def conv_mul(lin_op, rh_val, transpose=False, is_abs=False):
 constant = mul(lin_op.data, {}, is_abs)
 (constant, rh_val) = map(intf.from_1D_to_2D, [constant, rh_val])
 if transpose:
  constant = np.flipud(constant)
  return fftconvolve(rh_val, constant, mode='valid')
 elif (constant.size >= rh_val.size):
  return fftconvolve(constant, rh_val, mode='full')
 else:
  return fftconvolve(rh_val, constant, mode='full')

def conv_mul ( lin_op , rh_val , transpose = False , is_abs = False ) : constant = mul ( lin_op . data , { } , is_abs ) ( constant , rh_val ) = map ( intf . from_1D_to_2D , [ constant , rh_val ] ) if transpose : constant = np . flipud ( constant ) return fftconvolve ( rh_val , constant , mode = 'valid' ) elif ( constant . size >= rh_val . size ) : return fftconvolve ( constant , rh_val , mode = 'full' ) else : return fftconvolve ( rh_val , constant , mode = 'full' )
multiply by a convolution operator .