code: def plot_gross_leverage(returns, positions, ax=None, **kwargs):
      """
      Plots gross leverage versus date.
  
      Gross leverage is the sum of long and short exposure per share
      divided by net asset value.
  
      Parameters
      ----------
      returns : pd.Series
          Daily returns of the strategy, noncumulative.
           - See full explanation in tears.create_full_tear_sheet.
      positions : pd.DataFrame
          Daily net position values.
           - See full explanation in create_full_tear_sheet.
      ax : matplotlib.Axes, optional
          Axes upon which to plot.
      **kwargs, optional
          Passed to plotting function.
  
      Returns
      -------
      ax : matplotlib.Axes
          The axes that were plotted on.
      """
  
      if ax is None:
          ax = plt.gca()
      gl = timeseries.gross_lev(positions)
      gl.plot(lw=0.5, color="limegreen", legend=False, ax=ax, **kwargs)
  
      ax.axhline(gl.mean(), color="g", linestyle="--", lw=3)
  
      ax.set_title("Gross leverage")
      ax.set_ylabel("Gross leverage")
      ax.set_xlabel("")
      return ax
  
imports: from __future__ import division
  import datetime
  from collections import OrderedDict
  from functools import wraps
  import empyrical
  import matplotlib
  import matplotlib.patches
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytz
  import scipy
  from matplotlib import figure
  from matplotlib.backends.backend_agg import FigureCanvasAgg
  from matplotlib.ticker import FuncFormatter
  from .None import _seaborn
  from .None import capacity
  from .None import pos
  from .None import timeseries
  from .None import txn
  from .None import utils
  from .utils import APPROX_BDAYS_PER_MONTH, MM_DISPLAY_UNIT
label_desc: Use image node_id 18 for calling a global function with example usage: plot_gross_leverage(returns, positions, ax) and returns: ax