scipy/signal/_upfirdn.py
def apply_filter(self, x):
        """Apply the prepared filter to a 1D signal x"""
        output_len = _output_len(len(self._h_trans_flip), len(x),
                                 self._up, self._down)
        out = np.zeros(output_len, dtype=self._output_type)
        _apply(np.asarray(x, self._output_type), self._h_trans_flip, out,
               self._up, self._down)
        return out
Apply the prepared filter to a 1D signal x
Apply the prepared filter to a 1D signal x
Apply the prepared filter to a 1D signal x
def apply_filter(self, x):
        output_len = _output_len(len(self._h_trans_flip), len(x),
                                 self._up, self._down)
        out = np.zeros(output_len, dtype=self._output_type)
        _apply(np.asarray(x, self._output_type), self._h_trans_flip, out,
               self._up, self._down)
        return out
def apply_filter ( self , x ) : output_len = _output_len ( len ( self . _h_trans_flip ) , len ( x ) , self . _up , self . _down ) out = np . zeros ( output_len , dtype = self . _output_type ) _apply ( np . asarray ( x , self . _output_type ) , self . _h_trans_flip , out , self . _up , self . _down ) return out
Apply the prepared filter to a 1D signal x
Apply the prepared filter to a 1D signal x
"""Apply the prepared filter to a 1D signal x"""
self
x