code: def _pad_h(h, up):
      """Store coefficients in a transposed, flipped arrangement.
  
      For example, suppose upRate is 3, and the
      input number of coefficients is 10, represented as h[0], ..., h[9].
  
      Then the internal buffer will look like this::
  
         h[9], h[6], h[3], h[0],   // flipped phase 0 coefs
         0,    h[7], h[4], h[1],   // flipped phase 1 coefs (zero-padded)
         0,    h[8], h[5], h[2],   // flipped phase 2 coefs (zero-padded)
  
      """
      h_padlen = len(h) + (-len(h) % up)
      h_full = np.zeros(h_padlen, h.dtype)
      h_full[: len(h)] = h
      h_full = h_full.reshape(-1, up).T[:, ::-1].ravel()
      return h_full
  
file_path: catboost/contrib/python/scipy/py3/scipy/signal/_upfirdn.py
imports: import numpy
  from ._upfirdn_apply import _output_len, _apply, mode_enum
label_desc: Use image node_id 1 for calling a global function with example usage: _pad_h(h, up) and returns: h_full