Python matplotlib.ticker.AutoLocator() Examples

def _remove_labels_from_axis(axis):
    for t in axis.get_majorticklabels():
        t.set_visible(False)

    try:
        # set_visible will not be effective if
        # minor axis has NullLocator and NullFormattor (default)
        import matplotlib.ticker as ticker
        if isinstance(axis.get_minor_locator(), ticker.NullLocator):
            axis.set_minor_locator(ticker.AutoLocator())
        if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
            axis.set_minor_formatter(ticker.FormatStrFormatter(''))
        for t in axis.get_minorticklabels():
            t.set_visible(False)
    except Exception:   # pragma no cover
        raise
    axis.get_label().set_visible(False) 

def _remove_labels_from_axis(axis):
    for t in axis.get_majorticklabels():
        t.set_visible(False)

    try:
        # set_visible will not be effective if
        # minor axis has NullLocator and NullFormattor (default)
        import matplotlib.ticker as ticker
        if isinstance(axis.get_minor_locator(), ticker.NullLocator):
            axis.set_minor_locator(ticker.AutoLocator())
        if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
            axis.set_minor_formatter(ticker.FormatStrFormatter(''))
        for t in axis.get_minorticklabels():
            t.set_visible(False)
    except Exception:   # pragma no cover
        raise
    axis.get_label().set_visible(False) 

def _remove_labels_from_axis(axis):
    for t in axis.get_majorticklabels():
        t.set_visible(False)

    try:
        # set_visible will not be effective if
        # minor axis has NullLocator and NullFormattor (default)
        import matplotlib.ticker as ticker
        if isinstance(axis.get_minor_locator(), ticker.NullLocator):
            axis.set_minor_locator(ticker.AutoLocator())
        if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
            axis.set_minor_formatter(ticker.FormatStrFormatter(''))
        for t in axis.get_minorticklabels():
            t.set_visible(False)
    except Exception:   # pragma no cover
        raise
    axis.get_label().set_visible(False) 

def _remove_labels_from_axis(axis):
    for t in axis.get_majorticklabels():
        t.set_visible(False)

    try:
        # set_visible will not be effective if
        # minor axis has NullLocator and NullFormattor (default)
        import matplotlib.ticker as ticker
        if isinstance(axis.get_minor_locator(), ticker.NullLocator):
            axis.set_minor_locator(ticker.AutoLocator())
        if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
            axis.set_minor_formatter(ticker.FormatStrFormatter(''))
        for t in axis.get_minorticklabels():
            t.set_visible(False)
    except Exception:   # pragma no cover
        raise
    axis.get_label().set_visible(False) 

def _remove_labels_from_axis(axis):
    for t in axis.get_majorticklabels():
        t.set_visible(False)

    try:
        # set_visible will not be effective if
        # minor axis has NullLocator and NullFormattor (default)
        import matplotlib.ticker as ticker
        if isinstance(axis.get_minor_locator(), ticker.NullLocator):
            axis.set_minor_locator(ticker.AutoLocator())
        if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
            axis.set_minor_formatter(ticker.FormatStrFormatter(''))
        for t in axis.get_minorticklabels():
            t.set_visible(False)
    except Exception:   # pragma no cover
        raise
    axis.get_label().set_visible(False) 

def _remove_labels_from_axis(axis):
    for t in axis.get_majorticklabels():
        t.set_visible(False)

    try:
        # set_visible will not be effective if
        # minor axis has NullLocator and NullFormattor (default)
        import matplotlib.ticker as ticker
        if isinstance(axis.get_minor_locator(), ticker.NullLocator):
            axis.set_minor_locator(ticker.AutoLocator())
        if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
            axis.set_minor_formatter(ticker.FormatStrFormatter(''))
        for t in axis.get_minorticklabels():
            t.set_visible(False)
    except Exception:   # pragma no cover
        raise
    axis.get_label().set_visible(False) 

def axisinfo(unit, axis):
        'return AxisInfo instance for x and unit'

        if unit == radians:
            return units.AxisInfo(
                majloc=ticker.MultipleLocator(base=np.pi/2),
                majfmt=ticker.FuncFormatter(rad_fn),
                label=unit.fullname,
            )
        elif unit == degrees:
            return units.AxisInfo(
                majloc=ticker.AutoLocator(),
                majfmt=ticker.FormatStrFormatter(r'$%i^\circ$'),
                label=unit.fullname,
            )
        elif unit is not None:
            if hasattr(unit, 'fullname'):
                return units.AxisInfo(label=unit.fullname)
            elif hasattr(unit, 'unit'):
                return units.AxisInfo(label=unit.unit.fullname)
        return None 

def _remove_labels_from_axis(axis):
    for t in axis.get_majorticklabels():
        t.set_visible(False)

    try:
        # set_visible will not be effective if
        # minor axis has NullLocator and NullFormattor (default)
        import matplotlib.ticker as ticker
        if isinstance(axis.get_minor_locator(), ticker.NullLocator):
            axis.set_minor_locator(ticker.AutoLocator())
        if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
            axis.set_minor_formatter(ticker.FormatStrFormatter(''))
        for t in axis.get_minorticklabels():
            t.set_visible(False)
    except Exception:   # pragma no cover
        raise
    axis.get_label().set_visible(False) 

def cla(self):
        'clear the current axis'
        self.set_major_locator(mticker.AutoLocator())
        self.set_major_formatter(mticker.ScalarFormatter())
        self.set_minor_locator(mticker.NullLocator())
        self.set_minor_formatter(mticker.NullFormatter())

        self.set_label_text('')
        self._set_artist_props(self.label)

        # Keep track of setting to the default value, this allows use to know
        # if any of the following values is explicitly set by the user, so as
        # to not overwrite their settings with any of our 'auto' settings.
        self.isDefault_majloc = True
        self.isDefault_minloc = True
        self.isDefault_majfmt = True
        self.isDefault_minfmt = True
        self.isDefault_label = True

        # Clear the callback registry for this axis, or it may "leak"
        self.callbacks = cbook.CallbackRegistry()

        # whether the grids are on
        self._gridOnMajor = rcParams['axes.grid']
        self._gridOnMinor = False

        self.label.set_text('')
        self._set_artist_props(self.label)

        self.reset_ticks()

        self.converter = None
        self.units = None
        self.set_units(None) 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def create_slice(self, context):
        """ :type context: dict """
        model = self._model
        axes = self._image.axes
        """ :type: matplotlib.axes.Axes """

        axes.set_title(model.title, fontsize=12)
        axes.tick_params(axis='both')
        axes.set_ylabel(model.y_axis_name, fontsize=9)
        axes.set_xlabel(model.x_axis_name, fontsize=9)

        axes.get_xaxis().set_major_formatter(FuncFormatter(model.x_axis_formatter))
        axes.get_xaxis().set_major_locator(AutoLocator())

        axes.get_yaxis().set_major_formatter(FuncFormatter(model.y_axis_formatter))
        axes.get_yaxis().set_major_locator(AutoLocator())

        for label in (axes.get_xticklabels() + axes.get_yticklabels()):
            label.set_fontsize(9)

        self._reset_zoom()

        axes.add_patch(self._vertical_indicator)
        axes.add_patch(self._horizontal_indicator)
        self._update_indicators(context)

        self._image.set_cmap(cmap=context['colormap'])

        self._view_limits = context["view_limits"][self._model.index_direction['name']]

        if model.data is not None:
            self._image.set_data(model.data) 

def cla(self):
        'clear the current axis'
        self.set_major_locator(mticker.AutoLocator())
        self.set_major_formatter(mticker.ScalarFormatter())
        self.set_minor_locator(mticker.NullLocator())
        self.set_minor_formatter(mticker.NullFormatter())

        self.set_label_text('')
        self._set_artist_props(self.label)

        # Keep track of setting to the default value, this allows use to know
        # if any of the following values is explicitly set by the user, so as
        # to not overwrite their settings with any of our 'auto' settings.
        self.isDefault_majloc = True
        self.isDefault_minloc = True
        self.isDefault_majfmt = True
        self.isDefault_minfmt = True
        self.isDefault_label = True

        # Clear the callback registry for this axis, or it may "leak"
        self.callbacks = cbook.CallbackRegistry()

        # whether the grids are on
        self._gridOnMajor = rcParams['axes.grid'] and (rcParams['axes.grid.which'] in ('both','major'))
        self._gridOnMinor = rcParams['axes.grid'] and (rcParams['axes.grid.which'] in ('both','minor'))

        self.label.set_text('')
        self._set_artist_props(self.label)

        self.reset_ticks()

        self.converter = None
        self.units = None
        self.set_units(None) 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def cla(self):
        'clear the current axis'
        self.set_major_locator(mticker.AutoLocator())
        self.set_major_formatter(mticker.ScalarFormatter())
        self.set_minor_locator(mticker.NullLocator())
        self.set_minor_formatter(mticker.NullFormatter())

        self.set_label_text('')
        self._set_artist_props(self.label)

        # Keep track of setting to the default value, this allows use to know
        # if any of the following values is explicitly set by the user, so as
        # to not overwrite their settings with any of our 'auto' settings.
        self.isDefault_majloc = True
        self.isDefault_minloc = True
        self.isDefault_majfmt = True
        self.isDefault_minfmt = True
        self.isDefault_label = True

        # Clear the callback registry for this axis, or it may "leak"
        self.callbacks = cbook.CallbackRegistry()

        # whether the grids are on
        self._gridOnMajor = rcParams['axes.grid'] and (rcParams['axes.grid.which'] in ('both','major'))
        self._gridOnMinor = rcParams['axes.grid'] and (rcParams['axes.grid.which'] in ('both','minor'))

        self.label.set_text('')
        self._set_artist_props(self.label)

        self.reset_ticks()

        self.converter = None
        self.units = None
        self.set_units(None) 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def axisinfo(unit, axis):
        if unit != 'time':
            return None

        majloc = AutoLocator()
        majfmt = TimeFormatter(majloc)
        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label='time') 

def cla(self):
        'clear the current axis'
        self.set_major_locator(mticker.AutoLocator())
        self.set_major_formatter(mticker.ScalarFormatter())
        self.set_minor_locator(mticker.NullLocator())
        self.set_minor_formatter(mticker.NullFormatter())

        self.set_label_text('')
        self._set_artist_props(self.label)

        # Keep track of setting to the default value, this allows use to know
        # if any of the following values is explicitly set by the user, so as
        # to not overwrite their settings with any of our 'auto' settings.
        self.isDefault_majloc = True
        self.isDefault_minloc = True
        self.isDefault_majfmt = True
        self.isDefault_minfmt = True
        self.isDefault_label = True

        # Clear the callback registry for this axis, or it may "leak"
        self.callbacks = cbook.CallbackRegistry()

        # whether the grids are on
        self._gridOnMajor = rcParams['axes.grid']
        self._gridOnMinor = False

        self.label.set_text('')
        self._set_artist_props(self.label)

        self.reset_ticks()

        self.converter = None
        self.units = None
        self.set_units(None) 

def mirror(spec_top: MsmsSpectrum, spec_bottom: MsmsSpectrum,
           spectrum_kws: Optional[Dict] = None, ax: Optional[plt.Axes] = None)\
        -> plt.Axes:
    """
    Mirror plot two MS/MS spectra.

    Parameters
    ----------
    spec_top : MsmsSpectrum
        The spectrum to be plotted on the top.
    spec_bottom : MsmsSpectrum
        The spectrum to be plotted on the bottom.
    spectrum_kws : Optional[Dict], optional
        Keyword arguments for `plot.spectrum`.
    ax : Optional[plt.Axes], optional
        Axes instance on which to plot the spectrum. If None the current Axes
        instance is used.

    Returns
    -------
    plt.Axes
        The matplotlib Axes instance on which the spectra are plotted.
    """
    if ax is None:
        ax = plt.gca()

    if spectrum_kws is None:
        spectrum_kws = {}
    # Top spectrum.
    spectrum(spec_top, mirror_intensity=False, ax=ax, **spectrum_kws)
    y_max = ax.get_ylim()[1]
    # Mirrored bottom spectrum.
    spectrum(spec_bottom, mirror_intensity=True, ax=ax, **spectrum_kws)
    y_min = ax.get_ylim()[0]
    ax.set_ylim(y_min, y_max)

    ax.axhline(0, color='#9E9E9E', zorder=10)

    # Update axes so that both spectra fit.
    min_mz = max([0, math.floor(spec_top.mz[0] / 100 - 1) * 100,
                  math.floor(spec_bottom.mz[0] / 100 - 1) * 100])
    max_mz = max([math.ceil(spec_top.mz[-1] / 100 + 1) * 100,
                  math.ceil(spec_bottom.mz[-1] / 100 + 1) * 100])
    ax.set_xlim(min_mz, max_mz)
    ax.yaxis.set_major_locator(mticker.AutoLocator())
    ax.yaxis.set_minor_locator(mticker.AutoMinorLocator())
    ax.yaxis.set_major_formatter(mticker.FuncFormatter(
        lambda x, pos: f'{abs(x):.0%}'))

    return ax 

def _ticker(self):
        '''
        Return the sequence of ticks (colorbar data locations),
        ticklabels (strings), and the corresponding offset string.
        '''
        locator = self.locator
        formatter = self.formatter
        if locator is None:
            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(subs='all')
                elif isinstance(self.norm, colors.SymLogNorm):
                    # The subs setting here should be replaced
                    # by logic in the locator.
                    locator = ticker.SymmetricalLogLocator(
                                      subs=np.arange(1, 10),
                                      linthresh=self.norm.linthresh,
                                      base=10)
                else:
                    if mpl.rcParams['_internal.classic_mode']:
                        locator = ticker.MaxNLocator()
                    else:
                        locator = ticker.AutoLocator()
            else:
                b = self._boundaries[self._inside]
                locator = ticker.FixedLocator(b, nbins=10)
        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 

def update_plot(self):
        if len(self.Plotsignals) == 0:
            return
        self.ax.clear()
        for Plotsignal in self.Plotsignals:
            if Plotsignal.plotenable:
                if Plotsignal.plotnormalise:
                    data = Plotsignal.get_normalised_values()*100
                    self.ax.plot(data, color=Plotsignal.plotcolor)
                else:
                    data = Plotsignal.get_values()
                    self.ax.plot(convert_to_si(Plotsignal.unit,data)[1], color=Plotsignal.plotcolor)


        self.ax.grid(True)
        self.ax.get_yaxis().tick_right()
        self.ax.get_yaxis().set_label_position("right")
        self.ax.get_yaxis().set_visible(True)
        self.ax.get_xaxis().set_visible(False)
        all_normalised = True
        all_same_unit = True
        unit = ""
        iter = self.signalstore.get_iter(0)
        while iter is not None:
            if self.signalstore[iter][0] == True:
                if unit == "":
                    unit = self.signalstore[iter][4]
                if self.signalstore[iter][1] == False:
                    all_normalised = False
                if self.signalstore[iter][4] != unit:
                    all_same_unit = False
            if not all_normalised and not all_same_unit:
                break
            iter = self.signalstore.iter_next(iter)
        if all_normalised:
            self.ax.set_yticks(np.arange(0, 101, step=25))
            self.ax.set_ylabel('Percent [%]')
        else:
            self.ax.yaxis.set_major_locator(AutoLocator())
            if all_same_unit:
                self.ax.set_ylabel(unit)
            else:
                self.ax.set_ylabel("")
        self.canvas.draw()
        self.canvas.flush_events()