code: def _gen_gaussians(center_locs, sigmas, total_length):
      xdata = np.arange(0, total_length).astype(float)
      out_data = np.zeros(total_length, dtype=float)
      for ind, sigma in enumerate(sigmas):
          tmp = (xdata - center_locs[ind]) / sigma
          out_data += np.exp(-(tmp**2))
      return out_data
  
imports: from __future__ import division, print_function, absolute_import
  import copy
  import numpy
  from numpy.testing import assert_, assert_equal, assert_allclose, assert_array_equal
  import pytest
  from pytest import raises, warns
  from scipy._lib.six import xrange
  from scipy.signal._peak_finding import argrelmax, argrelmin, peak_prominences, peak_widths, _unpack_condition_args, find_peaks, find_peaks_cwt, _identify_ridge_lines
  from scipy.signal._peak_finding_utils import _local_maxima_1d, PeakPropertyWarning
label_desc: Use image node_id 1 for calling a global function with example usage: _gen_gaussians(center_locs, sigmas, total_length) and returns: out_data