Python ticker.LogLocator方法代碼示例

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def _autolev(self, z, N):
        """
        Select contour levels to span the data.

        We need two more levels for filled contours than for
        line contours, because for the latter we need to specify
        the lower and upper boundary of each range. For example,
        a single contour boundary, say at z = 0, requires only
        one contour line, but two filled regions, and therefore
        three levels to provide boundaries for both regions.
        """
        if self.locator is None:
            if self.logscale:
                self.locator = ticker.LogLocator()
            else:
                self.locator = ticker.MaxNLocator(N + 1)
        zmax = self.zmax
        zmin = self.zmin
        lev = self.locator.tick_values(zmin, zmax)
        self._auto = True
        if self.filled:
            return lev
        # For line contours, drop levels outside the data range.
        return lev[(lev > zmin) & (lev < zmax)] 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def _select_locator(self, formatter):
        '''
        select a suitable locator
        '''
        if self.boundaries is None:
            if isinstance(self.norm, colors.NoNorm):
                nv = len(self._values)
                base = 1 + int(nv/10)
                locator = ticker.IndexLocator(base=base, offset=0)
            elif isinstance(self.norm, colors.BoundaryNorm):
                b = self.norm.boundaries
                locator = ticker.FixedLocator(b, nbins=10)
            elif isinstance(self.norm, colors.LogNorm):
                locator = ticker.LogLocator()
            else:
                locator = ticker.MaxNLocator(nbins=5)
        else:
            b = self._boundaries[self._inside]
            locator = ticker.FixedLocator(b) #, nbins=10)

        self.cbar_axis.set_major_locator(locator) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def minorticks_on(self):
        """
        Display minor ticks on the axes.

        Displaying minor ticks may reduce performance; you may turn them off
        using `minorticks_off()` if drawing speed is a problem.
        """
        for ax in (self.xaxis, self.yaxis):
            scale = ax.get_scale()
            if scale == 'log':
                s = ax._scale
                ax.set_minor_locator(mticker.LogLocator(s.base, s.subs))
            elif scale == 'symlog':
                s = ax._scale
                ax.set_minor_locator(
                    mticker.SymmetricalLogLocator(s._transform, s.subs))
            else:
                ax.set_minor_locator(mticker.AutoMinorLocator()) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def test_colorbar_renorm():
    x, y = np.ogrid[-4:4:31j, -4:4:31j]
    z = 120000*np.exp(-x**2 - y**2)

    fig, ax = plt.subplots()
    im = ax.imshow(z)
    cbar = fig.colorbar(im)

    norm = LogNorm(z.min(), z.max())
    im.set_norm(norm)
    cbar.set_norm(norm)
    cbar.locator = LogLocator()
    cbar.formatter = LogFormatter()
    cbar.update_normal(im)
    assert np.isclose(cbar.vmin, z.min())

    norm = LogNorm(z.min() * 1000, z.max() * 1000)
    im.set_norm(norm)
    cbar.set_norm(norm)
    cbar.update_normal(im)
    assert np.isclose(cbar.vmin, z.min() * 1000)
    assert np.isclose(cbar.vmax, z.max() * 1000) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def _plot_walk(self, ax, parameter, data, truth=None, extents=None, convolve=None, color=None, log_scale=False):  # pragma: no cover
        if extents is not None:
            ax.set_ylim(extents)
        assert convolve is None or isinstance(convolve, int), "Convolve must be an integer pixel window width"
        x = np.arange(data.size)
        ax.set_xlim(0, x[-1])
        ax.set_ylabel(parameter)
        if color is None:
            color = "#0345A1"
        ax.scatter(x, data, c=color, s=2, marker=".", edgecolors="none", alpha=0.5)
        max_ticks = self.parent.config["max_ticks"]
        if log_scale:
            ax.set_yscale("log")
            ax.yaxis.set_major_locator(LogLocator(numticks=max_ticks))
        else:
            ax.yaxis.set_major_locator(MaxNLocator(max_ticks, prune="lower"))

        if convolve is not None:
            color2 = self.parent.color_finder.scale_colour(color, 0.5)
            filt = np.ones(convolve) / convolve
            filtered = np.convolve(data, filt, mode="same")
            ax.plot(x[:-1], filtered[:-1], ls=":", color=color2, alpha=1) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def _select_locator(self, formatter):
        '''
        select a suitable locator
        '''
        if self.boundaries is None:
            if isinstance(self.norm, colors.NoNorm):
                nv = len(self._values)
                base = 1 + int(nv/10)
                locator = ticker.IndexLocator(base=base, offset=0)
            elif isinstance(self.norm, colors.BoundaryNorm):
                b = self.norm.boundaries
                locator = ticker.FixedLocator(b, nbins=10)
            elif isinstance(self.norm, colors.LogNorm):
                locator = ticker.LogLocator()
            else:
                locator = ticker.MaxNLocator(nbins=5)
        else:
            b = self._boundaries[self._inside]
            locator = ticker.FixedLocator(b)

        self.cbar_axis.set_major_locator(locator) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def __init__(self, colorbar, *args, **kwargs):
        """
        _ColorbarLogLocator(colorbar, *args, **kwargs)

        This ticker needs to know the *colorbar* so that it can access
        its *vmin* and *vmax*.  Otherwise it is the same as
        `~.ticker.LogLocator`.  The ``*args`` and ``**kwargs`` are the
        same as `~.ticker.LogLocator`.
        """
        self._colorbar = colorbar
        super().__init__(*args, **kwargs) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def _ticker(self, locator, formatter):
        '''
        Return the sequence of ticks (colorbar data locations),
        ticklabels (strings), and the corresponding offset string.
        '''
        if isinstance(self.norm, colors.NoNorm) and self.boundaries is None:
            intv = self._values[0], self._values[-1]
        else:
            intv = self.vmin, self.vmax
        locator.create_dummy_axis(minpos=intv[0])
        formatter.create_dummy_axis(minpos=intv[0])
        locator.set_view_interval(*intv)
        locator.set_data_interval(*intv)
        formatter.set_view_interval(*intv)
        formatter.set_data_interval(*intv)

        b = np.array(locator())
        if isinstance(locator, ticker.LogLocator):
            eps = 1e-10
            b = b[(b <= intv[1] * (1 + eps)) & (b >= intv[0] * (1 - eps))]
        else:
            eps = (intv[1] - intv[0]) * 1e-10
            b = b[(b <= intv[1] + eps) & (b >= intv[0] - eps)]
        self._manual_tick_data_values = b
        ticks = self._locate(b)
        ticklabels = formatter.format_ticks(b)
        offset_string = formatter.get_offset()
        return ticks, ticklabels, offset_string 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def minorticks_on(self):
        'Add autoscaling minor ticks to the axes.'
        for ax in (self.xaxis, self.yaxis):
            if ax.get_scale() == 'log':
                s = ax._scale
                ax.set_minor_locator(mticker.LogLocator(s.base, s.subs))
            else:
                ax.set_minor_locator(mticker.AutoMinorLocator()) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def test_LogLocator():
    loc = mticker.LogLocator(numticks=5)

    assert_raises(ValueError, loc.tick_values, 0, 1000)

    test_value = np.array([1.00000000e-05, 1.00000000e-03, 1.00000000e-01,
                           1.00000000e+01, 1.00000000e+03, 1.00000000e+05,
                           1.00000000e+07, 1.000000000e+09])
    assert_almost_equal(loc.tick_values(0.001, 1.1e5), test_value)

    loc = mticker.LogLocator(base=2)
    test_value = np.array([0.5, 1., 2., 4., 8., 16., 32., 64., 128., 256.])
    assert_almost_equal(loc.tick_values(1, 100), test_value) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def __init__(self, colorbar, *args, **kwargs):
        """
        _ColorbarLogLocator(colorbar, *args, **kwargs)

        This ticker needs to know the *colorbar* so that it can access
        its *vmin* and *vmax*.  Otherwise it is the same as
        `~.ticker.LogLocator`.  The ``*args`` and ``**kwargs`` are the
        same as `~.ticker.LogLocator`.
        """
        self._colorbar = colorbar
        ticker.LogLocator.__init__(self, *args, **kwargs) 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def tick_values(self, vmin, vmax):
        vmin = self._colorbar.norm.vmin
        vmax = self._colorbar.norm.vmax
        ticks = ticker.LogLocator.tick_values(self, vmin, vmax)
        return ticks[(ticks >= vmin) & (ticks <= vmax)] 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def _ticker(self, locator, formatter):
        '''
        Return the sequence of ticks (colorbar data locations),
        ticklabels (strings), and the corresponding offset string.
        '''
        if isinstance(self.norm, colors.NoNorm) and self.boundaries is None:
            intv = self._values[0], self._values[-1]
        else:
            intv = self.vmin, self.vmax
        locator.create_dummy_axis(minpos=intv[0])
        formatter.create_dummy_axis(minpos=intv[0])
        locator.set_view_interval(*intv)
        locator.set_data_interval(*intv)
        formatter.set_view_interval(*intv)
        formatter.set_data_interval(*intv)

        b = np.array(locator())
        if isinstance(locator, ticker.LogLocator):
            eps = 1e-10
            b = b[(b <= intv[1] * (1 + eps)) & (b >= intv[0] * (1 - eps))]
        else:
            eps = (intv[1] - intv[0]) * 1e-10
            b = b[(b <= intv[1] + eps) & (b >= intv[0] - eps)]
        self._tick_data_values = b
        ticks = self._locate(b)
        formatter.set_locs(b)
        ticklabels = [formatter(t, i) for i, t in enumerate(b)]
        offset_string = formatter.get_offset()
        return ticks, ticklabels, offset_string 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def _ticker(self, locator, formatter):
        '''
        Return the sequence of ticks (colorbar data locations),
        ticklabels (strings), and the corresponding offset string.
        '''
        if isinstance(self.norm, colors.NoNorm) and self.boundaries is None:
            intv = self._values[0], self._values[-1]
        else:
            intv = self.vmin, self.vmax
        locator.create_dummy_axis(minpos=intv[0])
        formatter.create_dummy_axis(minpos=intv[0])
        locator.set_view_interval(*intv)
        locator.set_data_interval(*intv)
        formatter.set_view_interval(*intv)
        formatter.set_data_interval(*intv)

        b = np.array(locator())
        if isinstance(locator, ticker.LogLocator):
            eps = 1e-10
            b = b[(b <= intv[1] * (1 + eps)) & (b >= intv[0] * (1 - eps))]
        else:
            eps = (intv[1] - intv[0]) * 1e-10
            b = b[(b <= intv[1] + eps) & (b >= intv[0] - eps)]
        self._manual_tick_data_values = b
        ticks = self._locate(b)
        formatter.set_locs(b)
        ticklabels = [formatter(t, i) for i, t in enumerate(b)]
        offset_string = formatter.get_offset()
        return ticks, ticklabels, offset_string 

# 需要導入模塊: from matplotlib import ticker [as 別名]
# 或者: from matplotlib.ticker import LogLocator [as 別名]
def test_basic(self):
        loc = mticker.LogLocator(numticks=5)
        with pytest.raises(ValueError):
            loc.tick_values(0, 1000)

        test_value = np.array([1.00000000e-05, 1.00000000e-03, 1.00000000e-01,
                               1.00000000e+01, 1.00000000e+03, 1.00000000e+05,
                               1.00000000e+07, 1.000000000e+09])
        assert_almost_equal(loc.tick_values(0.001, 1.1e5), test_value)

        loc = mticker.LogLocator(base=2)
        test_value = np.array([0.5, 1., 2., 4., 8., 16., 32., 64., 128., 256.])
        assert_almost_equal(loc.tick_values(1, 100), test_value)