from IPython.core.display import Image 
Image(filename='logo.png', width=600) 

def sum_of_squares(a):
    return np.sum(a**2)

foo = np.array([1, 3, 5])
sum_of_squares(foo)

print Out[3] + 4

# With the --pylab inline option, matplotlib plots are inline as cell output
w = np.linspace(0, 4*pi, 1000)
plt.plot(w, np.sin(w))

import scipy.signal

scipy.signal.fi

help(scipy.signal.firwin)

# %timeit runs a single line a bunch of times and reports the average run time
%timeit np.arange(1000)
%timeit xrange(1000)

%%prun
# prun runs Python's profiler on the current cell
N = 1e5
scipy.signal.fftconvolve(np.random.rand(N), np.random.rand(N))

# Not a magic, but IPython also allows for running shell commands
!ls -lh

# The Python-Matlab bridge can be used as a magic
import pymatbridge as pymat
ip = get_ipython()
pymat.load_ipython_extension(ip)

# Python variable - a filter cutoff
Wn = .2

%%matlab -i Wn -o b
b = fir1(30, Wn);

import scipy.signal
w, h = scipy.signal.freqz(b);
plt.plot(w, np.abs(h))