code: def test_render_weighted_spans_zero():
      weighted_spans = DocWeightedSpans(
          document="ab",
          spans=[("a", [(0, 1)], 0.0), ("b", [(1, 2)], 0.0)],
          preserve_density=False,
      )
      np_err = np.geterr()
      np.seterr(all="raise")
      try:
          s = _render_weighted_spans(weighted_spans)
      finally:
          np.seterr(**np_err)
      assert s == '<span style="opacity: 0.80">ab</span>'
  
imports: import re
  import pytest
  import numpy
  from sklearn.datasets import make_regression
  from sklearn.linear_model import LinearRegression
  from eli5.base import DocWeightedSpans, FeatureWeight
  from eli5 import explain_weights_sklearn, explain_prediction_sklearn
  from eli5.formatters import format_as_text, format_as_html, format_html_styles, FormattedFeatureName
  from eli5.formatters.html import _format_unhashed_feature, render_weighted_spans, _format_single_feature, _format_feature, remaining_weight_color_hsl, weight_color_hsl
  from eli5.formatters.text_helpers import get_char_weights, PreparedWeightedSpans
  from .utils import write_html
label_desc: Use image node_id 10 for calling a global function with example usage: test_render_weighted_spans_zero() without return types