321 lines
11 KiB
Python
321 lines
11 KiB
Python
import numpy as np
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from matplotlib import docstring
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from matplotlib.contour import ContourSet
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from matplotlib.tri.triangulation import Triangulation
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class TriContourSet(ContourSet):
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"""
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Create and store a set of contour lines or filled regions for
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a triangular grid.
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User-callable method: clabel
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Attributes
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----------
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ax
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The axes object in which the contours are drawn.
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collections
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A silent_list of LineCollections or PolyCollections.
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levels
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Contour levels.
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layers
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Same as levels for line contours; half-way between
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levels for filled contours. See :meth:`_process_colors`.
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"""
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def __init__(self, ax, *args, **kwargs):
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"""
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Draw triangular grid contour lines or filled regions,
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depending on whether keyword arg 'filled' is False
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(default) or True.
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The first argument of the initializer must be an axes
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object. The remaining arguments and keyword arguments
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are described in the docstring of `~.Axes.tricontour`.
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"""
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ContourSet.__init__(self, ax, *args, **kwargs)
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def _process_args(self, *args, **kwargs):
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"""
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Process args and kwargs.
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"""
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if isinstance(args[0], TriContourSet):
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C = args[0].cppContourGenerator
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if self.levels is None:
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self.levels = args[0].levels
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else:
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from matplotlib import _tri
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tri, z = self._contour_args(args, kwargs)
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C = _tri.TriContourGenerator(tri.get_cpp_triangulation(), z)
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self._mins = [tri.x.min(), tri.y.min()]
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self._maxs = [tri.x.max(), tri.y.max()]
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self.cppContourGenerator = C
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return kwargs
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def _get_allsegs_and_allkinds(self):
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"""
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Create and return allsegs and allkinds by calling underlying C code.
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"""
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allsegs = []
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if self.filled:
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lowers, uppers = self._get_lowers_and_uppers()
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allkinds = []
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for lower, upper in zip(lowers, uppers):
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segs, kinds = self.cppContourGenerator.create_filled_contour(
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lower, upper)
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allsegs.append([segs])
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allkinds.append([kinds])
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else:
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allkinds = None
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for level in self.levels:
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segs = self.cppContourGenerator.create_contour(level)
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allsegs.append(segs)
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return allsegs, allkinds
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def _contour_args(self, args, kwargs):
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if self.filled:
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fn = 'contourf'
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else:
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fn = 'contour'
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tri, args, kwargs = Triangulation.get_from_args_and_kwargs(*args,
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**kwargs)
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z = np.ma.asarray(args[0])
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if z.shape != tri.x.shape:
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raise ValueError('z array must have same length as triangulation x'
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' and y arrays')
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# z values must be finite, only need to check points that are included
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# in the triangulation.
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z_check = z[np.unique(tri.get_masked_triangles())]
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if np.ma.is_masked(z_check):
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raise ValueError('z must not contain masked points within the '
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'triangulation')
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if not np.isfinite(z_check).all():
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raise ValueError('z array must not contain non-finite values '
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'within the triangulation')
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z = np.ma.masked_invalid(z, copy=False)
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self.zmax = float(z_check.max())
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self.zmin = float(z_check.min())
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if self.logscale and self.zmin <= 0:
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raise ValueError('Cannot %s log of negative values.' % fn)
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self._process_contour_level_args(args[1:])
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return (tri, z)
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docstring.interpd.update(_tricontour_doc="""
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Draw contour %(type)s on an unstructured triangular grid.
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The triangulation can be specified in one of two ways; either ::
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%(func)s(triangulation, ...)
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where *triangulation* is a `.Triangulation` object, or ::
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%(func)s(x, y, ...)
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%(func)s(x, y, triangles, ...)
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%(func)s(x, y, triangles=triangles, ...)
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%(func)s(x, y, mask=mask, ...)
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%(func)s(x, y, triangles, mask=mask, ...)
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in which case a `.Triangulation` object will be created. See that class'
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docstring for an explanation of these cases.
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The remaining arguments may be::
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%(func)s(..., Z)
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where *Z* is the array of values to contour, one per point in the
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triangulation. The level values are chosen automatically.
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::
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%(func)s(..., Z, levels)
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contour up to *levels+1* automatically chosen contour levels (*levels*
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intervals).
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::
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%(func)s(..., Z, levels)
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draw contour %(type)s at the values specified in sequence *levels*, which must
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be in increasing order.
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::
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%(func)s(Z, **kwargs)
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Use keyword arguments to control colors, linewidth, origin, cmap ... see below
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for more details.
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Parameters
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----------
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triangulation : `.Triangulation`, optional
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The unstructured triangular grid.
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If specified, then *x*, *y*, *triangles*, and *mask* are not accepted.
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x, y : array-like, optional
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The coordinates of the values in *Z*.
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triangles : int array-like of shape (ntri, 3), optional
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For each triangle, the indices of the three points that make up the
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triangle, ordered in an anticlockwise manner. If not specified, the
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Delaunay triangulation is calculated.
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mask : bool array-like of shape (ntri), optional
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Which triangles are masked out.
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Z : array-like(N, M)
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The height values over which the contour is drawn.
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levels : int or array-like, optional
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Determines the number and positions of the contour lines / regions.
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If an int *n*, use `~matplotlib.ticker.MaxNLocator`, which tries to
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automatically choose no more than *n+1* "nice" contour levels between
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*vmin* and *vmax*.
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If array-like, draw contour lines at the specified levels. The values must
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be in increasing order.
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Returns
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-------
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`~matplotlib.tri.TriContourSet`
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Other Parameters
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----------------
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colors : color string or sequence of colors, optional
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The colors of the levels, i.e., the contour %(type)s.
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The sequence is cycled for the levels in ascending order. If the sequence
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is shorter than the number of levels, it's repeated.
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As a shortcut, single color strings may be used in place of one-element
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lists, i.e. ``'red'`` instead of ``['red']`` to color all levels with the
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same color. This shortcut does only work for color strings, not for other
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ways of specifying colors.
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By default (value *None*), the colormap specified by *cmap* will be used.
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alpha : float, default: 1
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The alpha blending value, between 0 (transparent) and 1 (opaque).
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cmap : str or `.Colormap`, default: :rc:`image.cmap`
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A `.Colormap` instance or registered colormap name. The colormap maps the
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level values to colors.
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If both *colors* and *cmap* are given, an error is raised.
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norm : `~matplotlib.colors.Normalize`, optional
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If a colormap is used, the `.Normalize` instance scales the level values to
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the canonical colormap range [0, 1] for mapping to colors. If not given,
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the default linear scaling is used.
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origin : {*None*, 'upper', 'lower', 'image'}, default: None
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Determines the orientation and exact position of *Z* by specifying the
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position of ``Z[0, 0]``. This is only relevant, if *X*, *Y* are not given.
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- *None*: ``Z[0, 0]`` is at X=0, Y=0 in the lower left corner.
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- 'lower': ``Z[0, 0]`` is at X=0.5, Y=0.5 in the lower left corner.
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- 'upper': ``Z[0, 0]`` is at X=N+0.5, Y=0.5 in the upper left corner.
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- 'image': Use the value from :rc:`image.origin`.
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extent : (x0, x1, y0, y1), optional
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If *origin* is not *None*, then *extent* is interpreted as in `.imshow`: it
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gives the outer pixel boundaries. In this case, the position of Z[0, 0] is
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the center of the pixel, not a corner. If *origin* is *None*, then
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(*x0*, *y0*) is the position of Z[0, 0], and (*x1*, *y1*) is the position
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of Z[-1, -1].
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This argument is ignored if *X* and *Y* are specified in the call to
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contour.
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locator : ticker.Locator subclass, optional
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The locator is used to determine the contour levels if they are not given
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explicitly via *levels*.
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Defaults to `~.ticker.MaxNLocator`.
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extend : {'neither', 'both', 'min', 'max'}, default: 'neither'
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Determines the ``%(func)s``-coloring of values that are outside the
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*levels* range.
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If 'neither', values outside the *levels* range are not colored. If 'min',
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'max' or 'both', color the values below, above or below and above the
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*levels* range.
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Values below ``min(levels)`` and above ``max(levels)`` are mapped to the
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under/over values of the `.Colormap`. Note that most colormaps do not have
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dedicated colors for these by default, so that the over and under values
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are the edge values of the colormap. You may want to set these values
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explicitly using `.Colormap.set_under` and `.Colormap.set_over`.
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.. note::
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An existing `.TriContourSet` does not get notified if properties of its
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colormap are changed. Therefore, an explicit call to
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`.ContourSet.changed()` is needed after modifying the colormap. The
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explicit call can be left out, if a colorbar is assigned to the
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`.TriContourSet` because it internally calls `.ContourSet.changed()`.
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xunits, yunits : registered units, optional
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Override axis units by specifying an instance of a
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:class:`matplotlib.units.ConversionInterface`.""")
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@docstring.Substitution(func='tricontour', type='lines')
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@docstring.dedent_interpd
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def tricontour(ax, *args, **kwargs):
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"""
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%(_tricontour_doc)s
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linewidths : float or array-like, default: :rc:`contour.linewidth`
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The line width of the contour lines.
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If a number, all levels will be plotted with this linewidth.
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If a sequence, the levels in ascending order will be plotted with
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the linewidths in the order specified.
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If None, this falls back to :rc:`lines.linewidth`.
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linestyles : {*None*, 'solid', 'dashed', 'dashdot', 'dotted'}, optional
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If *linestyles* is *None*, the default is 'solid' unless the lines are
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monochrome. In that case, negative contours will take their linestyle
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from :rc:`contour.negative_linestyle` setting.
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*linestyles* can also be an iterable of the above strings specifying a
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set of linestyles to be used. If this iterable is shorter than the
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number of contour levels it will be repeated as necessary.
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"""
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kwargs['filled'] = False
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return TriContourSet(ax, *args, **kwargs)
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@docstring.Substitution(func='tricontourf', type='regions')
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@docstring.dedent_interpd
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def tricontourf(ax, *args, **kwargs):
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"""
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%(_tricontour_doc)s
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antialiased : bool, default: True
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Whether to use antialiasing.
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Notes
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-----
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`.tricontourf` fills intervals that are closed at the top; that is, for
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boundaries *z1* and *z2*, the filled region is::
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z1 < Z <= z2
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except for the lowest interval, which is closed on both sides (i.e. it
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includes the lowest value).
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"""
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kwargs['filled'] = True
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return TriContourSet(ax, *args, **kwargs)
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