Python lines.TICKDOWN属性代码示例

# 需要导入模块: from matplotlib import lines [as 别名]
# 或者: from matplotlib.lines import TICKDOWN [as 别名]
def apply_tickdir(self, tickdir):
        if tickdir is None:
            tickdir = rcParams['%s.direction' % self._name]
        self._tickdir = tickdir

        if self._tickdir == 'in':
            self._tickmarkers = (mlines.TICKUP, mlines.TICKDOWN)
            self._pad = self._base_pad
        elif self._tickdir == 'inout':
            self._tickmarkers = ('|', '|')
            self._pad = self._base_pad + self._size / 2.
        else:
            self._tickmarkers = (mlines.TICKDOWN, mlines.TICKUP)
            self._pad = self._base_pad + self._size 

# 需要导入模块: from matplotlib import lines [as 别名]
# 或者: from matplotlib.lines import TICKDOWN [as 别名]
def apply_tickdir(self, tickdir):
        if tickdir is None:
            tickdir = rcParams['%s.direction' % self._name]
        self._tickdir = tickdir

        if self._tickdir == 'in':
            self._tickmarkers = (mlines.TICKUP, mlines.TICKDOWN)
        elif self._tickdir == 'inout':
            self._tickmarkers = ('|', '|')
        else:
            self._tickmarkers = (mlines.TICKDOWN, mlines.TICKUP)
        self._pad = self._base_pad + self.get_tick_padding()
        self.stale = True 

# 需要导入模块: from matplotlib import lines [as 别名]
# 或者: from matplotlib.lines import TICKDOWN [as 别名]
def TickSpineFormatter(ax, sizeformat = "esurf"):
    """This formats the line weights on the bounding box and ticks.

    Args:
        ax1 (axis object): the matplotlib axis object
        size_format (str): The size format. Can be geomorhpology, esurf or big

    returns:
        The axis object

    Author: SMM
    """

    import matplotlib.lines as mpllines

    # some formatting to make some of the ticks point outward
    for line in ax.get_xticklines():
        line.set_marker(mpllines.TICKDOWN)

    for line in ax.get_yticklines():
        line.set_marker(mpllines.TICKLEFT)

    if sizeformat == "esurf":
        lw = 1.0
        pd = 8
    elif sizeformat == "geomorphology":
        lw = 1.5
        pd = 10
    elif sizeformat == "big":
        lw = 2
        pd = 12
    else:
        lw = 1.0
        pd = 8

    ax.spines['top'].set_linewidth(lw)
    ax.spines['left'].set_linewidth(lw)
    ax.spines['right'].set_linewidth(lw)
    ax.spines['bottom'].set_linewidth(lw)

    # This gets all the ticks, and pads them away from the axis so that the corners don't overlap
    ax.tick_params(axis='both', width=lw, pad = pd)
    for tick in ax.xaxis.get_major_ticks():
        tick.set_pad(pd)

    return ax



#==============================================================================
# This formats ticks if you want to convert metres to km
#============================================================================== 

# 需要导入模块: from matplotlib import lines [as 别名]
# 或者: from matplotlib.lines import TICKDOWN [as 别名]
def tukeyplot(results, dim=None, yticklabels=None):
    npairs = len(results)

    fig = plt.figure()
    fsp = fig.add_subplot(111)
    fsp.axis([-50,50,0.5,10.5])
    fsp.set_title('95 % family-wise confidence level')
    fsp.title.set_y(1.025)
    fsp.set_yticks(np.arange(1,11))
    fsp.set_yticklabels(['V-T','V-S','T-S','V-P','T-P','S-P','V-M',
                         'T-M','S-M','P-M'])
    #fsp.yaxis.set_major_locator(mticker.MaxNLocator(npairs))
    fsp.yaxis.grid(True, linestyle='-', color='gray')
    fsp.set_xlabel('Differences in mean levels of Var', labelpad=8)
    fsp.xaxis.tick_bottom()
    fsp.yaxis.tick_left()

    xticklines = fsp.get_xticklines()
    for xtickline in xticklines:
        xtickline.set_marker(lines.TICKDOWN)
        xtickline.set_markersize(10)

    xlabels = fsp.get_xticklabels()
    for xlabel in xlabels:
        xlabel.set_y(-.04)

    yticklines = fsp.get_yticklines()
    for ytickline in yticklines:
        ytickline.set_marker(lines.TICKLEFT)
        ytickline.set_markersize(10)

    ylabels = fsp.get_yticklabels()
    for ylabel in ylabels:
        ylabel.set_x(-.04)

    for pair in range(npairs):
        data = .5+results[pair]/100.
        #fsp.axhline(y=npairs-pair, xmin=data[0], xmax=data[1], linewidth=1.25,
        fsp.axhline(y=npairs-pair, xmin=data.mean(), xmax=data[1], linewidth=1.25,
            color='blue', marker="|",  markevery=1)

        fsp.axhline(y=npairs-pair, xmin=data[0], xmax=data.mean(), linewidth=1.25,
            color='blue', marker="|", markevery=1)

    #for pair in range(npairs):
    #    data = .5+results[pair]/100.
    #    data = results[pair]
    #    data = np.r_[data[0],data.mean(),data[1]]
    #    l = plt.plot(data, [npairs-pair]*len(data), color='black',
    #                linewidth=.5, marker="|", markevery=1)

    fsp.axvline(x=0, linestyle="--", color='black')

    fig.subplots_adjust(bottom=.125)