Python matplotlib.axes方法代碼示例

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def _RLClickDispatcher(event, sys, fig, ax_rlocus, plotstr, sisotool=False,
                       bode_plot_params=None, tvect=None):
    """Rootlocus plot click dispatcher"""

    # Zoom is handled by specialized callback above, only do gain plot
    if event.inaxes == ax_rlocus.axes and \
       plt.get_current_fig_manager().toolbar.mode not in \
       {'zoom rect', 'pan/zoom'}:

        # if a point is clicked on the rootlocus plot visually emphasize it
        K = _RLFeedbackClicksPoint(event, sys, fig, ax_rlocus, sisotool)
        if sisotool and K is not None:
            _SisotoolUpdate(sys, fig, K, bode_plot_params, tvect)

    # Update the canvas
    fig.canvas.draw() 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def plot_filled_polygons(self,polygons, facecolour='green', edgecolour='black', linewidth=1, alpha=0.5):
        """
        This function plots a series of shapely polygons but fills them in

        Args:
            ax_list: list of axes
            polygons: list of shapely polygons

        Author: FJC
        """
        from shapely.geometry import Polygon
        from descartes import PolygonPatch
        from matplotlib.collections import PatchCollection

        print('Plotting the polygons...')

        #patches = []
        for key, poly in polygons.items():
            this_patch = PolygonPatch(poly, fc=facecolour, ec=edgecolour, alpha=alpha)
            self.ax_list[0].add_patch(this_patch) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def cla(self):
        Axes.cla(self)

        self.set_longitude_grid(30)
        self.set_latitude_grid(15)
        self.set_longitude_grid_ends(75)
        self.xaxis.set_minor_locator(NullLocator())
        self.yaxis.set_minor_locator(NullLocator())
        self.xaxis.set_ticks_position('none')
        self.yaxis.set_ticks_position('none')
        self.yaxis.set_tick_params(label1On=True)
        # Why do we need to turn on yaxis tick labels, but
        # xaxis tick labels are already on?

        self.grid(rcParams['axes.grid'])

        Axes.set_xlim(self, -np.pi, np.pi)
        Axes.set_ylim(self, -np.pi / 2.0, np.pi / 2.0) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def gca(**kwargs):
    """
    Return the current axis instance.  This can be used to control
    axis properties either using set or the
    :class:`~matplotlib.axes.Axes` methods, for example, setting the
    xaxis range::

      plot(t,s)
      set(gca(), 'xlim', [0,10])

    or::

      plot(t,s)
      a = gca()
      a.set_xlim([0,10])

    """

    ax =  gcf().gca(**kwargs)
    return ax

# More ways of creating axes: 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def twinx(ax=None):
    """
    Make a second axes that shares the *x*-axis.  The new axes will
    overlay *ax* (or the current axes if *ax* is *None*).  The ticks
    for *ax2* will be placed on the right, and the *ax2* instance is
    returned.

    .. seealso::

       :file:`examples/api_examples/two_scales.py`
          For an example
    """
    if ax is None:
        ax=gca()
    ax1 = ax.twinx()
    draw_if_interactive()
    return ax1 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def clim(vmin=None, vmax=None):
    """
    Set the color limits of the current image.

    To apply clim to all axes images do::

      clim(0, 0.5)

    If either *vmin* or *vmax* is None, the image min/max respectively
    will be used for color scaling.

    If you want to set the clim of multiple images,
    use, for example::

      for im in gca().get_images():
          im.set_clim(0, 0.05)

    """
    im = gci()
    if im is None:
        raise RuntimeError('You must first define an image, eg with imshow')

    im.set_clim(vmin, vmax)
    draw_if_interactive() 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def test_polar_wrap():
    D2R = np.pi / 180.0

    fig = plt.figure()

    plt.subplot(111, polar=True)

    plt.polar([179*D2R, -179*D2R], [0.2, 0.1], "b.-")
    plt.polar([179*D2R,  181*D2R], [0.2, 0.1], "g.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
    assert len(fig.axes) == 1, 'More than one polar axes created.'
    fig = plt.figure()

    plt.subplot(111, polar=True)
    plt.polar([2*D2R, -2*D2R], [0.2, 0.1], "b.-")
    plt.polar([2*D2R,  358*D2R], [0.2, 0.1], "g.-")
    plt.polar([358*D2R,  2*D2R], [0.2, 0.1], "r.-")
    plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3]) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def make_base_image(self,ax_list):
        """
        This function creates the base image. It creates the axis for the base image,
        further drapes and point data are placed upon this image.

        Args:
            ax_list: A list of axes, we append the base raster to the [0] element
                of the axis

        Author: DAV and SMM
        """

        # We need to initiate with a figure
        #self.ax = self.fig.add_axes([0.1,0.1,0.7,0.7])

        print("This colourmap is: "+ self._RasterList[0]._colourmap)
        im = self.ax_list[0].imshow(self._RasterList[0]._RasterArray, self._RasterList[0]._colourmap, extent = self._RasterList[0].extents, interpolation="nearest", alpha = self._RasterList[0]._alpha)

        # This affects all axes because we set share_all = True.
        #ax.set_xlim(self._xmin,self._xmax)
        #ax.set_ylim(self._ymin,self._ymax)
        self.ax_list[0] = self.add_ticks_to_axis(self.ax_list[0])
        self._drape_list.append(im)

        print("The number of axes are: "+str(len(self._drape_list)))

        print(self.ax_list[0])
        return self.ax_list 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def add_drape_image(self,RasterName,Directory,colourmap = "gray",
                        alpha=0.5,
                        show_colourbar = False,
                        colorbarlabel = "Colourbar", discrete_cmap=False, n_colours=10,
                        norm = "None",
                        colour_min_max = [],
                        modify_raster_values=False,
                        old_values=[], new_values=[], cbar_type=float,
                        NFF_opti = False, custom_min_max = [], zorder=1):
        """
        This function adds a drape over the base raster.

        Args:
            RasterName (string): The name of the raster (no directory, but need extension)
            Directory (string): directory of the data
            colourmap (string or colourmap): The colourmap. Can be a strong for default colourmaps
            alpha (float): The transparency of the drape (1 is opaque, 0 totally transparent)
            show_colourbar (bool): True to show colourbar
            colourbarlabel (string): The label of the colourbar
            discrete_cmap (bool): If true, make discrete values for colours, otherwise a gradient.
            n_colours (int): number of colours in discrete colourbar
            norm (string): Normalisation of colourbar. I don't understand this so don't change
            colour_min_max( list of int/float): if it contains two elements, map the colourbar between these two values.
            modify_raster_values (bool): If true, it takes old_values in list and replaces them with new_values
            old_values (list): A list of values to be replaced in raster. Useful for masking and renaming
            new_values (list): A list of the new values. This probably should be done with a map: TODO
            cbar_type (type): Sets the type of the colourbar (if you want int labels, set to int)
            NFF_opti (bool): If true, uses the new file loading functions. It is faster but hasn't been completely tested.
            custom_min_max (list of int/float): if it contains two elements, recast the raster to [min,max] values for display.

        Author: SMM
        """
        print("N axes are: "+str(len(self.ax_list)))
        print(self.ax_list[0])

        self.ax_list = self._add_drape_image(self.ax_list,RasterName,Directory,colourmap,alpha,
                                             colorbarlabel,discrete_cmap,n_colours, norm,
                                             colour_min_max,modify_raster_values,old_values,
                                             new_values,cbar_type, NFF_opti, custom_min_max, zorder=zorder)
        #print("Getting axis limits in drape function: ")
        #print(self.ax_list[0].get_xlim()) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def add_point_colourbar(self,ax_list,sc,cmap = "cubehelix",colorbarlabel = "Colourbar",
                            discrete=False, n_colours=10, cbar_type=float):
        """
        This adds a colourbar for any points that are on the DEM.

        Args:
            ax_list: The list of axes objects. Assumes colourbar is in axis_list[-1]
            sc: The scatterplot object. Generated by plt.scatter
            cmap (string or colourmap): The colourmap.
            colorbarlabel (string): The label of the colourbar

        Author: SMM
        """
        fig = matplotlib.pyplot.gcf()
        ax_list.append(fig.add_axes([0.1,0.8,0.2,0.5]))
        cbar = plt.colorbar(sc,cmap=cmap, orientation=self.colourbar_orientation,cax=ax_list[-1])

        if self.colourbar_location == 'top':
            ax_list[-1].set_xlabel(colorbarlabel, fontname='Liberation Sans',labelpad=5)
        elif self.colourbar_location == 'bottom':
            ax_list[-1].set_xlabel(colorbarlabel, fontname='Liberation Sans',labelpad=5)
        elif self.colourbar_location == 'left':
            ax_list[-1].set_ylabel(colorbarlabel, fontname='Liberation Sans',labelpad=-75,rotation=90)
        elif self.colourbar_location == 'right':
            ax_list[-1].set_ylabel(colorbarlabel, fontname='Liberation Sans',labelpad=10,rotation=270)
        return ax_list 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def update(self, **kwargs):
        """
        Update the current values.  If any kwarg is None, default to
        the current value, if set, otherwise to rc.
        """

        for k, v in kwargs.iteritems():
            if k in self._AllowedKeys:
                setattr(self, k, v)
            else:
                raise AttributeError("%s is unknown keyword" % (k,))


        from matplotlib import _pylab_helpers
        from matplotlib.axes import SubplotBase
        for figmanager in _pylab_helpers.Gcf.figs.itervalues():
            for ax in figmanager.canvas.figure.axes:
                # copied from Figure.subplots_adjust
                if not isinstance(ax, SubplotBase):
                    # Check if sharing a subplots axis
                    if ax._sharex is not None and isinstance(ax._sharex, SubplotBase):
                        if ax._sharex.get_subplotspec().get_gridspec() == self:
                            ax._sharex.update_params()
                            ax.set_position(ax._sharex.figbox)
                    elif ax._sharey is not None and isinstance(ax._sharey,SubplotBase):
                        if ax._sharey.get_subplotspec().get_gridspec() == self:
                            ax._sharey.update_params()
                            ax.set_position(ax._sharey.figbox)
                else:
                    ss = ax.get_subplotspec().get_topmost_subplotspec()
                    if ss.get_gridspec() == self:
                        ax.update_params()
                        ax.set_position(ax.figbox) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def tight_layout(self, fig, renderer=None, pad=1.08, h_pad=None, w_pad=None, rect=None):
        """
        Adjust subplot parameters to give specified padding.

        Parameters:

        pad : float
            padding between the figure edge and the edges of subplots, as a fraction of the font-size.
        h_pad, w_pad : float
            padding (height/width) between edges of adjacent subplots.
            Defaults to `pad_inches`.
        rect : if rect is given, it is interpreted as a rectangle
            (left, bottom, right, top) in the normalized figure
            coordinate that the whole subplots area (including
            labels) will fit into. Default is (0, 0, 1, 1).
        """

        from tight_layout import (get_subplotspec_list,
                                  get_tight_layout_figure,
                                  get_renderer)

        subplotspec_list = get_subplotspec_list(fig.axes, grid_spec=self)
        if None in subplotspec_list:
            warnings.warn("This figure includes Axes that are not "
                          "compatible with tight_layout, so its "
                          "results might be incorrect.")

        if renderer is None:
            renderer = get_renderer(fig)

        kwargs = get_tight_layout_figure(fig, fig.axes, subplotspec_list,
                                         renderer,
                                         pad=pad, h_pad=h_pad, w_pad=w_pad,
                                         rect=rect,
                                         )

        self.update(**kwargs) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def set_xlim(self, *args, **kwargs):
        raise TypeError("It is not possible to change axes limits "
                        "for geographic projections. Please consider "
                        "using Basemap or Cartopy.") 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def can_zoom(self):
        """
        Return *True* if this axes supports the zoom box button functionality.

        This axes object does not support interactive zoom box.
        """
        return False 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import axes [as 別名]
def _init_axis(self):
        "move this out of __init__ because non-separable axes don't use it"
        self.xaxis = maxis.XAxis(self)
        self.yaxis = maxis.YAxis(self)
        # Calling polar_axes.xaxis.cla() or polar_axes.xaxis.cla()
        # results in weird artifacts. Therefore we disable this for
        # now.
        # self.spines['polar'].register_axis(self.yaxis)
        self._update_transScale()