Matplotlib添加一个特定的刻度线呈现轴最大 - 多个刻度单个观察

时间:2013-03-08 09:48:43

标签: python matplotlib plot scipy

尝试将观察分别绘制到每次观察的多个尺度,我设法产生以下图:

enter image description here

但是我想在每个比例中添加一个显示y-max 值的刻度,无论它与前一个刻度之间的差距如何。下面给出了这种情节的一个例子。当y-max是滴答间隔的倍数时产生。

enter image description here

谢谢, F。

以下是用于生成这些示例的代码。

import numpy as np
import pylab as pl
import matplotlib as plt
import matplotlib.ticker as ticker
import matplotlib.transforms

def add_scales(fig, axes, scales, subplot_reduction_factor=0.1, margin_size=50):
    nb_scales = len(scales)
    b,l,w,h = zoom_ax.get_position().bounds

    _, ymax = axes.get_ylim()

    # Saves some space to the right so that we can add our scales
    fig.subplots_adjust(right=1-(subplot_reduction_factor)*nb_scales)

    for (n, (vmin, vmax, color, label, alignment)) in enumerate(scales):

        # Adjust wrt. the orignial figure's scale 
        nax = fig_zoom.add_axes((b,l,w,(h * alignment) / ymax))
        nax.spines['right'].set_position(('outward', -40+n*margin_size))
        nax.set_ylim((vmin,vmax))

        # Move ticks and label to the right
        nax.yaxis.set_label_position('right')
        nax.yaxis.set_ticks_position('right')

        # Hides everything except yaxis
        nax.patch.set_visible(False)
        nax.xaxis.set_visible(False)
        nax.yaxis.set_visible(True)
        nax.spines["top"].set_visible(False)
        nax.spines["bottom"].set_visible(False)

        # Color stuff
        nax.spines['right'].set_color(color)
        nax.tick_params(axis='y', colors=color)
        nax.yaxis.set_smart_bounds(False)
        #nax.yaxis.label.set_color(color)

        if label != None:
            nax.set_ylabel(None)

if __name__ == '__main__':

    a=(np.random.normal(10,5,100))

    a=np.linspace(0,100,100) 
    c=np.linspace(0,80, 100)
    d=np.linspace(0,40,100)


    fig_zoom = plt.pyplot.figure()
    zoom_ax = fig_zoom.add_subplot(1,1,1)


    zoom_ax.plot(a,c)
    zoom_ax.plot(a,d)
    zoom_ax.set_title('Zoom')
    zoom_ax.set_xlabel('A')
    zoom_ax.set_ylabel('B')
    zoom_ax.set_ylim((0,100))
    zoom_ax.grid()
    add_scales(fig_zoom, 
               zoom_ax, [(0,.55,'green',None,40),
                          (0,.85,'blue',None,80)])

    fig_zoom.savefig(open('./test.svg','w'),format='svg')

1 个答案:

答案 0 :(得分:4)

您可以将最高的ytick值设置为最大值。如果第二个最高ytick值和最大值非常接近,则标签可能会混乱。

尝试将此添加到循环中:

tcks = nax.get_yticks()
tcks[-1] = vmax
nax.set_yticks(tcks)

enter image description here