Python ticker.LogFormatter方法代码示例

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def plot_y_axis(self, cbar_ax, plot_ax):

        if self.properties['transform'] in ['log', 'log1p']:
            # get a useful log scale
            # that looks like [1, 2, 5, 10, 20, 50, 100, ... etc]

            formatter = LogFormatter(10, labelOnlyBase=False)
            aa = np.array([1, 2, 5])
            tick_values = np.concatenate([aa * 10 ** x for x in range(10)])
            try:
                cobar = plt.colorbar(self.img, ticks=tick_values, format=formatter, ax=cbar_ax, fraction=0.95)
            except AttributeError:
                return
        else:
            try:
                cobar = plt.colorbar(self.img, ax=cbar_ax, fraction=0.95)
            except AttributeError:
                return

        cobar.solids.set_edgecolor("face")
        cobar.ax.tick_params(labelsize='smaller')
        cobar.ax.yaxis.set_ticks_position('left')

        # adjust the labels of the colorbar
        ticks = cobar.ax.get_yticks()
        labels = cobar.ax.set_yticklabels(ticks.astype('float32'))
        (vmin, vmax) = cobar.mappable.get_clim()
        for idx in np.where(ticks == vmin)[0]:
            # if the label is at the start of the colobar
            # move it above avoid being cut or overlapping with other track
            labels[idx].set_verticalalignment('bottom')
        for idx in np.where(ticks == vmax)[0]:
            # if the label is at the end of the colobar
            # move it a bit inside to avoid overlapping
            # with other labels
            labels[idx].set_verticalalignment('top') 

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def update_ticks(self):
        """
        Force the update of the ticks and ticklabels. This must be
        called whenever the tick locator and/or tick formatter changes.
        """
        ax = self.ax
        # get the locator and formatter.  Defaults to
        # self.locator if not None..
        locator, formatter = self._get_ticker_locator_formatter()

        if self.orientation == 'vertical':
            long_axis, short_axis = ax.yaxis, ax.xaxis
        else:
            long_axis, short_axis = ax.xaxis, ax.yaxis

        if self._use_auto_colorbar_locator():
            _log.debug('Using auto colorbar locator on colorbar')
            _log.debug('locator: %r', locator)
            long_axis.set_major_locator(locator)
            long_axis.set_major_formatter(formatter)
            if type(self.norm) == colors.LogNorm:
                long_axis.set_minor_locator(_ColorbarLogLocator(self,
                            base=10., subs='auto'))
                long_axis.set_minor_formatter(
                    ticker.LogFormatter()
                )
        else:
            _log.debug('Using fixed locator on colorbar')
            ticks, ticklabels, offset_string = self._ticker(locator, formatter)
            long_axis.set_ticks(ticks)
            long_axis.set_ticklabels(ticklabels)
            long_axis.get_major_formatter().set_offset_string(offset_string) 

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def test_pprint(self, value, domain, expected):
        fmt = mticker.LogFormatter()
        label = fmt.pprint_val(value, domain)
        assert label == expected 

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def test_sublabel(self):
        # test label locator
        fig, ax = plt.subplots()
        ax.set_xscale('log')
        ax.xaxis.set_major_locator(mticker.LogLocator(base=10, subs=[]))
        ax.xaxis.set_minor_locator(mticker.LogLocator(base=10,
                                                      subs=np.arange(2, 10)))
        ax.xaxis.set_major_formatter(mticker.LogFormatter(labelOnlyBase=True))
        ax.xaxis.set_minor_formatter(mticker.LogFormatter(labelOnlyBase=False))
        # axis range above 3 decades, only bases are labeled
        ax.set_xlim(1, 1e4)
        fmt = ax.xaxis.get_major_formatter()
        fmt.set_locs(ax.xaxis.get_majorticklocs())
        show_major_labels = [fmt(x) != ''
                             for x in ax.xaxis.get_majorticklocs()]
        assert np.all(show_major_labels)
        self._sub_labels(ax.xaxis, subs=[])

        # For the next two, if the numdec threshold in LogFormatter.set_locs
        # were 3, then the label sub would be 3 for 2-3 decades and (2,5)
        # for 1-2 decades.  With a threshold of 1, subs are not labeled.
        # axis range at 2 to 3 decades
        ax.set_xlim(1, 800)
        self._sub_labels(ax.xaxis, subs=[])

        # axis range at 1 to 2 decades
        ax.set_xlim(1, 80)
        self._sub_labels(ax.xaxis, subs=[])

        # axis range at 0.4 to 1 decades, label subs 2, 3, 4, 6
        ax.set_xlim(1, 8)
        self._sub_labels(ax.xaxis, subs=[2, 3, 4, 6])

        # axis range at 0 to 0.4 decades, label all
        ax.set_xlim(0.5, 0.9)
        self._sub_labels(ax.xaxis, subs=np.arange(2, 10, dtype=int)) 

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def test_LogFormatter_call(self, val):
        # test _num_to_string method used in __call__
        temp_lf = mticker.LogFormatter()
        temp_lf.axis = FakeAxis()
        assert temp_lf(val) == str(val) 

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def test_majlocator_type():
    fig, ax = plt.subplots()
    with pytest.raises(TypeError):
        ax.xaxis.set_major_locator(matplotlib.ticker.LogFormatter()) 

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def test_minlocator_type():
    fig, ax = plt.subplots()
    with pytest.raises(TypeError):
        ax.xaxis.set_minor_locator(matplotlib.ticker.LogFormatter()) 

# 需要导入模块: from matplotlib import ticker [as 别名]
# 或者: from matplotlib.ticker import LogFormatter [as 别名]
def __plot_colorbar(self, img, orientation='vertical'):
        if orientation == 'horizontal':
            ax_divider = make_axes_locatable(self.ax)
            if self.is_inverted:
                cax = ax_divider.append_axes("top", size=0.09, pad=0.2)
            else:
                cax = ax_divider.append_axes("bottom", size=0.09, pad=0.2)
            colorbar(img, cax=cax, orientation='horizontal')
        else:  # vertical
            y_ax = self.y_ax

            if self.properties['norm'] == 'log':
                from matplotlib.ticker import LogFormatter
                formatter = LogFormatter(10, labelOnlyBase=False)
                aa = np.array([1, 2, 5])
                c_min, c_max = self.matrix_val_range

                def abs_inc(num):
                    if num != 0:
                        sign = num / abs(num)
                        return int(sign * abs(num + 1))
                    else:
                        return 1

                lower_ = int(np.log10(c_min))
                upper_ = abs_inc(int(np.log10(c_max)))
                tick_values = np.concatenate([aa * 10 ** x for x in range(lower_, upper_)])

                c_bar = plt.colorbar(img, ax=y_ax, ticks=tick_values, format=formatter, fraction=0.98)
            else:
                c_bar = plt.colorbar(img, ax=y_ax, fraction=0.98)

            c_bar.solids.set_edgecolor("face")
            c_bar.ax.tick_params(labelsize='smaller')

            c_bar.ax.yaxis.set_ticks_position('left')