Python matplotlib.rc_context方法代碼示例

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def update_backend(self):
        with mpl.rc_context(fname=self.fig.fname, rc=self.fig.rc):
            ax = self.ax

            ax.set_xscale(self.xscale)
            ax.set_yscale(self.yscale)

            if self.xlim[0] != self.xlim[1]:
                ax.set_xlim(self.xlim)

            if self.ylim[0] != self.ylim[1]:
                ax.set_ylim(self.ylim)

            # set axes labels
            ax.set_xlabel(self.xlabel)
            ax.set_ylabel(self.ylabel)

            # set title
            ax.set_title(label=self.title)

            # set aspect ratio
            ax.set_aspect(self.aspect) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def save(
        self, path, format: Optional[str] = None, dpi: Optional[float] = 150
    ):
        """Saves the figure to a file.

        Parameters
        ----------
            path: ``tuple`` of ``float``, optional
                Path in which to store the file.

            format: ``str``, optional
                File format, e.g. ``'png'``, ``'pdf'``, ``'svg'``. If not
                provided, the output format is inferred from the extension of
                ``path``.

            dpi: ``float``, optional
                Resolution in dots per inch. If not provided, defaults to
                ``150``.

        """
        with mpl.rc_context(fname=self.fname, rc=self.rc):
            self.fig.savefig(path, dpi=dpi, bbox_inches="tight") 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rcparams():
    usetex = mpl.rcParams['text.usetex']
    linewidth = mpl.rcParams['lines.linewidth']

    # test context given dictionary
    with mpl.rc_context(rc={'text.usetex': not usetex}):
        assert mpl.rcParams['text.usetex'] == (not usetex)
    assert mpl.rcParams['text.usetex'] == usetex

    # test context given filename (mpl.rc sets linewdith to 33)
    with mpl.rc_context(fname=fname):
        assert mpl.rcParams['lines.linewidth'] == 33
    assert mpl.rcParams['lines.linewidth'] == linewidth

    # test context given filename and dictionary
    with mpl.rc_context(fname=fname, rc={'lines.linewidth': 44}):
        assert mpl.rcParams['lines.linewidth'] == 44
    assert mpl.rcParams['lines.linewidth'] == linewidth

    # test rc_file
    try:
        mpl.rc_file(fname)
        assert mpl.rcParams['lines.linewidth'] == 33
    finally:
        mpl.rcParams['lines.linewidth'] = linewidth 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rcparams_reset_after_fail():

    # There was previously a bug that meant that if rc_context failed and
    # raised an exception due to issues in the supplied rc parameters, the
    # global rc parameters were left in a modified state.

    if sys.version_info[:2] >= (2, 7):
        from collections import OrderedDict
    else:
        raise SkipTest("Test can only be run in Python >= 2.7 as it requires OrderedDict")

    with mpl.rc_context(rc={'text.usetex': False}):

        assert mpl.rcParams['text.usetex'] is False

        with assert_raises(KeyError):
            with mpl.rc_context(rc=OrderedDict([('text.usetex', True),('test.blah', True)])):
                pass

        assert mpl.rcParams['text.usetex'] is False 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rcparams_reset_after_fail():

    # There was previously a bug that meant that if rc_context failed and
    # raised an exception due to issues in the supplied rc parameters, the
    # global rc parameters were left in a modified state.

    with mpl.rc_context(rc={'text.usetex': False}):

        assert mpl.rcParams['text.usetex'] is False

        with pytest.raises(KeyError):
            with mpl.rc_context(rc=OrderedDict([('text.usetex', True),
                                                ('test.blah', True)])):
                pass

        assert mpl.rcParams['text.usetex'] is False 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rc_grid():
    fig = plt.figure()
    rc_dict0 = {
        'axes.grid': True,
        'axes.grid.axis': 'both'
    }
    rc_dict1 = {
        'axes.grid': True,
        'axes.grid.axis': 'x'
    }
    rc_dict2 = {
        'axes.grid': True,
        'axes.grid.axis': 'y'
    }
    dict_list = [rc_dict0, rc_dict1, rc_dict2]

    i = 1
    for rc_dict in dict_list:
        with matplotlib.rc_context(rc_dict):
            fig.add_subplot(3, 1, i)
            i += 1 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rc_tick():
    d = {'xtick.bottom': False, 'xtick.top': True,
         'ytick.left': True, 'ytick.right': False}
    with plt.rc_context(rc=d):
        fig = plt.figure()
        ax1 = fig.add_subplot(1, 1, 1)
        xax = ax1.xaxis
        yax = ax1.yaxis
        # tick1On bottom/left
        assert not xax._major_tick_kw['tick1On']
        assert xax._major_tick_kw['tick2On']
        assert not xax._minor_tick_kw['tick1On']
        assert xax._minor_tick_kw['tick2On']

        assert yax._major_tick_kw['tick1On']
        assert not yax._major_tick_kw['tick2On']
        assert yax._minor_tick_kw['tick1On']
        assert not yax._minor_tick_kw['tick2On'] 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rc_major_minor_tick():
    d = {'xtick.top': True, 'ytick.right': True,  # Enable all ticks
         'xtick.bottom': True, 'ytick.left': True,
         # Selectively disable
         'xtick.minor.bottom': False, 'xtick.major.bottom': False,
         'ytick.major.left': False, 'ytick.minor.left': False}
    with plt.rc_context(rc=d):
        fig = plt.figure()
        ax1 = fig.add_subplot(1, 1, 1)
        xax = ax1.xaxis
        yax = ax1.yaxis
        # tick1On bottom/left
        assert not xax._major_tick_kw['tick1On']
        assert xax._major_tick_kw['tick2On']
        assert not xax._minor_tick_kw['tick1On']
        assert xax._minor_tick_kw['tick2On']

        assert not yax._major_tick_kw['tick1On']
        assert yax._major_tick_kw['tick2On']
        assert not yax._minor_tick_kw['tick1On']
        assert yax._minor_tick_kw['tick2On'] 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_minorticks_rc():
    fig = plt.figure()

    def minorticksubplot(xminor, yminor, i):
        rc = {'xtick.minor.visible': xminor,
              'ytick.minor.visible': yminor}
        with plt.rc_context(rc=rc):
            ax = fig.add_subplot(2, 2, i)

        assert (len(ax.xaxis.get_minor_ticks()) > 0) == xminor
        assert (len(ax.yaxis.get_minor_ticks()) > 0) == yminor

    minorticksubplot(False, False, 1)
    minorticksubplot(True, False, 2)
    minorticksubplot(False, True, 3)
    minorticksubplot(True, True, 4) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_colorbar_closed_patch():
    fig = plt.figure(figsize=(8, 6))
    ax1 = fig.add_axes([0.05, 0.85, 0.9, 0.1])
    ax2 = fig.add_axes([0.1, 0.65, 0.75, 0.1])
    ax3 = fig.add_axes([0.05, 0.45, 0.9, 0.1])
    ax4 = fig.add_axes([0.05, 0.25, 0.9, 0.1])
    ax5 = fig.add_axes([0.05, 0.05, 0.9, 0.1])

    cmap = get_cmap("RdBu", lut=5)

    im = ax1.pcolormesh(np.linspace(0, 10, 16).reshape((4, 4)), cmap=cmap)
    values = np.linspace(0, 10, 5)

    with rc_context({'axes.linewidth': 16}):
        plt.colorbar(im, cax=ax2, cmap=cmap, orientation='horizontal',
                     extend='both', extendfrac=0.5, values=values)
        plt.colorbar(im, cax=ax3, cmap=cmap, orientation='horizontal',
                     extend='both', values=values)
        plt.colorbar(im, cax=ax4, cmap=cmap, orientation='horizontal',
                     extend='both', extendrect=True, values=values)
        plt.colorbar(im, cax=ax5, cmap=cmap, orientation='horizontal',
                     extend='neither', values=values) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_colorbar_autotickslog():
    # Test new autotick modes...
    with rc_context({'_internal.classic_mode': False}):
        fig, ax = plt.subplots(2, 1)
        x = np.arange(-3.0, 4.001)
        y = np.arange(-4.0, 3.001)
        X, Y = np.meshgrid(x, y)
        Z = X * Y
        pcm = ax[0].pcolormesh(X, Y, 10**Z, norm=LogNorm())
        cbar = fig.colorbar(pcm, ax=ax[0], extend='both',
                            orientation='vertical')

        pcm = ax[1].pcolormesh(X, Y, 10**Z, norm=LogNorm())
        cbar2 = fig.colorbar(pcm, ax=ax[1], extend='both',
                            orientation='vertical', shrink=0.4)
        np.testing.assert_almost_equal(cbar.ax.yaxis.get_ticklocs(),
                10**np.arange(-12, 12.2, 4.))
        np.testing.assert_almost_equal(cbar2.ax.yaxis.get_ticklocs(),
                10**np.arange(-12, 13., 12.)) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def __init__(self, layout, axis=None, create_axes=True, ranges=None,
                 layout_num=1, keys=None, **params):
        if not isinstance(layout, GridSpace):
            raise Exception("GridPlot only accepts GridSpace.")
        super(GridPlot, self).__init__(layout, layout_num=layout_num,
                                       ranges=ranges, keys=keys, **params)
        # Compute ranges layoutwise
        grid_kwargs = {}
        if axis is not None:
            bbox = axis.get_position()
            l, b, w, h = bbox.x0, bbox.y0, bbox.width, bbox.height
            grid_kwargs = {'left': l, 'right': l+w, 'bottom': b, 'top': b+h}
            self.position = (l, b, w, h)

        self.cols, self.rows = layout.shape
        self.fig_inches = self._get_size()
        self._layoutspec = gridspec.GridSpec(self.rows, self.cols, **grid_kwargs)

        with mpl.rc_context(rc=self.fig_rcparams):
            self.subplots, self.subaxes, self.layout = self._create_subplots(layout, axis,
                                                                             ranges, create_axes)
        if self.top_level:
            self.traverse(lambda x: attach_streams(self, x.hmap, 2),
                          [GenericElementPlot]) 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rcParams_bar_colors(self):
        import matplotlib as mpl
        color_tuples = [(0.9, 0, 0, 1), (0, 0.9, 0, 1), (0, 0, 0.9, 1)]
        with mpl.rc_context(
                rc={'axes.prop_cycle': mpl.cycler("color", color_tuples)}):
            barplot = pd.DataFrame([[1, 2, 3]]).plot(kind="bar")
        assert color_tuples == [c.get_facecolor() for c in barplot.patches] 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def __call__(self, **kwargs):
        """Figure realizer

        The Figure class only keeps track of a root panel.  It does
        not contain an actual matplotlib Figure instance.  Whenever a
        figure needs to be created, Figure creates a new matplotlib
        Figure in order to drew/rendered/realized the figure.

        Args:

            **kwargs (dict): Arbitrary Figure-specific keyworded
                arguments that are used to construct the matplotlib
                Figure.

        """
        kwprops = merge_dict(self.kwprops, kwargs)
        style   = kwprops.pop('style')

        with mpl.rc_context():
            mpl.rcdefaults()
            plt.style.use(style)

            imode = mpl.is_interactive()
            if imode:
                plt.ioff()

            fig = plt.figure(**kwprops)
            ax  = newaxes(fig)
            yield fig, ax

            if imode:
                plt.ion() 

# 需要導入模塊: import matplotlib [as 別名]
# 或者: from matplotlib import rc_context [as 別名]
def test_rcParams_bar_colors(self):
        import matplotlib as mpl
        color_tuples = [(0.9, 0, 0, 1), (0, 0.9, 0, 1), (0, 0, 0.9, 1)]
        try:  # mpl 1.5
            with mpl.rc_context(
                    rc={'axes.prop_cycle': mpl.cycler("color", color_tuples)}):
                barplot = pd.DataFrame([[1, 2, 3]]).plot(kind="bar")
        except (AttributeError, KeyError):  # mpl 1.4
            with mpl.rc_context(rc={'axes.color_cycle': color_tuples}):
                barplot = pd.DataFrame([[1, 2, 3]]).plot(kind="bar")
        assert color_tuples == [c.get_facecolor() for c in barplot.patches]