code: def test_formatter_order(boston_train):
      reg = LinearRegression()
      X, y, feature_names = boston_train
      reg.fit(X, y)
      res = explain_prediction_sklearn(reg, X[0], top=(3, 3))
      expl_text, expl_html = format_as_all(res, reg)
      neg_weights = get_all_features(
          res.targets[0].feature_weights.neg, with_weights=True
      )
      assert neg_weights["x10"] < neg_weights["x12"]
      for expl in [expl_text, expl_html]:
          assert expl.find("x10") > expl.find("x12")
  
file_path: eli5/tests/test_formatters.py
imports: from __future__ import absolute_import
  import re
  import pytest
  import numpy
  from sklearn.feature_extraction.text import TfidfVectorizer
  from sklearn.linear_model import LogisticRegression, LinearRegression
  from eli5.sklearn import explain_weights_sklearn, explain_prediction_sklearn
  from eli5.formatters import fields
  from eli5.formatters.text import _SPACE
  from .utils import format_as_all, get_all_features
label_desc: Use image node_id 2 for calling a global function with example usage: test_formatter_order(boston_train) without return types