class_docstr: Plotter for numeric independent variables with regression model.
  
  This does the computations and drawing for the `regplot` function, and
  is thus also used indirectly by `lmplot`.
class_docstr_tok: ["Plotter","for","numeric","independent","variables","with","regression","model",".","This","does","the","computations","and","drawing","for","the","`","regplot","`","function",",","and","is","thus","also","used","indirectly","by","`","lmplot","`","."]
docstr: Draw the model.
docstr_tok: ["Draw","the","model","."]
code: def lineplot(self, ax, kws):
      """Draw the model."""
      # Fit the regression model
      grid, yhat, err_bands = self.fit_regression(ax)
      edges = grid[0], grid[-1]
  
      # Get set default aesthetics
      fill_color = kws["color"]
      lw = kws.pop("lw", mpl.rcParams["lines.linewidth"] * 1.5)
      kws.setdefault("linewidth", lw)
  
      # Draw the regression line and confidence interval
      (line,) = ax.plot(grid, yhat, **kws)
      if not self.truncate:
          line.sticky_edges.x[
              :
          ] = edges  # Prevent mpl from adding margin
      if err_bands is not None:
          ax.fill_between(
              grid, *err_bands, facecolor=fill_color, alpha=0.15
          )
  
imports: import copy
  from textwrap import dedent
  import warnings
  import numpy
  import pandas
  import matplotlib
  import matplotlib.pyplot
  from .None import utils
  from .None import algorithms
  from .axisgrid import FacetGrid, _facet_docs
label_desc: Use image node_id 15 for calling the _RegressionPlotter obj's underlying member method code with example usage: obj.lineplot(ax, kws) without return types