class_docstr: number of zero crossings among two consecutive samples above a certain threshold for each
  variable in the segmented time series
class_docstr_tok: ["number","of","zero","crossings","among","two","consecutive","samples","above","a","certain","threshold","for","each","variable","in","the","segmented","time","series"]
code: def __call__(self, X):
      sign = np.heaviside(-1 * X[:, :-1] * X[:, 1:], 0)
      abs_diff = np.abs(np.diff(X, axis=1))
      return np.sum(
          sign * abs_diff >= self.threshold, axis=1, dtype=X.dtype
      )
  
imports: import numpy
  from scipy import stats
label_desc: Use image node_id 2 for calling the zero_crossing obj's underlying member method code with example usage: obj.__call__(X) and returns: np