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% FIR filter design with Python and SciPy
% Matti Pastell
% 15th April 2013
# Introduction
This an example of a script that can be published using
[Pweave](http://mpastell.com/pweave). The script can be executed
normally using Python or published to HTML with Pweave
Text is written in markdown in lines starting with "`#'` " and code
is executed and results are included in the published document.
The concept is similar to
publishing documents with [MATLAB](http://mathworks.com) or using
stitch with [Knitr](http://http://yihui.name/knitr/demo/stitch/).
```python
from pylab import *
import scipy.signal as signal
#Plot frequency and phase response
def mfreqz(b,a=1):
w,h = signal.freqz(b,a)
h_dB = 20 * log10 (abs(h))
subplot(211)
plot(w/max(w),h_dB)
ylim(-150, 5)
ylabel('Magnitude (db)')
xlabel(r'Normalized Frequency (x$\pi$rad/sample)')
title(r'Frequency response')
subplot(212)
h_Phase = unwrap(arctan2(imag(h),real(h)))
plot(w/max(w),h_Phase)
ylabel('Phase (radians)')
xlabel(r'Normalized Frequency (x$\pi$rad/sample)')
title(r'Phase response')
subplots_adjust(hspace=0.5)
#Plot step and impulse response
def impz(b,a=1):
l = len(b)
impulse = repeat(0.,l); impulse[0] =1.
x = arange(0,l)
response = signal.lfilter(b,a,impulse)
subplot(211)
stem(x, response)
ylabel('Amplitude')
xlabel(r'n (samples)')
title(r'Impulse response')
subplot(212)
step = cumsum(response)
stem(x, step)
ylabel('Amplitude')
xlabel(r'n (samples)')
title(r'Step response')
subplots_adjust(hspace=0.5)
```
## Lowpass FIR filter
Designing a lowpass FIR filter is very simple to do with SciPy, all you
need to do is to define the window length, cut off frequency and the
window.
The Hamming window is defined as:
$w(n) = \alpha - \beta\cos\frac{2\pi n}{N-1}$, where $\alpha=0.54$ and $\beta=0.46$
The next code chunk is executed in term mode, see the [Python script](FIR_design.py) for syntax.
Notice also that Pweave can now catch multiple figures/code chunk.
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