def convolve(self, other):
result = NDistanceFunction(self.dim)
result.offsets = [
so + oo for so, oo in zip(self.offsets, other.offsets)
]
result.vector = Convolve.convolve(self.vector, other.vector)
result.resetMaxDistance()
return result
def main(*args):
resolution = 0.1
fwhm = 0.5
# get some (random) data, i.e. a stick-spectrum
x = num.arange(-50, 50+resolution, resolution)
y = num.zeros(x.shape, num.Float)
for i in range(10):
y[ran.randint(0, len(y)-1)] = ran.random()
# create lineshape objects
g = ls.GaussProfile(num.arange(-10*fwhm, 10*fwhm+resolution, resolution), 1.0)
l = ls.LorentzProfile(num.arange(-10*fwhm, 10*fwhm+resolution, resolution), 1.0)
v = ls.VoigtProfile(num.arange(-10*fwhm, 10*fwhm+resolution, resolution), (0.6, 0.6))
# convolute data with profile
res_g = Convolve.convolve(y, g(), Convolve.SAME)
res_l = Convolve.convolve(y, l(), Convolve.SAME)
res_v = Convolve.convolve(y, v(), Convolve.SAME)
for i in zip(x, y, res_g, res_l, res_v):
print "%12.6f %12.6f %12.6f %12.6f %12.6f" % i
def convolve(self, other):
result = NDistanceFunction(self.dim)
result.offsets = [so + oo for so, oo in zip(self.offsets, other.offsets)]
result.vector = Convolve.convolve(self.vector, other.vector)
result.resetMaxDistance()
return result
