class_docstr: Visualize Multiple-dimensional data
  
  This class enables the visualization of multi-dimensional data, using
  a triangular grid of 2D plots.
  
  Parameters
  ----------
  ndim : integer
      Number of data dimensions
  inner_labels : bool
      If true, then label the inner axes.  If false, then only the outer
      axes will be labeled
  fig : matplotlib.Figure
      if specified, draw the plot on this figure.  Otherwise, use the
      current active figure.
  left, bottom, right, top, wspace, hspace : floats
      these parameters control the layout of the plots.  They behave have
      an identical effect as the arguments to plt.subplots_adjust.  If not
      specified, default values from the rc file will be used.
  
  Examples
  --------
  A grid of scatter plots can be created as follows::
  
      x = np.random.normal((4, 1000))
      R = np.random.random((4, 4))  # projection matrix
      x = np.dot(R, x)
      ax = MultiAxes(4)
      ax.scatter(x)
      ax.set_labels(['x1', 'x2', 'x3', 'x4'])
  
  Alternatively, the scatter plot can be visualized as a density::
  
      ax = MultiAxes(4)
      ax.density(x, bins=[20, 20, 20, 20])
docstr: Set the tick locators for the plots
  
  Parameters
  ----------
  locators : list or plt.Locator object
      If a list, then the length should match the data dimension.  If
      a single Locator instance, then each axes will be given the
      same locator.
docstr_tok: ["Set","the","tick","locators","for","the","plots","Parameters","--","--","--","--","--","locators",":","list","or","plt.Locator","object","If","a","list",",","then","the","length","should","match","the","data","dimension",".","If","a","single","Locator","instance",",","then","each","axes","will","be","given","the","same","locator","."]
code: def set_locators(self, locators):
      """Set the tick locators for the plots
  
      Parameters
      ----------
      locators : list or plt.Locator object
          If a list, then the length should match the data dimension.  If
          a single Locator instance, then each axes will be given the
          same locator.
      """
      # Import here so that testing with Agg will work
      from matplotlib import pyplot as plt
  
      if isinstance(locators, plt.Locator):
          locators = [deepcopy(locators) for i in range(self.ndim)]
      elif len(locators) != self.ndim:
          raise ValueError("locators do not match number of dimensions")
  
      for i in range(self.ndim):
          for j in range(self.ndim):
              ax = self.axes[i, j]
              if ax is not None:
                  ax.xaxis.set_major_locator(locators[i])
                  ax.yaxis.set_major_locator(locators[j])
  
file_path: astroML/astroML/plotting/multiaxes.py
imports: from copy import deepcopy
  import numpy
label_desc: Use image node_id 7 for calling the MultiAxes obj's underlying member method code with example usage: obj.set_locators(locators) without return types