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Support for FFT with non-uniform time sampling

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This commit is contained in:
Luke Campagnola 2013-08-16 21:28:03 -04:00
parent 79bd7ea187
commit 2095a4c8ae
1 changed files with 16 additions and 6 deletions
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22
pyqtgraph/graphicsItems/PlotDataItem.py
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@ -495,10 +495,7 @@ class PlotDataItem(GraphicsObject):
##y = resample(y[:len(x)*ds], len(x)) ## scipy.signal.resample causes nasty ringing
#y = y[::ds]
if self.opts['fftMode']:
f = np.fft.fft(y) / len(y)
y = abs(f[1:len(f)/2])
dt = x[-1] - x[0]
x = np.linspace(0, 0.5*len(x)/dt, len(y))
x,y = self._fourierTransform(x, y)
if self.opts['logMode'][0]:
x = np.log10(x)
if self.opts['logMode'][1]:
@ -666,8 +663,21 @@ class PlotDataItem(GraphicsObject):
self.xDisp = self.yDisp = None
self.updateItems()
def _fourierTransform(self, x, y):
## Perform fourier transform. If x values are not sampled uniformly,
## then use interpolate.griddata to resample before taking fft.
dx = np.diff(x)
uniform = not np.any(np.abs(dx-dx[0]) > (abs(dx[0]) / 1000.))
if not uniform:
import scipy.interpolate as interp
x2 = np.linspace(x[0], x[-1], len(x))
y = interp.griddata(x, y, x2, method='linear')
x = x2
f = np.fft.fft(y) / len(y)
y = abs(f[1:len(f)/2])
dt = x[-1] - x[0]
x = np.linspace(0, 0.5*len(x)/dt, len(y))
return x, y
def dataType(obj):
if hasattr(obj, '__len__') and len(obj) == 0: