### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.12 Reference Guide (DRAFT) »
- Signal processing (`scipy.signal`) »

# scipy.signal.fftconvolve

`scipy.signal.``fftconvolve`(in1, in2, mode='full')

  Convolve two N-dimensional arrays using FFT.

  Convolve in1 and in2 using the fast Fourier transform method, with the output size determined by the mode argument.

  This is generally much faster than `convolve` for large arrays (n > ~500), but can be slower when only a few output values are needed, and can only output float arrays (int or object array inputs will be cast to float).

  Parameters : | in1 : array_like First input. in2 : array_like Second input. Should have the same number of dimensions as in1; if sizes of in1 and in2 are not equal then in1 has to be the larger array. mode : str {‘full’, ‘valid’, ‘same’}, optional A string indicating the size of the output: `full` The output is the full discrete linear convolution of the inputs. (Default) `valid` The output consists only of those elements that do not rely on the zero-padding. `same` The output is the same size as in1, centered with respect to the ‘full’ output.
  Returns : | out : array An N-dimensional array containing a subset of the discrete linear convolution of in1 with in2.

### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.12 Reference Guide (DRAFT) »
- Signal processing (`scipy.signal`) »