code: def test_float_regex():
      some_strings = pd.Series("0.2 3 3. .3 -4 - .0.".split())
      res = [True] * 5 + [False] * 2
      assert (some_strings.str.match(_FLOAT_REGEX) == res).all()
  
imports: import os
  import pytest
  import random
  import string
  import warnings
  import numpy
  import pandas
  from sklearn.datasets import load_iris, load_digits
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import make_pipeline
  from sklearn.linear_model import LogisticRegression
  from dabl.preprocessing import USELESS_TYPES, detect_types, EasyPreprocessor, DirtyFloatCleaner, clean, _FLOAT_REGEX, _float_matching, detect_type_series
  from dabl.utils import data_df_from_bunch
  from dabl.datasets import load_titanic
  from dabl import plot
label_desc: Use image node_id 2 for calling a global function with example usage: test_float_regex() without return types