docstr: Test the scaling of y with logistic growth and a floor/cap.
docstr_tok: ["Test","the","scaling","of","y","with","logistic","growth","and","a","floor\/cap","."]
code: def test_logistic_floor(self, daily_univariate_ts, backend):
      """Test the scaling of y with logistic growth and a floor/cap."""
      train, _ = train_test_split(
          daily_univariate_ts, daily_univariate_ts.shape[0] // 2
      )
      train["floor"] = 10.0
      train["cap"] = 80.0
      m = Prophet(growth="logistic", stan_backend=backend)
      m.fit(train)
      assert m.logistic_floor
      assert "floor" in m.history
      assert m.history["y_scaled"][0] == 1.0
      for col in ["y", "floor", "cap"]:
          train[col] += 10.0
      m2 = Prophet(growth="logistic", stan_backend=backend)
      m2.fit(train)
      assert m2.history["y_scaled"][0] == pytest.approx(1.0, 0.01)
  
imports: import numpy
  import pandas
  import pytest
  from prophet import Prophet
  from prophet.utilities import warm_start_params
label_desc: Use image node_id 3 for calling the TestProphetDataPrep obj's underlying member method code with example usage: obj.test_logistic_floor(daily_univariate_ts, backend) without return types