def lpFiltSpec(fp, fs, nyqf):
nyqf = float(nyqf)
ord, wn = filter_design.buttord(fp / nyqf, fs / nyqf, 1, 12, analog=0)
b, a = butter(ord, wn, btype="lowpass", analog=0, output='ba')
w, h = freqz(b, a)
fig = _plt.figure()
_plt.plot(w * (nyqf / _N.pi), _N.abs(h))
def bpFilt(fpL, fpH, fsL, fsH, nyqf, y):
nyqf = float(nyqf)
ord, wn = filter_design.buttord((fpL / nyqf, fpH / nyqf),
(fsL / nyqf, fsH / nyqf),
1,
12,
analog=0)
b, a = butter(ord, wn, btype="bandpass", analog=0, output='ba')
fy = filtfilt(b, a, y)
return fy
def bpFiltSpec(fpL, fpH, fsL, fsH, nyqf):
nyqf = float(nyqf)
ord, wn = filter_design.buttord((fpL / nyqf, fpH / nyqf),
(fsL / nyqf, fsH / nyqf),
1,
12,
analog=0)
b, a = butter(ord, wn, btype="bandpass", analog=0, output='ba')
w, h = freqz(b, a)
fig = _plt.figure()
_plt.plot(w * (nyqf / _N.pi), _N.abs(h))
def low_filter(self, wavFile):
rate, sound_samples = read(wavFile)
sound_samples = np.float64(sound_samples / 32768.0)
pass_freq = 0.2
stop_freq = 0.3
pass_gain = 0.5 # permissible loss (ripple) in passband (dB)
stop_gain = 10.0 # attenuation required in stopband (dB)
ord, wn = buttord(pass_freq, stop_freq, pass_gain, stop_gain)
b, a = butter(ord, wn, btype='low')
filtered = lfilter(b, a, sound_samples)
filtered = np.int16(filtered * 32768 * 10)
write(self.__filteredFile, rate, filtered)
return self.__filteredFile
def hpFilt(fp, fs, nyqf, y, disp=False):
nyqf = float(nyqf)
ord, wn = filter_design.buttord(fp / nyqf, fs / nyqf, 1, 12, analog=0)
b, a = butter(ord, wn, btype="highpass", analog=0, output='ba')
fy = filtfilt(b, a, y)
return fy
flash_read(k)
else:
if((n-k)>= len(int_resp)):
temp += 0
else:
temp += data_buffer[k%64]*int_resp[n-k]
data_dump[n%64] = temp;
f = open('sample_vishwa.dat', 'r')
data = []
for i in f.readlines():
data.append(int(i))
data_test = zeros(len(data))
data_test[0] = 1
order, Wn = fd.buttord(0.2, 0.3, 1, 10)
print order, Wn
b, a = fd.butter(order, Wn)
response = sg.lfilter(b, a, data_test)[:256]
int_resp = []
resp_file = open('impulse_response_integer.dat', 'r')
for i in resp_file.readlines():
int_resp.append(int(i))
#op1 = conv(data[:1024], int_resp)
f.close()
op2 = range(1024)
conv(data)
op1 = convolve(int_resp, data)
clf()
plot(op1, 'r')
plot(op2)
