def cconv_2(x):
return numeric.circconv([x[0],x[1]],[x[2],x[3]])
def cconv_3(x):
return numeric.circconv([x[0],x[1],x[2]],[x[3],x[4],x[5]])
def origin_C(self):
if self.gate > 0.1:
return [0] * len(self.A)
else:
return circconv(self.A, self.B)
def convolution(x):
import numeric
return numeric.circconv([x[0], x[1], x[2]],
[x[3], x[4], x[5]])
def origin_C(self):
if self.gate > 0.1:
return [0] * len(self.A)
else:
return circconv(self.A, self.B)
def __imul__(self, other):
self.v = circconv(self.v, other.v)
#self.v=ifft(fft(self.v)*fft(other.v))
return self
def convolve(self, other):
x = circconv(self.v, other.v)
#x=ifft(fft(self.v)*fft(other.v)).real
return HRR(data=x)
def __imul__(self,other):
self.v=circconv(self.v,other.v)
#self.v=ifft(fft(self.v)*fft(other.v))
return self
def convolve(self,other):
x=circconv(self.v,other.v)
#x=ifft(fft(self.v)*fft(other.v)).real
return HRR(data=x)