geophysik.uni-muenchen.de/~lhuillier/teaching/AD2010/

Pylab continued ...
===================

Examples based on "... des données sous MATLAB"
-----------------------------------------------

.. code:: python

    set_printoptions(precision=2, suppress=True)

Excercise 1
~~~~~~~~~~~

.. code:: python

    aa = loadtxt('dipole_ref.txt')

.. code:: python

    aa.shape




.. parsed-literal::

    (21481, 3)



.. code:: python

    subplot(211)
    plot(aa[:,0], aa[:,1])
    xlabel("test1")
    subplot(212)
    plot(aa[:,0], aa[:,2])
    xlabel('TEST2')
    subplots_adjust(hspace=.5)



.. image:: 4_pylab_files/4_pylab_6_0.png


Excercise 2
~~~~~~~~~~~

.. code:: python

    aa = loadtxt('dipole_ref.txt')

.. code:: python

    bb = loadtxt('dipole_pert.txt')

.. code:: python

    t = bb[:,0]; 

.. code:: python

    d = bb[:,2] - interp(t, aa[:,0],aa[:,2]);

.. code:: python

    semilogy(t, abs(d))




.. parsed-literal::

    [<matplotlib.lines.Line2D at 0x7f911be2add8>]




.. image:: 4_pylab_files/4_pylab_12_1.png


Excercise 3
~~~~~~~~~~~

.. code:: python

    d = genfromtxt('spectre.txt', skip_header=1, dtype=None, names=('name', 'number', 'amplitude'))

.. code:: python

    d




.. parsed-literal::

    array([(b'a', 1, 9.5960921), (b'b', 2, 9.4450301), (b'c', 3, 7.5000147),
           (b'd', 4, 6.7446755), (b'e', 5, 4.7442346), (b'f', 6, 4.3416987),
           (b'g', 7, 2.9904522), (b'h', 8, 2.3769902), (b'i', 9, 1.8908512),
           (b'j', 10, 1.3387981), (b'k', 11, 1.0044059),
           (b'l', 12, 0.79748122), (b'm', 13, 0.5872564),
           (b'n', 14, 0.48502449), (b'p', 15, 0.34799267),
           (b'q', 16, 0.28167023), (b'r', 17, 0.20974501),
           (b's', 18, 0.16570928), (b't', 19, 0.12762576),
           (b'u', 20, 0.098378887)], 
          dtype=[('name', 'S1'), ('number', '<i8'), ('amplitude', '<f8')])



.. code:: python

    Y=log(d['amplitude']); Y




.. parsed-literal::

    array([ 2.26,  2.25,  2.01,  1.91,  1.56,  1.47,  1.1 ,  0.87,  0.64,
            0.29,  0.  , -0.23, -0.53, -0.72, -1.06, -1.27, -1.56, -1.8 ,
           -2.06, -2.32])



.. code:: python

    X = array((d['number'], 0*d['number']+1)).T; X




.. parsed-literal::

    array([[ 1,  1],
           [ 2,  1],
           [ 3,  1],
           [ 4,  1],
           [ 5,  1],
           [ 6,  1],
           [ 7,  1],
           [ 8,  1],
           [ 9,  1],
           [10,  1],
           [11,  1],
           [12,  1],
           [13,  1],
           [14,  1],
           [15,  1],
           [16,  1],
           [17,  1],
           [18,  1],
           [19,  1],
           [20,  1]])



.. code:: python

    X.shape, Y.shape




.. parsed-literal::

    ((20, 2), (20,))



.. code:: python

    A = lstsq(X, Y)[0]; A




.. parsed-literal::

    array([-0.25,  2.82])



.. code:: python

    subplot(211)
    plot(d['number'], d['amplitude'])
    subplot(212)
    semilogy(d['number'], d['amplitude'], 'o')
    semilogy(d['number'], exp(X.dot(A)))




.. parsed-literal::

    [<matplotlib.lines.Line2D at 0x7f9119b37ac8>]




.. image:: 4_pylab_files/4_pylab_20_1.png


Excercise 4
~~~~~~~~~~~

.. code:: python

    aa = loadtxt('anomalie.txt')

.. code:: python

    nx = len( unique(aa[:,0])); nx




.. parsed-literal::

    21



.. code:: python

    ny = len( unique(aa[:,1])); ny




.. parsed-literal::

    11



.. code:: python

    X=aa[:,0].reshape((nx, ny)); 

.. code:: python

    Y=aa[:,1].reshape((nx, ny)); 

.. code:: python

    data = aa[:,2].reshape((nx, ny));

.. code:: python

    pcolor( X, Y, data)




.. parsed-literal::

    <matplotlib.collections.PolyCollection at 0x7f9119cbe278>




.. image:: 4_pylab_files/4_pylab_28_1.png


.. code:: python

    imshow(data.T,  
               extent=[X.min(), X.max(), Y.min(), Y.max()],
               interpolation='gaussian', origin='lower')
    colorbar()




.. parsed-literal::

    <matplotlib.colorbar.Colorbar at 0x7f9119b30ef0>




.. image:: 4_pylab_files/4_pylab_29_1.png


.. code:: python

    contourf( X, Y, data)
    colorbar()




.. parsed-literal::

    <matplotlib.colorbar.Colorbar at 0x7f9119d93470>




.. image:: 4_pylab_files/4_pylab_30_1.png


.. code:: python

    from scipy.ndimage import zoom

.. code:: python

    data = array(zoom(data,3)).T

.. code:: python

    contourf(data, extent=[X.min(), X.max(), Y.min(), Y.max()])
    colorbar()
    #axis("equal")




.. parsed-literal::

    <matplotlib.colorbar.Colorbar at 0x7f9116fb7be0>




.. image:: 4_pylab_files/4_pylab_33_1.png


.. code:: python

    imshow(data,  
               extent=[X.min(), X.max(), Y.min(), Y.max()],
               interpolation='gaussian', origin='lower', aspect=1)
    colorbar()




.. parsed-literal::

    <matplotlib.colorbar.Colorbar at 0x7f9116ef5240>




.. image:: 4_pylab_files/4_pylab_34_1.png