pymks/filter.py
def convolve(self, X):
        """
        Convolve X with a kernel in frequency space.

        Args:
          X: array to be convolved

        Returns:
          convolution of X with the kernel
        """
        if X.shape[1:] != self.Fkernel.shape[1:]:
            raise RuntimeError("Dimensions of X are incorrect.")
        FX = np.fft.fftn(X, axes=self.axes)
        Fy = self._sum(FX * self.Fkernel)
        return np.fft.ifftn(Fy, axes=self.axes).real

        Convolve X with a kernel in frequency space.

        Args:
          X: array to be convolved

        Returns:
          convolution of X with the kernel
        
Convolve X with a kernel in frequency space.
Convolve X with a kernel in frequency space .
def convolve(self, X):
        if X.shape[1:] != self.Fkernel.shape[1:]:
            raise RuntimeError("Dimensions of X are incorrect.")
        FX = np.fft.fftn(X, axes=self.axes)
        Fy = self._sum(FX * self.Fkernel)
        return np.fft.ifftn(Fy, axes=self.axes).real
def convolve ( self , X ) : if X . shape [ 1 : ] != self . Fkernel . shape [ 1 : ] : raise RuntimeError ( "Dimensions of X are incorrect." ) FX = np . fft . fftn ( X , axes = self . axes ) Fy = self . _sum ( FX * self . Fkernel ) return np . fft . ifftn ( Fy , axes = self . axes ) . real
Convolve X with a kernel in frequency space.
Convolve X with a kernel in frequency space .
"""
        Convolve X with a kernel in frequency space.

        Args:
          X: array to be convolved

        Returns:
          convolution of X with the kernel
        """
convolution of X with the kernel
convolution of X with the kernel
self
X
array to be convolved
array to be convolved