old_contents: from __future__ import division
  
  import numpy as np
  import six
  
  from chainercv.visualizations.vis_image import vis_image
  
  
  def vis_point(img, point, mask=None, ax=None):
      """Visualize points in an image.
  
      Example:
  
          >>> import chainercv
          >>> import matplotlib.pyplot as plot
          >>> dataset = chainercv.datasets.CUBKeypointDataset()
          >>> img, point, mask = dataset[0]
          >>> chainercv.visualizations.vis_point(img, point, mask)
          >>> plot.show()
  
      Args:
          img (~numpy.ndarray): An image of shape :math:`(3, height, width)`.
              This is in RGB format and the range of its value is
              :math:`[0, 255]`. This should be visualizable using
              :obj:`matplotlib.pyplot.imshow(img)`
          point (~numpy.ndarray): An array of point coordinates whose shape is
              :math:`(P, 2)`, where :math:`P` is
              the number of points.
              The second axis corresponds to :math:`y` and :math:`x` coordinates
              of the points.
          mask (~numpy.ndarray): A boolean array whose shape is
              :math:`(P,)`. If :math:`i` th element is :obj:`True`, the
              :math:`i` th point is not displayed. If not specified,
              all points in :obj:`point` will be displayed.
          ax (matplotlib.axes.Axes, optional): If provided, plot on this axis.
  
      Returns:
          ~matploblib.axes.Axes:
          Returns the Axes object with the plot for further tweaking.
  
      """
      import matplotlib.pyplot as plot
      # Returns newly instantiated matplotlib.axes.Axes object if ax is None
      ax = vis_image(img, ax=ax)
  
      _, H, W = img.shape
      n_point = len(point)
  
      if mask is None:
          mask = np.ones((n_point,), dtype=np.bool)
  
      cm = plot.get_cmap('gist_rainbow')
  
      colors = [cm(i / n_point) for i in six.moves.range(n_point)]
  
      for i in range(n_point):
          if mask[i]:
              ax.scatter(point[i][1], point[i][0], c=colors[i], s=100)
  
      ax.set_xlim(left=0, right=W)
      ax.set_ylim(bottom=H - 1, top=0)
      return ax
  
new_contents: from __future__ import division
  
  import numpy as np
  import six
  
  from chainercv.visualizations.vis_image import vis_image
  
  
  def vis_point(img, point, mask=None, ax=None):
      """Visualize points in an image.
  
      Example:
  
          >>> import chainercv
          >>> import matplotlib.pyplot as plot
          >>> dataset = chainercv.datasets.CUBKeypointDataset()
          >>> img, point, mask = dataset[0]
          >>> chainercv.visualizations.vis_point(img, point, mask)
          >>> plot.show()
  
      Args:
          img (~numpy.ndarray): An image of shape :math:`(3, height, width)`.
              This is in RGB format and the range of its value is
              :math:`[0, 255]`. This should be visualizable using
              :obj:`matplotlib.pyplot.imshow(img)`
          point (~numpy.ndarray): An array of point coordinates whose shape is
              :math:`(P, 2)`, where :math:`P` is
              the number of points.
              The second axis corresponds to :math:`y` and :math:`x` coordinates
              of the points.
          mask (~numpy.ndarray): A boolean array whose shape is
              :math:`(P,)`. If :math:`i` th element is :obj:`True`, the
              :math:`i` th point is not displayed. If not specified,
              all points in :obj:`point` will be displayed.
          ax (matplotlib.axes.Axes): If provided, plot on this axis.
  
      Returns:
          ~matploblib.axes.Axes:
          Returns the Axes object with the plot for further tweaking.
  
      """
      import matplotlib.pyplot as plot
      # Returns newly instantiated matplotlib.axes.Axes object if ax is None
      ax = vis_image(img, ax=ax)
  
      _, H, W = img.shape
      n_point = len(point)
  
      if mask is None:
          mask = np.ones((n_point,), dtype=np.bool)
  
      cm = plot.get_cmap('gist_rainbow')
  
      colors = [cm(i / n_point) for i in six.moves.range(n_point)]
  
      for i in range(n_point):
          if mask[i]:
              ax.scatter(point[i][1], point[i][0], c=colors[i], s=100)
  
      ax.set_xlim(left=0, right=W)
      ax.set_ylim(bottom=H - 1, top=0)
      return ax
  
subject: remove optional