python – Matplotlib添加一个特定的刻度线呈现轴最大 – 多个刻度单个观察

试图将观察结果分别绘制到每次观察的多个尺度,我设法产生以下情节：

但是我想添加一个刻度,在每个刻度中显示y-max值,而不管它与前一刻度之间的差距.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.

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,(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',80)])

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

最佳答案

您可以将最高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)