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:
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。
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')
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)