text: from __future__ import (absolute_import, division, print_function,
                          unicode_literals)
  
  import six
  
  from matplotlib.contour import ContourSet
  from matplotlib.tri.triangulation import Triangulation
  import matplotlib._tri as _tri
  import numpy as np
  
  
  class TriContourSet(ContourSet):
      """
      Create and store a set of contour lines or filled regions for
      a triangular grid.
  
      User-callable method: clabel
  
      Useful attributes:
        ax:
          the axes object in which the contours are drawn
        collections:
          a silent_list of LineCollections or PolyCollections
        levels:
          contour levels
        layers:
          same as levels for line contours; half-way between
          levels for filled contours.  See _process_colors method.
      """
      def __init__(self, ax, *args, **kwargs):
          """
          Draw triangular grid contour lines or filled regions,
          depending on whether keyword arg 'filled' is False
          (default) or True.
  
          The first argument of the initializer must be an axes
          object.  The remaining arguments and keyword arguments
          are described in TriContourSet.tricontour_doc.
          """
          ContourSet.__init__(self, ax, *args, **kwargs)
  
      def _process_args(self, *args, **kwargs):
          """
          Process args and kwargs.
          """
          if isinstance(args[0], TriContourSet):
              C = args[0].cppContourGenerator
              if self.levels is None:
                  self.levels = args[0].levels
          else:
              tri, z = self._contour_args(args, kwargs)
              C = _tri.TriContourGenerator(tri.get_cpp_triangulation(), z)
              self._mins = [tri.x.min(), tri.y.min()]
              self._maxs = [tri.x.max(), tri.y.max()]
  
          self.cppContourGenerator = C
          return kwargs
  
      def _get_allsegs_and_allkinds(self):
          """
          Create and return allsegs and allkinds by calling underlying C code.
          """
          allsegs = []
          if self.filled:
              lowers, uppers = self._get_lowers_and_uppers()
              allkinds = []
              for lower, upper in zip(lowers, uppers):
                  segs, kinds = self.cppContourGenerator.create_filled_contour(
                      lower, upper)
                  allsegs.append([segs])
                  allkinds.append([kinds])
          else:
              allkinds = None
              for level in self.levels:
                  segs = self.cppContourGenerator.create_contour(level)
                  allsegs.append(segs)
          return allsegs, allkinds
  
      def _contour_args(self, args, kwargs):
          if self.filled:
              fn = 'contourf'
          else:
              fn = 'contour'
          tri, args, kwargs = Triangulation.get_from_args_and_kwargs(*args,
                                                                     **kwargs)
          z = np.asarray(args[0])
          if z.shape != tri.x.shape:
              raise ValueError('z array must have same length as triangulation x'
                               ' and y arrays')
          self.zmax = z.max()
          self.zmin = z.min()
          if self.logscale and self.zmin <= 0:
              raise ValueError('Cannot %s log of negative values.' % fn)
          self._contour_level_args(z, args[1:])
          return (tri, z)
  
      tricontour_doc = """
          Draw contours on an unstructured triangular grid.
          :func:`~matplotlib.pyplot.tricontour` and
          :func:`~matplotlib.pyplot.tricontourf` draw contour lines and
          filled contours, respectively.  Except as noted, function
          signatures and return values are the same for both versions.
  
          The triangulation can be specified in one of two ways; either::
  
            tricontour(triangulation, ...)
  
          where triangulation is a :class:`matplotlib.tri.Triangulation`
          object, or
  
          ::
  
            tricontour(x, y, ...)
            tricontour(x, y, triangles, ...)
            tricontour(x, y, triangles=triangles, ...)
            tricontour(x, y, mask=mask, ...)
            tricontour(x, y, triangles, mask=mask, ...)
  
          in which case a Triangulation object will be created.  See
          :class:`~matplotlib.tri.Triangulation` for a explanation of
          these possibilities.
  
          The remaining arguments may be::
  
            tricontour(..., Z)
  
          where *Z* is the array of values to contour, one per point
          in the triangulation.  The level values are chosen
          automatically.
  
          ::
  
            tricontour(..., Z, N)
  
          contour *N* automatically-chosen levels.
  
          ::
  
            tricontour(..., Z, V)
  
          draw contour lines at the values specified in sequence *V*,
          which must be in increasing order.
  
          ::
  
            tricontourf(..., Z, V)
  
          fill the (len(*V*)-1) regions between the values in *V*,
          which must be in increasing order.
  
          ::
  
            tricontour(Z, **kwargs)
  
          Use keyword args to control colors, linewidth, origin, cmap ... see
          below for more details.
  
          ``C = tricontour(...)`` returns a
          :class:`~matplotlib.contour.TriContourSet` object.
  
          Optional keyword arguments:
  
            *colors*: [ *None* | string | (mpl_colors) ]
              If *None*, the colormap specified by cmap will be used.
  
              If a string, like 'r' or 'red', all levels will be plotted in this
              color.
  
              If a tuple of matplotlib color args (string, float, rgb, etc),
              different levels will be plotted in different colors in the order
              specified.
  
            *alpha*: float
              The alpha blending value
  
            *cmap*: [ *None* | Colormap ]
              A cm :class:`~matplotlib.colors.Colormap` instance or
              *None*. If *cmap* is *None* and *colors* is *None*, a
              default Colormap is used.
  
            *norm*: [ *None* | Normalize ]
              A :class:`matplotlib.colors.Normalize` instance for
              scaling data values to colors. If *norm* is *None* and
              *colors* is *None*, the default linear scaling is used.
  
            *levels* [level0, level1, ..., leveln]
              A list of floating point numbers indicating the level
              curves to draw, in increasing order; e.g., to draw just
              the zero contour pass ``levels=[0]``
  
            *origin*: [ *None* | 'upper' | 'lower' | 'image' ]
              If *None*, the first value of *Z* will correspond to the
              lower left corner, location (0,0). If 'image', the rc
              value for ``image.origin`` will be used.
  
              This keyword is not active if *X* and *Y* are specified in
              the call to contour.
  
            *extent*: [ *None* | (x0,x1,y0,y1) ]
  
              If *origin* is not *None*, then *extent* is interpreted as
              in :func:`matplotlib.pyplot.imshow`: it gives the outer
              pixel boundaries. In this case, the position of Z[0,0]
              is the center of the pixel, not a corner. If *origin* is
              *None*, then (*x0*, *y0*) is the position of Z[0,0], and
              (*x1*, *y1*) is the position of Z[-1,-1].
  
              This keyword is not active if *X* and *Y* are specified in
              the call to contour.
  
            *locator*: [ *None* | ticker.Locator subclass ]
              If *locator* is None, the default
              :class:`~matplotlib.ticker.MaxNLocator` is used. The
              locator is used to determine the contour levels if they
              are not given explicitly via the *V* argument.
  
            *extend*: [ 'neither' | 'both' | 'min' | 'max' ]
              Unless this is 'neither', contour levels are automatically
              added to one or both ends of the range so that all data
              are included. These added ranges are then mapped to the
              special colormap values which default to the ends of the
              colormap range, but can be set via
              :meth:`matplotlib.colors.Colormap.set_under` and
              :meth:`matplotlib.colors.Colormap.set_over` methods.
  
            *xunits*, *yunits*: [ *None* | registered units ]
              Override axis units by specifying an instance of a
              :class:`matplotlib.units.ConversionInterface`.
  
  
          tricontour-only keyword arguments:
  
            *linewidths*: [ *None* | number | tuple of numbers ]
              If *linewidths* is *None*, the default width in
              ``lines.linewidth`` in ``matplotlibrc`` is used.
  
              If a number, all levels will be plotted with this linewidth.
  
              If a tuple, different levels will be plotted with different
              linewidths in the order specified
  
            *linestyles*: [ *None* | 'solid' | 'dashed' | 'dashdot' | 'dotted' ]
              If *linestyles* is *None*, the 'solid' is used.
  
              *linestyles* can also be an iterable of the above strings
              specifying a set of linestyles to be used. If this
              iterable is shorter than the number of contour levels
              it will be repeated as necessary.
  
              If contour is using a monochrome colormap and the contour
              level is less than 0, then the linestyle specified
              in ``contour.negative_linestyle`` in ``matplotlibrc``
              will be used.
  
          tricontourf-only keyword arguments:
  
            *antialiased*: [ *True* | *False* ]
              enable antialiasing
  
          Note: tricontourf fills intervals that are closed at the top; that
          is, for boundaries *z1* and *z2*, the filled region is::
  
              z1 < z <= z2
  
          There is one exception: if the lowest boundary coincides with
          the minimum value of the *z* array, then that minimum value
          will be included in the lowest interval.
          """
  
  
  def tricontour(ax, *args, **kwargs):
      if not ax._hold:
          ax.cla()
      kwargs['filled'] = False
      return TriContourSet(ax, *args, **kwargs)
  tricontour.__doc__ = TriContourSet.tricontour_doc
  
  
  def tricontourf(ax, *args, **kwargs):
      if not ax._hold:
          ax.cla()
      kwargs['filled'] = True
      return TriContourSet(ax, *args, **kwargs)
  tricontourf.__doc__ = TriContourSet.tricontour_doc
  