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)
            x0 = tri.x.min()
            x1 = tri.x.max()
            y0 = tri.y.min()
            y1 = tri.y.max()
            self.ax.update_datalim([(x0,y0), (x1,y1)])
            self.ax.autoscale_view()

        self.cppContourGenerator = C

    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 = """
        :func:`~matplotlib.pyplot.tricontour` and
        :func:`~matplotlib.pyplot.tricontourf` draw contour lines and
        filled contours, respectively, on an unstructured triangular
        grid.  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*

        ::

          tricontourf(..., Z, V)

        fill the (len(*V*)-1) regions between the values in *V*

        ::

          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.cm.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; eg 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

          *nchunk*: [ 0 | integer ]
            If 0, no subdivision of the domain. Specify a positive integer to
            divide the domain into subdomains of roughly *nchunk* by *nchunk*
            points. This may never actually be advantageous, so this option may
            be removed. Chunking introduces artifacts at the chunk boundaries
            unless *antialiased* is *False*.

        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.

        **Examples:**

        .. plot:: mpl_examples/pylab_examples/tricontour_demo.py
        """


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
