code: def test_daily_log_returns():
      orig = [
          [
              0.6931471805599453,
              0.4054651081081644,
              0.28768207245178085,
              0.22314355131420976,
          ],
          [
              0.10536051565782635,
              0.09531017980432493,
              0.0870113769896297,
              0.08004270767353636,
          ],
      ]
      l1 = np.array(range(1, 6)).astype(np.float64)
      l2 = [10 * 0.2 + i * 0.25 for i in range(1, 6)]
      d = {"1": l1, "2": l2}
      df = pd.DataFrame(d)
      ret = daily_log_returns(df)
      ret
  
      assert all(abs(ret["1"].values - orig[0]) <= 1e-15)
      assert all(abs(ret["2"].values - orig[1]) <= 1e-15)
  
file_path: FinQuant/tests/test_returns.py
imports: import numpy
  import pandas
  from finquant.returns import cumulative_returns, daily_log_returns, daily_returns, historical_mean_return, weighted_mean_daily_returns
label_desc: Use image node_id 4 for calling a global function with example usage: test_daily_log_returns() without return types