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Merge pull request #7170 from dcmarcu/master
[MRG+1] DOC updated hexbin documentation to numpydoc format.
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‎lib/matplotlib/axes/_axes.py

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@@ -4077,15 +4077,6 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
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"""
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Make a hexagonal binning plot.
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Call signature::
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hexbin(x, y, C = None, gridsize = 100, bins = None,
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xscale = 'linear', yscale = 'linear',
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cmap=None, norm=None, vmin=None, vmax=None,
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alpha=None, linewidths=None, edgecolors='none'
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reduce_C_function = np.mean, mincnt=None, marginals=True
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**kwargs)
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Make a hexagonal binning plot of *x* versus *y*, where *x*,
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*y* are 1-D sequences of the same length, *N*. If *C* is *None*
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(the default), this is a histogram of the number of occurences
@@ -4098,112 +4089,113 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
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specified, it must also be a 1-D sequence of the same length
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as *x* and *y*.)
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*x*, *y* and/or *C* may be masked arrays, in which case only
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unmasked points will be plotted.
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Optional keyword arguments:
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*gridsize*: [ 100 | integer ]
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The number of hexagons in the *x*-direction, default is
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100. The corresponding number of hexagons in the
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*y*-direction is chosen such that the hexagons are
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approximately regular. Alternatively, gridsize can be a
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tuple with two elements specifying the number of hexagons
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in the *x*-direction and the *y*-direction.
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Parameters
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----------
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x, y : array or masked array
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*bins*: [ *None* | 'log' | integer | sequence ]
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If *None*, no binning is applied; the color of each hexagon
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directly corresponds to its count value.
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C : array or masked array, optional, default is *None*
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If 'log', use a logarithmic scale for the color
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map. Internally, :math:`log_{10}(i+1)` is used to
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determine the hexagon color.
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gridsize : int or (int, int), optional, default is 100
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The number of hexagons in the *x*-direction, default is
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100. The corresponding number of hexagons in the
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*y*-direction is chosen such that the hexagons are
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approximately regular. Alternatively, gridsize can be a
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tuple with two elements specifying the number of hexagons
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in the *x*-direction and the *y*-direction.
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If an integer, divide the counts in the specified number
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of bins, and color the hexagons accordingly.
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bins : {'log'} or int or sequence, optional, default is *None*
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If *None*, no binning is applied; the color of each hexagon
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directly corresponds to its count value.
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If a sequence of values, the values of the lower bound of
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the bins to be used.
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If 'log', use a logarithmic scale for the color
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map. Internally, :math:`log_{10}(i+1)` is used to
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determine the hexagon color.
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*xscale*: [ 'linear' | 'log' ]
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Use a linear or log10 scale on the horizontal axis.
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If an integer, divide the counts in the specified number
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of bins, and color the hexagons accordingly.
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*yscale*: [ 'linear' | 'log' ]
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Use a linear or log10 scale on the vertical axis.
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If a sequence of values, the values of the lower bound of
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the bins to be used.
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*mincnt*: [ *None* | a positive integer ]
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If not *None*, only display cells with more than *mincnt*
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number of points in the cell
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xscale : {'linear', 'log'}, optional, default is 'linear'
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Use a linear or log10 scale on the horizontal axis.
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*marginals*: [ *True* | *False* ]
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if marginals is *True*, plot the marginal density as
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colormapped rectagles along the bottom of the x-axis and
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left of the y-axis
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yscale : {'linear', 'log'}, optional, default is 'linear'
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Use a linear or log10 scale on the vertical axis.
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*extent*: [ *None* | scalars (left, right, bottom, top) ]
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The limits of the bins. The default assigns the limits
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based on *gridsize*, *x*, *y*, *xscale* and *yscale*.
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mincnt : int > 0, optional, default is *None*
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If not *None*, only display cells with more than *mincnt*
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number of points in the cell
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If *xscale* or *yscale* is set to 'log', the limits are
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expected to be the exponent for a power of 10. E.g. for
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x-limits of 1 and 50 in 'linear' scale and y-limits
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of 10 and 1000 in 'log' scale, enter (1, 50, 1, 3).
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marginals : bool, optional, default is *False*
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if marginals is *True*, plot the marginal density as
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colormapped rectagles along the bottom of the x-axis and
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left of the y-axis
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Other keyword arguments controlling color mapping and normalization
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arguments:
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extent : scalar, optional, default is *None*
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The limits of the bins. The default assigns the limits
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based on *gridsize*, *x*, *y*, *xscale* and *yscale*.
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*cmap*: [ *None* | Colormap ]
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a :class:`matplotlib.colors.Colormap` instance. If *None*,
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defaults to rc ``image.cmap``.
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If *xscale* or *yscale* is set to 'log', the limits are
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expected to be the exponent for a power of 10. E.g. for
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x-limits of 1 and 50 in 'linear' scale and y-limits
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of 10 and 1000 in 'log' scale, enter (1, 50, 1, 3).
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*norm*: [ *None* | Normalize ]
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:class:`matplotlib.colors.Normalize` instance is used to
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scale luminance data to 0,1.
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Order of scalars is (left, right, bottom, top).
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*vmin* / *vmax*: scalar
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*vmin* and *vmax* are used in conjunction with *norm* to normalize
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luminance data. If either are *None*, the min and max of the color
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array *C* is used. Note if you pass a norm instance, your settings
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for *vmin* and *vmax* will be ignored.
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Other parameters
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----------------
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cmap : object, optional, default is *None*
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a :class:`matplotlib.colors.Colormap` instance. If *None*,
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defaults to rc ``image.cmap``.
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*alpha*: scalar between 0 and 1, or *None*
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the alpha value for the patches
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norm : object, optional, default is *None*
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:class:`matplotlib.colors.Normalize` instance is used to
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scale luminance data to 0,1.
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*linewidths*: [ *None* | scalar ]
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If *None*, defaults to 1.0. Note that this is a tuple, and
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if you set the linewidths argument you must set it as a
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sequence of floats, as required by
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:class:`~matplotlib.collections.RegularPolyCollection`.
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vmin, vmax : scalar, optional, default is *None*
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*vmin* and *vmax* are used in conjunction with *norm* to
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normalize luminance data. If *None*, the min and max of the
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color array *C* are used. Note if you pass a norm instance
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your settings for *vmin* and *vmax* will be ignored.
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Other keyword arguments controlling the Collection properties:
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alpha : scalar between 0 and 1, optional, default is *None*
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the alpha value for the patches
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*edgecolors*: [ *None* | ``'none'`` | mpl color | color sequence ]
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If ``'none'``, draws the edges in the same color as the fill color.
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This is the default, as it avoids unsightly unpainted pixels
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between the hexagons.
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linewidths : scalar, optional, default is *None*
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If *None*, defaults to 1.0.
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If *None*, draws the outlines in the default color.
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edgecolors : {'none'} or mpl color, optional, default is 'none'
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If 'none', draws the edges in the same color as the fill color.
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This is the default, as it avoids unsightly unpainted pixels
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between the hexagons.
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If a matplotlib color arg or sequence of rgba tuples, draws the
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outlines in the specified color.
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If *None*, draws outlines in the default color.
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Here are the standard descriptions of all the
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:class:`~matplotlib.collections.Collection` kwargs:
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If a matplotlib color arg, draws outlines in the specified color.
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%(Collection)s
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Returns
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-------
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object
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a :class:`~matplotlib.collections.PolyCollection` instance; use
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:meth:`~matplotlib.collections.PolyCollection.get_array` on
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this :class:`~matplotlib.collections.PolyCollection` to get
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the counts in each hexagon.
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The return value is a
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:class:`~matplotlib.collections.PolyCollection` instance; use
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:meth:`~matplotlib.collections.PolyColl B752 ection.get_array` on
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this :class:`~matplotlib.collections.PolyCollection` to get
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the counts in each hexagon. If *marginals* is *True*, horizontal
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bar and vertical bar (both PolyCollections) will be attached
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to the return collection as attributes *hbar* and *vbar*.
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If *marginals* is *True*, horizontal
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bar and vertical bar (both PolyCollections) will be attached
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to the return collection as attributes *hbar* and *vbar*.
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Examples
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--------
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.. plot:: mpl_examples/pylab_examples/hexbin_demo.py
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**Example:**
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Notes
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--------
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The standard descriptions of all the
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:class:`~matplotlib.collections.Collection` parameters:
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.. plot:: mpl_examples/pylab_examples/hexbin_demo.py
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%(Collection)s
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"""
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