def plotsig(x, samplingfreq_hz=None, hold=False, axis=0, welch=0, **kwargs):
"""
Makes two subplots, showing time-series <x> in the upper panel and its
amplitude spectrum in the lower panel. Set <hold> in order to re-use
a previous figure.
Any additional keyword arguments are passed through to pylab.plot for
both subplots.
"""###
fs = getfs(samplingfreq_hz)
if fs == None: fs = getfs(x, 2.0)
if hasattr(x, 'x'): x = x.x
elif hasattr(x, 'y'): x = x.y
if not isnumpyarray(x):
axis = 0
if isinstance(x[0], list) or isinstance(x[0], tuple): axis = 1
x = numpy.array(x, dtype='float')
xwin = x = project(x, axis).swapaxes(0, axis)
nsamp = x.shape[0]
class Unfinished(Exception):
pass
if welch == 1: xwin = x * project(hanning(nsamp), len(x.shape) - 1)
elif welch > 0: raise Unfinished, "Welch periodogram not yet implemented"
t = numpy.arange(0, nsamp) / float(fs)
ap = fft2ap(fft(xwin, axis=0), samplingfreq_hz=fs, axis=0)
f = ap['freq_hz']
a = 20.0 * numpy.log10(ap['amplitude'])
pylab = load_pylab()
if not hold: pylab.clf()
pylab.subplot(2, 1, 1)
h1 = pylab.plot(t, x, **kwargs)
ax = pylab.gca()
ax.set_xlim(t[0], t[-1])
ax.xaxis.grid(True)
ax.yaxis.grid(True)
pylab.subplot(2, 1, 2)
a[numpy.isinf(
a
)] = numpy.nan # crude workaround---pylab.plot can't cope with infinite values
h2 = pylab.plot(f, a, **kwargs)
ax = pylab.gca()
ax.set_xlim(f[0], f[-1])
ax.xaxis.grid(True)
ax.yaxis.grid(True)
pylab.draw()
def plotsig(x, samplingfreq_hz=None, hold=False, axis=0, welch=0, **kwargs): """ Makes two subplots, showing time-series <x> in the upper panel and its amplitude spectrum in the lower panel. Set <hold> in order to re-use a previous figure. Any additional keyword arguments are passed through to pylab.plot for both subplots. """### fs = getfs(samplingfreq_hz) if fs==None: fs = getfs(x,2.0) if hasattr(x, 'x'): x = x.x elif hasattr(x, 'y'): x = x.y if not isnumpyarray(x): axis = 0 if isinstance(x[0], list) or isinstance(x[0], tuple): axis = 1 x = numpy.array(x,dtype='float') xwin = x = project(x,axis).swapaxes(0, axis) nsamp = x.shape[0] class Unfinished(Exception): pass if welch==1: xwin = x * project(hanning(nsamp),len(x.shape)-1) elif welch > 0: raise Unfinished, "Welch periodogram not yet implemented" t = numpy.arange(0, nsamp) / float(fs) ap = fft2ap(fft(xwin,axis=0),samplingfreq_hz=fs,axis=0) f = ap['freq_hz'] a = 20.0 * numpy.log10(ap['amplitude']) pylab = load_pylab() if not hold: pylab.clf() pylab.subplot(2,1,1) h1 = pylab.plot(t,x,**kwargs) ax = pylab.gca() ax.set_xlim(t[0], t[-1]) ax.xaxis.grid(True) ax.yaxis.grid(True) pylab.subplot(2,1,2) a[numpy.isinf(a)] = numpy.nan # crude workaround---pylab.plot can't cope with infinite values h2 = pylab.plot(f,a,**kwargs) ax = pylab.gca() ax.set_xlim(f[0], f[-1]) ax.xaxis.grid(True) ax.yaxis.grid(True) pylab.draw()
def __init__(self, freq_hz, samplingfreq_hz, order=10, type='bandpass', method=scipy.signal.filter_design.butter, **kwargs): """ Returns a new online causal filter object f with coefficient arrays f.b and f.a computed by the specified <method>, given the <order> and <freq_hz> parameters, the latter being interpreted in the context of the specified <samplingfreq_hz>. Any additional keyword arguments are passed through to the <method>. For example, a 50 Hz notch filter for 250Hz data: f = causalfilter([48,52], 250, order=10, type='bandstop') x1_filtered = f.apply(x1) # x1 and x2 are channels-by-samples x2_filtered = f.apply(x2) # and are consecutive packets: x1 # is "remembered" when filtering x2 """### self.type = scipy.signal.filter_design.band_dict[type] self.order = int(order) self.order -= self.order%2 if not isinstance(freq_hz,list) and not isinstance(freq_hz,tuple): freq_hz = [freq_hz] self.freq_hz = map(float, freq_hz) self.samplingfreq_hz = getfs(samplingfreq_hz) self.method = method self.kwargs = kwargs lims = map((lambda x: x / self.samplingfreq_hz * 2.0), self.freq_hz); # TODO: for firwin, might need to transform optional arg <width> in the same way? self.b, self.a = method(N=self.order/2.0, Wn=tuple(lims), btype=self.type, output='ba', **kwargs) self.state = None self.samples_filtered = 0