code: def test_remaining_weight_color():
      FW = FeatureWeight
      assert remaining_weight_color_hsl(
          [], 0, "pos"
      ) == weight_color_hsl(1, 1)
      assert remaining_weight_color_hsl(
          [], 2, "neg"
      ) == weight_color_hsl(-2, 2)
      assert remaining_weight_color_hsl(
          [FW("a", -1), FW("b", -2)], 3, "neg"
      ) == weight_color_hsl(-1, 3)
      assert remaining_weight_color_hsl(
          [FW("a", 1), FW("b", 2)], 3, "pos"
      ) == weight_color_hsl(1, 3)
  
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 13 for calling a global function with example usage: test_remaining_weight_color() without return types